IJACSA Volume 9 Issue 4 - thesai.org

IJACSA Volume 9 Issue 4

Copyright Statement: This is an open access publication licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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Paper 1: On Prospects of Development of Telecommunication Systems and Services based on Virtual Reality Technology

Abstract: Virtual reality technologies are considered to be a basis and a promising development trend of telecommunication systems’ and services. New opportunities and sci-tech problems that need to be solved are currently undergoing analysis. In the nearest future, the possibility of creating a new segment in the international telecommunication services market that is oriented towards providing communication services to the mass consumer and the entertainment industry, new tools for goods promotion and education content delivery, as well as toward solving experimental problems in managing state structures and social economical systems, is being justified. Within the context of studying the necessary prerequisites to implementing this opportunity the following is being done: an approach to creating and charging for according telecommunication services is being given, opportunities for using the existing national and international cellular connection infrastructure is researched; the prospects of shifting towards new cellular network standards of the fifth generation are being analyzed, employing new ways of connecting to the Internet, as well as new formats of transmitting and processing multimedia, including the provision of immersion in the virtual reality environment; safety aspects of end-user equipment and VR-based telecommunication service exploitation are being updated. As a result of consolidating the given material, the authors are working on building grounds for the rapid development in this direction of telecommunication services and options provided by the Russian national and transnational cellular network operators. The paper was created as part of the project 2.7178.2017/БЧ “Researching Cognitive Semiotics in the Multimedia Virtual Reality Environment”.

Author 1: Andrey Zuev

Author 2: Roman Bolbakov

Keywords: Virtual reality; cellular network; mobile internet; telecommunication service; digital economy; informational society

Paper 2: Unifying Modeling Language-Merise Integration Approach for Software Design

Abstract: Software design is the most crucial step in the software development process that is why it must be given a good care. Software designers must go through many modeling steps to end up with a good design that will allow for a smooth development process later. For this, designers usually have to choose between two main modeling methodologies: Merise and UML. Both methodologies are widely used; however, each one has its own advantages and disadvantages. This paper combines both techniques and merges their advantages to come up with an approach that would help software designers make the best of both methodologies. This integration mainly targets the software design step in general but can be specifically applied to database design. It presents the weaknesses and strengths of each one of UML and Merise as two techniques used in database modeling and design. Later in this paper, a comparing of UML and Merise diagrams is lead and based on it, the decision on which of the two is the best at each step of the modeling process.

Author 1: Issar Arab

Author 2: Safae Bourhnane

Author 3: Fatiha Kafou

Keywords: UML; Merise; modeling; design; databases

Paper 3: Linear Quadratic Regulator Design for Position Control of an Inverted Pendulum by Grey Wolf Optimizer

Abstract: In this study, a linear quadratic regulator (LQR) based position controller is designed and optimized for an inverted pendulum system. Two parameters, vertical pendulum angle and horizontal cart position, must be controlled together to move a pendulum to desired position. PID controllers are conventionally used for this purpose and two different PID controllers must be used to move the pendulum. LQR is an alternative method. Angle and position of inverted pendulum can be controlled using only one LQR. Determination of Q and R matrices is the main problem when designing an LQR and they must be minimized a defined performance index. Determination of the Q and R matrices is generally made by trial and error method but finding the optimum parameters using this method is difficult and not guaranty. An optimization algorithm can be used for this purpose and in this way; it is possible to obtain optimum controller parameters and high performance. That’s why an optimization method, grey wolf optimizer, is used to tune controller parameters in this study.

Author 1: Hüseyin Oktay ERKOL

Keywords: Grey wolf optimizer; inverted pendulum; position controller; linear quadratic regulator; optimized controller design

Paper 4: Evaluation of Photo Contents of Conversation Support System with Protocol Analysis Method

Abstract: With the deepening of aging and low birth rate in China, the solitary elderly or old couple living alone is becoming more and more, who has a higher risk of senile dementia caused by disuse of cognitive function because of loneliness without communication. Due to the shortage of care workers, the young volunteer is expected becoming communication partner for them. But it is difficult for the young volunteer without the experience of communication with the elderly, and for two generations to find common topics. However, Conversation Support System was proposed so that the elderly and the young volunteer can talk smoothly with common photo contents. In order to evaluate the utility of photo contents of the system in China, we did the conversation experiment by photos in China, to analyze the expression and stress of subjects during the conversation. As a result, the photos which made the elderly and the young volunteer feel easy and difficult for the conversation were found. Then we analyzed utterance data of subjects with protocol analysis method to discuss the common features of these photos.

Author 1: Zhou Xiaochun

Author 2: Miyuki Iwamoto

Author 3: Noriaki Kuwahara

Keywords: Protocol analysis method; the elderly; the young volunteer; photo contents; conversation

Paper 5: Mutual Coupling Reduction of MIMO Antenna for Satellite Services and Radio Altimeter Applications

Abstract: Ground irregularities also known as defected ground structures (DGS) is a freshly presented innovatory way in designing of patch antennas to boost up the performance of antenna constraints. This study presents a novel proposal of ground irregularities or defected ground structure is proposed for suppression of mutual coupling effects among 2x1 multiple input multiple output patch array designed on Roggers Duroid 5880. The two adjacent M shape structures surrounding Dumbbell Shaped structure and sandwiched between Dumbbell shape patterns showed the significant level of surface wave suppression up to -42dB while maintaining the gain of 4.7dB and 5.6dBi of directivity. The patch array operates at 4 to 4.3GHz for Fixed and Radio satellite services (FSS) and (RSS) and radio altimeter application systems.

Author 1: Saad Hassan Kiani

Author 2: Khalid Mahmood

Author 3: Ahsan Altaf

Author 4: Alex J. Cole

Keywords: Multiple input multiple output (MIMO); mutual coupling; defected ground structures (DGS); fixed satellite services (FSS); radio satellite services (RSS); radio altimeters

Paper 6: Detection of Soft Atherosclerotic Plaques in Cardiac Computed Tomography Angiography

Abstract: Computed tomography angiography (CTA) has turned non-invasive diagnosis of cardiovascular anomalies into a reality as state-of-the-art imaging equipment is capable of recording sub-millimeter details. Based on high intensity, the calcified plaques are easily identified in cardiac CTA; however, low density based non-calcified plaque detection has been a challenging problem in recent years. We propose an efficient method in this work for automated detection of the non-calcified plaques using discrete radial profiles. The plaque detection is accomplished using support vector machine to differentiate abnormal coronary segments. We investigated a total of 32 CTA volumes and the detection mean accuracy of 84.6% was achieved, which is in-line with the reported literature.

Author 1: Muhammad Moazzam Jawaid

Author 2: Sajjad Ali Memon

Author 3: Imran Ali Qureshi

Author 4: Nasrullah Pirzada

Keywords: Coronary tree segmentation; support vector machines; non-calcified plaque detection; mean radial profiles; Rotterdam CTA dataset

Paper 7: Ethical Issues and Related Considerations Involved with Artificial Intelligence and Autonomous Systems

Abstract: The applications of artificial intelligence (AI) and automated systems (AS) demonstrate excellent outcomes in various sectors of industrial units to replace the human from jobs. However, the competitive world with evolutions, advancement of technologies and thrive for success by industrial gains by the managements are leaving the interests and benefits of larger number of human beings in the society. In this paper, various ethical issues related with the implementation of AI/AS are demonstrated with different perspectives. The ongoing developments in the area of AI/AS are critically evaluated and related advantages and serious concerns of the society are discussed. Various global initiatives and legal amendments across the globe to limit the excessive usage of AI/AS are being examined with critical assessments.

Author 1: Saud S. Alotaibi

Keywords: Ethical issues; artificial intelligence; automated systems; human values; evolutions

Paper 8: An Adaptive Cruise Control Model based on PDLCA for Efficient Lane Selection and Collision Avoidance

Abstract: Todays, safe and sans collision free traveling is essential in the present World. Because of the particular needs required by different usages of Vehicular Ad Hoc Networks (VANETs), mainly in evolving lane, outlining a constant Collision Avoidance (CA) and securely lane changing has turned into the foundation of controlling the vehicle in the dense environment. In our system, we proposed efficient lane selection and collision-free vehicle transportation system in the light of patience, speed and the distance between all types of vehicles. To maximize the efficiency of the existing transportation infrastructure and reduce collision, it is necessary to improve safety and communication in all vehicles. In this paper, we first define the patience based method and simulate model for safety and efficiency of traffic flow using the game theoretical technique. Then we have improved a new algorithm for lane selection and collision control using distance and speed of all vehicles gather from the vehicular communication. After two different methodologies for lane change and collision-free driving are compared like; random patience based method and car following method, based on different traffic density. In the part of contribution as an outcome, our experimental simulation setup is executed on highway road traffic scenarios to demonstrate the capacity of the all type of vehicles to select best-fit lane, identify collision, and explore around them to maintain the safe distance. Finally, it is concluded that our proposed algorithm outperforms in lane selection and collision avoidance to satisfy safety and efficiency in the Vehicular Ad Hoc Networks.

Author 1: Khawaja Iftekhar Rashid

Author 2: Ding Nan

Author 3: Muhammad Tahir

Author 4: Anil Ahmed

Keywords: Automatic vehicle; collision avoidance; lane selection; patience; threshold; traffic density

Paper 9: Object Contour in Low Quality Medical Images in Curvelet Domain

Abstract: The diagnosis and treatment are very important for extending the life of patients. The small abnormalities may also be manifestations of the diseases. One of the abnormalities is the contour of each object in medical images. Therefore, the contour is very important and special to low quality medical images. In this paper, we propose a new method to detect the object contour of low quality medical images based on the self affine snake, one of the types of active contour models. The method includes two periods. Firstly, we use augmented lagrangian method to remove noise and detect edges in low quality medical images in curvelet domain. Finally, the active contour model is improved to show the contour of objects. After comparing the appearance of the contour and the time processing with other algorithms, we confirm that the proposed method is better.

Author 1: Vo Thi Hong Tuyet

Author 2: Nguyen Thanh Binh

Keywords: Object contour; curvelet transform; augmented lagrangian

Paper 10: Analytical Study of Algorithms for Solving Inverse Kinematic Problems in Robot Motion Control

Abstract: The given article covers the general formulations of inverse kinematic problems for robot motion control systems. We have discussed the difficulties how to solve such problems using analytical and numerical methods. We have also analyzed the convergence of iterative algorithms with the regularization on the trajectory with the points outside of the gripper reachability. The example of an iterative calculation of joint trajectories for a 3-link robot using the recursive algorithm for the Jacobi matrix calculation has been presented.

Author 1: Dr. Osama Ahmad Salim Safarini

Keywords: Robot motion control systems; inverse kinematic problems; iterative methods; algorithm convergence; regularization

Paper 11: Terman-Merril Application for Intelligence Measurement

Abstract: The computational applications support different processes in organizations, one of these processes are those related to human resources, where one of the activities is the hiring of new personnel; the evaluation of human talent to be integrated into a company can be measured through different tests, one of which is the Terman-Merril intelligence test, which measures the intellectual quotient of candidates with a series of sub-tests. In this project, the waterfall method has been used for the development of a web computational application for the Terman-Merril intelligence test, as well as the management of the users and the results obtained to be visualized in spreadsheets for its subsequent analysis and graphing. The ASP.Net programming language and the SQL Server 2014 database have been used for the programming and the storage of information. As a result, it has been applied successfully in some companies, obtaining measurable and evaluable results on the candidates. The application has also been installed in a computer lab for students enrolled in the Bachelor of Human Resources at Faculty of Accounting and Administration at Coahuila, Mexico.

Author 1: Alicia Valdez

Author 2: Griselda Cortes

Author 3: Laura Vazquez

Author 4: Andrea de la Pena

Author 5: Blanca Montano

Keywords: Human resources; Terman-Merril test; intelligence test; ASP.Net

Paper 12: Software Cost Estimation using Enhanced Artificial Bee Colony Algorithm

Abstract: Cost estimation is very important in software development progress so that resource and time planning can be successfully performed. Accurate estimation of cost is directly related to the decision making mechanism in the software development process. The underestimated cost might lead to fewer resources and budget problems; in contrast, customer satisfaction might diminish due to waste of resources. This study represents an estimation model for the effort required for the development of software projects using a variant of artificial bee colony (ABC) algorithm. The proposed model is performed over a dataset consisting of NASA software projects and has better performance than the previous studies.

Author 1: Sevgi Yigit-Sert

Author 2: Pinar Kullu

Keywords: Software cost estimation; enhanced artificial bee colony algorithm; NASA software

Paper 13: Using Creative Educational Drama to Enhance Self-Development Skills for the Students at University Level

Abstract: This study has been undertaken using a creative drama in teaching in order to improve the communication and thinking skills for the students of preparatory year students at the Northern Border University. It aimed to measure the differences between the experimental and control groups in skills acquisition among students. The study was conducted on 140 students from both genders (males=70 and females=70). The students were divided into four groups: each has 35 students. The study adopted an experimental approach by observing students’ behavior through affecting their communication and thinking skills with using drama. The findings confirmed that using drama in teaching significantly affected on the experimental group than the students of the control group who were taught with traditional methods as the experimental group achieved better results than the control group. Furthermore, the study stressed the possibility of benefiting from the drama in teaching other practical courses at the university level and provided several recommendations in this regard as well.

Author 1: Hisham Saad Zaghloul

Keywords: Creative drama; creative educational drama; self-development skills; communication skills; thinking skills

Paper 14: Pakistan Sign Language Detection using PCA and KNN

Abstract: Every society has a large majority group of disable people. The technology is developing day by day but no significant developments are undertaken for the improvement of these people. Sign language is an efficient mean of information exchange with special people, such as Deaf and Dumb people, they communicate with each other through sign language, but it become difficult when they communicate to outer world so sign language is used for this purpose. Different research has been done for this in America, Indonesia and India, but not much work done in Pakistan. In this research paper, author introduce a system for recognizing Pakistan Sign Language (PSL) including the alphabet to facilitate communication between special people and normal. This system capture input through webcam without making use of any additional hardware, then using segmentation approach we separate hand from the background and extract required feature from image using Principal Component Analysis (PCA) and then finally classifies the gesture feature by utilizing K Nearest Neighbors (KNN). This research will fill the communication gap between the deaf and normal people of the Pakistan country.

Author 1: Muhammad Sheraz Arshad Malik

Author 2: Naila Kousar

Author 3: Tahir Abdullah

Author 4: Muhammad Ahmed

Author 5: Faiqa Rasheed

Author 6: Muhammad Awais

Keywords: Deaf and dumb; hand gesture recognition; k-nearest neighbors; Pakistan sign language; principal component analysis; Urdu alphabets

Paper 15: eHealth WBAN: Energy-Efficient and Priority-Based Enhanced IEEE802.15.6 CSMA/CA MAC Protocol

Abstract: This paper provided a general study of Wireless Body Area Network (WBAN) in health monitoring system as well as the study of the application of wearable and implanted Bio-Medical-Sensors (BMS) which are used to monitor the vital signs of a patient in early detection. Energy efficiency is a significant issue in WBAN which can be achieved by reducing the overhead of control packets, prioritizing sensor-nodes and sink-node selection. Moreover, uncertainty in network topologies, such as distance and link affect between sensor-nodes occurs due to the mobility of human. In this research, we propose a scheme to reduce the overhead of control packets and prioritizing the threshold values of vital signs by assigning low and high transmission power with enhanced IEEE802.15.6 CSMA/CA as well as introduce a Mobility Link Table (MLT) for selecting a sink-node to communicate with the coordinator. Compare it with existing IEEE802.15.6 CSMA/CA technique and results shows the proposed techniques regarding mean power consumption, network delay, network throughput.

Author 1: Ansar Munir Shah

Author 2: Abdelzahir Abdelmaboud

Author 3: Khalid Mahmood

Author 4: Mahmood ul Hassan

Author 5: Muhammad Kashif Saeed

Keywords: Wireless Body Area Network (WBAN); node; IEEE802.15.6; MAC; CSMA/CA; Mobility Link Table (MLT)

Paper 16: Cobit 5-Based Approach for IT Project Portfolio Management: Application to a Moroccan University

Abstract: Considering the problem of the management of IT project portfolios in universities, University managers face a lot of uncertainties when prioritizing projects that make up their portfolio. The alignment with their strategy becomes a major challenge and constitutes one of the essential elements of a governance approach. To overcome this challenge, the implementation of a project prioritization approach adapted to the university’s strategy, vision and culture is essential. In this context, this paper aims to provide a multi-criteria approach based on a combination of AHP and TOPSIS methodologies for the selection and prioritization of IT projects in universities. The main feature of our approach is the use of COBIT 5, its principles and enablers as prioritization criteria. In order to validate our model, project portfolio managers of a Moroccan public university were involved to evaluate the criteria and to prioritize their projects. This research demonstrates that the combined use of Multi Criteria Decision Making (MCDM) methodologies proves to be suitable for the implementation of COBIT sub-process APO05.03.

Author 1: Souad AHRIZ

Author 2: Abir EL YAMAMI

Author 3: Khalifa MANSOURI

Author 4: Mohammed QBADOU

Keywords: Component; IT governance; project portfolio management; Cobit 5; AHP; TOPSIS; prioritization; university

Paper 17: An Explorative Study for Laundry Mobile Application

Abstract: With the current rapid development of technology, many services need redesigning in order to keep up with customer demands. Therefore, organizations nowadays resort to redesigning services and business processes in order to maintain their competitiveness and success. With the recent advances in smartphone capabilities, and their growing penetration rate among individuals, organizations intend to take advantage of these devices by designing mobile applications to help evolve their business. The laundry business is one sector which has great potential for further development. Turning the ordinary routine of laundry into a service obtainable through a mobile application will contribute to reducing the burden of laundry tasks on individuals. This paper reviews the relevant literature and has design an instrument which investigates an individual’s need for such mobile applications.

Author 1: Doaa M. Bamasoud

Author 2: Asma M. Alqahtani

Author 3: Eman A. Aljdea

Author 4: Reem A. Alshomrani

Author 5: Maha S. Alshahrani

Author 6: Zohoor A. Alghamdi

Author 7: Ameerah M. Alghamdi

Author 8: Shahd F. Almaawi

Author 9: Asrar D. Alshahrani

Keywords: Business process change; smartphones; mobile application; laundry

Paper 18: Extraction of ERP Selection Criteria using Critical Decisions Analysis

Abstract: Companies use ERP systems to automate business processes in order to increase productivity, reduce costs, and meet customer requirements. ERP selection for an enterprise is a decision-making project that is both risky and expensive, a wrong selection of this system or project partners can lead to the failure of the ERP implementation project. In this paper, we combined the theoretical findings of ERP selection issue with expert’s practical recommendations to determine the critical decisions that need to be made in the pre-implementation phase. Then we presented a methodology to determine ERP selection criteria based on the critical decisions analysis. A part of this work was performed within a company that has just launched an ERP implementation project.

Author 1: Motaki Noureddine

Author 2: Kamach Oualid

Keywords: ERP selection; criteria; critical decisions; implementation; information system

Paper 19: Performance Analysis of Artificial Neural Networks Training Algorithms and Transfer Functions for Medium-Term Water Consumption Forecasting

Abstract: Artificial Neural Network (ANN) is a widely used machine learning pattern recognition technique in predicting water resources based on historical data. ANN has the ability to forecast close to accurate prediction given the appropriate training algorithm and transfer function along with the model’s learning rate and momentum. In this study, using the Neuroph Studio platform, six models having different combination of training algorithms, namely, Backpropagation, Backpropagation with Momentum and Resilient Propagation and transfer functions, namely, Sigmoid and Gaussian were compared. After determining the ANN model’s input, hidden and output neurons from its respective layers, this study compared data normalization techniques and showed that Min-Max normalization yielded better results in terms of Mean Square Error (MSE) compared to Max normalization. Out of the six models tested, Model 1 which was composed of Backpropagation training algorithm and Sigmoid transfer function yielded the lowest MSE. Moreover, learning rate and momentum value for the models of 0.2 and 0.9 respectively resulted to very minimal error in terms of MSE. The results obtained in this research clearly suggest that ANN can be a viable forecasting technique for medium-term water consumption forecasting.

Author 1: Lemuel Clark P. Velasco

Author 2: Angelie Rose B. Granados

Author 3: Jilly Mae A. Ortega

Author 4: Kyla Veronica D. Pagtalunan

Keywords: Artificial neural network; backpropagation; water consumption forecasting

Paper 20: A Linear Array for Short Range Radio Location and Application Systems

Abstract: Patch array antennas have primarily been good candidates for higher performance results in communication systems. This paper comprises of linear 1x4 patch antenna array study constructed on 1.575mm thick Roggers 5880 substrate with high gain of 12.8dB and focused directivity of 12.9dBi. The array network is fed using T Junction method showing well matched input impedance results. With higher performance parameters and reflection coefficient, voltage standing wave ratio, the proposed antenna array is suited for short range radiolocation and radio services application.

Author 1: Saad Hassan Kiani

Author 2: Khalid Mahmood

Author 3: Ahsan Altaf

Keywords: Linear array; gain; Roggers 5880; voltage standing wave ratio; directivity; radiolocation; short range radio applications

Paper 21: Factors Influencing Cloud Computing Adoption in Saudi Arabia’s Private and Public Organizations: A Qualitative Evaluation

Abstract: Cloud Computing is becoming an important tool for improving productivity, efficiency and cost reduction. Hence, the advantages and potential benefits of cloud computing are no longer possible to be ignored by organizations. However, organizations must evaluate factors that influence their decisions before deciding to adopt cloud computing technologies. Many studies have investigated cloud computing adoption in developed countries compared with few studies that have concentrated on examining the factors that influence cloud computing adoption in developing countries. It is not clear to see whether these factors that have been identified by these studies, can be applied in developing countries. The motive of this study is to contribute to the adoption of cloud computing, and to elevate the consciousness of cloud computing technology amongst authorities, researchers, administrators, business enterprise managers and service carriers, particularly within the Saudi Arabian context. This study explores factors that encourage the implementation of cloud or have the capacity to detract from adopting cloud computing in private and public organizations in Saudi Arabia. A qualitative approach through IT professional representatives’ interviews was adopted in this study, which explored two categories, namely, a) the negative impact category which includes: security and privacy, government policy, lack of knowledge, and Loss of control; and b) the positive impact category which includes three factors: reduce expenses, improve IT performance, and promote scalability and flexibility.

Author 1: Mohammed Ateeq Alanezi

Keywords: Cloud computing; private and public organization adoption; qualitative evaluation; Saudi Arabia

Paper 22: Multi-Level Encryption Framework

Abstract: Multi-level encryption approaches are becoming more popular as they combine the strength of multiple basic/traditional approaches into a complex one. Many multi-level encryption approaches have been introduced for different systems, like Internet of Things, sensor networks, big data, and the web. The main obstacles in building such approaches are to have a secure as well as a computationally efficient multi-level encryption approach. In this paper, we propose a computationally efficient multi-level encryption framework that combines the strength of symmetric, the encryption algorithm AES (Advance Encryption Standard), Feistel network, Genetic Algorithm’s Crossover and Mutation techniques, and HMAC. The framework was evaluated and compared to a set of benchmark symmetric encryption algorithms, such as RC5, DES, and 3-DES. The evaluation was carried out on an identical platform and the algorithms were compared using the throughput and running time performance metrics and Avalanche effect security metric. The results show that the proposed framework can achieve the highest throughput and the lowest running time compared to the considered benchmarked symmetric encryption algorithms and passes the avalanche effect criterion.

Author 1: Ahmad Habboush

Keywords: Multi-level encryption; Advance Encryption Standard (AES); Feistel encryption; symmetric encryption algorithm

Paper 23: A Developed Collaborative Filtering Similarity Method to Improve the Accuracy of Recommendations under Data Sparsity

Abstract: This paper presented a new similarity method to improve the accuracy of traditional Collaborative Filtering (CF) method under sparse data issue. CF provides the user with items, that what they need, based on analyses the preferences of users who have a strong correlation to him/her preference. However, the accuracy is influencing by the method that use to find neighbors. Pearson correlation coefficient and Cosine measures, as the most widely used methods, depending on the rating of only co-rated items to find the correlations between users. Consequently, these methods have lack of ability in addressing the sparsity. This paper presented a new proposed similarity method based on the global user preference to address the sparsity issue and improve the accuracy of recommendation. Thus, the novelty of this method is the ability to solve the similarity issue with a capability of finding the relationship among non-correlated users. Furthermore, to determine the right neighbors during the process of computing the similarity between a pair of users, the developed method considered two main factors (fairness and proportion of co-rated). The MovieLens 100K benchmark dataset is used to evaluate the developed method accuracy. The experiments’ result showed that the accuracy of the developed method is improved compared to the traditional CF similarity methods using a specific common CF evaluation metrics.

Author 1: Hael Al-bashir

Author 2: Mansoor Abdullateef Abdulgabber

Author 3: Awanis Romli

Author 4: Norazuwa Binti Salehudin

Keywords: Recommendation system; collaborative filtering; similarity method; data sparsity

Paper 24: An Optimization of Audio Classification and Segmentation using GASOM Algorithm

Abstract: Now-a-days, multimedia content analysis occupies an important place in widely used applications. It may depend on audio segmentation which is one of the many other tools used in this area. In this paper, we present an optimized audio classification and segmentation algorithms that are used to segment a superimposed audio stream according to its content into 10 main audio types: speech, non-speech, silence, male speech, female speech, music, environmental sounds, and music genres, such as classic music, jazz, and electronic music. We have tested the KNN, SVM, and GASOM algorithms on two audio classification systems. In the first audio classification system, the audio stream is discriminated into speech no-speech, pure-speech/silence, male speech/female speech, and music/ environmental sounds. However, in the second audio classification system, the audio stream is segmented into music/speech, pure-speech/silence, male speech/female speech. For pure-speech/silence discrimination, it is performed in the two systems according to a rule-based classifier. Concerning the music segments in both systems, they are discriminated into different music genres using the decision tree as a classifier. Also, the first audio classification system has succeeded to achieve higher performances compared to the second one. Indeed, in the first system using the GASOM algorithm with leave-one-out validation technique, the average accuracy has reached 99.17% for the music/environmental sounds discrimination. Moreover, in both systems, the GASOM algorithm has always reached the best results of performances compared to KNN and SVM algorithms. Therefore, in the first system, the GASOM algorithm has been contributed to obtain an optimized consumption time compared to that one obtained using the two HMM and MLP methods.

Author 1: Dabbabi Karim

Author 2: Cherif Adnen

Author 3: Hajji Salah

Keywords: Segmentation and classification audio; features extraction; features discrimination; GASOM algorithm

Paper 25: The Effectiveness of Cloud-Based E-Learning towards Quality of Academic Services: An Omanis’ Expert View

Abstract: The purpose of this paper is to understand the importance, relevance and the need of implementing Cloud-Based E-Learning (CBEL) in Higher education institutions (HEIs) in Oman. The paper maintains its emphasis on addressing the effectiveness of the cloud based e-learning system and also takes into account the activities of comparing and contrasting the before and after effects of the implementation of the CBEL on higher educational sector in Oman. Method: The methodological approach of this paper follows qualitative approach of data collection and the data analysis techniques used in this paper are interpretivist approach and thematic analysis. Results and Findings: The data analysis techniques used in this research paper helped in understanding and gathering meaningful insights relating to the need and significance of implementing CBEL in educational sectors.

Author 1: Qasim A. Alajmi

Author 2: Adzhar Kamaludin

Author 3: Ruzaini Abdullah Arshah

Author 4: Mohammed A. Al-Sharafi

Keywords: Cloud computing; e-learning; cloud-based e-learning; higher education institutions; quality of academic services

Paper 26: Design and Simulation of a Rectangular E-Shaped Microstrip Patch Antenna for RFID based Intelligent Transportation

Abstract: A low profile, rectangular E-shaped microstrip patch antenna is designed and proposed for radio-frequency identification (RFID) based intelligent transportation system (ITS) in this paper. The proposed antenna design aims to achieve high gain and low return loss at 0.96 GHz as it is suitable for ultra-high frequency (UHF) RFID tags. The proposed antenna composed of a radiating patch on one side of the dielectric substrate and the ground plane on the other side, copper is used to produce the main radiator. The simulation of the proposed antenna is performed employing the high-frequency structure simulator (HFSS). The dielectric substrate used for the suggested antenna is an FR4 substrate with dielectric constant of 4.3 and height 1.5 mm. The performance of the proposed antenna is measured in terms of gain, return loss, voltage standing wave ratio (VSWR), radiation pattern and the bandwidth. The antenna gain and the return loss of the suggested antenna at 0.96 GHz are 7.3 dB and -12.43 dB, respectively.

Author 1: Asif Ali

Author 2: Nasrullah Pirzada

Author 3: Muhammad Moazzam Jawaid

Author 4: Sajjad Ali Memon

Keywords: E-shaped microstrip patch antenna; antenna gain; return loss; voltage standing wave ratio (VSWR); high-frequency structure simulator (HFSS)

Paper 27: Method for Thermal Pain Level Prediction with Eye Motion using SVM

Abstract: Method for thermal pain level prediction with eye motion using SVM is proposed. Through experiments, it is found that thermal pain level is much sensitive to the change rate of pupil size rather than pupil size itself. Also, it is found that the number of blinks shows better classification performance than the other features. Furthermore, the eye size is not a good indicator for thermal pain. Moreover, it is also found that user respond to the thermal stimulus so quickly (0 to 3 sec.) while the thermal pain is remaining for a while (4 to 17 sec.) after the thermal stimulus is removed.

Author 1: Kohei Arai

Keywords: Eye motion; thermal pain; support vector machine; thermal stimulus; classification

Paper 28: Recommendation using Rule based Implicative Rating Measure

Abstract: The paper presents a rule based implicative rating measure to calculate the ratings of users on items. The paper also presents a new model using the ruleset with the rule length of 2 and the proposed measure to suggest to users the list of items with the highest ratings. The new model is compared to the three existing models that use items (such as the popular items, the items with highest similarities, and the items with strong relationships) to make the suggestion. The experiments on the MSWeb dataset and the MovieLens dataset indicate that the proposed recommendation model has the higher performace (via the Precision - Recall and the ROC curves) than the compared models for most of the given.

Author 1: Lan Phuong Phan

Author 2: Hung Huu Huynh

Author 3: Hiep Xuan Huynh

Keywords: Model evaluation; recommendation model; rule based implicative rating measure; ruleset

Paper 29: Distributed QoS Constraint based Resource Adaptation Strategy for Cognitive Radio Networks

Abstract: This paper primarily investigates and addresses the optimal power adaptation strategy problem for multi-user cognitive radio network. The need to determine the optimal power transmission for the secondary user (SU) in a distributed network environment is challenging and important. This requires an efficient adaptive strategy with high convergence capability in order to meet up with the multi-users quality of service (QoS) requirements in a cognitive network and ultimately ensure more efficient resource utilization amongst users. In this paper, a distributed QoS contraint scheme which considered both the transmission power and outage probability has been proposed to maximize the network performance and to control the SUs transmission power. Firstly, the QoS constraint optimization problem for distributed secondary users is formulated and solved in order to adapt with the network dynamics of the cognitive networks. Subsequently, the solution has been used to dynamically adjust the radio power of the SUs to conform with the stringent network constraint and ensures coexistence amongst the users. More importantly, the simulation result shows that the scheme increases the overall network utility when compared to the scheme without adaptation.

Author 1: Yakubu S. Baguda

Keywords: Cognitive radio network; outage probability; quality of service (QoS); network utility; power adaptation; primary user; secondary user

Paper 30: Robust Modeling and Linearization of MIMO RF Power Amplifiers for 4G and 5G Applications

Abstract: In this paper, a novel set of orthogonal crossover polynomials for the baseband modelling and linearization of MIMO RF Pas is presented. The proposed solution is applicable to WCDMA and LTE applications. The new modelling approach has considerably reduced the numerical instability problem associated with the conventional polynomial model identification. In order to validate the efficiency and the robustness of the proposed solution, a 2x2 MIMO LDMOS RF power amplifier has been measured modelled and linearized. A comparison with the conventional polynomial MIMO models showed clearly the superiority of the proposed solution in a fixed-point calculation environment such as DSP and FPGA boards.

Author 1: Imene ZEMZEMI

Author 2: Souhir LEJNEF

Author 3: Noureddine BOULEJFEN

Author 4: M.Fadhel GHANNOUCHI

Keywords: MIMO transmitter; RF power amplifiers; orthogonal polynomials; nonlinear transmitters; digital predistortion

Paper 31: Energy Harvesting for Remote Wireless Sensor Network Nodes

Abstract: Wireless Sensor Network (WSN) technology is widely used for controlling and monitoring purposes. Advancement accomplished in the past era in wireless communications and microsystems have allowed the change of minor degree and least effort sensor nodes outfitted with remote correspondence abilities ready to manufacture a wireless WSN node. Each sensor node is ordinarily outfitted with one or a couple of detecting units, information preparing units, remote correspondence interface and battery. WSNs have discovered application in an extensive variety of various spaces like home and biomedical health monitoring. Providing continuous supply of energy to these nodes at remote locations is a major concern. The aim of this paper is to provide un-interrupted supply of energy to remote WSN nodes. Solar energy is expected to provide the required energy; however, photovoltaic (PV) based system are not able to operate at night. This may influence the operation of WSN nodes, rendering them useless for that instant. Several techniques have been proposed to provide satisfactory energy storage. However, the utilization of a suitable device to provide the required energy storage and operate WSN node for all day long is an open issue. A complete WSN node is developed for flood monitoring with sensing capacity along with energy harvesting using PV system and storage unit, which is able to harvest and store energy for un-interrupted operation of WSN node at remote sites.

Author 1: Engr. Syed Ashraf Ali

Author 2: Engr. Syed Haider Ali

Author 3: Engr. Sajid Nawaz Khan

Author 4: Engr. Muhammad AAmir Aman

Keywords: Wireless sensor network (WSN); photovoltaic (PV)

Paper 32: The Impact of Knowledge Management on Organizational Performance

Abstract: In today’s business, knowledge is considered as a core asset in any organization, even it can be considered as important as technological capital. It is part of human abilities and thus human capital. Knowledge management (KM) is becoming a fad in an increasing way so many organizations are trying to apply it in order to enhance their organizational performance. In this paper, literatures were investigated critically in order to show the real influence of knowledge management and some of its practices on organizational performance. It has been founded that KM including knowledge process and infrastructure capabilities affect positively in a huge manner on all aspects of organizational performance directly or indirectly. In the same vein, there is a huge need to continuously train and educate the learning organizations’ CEOs about the importance of KM through group works and training programs.

Author 1: Hayfa.Y. Abuaddous

Author 2: Abdullah A.M. Al Sokkar

Author 3: Blaqees I. Abualodous

Keywords: Knowledge management; infrastructure capabilities; process capabilities; organizational performance; learning organizations

Paper 33: Wireless Body Area Network Security and Privacy Issue in E-Healthcare

Abstract: Wireless Body Area Network (WBAN) is a collection of wireless sensor nodes which can be placed within the body or outside the body of a human or a living person which in result observes or monitors the functionality and adjoining situations of the body. Utilizing a Wireless Body Area Network, the patient encounters a greater physical versatility and is never again constrained to remain in the hospital. As the Wireless Body Area Network sensor devices is being utilized for gathering the sensitive data and possibly will run into antagonistic situations, they require complicated and very secure security medium or structure to avoid the vitriolic communications within the system. These devices represent various security and privacy protection of touchy and private patient medical data. The medical records of patients are a significant and an unsolved situation due to which a changing or exploitation to the system is possible. In this research paper, we first present an overview of WBAN, how they utilized for healthcare monitoring, its architecture then highlight major security and privacy requirements and assaults at different network layer in a WBAN and we finally talk about various cryptographic algorithms and laws for providing solution of security and privacy in WBAN.

Author 1: Muhammad Sheraz Arshad Malik

Author 2: Muhammad Ahmed

Author 3: Tahir Abdullah

Author 4: Naila Kousar

Author 5: Mehak Nigar Shumaila

Author 6: Muhammad Awais

Keywords: E-Health; privacy; security; wireless body area networks

Paper 34: A Novel Stable Clustering Approach based on Gaussian Distribution and Relative Velocity in VANETs

Abstract: Vehicles in Vehicular Ad-hoc Networks (VANETs) are characterized by their high dynamic mobility (velocity). Changing in VANET topology is happened frequently which caused continuous network communication failures. Clustering is one of the solutions applied to reduce the VANET topology changes. Stable clusters are required and Indispensable to control, improve and analyze VANET. In this paper, we introduce a new analytical VANET's clustering approach. This approach aims to enhance the network stability. The new proposed grouping process in this study depends on the vehicles velocities mean and standard deviation. The principle of the normal (Gaussian) distribution is utilized and emerged with the relative velocity to propose two clustering levels. The staying duration of vehicles in a cluster is also calculated and used as an indication. The first level represents a very high stabile cluster. To form this cluster, only the vehicles having velocities within the range of mean ± standard deviation, collected in one cluster (i.e. only 68% of the vehicles allowed to compose this cluster). The cluster head is selected from the vehicles having velocities close to the average cluster velocity. The second level is to create a stable cluster by grouping about 95% of the vehicles. Only the vehicles having velocities within the range of mean ± 2 standard deviation are collected in one cluster. This type of clustering is less stable than the first one. The analytical analysis shows that the stability and the staying duration of vehicles in the first clustering approach are better than their values in the second clustering approach.

Author 1: Mohammed Saad Talib

Author 2: Aslinda Hassan

Author 3: Burairah Hussin

Author 4: Z.A. Abas

Author 5: Zaniab Saad Talib

Author 6: Zainab Sabah Rasoul

Keywords: VANET; clustering; cluster stability; Gaussian; relative velocity; staying duration

Paper 35: Comparison between NFC/RFID and Bar Code Systems for Halal Tags Identification: Paired Sample T-Test Evaluation

Abstract: Malaysia is a modern Muslim country where the research on Halal product identification is at the peak. In this study, the authors have developed the mobile application which is based on Radio frequency identification near field communication RFID/NFC. The author first developed the database based on the data from Jabatan Kemajuan Islam Malaysia JAKIM, which is Malaysian Halal logo identification authority then the mobile application which uses the Near Field Communication to detect the Halal food using the Radio Frequency Identification. In this paper authors have performed the experimental analysis by comparing the Barcode system that is comprised of parallel line detected by the simple webcam for the Halal logo identification and the new developed RFID NFC mobile application. Paired sample T-Test was performed by using the SPSS 23.0 version. The results revealed that there is significantly difference between the usability, efficiency, affordability, security and satisfaction. The users are more satisfied with the newly developed mobile application as compared to old halal logo system in Malaysia.

Author 1: Mohsen Khosravi

Author 2: Najma Imtiaz Ali

Author 3: Mostafa Karbasi

Author 4: Imtiaz Ali Brohi

Author 5: Irfan Ahmed Shaikh

Author 6: Asadullah Shah

Keywords: Halal products; RFID/NFC; JAKIM; paired sample T-test; Malaysia

Paper 36: Model of Interoperability of Multiple Different Information Systems using SOA Middleware Layer and Ontological Database on the Cloud

Abstract: The exponential evolution of technology and the environment surrounding the information systems (IS) forces companies to act quickly to follow the trend of business workflows with the use of high computer technologies and well adapted to the needs of the market. Currently, the performance of information system is considered a problem, we must intervene to make them more agile and responsive to better support the strategy of the company. The exchange and communication is a must between information systems to address these issues and new requirements, businesses are looking to integrate and interact even their information systems to interconnect applications. Interoperability is essential between information systems, it promotes alignment between the company’s business strategy and IT strategy while respecting the existing technical heritage of the company. The interoperability solutions between information systems face major problems since the SI is independently developed and designed differently and that solutions must meet certain criteria, namely, autonomy, scalability and resolve trade problems of data. The MDA approach is the most suitable solution to our problem because it ensures a degree of independence between the logic the company’s business and technology platform. Moreover, oriented architecture SOA service is used in this sense, it encapsulates the components of the information system into editable and reusable service. We want through this article to contribute to the development of a model for interoperability of several different IS, founded on a middleware layer compound of services according to the architecture SOA. The special feature of our model is that it uses an ontological database in the Cloud that will store concepts exchanged among interconnected IS and uses several transformation layers, integration, homogenization and adapting services.

Author 1: Meryem FAKHOURI AMR

Author 2: Khalifa MANSOURI

Author 3: Mohammed QBADOU

Author 4: Bouchaib RIYAMI

Keywords: Interoperability; middleware layer; SOA; information system (IS); cloud computing; ontological database (ODB)

Paper 37: Intelligent Educational Assistant based on Multiagent System and Context-Aware Computing

Abstract: This paper provides an overview of the current stage of EducActiveCore research, an orchestrated computational model, formed by different areas of artificial intelligent, combined to support personalized assistance to students in distance education process, mainly in interaction with Context-Aware environments. The Context-Aware environment applied in this research is observed in conjunction with IoT technologies. IoT is enabled by the latest developments in smart sensors, RFID, communication technologies, and Internet protocols. The basic premise is to have the resources availability and use arrangements, managed directly without human involvement to deliver a new class of smart environments for students. To support this central idea, a Multiagent model is proposed to assist students in interaction with context, determining autonomously the access to useful resources to students. This article introduces the overall research in progress and, the methods of an experiment tested with basic concepts of this scenario, implemented and used by a group of students in real locations. Results obtained during tests, indicates 93% of successful operation performed by this intelligent model on use prediction of resources and scheduling reservation.

Author 1: Fernão Reges dos Santos

Author 2: Pollyana Notargiacomo

Keywords: Context-aware computing; multiagent systems; artificial intelligence; internet of things

Paper 38: Helitron’s Periodicities Identification in C.Elegans based on the Smoothed Spectral Analysis and the Frequency Chaos Game Signal Coding

Abstract: Helitrons are typical rolling circle transposons which make up the bulk of eukaryotic genomes. Unlike of other DNA transposons, these transposable elements (TEs), don’t create target site duplications or end in inverted repeats, which make them particular challenge to identify and more difficult to annotate. To date, these elements are not well studied; they only attracted the interest of researchers in biology. The focus of this paper is oriented towards identifying the helitrons in C.elegans genome in the perspective of signal processing. Aiming at the helitron's identification, a novel methodology including two steps is proposed: the coding and the spectral analysis. The first step consists in converting DNA into a 1-D signal based on the statistical features of the sequence (FCGS coding). As for the second step, it aims to identify the global periodicities in helitrons using the Smoothed Fourier Transform. The resulting spectrum and spectrogram are shown to present a specific signature of each helitron’s type.

Author 1: Rabeb Touati

Author 2: Imen Messaoudi

Author 3: Afef Elloumi Ouesleti

Author 4: Zied Lachiri

Keywords: Helitrons; C.elegans; Frequency Chaos Game Signal (FCGS) coding; spectral analysis; tandem periodicities

Paper 39: Rainfall Prediction in Lahore City using Data Mining Techniques

Abstract: Rainfall prediction has extreme significance in countless aspects and scopes. It can be very helpful to reduce the effects of sudden and extreme rainfall by taking effective security measures in advance. Due to climate variations, an accurate rainfall prediction has become more complex than before. Data mining techniques can predict the rainfall through extracting the hidden patterns among weather attributes of past data. This research contributes by exploring the use of various data mining techniques for rainfall prediction in Lahore city. Techniques include: Support Vector Machine (SVM), Naïve Bayes (NB), k Nearest Neighbor (kNN), Decision Tree (J48) and Multilayer Perceptron (MLP). The dataset is obtained from a weather forecasting website and consists of several atmospheric attributes. For effective prediction, pre-processing technique is used which consists of cleaning and normalization processes. Performance of used data mining techniques is analyzed in terms of precision, recall and f-measure with various ratios of training and test data.

Author 1: Shabib Aftab

Author 2: Munir Ahmad

Author 3: Noureen Hameed

Author 4: Muhammad Salman Bashir

Author 5: Iftikhar Ali

Author 6: Zahid Nawaz

Keywords: Rainfall prediction; data mining; classification techniques

Paper 40: Concentrated Solar Power Site Suitability using GIS-MCDM Technique taken UAE as a Case Study

Abstract: In recent years, countries have begun to reduce the consumption of fossil fuels and replace them with renewable energy resources in order to mitigate the effects of fossil fuels on the environment and save money besides increasing energy security. This paper has investigated the suitability map for the large-scale projects in concentrated solar power (CSP) in United Arab Emirates (UAE) using GIS data and multi-criteria decision making technique (MCDM). The suitability map is composed of multi-maps (layers) of solar irradiation [Direct Normal irradiance (DNI) component], land slope, protected areas, land use, proximity to water bodies, power grid and the roads. Then, Analytic Hierarchy Process (AHP) method is applied to identify the weights of ranking criteria. The paper has highlighted the most-suitable location as well as non-suitable location among UAE to install CSP projects. The study’s results proved that UAE have multi-hotspot locations can be exploited for CSP projects.

Author 1: Mohammad Basheer Alqaderi

Author 2: Walid Emar

Author 3: Omar A. Saraereh

Keywords: Analytic hierarchy process (AHP); concentrated solar power (CSP); multi-criteria decision making (MCDM); direct normal irradiance (DNI); United Arab Emirates (UAE); hot-spot locations

Paper 41: Formal Specification and Analysis of Termination Detection by Weight-throwing Protocol

Abstract: Termination detection is a critical problem in distributed systems. A distributed computation is called terminated if all of its processes become idle and there are no in-transit messages in communication channels. A distributed termination detection protocol is used to detect the state of a process at any time, i.e., terminated, idle or active. A termination detection protocol on the basis of weight-throwing scheme is described in Yu-Chee Tseng, “Detecting Termination by Weight-throwing in a Faulty Distributed System”, JPDC, 15 February 1995. We apply model checking techniques to verify the protocol and for formal specification and verification the tool-set UPPAAL is used. Our results show that the protocol fails to fulfil some of its functional requirements.

Author 1: Imran Riaz Hasrat

Author 2: Muhammad Atif

Author 3: Muhammad Naeem

Keywords: Termination detection; weight-throwing protocol; formal specification and verification; model checking

Paper 42: Trajectory based Arabic Sign Language Recognition

Abstract: Deaf and hearing impaired people use their hand as a tongue to convey their thoughts by performing descriptive gestures that form the sign language. A sign language recognition system is a system that translates these gestures into a form of spoken language. Such systems are faced by several challenges, like the high similarities of the different signs, difficulty in determining the start and end of signs, lack of comprehensive and bench marking databases. This paper proposes a system for recognition of Arabic sign language using the 3D trajectory of hands. The proposed system models the trajectory as a polygon and finds features that describes this polygon and feed them to a classifier to recognize the signed word. The system is tested on a database of 100 words collected using Kinect. The work is compared with other published works using publicly available dataset which reflects the superiority of the proposed technique. The system is tested for both signer-dependent and signer-independent recognition.

Author 1: Ala addin I. Sidig

Author 2: Sabri A. Mahmoud

Keywords: Trajectory processing; sign language recognition; ensemble classifier; polygon description; parameters tuning; signer independent

Paper 43: A Traffic Congestion Framework for Smart Riyadh City based on IoT Services

Abstract: Internet of Things (IoT) has become one of the most challenging issues in many researches to connect physical things through the internet by creating a virtual identity for everything. Traffic congestion in Riyadh city is chosen due to the proliferation in the number of vehicles on Riyadh roads that is resulting in grumbling by citizens. Currently, there is no reliable service offered to Riyadh citizens from the traffic department enabling them to access traffic information. A new traffic congestion framework for Riyadh is proposed so that it can help the development of traffic congestion services. This framework aims to benefit from the current Riyadh road infrastructure and apply the IoT paradigm for detecting traffic congestion. Sensing devices are used to identify the congestion of the traffic flow through providing multiple proposed services to the citizens such as a vehicle counting, live streaming video and rerouting services. Citizens are able to access all the services by using proposed mobile application connected to the internet, as all those services are integrated with public map Service. By using the services, the citizens are able to identify the exact location where congestion occurs and an alternate solution can be provided easily. To achieve this, Business Process Execution Language (BPEL) is embedded in one of the framework layers. Due to the effectiveness of BPEL, workflows are built to combine the proposed services with the legacy Riyadh services. This approach clearly defines how the services are executed through BPEL models.

Author 1: Hailah Ghanem Al-Majhad

Author 2: Arif Bramantoro

Author 3: Irfan Syamsuddin

Author 4: Arda Yunianta

Author 5: Ahmad Hoirul Basori

Author 6: Anton Satria Prabuwono

Author 7: Omar M. Barukab

Keywords: Traffic congestion framework; Internet of Things; smart city; business process execution language; Software as a Service

Paper 44: Selection of Important Sets by using K-Skyband Query for Sets

Abstract: In this paper, we consider “sets” selection problem from a database. In conventional selection problem, which is “objects” selection problem, the skyline query has been utilized, since it can retrieve a set of important objects where each object isn’t dominated by another object in a database. However, it is not effective when we have to select important sets, each of which contains more than one objects. Thus, we consider a “set skyline query” that retrieves non-dominated sets of objects from a database, which we call “object sets.” The K-skyband query is a popular variant of the skyline query. It retrieves a set of objects, each of which is not dominated by K other objects. In this paper, we propose “K-Skyband set query.” It retrieves important sets instead of objects. We investigated the properties of the query, as well as developing pruning strategies to avoid the unnecessary enumeration of objectsets and comparisons among them. Intensive experiments have been performed to examine the implemented algorithm. The results demonstrate the effectiveness and efficiency of the proposed algorithm.

Author 1: Md. Anisuzzaman Siddique

Author 2: Asif Zaman

Author 3: Yasuhiko Morimoto

Keywords: Set Selection; Skyline Query; Skyline Set Query; Skyband Query; Skyband-set Query

Paper 45: Simulated Annealing with Levy Distribution for Fast Matrix Factorization-Based Collaborative Filtering

Abstract: Matrix factorization is one of the best approaches for collaborative filtering because of its high accuracy in presenting users and items latent factors. The main disadvantages of matrix factorization are its complexity, and are very hard to be parallelized, especially with very large matrices. In this paper, we introduce a new method for collaborative filtering based on Matrix Factorization by combining simulated annealing with levy distribution. By using this method, good solutions are achieved in acceptable time with low computations, compared to other methods like stochastic gradient descent, alternating least squares, and weighted non-negative matrix factorization.

Author 1: Mostafa A. Shehata

Author 2: Mohammad Nassef

Author 3: Amr A. Badr

Keywords: Simulated annealing; levy distribution; matrix factorization; collaborative filtering; recommender systems; metaheuristic optimization

Paper 46: Outsourcing of Secure k-Nearest Neighbours Interpolation Method

Abstract: Cloud computing becomes essential in these days for the enterprises. Most of the large companies are moving their services and data to the cloud servers which offer flexibility and efficiency. Data owner (DO) hires a cloud service provider (CSP) to store its data and carry out the related computation. The query owner (QO) sends a request which is crucial for its future plans to the CSP. The CSP computes all necessary calculations and returns the result back to the QO. Neither the data nor query owners want to reveal their private data to anyone. k-Nearest Neighbour (k-NN) interpolation is one of the essential algorithms to produce a prediction value for an unmeasured location. Simply, it finds k number of nearest neighbours around the query point to produce an output. Oblivious RAM (ORAM) has been used to protect the privacy in cloud computing. In our work, we will perform the k-NN method using the kd-tree and ORAM without revealing both the data-owner’s and query owner’s confidential data to each other or to third parties. The proposed solution will be analysed to ensure that it provides accurate and reliable predictions while preserving the privacy of all parties.

Author 1: Muhammad Rifthy Kalideen

Author 2: Bulent Tugrul

Keywords: Cloud computing; k-Nearest neighbour; spatial interpolation

Paper 47: Modeling of Quadrotor Roll Loop using Frequency Identification Method

Abstract: Model estimation is an important step in quadrotor control design because model uncertainties can cause unstable behavior especially with non-robust control methods. In this paper, a modeling approach of a quadrotor prototype has been proposed. First an initial dynamic model of quadrotor UAV based on Euler-Lagrange formalism was developed. Then the roll system has been estimated using closed loop identification method and frequency domain analysis. An experimental tests has been performed for the roll system to validate the estimated dynamic model.

Author 1: Mizouri Walid

Author 2: Najar Slaheddine

Author 3: Aoun Mohamed

Author 4: Bouabdallah Lamjed

Keywords: Quadrotor; modelling; frequency domain; closed loop identification

Paper 48: A Comparison of Near-Hidden and Information Asymmetry Interference Problems in Wireless Mesh Networks

Abstract: Multi-radio Multi-channel (MRMC) Wireless Mesh Networks (WMNs) have made quick progress in current years to become the best option for end users due to its reliability and low cost. Although WMNs have already been used still the capacity of WMNs is limited due to information asymmetry and near hidden interference among frequency channels. In the past, various research studies have been done to investigate both these issues. To minimise both these interference types and maximise network capacity; channel assignment has always been a critical area of research in WMNs. In this research, a comparative analysis is done between NH and IA interference based on their impact on network capacity. This comparison is made using the existing Optimal Channel Assignment Model (OCAM). After extensive simulations, it is figured out that NH interference performs a major role in degrading overall network capacity up to 4% in comparison to IA interference. Further, in this research an optimal channel assignment model Information Asymmetry and Near Hidden Minimization (INM) model is proposed that collectively minimises both NH and IA interference problems. The proposed model considers three non-overlapping channels 1, 6 and 11 from IEEE802.11b standard. For simulations, four different Multi-radio Multi-channel Wireless mesh topologies have been considered to find out the average network capacity. An extensive simulation in OPNET shows that the proposed INM model performs 7% better than the existing OCAM model in maximising the WMN net capacity.

Author 1: Sadiq Shah

Author 2: Muhammad Atif

Author 3: Samiullah Khan

Author 4: Misbah Daud

Author 5: Fahim Khan Khalil

Keywords: Wireless Mesh Network (WMN); near hidden and information asymmetry interference; non-overlapping channels

Paper 49: Convex Hybrid Restoration and Segmentation Model for Color Images

Abstract: Image restoration and segmentation are important areas in digital image processing and computer vision. In this paper, a new convex hybrid model is proposed for joint restoration and segmentation during the post-processing of colour images. The proposed Convex Hybrid model is compared with the existing state of the art variational models such as Cai model, Chan-Vese Vector-Valued (CV-VV) model and Local Chan-Vese (LCV) model using noises such as Salt & Pepper and Gaussian. Additional four experiments were performed with increasing combination of noises such as Salt & Pepper, Gaussian, Speckle and Poisson to thoroughly verify the performance of Convex Hybrid Model. The results revealed that the Convex Hybrid model comparatively outperformed qualitatively and has successfully removed the noises and segment the required object properly. The Convex Hybrid model used the colour Tele Vision (TV) as a regularizer for denoising of the corrupt image. The Convex Hybrid Model is convex and can get global minima. The PDEs obtained from the minimisation of the Convex Hybrid Model are numerically solved by using explicit scheme.

Author 1: Matiullah

Author 2: Samiullah Khan

Author 3: Noor Badshah

Author 4: Fahim ullah

Author 5: Ziaulla

Keywords: Color images; image restoration; image segmentation; noise

Paper 50: Object-Oriented Context Description for Movie Based Context-Aware Language Learning

Abstract: Context-aware ubiquitous learning is a promising way to learn languages; however, it requires developers and operators of much effort to construct, deploy, and use the specialized system. As its alternative, this paper proposes movie based context-aware language learning (MBCALL) that enables learners to learn languages through quizzes generated along virtual contexts occurring in the movie to be replayed. Since full automatic context capturing from the movie is impossible, the authors define an object-oriented context model (OOCM) and also a textual context description language subject to the OOCM to describe the movie context easily by human work. The OOCM introduces the case grammar concept of natural language processing. This enables quiz generation based on types of the words for objects, actions, and modes found in the movie. Evaluation with a small movie by three subjects shows that the OOCM can guide them to enrich information included in the movie context; therefore, we can generate more types of quizzes based on the movie context.

Author 1: Hazriani

Author 2: Tsuneo Nakanishi

Author 3: Kenji Hisazumi

Author 4: Akira Fukuda

Keywords: Movie based context-aware language learning (MBCALL); object-oriented context model (OOCM); context description language; case grammar

Paper 51: Smart Jamming Attacks in Wireless Networks During a Transmission Cycle: Stackelberg Game with Hierarchical Learning Solution

Abstract: Due to the broadcast nature of the shared medium, wireless communications become more vulnerable to malicious attacks. In this paper, we tackle the problem of jamming in wireless network when the transmission of the jammer and the transmitter occur with a non-zero cost. We focus on a jammer who keeps track of the re-transmission attempts of the packet until it is dropped. Firstly, we consider a power control problem following a Nash Game model, where all players take action simultaneously. Secondly, we consider a Stackelberg Game model, in which the transmitter is the leader and the jammer is the follower. As the jammer has the ability to sense the transmission power, the transmitter adjusts its transmission power accordingly, knowing that the jammer will do so. We provide the closed-form expressions of the equilibrium strategies where both the transmitter and the jammer have a complete information. Thereafter, we consider a worst case scenario where the transmitter has an incomplete information while the jammer has a complete information. We introduce a Reinforcement Learning method, thus, the transmitter can act autonomously in a dynamic environment without knowing the above Game model. It turns out that despite the jammer ability of sensing the active channel, the transmitter can enhance its efficiency by predicting the jammer reaction according to its own strategy.

Author 1: Moulay Abdellatif LMATER

Author 2: Majed Haddad

Author 3: Abdelillah Karouit

Author 4: Abdelkrim Haqiq

Keywords: Wireless networks; jamming attacks; game theory; reinforcement learning

Paper 52: A New Hybrid Intelligent System for Prediction of Medical Diseases

Abstract: This paper proposes a hybrid intelligent system as medical decision support tool for data classification based on the Neural Network, Galactic Swarm Optimization (NN-GSO), and the classification model. The goal of the hybrid intelligent system is to take the advantages and reduce the disadvantages of the constituent models. The system is capable of learning from data sets and reach great classification performance. Consequently, various algorithms have been developed that include Neural Network based on Galactic Swarm Optimization (NN-GSO), Neural Network based on Particle Swarm Optimization (NN-PSO) and Neural Network based on Genetic Algorithm (NN-GA) to improve NN structure and accuracy rates. For the evaluation process, the hybrid intelligent system has used multiple of benchmark medical data sets to evaluate the effectiveness. These benchmarks were gotten from the UCI Repository of Machine Learning. The three-performance metrics were calculated are accuracy, sensitivity and specificity. These metrics are useful for medical applications. The proposed algorithm was tested on various data sets which represent binary and multi-class medical diseases problems. The proposed algorithm performance analyzed and compared with others using k-fold cross validation. The significance tests results have proven that the proposed algorithm is effective to solve neural networks with good generalization ability and network structure for medical diseases detection.

Author 1: Sultan Noman Qasem

Author 2: Monirah Alsaidan

Keywords: Artificial neural network; galactic swarm optimization; particle swarm optimization; genetic algorithm; hybrid intelligent system; medical decision support

Paper 53: Unsupervised Ads Detection in TV Transmissions

Abstract: A novel framework is presented that can segment semantic videos and detect commercials (ads) in a broadcasted TV transmission. The proposed technique combines SURF features and color Histogram in a weighted combination framework resulting in detecting individual TV ads from the transmission after segmenting semantic videos. Thus, better results are achieved. The proposed framework is designed for TV transmissions those who do not use black frame technique between the ad and non-ad part of the transmission and is commonly used in Pakistani TV channels transmission. The television transmission standards in Pakistan are different from those that are used in other countries of the world. The framework used unsupervised technique to segment the semantic videos.

Author 1: Waseemullah

Author 2: Najeed Ahmed Khan

Author 3: Umair Amin

Keywords: TV ads; video segmentation; semantic analysis; ad segmentation; unsupervised segmentation

Paper 54: Performance Evaluation of IPv4/IPv6 Transition Mechanisms for Real-Time Applications using OPNET Modeler

Abstract: The problem of the potential depletion of IPv4 addresses has given rise to the development of a new version of the Internet Protocol named IPv6. This version of the protocol offers many improvements, including an increase in the address space from 232 to 2128 and improvements in security, mobility, and quality of service. However, the transition from the current version to the new version (IPv4 to IPv6) is complicated and cannot be performed in a short time. The size and complexity of Internet make this migration task extremely difficult and time-consuming. The Internet Engineering Task Force (IETF) took into account this migration problem and proposed transition mechanisms as temporary solutions allowing IPv4 to coexist and operate in parallel with IPv6 networks. The dual stack, manual tunnel, and 6to4 automatic tunnel appear to be promising solutions depending on their characteristics and benefits. In this paper, we study the performance of these transition mechanisms on real-time applications (VoIP and Video Conferencing) using the network simulator OPNET Modeler. Performance parameters such as delay, delay variation, jitter, MOS, and packet loss are measured for these transition mechanisms. The obtained results showed that the dual stack transition mechanism gave better network performance than the tunneling mechanisms.

Author 1: Khalid EL KHADIRI

Author 2: Ouidad LABOUIDYA

Author 3: Najib ELKAMOUN

Author 4: Rachid HILAL

Keywords: Dual stack; manual tunnel; 6to4; OPNET; VoIP; video conferencing

Paper 55: SVM Optimization for Sentiment Analysis

Abstract: Exponential growth in mobile technology and mini computing devices has led to a massive increment in social media users, who are continuously posting their views and comments about certain products and services, which are in their use. These views and comments can be extremely beneficial for the companies which are interested to know about the public opinion regarding their offered products or services. This type of public opinion otherwise can be obtained via questionnaires and surveys, which is no doubt a difficult and complex task. So, the valuable information in the form of comments and posts from micro-blogging sites can be used by the companies to eliminate the flaws and to improve the products or services according to customer needs. However, extracting a general opinion out of a staggering number of users’ comments manually cannot be feasible. A solution to this is to use an automatic method for sentiment mining. Support Vector Machine (SVM) is one of the widely used classification techniques for polarity detection from textual data. This study proposes a technique to tune the SVM performance by using grid search method for sentiment analysis. In this paper, three datasets are used for the experiment and performance of proposed technique is evaluated using three information retrieval metrics: precision, recall and f-measure.

Author 1: Munir Ahmad

Author 2: Shabib Aftab

Author 3: Muhammad Salman Bashir

Author 4: Noureen Hameed

Author 5: Iftikhar Ali

Author 6: Zahid Nawaz

Keywords: Sentiment analysis; polarity detection; machine learning technique; support vector machine (SVM); optimized SVM; grid search technique

Paper 56: Defining Network Exposure Metrics in Security Risk Scoring Models

Abstract: Organizations are exposed to cyber-attacks on a regular basis. Managers in these organizations are using scoring systems to evaluate the risks of the attacks they are exposed to. Information security methodologies define three major security objectives: confidentiality, integrity and availability. This work is focused on defining new network exposure measures affecting the availability. According to existing security scoring models network exposure risks are assessed by assigning availability measures on an ordinal scale using users’ subjective assessment. In this work quantitative objective measures are defined and presented, based on the specific organizational network, thus improving accuracy of the scores computed by the current security risk scoring models.

Author 1: Eli Weintraub

Author 2: Yuval Cohen

Keywords: Security; cyber-attack; risk scoring; vulnerability; exposure

Paper 57: Recovery of User Interface Web Design Patterns using Regular Expressions

Abstract: User Interface Web Design Patterns are standard solutions for the development of web applications. The recovery of these patterns from web applications supports program comprehension, reusability, reverse engineering, re-engineering, and maintenance of legacy web applications. The recovery of patterns from web applications becomes arduous due to the heterogeneous nature of web applications. Authors presented different catalogs and recovery approaches for extracting User Interface Web Design Patterns from source code in last one and half decade. There is still a lack of formal specifications for web design patterns, which are important for their recovery from source code. The objective of this paper is to specify User Interface Web Design Patterns (UIWDP) using semiformal specification technique and use these specifications for the recovery of patterns from the source code of web applications using regular expressions. 55 feature types are identified for the specification of 15 UIWDPs. We evaluated our approach on 75 randomly selected web applications and recovered 15 UIWDPs. The standard deviation, precision, recall and F-score measures are used to evaluate the accuracy of our approach.

Author 1: Khalid Mahmood

Author 2: Faiza Tariq

Author 3: Dr. Ghulam Rasool

Keywords: Design patterns; user interface patterns; web applications; web reverse engineering; regular expressions

Paper 58: Internet of Plants Application for Smart Agriculture

Abstract: Nowadays, Internet of Things (IoT) is receiving a great attention due to its potential strength and ability to be integrated into any complex system. The IoT provides the acquired data from the environment to the Internet through the service providers. This further helps users to view the numerical or plotted data. In addition, it also allows objects which are located in long distances to be sensed and controlled remotely through embedded devices which are important in agriculture domain. Developing such a system for the IoT is a very complex task due to the diverse variety of devices, link layer technologies, and services. This paper proposes a practical approach to acquiring data of temperature, humidity and soil moisture of plants. In order to accomplish this, we developed a prototype device and an android application which acquires physical data and sends it to cloud. Moreover, in the subsequent part of current research work, we have focused towards a temperature forecasting application. Forecasting metrological parameters have a profound influence on crop growth, development and yields of agriculture. In response to this fact, an application is developed for 10 days ahead maximum and minimum temperatures forecasting using a type of recurrent neural network.

Author 1: Khurshid Aliev

Author 2: Mohammad Moazzam Jawaid

Author 3: Sanam Narejo

Author 4: Eros Pasero

Author 5: Alim Pulatov

Keywords: Internet of Things; wireless sensor networks; smart agriculture; smartphone applications; artificial neural network; nonlinear autoregressive model; temperature forecasting

Paper 59: A Penalized-Likelihood Image Reconstruction Algorithm for Positron Emission Tomography Exploiting Root Image Size

Abstract: Iterative image reconstruction methods are considered better as compared to the analytical reconstruction methods in terms of their noise characteristics and quantification ability. Penalized-Likelihood Expectation Maximization (PLEM) image reconstruction methods are able to incorporate prior information about the object being imaged and have flexibility to include various prior functions which are based on different image descriptions. Median Root Priors intrinsically take into account the salient image features, such as edges, which becomes smooth owing to quadratic priors. Generally, a 3*3 pixels neighborhood support or root image size is used to evaluate the median. We evaluate different root image sizes to observe their effect on the final reconstructed image. Our results show that at higher parameter values, root image size has pronounced effect on different image quality parameters evaluated such as reconstructed image bias as compared to the phantom image, contrast and resolution in the reconstructed object. Our results show that for the small-sized objects, small root image is better whereas for objects of diameter more than two to three times of the resolution of the reconstructed object, larger root image size is preferable in terms of reconstruction speed and image quality.

Author 1: Munir Ahmad

Author 2: H. M. Tanveer

Author 3: Z.A. Shaikh

Author 4: Furkh Zeshan

Author 5: Usman Sharif Bajwa

Keywords: Penalized-Likelihood expectation maximization; median root priors; maximum-likelihood expectation maximization; full-width-at-half-maximum

Paper 60: Secure and Efficient Routing Mechanism in Mobile Ad-Hoc Networks

Abstract: Securing crucial information is always considered as one of the complex, critical, and a time-consuming task. This research investigates a significant threat to the security of a network, i.e., selective forwarding attack. Protection of information is considered as the main stimulating task in the design of an information system for an organization. The research work proposes a framework that detects the selective forwarding attacks and computes the harmful hosts residing an ad-hoc structure. Our solution is further split into two phases: initial phase is the detection of selective forwarding attacks and the second phase performs the identification of malicious nodes. Performance of the proposed model is evaluated based on the network throughput, which is for the enhancement of security. Simulation of the proposed model is performed using NetLogo and the results show an improvement of 20% in throughput of the network.

Author 1: Masroor Ali

Author 2: Zahid Ullah

Author 3: Meharban Khan

Author 4: Abdul Hafeez

Keywords: Ad-hoc on-demand distance vector; control ACK; mobile ad-hoc network; network throughput

Paper 61: A New Project Risk Management Model based on Scrum Framework and Prince2 Methodology

Abstract: With increasing competition in the software industry, software companies need to effectively manage the risks of software projects with minimal time and cost to deliver high quality products. High frequencies of warning errors and failures in software projects are indicative of human and financial costs in the software projects and teams. One of the reasons for the failure of software projects is the lack of risk management mechanism in the software development process, which can, in case of proper implementation of risk management, increase the success rate of such projects. In most projects, risk management activities are strongly confined to the adopted software methodology. Therefore, is needed a solution or model to overcome this constraint. Scrum is one of the most popular software development methodologies which has recently considered by software teams. This methodology seems not to have paid much attention to risk management. Focusing on this weakness, this research has been trying to provide a model for risk management with the participation of 52 Agile experts from six different countries using the Prince2 project management framework in Scrum methodology. The main goals of this model are to improve the coverage and appropriate risk management mechanism on software projects, increase the project’s success rate and to provide a good estimation of the required time, improve product quality and enhance quality parameters, such as the usability, flexibility, efficiency, and reliability.

Author 1: Mahdi Mousaei

Author 2: Taghi Javdani Gandomani

Keywords: Agile software development; risk management; risk management hybrid model; prince2; scrum; agile risk management

Paper 62: Load Balancing based on Bee Colony Algorithm with Partitioning of Public Clouds

Abstract: Cloud computing is an emerging trend in the IT industry that provides new opportunities to control costs associated with the creation and maintenance of applications. Of prevalent issues in cloud computing, load balancing is a primary one as it has a significant impact on efficiency and plays a leading role in improved management. In this paper, by using a heuristic search technique called the bee colony algorithm, tasks are balanced on a virtual machine such that their waiting time in the queue is minimized. In the proposed model, the cloud is partitioned into several sectors with many nodes as resources of distributed computing. Furthermore, the indices of speed and cost are considered to prioritize virtual machines. The results of a simulation show that the proposed model outperforms prevalent algorithms as it balances the prioritization of tasks on the virtual machine as well as the entire cloud system and minimizes the waiting times of tasks in the queue. It also reduces the completion time of tasks in comparison with the HBB-LB, WRR, and FCFS algorithms.

Author 1: Pouneh Ehsanimoghadam

Author 2: Mehdi Effatparvar*

Keywords: Cloud computing; load balancing; bee colony algorithm; public cloud; cloud partitioning

Paper 63: Combating the Looping Behavior: A Result of Routing Layer Attack

Abstract: Routing layer is one of the most important layers of the network stack. In wireless ad hoc networks, it becomes more significant because nodes act as relay nodes or routers in the network. This characteristic puts them at risk of routing attacks. A wormhole is the most treacherous attack on a routing layer of wireless ad hoc networks. The present proposed techniques require extra hardware, clock synchronization; or they make restrict assumption to deal with this attack. We have proposed a simple behavior-based approach which uses a small amount of memory for recording a few packets received and sent by the neighboring nodes. From this information, a behavior of these nodes is detected, that is, whether the behavior is benign or malicious. Nodes exhibiting malicious behavior are placed in the blocked node list. Malicious nodes are broadcasted in the network. None of the legal nodes in the network entertains any packet from these nodes. This approach has been simulated and verified in ns2.30 which detects and isolates wormhole nodes successfully. The current study focuses on the looping behavior of this attack.

Author 1: David Samuel Bhatti

Author 2: Kinza Sardar

Author 3: Meh Jabeen

Author 4: Umair B. Chaudhry

Keywords: Wormholes attack; wireless routing layer attack; detection time; throughput

Paper 64: Automated Segmentation of Whole Cardiac CT Images based on Deep Learning

Abstract: Segmentation of the whole-cardiac CT image sequence is the key to computer-aided diagnosis and study of lesions in the heart. Due to the dilation, contraction and the flow of the blood, the cardiac CT images are prone to weak boundaries and artifacts. Traditional manual segmentation methods are time-consuming and labor-intensive to produce over-segmentation. Therefore, an automatic cardiac CT image sequence segmentation technique is proposed. This technique was employed using deep learning algorithm to understand the segmentation function from the ground truth data. Using the convolution neural network (CNN) on the central location of the heart, filtering ribs, muscles and other contrasting contrast are not an obvious part of the removal of the heart area. Staked denoising auto-encoders are used to automatically deduce the contours of the heart. Therefore, nine cardiac CT image sequence datasets are used to validate the method. The results showed that the algorithm proposed in this paper has best segmentation impact to such cardiac CT images which have a complex background, the distinctness between the background and the target area which is not obvious; and the internal structure diversification. It can filter out most of the non-heart tissue part, which is more conducive to the doctor observing patient’s heart health.

Author 1: Rajpar Suhail Ahmed

Author 2: Jie Liu

Author 3: Muhammad Zahid Tunio

Keywords: Cardiac CT; segmentation; deep learning; automatic location; contour inference

Paper 65: Energy Efficient Algorithm for Wireless Sensor Network using Fuzzy C-Means Clustering

Abstract: Energy efficiency is a vital issue in wireless sensor networks. In this paper, an energy efficient routing algorithm has been proposed with an aim to enhance lifetime of network. In this paper, Fuzzy C-Means clustering has been used to form optimum number of static clusters. A concept of coherence is used to eliminate redundant data generation and transmission which avoids undue loss of energy. Intra-cluster and inter-cluster gateways are used to avoid nodes from transmitting data through long distances. A new strategy has been proposed to select robust nodes near sink for direct data transmissions. The proposed algorithm is compared with LEACH, MR-LEACH, MH-LEACH and OCM-FCM based upon lifetime, average energy consumption and throughput. From the results, it is confirmed that the performance of the proposed algorithm is much better than other algorithms and is more suitable for implementation in wireless sensor networks.

Author 1: Abhilasha Jain

Author 2: Ashok Kumar Goel

Keywords: WSN, clustering; sleep-awake; virtual grids; multi-hop; routing