The use of flux during welding is important because it prevents the formation of oxides thereby giving a better profile to the weld. In this study, nano- flux powder (CaO) developed from agrowastes (eggshell) and commercial flux powder were used during Metal Inert Gas (MIG) Welding. Materials prepared and welded were galvanized, stainless and mild steel plates and rods of 50 x 50 x 10 mm. The SEM and EDX of the fluxes were carried out while the welded joints of each samples were subjected to tensile, hardness and surface morphology tests using SEM. The high volume of 57.10% Iron and 29.45% Calcium respectively confirmed that the fluxes were Iron and Calcium Oxides suitable as fluxes for the welding. The mechanical properties of the joints proved better in nano flux than the commercial and when no flux applied.

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Essential additives, such as fibers, are widely used to improve the mechanical properties and performance of concrete. Fibers can be added to concrete in a mono or hybrid form of both metallic and non-metallic type. Although benefits of hybrid fibers addition to concrete are established in the literature, the bond stress slip response of embedded reinforcing steel in hybrid fiber reinforced concrete is not thoroughly studied. In this study, the bond stress-slip behavior of reinforcing steel bars embedded in concrete containing hooked end steel fibers and polypropylene fibers is assessed by carrying out pull-out tests. The variables considered in this study include polypropylene fiber volume (i.e. 0.1% and 0.2%), hooked end steel fiber volume (i.e. 0.5% and 1%), and the diameter of embedded reinforcement bars (i.e. 10 mm and 12 mm). The experimental results indicate that adding hybrid fibers of 0.1% polypropylene and 1% hooked end steel fibers yield the highest bond strength and hence the highest reduction in the embedded (development) length. The addition of hybrid fibers to concrete also improved the toughness of concrete and increased the slip measurements prior to failure of the bond between rebar and concrete.

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Energy plays an important role in a country’s development. Traffic energy is one of the alternative energies being investigated worldwide. Over the years, investigations are being carried out to improve the functionality and efficiency of various types of devices used in traffic energy harvesting. There are still questions on the possible impact these traffic energy harvesters impose on vehicles and users. However, there is a limited study on the impact of traffic energy harvesters on vehicles and users. A detailed investigation of the possible impact of traffic energy harvesters is necessary to identify and mitigate the challenges which would help promote this promising alternative energy in the future. In this paper, a MATLAB simulation was carried out to investigate the impact of a rack-and-pinion based speed bump on vehicles and users in comparison with that of a conventional speed bump, in terms of its fuel consumption rate, impact on vehicle suspension, and ride comfort. The investigation revealed that power bumps do have negative influences on vehicles’ performance compared to that of conventional speed bumps.

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A different way to reduce fluctuations in the reactivity calculation using the exponential filter and the inverse point kinetics equation is shown. The reactivity is calculated using the Boolean rule for different time steps, the neutron density is supposed that contains Gaussian noise around of the mean values. There are four terms of convolution sum between the nuclear density population and the impulse response. The convolution sum represents a finite impulse response filter. The different numerical experiments show that it is possible to reduce the fluctuations using the proposed method.

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In recent years, the use of surveillance cameras is increasingly recommended and they have been installed in many places. Snowy conditions at the time of an accident were associated with the problem that cars and accident circumstances become difficult to discern in images shot during snowfall. Previous techniques proposed methods for elimination of noise caused by snow using image shift or dedicated filters for the elimination of snowfall in video. However, these are associated with issues such as inability to cope with heavy snowfall or moving objects fading from view or being hard to discern. The present study proposes a method for snowfall noise elimination by extracting moving objects using the travel and the size of the moving object region between continuous frames, shaping a moving object using a convex hull algorithm, and compositing images while using the difference mask image excluding the moving object area. By distinguishing between falling snow and other moving objects, we can prevent objects other than snowfall becoming invisible. In addition, the convex hull can prevent to get out of shape of moving objects other than snowfall. In order to confirm the effectiveness of the proposed method by experiments, we used a video in which cars actually run in a snowfall environment. As shown in the experimental results, it can be confirmed that the snow grains are removed and the shapes of the cars in the image are kept well.

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Supplying and sharing power with grid has become one of the most wanted photovoltaic applications (PV). Moreover, PV based inverter and DC to DC converters are getting more attention in recent days mainly in remote areas where connection to the grid is technically not possible. Power generation by Photovoltaic is free and reliable. This paper presents the novel technique for maximum-power point tracking based on perturb and observe algorithm of photovoltaic (PV) energy conversion system. In order to obtain the maximum power extracted from the PV array, usually two parameters are considered, namely solar irradiation and temperature, most of the research work has been carried out by considering these two parameters. The proposed technique gives optimum utilization of PV array and enhances the applications of PV systems for both stand alone and grid connected systems. The study has been carried out in the MATLAB-Simulink environment. And also validation of the simulated results with the theoretical results shows proper matching. The results obtained from the simulation of the system are very much satisfactory. It is found that PV fed inverter system is working better.

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The design and analysis procedures of signalized intersections depend on several factors including the base saturation flow rate. The Highway Capacity Manual (HCM) assumes a base saturation flow rate of 1900 passenger car/hour/lane (PCPHPL) for areas with population of more than or equal 250,000 and 1750 PCPHPL for areas with population of less than 250,000. This research aimed at determining the base saturation flow rate in Jordan and Kuwait based on field data collected from 60 signalized intersection approaches. The methodology was based on the direct field measurement of saturation flow rate and its main influencing factors. The HCM standard procedure was followed in the field data collection and results showed that the HCM base saturation flow rate value of 1900 PCPHPL is not suitable for Jordan and Kuwait. The study recommends a value of 2050 PCPHPL for Jordan and 2100 PCPHPL for Kuwait, while a value of 2075 PCPHPL may be used for other Middle Eastern countries that do not have field measured values. The saturation flow rate was found to be significantly affected by the speed limit, lane marking, city, and location (CBD/ Non-CBD) at 95 % confidence. On the other hand, the saturation flow rate was found not significantly affected by the number of lanes, time period, traffic volume, land use, area type, and development density at 95 % confidence.

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Motivated by the looming radio frequency (RF) spectrum crisis, this paper aims at demonstrating that optical wireless communication (OWC) has now reached a state where it can demonstrate that it is a viable and matured solution to this fundamental problem. In particular, for indoor communications where most mobile data traffic is consumed, light fidelity (Li-Fi) which is related to visible light communication (VLC) offers many key advantages, and effective solutions to the issues that have been posed in the last decade. This paper discusses all key component technologies required to realize optical cellular communication systems referred to here as optical attocell networks. Optical attocells are the next step in the progression towards ever smaller cells, a progression which is known to be the most significant contributor to the improvements in network spectral efficiencies in RF wireless networks. In this paper we analyzed the Li-Fi system using an optisystem simulation tool. In this analysis, we considered two propagation models. In a LOS propagation model in the receiving end, we can regenerate approximated transmitted signal.

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Pakistan currently has the largest percentage of young people in its history that makes Pakistan one of the youngest country in the world and second in Asia Pacific region. To understand the macro level pattern of daily life activities for everyone can reveal significant information about people of a particular region. This information at the persons’ own end can be used to adapt a desirable, more healthy and smart options to plan further. On the other hand this information if used by mass planning and governments to promote and plan future strategies in wide range. This study entangles a case study for the daily life activities of Pakistani peoples. In Pakistan there is no such platform exists where people can understand the life pattern of their daily life activities with respect to time and location. We used dynamic flowing bubble graph technique (Force Directed Graph) and scatter plots to observe and analyse human daily life activities. We used 20 volunteers of age group between 19 to 29 years residents of Islamabad/ Rawalpindi. We modeled spatial and temporal features of data by catering 18 distinct daily life activities of each person. A dataset generated with 6 attributes having 709 daily life activity instances of volunteers. This comprises a web based application coupled with a mobile application to represent the human daily life activities using force-directed graph. Results shows the desired offline analysis of Pakistani peoples’ daily life activities.

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We present results of our calculations on the optical properties of the freestanding (2,2) singled-walled boron nitride nanotube (SWBNNT) using the density functional theory (DFT) and random phase approximation (RPA). Previous study shows that freestanding (2,2) SWBNNT holds a narrow band gap of 3.01 eV. Then, our optical calculations exhibit that freestanding (2,2) SWBNNT generates the main absorption peaks are in the ultraviolet (UV) energy ranges. Furthermore, the freestanding (2,2) SWBNNT can absorb light at longer wavelengths. It starts from the visible light until the ultraviolet type C (UVC). These findings offer a chance that material can be applied as a photocatalyst.

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Algorithm visualization which is a form of high-level dynamic visualization of software that uses user interface techniques to portray and monitor the computational steps of algorithms. Moreover, algorithm visualization systems are also useful tools in algorithm engineering, particularly at several stages during the design, implementation, analysis, tuning, experimental evaluation, and presentation of the algorithms process. Algorithms are a captivating use case for visualization. It does not simply fit data to a chart to visualize an algorithm, there is no main data set. Rather there are consistent principles that depict conduct. This is because algorithm visualizations are so uncommon, as designer’s experiment with novel forms to better communicate. Algorithm visualization (AV) uses graphics to portray an algorithm's actions. AV holds the promise of helping computer science students understand algorithms more effectively and in more prominent profundity. The purpose of this study is to design a system for sorting algorithm visualization and implement the system.

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Image de-noising is an important part in every image processing techniques. At the same time it can be considered as one of the primary challenges in image processing and computer vision. This paper describes wavelet thresholding based de-noising technique for color images. In this method the optimal threshold is determined using NeighShrink thresholding method with Stein’s unbiased risk estimate (SURE). Mean square error (MSE) and peak signal to ratio (PSNR) are used for the evaluation of image quality after de-noising.

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Applying the methods of computational mathematics in terms of specific optimal operational indices of a reused mine working makes it possible to reduce resource intensity of the operations performed at that stage. However, the obtained results are hard to interpolate with respect to the whole mine working network. The problem is aggravated when mining and geological conditions of mine working drivage differ considerably within one and the same mine field. Grid methods of solution allow modeling peculiarities of a geomechanical model in a wide range; though, they have a set of features preventing from guaranteeing unambiguously the calculation quality. Field experiment, which is possible to carry out only after mine working drivage, is a standard practice to substantiate the efficiency of the developed technological solutions. In terms of the considered mining and engineering conditions, stress and strain of the geomechanical model components are to be measured throughout the mine working length. Consequently, it is possible to confirm the selection quality of support parameters of the mine working only when it is completely driven. In some cases, optimal indices may be obtained at the expense of changes in the mine working border shape; that requires considerable complication of the procedure to optimize computational models. The developed calculation methodology of calculation and performance of a field experiment has made it possible to implement the procedure of optimization of selecting the support for a reused mine working by comparing analysis of stress and strain state patterns for similar geomechanical models.

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In this paper are studied the possibilities of using technical lignin as a promising raw material for the development of various types of binder for foundry. In order to overcome the resource deficit problem, new technical solutions are required for the use of new materials, the advantages of which are to rationalize the use of the available resource potential of the plant processing industry, using technical lignin's as an example. Experimental studies have been conducted to find effective modifiers of technical lignin. A class of substances has been established that makes it possible to increase the binding ability of technical lignosulfonates in a technologically acceptable level. The results of the development of foundry binder material based on technical lignin (TLS) allow us to talk about the technological feasibility of creating binder materials based on lignin materials that can successfully compete with phenol-based synthetic resins widely used now. Lignosulfonate materials can be considered as a typical example of technology for resource conservation and rational use of secondary raw materials produced from renewable natural resources.

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This research was aimed to compare the quality characteristics of “chikuwa” (a Japanese jelly-like food product made from ingredients such as fish surimi, salt, sugar, starch). In this study four species of fish such as catfish, milkfish, tilapia and red snapper were produced with the addition of 2% liquid smoke as flavouring agent. The parameters includes the changes of hedonic test, amino acid profile and proximate composition (moisture content, protein content, fat content and ash content) in chikuwa without addition of liquid smoke (control) and by the treatment of adding 2% liquid smoke to the safety level and characteristics of chikuwa. Different fish species and methods gave significantly different effect (p<0.05) to quality of “chikuwa”. The results showed the water content was found between 65.107% to 79.112%, protein content between 8.897% to 17.757% and fat content between 0.634% to 2.158% and ash content between 0.928% to 4.63%. There were about 16 amino acids found in this study, whereas the fatty acids were found about 11. Amino acid profile highest content in fresh milkfish was lysine of 221.8086 ppm and fatty acids content in composition was oleic acid ranging from 7.85% – 50.75% with an average of 40.42%. Chikuwa made from tilapia was found as the most acceptable by panelist with hedonic values; 8.68 < µ < 8.69.

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This search integrates stratigraphical and morphometrical analyses to identify the control of geological development on drainage networks and ground water occurrence in a dryland catchment (Wadi Ramliya). I is a flood prone area, incised in the sedimentary plateau in the northern part of the Eastern Desert of Egypt. The morphometrical characteristics are delineated using remote sensing and GIS. The available Digital Elevation Model (DEM) was hydrologically processed into Geographic Information System (GIS) using ArcGIS algorithms to compute the morphometric parameters according to the established linear formulas. The morphometric analyses indicated that Wadi Ramliya is a young wadi of structurally controlled geologic developments as the drainage pattern is relatively coarse and the subtle relief variation of the longitudinal profile still high. The stratigraphic analyses showed that the catchment is built up of two main lithostratigraphic successions of various sedimentary natures related to Eocene (limestone and marl) and Pliocene-Quaternary (clays, sands and gravels) dominated in the lower part of the catchment. Thus, the calcareous and impermeable plateau promotes the development of significant runoff, which is being routed through the alluvial channels. Applying stratigraphic correlation of surface and subsurface successions enabled access to the water bearing formation and interpreted the subsurface stratigraphic occurrence of the Pliocene-Quaternary deposits as essentially related to irregularities in the Pliocene basin of deposition that resulted in a graben-like structure. The groundwater aquifer is therefore, suggested to occupy the shallow, near earth surface zone. The borehole data confirmed the development of a local groundwater aquifer due to the accumulation of water-saturated gravely deposits in the southern side of downstream. Furthermore, the catchment has been subdivided into cascading upstream-downstream time area zones to compute the synthetic hydrographs of the flash floods. The estimated flash floods, even of limited development, pose dangerous threat to the different anthropogenic activities occupying or obstructing the pathways of the main Wadi trunk. Therefore, it is strongly recommended to construct flash flood controlling dyke on the outlet of the graben-like area to replenish the fragile aquifer system.

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In this work, a frequency domain method based on the Transfer Function Analyzer (TFA) technique for the identification of an electromechanical system was developed. The novelty of the study used variable sample time in the chirp signal used as the input for the identification. The TFA identification was applied to the system to identify the Bode response. The bode response with the TFA method was quite similar to the obtained with the mathematical model. Although the resonance frequencies estimated with the TFA algorithm were not the same frequencies calculated with the mathematical model, they were very close.

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Cloud Computing is an emerging technology. It allows users to enjoy on-demand services, broad network access without the burden of data storage and maintenance costs. However, the outsourcing of resources was accessing; it makes some of the security issues happened. The customer registers its authentication security module with the cloud security service, and that security module is then used to control what persons or entities can access information associated with the application. The most important concerns are authentication and access control. This paper proposes a novel mechanism compare with previous proposing solutions to authentication issues in the Cloud environment. The main aim of this paper to develop new authentication mechanisms related to cloud services. This novel authentication mechanism is very useful for cloud users whenever data are accessing the cloud.

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A method has been developed for the modification of polymer materials of the FIBAN brand, which allows to immobilize up to 5.5% of peroxyacid functional groups on them without significant changes in their physical and mechanical properties. It has been shown that the concentration of active groups and the stability of the synthesized materials depend strongly on the nature of the polymer carrier. Method for chemical analysis of the concentration of immobilized peroxyacid groups have been proposed, and the features of the IR spectra of modified materials have been described. It has been proved that all synthesized materials exhibit pronounced antimicrobial activity. Such materials can be used for manufacturing goods with increased resistance to microbial colonization, including medical masks, respirator filters, wound dressings, etc.

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Profile cutting of high carbon-high chromium (HCHC) tool steel (AISI D3 steel) using molybdenum wire electrode in Wirecut-electrical discharge machining (WEDM) was investigated in this work. Independent variables considered were cutting speed, Ton and Toff, wire tension, servo feed rate, input current, wire feed rate and servo voltage over the dependent variables material removal rate (MRR) and surface roughness (SR). Experimental design was formulated based on L18(21,37) and output responses were optimized using Grey Relational Analysis (GRA). Outcomes from experiment shows that, with increase in cutting speed, both MRR and SR increases abruptly, higher Ton produces higher MRR and lower SR, but with higher Toff a reduction in MRR and SR was observed. With higher wire tension, MRR tends to increase whereas SR reduces considerably. SR tends to increase with higher servo voltage, increasing the servo feed rate decreases the MRR, whereas SR tends to reduce. The most influential input parameter contributing towards grey relational grade was wire tension by 22.94%, servo feed rate by 16.92% with an R2 value of 95.29%, identified using Analysis of Variance (ANOVA). An error percentage of 1.46% was obtained between the confirmation experiment and predicted GRGs.

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Computer-Supported Collaborative Learning (CSCL) emerges as an instrument of learning and training that can encourage the social nature of learning by adopting range of computer-mediated communication tools and pedagogical methods. These tools are used to facilitate the learning and instructional communication among students and learners in small groups. In this process, group formation becomes painstaking and challenging task. Various factors are involved affecting group formation that includes; personal characteristics, social, cultural, psychological and cognitive diversity. Although, this issue was addressed in various research studies yet an optimal solution for dynamic group formation is not discussed evidently. In dynamic groups, students work or collaborate on a short-term task in a group that change frequently based on the performance of students. In this research study we have proposed a method for dynamic group formation and the impact of dynamic group formation in collaborative learning among peers is demonstrated by conducting an experiment. This experiment is conducted in two phases. In first phase of the experiment, learning styles are assigned to the students and their knowledge level is calculated. Whereas, in second phase of the experiment, the impact of dynamic grouping on collaborative learning of students is determined. Further, two algorithms are proposed, first is used for determining initial number of clusters and second algorithm is used for dynamic grouping after the completion of each permutation. Results of our experiment shows a positive impact of dynamic grouping on learning of students as the performance of collaborative learning among peers is better than individual performances.

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Ensuring safety of the pilgrims is the top priority of Saudi government. More than two millions of pilgrims visit the holy cities of Makkah and Madinah, in KSA, to perform Hajj and Umrah rituals every year. Therefore, kingdom considers health, safety and security a red line that is not supposed to be crossed at any extent, considering the magnitude of related consequences. A higher tendency of persons is found who get separate from their group of members during Hajj and Umrah rituals; especially in the case of children and old-aged ones. Our survey from pilgrims who lost their elders or children shows that amongst the missing 8% were elderly persons and 92% were children. The lost elderly persons and children need an efficient system to track them. Therefore, this paper proposes a system model and a prototype application for effective reporting and tracking of lost and found persons in a huge crowd gathering scenario of Al-Nabawi mosque Madinah. Our proposed system’s model aims to facilitate both pilgrims and the center of lost and found persons in Madinah. It allows pilgrims to report and search lost persons effectively. It matches the reported spatio-temporal contextual information of lost persons along with integrated support of the face recognition and biometric verification techniques. We used an existing deep learning method based on a face recognition algorithm which results in high accuracy during small-scale testing on labeled faces in the Wild benchmark. The tracking procedure is made more efficient by coupling the face recognition technique employed with biometric verification and reported spatio-temporal features of lost pilgrims.

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Today, social media is considered as the most powerful source of information flow and provides a portfolio for online discussion and sharing ideas with other people. Considering the key role of the social media in modern day life, it’s worth exploring to know the people feelings and opinion about particular event or product on media that known as sentiment analysis. It has been found that, large volumes of internet-web user are adopted to write Roman Urdu script instead of Urdu script, national language of Pakistan, on the internet. For better understanding of their expression in non-English language, it is need of time to mine Urdu data for the sentiment analysis about the desired information. Sentiment analysis tools or applications have been developed for other languages like English, Chinese and French; however, no work is reported on sentiment analysis for Urdu yet. Employing the lexicon-based approach, current study aimed to develop an application for sentiment analysis for Urdu data for user/customers’ reviews and comments. The data was collected from famous Urdu websites and databases. Given the raising internet users and growth of digital industry in the country, we anticipate that his research work will be worth of interest for Urdu language users.

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Technical education is becoming more and more career-oriented. Therefore, most of the researchers and studies have contributed their part by predicting students’ career. On the other hand, students’ career after graduation has become a major factor in building the reputation of the institutes. Predicting their degrees and future direction beforehand can help to take timely action by institutions. Data mining is a process of finding patterns and correlations within large datasets to predict outcomes. When the data mining process is used to study the learning characteristics, behaviour and performance of the student, it is called Educational Data Mining (EDM). This study implements a supervised machine learning technique to predict career of IT applicants whether IT or Non-IT by analyzing the data of those students’ who had graduated. The dataset is collected from the Course Management System (CMS) of Barani Institute of Information Technology (BIIT) PMAS, AAUR Rawalpindi and mapped with the alumni dataset which is collected from BIIT graduated students using Google forms to have one dataset for experimental use. The major concerns of this work is to develop an efficient student recommendation system for predicting career of BSCS/BSIT applicants’ whether IT or Non-IT at the time of admission and enhance the performance of learning model by re-sampling of dataset with SMOTE algorithm. This work also highlights the impact of selection of most relevant set of features for accurate results. The system efficiency has been tested upon the data of 3327 students. The total number of 11 attributes have been considered for career prediction i.e. gender, current degree program, demography details, SSC board, SSC subject, SSC grade, HSSC board, HSSC subject, HSSC grade, final degree CGPA and alumni job. To improve accuracy of learning models, re-sampling of dataset technique is sused to handle class imbalance problem by applying SMOTE algorithm. In this research, Random Forest, C4.5(J48) and Support Vector Machine (SVM) models are used to determine the best predictive model for supervised machine learning. 10-fold cross validation and standard performance evaluation measures such as: accuracy, precision, recall, F-Measure are used to evaluate the classifiers results. During the experiments Random Forest obtained 96.86% accuracy measure which is better than all of the learning algorithms, i.e., C4.5(J48) 96.55% and SVM 96.15% after handling class imbalance problem with SMOTE. This recommendation system may be more helpful by predicting career of IT department applicants’ at the time of enrollment.

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