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Customer Experience-Management (CEM) has emerged as a key differentiator in recent fierce market of telecommunication. A positive customer experience leads to increased loyalty, lower churn rate, more recommendations and optimistic word of mouth. In this era of technology, digital data has become an asset of any business. This paper proposes a technique that calculates the Customer Experience Management Index (CEMI) of subscribers of cellular network services providers by using their Call Detail Records (CDRs). In the first phase, CDR Dataset of subscribers, using the same cellular network operators, is collected. In the second phase, a close-ended telephonic survey is prepared and conducted on these subscribers of targeted valued community or social network. Six attributes of telecommunication service are selected i.e. network coverage, voice call quality, drop call rate, Short Message Service delivery, internet service and call setup duration. The subscribers are requested to grade each attribute as per their experience while using that service and to rate the service collectively in order to identify the overall experience. Genetic Algorithm (GA) is applied to optimize the weights for each attribute to eventually formulate a mathematical model for CEMI calculation. The proposed technique uses the difference between weighted attributes based on calculated CEMI and actual CEMI provided during survey process as cost function for GA which updates weights in such a way to have minimal value of this cost function. Same attributes are selected from CDRs and they are graded on the same scale which is used in survey based on the events and flags presented in the CDRs. While concluding the results, the obtained optimized weights are applied to the technical attributes of the CDRs data set and the CEMI is calculated. The proposed technique calculates the CEMI in real-time with an accuracy of 84.5 % and error of 0.248.

The advancements in electronic devices have increased the demand for the internet of things (IoT) based smart homes, where the connecting devices are growing at a rapid pace. Connected electronic devices are more common in smart buildings, smart cities, smart grids, and smart homes. The advancements in smart grid technologies have enabled to monitor every moment of energy consumption in smart buildings. The issue with smart devices is more energy consumption as compared to ordinary buildings. Due to smart cities and smart homes' growth rates, the demand for efficient resource management is also growing day by day. Energy is a vital resource, and its production cost is very high. Due to that, scientists and researchers are working on optimizing energy usage, especially in smart cities, besides providing a comfortable environment. The central focus of this paper is on energy consumption optimization in smart buildings or smart homes. For the comfort index (thermal, visual, and air quality), we have used three parameters, i.e., Temperature (°F), illumination (lx), and CO2 (ppm). The major problem with the previous methods in the literature is the static user parameters (Temperature, illumination, and CO2); when they (parameters) are assigned at the beginning, they cannot be changed. In this paper, the Alpha Beta filter has been used to predict the indoor Temperature, illumination, and air quality and remove noise from the data. We applied a deep extreme learning machine approach to predict the user parameters. We have used the Bat algorithm and fuzzy logic to optimize energy consumption and comfort index management. The predicted user parameters have improved the system's overall performance in terms of ease of use of smart systems, energy consumption, and comfort index management. The comfort index after optimization remained near to 1, which proves the significance of the system. After optimization, the power consumption also reduced and stayed around the maximum of 15-18wh.

Cloud computing is the de facto platform for deploying resource- and data-intensive real-time applications due to the collaboration of large scale resources operating in cross-administrative domains. For example, real-time systems are generated by smart devices (e.g., sensors in smart homes that monitor surroundings in real-time, security cameras that produce video streams in real-time, cloud gaming, social media streams, etc.). Such low-end devices form a microgrid which has low computational and storage capacity and hence offload data unto the cloud for processing. Cloud computing still lacks mature time-oriented scheduling and resource allocation strategies which thoroughly deliberate stringent QoS. Traditional approaches are sufficient only when applications have real-time and data constraints, and cloud storage resources are located with computational resources where the data are locally available for task execution. Such approaches mainly focus on resource provision and latency, and are prone to missing deadlines during tasks execution due to the urgency of the tasks and limited user budget constraints. The timing and data requirements exacerbate the efficient task scheduling and resource allocation problems. To cope with the aforementioned gaps, we propose a time- and cost-efficient resource allocation strategy for smart systems that periodically offload computational and data-intensive load to the cloud. The proposed strategy minimizes the data files transfer overhead to computing resources by selecting appropriate pairs of computing and storage resources. The celebrated results show the effectiveness of the proposed technique in terms of resource selection and tasks processing within time and budget constraints when compared with the other counterparts.

Background and Objective: The process of solving the Maximum Clique (MC) problem through approximation algorithms is harder, however, the Maximum Vertex Cover (MVC) problem can easily be solved using approximation algorithms. In this paper, a technique has been proposed to use the approximation algorithms of Minimum Vertex Cover (MVC) for the solution of the Maximum Cliques (MC) problem. Material and methods: To test the proposed technique, selected approximation algorithms have been developed to small graph instances. The algorithms that were used for experiments are Maximum Degree Greedy (MDG). Vertex support Algorithm (VSA). Mean of Neighbors of Minimum Degree Algorithm (MNMA), Modified Vertex Support Algorithm (MVSA), Maximum Adjacent Minimum Degree Algorithm (MAMA), and Clever Steady Strategy Algorithms (CSSA). Results: The development of an efficient approximation algorithm for the Maximum Clique (MC) problem is very difficult due to its complex nature. The only way left is to use the approximation algorithm of Minimum Vertex Cover (MVC) for the solution of the Maximum Clique (MC) problem. The experimental analysis of the proposed algorithm has revealed that the Maximum Clique (MC) problem can be efficiently solved with approximation algorithms of Minimum Vertex Cover (MVC). The proposed algorithm has efficiently solved the MC problem within the reduced time limit. conclusions: It is a difficult task to directly solve the MC problem through approximation algorithms. The proposed method provides a platform to efficiently solve the MC problem by using approximation algorithm of Minimum Vertex Cover (MVC).

Social web and social media are evidenced to be a rich source of user-generated social content. Social media includes multiple numbers of social dimensions represented by different social networks. The identification of important player in these real-world social networks has been in high emphasis due to its effectiveness in multiple disciplines, especially in law enforcement areas working on dark networks. Many algorithms have been proposed to identify key players according to the objective of interest using suitable network centrality measures. This paper proposes a new perspective of dealing with key player identification by redefining it as a problem of “Key Individual Identification,” across multiple social dimensions. Research deals with each social dimension as a layer in the multiple-layer social network model. The proposed technique extracts a number of features from each network based on social network analysis. The features are assembled to formulate a global feature set representing the behaviors of individuals in all networks individually. The technique then attempts to find key individuals using hybrid classifiers. The results from all classifiers are formulated, and the final decision of an individual to be part of the individual key set is based on majority voting. This novel technique gives good results on a number of known networks.

In recent years, due to the unnecessary wastage of electrical energy in residential buildings, the requirement of energy optimization and user comfort has gained vital importance. In the literature, various techniques have been proposed addressing the energy optimization problem. The goal of each technique was to maintain a balance between user comfort and energy requirements such that the user can achieve the desired comfort level with the minimum amount of energy consumption. Researchers have addressed the issue with the help of different optimization algorithms and variations in the parameters to reduce energy consumption. To the best of our knowledge, this problem is not solved yet due to its challenging nature. The gap in the literature is due to the advancements in the technology and drawbacks of the optimization algorithms and the introduction of different new optimization algorithms. Further, many newly proposed optimization algorithms which have produced better accuracy on the benchmark instances but have not been applied yet for the optimization of energy consumption in smart homes. In this paper, we have carried out a detailed literature review of the techniques used for the optimization of energy consumption and scheduling in smart homes. The detailed discussion has been carried out on different factors contributing towards thermal comfort, visual comfort, and air quality comfort. We have also reviewed the fog and edge computing techniques used in smart homes.

With the emerging concepts of internet of things (IoT), bring your own device (BYOD), smart homes, vehicular adhoc networks 9VANETS), mobility and new service demands, legacy networking approaches are being considered complex and inefficient. In recent past a new approach called software defined networks (SDN) has emerged to revolutionize the four decades old networking approaches. The SDN's capacity to programmatically control and modify the network behavior has given extra edge to its wide scale proliferation. After some large scale successful deployments by Google, VMware, Facebook etc., SDN has attained huge research and vendor attention. Almost all large scale national research and education networks (NRENs) have prepared Opne flow based SDN test beds for collaborative future networking research.Pakistan education Research Network (PERN) project is still lagging behind in utilizing its network infrastructure for research and experimentation purpose. Although, green filed network migration of PERN is a challenging task and requires lot of budget and technical expertise, transitional approaches are the best way to migrate from legacy networking to SDN. This study highlights the role of SDN and its deployments in educational research networks for next generation network experimentation. This study proposes transitional approaches for the migration of PERN towards OpenFlow based SDN environment. In this study, it will also discuss how SDN based PERN can facilitate IT, telecommunications, software engineering, computer scientist and network engineering researchers in conducting future network experimentation.

Offline signature recognition has great importance in our day to day activities. Researchers are trying to use them as biometric identification in various areas like banks, security systems and for other identification purposes. Fingerprints, iris, thumb impression and face detection based biometrics are successfully used for identification of individuals because of their static nature. However, people’s signatures show variability that makes it difficult to recognize the original signatures correctly and to use them as biometrics. The handwritten signatures have importance in banks for cheque, credit card processing, legal and financial transactions, and the signatures are the main target of fraudulence. To deal with complex signatures, there should be a robust signature verification method in places such as banks that can correctly classify the signatures into genuine or forgery to avoid financial frauds. This paper, presents a pixels intensity level based offline signature verification model for the correct classification of signatures. To achieve the target, three statistical classifiers; Decision Tree (J48), probability based Naive Bayes (NB tree) and Euclidean distance based k-Nearest Neighbor (IBk), are used. For comparison of the accuracy rates of offline signatures with online signatures, three classifiers were applied on online signature database and achieved a 99.90% accuracy rate with decision tree (J48), 99.82% with Naive Bayes Tree and 98.11% with K-Nearest Neighbor (with 10 fold cross validation). The results of offline signatures were 64.97% accuracy rate with decision tree (J48), 76.16% with Naive Bayes Tree and 91.91% with k-Nearest Neighbor (IBk) (without forgeries). The accuracy rate dropped with the inclusion of forgery signatures as, 55.63% accuracy rate with decision tree (J48), 67.02% with Naive Bayes Tree and 88.12% (with forgeries).

The police stations have adequate importance in the society to control the law and order situations of the country. In Pakistan, police stations manage criminal records and information manually. We have previously developed and improved a desktop application for the record keeping of the different registers of the police stations. The data of police stations is sensitive and that need to be handled within secured and fully functional software to avoid any unauthorized access. For the proper utilization of the newly developed software, it is necessary to test and analyze the system before deployment into the real environment. In this paper, we have performed the testing of an application. For this purpose, we have used Ranorex, automated testing tool for the functional and performance testing, and reported the results of test cases as pass or fail.

Learning using the Internet or training through E-Learning is growing rapidly and is increasingly favored over the traditional methods of learning and teaching. This radical shift is directly linked to the revolution in digital computer technology. The revolution propelled by innovation in computer technology has widened the scope of E-Learning and teaching, whereby the process of exchanging information has been made simple, transparent, and effective. The E-Learning system depends on different success factors from diverse points of view such as system, support from the institution, instructor, and student. Thus, the effect of critical success factors (CSFs) on the E-Learning system must be critically analyzed to make it more effective and successful. This current paper employed the analytic hierarchy process (AHP) with group decision-making (GDM) and Fuzzy AHP (FAHP) to study the diversified factors from different dimensions of the web-based E-Learning system. The present paper quantified the CSFs along with its dimensions. Five different dimensions and 25 factors associated with the web-based E-Learning system were revealed through the literature review and were analyzed further. Furthermore, the influence of each factor was derived successfully. Knowing the impact of each E-Learning factor will help stakeholders to construct education policies, manage the E-Learning system, perform asset management, and keep pace with global changes in knowledge acquisition and management.

Many approaches for modeling security requirements have been proposed, but software industry did not reach on an agreement on how to express security requirements in a system model or software architecture. The main objective of this perspective paper is to summarize the problem space of representation of security patterns when designing security requirements. Many security patterns are proposed in the literature to help the developers who lack expertise in security to implement it. Application of security patterns has been hindered by the fact that they lack directions for their implementation in a specific scenario. This paper presents a technique for using mitigation use cases for representing solution provided by security patterns. Different challenges and issues were identified related to the application of security patterns in industry

Social media makes ultimate building blocks in the development of novel approach in e-business of Pakistan with conjuncture of Web 2.0. Social media has a variety of application domains, including social commerce. S-commerce is redesigning modern e-business with promising economic, technological and social outcrops. Customers keep their expectation higher always, so precisely all businesses are trying to exceed the customers' expectations with pre and post-sale interaction on social networking sites like Facebook or Twitter accounts. Customers can interact, look and compare company products' reviews and feedback in their social circle friends or friends of friends. This paper proposes a survey about prospects of social commerce in e-business of Pakistan. In addition, this paper would propose a research framework to foster future e-business opportunities, challenges and provide the solutions to build up buyers' trust as well as to enhance the interactive online buying process in local e-business of Pakistan using social media.

Electronic commerce has gained the popularity since last two decades, due to its recompenses towards the online transactions. Academicians and e-retailers eagerly want to identify the factors which affect the e-commerce success. The main intention of this study to investigate the factors which are essential to draw the net benefits of e-commerce from an individual perspective rather than the organization perspective. The proposed framework in this paper is based on Mclean and Delone 2003 IS success model along with two extra variables that are privacy and trust. In this paper, the author discussed the result of the pilot study. The authors designed the quantitative research questionnaire by adopting the items from the previous studies and conducted the pilot study to check the reliability of the questionnaire. The overall value for Cronbach's alpha was 0.89 and also the Cronbach's alpha value for individual constructs were greater than 0.7, which indicates that there is a strong relation between the items. This research engrossed on four factors that are system quality, service quality, privacy, trust, that are essential for achieving the user satisfaction which in turn leads to achieve the e-commerce net benefits. In addition to service quality and system quality, trust and privacy are the important factors that affect the net benefits through user satisfaction, hence the modified version of Delone and Mclean IS success model from an individual perspective is proposed.

In this paper, we have discussed the architectural structure, static network performance, and dynamic communication performance of a new hierarchical interconnection network called hierarchical Tori connected mesh network (HTM). For the exploration of static network performance, we have evaluated degree, diameter, cost, average distance, arc-connectivity, bisection width, and wiring complexity. We have also evaluated the dynamic communication performance of HTM, its counter rival H3DM, and conventional mesh and torus networks using a deadlock-free dimension order routing using two virtual channels under uniform and non-uniform traffic patterns. The dynamic communication performance is evaluated using computer simulation. We discovered that the HTM has a number of lucrative properties. These include constant node degree, small diameter, low cost, small average distance, moderate (neither too low, nor too high) bisection width, and less wiring complexity. HTM also yields high throughput per link and...

Electronic Learning (e-learning) is considered as an innovative approach to education delivery via electronic forms of information. e-learning is an online education or distance education, which means that it can deliver education to everyone around the world online through the electronic means such as the internet from different distant countries. The success of E-learning process in universities needs to some factors that should be fit with the revolution of technology and enhance the learner's knowledge. Universities in developing countries such as Iraq, in order to be fit with the rapid growth of technology, it needs to analyze the current capabilities, analyzing previous studies, evaluating it and developing solutions fit with the updated technology in which these countries could save the time and reduce the cost and offer modern alternative means, tools, and methods of e-learning in its universities This paper reviews e-learning studies and status in Iraqi universities, identifying gaps and proposed some alternative solutions for that in order to enhance the e-learning process in Iraqi universities.

Electronic Learning (e-learning) is the process of offering education in a creative method by using the electronic shapes of information and contents. e-learning is the process of education that offered can be divided into online or distance education, which means that it can deliver education to everyone around the world online through the electronic means such as the internet from different distant countries. The success of E-learning process in universities needs to some factors that should be fit with the revolution of technology and enhance the learner's knowledge. Universities in developing countries such as Iraq, in order to be fit with the rapid growth of technology, it needs to collaborate with other national and international universities to develop e-learning tools and methods. In order to contribute to the success of the e-learning process in universities in Iraq, these universities have to adopt collaboration culture with other universities and adhocracy culture to follow the innovation in e-learning process. This paper proposes an integrated model of e-learning through an innovative collaboration environment which could participate to improve and add values to the e-learning process in universities in Iraq.

To compete, cellular network operators must be very responsive to their customer needs. One effective approach that could make a business more productive is anticipatory decisions while considering customer’s problem. Communication Service Providers must have greater insights into their own Call Details Record data in order to gauge and tune up the company’s performance. CSPs must promptly react to ever changing competitive environment by providing quick and personalized services. However, reacting quickly to changing customer expectations is not a simple task. In this paper, a method has been proposed in order to tackle this challenging problem. Proposed solution is using CDR data as the primary data source to detect valued social networks and monitored the QOS provided to the identified valued social network. Calls of valued customers will be prioritized by inserting priority tag in MSC. The final step of proposed technique deduces a proactive approach in order to retain the high revenue generating customers.

Crowdsource management imposes many challenges including varying degree of demands for food and daily routine consumables. The explicit problem for estimating increase or decrease in demand arises when crowd moves dynamically to different locations with respect to time. This may result in wastage or shortage of many resources and loss for various stakeholders. To overcome the issue of demand estimation more precisely food demand and efficient supply, this paper proposes a conceptual framework to sense the data of crowd such as number of humans and update the suppliers timely. IoT and WSN techniques are used to count the number of humans in crowd at some particular area with respect to time for food demand estimation.

The Carnegie Mellon University's (CMU) Sphinx framework is increasingly used for the Arabic speech recognition in general and applied to the Holy Quran in particular. Generating the language model includes a tedious task of preparing the transcriptions for all the data. In this paper, we investigate the fault-tolerance of the automatically generated language model as compared to a corrected and uncorrected transcription with and without silence tagging. This editing addresses the different repetitions and pauses encountered during recitations. Experiments show that the average difference between the lowest and highest Word Error Rate (WER) for each configuration of the number of Senones is 0.6% when using all files for the training and 1.6% when using 80% of the files for training the language model of 17 chapters of the Holy Quran. Results show that the performance of trained models without any correction can be close to when all required rectifications of transcriptions are performed.

This study is focused on validating halal status for food products by using Radio Frequency Identification (RFID) or Near Field Communication (NFC) technology to enhance existing methods in Malaysia. In this research, an effective method to identify and confirm the food status is proposed. Besides, designing a database of halal products, halal identification and validation applications for android smart phones are considered. Investigation on advanced technologies to introduce an RFID based identification system using current smart phones and evaluation of other methods to realize the suitable method is highlighted.

With the influx of the Internet, Business to Customer E-commerce (B2c e-Commerce) has gained popularity around the globe. Although a number of researches has been done to know the factors affecting the adoption of e-commerce, however, not much research has done to know the effects of e-commerce on online shopping success. DeLone and McLean introduced the Information System (IS) success model in year 1992, later on, refined the same model with the newer concept, to fully understand the effects of IS success. In this paper, authors have used the DeLone and McLean IS success model 2003 with addition two constructs Privacy and Trust. Seven interrelated dimensions of e-commerce were examined namely, Service Quality, System Quality, Trust, Privacy, User satisfaction and Net benefits. The proposed model and the relationship between the various constructs were measured by gathering the data from 381 users from the business faculty of Klang valley universities in Malaysia. Seven interconnected dimensions of B2C e-commerce success were confirmed namely, Service Quality, System Quality, Information Quality, Trust, Privacy along with User Satisfaction and Net Benefits. Confirmatory Factor Analysis CFA and SEM were used to analyse the collected data and proved the hypothesis. The results revealed that system quality, service quality, trust and privacy are directly related to user satisfaction which in turn directly related to net benefits, whereas information quality has no any influence on user satisfaction in terms of e-commerce.

Wearable devices such as exoskeletons are being opted frequently during rehabilitation processes for the post stroke recovery. Such devices are playing important role in the development of assistive rehabilitation robotic systems. In this paper three control strategies MPC and LQR and PID are introduced which were applied to knee joint of lower limb exoskeleton model for passive exercise. The two controls MPC and LQR are model based control which empowers them for stable responses. In this paper the analysis of robustness of control is done under the noisy and disturbance conditions. The results showed good performance of the exoskeleton model with the applied controls in the provided condition. In the future work the applied controls will be implemented on hardware.

The research aimed to design and evaluate an innovative Web 2.0-based collaborative learning with the Islamic ethical system to support Islamicisation and the practice of Islam as a way of life that is the main goal of Islamic education. This is in response to the lesser amount of focus in Islamic education on the real example of integrating ICT into the collaborative learning process that could support social constructivist learning goals and skills for use of Islamic knowledge in daily life. The most important argument is that the students should be given an appropriate and practical platform where they can practice collaboratively and share their experiences that design science research methodology and Facebook features in this study could support these needs and arguments. Expert review, user testing were conducted and quality, effectiveness and usability of developed Web 2.0-based collaborative learning confirmed.

In engineering and technology safety of human life has always been a top priority. With the increasing usage of vehicles in everyday life, probability of deaths and injuries has also increased. This paper provides a critical review on the optimization of vehicle frontal crashworthiness studied by researchers using various methods. They investigated the effects of crash at a defined speed using the method of FRB and ODB impact. It further discusses other methods that can be used to save passengers’ life. Also, the designing and manufacturing limitations faced by engineers in actual development processes. Finally, it is concluded that improved structure design and material composition can significantly increase the overall crashworthiness of the vehicle.