Aluminum alloys have been attracted by several engineering sectors due to their excellent strengthweight ratio and corrosion resistant properties. These are categorized into 1, 2, 3, 4, 5, 6, 7and 8xxx on the basis of alloying elements. Among these 6xxx series contains aluminum–magnesium–silicon as alloying elements and are widely used in extruded products and automotive body panels. The major advantages of these alloys are good corrosion resistance, medium strength, low cost, age hardening response no yield point phenomenon and Ludering. 6xxx series alloys generally have lower formability than other aluminum alloys which restrict their utilization for wide applications. Keeping in view of the shortcomings in the set of mechanical properties of 6xxx series the efforts were made to improve the tensile strength and toughness properties through age hardening. In present study heat treatment cycles were studied for 6061 aluminum alloy. Three different age hardening temperatures 160, 200 and 240oC were selected. The obtained results showed that 17.26, 7.69, and 10.51% improvement in tensile strength, toughness and hardness respectively was achieved with solution treatment at 380oC followed by an aging 240oC. Microstructural study revealed that substantial improvements in the mechanical properties of 6061 aluminum alloy under heat treatment were achieved due to precipitation of Mg2Si secondary phase.

Apneic-event based sleep disorders are very common and affect greatly the daily life of people. However, diagnosis of these disorders by detecting apneic events are very difficult. Studies show that analyzes of airflow signals are effective in diagnosis of apneic-event based sleep disorders. According to these studies, diagnosis can be performed by detecting the apneic episodes of the airflow signals. This work deals with detection of apneic episodes on airflow signals belonging to Apnea-ECG (Electrocardiogram) and MIT (Massachusetts Institute of Technology) BIH (Bastons’s Beth Isreal Hospital) databases. In order to accomplish this task, three representative feature sets namely classic feature set, amplitude feature set and descriptive model feature set were created. The performance of these feature sets were evaluated individually and in combination with the aid of the random forest classifier to detect apneic episodes. Moreover, effective features were selected by OneR Attribute Eval Feature Selection Algorithm to obtain higher performance. Selected 28 features for Apnea-ECG database and 31 features for MITBIH database from 54 features were applied to classifier to compare achievements. As a result, the highest classification accuracies were obtained with the usage of effective features as 96.21% for Apnea-ECG database and 92.23% for MIT-BIH database. Kappa values are also quite good (91.80 and 81.96%) and support the classification accuracies for both databases, too. The results of the study are quite promising for determining apneic events on a minute-by-minute basis.

Wavelet based image processing techniques do not strictly follow the conventional probabilistic models that are unrealistic for real world images. However, the key features of joint probability distributions of wavelet coefficients are well captured by HMT (Hidden Markov Tree) model. This paper presents the HMT model based technique consisting of Wavelet based Multiresolution analysis to enhance the results in image processing applications such as compression, classification and denoising. The proposed technique is applied to colored video sequences by implementing the algorithm on each video frame independently. A 2D (Two Dimensional) DWT (Discrete Wavelet Transform) is used which is implemented on popular HMT model used in the framework of Expectation-Maximization algorithm. The proposed technique can properly exploit the temporal dependencies of wavelet coefficients and their non-Gaussian performance as opposed to existing wavelet based denoising techniques which consider the wavelet coefficients to be jointly Gaussian or independent. Denoised frames are obtained by processing the wavelet coefficients inversely. Comparison of proposed method with the existing techniques based on CPSNR (Coloured Peak Signal to Noise Ratio), PCC (Pearson’s Correlation Coefficient) and MSSIM (Mean Structural Similarity Index) has been carried out in detail.The proposed denoising method reveals improved results in terms of quantitative and qualitative analysis for both additive and multiplicative noise and retains nearly all the structural contents of a video frame

Collection and delivery of laundry is an important process in the laundry business. The laundry businesses have adopted diverse models such as over the counter collection/delivery, online booking etc. The laundries are collected or delivered from customers’ doorstep or from customers’ desired location at a convenient time. In this paper, business process re-engineering concept has been incorporated to improve the collection and delivery process of laundry using RFID (Radio-Frequency Identification) tagging and Automated Laundry Collection Drop Box. The Devil’s Quadrangle has been used as a tool for evaluation. The proposed model will result in reduction in cost, time and improvement in service quality. It ultimately results in customers’ loyalty, economic efficiency and gain of a competitive advantage over competitor. Other advantages for laundry business include automatic collection and delivery, enhanced customer convenience, enhanced flexibility and industry economic savings, enhanced customer satisfaction and decreased labor work. In the proposed automated laundry collection model, reputed laundry businesses will make a consortium and outsource collection and delivery process to a courier company. Different collection and delivery options are proposed in the model.

Growing E-Participation services compel democratic governments to re-examine their E-Governance service system readiness assessment models with respect to their usability, effectiveness and participatory governance. In practice, the open government data, E-Participation initiatives, and their integration levels, are essential ingredients of E-Governance service systems. The debate about what constitutes EGovernance success, their quantifiable and qualitative variables, their divergent socio-technical dependencies, etc. is still on-going. E-Governance has emerged as a large-scale socio-technical and human centered problem space. We, therefore, assert that HCI (Human Computer Interaction) based system modeling and its supporting socio-technical tools and technologies can effectively be used to design and develop E-participatory governance systems. The research gap analysis highlights a stark paradox by showing a weak correlation between UN (United Nation) provided E-Participation Index and a perceived governance index. As a result, the authors in this paper propose an exclusive human centered and socio-technical design of E-GovSSRA (E-Governance Service System Readiness Assessment) framework by redefining E-Participation model in HCIs CSCW (Computer Supported Cooperative Work) perspective that aimed to present relatively strong correlation with a perceived governance index.

Achieving and maintaining quality values are indispensable for attaining organizational and customer satisfaction. This research investigates different aspects of operationalize quality culture and factors affecting the quality of building construction in under developed countries like Pakistan. A qualitative and quantitative survey was circulated among different stakeholders including Clients, Consultants and Contractors to assess the level of the contractor’s performance, the project monitoring and controlling techniques, proper health and safety requirements, client satisfaction and workers experience in construction industry projects. The practice of professional quality management in building projects is increasing, however, many flaws and negligence are still found in local practices. This analysis also indicates that political and socio-economic factors play a significant role in maintaining the quality level in local industry. Therefore, the allocation of sufficient resources, proper training of workers, and recruitment of quality control staff and the use of advanced technologies are recommended for proper implementation of QMS (Quality Management System).

Autonomous navigation of the vehicles or robots is very challenging and useful task used by many scientists and researchers these days. By keeping this fact in mind, an algorithm for autonomous navigation of mobile robot in outdoor environment is proposed. This navigation track consists of colored border containing obstacles and some unplanned surfaces along with some specific points for GPS (Global Positioning System) alarms. The main goal is to avoid colored border and obstacles. For the vision problem webcam is used. First the colored border is detected by using OpenCV library by following HSI (Hue Saturation Intensity)technique. The Canny edge algorithm is used to find both edges of the border, then for detecting straight lines on both sides of track, Hough transformation is used. Finally, the closest border line is detected and its center point is calculated for which the mobile robot has to steer to avoid it. Second step is to avoid the obstacles, which is done by LRF (Laser Range Finder), first the range of LRF is defined, because not all obstacles have to be avoided, only those obstacles are detected and avoided which are in specified range as defined before, and finally GPS receiver is used to make alarms at some specific points. As a result, a successful navigation of the mobile robot in the outdoor environment is implemented.

This study investigated the effects of steel fibers on the fresh and hardened properties, and heat of hydration of concrete containing FA (Fly Ash). A total of 192 samples were cast comprising cubes, cylinders, and prisms, for six concrete mixes with varying contents of steel fibers by volume and a fixed content of FA i.e. 15% by weight of cement. The semi adiabatic setup was used to monitor temperature rise due to the heat of hydration in the concrete mixes for fourteen days. The use of FA increased workability, and decreased early compressive strength, tensile strength and heat of hydration of concrete. However, an increase in the compressive strength of FA concrete was observed by the addition of steel fibers up to 0.9% whereas a consistent increase in the splitting tensile strength and modulus of rupture was observed with the addition of the steel fibers from 0.4-1.8%. Further the test results showed that increasing steel fibers content decrease the evolution of heat due to hydration. It was concluded that the FA concrete with steel fibers can be used in precast industry and mass construction projects due to the improved mechanical properties and lower heat of hydration.

The problem of delay in construction industry is a regular phenomenon worldwide, and construction industry of Pakistan has no exception, particularly in highways projects. Delay can be described as the extension of time to complete the construction project. The aim of this paper is to identify main causes of delays in highway projects of Pakistan, and to determine mitigating measures for the identified causes. The research method of this study is based on literature review, questionnaire survey and semi structured interview. From in-depth literature review, twenty-six common causes of delay were found. A questionnaire survey was carried out among construction professionals of highway projects. The causes of delay in highways projects were ranked referring to their Mean values. A semi structured interview was carried out to determine mitigation measures for the top ten causes of delays. The data gathered from questionnaire survey was analyzed using SPSS (Statistical Package for the Social Sciences) while, data collected through semi structured interviews was analyzed using Nvivo software. The findings of this study are expected to be useful for construction parties, to mitigate the delays in highway construction projects of Pakistan.

The aim of this research is to develop a decentralized communication system of multiple robots which have capability to communicate and coordinate with each other, by which all robots work individually while keeping connectivity among them. Decentralized communication between robots is the main part of this project. This type of communication shows great potential in many aspects. A decentralized system is the combination of both intelligent and decision making inspired from nature. To meet this object two identical robots are developed which successfully communicate with each other to complete an assigned task. A single task is given to both robots; to find specific object/target location. Once the target is found by any of the robot that robot will then communicate with second robot to guide the path of object/target location. Guiding path to the second robot is the challenging task as discussed in this paper. The Robots use Bluetooth devices to calculate and extract the RSSI (Received Signal Strength Indication)values for communication purpose.Both robots work together as a team. By working in communicated way their time is reduced to achieve the task and create synergy. Any task could be easily attained in team work than by the work of the single individual robot.

The insufficiency of energy resources, increased cost of generation and rising load demand necessitate optimized economic dispatch. The real world ED (Economic Dispatch) is highly non-convex, nonlinear and discontinuous problem with different equality and inequality constraints. In this research paper, a novel hybrid MFO-SQP (Moth Flame Optimization with Sequential Quadratic Programming) is proposed to solve the ED problem. The MFO is stochastic searching algorithm minimizes by random search and SQP is definite in nature that refines the local search in vicinity of local minima. Proposed technique has been implemented on 6, 15 and 40 units test system with different constraints like valve point loading effect, transmission loss, prohibited zones, generator capacity limits and power balance. Results, obtained from proposed technique are compared with those of the techniques reported in the literature, are proven better in terms of fuel cost and convergence.

Surface water supplies are gradually becoming short in arid and semi-arid regions of the world. Thus, assessment of groundwater quality for crop use appears to be very essential for management and utilization of precious natural water resources. This study reports the water quality of 52 hand pumps and one tubewell located in the most remote areas of desert region, viz. Islamkot and Mithi talukas of district Tharparkar. The water samples were collected during April 2016 (just before the start of rainy season). The water samples were analyzed for EC (Electrical Conductivity), pH, CO32-, HCO3-, Cl-, Ca2+, Mg2+ and Na+ concentration. The SAR (Sodium Adsorption Ratio) and RSC (Residual Sodium Carbonates) were estimated using their respective formula. The categorization of water samples based on their soluble salt content clearly revealed that the water bodies of majority (65%) of areas were hazardous, while 25% areas were marginal. Thus, only 11% water samples of the area under study had useable irrigation water. Because of SAR and RSC the majority (89 and 77%, respectively) of water samples were found to be free from the sodicity hazard. The study concluded that salinity, and not sodicity was the major threat to the area under irrigation with these water bodies. It is, therefore, suggested that the salinity tolerant crops and their genotypes may be used in this area to sustain crop production.

Over the past decennium, Wi-Fi fingerprinting based indoor localization has seized substantial attention. Room level indoor localization can enable numerous applications to increase their diversity by incorporating user location. Real-world commercial scale deployments have not been realized because of difficulty in capturing radio propagation models. In case of fingerprinting based approaches, radio propagation model is implicitly integrated in the gathered fingerprints providing more realistic information as compared to empirical propagation models. We propose ensemble classifiers based indoor localization using Wi-Fi fingerprints for room level prediction. The major advantages of the proposed framework are, ease of training, ease to set up framework providing high room-level accuracy with trifling response time making it viable and appropriate for real time applications. It performs well in comparison with recurrently used ANN (Artificial Neural Network) and kNN (k-Nearest Neighbours) based solutions. Experiments performed showed that on our real-world Wi-Fi fingerprint dataset, our proposed approach achieved 89% accuracy whereas neural network and kNN based best found configurations achieved 85 and 82% accuracy respectively.

Accurate segmentation of anatomical organs in medical images is a complex task due to wide interpatient variability and several acquisition dependent artefacts. Moreover, image noise, low contrast and intensity inhomogeneity in medical data further amplifies the challeng. In this work, we propose an effective yet simple algorithm based on composite energy metric for precise detection of object boundaries. A number of methods have been proposed in literature for image segmentation; however, these methods employ individual characteristics of image including gradient, regional intensity or texture map. Segmentation based on individual featres often fail for complex images, especially for medical imagery. Accordingly, we propose that the segmentation quality can be improved by integrating local and global image features in the curve evolution. This work employs the classic snake model aka active contour model; however, the curve evolution force has been updated. In contast to the conventional image-based regional intensity statistics, the proposed snake model evolves using composite image energy. Hence, the proposed method offers a greater resistance to the local optima problem as well as initialization perturbations. Experimental results for both synthetic and 2D (Two Dimensional) real clinal images are presented in this work to validate the performance of the proposed method. The performance of the proposed model is evaluated with respect to expert-based manual ground truth. Accordingly, the proposed model achieves higher accuracy in comparison to the state-of-the-art region based segmentation methods of Lankton and Yin as reported in results section.

The linguistic corpus of Sindhi language is significant for computational linguistics process, machine learning process, language features identification and analysis, semantic and sentiment analysis, information retrieval and so on. There is little computational linguistics work done on Sindhi text whereas, English, Arabic, Urdu and some other languages are fully resourced computationally. The grammar and morphemes of these languages are analyzed properly using dissimilar machine learning methods. The development and research work regarding computational linguistics are in progress on Sindhi language at this time. This study is planned to develop the Sindhi annotated corpus using universal POS (Part of Speech) tag set and Sindhi POS tag set for the purpose of language features and variation analysis. The features are extracted using TF-IDF (Term Frequency and Inverse Document Frequency) technique. The supervised machine learning model is developed to assess the annotated corpus to know the grammatical annotation of Sindhi language. The model is trained with 80% of annotated corpus and tested with 20% of test set. The cross-validation technique with 10-folds is utilized to evaluate and validate the model. The results of model show the better performance of model as well as confirm the proper annotation to Sindhi corpus. This study described a number of research gaps to work more on topic modeling, language variation, sentiment and semantic analysis of Sindhi language.

The intent of study is to establish a criterion for the experimental setup of rasterstereography, one that is more efficient, simple, accurate and precise to examine and analyse the curvature of the object or the subject. Firstly, the setup is needed to be calibrated and for this purpose we considered a reference plane, eleven cylinders of different diameter ranging from 30-119mm were used for calibration of curvature maps of cylinders and cylindrical objects through the regression line. Further this model was tested on subjects and for that we reckoned cylindrical body parts of boys and a total of 30 college students were involved as subjects in this process. The body parts to be measured had curvature like cylinders of different diameters ranging from 42-120mm. The distortion of raster grid was observed, quantified and recorded with the help of different tools and results were established. The regression line was obtained between the measured (x) and computed (y). The standard error of the cylindrical object was 0.04 and that of cylindrical body parts of subjects was 0.0407. This technique was validated through the coefficient of correlation for objects and subjects which was found to be 0.99982 and 0.999141 respectively. Accuracy and Precision were also calculated for this model, which were 99.60% accurate and 99.49% precise. Curvature maps were found more than 99%. This technique is inexpensive, reliable, reproducible and may be installed easily in hospitals to examine appraise body shape, composition and deformities of young men.

Modern Telecom Sector is eventually facing exceptionally tough challenges because of continuous and unexpected increase in power density requirement for the communicating machinery and equipment. To fulfil the power requirements for the equipment, a significant architecture and an optimal technique must be introduced. In this paper, a microcontroller-based optimization use of power-density has been carried out. Meeting above requirements, various equipment and electronic devices are employed. We have designed a microcontroller-based system via PROTEUS Virtual System Modeling to acquire efficient and effective results. The main focus of our work is to supply the power to Telecom equipment in meantime. The power is feeding on batteries and DG (Diesel Generator) set, depending on the condition of the power requirements. The changeover operations are performed by different relays, which are dully programmed via a microcontroller in Keil software. The power capacity of Telecom ((Telecommunication) equipment is ranged from 39-48 Volts DC. The rectification process is done by switch mode rectifiers instead of linear rectifiers. Because the switch-mode rectifier technology has brought fabulous improvements in power density as compared to linear rectifiers. This is done via simulation of the smart switch in PROTEUS software. The outcomes of the proposed system are cost effective in terms of fuel consumption of DG.

Geotechnical investigation is one of the major steps in the safe and economic design of foundation for any structure. This requires some soil parameters to be established. CI (Compression Index) is one of these parameters. The stability of a foundation is not fully justified as long as the magnitude of settlement is unknown. The problem arises when the value of CI is needed badly and a consolidation test is set up for this purpose which consumes almost 3 days for its completion provided that the assembly would not be disturbed. Little amount of disturbance can cause serious error in further calculations and plotting of data. Undisturbed soil sample is the primary demand of consolidation test which is a tough job for a person having not been experienced very much in the fieldwork. In order to overcome these complexities, the researchers have established various correlations between compression index and some basic soil properties like Atterberg limits, void ratio, natural moisture content and OMC (Open Moisture Content), as they are simple to be determined and takes small amount of time. This research has been conducted on soil samples collected from a single spot at an interval of 5ft depth for the sake of validation of a suitable correlation for Bannu District, KPK (Khyber Pakhtunkhwa), Pakistan so that the determination of compression index becomes simple and convenient.

Slotted circular printed layered patch antenna is designed, simulated and fabricated for 5G (Fifth Generation) wireless communication applications. The antenna consists of slots in the main radiating circular patch element for miniaturizing the size of the radiating element and providing dual band radiation characteristics. The feed line is separated on bottom substrate layer with EBG (Electromagnetic Band-Gap) embedded for enhancing the gain characteristics of the antenna. Superstrate layer is also used for improving the gain of the antenna where the distance from the radiating antenna element is optimized for maximizing the impedance bandwidth and radiation characteristics. The feed realization and impedance matching of the radiating slotted circular patch antenna is done by inducing slot at the middle ground plane of the slot embedded circular patch antenna system. The proposed configuration provides power radiation gain values of more than 5 dB for the Ka band of communications, whereas the impedance bandwidth of the antenna is verified for the dual resonances at 27.5 and 28.5 GHz. Dual band radiation characteristics are attained by embedding and optimizing the slot length and width in the circular patch radiator element that is placed on the upper face of the substrate RT Rogers Duroid 5880 layer. The length of the microstrip feed line embedded in the lower layer of the substrate is optimized for providing required bandwidth characteristics for the dual frequency point radiations. The antenna configuration is designed, modeled and simulated in CST (Central Standard Time) Microwave studio. The antenna is fabricated and measured vs simulated frequency response, gain patterns and current density plots are presented for the verification of antenna operation in the desired frequency bands.

Image processing techniques are widely used for the detection and classification of diseases for various plants. The structure of the plant and appearance of the disease on the plant pose a challenge for image processing. This research implements SVM (Support Vector Machine) based image-processing approach to analyze and classify three of the rice crop diseases. The process consists of two phases, i.e. training phase and disease prediction phase. The approach identifies disease on the leaf using trained classifier. The proposed research work optimizes SVM parameters (gamma, nu) for maximum efficiency. The results show that the proposed approach achieved 94.16% accuracy with 5.83% misclassification rate, 91.6% recall rate and 90.9% precision. These findings were compared with image processing techniques discussed in review of literature. The results of comparison conclude that the proposed methodology yields high accuracy percentage as compared to the other techniques. The results obtained can help the development of an effective software solution by incorporating image processing and collaboration features. This may facilitate the farmers and other bodies in effective decision making to efficiently protect the rice crops from substantial damage. While considering the findings of this research, the presented technique may be considered as a potential solution for adding image processing techniques to KM (Knowledge Management) systems.

Image processing techniques are widely used for the detection and classification of diseases for various plants. The structure of the plant and appearance of the disease on the plant pose a challenge for image processing. This research implements SVM (Support Vector Machine) based image-processing approach to analyze and classify three of the rice crop diseases. The process consists of two phases, i.e. training phase and disease prediction phase. The approach identifies disease on the leaf using trained classifier. The proposed research work optimizes SVM parameters (gamma, nu) for maximum efficiency. The results show that the proposed approach achieved 94.16% accuracy with 5.83% misclassification rate, 91.6% recall rate and 90.9% precision. These findings were compared with image processing techniques discussed in review of literature. The results of comparison conclude that the proposed methodology yields high accuracy percentage as compared to the other techniques. The results obtained can help the development of an effective software solution by incorporating image processing and collaboration features. This may facilitate the farmers and other bodies in effective decision making to efficiently protect the rice crops from substantial damage. While considering the findings of this research, the presented technique may be considered as a potential solution for adding image processing techniques to KM (Knowledge Management) systems.