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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

August 2017 | Vol. 95 No.16

Title:	NEW APPROACH IN COLOR DISTORTION REDUCTION IN UNDERWATER CORAL REEF COLOR IMAGE ENHANCEMENT BASED ON ESTIMATION ABSORPTION USING EXPONENTIAL EQUATION
Author:	PUJIONO, PULUNG NURTANTIO ANDONO, EKO MULYANTO YUNIARNO, I KETUT EDDY PURNAMA, MOCHAMAD HARIADI
Abstract:	Indonesias coral reef shares 18% part of the worlds coral reef. It is estimated that Indonesias coral reef comprises of 51,000 km2. It is estimated that 7% of coral reef is in very good condition, 33% good, 45% is damaged, and 15% poor. The color of coral reef indicates its health. One difficulty to identify the original color of coral reef is that the color changes when it is taken out of water. Color distortion of an underwater image is caused by light spread and color change. Color spread occurs because some light beam is reflected and refracted by underwater environment, whereas underwater object color change is caused by different light wave when spreading in the water. This research proposes an exponential approach to enhance the appearance of coral reef in underwater image. This approach restores the color constancy of red, green, and blue. The result is measured by using Peak Signal to Noise Ratio, and it gives PSNR value of 20.58. We concluded that exponential approach can enhance underwater coral reef color well.
Keywords:	Coral Reef, Color Image Enhancement, Absorption, Color Constancy, Exponential Equation
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	PARALLEL IMPLEMENTATION OF COVARIANCE TRACKING WITH EFFICIENT MODEL UPDATE
Author:	ANUJA KUMAR ACHARYA, BISWA RANJAN SWAIN, BISWAJIT SAHOO
Abstract:	Most of the appearance based tracking algorithm developed in the recent past are characterized by high computation-intensive operations and demands high memory and performance requirements. These appearance based model are also highly sensible to the variation of extrinsic and intern-sic parameter of the feature. In order to track the object under the variation of intern-sic and extern-sic factor , a new model update approach is developed and implemented using a thread level parallelism. Furthermore Particle filter is added to this current method to better handle the back ground clutter, as well as the temporary occlusion. Parallelized implementation achieves significant speedup, and meets the target frame rate under various configurations. Simulation shows that the current parallel method is robust and very effective for the object tracking.
Keywords:	Covariance Matrix, Feature Vector, Thread, Spatial Feature.
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	THE STRATEGIC ROLES OF INFORMATION SYSTEM: A CASE OF SMALL MEDIUM ENTERPRISES
Author:	WILSON WIYATNO, TOGAR ALAM NAPITUPULU, EDI ABDURACHMAN
Abstract:	Information system is not only a support or tool for enterprise, but it has also plays strategic role, a new weapon to enhance business competitiveness. Development of small medium enterprises in Jakarta, Indonesia is very fast, that it makes intense competition between small medium enterprises. This research aims at finding the impact of information system strategy on business competitiveness among small medium enterprises moderated by technology dependency. Questionnaires are distributed to low to top level management of small medium enterprises in Jakarta. Data are analyzed using Structural Equation Model with Partial Least Square method. The result proves that there are significant effects of information system strategy on business competitiveness of small and medium enterprises. Hence, IS/IT strategy does contribute to enhancing competitiveness of small and medium enterprises. The contribution however varies between 57 to 67 percent from the four Business Balanced Score Card perspectives. It was also found that there are no significance differences between technology dependent enterprise and non-technology dependent enterprise on the impact of IS/IT strategy on competitiveness of the SMEs.
Keywords:	Information System Strategy, Business Competitiveness, Small Medium Enterprises, Technology Dependency, Partial Least Square
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	INTEGRATING QUALITY FEATURES INTO TECHNOLOGY ACCEPTANCE MODEL FOR EXAMINING THE ACCEPTANCE OF MOBILE BANKING
Author:	MALEK ZAKARYA ALKSASBEH, BASSAM A. Y. ALQARALLEH
Abstract:	Although the banking sector in Jordan is a regional leader in Mobile banking (MB), but it is still working hard to achieve full utilization of MB services to add value to users in order to enhance customer relationships and to achieve some cost advantages. Advancements and innovations in mobile technologies are leading the banking sector to new and innovative banking services. New MB system technologies and services enable some new capabilities that allow customers to be active. When MB system with new technologies and services is presented, it needs to be accepted by its users. The acceptance of MB system can be influenced by different factors. The aim of this study is to examine the effect of three key quality features (system quality, information quality, and service quality) on customers beliefs which may significantly influence the users acceptance of MB. The model of this study is mainly based on extending technology acceptance model (TAM). The questionnaires were distributed to 354 customers selected based on the systematic sampling method. 253 usable questionnaires were returned and used to conduct the hypothesis test. The usable response rate was 71 %. Our study highlights the importance of the system quality, information quality, and service quality as the primary antecedents of MB acceptance. The research results revealed that these three variables had positive effects on customers perception with regard to their beliefs (i.e., perceived usefulness and perceived ease of use); and as a result, this positive effect can lead to enhance customers behavioral intention to use MB application.
Keywords:	Mobile banking acceptance, TAM model, System quality, Information quality, Service quality
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	FAST SUMMARIZATION OF LARGE-SCALE SOCIAL NETWORK USING GRAPH PRUNING BASED ON K-CORE PROPERTY
Author:	ANDRY ALAMSYAH, YOGA PRIYANA, BUDI RAHARDJO, KUSPRIYANTO
Abstract:	Graph based modelling is common in many implementation areas involving combinatorics relationship such as in social network. The data explosion produced from user generated content in online social network services trigger the emergence of large-scale social network. Having large graph at our disposal gives us many opportunity but at the same time increase the complexity problem, especially in several graph metric computations and also at graph visualization. A fast summarization methods is needed to reduce the graph size into the only most important pattern. This summarize sub-graph should represent the property or at least converge to the value of the original graph property. Social Network is characterized by scale free degree distributions, which have fat-head less important nodes that can be removed. Graph Pruning method is introduced to remove less important nodes in certain graph context, thus reduce the complexity of large-scale social network while still retain the original graph properties. The method is based on k-core graph properties. The paper show how is the effect of graph pruning to the several most used social network properties.
Keywords:	Social Network Analysis, Graph Pruning, Graph Theory, K-Core, Graph Sampling
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	A PATIENTS INDOOR POSITIONING ALGORITHM USING ARTIFICIAL NEURAL NETWORK AND SVM
Author:	YUSRINA TIFANI, BYUNGKWAN LEE , EUNHEE JEONG
Abstract:	This paper proposes a patients Indoor Positioning Algorithm using Artificial Neural Network and Support Vector Machine (SVM). The proposed algorithm is ANN-SVM which combines Artificial Neural Network and Support Vector Machine to estimate the user position for IPS. The input data for the algorithm consists of Received Signal Strength Indicator and the location vector which is extracted by Access Point. The output is input weight and output weight. The input and output weight are processed by SVM with Room ID data. The last output is the estimated x and the room ID. According to the result of average class loss rate, SVM and ANN-SVM are 0.45 and 0.4, ANN-SVM has lower class loss rate by 0.05 than SVM. The accuracy rate of SVM and ANN-SVM are 65% and 70%. The ANN-SVM has more accuracy rate by 5% than SVM.
Keywords:	Indoor Positioning System, Received Signal Strength, Artificial Neural Network, Support Vector Machine, ANN-SVM
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	CONCEPTUAL AND PHYSICAL DESIGN OF EVALUATION PROGRAM FOR OPTIMIZING DIGITAL LIBRARY SERVICES AT COMPUTER COLLEGE IN BALI BASED ON CSE-UCLA MODEL MODIFICATION WITH WEIGHTED PRODUCT
Author:	DEWA GEDE HENDRA DIVAYANA, AGUS ADIARTA, IDA BAGUS GEDE SURYA ABADI
Abstract:	This study aimed to obtain information about the appropriate aspects used to evaluate digital library services in the terms of System Assessment, Program Planning, Program Implementations, Program Improvements and Program Certifications components, as well as to obtain the conceptual and physical application design for CSE-UCLA evaluation model that had been modified by weighted product. The method used in this research was development method with Borg and Gall development design model. The subjects involved in the preliminary trial of this study were educational experts and informatics experts. Data analysis technique used in this research was quantitative descriptive analysis technique. The results of this study indicated that there were 26 aspects used in evaluating digital library services reviewed by CSE-UCLA model components. It was profen by the assessment percentage average which reached 92.86% with very good category, the conceptual design in the form of database design was appropriate with the standard needs of a database was proven by assessment average percentage at 87.50% with good category, the physical design in the form of user interface design was suitable with the needs of application programming functionality. It was proven by the assessment average percentage. It was 88.75% with good category.
Keywords:	Evaluation, CSE-UCLA, Weighted Product, Digital Library
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	AN OPTIMAL KEY MANAGEMENT TECHNIQUE FOR SECURE DATA TRANSMISSION IN MANET
Author:	M. ANUPAMA, DR. B. SATHYANARAYANA
Abstract:	Cryptographic techniques are commonly used for secure data transmission in wireless networks. Most cryptographic techniques, such as symmetric and asymmetric cryptography, often involve the use of cryptographic keys. Key management is one of the vital aspects of security in mobile ad hoc networks. In mobile ad hoc networks, the processing load and complexity of key management are strongly subject to restriction by the nodes available resources like energy and the dynamic nature of network topology. The Key Management technique is proposed which uses symmetric key management. The distribution of keys in an authenticated manner is a difficult task in MANET. In this paper, we have proposed a secure and optimal key management system in MANET. Initially the mobile input nodes are selected with the aid of soft computing technique. The nodes are clustered by using Fuzzy C-means (FCM) clustering algorithm. The clustered nodes are then optimized in order to select the exact amount of nodes for communication. This optimization can be performed with the aid of Enhanced Bacterial Foraging Optimization (EBFO) technique. We use this for authenticating and key sharing to forward security parameters in a novel and secure way. For authentication, we will use the Elliptic Curve Deffie-Hellman (ECDH). This key exchange scheme shares a symmetric key among parties, which is necessary to have a low cost confidentiality in upcoming communications. This delivers a minimum overhead on the network by using ECDH.
Keywords:	Cryptography, Key Management, MANET, Fuzzy C-means clustering, Enhanced Bacterial foraging, Elliptic Curve Deffie-Hellman
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	SOCIALIZING BUSINESS PROCESS USING ENTERPRISE SOCIAL NETWORK SENTIMENT ANALYSIS: ESAF
Author:	AMJED AL-THUHLI, MOHAMMED AL-BADAWI
Abstract:	Sentiment analysis has become a rich research area due to the growth of social networks applications in the enterprise market. The influence of sentiment analysis has entered the business process domain through enterprise social networks. Sentiment analysis collected from public applications such as Twitter helps organizations to improve their business processes in order to provide good service or better products. However, the amount of research in this field is limited. Existing studies and researches focus only on the results of sentiment analysis without considering impact of these results on the organization business process and how it effects the improvement of products or services. In this context, this research identifies the process of reusing the analysis of sentiment analysis in the organization business application and proposes a framework, eSAF (Enterprise Sentiment Analysis Framework) to enhance organization business processes using Twitter sentiment analysis. The framework crawlers Twitter API from ESN, filter gathered data and apply sentiment analysis techniques based on Naive Bayes algorithm. Finally, it exposes the result into a SOA environment in the form of web services to be used in other business applications. The framework shows promising results in term of users opinions and satisfaction, which provides organizations with accurate statistics about their products or services allowing for future improvements.
Keywords:	Sentiment Analysis, Web Service, Business Process, SOA
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	OPTIMIZING GENOME FEATURES USING T-TEST TO CLASSIFY THE GENE EXPRESSIONS AS CORONARY ARTERY DISEASE PRONE AND SALUBRIOUS
Author:	E. NEELIMA , M.S. PRASAD BABU
Abstract:	Cardio Vascular Disease in terms of coronary artery disease and myocardial infractions are one of the majorly impacting factors towards the mortality rates. The kind of revolutionary developments that has taken place in the genomic diagnosis and the solutions that are developed for diagnosis of heart diseases based on analysis of molecular data of blood cells has improved the accuracy of diagnosis phenomenally. In recent past, analysing gene expression data and using for contemporary misnaming models. Particularly using machine learning strategies to predict and classify the given unlabelled gene expression record. In regard to this a substantial requirement is feature optimization, which is since the overall genes observed in human body are closely 25000 and among them 636 genes are cardio vascular related. Hence, it complexes the process of training the machine learning models using these entire cardio vascular gene features. Hence, this manuscript proposed the usage of ANOVA standard called t-test to select optimal features. The experimental study indicating that the number of optimal features those selected by proposed model is substantially low that compared to the other contemporary models. Divergent classifiers those trained by the features selected through proposal evinced significance in classification accuracy. We compare the results obtained from divergent classifiers those trained by the features selected using proposal and other contemporary model for performance analysis.
Keywords:	Gene Expression, Cardio Vascular Disease, Myocardial Infraction, T-Test, Coronary Artery Disease, Predictive Analysis, Genome Feature Optimization, CAD Genes, Loci, Snps
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	ASSESSING THE BEHAVIOURAL INTENTION OF STUDENTS TOWARDS LEARNING MANAGEMENT SYSTEM, THROUGH TECHNOLOGY ACCEPTANCE MODEL - CASE OF IRAQI UNIVERSITIES
Author:	LAYLA SAFWAT JAMIL
Abstract:	The increasing pace of advancements in the technological domain has influenced all the business and economy sectors of the world. Similar trends have been observed in the educational domain in terms of the adoption of e-learning platforms of LMS - Learning Management System, particularly. The success rate of e-learning adoption is exceptional in the developed regions of the world; however, its adoption in the Middle East and other developing economies is regarded as being in its infancy. This particular study has assessed the behavioural intention of the students of Iraq, being in its infancy in terms of internet adoption; thus, going through the transformation of traditional modes of learning into e-learning modes. The study believes the adopted situation of LMS as the e-learning tool in the four selected higher educational institutes of Iraq. Accordingly, Technology Acceptance Model is deployed to assess the behavioural intentions of the students towards LMS. As a result, the students are affirmed to have significant impacts of perceived ease of use - E, and perceive usefulness - PU over their behavioural intention - BI for LMS. Besides, the attitudes towards the use (A) of LMS are also affirmed to have significant association with the other constructs of TAM.
Keywords:	Technology Acceptance Model (TAM), e-learning, Learning Management System (LMS), Higher Education, Iraq
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	FLEXIBLE CHANNEL EXTRACTOR FOR WIDEBAND SYSTEMS BASED ON POLYPHASE FILTER BANK
Author:	S. CAPPELLO, G.C. CARDARILLI, L. DI NUNZIO, R. FAZZOLARI, M. RE P. ALBICOCCO
Abstract:	Some applications as Software Defined Radio (SDR) and Cognitive Radio require the analysis of wideband signals and/or the processing of multiple channels that can be located anywhere in the available band. These requirements can be satisfied using hardware platforms based on fast Analog to Digital Converters (ADCs) and reconfigurable hardware, such as FPGAs. Unfortunately, while modern ADCs allow the acquisition of wideband signals at high sampling rates (many Gsps), FPGAs are not able to work with very high rates. In this work, authors propose a solution to overcome this problem in a class of applications. The solution is based on the coupling of a Time-Interleaved ADC (TI-ADC) with an FPGA front-end, exploiting the properties of a perfect reconstruction polyphase filter bank. The proposed system is able to select and process channels located anywhere in the input wide band and to re-aggregate two or more of them obtaining a new channel with variable width.
Keywords:	SDR, Cognitive radio, Polyphase filter bank, FPGA, TI-ADCs
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	REAL TIME MOTION DETECTION AND TRACKING SYSTEM BY KALMAN FILTER
Author:	Dr. S. SHIYAMALA, Dr. T. KAVITHA , Dr. P. NAGARAJAN
Abstract:	The immense growth in the area of computer vision systems made motion detection and tracking an at-tractive research topic. Video surveillance is an vital area, its applications including both indoor and out-door automated surveillance systems. In the context of smart home environments, surveillance systems have as principal end to control the safety and the security of materials and of people living in a domestic environment. The automatic analysis and understanding of behaviour and interactions is a crucial job in the design of socially intelligent video surveillance system. The automatic detection addresses several hu-man factor issues underlying the existing surveillance systems. This paper introduces a technique for mo-tion detection and tracking that incorporates several innovative mechanisms. The algorithm presented here is applicable only for binary images and it have two-step procedure. Most challenging task in any facial classification technique is the representation of face in terms of a vector. This vector provides input to a trained classifier and classifier performs final classification. Input vector should represent facial character-istics in most efficient manner such that while it contains all possible information about face. When the segmentation value becomes 1.5, could achieve 95% of tracking of the human in the real time video.
Keywords:	Background estimator, motion detection, image segmentation, object classification, auto threshold.
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	NEW HIERARCHICAL MODEL FOR MULTICLASS IMBALANCED CLASSIFICATION
Author:	HANAA S. ABDALAZIZ, FAKHRELDEEN A. SAEED
Abstract:	Multiclass imbalanced datasets exist in a wide variety of real-world applications where each instance should be assigned to one of N different classes that suffer from imbalanced distribution of instances. The misclassification of such instances is much expensive because they are the most intended. Another fact is that there is a significant concentration on the binary class imbalance problem, while multiclass datasets have been received less consideration. The main aim of this paper is at getting a more precise assignment of the few or the rare examples to their minority classes via presenting a novel hierarchical model based on Support Vector Machine (SVM) and MultiSVM. The model works using a new Algorithm (we call it Grouping Algorithm, it is not clustering) to create new balanced artificial groups from the original imbalanced classes, then heals the multiclass situation and carries out classification process through hierarchical steps. The model is tested with and without adding weights during classification process as well as the support vector machine, so results of the four machines are compared. The experiments are performed on nine Multiclass imbalanced datasets from U.C.I Repository from different fields and characteristics. When applying the proposed hierarchical model without weight, it achieves the best results in 4 out of 9 datasets in terms of Accuracy and kappa. When empowered with the weight it presents the best of 6 of 9 datasets in terms of G-mean, 4 of the 9 datasets considering Mean F-Measure(MFM) but they vary regarding the OVERALL ACCURACY. The experiments also demonstrate that the proposed model performs well even when increasing the number of classes.
Keywords:	Imbalanced Multiclass dataset, Imbalanced learning, Hierarchical classification
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	COMBINATION OF SECOND ORDER MODELING AND ACP TOOL FOR FAULT ISOLATION
Author:	BELAID MOUNA, OUNI KHALED, CHAOUCHE HANENE, NABLI LOTFI
Abstract:	Automation has become important to meet the needs and requirements of industries especially the transportation industries. Thus, in a transport context, the aim is to increase the level of traffic flow and to develop monitoring techniques by monitoring the evolution of the performance indicators of a system; The detection of a defect and its diagnosis are of great interest and the prognosis is currently the subject of several in-depth studies. This paper suggests a detection approach in the flow problem regarding the road traffic the rough principal component analysis (PCA). This control technique is considered very effective in the field of surveillance. The PCA is considered an indispensable tool applied by industries with the objective of avoiding or reducing any anomaly that may intervene in the field of operation of the system. . It is applied to a road section of Lille-France with 829 measurements with four variables: traffic density, flow rate, average speed and occupancy rates following the application of a modeling tool of the second order in the Pre-processing phase of the data. The PCA is used to detect defects by statistical predictive square error SPE and method Hotteling T2. Thus before the isolation, the segmentation has become a necessary step to ensure the visualization of classes (in faults and without defects). The calculations of contributions allow isolating faults and identifying faulty variables. In our example, the defectives variables are both the flow rate and the average speed.
Keywords:	Modeling of second order, Linear PCA, Fault detection, segmentation, Fault isolation
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	DATAMINING BASED MULTIMODE APPROACH FOR ESTIMATING THE RISK UNDER HEART FAILURE CASES
Author:	SYED UMAR, G. SRIDEVI, YERRAGUDIPADU SUBBARAYUDU, N. YOGENDER NATH
Abstract:	Predictive modelling solutions difficult to assess the risks in the health information technology. People to work longer is the integration of clinical researchers from different areas in different parts of the doctor. Some pages are thick in general, varied and meaningful change over time. Parallel construction tools large data tools can be built and called the doctor can help clinical decisions. In this article, we combine a multi-model forecasts to a new approach to the predictive power of many models to better predict. We show the effectiveness and efficiency of the creative work of the heart study. The results showed that the idea of a predictive model multi-architecture method is better than the best. With modelling errors of prediction models, we can select a group structure that offers value. Further details are made at different levels in the extraction system, resulting in a greater accuracy of the predictions.
Keywords:	Multi node model, Clustering, Hadoop.
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	A REVIEW OF KEY FACTORS OF CLOUD ENTERPRISE RESOURCE PLANNING (ERP) ADOPTION BY SMEs
Author:	USMAN MUSA ZAKARI USMAN, MOHAMMAD NAZIR AHMAD, NOR HIDAYATI ZAKARIA, AHMED ALAA HANI ALKURDI
Abstract:	The adoption of cloud ERP is influenced by several factors. However, the significant factors can contribute to the adoption of ERP among SMEs which are unclear and the minimum attempts made to summarize for examination in the existing research. The aim of this paper is to provide better understanding of the significant factors which influence on the adaption of cloud ERP for SMES. The approach followed in this paper is based on the Systematic Literature Review. The presented review relates to the advantages such as compatibility, complexity, top management support, Cloud awareness, technology-readiness competitive pressure, and government regulations, amongst others, featured as prior factors that can be considered as the most influential for the adaption of Cloud ERP. This study briefly discusses the adoption of the cloud ERP among SMEs, by pointing out the most influential factors of the adoption cloud ERP. The output of this study adds structure to the previously discussed papers which are based on the adaption of cloud ERP in addition; this paper presents systematic reviews on the relevant literature. This study highlights an insight into the identification of the potential issues and challenges for the advancement of theories in the Information Systems field. Further, this study focuses on the direction for research and contributes to determinants for the adoption of Cloud ERP. The result increases the understanding of the influential factors of the cloud ERP which are based on the benefits of SMEs.
Keywords:	Cloud, Review, Enterprise Resource Planning, adoption, SMEs.
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	TOWARDS A NEW FORMULATION OF THE MAINTENANCE PROCESS QUALITY RATE USING THE AHP AND SIX-SIGMA METHODS
Author:	MY ABDELBAR KOUSSAIMI, DRISS BOUAMI, SAID ELFEZAZI
Abstract:	This work proposes an approach based on methods Analytical hierarchy process (AHP) and Six sigma in order to formulate a new maintenance process quality rate and led to raise up the quality processs performance. Steps of this approach will be illustrated by industrial applications. It proposes an approach based on a combination of methods: Analytical hierarchy process (AHP) and Six sigma. This approach is based on a new formulation of a Maintenance process quality rate and led to improve maintenances performance. This approach led to apply easily improvement maintenance by using combination of methods: Analytical hierarchy process (AHP) and Six sigma. In the industrial application, this approach helps us to improve the maintenances process quality rate. After following the steps simulated by the proposed approach, the quality rate will be deducted and illustrated by the industrials application. At present, there is not explicit improvement quality maintenance process based on quality rate, to lead to specific maintenance actions on maintenances process.
Keywords:	Improvement Maintenance, Maintenance Process, Maintenance Process Quality Rate, Six Sigma, Analytical Hierarchy Process.
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	COMPARISON BETWEEN INTERLEAVED BOOST CONVERTER BASED 6-SWITCH AND 4-SWITCH VSI FED PMBLDC MOTOR DRIVE
Author:	V. RAMESH , Y. KUSUMA LATHA
Abstract:	In this paper, an improved interleaved boost converter topology for PMBLDC Motor has been proposed. The proposed interleaved boost converter topology has been used for 6-switch and 4-switch VSI fed PMBLDC motor drive and details are presented. The proposed research work has been implemented under Matlab/Simulink environment and tested for different operating conditions. The performance of 4-switch VSI fed PMBLDC motor drive compared with the performances of 6-switch VSI fed PMBLDC motor. From the results, it is observed that 4-switch VSI fed PMBLDC motor performance is superior to 6-switch VSI fed drive in certain aspects. In some other aspects performance of 6-switch VSI fed drive is superior to 4-switch VSI fed drive. Merits and demerits of each one of the schemes are investigated thoroughly under different operating conditions and corresponding results are presented.
Keywords:	BLDC Motor, Interleaved Boost Converter, Torque Ripple, 4-switch VSI, 6-switchVSI
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	SPIRITUAL DESIGN ELEMENTS AS EMOTIONAL THERAPY FOR MALAY MUSLIM ELDERLY WITH ALZHEIMERS DISEASE USING THERAPEUTIC ROBOT
Author:	NIK NOR NABILA NIK ISMAIL, ANITAWATI MOHD LOKMAN, FAUZIAH REDZUAN
Abstract:	The worlds population of people aging over 60 years will double from 11% to 22% between the year 2000 and 2050. Malaysia is expected to become an aging nation by 2030 in which 15% of the population is aged 60 years and above which entails a rise in the number of elderlies in the nation. In addition to that, results obtained from a preliminary study concluded that the early stages of the Alzheimers disease effects elderlies memory in terms of performing tasks in their daily lives which needs assistance and support from family members or caregivers. This paper is focused on identifying the spiritual emotion words for the Kansei Spiritual Therapeutic Robot Interaction (KS-TRI), determining spiritual design elements for the Kansei Spiritual Therapeutic Robot Interaction (KS-TRI) as well as proposing a design guide for spiritual practices in the Kansei Spiritual Therapeutic Robot Interaction (KS-TRI). The methodology used for this research is a qualitative method using the KJ method for objective 1 and an interview with spiritual and elderly experts is deployed for objective 2 whereas for objective 3, an in-depth user study is conducted with elderlies that suffers early stages of the Alzheimers disease. The finding revealed that utilizing the therapeutic robot which is embedded with spiritual design elements of spiritual practices is able to derive positive effects as well as enhance spiritual emotions towards elderlies. This research is significant for elderlies suffering from early stages of the Alzheimers disease where they benefit the technology in terms of performing spiritual practices.
Keywords:	Robot; Therapeutic Robot; Elderly; Aging; Alzheimer; Spiritual Practices
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	THE STATE OF DATA QUALITY ARTS IN (TECHNICAL) SERVICE REPORTING
Author:	A. T. KHALILIAN, OTHMAN IBRAHIM
Abstract:	Service Level Management (SLM) in IT Service Management (ITSM) contains Technical Service Reports (TSRs) to report Service Quality (SQ) based on the Service Level Agreement (SLA). However, producing TSRs for a large enterprise has Data Quality (DQ) challenges. The source of technical metrics in TSRs comes from large, unverified and non-normalized system-generated events and logs in a large enterprise environment. Moreover, configuration items and service information meta-data that are essential for producing these SLM reports are facing DQ problems. These challenges lead to low reports' Data Quality (DQ) that destroy customer's trust and management visibility, which leads to financial penalties and SQ issues. In order to improve the TSRs' DQ and consequently improving the SQ and reducing the risks of financial penalties, researchers need to know the limitations and definitions of DQ for TSRs, and this is not feasible, except for having a comprehensive overview of DQ dimensions and its processes. This paper provides a statement on the situation of the DQ in existing literature by having eyes on technical service reporting issues.
Keywords:	Data Quality, Technical Service Report, Service Level Management, DQ, TSR, SLM
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	A SURVEY ON DEVELOPMENT OF PATTERN EVOLVING MODEL FOR DISCOVERY OF PATTERNS IN TEXT MINING USING DATA MINING TECHNIQUES
Author:	RAVINDRA CHANGALA, DR.D RAJESWARA RAO
Abstract:	As the data increasing, retrieving useful information and knowledge for the users is an open issue in the text mining domain in spite of having many existed data mining techniques. We focused on this by conducting a survey over existed techniques with our new method called pattern discovery models. We found that the existed model yields few drawbacks like low frequency problem, effective usage of discovered patterns, noisy data, polysemy and synonymy etc. Most people felt with the hypothesis that pattern based methods will perform better than the term based techniques. We got support to prove our model is better example for effective use of patterns in text mining than the existed.
Keywords:	Text Mining, Pattern Evolving, Pattern Deploying, Information Retrieval, Pattern Taxonomy Model, Data Mining Techniques
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	A SWARMED GA ALGORITHM FOR SOLVING TRAVELLING SALESMAN PROBLEM
Author:	VIKAS RAMAN, NASIB SINGH GILL
Abstract:	TSP (Travelling Salesperson Problem) is one of the leading problems that are considered as an NP-hard and has been broadly studied problem in the area of combinatorial. TSP is termed as, a salesperson who wishes to visit m cities, and assumed to find out the shortest tour by visiting all the cities exactly once and lastly returning to the starting city. Genetic algorithm (GA) is a heuristic algorithm used for solving the TSP. Genetic Algorithm (GA) was emphasized to give better performance in solving TSP. But GA frequently undergoes into premature convergence because of the difficulty in avoiding the loss of genomic variety in the population. To overcome this drawback, GA that uses Intelligent Swarm Optimization algorithm’s characteristic is presented. The presented algorithm is referred as Swarmed Genetic Algorithm (SGA) that contains an upgrading approach for the solution. The new approach was altered by inserting the three distinguished GAs mutation operators in the proposed algorithm which are the scrambled mutation, inversion mutation and displacement inversion mutation operators. This algorithm was compared with other GAs containing various mutation operators on instances from TSPLIB. Results obtained showed that the algorithm is much more efficient as compared to the GA and outperformed in most of the TSP instances.
Keywords:	TSP, GA, Mutation, SSO.
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	ANALYSIS ON STUDENTS PERFORMANCE USING NAIVE BAYES CLASSIFIER
Author:	MOKHAIRI MAKHTAR, HASNAH NAWANG, SYADIAH NOR WAN SHAMSUDDIN
Abstract:	Classification of students academic performance for Sijil Pelajaran Malaysia (SPM) at early stage of their previous study will able to help in identify the students achievement to will assist the educators and school management taking the necessary actions. In this research, data mining techniques are used to classify students’ of Maktab Rendah Sains MARA (MRSM) Kuala Berang performance based on their performance in certain subjects. The aim of this study is to examine the Naive Bayes algorithm which is one of the classification methods in data mining, to identify the hidden information between subjects that affected the performance of students in Sijil Pelajaran Malaysia (SPM). Data was collected from the second semester obtained from year 2011 until 2014 with the total of 488 students data were used to train the algorithm. It has been shown that with 10 cross fold-validation that Naive Bayes algorithm can be used for classification of students performance in early stages of second semester with an accuracy of 73.4%.
Keywords:	Classification, Data Mining, Feature Selection, Naive Bayesian
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	PAPER SURVEY AND EXAMPLE OF COLLABORATIVE FILTERING IMPLEMENTATION IN RECOMMENDER SYSTEM
Author:	HANAFI, NANNA SURYANA, ABDUL SAMAD BIN HASAN BASHARI
Abstract:	The development of recommender system research has expanded to various applications. Recommender system issues can be analyzed from many perspectives such as user rating strategy, user preferences and text mining. User rating strategy and user preferences are associated with user behavior to find suitable recommended items. Text mining is considered the most related field to database management and web search queries. The relation to the database query, it needs suitable query algorithm web search and user profiling strategy. Our paper survey showed that Latent Semantic Analysis (LSA) method has a better chance to solve recommender system issues especially in web search and user profiling. By comparing with restaurant samples, we describe adequate measures to evaluate the recommender system quality in user profiling. Some algorithm can provide benefits to improve the quality of personalized recommendations that are tailored to user attributes. Further research can provide newer algorithm to handle cold start problem and sparse data from both text mining and mining computation perspectives.
Keywords:	Latent Semantic Analysis, Restaurant, food menu Recommendation, Semantics, User Behavior
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	KERNEL LINEAR COLLABORATIVE DISCRIMINANT REGRESSION CLASSIFICATION FOR FACE RECOGNITION USING LOCAL BINARY PATTERN
Author:	P. KIRAN KUMAR REDDY
Abstract:	Binary feature descriptors have been widely used in computer vision field due to their excellent discriminative power and strong robustness, and local binary patterns (LBP) and its variations have proven that they are effective face descriptors. However, the forms of such binary feature descriptors are predefined in the hand-crafted way, which requires strong domain knowledge to design them. In this paper, we propose a simple and efficient Kernel Linear Collaborative Discriminant Regression Classification (KLCDRC) feature learning method to learn a discriminative binary face descriptor in the data-driven way. Firstly, similar to traditional LBP method, we extract block based feature vectors by computing and concatenating the difference between center patch and its neighboring patches. Then learn a feature mapping to project these pixel difference vectors into low-dimensional binary vectors. Lastly, we cluster and pool these projected binary codes into a histogram-based feature that describes the co-occurrence of binary codes. And we consider the histogram-based feature as our final feature representation for each face image. We investigate the performance of our KLCDRC-LBP, KLCDRC and LCDRC on ORL and YALE databases. Extensive experimental results demonstrate that our KLCDRC descriptor outperforms other state-of-the-art face descriptors.
Keywords:	Binary feature descriptors, Histogram, Low dimensional binary vectors, Local Binary Patterns, Kernel LCDRC
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	EPILEPTIC SEIZURE PREDICTION USING HYBRID FEATURE SELECTION
Author:	M. RAVI KUMAR, Y. SRINIVASA RAO
Abstract:	A comprehensive research of Electroencephalography (EEG) is carried out on Empirical Mode Decomposition (EMD) and Discrete Wavelet Transform (DWT) domains. In this scenario, the hybrid feature extraction is performed by utilizing entropy features like Shannon entropy, log-energy entropy and Renyi entropy. Generally, the entropy measures are effective in evaluation of non-linear interrelation and complexity of signals. After that, a superior classifier named as Support Vector Machine (SVM) is implemented for classifying the signals. Experimental outcome proves that the advanced method distinguishes the focal and non-focal signals with a superior accuracy.
Keywords:	Empirical Mode Decomposition (EMD), Intrinsic Mode Function (IMF), Support Vector Machine (SVM)
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	HDFS CACHE PERFORMANCE USING SET ASSOCIATIVE CACHE MEMORY
Author:	B.PURNACHANDRA RAO, Dr.N.NAGAMALLESWARA RAO
Abstract:	Due to online activities and use of resources related to computing, data is being generated at an enormous rate. Distributed systems are the efficient mechanism to access and handle such huge data. One such mechanism is a Hadoop distributed file system (HDFS). An HDFS instant usually contains several nodes, each of which stores a small portion of its data. It creates multiple data blocks and store each of the block redundantly across the pool of servers to enable reliable, extreme rapid computation. HDFS supports common file system operations such as read and write files , create and delete directories. In this paper we are presenting a new paradigm for improving file accessing time in HDFS. It is known that accessing data from cache is much faster than disk access. The cache memory is used to store frequently accessed data & hence process it much more quickly. We have already observed the performance improvement using cache memory in the existing Hadoop environment. In this paper we will prove the performance further improvement by using set associative cache memory. Set associative cache mechanism is for managing the interaction between main memory and cache memory.
Keywords:	Hadoop Distributed File System (HDFS), MapReduce, Cache Memory , Set Associative Cache Memory, Average Memory Access Time AMAT, NameNode, DataNode, Second Level Cache, Victim Buffer, Prefetching
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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Title:	A FRAMEWORK FOR SEMENTIC LEVEL SOCIAL SENTIMENT ANALYSIS MODEL
Author:	MADHU BALA MYNENI, L V NARASIMHA PRASAD, J SIRISHA DEVI
Abstract:	Social sentiment analysis is playing a vital role in analytics applications like product assessments, people opinions on sudden events and disaster assessments etc. Now the current research is focusing on dynamic big data analysis. The rich sources of dynamic data are twitter, face book, linkedln, snapchat, instagram, reddit and e-commerce web resources. In this paper the importance of semantic level social sentiment analysis with issues, tools and algorithms and machine learning algorithms role are discussed. A case study on Indian railway passenger tweets analysis is discussed and finds the sentiment of passengers on railway services.
Keywords:	Social Sentiment, Machine Learning, Text Processing
Source:	Journal of Theoretical and Applied Information Technology 31^st August 2017 -- Vol. 95. No. 16 -- 2017
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