This study presents an automated system for identifying and classifying the growth patterns of Scenedesmus sp, a type of cyanobacteria. Different geometrical features associated with the species are used to detect, identify and classify cell growth patterns of the genera. The workflow proposed for segmentation comprises active contours and mathematical morphological operators and classification comprises a rule- based classifier or decision trees to delineate cell growth patterns as different morphological phases. The methods proposed have been compared against the gold standard – images segmented and labeled by human experts – and the results are found to be promising.

It is important to design an intelligent fire detection system based on the nervous system and particle optimization to find the fire time in the building. The use of intelligent methods in the fire detection system for data processing can reduce the risk of fire. In this paper, the original information of the firefighter network (FFN) is processed intelligently according to the possibility of the nervous system and the fire. In order to improve the quality of the system, the sensor data is applied to the generalized singular-value decomposition technique by analyzing the sound waves in the data. At the same time, the proposed neurological system was used for cell quality implantation new model particle mass optimization (PMO) using sushisen algorithms. In the simulation work, the data sensor is stored in the room by the network and is suitable for the target network. After that, compare the product to the traditional Multilayer Perceptron network. The simulation results represent a classic result.

With the introduction of Web 2.0; The users’ generated content like Reviews, Feedbacks, comments, Web Chats, Votes (Likes | Dislikes), Ratings (Stars Ratings) have grown exponentially over time and provided great opportunity for Research Scholars, Organizations, Businesses to mine this useful information and make use of it for variety of novel work like Recommendations. As the time passed, the information overloading problem arrives. There is lot of users’ generated data collected by Organizations and Businesses such as Reviews; How to extract useful information from these reviews and make a perfect recommendation is crucial. Traditional Recommender Systems (RS) considering a number of factors, such as product category, Stars Ratings, Location, user purchase history and other social factors. In this paper we have implemented the Recommender System as proposed by Lei et. al. [5]. The dataset was taken from yelp.com. Model Training is done by Latent Dirichlet Algorithm(LDA) along with Sentimental Dictionaries and Score computation methods as proposed by Lei et. al.[5]. The whole work has been implemented on MatLab (2016a) and experimental results were also analyzed.

As we know that MANET is formed by a number of mobile nodes and each node communicate with each other using bandwidth. In MANET batteries carries by each node have limited power, which in turn limiting the applications given by the MANET. Such limitations need the traffic to be evenly distributed among the mobile hosts. Otherwise, the nodes with heavy load can cause congestion, large delay and consume more energy, thus, increasing the cost of the network. In MANET, job completion becomes difficult, when massive load is given to the nodes with less processing capabilities and which do not have any resources to distribute the load. The possibility of imbalance of load is due to that the computing or processing power of the systems is non-uniform. There are situations where some nodes may be idle and some will be overloaded. A node which has high processing power finishes its own work quickly and is estimated to have less or no load at all most of the time. So, in the presence of under-loaded nodes keeps idle, the need for over-loaded nodes is objectionable. There are lots of routing approaches developed for load balancing in mobile ad hoc networks. In the proposed work, optimized Link State routing protocol (OLSR) will be used. It is a proactive link state routing protocol which uses Hello and topology control messages to discover and then deliver information throughout the MANET. The performance of OLSR will be improved by using Genetic algorithm in combination with Fuzzy logic. GA is an optimization technique that will used to improve the performance on the basis of natural selection and biological evolution. After applying these two approaches the code is simulated in MATLAB environment and thus, performance parameters of the MANET like Throughput, delay, energy consumption and Bit error rate will be determined.

Breast Cancer is the second most leading cancer among women in the world. Detecting the disease at the earliest and parallel treatment may significantly increase the survival of the victim. A clinical trial has made an attempt to evaluate the low risk called ductal carcinoma in situ (DCIS), a monitoring approach rather surgery. This paper implements a quantitative model for mining the gene expression of DCIS for early detection of breast cancer under active surveillance that offers a close monitoring for the signs of progression of breast cancer. The proposed work determines whether the low-risk DCIS can undergo active surveillance without degrading the quality of life when compared to the conventional treatments. Our research proposes a classification technique using quantitative model based SVM, a hybrid technique for analyzing the gene expression of low risk patients.

Cloud computing has offered services related to utility aligned IT services. Reducing the schedule length is considered as one of the significant QoS need of the cloud provider for the satisfaction of budget constraints of an application. Task scheduling in a parallel environment is one of the NP problems, which deals with the optimal assignment of a task. To deal with the favorable assignment of some task, task scheduling is considered as one of the NP problem. In this research work the jobs are distributed in a centralized environment. In Centralized environment every job request is forwarded to a central server. The central server passed the jobs to sub servers that are present with in the area of request. This has been performed by using distance formula. In our research work we reduce the energy consumption by each sub-server and it is possible by using formation of feedback queue. Job scheduling has been optimized on the basis of priority by using genetic algorithm Fuzzy logic also used for classification of the jobs to decide which job has been allotted to the system. Metrics namely, SLR, CCR (Computation Cost Ratio) and Energy consumption are used for the evaluation of the proposed work. All the simulations will be carried out in Cloud sim environment.

Proteins are molecular devices in the nanometer scale where biological function is exerted the building blocks of all cells in our bodies. DNA molecule is encoded in the dynamic process of life maintenance; replication, defense and reproduction are carried out by proteins. There are twenty natural amino acids whose frequency is higher and with the particular functions are forming polypeptide chains or proteins in different ways determined by the genetic code and limited by stereo chemical properties. Molecular Function is describes the tasks performed by individual proteins and can be broadly divided into twelve subcategories such as cellular processes, metabolism, DNA replication/modification, transcription/translation, intracellular signaling, cell-cell communication, protein folding/degradation, transport, multifunctional proteins, cytoskeletal/structural, defense and immunity, and miscellaneous functions. Biochemical reactions of cell breathing, oxygen and carbonic gas transport, food absorption, energy usage, energy storage, heat or cold physiological reactions, or any life process one can carry out by a protein or a protein complex. The primary structure of a protein referred to its complete covalent structure but it is more frequently interpreted as the sequence of amino acids of each polypeptide chain of which the protein is composed. All processes in a living organism have proteins are acting as the developed under the natural selection. All proteins functions are dependent on their structure which depends on physical and chemical parameters. The genome sequences make it more difficult to identify our target sequence to find the putative gene directly or DNA sequences containing the putative gene. The bioinformatics have been working together in a new area known as molecules, classical biological, physical, chemical, mathematical and informatics to allow a new level of knowledge about life organization.

This paper of bang-bang modulation of FACTS signals, developed a damping control scheme for Flexible Alternating Current Transmission System (FACTS) devices. The low frequency oscillations have mainly observed in power system because of the presence of high gain of exciters, operating the system under stressed conditions and the contingencies. The proposed control strategy of stabilizing controller has been tested with SVC and PSS in MATLAB/SIMULINK. The Sim-Power toolbox is used for detailed modeling of 400 KV, 700KM line, taken as an example. With the Power System Stabilizer and FACTS controllers, better damping is achieved. The Paper studies the comparative performance of SVC (Static Var Compensator) and Power system stabilizer (PSS) for the improvement of transient stability and damping control for Long Transmission Line System. Shunt FACTS devices play an important role in improving the transient stability, increasing transmission capacity and damping low frequency oscillations. For the implementation of this proposed work the Simulink Part under Matlab software is used.

Cloud computing has offered services related to utility aligned IT services. Reducing the schedule length is considered as one of the significant QoS need of the cloud provider for the satisfaction of budget constraints of an application. Task scheduling in a parallel environment is one of the NP problems, which deals with the optimal assignment of a task. To deal with the favorable assignment of some task, task scheduling is considered as one of the NP problem. In this research work the jobs are distributed in a centralized environment. In Centralized environment every job request is forwarded to a central server. The central server passed the jobs to sub servers that are present with in the area of request. This has been performed by using distance formula. Also to reduce the energy consumption by each sub-server is possible by using formation of feedback queue. Job scheduling has been optimized on the basis of priority by using genetic algorithm. Rules are set according to the priorities of the job then scheduling is done by using genetic algorithm. Fuzzy logic also used for classification of the jobs to decide which job has been allotted to the system. Metrics namely, SLR, CCR (Computation Cost Ratio) and Energy consumption are used for the evaluation of the proposed work. All the simulations will be carried out in CLOUDSIM environment.

Cloud computing has offered services related to utility aligned IT services. Reducing the schedule length is considered as one of the significant QoS need of the cloud provider for the satisfaction of budget constraints of an application. Task scheduling in a parallel environment is one of the NP problems, which deals with the optimal assignment of a task. To deal with the favorable assignment of some task, task scheduling is considered as one of the NP problem. In this research work the jobs are distributed in a centralized environment. In Centralized environment every job request is forwarded to a central server. The central server passed the jobs to sub servers that are present with in the area of request. This has been performed by using distance formula. Also to reduce the energy consumption by each sub-server is possible by using formation of feedback queue. Job scheduling has been optimized on the basis of priority by using genetic algorithm. Rules are set according to the priorities of the job then scheduling is done by using genetic algorithm. Fuzzy logic also used for classification of the jobs to decide which job has been allotted to the system. Metrics namely, SLR, CCR (Computation Cost Ratio) and Energy consumption are used for the evaluation of the proposed work. All the simulations will be carried out in CLOUDSIM environment.

Objective: Indian Government attempted to empower residents of India with a unique identity and a digital platform to establish their identity anytime and at any place by providing aadhaar card. The objective of this study is to find out whether this identity can be forged or not. Materials and Methodology: Photocopies of the samples of both printed and posted cards were taken. Various measurements of various parameters were done using scales. Results: When the results of all the samples were compared, it was observed that variations were present in between the cards printed by oneself and posted through the authority. Variations in dimension of photographs, lengths of bar code, dimensions of card etc. were observed. Conclusion: From the present study it can be concluded that no strict pattern or guidelines are followed while printing aadhaar cards of the individuals and it is suggested that the authorities should make standards so that these cannot be easily forged. It is suggested to install aadhaar card reader devices wherever aadhar card is asked as an identity proof.

Objective: Indian Government attempted to empower residents of India with a unique identity and a digital platform to establish their identity anytime and at any place by providing aadhaar card. The objective of this study is to find out whether this identity can be forged or not. Materials and Methodology: Photocopies of the samples of both printed and posted cards were taken. Various measurements of various parameters were done using scales. Results: When the results of all the samples were compared, it was observed that variations were present in between the cards printed by oneself and posted through the authority. Variations in dimension of photographs, lengths of bar code, dimensions of card etc. were observed. Conclusion: From the present study it can be concluded that no strict pattern or guidelines are followed while printing aadhaar cards of the individuals and it is suggested that the authorities should make standards so that these cannot be easily forged. It is suggested to install aadhaar card reader devices wherever aadhar card is asked as an identity proof.

In the past many studies have been conducted to estimate age, sex, stature, etc. of an individual from footprints. Footprint is one important evidence which cannot be erased completely since “it needs to go somewhere to do something”. In present study, inked footprints of the individuals of Himachal Pradesh and Delhi were studied to get an idea of the basic differences between the footprints of the two communities. Measurements of various angles and lengths were performed using protectors and scales. Various parameters were set and analyzed. It was observed that parameters foot breadth, foot length, alpha angle, etc. gave good significant results whereas first toe length,phalange marks and foot index, etc. gave non- significant results when the two populations were compared. Various statistical formulas were applied and it was observed that, 11 out of 25 parameters gave significant results. This study suggests that using these 11 significant parameters, an expert can get an estimate of whether the footprint found at any crime scene belongs to Delhi population or Himachal Pradesh population.