5th Generation wireless communication technology 5G is a revolutionary step change in the field of mobile networks. 5G is an advancement in the existing 4G system that is intended to address the growing demands of data hungry applications requiring higher transmission speeds, extremely low latencies and better reliability. Unlike the voice and mobile broadband focus of the previous generation, 5G is a unifying communications framework that incorporates enhanced mobile broadband, massive machine type communication and ultrareliable low latency communication, enabling new digital services and communication capabilities that go far beyond the capabilities of previous networks. Key underlying technologies driving 5G include the use of higher frequency bands specifically millimeter wave or mmWave bands to provide huge amounts of bandwidth that is necessary to support multi gigabit data rates. These higher frequencies will likely lead to a reduced coverage area, the radio signals will be attenuated by objects. Massive Multiple Input Multiple Output Massive MIMO which increases the efficiency and capacity of wireless networks through the use of large arrays of antennas at the base station and beamforming that strengthens and focuses the signal strength toward specific user by directing it, are implemented in 5G networks to address the limitations posed by the higher frequency spectrum. The benefits of 5G networks include massive increase in speed that may go up to several gigabits per second in ideal situations, extreme low latency in near real time communication between devices and immense scale to support a massive number of simultaneously connected devices to handle the growth of global data traffic which is projected to grow exponentially. Billions of devices will be connected to 5G networks worldwide that include smart phones, IOT devices and sensors and generation of considerable economic gains is also expected from new digital services, business models and industrial solutions made possible by 5G technology. In the health sector, 5G facilitates applications such as telemedicine, real time remote monitoring and robotic surgery. For these applications, connectivity should be reliable and the latency should be extremely low, and these can be satisfied by 5G technology, thereby medical professionals can carry out the diagnosis, monitor the health of patient even perform procedures from a distant location with high precision. Vehicle to everything V2X communication made possible by 5G in transport sector enable vehicles to communicate with each other and with road infrastructure which play a critical role in facilitating autonomous driving, reducing traffic congestions and improving road safety. Smart factories rely on 5G networks to make Industry 4.0 possible, the smart factories equipped with 5G networks support automation, robotics, and real time data analytics to boost production efficiency. In a smart factory environment thousands of devices and sensors supported by Massive Machine Type Communication networks, can be deployed to perform tasks like predictive maintenance, seamlessly collaborate with each other and monitor the production in real time. Smart cities use the potential of 5G to implement smart transport systems, energy grids and environmental monitoring and improved public services. Additionally augmented reality and virtual reality systems AR and VR heavily rely on high bandwidth and low latency to provide more immersive experiences. Anurag Patre | Shreyash Kharkate "5G Systems: Techniques & Application" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Recent Advances in Computer Applications and Information Technology , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101500.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101500/5g-systems-techniques-and-application/anurag-patre

Generative AI has transitioned from a technical novelty to a transformative force, reshaping industries by boosting productivity and sparking innovation in complex fields like drug discovery and language translation 7 . While its ability to automate workflows and assist in creative research is groundbreaking, the technology is not without its flaws. We are currently navigating significant hurdles, including the tendency for models to hallucinate inaccurate information, inherent biases in data, and complex ethical debates surrounding privacy and plagiarism 7 . Addressing these challenges isnt just a matter of better code it requires a commitment to human AI collaboration and transparent regulatory frameworks to ensure we are deploying these tools responsibly 5 . This need for a human touch is most evident in the healthcare sector. While AI can process vast quantities of patient data, lab results, and medical imagery with incredible speed, it cannot replace the nuanced judgment of a clinician 2 . AI serves as a powerful diagnostic aid, but the final decision making remains a human responsibility. Healthcare professionals must step in to validate AI derived insights, ensuring that every treatment plan is not only accurate and evidence based but also personalized to the actual person behind the data 2 . The synergy between AI technology and human intelligence has the potential to make the healthcare system more efficient, accurate, and patient centric. Furthermore, AI contributes to improving hospital operations, patient monitoring, and healthcare resource management through automation and predictive analytics. AI powered tools such as medical imaging systems, wearable health monitoring devices, virtual health assistants, and robotic surgical systems are improving the quality of care while reducing operational costs. The integration of multimodal data from different sources enhances the performance of AI systems, enabling more accurate and comprehensive analysis of patient health. Despite these advancements, the study emphasizes the importance of human supervision, ethical considerations, data privacy, and fairness in AI implementation. Challenges such as data bias, lack of transparency, and limited generalizability across diverse populations must be addressed to ensure reliable Generative AI has quickly evolved into a powerful partner across industries, offering a significant boost to efficiency and opening new doors for creative problem solving 8 . By accelerating research and automating the busy work of complex workflows, it has become an essential tool in specialized fields like drug discovery, hypothesis generation, and global language translation 8 . However, this rapid progress comes with a set of very human challenges. We are currently navigating issues like hallucinations —where the AI confidently presents inaccurate information—as well as inherent biases, ethical questions regarding data privacy, and the high environmental and financial costs of computing 8 . Ultimately, the success of these tools depends on a human in the loop approach. Truly responsible adoption requires more than just better algorithms it demands robust regulatory frameworks, transparency in how models are built, and a commitment to human AI collaboration 8 . This highlights the dual nature of the technology while its potential to innovate is vast, its limitations remind us that development must be balanced with careful, ethical deployment to ensure it remains a force for good 6 . Kaushik Fating | Pritam Shende "Advantages & Challenges of Generative AI" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Recent Advances in Computer Applications and Information Technology , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101876.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101876/advantages-and-challenges-of-generative-ai/kaushik-fating

The “Resume Builder with AI Analyzer” is an intelligent web based application designed to assist job seekers in creating professional and ATS compatible resumes. The system utilizes Artificial Intelligence techniques to analyze resumes and compare them with job descriptions to identify relevant keywords, evaluate content quality, and provide optimization suggestions. The application helps users improve their resumes by suggesting missing skills, formatting enhancements, and keyword optimization. By increasing ATS compatibility and overall resume quality, the system enhances the chances of candidates being shortlisted by recruiters. The project combines modern web technologies and AI driven analysis to provide a user friendly and efficient solution for resume creation and evaluation. Priyanshu Pise "Resume Builder with AI Analyzer" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102154.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102154/resume-builder-with-ai-analyzer/priyanshu-pise

Healthcare expenses have increased significantly worldwide, creating challenges for individuals, insurance providers, and healthcare organizations. Predicting medical costs accurately helps insurance companies determine premiums, enables healthcare providers to optimize resources, and assists patients in financial planning. This research presents a machine learning based Health Cost Prediction System that estimates an individuals medical expenses based on demographic and health related factors such as age, gender, Body Mass Index BMI , smoking habits, number of dependents, and geographic region. Various machine learning algorithms including Linear Regression, Decision Tree Regression, Random Forest Regression, and Gradient Boosting Regression are evaluated to determine the most effective model for cost prediction. The proposed system demonstrates how data driven approaches can improve prediction accuracy and support informed healthcare decision making. Shivaji Dhok "Health Cost Prediction Using Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102155.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102155/health-cost-prediction-using-machine-learning/shivaji-dhok

Email spam detection is an important application of machine learning and data mining that aims to identify and filter unsolicited, fraudulent, or unwanted emails. The increasing volume of spam emails poses significant challenges to individuals and organizations, including security threats, phishing attacks, and loss of productivity. This project proposes an email spam detection system that analyzes email content and classifies messages as either spam or legitimate ham . Various text preprocessing techniques such as tokenization, stop word removal, and feature extraction are applied to improve classification accuracy. Machine learning algorithms, including Naïve Bayes, Support Vector Machine SVM , and Decision Trees, can be utilized to train the model on labeled email datasets. The performance of the system is evaluated using metrics such as accuracy, precision, recall, and F1 score. The proposed approach helps automate email filtering, reduces user effort, and enhances cybersecurity by minimizing the impact of spam and malicious emails Sumanshu Mehar "Email Spam Detection" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102159.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102159/email-spam-detection/sumanshu-mehar

Higher education is considered an important tool for the intellectual, social, economic and cultural development of an individual. Education develops knowledge, skills, leadership qualities and a sense of social responsibility in an individual. However, even in todays modern and technological era, gender inequality is clearly visible in the field of higher education. Women in particular face obstacles in getting equal opportunities in higher education due to social norms, economic constraints, patriarchal mentality, security issues and institutional constraints. Dr. Kavita Ramchandra Kamble "???? ?????????? ???? ????" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102102.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102102/????-??????????-????-????/dr-kavita-ramchandra-kamble

The Eduwings College Management System is a web based application developed to automate and simplify the academic and administrative activities of educational institutions. Managing student records, admissions, enquiries, certificates, and other academic information manually is time consuming, errorprone, and difficult to maintain. The proposed system provides a centralized digital platform that enables efficient management of college operations while reducing paperwork and administrative workload. The system is designed using a Role Based Access Control RBAC mechanism, ensuring that administrators, faculty members, and students can securely access only the functionalities assigned to their roles. This enhances data security, confidentiality, and operational efficiency. The user interface is developed using HTML, CSS, and JavaScript to provide a responsive and user friendly experience, while the backend is built using Node.js and Express.js. Secure authentication is implemented using JSON Web Tokens JWT and cookies. The system uses MongoDB as the database for storing and managing information related to users, admissions, enquiries, certificates, and other institutional records. The Eduwings College Management System successfully digitizes manual processes, improves data management, accelerates administrative tasks, and enhances communication among stakeholders. The system provides a reliable, secure, and efficient solution for modern educational institutions, contributing to improved productivity and better management of academic operations. Sachin Mehune "Eduwings Platform" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102157.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102157/eduwings-platform/sachin-mehune

In the era of digital commerce, online platforms generate enormous volumes of transaction data every day. This data contains valuable information about customer preferences, purchasing behaviour, product demand, pricing trends, and overall market dynamics. Understanding these behavioural patterns is essential for businesses to improve customer experience, optimize product strategies, and make informed decisions. This research presents a data driven approach for analysing behavioural patterns in e commerce transaction data. Product information was collected from Flipkart using automated web scraping techniques implemented with Selenium WebDriver and Python. The dataset primarily includes electronic product categories such as mobiles, headphones, smart watches, speakers, and accessories, along with attributes like price, ratings, and customer reviews. After collection, the raw data was stored in CSV format and processed using Python libraries including Pandas and NumPy. Data preprocessing techniques such as duplicate removal, handling missing values, formatting correction, and product categorization were applied to improve data quality and analytical accuracy. Exploratory Data Analysis EDA was then performed to identify customer preferences, spending behaviour, product popularity, and emerging demand trends. The study further demonstrates how visualization tools such as Power BI can transform complex transaction records into intuitive dashboards and reports. These visual insights help businesses quickly identify patterns, compare product performance, and support data driven decision making. Overall, the research highlights the practical value of combining web scraping, data preprocessing, behavioural analysis, and visualization to understand online consumer behaviour and enhance strategic business planning. Sarvesh Umale "Exploring Behavioural Patterns in Transaction Data: A Data-Driven Study" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102156.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102156/exploring-behavioural-patterns-in-transaction-data-a-datadriven-study/sarvesh-umale

Teacher professional development is increasingly shaped by the need for interdisciplinary and holistic approaches aligned with contemporary educational reforms. In this context, the National Education Policy 2020 advocates the integration of multidisciplinary learning within teacher education to enhance pedagogical effectiveness, critical thinking, and learner outcomes. The present study investigates pre service teachers perceptions of multidisciplinary education with particular reference to professional development and institutional support. The study employed a convergent mixed method research design involving 75 pre service teachers from teacher education institutions. Quantitative data were collected using a structured Likert scale questionnaire, while qualitative insights were obtained through open ended responses. The instrument demonstrated excellent internal consistency reliability Cronbach’s a = 0.957 . Descriptive statistical analysis revealed generally positive perceptions toward multidisciplinary education Mean range 2.04–2.67 , with comparatively higher scores in professional readiness and lower scores in teaching practice implementation. Thematic analysis identified major concerns including insufficient practical exposure, structural limitations, inadequate interdisciplinary integration, and lack of institutional mentoring. Triangulated findings indicate a substantial gap between conceptual understanding and practical implementation. Although pre service teachers exhibit favorable attitudes toward multidisciplinary pedagogy, their operational readiness remains limited due to systemic and pedagogical constraints. The study highlights the need for structured institutional frameworks, experiential teacher preparation, technology integrated pedagogical training, and strengthened mentorship models to effectively realize the objectives of multidisciplinary teacher education envisioned in NEP 2020. Asst. Prof. Ms. Rachana Das | Dr. Tulika Tyagi "Multidisciplinary Education in Teacher Education: Pre-Service Teachers Perceptions, Professional Development, and Institutional Support" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102101.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102101/multidisciplinary-education-in-teacher-education-preservice-teachers-perceptions-professional-development-and-institutional-support/asst-prof-ms-rachana-das

The rapid growth of internet technologies has significantly transformed traditional business models into digital platforms. E commerce websites enable customers to purchase products and services online without geographical limitations. This research presents the design and development of a Computer Shop E Commerce Website that facilitates online browsing, ordering, and management of computer related products. The system aims to provide a user friendly platform for customers while reducing manual business operations. The website incorporates modern web technologies such as HTML, CSS, JavaScript, and AJAX to improve user experience and operational efficiency. The study demonstrates how e commerce solutions contribute to business growth, customer convenience, and digital transformation. Ankit Karmore "Computer Shop Web-Site" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102153.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102153/computer-shop-website/ankit-karmore

The rise of artificial intelligence AI revolutionized both cybersecurity defenses and cyber criminals’ methods to exploit vulnerabilities. Cybercriminals continue to exploit previously undiscovered vulnerabilities, known as zero day attacks, posing severe threats to cyber security. These attacks are particularly challenging to detect, as they target unknown weaknesses in systems before security teams can respond or act. Traditional intrusion detection systems IDS rely heavily on pre existing attack signatures, making them ineffective against zero day threats. Machine learning ML algorithms have recently become a promising solution for enhancing IDS capabilities by identifying anomalies and predicting potential vulnerabilities in real time. Aniket Mehar "Zero Day Hunter : AI-Based Detection of Zero-Day Attacks in Modern Network Environment" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102149.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102149/zero-day-hunter--aibased-detection-of-zeroday-attacks-in-modern-network-environment/aniket-mehar

Information and Communication Technology ICT has become central to contemporary education. Teachers are expected to use digital tools for lesson planning, classroom instruction, assessment, communication, and professional development. Therefore, B.Ed. student teachers must develop strong ICT competencies before entering the teaching profession. This conceptual paper presents a framework for understanding ICT competency development among B.Ed. student teachers through three interrelated dimensions knowledge, skills, and attitudes. ICT knowledge refers to understanding digital concepts, tools, and pedagogical applications ICT skills involve the practical ability to use technological tools effectively and ICT attitude reflects beliefs, confidence, and willingness to integrate technology into teaching. The paper discusses the theoretical foundations, conceptual model, and implications for teacher education institutions. Asst. Prof. Pratibha Kambli | Prof. (Dr.) Sanjay Shedmake "A Conceptual Framework for ICT Competency Development among Pre-Service Teachers" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102103.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102103/a-conceptual-framework-for-ict-competency-development-among-preservice-teachers/asst-prof-pratibha-kambli

The rapid advancement of Artificial Intelligence and Natural Language Processing technologies has transformed the educational sector by introducing intelligent systems capable of automating communication and academic support services. The AI Powered Smart Education Chatbot is designed to provide students and parents with instant, accurate, and reliable responses related to admissions, academic guidance, fee structures, scholarships, placements, and graduation planning. The proposed system uses conversational AI techniques to simulate human interaction and provide a personalized user experience. The system integrates Natural Language Processing, database management, and intelligent response generation to improve accessibility and reduce administrative workload. The chatbot is available 24 7 and acts as a centralized platform for educational assistance. Agile development methodology is adopted for designing, implementing, and testing the system. The proposed chatbot significantly improves response time, user engagement, and operational efficiency. Future enhancements may include multilingual support, voice enabled interaction, machine learning recommendation systems, and personalized learning analytics. Mohini Harish Umredkar "AI-Powered Smart Education Chatbot for Admission and Academic Guidance" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102147.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102147/aipowered-smart-education-chatbot-for-admission-and-academic-guidance/mohini-harish-umredkar

The present study aims to identify the academic stress among IXth Standard students of Parag English School. Results of the study reveal that more than 50 students are academically stressed due to various factors including online classes, school environment, family background and economic background. Shweta Shukla | Asst. Prof. Dr. Minoo Raichurkar "A Study of Reasons Leading to Academic Stress Among the IXth Standard Students" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102104.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102104/a-study-of-reasons-leading-to-academic-stress-among-the-ixth-standard-students/shweta-shukla-

The rapid growth of e commerce platforms has significantly increased the number of products available to online consumers. As a result, customers often face difficulties in discovering products that match their preferences and requirements. Recommendation systems have emerged as an effective solution for addressing this challenge by providing personalized product suggestions based on user behavior and interests. This research presents the design and development of an Online E Commerce Recommendation System that analyzes user activities such as browsing history, search patterns, product views, and purchase history to generate relevant product recommendations. The proposed system utilizes web technologies along with recommendation algorithms to enhance product discovery and improve user experience. The recommendation engine assists customers in finding suitable products efficiently, thereby reducing search time and increasing customer satisfaction. From a business perspective, the system contributes to higher customer engagement, improved conversion rates, and increased sales performance. The study demonstrates how recommendation systems can play a crucial role in modern e commerce applications and highlights their potential for future integration with Artificial Intelligence and Machine Learning techniques. Disha Pravin Chavhan "Online E-Commerce Recommendation System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102152.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102152/online-ecommerce-recommendation-system/disha-pravin-chavhan

This paper documents the design, implementation, and evaluation of a professional real estate website for R R Developers, created to improve online visibility, generate leads, and support digital marketing. The project used WordPress, Elementor, custom HTML CSS JavaScript, and SEO tooling Rank Math, Google Search Console to deliver a responsive, conversion focused site. The study reports implementation choices, performance and lead capture outcomes, testing strategy, and recommendations for future enhancements such as CRM integration and immersive property tours. From the project document “RR Developers wanted a professional website to bring their real estate business online, improve visibility, and support digital marketing efforts.” This sentence summarizes the client need that motivated the work. Utkarsh Burle "Real Estate Business Website - RR Developers" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102151.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102151/real-estate-business-website--rr-developers/utkarsh-burle

Adolescence is a critical developmental stage where students begin to explore their identities and future goals. This study examines the level of career awareness and aspirations among 100 adolescent students of Standard IX in an English Medium secondary school for the academic year 2025 26. The research utilised a descriptive survey method, employing a structured questionnaire to measure awareness across four domains career options, self assessment, sources of information, and decision making. The study involved a pre test to establish baseline awareness, followed by a systematic intervention comprising career guidance sessions, aptitude and personality tests, workshops, and goal setting activities. Findings revealed a significant improvement in student knowledge for instance, awareness of diverse career options rose from 7 in the pre test to 96 in the post test. The study concludes that structured career guidance is essential in secondary education to help students align their aspirations with their personal strengths and societal opportunities. Mrs. Mamatha Shetty "A Study on Career Awareness and Aspiration among Adolescent Students of Secondary Schools" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102107.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102107/a-study-on-career-awareness-and-aspiration-among-adolescent-students-of-secondary-schools/mrs-mamatha-shetty

This paper examines the structured methodologies required to establish secure, legally compliant, and optimized enterprise computing environments using proprietary software ecosystems. Focusing on Microsoft Windows Operating Systems and the Microsoft Office 365 Productivity Suite, this study explores the technical protocols of deployment alongside modern licensing frameworks. Historically, uncoordinated software installations have led to security vulnerabilities, configuration drift, and compliance penalties. Through a systematic literature review, this research consolidates industry standard installation practices, hardware validation procedures, and official cryptographic activation mechanisms—such as the Key Management Service KMS and Cloud Based Subscription Activation. The paper demonstrates that enforcing strict legal procurement pipelines and automated deployment policies mitigates systemic security risks and ensures long term infrastructure stability. 1, 2 . Prathamesh Rajendra Kadukar "A Comprehensive Study of Installation and Activation of Licensed Microsoft Windows Operating Systems" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102150.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102150/a-comprehensive-study-of-installation-and-activation-of-licensed-microsoft-windows-operating-systems/prathamesh-rajendra-kadukar

In today’s educational system, academic achievement alone is not enough for the complete development of students. Secondary school students face many challenges such as stress, peer pressure, emotional problems, competition, and social conflicts. Therefore, life skills education has become an important part of modern education. Life skills education helps students develop communication skills, problem solving ability, decision making skills, emotional control, self confidence, teamwork, and leadership qualities. This research paper studies the impact of life skills education on secondary school students. It explains the meaning and importance of life skills education and its role in improving students’ academic performance, emotional development, social behavior, and personality development. The paper also discusses the challenges faced in implementing life skills education and provides suggestions for improvement. The study concludes that life skills education plays a major role in preparing students for successful academic, personal, and social life. Ms. Rohini Jadhav "Impact of Life Skills Education on Secondary School Students" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102105.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102105/impact-of-life-skills-education-on-secondary-school-students/ms-rohini-jadhav

This paper explores the connections between life skills, soft skills, and 21st century skills in modern education. It aims to clarify the differences and similarities between these skill sets, examine their roles in the overall development of students, and discuss their effects on curriculum design and teaching strategies. The findings emphasize the importance of integrating these skills to prepare students for complex and changing global environments. By looking at the evolving definitions and frameworks that shape these constructs, this paper highlights their combined significance in developing adaptable, resilient, and capable individuals who can succeed in various personal and professional situations. Additionally, it addresses the challenges and opportunities of implementing these skills in educational systems, focusing on the roles of policy, teacher training, and new assessment methods in promoting skill development. It also considers the social and economic factors that affect skill acquisition and stresses the need for inclusive education to address equity gaps. Mrs. Savita Sandip Upasani | Dr. Jayesh R. Jadhav "Theoretical Linkages Between Life Skills, Soft Skills, and 21st-Century Skills in Contemporary Educatio" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102106.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102106/theoretical-linkages-between-life-skills-soft-skills-and-21stcentury-skills-in-contemporary-educatio/mrs-savita-sandip-upasani

The E Learning Management System is a web based application designed to facilitate online education and digital learning management. The system allows students to access courses, assignments, quizzes, study materials, and video lectures through an online platform. Teachers can upload content, monitor student progress, conduct assessments, and manage educational activities efficiently. The proposed system reduces manual work and improves accessibility, scalability, and communication between students and instructors. The project is developed using modern web technologies such as HTML, CSS, JavaScript, PHP Python, and MySQL. Tushar Mishra "E-Learning Management System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102148.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102148/elearning-management-system/tushar-mishra

In todays information and technology driven era, Information and Communication Technology ICT has become an effective tool for social, educational, economic, and cultural development. Vidyadhar Dattatreya Karnuk | Prof. Pratibha Kambli "?????? ???????????? ?????? ? ???????? ?????????? (ICT)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102108.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102108/??????-????????????-??????-?-????????-??????????-ict/vidyadhar-dattatreya-karnuk

The rapid advancement of Artificial Intelligence and Natural Language Processing technologies has transformed the educational sector by introducing intelligent systems capable of automating communication and academic support services. The AI Powered Smart Education Chatbot is designed to provide students and parents with instant, accurate, and reliable responses related to admissions, academic guidance, fee structures, scholarships, placements, and graduation planning. The proposed system uses conversational AI techniques to simulate human interaction and provide a personalized user experience. The system integrates Natural Language Processing, database management, and intelligent response generation to improve accessibility and reduce administrative workload. The chatbot is available 24 7 and acts as a centralized platform for educational assistance. Agile development methodology is adopted for designing, implementing, and testing the system. The proposed chatbot significantly improves response time, user engagement, and operational efficiency. Future enhancements may include multilingual support, voice enabled interaction, machine learning recommendation systems, and personalized learning analytics. Mohini Harish Umredkar "AI-Powered Smart Education Chatbot for Admission and Academic Guidance" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102147.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102147/aipowered-smart-education-chatbot-for-admission-and-academic-guidance/mohini-harish-umredkar

This study investigates the influence of self efficacy on prospective teachers willingness and ability to adopt AI integrated teaching practices. With the increasing incorporation of artificial intelligence in educational settings, understanding the psychological factors that affect technology adoption is critical. Self efficacy, defined as an individuals belief in their capacity to execute behaviors necessary to produce specific performance attainments, is hypothesized to play a pivotal role in shaping prospective teachers attitudes and intentions toward AI enabled instructional methods. The research employs a mixed methods approach to assess the relationship between self efficacy levels and the adoption of AI tools in teaching simulations and lesson planning. Findings aim to inform teacher education programs by highlighting the importance of enhancing self efficacy to facilitate effective integration of AI technologies in future classrooms. Mrs. Savita Sandip Upasani | Dr. Jayesh R. Jadhav "Examining the Impact of Self-Efficacy on Prospective Teachers Adoption of AI-Integrated Teaching Practices" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102109.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102109/examining-the-impact-of-selfefficacy-on-prospective-teachers-adoption-of-aiintegrated-teaching-practices/mrs-savita-sandip-upasani

Modern communication networks rely on multiple protocols to manage data transmission efficiently. However, traditional protocol optimization techniques often struggle to adapt dynamically to changing network conditions, resulting in increased latency, packet loss, and reduced throughput. This challenge motivated the development of the Neural Network Based Protocol Optimizer NN PO . This paper presents the design and implementation of an intelligent optimization system that utilizes Artificial Neural Networks ANNs to analyze network traffic patterns and automatically optimize communication protocol parameters in real time. The NN PO system collects network performance metrics such as bandwidth utilization, latency, packet delivery rate, congestion levels, and transmission errors. These parameters are processed through a trained neural network model that predicts optimal protocol configurations for varying network conditions. The system continuously learns from historical and real time network data, enabling adaptive decision making and improved communication efficiency. Yash Wadpalliwar "Neural Network Based Protocol Optimizer (NN-PO)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102146.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102146/neural-network-based-protocol-optimizer-nnpo/yash-wadpalliwar

Web applications today need to talk to users away. This makes the application more interesting and responsive. Old systems that constantly check for updates have delays and waste resources. This project is about a service that sends notifications when something happens in the system. It does this in a way. From the perspective of the person building the user interface the system is about creating an interface that can change and respond quickly. It gets notifications. The system can handle users and is efficient. It is suitable for all kinds of applications, such, as shopping, healthcare and education. Rufaiz Ansar Baig "Event Driven Notification Broadcasting Service Web Development" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102047.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102047/event-driven-notification-broadcasting-service-web-development/rufaiz-ansar-baig

Teaching is an emotionally demanding profession that requires educators to regulate emotions effectively while maintaining pedagogical competence, classroom discipline, and positive student relationships. Emotional competence is particularly important for pre service teachers who are in the process of developing their professional identity and instructional confidence. The present study investigates emotional awareness, emotional challenges, emotional regulation, coping strategies, and support needs among pre service teachers. The study employed a descriptive correlational survey design involving 67 pre service teachers enrolled in teacher education programmes. Quantitative data were collected using a structured questionnaire consisting of 20 Likert scale items measuring five dimensions of emotional competence. Descriptive statistics and Pearson’s correlation analysis were utilized to examine relationships among the variables. Reliability analysis using Cronbach’s Alpha a = 0.64 indicated moderate internal consistency acceptable for exploratory educational research. The findings revealed that participants demonstrated high emotional awareness M = 4.09 and strong coping strategies M = 4.02 , while experiencing moderate emotional challenges M = 2.85 during teaching practice. Correlation analysis showed significant positive relationships between emotional awareness, emotional regulation, and coping strategies, whereas emotional challenges demonstrated negative correlations with these dimensions. The results further highlighted a strong perceived need for emotional management training and structured institutional support. The study underscores the importance of integrating emotional intelligence development, reflective practices, emotional resilience training, and mentorship support within teacher education programmes to strengthen emotional competence and professional well being among future educators. Asst. Prof. Ms. Rachana Das | Ms. Ansha Wandalkar "Coping with Emotions among Pre-Service Teachers: An Empirical Study on Emotional Awareness, Regulation, and Support Needs" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102110.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102110/coping-with-emotions-among-preservice-teachers-an-empirical-study-on-emotional-awareness-regulation-and-support-needs/asst-prof-ms-rachana-das

The integration of Information and Communication Technology ICT has emerged as a central component of contemporary educational transformation, aiming to enhance pedagogical effectiveness, learner engagement, and digital competency development. Despite increasing policy emphasis on digital pedagogy, a persistent gap continues to exist between teachers’ theoretical understanding of ICT and its effective classroom implementation. The present study investigates and compares the theory–practice gap among pre service and in service teachers in relation to ICT integration. The study employed a quantitative comparative survey research design involving 46 pre service teachers and 50 in service teachers. Data were collected using a structured questionnaire consisting of 22 Likert scale items measuring six dimensions theoretical knowledge, practical readiness, ICT skills, training and exposure, barriers, and perceived theory–practice gap. Reliability analysis indicated excellent internal consistency Cronbach’s Alpha = 0.90 for pre service teachers and 0.88 for in service teachers . Descriptive statistics and independent samples t tests were utilized for data analysis. The findings reveal that pre service teachers demonstrate significantly higher levels of theoretical knowledge and ICT training exposure, whereas in service teachers report greater barriers and a more pronounced theory–practice gap. No statistically significant differences were observed in practical readiness and ICT skills. The results suggest that although teacher education programmes provide conceptual preparedness, real world institutional and infrastructural constraints hinder effective ICT implementation. The study highlights the need for experiential learning opportunities, institutional support systems, continuous professional development, and context responsive teacher preparation programmes to effectively bridge the gap between ICT theory and classroom practice. Asst. Prof. Ms. Rachana Das | Ms. Neha Harshad Deshpande "Bridging the Theory–Practice Gap in ICT Integration: A Comparative Study of Pre-Service and In-Service Teachers" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102111.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102111/bridging-the-theory–practice-gap-in-ict-integration-a-comparative-study-of-preservice-and-inservice-teachers/asst-prof-ms-rachana-das

Face detection is a job in computer vision and data science. It helps with things like recognition, surveillance systems, biometric authentication and human computer interaction. The main goal of this research is to make a face detection system that works in time. The classifier is already trained on images so it can find eyes, nose and mouth with accuracy. Our system works with images. Live webcam feeds. We test it with both. We convert them to grayscale to make it faster. This helps our system work quickly. Our face detection model is fast so it is good for applications that need processing. Face detection is important for these applications. It does not need a lot of power so it can run on systems that do not have a lot of power. This makes face detection for devices. The test results show that it works well in light and can find many faces at once. We see this in our tests. It may not work well in light or when faces are hidden. We need to improve face detection for these cases. The results of this research show that OpenCV face detection works well in life. Face detection is really helpful. It is fast and accurate. We like these results. This work helps the field by giving a way to detect faces. Face detection is important, for things. We can make face detection better with learning and practice. We will keep working on face detection. In the future we can add models like CNNs to make face detection more accurate and adaptable. This will make face detection better. We will try this. See how it works with face detection. Shreyash Sutrave "Face Detection Using OpenCV” by Using Python" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102145.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102145/face-detection-using-opencv”-by-using-python/shreyash-sutrave

The rapid expansion of retail participation in global financial markets has created significant challenges in processing and analyzing trading data efficiently. Traditional charting platforms often produce cognitive overload because they lack automated, forward looking trend synthesis, leaving complex technical analysis to the end user. This paper presents the design and implementation of PredictX, an AI driven financial market intelligence terminal that utilizes statistical machine learning and hybrid momentum techniques to enhance the accuracy and rendering speed of short term price target generation. The proposed system processes monocular time series data using sequential API integration and generates instantaneous trend projections to better understand the momentum behind the visual market frames. It then applies a 14 day Linear Regression engine combined with a 10 day Simple Moving Average SMA algorithm to optimize and render the most realistic 24 hour targets. The system architecture consists of modules for secure authentication, asynchronous data preprocessing, algorithmic synthesis, categorical sentiment classification, and dynamic Glassmorphism rendering. Techniques such as single page application SPA state management and Chart.js hardware accelerated canvases are integrated to improve visual precision and fidelity. Experimental evaluation shows that the proposed PredictX approach outperforms traditional heavy Python based predictive frameworks in terms of render speed, server memory usage, and execution latency. The system demonstrates improved algorithmic understanding, faster generation times, and higher user satisfaction. The proposed solution is suitable for applications such as retail trading platforms, educational finance tools, and personal portfolio management. The results indicate that integrating optimized native array mathematics into MVC based web mechanisms significantly enhances the effectiveness and efficiency of modern financial computing systems. Aman Singh "Predictx: An AI-Powered Financial Market Intelligence Terminal" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102144.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102144/predictx-an-aipowered-financial-market-intelligence-terminal/aman-singh

Mass assemblies taken in open areas are usually safety hazards because of overcrowding, mismanagement, or delayed emergency response. Traditional surveillance tools are very manual oriented and restrict the ability to capture severe conditions on time. This study proposes an Intelligent Crowd Detection and Accident Prevention System using OpenCV controlled image processing integrated with YOLOv8 object detection and IoT communication. The system estimates crowd density through land visibility analysis, tracks movement velocity, and delivers threshold based warnings to authorities. Zone based monitoring detects localized overcrowding. The architecture offers an affordable, scalable, and real time solution flexible to diverse settings like stadiums, transport stations, and community events, achieving 90–92 accuracy in crowd estimation with 2–3 second alert response time. Siddhi Atkare "Design and Deployment of an Intelligent Crowd Detection and Accident Prevention System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102143.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102143/design-and-deployment-of-an-intelligent-crowd-detection-and-accident-prevention-system/siddhi-atkare

The rapid growth of e commerce and quick commerce industries has resulted in the generation of large volumes of business data on a daily basis. Managing and analyzing this data manually is a complex and time consuming process that often fails to provide accurate insights for effective decision making. To overcome these challenges, this research presents the development of a “Blinkit Dashboard – Data Analysis and Visualization System Using Python and Power BI.” The proposed system focuses on collecting, processing, analyzing, and visualizing business data related to sales, customers, products, categories, and delivery operations. Python libraries such as Pandas, NumPy, Matplotlib, and Seaborn are used for data preprocessing, cleaning, and analytical operations, while Power BI is used to create interactive dashboards and graphical reports. Akshay Manekar "Blinkit Dashboard – Data Analysis and Visualization System Using Python & Power BI" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102142.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102142/blinkit-dashboard-–-data-analysis-and-visualization-system-using-python-and-power-bi/akshay-manekar

The rapid growth of Artificial Intelligence and automation technologies has increased the demand for smart virtual assistant systems capable of simplifying complex software setup and system management tasks. This research presents Jarvis One Click Set Up, an AI powered automation platform designed to streamline installation, configuration, and execution processes through a centralized and user friendly interface. The system minimizes manual intervention by automating repetitive setup operations, thereby reducing technical complexity and improving productivity for developers and end users. Mr. Ehsan Danish "Jarvis – AI Powered Virtual Assistant and Automation System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102141.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102141/jarvis-–-ai-powered-virtual-assistant-and-automation-system/mr-ehsan-danish

YARDAT is an advanced Online Marketplace System designed to provide a secure, scalable, and user friendly platform for buyers and sellers. The system enables users to browse products, manage orders, process online payments, and track deliveries efficiently. The project integrates cloud based architecture, secure authentication, recommendation systems, and real time analytics to improve the online shopping experience. Yukti Piplewar "Yardat: Online Market Place System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102138.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102138/yardat-online-market-place-system/yukti-piplewar

Despite the progressive vision of the National Education Policy NEP 2020, a persistent disconnect continues to exist between policy intent and classroom realities in the implementation of inclusive education in India. While the policy advocates equitable, flexible, and learner centered approaches, its translation into classroom practice remains inconsistent and fragmented, particularly within diverse and socio culturally complex educational settings. Addressing this critical gap, the present conceptual paper proposes a Contextualised Indian Model for Inclusive Pedagogy C IMIP , designed to operationalise inclusive education through structured, context sensitive, and practice oriented pedagogical strategies. The proposed framework integrates five interrelated dimensions—multilingual pedagogy, socio emotional inclusion, differentiated instruction, community participation, and assessment flexibility—grounded in Universal Design for Learning UDL , constructivist learning theory, and social inclusion theory. The model conceptualises inclusive pedagogy as a dynamic and interconnected process rather than a collection of isolated interventions. By contextualising global inclusive education frameworks within Indian educational realities, the study offers a comprehensive pedagogical approach for educators, teacher educators, policymakers, and institutions. The paper contributes to the discourse on inclusive education by bridging the divide between policy aspirations and pedagogical practice while advancing a holistic and contextualised understanding of inclusion in Indian classrooms. The study further highlights the need for practice oriented teacher education, systemic institutional support, and flexible pedagogical structures for the effective implementation of inclusive education under NEP 2020. Asst. Prof. Ms. Rachana Das | Mr. Omkar Yadav "Bridging Policy Intent and Classroom Realities: A Contextualised Indian Framework for Inclusive Pedagogy under NEP 2020" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102112.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102112/bridging-policy-intent-and-classroom-realities-a-contextualised-indian-framework-for-inclusive-pedagogy-under-nep-2020/asst-prof-ms-rachana-das-

Video editing is a critical skill in the modern digital landscape, required by content creators, educators, journalists, and professionals across industries. Traditional video editing tools demand significant technical expertise, prolonged learning curves, and complex timeline based interfaces that discourage casual adoption. This paper presents Praxys Studio, an intelligent browser based video editing platform that leverages Artificial Intelligence and Natural Language Processing NLP to allow users to edit videos through plain English descriptions. Instead of manually trimming clips, adjusting color grades, or configuring export settings, users simply type commands such as trim to the best 30 seconds or make it cinematic, and the system interprets these instructions and applies the corresponding FFmpeg video processing operations in real time. The system processes all video data locally in the browser using FFmpeg compiled to WebAssembly, ensuring complete user privacy with zero cloud uploads. Experimental evaluation demonstrates high intent to operation translation accuracy, sub second processing latency for most operations, and strong user satisfaction scores across diverse editing tasks. Praxys Studio represents a significant step toward democratizing video production by combining AI language understanding with professional grade video processing capabilities. Atharva Verma "Praxys Studio: An AI-Powered Natural Language Video Editing System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102140.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102140/praxys-studio-an-aipowered-natural-language-video-editing-system/atharva-verma

The increased use of digital infrastructure in education has led to increased scrutiny of traditional paper based examination methods, which often run into logistical difficulties, such as the distribution of physical exams, manual grading, the storage of answer sheets and other exam materials, and the potential for cheating. There has been a need for alternative methods of administering assessments remotely since the COVID 19 pandemic and many educational institutions have turned to tools that have been hastily adapted for online use, illustrating the continued lack of a scalable, secure, and purpose built examination platform. This paper describes an innovative Cloud Based Online Examination System designed and developed to provide a solution for the problems outlined above using a distributed service oriented architecture that is hosted on Amazon Web Services. The system supports the entire examination lifecycle, including the creation and randomization of question papers, the delivery of timed exams, automated grading of exams, processing of exam results, and performance analytics, through a single web interface that can be accessed from any device with internet access. Three distinct user types are represented Admin, Instructor, and Student. Each user type has its own dashboard i.e., Instructor Dashboard, Student Dashboard, and Admin Dashboard with role specific access controls, and all role specific access controls are enforced using JSON Web Tokens for authentication. Specifically, to help with the exam creation process, the Question Bank module provides a categorically organized pool of questions that an Instructor can use to develop exam sets that include dynamically created randomizations to minimize the re use of the same paper by different cohorts of students during a given time period. Additionally, an integrated proctoring module using both webcam monitoring and tab switch detection to deter cheating during the live administration of exams. The system is built on a Node.js microservices software architecture, uses React.js as its front end technology, and stores user records in MySQL, question data in MongoDB, and result data in PostgreSQL, resulting in a polyglot data storage architecture. AWS Elastic Load Balancing and AWS Auto Scaling Groups are used to manage variable volumes of exams delivered at the same time, and Redis is used to cache frequently accessed question data to reduce the number of database calls. The Performance Benchmarks for the proposed exam taking platform have been developed on a simulated exam giving receiving scenario of 10,000 concurrent users, and the average response time for a test to return results is 500 ms. For 12 months, the Availability of the proposed exam taking platform has achieved a sustained level of 99.3 Availability. Compared to the Performance Benchmarks established using a representative sample of a traditional online exam platform, the average module response time of the proposed platform decreased by 64.7 over the same time period. Security evaluations have confirmed that the system is resistant to common types of web vulnerabilities, such as SQL injection, cross site scripting, and session hijacking. These evaluations were conducted using the OWASP ZAP scanning tool. A user acceptance testing process was conducted with 240 students and 18 instructors from three departments and the resulting System Usability Scale score of 84.6 indicates that the system is highly usable. The time required to process results that were previously completed over a three to five day period with a paper based system has been reduced to only seconds once an exam has been submitted. The following paper contains comprehensive comparative analysis, system design walkthroughs, performance evaluation, and an honest discussion of the current limitations and directions in the future for the system, including offline examination capabilities and AI generated questions. Aman Pathan "Cloud-Based Online Examination System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102135.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102135/cloudbased-online-examination-system/aman-pathan

SAFE4SURE is an AI powered Mobile Device Management and Digital Wellbeing System developed to monitor smartphone activities, improve productivity, reduce screen addiction, and provide secure parental control features. The system uses Artificial Intelligence and cloud technologies to analyze user behavior, detect excessive usage patterns, and generate personalized wellbeing recommendations. The research focuses on mobile security, digital wellness analytics, application monitoring, and real time usage management. Sharshti Bisen "SAFE4SURE: AI Based Mobile Device Management & Digital Wellbeing System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102137.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102137/safe4sure-ai-based-mobile-device-management-and-digital-wellbeing-system/sharshti-bisen

This project presents the design and development of an AI Assistant that can interact with users and provide intelligent responses in real time. The system is based on technologies such as Artificial Intelligence, Machine Learning, and Natural Language Processing, which enable it to understand and process human language effectively. The AI Assistant accepts user input in the form of text or voice, analyzes the query, and generates appropriate responses based on predefined logic or learning models. The system is designed with multiple modules, including user interface, input processing, NLP module, and response generation module, ensuring smooth and efficient communication. The main objective of this project is to simplify human computer interaction, reduce manual effort, and save time by automating basic tasks. The assistant can be applied in various domains such as customer support, education, and business services. Grishma Chamatkar "AI-Based Virtual Assistant for Real-Time Human Computer Interaction" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102059.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102059/aibased-virtual-assistant-for-realtime-human-computer-interaction/grishma-chamatkar

This project presents the design and implementation of a high performance, web based 3D World Map Visualization interface. Traditional 2D maps often struggle to represent complex volumetric data and spatial relationships effectively. This project addresses these limitations by leveraging WebGL via Three.js and React to create an immersive three dimensional environment. The system is built using TypeScript to ensure type safety and scalable architecture. The core implementation involves a custom rendering engine that extrudes geospatial data GeoJSON into 3D meshes, allowing for the visualization of data density through height and color gradients. Key technical features include GPU accelerated performance, a responsive HUD Heads Up Display built with React, and an interactive Raycasting system for realtime object selection. The user interface follows modern UI UX principles, employing a Dark Mode aesthetic with neon data highlights to reduce cognitive load and enhance visual clarity. The result is a highly interactive tool capable of rendering thousands of data points at 60 FPS, providing a superior platform for urban planning, logistics monitoring, and global data analysis. Aditya Vinayak kochare "3D Visualization Map Using UI/UX" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102136.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102136/3d-visualization-map-using-uiux/aditya-vinayak-kochare

The paradigm of special education has undergone a massive transformation globally, transitioning from models of segregation and integration to the more equitable framework of inclusive education. This conceptual paper explores the theoretical underpinnings, practical implications, and systemic challenges associated with implementing inclusive education for Children with Special Needs CWSN . Grounded in the Social Model of Disability, Vygotsky’s Sociocultural Theory, and the principles of Universal Design for Learning UDL , this paper argues that true inclusion extends beyond mere physical placement in a mainstream classroom. It requires a fundamental restructuring of pedagogical practices, school culture, and systemic policies to ensure equitable access, active participation, and meaningful learning outcomes for all students. The paper concludes by proposing actionable strategies for educators, policymakers, and stakeholders to bridge the gap between inclusive policy and classroom practice. Mrs. Nirupama Sahu "Beyond Integration: Fostering Genuine Inclusive Education for Children with Special Needs (CWSN)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102114.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102114/beyond-integration-fostering-genuine-inclusive-education-for-children-with-special-needs-cwsn/mrs-nirupama-sahu

Artificial Intelligence AI has emerged as a transformative force in education, reshaping teaching methodologies, assessment practices, and learner engagement. While AI offers significant pedagogical benefits, it simultaneously raises ethical concerns such as data privacy, academic integrity, algorithmic bias, and over dependence on technology. The present study examines the ethical preparedness of B.Ed. student teachers in relation to AI usage in educational contexts. Using a descriptive survey method, data were collected from 77 student teachers through a structured questionnaire. The findings reveal a high level of awareness regarding ethical issues however, there exists a substantial gap in formal training and practical preparedness. The study highlights the discrepancy between conceptual understanding and real world application, emphasizing the need for structured integration of AI ethics in teacher education programmes. The paper concludes with recommendations for curriculum reform, experiential training, and policy level interventions to ensure responsible and value based use of AI in education. Mr. Nandkishor Damodhar Bodkhe "Bridging Awareness and Practice: Ethical Preparedness for Artificial Intelligence Use among B.Ed. Student Teachers" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102113.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102113/bridging-awareness-and-practice-ethical-preparedness-for-artificial-intelligence-use-among-bed-student-teachers/mr-nandkishor-damodhar-bodkhe

Attendance management is a fundamental administrative task in educational institutions and organizations however, conventional methods such as manual roll calls, sign sheets, and card based systems are time consuming, error prone, and vulnerable to proxy attendance. To overcome these limitations, this research paper presents the design and implementation of a computer vision–based face recognition attendance system that automatically identifies individuals and records attendance in real time using facial features. The proposed system integrates image processing and deep learning techniques to detect, recognize, and verify human faces from live video streams captured through a camera. Initially, face detection is performed to localize facial regions from input frames, followed by preprocessing steps such as normalization, alignment, and noise reduction to improve recognition accuracy. A convolutional neural network CNN based face recognition model is employed to extract discriminative facial embeddings, which are then compared with a pre trained facial database using similarity metrics. Upon successful recognition, the system automatically logs attendance along with date, time, and confidence score into a centralized database. The system is designed to operate in real world environments and is robust to variations in illumination, facial expressions, pose, and minor occlusions. Experimental results demonstrate that the proposed approach significantly improves accuracy and efficiency compared to traditional attendance systems, while minimizing human intervention. The automation of attendance tracking not only saves time but also enhances reliability, security, and scalability. This research highlights the potential of computer vision and deep learning technologies in developing intelligent, contactless, and efficient attendance management solutions suitable for modern smart environments. Nishant Umrao Kale "Computer Visioned Based Face Recognition Attendence System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102134.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102134/computer-visioned-based-face-recognition-attendence-system/nishant-umrao-kale

Quicklancer is a website that helps people who need work done find professionals who can do the jobFreelancers can say they want to do the job. Freelancers decide if they want to do the job based on what theyre good at and how much money they think it will take to do the job. The main goal of Quicklancer is to make it easy for clients to find the person, for the job and to make sure everyone is honest and fair. Quicklancer wants to make a system that people can trust when they are working with someone from a place. The application has three parts Client, Freelancer and Admin. Clients can make an account post a project look at bids hire a freelancer and handle payments. Freelancers can make a profile look at projects send a proposal talk to clients and give work. The Admin part watches over the platform handles users keeps an eye on transactions and solves problems to make sure everything works well. However, I can do better The application has three parts Client, Freelancer and Admin. Clients can create an account. They can post a project. They hire freelancers. Manage payments. Freelancers create a profile. They browse projects. They submit proposals to clients. They communicate with clients. They deliver completed work to clients. The Admin module oversees the platform. It manages users on the platform. It monitors transactions happening on the platform. It resolves disputes. This ensures functioning of the platform. Yash Tangle "QuickLancer: A Smart Platform for Connecting Freelancers and Clients Efficiently" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102132.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102132/quicklancer-a-smart-platform-for-connecting-freelancers-and-clients-efficiently/yash-tangle

Urban transit systems like airports, railway stations, and metro networks are essential public infrastructures that need strong security measures to keep passengers safe. Traditional surveillance mainly relies on video monitoring and manual oversight, which can delay responses in spotting potential threats. This research introduces the Urban Transit Vigilance and Defense System, a technology based solution aimed at improving security through real time speech recognition and automated threat detection. The proposed system captures audio from transit environments and processes it using real time speech recognition technology. It converts spoken conversations into text. The transcribed data is then analyzed to find specific alert words that may signal security threats. When the system detects these keywords, it logs the event with exact timestamps and automatically sends notifications, including email alerts to authorized security staff. This setup allows for quick responses and helps Security Operations Center SOC analysts identify and manage potential risks effectively. The system combines various technologies to ensure it is scalable, efficient, and easy to deploy. The front end interface is built using React.js, while the back end services use Flask or Django frameworks with PostgreSQL for managing the database. It also includes features like QR code scanning for user interaction, real time speech processing, and automated alert systems to improve its functionality. The application is designed with Docker based containerization and CI CD pipelines, making deployment on cloud services seamless and maintenance easier. By blending speech recognition, automated alert generation, and modern web technologies, the proposed system aims to offer a proactive and scalable security solution for urban transit settings. The Urban Transit Vigilance and Defense System provides actionable insights for security analysts, enabling quicker identification and handling of potential threats, ultimately leading to safer public transportation systems. Nishtha Shambharkar "Urban Transit Vigilance and Defense System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102131.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102131/urban-transit-vigilance-and-defense-system/nishtha-shambharkar

The rapid advancement of technology has significantly improved the healthcare sector through intelligent systems that assist in medical diagnosis and patient care. This research paper presents the development of an AI based Medical Symptom Checker Web Application designed to provide preliminary health guidance to users based on their symptoms. The system allows users to input symptoms through text, speech, or images, which are processed using techniques from Artificial Intelligence, Machine Learning, and Natural Language Processing. The application analyzes the symptoms and predicts possible diseases using trained machine learning models. It then provides basic medical suggestions and recommendations for further consultation if necessary. The system aims to improve accessibility to healthcare information and assist users in early symptom assessment .The results demonstrate that AI based healthcare tools can enhance digital health services and support medical awareness while complementing professional medical consultation The arrival of modern technologies like Artificial Intelligence AI , Internet of Things IoT , and Deep Learning DL has brought big changes in healthcare, offering new ways to provide personalized care by improving the quality of various medical services. Our approach involves creating a medical chatbot based on BERT, which uses advanced deep learning technology to improve communication and make healthcare more accessible. Traditional medical chatbots often have problems like not understanding medical conversations well, giving incorrect responses to medical terms, and not being able to offer personalized help. We use BERT, a powerful deep learning model, to solve these issues. The performance of our chatbot is very good. It has an accuracy of 98 , which means it handles medical questions with high precision. A precision score of 97 shows that the responses are accurate and reliable. The proposed web application is designed to provide quick and accessible healthcare guidance, especially for individuals who may not have immediate access to medical professionals. By analyzing the symptoms entered by users, the system generates possible disease predictions and provides basic medical recommendations. This helps users understand the severity of their symptoms and decide whether professional medical consultation is necessary. In addition, the system integrates chatbot functionality to enable interactive communication with users. The chatbot can answer common health related questions and provide guidance in a conversational manner. Advanced language models such as BERT Bidirectional Encoder Representations from Transformers can be used to improve the accuracy of symptom interpretation and response generation. The main objective of this research is to design and implement an intelligent web based system that improves accessibility to preliminary health information while reducing the workload on healthcare institutions. Although such systems cannot replace professional medical diagnosis, they can serve as a helpful first step in guiding patients toward appropriate healthcare services. The study demonstrates how AI powered healthcare tools can enhance digital healthcare services and contribute to more efficient and accessible medical support. Renu Adekar "AI Medical Symptom Checker Web Application" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102060.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102060/ai-medical-symptom-checker-web-application/renu-adekar

In the present educational scenario, integration of employability skills within the curriculum has gained prime importance Yorke and Knight, 2006 . Rapid changes in work environments and industrial expectations demand that students not only acquire academic knowledge but also develop competencies that make them employable and capable of sustaining themselves in dynamic workplaces Tymon, 2013 . This paper focuses on curriculum integration with employability and highlights the need to embed essential employability skills into teaching–learning processes Yorke, 2006 . The objectives of the study are 1 to analyze and understand the significance of curriculum integration with employability skills 2 to recognize and associate key employability skills such as interpersonal skills, analytical reasoning, collaboration and harmony, resourcefulness and IT proficiency, which are essential in the work environment 3 to search successful productive techniques for embedding skills into teaching–learning practices and 4 to understand the significance and importance of educational organizations in preparing students for industry demands Rao and Gopal, 2010 . A qualitative and descriptive research approach is proposed for this study, drawing on review of existing literature, academic journals, policy documents and studies related to curriculum and employability skills Knight and Yorke, 2003 Ministry of Education, 2020 . The data collected through such review will be used to understand various plans and modules for achieving collaboration between employability skills and academic progress, with special attention to the role of internships and project based teaching–learning in experiential learning Kolb, 2015 . The study concludes that integrating employability skills into the teaching–learning curriculum is essential for preparing students for emerging workplaces and for improving their confidence, competence and employability prospects Yorke, 2006 Yorke and Knight, 2006 . Dr. Deepti Joshi "Curriculum Integration with Employability Skills" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102115.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102115/curriculum-integration-with-employability-skills/dr-deepti-joshi

Dark patterns are interfaces which use the psychology of users to convince them to behave in ways which are not in their best interest, often to the benefit of the provider of the interface. Dark patterns are a type of user interface manipulation in websites and applications to nudge or trick users into doing something that the website owner benefits from at the user’s expense such as enrolling them in a service, collecting sensitive information or for achieving various monetary gains through purchases by misdirection or confusing the user. Examples of dark patterns include charging people on a free trial by checking the wrong account, buttons that look like they allow you to opt out, requiring you to create a new account on a site that you already have an account on or convoluting privacy settings. With the proliferation of the Internet and the growth of social media, the identification of these abusive behaviors is a significant research challenge. Manual detection is difficult because websites frequently update their design and new types of dark patterns continue to appear. PhishMe Scan identifies potentially malicious design elements such as button labels, pop up messages and webpage layout to determine if they exhibit characteristics of social engineering deception. The technology applies advanced Natural Language Processing NLP techniques to text elements and machine learning based classification to understand and identify suspicious patterns. Our approach can be used to detect unethical interface design and help achieve more transparent and ethical technology. Yash M. Domle "Dark Pattern AI Detecytor Using Ml" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102058.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102058/dark-pattern-ai-detecytor-using-ml/yash-m-domle

This project is about a website that helps companies automate the way they do things. The Business Process Execution and State Transition Platform is a tool that lets people define how things are done manage how things change from one step to another and keep track of whats happening at the same time. The Business Process Execution and State Transition Platform makes sure that people do not make as mistakes that everything is clear and that tasks are done in a logical order from start to finish. The Business Process Execution and State Transition Platform is really good, for companies because it helps them get things done efficiently. Daniyal Salahuddin "Business Process Execution and State Transition Platform Web Development" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102057.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102057/business-process-execution-and-state-transition-platform-web-development/daniyal-salahuddin

Water is one of the most essential natural resources for sustaining life, yet its availability is increasingly threatened by overconsumption, population growth, and inefficient management practices. This research paper presents a comprehensive water audit conducted at Guru Nanak College of Education and Research. The study focuses on identifying water wastage, analyzing its long term impact, and promoting sustainable water management practices within an educational institution. The findings reveal that even minor leakages can lead to significant annual water loss, amounting to approximately 9460.8 liters from a single source. The study highlights the importance of water audits as an effective tool for conservation and emphasizes the role of educational institutions in fostering environmental awareness and responsible behavior among students. The research concludes with practical recommendations for reducing water wastage and promoting sustainability at both institutional and individual levels. Dr. Samidha Suhas Parab "Water Auditing as a Framework for Sustainable Resource Management in Educational Institutions" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102127.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102127/water-auditing-as-a-framework-for-sustainable-resource-management-in-educational-institutions/dr-samidha-suhas-parab

Artificial Intelligence AI has the potential to either exacerbate or mitigate existing social inequalities. This abstract explores the intersection of AI, equity, inclusion, and social justice, highlighting the need for AI systems that promote fairness, transparency, and accountability. We discuss the risks of AI perpetuating biases and propose strategies for inclusive AI design, such as diverse and representative data, bias detection, and explainable AI. By prioritizing equity and inclusion in AI development, we can harness its potential to drive social justice and promote a more equitable society. Dr. Bhagirath Shamdas Pande "Equity, Inclusion and Social Justice in Education" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102116.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102116/equity-inclusion-and-social-justice-in-education/dr-bhagirath-shamdas-pande

In todays era of globalization, digitalization, and artificial intelligence AI , the career field is constantly changing. New professions, skills, employment opportunities, and educational courses are evolving every day. In such a situation, students need up to date, accurate, and reliable information to choose the right career. Mrs. Kaveri Rajesh Mandhare | Mr. Pratibha Kambli "????? ?????????? ?????? ?????????? ???????? ???????? ????????? ????? ????? ? ??????? ?????????" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102117.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102117/?????-??????????-??????-??????????-????????-????????-?????????-?????-?????-?-???????-?????????/mrs-kaveri-rajesh-mandhare

Because of the very unstable and unpredictable character of bitcoin assets, forecasting market volatility remains a difficult challenge for investors and risk managers. Traditional econometric models, such as GARCH, have been widely utilised for volatility forecasting, but they typically fail to capture the complex nonlinear patterns and abrupt market movements that occur with cryptocurrencies. Deep learning approaches have grown in prominence in recent years as a result of their improved capacity to handle complicated data patterns. However, there is still a paucity of research that properly compares the forecasting effectiveness of deep learning models to older approaches while also taking into account computing efficiency. The GARCH 1,1 , EGARCH, and TGARCH models, together with deep learning architectures like Long Short Term Memory LSTM and Gated Recurrent Unit GRU , are compared in this study in an effort to bridge this gap. From January 2020 to December 2023, the study uses a walk forward validation technique to analyse daily Bitcoin and Ethereum price data in order to arrive at a trustworthy and accurate assessment. The findings reveal that deep learning models beat classic econometric techniques in prediction accuracy. The LSTM model decreases RMSE by roughly 18.2 , while the GRU model produces an MAE that is approximately 22.4 lower than the best performing GARCH model. Traditional models, on the other hand, have a significant computational efficiency advantage since they require almost 200 times less training time than deep learning approaches. Statistical testing demonstrate that the performance differences are very significant at the 1 confidence level. Overall, this study provides researchers and practitioners with practical advice on how to select appropriate volatility prediction models based on their accuracy, interpretability, and computational resource requirements, as well as a clear benchmark comparison of traditional and contemporary forecasting techniques. Mayank Vijay Singh Kashyap "Beyond GARCH: A Comparative Study of Deep Learning Models (LSTM, GRU) vs Traditional Time Series Models for Cryptocurrency Volatility Forecasting" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102056.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102056/beyond-garch-a-comparative-study-of-deep-learning-models-lstm-gru-vs-traditional-time-series-models-for-cryptocurrency-volatility-forecasting/mayank-vijay-singh-kashyap

The proposed system is a web based visual design interface developed to simplify the process of creating digital designs such as certificates, invitations, and other graphical layouts. Traditional design tools often require technical expertise and experience, which creates a barrier for beginners and non technical users. This system addresses that problem by providing an easy to use drag and drop interface, allowing users to create designs without needing advanced design knowledge. The platform is built using modern web technologies, including HTML5 for structure, CSS3 for styling, JavaScript ES6 for interactivity, and React.js for building a component based user interface. These technologies ensure that the system is fast, scalable, and responsive. A key feature of this system is its real time preview functionality, where any changes made by the user—such as editing text, moving elements, or changing colors—are instantly visible on the screen. This reduces errors and improves design accuracy. Additionally, the system is designed to be fully responsive, meaning it works smoothly across different devices like desktops, tablets, and mobile phones. Since it runs entirely in a web browser, there is no need for installation or high end hardware. Overall, the system aims to provide a user friendly, efficient, and accessible solution for digital design creation, making professional quality design possible for everyone. Asmit R. Nagdeve "Web-Based Visual Design Interface: An Interactive Drag-and-Drop Design Platform" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102055.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102055/webbased-visual-design-interface-an-interactive-draganddrop-design-platform/asmit-r-nagdeve

The Society Maintenance System is a website that helps people who live in societies. It makes things easier by sending bills and tracking payments. This system also helps people talk to each other. It saves time. Makes things clearer. The Society Maintenance System does this with the help of dashboards, online payments and messages on WhatsApp when people make payments. The Society Maintenance System is really good, at making things work better. Tanmay Sunil Dudhabade "Society Maintenance System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102054.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102054/society-maintenance-system/tanmay-sunil-dudhabade

Thailand is a major country in Southeast Asia. The study and spread of Sanskrit has been going on here for a long time. The association prescribed for the original source of Thai and Southeast Asian languages with Sanskrit, however, reflects the relationship between Sanskrit and them since time immemorial. Thai literature and culture have felt a profound influence of Sanskrit. The present royal family, which belongs to the Chakru dynasty, has respectfully accepted the study of Sanskrit. Dr. Suman K. S. "??????? ?????????? ??? ??????????" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102163.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/sanskrit/102163/dr-suman-k-s

The healthcare industry is always changing. One of the changes happening now is the use of data analytics. This article is about something called the Smart Health Metrics Analysis Engine. The Smart Health Metrics Analysis Engine is a tool that uses machine learning to look at health information. It gives people personalized health information. The Smart Health Metrics Analysis Engine looks at things, such as body mass index, blood pressure, what people do for exercise and their medical history. It helps people keep track of their health in time and makes predictions about their health. The Smart Health Metrics Analysis Engine also gives people personalized advice on how to stay healthy. Achal Janardhan Malode "Smart Health Metrics Analysis Engine" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102053.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102053/smart-health-metrics-analysis-engine/achal-janardhan-malode

This study aims to determine the effect of Customer Relationship Management CRM on Customer Satisfaction and its impact on Customer Loyalty of Islamic Bank in Aceh’s Province. The study population is all customers in in the Islamic Bank. This study uses convinience random sampling with a sample size of 250 respondents. The analytical method used is structural equation modeling SEM . The results showed that the Customer Relationship Management significantly influences both on satisfaction and its customer loyalty. Furthermore, satisfaction also affects its customer loyalty. Customer satisfaction plays a role as partially mediator between the influences of Customer Relationship Management on its Customer Loyalty. The implications of this research, the management of Islamic Bank needs to improve its Customer Relationship Management program that can increase its customer loyalty. Yash Nashine "Customer Relationship Management, Customer Satisfaction and its Impact on Customer Loyalty" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102052.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102052/customer-relationship-management-customer-satisfaction-and-its-impact-on-customer-loyalty/yash-nashine

The real estate market is changing fast because of new digital technologies and people wanting better ways to find properties. Normally people use things like price, location and what kind of property it is to search for houses.. These old ways might not give people the exact results they want. New technologies like Artificial Intelligence and special maps can make searching for properties a lot The AI Based Real Estate Spatial Search Engine is a system that uses maps and artificial intelligence to help people find properties. This system can help people find properties based on where theyre how much they cost how big they are and other important things. We can use maps to show people where properties are which makes it easier for them to find what they want. Artificial Intelligence can look at lots of property information. Figure out what people like to suggest properties to them. The system can also use ways of organizing property information to make searching faster. We can build this system using things, like HTML, CSS and React to make it look nice and easy to use and databases like MySQL and MongoDB to store all the property information. The real estate market and Artificial Intelligence can work together to make property search tools better. Shruti Anil Karekar "AI-Based Real Estate Spatial Search Engine" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102051.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102051/aibased-real-estate-spatial-search-engine/shruti-anil-karekar

The User Module of the Integrated Digital Examination and Assessment Portal IDEAP is designed to provide students with a secure, efficient, and user friendly digital examination experience. This module enables students to register, log in securely, update their profiles, and access examination related information through a centralized dashboard. It allows users to view available exams, download hall tickets, receive notifications, and attempt online examinations within a controlled environment. The system ensures authentication and authorization to maintain data security and prevent malpractice. Students can track their exam schedules, monitor submission status, and view results and performance analytics after evaluation. The module is developed with a responsive interface to ensure accessibility across devices, promoting convenience and transparency in the examination process. By digitizing exam management and assessment tracking, the User Module enhances efficiency, reduces manual errors, and supports a streamlined academic evaluation system. If you want, I can also provide Admin module abstract Examiner module abstract Full project abstract complete IDEAP system ER diagram explanation SRS document content Sakshi Kavadu Jumde "Integrated Digital Examination and Assessment Portal" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102045.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102045/integrated-digital-examination-and-assessment-portal/sakshi-kavadu-jumde

The real estate market is changing fast because of new digital technologies and people wanting better ways to find properties. Normally people use things like price, location and what kind of property it is to search for houses.. These old ways might not give people the exact results they want. New technologies like Artificial Intelligence and special maps can make searching for properties a lot The AI Based Real Estate Spatial Search Engine is a system that uses maps and artificial intelligence to help people find properties. This system can help people find properties based on where theyre how much they cost how big they are and other important things. We can use maps to show people where properties are which makes it easier for them to find what they want. Artificial Intelligence can look at lots of property information. Figure out what people like to suggest properties to them. The system can also use ways of organizing property information to make searching faster. We can build this system using things, like HTML, CSS and React to make it look nice and easy to use and databases like MySQL and MongoDB to store all the property information. The real estate market and Artificial Intelligence can work together to make property search tools better. Shruti Anil Karekar "AI-Based Real Estate Spatial Search Engine" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102051.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102051/aibased-real-estate-spatial-search-engine/shruti-anil-karekar

In an increasingly globalized world, classrooms are becoming more culturally, linguistically, and socially diverse. This diversity presents both opportunities and challenges for educators. The increasing diversity of classrooms across the world has made equity a central concern in education. Learners differ in language, culture, socioeconomic background, and learning abilities, requiring educators to move beyond uniform teaching approaches. Equity in a multicultural classroom focuses on fairness by ensuring that each learner receives appropriate support according to their needs. Equity in education ensures that all students receive the support they need to succeed, recognizing that each learner’s circumstances differ. Nurturing equity requires intentional effort, reflective teaching, and institutional support. This paper examines the concept of equity, identifies key challenges in multicultural settings, and proposes practical strategies for fostering inclusive learning environments. Drawing on educational theories and classroom practices, the paper emphasizes the importance of responsive pedagogy, institutional support, and reflective teaching in promoting equitable education. Dr. Sarika M. Patel "To Nurture Equity in a Multicultural Classroom" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102121.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102121/to-nurture-equity-in-a-multicultural-classroom/dr-sarika-m-patel

Multi Level Marketing MLM organizations operate through complex hierarchical referral structures where commission calculations, wallet management, payouts, and administrative approvals must be handled efficiently and transparently. Manual or semi automated systems often result in calculation errors, payout disputes, financial mismanagement, and lack of transparency among members. This research presents the design and implementation of a Python Full Stack based MLM Operations and Wallet Management System named Unity Grow Network. The system automates referral tracking, genealogy management, multi level commission distribution, wallet transactions, withdrawal processing, and administrative workflows using a secure, role based web architecture. The application is developed using HTML, CSS, JavaScript, Bootstrap Frontend , Python and Django Backend , and MySQL PostgreSQL Database . The proposed system ensures automated income calculation across multiple wallet types including Referral Wallet, Matching Wallet, Level Income Wallet, Activation Wallet, and Scheme Based Wallets. Experimental deployment and validation show that the proposed system significantly reduces manual intervention, improves financial transparency, minimizes calculation errors, and enhances scalability for large member networks. The modular architecture supports thousands of users while maintaining security and performance efficiency. Divya Aher "Unitygrow Network – Multi-Level Marketing (MLM) Operations & Wallet Management System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102050.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102050/unitygrow-network-–-multilevel-marketing-mlm-operations-and-wallet-management-system/divya-aher

In modern software applications, it is necessary to ensure that the applications are deployed in scalable, reliable, and efficient environments. It has been identified that traditional application deployment techniques face difficulties in handling modern distributed applications. This has created problems in terms of scalability, reliability, and maintenance. However, an open source system called Kubernetes has been proposed to resolve the problems associated with modern application deployment. This research paper aims to explore the architecture and working of the Kubernetes system in application deployment. This paper is based on the study of the application of Kubernetes in modern application deployment. It has been identified that the application of Kubernetes in modern application deployment is effective in terms of system reliability, scalability, and efficiency. This research paper explores the architecture, components, and working principles of Kubernetes in application deployment. It also analyzes deployment workflows, strategies, and real world implementation scenarios. The study concludes that Kubernetes significantly enhances system reliability, scalability, and operational efficiency, making it a cornerstone technology in modern DevOps and cloud native environments. Vivek Someshwar Ghosekar "Deploying Application Using Kube Rnetes" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102049.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102049/deploying-application-using-kube-rnetes/vivek-someshwar-ghosekar

The Hospital Management System is a system that is built on the Salesforce platform. This system helps hospitals manage things like admissions and appointments. It makes things easier and faster for hospitals to do their work. This is because it uses cloud technology. Old hospital systems use paper. People have to enter data by hand. This can be slow. People can make mistakes. The Hospital Management System uses Salesforce to keep track of people who ask about the hospital and to follow up with them. It also makes reports to help doctors and administrative people make decisions. The Hospital Management System uses Salesforce tools like Leads and Accounts and Contacts. It also uses custom things like Department and Patient Records to keep data organized. The system automatically sends reminders and confirmations and notifications. This means that no one forgets about a patient who asked about the hospital. The Hospital Management System also makes reports and dashboards that show what is happening with admissions and how departments are doing and information about patients. By using the Hospital Management System hospitals can work better. Do not have to do as much work, by hand. They can also talk to patients better. Help them more. Chetan Gangale "Design and Implementation of a Smart Hospital Management System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102048.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102048/design-and-implementation-of-a-smart-hospital-management-system/chetan-gangale

The process of issuing formal documents which includes academic certificates and corporate participation letters and event invitations remains an unexpectedly time consuming endeavor for most organizations. The digital tools which organizations now use for their work processes still require workers to complete multiple manual tasks which include entering names into templates and cross checking spreadsheets and composing individual emails and dispatching them one by one. The two methods of operation at small scale through which errors in systems operate at institutional scale have been proved to cause untraceable document errors which remain undetected until after the documents have been sent. The paper demonstrates SmartCert, which functions as a complete document creation system that enables users to design documents and distribute them through secure automated channels. The system uses a browser based design interface which employs React.js components to create a design environment that users can use to design their components and access permanent data through RESTful APIs and JSON Web Token authentication and detailed access control based on user roles. Users can create professional certificates and cards through a visual interface that functions in real time without requiring them to learn coding skills. Users can create professional certificates and cards through a visual interface that functions in real time without requiring them to learn coding skills. Users can create professional certificates and cards through a visual interface that functions in real time without requiring them to learn coding skills. Users can create professional certificates and cards through a visual interface that functions in real time without requiring them to learn coding skills. Users can create professional certificates and cards through a visual interface that functions in real time without requiring them to learn coding skills. Users can create professional certificates and cards through a visual interface that functions in real time without requiring them to learn coding skills. Users can create professional certificates and cards through a visual interface which operates in real time without the need to learn coding skills. Users can create professional certificates and cards through a visual interface which operates in real time without the need to learn coding skills. The system evaluation showed that every assessment area achieved measurable performance improvements which resulted in reduced administrative tasks and increased bulk processing capacity and complete elimination of record errors through upload time data validation and total operational visibility through delivery tracking. The central finding is that co designing the front end and backend as a single coherent system rather than connecting independent products after the fact yields benefits that neither component could achieve independently. Riya K. Pandey "Smartcert: An Integrated Interactive Design Interface and Automated Certificate Delivery Management System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102046.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102046/smartcert-an-integrated-interactive-design-interface-and-automated-certificate-delivery-management-system/riya-k-pandey

Holistic development of students is possible in safe inclusive classrooms where schools play a major role in making every child feel accepted. Gender non conforming children often face discrimination and harassment in educational settings due to differences between their gender expression and assigned sex at birth. Traditional school uniforms emphasize fixed gender norms that may affect the mental health of the students. For students whose gender expression doesnt match the assigned attire, they may feel discomfort and may be more vulnerable to bullying. The National Education Policy 2020 recommends that teachers need to create safe inclusive classrooms for such children ensuring freedom of gender expression in behaviour, mannerisms and attire. Gender neutral uniforms help children to be comfortable and free from bullying and discrimination. Teacher perspectives regarding gender neutral uniforms are significant as it directly impacts the policy decisions in addition to shaping the school culture. This qualitative exploratory study examines pre service teachers perceptions about gender neutral uniforms as a part of inclusive classrooms. It aims to give a deeper insight on pre service teachers thoughts about gender inclusivity and their ability for supporting the unique identity of each and every child. The findings of the study set implications for teachers, school administrators, and Policymakers, thereby advocating inclusive practices and laying a strong foundation for encouraging acceptance as well as respect for all the children Dr. Usha Sharma | Tanishqa Sharma | Riya Katira | Anas Khan "Unmasking bias: Pre-Service Teachers Perceptions of Gender Neutral Uniforms" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102118.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102118/unmasking-bias-preservice-teachers-perceptions-of-gender-neutral-uniforms/dr-usha-sharma

Exclusion and discrimination based on skin tone are common in Indian schools. Often dismissed as teasing, this is rarely addressed and leads to no corrective action. This colour based discrimination, much like its counterpart in Western countries, has become more visible in recent years. In India, however, it appears in complex ways, linked with caste, class, language, and religion. With India being a diverse nation, these factors largely impact the experience and expression of discrimination, along with the preconceived notion of darker skin tones’ association with social disadvantage. This study uses an Arts based research approach along with semiotic analysis to examine student’s lived experiences of colourism in the everyday school atmosphere. Thus, the high risk zones are identified based on the visual representation by them. Semiotic analysis revealed symbolic representations of power, emotional responses, and resilience. This uncovered social hierarchies and student coping mechanisms. It provides a visual framework for educators to address colourism in anti bullying policies. The text also emphasises art based methodologies to help students voice their needs and promote inclusive educational practices. Dr. Usha Sharma | Nimisha Ravikumar "Shadows of Bias: A Qualitative Exploration of Students Lived Experiences with Skin-Tone Discrimination" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102119.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102119/shadows-of-bias-a-qualitative-exploration-of-students-lived-experiences-with-skintone-discrimination/dr-usha-sharma

Optical character recognition OCR technology plays an important role in the digitization of documents and intelligent data extraction. OCR allows computers to read text that appears inside images and videos. Traditional OCR systems have proven to have a high degree of accuracy when used to read text contained in non moving i.e., still images however, the use of OCR technology for real time applications has been severely limited due to limitations on processing power, physical conditions e.g., low light levels and quick turnaround times. This paper provides details on the development and implementation of a real time OCR system that can read text from live cameras using computer vision and convolutional neural networks CNNs . This real time OCR system uses CNN based algorithms along with computer vision techniques to create an effective and scalable real time OCR solution that can be used in real life situations. Using OpenCV, Frames from Live Camera Feed requiring Image Manupulation Pre processing are Captured Then The Text Are Recognised Through EasyOCR . The Pre processing Steps Include Grayscale Conversion to Improve Magnitude of the Input Image, However Given The Time Constraints of Real Time Optimisation Because of Frame Skipping and Scaling Convert some of the Resistance Between Computation Cost and Output Cost While Im In Multilingual Environments For Example English and Hindi Throughout Data Collection Evaluation of The System Using Various Performance Measurments As Well Using Accuracy Data as welll Omega 3 Oil Performance As Far As Its Effects On Cognitive Developement Based On The Results Puls Standars of Labour Cost Are Potential Future Development. This study has developed an economically viable and viable OCR solution for use in many typical applications in everyday life, including improving assistive technologies, implementing automatic data entry systems, and performing document and image analysis through the use of modern deep learning algorithms and classical image processing methods to create robust OCR systems on platforms with limited resources, while achieving acceptable performance and accuracy levels. Akshay Gharpure "A Real-Time OCR System for Multilingual Text Recognition Using Camera and Deep Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102044.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102044/a-realtime-ocr-system-for-multilingual-text-recognition-using-camera-and-deep-learning/akshay-gharpure

Quality education is one of the key goals outlined in the Sustainable Development Goals SDGs introduced by the United Nations in 2015. Through the implementation of the National Education Policy NEP 2020, India is making significant progress toward achieving this objective, with Artificial Intelligence AI serving as a major driving force. AI is contributing significantly to the successful implementation of NEP’s major goals, such as universal access to education, modernization of the education system, and the development of a holistic and multidisciplinary learning approach. Its components—machine learning, deep learning, and extensive data based knowledge systems—are transforming the educational landscape. By presenting vast amounts of human knowledge in an accessible and user friendly way, AI has revolutionized learning. However, this progress also raises concerns about the possibility of machines replacing human roles. Despite this, the human element in education remains essential and cannot be replicated by machines. Teachers play a vital role as they nurture students’ emotional intelligence, social skills, resilience, interpersonal abilities, and sense of psychological safety—all of which are crucial for meaningful learning. Therefore, rather than reducing the importance of teachers, AI actually strengthens and supports their role. Instead of imagining a future where AI replaces teachers with robotic substitutes, it is more realistic to view AI as transforming the role of educators. It allows teachers to utilize their time more efficiently and apply their expertise more effectively, leading to improved learning experiences. Ultimately, AI does not replace teaching it enhances it. Teachers will continue their fundamental role of educating and guiding students, but with more advanced tools and resources at their disposal. Mrs. Nilima Shivdas Kamlu "NEP 2020 and AI: Redefining the Role of Teachers" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102120.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102120/nep-2020-and-ai-redefining-the-role-of-teachers/mrs-nilima-shivdas-kamlu

The rapid growth of digital financial services has increased the demand for intelligent systems capable of automating loan approval processes. Traditional loan evaluation methods rely heavily on manual decision making and require significant time and effort, which may lead to inconsistent and inefficient results. To address these challenges, this research proposes a Loan Eligibility Prediction System using Apache Spark and Machine Learning techniques. The proposed system analyzes various financial attributes of loan applicants such as income, employment length, loan amount, interest rate, loan intent, and credit history to determine the eligibility of a loan applicant. Apache Spark is used as the primary framework for distributed data processing, enabling efficient handling of large datasets and scalable machine learning model training. A machine learning pipeline is implemented using PySpark to preprocess data, perform feature engineering, and train predictive models capable of identifying loan approval risk. Furthermore, a web based interface developed using the Flask framework allows users to input loan application details and receive real time eligibility predictions. The experimental results demonstrate that the proposed system effectively predicts loan eligibility and supports financial institutions in improving decision making processes. The integration of big data technologies with machine learning techniques significantly enhances prediction accuracy, processing efficiency, and scalability. This research contributes to the development of intelligent financial decision support systems capable of reducing risk and improving loan approval processes in modern banking environments. Rajnikant Parate "Distributed Financial Risk Assessment System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102043.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102043/distributed-financial-risk-assessment-system/rajnikant-parate

In the era of digital transformation, higher education is increasingly mediated by technological platforms that shape access, participation, and learning outcomes. However, linguistic diversity remains a significant barrier to achieving equity and inclusion. This conceptual paper explores the role of multilingual digital platforms in fostering social justice within higher education. It argues that language inclusive technologies can democratize knowledge by enabling learners from diverse linguistic backgrounds to engage meaningfully in academic discourse. The paper examines how multilingual interfaces, AI based translation tools, and culturally responsive digital content contribute to reducing systemic inequities in education. It further highlights the need for policy frameworks and institutional commitment to integrate multilingualism into digital learning ecosystems. Drawing upon principles of inclusive pedagogy and digital equity, the paper proposes a framework for designing and implementing multilingual platforms that are accessible, context sensitive, and learner centered. The study concludes that embracing linguistic diversity through digital innovation is not only a technological necessity but also a moral imperative to ensure social justice in education. Such initiatives can significantly enhance participation, retention, and academic success among marginalized and underrepresented student populations. Dr. Vinu Agrawal "Bridging Linguistic Divides through Multilingual Digital Platforms: Advancing Equity, Inclusion, and Social Justice in Higher Education" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102122.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102122/bridging-linguistic-divides-through-multilingual-digital-platforms-advancing-equity-inclusion-and-social-justice-in-higher-education/dr-vinu-agrawal

Artificial Intelligence AI has emerged as one of the most transformative technological developments of the twenty first century, significantly influencing social institutions, cultural practices, economic systems, and human interaction. While AI offers opportunities for innovation, efficiency, and global connectivity, it simultaneously raises critical sociological concerns related to inequality, ethics, employment, surveillance, and social stratification. The present conceptual paper examines the relationship between Artificial Intelligence and society through a sociological lens by integrating major theoretical perspectives such as structural functionalism, conflict theory, symbolic interactionism, and technological determinism. The paper explores the impact of AI on education, employment, governance, culture, and global inequality while critically analyzing emerging ethical and social challenges including algorithmic bias, digital exclusion, and loss of human autonomy. Drawing upon contemporary sociological discourse, the study emphasizes the need for responsible and human centered AI development supported by inclusive policies, digital equity, and interdisciplinary collaboration. The paper contributes to the growing discourse on AI and society by offering a comprehensive conceptual understanding of how technological transformation reshapes social structures and human experiences in contemporary society. Mrs. Aaditi Abhijeet Bhat "Artificial Intelligence and Society: A Sociological Perspective on Technological Transformation and Social Change" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102123.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102123/artificial-intelligence-and-society-a-sociological-perspective-on-technological-transformation-and-social-change/mrs-aaditi-abhijeet-bhat

Across educational institutions, corporate offices, and personal celebrations, the routine task of producing well designed digital documents remains unnecessarily difficult for individuals who lack formal training in graphic design. Existing solutions either carry a steep technical learning curve or depend on costly subscription models, making them practically inaccessible to a wide segment of potential users. This paper describes the conception, architecture, and implementation plan of CertiVerse, a purely browser based document design utility that empowers users to independently produce polished certificates, event invitations, and occasion based greeting cards without installing any external software or acquiring design expertise. The underlying technology stack comprises HTML5 for semantic structure, CSS3 for styling, ES6 JavaScript for dynamic behavior, and React.js for a reactive, component organized front end. A distinguishing feature of the platform is its synchronous canvas update mechanism, which mirrors every user input onto a live design preview with no perceptible delay. Templates are catalogued across multiple use case categories, and each template exposes a comprehensive set of tunable parameters covering typography, element arrangement, and color application. Built as a single page application that runs entirely on the client side, CertiVerse eliminates server round trip latency and enables consistent operation across varying network conditions. Measured benchmarks target a template initialization time below half a second, a preview synchronization lag under fifty milliseconds, and a successful task completion rate exceeding ninety percent across user trials. The platform is engineered to serve as a scalable foundation that can be incrementally enriched with backend verification capabilities, AI guided design assistance, and enterprise level workflow integrations. Vaishnavi Rajendra Shende "CertiVerse: An Interactive Web-Based Certificate, Invitation and Greeting Card Design Interface" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102042.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102042/certiverse-an-interactive-webbased-certificate-invitation-and-greeting-card-design-interface/vaishnavi-rajendra-shende

Education is facing a radical change in terms of technology with the introduction of artificial intelligence AI into education. Over the past few years, there has been an ongoing integration of AI based tools into teaching and research activities at the postsecondary level. One specific area of this transformation is within the field of teacher education therefore, educators will require knowledge and skills related to digital competency if they are going to successfully integrate technology into their teaching and research activities. The purpose of this study is to assess the adoption and the opportunities that artificial intelligence provides in both teaching and research across teacher education institutions. It employs a descriptive research design that includes both conceptually analysing the relevant literature from AI and related fields of research, in addition to conducting a perception science based survey with teacher educators and B.Ed. student teachers. A structured questionnaire was administered to a sample size of forty 40 respondents regarding their perceptions about using AI technologies and related applications in teaching and research. Overall responses from participants demonstrate that AI based tools support innovative teaching practices, improve research productivity, and enhance access to digital learning resources. Additionally, respondents indicated that teacher preparation professionals must provide opportunities for teachers to participate in training programs so they are able to effectively utilize AI in their instructional practices. Based on the findings from the study, it is necessary for institutions of higher education to create technology enhanced teacher preparation programs to promote AI literacy and technology enhanced digital pedagogy. Overall, AI has the capacity to make a positive impact on the way we deliver education by providing new levels of creativity. Dr. Paradkar Dnyaneshwar Maruti "Artificial Intelligence Adoption in Teaching and Research: Transforming Teacher Education in the Digital Era" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102124.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102124/artificial-intelligence-adoption-in-teaching-and-research-transforming-teacher-education-in-the-digital-era/dr-paradkar-dnyaneshwar-maruti

Within this paper, the challenges associated with real estate data management, including information sources, lack of centralised access, and difficulties in verifying data related to real estate, are addressed. The current systems are scattered across various platforms, which makes it difficult for users to access reliable information. Within this research, a web based system for compliance monitoring and real estate transparency is proposed using a secure cloud database system. The system is designed as a full stack web application using various technologies such as HTML, CSS, JavaScript, PHP, and MySQL to enable efficient performance. The system is designed as a layered system consisting of a frontend, backend, and database layer. It is designed as a centralised system in which users can access information related to real estate and analyse it using a dashboard system. It is designed as a secure database system in which users can access reliable information. It is evident from the implementation of the system that the proposed system is efficient in terms of accessibility, accuracy, and usability of data related to real estate. Shruti Paradkar "Design and Development of a Web-Based RERA Compliance : Monitoring and Real Estate Transparency System Using Secure Database Architecture" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102041.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102041/design-and-development-of-a-webbased-rera-compliance--monitoring-and-real-estate-transparency-system-using-secure-database-architecture/shruti-paradkar

When assessing the efficacy of instruction, the caliber of the curriculum, and the overall academic experience, student feedback is essential. However, it is ineffective and frequently inconsistent to manually analyze vast amounts of unstructured textual feedback. In order to automatically classify student feedback into three categories—positive, neutral, and negative—this study suggests a Student Sentiment Analysis System that makes use of transformer based deep learning techniques. The system uses self attention mechanisms and a transformer architecture based on RoBERTa to capture contextual relationships within text. The suggested model creates contextual embeddings that interpret sentiment based on complete sentence meaning rather than isolated keywords, in contrast to conventional machine learning techniques that rely on manual feature engineering. Batch processing and real time feedback analysis are made possible by an interactive web interface created with Streamlit. An interactive web interface developed using Streamlit enables real time feedback analysis and batch processing. Experimental evaluation demonstrates reliable classification performance and practical applicability in educational environments. The system transforms raw textual feedback into structured sentiment insights, supporting data driven academic decision making. Khushi Wanve "Student Sentiment Analysis System Using Machine Learning Techniques" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102040.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102040/student-sentiment-analysis-system-using-machine-learning-techniques/khushi-wanve

Globally, educational systems are changing due to the introduction of technological innovations that use Artificial Intelligence AI to improve the processes of teaching and learning. AI technology also creates an opportunity for students to develop digital literacy, computational thinking, and problem solving skills in their studies of Information and Communication Technology ICT within school education. This research project focusses on how AI has enhanced digital learning through computational thinking for secondary students enrolled in ICT classes following international curricula. This study was conducted using a descriptive survey research approach that included a conceptual analysis of data that was collected through a perceptual based survey. The survey sample consisted of secondary school students from Grades 8 10 who completed a structured survey questionnaire that contained 10 statements associated with learning supported by AI. The data was collected from 48 students and presented their perceptions related to the use of AI technologies in ICT education. The results of this research suggest that secondary school students perceived AI supported learning tools as having a substantial positive impact on these students engagement, ability to problem solve and improve their computational thinking skills. This study also indicated the importance of implementing concepts and ideas associated with AI into the school ICT curriculum in order for students to be better prepared for future careers that will be driven by technology. Additionally, AI supported learning environments will significantly enhance digital learning in secondary schools when they are appropriately supported by technology infrastructures and the methodologies and techniques utilized by teachers. Mr. R. Sridhar "Artificial Intelligence and the Future of ICT Education: Developing Digital Learning and Computational Thinking in Secondary Schools an Exploratory Study among IGCSE and IB Students" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102126.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102126/artificial-intelligence-and-the-future-of-ict-education-developing-digital-learning-and-computational-thinking-in-secondary-schools-an-exploratory-study-among-igcse-and-ib-students/mr-r-sridhar

Road traffic accidents represent a major global public health crisis, claiming approximately 1.35 million lives annually and causing 20 50 million non fatal injuries according to the World Health Organization. Driver drowsiness and fatigue are identified as contributing factors in 15 30 of all road crashes across different countries, making drowsiness related accidents a leading cause of highway fatalities second only to alcohol impaired driving. Drowsy driving significantly impairs reaction time, attention, decision making, and vehicle control, with severely fatigued drivers exhibiting impairment levels comparable to legally drunk drivers. Despite widespread recognition of drowsiness dangers, effective countermeasures remain limited, as drivers often fail to recognize their own drowsiness levels or overestimate their ability to continue driving safely. Traditional approaches including driver education, road design improvements, and rumble strips provide limited protection, creating urgent need for active real time drowsiness detection systems that can warn drivers before accidents occur. This research presents a comprehensive driver drowsiness detection and alert system utilizing computer vision and machine learning techniques to monitor driver physiological and behavioral indicators in real time, detecting drowsiness onset and issuing timely warnings to prevent accidents, and driving pattern analysis monitoring steering wheel movements, lane deviations, and speed variations revealing attention lapses. The system integrates these indicators using a decision fusion algorithm combining multiple weak signals into robust drowsiness assessment, reducing false positives while ensuring timely detection. The system was developed using Python with OpenCV for computer vision operations, dlib for facial landmark detection, TensorFlow for deep learning models, and deployed on embedded hardware Raspberry Pi 4 with camera module enabling practical in vehicle implementation. The dataset for training and evaluation comprised 12,500 driving session recordings from 85 drivers under controlled and naturalistic conditions, totaling over 420 hours of driving data including alert driving, mildly fatigued driving, and severely drowsy driving with ground truth annotations based on driver self reports, expert observer ratings, and physiological measurements EEG, ECG . Data collection occurred across various conditions including time of day daytime, nighttime , road types highway, urban, rural , weather conditions, and driver demographics age 22 68, gender balanced ensuring comprehensive representation. Experimental results demonstrated strong detection performance with 94.7 accuracy in classifying driver states alert vs drowsy , precision of 93.8 low false alarm rate , recall of 95.3 low missed detection rate , and F1 score of 94.5 . Average detection latency was 1.8 seconds from drowsiness onset to alert generation, providing sufficient warning time for driver corrective action. The system achieved 89.2 accuracy on nighttime driving scenarios despite reduced visibility and 91.4 accuracy across different driver demographics. Comparison with single indicator approaches revealed multi modal fusion substantially improved performance EAR only detection achieved 86.3 accuracy, yawn only achieved 78.5 , head pose only achieved 81.7 , while integrated fusion achieved 94.7 , validating the multi indicator strategy. Real world validation through simulator based evaluation with 45 participants demonstrated 92.4 practical accuracy, with 87 of participants rating alert timing as appropriate and 89 expressing willingness to use such a system in their personal vehicles. Subjective feedback indicated the system provided valuable safety benefits without excessive false alarms that would lead to user annoyance and system disablement. Tanmai Nilesh Jiwtode "Driver Drowsiness Detection and Alert System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102031.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102031/driver-drowsiness-detection-and-alert-system/tanmai-nilesh-jiwtode

This research paper focuses on the development, implementation, and assessment of a full stack Conversational AI for personalized academic planning and career guidance. The proposed framework involves a combination of NLP technologies, trend based performance analytics, and a modular full stack architecture to overcome limitations of conventional, static advisory practices. First, the existing literature on AI technologies applied in an educational environment was analyzed and researched to define areas requiring further investigation. This allowed me to highlight crucial research gaps in the area, such as the absence of real time conversation based interactions, the automation of document analysis and summarization processes, and personalized, statistically based performance tracking. Consequently, in this study, a completely new system is developed using a React.js frontend, a Node.js backend, a PostgreSQL database, and a dual model AI engine that uses both the Google Gemini API and a local LLM as a fallback option. Specifically, the methodology includes the use of OCR based on Tesseract.js for automated marksheet digitization, an algorithmic statistical trend estimation model for cumulative GPA prediction, and a dynamic rule based engine for creating customized career maps. Shruti Nikaju "Conversational AI System for Personalized Academic Planning and Career Guidance Using Natural Language Processing" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102038.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102038/conversational-ai-system-for-personalized-academic-planning-and-career-guidance-using-natural-language-processing/shruti-nikaju

The way people shop for fashion online has shifted quite dramatically over the last few years. Consumers today no longer simply look for clothes — they want the right clothes, at the right price, from the right platform, all without switching between multiple apps. Yet, when one looks at the landscape of existing fashion e commerce platforms, a rather glaring problem becomes visible personalization, price discovery, and user experience are each handled in isolation, never together. In this paper, we take up exactly this challenge and propose a unified platform architecture that brings all three dimensions under one roof. In this research, the proposed system integrates an AI based recommendation engine built on CLIP embeddings and ResNet50 based collaborative filtering, a real time multi vendor price aggregation module powered by web scraping and RESTful microservices, and an adaptive UI UX layer designed around user centered principles. The platform targets fashion conscious digital consumers who demand both personalization and value transparency. In this paper, we draw upon thirteen existing peer reviewed research works to map the current state of the field, analyze their individual strengths and weaknesses, and identify the precise gap that this research occupies. The findings of this research suggest that fusing these three sub systems within a single scalable platform represents a novel and practically significant contribution to fashion e commerce. In this paper, no prior work was found that addresses all three dimensions simultaneously, which establishes the originality of this research. Namita Raghuwanshi "Design of a Smart Fashion Shopping Platform with AI Recommendations and Real-Time Price Aggregation" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102037.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102037/design-of-a-smart-fashion-shopping-platform-with-ai-recommendations-and-realtime-price-aggregation/namita-raghuwanshi

In todays era of globalization and technology, the scope of education is no longer limited to academic knowledge. Sharyu Shantaram Jadhav "?????????? ???? ?????????? ????? ?? ?????? ???" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102128.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102128/??????????-????-??????????-?????-??-??????-???/sharyu-shantaram-jadhav

The AI Based Document Summarization Tool is a website that helps you quickly summarize documents. It uses computer language techniques to find information in your documents. This information is then shown in a way thats easy to read and understand. The AI Based Document Summarization Tool has a user interface that makes it easy to use. The AI Based Document Summarization Tool works on all devices and browsers. You can easily upload your document process it and view the summary with the AI Based Document Summarization Tool. Using the AI Based Document Summarization Tool saves you time when analyzing documents. Kartik Gajanan Karnase "Al Based Documnet Summarisation Tool" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102034.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102034/al-based-documnet-summarisation-tool/kartik-gajanan-karnase

Shopping today is very easy for customers. People can find what they need quickly. Some people browse on their phones when they are on their way to work or school. They compare options on their laptops when they are at home. They complete purchases in stores without thinking about where they are shopping whether it is online or in person. Shopping is easy these days. Businesses have made shopping very smooth by connecting stores and websites and mobile apps. This makes it easy for customers to shop at stores or shop on websites or shop, or on apps wherever they want. Shopping is convenient for customers. It is not without its challenges for businesses. Retailers often face problems because their sales data, inventory records and customer information are all in systems. These systems do not always talk to each other which makes it hard to get a picture of what is really happening in business. When information is not connected it is hard to see what is really going on. This study is about solving that problem of information. It offers a way to bring sales and inventory data together so retailers can see everything clearly. The goal of this study is to use data to understand what customers want so retailers can predict what will sell and make inventory decisions. The framework for doing this has four stages. First it puts data from all channels, including stores, websites and mobile apps into one system. Second it uses forecasting models to guess what customers will want using data and machine learning to make predictions. Third it uses optimization models to make decisions about stock and orders balancing cost and customer satisfaction. Finally, it shows insights on a dashboard that track performance indicators making results easy to understand. To test this framework a case study was done using six months of sales data from three channels stores website app The dataset had 500 products and nearly 100,000 transactions, which is a lot of data. The findings were very good. The inventory turnover at the store got a lot better, it improved by 23 percent, whichs a really big improvement for the inventory turnover. There were a lot of stock outs, the number of stock outs decreased by 31 percent so now customers can usually find what they want when they come to the store. The forecasting accuracy got better by 18 percent so retailers can now make guesses about what products will sell and what will not sell, which helps the retailers with forecasting accuracy. The cost of fulfilling orders fell by 15 percent, which means the retailers will save money on the fulfillment costs and that is a deal for the retailers and their fulfillment costs. Cross channel analysis showed customer behavior patterns, whichs interesting. Customers who browsed online had a 76 percent chance of buying in stores, which shows that online browsing leads to in store sales. Mobile app users brought in 28 percent value, whichs a significant amount. This study shows that linking sales and inventory information is very important in an omnichannel retail environment. By breaking down data silos and using analytics retailers can improve financially. Delivery good customer experience. Omnichannel retail is about making shopping easy for customers and this study helps retailers do that. The study uses sales analytics, inventory optimization, data integration, demand forecasting, retail performance, machine learning and convolutional neural networks to achieve its goals. These are all tools for retailers who want to succeed in an omnichannel retail world. Omnichannel retail, sales analytics, inventory optimization, data integration, demand forecasting, retail performance, machine learning and convolutional neural networks are all key to shopping, for customers. Purva Vijay Mandavkar "Building a Simple Analytics Setup to Improve Sales and Manage Inventory Better in Omnichannel Retail" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101699.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101699/building-a-simple-analytics-setup-to-improve-sales-and-manage-inventory-better-in-omnichannel-retail/purva-vijay-mandavkar

This paper presents an overview of the machine learning techniques that can be used to predict a student’s placement performance. The ability to predicting the performance of a student is a very essential task of all educational institutions. Since this is the task of predicting student’s placement of undergraduate students. This paper can be used to predict the probability of an undergraduate student getting placed by applying different machine learning algorithms. In this system, multilayer perceptron MLP , logistic model tree LMT , sequential minimal optimization SMO , simple logistic, and logistic classifiers are applied to predict student performance. These classifiers independently predict the results and then compare the accuracy of the algorithms, which is based on the data set. After performing analysis on different matrices time taken to build classifier, correctly classified instances, root mean squared error, incorrectly classified instances, precision, recall, F measure, ROC area by different machine learning algorithms, we are able to find which algorithm is performing better than other on the student data set, so that we are able to make a guideline for future improvement of student placement performance in education. Vishal Rajesh Sonewane "Student Placement Prediction System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102035.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102035/student-placement-prediction-system/vishal-rajesh-sonewane

Document data extraction represents a critical challenge in digital transformation initiatives across industries, with organizations processing millions of documents including invoices, receipts, purchase orders, identity documents, contracts, and forms that contain valuable structured information trapped in unstructured formats. Manual data entry from these documents is labor intensive, error prone, time consuming, and costly, creating significant operational inefficiencies and bottlenecks in business processes. Traditional template based document processing systems require extensive configuration for each document type, fail when document layouts vary, and cannot handle the diversity of real world documents encountered in production environments. Optical Character Recognition OCR technology has existed for decades but historically struggled with accuracy on degraded documents, complex layouts, handwritten text, and diverse fonts, limiting practical applicability. Recent advances in artificial intelligence, machine learning, and computer vision have revolutionized document understanding, enabling intelligent systems that can automatically extract, classify, and structure data from diverse document types with minimal configuration. This research presents a comprehensive AI and ML based document data extraction system integrating state of the art OCR engines, computer vision techniques, and deep learning models to automatically process diverse document types with high accuracy and minimal human intervention. The system architecture combines multiple technologies Tesseract OCR for open source text recognition, Google Cloud Vision API for cloud based OCR with superior accuracy, preprocessing pipelines using OpenCV for image enhancement including noise reduction, binarization, deskewing, and perspective correction, layout analysis algorithms for document structure understanding including text block detection, table recognition, and reading order determination, named entity recognition NER using BERT based models for identifying key information fields like dates, amounts, account numbers, and entity names, template free extraction using attention based sequence models that learn extraction patterns from examples without requiring manual template definition, and post processing validation ensuring extracted data meets business rules and consistency requirements. Comparative analysis demonstrated substantial advantages over baseline approaches including traditional template based extraction 78.4 accuracy , pure OCR without ML post processing 82.7 accuracy , and rule based extraction 84.2 accuracy . Real world deployment in three organizations financial services firm, logistics company, healthcare provider processing 150,000 documents over six months validated system effectiveness with 95.2 practical accuracy, 94 straight through processing rate documents processed without human intervention , 87 reduction in manual data entry time, 76 decrease in data entry errors, and estimated annual cost savings of 180,000 per 100,000 documents processed. User acceptance was high 91 satisfaction with particular appreciation for handling document variety without configuration overhead, automatic error detection and confidence scoring, and seamless integration with existing business systems through REST APIs and batch processing interfaces. Sourabh Manohar Pathak "Al & Ml Based Document Data Extraction" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102032.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102032/al-and-ml-based-document-data-extraction/sourabh-manohar-pathak

Climate prediction is really important for our growth. It helps make sure we develop in a way thats friendly, to the Earth. We want the Earth to be a place for people to live on the Earth. By doing this we can reduce the chance of problems like floods and storms happening to the Earth. This is good for the Earth and, for us. This is good for our future and the planets future. We can prepare better. Be safer with accurate climate predictions. It helps us make choices, about how to grow and live. The planet and we both benefit from this. To make decisions we must know what the climate will be like. This knowledge enables us to plan ahead. We can prepare for floods and storms. The climate prediction helps us. We need to make choices. These choices will benefit the planet. They will also keep us safe. We rely on climate prediction. It guides our actions. We want to develop. This way we protect the planet. By predicting the climate we can act. We can prepare for the future. This helps us make decisions. The decisions are good for the planet and, for us. Climate prediction is key. It helps us grow safely. We can reduce risks. We can make choices.. Climate prediction helps us do that. It is crucial for the planet and, for our safety. We need to look after the earth and climate predictions important. Climate prediction is something we have to think about so we can be ready, for storms and other bad things that can happen to the planet. We have to think about climate prediction to keep the earth safe. The old ways of predicting the weather often do not work well for areas. This project is about creating a Smart Hyperlocal Climate Analysis Platform. The Hyperlocal Climate Analysis Platform uses intelligence and data analysis to give us a better understanding of the climate in specific areas. The system gets information from different sources. These include sensors that are connected to the internet pictures taken by satellites, weather stations and government websites. The information that is collected is then cleaned up. Made ready for use. This is done by fixing mistakes making sure everything is consistent and changing the data into a format that can be used. Then machine learning and deep learning are used to look for patterns in the climate information. This helps us make predictions about things like temperature, rainfall and humidity. The Hyperlocal Climate Analysis Platform shows us what is happening with the climate now and makes predictions for the future. We can see this information on a website or on our phones. The system is better at making predictions, than the ways. Farmers and city planners and people who deal with disasters can get the information they need This information is really useful for farmers. The farmers will look at the farming information. Then they will make farming decisions. This is going to be very helpful for the farmers and their farming. The farming information will be used by farmers to make farming plans. This is a thing for the farmers and their farming work. The farmers will use the farming information to help them with their farming. This will make farming easier, for the farmers. The farmers will be happy to have the farming information to help them with their farming. They will look at the information. Then they will decide what is best for their farming business. City planners will use this data to plan cities Disaster teams will also find this information helpful, in their work. This information will help people who deal with disasters and farmers and city planners make decisions, about farming and city planning and dealing with disasters. will use this information to respond to disasters. The information is useful for farmers to make decisions about farming and for city planners to make decisions about city planning and for people who deal with disasters to make decisions, about disaster response.. The farmers and city planners and people who deal with disasters need this information to do their jobs well. They need the information to make sure that farming and city planning and disaster response are done in a way. The information is very important, for the farmers and city planners and people who deal with disasters. The information is really helpful for farmers because it helps them with farming. It is also helpful for city planners because they need it for city planning. People who deal with disasters find the information helpful for disaster response. The information is really helpful, for farmers and city planners and people who deal with disasters.. They can use this information to make decisions, about farming. It also helps with city planning. Additionally it aids in disaster response. Unnati Ramesh Ambadkar "Smart Hyperlocal Climate Analysis Platform" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101694.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101694/smart-hyperlocal-climate-analysis-platform/unnati-ramesh-ambadkar

The emergence of generative artificial intelligence GenAI has significantly transformed educational discourse, particularly within mathematics teacher education. While the Technological Pedagogical Content Knowledge TPACK framework remains influential in explaining technology integration, contemporary AI mediated learning environments demand broader pedagogical and epistemic considerations. Existing AI TPACK models largely emphasize technological efficiency, instructional automation, and digital competence, yet inadequately address critical concerns such as cognitive dependency, epistemic trust, reflective pedagogical judgment, ethical mediation, and preservation of authentic mathematical reasoning. Mathematics learning, rooted in abstraction, conceptual reasoning, metacognition, and logical coherence, becomes especially vulnerable in AI mediated classrooms where algorithmic outputs may replace productive cognitive engagement. This conceptual paper proposes a novel Humanistic Epistemic Technological Pedagogical Content Knowledge HE TPACK framework that extends traditional TPACK through four interconnected dimensions Epistemic Awareness, Reflective Pedagogical Agency, Cognitive Integrity, and Ethical Affective Mediation. Drawing upon TPACK theory, social constructivism, epistemic cognition theory, critical digital pedagogy, and human AI collaboration discourse, the framework reconceptualizes mathematics teacher education for the generative AI era. The paper critically examines the limitations of current AI TPACK approaches, discusses the risks of cognitive outsourcing and algorithmic dependency in mathematics learning, and argues for a transition from techno centric integration toward human centered AI pedagogical orchestration. The HE TPACK framework provides a theoretical foundation for redesigning mathematics teacher education programs capable of preserving conceptual understanding, ethical responsibility, pedagogical autonomy, and authentic mathematical cognition within increasingly intelligent educational ecosystems. Asst. Prof. Ms. Rachana Das "Beyond AI-TPACK: A Human-Centered Epistemic Pedagogy Framework for Mathematics Teacher Education in the Generative AI Era" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102129.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102129/beyond-aitpack-a-humancentered-epistemic-pedagogy-framework-for-mathematics-teacher-education-in-the-generative-ai-era/asst-prof-ms-rachana-das-

The period between 1905 and 1947 marked a decisive phase in the historical transformation of Munger District, Bihar, where education emerged as a significant catalyst for social change and political awakening. While the history of Indias nationalist movement has received considerable scholarly attention, the localized relationship between educational expansion, social transformation, and political consciousness in districts such as Munger has remained comparatively underexplored. This study examines how the spread of modern education during the colonial period reshaped social relations, encouraged public participation, and contributed to the growth of nationalist sentiments in Munger. It argues that educational institutions functioned not merely as centers of learning but also as spaces where ideas of social reform, civic responsibility, and national identity were cultivated. The research adopts the historical method and is based on a critical examination of archival records, district gazetteers, census reports, educational reports, newspapers, and relevant secondary literature. By integrating educational history with social and political developments, the study explores the emergence of an educated middle class, the gradual expansion of womens education, changing caste relations, the influence of print culture, and the participation of students and teachers in the Indian freedom movement. The analysis demonstrates that educational opportunities created new forms of social mobility and intellectual engagement, which, in turn, strengthened political awareness among diverse sections of society Datta, 1974, pp. 142–156 . The study further highlights that the nationalist movements, including the Swadeshi Movement, the Non Cooperation Movement, the Civil Disobedience Movement, and the Quit India Movement, gained wider public support in Munger because educational institutions and local intellectual networks disseminated nationalist ideals beyond urban elites Kumar, 2005, pp. 91–108 . Rather than viewing education solely as a colonial administrative instrument, this research interprets it as a dynamic force that enabled local communities to negotiate social inequalities and participate in broader political transformations. The findings contribute to regional historiography by demonstrating that the historical experience of Munger reflects the interconnected processes of educational development, social reform, and political mobilization in colonial Bihar. The study also offers a localized perspective that enriches the broader understanding of Indias struggle for independence and the historical role of education in shaping democratic consciousness Sarkar, 2019, pp. 221–239 Chaudhuri, 1964, pp. 58–74 . Amit Ranjan Jha "Education, Social Change, and Political Awakening in Munger District (1905–1947): A Historical Study" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102160.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102160/education-social-change-and-political-awakening-in-munger-district-1905–1947-a-historical-study/amit-ranjan-jha

With the simple and flexible capabilities of personal assistants, they have become intermediaries, changing the dynamics of artificial intelligence AI , and transforming human computer interactions This project uses AI powered personal assistant systems built on Python and introduces state of the art enhancements to language recognition features. The system seamlessly integrates state of the art natural language processing NLP and machine learning techniques using powerful Python libraries and programs to enable precise interpretation of spoken commands, and contextual understanding with intelligent response generation and achieves real time processing, ensuring rapid and appropriate communication in context using cloud services. The usefulness of the system is confirmed through empirical research, which shows its exceptional speech recognition accuracy, quality of response, and ability to deal with language difficulties. The program includes several features, such as Fluid Google search, email functionality through Gmail integration, real time news feed extraction, and dynamic Thanks to weather reports, clever use of familiar systems like WhatsApp and YouTube , this Python based AI personal assistant is a perfect example of how AI power, precise voice recognition and flexible functionality can all work together in harmony , Project Simple Effective and focuses on the power of work triggered by voice commands, and highlights the transformational impact of personal assistants using AI capabilities in conjunction with modern technology This is done by reframing the user interface. J.A.R.V.I.S. is an abbreviation of Just A Rather Very Intelligent System which refers to a AI System that is capable of performing additional features for humans and interacting accordingly. Ketan Suresh Ingale "Personal Desktop AI Assistant Using Python (J.A.R.V.I.S)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102033.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/102033/personal-desktop-ai-assistant-using-python-jarvis/ketan-suresh-ingale

The limitations of traditional alarm systems arise from their time based triggers which remain inactive during periods of user activity. Users who operate mobile devices encounter alarms which function as basic on off switches that do not possess abilities to comprehend their requirements or detect changes in their surroundings. The paper develops a new system called Smart Alarm Powered by Spring AI which uses an intelligent backend system to modernize traditional wake up calls through its interactive dialogue based system. The system combines Spring Boot framework with Spring AI library and local Large Language Models LLMs which use Ollama technology to create a system that connects basic task scheduling with advanced natural language handling capabilities. The proposed architecture enables a seamless real time voice to voice interaction paradigm, moving beyond the text heavy interfaces of contemporary virtual assistants. The system uses ElevenLabs high fidelity neural text to speech synthesis system to produce customized human like speech output, which goes beyond traditional applications that depend on fixed pre recorded sound alerts. The backend system uses MongoDB persistent metadata storage to keep user information, previous system interactions, and specific behavioral triggers, which helps the system provide continuous relevant user experiences. The AI generates context based answers through its ability to modify voice tone according to meeting urgency and present customers with instant weather and schedule briefings. The research examines two main technical problems which include low latency audio processing requirements and the need to establish AI systems that operate securely through local first deployment methods. Ritik Sapate "Autonomous Context-Aware Smart Alarms: A Localized Orchestration Framework using Spring AI and Ollama" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101700.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101700/autonomous-contextaware-smart-alarms-a-localized-orchestration-framework-using-spring-ai-and-ollama/ritik-sapate

The history of Indias freedom struggle demonstrates that women were not merely participants in political movements but also architects of social transformation. Among these influential figures, Prabhavati Devi emerged as a remarkable Gandhian leader whose contributions extended beyond the struggle for national independence to the advancement of womens education, social reform, and community development. Between 1920 and 1947, she actively promoted womens participation in public life through constructive programmes, rural mobilization, self reliance, and value based education. Her work reflected the Gandhian belief that true empowerment could only be achieved by combining education, moral leadership, and social responsibility. Although Prabhavati Devis role has often been discussed within the broader narrative of the Indian freedom movement, its implications for contemporary higher education remain insufficiently explored. This study adopts a historical and qualitative research approach based on the analysis of archival materials, published literature, and historical documents to examine Prabhavati Devis contribution to womens empowerment and its relevance to transformative higher education. The article argues that her educational philosophy anticipated many principles now emphasized in twenty first century higher education, including experiential learning, ethical leadership, community engagement, gender equity, and social inclusion. Her emphasis on character formation, service to society, and the empowerment of marginalized women resonates strongly with the objectives of the National Education Policy NEP 2020 and the global commitment to Sustainable Development Goals SDGs 4 and 5 . By connecting the ideals of the freedom struggle with present day educational reforms, this study highlights how historical experiences can inform institutional strategies for developing socially responsible and empowered women leaders. It concludes that Prabhavati Devis legacy offers an enduring framework for integrating democratic values, gender justice, and community oriented learning into higher education, thereby strengthening the transformative role of universities in promoting inclusive and equitable social development Forbes, 1996 Kumar, 2005 . Anamika Kumari "From the Freedom Struggle to Transformative Higher Education: Lessons from Prabhavati Devis Contribution to Womens Empowerment (1920–1947)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102161.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102161/from-the-freedom-struggle-to-transformative-higher-education-lessons-from-prabhavati-devis-contribution-to-womens-empowerment-1920–1947/anamika-kumari

In todays world news spreads fast on media, news websites and messaging apps. This is a thing because we get news quickly.. It also means false information and fake news can spread easily. Fake news can change peoples thoughts cause panic and create problems in society and politics. So we need systems that can automatically find and stop information. The system uses data science, natural language processing and machine learning to figure out if newss real or fake. The Fake News Detection System looks at the text users enter and processes it step by step including cleaning up the data finding features and making predictions. It uses things, like TF IDF vectorization and Logistic Regression to understand language and find misleading information. The Fake News Detection System is easy to use. Has a simple interface. Users can paste news content. Get results right away that say if the news is real or fake. By helping people share information responsibly the Fake News Detection System reduces the spread of information and makes the online world a more trustworthy place. Priyanka Dattu Chandurkar "Fake News Detection Using Machine Learning Techniques" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101698.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101698/fake-news-detection-using-machine-learning-techniques/priyanka-dattu-chandurkar

Thailand is a major country in Southeast Asia. The study and spread of Sanskrit has been going on here for a long time. The association prescribed for the original source of Thai and Southeast Asian languages with Sanskrit, however, reflects the relationship between Sanskrit and them since time immemorial. Thai literature and culture have felt a profound influence of Sanskrit. The present royal family, which belongs to the Chakru dynasty, has respectfully accepted the study of Sanskrit. Dr. Suman K. S. "??????? ?????????? ???? ??????????" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102163.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/sanskrit/102163/???????-??????????-????-??????????/dr-suman-k-s

Education emerged as one of the most significant instruments of social transformation during the Indian National Movement, particularly for Dalit and backward communities who had long experienced systemic exclusion from formal learning and public life. This study examines the growth of educational consciousness and its relationship with the pursuit of social equity among these marginalized communities in North Bihar between 1917 and 1947. The selection of 1917 as the starting point corresponds with the Champaran Satyagraha, which not only marked a new phase in Indias freedom struggle but also initiated constructive programmes emphasizing literacy, basic education, and social reform. The study explores how nationalist initiatives, social reform movements, local leadership, and community participation collectively contributed to expanding educational opportunities for historically disadvantaged groups. Adopting the historical research method, the study relies on archival records, census reports, government educational documents, district gazetteers, newspapers, and relevant secondary literature to analyze patterns of educational access and social change. It argues that educational awareness gradually evolved into a powerful means of challenging caste based discrimination, promoting social mobility, and strengthening political participation among Dalit and backward communities. Although colonial educational policies remained limited in addressing structural inequalities, the combined efforts of nationalist leaders, local reformers, voluntary organizations, and community institutions created new opportunities for learning and public engagement. Educational initiatives encouraged greater participation in civic life and fostered aspirations for equality, dignity, and self representation Ambedkar, 1936, pp. 41–45 . The study further contends that educational consciousness was not merely an outcome of political mobilization but also a catalyst for broader social transformation in North Bihar. By connecting educational development with struggles for social justice during the national movement, the article contributes to a deeper understanding of the historical roots of inclusive education and democratic citizenship in modern India. The findings highlight that the quest for education among marginalized communities laid an important foundation for post independence policies aimed at equality, social justice, and educational inclusion Jha, 1977, pp. 212–218 . Puja Kumari "Educational Consciousness and Social Equity among Dalit and Backward Communities during the Indian National Movement: A Study of North Bihar (1917–1947)" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | National Level Conference on Transformative Higher Education-Skills, Equity, Innovation (THE-SEI 2026) , May 2026, URL: https://www.ijtsrd.com/papers/ijtsrd102162.pdf Paper URL: https://www.ijtsrd.com/humanities-and-the-arts/education/102162/educational-consciousness-and-social-equity-among-dalit-and-backward-communities-during-the-indian-national-movement-a-study-of-north-bihar-1917–1947/puja-kumari

Preparing for job interviews can be challenging for many students and job seekers due to the lack of structured practice platforms and real time feedback. Traditional mock interview sessions often rely on human evaluators and therefore may lack consistency and accessibility. This research presents an AI based mock interview web application that integrates artificial intelligence, speech recognition, and facial expression analysis to simulate realistic interview scenarios. The proposed system is developed using React.js for the frontend interface and Node.js with PostgreSQL for backend data management. The application utilizes the Google Gemini API to dynamically generate interview questions tailored to the users selected job role and experience level. In addition, computer vision techniques implemented using OpenCV and the Haar Cascade classifier enable the system to analyse facial expressions and detect emotional indicators such as confidence and stress during interview responses. The React Speech Recognition Hook allows candidates to respond verbally, creating a more natural and interactive interview experience. By combining AI generated questions, speech recognition, and real time emotion analysis, the system provides meaningful feedback that helps candidates improve communication skills, confidence, and overall interview performance. Priya Kushwaha "AI Based Mock Interview Web-Application with Real-Time Facial Expressions Recognition" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101696.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101696/ai-based-mock-interview-webapplication-with-realtime-facial-expressions-recognition/priya-kushwaha

Search tools are a fundamental pillar in the journey of a scientific researcher, representing the gateway to accessing the knowledge and information necessary to enrich and develop research. These tools include various material and electronic resources used throughout studies, including mechanisms and research websites. This paper focuses on digital search tools search engines , which are the main instruments available for online research, where the choice of tool depends on the researcher’s needs. AI powered search engines represent one of the most important stages of the technological revolution today. These engines enhance search quality and user experience by providing faster and more accurate results. The study discusses the importance of AI technologies in improving search engines’ ability to understand user queries and deliver customized content. The study focuses on search engines relying on AI technologies such as machine learning and natural language processing, explaining their working mechanisms and practical applications. The research problem concerns improving the effectiveness and efficiency of traditional search engines using AI technologies and addressing challenges related to accuracy, speed, and personalization. Pratik Khushal Thakare "Ai-Based Search and Ranking System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101695.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101695/aibased-search-and-ranking-system/pratik-khushal-thakare

The transformation of workplaces from traditional office settings to digital environments has significantly impacted employee well being. While traditional workplaces emphasize physical interaction and structured routines, digital workplaces offer flexibility, autonomy, and technological integration. This paper presents a secondary research based comparative analysis of employee well being in traditional and digital workplaces. It examines key dimensions such as mental health, work life balance, productivity, and stress. The study concludes that while digital workplaces enhance flexibility and satisfaction, they also introduce new challenges such as technostress and burnout, requiring balanced organizational strategies. Trupti Kharche "Comparative Study of Employee Well-Being: Traditional Vs Digital Workplace" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Reimagining Management-Sustainability and Innovation in the AI Era , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101918.pdf Paper URL: https://www.ijtsrd.com/management/other/101918/comparative-study-of-employee-wellbeing-traditional-vs-digital-workplace/trupti-kharche

With digital services growing cyber threats like phishing, credential stuffing, brute force attacks and identity theft are on the rise. Old single factor authentication systems that only use passwords are not enough to protect information and critical systems. This paper looks at how Two Factor Authentication 2FA can improve security. 2FA is a security method that requires users to give two verification factors to access a system. It combines least two of the following 1. Something the user knows password or PIN 2. Something the user has OTP token, smartphone or smart card 3. Something the user is verification . By adding a layer of security 2FA greatly reduces the risk of unauthorized access even if passwords are compromised. The study looks at 2FA techniques, including SMS based One Time Passwords OTP Time Based One Time Passwords TOTP hardware tokens, biometric authentication. It checks how well they work, how easy theyre to use the challenges of implementing them and potential vulnerabilities like SIM swapping and phishing attacks. The paper also looks at real world examples of organizations that used 2FA to prevent security breaches. It discusses practices for integrating 2FA into web applications using secure protocols and encryption standards. The research concludes that 2FA is a cost practical solution for improving cyber security in areas like banking, education, government and enterprise environments. The use of layered authentication mechanisms is crucial, in building strong digital ecosystems and protecting confidential information against evolving cyber threats, Two Factor Authentication 2FA helps to achieve this. Pawan Ashok Jagdeve "Strengthening Cyber Security Through 2F Authentication" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101693.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101693/strengthening-cyber-security-through-2f-authentication/pawan-ashok-jagdeve

The global transition toward electric vehicles EVs has accelerated as a primary strategy for climate change mitigation and the achievement of net zero emission targets. The transition to this new system encounters major technical obstacles which hinder efforts to reduce greenhouse gas emissions. The automotive industry requires rigorous research into market development and battery optimization as technology evolves. The process of electrification helps the environment but creates new challenges for power grid stability and battery safety management. EV technology has emerged as a critical field within Energy Informatics which uses data science to connect green transportation systems with economic systems. Machine Learning ML serves as the foundation for contemporary sales prediction which enables businesses to estimate market growth and consumer preferences with increased efficiency and lower costs. The public transit sector and personal transportation industry both adopt EV technology despite its high initial capital costs because it helps reduce global petroleum dependence. The current pace of technological development makes it hard for stakeholders to tell temporary market changes apart from long term market growth which results in increased investor uncertainty and stock market fluctuations. The primary objective of this project is to conduct an accurate evaluation of EV market dimensions while identifying the essential factors driving expansion through data analysis. This study used predictive algorithms to analyze major worldwide datasets which included both socio economic and socio technical factors to determine adoption patterns. The research team created and tested regional models using data from the United States, China, and Europe to confirm their geographical applicability. Omkar Tijare "Predictive Modeling of Electric Vehicle Market Using Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101692.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101692/predictive-modeling-of-electric-vehicle-market-using-machine-learning/omkar-tijare

Object detection is a task in computer vision. It focuses on finding and locating objects in images or videos. With deep learning advancements, object detection systems have improved a lot in accuracy and speed. This research paper presents an object detection system using modern deep learning algorithms. The system uses neural networks CNN to detect and classify objects in real time. A large labeled dataset trains the model to recognize object categories. The system processes images. Generates bounding boxes around detected objects along with their labels. Object detection systems use frameworks like YOLO to enhance detection speed and performance. The proposed method aims to achieve precision while maintaining low computational complexity. Experimental results show that the system performs under different lighting and environmental conditions. The model shows accuracy in detecting multiple objects simultaneously .Object detection systems can be integrated into applications like surveillance systems and autonomous vehicles. They can also be used in security systems and traffic monitoring. The research highlights the importance of deep learning techniques in object detection systems.The proposed approach provides an scalable solution for real world applications. Future work will focus on improving detection accuracy and expanding the dataset. The system can be optimized for embedded devices. Overall the proposed object detection system demonstrates promising results, for visual recognition tasks. Rutuja Kale "Object Detection System using Machine learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101691.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101691/object-detection-system-using-machine-learning/rutuja-kale

The importance of internships in advancing student careers has increased due to the increasing demand for graduates who are ready for the workforce. However, there is a significant gap between the skills that students possess and the credentials that employers are looking for. Most online internship sites rely on keyword filtering and dont provide personalized assistance or skill deficiency analysis. This often leads to unsuccessful applications, ongoing rejections, and a lack of structured professional growth. In order to bridge the gap between academic preparedness and industry demands, this document presents SkillBridge, an online internship suggestion and skill gap assessment system. The platform uses machine learning driven similarity scoring to generate customized internship recommendations, rule based criteria evaluation, and Natural Language Processing NLP for resume analysis. Additionally, it identifies skills that are lacking or inadequate and provides structured suggestions for improvement. By focusing on student focused career support and combining opportunity exploration with useful skill enhancement insights, SkillBridge sets itself apart from conventional internship platforms. Controlled functional testing was used to evaluate the system using a variety of simulated student profiles. Results show that the proposed hybrid approach effectively generates relevant internship recommendations and accurately identifies skill gaps, supporting well informed decisions and improving employability. The goal of SkillBridge is to serve as a useful tool for career counseling that helps students make informed decisions, develop their skill sets, and increase their chances of landing suitable internships in competitive environments. Vedant Dhanraj Wankhede "SkillBridge – Internship & Skill Gap Analyzer" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101689.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101689/skillbridge-–-internship-and-skill-gap-analyzer/vedant-dhanraj-wankhede

My cousin called me last year saying her AC stopped working and she had no idea who to call. She tried three numbers she found online — one didnt pick up, one asked for advance payment before even seeing the problem, and the third quoted something on the phone that doubled by the time the job was done. No receipts. No accountability. Just frustration. Honestly that experience stuck with me and its a big reason why I started working on EasyCare. EasyCare is a mobile app I put together for home repair and maintenance — AC work, plumbing, electricals, painting, tiles, that kind of thing. UI UX wasnt something I tacked on at the end I started there. My thinking was simple — if someones pipe is leaking at 10pm, they shouldnt need to figure out the app. It should just work. Before any wireframe, I sat down with actual people — homeowners, renters, professionals, older folks who live by themselves. Just asked them to walk me through what happens when something breaks. I listened. I took notes. From those conversations I built personas, made rough sketches, then prototypes, then tested them. Every session revealed something that needed fixing. That process of testing, breaking, fixing — thats what the final design came from. Trust kept coming up. Every person I spoke to mentioned it in some form. Youre letting a stranger into your bedroom, your bathroom, your kitchen — thats not nothing. So I made sure the app shows verification status, past ratings, and job history right where youre making the decision. Not buried three screens deep. Right there. Pricing visible before you tap confirm. What you see is what you pay. When I tested prototypes with users, the feedback was mostly positive — people moved through bookings faster, said they felt more confident, and described the whole thing as less stressful than what theyre used to. The technicians I spoke to also liked the idea of having a dashboard to manage their work instead of relying on phone calls and WhatsApp messages. That matters to me — its not just about making things easier for customers, the workers need a better system too. Vrushika Urade "EasyCare: A UI/UX-Centered Mobile Application for Streamlined Home Repair and Maintenance Services" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101688.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101688/easycare-a-uiuxcentered-mobile-application-for-streamlined-home-repair-and-maintenance-services/vrushika-urade

It is a systematic literature review that summarizes the results of 45 peer reviewed articles 2021 2025 analyzing the role of generative AI in creative gig platforms and creative work, employing corpus based semantic search across multidisciplinary databases with rigorous inclusion exclusion criteria and thematic synthesis. Findings indicate the existence of a paradoxical situation sharpening productivity by 25 50 and opening access to various types of designs, generation AI, on the other hand, initiates a decline in prices by 64 and concentrates market gains in the hands of existing players, forcing freelance employees to seek alternative employment opportunities. The technology fundamentally transforms the way the skills are valued, placing the power not in the specialized expertise, but in the general cognitive proficiency, hence increasing instead of diminishing inequality. Some of the main issues are intellectual property matters, the loss of professional identity, and the tragedy of the generative commons such that the widespread adoption of AI would reduce collective creative integrity. W Nicolas | Dr. Kiirii Onand Monsang "Generative AIs Impact on Creative Gig Platforms: A Systematic Review 2026" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Reimagining Management-Sustainability and Innovation in the AI Era , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101901.pdf Paper URL: https://www.ijtsrd.com/management/other/101901/generative-ais-impact-on-creative-gig-platforms-a-systematic-review-2026/w-nicolas

The real estate sector has grown fast because of digital technologies. Traditional real estate systems are often slow because they rely on processes like brokers visiting properties in person and not having clear information. This leads to delays and inefficiency. This research paper talks about building an Intelligent Web Based Real Estate Portal using web technologies like React.js, Node.js, Express.js, MongoDB and cloud services. The portal lets buyers search and filter properties online. Sellers can. Manage their property listings. Administrators can check listings. Manage users. The system keeps user data safe handles information efficiently. Has a user friendly interface. The goal is to save time make things more transparent and improve communication between buyers and sellers. The Real Estate Portal also plans to add features, like AI based recommendations predicting property prices and virtual property tours in the future. Minal Khadgi "An Intelligent Web-Based Real Estate Portal Using Modern Web Technologies" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101678.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101678/an-intelligent-webbased-real-estate-portal-using-modern-web-technologies/minal-khadgi

We live in a world where we buy things online. There are many websites that sell things and they have a lot of details about the products they sell. These details include the price of the products what other people think of them and what the products are. It takes a time to look at all these details by hand. That is why we use something called web scraping to collect details from websites. This project is about a system that uses Python to collect details from Flipkart. The system uses tools like Requests and Beautiful Soup and Selenium to get details about the products on Flipkart. We want to know the names of the products how much they cost what people think of them and what they are. We take the details we collect. Make them clean and easy to use. We store the Flipkart details in a format like a CSV file or a SQL database. We can use the Flipkart details we collect to see what is happening in the market. This system shows how we can use automation and collecting Flipkart details to help us make decisions and to do research on Flipkart products. The system is designed to extract product details from Flipkart. It uses Python to do this. We use the collected Flipkart data to do things like market analysis, price comparison and consumer behavior analysis. Consumer behavior analysis is the study of what people buy from Flipkart and why they buy these products from Flipkart. This project is about using automation to collect details from websites like Flipkart. It shows how this can be useful, for people who want to do research or make business decisions using Flipkart details. We can learn a lot from the details we collect from Flipkart. We can use Flipkart details to make decisions. Taniya Pawan Pal "Automated Web Scraping System for E-Commerce Data Extraction Using Python" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101687.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101687/automated-web-scraping-system-for-ecommerce-data-extraction-using-python/taniya-pawan-pal

In todays digital marketplace, brands leverage Artificial Intelligence AI to deliver targeted green marketing campaigns on social media, aiming to influence young Indian consumers aged 18–30 toward sustainable choices. This study examines how AI driven strategies personalized advertisements, recommendation algorithms, and influencer partnerships affect trust in eco friendly claims, purchase intentions, and willingness to pay premiums. Objective To bridge gaps in understanding AIs role in promoting genuine sustainability versus greenwashing risks, this paper proposes the AI Enabled Green Branding Trust – Outcome AIGTO Framework through conceptual synthesis of literature on AI personalization, green branding, and social medias impact on eco conscious behavior in India. Findings Transparent AI use enhances consumer trust and sustainable purchase intentions, while opaque or exaggerated claims undermine them. Implications Marketers should prioritize verifiable green credentials in AI campaigns, ensure influencer authenticity through disclosures, and integrate ethical AI practices to drive genuine environmental impact. This framework contributes to reimagining sustainable innovation in the AI era, benefiting brands, consumers, and society. Nikita Lakhani " AI-Powered Green Marketing and Consumer Trust: A Conceptual Framework for Fostering Sustainable Choices among Indian Youth on Social Media" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Reimagining Management-Sustainability and Innovation in the AI Era , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101902.pdf Paper URL: https://www.ijtsrd.com/management/other/101902/-aipowered-green-marketing-and-consumer-trust-a-conceptual-framework-for-fostering-sustainable-choices-among-indian-youth-on-social-media/nikita-lakhani

Cybersecurity has become a critical concern in today’s digital world due to the rapid growth of cyber attacks such as malware, ransomware, phishing and data breaches. Organizations and individuals face serious threats that may cause financial and information loss. Although cybersecurity education is growing, most students lack practical exposure because testing malicious software on real systems is risky and may lead to system failure or data leakage. This research proposes a Cybersecurity Sandbox Application that provides a secure and isolated environment for executing and analyzing suspicious files. The system allows users to monitor malware behaviour such as file modification, network activity and resource consumption without affecting the host system. The proposed framework focuses on educational purposes and beginner friendly design. The implementation is carried out using Python, Flask, HTML, CSS and JavaScript. The results demonstrate that the system successfully detects suspicious behaviour and improves practical cybersecurity learning. The proposed solution helps bridge the gap between theoretical knowledge and real world cybersecurity skills. Nisha Hanumanta Lashkar "Design and Implementation of a Cyber Security Sandbox for Malware Analysis" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101686.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101686/design-and-implementation-of-a-cyber-security-sandbox-for-malware-analysis/nisha-hanumanta-lashkar

Rapid developments in technology, globalization, and changes in demands in the workplace require the education system to move towards greater autonomy and flexibility in learners along with their ability to transfer knowledge and skills. This paper explores empirical findings in relation to pedagogies that promote leadership among students and look to the future, focusing on project based learning PBL , competency based education CBE , metacognition and self regulated learning SRL , retrieval practice, universal design for learning UDL , design thinking, and ethical use of artificial intelligence AI . Based on frameworks developed internationally by organizations like the OECD Learning Compass 2030 and the World Economic Forum’s skills outlook, this paper proposes an integrated framework for high impact classrooms. Mallika Menon "Future Focused Learning: Shaping Tomorrows Classrooms Through Student Led Approaches" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Reimagining Management-Sustainability and Innovation in the AI Era , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101909.pdf Paper URL: https://www.ijtsrd.com/management/other/101909/future-focused-learning-shaping-tomorrows-classrooms-through-student-led-approaches/mallika-menon

As organizations increasingly delegate high stakes decisions from talent acquisition to resource allocation to autonomous systems, a responsibility gap emerges. This paper investigates the concept of moral residue in the age of automation the lingering ethical obligation that remains with a leader even when an algorithm executes a choice. While AI driven innovation promises unparalleled efficiency, it often creates algorithmic distance, potentially leading to moral decoupling and an abdication of leadership oversight. This research proposes a governance framework for ethical accountability, shifting the focus from technical black box mechanics to the leader’s duty of understanding. By integrating Human in the Loop HITL protocols and transparency audits, the study argues that true organizational sustainability is only achievable when innovation is anchored in human centric responsibility. The paper concludes that leaders must embrace, rather than outsource, the moral consequences of automated outcomes to maintain stakeholder trust and long term social legitimacy. Moushmi Prasad " The Moral Residue of Automated Decisions: A Framework for Leader Accountability" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Reimagining Management-Sustainability and Innovation in the AI Era , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101903.pdf Paper URL: https://www.ijtsrd.com/management/other/101903/-the-moral-residue-of-automated-decisions-a-framework-for-leader-accountability/moushmi-prasad

Student dropout is one of the most complex challenges facing the education systen worldwide. Is order to evaluate the success of Machine Learning and Deep Leaming algorithms in predicting student dropout, a systematic review was conducted. The search was carried out in several electronic bibliographic databases, including Scopus, IEEE, and Web of Science, covering up to June 2023, having 246 articles as search reports. Exclusion criteria such as review articles. editorials, letters, and comments, were established. The final review included 23 studies in which perfornance metric such as accuracy precision, sensitivity recall, specificity, and area under the curve AUC were evaluated. In addition aspects related to study modality, training, testing strategy, cross validation, and confounding matrix were considered. The review results revealed that the most used Machine Learning algorithm was Random Forest, present in 21.73 of the studies this algorithm obtained an accuracy of 99 in the prediction of student dropout, higher than all the algorithms used in the total number of studies reviewed. Sanzal Chandrakant Fulewale "Student Dropout Risk Prediction with Academic Trend Analysis -Using AI/ML" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101683.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101683/student-dropout-risk-prediction-with-academic-trend-analysis-using-aiml/sanzal-chandrakant-fulewale

Rainfall predictions are critical exercises in agricultural, water resource, disaster and climate management. Conventional rainfall prediction techniques rely primarily on numerical weather prediction models, which may be computationally expensive and sometimes inadequate for predicting complex weather patterns. This research work champions an Artificial Intelligence AI and Machine Learning ML based rainfall prediction system. Rainfall prediction variables input will, therefore, be the historical weather variables such as temperature, humidity, atmospheric pressure, wind speed, and rainfall. Machine learning algorithms such as Decision Tree, Random Forest, Support Vector Machine, and LSTM networks are trained and then performance compared to select the best performing algorithm. Methods of data processing include normalization, feature extraction, and missing data treatments to improve the efficiency of the models. Based on classification or regression performance metrics, the models are evaluated with an accuracy, precision, and recall, mean absolute error MAE , and a root mean square error RMSE . Experimental results show that ensemble models and deep learning models provide more prediction accuracy compared to statistical approaches. Nehal Ganpati Bansod "A Predictive Model for Rainfall Forecasting Using Artificial Intelligence and Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101685.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101685/a-predictive-model-for-rainfall-forecasting-using-artificial-intelligence-and-machine-learning/nehal-ganpati-bansod

Human Resource Management HRM , the crucial part in improving the efficiency and effectiveness of Human Resource in public welfare programs. With the increasing use of digital tools in government run schemes, lot of existent practices are slowly and gradually being taken over by digital programs. We may refer, Integrated Child Development Services ICDS program, which has also adopted various digital tools for management of these human resources, comprising of digital reporting, online attendance, tech driven training structure and electronic communication facility. In this context, this study aims at evaluating and comparing traditional manual and modern digital Human Resource Management HRM systems in ICDS and analyse its impact on program efficiency. This study follows a detailed study pattern to understand the prevailing HRM practices and their influence on the performance of ICDS staff such as Anganwadi Workers, Helpers, Supervisors, and Child Development Project Officers. Data are collected using a structured questionnaire focusing on major HRM functions including recruitment, training and development, performance management, compensation, employee relations, and HR administration. The study attempts to highlight how the shift from manual procedures to digital HRM systems has influenced transparency, communication, monitoring, and service delivery. The findings of the study are expected to provide insights into the effectiveness of digital HRM practices in improving employee efficiency and administrative functioning within ICDS. Furthermore, the study may help policymakers and administrators understand the benefits and challenges associated with digital transformation in HR management and suggest ways to strengthen digital HR systems in social welfare programs. Jayshree Sharma | Dr. Manish Sharma "Traditional vs Digital Human Resource Management Systems in ICDS: A Comparative Study of Their Impact on Employee Efficiency" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Reimagining Management-Sustainability and Innovation in the AI Era , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101904.pdf Paper URL: https://www.ijtsrd.com/management/other/101904/traditional-vs-digital-human-resource-management-systems-in-icds-a-comparative-study-of-their-impact-on-employee-efficiency/jayshree-sharma

Digital healthcare solutions are increasingly being adopted to improve accessibility and timely medical support. However, many individuals still struggle to obtain primary healthcare due to factors such as limited availability of medical professionals, high treatment costs, and lack of awareness about preventive care. With the growing penetration of smartphones, a self help Medicare mobile application can act as a convenient health guidance tool for the general population. This study examines the awareness, need, and acceptance of such an application among users. A descriptive research approach was adopted using a structured questionnaire, with primary data collected from respondents through convenience sampling. The findings indicate that although people frequently rely on smartphones, awareness about healthcare apps remains low. Respondents expressed strong interest in a simple, trustworthy, multilingual app providing first aid assistance, symptom assessment, and basic medical guidance. The study concludes that there is significant potential and user readiness for a self help Medicare app, provided it ensures ease of use, information accuracy, and data privacy. The insights from this research offer recommendations for designing an effective mobile health application to support preventive healthcare and reduce the burden on traditional medical infrastructure. Dr. Hema S. Dhaware | Mr. J. K. Mahida "The Study on Awareness, Need & Acceptance of a Self-Help Application" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Reimagining Management-Sustainability and Innovation in the AI Era , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101905.pdf Paper URL: https://www.ijtsrd.com/management/other/101905/the-study-on-awareness-need-and-acceptance-of-a-selfhelp-application/dr-hema-s-dhaware

DocuFlow, another name for a centralized document management system with secure cloud storage DMS , is an web app that keeps all types of documents in one location. Employees and admin are among the access based roles that are used by the DocuFlow management system, which keeps the document in cloud storage. The web application is protected by encryption and authentication. Everything is safely kept in the cloud and controlled via a single platform that is backed up on cloud storage, as opposed to being stored on local devices or dispersed folders. Some issues with the traditional file management system include lost files, improper access control, version control, and security. It is also difficult to determine who made changes without a central backup. Based on the given problems of storing documents in traditional ways, a centralized document system with a secure cloud solution comes up. A centralized DMS solves all of these problems, and many Industries using DMS in the following sectors banks, Hospitals, Colleges, IT companies, and Government Offices. DMS provides centralized storage for documents, ensuring secure access using authentication and authorization with role based access control RBAC While maintaining document version history and activity logs with encrypted cloud storage, enable easy retrieval and search. Sonali Bihari Buwade "Centralized Document Management System with Secure Cloud Storage - DocuFlow" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101684.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101684/centralized-document-management-system-with-secure-cloud-storage--docuflow/sonali-bihari-buwade

This research critically examines the transformative role of AI chatbots in recruitment compared to traditional methods, with specific focus on candidate experience. Through systematic analysis of existing literature and industry case studies, the study reveals that AI chatbots reduce recruitment time by 43 and costs by up to 50 while providing 24 7 candidate engagement. However, significant challenges persist including algorithmic bias, lack of human empathy, and transparency issues. Traditional recruitment methods, while offering personal interaction, remain time consuming and prone to human bias. The study synthesizes findings from three foundational research papers spanning 2021 2025 to identify technological growth patterns, including advancements in Natural Language Processing, predictive analytics, and conversational AI. Case studies from Indian organizations including Infosys, Reliance Industries, and Flipkart demonstrate successful AI implementation, with Unilever reporting 75 reduction in hiring time. The research identifies critical research gaps including missing candidate centric perspectives, cross cultural insights, and underexplored hybrid models. Findings suggest that optimal recruitment outcomes require balanced integration of AI efficiency with human judgment, supported by ethical oversight and continuous bias auditing. The study concludes with recommendations for developing hybrid recruitment frameworks and global ethical standards for AI powered hiring. Prabhpreet Kaur Nagpal "A Critical Comparative Study of AI Chatbots and Traditional Recruitment Approaches: Reviewing Candidate Experience in Terms of Challenges, Technological Growth, and Future Opportunities" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Reimagining Management-Sustainability and Innovation in the AI Era , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101906.pdf Paper URL: https://www.ijtsrd.com/management/other/101906/a-critical-comparative-study-of-ai-chatbots-and-traditional-recruitment-approaches-reviewing-candidate-experience-in-terms-of-challenges-technological-growth-and-future-opportunities/prabhpreet-kaur-nagpal

The tectonic changes that have permeated the Business world today has revolutionised the manner in which key functions have been automated and operationalised. AI driven tasks have simplified routine, repetitive tasks, potentially rendering human involvement redundant. The paper delves into how AI enabled systems are changing the complexion of core HR activities, even as it brings to the fore, crucial issues such as Bias, Opacity, Data usage in the decisioning process. The paper examines the need to balance the efficiency that AI provides with the concomitant ethical issues of trust, accountability and equity. Theoretically, it reviews the various AI tools deployed in recruitment such as predictive analytics, tracking systems, juxtaposing it with the ethical challenges that ensue, such as lack of transparency, bias and privacy issues. The paper then seeks to provide suggestions to mitigate these issues, so as to bring into play a responsible and ethically acceptable methodology. The HR personnel need to be sensitive to and cognisant of this need for balance, ensuring that employee well being is not sacrificed at the altar of efficiency. Human oversight, Impact audits, clear articulation about the deployment of AI with prospective employees and using an human centric, inclusive approach can help drive the ethical framework, resulting in aligning organisational goals in a sustainable, socially responsible manner. Ms Bharati Pratik Roy "AI in the Field of Human Resource Management - Implications for Employee Well-Being and the Related Ethical Issues" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Reimagining Management-Sustainability and Innovation in the AI Era , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101907.pdf Paper URL: https://www.ijtsrd.com/management/other/101907/ai-in-the-field-of-human-resource-management--implications-for-employee-wellbeing-and-the-related-ethical-issues/ms-bharati-pratik-roy

The rapid integration of artificial intelligence AI into digital marketing has transformed how organizations engage with consumers through personalization, predictive analytics, and automated decision making. While these technologies enhance efficiency and customer experience, they also raise significant concerns regarding ethics and transparency, particularly in areas such as data privacy, algorithmic bias, and opaque decision making processes. This research paper examines the ethical challenges associated with AI driven digital marketing and emphasizes the importance of transparency as a critical factor in building consumer trust. It proposes a structured framework that integrates ethical principles into marketing strategies, focusing on data protection, informed consent, algorithmic accountability, and explainability. Additionally, the paper presents case studies from leading organizations such as Google, Amazon, Meta, Netflix, and Spotify to illustrate real world applications and challenges. The findings highlight that organizations that prioritize ethical transparency are more likely to build long term trust, improve brand reputation, and achieve sustainable success in the digital economy. Sheenu Tiwari "Ethical and Transparent Digital Marketing in the Age of AI: A Framework for Trust Building" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Reimagining Management-Sustainability and Innovation in the AI Era , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101908.pdf Paper URL: https://www.ijtsrd.com/management/other/101908/ethical-and-transparent-digital-marketing-in-the-age-of-ai-a-framework-for-trust-building/sheenu-tiwari

The rapid growth of digital financial markets has produced large amounts of stock related data that need efficient analysis for meaningful interpretation. Manually observing market trends takes a lot of time and is often unreliable for decision making. This study introduces a web based stock market prediction system that combines data analysis techniques with simple machine learning models to help users understand stock behavior. The proposed system gathers historical stock data, processes relevant indicators, and generates short term trend predictions. A web interface is created to display stock performance through interactive charts and tables, allowing users to interpret patterns without needing technical knowledge. The system combines Python for backend processing with web technologies for real time user interaction. Experimental results show that the system effectively identifies stock movement trends and offers an easy to use platform for market analysis. This approach focuses on simplicity, interpretability, and educational usability, making it suitable for both academic and practical uses in financial data analysis. Sanskruti Sanjay Dube "Web-Based Stock Market Prediction Using Artificial Intelligence" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101682.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101682/webbased-stock-market-prediction-using-artificial-intelligence/sanskruti-sanjay-dube

As Small and Medium Enterprises SMEs in India transition toward automated management, AI driven Applicant Tracking Systems ATS have become the primary gatekeepers of employment. However, these innovations often carry an Algorithmic Glass Ceiling —a systemic bias that marginalizes candidates based on linguistic accents, institutional backgrounds, and digital formatting literacy. This paper investigates the shift from human centric to machine centric hiring in India. By analyzing the Tokenization Gap and Data Colonialism, the study proposes a Transparent Inclusion Framework The 3 A Audit . The research concludes that for AI to be a sustainable tool in Indian management, it must be redesigned to recognize merit over keyword compliance, ensuring that the 63 million SMEs in India can tap into the country’s diverse talent pool. Asst. Prof. Manimekhalai Sethuraman Iyer | Asst. Prof. Sampada Mavalankar "The Algorithmic Glass Ceiling: A Socio-Technical Management Framework for Mitigating Bias in AI-Driven Recruitment for Indian SMEs" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Reimagining Management-Sustainability and Innovation in the AI Era , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101921.pdf Paper URL: https://www.ijtsrd.com/management/other/101921/the-algorithmic-glass-ceiling-a-sociotechnical-management-framework-for-mitigating-bias-in-aidriven-recruitment-for-indian-smes/asst-prof-manimekhalai-sethuraman-iyer

The rapid advancement of Artificial Intelligence AI and Machine Learning ML has facilitated the creation of highly sophisticated digital forgeries, commonly known as deepfakes. These manipulations, which involve layering one individuals facial features over another using Generative Adversarial Networks GANs , pose significant security risks by enabling the spread of misinformation, fake news, and fabricated electronic evidence. This project presents ForensiX Image Forgery Detector, a comprehensive multi stage forensic framework designed to authenticate digital media and detect sophisticated image and video forgeries. The ForensiX system utilizes a hybrid detection strategy that integrates traditional forensic techniques with deep learning architectures. The methodology begins with a detailed preprocessing phase where individual video frames are extracted and analyzed using a 68 point facial landmark predictor. This allows the system to track temporal facial features such as eye blinking patterns—calculated via the Eye Aspect Ratio EAR —and inconsistencies in the shapes of the eyes, nose, and lips. Furthermore, the system incorporates Error Level Analysis ELA to identify compression inconsistencies often introduced during digital manipulation. The core classification engine of ForensiX is a customized Convolutional Neural Network CNN model consisting of 20 layers, including four convolutional layers, six batch normalization layers, and dropout layers to prevent overfitting. This model was trained and validated using a diverse dataset composed of 318 videos from the Kaggle Deepfake Detection Challenge and YouTube, totaling approximately 10GB of data. Experimental results demonstrate that the customized CNN model significantly outperforms standard CNN and MLP CNN architectures. The ForensiX detector achieved a superior training accuracy of 97.21 and a validation accuracy of 91.47 , with a reduced loss value of 0.342 and an Area Under the Curve AUC of 0.92. These metrics indicate a 92 probability of successfully distinguishing forgeries from authentic media. Developed for forensic operatives in the Nagpur Division, the suite includes real time IST synchronized logging, luminance gradient analysis, and automated CSV reporting to maintain a strict chain of custody for digital evidence. Future work will focus on expanding the datasets diversity and integrating blockchain technology to ensure immutable forensic logging. Sanskar Vijay Dhore "ForensiX: A Multi-Stage Forensic Framework for Image Forgery Detection using Error Level Analysis and Convolutional Neural Networks" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101681.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101681/forensix-a-multistage-forensic-framework-for-image-forgery-detection-using-error-level-analysis-and-convolutional-neural-networks/sanskar-vijay-dhore

We expect financial reports to tell the truth. But managers have their discretion in how they present numbers, and sometimes, they use that flexibility to polish the reality. This is called ‘Earnings Management’ Dechow et al., 2010 , and it quietly erodes investor trust. The problem runs deeper in emerging markets, when a handful of promoters calls the shots and governance rules are still evolving, earnings management can easily fly under the radar. Now, enter AI. Artificial Intelligence is transforming how companies report, how boards oversee, and how regulators detect trouble. Smart algorithms can scan millions of transactions, flag suspicious patterns, and alert auditors in real time. In theory, AI could make earnings management much harder to hide. But technology alone is not enough. This paper asks a simple question as AI reshapes financial reporting, can stronger governance and smarter ownership structures keep earnings management in check Or will new tools just create new ways to game the system Rather than running fresh models, this study synthesizes decades of research on why ownership matters, how boards and audit committees guard transparency, and where institutional investors make a difference Jensen and Meckling, 1976 Shleifer and Vishny, 1997 . It then brings these insights into the AI era, asking whether old governance rules still apply when machines are part of the picture. The takeaway AI driven tools can certainly strengthen oversight. But they work best when grounded in robust governance frameworks. Technology without strong oversight is just speed without direction. Mishra Himanshu K " Corporate Governance in the AI Era: Can Technology Curb Earnings Management in Emerging Markets?" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Reimagining Management-Sustainability and Innovation in the AI Era , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101910.pdf Paper URL: https://www.ijtsrd.com/management/other/101910/-corporate-governance-in-the-ai-era-can-technology-curb-earnings-management-in-emerging-markets/mishra-himanshu-k

Edtech has changed education. We can use it anytime from anywhere to access resources. Educational websites that are easy to use and work on all browsers are becoming more necessary as people learn. This research aims to create an EdTech website that makes it easy for students to access, use, and buy content. The proposed system focuses on design principles, easy navigation and structured presentation of course information. The website was made with HTML and CSS and JavaScript and Bootstrap. These things help the platform work, on computers and phones and everything. We developed the platform in stages interface design, development, testing, analysis, and deployment. The results show that our platform offers design, easy navigation, and simple access to educational resources. As a result, student engagement increases. The study says that flexible web design is crucial for creating a learning environment. Flexible web design helps people learn easily. Sakshi A Thakre "Design and Development of a Responsive EdTech Website for Enhanced Digital Learning Experience" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101680.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101680/design-and-development-of-a-responsive-edtech-website-for-enhanced-digital-learning-experience/sakshi-a-thakre

The retail industry has undergone a profound transformation over the past decade, driven by technological advancements and evolving consumer expectations. Among these changes, social media has emerged as a dominant force influencing how retailers design and present their products. Asst Prof Shubha Shah | Dr. Usha V Bhandare "Digital Influence on Retail Aesthetics: Examining the Role of Social Media in Transforming Visual Merchandising Strategies" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Reimagining Management-Sustainability and Innovation in the AI Era , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101912.pdf Paper URL: https://www.ijtsrd.com/management/other/101912/digital-influence-on-retail-aesthetics-examining-the-role-of-social-media-in-transforming-visual-merchandising-strategies/asst-prof-shubha-shah

Growing awareness of sustainable practices has reshaped both consumer behaviour and corporate strategy. As environmental consciousness increases, organizations are revisiting traditional marketing approaches and integrating eco friendly strategies into core branding. This study examines how environmentally responsible marketing practices contribute to sustainable brand equity using secondary data from existing research, corporate reports, and industry analyses. It explores how authentic communication, transparency, and genuine environmental commitment influence consumer trust, brand perception, and purchase decisions. The study also highlights the challenges of greenwashing, demonstrating that misleading sustainability claims can harm corporate reputation and undermine long term loyalty. By evaluating the alignment between sustainability messaging and actual corporate actions, the research emphasizes the importance of ethical marketing practices. Findings indicate that enduring brand value is achieved not merely through environmental messaging, but through consistent, measurable sustainability initiatives communicated transparently. Authenticity and strategic coherence emerge as essential determinants of long term relationships with environmentally conscious consumers. Asst. Prof. Janhavi Patil " Green Marketing And Sustainable Brand Equity: The Role of Authenticity, Transparency and Ethical Communication" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Reimagining Management-Sustainability and Innovation in the AI Era , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101911.pdf Paper URL: https://www.ijtsrd.com/management/other/101911/-green-marketing-and-sustainable-brand-equity-the-role-of-authenticity-transparency-and-ethical-communication/asst-prof-janhavi-patil

Melanoma grows fast and new cases increase each year, above all in people who have light skin that develops freckles after a short stay in strong sun. Detect the tumour at the first stage plus the outcome changes completely, in the same way that a spark caught at the instant it crackles prevents a fire. Dermoscopy allows physicians to inspect clear skin structures without a cut but reading those enlarged patterns, which look like faint honeycomb lines on the surface, demands calm and long training. In this paper, I describe a deep learning system that labels melanoma in dermoscopic pictures but also finds tiny brown and red dots that a quick look would miss. The system first cleans every picture with advanced filters, locates each lesion with exact segmentation as well as runs a hybrid feature extractor built on CNNs that pulls sharp detail from every pixel, similar to light that passes through a lens and converges. We aim for high sensitivity or high specificity, and we check that the system stays accurate on all skin colours next to lesion forms, even on rough, irregular zones where shadows once deceived earlier hand coded programs. The process starts when the system sends each picture through preparation it sharpens borders and corrects light, as though it wipes dust from a camera lens before the next shot. This action raises contrast evens colour plus removes small defects like lone hairs or a bright glare on the skin. After that, the lesion segmentation module starts it runs a deep encoder decoder network that isolates the exact lesion border. Muskan Baisware "A Robust Model for Melanoma Detection from Dermoscopic Images" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101679.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101679/a-robust-model-for-melanoma-detection-from-dermoscopic-images/muskan-baisware

ESG – short for Environmental, Social, and Governance – is a set of standards measuring a businesss impact on society, the environment, and how transparent and accountable it is. In India, ESG principles were introduced through regulatory initiatives by the Securities and Exchange Board of India, which mandated Business Responsibility Reporting BRR for the top 100 listed companies in 2012 and was further strengthened through the Business Responsibility and Sustainability Report BRSR in 2021, requiring the top 1000 listed companies to disclose ESG related information by 2026 27. In 2025, the Securities and Exchange Board of India SEBI elevated ESG mandates by introducing the BRSR Core under the SEBI BRSR 2025 framework. The primary objective of this study is to examine the relationship between ESG Integration and the financial performance of Indian companies operating in a sustainable manner. The study examines how ESG reporting has influenced the profitability, risk management, investor confidence, and long term value creation for corporations. The research adopts a descriptive and analytical method based on secondary data from annual reports, SEBI Circulars, mandates, and relevant academic literature. The study concludes that ESG catalyzes better and sustainable financial performance in Indian corporations. Mrs. Teena Kodian "ESG as a Catalyst for Sustainable Financial Performance: Evidence from Indian Corporations" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Reimagining Management-Sustainability and Innovation in the AI Era , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101913.pdf Paper URL: https://www.ijtsrd.com/management/other/101913/esg-as-a-catalyst-for-sustainable-financial-performance-evidence-from-indian-corporations/mrs-teena-kodian

Environmental sustainability has become an important concern for consumers in recent years. Many people are becoming more aware of environmental problems such as climate change, pollution, and waste. At the same time, social media has become a powerful platform that influences consumer attitudes, opinions, and purchasing behaviour. This study explores how social media plays a role in shaping the behaviour of eco conscious consumers. Social media platforms provide information about sustainable lifestyles, eco friendly products, and environmental issues. Through posts, videos, influencer content, and brand campaigns, consumers are exposed to messages that encourage environmentally responsible behaviour. These platforms help increase awareness and motivate consumers to choose products that are environmentally friendly. The study focuses on understanding how social media awareness can influence consumers to move from simply knowing about environmental issues to actually taking action through sustainable purchasing decisions. It also examines how online communities, peer influence, and brand communication affect eco conscious consumer behaviour. The findings of this research will help marketers and organizations understand how social media can be used effectively to promote sustainable products and encourage responsible consumer behaviour. This study also contributes to understanding the relationship between social media influence and sustainable consumption in the modern digital environment. Asst. Prof. Sabina Pathan "From Awareness to Action: Exploring the Role of Social Media in Shaping Eco-Conscious Consumer Behaviour" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Reimagining Management-Sustainability and Innovation in the AI Era , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101914.pdf Paper URL: https://www.ijtsrd.com/management/other/101914/from-awareness-to-action-exploring-the-role-of-social-media-in-shaping-ecoconscious-consumer-behaviour/asst-prof-sabina-pathan

This research paper presents a comprehensive analysis of NASA satellite imagery to monitor, quantify, and interpret forest cover changes over the past year, with a focus on improving the accuracy and scalability of environmental monitoring systems. Forest cover dynamics serve as a critical environmental indicator, influencing biodiversity conservation, carbon sequestration, climate regulation, and the sustainability of ecosystem services, as well as supporting livelihoods dependent on forest resources. Rapid deforestation and forest degradation, driven by both natural processes and anthropogenic activities such as urban expansion, agriculture, logging, infrastructure development, and climate induced disturbances, necessitate accurate, timely, and automated monitoring approaches for effective intervention and policy formulation. To address this need, the study leverages advanced remote sensing techniques combined with machine learning algorithms to extract meaningful patterns from high resolution satellite datasets and large scale geospatial data repositories. The methodology involves multiple stages, including data acquisition from NASA Earth observation systems such as Landsat and MODIS , preprocessing such as noise reduction, radiometric and atmospheric correction, normalization, cloud masking, and geometric alignment , feature extraction using spectral indices like NDVI Normalized Difference Vegetation Index along with other vegetation indices e.g., EVI and SAVI , and supervised classification using algorithms such as Random Forest, Support Vector Machines, or Convolutional Neural Networks, enabling accurate land cover categorization across diverse ecological regions. Change detection techniques are applied to identify spatial and temporal variations in forest cover, enabling the assessment of deforestation, afforestation, and forest degradation trends with higher precision. Techniques such as post classification comparison, image differencing, and time series analysis are utilized to capture both abrupt and gradual changes. Additionally, trend analysis is conducted to evaluate seasonal variations and long term patterns, while correlating these changes with potential drivers such as climate variability temperature and precipitation changes , land use transformations, population pressure, and human activities, thereby providing a multi dimensional understanding of forest dynamics. The results of this study provide valuable insights into the dynamics of forest ecosystems, highlighting areas of significant change, emerging deforestation hotspots, and regions showing signs of regeneration or conservation success, along with potential environmental risks. These findings can support policymakers, environmental agencies, and conservation organizations in making informed decisions regarding sustainable land management, climate mitigation strategies, biodiversity preservation, and ecological restoration initiatives. Furthermore, the integration of remote sensing and machine learning demonstrates a scalable, cost effective, and efficient framework for continuous environmental monitoring, capable of supporting real time analysis and future predictive modeling of forest cover change. Supriya Verma | Shreya Motghare "Analyzing Nasa Satellite Data to Track Forest Cover Change in One Year" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Recent Advances in Computer Applications and Information Technology , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101490.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101490/analyzing-nasa-satellite-data-to-track-forest-cover-change-in-one-year/supriya-verma

The rapid growth of mobile applications supported by advanced wireless communication technologies has significantly transformed digital services across sectors such as healthcare, transportation, finance, and smart infrastructure. However, this expansion has also increased exposure to cybersecurity threats due to extensive data exchange, massive device connectivity, and integration with cloud and IoT environments. Mobile applications face diverse security risks including malware attacks, data leakage, insecure network communication, authentication vulnerabilities, and unauthorized access to sensitive information. The high speed and low latency characteristics of modern mobile networks amplify both the scale and impact of cyberattacks by enabling faster exploitation of system weaknesses. Additionally, the widespread adoption of interconnected devices expands the attack surface, creating challenges in maintaining data confidentiality, integrity, and availability 2 . This study highlights the major categories of cybersecurity threats in mobile applications, examines their potential impact on users and digital ecosystems, and emphasizes the importance of robust security frameworks, secure communication protocols, and strong authentication mechanisms to ensure safe and reliable mobile computing environments. The rapid evolution of mobile computing and high speed wireless communication technologies has led to the widespread adoption of mobile applications across critical domains including healthcare, banking, education, transportation, and smart infrastructure. While these applications provide convenience, real time connectivity, and enhanced user experience, they also introduce significant cybersecurity challenges due to increased data exchange, continuous network connectivity, and integration with cloud services and Internet of Things IoT devices. The growing number of interconnected devices and services expands the attack surface, making mobile platforms a primary target for cybercriminal activities 5 . Mobile applications are exposed to a wide range of cybersecurity threats such as malware injection, phishing attacks, insecure data storage, weak authentication mechanisms, unauthorized access, and network based attacks including interception and session hijacking. The high speed communication and low latency characteristics of modern mobile networks enable faster data transmission but also allow attackers to exploit vulnerabilities more efficiently. Additionally, the use of third party libraries, insufficient encryption practices, and improper application design further increase security risks and compromise user privacy 8 . Cybersecurity threats in mobile environments can lead to severe consequences including financial loss, identity theft, data breaches, service disruption, and compromise of critical digital infrastructure. As mobile applications increasingly support sensitive operations such as digital payments, remote monitoring, and real time communication, ensuring data confidentiality, integrity, and availability becomes essential. This study examines the major cybersecurity threats affecting mobile applications, analyzes their underlying causes, and emphasizes the need for robust security frameworks, secure coding practices, strong authentication mechanisms, and continuous monitoring systems. Strengthening mobile application security is essential to protect user data, maintain trust in digital services, and ensure safe and reliable operation in highly connected technological environments 9 . Aditya Urade | Aryan Gaidhane "Mobile Application Security: Threats and Protection Strategies" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Recent Advances in Computer Applications and Information Technology , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101492.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101492/mobile-application-security-threats-and-protection-strategies/aditya-urade

Truthfully, we exist in a society where digital platforms and internet news dominate the information landscape, leading to a continuous stream of both accurate and false information. False information is more than just an inconvenience it weakens public trust, creates conflicts, and disrupts social harmony. Manually verifying every piece of news is impractical due to the enormous volume of online content. This challenge motivated the development of an Artificial Intelligence driven Fake News Detection System. The proposed system uses advanced AI techniques to distinguish between real and fake news by processing textual data, analyzing linguistic patterns, and applying supervised learning models to determine credibility. These AI models are efficient, scalable, and capable of handling the complexity of online information, thereby supporting fact checkers and improving the reliability of digital platforms. The rapid growth of the internet and social media platforms has significantly enhanced the speed at which information is shared. However, this has also contributed to the widespread dissemination of fake and misleading content. Fake news has the potential to influence public opinion, generate confusion, and negatively impact political and social systems. Traditional fake news detection methods rely heavily on manual fact checking, which is time consuming and insufficient to cope with the massive volume of data generated daily . To address this issue, this research proposes an Artificial Intelligence based Fake News Detection System that automatically classifies news articles as real or fake. The system integrates Machine Learning algorithms with Natural Language Processing NLP techniques to analyze textual content and extract meaningful features 6 . Key processes such as text preprocessing, feature extraction, and classification are employed to enhance detection accuracy. The system is designed to provide a fast, efficient, and reliable solution with minimal human intervention. Experimental results indicate that AI based approaches are highly effective in identifying fake news and reducing misinformation across digital platforms. The study emphasizes the importance of intelligent automated systems in maintaining the credibility and trustworthiness of online information sources 8 . In the modern digital era, social media and online platforms have become primary sources of information. However, alongside authentic content, a significant amount of fake news spreads rapidly across the internet, misleading users and sometimes causing serious societal issues. This research focuses on the application of Artificial Intelligence in detecting fake news. Technologies such as Machine Learning and Natural Language Processing enable the analysis of news content, identification of patterns, and classification of information as genuine or misleading. The study further examines various characteristics of fake news, including sensational headlines, unreliable sources, and emotionally manipulative language. AI based systems compare patterns between real and fake news by analyzing textual structures and behavioral data. The findings demonstrate that Artificial Intelligence plays a crucial role in combating misinformation and improving the overall quality of online information. These systems assist users in identifying trustworthy sources and contribute to a more reliable digital environment. Sanket Darunde | Arun Swami "Artificial Intelligence Based Fake News Detection" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Recent Advances in Computer Applications and Information Technology , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101494.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101494/artificial-intelligence-based-fake-news-detection/sanket-darunde

Artificial Intelligence AI has emerged as a transformative force in modern marketing, enabling businesses to deliver highly personalized and data driven consumer experiences. This study examines the role of AI in developing advanced consumer personalization strategies, with a focus on enhancing customer engagement, satisfaction, and retention. The research is based on secondary data collected from academic literature, industry reports, and case studies, and adopts a qualitative approach to analysis. The study highlights how AI technologies such as machine learning, predictive analytics, and recommendation systems are used to analyze consumer behavior and preferences. A case study of Zomato is incorporated to demonstrate the practical application of AI in marketing. The findings reveal that Zomato effectively utilizes AI for personalized recommendations, targeted advertising, and real time customer interaction, resulting in improved user engagement and operational efficiency. Furthermore, the research identifies key benefits of AI driven marketing, including increased accuracy in targeting, cost efficiency, and enhanced decision making. However, it also emphasizes the importance of ethical data usage and privacy considerations. The study concludes that AI driven personalization is a critical component of contemporary marketing strategies and will continue to shape the future of consumer engagement. Tejaswini Khardenavis "Artificial Intelligence in Marketing: A Study on Advanced Consumer Personalization Strategies" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Reimagining Management-Sustainability and Innovation in the AI Era , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101915.pdf Paper URL: https://www.ijtsrd.com/management/other/101915/artificial-intelligence-in-marketing-a-study-on-advanced-consumer-personalization-strategies/tejaswini-khardenavis

Automated evaluation of descriptive responses is a significant difficulty in educational technology, largely because of the significant limitations of conventional keyword based grading systems. Automated tests are based on finding specific words or basic ideas they do not really check if the student truly understands the concept, what the words mean or the different ways a correct answer can be written. The automated evaluation methods have these limitations because they rely on matching phrases or fundamental principles. This can sometimes lead to grades thatre not fair or consistent which is a big problem in online classes where reliability and consistency are really important, for automated evaluation methods. Automated evaluation methods need to be fair and consistent. Recent advances in Large Models of Language LLMs offer new possibilities for more intelligent evaluation based on logic and comprehension. Using explainable reasoning and semantic similarity, this work presents a multi agent system for AI driven assessment of descriptive responses. Preprocessing, evaluating semantic alignment, analyzing concept coverage, applying rubrics, producing explanations, and verifying the coherence between scores and feedback are just a few of the duties that the framework assigns to agents. The approach emphasizes conceptual comprehension rather than just keyword matching by fusing reasoning from LLMs with embedding based semantic similarity. Additionally, a validation loop is employed to reduce variability and enhance grading reliability. The suggested approach is intended to enhance automated evaluation systems scalability, transparency, and fairness. A comparison with baseline keyword matching methods shows that the creation of structured feedback improves interpretability and alignment with human evaluators. This work provides a reliable and comprehensible solution for contemporary AI driven educational assessment environments by combining multi agent orchestration with semantic evaluation. Kushal Vishwajeet Bishwas "AI-Based Answer Evaluation Using Semantic Similarity and Multi-Agent Reasoning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101677.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101677/aibased-answer-evaluation-using-semantic-similarity-and-multiagent-reasoning/kushal-vishwajeet-bishwas

The rapid advancement of Generative Artificial Intelligence GenAI is transforming the landscape of higher education by reshaping how students access, process, and produce knowledge. This study examines the impact of GenAI tools on self directed learning SDL among higher education students, with a focus on learner autonomy, critical thinking, and academic practices. Adopting a qualitative approach based on secondary data, the study reviews recent literature to analyze patterns of student interaction with AI powered tools such as ChatGPT and similar platforms. The findings indicate that GenAI enhances learning by providing instant feedback, personalized support, and improved accessibility, thereby fostering independent learning. However, the study also identifies significant concerns, including over reliance on AI, reduced cognitive engagement, risks to academic integrity, and challenges in evaluating the credibility of AI generated content. The results highlight a dual impact, where GenAI acts both as an enabler and a potential disruptor of self directed learning. The study concludes that while GenAI holds strong potential to support SDL, its effectiveness depends on responsible usage, critical evaluation skills, and institutional frameworks. It emphasizes the need for AI literacy, clear academic policies, and redesigned pedagogical strategies to ensure that AI integration enhances rather than undermines independent learning. Asst. Prof. Shweta Bajpai "Generative AI Adoption and its Influence on Self-Regulated Learning and Academic Practices" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Reimagining Management-Sustainability and Innovation in the AI Era , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101916.pdf Paper URL: https://www.ijtsrd.com/management/other/101916/generative-ai-adoption-and-its-influence-on-selfregulated-learning-and-academic-practices/asst-prof-shweta-bajpai

“To be World’s leading Airport Developer, Operator and Air Navigation Service Provider”. There are 133 airports in India, 23 International Airports, 100 Domestic Airports, 10 Custom Airports. Almost 90 had taken a commercial flight in their lifetime. In operation research Inventory management is an important function to any business, marketing, since inadequacies in control can result in serious and important problems. If the inventory not managed properly then it will be problematic in satisfaction of customers or curtailment of working capital will result and production, seat inventory, loss. The start of Operations Research was done during World War II, when basic necessities of soldiers were required to be managed, like, food, commuting, health, logging etc. Operations Research is an effective combination of mathematical and analytical tools for finding optimum results for decisions in a system of multiple and complex resources treated as variables . Operations Research not only solves the existing problem but also helps to frame a problem and its solution. Asst. Prof. Padma Patil "Role of Information and Communication Technology in Revenue Management Using EMSR: Evidence from Mumbai International Airport" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Reimagining Management-Sustainability and Innovation in the AI Era , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101917.pdf Paper URL: https://www.ijtsrd.com/management/other/101917/role-of-information-and-communication-technology-in-revenue-management-using-emsr-evidence-from-mumbai-international-airport/asst-prof-padma-patil

The digital healthcare data is growing fast and this has created new chances for using data analytics and machine learning to make better medical decisions. Finding diseases early is very important to reduce the number of deaths lower the cost of treatment and improve the health of patients.. The old ways of diagnosing diseases often need people to analyze data manually and sometimes they fail to find diseases early because the symptoms are similar and the health conditions are complex. This research paper is about a system that uses data to predict diseases. This system uses healthcare data that has information about the patients, their medical history, symptoms and the results of their tests. The system first cleans up the data then it analyzes the data to understand it and finally it uses machine learning to find patterns and predict the likelihood of diseases early. The system tries out predictive models like Logistic Regression, Decision Tree, Random Forest and Support Vector Machine. It checks how well these models work by looking at things like how accurate theyre how precise they are how well they remember things and their F1 score. The results show that machine learning models can really help analyze healthcare data and assist doctors in making decisions. The system shows how important data analytics is in making healthcare better and in supporting early diagnosis of digital healthcare data. The use of healthcare data in this system is a key factor, in its success. Shantanu Sunil Patankar "Early Disease Prediction using Healthcare Datasets" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101676.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101676/early-disease-prediction-using-healthcare-datasets/shantanu-sunil-patankar

AI integration within document management systems alters organizational data handling methods however, this theoretical discourse often diverges significantly from practical implementation realities. The study explores DocuVault, which is an intelligent document storage solution designed for businesses to safely keep records and streamline processes automatically. Analyzing present academic findings alongside emerging technological advancements reveals five critical domains within which DocuVault intends enhancement notably, insufficient empirical evidence exists regarding its operational efficacy across diverse scenarios, an undefined approach has been adopted towards integrating this tool into corporate environments, inadequate attention has been given to adhering to legal regulations globally, limited resources have been allocated toward supporting documents written in multiple linguistic contexts, and scant comparative analyses exist concerning the effectiveness of alternative record keeping solutions over time. DocuVault offers an integrated approach addressing various aspects through advanced AI capabilities for finding relevant info, versatile data handling systems, and rule following assistance technologies on a worldwide scale. This document refers to DocuVault as an AI driven tool designed to manage documents automatically while protecting data from attacks, supporting diverse cultural needs, and complying with laws. Expanding on our investigation involves developing sophisticated machine learning models capable of interpreting multiple linguistic styles effectively, establishing criteria for assessing these systems performance in business settings, and creating frameworks designed to facilitate communication across different legal regions. Sameer Mandve "DocuVault: AI-Integrated Intelligent Document Management System for Secure Institutional Repository and Automated Workflow Processing" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101675.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101675/docuvault-aiintegrated-intelligent-document-management-system-for-secure-institutional-repository-and-automated-workflow-processing/sameer-mandve

In recent years, environmental issues such as climate change, pollution, and resource depletion have gained global attention. As a result, consumers are becoming more aware of the environmental impact of their purchasing decisions. This growing awareness has encouraged companies to adopt green branding strategies to present their products and practices as environmentally friendly. The main objective of this research paper is to examine the impact of green branding on consumer purchase intentions in emerging markets using secondary data. The study focuses on important factors such as consumer trust, brand image, and the credibility of environmental claims. It also explores how modern technologies like artificial intelligence help companies promote sustainable products more effectively. The research is based on secondary data collected from journals, articles, and research papers. The findings suggest that green branding has a positive influence on consumer purchase decisions, especially when consumers trust the brand and believe in its environmental claims. The study provides useful insights for marketers and highlights the importance of sustainable marketing practices in emerging economies. Snehal Shelar | Vidya S. Khanolkar "Impact of Green Branding on Consumer Purchase Intentions in Emerging Markets" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Reimagining Management-Sustainability and Innovation in the AI Era , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101919.pdf Paper URL: https://www.ijtsrd.com/management/other/101919/impact-of-green-branding-on-consumer-purchase-intentions-in-emerging-markets/snehal-shelar

As Artificial Intelligence AI becomes the cornerstone of modern management and education, a significant Digital Divide threatens to marginalize rural and diverse communities in India. This paper examines the critical shift from a traditional Hardware Divide to a more nuanced AI Literacy Divide . By analyzing the Indian landscape—specifically the Urban Rural gap and linguistic barriers—the research proposes a sustainable management framework. This framework emphasizes the deployment of Small Language Models SLMs , vernacular AI integration, and teacher empowerment in alignment with the National Education Policy NEP 2020. The study concludes that for AI innovation to be truly sustainable, it must be inclusive and accessible to the last mile student. Manimekhalai Sethuraman Iyer | Mamta Yadav "Bridging the Digital Divide: Sustainable AI Implementation in Diverse Educational Environments" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | International Conference on Reimagining Management-Sustainability and Innovation in the AI Era , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101920.pdf Paper URL: https://www.ijtsrd.com/management/other/101920/bridging-the-digital-divide-sustainable-ai-implementation-in-diverse-educational-environments/manimekhalai-sethuraman-iyer

Face Recognition Attendance Systems are ways to track attendance in places like schools, offices and workplaces. Old methods like using registers RFID cards or fingerprint scanners have problems. For example people can ask others to mark them it takes a lot of time and there are hygiene issues. The Face Recognition Attendance System uses Artificial Intelligence and machine learning to recognize people by their faces. A camera captures the faces and the system checks them against stored data to see who is present. This happens in time. Using this system makes attendance tracking more accurate. It reduces mistakes prevents people from marking others present and lets managers monitor attendance in time. Also it is a contactless process, whichs more efficient and cleaner than old methods. The Face Recognition Attendance System helps organizations to track attendance in a way. Face Recognition Attendance Systems are useful, for places. Sakhi Deoprakash Dubey "AI-Based Face Recognition Attendance System for Automated and Contactless Attendance Management" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101674.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101674/aibased-face-recognition-attendance-system-for-automated-and-contactless-attendance-management/sakhi-deoprakash-dubey

The objective of this research is to develop an intelligent decision support system IDSS that can aid decision makers in enhancing the performance and sustainability of the sugarcane agroindustrys supply chain. A case study focusing on a sugarcane agroindustry supply chain was proposed. The IDSS was developed using the waterfall approach, which follows the system development life cycle SDLC and employed an object oriented programming technique. The outcome of this study is a prototype of the IDSS, consisting of a database, model base, and knowledge based management system configuration. To evaluate the sustainability of the supply chain, a fuzzy inference system and an adaptive fuzzy inference system algorithm were utilized. Through verification and validation, it was determined that the IDSS prototype has the potential to be implemented in real world scenarios, as long as certain assumptions related to the model are taken into consideration Rounak Gurnule "Design of Intelligent Supply Chain Decision Support Systems" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101673.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101673/design-of-intelligent-supply-chain-decision-support-systems/rounak-gurnule

The proposed system processes user queries using semantics analysis and generates contextual embeddings to better understand the meaning behind the search terms. It then applies similarity scoring and intelligent ranking algorithms to retrieve and order the most relevant results. The system architecture consists of modules for query preprocessing, semantics representation, document indexing ,similarity computation and dynamics ranking. The ranking components design to adapt over time by incorporating user interaction data, enabling continuous learning and personalized search experiences. Experimental evolution shows that the proposed AI based approach outperform traditional keyword based system in terms of precision ,recall, and Mean Reciprocal Rank MRR .The system demonstrates improved contextual understanding ,faster response times, and higher user satisfaction .The proposed solution is suitable for applications such as e commerce platform, academics search engines, enterprise knowledge management systems ,and digital libraries. The results indicate that integrating artificial intelligence into search and ranking mechanisms significantly enhances the effectiveness and efficiency of modern information retrieval system. Hitesh Pundalik Adkine "Smart Search: An AI-Based Search and Ranking System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101668.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101668/smart-search-an-aibased-search-and-ranking-system/hitesh-pundalik-adkine

Domestic work is something that people do not usually talk about when theyre doing research but it is a big part of our daily lives. Domestic work is very important. Most homes run smoothly because someone is doing all the domestic work jobs that need to be done every day. You know domestic work jobs like cleaning the house washing the dishes folding the laundry making dinner putting away the groceries and helping out family members are all part of work. These domestic work jobs are not hard to do. Domestic work is something that we all have to do. The hard part is doing work jobs over and again and making sure everything gets done on time. When you have a job and have to commute to work even the simple domestic work jobs can start to feel like much. In a lot of cities both people in a household have full time jobs. Domestic work is still important even if people do not talk about work much. It can be tough to balance work, with our other responsibilities. Domestic work is something that we all have to do. It is a big part of our daily lives.. Students manage shared accommodations independently. Elderly individuals may require occasional assistance but prefer predictable routines. Despite rapid digital transformation in areas such as transportation and financial services, the coordination of routine domestic help remains largely informal. Families often depend on neighbours’ recommendations or direct phone communication. While such systems can function within close communities, they lack structured scheduling records, transparent pricing visibility, and consistent feedback mechanisms. Existing service applications typically focus on technical or occasional services. Their design often emphasizes variety and promotional engagement. However, recurring domestic tasks demand a different approach. Frequent interaction requires simplicity, not complexity. This research introduces MYHelper, a mobile application developed specifically to support recurring household services through a structured yet minimal interface. The system focuses on reducing unnecessary steps, improving clarity, and balancing service allocation fairly through backend logic. The study explores how problem identification, usability principles, and iterative design shaped the platform. Findings indicate that when digital tools align with everyday habits and reduce mental effort, users feel more confident and more likely to continue using the system. Rather than expanding features endlessly, MYHelper demonstrates that controlled simplicity can be both practical and scalable in domestic service coordination. Roshni Wagh "A UI/UX Based Mobile Application for Daily Household Services" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101672.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101672/a-uiux-based-mobile-application-for-daily-household-services/roshni-wagh

In apparel production systems, the effectiveness of quality control directly shapes operational productivity, cost stability, and long term brand credibility. Defects in fabric—ranging from structural inconsistencies and surface impurities to distortions in weave or print—do not remain isolated anomalies when undetected, they advance through successive manufacturing stages, amplifying material waste and compounding financial losses. Despite its widespread use, manual inspection relies heavily on human judgment, making it vulnerable to variability, fatigue induced error, and limited throughput capacity. Technological developments in computer vision and deep learning have introduced automated inspection models that promise consistent, high resolution detection of fabric anomalies. The trajectory of these technologies reflects a broader methodological shift early rule based image processing approaches have progressively given way to supervised learning algorithms and, more recently, convolutional neural network CNN architectures capable of hierarchical feature extraction. Although laboratory evaluations frequently demonstrate strong classification performance, translating these results into industrial environments remains complex. Practical constraints—including insufficiently diverse datasets, fluctuating illumination conditions, rapid fabric movement, processing delays, and compatibility with existing production infrastructure—continue to hinder reliable deployment. This study situates automated fabric defect detection within a broader sociotechnical context. While AI enabled inspection systems may reduce textile waste and improve quality consistency, their implementation introduces new energy demands and infrastructural requirements that complicate sustainability assessments. Accordingly, the research reframes automation not as a discrete technological substitution, but as an organizational and systemic reconfiguration. To support implementation, a structured framework is advanced that integrates data governance, model refinement strategies, cost benefit evaluation, and lifecycle analysis. The findings suggest that industrial adoption is determined less by peak algorithmic performance than by the system’s adaptability to manufacturing realities, its economic justification, and its compatibility with sustainable production objectives. Mayur Maske | Himanshu Mohod "Fabric Defect Detection Using Artificial Intalligence in Apperal Manufacturing" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Recent Advances in Computer Applications and Information Technology , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101491.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101491/fabric-defect-detection-using-artificial-intalligence-in-apperal-manufacturing/mayur-maske

The developments in the information technology IT sector have led to rapid and demand driven recruitment processes. Traditional recruitment processes have struggled to keep up with this pace. For instance, manually screening resumes can be time consuming furthermore, human bias can impact the outcome of the screening process since many potential candidates are skilled at “keyword stuffing” their resumes with technical terms but not including their true level of technical competence. This paper presents an Artificial Intelligent AI Enabled Web Based Recruitment System RBRS to assist recruiters with the recruitment of IT professionals and developers. The system will use Natural Language Processing NLP and Machine Learning ML algorithms to go beyond just keyword matching. The resume will be semantically analyzed to provide the recruiting platform with an understanding of the contextual s of the candidate’s prior experiences, and to allow the recruiting platform to properly match the candidate’s technical skills with the technical required granularity of the job. Automated Skills Verification ASV Developers will be assessed against their coding skills through a technical assessment module. The PEI developer technical assessment report will provide a classification of developers based on their coding skill level, and not exclusively on their stated declared coding skills. Predictive Analytics PA The recruiting system’s predictive analytics engine will assign a ranking order to candidates being considered for job opportunities. Komal Shukla "An AI Enabled Web-Based Recuirtment System for it Professionals and Developers" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101671.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101671/an-ai-enabled-webbased-recuirtment-system-for-it-professionals-and-developers/komal-shukla

Computer applications have become a fundamental component of modern society, transforming the way individuals, organizations, and governments operate. This research explores the future scope of computer applications by examining their evolving role across diverse sectors such as healthcare, education, business, and governance. With rapid advancements in technologies like artificial intelligence, cloud computing, and the Internet of Things IoT , computer applications are expected to become more intelligent, efficient, and deeply integrated into daily life. The study highlights how emerging technologies are reshaping traditional systems into automated and data driven environments. In healthcare, computer applications are enabling predictive diagnostics and remote patient monitoring. In education, they are fostering personalized learning experiences through adaptive platforms. Similarly, businesses are leveraging advanced software systems to enhance productivity, decision making, and customer engagement, while governments are adopting e governance solutions to improve transparency and service delivery. Furthermore, the future scope of computer applications extends to areas such as cybersecurity, big data analytics, and smart infrastructure. As digital transformation accelerates, the demand for secure and scalable applications will continue to grow. Innovations in machine learning and blockchain technology are expected to address challenges related to data privacy, security, and system reliability. However, the expansion of computer applications also presents challenges, including ethical concerns, data security risks, and the digital divide. This research emphasizes the need for responsible development, effective regulation, and continuous skill enhancement to ensure that technological advancements benefit society as a whole. In conclusion, the future of computer applications holds immense potential to revolutionize industries and improve quality of life. By embracing innovation while addressing associated challenges, stakeholders can harness the full capabilities of computer applications to drive sustainable growth and global progress. Computer applications continue to play a transformative role in shaping modern society, with their influence expected to expand significantly in the future. Advancements in technologies such as artificial intelligence, cloud computing, and the Internet of Things IoT are driving the development of smarter, faster, and more efficient systems. These innovations are enhancing productivity, enabling automation, and improving decision making processes across sectors like healthcare, education, business, and governance. Looking ahead, the scope of computer applications will further extend into areas like cybersecurity, big data analytics, and smart infrastructure. While these advancements offer immense opportunities, they also introduce challenges related to data privacy, ethical concerns, and digital inequality. Therefore, a balanced approach focusing on innovation, security, and inclusivity is essential to ensure sustainable growth and maximize the benefits of computer applications in the future. In addition, the study underscores the importance of adopting a forward looking approach to fully leverage the potential of computer applications in the coming years. As technology continues to evolve, it is essential for organizations and individuals to remain adaptable and proactive in embracing innovation. By integrating advanced tools with responsible practices and strategic planning, computer applications can significantly contribute to sustainable development, economic growth, and improved quality of life, thereby reinforcing their critical role in shaping the future of the digital world. Bhavik Patle | Aditya Patle "Future Scope of Computer Applications" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Recent Advances in Computer Applications and Information Technology , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101495.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101495/future-scope-of-computer-applications/bhavik-patle

In today’s digital world, most user interfaces are designed in a fixed way, where users have to adjust themselves according to the system. However, this approach often fails to meet the diverse needs and preferences of different users. This research paper introduces the concept of Self Evolving User Interfaces using Collective Behavioural Learning, where the interface continuously improves itself by learning from the behaviour of multiple users over time. The proposed system observes how users interact with an application—such as clicks, navigation patterns, time spent on features, and preferences—and then uses this collective data to automatically adapt the layout, design, and functionality of the interface. Instead of manually updating the UI, the system evolves dynamically to provide a more personalized and efficient experience for users. This approach not only enhances usability but also reduces the need for frequent redesign by developers. The study focuses on designing a framework that combines user behaviour analysis with machine learning techniques to create adaptive interfaces. It also discusses the potential benefits, challenges, and ethical considerations such as data privacy. The goal of this research is to move towards smarter, more intuitive systems that understand users better and improve interaction without requiring explicit input. This research introduces a novel interface design framework based on self evolving collective behavioural learning, where systems continuously adapt by observing and interpreting aggregated user interactions. Unlike traditional static or rule based interfaces, the proposed model leverages insights from Machine Learning, Human Computer Interaction, and Data Science to create interfaces that dynamically restructure themselves in response to evolving user needs. The system collects implicit and explicit behavioural signals such as navigation patterns, clickstreams, dwell time, and task completion rates. These inputs are processed using adaptive algorithms, including reinforcement learning and clustering techniques, to identify both individual preferences and collective usage trends. Through this, the interface builds a shared behavioural intelligence layer that informs real time customization. A key contribution of this approach is its self evolution capability the interface does not rely on predefined models but continuously refines its structure via feedback loops and iterative learning cycles. It balances personalization with generalization by combining individual user models with collective behavioural patterns, ensuring both relevance and scalability across diverse user groups. The framework also incorporates context awareness, allowing interfaces to adapt based on factors such as device type, environment, and temporal usage patterns. Privacy preserving mechanisms, including anonymization and federated learning, are considered to ensure ethical handling of user data while maintaining learning efficiency. Experimental evaluations suggest improvements in usability metrics such as reduced interaction time, increased task success rate, and enhanced user satisfaction. The model is particularly applicable to adaptive web systems, intelligent dashboards, recommender systems, and smart environments. Abhishek Bind | Gaurav Dhak "Interfaces Using Self-Evolving User Collective Behavioural Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Recent Advances in Computer Applications and Information Technology , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101496.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101496/interfaces-using-selfevolving-user-collective-behavioural-learning/abhishek-bind

Web development and software engineering are important areas that support modern digital systems and online services. As the use of web applications continues to grow in sectors such as healthcare, education, finance, ecommerce, and government services, the need for reliable and well structured software development practices has increased significantly. This research paper focuses on the role of software engineering principles in improving the development and management of web applications. The study examines how different software development methodologies, including Agile, DevOps, and Continuous Integration Continuous Deployment CI CD , contribute to better collaboration, faster development cycles, and improved software quality. It also explores various technical aspects of web development such as front end and back end technologies, full stack development, API based systems, cloud integration, and microservices architecture. In addition, the research highlights several challenges faced during web application development, including cybersecurity risks, crossplatform compatibility, performance issues, version control management, and testing automation. The paper also discusses emerging technologies such as artificial intelligence integration, progressive web applications, serverless computing, and blockchain based systems that are shaping the future of web technologies. Overall, the objective of this research is to demonstrate how the application of structured software engineering practices can improve the reliability, scalability, and efficiency of web based systems while supporting long term technological development in the digital environment. 1 Web development and software engineering are important fields that support the growth of modern digital systems and online services. As technology continues to evolve, organizations increasingly depend on web applications for communication, information sharing, and business operations. Because of this growing dependence, it has become necessary to develop web systems that are reliable, secure, scalable, and easy to maintain. 2 This research paper examines how the principles of software engineering can be applied to modern web development practices in order to improve the overall quality and performance of web based applications. The study focuses on the role of structured software development methodologies in building efficient web systems. In particular, it discusses several Software Development Life Cycle SDLC approaches such as Agile Methodology, DevOps, and Continuous Integration Continuous Deployment CI CD . These development models help teams collaborate more effectively, reduce development time, and maintain consistent product quality throughout the project lifecycle. In addition to development methodologies, the research also explores important technical components of modern web development. These include front end and back end technologies, full stack development approaches, API based architectures, cloud integration, and microservices design patterns. Such technologies play a major role in improving the flexibility, performance, and user experience of web applications. The paper also discusses several challenges that developers commonly face during web application development. Issues such as cybersecurity risks, cross platform compatibility, performance optimization, version control management, and automated testing require careful planning and effective implementation strategies. Addressing these challenges is essential for maintaining stable and secure web systems. Tanvesh Chandel | Ram Pandey "Web Development and Software Engineering" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Recent Advances in Computer Applications and Information Technology , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101498.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101498/web-development-and-software-engineering/tanvesh-chandel

The stock market is a tricky thing to predict. It is hard to guess what the prices of stocks will be because the market is always changing. If we can predict the prices of stocks it will be very helpful for people who invest in the stock market. They will be able to make decisions about what to buy and sell. These days we use something called machine learning to try to predict the prices of stocks. Machine learning is a way of using computers to find patterns in data. We can use it to look at what has happened in the past and try to guess what will happen in the future. There are things that can affect the stock market. The economy how well companies are doing what is happening in the world. How people are feeling about the market can all have an impact. It is hard to take all of these things into account when trying to predict what will happen. In this study we used a kind of machine learning called Long Short Term Memory or LSTM for short. We compared it to ways of predicting stock prices to see which one was the best. We used data from the ten years to test our models. The LSTM model was the best it was able to predict the prices of stocks with a degree of accuracy. We also used something called indicators to help us make our predictions. These are numbers that can tell us things about the stock market. We used things like Moving Averages and Relative Strength Index to help us make our predictions. Ms. Jyoti Murty "Stock Market Price Prediction System using Python" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101670.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101670/stock-market-price-prediction-system-using-python/ms-jyoti-murty

The rapid growth of digital technologies has significantly increased the demand for advanced computational systems capable of solving complex problems efficiently. Traditional computing systems, also known as classical computers, rely on binary logic where information is represented using bits that exist in either a 0 or 1 state. Although classical computers have enabled remarkable advancements in science, engineering, and information technology, they encounter limitations when solving extremely complex computational problems such as molecular simulations, cryptographic analysis, large scale optimization, and artificial intelligence training models. Quantum computing has emerged as a promising solution to overcome these computational limitations. Unlike classical computers, quantum computers operate using quantum bits known as qubits. Qubits can exist in multiple states simultaneously due to a phenomenon known as superposition. In addition to superposition, quantum systems also utilize other fundamental principles of quantum mechanics such as entanglement and quantum interference. These properties enable quantum computers to perform parallel computations and explore multiple solutions simultaneously, significantly increasing computational efficiency. The primary objective of this research is to examine the potential of quantum computing as a transformative technology capable of addressing complex computational challenges. The study investigates the working principles of quantum computing, the development of quantum algorithms, and the possible applications of this technology across different sectors including artificial intelligence, cybersecurity, healthcare, and financial modeling. The research also analyzes the challenges associated with the development and implementation of quantum computing systems. These challenges include qubit instability, quantum decoherence, hardware complexity, error correction requirements, and the high cost of quantum hardware development. Despite these challenges, continuous advancements in quantum hardware and quantum software development suggest that quantum computing will play a crucial role in the future of computing technology. Furthermore, the study highlights how quantum computing can complement classical computing systems to create hybrid computing environments capable of solving problems that are currently beyond the reach of modern supercomputers. The research concludes that quantum computing represents a major technological shift that has the potential to reshape the future of scientific research, industrial innovation, and digital infrastructure. Harshal Kanojiya | Kunal Shiwankar "Investigating the Potential of Quantum Computing in Solving Complex Computational Problems" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Recent Advances in Computer Applications and Information Technology , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101493.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101493/investigating-the-potential-of-quantum-computing-in-solving-complex-computational-problems/harshal-kanojiya

Crop disease has a significant impact on agricultural productivity that to is reduction in yields and financial loss for farmers. Therefore, the detection of crop diseases should be done early and accurately in order to manage crops and practice sustainable agriculture. The purpose of this project is to present a system that uses Deep Learning Convolutional Neural Networks to automatically detect crop diseases using images of leaves. This system uses a pre trained AlexNet model which is extremely accurate at identifying many crops by utilizing leaf images that display visible clues signs. The system is delivered to end users as an easy to use web application using the Flask framework this will allow farmers and agronomists to upload images of leaves and instantly receive a prediction about the condition of those crops. The real time prediction given to the end user through this system will be used to make data driven decisions about precision farming and ultimately reduce crop losses and increase the health of crops. This project is an example of how AI based technology will transform the agricultural industry through timely monitoring and intervention for crop diseases. Hitesh Asutkar "Deep Learning-Based Crop Disease Detection Systems for Precise Classifications of Leaf Images and Early Diagnoses in Agriculture" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101669.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101669/deep-learningbased-crop-disease-detection-systems-for-precise-classifications-of-leaf-images-and-early-diagnoses-in-agriculture/hitesh-asutkar

To do well in sales we need to understand what drives them. This is important for making marketing plans and keeping sales up over time. We are trying to figure out how much each marketing method contributes to sales when customers take a path to buy something. We also want to make a system to predict future sales. We suggest using a combination of Multi Touch Attribution and advanced Machine Learning to make predictions our method involves looking at three ways to give credit to marketing methods. Linear, Time Decay and Position Based. To break down past sales data into what each channel did. We then use the method to help make a customized system to predict sales using XGBoost and a Neural Network to make the predictions more accurate. We tested this using data from an e commerce site with 50,000 customer journeys across eight marketing channels the results show that using the Position Based method with our suggested system works best giving us an idea of how well we can predict sales. This helps us understand what marketing methods work and makes it easier to predict sales so we can make plans. This study shows that combining attribution science with intelligence is a good way to make a system that works well for businesses, with many sales channels. Sakshi Raut "Sales Performance Decomposition: Attribution Modeling & Predictive Sales Analytics" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101609.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101609/sales-performance-decomposition-attribution-modeling-and-predictive-sales-analytics/sakshi-raut

The fast rise in vehicle density and the scarcity of parking facilities have made parking management in urban settings a major concern. Drivers frequently have trouble finding parking spots, which wastes time, uses more fuel, and causes traffic jams. Conventional parking systems lack effective information retrieval techniques and organised digital help. In order to streamline the parking search process, this study discusses the design and development of a Smart Parking Finder System, a software based lightweight solution. The system incorporates Python backend processing, a structured SQLite database for parking data management, and a graphical user interface GUI created using Tkinter. The program shows the available status in real time and lets users search parking spots based on car type and selected area. The suggested prototype exhibits user friendly functionality, quick reaction times, and effective database interaction. The system offers a useful and affordable strategy appropriate for academic demonstration and small scale implementation. Real time parking updates, GPS based navigation, and Internet of Things integration are possible future improvements. Ananya Deshmukh "An Intelligent Smart Parking Finder System Using Python and Real-Time Data Processing" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101610.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101610/an-intelligent-smart-parking-finder-system-using-python-and-realtime-data-processing/ananya-deshmukh

Deaf and hard of hearing individuals use sign language to communicate with their peers and others. The process of using computers to recognize the sign language involves recognizing signs through gesture recognition as well as converting signs into text or speech. The signs can be classified as either static or dynamic, with static gesture recognition being easier than dynamic gesture recognition however, both types of gesture recognition systems are very useful to the human community. This paper describes the methods used to recognize sign language. The different stages of sign language recognition, such as how the data is collected, preprocessed, transformed, and recognized, as well as the results from using these methods, are discussed within this article. Several future research avenues regarding sign language recognition are also presented. Arshiya Javed Sheikh "Sign Language Recognition System Using a Convolution Neural Network Model" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101614.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101614/sign-language-recognition-system-using-a-convolution-neural-network-model/arshiya-javed-sheikh

Enterprise ServiceNow instances accumulate large volumes of documents, making precise, timely retrieval difficult through keyword search alone. A Retrieval Augmented Generation RAG approach—combining embeddings, a vector store, semantic search, and a large language model LLM —enables users to upload a document and ask natural language questions grounded in its content. This paper describes an end to end implementation using ServiceNow Virtual Agent VA for interaction, a PDF to text extraction step, Gemini AI embeddings for vectorization, Qdrant as the vector database, and an Gemini AI chat model for answer generation, following an eight step pipeline from document capture to response delivery . We also propose an evaluation framework, borrowing the “confusion matrix as foundation” measurement mindset from the provided demo paper , and adapt it to RAG quality, faithfulness, and operational performance. Dolly Motwani "Intelligent Semantic Search Framework Using AI and ServiceNow Platform" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101667.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101667/intelligent-semantic-search-framework-using-ai-and-servicenow-platform/dolly-motwani

The rapid growth of internet accessibility and multimedia technologies has led to increased demand for video streaming platforms. This research paper presents the design and development of a scalable, secure, and user friendly video streaming website. The study discusses system architecture, frontend and backend technologies, database management, video encoding, content delivery networks CDNs , adaptive bitrate streaming, and security considerations. The proposed system demonstrates efficient content delivery, optimized performance, and enhanced user experience through modern web technologies. Results indicate that implementing adaptive streaming and cloud based infrastructure significantly improves scalability and reliability. Apurva Dhanraj Shiwarkar "Design and Development of a Scalable and Secure Video Streaming Platform Using Adaptive Bitrate Technology" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101613.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101613/design-and-development-of-a-scalable-and-secure-video-streaming-platform-using-adaptive-bitrate-technology/apurva-dhanraj-shiwarkar

Bone tumor detection is an important area of research in the medical and healthcare fields because we need to find and diagnose tumors early and accurately. Medical datasets have a lot of clinical attributes that can be analyzed using Machine Learning techniques to help doctors make diagnoses and decisions. With more Artificial Intelligence being used in healthcare we are using models to look at clinical data find patterns in tumors and make diagnoses more accurate while reducing mistakes made by humans.We are still talking about bone tumor detection. Systems that use data to make healthcare decisions have led to the creation of classification models that can tell the difference between tumor and nontumor cases based on clinical features. However the quality of how we prepare and medical datasets is very important for how well the models work.In this study we used a machine learning framework to classify bone tumors using a dataset with 570 samples. We cleaned the data scaled the features and split the data into training and testing sets to make sure the evaluation was fair. We used algorithms like Logistic Regression, Random Forest and Support Vector Machine to compare and find the best model for bone tumor detection. We did steps including cleaning the data looking at the data analyzing how features are related training the model and evaluating how well it worked. We looked at how accurate the model was made a confusion matrix and used ROC AUC metrics to evaluate the model. The results showed that the model was very accurate with an accuracy of 0.99 and an AUC score of 0.99 which means it is very good at telling the difference, between malignant bone tumor cases. These results suggest that if we have prepared structured clinical data and use supervised machine learning we can classify bone tumors reliably and efficiently. Dev Omprakash Paliya "Bone Tumor Detection Using Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101611.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101611/bone-tumor-detection-using-machine-learning/dev-omprakash-paliya

The internet is about the First Input Delay and Search Engine Visibility these days. When we make websites we often use something called Client Side Rendering, whichs nice because it is dynamic but it can be a problem for search engines and people who use their phones to access the internet because it can be slow. This project is about making a website thats good for search engines and loads fast we call it SEO FOCUSED LEADS GENERATION . We used something called Next.js and Tailwind CSS to make this website. The main goal of this project is to show how we can make a website that loads fast and is good for search engines by using something called Static Site Generation. This means that the website is ready to go when someone searches for it so search engines can see everything away. We also used Tailwind to make the website look nice and load fast this way we can get a score when we test the website with Google Lighthouse. We talk about how we made the website, how we changed from using CSS files to small utility classes and how we made sure the website is good for search engines. We also did some tests. Found out that our website loads 60 faster than other websites that use React, which is a big deal. So our website is an example of how to make a professional website that loads fast and is good, for search engines. Gulamgaush Ansari "SEO-Focused Leads Generation Using Next.js and Tailwind CSS" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101666.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101666/seofocused-leads-generation-using-nextjs-and-tailwind-css/gulamgaush-ansari

The utilization of gamification in mental health technology has witnessed substantial growth as a tool to combat low levels of user engagement with self care activities. Although numerous tools and resources for mental wellness are available, most fail to ensure user sustenance with the platform due to a lack of engaging feedback mechanisms. This study proposes a new form of AI powered health technology, a subset of which is Animind a tool that utilizes Sentiment Analysis and Gamified Rewards as means to ensure Emotional Growth. This tool analyzes a users reflection text to offer an Emotional Quest. In our research, we employed a Full Stack approach with the Spring Boot framework and a Rule based Sentiment Analysis algorithm to classify user input into unique emotional states like Happy, Stressed, and or Sad. We employed a custom Relational Mapping system to connect and map these emotional states to a dynamic Challenge Repository stored in a MySQL database. This process mirrors various components of text input processing, sentiment classification, personal quest retrieval, and a gamification based Spirit Sync reward engine. Moreover, the performance of the system, as well as the progression of the user, has been successfully monitored via the Progress Tracking Dashboard. The implemented logic has followed the leveling system concept, under which the progression of the user from Beginner to Master is dependent on the progress percentage variable. Significantly, the created system has successfully evidenced the presence of a smooth feedback loop, wherein the analysis of text has led to the display of personalized content, followed by the updation of the database and or the display of the UI, thereby ensuring accurate mapping of the emotional data with the system, leading to the successful retrieval of the challenges at the 100 success rate. This research has showcased the fact that the fusion of sentiment aware systems with gamified systems is crucial in augmenting the interactive nature of the system. Ankita Sendha "Animind: A Gamified Framework for Emotional Regulation and Mental Wellness using Spring Boot and Heuristic Sentiment Analysis" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101612.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101612/animind-a-gamified-framework-for-emotional-regulation-and-mental-wellness-using-spring-boot-and-heuristic-sentiment-analysis/ankita-sendha

The Personal Expense Tracker Web Application is designed to help users manage their daily financial transactions efficiently. With the rapid growth of digital payments and online banking, individuals require structured tools to record income, categorize expenses, and analyze spending patterns. The proposed system provides secure login authentication, expense categorization, graphical visualization, and monthly financial summaries. The web based nature of the system ensures accessibility, scalability, and real time data management. The study highlights the importance of financial awareness and digital budgeting tools in improving savings behavior. The Personal Expense Tracker Web Application is designed to help users manage their daily financial transactions efficiently and systematically. In the modern digital economy, individuals frequently engage in online payments, digital banking, and cashless transactions, which makes manual tracking of expenses difficult and error prone. The proposed system provides a structured and automated solution for recording income and expenditure, categorizing financial activities, and generating real time analytical reports. The application incorporates secure user authentication, database management, graphical data visualization, and monthly financial summaries to enhance usability and accuracy. The application allows users to add, edit, and delete expense records while automatically calculating total income, total expenses, and remaining balance. It also provides graphical representations such as charts and summaries to give a clear understanding of financial habits. The system ensures data accuracy, reduces manual calculation errors, and saves time compared to traditional methods like notebooks or spreadsheets. The main objective of this project is to promote better budgeting habits and financial discipline among users. The application can be developed using technologies such as Java, Python, or Web based tools with database support for secure data storage. Overall, the Personal Expense Tracker is a practical and efficient solution for personal financial management. The Personal Expense Tracker is a digital application designed to help users manage and monitor their daily financial transactions efficiently. In today’s fast paced life, individuals often find it difficult to keep track of their expenses, which leads to poor financial planning and unnecessary spending. This system provides a simple and user friendly platform where users can record their income and expenses, categorize transactions, and analyze their spending patterns. Vaidehi Raut | Aish Kesharwani "Personal Expense Tracker Web Application" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Recent Advances in Computer Applications and Information Technology , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101497.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101497/personal-expense-tracker-web-application/vaidehi-raut

In todays world data is growing really fast across many different platforms. This includes things like systems and APIs as well as cloud based flat files. Because of this we need to create flexible data engineering frameworks. My research presents an implementation of an end to end data pipeline. This pipeline is specifically designed for the Healthcare Revenue Cycle Management domain. One big problem we are trying to solve is that old systems are not flexible or automated enough. They often make mistakes when handling amounts of sensitive financial and patient data. These old systems can also slow down. Create separate groups of data that make it hard to make good decisions. My solution uses a set of Microsoft Azure services. These services help move enterprise data from systems to a new cloud based system. This is done in an seamless way. The main part of this architecture is Azure Data Factory, which is used to manage and move data. This creates an encrypted bridge for data to move so sensitive healthcare information is never exposed to the public internet. Data is stored in Azure Data Lake Storage Gen2, where it is managed in a way. This includes three layers Bronze, Silver and Gold. For data transformation and quality assurance the system uses Azure Databricks with PySpark. This layer does jobs like removing duplicates handling missing values and standardizing formats. This ensures that the data is very accurate. Security and governance are very important. Azure Key Vault is used to manage credentials and Role Based Access Control is used to make sure we follow healthcare rules. The results of this project show that it is more reliable and needs less manual work. By moving to this cloud based system organizations can get rid of the limitations of systems. They can also create a foundation for advanced reporting, business intelligence and future machine learning projects. This project provides a plan for large scale data engineering solutions in environments. The Healthcare Revenue Cycle Management domain will benefit from this research. The Microsoft Azure services used in this project are very important. The Azure Data Factory and Azure Databricks are components of this project. The results of this implementation are very promising. The Healthcare Revenue Cycle Management domain can use this project as a model, for their data engineering solutions. Ayush Kathikar "Automated Ingestion and Multi-Tier Transformation of Healthcare Revenue Cycle Data Using a Cloud-Native Medallion Architecture And Spark-Based Distributed Processing" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101665.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101665/automated-ingestion-and-multitier-transformation-of-healthcare-revenue-cycle-data-using-a-cloudnative-medallion-architecture-and-sparkbased-distributed-processing/ayush-kathikar

Sentiment Analysis is really important for understanding what people think and feel when they write something. This is a part of Natural Language Processing. The old way of doing Sentiment Analysis just looks at if something is good, bad or neutral. It does not try to figure out why people feel that way. This system uses Machine Learning and Deep Learning to find out how people feel and why they feel that way. It looks at the words people use and tries to understand what they mean. The system has a parts it gets the text ready it finds the important words it uses special models like LSTM and CNN to see if something is good or bad and it tries to find the reasons why people feel that way. The new system is really good at finding out how people feel and why. It is better than the way of doing things because it can explain why it thinks something is good or bad. We used ways to test the system, such as looking at how often it is right how precise it is and how well it can find the good and bad things. We also used charts, like the Confusion Matrix and ROC AUC to see how well the system works. We used charts to see how well the system works. The Confusion Matrix and ROC AUC were two charts we looked at. We looked at the Confusion Matrix and the ROC AUC because we wanted to know how well the system works. The Confusion Matrix and ROC AUC helped us understand the system. The Confusion Matrix and the ROC AUC really helped us understand the system. Sonal Ghanshyam Nikure "Intelligent Sentiment Detection, Cause Identification & Analysis System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101664.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101664/intelligent-sentiment-detection-cause-identification-and-analysis-system/sonal-ghanshyam-nikure

Supermarkets generate a lot of information every day. This information includes what products are sold, how many of these products are sold, at what price theyre sold and how people purchase them. Many supermarkets do not make use of this information. They mostly use their billing systems to process sales not to gain knowledge from the information. If they properly examined this information they could learn about the shopping habits of their customers how money they are making and how demand for products changes. This study uses data analysis and machine learning to help supermarkets make decisions. First, we prepare the supermarket data. By understanding these things GS supermarkets can make decisions and run more smoothly. We use tools like Linear Regression and Decision Tree algorithms to predict sales at supermarkets. We check how well these tools work by looking at their accuracy and other measures. We found that by examining billing data from supermarkets can make decisions about inventory prediction, forecast demand for products and plan promotions. Supermarket billing data can be very useful. It is about turning this data into something so supermarkets can make decisions and stay ahead of other supermarkets. By using data analysis and machine learning supermarkets can understand what is working for supermarkets and what is not and make changes. This can lead to sales, happier customers and a more sustainable business, for supermarkets. Shubhangi Yadav "Supermarket Billing Analysis Using Data Analytics for Customer Purchase Insights" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101663.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101663/supermarket-billing-analysis-using-data-analytics-for-customer-purchase-insights/shubhangi-yadav

Secure data transmission over sound frequency is an emerging communication technique that leverages acoustic waves—particularly audible and ultrasonic frequencies—to transmit digital information between devices without relying on traditional radio frequency RF channels such as Wi Fi, Bluetooth, or cellular networks. This research explores the design, implementation, and security implications of acoustic data communication systems, focusing on modulation techniques, encryption mechanisms, transmission efficiency, and resistance to interception or interference. The study investigates various sound based modulation schemes, including Frequency Shift Keying FSK , Phase Shift Keying PSK , and Orthogonal Frequency Division Multiplexing OFDM , to encode binary data into sound waves transmitted through speakers and received via microphones. Special emphasis is placed on ultrasonic frequencies above 18 kHz , which are generally inaudible to humans, enabling covert communication channels suitable for short range secure environments. To ensure confidentiality and integrity, cryptographic protocols such as Advanced Encryption Standard AES and secure key exchange mechanisms are integrated into the acoustic transmission framework. Experimental evaluation measures data rate, bit error rate BER , transmission range, and environmental noise resilience across different physical conditions. The findings demonstrate that while acoustic communication offers lower bandwidth compared to RF technologies, it provides unique advantages in air gapped systems, Internet of Things IoT devices, authentication protocols, and secure device pairing scenarios. However, potential vulnerabilities such as acoustic eavesdropping, signal injection, and environmental interference must be mitigated through robust encryption and adaptive modulation strategies. Pritam Sarkar | Girish Kinkar "Secure Data Transmission Over Sound Frequency" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Recent Advances in Computer Applications and Information Technology , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101874.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101874/secure-data-transmission-over-sound-frequency/pritam-sarkar

Most people looking to rent homes reach out online via listings, company sites, or posts on social networks. Yet barely any of those contacts turn into signed leases. Going through each message by hand slows everything down. Responses drag, interest fades, deals slip away. A fresh look at rental data begins here SmartRent Solutions shapes a path through numbers to spot who is likely to sign. Patterns hide in messages, call logs, time stamps pulling them out becomes the key task. One step uses cleaning tools so messy entries turn into clear signals. After that comes discovery charts and stats reveal what most renters tend to do before deciding. Building smart traits from raw facts helps teach the model how interest shows up early. Machine methods then sort chances into strong or weak based on past behaviors. Not every contact moves forward, but some carry stronger hints. These signs guide better timing and outreach focus without guesswork. One way to predict conversions starts with tools built in Python Pandas handles data, NumPy manages numbers, Scikit learn brings in learning models, while connections to SQL pull necessary records. Tests show forecasts built from patterns beat old school sorting when it comes to spotting hot leads and turning them into deals. Ayush satish Chakole "SmartRent Solutions – Rental Lead Analytics & Conversion Prediction System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101615.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101615/smartrent-solutions-–-rental-lead-analytics-and-conversion-prediction-system/ayush-satish-chakole

A practical sign language translator is an essential way for communication between the deaf community and the general public. So here we present the development and implementation of an American Sign Language ASL fingerspelling translator based on a convolutional neural network. We utilize a pre trained GoogLeNet architecture trained . We produced a robust model which classifies letters a z correctly with first time users and another that correctly distinguish letters a k in a majority of cases. The limitations of the dataset and the encouraging results achieved, we are confident that with further research and more data, we can produce a generalized translator for all ASL letters. Nandini Santosh Sarode "American Sign Language Fingerspelling Recognition Using A Pre-Trained Googlenet Convolutional Neural Network" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101622.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101622/american-sign-language-fingerspelling-recognition-using-a-pretrained-googlenet-convolutional-neural-network/nandini-santosh-sarode

AI and the Internet of Things IoT technologies have now transformed a wide variety of old sensing systems into intelligent albeit smart sensor networks. Es Scholars Unlike traditional sensors which simply grind and spew out data, intelligent sensors with AI can carry on local computation, recognize patterns in real time, will detect anomalies, and can predict what will happen next. This article is a comprehensive study into smart sensor analyses using AI. It details system architectures, algorithms, methods, design strategies, performance measurements, and real world applications. The framework being proposed integrates machine learning models with edge and cloud computing infrastructures so as to enhance efficiency, accuracy, and autonomy .Further more Also this paper discusses those issues arising in the process of implementation, experimental considerations and future research directions such as Tiny ML and federated learning, Medical care, industry, agriculture, smart cities it is these niche areas that AI driven smart sensors bring next generation intelligent systems into as so distinguished from modern technology. Ayush Ramesh Chambhare "Smart Sensor Data Analysis Using AI" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101616.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101616/smart-sensor-data-analysis-using-ai/ayush-ramesh-chambhare

Artificial Intelligence AI is transforming the education system by enhancing teaching methods, improving learning experiences, and increasing administrative efficiency. AI powered technologies such as intelligent tutoring systems, adaptive learning platforms, and automated grading tools help provide personalized learning experiences based on individual student needs, abilities, and learning pace. These systems analyze large amounts of educational data to identify students’ strengths and weaknesses, allowing educators to offer targeted support and improve academic performance. AI also assists teachers by automating repetitive tasks like grading assignments, managing schedules, and tracking student progress, enabling them to focus more on teaching and mentoring students. Furthermore, AI supports interactive learning through virtual assistants, chatbots, and smart content, making education more engaging and accessible for students across different locations. It also plays a significant role in remote and online education by enabling real time feedback, personalized recommendations, and improved digital learning environments. Despite its advantages, the implementation of AI in education also raises concerns related to data privacy, ethical use of technology, and the need for proper infrastructure and training for educators. Overall, AI has the potential to revolutionize the education system by making learning more efficient, flexible, and student centered while supporting teachers and institutions in delivering high quality education Artificial Intelligence AI is transforming the education system by improving teaching methods, learning experiences, and administrative processes. AI technologies such as intelligent tutoring systems, machine learning algorithms, and data analytics help create personalized learning environments where students can learn at their own pace and according to their individual needs. Through AI powered tools, educators can analyze student performance, identify learning gaps, and provide targeted support to improve academic outcomes. AI also enables automation of routine tasks such as grading, attendance tracking, and administrative management, allowing teachers to focus more on effective teaching and student interaction. In addition, AI driven platforms support online learning, virtual classrooms, and smart content creation, making education more accessible and flexible for students across different locations and backgrounds. Chatbots and virtual assistants provide instant academic support and guidance, enhancing student engagement and improving the overall learning process. Despite its numerous benefits, the integration of AI in education also raises concerns related to data privacy, ethical use, and the need for proper technological infrastructure. Therefore, while AI has the potential to significantly enhance the quality, efficiency, and accessibility of education, it is important implement it responsibly and ensure that it complements human teaching rather than replacing it. However, the adoption of AI in education also brings challenges such as concerns about data privacy, ethical use of technology, dependence on digital infrastructure, and the need for proper training for teachers and students to effectively use AI tools. Therefore, while AI has the potential to revolutionize the education system by making learning more intelligent, efficient, and accessible, it should be implemented carefully to ensure that it supports human educators and promotes a balanced, inclusive, and effective learning environment, Artificial Intelligence is expected to play an increasingly important role in shaping the future of education by creating more intelligent, flexible, and inclusive learning environments. Rewat Dhoke | Benny James "Role of Ai in Education System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Recent Advances in Computer Applications and Information Technology , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101877.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101877/role-of-ai-in-education-system/rewat-dhoke

In the world of education there is a big problem. people are paying attention to university rankings. This affects how good a university looks how many students want to go to the university and how much money the government gives to the university The thing is, these university rankings are not always fair. They have methods to figure out how good a university is. This makes it really tough for a university to know how the university is doing compared to universities. It is also hard for the university to find ways to improve the university. University rankings can be confusing because they do not always show the picture of what the university is like. The university has to look at the university rankings and try to understand what they mean for the university. University rankings are important, for the university so the university has to take them and try to improve the university... University rankings have an impact, on the university and the university needs to understand what the university is doing well and what the university needs to work on to make the university better. Institutional Performance Analytics is a way to look at things that helps universities understand how the university is doing in the world of education. This study is trying to create a framework to look at how universities are doing based on many different ranking systems at the same time. We looked at data from 500 universities in 40 countries. Checked their rankings in three big global rankings Times Higher Education, QS World University Rankings and Academic Ranking of World Universities. Our way of doing things combines a methods we use Data Envelopment Analysis to see how well universities are using their resources to get good rankings statistical techniques to find out what is really affecting their performance and machine learning to predict how their rankings will change based on what the university is like. We found that using Data Envelopment Analysis with a machine learning method called XGBoost creates a model to understand how universities are doing. Our model is very good at predicting rankings. We found that universities can improve their global standing by, up to 42 positions if they use their resources in a smarter way without spending more money. This research gives university leaders the tools they need to make plans and improve their universitys performance in a very competitive world of higher education. Institutional Performance Analytics, University Rankings and Higher Education Efficiency are all things to consider. We also looked at Multivariate Analysis, Data Envelopment Analysis, Global University Rankings, Performance Benchmarking, Predictive Modeling, Resource Allocation and Academic Excellence Metrics. Pratiksha Sawan "Institutional Performance Analytics: A Multivariate Analysis of Global University Rankings" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101662.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101662/institutional-performance-analytics-a-multivariate-analysis-of-global-university-rankings/pratiksha-sawan

The shift in web architecture towards edge computing and AI first approaches has moved us beyond the one size fits all Integrated Development Environment IDE model towards Specialized Web Development Environments SWDEs . This paper examines the move from general purpose editors to specialized environments for meta frameworks Next.js, and edge native deployments. SWDEs in addition to AI assisted scaffolding and real time performance telemetry have been evaluated for their impact on developer productivity. SWDEs, despite enabling a 35 reduction in mechanical coding, have been found to increase the burden associated with the cognitive load of verifying AI generated code 1 . This study illustrates the path to the future of web development tools. The need for rapidly adaptable and highly specialised web solutions has created a niche for specialized web development environments. Offering industry specific tools, these environments specialise in creating, deploying, and testing web environments for certain verticals. Development environments for other industries may have configurable development environments more tailored for specific verticals. Specialized web development environments may also have specific tailored vertical libraries for specific secured and compliant web development verticals 2 . Specialized environments may deploy pre built and tested libraries for specific types of environments. Specialized web development environments have improved collaboration by combining cloud integrated development environments and code assistance AI. The Integrated Development Environment IDE ,Cloud based development, Web development frameworks, DevOps tools ,Version control ,Code editor ,Front end development, Back end development ,Full stack development, Web application development, Containerization Docker , Continuous Integration Continuous Deployment CI CD purpose of this paper is to describe the specialized web development environments of the future 3 , the architecture and design of these environments, the challenges and the future adaptable web development environments. As traditional integrated development environments IDEs struggle with real time rendering and integration of AI, there is a need for modern web development environments to cater to data intensive applications in 2026 4 . This paper introduces NexusDev, a web development environment created for data intensive applications and real time data streams. NexusDev uses an edge first rendering architecture, coupled with a Web Assembly processing engine, for offloading main UI thread heavy computations. Additionally, we implemented a number of developer centric features, including an automated predictive code completion module for D3.js and Three.js frameworks. In assessing the environment 5 , we performed a comparative study with several cloud IDEs in a similar category, and found that NexusDev decreases latency by 45 in the data to visualization pipeline and assists in reducing the cognitive load of developers by providing debugging tools for asynchronous streams. Therefore, NexusDev innovatively meets the demands of modern front end engineering and data centered requirements complexity, and is a solid candidate for the next iteration 6 of the “Experience Economy” frontier 7 . Kashish Lanjewar | Poonam Nawkhare "Specialised Web Development Environment" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Recent Advances in Computer Applications and Information Technology , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101875.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101875/specialised-web-development-environment/kashish-lanjewar

Nowadays, companies rely more heavily on organized input and sentiment analysis when making decisions. Traditional methods like hand filled questionnaires, printed forms, or basic digital apps often lack real time insights, monitoring features, strong data protection, and structured summaries. This paper presents the development of InsightPulse Solutions—an enterprise polling and response management tool built as a web platform using Python Django , HTML, CSS, JavaScript, and Bootstrap, integrated with databases via SQL. Organizations such as human resources departments, universities, or event management teams can create various polls through this system. Responses are collected securely and displayed instantly using bar charts or pie graphs. Built on an MVC architecture, the system remains flexible, easy to maintain, and performs without lag. Access is role based, each user votes only once, poll timing is controlled, and administrative checks ensure accuracy behind the scenes. Testing evaluated system response speed, database performance, login security, and result display latency. Real time analysis performed smoothly during trials despite varying data loads. A single hub now manages feedback without requiring paper surveys or spreadsheets. Jagruti Khanwani "InsightPulse Solutions – Enterprise Polling & Feedback Management System A Secure and Scalable Web-Based Real-Time Polling Platform Using Python Full Stack" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101617.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101617/insightpulse-solutions-–-enterprise-polling-and-feedback-management-system-a-secure-and-scalable-webbased-realtime-polling-platform-using-python-full-stack/jagruti-khanwani

Booking a resort should be simple, but too often it means sifting through endless listings, calling to check availability, waiting forever for a confirmation, and just hoping the room is actually there when you arrive. Resort owners deal with their own headaches too—missed calls, double bookings, messy records, and no clear way to track how the business is doing. This project set out to fix that by building an Online Resort Booking System, a web based platform where guests can browse resorts, view rooms and photos, check real time availability, and make secure payments all in one place—no phone calls needed. For staff, there’s a dashboard to manage listings, track reservations, monitor occupancy, and keep a clean record of every transaction. The focus was on building a reliable backend to prevent booking errors and a simple frontend that anyone could use, with real time availability being a top priority to avoid double bookings. When we tested it with real users, guests found the process smooth and trustworthy, and resort staff said it made their daily operations much easier. The system shows that a well designed digital tool can genuinely improve the experience for both travelers and resort owners, and that running a hospitality business isn’t just about comfort—it’s about building something people can actually depend on. Ashish Kamdee "A Resort Booking Web Site for Booking Affordable and Luxurious Resort for Events and Relaxation" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101661.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101661/a-resort-booking-web-site-for-booking-affordable-and-luxurious-resort-for-events-and-relaxation/ashish-kamdee

Cybersecurity risks like ransomware attacks, phishing campaigns, data breaches, and zero day vulnerabilities have significantly increased as a result of the quick expansion of digital infrastructure and internet based services. For people, organizations, and cybersecurity experts, timely awareness of such threats is essential. However, cybersecurity related information is frequently presented in complicated technical language and is highly fragmented across multiple online platforms, making it difficult for novices to understand and time consuming for experts to analyze. Current news aggregation systems lack intelligent analysis, adaptive explanation mechanisms, and career oriented guidance, instead concentrating on content retrieval. In order to improve cybersecurity awareness and knowledge sharing, this research paper suggests a Security News Intelligence Agent that combines automated web crawling and Large Language Models LLMs . The suggested system retrieves news articles about cybersecurity. For people, organizations, and cybersecurity experts, timely awareness of such threats is essential. However, cybersecurity related information is frequently presented in complicated technical language and is highly fragmented across multiple online platforms, making it difficult for novices to understand and time consuming for experts to analyze. Current news aggregation systems lack intelligent analysis, adaptive explanation mechanisms, and career oriented guidance, instead concentrating on content retrieval. Jay Sunil Dhanwalkar "Security News Intelligence Agent Using Web Crawling and Large Language Models for Multi-Level Cybersecurity Awareness" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101618.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101618/security-news-intelligence-agent-using-web-crawling-and-large-language-models-for-multilevel-cybersecurity-awareness/jay-sunil-dhanwalkar

Starting with food choices, keeping blood sugar steady means watching what you eat every single day. To make that easier, a new tool called SugarGuard helps track meals using smart technology built into cloud systems. Instead of guessing portions or ingredients, it uses advanced image recognition along with large language models that understand context. Working in real time, the system breaks down meals from photos, estimating carbs and nutrients on the spot. Rather than relying only on manual logs, people get immediate feedback tailored to their health needs. Built using scalable design, it runs smoothly across devices without slowing down. Testing shows consistent accuracy when comparing its analysis to lab verified meal data. Though still in development, early outcomes suggest fewer errors in carb counting. Because it adapts to different cuisines, users from varied backgrounds can benefit equally. With secure processing, personal details stay protected behind encrypted channels. Keeping track of what people eat usually means writing it down by hand or talking to a dietitian. Mistakes happen easily that way, plus many find it hard to stick with the process. Results come back slowly too slow when blood sugar after meals is the concern. Enter SugarGuard an artificial intelligence tool built to help right away. It pulls together image analysis, meal details, and smart processing through a flexible online structure. Instead of waiting, users get immediate feedback on food choices related to diabetes care. Old problems fade when tech steps in like this one does. Snap a photo or speak into the device to log what you eat. With both image and text inputs, the model handles food pictures alongside spoken notes at once. Vision tools inside spot items on the plate, judge how much is there, even guess volume by shape and container. Merging those findings with nutrition facts pulls together clear reports on carbs, protein, fat. Blood sugar impact gets calculated too, using portion size and ingredient mix to estimate glycemic load. Output shows totals plus how each meal might affect glucose. Running on a cloud foundation, SugarGuard splits tasks into small independent parts handled by tools such as Docker. These pieces work together through Kubernetes, keeping everything fast when needed. Performance stays sharp during live use while adapting smoothly to changing loads. Stability holds firm even under pressure. Arpit Rokade "Sugarguard: A Proactive Metabolic Intervention System Using Multimodal Llms and Customized Convolutional Neural Networks" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101660.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101660/sugarguard-a-proactive-metabolic-intervention-system-using-multimodal-llms-and-customized-convolutional-neural-networks/arpit-rokade

Every single day, businesses and organizations receive too many resumes to feasibly go through manually. Standard Applicant Tracking Systems ATS primarily work by matching keywords therefore, there are many qualified applicants that will sometimes not appear in an ATS because they described their experiences with words that were not searched upon. In addition to the applicant’s language being different than what was searched for, resumes are typically formatted differently, which makes the task of comparing resumes even more difficult than it already is. The intelligent resume parsing and skills analytic system that we propose will utilize Natural Language Processing NLP to provide a solution to many of the ATS’ problems in regards to matching resumes to jobs. When any PDF resume is submitted to the intelligent resume parsing system, there will be a multi stage process to extracting information from the resume The first stage will extract the text from the PDF file, then format the text, identify important entities e.g. Name and contact information , and finally retrieve all relevant technical skills. The final stage involves scoring each applicant’s experience education relative to the job description using TF IDF vectorization through cosine similarity, which produces a score that can be easily compared between applicants. All information will be stored in a SQLite database and recruiters will interact with this information through a Streamlit web interface which provides visualizations, metrics, and side by side comparisons of applicants.In testing, the intelligent resume parsing system was able to extract 92.1 of the entities included in 500 resumes from various technology fields classify technical skills with 89.4 accuracy and provide approximately 90.2 resume to job matching accuracy. These testing results confirm that the combination of utilizing NLP, scoring based upon similarity to job descriptions and recruiter interaction through visualization are effective in gathering accurate information for applicants and generating an accurate comparison between two or more applicants. Yash Manjare "Intelligent Resume Parsing and Skill Analytics System Using NLP and Web Visualization" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101619.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101619/intelligent-resume-parsing-and-skill-analytics-system-using-nlp-and-web-visualization/yash-manjare

Crop diseases are a serious worldwide concern because they cause yield losses of 20–40 per year and have a substantial effect on the food security of expanding populations. In order to minimize excessive pesticide use, minimize crop damage, and stop the spread of disease, early and precise disease identification is crucial. Traditional techniques of detection, however, rely on the human visual inspection of skilled agricultural professionals, which is subjective, time consuming, and frequently unavailable to farmers in remote or rural locations. The lack of plant pathologists causes additional delays in diagnosis and treatment, which leads to avoidable financial losses. Plant disease identification can be automated with the help of breakthroughs in deep learning and computer vision. This will allow for quick, scalable, and expert level diagnosis using smartphone apps that farmers may use anywhere in the world. The comprehensive AI based leaf disease detection system presented in this study makes use of cutting edge Convolutional Neural Networks CNNs with transfer learning strategies. Pre trained architectures such as ResNet 50, VGG 16, and MobileNetV2 were refined using a dataset of 87,000 leaf pictures from 14 crop species, including tomato, potato, corn, grape, apple, cherry, peach, pepper, and strawberry, that represented 38 disease categories. The dataset contains leaves in good health as well as those with bacterial, viral, fungal, and nutritional deficiencies. In order to improve resilience and generalization in real world imaging scenarios, the effective dataset was enlarged to over 200,000 photos with intensive data augmentation, including flipping, zooming, rotation, brightness and contrast correction, and color jittering. Multi class classification, deep feature extraction, semantic segmentation based background removal, picture preprocessing, disease severity estimation based on impacted leaf area, and a treatment recommendation engine linked to agricultural knowledge bases are all integrated into the system architecture. The entire framework is made available as an intuitive mobile application with multilingual support, offline capabilities, and integration with agricultural extension agencies for professional advice as needed. During a four month growing season, 150 farmers from Maharashtra, Punjab, and Karnataka participated in field validation, which showed excellent real world performance. The technology produced results in an average of 8.3 seconds from image collection and achieved 93.7 practical diagnostic accuracy when compared to expert pathologist ratings. 89 of users were satisfied, and 67 of the time the system was able to identify ailments in their early stages, before they were obvious to untrained observers. Due to focused treatment suggestions, quicker treatment commencement than with standard expert consultation delays, and projected crop loss reductions of 15–25 , farmers reported a 32 decrease in pesticide usage. According to economic research, yield preservation and optimized input costs resulted in a 340 return on investment in a single growing season. Additionally, by enhancing agricultural extension databases through crowdsourcing validation, enabling regional disease monitoring, and increasing farmer awareness of disease indicators and management strategies, the system exhibited its promise as a scalable solution. Manasvi Gajbhiye "A Computer Vision Method for Plant Leaf Disease Early Detection" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101624.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101624/a-computer-vision-method-for-plant-leaf-disease-early-detection/manasvi-gajbhiye

The field of education is changing rapidly because of Artificial Intelligence 1 . This has led to the development of intelligent learning assistants that improve the academic experience of students. This research paper focuses on an “AI Study Partner,” an Artificial Intelligence powered assistant designed to help students learn, plan their academic activities, and gain knowledge in a personalized and interactive way 2 . The main objective of this study is to analyze how AI Study Partners can make learning more efficient, improve academic performance, and increase student engagement. This is achieved by providing real time assistance, customized study materials, and smart feedback to students 3 . The research also explores the technologies behind AI Study Partners, such as Natural Language Processing and Machine Learning, which allow the system to understand student queries and provide subject specific guidance 1 . Artificial Intelligence can also simplify complex topics, assist in research work, generate summaries, and provide notes. Additionally, AI Study Partners act as continuous support systems that are available to students at any time 4 . To evaluate the effectiveness of AI Study Partners, a conceptual and analytical methodology is used. The study examines features such as personalized learning paths, instant doubt resolution, time management assistance, and smart content recommendations. The results indicate that AI Study Partners improve accessibility to learning resources, support self paced learning, increase productivity, and reduce academic stress 5 . However, the study also highlights certain limitations, such as over dependence on Artificial Intelligence, the possibility of inaccurate information, and the continued need for human teachers in the learning process. The findings suggest that AI Study Partners should be used as supportive tools rather than replacements for traditional teaching methods. The study concludes that the integration of AI Study Partners in education can transform the learning process by making it more personalized, efficient, and student centered. Artificial Intelligence has the potential to enhance education, and AI Study Partners represent an important step toward smarter learning systems 1 . Nandini Pathaka | Nikhil Lonare "AI Study Partner" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Recent Advances in Computer Applications and Information Technology , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101880.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101880/ai-study-partner/nandini-pathaka

In today’s world, digital payments and online financial activities have become a central part of everyday life. As a result, many people now depend on digital tools to keep track of how much they spend. But often, most expense trackers focus on how they look or how users enter data, and their backends simply can’t keep up. In this study, we share a backend system built to grow with users over time. We break it down into layers like a user dashboard, business logic, alert engine, and a secure data layer so that no matter how many users come on board, the system stays quick and dependable. One of the most important features is that real time budget alerts, which immediately let users know when they are about to exceed their planned spending. We didn’t just stop at being scalable we also put security first. By using strong authentication and encrypted storage, we make sure everyone’s financial data stays safe After we ran tests with hundreds of users simultaneously, we noticed a huge improvement in both how quickly and how steadily the system performed, especially when compared to the old approach. As a result, we developed a simple, dependable tool that truly helps people make sense of their spending and gives them the reassurance to make better financial choices every day. Anjali Bobade "Design And Implementation of a Scalable Real-Time Expense-Tracking Backend System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101659.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101659/design-and-implementation-of-a-scalable-realtime-expensetracking-backend-system/anjali-bobade

The paper proposes a framework for emotional recognition and sentiment analysis utilizing AI and a combination of facial analysis and text based emotional modelling to aid individuals in improving their emotional health. The framework uses DeepFace software to analyse other peoples facial characteristics, such as emotional expression, age, gender, and the quantity of faces present, and utilizes face preprocessing techniques i.e. , face detection, alignment, and normalization to improve facial recognition. Textual data is analysed by various types of transformer based learning models DistilRoBERTa and RoBERTa, in the case of emotional and sentiment detection, respectively . Additionally, the framework incorporates a variety of fallback strategies that create outputs under limited resource conditions, through randomization of the number of faces, age, and gender, and based on the identified emotional characteristics of the referenced text data. The framework is trained and evaluated using data from the FER 2013 and AffectNet databases to be capable of recognizing multiple types of emotion rather than just using positive or negative sentiment detection methodology. User interface related tools developed for the proposed framework will aid in the creation of emotion diaries and long term mood assessments to enhance users decision making processes and provide them with customized recommendations. This framework will ultimately guide the development of an empathetic AI system to assist with managing mental wellness and develop the basis for a future, contextually aware, and holistic emotional recognition and sentiment analysis based on a combination of face based analyses performed by DeepFace and text based analyses performed by transformer supported methods, as well as fallback strategies. Yash Mahajan "An Integrated Deep Learning Framework for Multimodal Emotion and Sentiment Recognition" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101620.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101620/an-integrated-deep-learning-framework-for-multimodal-emotion-and-sentiment-recognition/yash-mahajan

Recommendation systems have become an essential component in various industries such as e commerce and OTT platforms. These systems use various algorithms to recommend the most relevant data to the user. Movie recommendation systems, in particular, suggest movies based on the users interests, thus saving time and effort for the user in searching through a large list of movies to watch. The aim of this project was to develop a movie recommendation system using cosine similarity algorithm. The system is designed to provide personalized movie recommendations based on the users movie preferences. The project began with data collection from various sources, including movie reviews, ratings, and user preferences. The collected data was preprocessed and transformed into a structured format suitable for analysis. The development of a cosine similarity algorithm comes next. This algorithm is used to compare two sets of vectors. The technique was used to assess how well the films in the dataset fit the users preferences. The method for proposing films was built using a web based interface. The interface allows users to enter their film tastes and receive suggestions based on what they say. The suggestions are presented in descending order of similarity, with the most comparable films at the top. Even films that the user has never heard of could be suggested by the system. Giving users a wide range of recommendations that are tailored to their particular preferences is made possible thanks to this capability. In conclusion, the projects goal of developing a cosine similarity based movie recommendation system was accomplished. Users could easily access and interact with the system because of its web based interface, and it was quite accurate at providing individualized recommendations. Amisha Dixit "Movie Recommendation System Using Python, SQL, and Statistics" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101658.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101658/movie-recommendation-system-using-python-sql-and-statistics/amisha-dixit

The field of education is changing rapidly because of Artificial Intelligence 1 . This has led to the development of intelligent learning assistants that improve the academic experience of students. This research paper focuses on an “AI Study Partner,” an Artificial Intelligence powered assistant designed to help students learn, plan their academic activities, and gain knowledge in a personalized and interactive way 2 . The main objective of this study is to analyze how AI Study Partners can make learning more efficient, improve academic performance, and increase student engagement. This is achieved by providing real time assistance, customized study materials, and smart feedback to students 3 . The research also explores the technologies behind AI Study Partners, such as Natural Language Processing and Machine Learning, which allow the system to understand student queries and provide subject specific guidance 1 . Artificial Intelligence can also simplify complex topics, assist in research work, generate summaries, and provide notes. Additionally, AI Study Partners act as continuous support systems that are available to students at any time 4 . To evaluate the effectiveness of AI Study Partners, a conceptual and analytical methodology is used. The study examines features such as personalized learning paths, instant doubt resolution, time management assistance, and smart content recommendations. The results indicate that AI Study Partners improve accessibility to learning resources, support self paced learning, increase productivity, and reduce academic stress 5 . However, the study also highlights certain limitations, such as over dependence on Artificial Intelligence, the possibility of inaccurate information, and the continued need for human teachers in the learning process. The findings suggest that AI Study Partners should be used as supportive tools rather than replacements for traditional teaching methods. The study concludes that the integration of AI Study Partners in education can transform the learning process by making it more personalized, efficient, and student centered. Artificial Intelligence has the potential to enhance education, and AI Study Partners represent an important step toward smarter learning systems 1 . Nandini Pathaka | Nikhil Lonare "AI Study Partner" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Recent Advances in Computer Applications and Information Technology , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101880.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101880/ai-study-partner/nandini-pathaka

Construction equipment breakdowns create numerous complications. Some of these include delayed work, increased maintenance costs due to repairs, safety issues related to equipment having the potential to break down or malfunction unexpectedly. In response, we have initiated a research project, which focuses on developing a method of maintaining construction equipment prior to any type of failure. We will accomplish this with the use of IoT devices modules with the ability to send and receive information , as well as using machine learning, or intelligent algorithms capable of learning from historical and current operating data. By using this innovative maintenance method, we will effectively have the ability to monitor equipment operations on an ongoing basis, as well as identify any abnormalities and predict when equipment may have failure related issues. We will gather a substantial amount of data from several different types of sensors located on the equipment we are monitoring. For example, the sensors will identify how well the construction equipment is operating and the environmental conditions surrounding it. We will be utilizing The Azure IoT Hub to facilitate the management of the data we collect, with all of the data being migrated into Azure Cosmos DB for storage and processing. The provided robust data model supports the organization and structure of newly collected data through ETL process for machine learning purposes. We will analyze the historical operating characteristics of each piece of equipment to develop predictive models to identify early indications of mechanical wear and optimize maintenance strategies by predicting failure of the equipment before it becomes an issue. Finally, we will develop a Power BI real time monitoring dashboard to display the overall health of each piece of construction equipment. Janvi Sanjay Malve "A Cloud-Based Predictive Maintenance System for Construction Machinery Using Iot and Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101621.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101621/a-cloudbased-predictive-maintenance-system-for-construction-machinery-using-iot-and-machine-learning/janvi-sanjay-malve

The financial markets are strongly nonlinear and volatile, driven by the dynamic economic factors that make forecasts to be non trivial. Conventional statistical models like ARIMA and GARCH often do not capture the complex patterns in stock movement. The recent success of deep learning, especially Generative Adversarial Networks GANs and Reinforcement Learning RL , offer strong potentials to model financial time series data. This work introduces a hybrid Reinforcement Learning Enhanced GAN framework for financial prediction. GANs produce realistic artificial financial data, enhancing the diversity of the data and generalizing, while RL is learning based on rewards to optimize the trade strategies. 1 The combination improves the forecasting power, flexibility to market unpredictability and investment preference. Empirical analysis with the standard financial performance measures i.e., RMSE, Sharpe Ratio, and cumulative return shows that the proposed RL GAN model outperforms conventional statistical and single deep learning models. Financial prediction is still one of the most difficult problems in computational finance since asset prices behave stochastically, nonlinearly and highly volatile. Conventional statistical methodologies frequently lack to adjust for fast changes in market structures and extreme events. 2 In recent years, artificial intelligence techniques show advantageous performance to deal with complicated financial date patterns. In this study, a hybrid Generative Adversarial Network GAN and Reinforcement Learning RL model is developed for enhancing the prediction accuracy and trading strategy optimization. The proposed model utilizes GANs in generating synthetic, high quality financial time series data to mitigate problems associated with small training samples and enhance generalization during infrequent market regimes. We also integrate reinforcement learning to facilitate trading decisions that can adaptively switch among different trade agents by reward optimized methods so as to achieve timely adjustment during market dynamics. 3 Contrary to traditional forecasting models, the RL enriched GAN framework intertwines data augmentation and sequential decision awareness. Experimental results on stock market historical datasets show enhancements in predictability, total returns and risk adjusted performance of the two models. This observation indicates that the combination of generative modelling with reinforcement learning is a robust and scalable methodology for intelligent financial forecasting systems. The findings constitute a novelty to the rapidly growing area of AI driven quantitative finance and materialize in the form of demonstrating advantages and possibilities when hybrid DL architectures are applied to actual trading conditions. 4 . Jasmeet Gandhi | Kuljeet Gandhi "Reinforcement Learning – Enhanced GANs for Financial Forecasting" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Recent Advances in Computer Applications and Information Technology , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101881.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101881/reinforcement-learning-enhanced-gans-for-financial-forecasting/jasmeet-gandhi

Cyber Insights is a website that teaches people about programming and cybersecurity. It is made to help people learn about safety. Cyber Insights has courses thatre easy to understand for people who are just starting out and for those who already know a little bit about programming and cybersecurity. Cyber Insights teaches programming languages like C, C , Java and Python. It also teaches about cybersecurity topics like network security, cryptography and threat management. As we are upgrading daily our education system is also upgrading and taking a new a way of learning. This new way of learning uses internet and combination of applications termed as “platforms”. These applications is built with programming languages and are software’s in nature this software make use of hardware for physical interaction with user. So this research paper seeks out to find out what are e learning is meant to because the e eLearning is gaining popularity day by day and has many users. There are several e learning platforms available online. And will the e learning based learning will be a better option in future than traditional way of learning Ali Alfiya Nizam "Cyber Insight: An Intelligent E-Learning Platform for Enhancing Digital Education" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101657.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101657/cyber-insight-an-intelligent-elearning-platform-for-enhancing-digital-education/ali-alfiya-nizam

The rapid progress of Artificial Intelligence AI has greatly impacted the growth and development of digital learning will continue to evolve as AI enables improved personalization, automation, and accessibility of education. The current research details the design process and implementation of an Artificial Intelligence AI based education system as a web based platform using Python and Django. An integrated AI Natural Language Processing NLP model will be used to read and respond to student questions provide human like assistance with academic work, and data driven context related explanations for learning a variety of subject areas. In addition to being able to answer questions intelligently, the AI Education System will provide students with personalized learning path recommendations using data collected about the user, including performance trends and preferences. The AI based Education System is built with an architecture that separates functions into modular components for scalability, user interaction, and the processing of data efficiently. The back end of the AI Education System will utilize Machine Learning Algorithms for text analysis, information retrieval, and suggestion generation while providing a user friendly web interface to any web browser. The AI Education System promotes learning via interactive study methods by giving students the ability to receive immediate academic support without constant supervision by humans. Through experimental observation, the AI education system is able to enhance overall study time, increase student access to learning resources and assist with decision making when developing an academic plan. The results of student engagement expressed satisfaction due to the individualized learning that they received. Mayank Barmaiyya "Ai-Powered Learning Web Application With Advanced Learning Support Tools Using Python and Django" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101623.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101623/aipowered-learning-web-application-with-advanced-learning-support-tools-using-python-and-django/mayank-barmaiyya

The popularity of digital education has raised the need for robust and scalable online examination platforms. Conventional inspection techniques are frequently labor intensive, error prone, and involve much manual work for storing and evaluating records. Welcome. This paper is an implementation of a Virtual exam and Quiz Management System that enables lecturers to create, manage, and grade exams students take their exams remotely. The proposed system supports fundamental features such as quiz building and design, question bank segment management, timed examination screens with a countdown timer mechanism, and final results upon exam submission, including an automated performance analytics dashboard. Security checks, along with verification steps, keep results fair and precise while live tracking watches performance. Built in blocks, the design grows easily and stays easier to manage over time. Tests show it calculates outcomes correctly, also making interactions smoother for people using it. To check how well it holds up, methods like confusion matrices appear alongside ROC curve reviews. One look at the data shows the new platform cuts down on busywork while making grading clearer. With it, schools moving toward online testing gain a tool that works without extra steps or confusion. A closer look at how cheating can be spotted in digital exams reveals tools that watch and listen while students work. Because of lockdowns and remote learning, schools turned fast to web based classes. Watching for dishonesty now happens through live analysis of sound and video feeds. These recordings need to clearly show what learners do and say. When lessons moved online, programs using smart algorithms grew common. Spotting fake moves became part of keeping grades fair. Yet worries linger about how private data gets handled when gathered through such platforms. This piece looks into both artificial intelligence driven and conventional oversight setups, weighing what each brings along with their downsides. Across the globe, academic centers and tech schools run digital classes, assessments, and utilities, opening up access while cutting expenses. A fresh take on overseeing tests via camera is presented here, placing value on safeguarding exams without piling pressure on students. When stacked next to older techniques, watching examinees through web linked cameras shows promise under scrutiny. Keeping remote evaluations trustworthy stays tough, yet examining live video checks helps uncover how well they tackle those hurdles. Anjali Vinod Rangankar "Design and Development of an Intelligent Online Exam and Quiz Management System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101601.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101601/design-and-development-of-an-intelligent-online-exam-and-quiz-management-system/anjali-vinod-rangankar

In this project we use natural language processing and machine learning to look at what students say on media. We want to see if we can find out if they have health conditions. What we found out is that computers can help us find these conditions on. This way we can get students the help they need while making sure we do it in a way thats fair to them. We are talking about natural language processing and machine learning again because these are tools, for analyzing student generated social media text. Milan Gaikwad "Mining Social Media Data to Analyze Student Mental Health" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101656.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101656/mining-social-media-data-to-analyze-student-mental-health/milan-gaikwad

Most pet owners genuinely care about their animals, but in reality, very few maintain proper digital health records. Vaccination dates, weight history, and previous medical issues are often stored in paper form or simply forgotten. Small signs like reduced appetite or unusual tiredness are sometimes ignored until the condition becomes serious. To address this issue, a desktop based Smart Animal Health Monitoring and Diagnosis System was developed. The application is built using Python, with PyQt5 for the graphical interface and SQLite for local database storage. It allows users to store pet details, track growth using graphical visualization, set reminders for vaccination or medication, analyze symptoms using a rule based scoring system, and view nearby veterinary locations. The system does not use complex medical datasets but instead applies a simple and interpretable scoring logic to classify health conditions into Low, Moderate, or High risk categories. The main objective of this project is to assist pet owners in early health awareness and organized record management rather than replacing professional veterinary advice. Ritika Ravindra Thakur "AI-Powered Smart Animal Health Monitoring and Diagnosis System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101655.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101655/aipowered-smart-animal-health-monitoring-and-diagnosis-system/ritika-ravindra-thakur

This study introduces SkillBridge Careers—an artificial intelligence tool built with Python that runs in browsers, guiding users through practice job interviews. Built into the platform, smart algorithms create tailored questions on the fly while assessing answers in real time. Instead of static formats, it adapts each session based on user input, offering live feedback grounded in predefined evaluation criteria. Scoring follows consistent patterns, drawing from behavioral cues and content relevance detected by machine learning layers. Insights appear through visual reports showing strengths, gaps, progress over sessions. Behind the scenes, full stack architecture supports seamless flow between interface actions and backend processing. A web platform built with Django, Python, plus front end tools like HTML, JavaScript, and Bootstrap runs on an SQL backed data store. Instead of relying only on human reviewers, it checks skills through coded rules alongside natural language processing to judge answers. Tests show scores stay more consistent, need less hand grading, track applicant progress better, while giving clear reports on each persons replies. A fresh approach takes shape when machines handle interviews at scale. Growth in job readiness becomes possible through consistent feedback loops. Performance insights emerge clearly once decisions rely on collected responses. One way to look at it—software that uses artificial intelligence to run job interviews. Picture a tool that simulates real interview scenarios without human help. This setup grades applicants through structured feedback loops. Built using Python across front and back ends, handling everything in one stack. Language processing steps in to judge speech patterns and word choices. Data flows into reports showing how ready someone is for work. Each piece connects, yet runs its own course behind the scenes. Abhijeet Kumar Yadav "SkillBridge Careers: An AI-Based Interview Assessment and Candidate Evaluation Platform Using Comparative Evaluation Models" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101602.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101602/skillbridge-careers-an-aibased-interview-assessment-and-candidate-evaluation-platform-using-comparative-evaluation-models/abhijeet-kumar-yadav

The majority of firms are moving toward AI in this day and age. Nonetheless, manual procedures and conventional booking techniques are still used by photography studios. Studio confirmation response times are sluggish due to these manual methods. Confusion and perhaps double bookings result from this, which are challenging to handle. An artificial intelligence powered centralized digital platform is necessary to overcome these inefficiencies. This research paper proposes a web based booking system for users and a portfolio platform for studios. The primary objective is to increase booking efficiency and enhance communication between users and studios. We employ Artificial Intelligence for real time studio interactions and machine learning for studio recommendations. The booking and payment systems are integrated. For data storage, we use MySQL as the backend technology. Users register, browse studios, and view portfolios. They interact with the intelligent system and receive personalized studio suggestions based on city and other filters. This process improves response times compared to manual systems and reduces workload. It also enhances the user experience and coordination with studios during booking. The suggested method shows how artificial intelligence can be used to modernize studio operations by providing a scalable and effective way to overcome the drawbacks of manual processes. Ajit Durgam "A Smart AI-Powered Online Portfolio and Scheduling Platform for Photo Studios" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101603.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101603/a-smart-aipowered-online-portfolio-and-scheduling-platform-for-photo-studios/ajit-durgam

This research paper presents the design, development, and conceptual framework of the Icchhapurti Manifestation Pen web application, a full stack MERN MongoDB, Express.js, React.js, Node.js platform that integrates e commerce functionality with mindfulness oriented content delivery. The study examines how digital platforms can bridge the gap between spiritual product marketing and evidence based psychological principles of goal setting, journaling, and intention based writing. Through a comprehensive analysis of related literature in positive psychology, consumer behavior, and human computer interaction, this research explores the positioning of manifestation tools within contemporary personal development practices. The paper proposes a structured methodology for evaluating user engagement with intention based writing tools and presents a scalable web architecture designed to support both commercial objectives and educational content delivery. Key findings from related literature suggest that intention based writing practices, when combined with physical tools that carry symbolic meaning, may enhance user engagement through mechanisms including conditioned superstition, spiritual branding authenticity, and the self creation effect. The research contributes to understanding how technology can support mindfulness practices while proposing future empirical validation frameworks for manifestation based interventions. Lokesh Khetade "Icchhapurti Manifestation Pen – Mern Stack Web Application" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101625.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101625/icchhapurti-manifestation-pen-–-mern-stack-web-application/lokesh-khetade

The Global Shipment Tracker GST —Transaction Management System TMS is an Internet based WEB application that will streamline and centralize logistics management for international shipments. The GST is a complete end to end solution for tracking cargo from origin to destination, managing shipment transactions, tracking logistics activities in real time, and providing visibility across the entire supply chain. Users – specifically, logistics managers, transport agencies, and customers – will be able to register shipments, update their transit status, verify delivery milestones, and maintain a complete historical record of the transaction from both the origin and the destination through the use of this system. The backend architecture will facilitate secure storage of data, efficient processing of transactions, and integration with third party APIs that allow users to proactively track live locations of their shipments. The frontend architecture will facilitate an easy to use interface to help users visualize their shipment route through time and with operational analytics. The GST TMS will improve the transparency, the speed, and the accuracy of decision making in international logistics operations, thanks to the automation of manual processes and reliable real time information. The GST demonstrates how full stack technologies can be used in practice to address complex issues associated with modern international shipping and supply chain management. Tanushree Tembhare "A Scalable Full-Stack Web Application for Global Shipment Tracking and Realtime Logistics Monitoring" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101604.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101604/a-scalable-fullstack-web-application-for-global-shipment-tracking-and-realtime-logistics-monitoring/tanushree-tembhare

Digital marketing has changed the way companies talk to their customers. Nowadays companies have to keep making meaningful things to say on many online platforms. Making sure they have something to say all the time and saying it at the right moment is still a big problem for people who do marketing. This study suggests a Smart Content Automation Framework that uses artificial intelligence to make digital marketing easier and better. The framework uses techniques like understanding what people mean predicting what they will do looking at how people feel and scheduling things to happen automatically. By using these techniques the system can make personalized marketing messages predict how people will react and choose the best time to send messages. Faizan Siddiq Ali Salmani "Generative AI for Digital Marketing a Smart Content Automation Frame Work" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101626.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101626/generative-ai-for-digital-marketing-a-smart-content-automation-frame-work/faizan-siddiq-ali-salmani

Hiring the right candidate is a tough and time consuming task, especially when HR departments receive hundreds of resumes for a single job post. Going through them manually takes a lot of time and can lead to human bias or errors. To solve this practical problem, we developed Career Navigator, an automated resume screening system. Unlike older Applicant Tracking Systems ATS that only look for exact keywords, our project tries to understand the actual meaning of the text using Natural Language Processing NLP . We used TF IDF to extract important features from the resumes and built a Recurrent Neural Network RNN to classify them into specific job domains. Additionally, we added a recommendation engine using Cosine Similarity to suggest the best fitting jobs and show candidates what skills they are missing. Our tests showed promising results, achieving a classification accuracy of 91.4 while heavily reducing the time needed to screen a profile. Vandana Dewangan "Automated Resume Screening and Job Recommendation System Using Natural Language Processing and Deep Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101605.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101605/automated-resume-screening-and-job-recommendation-system-using-natural-language-processing-and-deep-learning/vandana-dewangan

Running exams in colleges involves a lot more effort than most people realize. Setting question papers, evaluating hundreds of answer sheets, and publishing results every single step demands time, coordination, and manpower. And mistakes do happen. A wrong total here, a misplaced sheet there, and students start filing complaints while staff redo work they had already done. This project grew out of a real frustration with how much manual effort goes into something that repeats every semester. I made a web based exam management system. This system does everything from making question papers to showing results to students. You do not need to use a lot of tools or spreadsheets.The frontend of the system uses React. The backend uses Node.js.There are login roles for admins and teachers and students. Each person can only see what they are supposed to see.When students answer questions they get scored right away when they hit submit.Descriptive answers go to a queue where teachers can review them.When we tested the system it worked well with a lot of users at the time.Making results for exams used to take days but now it only takes a few minutes after the exam is closed.The web based exam management system is really helpful, for managing exams.The system makes it easy for admins and teachers and students to do their work. Shruti Pimpalshende "Secure and Integrated Exam and Quiz Management System Using React and Node.js" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101654.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101654/secure-and-integrated-exam-and-quiz-management-system-using-react-and-nodejs/shruti-pimpalshende

The Shri Bindu Madhav Mandir is near the Panchganga Ghat, whichs a very holy place. For a time people from all over India have been visiting the Shri Bindu Madhav Mandir. These people include pilgrims, academics and tourists. There are references to the Shri Bindu Madhav Mandir, in Hindu scriptures Puranas and travelogues. These references suggest that the Shri Bindu Madhav Mandir has a long history. It is believed that the old Shri Bindu Madhav Mandir was really big and had architecture. The Shri Bindu Madhav Mandir is still an important place today.The temple was rebuilt in a way after it was destroyed during the medieval invasions. It still holds a lot of meaning. The temple has done well as a place of worship with all the problems it had. This shows that the people who worship there are very strong and committed to their religion.The temple has a North Indian style of building. This style is seen in the rooms where ceremonies are held the sculptures and the way the sanctuary is designed. The temple is a place, for religious events and festivals. Examining how Shri Bindu Madhav Mandir has changed over time its architectural features and its religious importance is what this study aims to do.The study also checks how the Shri Bindu Madhav Mandir takes part in community life like organising services, festivals and rituals.The study looks into how the Shri Bindu Madhav Mandirs managed and run making sure it is clean, safe and well taken care of and that its culture is preserved.The study also tries to see how the Shri Bindu Madhav Mandir handles crowds and keeps everything secure.The focus is on how planning and modern tech can improve the visitor experience while keeping values.The results show that Shri Bindu Madhav Mandir is a symbol of identity and history not just a place of worship.This temple supports tourism, which helps people know about Indias various religious traditions and also boosts the local economy.The temple is an area of study, for scholars and cultural experts because it is a great example of ongoing devotion, architectural history and sustainable management. Kamlesh Moreshwar Kumbhare "Digital Management System for Shri Bindu Madhav Mandir" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101627.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101627/digital-management-system-for-shri-bindu-madhav-mandir/kamlesh-moreshwar-kumbhare

Data breaches that impact millions of users and result in annual damages of billions of dollars are the reason behind the current increase in cybersecurity dangers. Since authentication systems are an organizations first line of defense against unauthorized access, their effectiveness is crucial to its security posture. Nowadays, phishing, credential stuffing, brute force assaults, and social engineering are just a few of the attack methods that might compromise traditional password based single factor authentication SFA . By requiring a second. verification factor in addition to passwords, two factor authentication 2FA increased security. Usually, this is something that the user is biometric data or has security token, smartphone . Expert attackers have demonstrated that they can circumvent 2FA in a variety of methods, including by employing malware that intercepts one time passwords, SIM swapping attacks, and sophisticated phishing techniques. Three factor authentication 3FA is a more dependable method that combines three distinct authentication factors something you know password or PIN , something you own security token or smartphone , and something you are biometric identification . As a result, there are several distinct barriers that attackers must simultaneously overcome. The influence of three factor authentication on system security is thoroughly examined in this study through theoretical analysis, experimental implementation, and evaluation of real world deployment. Inherence based authentication fingerprint biometric with liveness detection possession based authentication time based one time password via hardware security token and mobile authenticator app and knowledge based authentication password with complexity requirements were all integrated into the security system we created. Throughout the course of a six month evaluation period, the system was implemented in three organizational environments a technology startup with 120 employees, a healthcare provider with 180 employees, and a financial services company with 250 employees. A total of 550 users were involved. Security effectiveness was measured through penetration testing, simulated attack scenarios incident monitoring, and comparative analysis against SFA and 2FA implementations. Usability impact was assessed through user surveys, login time measurements, help desk ticket analysis, and user error rate tracking. The findings show that 3FA offers significant security advantages over SFA and 2FA. Across simulated attack scenarios, such as phishing 0.8 success vs 45 for SFA, 12 for 2FA , credential stuffing 0.0 success vs 38 for SFA, 8 for 2FA brute force attacks 0.0 success vs 22 for SFA, 3 for 2FA and man in the middle attacks 1.2 success vs 31 for SFA, 15 for 2FA , the successful breach rate dropped by 99.2 when compared to SFA and 87.3 when compared to 2FA. Account takeover incidents in real deployments dropped to 0 cases compared to 23 incidents over the previous year with 2FA. But usability problems emerged in the first month, the average authentication time increased to 18.7 seconds compared to 8.4 seconds for 2FA and 4.2 seconds for SFA , help desk queries increased by 41 and initial user satisfaction decreased by 23 . As customers grew accustomed to the new login procedure, these issues significantly diminished after the first 30 days.According to long term studies, 78 of users acknowledged increased security awareness, and 84 supported continuing to use 3FA despite additional authentication processes, with user satisfaction returning to within 8 of baseline levels. Nutan Shah "Assessing Three-Factor Authentications Effect on User Trust and System Security Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101647.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101647/assessing-threefactor-authentications-effect-on-user-trust-and-system-security/nutan-shah

Modern industries have mechanical systems that must be monitored continuously and in realtime to guarantee the reliability of mechanical operations, minimize the downtime, and guarantee the improved safety. Other conventional maintenance methods such as reactive scheduled maintenance check are inadequate in complex industrial environment. This combination of smart sensors, advanced data analytics, and artificial intelligence offers the predictive maintenance capability, early fault detection, and intelligent decision making capability. This literature review presents a synthesis of the recent trends in the smart sensor technology like vibration, strain, temperature, MEMS, fibre optic and nanocarbon based sensors, and AI based data analysis methods like machine learning, deep learning, and soft sensor models. The review goes further to discuss techniques of combining sensors with cloudedge computing, Internet of Things platforms and digital twin frameworks to attain real time monitoring and automatic maintenance. The main issues such asthe inability to combine multisensors, low interpretability of AI models, energy inefficiency, the absence of unified frameworks, and interoperability problems are discussed. The research gaps and future directions in the study include explainable AI, sustainable low power sensor design, crossdomain validation, and scalable cyber physical architectures. The review is a good generalization of the state of capabilities, limitations, and opportunities that can be used in the design of intelligent, reliable, and sustainable mechanical monitoring systems by researchers and practitioners in accordance with Industry 4.0 and Industry 5.0 goals. Keywords Smart sensors, Data analytics, Artificial intelligence, Real time monitoring, Predictive maintenance, Internet of Things, Digital twin, Mechanical systems, Fault detection, Industrial monitoring. Aman Padole "Smart Sensors and Data Analytics Using AI" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101606.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101606/smart-sensors-and-data-analytics-using-ai/aman-padole

The healthcare industry requires intelligent, secure, and scalable digital systems to manage patient interactions, hospital operations, and emergency preparedness. Traditional Hospital Management Systems HMS lack intelligent slot optimization, real time resource monitoring, and integrated patient lifecycle tracking. This research proposes MediPulse, a Smart Healthcare Management System built using the MERN stack MongoDB, Express.js, React.js, Node.js . The system integrates CRM Customer Relationship Management , ERP Enterprise Resource Planning , Emergency Resource Monitoring, AI ready architecture, and Secure SDLC practices. Key features include intelligent slot allocation, emergency priority scoring, real time resource tracking, staff shift management, medicine expiry alerts, telehealth integration, multilingual interface, and advanced security mechanisms such as JWT authentication and role based access control. The system demonstrates improved slot utilization 90 and reduced emergency response time 6 minutes compared to traditional systems. The proposed solution presents a scalable, secure, and future ready healthcare ecosystem. Shruti N. Mahatme "Mr." Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101653.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101653/mr/shruti-n-mahatme Digital Brain tumor detection is a critical challenge in medical imaging and diagnosis, with early detection being vital for effective treatment and management. With the advent of machine learning ML techniques, significant progress has been made in automating brain tumor detection from medical images such as MRI scans 1 , 2 . This paper presents a comprehensive study on the application of various machine learning algorithms for brain tumor detection, with a focus on the Support Vector Machine SVM model. The objective is to evaluate the performance and accuracy of SVM compared to other popular machine learning models, including Decision Trees, Random Forests, K Nearest Neighbors KNN , and Logistic Regression. In this study, a dataset of MRI brain images is pre processed using techniques like normalization and feature extraction. Several classification algorithms are applied to detect and classify brain tumors as benign or malignant. Among all tested models, the SVM outperforms the others in terms of accuracy, precision, recall, and F1 score. The SVM model uses a kernel trick to map input features into higher dimensional spaces, providing better classification boundaries and generalization capabilities. This enables the SVM model to handle non linear data more efficiently than linear classifiers. Additionally, SVMs ability to work with a small number of training samples and high dimensional data further enhances its performance. Madhura Mardikar "Brain Tumor Detection Using Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101652.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101652/brain-tumor-detection-using-machine-learning/madhura-mardikar

Digital devices are being quickly adopted by schools for communication and learning purposes, but this change also exposes students to more online hazards, including inappropriate content, cyberbullying, excessive screen time, and early warning signs of mental illness. In reality, many institutions rely on reactive manual supervision and fragmented device restrictions that dont offer auditable incident handling or real time visibility. In this paper, we introduce Safe4Sure, a privacy first, AI powered monitoring and protection platform that works on both Windows and mobile devices and is tailored for educational settings. The platform is set up as a modular client server system that integrates i monitoring of devices and activities, ii content protection based on policies, iii AI assisted risk detection for harmful language signals and abnormal activity patterns, iv monitoring of wellbeing trends, and v safe alerts, reporting, and analytics through a centralized web dashboard. Safe4Sure prioritizes role based access control, encryption, secure authentication, audit trails, and data minimization principles in line with child protection and privacy guidelines to maintain fair and compliant monitoring. We outline the context of the problem, relevant literature, the design science approach that organized the work, the data pipeline and preprocessing procedures, and the suggested algorithms for alert triage and risk scoring. In conclusion, we present an evaluation strategy that assesses detection quality, system latency, school staff usability, and privacy security controls prior to implementation. Megha Umashankar Shahare "SAFE4SURE – AI-Enabled Child Safety, Wellbeing & Monitoring Platform for Schools" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101628.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101628/safe4sure-–-aienabled-child-safety-wellbeing-and-monitoring-platform-for-schools/megha-umashankar-shahare

The integration of Large Language Models LLMs into schedule management systems represents a significant evolution in conversational AI assistance. This paper synthesizes recent research from 2024 2025 examining the design, implementation, and evaluation of LLM based chatbots for scheduling tasks. Across multiple studies, researchers have explored multi agent architectures, human AI collaboration models, explainability mechanisms, and domain specific applications. Key findings indicate that while LLM agents demonstrate considerable promise as daily assistants, their effectiveness depends critically on architectural choices, user trust calibration, and the integration of structured reasoning capabilities. Systems employing graph structured multi agent coordination and hybrid symbolic LLM approaches show particular promise for handling the temporal reasoning and constraint satisfaction requirements inherent in schedule management. This review synthesizes current research contributions and identifies future directions for the field. Abhishek Bahe "AI Schedule Management: AI-Integrated Development of a Smart Conversational AI Chatbot for Efficient Schedule and Time Management" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101651.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101651/ai-schedule-management-aiintegrated-development-of-a-smart-conversational-ai-chatbot-for-efficient-schedule-and-time-management/abhishek-bahe

Modern software engineering teams depend on a fragmented set of tools to manage planning, development, version control, collaboration, and monitoring activities. While each tool is effective individually, the lack of seamless integration among them results in fragmented workflows, limited visibility, and increased operational complexity. This paper presents DevSync OS — Unified Engineering Lifecycle Orchestrator, a centralized web based platform designed to integrate and streamline the complete software development lifecycle SDLC into a single cohesive environment. The system connects project lifecycle management, GitHub repository activity, workflow visualization, and team collaboration through a unified operational interface. Built on the MERN stack MongoDB, Express.js, React.js, Node.js , DevSync OS integrates with GitHub via the Octokit API for real time repository synchronization. Workflow and system architecture visualization are powered by React Flow and Mermaid.js. The system implements role based access control RBAC through JSON Web Tokens JWT to ensure secure, structured access across Administrator, Project Manager, and Developer roles. Test results demonstrate API response times under 200ms, 100 database uptime during load testing, and stability for up to 20 concurrent simulated users. DevSync OS successfully reduces context switching, improves transparency, and increases team coordination, offering a scalable solution aligned with modern Agile and DevOps engineering practices. Vrushali P. Ghaywankar "DevSync OS – Unified Engineering Lifecycle Orchestrator: A Centralized Web-Based Platform for Software Development Workflow Integration" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101607.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101607/devsync-os-unified-engineering-lifecycle-orchestrator-a-centralized-webbased-platform-for-software-development-workflow-integration/vrushali-p-ghaywankar

In the healthcare field there is a problem. Medical costs are going up. Budgets are limited. We need models to make the most of what we have without hurting patient care. Healthcare Economics and Outcomes Research is an area that helps us understand the value and effectiveness of medical treatments this study creates a framework. It looks at costs. How well services are delivered. We use a mix of methods, including Data Envelopment Analysis to see how efficient things are. We also use machine learning to predict what will happen with resources we looked at 15,000 cases from eight departments in a big hospital. We checked costs, patient outcomes and how well the hospital worked. Our model looks at how resources are used and how they are distributed. We found that using a model with DEA and XGBoost works well. It can predict costs and quality accurately. We got an R 2 of 0.87 a Mean Absolute Percentage Error of 8.2 and an Area Under the Receiver Operating Characteristic Curve of 0.91 this approach also found ways to save money. We can cut costs by 18.7 without hurting quality. This study helps healthcare leaders make decisions. They can use our method to make healthcare better and more efficient. Sahib Qureshi "Healthcare Economics & Outcomes Research (HEOR): Cost Efficiency & Service Delivery Analysis" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101608.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101608/healthcare-economics-and-outcomes-research-heor-cost-efficiency-and-service-delivery-analysis/sahib-qureshi

In todays digital world, were surrounded by many events happening around us from music concerts and food festivals to professional workshops and community meetups. While platforms like Eventbrite and Meetup make event information easily accessible, users often feel overwhelmed by the huge volume of listings that rarely match their personal interests or consider where they actually are. This research tackles this problem by developing a smart event discovery system that learns what users like and where they are located to suggest events theyd genuinely want to attend. The system works by combining three different recommendation approaches. It looks at what similar users have enjoyed then it analyzes event descriptions and categories to find events matching a users stated preferences. and most importantly, it considers how far each event is from the users location, because even the perfect event isnt useful if its too far away. These three factors are balanced, with collaborative filtering contributing 40 , content matching 30 , and location convenience 30 . To test the system, we used real event data from Eventbrite and Meetup, including events across 25 different categories, multiple users, and user interactions like event views, saves, and attendance our system correctly identified relevant events most of the time. When recommending ten events to a user, nearly nine out of ten matched their interests, and the system captured more than seven out of every ten events users actually wanted. These numbers significantly outperformed traditional recommendation methods. We also conducted an ablation study to understand each components contribution. Removing the location factor dropped performance noticeably, confirming that where an event happens matters almost as much as what its about. A user study with 50 participants reinforced these findings people rated our system 4.3 out of 5, significantly higher than the 3.8 rating for existing approaches. Participants particularly appreciated getting suggestions for events within reasonable traveling distance. This research shows that combining what users like with where they can creates genuinely helpful event recommendations. The approach can benefit various applications from helping tourists discover local happenings to connecting community members with neighborhood activities and supporting smart city initiatives that bring people together. Sanika Bhulgaonkar "An Online Event Discovery System Using User Preferences and Location Data" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101650.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101650/an-online-event-discovery-system-using-user-preferences-and-location-data/sanika-bhulgaonkar

E commerce delivery prognostications for 2026 indicate strong and sustained growth, particularly in India, where the request is anticipated to reach nearly 200 billion, driven by rising internet access and adding smartphone penetration across civic and pastoral regions. A major share of this growth is projected to come fromnon metro druggies, contributing to an estimated 80 expansion in the sector. Quick commerce platforms similar as Blinkit, Instamart, and Zepto are anticipated to significantly expand their structure by adding around 2,000 – 2,500 new dark stores, fastening on perfecting functional effectiveness and optimizing delivery routes. Hyperlocal commerce is set to come the new standard, as consumers decreasingly prefer briskly delivery times and lower service charges. Smart logistics systems incorporating route optimization, micro warehousing, and real time shadowing updates will further enhance delivery performance and client satisfaction. Mobile commerce is also projected to substantiation substantial growth encyclopedically, anticipated to reach 2.4 trillion in 2026, with continued expansion at a steady rate in the coming times. also, sustainability is arising as a core focus, with companies investing in automatedmicro fulfillment centers andeco friendly practices. still, competition remains violent, especially among request leaders like Blinkit and Swiggy, where shifting perimeters and aggressive expansion strategies produce an changeable competitive geography. Arising trends similar as AI powered personalization, voice commerce, and multilingual shopping gests are also anticipated to shape the future ofe commerce delivery ecosystems. Sumedha. V. Vaidya "E-Commerce Delivery Predictrions and Sales Insights" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101649.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101649/ecommerce-delivery-predictrions-and-sales-insights/sumedha-v-vaidya

House prices need careful guessing because choices here carry big money risks. Old ways of judging value usually depend on people looking closely, using their experience this can bring bias or mixed results. As AI and ML grew stronger, number based techniques started offering sharper estimates, changing how homes are priced. Looking at how different machine learning methods predict home values, this work uses organized real estate information. Features like size of the land, count of rooms, age of construction, space for vehicles, general condition ratings, and neighborhood details make up the data set. Cleaning steps fixing gaps in records, turning categories into numbers, adjusting scale differences, eliminating odd entries helped sharpen predictions. Instead of just one approach, four were tested straight line fitting, tree style splitting, forest based averaging, then boosting driven refinement. Each was judged by average mistake size, error spread, plus explained variance not magic, just math tracking accuracy. When tested, ensemble techniques did better than standard regression. Random Forest stood out by predicting most accurately. These outcomes show artificial intelligence models boost how well property values are estimated. Efficiency gets a clear lift from using such systems. Shreyash S. Donarkar "House Price Prediction using Artificial Intelligence and Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101648.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101648/house-price-prediction-using-artificial-intelligence-and-machine-learning/shreyash-s-donarkar

The Indian market is growing at a tremendous rate, and at the moment, the Indian market is set to become the fastest growing market in the world. We are talking about a growth rate of 6.9 between the years 2026 and 2030. This is a huge jump. To be more precise, we are talking about an increase of 8 11 in FY26 in the life insurance segment. This is because of the newfound interest in annuity savings and protection products. The segment that is growing at an enormous rate is health insurance. This is the segment that is looking at a massive CAGR of 20.9 between now and 2030, meaning this will be the segment that will contribute nearly 38 of the total premiums generated in the non life insurance category. The general segment is looking at a healthy growth rate of 12 14 in FY27. If we look at this, we will understand the enormity of this market because the non life insurance penetration is at a mere 1 . This is because of a few factors, namely regulations, people having more money in their pockets, and the fact that digitalization has finally made it easy for people to access this. Sanika Vinod Vaidya "Insurance Premium Predictions by Using Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101646.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101646/insurance-premium-predictions-by-using-machine-learning/sanika-vinod-vaidya

In the world information management systems have become fundamental components of personal use and organizational knowledge infrastructure. With the high growth of user generated data, there is a growing need for structured, secure, scalable, and highly available systems to manage digital notes and textual information. Traditional deployment methods for web applications often suffer from environment inconsistencies, configuration drift, dependency conflicts, and scalability limitations. These challenges necessitate the adoption of modern architectural and deployment strategies such as containerization and service isolation. This project presents a comprehensive theoretical and practical framework for designing and deploying a Containerized Notes Management Application using Django, MySQL, and Nginx, orchestrated through Docker containers. The proposed system follows a layered three tier architecture consisting of presentation, application, and data layers, each operating in isolated containers to ensure modularity and portability. Django, a high level Python web framework, is utilized to implement the Model View Template MVT architecture, enabling clean separation of concerns and secure web application development. MySQL is employed as a relational database management system, ensuring ACID compliance and data integrity through structured schema design and relational constraints. Nginx acts as a reverse proxy server, managing HTTP request routing, static file serving, and load balancing, thereby improving system performance and reliability. Docker containerization encapsulates each component into lightweight, portable environments that share the host operating system kernel while maintaining process isolation. Docker Compose orchestrates multi container communication, networking, and persistent storage management. Neha S. Pathan "Container-Driven Notes Management System Implementation Using Django and Nginx" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101645.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101645/containerdriven-notes-management-system-implementation-using-django-and-nginx/neha-s-pathan

Since the rise of information technology, manual has turned out to be exercise in futility and vitality particularly in the created nations. In Malaysia, fundamentally the manual system is as yet working and it must be progressed. The fundamental purpose behind not building up a robotized system is expected the absence of learning and inventiveness in information technology field. The essential point to carry out this venture is to make and plan basically by building a Bus booking system of Android Application for the organization in Malaysia, keeping in mind the end goal to exchange all their manual undertakings or routine operations into computerized system, which will enable the organization to serve its clients up to their ideal fulfillment. It is a typical thing that information technology has changed numerous manual operations to mechanized and individuals are getting a charge out of it much better that the manual system. The proposed system will serve and remain as a worldwide system communication arrangement of the organization with clients.The system allows users to book ticket on their fingertips without getting stress or going to the counter to purchase a ticket. Once you register by filling in all the necessary information you become a user by having all the access to use the system. The system has so many functionality such as the bottom shows on application by knowing the routes, knowing the price and discount also displaying when booking, payment also is been provided all in the system. The system contains admin part which takes all the responsibility for updating most the information need for the benefit of the customers and also allow users to know all the information where each bus is going to and also by knowing the destination. The system also shows on how to get to each stop, and give users the fares for each route and also is trickily based on the location that is been provided for a user’s. Aditi Arvind Daf "An Intelligent Public Transport Tracking and Real-Time Monitoring System Using GPS and IoT" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101644.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101644/an-intelligent-public-transport-tracking-and-realtime-monitoring-system-using-gps-and-iot/aditi-arvind-daf

Academic timetables development is an intricate combinatorial problem to solve to a greater extent that schools have for every academic session. Traditional manual scheduling methods with spreadsheets become unhelpful due to their failure to account for scale and inaccuracy with the institutions complexity and typically result in resource conflicts, teacher overlaps, and uneven workload distribution. In this work, we present a smart, automated timetable generation system using the principles of evolutionary computation to deal with this NP hard scheduling problem. The architecture of the system integrates a GA Genetic Algorithm that aims to provide satisfaction around multi constraints including hard constraints e.g. overlaps between teacher unavailability, room conflicts and capacity limitations and soft constraints to improve schedule quality. It’s a full stack web app made using Python Django and featuring a modular layout to take care of teachers, courses, departments, sections, rooms, and time slots. We are interested in the Genetic Algorithm, which will employ tournament selection, single point crossover, and random mutation operators to adapt optimal timetable solutions generationally. Results show that the system can generate conflict free schedules in 50 100 generations at a 100 hard constraint satisfaction it has the ability to optimize for soft constraints. This implementation achieves an 85 time reduction in timetable preparation compared to manual approaches and a scalable architecture fit for institutions that operate with multiple departments or diverse academic structures. Saloni Kanhekar "Applying Genetic Algorithms for Dynamic Timetable Generation and Optimization" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101643.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101643/applying-genetic-algorithms-for-dynamic-timetable-generation-and-optimization/saloni-kanhekar

In the movie rental industry, inventory value depreciates at an exceptionally rapid pace, creating a unique and punishing economic environment for retailers. Unlike traditional retail sectors where products retain value over months or years, a new release DVD or digital copy loses the vast majority of its rental demand within weeks of its street date. This compressed lifecycle creates a high stakes operational dilemma excess stock of yesterdays release sitting on shelves past its prime demand window immediately triggers capital loss through writedowns and mounting carrying costs, while stockouts during the opening weekend cause permanent and unrecoverable revenue loss as customers turn to competitors or alternative entertainment options. This paper systematically analyzes how the disciplines of time series forecasting and inventory economics intersect to solve this fundamental allocation problem, proposing a data driven framework for navigating the narrow profitability window of new release titles. The research introduces a novel application of a mixed effects time series model specifically designed for the movie rental context. Unlike conventional forecasting approaches that treat all titles uniformly, our model distinguishes between the universal decay pattern common to all rentals—the fixed effect—and title specific deviations driven by unique characteristics—the random effects. Crucially, the model incorporates a comprehensive set of external regressors to measure their quantitative effect on rental velocity throughout a titles lifecycle. These regressors include pre release box office performance opening weekend gross and total gross , critical reception metrics Rotten Tomatoes Tomatometer scores and audience scores , audience engagement indicators IMDB user ratings and social media buzz , and industry recognition events major award season nominations such as Oscars or Golden Globes . By dynamically integrating these external signals, the model can anticipate whether a critically acclaimed independent film will demonstrate stronger long tail demand than a big budget blockbuster that peaks and declines rapidly. Our optimization technique employs a sophisticated cost function approach that asymmetrically weights forecast errors based on their timing and financial impact. Rather than minimizing standard error metrics equally across all periods, the model assigns differential penalties that reflect the real world economics of movie rental stockouts are penalized more heavily during week one when rental velocity and customer expectations are at their peak, while overstocking is penalized more heavily during week four when inventory has substantially depreciated and carrying costs accumulate. This asymmetric weighting ensures that inventory decisions are economically rational rather than statistically convenient, aligning operational execution with profit maximization objectives. The results chart a viable path toward precision retailing in the entertainment software sector. By implementing our integrated forecasting and optimization framework, retailers can achieve a 12 reduction in total inventory carrying costs through more accurate alignment of supply with the rapidly decaying demand curve. Simultaneously, the models focus on preventing early period stockouts contributes to measurable improvements in customer retention rates, as subscribers experience consistently better availability of high demand new releases during their critical opening windows. These findings demonstrate that the intersection of advanced time series methods and inventory economics offers a powerful solution to the acute allocation problem inherent in short life cycle products, with implications extending beyond movie rental to any industry facing rapid demand decay and asymmetric error costs. Prachi. P. Ingle "Retail Inventory & Demand Forecasting: A Time-Series Analysis of Movie Rental Economics" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101631.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101631/retail-inventory-and-demand-forecasting-a-timeseries-analysis-of-movie-rental-economics/prachi-p-ingle

Finding useful research papers today takes more effort because so many new studies appear every year. Because there are too many articles, people often miss key sources when picking citations by hand. This project introduces an automated way to recommend references using language analysis tools instead. The system looks at how closely ideas match between texts to offer suitable academic sources. Instead of searching endlessly, researchers get suggestions shaped by what they write. Tools like these help reduce missed connections across growing bodies of work. By focusing on meaning, it picks out papers that align well with the users content. What matters most is matching context, not just keywords or titles alone. Automated support like this fits into writing without slowing it down. It works quietly in the background while authors develop their arguments further. A fresh approach begins by cleaning up scholarly texts removing clutter like common filler words and adjusting word forms. Following that, pieces of text get split into smaller units so each part can be analyzed properly. Words are then transformed into standardized versions before turning them into numerical patterns via TF IDF weighting. Once converted, these patterns let the software compare files by measuring angles between vectors instead of exact matches. Close matches rise to the top when rankings form based on how closely they align numerically. Recommendations appear once comparisons finish, offering users nearby works tied by theme or topic. Python runs the setup, relying on tools like NLTK along with Scikit learn. Its goal Less hands on work, sharper citations, smoother research flow. Tests show it picks useful academic sources well giving writers and learners a solid edge. This work shows how NLP tools can actually help in academic support setups while offering a design that grows easily for suggesting citations automatically. Lina Vijay Kawadkar "Development of NLP-Based Citation Recommendation System for Automatic Research Paper Reference Identification and Academic Support" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101642.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101642/development-of-nlpbased-citation-recommendation-system-for-automatic-research-paper-reference-identification-and-academic-support/lina-vijay-kawadkar

AI and machine learning are shaking up the financial world, especially when it comes to risk management. Old school credit checks lean on rigid rules and basic scoring systems, but let’s be honest—they miss a lot, especially the messy, unpredictable behaviour of real borrowers or the massive flood of data banks handle now. In this study, I put forward a credit risk modelling and loan portfolio optimization system powered by AI. Here’s what’s inside clean data prep, smart feature engineering, supervised learning, and key risk measurements like Probability of Default, Loss Given Default, and Exposure at Default. On top of that, the system tackles portfolio optimization, so it’s not just about single loans but the whole picture. I compared a bunch of machine learning models to see which ones really nail the predictions. The results are clear ensemble based AI models leave traditional stats in the dust when it comes to accuracy and holding up under pressure. This new framework doesn’t just predict losses better—it actually helps banks allocate capital more wisely and meet tough regulatory standards. In short, it’s a serious upgrade for financial stability. Credit Risk Modelling and Probability of Default PD artificial intelligence, and machine learning all play a part in figuring out things like probability of default, loss given default, and exposure at default. You end up with a clearer picture of expected loss and how to optimize loan portfolios. Predictive analytics gets involved too, along with ensemble methods and deep learning. Then there’s Basel III, which sets the rules for financial risk management. Lately, people are also turning to alternative data and explainable AI to make better decisions and really understand what’s driving the numbers. In the end, it’s all about finding the best risk adjusted returns. Kunal Pramod Farkade "Artificial Intelligence–Based Credit Risk Evaluation for Optimizing Loan Portfolio" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101641.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101641/artificial-intelligence–based-credit-risk-evaluation-for-optimizing-loan-portfolio/kunal-pramod-farkade

In the age of generative AI systems and large language models LLMs , prompt engineering has become an essential ability. However, developing the best prompts is difficult for non expert users because it takes a lot of experience, trial and error iterations, and knowledge of model behavior. In addition to being time consuming and uneven between users, manual prompt development frequently falls short of utilizing best practices that have been identified via significant experimentation. With AI adoption accelerating across industries, there is a growing need for automated systems that can produce high quality prompts depending on user intent. Combining machine learning algorithms with Natural Language Processing NLP approaches offers interesting ways to automate prompt production, increasing the usability and productivity of AI systems for a range of user demographics. An automated prompt creation system is shown in this study that generates optimum prompts from basic user queries using sophisticated natural language processing NLP techniques such as BERT embeddings, GPT based transformers, and reinforcement learning. Intent classification, context extraction, fast template selection, parameter optimization, and quality assessment make up the systems multi stage pipeline. To generate structured prompts, we used a deep learning architecture that combined sequence to sequence models with bidirectional transformers to grasp user intent. The system examines effective prompt patterns from a carefully selected collection of more than 50,000 professionally written prompts in a variety of fields, such as question answering, data analysis, code development, and creative writing. Automatic prompt refining based on output quality feedback, domain specific optimization, multi turn conversation handling, and context aware prompt expansion are examples of advanced capabilities. Saloni Gautam "An Automated Prompt Generation System Using Deep Learning and Natural Language Processing" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101640.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101640/an-automated-prompt-generation-system-using-deep-learning-and-natural-language-processing/saloni-gautam

In the contemporary landscape of computer vision and affective computing, the ability of machines to perceive not only human identity but also psychological state is a cornerstone of advanced Human Computer Interaction HCI . While traditional surveillance and authentication systems focus exclusively on identity verification, they often ignore the contextual layer of human emotion, which is vital for applications ranging from personalized marketing to mental health monitoring. This research proposes a high performance, integrated framework for simultaneous Real Time Face Recognition and Emotion Detection. The system architecture employs a multi stage computational pipeline initial face localization is achieved via Haar Cascade Classifiers, identity recognition is processed through Local Binary Pattern Histograms LBPH , and affective state classification is performed by a deep Convolutional Neural Network CNN optimized for real time inference. Our proposed model tackles the limitations of high latency, cloud based architectures by utilizing localized edge processing, granting data privacy, and minimizing processing times. A hybrid dataset an identity matching custom facial repository and an emotion classification FER 2013 benchmark dataset was used to train and validate the model. The performance of the training set was recorded via stable frame rates 22 and 25 FPS on common consumer grade hardware, achieving recognition accuracy of 91.4 and emotion classification precision of 88.7 in the four core emotional states Happiness, Sadness, Anger, and Neutrality . Consequently, we can use classical texture based descriptors together with hierarchical deep learning features to form a solid and lightweight approach applicable in smart environments, interactive educational tools, and automated security protocols. Rushab Dhiraj Satfale "A Real-Time Facial Recognition and Emotion Detection Framework Using OpenCV and Pre-Trained Convolutional Neural Networks" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101639.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101639/a-realtime-facial-recognition-and-emotion-detection-framework-using-opencv-and-pretrained-convolutional-neural-networks/rushab-dhiraj-satfale

In the digital age we live in now, the amount of information available is rapidly increasing due to the rapid growth of online resources this makes finding knowledge easier than ever however, it also raises some very serious issues concerning plagiarism. Plagiarism, defined as taking or copying someone elses work without their permission, is becoming a serious problem for universities and colleges, research organizations, and businesses that rely on content as part of their product service. In the past, plagiarism detection relied heavily on exact matching techniques and the time consuming processes of manually comparing the suspected plagiarized material to source material, which often miss paraphrased or similar semantics. This proposed system will provide accurate and efficient plagiarism detection using Artificial Intelligence based methods such as Machine Learning and Natural Language Processing. The system will preprocess documents submitted by users to provide a cleaned document using tokenization, stop word removal, and normalization , and then extract relevant features meaningful linguistic patterns in the cleaned document before applying advanced similarity measurement algorithms and trained ML models to the extracted features to identify duplicate, paraphrased and contextually similar material. In contrast to traditional approaches, the proposed approach uses semantic analysis to derive meaning from the textual content, rather than just comparing words on the surface. The output of the system is a detailed report of the similarity of the input docu ments to documents that produced matches, with an accompanying percentage of plagiarism, to aid in determining the extent of plagiarism to assist users in assessing their respective submissions in terms of likely academic integrity violations. Khilendra Shivprasad Thakre "Adaptive Machine Learning System for Contextual Plagiarism Identification" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101638.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101638/adaptive-machine-learning-system-for-contextual-plagiarism-identification/khilendra-shivprasad-thakre

Employee Management and Payroll System Design, Implementation, and Performance Analysis Raj Shankar Katarpawar "Employee Management and Payroll System: Design, Implementation, and Performance Analysis" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101637.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101637/employee-management-and-payroll-system-design-implementation-and-performance-analysis/raj-shankar-katarpawar

Turning messy human writing into clean digital text sits at the heart of image analysis work. Because people write so differently some slant letters, others stretch or shrink them getting it right isn’t simple. Older techniques that rely on fixed rules tend to stumble when faces odd forms. Instead of forcing patterns, letting machines discover them works better here. A system built around layered networks studies raw ink marks without handcrafted shortcuts. Patterns emerge through repeated exposure, much like how eyes get used to scribbles over time. Digital neurons tune themselves to curves, angles, and blobs found in samples. No preset logic guides the process just gradual shaping by example after example. What once needed manual tuning now happens in the background, unseen but effective. The model grows sharper not by instruction, but by seeing more variations unfold. One way it works is by using the MNIST dataset to train and check results. To make images work better, they get resized then normalized. What happens next uses a CNN built with TensorFlow and Keras inside Python code. After setup, testing begins where success shows through correct guesses plus how often mistakes happen. When tested, the new CNN model beats older methods at spotting patterns correctly. Built on solid design, it handles paperwork scanning plus fills forms without hiccups. Learning from images gets easier because this setup uses neural networks in a smart way. Tough sorting jobs show how well layers inside the network adapt during use. Progress here opens doors for better reading of hand written notes down the line. Kartik Panchariya "Automatic Handwritten Character Recognition Using Convolutional Neural Networks for Efficient Image-Based Text Detection and Classification" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101636.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101636/automatic-handwritten-character-recognition-using-convolutional-neural-networks-for-efficient-imagebased-text-detection-and-classification/kartik-panchariya

This report describes a complete Face Recognition Attendance System based on AI. With this system, attendance will be taken automatically with the use of a camera and the latest technologies in Deep Learning. Currently, the traditional ways of taking attendance are limited by requiring large amounts of manual effort. The comprehensive AI based Face Recognition Attendance System will offer a single integrated solution that includes i Registration of a students face, ii Capture of live attendance through a camera, iii Automatic marking of attendance, iv Generation of attendance reports, and v Providing verification logs. The Face Recognition Attendance System has a comprehensive architecture which consists of using Convolutional Neural Networks CNN as the method of facial feature extraction and facial recognition, while preventing duplicate entries and handling unknown faces. The technology stack used for developing the Face Recognition Attendance System consists of React for the user interface, Node.js for the API server, Python for the Deep Learning components, and MySQL for database management. The implementation of the Face Recognition Attendance System uses a number of common Python libraries, including TensorFlow for training Deep Learning models, OpenCV for detecting faces and performing image processing, and NumPy for performing numerical calculations. The system can be divided into three main phases i Detecting a face using Haar Cascade Classifiers, ii Recognising a face using trained CNN models, and iii Logging the recognition to a secure database with a time stamp. The results from the experiments conducted at the school demonstrate an overall recognition accuracy of 94.2 when students were attendance in a classroom setting. The results also indicate that the FBAS can effectively manage errors such as unknown faces and duplicates through time locks. The research supports the findings. Prerna Binzade "An Efficient Facial Recognition Model Using Convolutional Neural Networks" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101635.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101635/an-efficient-facial-recognition-model-using-convolutional-neural-networks/prerna-binzade

This paper presents the development and evaluation of Finance Tracker, a web based personal finance management system designed to automate and streamline financial tracking, budgeting, and goal setting. Leveraging modern web technologies, the system offers seamless recording, monitoring, and analysis of financial transactions, ensuring scalability, reliability, and accessibility across various devices. Finance Tracker addresses the prevalent inefficiencies and fragmentation found in existing personal finance tools by unifying essential services such as income and expense logging, transaction categorization, and financial goal management. The system provides an intuitive graphical user interface, real time updates, and insightful reports, empowering users to make informed financial decisions. Our implementation successfully demonstrates core functionalities including robust user authentication, budget planning, transaction tracking, secure document storage, and efficient notification services. Through a comprehensive evaluation, Finance Tracker exhibits strong performance in data retrieval and synchronization, proving its feasibility as a scalable and efficient solution for digital finance management with significant potential for future expansion. Pratham Choudhari "Automated Expense Categorization and Anomaly Detection using Customized Deep Learning Models" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101634.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101634/automated-expense-categorization-and-anomaly-detection-using-customized-deep-learning-models/pratham-choudhari

Student feedback plays a crucial role in evaluating teaching effectiveness, course quality, and overall academic experience. However, manually analyzing large volumes of textual feedback is time consuming and prone to bias. With the rapid growth of educational institutions and digital feedback systems, there is a need for an automated and intelligent approach to analyze student opinions efficiently. This project presents a Student Feedback Sentiment Analysis system using Natural Language Processing NLP and Machine Learning ML techniques to automatically classify feedback into Positive, Negative, and Neutral categories. The proposed system processes raw student feedback text through several stages including text preprocessing, feature extraction using TF IDF, and sentiment classification using college safe machine learning algorithms such as Naive Bayes, Logistic Regression, and Support Vector Machine SVM . The dataset consists of real student feedback collected at the college level. Experimental results show that the proposed approach achieves high accuracy and reliable sentiment classification performance. The system helps educational institutions identify strengths and weaknesses in teaching methodologies, course structure, and infrastructure, enabling data driven decision making for academic improvement. Kalash Gadhave "Sentiment Analysis of Student Feedback Using Natural Language Processng and Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101633.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101633/sentiment-analysis-of-student-feedback-using-natural-language-processng-and-machine-learning/kalash-gadhave

The technological developments in deep learning have led to the development of very realistic face swap deepfake videos, which are a significant threat to digital security and trust. Deepfake videos, developed using methods such as Generative Adversarial Networks GANs , autoencoders, and neural face swap algorithms, have the capability to manipulate facial identities in a very realistic way, making it extremely difficult to manually identify them. The objective of this research work is to develop a comprehensive AI ML system for the identification of face swap deepfake videos using spatial and temporal facial feature analysis. The proposed system combines frame extraction, facial landmark detection, temporal inconsistency modeling, and a custom developed Convolutional Neural Network CNN model for binary classification of videos into REAL and FAKE categories. The latest preprocessing methods such as facial region cropping, normalization, and data augmentation are used to improve the robustness of the model and prevent overfitting. Temporal feature aggregation is also employed to detect the unnatural blending artifacts, irregular blinking rates, and frame distortions that are generally present in manipulated videos. The experimental evaluation is conducted by utilizing structured training, validation, and testing data. The proposed model performs well on the testing data with a high accuracy of 91.47 , very low Binary Cross Entropy loss, and an excellent Area Under the Curve AUC value of 0.92, which shows a strong classification ability. The performance comparison of the proposed model with the existing CNN and hybrid models confirms the superiority of the proposed model in generalization performance and detection robustness. The experimental result clearly shows that the combination of spatial and temporal feature analysis is an important factor in enhancing the effectiveness of deepfake detection. Future work includes the design of transformer models, real time systems, and adversarial robustness enhancement. Mohit Umendra Thakur "AI/ML System for Accurate Detection of Face Swap Deepfake Videos" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101632.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101632/aiml-system-for-accurate-detection-of-face-swap-deepfake-videos/mohit-umendra-thakur

The global real estate market, particularly within the rapidly urbanizing corridors of India, has long been characterized by extreme information asymmetry and a lack of pricing transparency. For the average home seeker or small scale investor, determining the fair market value of a rental property is often an exercise in guesswork which depends on broker evaluations and current market conditions. This research addresses these systemic inefficiencies by proposing and implementing an intelligent data driven framework for real estate valuation which connects advanced machine learning concepts with user learning needs. The framework includes a strong predictive system which operates through Random Forest Regression technology. The Random Forest algorithm provides an effective solution for urban housing challenges because it can understand the complex relationships between property features and local geographical patterns which include square footage and BHK configuration. Our model was developed using a complete data collection that included various Indian metropolitan areas and it went through an extensive preprocessing procedure which involved converting Furnishing and City data into categorical formats and creating a special Luxury Score assessment tool. This score measures the total effect of secondary facilities which include balconies and bathrooms to help the model differentiate between standard and premium listings with accurate statistical results. The research introduces a new method for prediction which replaces static prediction methods with dynamic simulation techniques. Users frequently encounter what if scenarios so we created an AI driven Feature Simulator. Users can change property features through this tool which provides interactive property variable manipulation. Rohit Uddhar "Predictive Analytics for Real Estate Valuation: A Random Forest Approach for High-Precision Rental Price Estimation in Indian Metropolitans" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101630.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101630/predictive-analytics-for-real-estate-valuation-a-random-forest-approach-for-highprecision-rental-price-estimation-in-indian-metropolitans/rohit-uddhar

in the business world we live in today companies use tools to look at numbers and make decisions just having a lot of data from transactions is not enough to really understand what is going on unless we can make sense of it and show it in a way that is easy to see this project is about creating a system for business intelligence using the adventure works dataset which is from a company that makes bicycles and is available in a simple format called csv we took the data put it into microsoft power bi then we cleaned it up made it look nice with power query we used some ways to organize the data like star schema relationships and cardinality management we figured out some numbers like revenue and profit we also looked at return rate how different customers are we used something called data analysis expressions or dax for short to calculate these numbers we made a dashboard that people can use to look at the data this dashboard shows what is happening each month it also shows where sales are coming from and how well products are doing it shows what customers are doing we used microsoft power bi to make this dashboard this study shows how business intelligence tools can turn raw organizational data into valuable insights that improve managerial decision making keywordsbusiness intelligence power bi data modeling dax kpi sales analysis dashboard. Sohail Ishak Kalut "Adventure Works Sales Analytics and Visualization Using Data Science & AI/ML" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Special Issue | Smart Innovations in Computer Science and Applications , March 2026, URL: https://www.ijtsrd.com/papers/ijtsrd101629.pdf Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/101629/adventure-works-sales-analytics-and-visualization-using-data-science-and-aiml/sohail-ishak-kalut