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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
February 2014 | Vol. 60 No.3

Title:	THE MIXTURE MODEL: COMBINING LEAST SQUARE METHOD AND DENSITY BASED CLASS BOOST ALGORITHM IN PRODUCING MISSING DATA AND BETTER MODELS
Author:	LADAN MALAZIZI
Abstract:	The problem of missing values in data tables arises in almost all domains. With the volume of the information growing every day on the communication channels and the necessity of the integration of this data for data analysis and data mining, this reflects even more. In this paper with two step process first we recover missing values using Least Square method (LS) [1] then we use our own Density Based Class Boost Algorithm (DCBA) [2] in order to improve learner performance. In this process we model the data using Meta learner once when data tables have been cleaned (removing empty rows containing missing values), then when data has been recovered and lastly after application of The Mixture Model. In this paper our contributions are toward three issues: first the effect of data cleaning in the mean of losing data with missing cells in model performance, second the effect of Least Square method in data generation in such highly correlated features datasets and third the effect of the combination model in classifier performance.
Keywords:	Least Square, Density Based Class Boost, Missing Data Recovery
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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Title:	DIRECT TORQUE CONTROL TECHNIQUE IN INDUCTION MOTOR DRIVES - A REVIEW
Author:	S ALLIRANI, V JAGANNATHAN
Abstract:	The aim of this paper is to review the origin and developments of direct torque control (DTC), an advanced control technique of induction motor drives yielding superior performance. The direct torque control is one of the excellent control strategies available for torque control of induction machine. It is considered as an alternative to field oriented control (FOC) technique. The DTC is characterized by the absence of PI regulators, co-ordinate transformations, current regulators and pulse width modulated signal generators. DTC also allows a good torque control in steady state and transient operating conditions. In this paper, development of DTC is discussed. The DTC based on space vector modulation (SVM) and switching table has been reviewed. With successively improving reliability and performance of digital technologies, digital control techniques have predominated over analog techniques. Digital control techniques are carried out with microcontrollers, digital signal processors due to their software flexibility and low cost which are being reviewed. Intelligent control techniques like neural networks (NN) and fuzzy logic based DTC are reviewed. Field Programmable Gate Arrays (FPGAs) are a useful platform for the implementation of high bandwidth control systems and the role of FPGA on DTC based induction motor drive is also presented.
Keywords:	Direct Torque Control, Field Programmable Gate Array, Fuzzy Logic, Induction Motor, Space Vector Modulation, Neural Network
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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Title:	IMPLEMENTING DATA WAREHOUSE AS A FOUNDATION FOR DECISION SUPPORT SYSTEM (PERSPECTIVE : TECHNICAL AND NONTECHNICAL FACTORS)
Author:	Tanty Oktavia
Abstract:	A company needs a system to conduct the process of analyzing data in order to support decision maker takes the best decision. Data warehousing system as one solution can accommodate that need. The system has been accepted as a key which enables company or organizations to improve their abilities in the data analysis, the decision support for managerial, and the automatic extraction of knowledge. With the developing of information included in the decision making process, the considered data become more complex, in both structure and semantics. The aim of this research is to identify the classification technical and non-technical factors on data warehouse implementation to help the management decide what to be prepared for the company if they want to develop data warehouse project. It also explores on how to integrate the data warehouse system into strategic business process. The study results show that the successful implementation of data warehouse influenced by how the company aware about technical and non-technical factor when implemented the project.
Keywords:	Data Analysis, Decision Support, Technical, Non-Technical
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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Title:	LIVER SEGMENTATION FROM ABDOMEN CT IMAGES WITH BAYESIAN MODEL
Author:	NIDAA ALDEEK, RAJA S. ALOMARI, M B AL-ZOUBI, HAZEM HIARY
Abstract:	Liver segmentation from CT volumes has been a challenging problem due to the high inter-organs intensity similarity, the intra-liver intensity variability, and the partial volume effect. In this paper, we perform an extensive review of the liver segmentation literature from CT and MRI. Furthermore, we propose a Bayesian model for a robust and reproducible semi-automatic technique for liver segmentation from CT volumes. We train our model and validate it using 44 clinical volumes for patients with various types of liver abnormality including tumor. Our segmentation results show a robust and clinically acceptable liver volume for all the 44 clinical cases we have with average area overlap accuracy over 87%. Our method is superior to all state of the art methods that has only been validated on less number of subjects as we show during the literature survey.
Keywords:	Liver Segmentation, Bayesian Model, Computed Tomography, Abdomen
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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Title:	WIRELESS VIDEO TRANSMISSION OVER UWB CHANNEL USING FUZZY BASED RATE CONTROL TECHNIQUE
Author:	S.GNANAVEL, S.RAMAKRISHNAN, N.MOHANKUMAR
Abstract:	Communication has always been on the rise especially when it comes to the transmission of video signals. The problems faced by video transmission include consumption of large bandwidth and video quality at the receiving side. This can be overcome by having a propervideo coding and proper control over the rate of transmission based on channel conditions. In our paper, we focus on these areas and present transmission control technique for wireless video transmission over UWB channel. In our technique, the major emphasis lies on the H.264 encoder and the use of fuzzy controller. The technique comprises of three modules, namely transmission module, control module and receiver module.Proposed technique is implemented using Matlab and the evaluation metrics used are BER and MSE. Comparative analysis is made by comparing our proposed technique to the SamiaShimuet al.[1] results. From the results, the net average BER came about 0.034 for the base compared to 0.032 for the proposed technique and net average MSE came about 117 for the base compared to 48.8 for the proposedtechnique. The obtained values show the effectiveness of the proposed technique by having lower MSE and BER values.
Keywords:	Transmission Control, Fuzzy Controller, PSNR, MSE, BER, UWB, H.264 Encoder And Decoder, QPSK.
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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Title:	FINANCIAL AND PERFORMANCE TRANSPARENCY ON THE LOCAL GOVERNMENT WEBSITES IN INDONESIA
Author:	DWI MARTANI , DEBBY FITRIASARI , ANNISA
Abstract:	E-government in Indonesia started since the issuance of Presidential Instruction Number 3 Year 2003. Local Governments are expected to provide relevant information related to their finance and performance to the public through the media that is easily accessible in order to meet the principles of accountability and transparency. This study has two objectives, that are 1) to analyze the development of the implementation of Presidential Instruction Number 3 Year 2003 with a focus on the transparency of financial and performance information and 2) to analyze the factors that affect the transparency level of financial and performance information in local government websites. To achieve these two objectives, we calculate the level of financial and performance information transparencies based on checklist and analyze the results descriptively then perform multiple regressions to test the influence of economic factors and characteristics of local government on the level of financial and performance information transparency at local government’s websites in Indonesia. Observation was conducted in mid-May 2013 until the end of July 2013. There are 429 of the total 491 government websites were successfully accessed and analyzed further. Based on the checklist made, the transparency level of financial and performance information just reached 15%. The most frequently disclosed information related to financial and performance information is in the form of news and Local Governments in Figures. Whereas the disclosure of main financial and performance informations that are in the form of regional budgets (APBD), financial statements, and performance reports are still below 10%. From the regression test of the 403 local governments, it confirms that size, level of dependency on the central government, and the local government society welfare have positive influence on the financial and performance information transparency level of Indonesia local government level.
Keywords:	E-Government, Financial Information, Local Government Website, Performance Report, Transparency.
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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Title:	DECISION SUPPORT SYSTEM FOR PREDICTING THE DEGREE OF A CANCER PATIENT’S EMPOWERMENT
Author:	Abdellah ABOUABDELLAH, Abdelghani CHERKAOUI
Abstract:	In this paper, we develop a decision support system (DSS) based on Knowledge Discovery from Databases (KDD). This system allows the prediction of the empowerment of a patient with cancer treated by chemotherapy. The first part of this article presents the process of empowerment of the patient. The second part explains the principle of decision support systems and the principle of the Knowledge Discovery from Databases (KDD), inspired by the data mining method. The third part describes the platform for predicting the degree of a cancer patient’s empowerment.
Keywords:	DSS, KDD, Data Mining, Prediction, Empowerment.
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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Title:	S-ARMA MODEL FOR NETWORK TRAFFIC PREDICTION IN WIRELESS SENSOR NETWORKS
Author:	S.PERIYANAYAGI , Dr.V.SUMATHY
Abstract:	Future network traffic in WSN can be predicted by time series models. The knowledge of traffic can be used for routing, load balancing and QoS provisioning. S-ARMA model has been proposed to predict the future traffic in WSN.The abnormality in traffic is predicted and it indicates the possibility for Dos attack and it initiates frequency hopping to avoid this. Increase in the frequency hopping time is identified by S-ARMA model, alerts the network to avoid the anomaly channel. Effectiveness of this model is been proved to be efficient in detecting the anomaly channel from the simulation results since the information about the attackers in the channel can be known using swarm intelligence (ants).
Keywords:	S-ARMA, Network Traffic, Frequency Hopping, Swarm Intelligence
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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Title:	A CUSTOMIZABLE SoPC ARCHITECTURE FOR GA BASED ON COMPLETE HARDWARE EVOLUTION
Author:	A. SWARNALATHA, A.P. SHANTHI
Abstract:	A Genetic Algorithm (GA) is a computer based search optimization technique that uses the Darwinian “Theory of Evolution” as a model for finding exact and approximate solutions. GAs belong to a large family of heuristic algorithms called Evolutionary algorithms (EA) which are being increasingly utilized for solving complex optimization and search problems. The large computation time consumed by a GA implemented in software makes it unsuitable for real time applications. This hurdle is overcome by shifting the implementation to hardware, which drastically speeds up the time factor, thus presenting a scope for real time applications. Major issues to be addressed in hardware implementation are silicon utilization, scalability, providing flexibility and reduced computational delays. This work presents a customizable Complete Hardware Evolution (CHE) based GA architecture. Along with the generic modules for the genetic operators of the GA, modules named Flush and Replace Memory (FRM), Memory Module (MM), and a sorting module form the main components of this architecture. These modules can facilitate System on Programmable Chip (SoPC) implementation for different applications of GA. The coding is done using Verilog Hardware Description Language (HDL) and simulated using Xilinx ISE 9.1i simulator. Each module is separately simulated and synthesized for a Commercial Off The Shelf (COTS) Field Programmable Gate Array (FPGA). The resource utilization and the critical path delay of the modules are evaluated and presented for Xilinx Virtex – 4 FPGA.
Keywords:	Genetic Algorithm, Complete Hardware Evolution, FPGA, Sopc, Computational Delay, Resource Utilization..
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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Title:	REVERSIBLE IMAGE WATERMARKING USING BIORTHOGONAL WAVELET TRANSFORM AND IMPORTANCE MEASURE MODEL
Author:	T.SUJATHA, K.GEETHA
Abstract:	Image Watermarking is a technique by which a person can attach hidden data into the image by use of embedding and extraction process. In reversible watermarking, after the extraction of the watermark, the cover image can be restored completely. Reversible image watermarking algorithm is proposed in this paper. Initially, the image is resized and applied bi-orthogonal discrete wavelet transform to decompose into bands. The best band suitable for embedding is found with the help of entropy. The best locations in the selected band are found using the importance measure model. Subsequently, the proposed embedding process is carried out to embed the image with a watermark image which is binary. The proposed extraction procedure is carried out after finding out best band and location. The evaluation metric used to evaluate the proposed watermarking technique is carried out with the use of PSNR and NC. The proposed technique obtained good results having an average PSNR value of 31.3 and NC value of 1. The robustness of the proposed watermarking technique is evaluated with the aid of different filtering techniques and good results were achieved in all cases. Comparison is also made with existing technique and from the results; we can see that our technique outperforms other technique by having better PSNR and NC values.
Keywords:	Reversible Watermarking, Biorthogonal DWT, Entropy, Robustness, Importance Measure, PSNR, NC
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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Title:	HANDWRITTEN DEVNAGARI DIGIT RECOGNITION: BENCHMARKING ON NEW DATASET
Author:	RAJIV KUMAR, KIRAN KUMAR RAVULAKOLLU
Abstract:	The paper presents handwritten Devnagari digit recognition results for benchmark studies. To obtain these results, we conducted several experiments on CPAR-2012 dataset. In these experiments, we used features ranging from the simple most features (direct pixel values), slightly computationally expensive, profile based features, to more complex gradient features extracted using Kirsch and wavelet transforms. Using these features we have measured recognition accuracies of several classification schemes. Among them the combined gradient and direct pixel feature using KNN classifier yielded the highest recognition accuracy of 95.2 %. The recognition result was improved to 97.87% by using multi stage classifier ensemble scheme. The paper also reports on the development of CPAR-2012 dataset that is being developed for Devnagari optical document recognition research. Presently, it contains 35,000 (15,000 constrained, 5,000 semi-constrained and 15,000 unconstrained) handwritten numerals, 82,609 handwritten isolated characters, 2,000 unconstrained and 2,000 constrained pangram text, and 4,000 digitized data collection forms.
Keywords:	CPAR-2012 dataset, Devnagari digit recognition, neural network classifier, majority voting, shape similar digits
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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Title:	A PERFORMANCE STUDY OF HARDWARE IMPACT ON FULL VIRTUALIZATION FOR SERVER CONSOLIDATION IN CLOUD ENVIRONMENT
Author:	S.SURESH, M.KANNAN
Abstract:	Underutilization of hardware resources has always been a problem in single workload driven traditional OS environment. To improve resource utilization, virtualization of multiple VMs and workloads onto the same host with the aid of Hypervisor has been the recent trend. Its use cases such as server consolidation, live migration, performance isolation and on-demand server provisioning make it as a heart part of enterprise application cloud. Cloud is an on-demand, service provisioning technology, where performance plays a vital role for user acceptance. There are numerous virtualization technologies are available from full virtualization to paravirtualization, each has its strength and weakness. As performance study is an ongoing pursuit, hardware and software development getting matured day by day, it is desirable to do this sort of performance study in regular interval that often sheds new light on aspects of a work not fully explored in the previous publication. Hence, this paper focus performance behaviours of various full virtualization models such as hosted (VirtualBox) and bare metal (KVM) virtualization using variety of benchmarks from micro, macro and application level in the cloud environment. We compare both virtualization solutions with a base system in terms of application performance, resource consumption, low-level system metrics like context switch, process creation, interprocess communication latency and virtualization-specific metrics like virtualization layer consumption. Experimental results yield that VirtualBox outperforms KVM in CPU and thread level parallelism and KVM outperforms in all other cases. Both are very reluctantly accepted for disk usages comparing with native system.
Keywords:	Full Virtualization, VirtualBox, KVM, Server Consolidation, Performance
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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Title:	AN IMPROVED OF SPAM E-MAIL CLASSIFICATION MECHANISM USING K-MEANS CLUSTERING
Author:	NADIR OMER FADL ELSSIED, OTHMAN IBRAHIM, WAHEEB ABU-ULBEH
Abstract:	Spam e-mails are considered as a serious violation of privacy. In addition, it has become costly and unwanted communication. Although, Support Vector Machine (SVM) has been widely used in e-mail spam detection, yet the problem of dealing with huge data is time and memory consuming and low accuracy. This study speeds up the computational time of SVM classifiers by reducing the number of support vectors. This is done by the K-means SVM (KSVM) algorithm proposed in this work. Furthermore, this paper proposes a mechanism for e-mail spam detection based on hybrid of SVM and K-means clustering and requires one more input parameter to be determined: the number of clusters. The experiment of the proposed mechanism was carried out using spambase standard dataset to evaluate the feasibility of the proposed method. The result of this hybrid method led to improved SVM classifier by reducing support vectors, increasing the accuracy and decreasing the time of e-mail spam detection. Experimental results on spambase datasets showed that the improved SVM (KSVM) significantly outperforms SVM and many other recent spam detection methods in terms of classification accuracy (effectiveness) and time consuming (efficiency).
Keywords:	K-means clustering, Machine Learning, Spam detection, SVM.
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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Title:	A NOVEL LOW COMPLEXITY DIAGONAL REDUCTION ALGORITHM OF LATTICE REDUCTION FOR SIGNAL DETECTION IN MIMO RECEIVER
Author:	Prof. G. RANJITHAM, Dr. K. R. SHANKAR KUMAR
Abstract:	This Paper analyses the performance of Multiple Input Multiple Output (MIMO) wireless communication system by combining it with an efficient algorithm Diagonal Reduction (DR). DR is a powerful tool to achieve more efficiently a high performance with less complexity when applied to MIMO detection. This paper proposes a DR algorithm in order to reduce its complexity named Greedy Diagonal Reduction (GDR) algorithm which gives reduced complexity with efficient performance at the receiver using the MATLAB communication tool box version 7.1 as a simulation tool. From the simulation results of various reduction algorithms it is observed that,DR can reduce the number of iterations using size reduction operations. Proposed DR algorithm gives identical Bit Error Rate (BER) performance with LLL algorithms when applied to Successive Interference cancellation (SIC) decoding. Greedy DR reduces the computational complexity in Multiple Input Multiple Output systems by improving the efficiency in terms of size reduction operations.
Keywords:	Mimo, Diagonal Reduction (Dr), Low Complexity, Greedy Diagonal Reduction (Gdr), Bit Error Rate (Ber)
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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Title:	CHALLENGES IN MINIMISING ENERGY CONSUMPTION FOR WIRELESS SENSOR NETWORKS
Author:	SUDHEER PEMBUSANI, ABHISHEK GUDIPALLI, SARAVANAN MAHADEVAN
Abstract:	Wireless sensor networks is one of the active research area now a days due to its vast applications in different fields such as defence , civilian and medical fields. One of the basic challenges in the design of Wireless Sensor Network (WSN) is maximizing their lifetime because of the sensors placement in remote places which is having batteries as power sources. To extend the WSN lifetime, energy management is the most important and critical aspect, for that we need different techniques in different aspects of WSN. This paper presents some methods which will be useful to minimize energy consumption in sensor networks and to increase lifetime of the WSN. Sensor nodes are using batteries as their power sources, effective and efficient utilization of these power sources is essential in order to use sensor networks for longer period hence it is required to reduce data transfer rate inside sensor networks, reduce amount of data that required to send to base station. For this, data aggregation methods are useful for aggregating data in an effective energy efficient manner so that network lifetime will enhance. In most applications once WSN deployed, it should continue to work for a long period of time, without the maintenance of the nodes and the replacement of their energy sources. Each sensor node in the network consumes power in different stages like sensing data, processing data and transmitting/receiving. In all stages minimizing energy consumption is required. Therefore routing protocols designed which should minimize power consumption in every stage of WSN because of its effective function.
Keywords:	Wireless Sensor Networks, Data Aggregation, Routing Protocols, ESPDA Protocol, Energy Consumption
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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Title:	AUTOMATIC MOTIF DETECTION FOR ISLAMIC GEOMETRICAL PATTERNS
Author:	ABDELBAR NASRI, RACHID BENSLIMANE
Abstract:	In this paper, we present a new method to detect the basic unit cell of a periodic Islamic Geometrical Pattern (IGP). This method is based on the autocorrelation function (ACF), a function known to be appropriate to analyze and extract a repetitive motif from a regular texture. The motif can be successfully extracted when the peaks detected in the autocorrelation function of an image are pertinent. To optimize the peaks detection, we propose a new method based on the stability of the motif surface which is defined by two short displacement vectors. Compared to classical extraction methods of periodicity, the proposed method hereby is tolerant to geometric distortion, noise and changes in intensity. Tests on 166 images with different visual quality demonstrate the capability of the proposed method to extract the periodic motif automatically without the need of human intervention.
Keywords:	Autocorrelation, Wallpaper Groups, Islamic Art, Pattern Extraction, Displacement Vector.
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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Title:	A FULLY ASSOCIATIVE CACHE ALGORITHM WITH IMPROVED PERFORMANCE
Author:	S.SUBHA
Abstract:	Fully associative caches enable all blocks to map address. This paper proposes an algorithm to enable one fully associative block. The address a is right shifted by certain prefixed number of bits. The result is XOR’ed with n-1, n being the number of fully associative cache blocks. The bit selection of the result to map to one of the n blocks in fully associative cache is performed. The chosen block is enabled to access a line or place cache line. The proposed algorithm is simulated with SPEC2K benchmarks. The average memory access time is improved by 16% with energy savings of 9%. The proposed model shows 30% degradation in average memory access time with no change in energy consumption over direct mapped cache of same size.
Keywords:	Average Memory Access Time, Cache Algorithm, Cache Performance, Energy Saving, Fully Associative Cache
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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Title:	ANALYSIS OF TRAFFIC FLOW IN CONGESTED CITIES USING CELLULAR AUTOMATA
Author:	S.RAJESWARAN AND S.RAJASEKARAN
Abstract:	The present study is to model heterogeneous traffic at a congested place in Chennai using Cellular Automata (CA) and traffic simulator VISSIM. Vehicle type, its volume, density, average velocity, dimensions of study area and signal cycle length are used as input parameters for computer simulator VISSIM to find the dynamics of vehicular traffic. The output obtained substantiates that there will be decrease in delay time and increase in maximum achievable velocity when there is reduction in 2W (Two Wheeler) population. In fact, if no 2W is allowed then the delay time will be reduced to 70.70% and the maximum achievable velocity will be increased to 34.33%. Using CA rules, simulation was carried out on the traffic flows in roads of length 100 (small system) and 1000(large system). The results obtained show that small systems behave differently from long ones and the traffic reaches a maximum of 420 when the density is 0.1 for small systems and 323 when the density is 0.09 for large system.
Keywords:	Cellular Automata, Heterogeneous Traffic, Vehicular Traffic, Single-Lane Traffic Flow, Simulation.
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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Title:	IDENTIFICATION OF INSTABILITY AND ITS ENHANCEMENT THROUGH THE OPTIMAL PLACEMENT OF FACTS USING L-INDEX METHOD
Author:	K.VENKATA RAMANA REDDY, Dr.M.PADMA LALITHA
Abstract:	In this paper an IEEE standard test system is considered and it is tested using Newton- Raphson method with the help of MATLAB. The voltage magnitudes of each bus are examined and the corresponding weak bus is incorporated with FACTS such as SVC and TCSC. The optimal placement of FACTS can be identified using L-Index method. The value of L-index which approach unity implies that it reaches to instability. From this instability point the system stability is improved during steady state and Fault conditions. The disturbance is created in the system by changing the Load Reactive Power at a particular Bus.
Keywords:	Steady State Condition, Fault condition, SVC, TCSC, MATLAB.
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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Title:	BSFD: BACKGROUND SUBTRACTION FRAME DIFFERENCE ALGORITHM FOR MOVING OBJECT DETECTION AND EXTRACTION
Author:	D STALIN ALEX, Dr. AMITABH WAHI
Abstract:	Advantages and drawbacks of two common algorithms often employed in the moving target detection, background subtraction technique and frame distinction methodology are analyzed and compared during this paper. Then supported the background subtraction methodology, a BFSD target detection rule is projected. The background image used to process the next frame image is generated through superposition of the current frame image and therefore the current background image with certain chance. This algorithm makes the objects that keep long-standing, however not be detected as a part of the background. The experimental results show that this algorithm can detect moving objects a lot of effectively and precisely.
Keywords:	Background Subtraction –Frame Difference –Moving Object Detection –Dynamic Background
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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Title:	SIMPLIFIED SCHEME FOR PERFORMANCE AUGMENTATION OF WEB DATA EXTRACTION
Author:	G.NAVEENSUNDAR, D.NARMADHA, DR.A.P.HARAN
Abstract:	Web mining is the application of data mining techniques to automatically discover and extract information from Web data. Furthermore, it uses the data mining techniques to make the web more profitable and to enhance the effectiveness of our interaction with the web. Users always expect maximum accurate results from search engines. But, unfortunately most of the web pages contain more unnecessary information than actual contents. The unnecessary information present in web pages is termed as templates. Template leads to poor performance of search engines due to the retrieval of non-contents for users. Therefore the performance of search engines can be improved by making web pages free of templates. Our method focuses on detecting and extracting templates from web pages that are heterogeneous in nature by means of an algorithm. Locality sensitive hashing algorithm finds the similarity between the input web documents and provides good performance compared to Minimum Description Length(MDL) principle and hash cluster process in terms of execution time.
Keywords:	Cluster, Non-Content Path, Template Detection, Locality Sensitive Hash, Minimum Description Length
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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Title:	SKYLINE IN CLOUD COMPUTING
Author:	ABDELLAH IDRISSI, MANAR ABOUREZQ
Abstract:	The cloud computing technology is booming. The utility of this technology is no longer to show. In this paper, we investigate the problem of search and selection systems allowing users to search through Cloud services and find the ones that best meet their needs. In this context, we propose a new algorithm to address this problem. This algorithm is based on the principle of the Skyline. One of the main contributions of our work is the construction of a Web Agent using the Skyline method to determine which Cloud services best meet users’ requirements. In this work, we expose our algorithm and present some experimental results showing that our approach is very promising.
Keywords:	Cloud Computing, Cloud Services, Skyline, Block-Nested Loops Algorithm.
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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Title:	TOWARDS POPULARITY AWARE HYBRID CACHING TO IMPROVE SEARCH IN SOCIAL RELATIONSHIP BASED P2P NETWORKS
Author:	G. RAMACHANDRAN, DR. K. SELVAKUMAR
Abstract:	The widespread use of recent Peer-to-peer (P2P) file sharing has been mainly influenced by the scalability of their architecture and high versatile search mechanisms. However, most of the P2P networks construct loosely coupled overlay on the top of the internet based on the physical network constraints without taking user preferences or relationship into account. It leads to high inefficiency in their search algorithms, which mainly relies on the simple flooding or random walk strategies. In this paper, we present the architecture of adaptable fully decentralized social based P2P overlay as well as efficient cognitive community P2P search technique to improve the searching efficiency. This paper proposes a Dynamic Overlay Adaptation (DOA) algorithm, which creates social communities by connecting group of peers having similar interest within the shortest path based on the social relationship between them. The basic premise of the creation of social communities is that generated queries are most probably satisfied within its own community. Therefore, it significantly improves the searching efficiency with a higher success rate and less response time. In addition to, this paper proposes a Popularity aware Hybrid Caching (PaHC) which caches the file based on its size to improve cache performance. To accomplish high data availability, popularity aware strong data consistency is proposed that eliminates the duplicate content replication among the peers. Experimental evaluation reveals the effectiveness and efficiency of the proposed approach in terms of success rate, network traffic, response time and cache hit ratio.
Keywords:	Unstructured P2P Networks, Peer Search, Social based P2P Overlay, Popularity Aware Hybrid Caching
Source:	Journal of Theoretical and Applied Information Technology 28 February 2014 -- Vol. 60. No. 3 -- 2014
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