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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
November 2017 | Vol. 95 No.22

Title:	AN EMPIRICAL EVALUATION FOR THE INTRUSION DETECTION FEATURES BASED ON MACHINE LEARNING AND FEATURE SELECTION METHODS
Author:	MOUHAMMD ALKASASSBEH
Abstract:	Despite the great developments in information technology, particularly the Internet, computer networks, global information exchange, and its positive impact in all areas of daily life, it has also contributed to the development of penetration and intrusion which forms a high risk to the security of information organizations, government agencies, and causes large economic losses. There are many techniques designed for protection such as firewall and intrusion detection systems (IDS). IDS is a set of software and/or hardware techniques used to detect hacker's activities in computer systems. Two types of anomalies are used in IDS to detect intrusive activities different from normal user behavior. Misuse relies on the knowledge base that contains all known attack techniques and intrusion is discovered through research in this knowledge base. AAnomaly Detection, Attacks, Dos, SNMP, MIB, Classification, Feature Selection rtificial intelligence techniques have been introduced to improve the performance of these systems. The importance of IDS is to identify unauthorized access attempting to compromise confidentiality, integrity or availability of the computer network. This paper investigates the Intrusion Detection (ID) problem using three machine learning algorithms namely, BayesNet algorithm, Multi-Layer Perceptron (MLP), and Support Vector Machine (SVM). The algorithms are applied on a real, Management Information Based (MIB) dataset that is collected from real life environment. To enhance the detection process accuracy, a set of feature selection approaches is used; Infogain (IG), ReleifF (RF), and Genetic Search (GS). Our experiments show that the three feature selection methods have enhanced the classification performance. GS with bayesNet, MLP and SVM give high accuracy rates, more specifically the BayesNet with the GS accuracy rate is 99.9%.
Keywords:	Anomaly Detection, Attacks, Dos, SNMP, MIB, Classification, Feature Selection
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	IMAGE STEGANOGRAPHY BASED ON ODD/EVEN PIXELS DISTRIBUTION SCHEME AND TWO PARAMETERS RANDOM FUNCTION
Author:	MOHAMMED MAHDI HASHIM, MOHD SHAFRY MOHD RAHIM
Abstract:	Presently, the evolution massive of the internet gives more attention, play important role in the field of communication, and transfer messages. Nowadays, hiding sensitive or secret information inside trusted media such image without being noticed by the intruder is more needed because of the privacy cases, this method called steganography. In this paper, a method of hiding secret data in an image based on odd/even pixels distribution scheme and two parameters random function have introduced. The objective of this study is to increase the imperceptibility of proposed method with a high payload capacity of secret message. Two main process are used in the proposed method, which are embedding process and extracting process. Huffman coding technique is utilize to compress the secret message before embedding process. The security and capacity of the proposed method will increase after preparation secret message. The main objective of proposed scheme is to increase image quality (PSNR) in stego image. Two main things make the method effective: first, checking matching of secret bits with LSB and mapping to determine even and odd word during embedding, and second, segmenting the secret message to track and map every bit in stego image. Experimental results of the proposed method can achieve a high imperceptibility and robustness was emphasized.
Keywords:	Image Steganography, Least Significant Bit (LSB), Odd/Even pixel distribution, Peak Signal to Noise Ratio (PSNR), Information Security
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	IT PRE-ENTREPRENEUR'S FOUNDING DECISION MAKING AND PSYCHOLOGICAL MECHANISM
Author:	KYUNGYOUNG OHK, JAEWON HONG
Abstract:	This study explored IT pre-entrepreneur’s decision making process between psychological perception of self and behavioral intentions toward founding. For this purpose, we investigated the influence of career development, job attitude, and job self-esteem on founding intention. The results of the analysis are summarized as follows. First, job attitude and job self-esteem are positively influenced by career development. This suggests that career development can increase job attitude and job self-esteem. Second, job attitude which influenced by career development have positively effects on founding intentions. But, job self-esteem does not influence on intentions of founding. Third, career development positively influences on job self-esteem, but job self-esteem has no effect on intention of founding. Therefore, it is necessary to make efforts to improve job attitude rather than job self-esteem in order to activate start-up business of IT pre-founder. This study has important implications for analyzing the cognitive mechanism in the decision-making process of IT pre-entrepreneur. So this study is expected to help the development of entrepreneurial decision making information system for IT start-up.
Keywords:	IT pre-entrepreneur, Decision making, Psychological mechanism, Founding information system, IT Star-up
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	THE RELATIONSHIP BETWEEN CELLULAR PHONE ADDICTION AND SELF ESTEEM OF ELEMENTARY SCHOOL STUDENTS IN HIGHLY MOBILE ENVIRONMENT
Author:	KWANG-OK LEE, HYUN-JU CHAE
Abstract:	The purpose of this study was to investigate the cellular phone addiction status and the relationship between cellular phone addiction and self-esteem of elementary school students in today’s highly mobile environment. The study participants were 1,173 upper grade elementary school students in Chungnam province. Data were collected by a self-administered questionnaire from November 5 to 26, 2012. Collected data were analyzed using the IBM SPSS 20.0 program with descriptive statistics, Pearsons correlation coefficient, independent t-test, one-way ANOVA and Scheffe test. The level of the cellular phone addiction in upper grade elementary school students was generally low but high risk students also existed. In addition, a negative correlation was observed between self-esteem and cellular phone addiction in upper grade elementary school students. These results suggest that various interventions to prevent and manage the cellular phone addiction should be provided for elementary school students in today’s highly mobile environment and interventions for high risk students of cellular phone addiction should be provided urgently. In addition, inclusion of interventions to increase the self esteem of upper grade elementary school students in those interventions should be also needed.
Keywords:	Cellular Phone, Addiction, Self-Esteem, Elementary School, Mobile Environment
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	PROBABILISTIC MODEL OF ALLOCATION LAWS OF EXPERIMENTAL DATA IN INFORMATION SYSTEMS
Author:	YURI YURIEVICH GROMOV, YURI VIKTOROVICH MININ, OLGA GENNADEVNA IVANOVA, ALEKSANDR GEORGIEVICH DIVIN, HUDA LAFTA MAJEED
Abstract:	On the basis of the beta distributions of the 1st and 2nd kind were received probabilistic models of distribution laws, which allow to approximate wider class of distribution laws of experimental data, than the existing Pearsons system of distributions. The method of identification parameters was developed of the generalized beta distribution using power, exponential and logarithmic moments.
Keywords:	Information System, Experimental Data, Probability, Distribution Laws, Approximation.
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	DR-QPO: DISCRETE RANK BASED QUERY PATTERN OPTIMIZATION TOWARDS PARALLEL QUERY PLANNING AND EXECUTION FOR DISTRIBUTE TRIPLE STORES
Author:	K.SHAILAJA, Dr. P.V. KUMAR, Dr. S.DURGA BHAVANI
Abstract:	This manuscript proposed and explored a novel strategy for query pattern optimization towards parallel query planning and execution in Distributed RDF environments. The critical objective of the proposal is to optimize the query patterns from the query chains initiated to execute parallel in distributed RDF environment, which is unique regard to the earlier contributions related to parallel query planning and execution strategies found in contemporary literature. All of these existing models aimed to notify the query patterns from the given query chain, which are less significant to optimize the parallel process of the query patterns that discovered from multiple query chains submitted in parallel in distributed environment (such as cloud computing) to query the distributed triple stores. In order to this, the Discrete Rank based Query Pattern Optimization (DR-QPO) strategy is proposed. The DR-QPO optimizes the query patterns from multiple query chains initiated in parallel. A novel scale called Discrete Rank ConsistenceScore (DRDCS) defined, which uses the order of other metrics query pattern occurrence count, search space utilization, and access cost as input. The experiments conducted on the proposed model and other benchmark models found in contemporary literature. The results obtained from the experimental study evincing that the proposed model is significant and robust to optimize the query patterns in order to execute distribute query chains in parallel. The comparative analysis of the results obtained from DR-QPO and other contemporary models performed using ANOVA standards like t-test, Wilcoxon signed rank test.
Keywords:	RDF, Query Optimising, Parallel Planning, SPARQL, DRDCS, Access Cost Search Space Utilization Distributed Query Science
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	A CERTAIN INVESTIGATION ON SECURE LOCALIZATION ROUTING PROTOCOL FOR WSN
Author:	N. A. NATRAJ, Dr. S. BHAVANI
Abstract:	Wireless Sensor Network (WSN) is an advancement of wireless network where nodes are located with respect to static or dynamic. Secure Localization is a major challenge in WSN where location of unknown nodes may not be identified. In previous work, authors focused on secure localization but not balancing energy consumption. In this proposed work, Secure Localization Routing Protocol (SLRP) is developed to attain balancing between secure location integrity and energy efficiency. This protocol contains three phases. In first phase, cluster member selection and route formation is implemented to forward packet to next hop node efficiently. In second phase, localization procedure is adopted based on location hop distance value, residual energy of node for location discovery and minimum cost function. In last phase, secure localization scheme is implemented to secure location information about cluster members from attackers. Localization procedure is implemented with confidentiality using effective cryptography technique to protect messages from attackers and worms. The extensive simulation results are performed over SLRP, RMSR, ECHERP and ENSOR in terms of location integrity rate, location accuracy, location update rate, control overhead, packet delivery ratio and packet delay. Proposed protocol SLRP produces better results than existing schemes.
Keywords:	WSN, Cluster Member Selection, Route Establishment, Localization Procedure, Secure Localization Scheme And Minimum Cost Etc
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	MICRO CONTROLLED AND DIRECTED ALARM SYSTEM FOR BLIND PERSON
Author:	Dr. RASHID A. FAYADH
Abstract:	Blindness is a lacking state of visual perception due to neurological or physiological factors. Partial blindness represents the integration lack in the optic nerve growth or the eye visual center. The total blindness is defined as the full absence of light visual perception. The deaf and blind persons are frequently suffering at mostly exercising of basic things in daily life. This suffering makes lives almost at risk during traveling through obstacles, due to necessary equipment lack in my country that provides them an assistance state to avoid or cross over the risk. For this reason, the idea of research was come to design and manufacturing ultrasonic sensor. The proposed work contains friendly user, cheap, and simple alarm system that is implemented and designed support the mobility of both visually impaired and blind people in a specific area. This work includes wearable equipment that consists of cummerbund for helping the blind person in the way navigation safely alone by avoiding encountered obstacles whether mobile or fixed to prevent any possible hard accident. The main system component is the ultrasonic wireless sensor which is used for scanning the predetermined around area of the blind by emitting-reflecting waves. The echo or reflected signals are received by Arduino microcontroller which are coming from barrier objects. The issued commands are carried out by the microcontroller to communicate the status of device back or given appliance to the vibration device. In this project a sensor is used to detect around obstacles within 150 cm of designed range. It can change the distance by simply changing the variable resistance button to avoid the blind person through the vibration when there is a risk.
Keywords:	Arduino Microcontroller, Blind Mobility, Blindness And Darkness, Emitting Reflecting Waves, Ultrasonic Sensor
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	OTSUS SEGMENTATION: REVIEW, VISUALIZATION AND ANALYSIS IN CONTEXT OF AXIAL BRAIN MR SLICES
Author:	HUMERA TARIQ, ABDUL MUQEET, AQIL BURNEY, MUHAMMAD AKHTER HAMID, HUMERA AZAM
Abstract:	Otsu s Method is a non parametric approach for image segmentation and is an attractive alternative to Bayes decision rule. Use of Nelder Mead for Otsus optimization has been used since long but cannot be seen in image segmentation literature. We in this paper address this gap in a novel way and revive classical literature of Otsu’s Image segmentation by experimenting it for voxel based tissue classification which then follows volume measurement of MRI base subjects. The other methods used to meet objective includes: spatial filtering, skull stripping and binarization of brain MR slices. The “goodness” of thresholds lies between 0.90<η^*<0.99 for every brain MR slice in the volume. Significant difference was found (p<0.01) and (F >>1) amongst mean gray level of tissues, mean tissue volume densities within slices of each subject and in average volume tissue density of all Ten subjects.
Keywords:	MR Brain Images, Otsu’s Segmentation, Nelder-Mead Simplex Optimization, Image Segmentation, Volume Measurement, Skull Stripping, Tissue Classification
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	PERFORMANCE ENHANCEMENT OF BLIND ALGORITHMS BASED ON MAXIMUM ZERO ERROR PROBABILITY
Author:	NAMYONG KIM, KIHYEON KWON
Abstract:	In this paper, the error-Gaussian-kernelled input of the algorithm developed by maximization of zero-error probability of constant modulus error (MZEP-CME) is studied for developing a method to reduce the weight perturbation of the MZEP-CME under impulsive noise. The proposed method is to normalize the input of MZEP-CME with the norm of the error-Gaussian-kernelled input (EGKI) in order to reduce weight perturbation. Then the denominator of the step size can make the algorithm unstable when it has a very small value or wide fluctuations. To prevent these incidents, a balanced power of EGKI between the current power and the past one is employed. This normalization with balance power provides an additional function for reducing further the weight perturbation in impulsive noise environment. Simulation results show that the weight fluctuation after convergence of the proposed algorithm is below half of that of the MZEP-CME. Also compared with the MZEP-CME, the proposed approach lowers the steady state MSE (mean squared error) by about 1 dB under impulsive noise.
Keywords:	Impulsive Noise, Maximization Of Zero-Error Probability, Constant Modulus, Error-Gaussian-Kernelled Input, Weight Perturbation
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	RESOURCES OPTIMIZATION METHODOLOGY FOR HETEROGENEOUS COMPUTING SYSTEM
Author:	MAHENDRA VUCHA, DVS CHANDRA BABU, ARVIND RAJAWAT, KARTHIK R
Abstract:	Nowadays embedded systems are being equipped with one or more processing cores to support parallel processing of applications and meets design goals at optimized resource utilization. Optimization of resources utilization can be achieved by estimating application requirements in terms of many aspects like performance, resource usage, memory usage, energy consumption, cache performance etc. Among these aspects, estimation of resources is an important to boost execution speed of an application with optimal resources utilization. So, ever increasing system and application complexities made the resources estimation is quite necessary to optimize resources utilization for an application. This paper addresses an optimized heterogeneous computing platform called Heterogeneous Reconfigurable Computing System (HRCS) and also a resources profiling methodology to estimate HRCS resource required for multifarious real life application. The HRCS has been modeled on a single chip Virtex-5 FPGA device and it has been equipped with multiple Reconfigurable Logic Units (RLUs) in combination with a softcore processor as Processing Elements (PEs).
Keywords:	Reconfigurable Logic Unit, Heterogeneous Reconfigurable Computing System, System on Chip, Design Space Exploration
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	METHOD AND ALGORITHM FOR DIAGNOSTIC OF EPILEPTIC EEG SIGNALS USING THE ADAPTIVE ORTHOGONAL TRANSFORM
Author:	ASMA HAFDI, ABDENBI ABENAOU, AHMED TOUMANARI
Abstract:	Electroencephalography (EEG) is one of the most used techniques for evaluating the functional status of the brain. It is essential for diseases’ diagnosis such as epilepsy. This pathology results from a cerebral dysfunction. The diagnosis of this pathology consists of detecting the appearance of paroxysmal activities in the EEG signals. The diagnostic of Epilepsy in EEG plays a crucial role in Computer Aided Diagnosis system (CAD). In this article, we suggest an approach based on the orthogonal adaptive transformation theory which makes it possible to extract the informative features of the EEG signals. The size of the vectors of the informative features obtained by this method is very short. This will allow to improve the quality of signals analysis and to increase their certainty of diagnosis
Keywords:	Adaptive Orthogonal Transformation, Basis Functions, Extraction of the Informative Features
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	MULTISET CONTROLLED GRAMMARS
Author:	SALBIAH ASHAARI, SHERZOD TURAEV, M. IZZUDDIN M. TAMRIN
Abstract:	This study focusses on defining a new variant of regulated grammars called multiset controlled grammars as well as investigating their computational power. In general, a multiset controlled grammar is a grammar equipped with an arithmetic expression over multisets terminals where to every production in the grammar a multiset is assigned, which represents the number of the occurrences of terminals on the right-hand side of the production. Then a derivation in the grammar is said to be successful if only if its multiset value satisfies a certain relational condition. In the study, we have found that control by multisets is powerful tool and yet a simple method in regulation of generative processes in grammars. We have shown that multiset controlled grammars are at least as powerful as additive valence grammars, and they are at most powerful as matrix grammars.
Keywords:	Multisets, Context-free Grammars, Regulated Grammars, Generative Capacity.
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	UNDERSTANDING VISITOR BEHAVIOR ON SOCIAL MEDIA USAGE IN INDONESIAS MUSEUM
Author:	ARTA MORO SUNDJAJA, FORD LUMBAN GAOL, SRI BRAMANTORO ABDINAGORO, BAHTIAR S. ABBAS
Abstract:	The purpose of this study was to understand the behavior of visitors that visited the museum and the adoption of social media technologies in the museum in Indonesia. The growing presence of social media allows the opportunity for the branding and marketing of the non-profit organization with limited resources but demand high impact. Museum industry in Indonesia needs to preserve and communicate their culture to the public with limited financial and human resources. Social media was proven to solve this problem. The data was collected from a sample of 63 respondents using a questionnaire. The data were analyzed using descriptive analysis. The results were most of the social media users are in the productive age who have the minimum an undergraduate education, and most of them live in Java. They are not visiting the museum frequently, and their visiting purposes are to learn or study about Indonesia culture triggered by their school, relaxing, personal desires, and visit by accident. They know information about the museum from the search engine, offline, and social media. Most of the museum in Indonesia give bad experience to their visitor, and only some offer a positive experience. The limited social media users in Indonesia, who already aware of museum presence in social media, utilize it to get information about the museum (profile, exhibition, collection, and news), socializing with other social media members, and showing their existence in society. They suggest that museum management should update their social media frequently. This study examines the characteristics of Facebook Fan Page Museum user (age group, gender, residence location, and education level) and their behavior in using Facebook Fan Page Museum. Since there is no research in this field in Indonesia, the findings can be used by museum managers for managing their social media in marketing and education for the community.
Keywords:	Online Visitor Behavior, Museum Social Media, Edutainment Marketing, Online Visitor Expectation, Indonesia Museum.
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	A NOVEL SWARM INTELLIGENCE BASED ENERGY EFFICIENT PROTOCOL FOR WIRELESS SENSOR NETWORKS
Author:	SUPREET KAUR, RAJIV MAHAJAN
Abstract:	Energy efficiency has recently turned out to be primary issue in wireless sensor networks. Sensor networks are battery powered, therefore become dead after a certain period of time. Thus, improving the data dissipation in energy efficient way becomes more challenging problem, in order to improve the lifetime for sensor devices. The clustering and tree based data aggregation for sensor networks, can enhance the network lifetime of wireless sensor networks. Hybrid Ant colony optimization (ACO) and particle swarm optimization (PSO) based energy,, efficient clustering and tree based routing protocol is proposed. Initially, clusters are formed on the basis of remaining energy, then, hybrid ACOPSO based data aggregation will come in action to improve the inter-cluster data aggregation further. Extensive analysis demonstrates that proposed protocol considerably enhances network lifetime over other techniques.
Keywords:	Wireless Sensor Networks, Ant Colony Optimization, Energy Efficient, Particle Swarm Optimization
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	EEG BASED USER IDENTIFICATION METHODS USING TWO SEPARATE SETS OF FEATURES BASED ON DCT AND WAVELET
Author:	HEND A. HADI, DR. LOAY E. GEORGE
Abstract:	Brain activities may represented by EEG signals, which are set of measures using electrodes along the scalp, they are more secret, sensitive, and hard to steal and reproduce. They hold great potential to provide robust and secure biometric system for user identification and verification. This paper aims to present a comparison between our previous proposed feature set that based on Partitioned Fourier spectra and some new features sets proposed in this work. They established as simple, fast, and promising set of features for EEG-based identification system. The first introduced feature set is based on the energy distribution of DCT AC-components, and the second set is the statistical moments for three types of wavelet transforms. Each set of features is tested using normalized distance measures for matching stage. Each proposed method was tested using the publicly available EEG CSU dataset which was collected from seven healthy volunteers and the publicly available EEG Motor Movement/Imagery dataset which is relatively large dataset was collected from 109 healthy subjects. The attained identification results are encouraging with best recognition rate is (100%) for all proposed methods and for both datasets. All tested feature sets were extracted under the condition, which was adopted in our previous work, that is "they should extracted from EEG data belong to single task & signal channel". All achieved results are considered competitive when compared with the results of other recently published works. The adopted condition reduced the computational complexity and thus reduced the required processing time. Also, the wavelets based methods hold computational complexity less than DFT and DCT with recognition rates are more competitive to them.
Keywords:	Signal Processing, Wavelet Transforms, DCT, Energy Features, And Statistical Moments
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	TRACKING COMMUNITY EVOLUTION IN SOCIAL NETWORKS
Author:	LOUBNA BOUJLALEB, ALI IDARROU, DRISS MAMMASS
Abstract:	Recently, social network analysis is gaining on importance and bringing several challenges in the computer science discipline. Most social networks are dynamic and evolve gradually and the communities in these dynamic networks usually have changing members and could grow and shrink over time. The analysis of communities and their evolution is a relevant research domain that attracts researchers from a variety of fields; having suitable information and methods for dynamic analysis, one may challenge to forecast the future of the communities, and then conduct it appropriately in order to attain or modify this predicted future according to precise requirements. This capability would be a strong mechanism used by marketing, human resource managers, personnel recruitment, etc. In this paper, we are analyzing the changes in the dynamic network through tracking and examining the dynamic evolution of communities within a sequence of snapshots. We start by describing some basic dynamic features of social networks. Then, we propose a new technique called CED (Community Evolution Detection) which was developed in order to detect community evolution in the social network. The central elements of this technique are that it greatly depends on key nodes and QuantityInsertion metric. It also focuses on both efficiency and parameter free. We demonstrate the abilities and potential of our approach by testing it in real datasets and compare it with well-known algorithm with regard to complexity, accuracy and flexibility.
Keywords:	Community Evolution, Dynamic Network Analysis, Dynamic Social Network, Evolutionary Analysis, Community Dynamics
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	NANOTECHNOLOGY THEORY USED FOR SIMULATION OF EMERGING BIG DATA SYSTEMS ON HIGH PERFORMANCE COMPUTING: A CONCEPTUAL FRAMEWORK
Author:	NORMA ALIAS, MAI, 1HAFIZAH MUSA, VICTOR RIYADH SERGEY, NORHAFIZA HAMZAH, WALEED MUGAHED AL-RAHMI
Abstract:	The Implications of big data analytics of current trends in nanotechnology theory, model and simulation are becoming impressive issues. The potential applications of nanotechnology in the industrial sector, identifying and prioritizing research across the emerging technology are motivating to perform the integration between the conceptual framework of nanotechnology and a big data system development. This paper presents six variations to meet the contexts of a conceptual framework for modeling the complex systems involve nanotechnology theory, modeling, large scale numerical simulation in the real world problem. Integrated mathematical modeling and large scale numerical simulations are the tools to solve the complex systems. The conceptual framework is a comprehensive concept in theory, ordinary differential equation (ODE) or partial differential equation (PDE) modeling and simulation based on high performance computing (HPC). The main objective is to improve the process of huge computation of the big data modeling and to increase the performance evaluation of parallel programming on HPC platform. The framework organizes the idea and step to be considered for solving the integrated theory, mathematical modeling with fast numerical simulation , specific parallel computing strategy , communication software and HPC hardware system which are applicable for solving large scale nanotechnology applications.
Keywords:	Nanotechnology Theory, Big Data, High Performance Computing
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	IMPACT OF LEAN SOFTWARE DEVELOPMENT INTO AGILE PROCESS MODEL WITH INTEGRATION TESTING PRIOR TO UNIT TESTING
Author:	SHAIK MOHAMMAD SHAHABUDDIN, DR.PRASANTH YALLA
Abstract:	The current academic thinking on integration testing prior to unit testing using agile methodology shows that it is an innovative approach little understood and practiced formally. However, this approach according to Brown et al. contributes to economic governance, disciplined delivery and measure improvement for achieving agility at scale in software industry. This has motivated us to investigate and propose a conceptual model and make an empirical study in our previous work. In this paper, we reinforce the study with a case study based approach and quantify the real benefits of the new cultural shift in testing known as integration testing prior to unit testing. In addition to this, we studied the lean software development in terms of testing and integrated it with the phenomenon of integration testing prior to unit testing. We identified many aspects of lean principles. Nevertheless, we found mind mapping and identification of infeasible test cases are two important aspects. They are associated with lean principle like removal of waste to improve productivity further in agile and lean software development environment. The empirical results revealed that productivity is increased with the paradigm shift in testing arena. The quantification of benefits in terms of productivity shows significant performance differences between traditional approach and the leagile (new term referring to lean and agile) approach in software testing.
Keywords:	Lean Software Development, Agile Process Model, Software Testing, Integration Testing Prior To Unit Testing
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	MOTION ESTIMATION AND CONVOLUTIONAL CODING FOR VIDEO STREAMING OVER WIRELESS CHANNELS
Author:	SALAH A. ALIESAWI, SALAH S. MUSTAFA , SAEED A. GATHBAN
Abstract:	In this paper, a source and channel coding scheme is proposed for lossy video transmission over wireless channels. The source coding is used to reduce the redundancy so that the bit streams/video can be stored or sent efficiently over a network. The block-Matching (BM) with Quintet Search (QS) algorithm for motion estimation (ME) uses as a source coding or video compression technique. In the new QS algorithm, the number of searching points is reduced to five points instead of eight points in standard algorithm. The channel/convolutional coding (CC) adds useful redundancy to combat channel effects of the wireless environments and improve the system performance. The results of compression using different searching algorithms and different settings of the H.261 encoder parameters are computed for different videos with 176×144 dimension to select the proper settings that can be applied to the input video streams being transmitted over wireless links. The results show that the proposed system can produce a balance between the compression performance and preserving the video quality in video conference applications. Further, the performance of coded systems over additive white Gaussian Noise (AWGN) channels is also computed and compared with the system without channel coding.
Keywords:	Block-Matching, Motion Estimation, Convolutional Coding, Video Transmission.
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	AN EFFICIENT ALGORITHM FOR DATA CLEANSING
Author:	Saleh Rehiel Alenazi, Kamsuriah Ahmad
Abstract:	The data that have been collected from different resources might be redundant and duplicate. These data need to be cleaned in order for it to be used for other processing. The data should undergo detection process for any occurrence of duplication in the datasets. Two strategies are used to identify duplicates which are windowing or blocking. The aims of this paper are to review, to analyze and to compare algorithms in order to find the most efficient in terms of better accuracy and less number of comparisons. A comparison was made with the five most popular algorithms: DYSNI, PSNM, Dedup, InnWin and DCS++. Two benchmark datasets were used for the experiment, which are Restaurant and Cora. The results reveal that the DYNSI algorithm using both datasets gives high accuracy with respect to the number of comparisons. It is hoped that the results obtained from this study able to give the best review and comparison among the existing algorithms in producing high quality data and serve as a guidance to implement a better initiative for data storage system.
Keywords:	Data Cleansing, Record Deduplication Deduction Algorithm, Windowing-based, Efficiency, Accuracy, Data Quality
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	SAGG: A NOVEL LINKED DATA VISUALIZATION APPROACH
Author:	NOEMI SCARPATO, GIANFRANCO ALESSIO
Abstract:	In this paper, we describe the Semi-automatic GUI Generator (SAGG), a knowledge-based visualization system able to create GUI in a semi-automatically way. Since the linked has been introduced their expressiveness made possible to provide users with a lot of useful information, visualize this information is a crucial issue in the realization of the semantic web principles. The objective of our approach is the induction of tailored GUI able to show the considered linked data in the better way. The key idea behind our approach is the exploitation of existing web pages to deduct visualization patterns for linked data. Our intent is to provide common users with a semi-automatic GUI generator, this system is able to visualize linked data without the necessity for the above-mentioned users to know semantic technologies for data visualization. Following, we present an introduction to linked data visualization systems, our solution to linked data visualization issue: the SAGG system, its architecture, the implemented algorithms to realize it and its user interaction mechanisms.
Keywords:	Linked Data Visualization, Semantic Web, Information Visualization, Knowledge Visualization, OWL, SPARQL
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	HYBRID GENETIC VARIABLE NEIGHBORHOOD SEARCH BASED JOB SCHEDULING WITH DUPLICATION FOR CLOUD DATA CENTERS
Author:	RACHHPAL SINGH, KARANJIT SINGH KAHLON, GURVINDER SINGH
Abstract:	Background/Objectives: Scheduling is one of the important way to provide high availability of processors to cloud users. Majority of scheduling approaches are NP-Hard. Therefore, meta-heuristics techniques are required to schedule the jobs on virtual machines (VMs). Meta-heuristic techniques usually suffer from inter-processor communication issues as well as premature convergence and global optima. Methods: To handle these issues, hybrid scheduling technique was proposed using Genetic Algorithm (GA) and Variable Neighborhood Search (VNS) with Task Duplication (TD). Thus, proposed technique can reduce the inter-processor scheduling overheads among high-end servers. Results: To attain the objectives of the proposed approach, the cloud based model was designed by considering well-known Fast Fourier Transformation (FFT) problem using Directed Acyclic Graph (DAG). A simulation environment was designed to implement the proposed technique. Extensive experiments have shown that the proposed technique outperforms over available techniques regarding Makespan, Speedup, and Efficiency. Conclusion: From a comparative analysis of existing and scheduling techniques it has been found that the mean reduction in makespan is 7.07%. The comparative studies have demonstrated that the mean improvement of proposed technique over other techniques concerning efficiency is 0.031%.
Keywords:	Cloud Environment, Task Duplication, Variable Neighborhood Search, Genetic Algorithm, Directed Acyclic Graph
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	DETECTION AND CLASSIFICATION OF POWER TRANSFORMER FAULTS USING FFA BASED RNN TECHNIQUE
Author:	P.LAKSHMI SUPRIYA, P.SUJATHA
Abstract:	In this paper, proposed an intelligent technique for diagnosing the internal faults conditions in power transformers. The proposed intelligent technique is the composites of wavelet transform and RNN based FFA optimization technique. Initially, the normal signals are analyzed at the particular time instant. After that, investigate any faults occurred or not in the power transformer with the help of proposed technique. With the utilization of the proposed technique, the current signals of the power transformer is monitored and detected. Initially, the MWT is utilized to extract the features of the signal. In wavelet transform, the feature approximation of the signal is depends on the decompose levels of high and low frequency components. The extracted features are applied to the input of the FFA. The FFA is selected the optimized training dataset for training the RNN. After that the RNN testing process is evaluated the signal and classified the fault signal type. The effectiveness of the proposed technique is evaluated based on the statistical measures like accuracy, sensitivity and specificity qualities. The proposed method is implemented in MATLAB/Simulink platform and compared with the existing techniques.
Keywords:	Power Transformer, Fault Detection and Classification, Multi-Wavelet Transforms (MWT), Recurrent Neural Network (RNN) and Firefly Algorithm (FFA)
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	THE IMPACT OF SOCIAL NETWORKS ON INDIVIDUAL’S BEHAVIORAL CHANGE IN KINGDOM OF BAHRAIN
Author:	JAFLAH ALAMMARY
Abstract:	The growth in Social Networks in Arab countries played a crucial role in civil mobilization, empowerment, shaping opinion and influencing change. The popularity of Social Networks tools has continued to grow, however, extent to what the communication via Social Networks can lead to social or individual change is still debatable in these countries. The present study proposed and tested a holistic model that extended the Theory of Planned Behavior - TPB and redefined behavioral intention toward using technology to behavioral change as an effect of using new technology by exploring the impact of Social Networks on the individual behavioral change. Toward achieving the objectives of the current research, a quantitative research method was adopted. Three hundred surveys were distributed to residents from the different governorates in Kingdom of Bahrain. The research indicates that there is a need for an action to be taken by the decision makers and governance people in the Arab countries towards SN which essentially have become a weapon of mass persuasion. This weapon can be used by unconcerned individuals to change the society: socially, politically or even economically. The impact of Social Networks on changing behavior should be considered strategically. More attention needs to be paid on controlling the information and material which are exchanged on Social Networks to redirect their impact positively.
Keywords:	Social Networking, Behavioral Change, Perceived Privacy, Trust, Kingdom Of Bahrain
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	NEAREST DRIVER-FIFO COMBINATION MODEL IN ONLINE MOTORCYCLE TAXI DISPATCH SYSTEM
Author:	PURBA DARU KUSUMA
Abstract:	Dispatch system is one critical aspect in online motorcycle taxi system. Dispatch system affects both customer satisfaction and driver’s productivity. In online taxi system, nearest driver method is applied in most dispatch system. Meanwhile, FIFO method is applied in most taxi stands, such as in airport, railway station, etc. In this paper, we propose new dispatch system by combining nearest driver method and FIFO method. There are three combination methods. In the first method, both FIFO and nearest driver methods are weighted and then they are summed. Pickup request then will be allocated to the driver with the highest value of the summation. In the second method, pickup request will be allocated to the available driver with the highest idle time in certain broadcast area. If there are more than one drivers, the pickup request will be allocated to the nearest driver with the same idle time. In the third method, both driver’s idle time and driver-passenger distance are divided into certain classes. Each class is scored. Then, driver’s idle time score is summed with driver-passenger distance score. Pickup request is allocated to the driver who has highest score. Based on the simulation result, when the driver-passenger distance factor is dominant, weighted nearest driver-FIFO method is better than the existing nearest driver method. When the broadcast range is 0.5 kilometer, serial FIFO-nearest driver method is better than the nearest driver method.
Keywords:	Motorcycle Taxi, Dispatching System, FIFO, Nearest Driver
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	NEW TEXT STEGANOGRAPHY TECHNIQUE BASED ON A SET OF TWO-LETTER WORDS
Author:	SALWA SHAKIR BAAWI, MOHD ROSMADI MOKHTAR, ROSSILAWATI SULAIMAN
Abstract:	Steganography is a secret writing wherein one person communicates with another without drawing suspicion to the secret communication through the medium. Text steganography is regarded the most difficult carrier to conceal secret data with because of its insufficient redundant information compared to image, audio, or video files. In this paper, we propose a new method for concealing information in English writing using non-printing characters, such as zero width non-joiner (ZWNJ) and zero width joiner (ZWJ). This approach uses to text steganography on text files. Secret information is embedded inside the English script using two-letter words based on their locations, hence achieving steganography. Results show that the technique satisfies perceptual transparency and information hiding capacity in the cover file by comparing with two previous developed existing methods. However, the size of the cover and stego document increases by approximately (22.61%) from the original size.
Keywords:	Data Security, Information Hiding, Text Steganography, Carrier File, Unicode
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	DETECTION OF BREAST CANCER IN MAMMOGRAMS THROUGH A NEW FEATURES AND DECISION TREE BASED, CLASSIFICATION FRAMEWORK
Author:	ANWAR YAHYA EBRAHIM
Abstract:	This research proposes a new framework for detection of breast cancer. Currently, mammography is the primary tool for early detection and diagnosis. The use of computer systems to assist clinicians in digital mammography image screening has advantages over traditional methods. Computer-aided techniques can enhance the appearance of the mammogram images and highlight suspicious areas. Also it extracts certain dynamic features to distinguish between benign and malignant mammograms. Although great efforts have been made to come out with effective methods, their performances especially in terms of accuracy are fallen short due to poor image resolution, noise, and distinction between cancerous and non-cancerous tumours is very subtle. Thus, this study presents an automatic classification scheme to classify breast cancer into normal, benign and malignant, which covers background detection, image enhancement, pectoral muscles separation, selected features and classification processes. To this aim, this framework uses set of various techniques. First step we have achieved improvement on mammogram to improve the image accuracy based on this framework, after new method has been used for features extraction. A new method named Weighted Sparse Principal Component Analysis (WSPCA) is applied to select the distinctive features of the images of mammogram. The analysed mammograms of images are then identified as benign or malignant through decision tree by comparing the performance of Decision Tree with Support Vector Machine (SVM) and Bayesian classification on the MIAS data set. Decision Tree classifier is chosen to classify the mammograms using the above features as its input. The evaluations are carried out on the entire Mammography Image Analysis Society (MIAS) standard dataset. The proposed framework tested on MIAS data set achieved an overall accuracy of 90% with Decision Tree classifier and the perform accuracy of 97.8% using WSPCA features with Decision Tree classifier for sequential selection of benign versus malignant mammograms. Suggested method achieves good results when we have verified on various mammograms.
Keywords:	Chest Cancer, Mammograms, Feature Extraction, Weighted Features, Classification Techniques
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	SOCIAL DAMAGE COST ESTIMATION MODEL FOR MOBILE DIGITAL DIVIDE
Author:	GYOO GUN LIM, JOONGHO SEOL
Abstract:	The previous studies on the digital divide mainly consisted of comparative studies among groups according to education, age, occupation, and region. However, the digital divide is expected to vary depending on the individual situation. Therefore, this study suggests a model that calculates social damage cost of mobile divide at individual level based on individual cognitive value. According to this model, we conduct empirical verification by social damage types. For the empirical analysis of this study, 800 questionnaire data were collected. Based on the collected data, the cost of social damage caused by the individual mobile digital divide per person was estimated to be about 120,000 KRW, and the social cost of about 5.6 trillion KRW was calculated as a result of applying it to the population of South Korea. In the detailed analysis, males felt more harm than females, and people in their 40s or older felt more vulnerable than those in their 30s or less. Also, non-metropolitan area residents felt more damage than metropolitan area residents. In addition, the results of social damage analysis showed that the mobile digital divide was more significant in social participation activities, family issues and interpersonal relationships, and medical services. The results of this study are expected to contribute to the study of mobile digital divide and to the development of meaningful policies.
Keywords:	Mobile Digital Divide; Digital Divide; Mobile Divide; Social Damage Cost; Cost Estimation
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	INFORMATION MODEL TO SUPPORT SUSTAINABLE PROCUREMENT
Author:	EMELIA AKASHAH P.AKHIR, ROBERT T.HUGHES , KARL COX
Abstract:	Sustainable practices which increase awareness of people in industries which deal with environmental issues need to be implemented. However, information that needs to be considered to make informed decision on sustainable procurement is located in different places and comes in different form, either internal or external of the organizations. Thus, there is a strong need to consider this information to be interrelated and put in one place for easy access. The aim of this paper is to consider all of these concerns and develop information model to support sustainable procurement. It is hope that this information model is able to guide buyers in making the most informed decisions.
Keywords:	Sustainable Procurement, Information Model, Knowledge Management, Universities, Informed Decision Making
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	CUSTOMER ENGAGEMENT IN SOCIAL COMMERCE: A THEORETICAL REVIEW
Author:	ABDELSALAM H H BUSALIM, AB RAZAK CHE HUSSIN, AHMAD FADHIL YUSOF
Abstract:	Social commerce (s-commerce) has changed both businesses and customers. The role of customer has dramatically changed with the rapid growth of s-commerce. Customer engagement behavior in the s-commerce context has become a key competitive advantage for companies that aim to build a customer-centric business and utilize the power of social media. Numerous studies have conducted to understand the customer behavior to engage in s-commerce, but little effort have been made to incorporate the previous studies to provide theoretical foundation of customer engagement in s-commerce context. The aim of this study is to identify the well utilized theories and factors that influence customer engagement behavior in s-commerce. The study used a systematic Literature Review (SLR) as a method to identify and analyze the theories and factors related to customer engagement. The results shows that the theories which constitute the foundation of customer engagement studies can be classified into: social related theories, technological related theories, behavioral theories and motivational theories, and most of the well utilized factors are tapped under theses classifications. This study provides a comprehensive view of the theoretical foundation of customer engagement studies in s-commerce, and provide theoretical basis for IS research towards the development of empirical research on customer engagement and s-commerce.
Keywords:	Social Commerce, Social Media, Customer Engagement Behavior, Systematic Literature Review
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	A MOBILE BASED APPLICATION ON ENVIRONMENTAL EDUCATION FOR PRIMARY SCHOOLCHILDREN IN MALAYSIA
Author:	K.S. SAVITA, NUR AIN ZAINUDDIN, MANORANJITHAM MUNIANDY, MAZLINA MEHAT
Abstract:	The ever-rising environmental issues on industrial pollution and daily life activities are affecting our environment, and bringing negative implications globally. The Malaysian government has taken steps to overcome these problems through the implementation of 11th Malaysia Plan with focus to create green environment and sustainable nation. To do so, Malaysian government needs the cooperation and support from the society. An environmental caring society could only be established if the environmental caring habit is cultivated at early age. One of the methods is to nurture awareness on environmental friendly activities through early education. However, environmental education is still limited in the current syllabus of primary schools in Malaysia. The environmental-based contents are included in language textbooks, which with focus of educating the students on the languages and not on the importance of caring for the environment. Thus, teachers are experiencing insufficiency of appropriate teaching materials to deliver on environmental education. As one of the intervention and, to assist in teaching and learning of environmental education, a mobile based application incorporating basic environmental education topics has been developed. It is the first version of the prototype, “LOVE2GreenMY”, has been tested among Standard 4 primary schoolchildren from a few schools in Kuala Lumpur and Perak. The schoolchildren and teachers have provided positive feedbacks on the proposed solution, yet further improvements on the content and design will be carried out in the second version of the prototype. In the second version, greater scope of environmental topics and game-based activities will be included. LOVE2GreenMY aims to be the platform that educates environmental education, not only at schools but also at homes.
Keywords:	Environmental Education; Education for Sustainable Development; Malaysia; Mobile Application; Schools; Children; Teachers
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	THE CHALLENGES OF EXTRACT, TRANSFORM AND LOAD (ETL) FOR DATA INTEGRATION IN NEAR REAL-TIME ENVIRONMENT
Author:	ADILAH SABTU, NURULHUDA FIRDAUS MOHD AZMI, NILAM NUR AMIR SJARIF, SAIFUL ADLI ISMAIL, OTHMAN MOHD YUSOP, HASLINA SARKAN, SURIAYATI CHUPRAT
Abstract:	Organization with considerable investment into data warehousing, the influx of various data types and forms require certain ways of prepping data and staging platform that support fast, efficient and volatile data to reach its targeted audiences or users of different business needs. Extract, Transform and Load (ETL) system proved to be a choice standard for managing and sustaining the movement and transactional process of the valued big data assets. However, traditional ETL system can no longer accommodate and effectively handle streaming or near real-time data and stimulating environment which demands high availability, low latency and horizontal scalability features for functionality. This paper identifies the challenges of implementing ETL system for streaming or near real-time data which needs to evolve and streamline itself with the different requirements. Current efforts and solution approaches to address the challenges are presented. The classification of ETL system challenges are prepared based on near real-time environment features and ETL stages to encourage different perspectives for future research.
Keywords:	ETL, Near Real-Time Environment, High Availability, Low Latency, Horizontal Scalability
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	CO-DEPENDENCE RELATIONSHIP BETWEEN MASTER DATA MANAGEMENT AND DATA QUALITY: A REVIEW
Author:	FAIZURA HANEEM, AZRI AZMI, NAZRI KAMA
Abstract:	Master Data Management refers to the consolidation, integration and standardization of master data from multiple data sources into a centralized system to support data quality improvement in an organization. Nevertheless, while Master Data Management came into prominence in the information systems field of study, there is a lack of review papers for this topic have been published. Hence, this paper reports the results of a systematic literature review on the Master Data Management research topic. It aims to summarize the research progress of Master Data Management since 2000 to July 2016 and to review the association of Master Data Management and Data Quality. Search strategies with relevant keywords were used to identify literature from seven prestigious academic databases, namely 1) ACM Digital Library; 2) Emerald; 3) IEEE; 4) Science Direct; 5) Scopus; 6) Springer Link; 7) Web of Science, and one industry research database, namely Gartner. Additionally, the study made use of Google Scholar to find more related literature on the MDM research topic. From the review, 777 articles were found during the initial search and 347 relevant articles were filtered out for the analysis of MDM research progress. Then, out of the relevant articles, 49 were selected to discuss the association of MDM and Data Quality. This paper is a first academic systematic literature review on the progress of Master Data Management and its association with Data Quality. The result of the review shows that Master Data Management came into prominence from 2009 in parallel with the Big Data movement. Most researchers describe Master Data Management as a means to resolve data quality issues encountered during the management of multiple data sources. It ensures better data quality in the organization by combining a set of processes, data governance, and technology implementations.
Keywords:	MDM, Data Quality, Systematic Literature Review
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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Title:	TAG BASED NOISE REMOVAL FROM WEB PAGES
Author:	MAYAJOHN, JAYASUDHA J S
Abstract:	Over years the web has evolved as the largest repository of information available to mankind. Web pages have pieces of information which degrade the performance of mining data. The aforesaid type of information is termed as web noise which may be local or global in nature. A tag analysis based technique to eliminate local noises from a web page is proposed in this paper. Irrelevant images and links in a web page can be removed by analyzing the attributes and content of tags. Noisy information is eliminated either by filtering the tags representing noise or by modifying the attributes of tags. The contents in web page which are considered as noise by the proposed work include image advertisements, background images, unimportant link, search panel, copyright information etc. The efficiency in removing image advertisements was analyzed in terms of precision, recall and F-Score. The web pages after noise removal were found to have good compression ratio and showed a significant decrease in load time. As a result of removal of noise tags from web pages the size of source code of the web pages were also decreased considerably.
Keywords:	Advertisements, Block, Noise, Tag, Web page
Source:	Journal of Theoretical and Applied Information Technology 30^th November 2017 -- Vol. 95. No. 22 -- 2017
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