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Journal receives papers in continuous flow and we will consider articles from a wide range of Information Technology disciplines encompassing the most basic research to the most innovative technologies. Please submit your papers electronically to our submission system at http://jatit.org/submit_paper.php in an MSWord, Pdf or compatible format so that they may be evaluated for publication in the upcoming issue. This journal uses a blinded review process; please remember to include all your personal identifiable information in the manuscript before submitting it for review, we will edit the necessary information at our side. Submissions to JATIT should be full research / review papers (properly indicated below main title).

Journal of Theoretical and Applied Information Technology
July2019 | Vol. 97 No.13

Title:	RЀNYI ENTROPY FOR MIXTURE MODEL OF ULTIVARIATE SKEW NORMAL-CAUCHY DISTRIBUTIONS
Author:	SALAH H. ABID, UDAY J. QUAEZ
Abstract:	Rényi entropy is the important concept developed by Rényi in the context of entropy theory. We study in detail this measure of information in case of multivariate skew normal Cauchy distributions. Mixture model of these distributions is proposed. In addition, upper and lower bounds of entropy both types Shannon and Rényi are found on this model. Also, an asymptotic expression for Rényi entropy for a mixture of skew distributions is given in approximation by using some inequalities, multinomial theorem and properties of L^p -spaces. Finally, we give a real data examples to illustrate the behavior of Rényi entropy of the proposed mixture model.
Keywords:	Rényi Entropy, Mixture Model, Multivariate Skew Normal Cauchy Distribution, Multinomial Theorem, Approximate Entropy.
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2019 -- Vol. 97. No. 13 -- 2019
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Title:	COMPUTATIONAL-RABIS DRIVER TRAINING MODEL FOR PRIME DECISION-MAKING IN DRIVING
Author:	RABI MUSTAPHA, YUHANIS YUSOF , AZIZI AB AZIZ
Abstract:	Recent development of technology has led to the invention of driver assistance systems that support driving and help to prevent accidents. These systems employ Recognition-Primed Decision (RPD) model that explains how human make decisions based on prior experience. However, the RPD model does not include necessary training factors in making prime decision. Although, there exist an integrated RPD-SA model known as Integrated Decision-making Model (IDM) that includes training factors from Situation Awareness (SA) model, the training factors were not detailed. Hence, the model could not provide reasoning capability. Therefore, this study enhanced the IDM by proposing Computational-Rabi’s Driver Training (C-RDT) model that includes improvement on RPD component of the IDM. The C-RDT includes 18 additional training factors obtained from cognitive theories that make a total of 24 training factors that facilitate driver’s prime decision-making during emergencies. The designed model is realized by identifying factors for prime decision-making in driving domain, designing the conceptual model of the RDT model and formalizing it using differential equation. To demonstrate the designed model, simulation scenarios based on driver’s training and awareness has been implemented. The simulation results are found to support related concepts found in literature. The results also provide insight into the robustness nature of the model. The computational model realized in this study practically can serve as a guideline for software developers on the development of driving assistance systems for prime decision-making process. Also, the computational model when combined with support components can serve as an intelligent artefact for driver’s assistance system. Moreover, the C-RDT model offers reasoning ability that allows backtracking on why certain prime-decision has been made.
Keywords:	Computational Model, Integrated Decision-Making Model, Situation Awareness Model, Primed-Decision Making, Driving Assistance System
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2019 -- Vol. 97. No. 13 -- 2019
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Title:	AUTO-MEASURING USABILITY METHOD BASED ON RUNTIME USER’S BEHAVIOR: CASE STUDY FOR GOVERNMENTAL WEB-BASED INFORMATION SYSTEMS
Author:	ABDELRAHMAN OSMAN ELFAKI, ZAID BASSFAR
Abstract:	Usability testing is a key process in quality assurance of information systems. The traditional usability testing is based on questionnaire techniques which are expensive, time-consuming, and complete by human evaluators including end users opinion, relatively, any evaluation done by human is subjective and expensive. There are no standard usability values that match with all users, hence conduct usability evaluation for each project is recommended. The previous two facts are providing motivation for developing auto-measuring usability method based on runtime user’s behavior. The proposed method is developed based on six metrics extracted from literature. Two software applications represent governmental web-based information system have developed and the six metrics are embedded in these two applications. An experiment has been conducted by using these two software applications. The results are analyzed by statistical methods; and the results prove the practicality and applicability of the proposed method.
Keywords:	Human Computer Interaction; User Interfaces; Information System.
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2019 -- Vol. 97. No. 13 -- 2019
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Title:	MODIFIED APPROACH FOR SOLVING RANDOM ORDINARY DIFFERENTIAL EQUATIONS
Author:	ALI A. ABDULSAHIB, FADHEL S. FADHEL, SALAH H. ABID
Abstract:	This paper deals with the derivation of a modified approach for solving initial value problems of the n-th order random ordinary differential equations by means of using the variational iteration method and numerical integration methods. In addition, the convergence of the obtained sequence of approximate solutions to the exact solution has been proved. Also, some illustrative examples are presented as a numerical simulation in order to illustrate the accuracy and applicability of the proposed approach.
Keywords:	Random Ordinary Differential Equations, Variational Iteration Method, Numerical Integration Method, Trapezoidal Rule.
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2019 -- Vol. 97. No. 13 -- 2019
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Title:	A SMART FUZZY AUTO SUGGESTION SYSTEM FOR A MULTILAYER QR CODE GENERATOR
Author:	BAKRI BADAWI, TEH NORANIS MOHD ARIS, NORWATI MUSTAPHA, NORIDAYU MANSHOR
Abstract:	One of the current major developments in color Quick Response (QR) code requires larger data capacity. Many research works proposed color QR code with a data capacity three times larger compared to black and white QR code. These works emphasize on the algorithm about how to generate color QR code but, it does not provide sufficient information on color QR code generator implementation. In this paper, we will show the implementation for multilayer QR code generator with smart suggestion for the number of colors, based on size available on paper and size of data file. Fuzzy technique is utilized for the smart suggestion. The proposed generator also explains how to add color reference for the generated QR code. This color reference indicates how many colors are used for this QR code. The proposed generator can generate color QR code with data capacity four times larger compared to black and white QR code and a 25% larger color QR code compared to any existing work.
Keywords:	Smart, Fuzzy, Suggestion, Color QR Code, Generator
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2019 -- Vol. 97. No. 13 -- 2019
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Title:	A METHODOLOGY FOR MULTIPLE OBJECT TRAJECTORY PREDICTION IN AIRPORT ENVIRONMENT
Author:	HAMZA TAHERI, AMINA EL GENNOUNI, ABDELOUAHID LYHYAOUI
Abstract:	In Airport environment no single sensor system is capable to fulfil the requirement of tracking and identifying all types of moving objects. Recent years have witnessed the deployments of Wireless Sensor Networks (WSNs) for many critical applications such as security surveillance and target tracking. This technology can help to meet the airport surveillance requirements at a lower cost, being especially interesting for small airports, and to fill radar coverage gaps at larger ones. This paper proposes a global and integrated solution using acoustic sensors to predict target trajectories and prevent collisions critical areas of the airport environment. The proposed system represents a low-cost effective surveillance technology for locating and tracking moving objects, by using a more up-to-date wireless sensor network and tracking algorithms. The preferred system could eventually be an alternative to surface movement primary radar (SMR) which is the most widely used in the world to track airport ground movements. The proposed tracking system uses a special form of PHD filter and particle filter to accurately track multiple targets.
Keywords:	WSN, Particle filter, GM-PHD filter, Tracking, A-SMGCS, Airport;
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2019 -- Vol. 97. No. 13 -- 2019
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Title:	IMPROVING THE TASK SCHEDULING IN CLOUD COMPUTING WITH ANALYTIC HIERARCHY PROCESS
Author:	NAOUFAL ER-RAJI, FAOUZIA BENABBOU, NAWAL SAEL
Abstract:	Cloud Computing has been recently considered as the most demanded technology. It is a new technology that aims to provide computing resources through a network (mostly internet) with an easy use. However, since it is a new technology, it is struggling with some difficulties, one of which is Task Scheduling. The latter, not only has an important role in the Quality of Service (QoS) but also has a big impact regarding the Service Level Agreement (SLA). In this paper, we strive to use Analytic Hierarchy Process (AHP) in order to improve and give more precision for Task Scheduling in Cloud Computing environment through improving the tasks classification in the tasks priority queues. The results of this paper demonstrate that AHP can be used to give more precision for the tasks priority queues instead of the use of the traditional algorithms.
Keywords:	Cloud Computing, Task Scheduling, Analytic Hierarchy Process, Priority Queues.
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2019 -- Vol. 97. No. 13 -- 2019
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Title:	AN SDN TESTBED FOR EVALUATING WIRELESS HETEROGENEOUS NETWORKS
Author:	JUNHYUK PARK, JANFIZZA BUKHARI, WONYONG YOON
Abstract:	This paper presents a proof-of-concept hybrid testbed based on Software-defined networking (SDN) for wireless heterogeneous networks (HetNets) which can be helpful for researchers to assess algorithms and protocols at a large-scale. This prototype uses open source state-of-the-art OpenDaylight controller based on SDN to control simulated OpenFlow switches and Network Simulator NS3 running network topology supporting LTE and WLAN technologies. The proposed testbed can be useful to renovate the HetNets, a feature provided by SDN, given the escalating demand of reliable bandwidth-intensive broadcast services. Targeting multiple radio access technologies (multi-RAT) users, we install Open vSwitch (OVS) on end user devices and use real TCP/IP protocol stack in Linux kernel to generate accurate results. We integrate our testbed to a VLC media server that allows to stream multimedia packets over simulated network and deploy a few use cases over configurable testbed to validate the functionality of our testbed in practice.
Keywords:	SDN, OpenDaylight, LTE, WLAN, Open vSwitch
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2019 -- Vol. 97. No. 13 -- 2019
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Title:	A STUDY ON SENIOR HIGH SCHOOL STUDENTS’ ACCEPTANCE OF MOBILE LEARNING MANAGEMENT SYSTEM
Author:	STEFANUS , TUGA MAURITSIUS
Abstract:	This study investigates senior high school students’ acceptance of mobile learning management system (LMS) and the effect of the level of acceptance on the success of the system in the form of perceptions of satisfaction and student. With 300 respondents from students of private school in Indonesia and using the Structural Equation Modeling (SEM) method, the study was conducted by combining the extended Technology Acceptance Model (e-TAM) and Information System Success (ISS) models. The results showed that self efficacy, personal innovativeness, subjective norms, relative advantages and accessibility systems had a significant positive effect on perceived usefulness and perceived ease of use. Perceived usefulness and perceived ease of use give a significant positive effect on the behavioral intention of students to use mobile LMS. Students' behavioral intention has a significant positive effect on learning satisfaction and learning achievement perceived by students. The findings of this study present an understanding of the use of mobile LMS by students in senior secondary education.
Keywords:	Information System Success Model, Mobile Learning Management System, Learning Achievement, Learning Satisfaction, Technology Acceptance Model.
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2019 -- Vol. 97. No. 13 -- 2019
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Title:	ADAPTIVE LOAD BALANCE METRIC FOR OPPORTUNISTIC MULTIMEDIA WIRELESS MESH NETWORKS
Author:	S. HARIKISHORE, Dr.V.SUMALATHA
Abstract:	Opportunistic Routing (OR) is a novel routing prototype that carries benefit of the transmission characteristic of a wireless channel for video data distribution in a Wireless Mesh Network (WMN). In a WMN, the communication efficiency diminishes due to the limitation of channel interference, packet loss, and bandwidth. However, most of the existing OR focused on a suitable conniving solution for electing the forwarder node. As a result, several nodes may become overloaded with high traffic and seriously congested. To overcome these problems, we introduce an Adaptive Load Balance metric for Opportunistic Multimedia (ALBOM) WMN. The main objective of this scheme is to reduce overload and increases OR efficiency in WMNs. In this scheme, the adaptive load balance metric is measured by channel access overhead, protocol overhead, the rate of video data transmission and transmission state time. This metric computation that helps to reduces traffic congestion and improves overall network throughput. In this scheme, the best forwarder node is elected by the cuckoo search algorithm. This algorithm finds the best node from the forwarder list based on the Adaptive Load Balance metric, the packet received ratio and deviation time. The ALBOM maximizes the progress each packet to guarantee that the most desired relays the packet with less overload. The simulation results illustrate that ALBOM mechanism increases the throughput and reduces the network delay in WMN.
Keywords:	Opportunistic Routing, Adaptive Load Balance Metric, Forwarder Node, Cuckoo Search Algorithm, Wireless Mesh Network.
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2019 -- Vol. 97. No. 13 -- 2019
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Title:	THE USE OF AUTOMATION AND ROBOTIC INNOVATIONS IN THE TRANSFORMATIONAL COMPANIES: SYSTEMATIC LITERATURE REVIEW
Author:	MOHAMMED ALDOSSARI, ABDULLAH MOHD ZIN
Abstract:	Without a doubt, robotics has a crucial role to play in industrial firms, and in turn, in the overall economic development. Robotics and automation can hold the key to industrial companies’ progress and as such, for the industry to be enhanced, new technologies have to be adopted for increased productivity. In effect, the adoption of new technologies calls for the examination of the factors that could facilitate their proper and effective adoption and use. Robots call for the determination of innovative and creative ways to make use of technology in the hopes of differentiating the company from its rivals in order to ultimately achieve sustainable advantage. This paper aims to identify the factors influencing the behavioral intention to adopt robotics and automation among transformational companies in the kingdom of Saudi Arabia (KSA). This identification is based on systematic literature review that lead to construct a conceptual framework for the proposed adoption of robotics and automation. The results show that there are main factors to guarantee the successful use and adoption for robotics and automation. These are perceived ease of use, perceived usefulness, it infrastructure, subjective norm, top management support, financial support, training, readiness, efficacy, reliability, security and anxiety.
Keywords:	Robotics, Automation, Adoption, Saudi Arabia, Transformational Companies.
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2019 -- Vol. 97. No. 13 -- 2019
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Title:	USING FUZZY SOFT SET ASSOCIATION RULE MINING APPROACH TO IDENTIFY THE STUDENT SKILL DATA ASSOCIATION
Author:	DEDE ROHIDIN, NOOR A. SAMSUDIN, MOHD F. AB. AZIZ, SHAMSUL K. A. KHALID
Abstract:	Graduates shall see the importance of improving their skills to prepare themselves to get the right jobs. Considering such important requirements, therefore many universities have designed various skill development programs in their curriculum. The students enrol in these programs and eventually, their skills performance will be evaluated using certain scores. This research does not aim to calculate the scores. Instead, we focus on how to find the relationship between parameters presented for the evaluation. In this study, we use the fuzzy-soft-association-rule mining (FSAR) approach and proposed the fast algorithm for finding association rule on fuzzy soft set. FSAR is a tool that combines Fuzzy Soft Set concepts and Association Rule Mining. We found that FSAR is an effective method to describe the relationship between parameters in large size data. Using FSAR, we will find a significant parameter or uncorrelated parameters for further analysis. This study recommends the selected parameters for determining the type of training for students. By selecting the right training, the University can reduce training cost significantly.
Keywords:	Association Rules, Soft Set, Fuzzy-Soft-Association Rule
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2019 -- Vol. 97. No. 13 -- 2019
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Title:	CONDITION-BASED MAINTENANCE USING DATA MINING TECHNIQUES ON INTERNET OF THINGS GENERATED DATA
Author:	FRANKY RADIANSYAH, TUGA MAURITSIUS
Abstract:	Heavy Equipment Industry have various business counterparts, including mining industries, infrastructure contractors, and as well as any kind of manufactures. Currently companies in the similar business are working hard on how to optimize the maintenance activities on their heavy equipment. Maintenance of those equipment could be very crucial to the business continuity. This paper provides an alternative to optimize such an activity through an approach called condition-based maintenance. We conducted our research in one international heavy equipment rental company based in Singapore and has a branch in Indonesia. The company's core business is on heavy equipment rental including Excavator. The research focused on utilizing data generated by sensors attached to the Excavator with the main aim is to predict the Remaining Useful Life (RUL) of Oil Grease Pump which is a crucial component of the Excavator. We used some machine learning techniques such as Linear Regression, Decision Tree Regression, and Random Forest methodology to build models to predict the RUL. The results from each models were compared each other to gain a deeper insight on the predictive ability of each model using the data provided. It turns out that the linear regression model gives the highest predictive accuracy with 61% of RMSE.
Keywords:	Machine Learning, Condition Based Maintenance, Predictive Maintenance
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2019 -- Vol. 97. No. 13 -- 2019
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Title:	PRIVACY ISSUES IN E-COMMERCE
Author:	MOHAMMAD AWNI AHMAD MAHMOOUD, ABEER ATALLAH ALOUDAT, LAITH TALAL KHRAIS, SUKINAH ALJISHI, YOSRA HAMZA, MOHAMED NOURELDIN SAYED
Abstract:	The sales and purchase of goods and services through online platforms is increasingly gaining prominence around the globe. Most businesses are currently adopting e-commerce as an option of increasing the profitability of their goods and services. The internet has been an important channel for consumers to source for goods and services, and also as convenient way of making payments. Security of the online business is very important for its success. The research, therefore intends to identify and discuss various privacy and security issues within e-commerce. The research found that there were different causes of security breaches which can compromise the safety of e-commerce operations. The study also found out that there were numerous measures that businesses can implement to counter the rising threat to the security of online-based businesses.
Keywords:	Privacy, E-Commerce, Cyber Law, Technology, Cyber Attacks
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2019 -- Vol. 97. No. 13 -- 2019
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Title:	IMPROVING TRAFFIC SIGN DETECTION WITH DEEP CONVOLUTIONAL NEURAL NETWORKS
Author:	HOANH NGUYEN
Abstract:	Motivated by the observation that traffic signs are still not well-detected by deep convolution neural network-based methods because of the constraint of the size of feature maps, this paper is focused on improving the performance of traffic sign detection, especially for small-sized traffic signs. In this paper, a novel approach for traffic sign detection based on Faster R-CNN framework is proposed. First, Inception-ResNet model is used as the base network to provide a rich and discriminative hierarchy of feature representations. Next, a deconvolutional module is integrated into Faster R-CNN framework to bring additional context information which is helpful to improve the detection accuracy for small-sized traffic signs. Finally, atrous convolution is adopted in the region proposal network to enlarge the receptive field of the synthetic feature map. Experimental results on the German traffic sign detection benchmark show that the proposed approach obtained an accuracy comparable to other the state-of-the-art approaches in traffic sign detection.
Keywords:	Traffic Sign Detection, Convolutional Neural Network, Intelligent Transportation Systems, Object Detection, Deep Learning
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2019 -- Vol. 97. No. 13 -- 2019
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Title:	INTEGRATION OF SPECTRAL MIXTURE ANALYSIS FROM THAICHOTE SATELLITE DATA TO IDENTIFY GREEN VEGETATION CANOPY DENSITY
Author:	SUNSANEE MANEECHOT, RASAMEE SUWANWERAKAMTORN
Abstract:	Many studies have assessed forest canopy density which is a major factor in evaluating forest status and is an important indicator of possible management interventions. Using satellite remote sensing has proved cost effective means of mapping and monitoring environment in terms of vegetation and other ecological issues. In this study, we demonstrated a new method based on the spatial integration which was operated by combining a spectral mixture analysis (SMA) into multispectral bands to create the green vegetation canopy density (GVCD). The GVCD approach was used to classify the forest canopy density in the Phu Phan National Park, Sakon Nakhon province where it is located in the Northeast of Thailand; it covers an area of approximately66,470 hectares. THAICHOTE multispectral image with 15-m resolution acquired in 2015 was used in the analyzing process. A spatial integration of green vegetation fraction (GV) and soil fraction derived from SMA technique and scaled shadow index (SSI) was digitally performed and analyzed to classify GVCD. In addition, ground truth investigation of 48 exemplars was conducted to establish the reliability of model used for GVCD. The agreement between the results and the ground observation was reliably obtained with Kappa coefficient of 0.68 and overall accuracy of 79.17%. The results showed the ability of GVCD approach measured by using the analyzed results of VD and SSI to calculate and detect the forest canopy density. This study also revealed the potentiality of THAICHOTE data in monitoring and identifying vegetation conditions.
Keywords:	Spectral Mixture Analysis (SMA); Green Vegetation Canopy Density (GVCD); Green Vegetation fraction (GV); Soil fraction; THAICHOTE data
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2019 -- Vol. 97. No. 13 -- 2019
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Title:	STRUCTURING THE QUADRATIC EFFECT OF MOTIVATION TOWARDS MENTAL TASKS PERFORMANCE AMONG UNIVERSITY STUDENTS
Author:	ANATALIA N. ENDOZO
Abstract:	The concept of mental tasks performance is widely used, but practical evidence is essential to completely understand this construct and its related variables. The purpose of this paper was to explore the quadratic effect of motivation towards mental tasks performance and its relationship towards concentration, confidence, coping up with pressures and motivation among university students in the Philippines. Additionally, modern institutions are placing emphasis on motivation theories cognizant to mental task performance implications, Most of the studies focused on sports and descriptive findings lack critical investigation. Therefore, it is suggested that current theories could be developed as a new model. A questionnaire was adopted and version three of SmartPls software was utilized to structure the quadratic effect of motivation model with over four hundred respondents. All the suggested key drivers supported at the p-value <.5 and no quadratic motivation effect on cope with pressure. A total variance explained of 59.2% was achieved. Replication of this study in the future would support the generalibility of findings.
Keywords:	Smartpls, Quadratic Motivation Effect, Mental Task Performance, Motivation, University Students
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2019 -- Vol. 97. No. 13 -- 2019
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Title:	TEAM PERFORMANCE IN SAFETY CRITICAL SYSTEMS: REVIEW AND APPROXIMATION BY FUZZY-AHP
Author:	JIHAD OUAHLI, ABDELGHANI CHERKAOUI
Abstract:	The question of team performance still a big challenge for ergonomics in industrial and safety critical systems (SCS) where failure might generate a loss in life, significant economic damage or environmental harm. While the human factor is an important component of safety creation and while team work processes are primordial in SCS, it is important to monitor and enhance team performance to promote the global safety. In fact, there is no consensus on team performance (TP) modeling because of multitude of parameters and their inference involving different disciplines. In addition, an applicable numerical quantification and measurement of TP in ergonomics still needed. In this paper, we present a new TP model based on largely debated cognitive concepts, such as situation awareness and human reliability in systemic approach of safety management. The proposed model is a macro perspective of TP operation that could be generalized and applicable in different SCS. In the second part, we aim to benefit from the Fuzzy Analytic Hierarchy Process (FAHP) progress, as a tool of decision making, to propose a method of team selection. The TP model presented in first section is the basis of a FAHP numerical problem. This application is a novelty in approximating TP according to multi-criteria decision making modeling and proposes an applicable tool to practitioners and managers in industrial SCS. A numerical case study in railway is proposed to explicit the methodology of application.
Keywords:	Team performance, situation awareness, Fuzzy- AHP, safety critical system.
Source:	Journal of Theoretical and Applied Information Technology 15^th July 2019 -- Vol. 97. No. 13 -- 2019
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