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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
July 2014 | Vol. 65 No.3

Title:	EFFICIENT SCHEDULING OF WORKFLOW IN CLOUD ENVIORNMENT USING BILLING MODEL AWARE TASK CLUSTERING
Author:	D.A.PRATHIBHA , B.LATHA, G. SUMATHI
Abstract:	Cloud computing is a cost effective alternative for the scientific community to deploy large scale workflow applications.For executing large scale scientific workflow applications in a distributed hetereogenous enviornment ,scheduling of workflow tasks with the dynamic resources is a challenging issue.Moreover in a utility based computing like cloud which supports pay per use model of the resources ,scheduling algorithm must efficiently utilize the available time of the resource.Most of the existing scheduling heuristics does not consider the dynamic nature of the cloud and hence produce the static schedule. Public cloud enviornment like Amazon EC2 offers catalog of resources and the price is generally metered per hour.Here any fractional usage is rounded off to the next hour.To meet the budget and deadline of the customers proposed work focuses to incorporate a billing model aware task clustering mechanism in the workflow scheduling process . This work also presents a resource selection algorithm which can be used for choosing proper resource at each stage in the workflow. Preliminary results obtained by running two scientific applications Montage and Cybershake with different resources and task clustering mechanisms are discussed.
Keywords:	Cloud Computing,Workflow,Resource Selection,Deadline,Budget,Task Clustering
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	CHDS: A FAST SEARCH ALGORITHM FOR MOTION ESTIMATION IN VIDEO CODING STANDARDSR. VANI, M. SANGEETHA, P. DAVIS
Author:	R. VANI, M. SANGEETHA, P. DAVIS
Abstract:	In this paper, we propose a new hybrid Cross Hexagon Diamond Search algorithm (CHDS) using cross-shaped search pattern as the initial step and asymmetric hexagon-shaped patterns and small diamond pattern as the subsequent steps for fast block motion estimation. In block motion estimation, search pattern with different shape or size and the center biased motion vector distribution characteristics has a great impact on search speed and distortion performance. The previously developed fast search algorithms focus on improvement of either coarse search or inner search. The Proposed CHDS algorithm reduces the number of search points by exploiting the distortion information in the neighbouring search points. Simulations are done using MATLAB and our experimental results indicate that the proposed CHDS algorithm reduces an average of 39.78% of time for motion estimation compared to New Hexagon Search (NHEXS), 10.86% of time for motion estimation compared to Hexagon Search (HS) and 38.64% of time for motion estimation compared to Diamond Search (DS).
Keywords:	Motion Estimation, Block Matching, Motion Vector, Search Algorithm
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	OPTIMIZED PRIORITY ASSIGNMENT SCHEME FOR CONGESTED WIRELESS SENSOR NETWORKS
Author:	BEULAH JAYAKUMARI. R, DR. JAWAHARSENTHILKUMAR V
Abstract:	Congestion is a likely event in wireless sensor networks due to node density and traffic convergence. Congestion can decrease network lifetime and reduce information accuracy. Transferring crucial data during congestion is a challenging problem in wireless sensor network. To achieve this we have proposed a competent data delivery protocol called Optimized Priority Assignment Scheme for congested wireless sensor network (OPAS). It dynamically assigns priority to every data based on their time critical nature and drops highly correlated duplicate data by considering delivery probability and finally tend to forward high and low priority data on two mutually exclusive routes only on congestion. OPAS improves data delivery and decreases packet drop for a predominantly congested wireless sensor network.
Keywords:	Wireless Sensor Network, Priority Assignment Scheme, Redundant Data, Data Delivery Protocol
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	STUDY OF A REAL TIME AIRCRAFT LANDING SCHEDULE WITH AN ATTEMPT TO OPTIMIZE THE SAME USING NON TRADITIONAL ALGORTHIMS
Author:	C.NITHYANANDAM, Dr.G. MOHANKUMAR
Abstract:	In this percent decade’s, airport scheduling operation are most essential for aircraft landing and takeoff. The radar range control systems act as the brain for the aircraft scheduling operations. Arrival runways are a critical resource in the air traffic system. Arrival delays have a great impact on airline operations and cost. Radar system is to communicate with all the aircrafts within the 200 nautical miles (370 km). In this paper the technique describes the execution time and penalty cost of the each aircrafts. Throughout, we discuss how our formulations can be utilized to model a number of issues (aircraft selection, precedence restrictions, restricting the number of landings and takeoffs in a given time period, runway workload balancing) commonly encountered in practice. Existing techniques does not considered the timing factor, so based on the time factor penalty cost is very high. Many of the techniques are used to reducing the penalty cost whenever possible to landing and takeoff operations are done for the emergency flights. These experiment shows whenever flights landing on the runway at that time no congestion on that particular path, if it’s occur then its seems to be problem. In order to eradicate these problem, neural network and Genetic Algorithms are utilized to eradicate the congestion occur in the runway and also our proposed technique reduced the penalty cost to be charged.
Keywords:	Artificial Neural Network, Aircraft Selection, Runway Selection, Scheduling, Genetic Algorithm
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	HANDWRITTEN DIGIT RECOGNITION FOR MANAGING EXAMINATION SCORE IN PAPER-BASED TEST
Author:	APICHAT SURATANEE, NANTAPORN LERTSARI, SETHAWAT KAMPHASEE, KRITSADA SRIKET
Abstract:	Calculating scores of a paper-based test with a large number of students is a difficult task. Suppose a large number of students, e.g., more than 1200 students, in a class take a paper-based examination with more than 6 questions in the test. Teachers need to write the score of each question on the examination cover sheet, calculate total scores of all students and fill the scores on the student list. These tasks really take a lot of time. We, therefore, develop an automatic system for reducing some procedures of these tasks for time-saving. Our developed system uses handwritten number recognition that has been widely used in several fields. In this study, we employ the recognition with artificial neural network to automatically identify the student identification number and scores of all questions from a scanned image of the cover page. The summation of scores is calculated automatically. Both of total score and the student identification number are exported into excel format. With the neural network classification to recognize the digits, we obtain high performance with overall accuracy of 99.89%. In conclusion, two main processes are improved from our system: (i) automatic total score calculation and (ii) exportation of scores to excel format. This designed system could successfully reduce the time for evaluating scores of students and yields more accurate score calculation.
Keywords:	Examination Cover Page, Handwritten Digit Recognition, OCR, Artificial Neural Network.
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	OPTIMIZATION ON SHORTEST PATH FINDING FOR UNDERGROUND CABLE TRANSMISSION LINES ROUTING USING GIS
Author:	VISWARANI.C.D, VIJAYAKUMAR.D, SUBBARAJ.L, S.UMASHANKAR, KATHIRVELAN.J
Abstract:	In cable trench construction, one of the tasks for engineers is to select a suitable route to minimize construction cost and obstructions. This paper discusses the development of a Geographic Information Systems (GIS)-based Customized system to automate the process of optimum shortest path finding for routing of underground power supply cable between any two substations. It combines the spatial analysis capabilities of GIS with the sophistication of one of the Artificial Intelligence technique “Simple Ant Colony Optimization” to deal with the complexity inherent in optimum shortest path finding. The results of this project are validated and compared with an inbuilt tool Network analyst of GIS software ArcGIS and explained in the Result and discussion of this paper. In this project only optimum shortest path finding is aimed and this will be one of the main input data in my future work of improving distribution efficiency using GIS.
Keywords:	Geographic Information System (GIS), Ant Colony Optimization (ACO), Network Analyst (ArcGIS), Electrical Distribution System
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	FUZZY CLUSTERING BASED ANT COLONY OPTIMIZATION ALGORITHM FOR MR BRAIN IMAGE SEGMENTATION
Author:	P. HARI KRISHNAN, DR. P. RAMAMOORTHY
Abstract:	The conventional methods for segmenting MR brain images with various noises were less effective. In this paper, we aimed for a novel method which intellectually determines the cluster centers before applying the (FCM) fuzzy c-means, thus increasing the iteration efficiency and reducing the computation time. The main feature of this proposed method is to utilize Ant Colony Optimization Algorithm (ACOA) to initialize the cluster centers and classification is made from thereafter using the initial values. Thus it helps to avoid the noisy pixel to be wrongly placed under any of the classes during the iterative process of FCM clustering algorithm, hence a better segmentation of MRI brain images which were scanned for detection of tumors was achieved. The methodology has been successfully carried out on Magnetic Resonance Imaging (MRI) images and efficient segmentation is was carried out on brain tumor images.
Keywords:	Ant Colony Optimization Algorithm (ACOA), Fuzzy C-Means (FCM), Magnetic Resonance Imaging (MRI), Clustering and Brain Tumor.
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	COMPOSITE TERMINAL SLIDING MODE CONTROL FOR SPACECRAFT WITH COUPLED TRANSLATION AND ATTITUDE DYNAMICS
Author:	CHUTIPHON PUKDEBOON
Abstract:	The composite terminal sliding mode controller design to deal with translation and attitude control of a rigid spacecraft is studied. Based on the terminal sliding mode (TSM) concept, a finite-time controller is designed to achieve translation and attitude maneuvers in the presence of model uncertainties and external disturbances. A finite-time disturbance observer (FTDO) is introduced to estimate the total model uncertainties and external disturbances. The proposed composite terminal sliding mode control consists of a finite-time controller based on TSM concepts and a compensation term based on FTDO. The Lyapunov theory is applied to prove the finite-time stability of the closed-loop system. Numerical simulations on translation and attitude control of a rigid spacecraft are also provided to demonstrate the performance of the proposed controller.
Keywords:	Composite Control, Terminal Sliding Mode Control, Finite-Time Disturbance Observer
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	SPEAKER RECOGNITION IN CLEAN AND NOISY ENVIRONMENT USING RBFNN AND AANN
Author:	R. VISALAKSHI, P. DHANALAKSHMI
Abstract:	In this paper, we propose a speaker recognition system based on features extracted from the speech recorded using close speaking microphone in clean and noisy environment. This system recognizes the speakers from a number of acoustic features that include linear predictive coefficients (LPC), linear predictive cepstral coefficients (LPCC) and Mel-frequency cepstral coefficients (MFCC). RBFNN and AANN are two modelling techniques used to capture the features. RBFNN model enables nonlinear transformation followed by linear transformation to achieve a higher dimension in the hidden space. The proposed work compares the performance of RBFNN with Autoassociative neural network (AANN). The autoassociative neural network (AANN) is used to capture the distribution of the acoustic feature vectors in the feature space. This model captures the distribution of the acoustic features of a class, and the backpropagation learning algorithm is used to adjust the weights of the network to minimize the mean square error for each feature vector. The experimental results show that, the performance of AANN performs better than RBFNN. AANN gives an accuracy of 94.93% for various acoustic features both in clean and noisy environment.
Keywords:	Radial Basis Function Neural Network (RBFNN); Autoassociative Neural Network (AANN); Linear Predictive Coefficients (LPC); Linear Predictive Cepstral Coefficients (LPCC); Mel-Frequency Cepstral Coefficients (MFCC); Speaker Recognition (SR)
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	PERFORMANCE EVALUATION FOR MULTI-HOLE PROBE WITH THE AID OF ARTIFICIAL NEURAL NETWORK
Author:	J.V. MURUGA LAL JEYAN, Dr.M. SENTHIL KUMAR
Abstract:	The multi hole conical probe is extensively employed in the fluid fields for estimating the overall and static pressure and velocity of the vibrant fields. The probe is formed by various types of materials such as aluminum, copper and stainless steel which are utilized in the wind tunnel to determine the static and total pressure of the fluid fields. Many varied material probes are engaged to assess their efficiency in execution in the concurrent surroundings at diverse Mach number situations and the yields are calculated according to displacement and stress for diverse material probes. The innovative artificial neural network is effectively employed to forecast the varied material accomplishment of the probe by making use of the Levenberg-Marquette algorithm of the artificial neural network, which is applied in the artificial neural network to estimate the yields of the various material probes and the outcomes are subjected to analysis and contrast with the Conjugate Gradient with Beale (CGB) algorithm, Variable Learning Rate Gradient Descent (GDX) algorithm and Scaled Conjugate Gradient (SCG) algorithm of the artificial neural network. The MATLAB software is performed to assess the efficiency of the artificial neural network for various kinds of material probes.
Keywords:	Multi-Hole Probe, Materials, Artificial Neural Network, Levenberg-Marquette Algorithm
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	WEIGHTED QUANTUM PARTICLE SWARM OPTIMIZATION TO ASSOCIATION RULE MINING AND PSO TO CLUSTERING
Author:	D.GOKILA, DR.S.RAJALAKSHMI
Abstract:	In the area of association rule mining (ARM), the most major algorithms is Apriori algorithm. In the existing Apriori algorithm minimum support and confidence are determined subjectively or through trial and error method so, the algorithm lacks the objectiveness and efficiency. To improve the efficiency of association rules, Particle Swarm Optimization (PSO) algorithm is projected, which gives feasible threshold values for minimum support and confidence. In the PSO algorithm, initially it looks for the optimum fitness value of each particle and then finds their corresponding support and confidence as minimum threshold values. The difficulty of PSO algorithm is that, it guesses that the items have the same implication without taking into account of their weight/attributes within a transaction or within the whole item space. To overcome this drawback, this paper proposes a weighted quantum particle swarm optimization algorithm (WQPSO) with weighted mean best position according to fitness values of the particles. WQPSO algorithm provides faster local convergence, fallout in better balance between the global and local searching of the algorithm, so it generates good performance. The proposed WQPSO algorithm is experienced with several benchmark functions and compared with standard PSO. The experimental result shows the supremacy of WQPSO and it is verified by applying the FoodMart2000 database of Microsoft SQL Server 2000. Likewise, in clustering, there are many unsupervised clustering algorithms have been developed one such algorithm is K-means which is simple and straightforward. The main drawback of the K-means algorithm is that, the result is sensitive to the selection of the initial cluster centroids and may converge to the local optima. This is solved by PSO as it performs globalized search and produces clusters with high intra class similarity.
Keywords:	Data mining, Association Rule Mining, Particle Swarm Optimization, K-Means, Weighted Quantum Particle Swarm Optimization, Clustering
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	AN EFFICIENT ASCII-BCD BASED STEGANOGRAPHY FOR CLOUD SECURITY USING COMMON DEPLOYMENT MODEL
Author:	C.SARAVANAKUMAR, C.ARUN
Abstract:	Cloud computing is a service oriented computing which offers everything as a service by following the pay-as-you-go model. It is more popular because the cloud data are accessed by variety of customers. An important issue of the cloud computing is to secure the customer data in geographical disperse locations. There are plenty of security standards and policies are available in order to secure the data, but these standards are exist only at the cloud end. It is a critical task for the customer as well as provider to store, retrieve and transmit the data over the cloud network and storage in a secure manner. The customer can store or process the sensitive data who needs a security during the time of travel over the network to the processing environment. The existing security algorithm secures customer data at the provider end which are not known by the customer and also multiple boundaries exists in the cloud resource access which leads the reliability problem. The main objective of the proposed algorithm is to develop a customer owned security algorithm and the encrypted data are send to the provider end. The provider can also apply the security over the customer’s data by using efficient algorithm. The customer’s data are in a secure manner at both the end to achieve maximum reliability. The proposed algorithm uses ASCII and BCD security with steganography that stores the encrypted data in an image file which will be send to the provider end. The security algorithm has to be implemented by using the CDM (Common Deployment Model) which also provides an interoperable security services over the cloud. In future, steganography can be applied to secure the virtual images in the cloud computing.
Keywords:	Cloud Computing, Cryptography, Steganography, Distributed Systems, CDM
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	SYMBOLIC DATA CONVERSION METHOD USING THE KNOWLEDGE-BASED EXTRACTION IN ANOMALY INTRUSION DETECTION SYSTEM
Author:	JATUPHUM JUANCHAIYAPHUM, NGAMNIJ ARCH-INT, SOMJIT ARCH-INT, SAIYAN SAIYOD
Abstract:	In anomaly intrusion detection systems, machine learning algorithms, e.g. KNN, SOM, and SVM, are widely used to construct a model of normal system activity that are designed to work with numeric data. Consequently, symbolic data (e.g., TCP, SMTP, FTP, OTH, etc.) need to be converted into numeric data prior to being analyzed. From the previous works, there were different methods proposed for handling the symbolic data; for example, excluding symbolic data, arbitrary assignment, and indicator variables. However, these methods may entail a very difficult classification problem, especially an increase of the dimensionality of data that directly affect the computational complexity of machine learning algorithm. Thus, this paper proposed a new symbolic conversion method in order to overcome limitations of previous works by replacing the symbolic data with their risk values, obtained from knowledge-based extraction. The experiments affirmed that our proposed method was more effective in improving the classifier performance than did the previous works, and it did not increase the dimensionality of data.
Keywords:	Symbolic Conversion, Knowledge Extraction, Anomaly Detection, IDS, Machine Learning
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	DESIGN OF SECOND ORDER SIGMA-DELTA MODULATOR FOR AUDIO APPLICATIONS
Author:	DHANABAL R, BHARATHI V, NAAMATHEERTHAM R SAMHITHA, G.SRI CHANDRAKIRAN, SAI PRAMOD KOLLI
Abstract:	The paper includes the design of second order sigma-delta modulator. A comparative study between a first order and second order sigma-delta modulator is carried out. The second order is preferred over the first order sigma-delta modulator due to its better signal-to-noise ratio (SNR). The comparative study between the modulators is done in Matlab, the second-order sigma-delta modulator is designed and modelled in Verilog-A and simulated in Cadence SpectreS. The second order sigma-delta modulator provides an enhancement of 27% in SNR as compared to the first order sigma-delta modulator.
Keywords:	Sigma Delta Modulator, SNR, Oversampling, Noise Shaping
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	DESIGN AND IMPLEMENTATION OF FACE DETECTION USING ADABOOST ALGORITHM
Author:	SENTHILSINGH C, M.MANIKANDAN
Abstract:	Face recognition system is an application for identifying someone from image or videos. Face recognition is classified into three stages ie)Face detection,Feature Extraction ,Face Recognition. Face detection method is a diﬃcult task in image analysis. Face detection is an application for detecting object, analyzing the face, understanding the localization of the face and face recognition.It is used in many application for new communication interface, security etc.Face Detection is employed for detecting faces from image or from videos. The main goal of face detection is to detect human faces from different images or videos.The face detection algorithm converts the input images from a camera to binary pattern and therefore the face location candidates using the AdaBoost Algorithm. The proposed system explains regarding the face detection based system on AdaBoost Algorithm . AdaBoost Algorithm selects the best set of Haar features and implement in cascade to decrease the detection time .The proposed System for face detection is intended by using Verilog and ModelSim,and also implemented in FPGA.
Keywords:	Adaboost, Face Detection, FPGA, Haar Classifier, Image Processing, Real-Time.
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	MALICIOUSNESS IN MOBILE AD HOC NETWORKS: A PERFORMANCE EVALUATION
Author:	K. TAMIZARASU, A.M. KALPANA, Dr. M. RAJARAM
Abstract:	Mobile Ad hoc Networks (MANETs) combine wireless communication with high node mobility. Limited wireless communication range and node mobility ensure that nodes cooperate with each other to provide networking, with network dynamically changing to ensure needs are met continually. The protocols dynamic nature enables MANET operation as suited to deployment in extreme circumstances. Hence, MANETs are a popular research topic and are proposed for use in areas like rescue operations, tactical operations and environmental monitoring. This study evaluates impact of malicious node attack (Black Hole Attack) on Ad hoc On-demand Distance Vector (AODV) MANET routing. The experiment consists of 25 nodes distributed over 2 square kilometres. AODV routing protocol is resorted to. Three experiments were conducted, the first without malicious nodes and with 10% and 20% of malicious nodes.
Keywords:	Mobile Ad Hoc Networks (Manets), Routing In MANET, Ad Hoc On-Demand Distance Vector (AODV), And Black Hole Attack
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	A MULTI-OBJECTIVE APPROACH FOR ENERGY EFFICIENT CLUSTERING USING COMPREHENSIVE LEARNING PARTICLE SWARM OPTIMIZATION IN MOBILE AD-HOC NETWORK
Author:	A.KARTHIKEYAN, SANYUKTA, 2SHEPHALI GUPTA, T.SHANKAR
Abstract:	A mobile ad-hoc network (MANET) faces various challenges including limited energy, limited communication bandwidth, computation constraint and cost. Therefore, clustering of sensor nodes is adopted which involves selection of cluster-heads for each cluster. This enhances system performance by enabling bandwidth reuse, better resource allocation and improved power control. The various existing clustering techniques provide a single optimized solution in a single simulation run. Therefore, a multi-objective approach is used to optimize the number of clusters and to manage the energy dissipation issues. The proposed algorithm is a multi-objective variant of Particle Swarm Optimization (PSO) called multi-objective comprehensive learning particle swarm optimization (MOCLPSO) which reduces the time-complexity and increases the speed of the algorithm. In this technique, the best position of a randomly selected particle from the population is used to update the velocity of particle in each dimension, rather than using the personal or global best positions. The parameters taken into consideration in the proposed algorithm includes degree of nodes, transmission range and battery power consumption of the nodes. This technique provides multiple trade–off solutions in a single run of the algorithm. The performance of the proposed algorithm is compared with various clustering techniques: LEACH, PSO, WCA, CLPSO and MOPSO.
Keywords:	Comprehensive Learning Particle Swarm Optimization (CLPSO), Multi-objective Particle Swarm Optimization (MOPSO), Multi-objective Comprehensive Learning Particle Swarm Optimization (MOCLPSO), Particle Swarm Optimization (PSO), Weighted Clustering Algorithm (WCA)
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	TSAAC: THRESHOLD SENSITIVE ASSISTANT AIDED CLUSTERING PROTOCOL FOR HETEROGENEOUS WSNs USING NICHING PARTICLE SWARM OPTIMIZATION
Author:	A. KARTHIKEYAN, 2FALAK JINDAL, NEERAJ KAUR BUMRAH, SWAPNIL PAMECHA, T.SHANKAR
Abstract:	The energy efficiency and improvement in network’s lifetime are some of the critical issues in wireless sensor networks (WSNs). Remote environmental monitoring and target tracking are the important applications of a wireless sensor network. In this paper, TSAAC (Threshold Sensitive Assistant Aided Clustering) a heterogeneous protocol using Niching Particle Swarm Optimization (NPSO), for wireless sensor networks is proposed. It employs three levels of heterogeneity with cluster head being selected optimally based on the fitness function of NPSO, which is an important technique for multimodal optimization. To further balance the energy dissipation and enhance the system robustness, an assistant cluster head can be selected based on the cluster state information. Being threshold sensitive, this protocol significantly improves the stability period and reduces energy consumption considerably by 14% compared to TSEP (Threshold Sensitive Stable Election Protocol). The performance of the proposed protocol is compared with the existing protocols like LEACH, AAAC-NPSO, SEP and TSEP. The simulation results show that TSAAC-NPSO can achieve better network lifetime.
Keywords:	WSNs (Wireless Sensor Networks), NPSO (Niching Particle Swarm Optimization), Heterogeneity, Assistant-Aided Clustering, Thresholding.
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	MULTI-FACTOR APPROACH FOR EFFECTIVE REGRESSION TESTING USING TEST CASE OPTIMIZATION
Author:	S RAJU, G V UMA
Abstract:	Regression testing intends to ensure that a software applications works as specified after changes have been made to it, is an important phase in software development lifecycle. Regression testing is the re-execution of some subset of test that has already been conducted. In regression testing, number of regression tests increases and it is impractical and inefficient to re execute every test for every application or function when change occurs. It is an expensive testing process used to detect regression faults. Regression testing has been used to support software-testing activities and assure acquiring an appropriate quality through several versions of a software product during its development and maintenance. Test suites can be large and conducting regression tests is tedious. Regression testing assures the quality of modified applications against unintended changes. The test case selection and prioritization is important in regression testing. Test case prioritization seeks to find an efficient ordering of test case execution for regression testing. Test case prioritization is used in regression testing, at the test suite level, with the goal of detecting faults as early as possible in the regression testing process, given a test suite inherited from previous versions of the system.
Keywords:	Regression Test, Test Case Prioritization, Priority Factors, Defect Density, Defect Removal Efficiency, Average Percentage of Fault Detected (APFD), Genetic Algorithm, Clustering.
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	COOPERATIVE PACKET DELIVERY USING ENHANCED COOPERATIVE OPPORTUNISTIC ROUTING SCHEME (ECORS) IN MANET
Author:	VIJAYAKUMAR A, SELVAMANI K
Abstract:	Cooperative communication is an active area of research today. It enables the nodes to achieve spatial diversity, which leads to tremendous improvement in system capacity and delay. In this proposed system cooperative communication mechanism is used to determine a list of intermediate relay nodes that follows en-route to the destinations. Here, when data packets are broadcasted from a source node and the packets are received by a destination node along with the route. Cooperative communications which utilizes nearby terminals to relay the message transmissions also induces the non-cooperative nodes to participate in some opportunistic environments for achieving the diversity gains and to improve the efficiencies among the mobile nodes in wireless mobile ad hoc networks. The Enhanced Cooperative Opportunistic Routing Scheme (ECORS) which is based on light weight proactive source routing is used in this work to ensure the cooperation of participating mobile nodes in MANETs. This new protocol is used to easily identify the intermediate nodes and establishing the trusted routes. The comparative performance analyses among AODV versus ECORS are properly carried out and the better cooperative packet delivery ratio, increased throughput and decreased delay in packet delivery are achieved in this network simulation.
Keywords:	Cooperative communication, MANETs, Opportunistic packet forwarding, Packet delivery, Retransmission, Throughput.
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	TERRESTRIAL-TO-SATELLITE INTERFERENCE IN THE C-BAND: TRACTABLE CALCULATION TECHNIQUE
Author:	LWAY FAISAL ABDULRAZAK, A. HAMEED
Abstract:	This paper presents a research conducted on the interference mitigation between IMT-Advanced and Fixed Satellite Services (FSS). It covers a deterministic analysis for interference to noise ratio (I/N), adjacent channel interference ratio (ACIR) and path loss propagation, in order to determine the separation distances in the co-channel interference (CCI) and adjacent channel Interference (ACI) scenarios. An analytical model has been developed based on the deterministic analysis of the propagation model. The IMT-Advanced parameters have been represented by Worldwide Interoperability for Microwave Access (WiMAX) 802.16e. The impact of different FSS channel bandwidths, guard band separations, antenna heights and different deployment areas on co-existence feasibility are considered. The results obtained in terms of minimum required separation distance in three scenarios, co-channel, zero-guard band, and adjacent channel are analyzed.
Keywords:	Interference, Separation Distance, Bandwidth, IMT-Advanced, Guard Band
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	FEATURE EXTRACTION AND DIMENSIONALITY REDUCTION IN PATTERN RECOGNITION USING HANDWRITTEN ODIA NUMERALS
Author:	PRADEEPTA K. SARANGI, KIRAN K. RAVULAKOLLU
Abstract:	Feature extraction is the initial and critical stage which needs to be carried out very carefully for any recognition system that uses pattern matching. In order to reduce the feature extraction complexity, dimensionality reduction is applied. This also increases the performance and recognition accuracy. This paper proposes the concept of a new feature extraction and dimensionality reduction method based on a set of linear transformation of the character image. The verification of the method has been carried out by implementing a simple recurrent neural network (RNN) with a data set consisting of 1500 isolated handwritten Odia numerals. An accuracy of 92.41% is reported. Experimental results show that the proposed method has the potential to be used as a feature extraction method for handwritten Odia numerals.
Keywords:	Handwritten Recognition, Odia Numerals, Recurrent Neural Network, Feature Extraction
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	RESOURCE MEDIAN MULTICAST ROUTING PROTOCOL FOR ENERGY CONTROLLED MULTIPATH COMMUNICATION IN WIRELESS AD-HOC NETWORK
Author:	SHANMUGASUNDARAM , CHANDRASEKAR
Abstract:	Many applications in network consisting of scattered interactive method, software improvements and replica model for distributed database envisages optimized routing, scheduling and data dispersal schemes. A large wireless ad-hoc network broadcast messages from the source to all the elements in a multicast group. Certain research works based on the leader election model (DSLE) focus on the incentives in the form of reputations ensuring security to participate in the election process. With the application of DSLE, the consumption of resources was balanced during the detection of intrusion whereas the detection service through routing was not effective. In order to discover the path the method Channel-Aware Ad hoc On-Demand Multipath Distance Vector (CA-AOMDV) chooses the stable links and also predicts the path failure for improving the routing decisions. To improve the routing decision, CA-AOMDV uses the channel average non-fading period as a routing metric but maximal energy was consumed for obtaining the channel state information in wireless ad-hoc network. To handle the communication using multi-path routing path effectively, Resource Median Multicast Routing (RMMR) Protocol is designed. The protocol RMMR adapt to any form of wireless ad-hoc network with median multicast tree for effective routing service. The initial connection between the wireless nodes is counted and computation effort is minimized using the median multicast trees. Median Multicast employs Energy Controlled Active Multicast (ECAM) algorithm which constructs a multicast tree with minimal energy consumption while transferring the information. ECAM algorithm uses the idling concept to reduce the energy consumption while performing the multipath communication in wireless ad-hoc network. The simulation metric taken for experimenting the RMMR Protocol are the factors such as energy consumption on multipath communication, routing control overhead, packet delivery ratio on wireless nodes, throughput based on mobility speed.
Keywords:	Resource Median Multicast Routing, Wireless Ad-hoc Network, Active Multicast, Idling, Routing Protocol, Channel State Information
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	OFFLINE HANDWRITTEN SIGNATURE VERIFICATION USING BACK PROPAGATION ARTIFICIAL NEURAL NETWORK MATCHING TECHNIQUE
Author:	ANWAR YAHY EBRAHIM, GHAZALI SULONG
Abstract:	Handwriting is a skill that is highly personal to individuals and consists of graphical marks on the surface in relation to a particular language. Signatures of the same person can vary with time and state of mind. Several studies have come up with several methods on how to detect forgeries in signatures given to the security implication of signatures to daily business and personal transactions. This paper illustrates the proposed methodology for an offline handwritten signature identification and verification system which extracts certain dynamic features derived from velocity and acceleration of the pen together with other global parameters like total time taken and number of pen-ups in order to distinguish between forged signatures and genuine signatures signed under duress. Adaptive Window Positioning technique was employed for feature extraction, which focuses on not just the meaning of the handwritten signature but also on the individuality of the writer by dividing the handwritten signatures into 13 small windows of size nxn (13x13) such that it is large enough to contain ample information about the style of the author and small enough to ensure a good identification performance. Then, a signer specific codebook approach was used to generate a separate codebook of patterns for each individual signer such that the number of classes in each codebook varies as a function of the writing sample (signer), and a 3-layered Backward Propagation Artificial Neural Network (BPANN) method was used to produce a maximal matching and preserve the efficiency of the network. The proposed method was validated using a trained GPDS data set of 2400 original signatures of 100 different signers and comparing the results with those of two different known techniques of offline handwritten signature verification systems. The findings indicate that the proposed technique had the lowest ERR value of 7.23, indicating a more improved performance when compared against the two known techniques respectively thus proving to be a more efficient and superior method for offline handwritten signature identification and verification.
Keywords:	Offline Handwritten Signature, Identification, Verification, Adaptive Window Positioning, Signer Specific Codebook, Backward Propagation Artificial Neural Network
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	RSA-DWT BASED MEDICAL IMAGE WATERMARKING FOR TELEMEDICINE APPLICATIONS
Author:	N.VENKATRAM, L.S.S.REDDY, P.V.V.KISHORE, CH.SHAVYA
Abstract:	Medical images convey important information to the doctor about a patient’s health condition. Internet transmits these medical images to remote locations of the globe to be examined by expert doctors. But data transmission through unsecured net invokes authentication problems for any image data. This problem of authentication of medical images is addressed in our research as medical image watermarking with patient images. Medical images contain very sensitive information. Watermarking medical images require careful modifications preserving the data in the images. This is being accomplished using RAS (Rivest, Shamir and Adleman) algorithm for patient image encryption and decryption. The host images are set of medical images such as MRI, CT and Ultrasound scans of patient body parts. These medical images are watermarked with encrypted patient image in transform domain using 2D Discrete Wavelet Transform (DWT). The host medical image and watermark image are transformed into wavelet domain and are mixed using two scaling factors alpha and beta. Finally these watermarked medical images are transmitted through the internet along with the secret key that will be used for decryption. At the receiving the embedded encrypted watermark is extracted using 2DWT and decryption key. The robustness of the proposed watermarking techniques is tested with various attacks on the watermarked medical images. Peak-Signal-to-Noise ratios and Normalized cross correlation coefficients are computed to accesses the quality of the watermarked medical images and extracted patient images. The results are produced for three types of medical images with one patient image watermarks using single key by using four wavelets (haar, db, symlets, bior) at four different levels (1,2,3,4).
Keywords:	Medical Image Watermarking, RAS (Rivest, Shamir and Adleman) algorithm, Discrete Wavelet Transform (DWT), MRI, CT and Ultrasound Images.
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	ANALYSIS OF OPTIMIZATION TECHNIQUES IN CHI-SQUARED AUTOMATIC INTERACTION DETECTION
Author:	SWARNALATHA S.R, G.M. KADHAR NAWAZ
Abstract:	In the context of pattern classiﬁcation, one of the major issues discussed by most of researchers is ‘curse of dimensionality’ problem which occurs in data classification because the data processed in most of the application is high-dimensional feature space.So, the essential consideration here is that irrelevant features should be identified which causes less classiﬁcation accuracy and the main motto is to find a minimum set of attributes from the initial set of data helping to make the patterns easier to understand along with improved classification accuracy and reduced learning time. Therefore, the selection of feature set is the process to search for an optimal feature subset from the initial data set without compromising the classiﬁcation performance and efficiency in generating classiﬁcation model. In this paper, we develop a hybrid classifier by combining CHAID and genetic algorithm. Initially, the genetic algorithm with ABC operator will extract the best attributes and based on the extracted attributes the CHAID will generate the decision tree. We analyze the performance with different datasets and compare the analysis with the existing technique.
Keywords:	Optimization, Chi-Square, Automatic Interaction, Detection
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	POWER SYSTEM LOADABILITY IMPROVEMENT BY OPTIMAL ALLOCATION OF FACTS DEVICES USING REAL CODED GENETIC ALGRORITHM
Author:	R.MEDESWARAN, N.KAMARAJ
Abstract:	FACTS devices can effectively control the load flow distribution, improve the usage of existing system installations by increasing transmission capability, compensate reactive power, improve power quality, and improve stabilities of the power network. However, the location and settings of these devices in the system plays a significant role to achieve such benefits. This work presents the application of Real Coded Genetic Algorithm (RGA) for finding out the optimal locations, and the optimal parameter settings of single type and multi type FACTS devices to achieve maximum system loadability (MSL) in the power system. The FACTS devices used are Thyristor Controlled Series Capacitor (TCSC) and Unified Power Flow Controller (UPFC). The reactance model for TCSC and the decoupled model for UPFC are considered for this work. The thermal limits of the line and voltage limits of the buses are taken as constraints during the optimization. Simulated Binary Crossover (SBX) and Non-uniform polynomial mutation are employed to improve the performance of the Genetic Algorithm used. Simulations are performed on IEEE 6 bus and 30 bus power systems. The obtained results are encouraging and show the effectiveness of RGA.
Keywords:	Loadability, FACTS, TCSC, UPFC, and Real Coded Genetic Algorithm
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	DOCUMENT CLUSTERING USING CO-WORD ANALYSIS AND FORMATION OF KEYWORD AGAINST DOCUMENT MATRIX
Author:	Document Clustering, Text Mining, Keyword Extraction, Co-word Analysis, HTML Tags.
Abstract:	A complexity of the retrieval of relevant document from a large corpus of documents is the most common challenging problem in the areas of web mining and search engines. In addition, the growth of unlabelled and unsupervised documents are also increases this complexity. Document clustering algorithms plays a vital role to reduce this problem. In this paper, an algorithm was proposed to cluster the documents based on their concepts. The proposed algorithm in its first part identifies the vital keywords of the document, those helps to find out the concept of the document, using our new statistical text mining algorithm. In the second part, based on the results derived, the given documents are clustered using
Keywords:	Vs Documents matrix analysis. This proposed Document Clustering algorithm gives more than 90 % accuracy.
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	A NOVEL APPROACH OF FIC FOR COMPRESSION OF LARGE SCALE REMOTE SENSING COLOR IMAGES
Author:	D.SOPHIN SEELI, DR.M.K.JEYAKUMAR
Abstract:	Image compression has become an important issue in the storage and the transmission of images including satellite and aerial photographs. A new approach was used for compressing satellite images is to construct compression algorithms by using the fractal theory. This paper is based on a novel image structure, Spiral Architecture, which has hexagonal instead of square pixels as the basic element. In the proposed work, we use only two codebooks for all images. Open and private code book is generated for the remote sensing image gallery, instead of using separate codebook for each during the process; hence high compression ratio can be achieved. Introducing Spiral Architecture into fractal image compression for remote sensing images will improve the compression performance in compression ratio, reduction of memory and bandwidth cost of large-scale remote sensing images.
Keywords:	Fractal Image Compression; Compression Ratio; Large-Scale Remote Sensing Image; Hexagonal Structure; Spiral Architecture; Codebook.
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	DETERMINING MAXIMUM/MINIMUM VALUES FOR TWO-DIMENTIONAL MATHMATICLE FUNCTIONS USING RANDOM CREOSSOVER TECHNIQUES
Author:	SHIHADEH ALQRAINY
Abstract:	This paper presents a solution to determining the maximum/minimum values for two-dimensional mathematical functions using the three most popular crossover techniques (Single point, Two point and cut and splice) randomly in genetic algorithm. A set of experiments were ran over 20 complex functions, the obtained results show that using random crossover techniques tends to be worst compared with traditional genetic algorithm that uses specific crossover method such as single point crossover.
Keywords:	Genetic Algorithm, Machine Learning, Heuristic Search. Crossover Methods
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	TWO-WAYS DATABASE SYNCHRONIZATION IN HOMOGENEOUS DBMS USING AUDIT LOG APPROACH
Author:	RAI GUDAKESA, I MADE SUKARSA, I GUSTI MADE ARYA SASMITA
Abstract:	Data integration is the most important part in applying distributed database, in which data from various data source can be united by implementing integration. Data replication is one of the data integration forms which is very popular nowadays, since it is convenient or it can do backup towards data in various different sites. The practice absolutely has shortcomings in data integration, as there is no control over the integration from replicated data, therefore it is necessary to do synchronization towards data. Data synchronization is a part of replication, it is a process to ensure each copy of database contains similar object and data. Data synchronization can be applied in numerous methods, one of them is utilizing Audit Log that is recorded every activities occur at database. Audit Log can be applied to almost any Database Management System (DBMS). This research utilized TCP Socket and client-server architecture to distribute data from Audit Log. The final result concludes that Audit Log can be utilized in synchronization with client-server implementation, yet it has limitation in recording data. This paper also showing how Audit Log created and managed to be used as replication and synchronization procedure.
Keywords:	Distributed Database, Data Integration, Data Replication, Data Synchronization, Audit Log
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	A FUZZY AHP PROCESS IN GIS ENVIRONMENT FOR LANDFILL SITE SELECTION
Author:	BENNIS Kaoutar, BAHI Lahcen
Abstract:	The purpose of this paper is to present a hybrid methodology combining Geographic Information Systems (GIS), Fuzzy Analytic Hierarchical Process (FAHP) and stakeholder’s judgment. This multi-level decision-making tool captures the ambiguity and impreciseness in decision making judgments, and results in a final priority ranking to site a new waste disposal area for the city of Tangier in the north of Morocco. The criteria at hand are spatial by nature and contribute differently to the choice-making process, the GIS-FAHP integration allows to deal with geospatial data while accounting for the tradeoffs of the criteria with regard to the main objective. In fact, the FAHP acts in a first time as a method of extracting the weights of each criteria/layer from a pair-wise comparison matrix, then, in a second time, FAHP acts as a method in selecting the best site from a set of most viable sites; the pair-wise comparison matrices are the result of stakeholders evaluation of all criteria, sub-criteria and sites. The set of most viable sites is obtained with the GIS tool in which we conducted the data preparation, each criterion is represented by a layer which is either extracted from remote sensing imagery or digitalization of local maps, a weighted linear combination (WLC) processes the layers and results in a map of suitability for landfill siting.
Keywords:	Fuzzy Analysis, Analytic Hierarchical Process (AHP), Geographic Information System (GIS) , Weighted Linear Combination (WLC), Suitability.
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	SEARCH IN TEXT DOCUMENTS BASED ON N-GRAMS AND FOURIER WINDOW TRANSFORMATION
Author:	K.YA KUDRYAVTSEV
Abstract:	This paper is of theoretical nature and is devoted to the development and theoretical justification of the new Full Text Search method in documents. The idea of the method is to partition the text into N-grams, to construct "spectrograms" of a text document using the windowed Fourier transform. Then a fast Fourier transform algorithm is used and "spectrogram" of the text of the document is compared to the "spectrogram" of the search line in special "control" points. This paper provides a rigorous mathematical justification of the proposed method, the possibility of forming conclusions on the presence of the search line in the document is proven. A generalized algorithm of a new method of full-text search is presented.
Keywords:	Full-text search in databases, Window Fourier transform, Fast Fourier Transform, Spectrogram text, N-Grams.
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	GA BASED FEATURE RANKING MECHANISM TO DETECT NEW BORN INFANTS JAUNDICE WITH AN ENSEMBLE TREE STRATEGY
Author:	A. ARULMOZHI, DR.M. EZHILARASI
Abstract:	Jaundice is a yellow discoloration of the skin and whites of the eyes that is often seen in newborns. Newborn jaundice can be analyzed by scrutinizing the infant and examining blood levels of bilirubin. Infants with high blood levels of bilirubin called hyperbilirubinaemia, evolve the yellow color when bilirubin acquires in the skin. The major symptom of jaundice is yellow coloring of the skin and conjunctiva of the eyes. A Genetic Algorithm (GA) is used to enhance or optimize the overall behavior by evolving the population. Genetic Algorithms (GAs) are a virtually new criterion for a search, based on the precept on instinctive selection. Ensemble methods are learning algorithms that design a set of classifiers. An ensemble of classifiers is a predetermined classifier whose individual decisions are combined in some way to classify new examples. In this analysis, an ensemble of fitness evaluations would produce an ensemble of fitness values for each individual. The experimental results reveal that the proposed method can act as a supplement to support earlier detection and more effective treatment due to improved jaundice detection.
Keywords:	Fitness Evaluation, Jaundice, Hyperbilirubinaemia, Maximal Information Compression Index (MICI), Machine Learning, Kernel Support Vector Machine (SVM), Gray Level Co-occurrence Matrix (GLCM), Genetic Algorithm (GA).
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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Title:	REDUCED ORDER LINEAR QUADRATIC REGULATOR PLUS PROPORTIONAL DOUBLE INTEGRAL BASED CONTROLLER FOR A POSITIVE OUTPUT ELEMENTARY SUPER LIFT LUO-CONVERTER
Author:	N.ARUNKUMAR, T.S. SIVAKUMARAN, K.RAMASH KUMAR, S.SARANYA
Abstract:	The design and analysis of reduced-order linear quadratic regulator (ROLQR) plus proportional double integral controller (PDIC) for enhancing the dynamic performance of the positive output elementary super lift Luo-converter (POESLLC) worked in continuous conduction mode (CCM) is carried out, The ultimate aim is designing the PDIC is to obtain the efficient output voltage regulation with zero steady state error. The ROLQR is mainly designed to regulate inductor current which in turn enhances the dynamic performance of the converter. The POESLLC is modeled using state space average technique. Extensive simulation is carried under both line and load variations and the controller platform are evaluated using well as in the experimental model (digital dsPIC30F4011controller). The simulation and experimental results are illustrated that the POESLLC with ROLQR plus PDIC tracks reference voltage, regulate the inductor current and robust in spite of line and load variation.
Keywords:	DC-DC Power Conversion, Positive Output Elementary Super Lift Luo-Converter, Linear Quadratic Regulator, Proportional Double Integral Controller And State-Space Average Model.
Source:	Journal of Theoretical and Applied Information Technology 31 July 2014 -- Vol. 65. No. 3 -- 2014
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