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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
October 2014 | Vol. 68 No.1

Title:	CLUSTER HEAD BASED GROUP KEY MANAGEMENT FOR MALICIOUS WIRELESS NETWORKS USING TRUST METRICS
Author:	V.BHUVANESWARI, Dr. M.CHANDRASEKARAN
Abstract:	The process of transferring messages from a member to another member securely within a network is known as secure group communication. Key management is an important primitive to ensure this, as it provides a secure method for cryptographic keys creation, distribution and management. Group key establishment/management methods are key management’s two sides. Group members use group key (GK) for encryption/decryption of messages in group communication. Communication needs quality and security for better performance and for acceptance of users and client companies. Diffie-Hellman (DH) was the first published public key algorithm that is used for secure key exchange mechanism. The purpose of algorithm is used to enable users to security exchange a key that can be used for subsequent encryption. Earlier schemes used only one group controller and were thus affected by single point failure (1-affects-n problem). To prevent this, a new technique where a control group generates the group key is introduced based on the nodes capability within two hops. In this scheme, direct trust and indirect trust is computed to identify Cluster Heads (CH) and the concept of auxiliary cluster head is introduced for effective key management.
Keywords:	Mobile ad hoc networks (MANETs), Dynamic Source Routing (DSR), Malicious Nodes, Clustering, Key Management
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	A CROSS LAYER SCHEDULING SCHEME FOR WIMAX
Author:	CHANDRASEKARAN V , NAGARAJAN N
Abstract:	In this paper, we propose a novel scheduling scheme that will provide quality-of-service (QoS) support in the downlink (DL) of a WiMAX system. The proposed Subchannel mapping Scheduling Algorithm completely exploits the physical layer properties of the Orthogonal Frequency Division Multiple Access (OFDMA) in order to improve the throughput of the WiMAX network at the same time improving the QoS of the various services guaranteed by the network. The proposed scheduling scheme has three parts. The first stage of the scheduling shame is the optimized queuing model that will carry out effective mapping between the admitted service flows and the packet arrival statistics. The performance of the algorithm is improved further by the enhancement scheme which would further improve the performance of the proposed scheme through fuzzy logic design. At the last stage we have the slot allocation process which completes the process. The cross -layer approach followed in the scheduling scheme provides effective slot allocation under various channel conditions. It also offers more options for the network to cater delay- sensitive multimedia traffic by reducing the delay in the network. Simulation results have demonstrated that the proposed scheduling scheme improves the throughput and also reduces the delay of the WiMAX network.
Keywords:	Mobile Wimax, Orthogonal Frequency Division Multiple Access (OFDMA), Scheduling, Quality-Of-Service.
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	EFFECTIVE FEATURE EXTRACTION FOR DOCUMENT CLUSTERING TO ENHANCE SEARCH ENGINE USING XML
Author:	P.AJITHA, DR. G. GUNASEKARAN
Abstract:	Clustering is the task of grouping a set of objects in such a way that objects in the same group are more similar to each other than to those in other groups. Clustering is done using lingo algorithm by extracting the data contents in the document. The data is stored in XML, which manages large volume of data. Lingo combines several existing methods to put special emphasis on meaningful cluster descriptions, apart from identifying document similarities. The steps involved in this process are designing the term-document matrix and then extracting the frequent phrase using suffix arrays. Readable and unambiguous descriptions of the thematic groups are an important factor of the overall quality of clustering. The Lingo algorithm consist of five phases, they are Pre-processing, Extraction of Frequent phrase, Induction of Cluster label, Discovery of Cluster content, Final cluster formation.
Keywords:	Lingo, XML, SVD, LSI, Phrase matrix.
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	VLSI DESIGN OF 12-BIT ADC WITH 1GSPS IN 180NM CMOS INTEGRATING WITH SAR AND TWO-STEP FLASH ADC
Author:	K.LOKESH KRISHNA, T.RAMASHRI
Abstract:	In this paper, a Novel Hybrid ADC consisting of two-step quantizer which has Flash ADC and SAR ADC along with Resistor String DAC is designed and implemented. This Hybrid ADC improves the speed by employing Flash ADC and resolution and power reduction can be achieved by utilizing SAR ADC. The Hybrid architecture carrying 12 bits as resolution, input frequency as 100MHz and sampling frequency is 1GHz. CMOS level schematic diagram of sub-blocks has been designed and implemented using Cadence Virtuoso 180nm technology at an operating voltage of 1.8 V. Layout design is captured using Virtuoso and then it is optimized for area. Based on the obtained result, INL and DNL has been identified as +0.034V to – 0.001V and + 0.06V to -0.05V respectively. The performance results show that the architecture achieves low power, high speed and less area.
Keywords:	Sample and Hold Circuit, Comparator, Transmission Gate, Hybrid ADC, Two-step Quantizer, SAR and Flash ADC.
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	MEDICAL DIAGNOSIS SYSTEM FOR THE DIABETES MELLITUS BY USING BACK PROPAGATION-APRIORI ALGORITHMS
Author:	K. SRIDAR M.E., Dr. D. SHANTHI
Abstract:	Diabetes is a chronic disease and a major public health challenge worldwide. According to the International Diabetes Federation, there are currently 246 million diabetic people worldwide, and this number is expected to rise to 430 million by 2030. Furthermore, 3.8 million deaths are attributable to diabetes complications each year. It has been shown that 80% of type 2 diabetes complications can be prevented or delayed by early identification of people at risk. Early detection of diabetes would be of great value given the fact that at least 50% and 80% in some countries, of all people with diabetes are unaware of their condition and will remain unaware until complications appear. Several data mining and machine learning methods have been used for the diagnosis, prognosis, and management of diabetes. In my research work, clinical data are collected based on the attributes downloaded from Pima Indians Diabetes Database. Real time input have been given to the system from the Glucometer (ie Glucose level for the patient before breakfast and Glucose level for the patient two hours after breakfast) then some on the input attributes given manually to the system. All the inputs have been given to the BP Algorithm (ANN) and Apriori Algorithm (ARM) for diagnosing diabetes. The Diagnosis system can be implemented in Java, Dotnet. The output of the system shows how much percentage of the patient suffers from the diabetes (low, medium or high risks)? In proposed work it is decided to implement the system in Online. The main objective is that the patients can know about their risk in diabetes without the help of doctors. The patient can just login into the website and they can give their attributes (ie) data collected from labs as input and they can diagnosis their own result without doctors.
Keywords:	Artificial Neural Network (ANN), Back Propagation Algorithm, Association Rule Mining (ARM), Apriori Algorithm, Disease Diagnosis.
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	SOFTWARE RELEASE PLANNING- A MODEL INCORPORATING ENVIRONMENTAL PARAMETERS
Author:	SANDHIA VALSALA, DR. ANIL R NAIR
Abstract:	A software release planning can be seen from two dimensions “what to release” and “when to release”. The most crucial decision is whether or not to select a feature for implementation in the next software release. A number of software release planning models are available which considers a wide variety of factors in deciding the implementation of a feature in a release.This paper analyzes 31 release planning models and the selection factors used by these models. Most of these models use only in-project parameters in deciding on the features to be included in a release. A new release planning model incorporating a group of “environmental factors” ,which plays a crucial role in deciding the priority of features to be included in each release is then proposed .The paper emphasize the need to include environmental parameters which are parameters not directly linked to project, but influences the project from outside in planning a release.
Keywords:	Software Release, Release Planning, Environmental Parameters, In-Project Parameters, Feature Priority
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	AN EFFICIENT MULTI-PATH ROUTING ALGORITHM BASED ON HYBRID ARTIFICIAL BEE COLONY ALGORITHM FOR WIRELESS MESH NETWORKS
Author:	K.KUMARAVEL and Dr.A.MARIMUTHU
Abstract:	The number of services obtainable by wireless network has been improved for recent years. It motivates to the improvement of new wireless technologies. New technologies are required to satisfy the requirements or necessitated of the users regarding wireless services. The newly developed wireless technology with mesh topology is known as wireless mesh networks (WMN). Routing is one of the most significant problems handled by every WMN technologies during data transmission .In Wireless Mesh Networks (WMN), the Multi-path routing is one of the mainly significant problems occurred throughout data transmission process based on their ability of the link for multiple paths. To overcome the problem of the multipath routing earlier work presents a Dijkstra’s Algorithm (DA) for route setup and ant colony based optimization (ACO) algorithm for route examination. But the algorithm used for route examination have lower meeting time in ACO and worst-case running time in DA for route setup .In order to solve the above mentioned issues in this work presents an Filter-Kruskal algorithm for first route setup from source to destination path . The multiple routes path are examined and maintained based on the hybrid artificial bee colony (HABC) algorithm. The routes explored for data transmission are chosen based on their expected honey bee values. If any failure occurs in this HBAC route examination step it is forwarded to route maintenance system. Proposed FKAWMNet efficiently solves multipath routing problem in wireless mesh networks (WMN). The simulation results of the proposed FKAWMNet show that proposed work achieves a higher packet delivery ratio, lesser end to end delay and lesser routing overhead than the existing routing protocols such as DAWMNet and AntHocNet. So the proposed FKAWMNet achieves highly reliable communication, assurance of load balancing and easily applicable to topological changes without node failure.
Keywords:	Multi-path routing, Industrial wireless mesh networks, Filter-Kruskal algorithm (FKA), Hybrid Artificial Bee Colony (HABC)
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	AUTOMATIC SEGMENTATION OF LUNG CT IMAGES BY CC BASED REGION GROWING
Author:	A.PRABIN , DR. J.VEERAPPAN
Abstract:	Computer Aided Diagnosis (CAD) of CT lung image has been a revolutionary step in the early diagnosis of diseases present in the lung. Developing an efficient and robust algorithm for Lung computer tomography (CT) image segmentation has been a demanding area of growing research of interest during the last two decades. The initial step in computer aided diagnosis of lung CT image is generally to segment the Region of Interest (ROI) present in it and then to analyze each area separately inorder to find the presence of pathologies present in it. This research reports on segmentation of the ROI by segmenting the CT lung images using supervised contextual clustering along with the combination of region growing algorithm. Region growing has been combined with CC in this work since it reduces the number of steps in segmentation for the process of identifying a tissue in the CT lung image. The performance of this proposed segmentation is proved to be better when it is compared with other existing conventional segmentation algorithms like ‘Sobel’, ‘Prewitt’, ‘Robertz’, ‘Log’, ‘Zerocross’. From the experimental results, it has been observed that the proposed segmentation approach provides better segmentation accuracy.
Keywords:	Contextual Clustering, Segmentation Algorithm, Computer Tomography, Pulmonary Lung Image.
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	CCTF-RQ FRAMEWORK: COMMAND AND CONTROL TRAFFIC FLOW WITH RESOURCE QUEUING IN CLOUD INFRASTRUCTURE
Author:	DURAIRAJ, CHANDRASEKAR
Abstract:	Cloud infrastructure interact with different components ensuring traffic free environment for both the simple and complex traffic and provide services to different type of vendors. Most previous studies conducted using prediction based resource management aim at providing resources to the user using statistical model that measure the traffic flow required for the future. However in practice it is not effective to provide appropriate resources using predictive analysis as it does not take into account the complex traffic pattern. In addition, prediction framework in cloud zone is much less compact for the business persons as it does not follow the dynamic flow generation part. Methods for controlling the traffic in cloud using virtualization based cloud data centers called as VMPlanner used the stepwise optimization approach. The approach, VMPlanner failed to incorporate certain level of links redundancy, where the communication latency was achieved during the data flow, but resulted in network failures. In this paper, a framework called Command and Control Traffic Flow with Resource Queuing (CCTF-RQ) is presented to facilitate business persons eventually with dynamic data flow in cloud zone. The framework, CCTF-RQ works well by obtaining the prior knowledge about the server and the client system on the cloud for easy analyze of flow correlations. The proposed framework, CCTF-RQ clusters the similar configuration of server and client systems on the cloud and significantly solves the complex traffic occurring on user communication patterns. Further, in cloud environment certain level of link redundancy may deteriorate the network. We address the problem by clustering exactly the similar command control traffic patterns in cloud zone followed by which the session gets established to access the network without any communication latency. An efficient algorithm called Banker’s Safety algorithm is developed to overcome the network failures during data flow. CCTF-RQ Framework on cloud zone is implemented with CloudSim in JAVA and experiment is conducted on the parametric factors such as Server response time, CPU utilization for correlation analysis, Mean Absolute Percentage Error, Traffic rate.
Keywords:	Cloud Infrastructure, Command and Control, Resource queuing, Banker’s Safety algorithm, Server Configuration, Network Resources.
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	SIMPLIFIED FIVE LEVEL INVERTER AS SERIES ACTIVE POWER FILTER FOR MINIMIZING THD IN A NON-LINEAR SYSTEM
Author:	C.RAMAKRISHNAN , S.VIJAYAN , K.ARTHI
Abstract:	A series hybrid Active Power Filter has been focused more in the area of power quality. The hybrid filter is implemented with three phase simplified asymmetrical five level inverter as active filter and LC filter connected in parallel with power lines acting as passive filter. The harmonics produced by the non linear loads are filtered out by the passive filters and the filtering property of it is improved by active filter. The multi level voltages are obtained from a simplified inverter, which operates at lower switching frequency intern reduces the switching losses compared to conventional cascaded five level inverter. The filter is developed to inject voltage in series and also for harmonic isolation. Current harmonics are eliminated by controlling the APF with the P-Q theory based control strategy developed for this simplified inverter. The system produces voltage of same amplitude but opposite to load harmonic voltage to nullify the harmonics injected into the system. For current harmonics, the system produces voltage proportional to the current and offers high impedance path to the current harmonics. The validity of the control scheme is verified by simulation study with help of MATLAB/SIMULINK and comparative analysis is carried out with help of simulated values to obtain the harmonic values within standard values.
Keywords:	Active Filters, Harmonic Distortion, PQ theory, Multilevel Converters, Power Quality
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	FUZZY C-MEANS AND ENTROPY BASED GENE SELECTION BY PRINCIPAL COMPONENT ANALYSIS IN CANCER CLASSIFICATION
Author:	SOMAYEH ABBASI, HAMID MAHMOODIAN
Abstract:	Microarray analysis is used in human cancer diagnosis and tumor classification. However, microarray data often have high dimensionality and small sample size. Gene selection is a significant preprocessing of the discriminant analysis of microarray data to select the most informative genes from thousands of genes. In this paper, a gene selection method proposed for cancer classification in two stages. First, the initial reduction of data by Fuzzy C-Means clustering (FCM) and filter method (T-test) is performed for dimensionality reduction. The next stage is to perform gene selection based on an entropy measure of eigenvalues from Principal Component Analysis on a leave-one-out basis, which is called PCA-entropy. Colon cancer, leukemia and lung datasets have been classified based on proposed gene selection algorithm by SVM and KNN classifiers. In most cases, the results show a good performance compared to the other recent studies.
Keywords:	Classification, Clustering, Entropy, Gene selection, Principal Component Analysis.
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	IMPROVED GENERAL SELF-ORGANIZED TREE-BASED ROUTING PROTOCOL FOR WIRELESS SENSOR NETWORK
Author:	M.SENGALIAPPAN , Dr.A.MARIMUTHU
Abstract:	Wireless Sensor Networks (WSNs) is a promising structure used to assist the stipulation of many military and industrial services. They have many different constraints, such as computational power, storage capacity, energy supply and etc are the important issue is their energy constraint. Many issues hold back the effectiveness of WSNs to support different applications, such as the resource confines of sensor devices and the finite battery power. To overcome this problem and to improve the performance need not only to minimize total energy consumption but also to balance WSN load. In this research, a novel tree based routing protocol is proposed which builds a routing tree using a process where, for each round, BS assigns a root node and broadcasts this selection to all sensor nodes. Subsequently, each node selects its parent by considering only itself and its neighbors’ information, thus making a dynamic protocol. The simulation results shows that the proposed approach performs better that other existing approaches.
Keywords:	Keywords: Wireless Sensor Network, Routing, Network Lifetime, Clustering, Tree Based Routing
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	ADAPTIVE MODULATION IN RECONFIGURABLE PLATFORM
Author:	S. SELVAKUMAR, Dr.S.RAVI, M.VINOTH, R.KAMALAKNNAN, V.JAYAPRADHA
Abstract:	Autonomous modulation and detection technique in modern communication systems is done using proper signal detection schemes and prominent receiver structure. The modulation schemes used in this paper are ASK, FSK, BPSK and QAM. Modulation techniques are created in Simulink which is converted into Xilinx core and this further undergoes changes using system generator module. This results in the generation of Verilog files and is deployed in FPGA. Using a microcontroller the FPGA was programmed with respective bit files and the modulation that had the best channel support is selected. The methodology used to identify the best modulation for a particular link in reconfiguration is called adaptive modulation process. The interface is done between the reconfiguring controller (STM32) and the reconfigured FPGA (XCS250-pq144) using JTAG port. The programmed files were created (XSVF format) and placed in SD-card of microcontroller. The condition for changing from one modulation to another is based on the link support and signal position. The HyperTerminal displays the output corresponding to different modulation selections autonomously. Signal to Noise Ratio (SNR), Available Bandwidth and Bit Error Rate (BER) are the factors responsible for the selection of modulation scheme. Hence, better quality of service, system complexity, power efficiency, bandwidth efficiency and cost effectiveness are the advantages of Adaptive Modulation technique.
Keywords:	BER, FPGA, Microcontroller, Modulations, SNR, and Xilinx.
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	PROPOSE AN INTEGRATION BETWEEN UML STATIC AND DYNAMIC MODELS USING ENTITY-ATTRIBUTE-VALUE UNDER THE MDA CONTEXT
Author:	AHMED MOHAMMED ELSAWI, SHAMSUL SAHIBUDDIN, ABDELHAMID ABDELHADI
Abstract:	The Model Driven Architecture (MDA) is adopting models to improve the software productivity, reusability, maintainability and quality by focusing on models and metamodels in place of conventional code. The MDA separates the technical details from the business logic in two different models. The Platform Independent Model (PIM) is concerned with the business logic while the Platform Specific Model (PSM) is more focusing on the targeted platform. Normally, PIM and PSM models stand in different level of abstraction. Moving from one level of abstraction to another is achieved by Model transformation. Both PIM and PSM are modeled using UML diagrams. The UML supports a variety of diagrams that can be categorized into static and dynamic diagrams. The static diagrams are normally targeted the system’s structures and it is commonly used to define the PIM and PSM models. On the other hand, the dynamic diagrams are targeting the system’s behavior and its dynamic elements. To successfully develop a complete software using the MDA methodology, all structural and behavioral elements should be captured. Hence, different versions of the PIM and PSM models should be employed to cover the structural and behavioral elements of the system. Consequently, beside time, cost, and complexity issues a considerable number of model transformation iterations are required for each version separately. Into face of these issues, we propose this work to address the integration between UML behavioral and structural diagrams using the Entity-Attribute-Value (EAV) model. Also, we presented an example to show how this proposed concept not only allowing for an integration between UML static and behavioral models, but also shows the flexibility of integration models in different level of abstraction.
Keywords:	UML Models Integration, behavioral models, Static Models, MDA, EAV
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	CLASSIFICATION OF ARM MOVEMENT BASED ON UPPER LIMB MUSCLE SIGNAL FOR REHABILITATION DEVICE
Author:	M.H.JALI, I.M.IBRAHIM, Z.H.BOHARI, M.F.SULAIMA, M.N.M.NASIR
Abstract:	Rehabilitation device is used as an exoskeleton for people who experience limb failure. Arm rehabilitation device may ease the rehabilitation programme for those who suffer arm dysfunctional. The device used to facilitate the tasks of the program should improve the electrical activity in the motor unit by minimising the mental effort of the user. Electromyography (EMG) is the techniques to analyse the presence of electrical activity in musculoskeletal systems. The electrical activity in muscles of disable person are failed to contract the muscle for movements. To prevent the muscles from paralysis becomes spasticity or flaccid the force of movements has to minimise the mental efforts. To minimise the used of cerebral strength, analysis on EMG signals from normal people are conducted before it can be implement in the device. The signals are collect according to procedure of surface electromyography for non-invasive assessment of muscles (SENIAM). The implementation of EMG signals is to set the movements’ pattern of the arm rehabilitation device. The filtered signal further the process by extracting the features as follows; Standard Deviation(STD), Mean Absolute Value(MAV), Root Mean Square(RMS), Zero Crossing(ZCS) and Variance(VAR). The extraction of EMG data is to have the reduced vector in the signal features for minimising the signals error than can be implement in classifier. The classification of features is by SOM-Toolbox using MATLAB. The features extraction of EMG signals is classified into several degree of arm movement visualize in U- Matrix form.
Keywords:	Arm Rehabilitation Device, Electromyography, Self-Organizing Map, Time Domain Features Extraction, Exoskeleton
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	UPGRADING THE SEMANTICS OF THE RELATIONAL MODEL FOR RICH OWL 2 ONTOLOGY LEARNING
Author:	BOUCHRA EL IDRISSI, SALAH BAINA, KARIM BAINA
Abstract:	This paper is interested in the ontology learning from relational databases (RDB) that exploits already approved semantics about a domain and translates them to application ontology. However, the relational model is recognized to be less expressive and incapable to support some conceptualizations. Without an explicit model of the domain semantics in the relational model, the automatic learning of ontology risks to infer incorrect semantics. In this paper, we give some proof case studies and we propose a model to upgrade the semantics of the relational model, before the ontology learning. The paper presents the constructs of the proposed model and it shows how they are translated to constructs of OWL 2 ontology.
Keywords:	Ontology Learning, Relational Database, Semantic Enrichment, OWL 2.
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	PERFORMANCE & ANALYSIS OF BLOCKING ARTIFACTS REDUCTION USING GUASSIAN ADAPTIVE SPATIAL LOW PASS FILTER
Author:	Dr.M.ANTO BENNET, R.SRINATH, P.MARAGATHAVALLI, B.SUBHASHINI
Abstract:	Ringing artifacts that appear as spurious signal near sharp transitions in a signal appear as ghosts (or) near edges. Two techniques called LPF and ASLPF is used. LPF is used for only just identifying the artifacts present in the video image. ASLPF (Adaptive Spatial Low Pass Filter) is used to identify the artifacts whether it is present in horizontal (or) vertical position (or) near edges. DCT is applied to each and every pixel in the block; the spatial domain is converted into frequency domain. But now a technique called Adaptive Spatial Low Pass Filter (ASLPF) is used to identify the artifacts and remove it completely. Video is converted into frames and each frame is compressed for removing the artifacts. Finally the reduction of artifacts is shown in PSNR.
Keywords:	Low Pass Filter, Adaptive Spatial Low Pass Filter, Discrete Cosine Transform, Peak Signal to Noise Ratio, Blocking Artifacts and Ringing Arifacts.
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	DEVELOPING A SAAS-CLOUD INTEGRATED DEVELOPMENT ENVIRONMENT (IDE) FOR C, C++, AND JAVA
Author:	A.B. MUTIARA, R. REFIANTI, B.A WITONO
Abstract:	Cloud era brought revolution of computerization world. People could access their data from anywhere and anytime with different devices. One of the cloud's model is Software as a Service, which capable to provide applications that run on a cloud infrastructure.An IDE (Integrated Development Environment) is the most popular tool to develop application in the network or single computer development. By installing IDE in each computer of the network could causes the lot of time and budget spending. The objective of the research is developing an efficient cloud based IDE. The IDE could compile the code which sent from client browser through SaaS IDE to the server and send it back to the client. The method that used in the research is the System Development Life-Cycle: Waterfall and Unified Model Language as system designing tool. The research successfully produced the cloud-based SaaS IDE with excellent result from several testing in local network and internet.
Keywords:	Cloud, IDE, SAAS, IDE, UML
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	RECOGNITION OF DIABETIC RETINOPATHY USING BLOOD VESSELS FROM VIDEO SEQUENCES
Author:	D.STALIN ALEX, Dr.AMITABH WAHI, Dr.J GEORGE CHELLIN CHANDRAN, A.USHA RUBY, Dr.R.REVATHI
Abstract:	Diabetic Retinopathy (DR) could be a condition occurring in persons with blood sugar, which causes progressive damage to the retina. At the beginning, Diabetic Retinopathy may cause no symptoms or mild vision problems. Eventually, however Diabetic Retinopathy can result in blindness. It is mainly due to the development of abnormal blood vessels in the retina. In this approach, we propose an efficient method to detect the blood vessels. The main focus of this paper is instead of using still images, the blood vessels are extracted from the video sequences. Contrast enhancement done in color image followed by thresholding, which helps in the dynamic preservation of the local contrast characteristics and median filtering carried in order to smoothen the background noise. The results of the proposed algorithm show a considerable improvement in the detection of blood vessels.
Keywords:	Diabetic Retinopathy (DR), Color Contrast Enhancement (CCE), Smoothening, Video Processing(VP),Object Extraction(OE).
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	A MMKP BASED HEURISTIC FOR QUALITY ENHANCED SCALABLE VIDEO STREAMING OVER WIRELESS NETWORKS
Author:	SWARNA PARVATHI, RAJU DAS, EASWARAKUMAR, KALAIARASI
Abstract:	Scalable Video Coding (SVC) is a very promising encoding technique that adapts to streaming video over wireless networks with bandwidth fluctuations. This paper proposes a Bandwidth Aware Layered Streaming Algorithm (BALSA), a MMKP (Multi-dimensional Multiple-Choice Knapsack Problem) based GHPMH (Gradational Hull Pareto Minimization Heuristic) to stream scalable video to heterogeneous users with different client’s display under bandwidth limitations so as to maximize the average video quality over all the streams. Using extensive simulation we show that our algorithm finds solutions which are close to the optimal (within 1 db) under realistic conditions with reduced computational complexity.
Keywords:	MMKP (Multi-dimensional Multiple Choice Knapsack Problem), Scalable Video Streaming, Pareto Minimization
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	PRIORITIZED DIRECTIONAL BROADCAST TECHNIQUE FOR MESSAGE DISSEMINATION IN VANETS
Author:	S. LAKSHMI , Dr. R.S.D.WAHIDA BANU
Abstract:	In Vehicular Ad Hoc Network (VANET), there is a possibility of occurrence of accidents within a cluster, when the driver does not react rapidly. To resolve this problem, in this paper, we propose a Prioritized Directional Broadcast Technique for Message Dissemination in VANET. Initially, message priority assignment technique is used in which three levels of message priorities, that is, very urgent, urgent and general messages are considered. Binary partition phase is then performed for finding the candidate relay node inside the coverage area of the source. Simulation results shows that the proposed approach provides high reliability during emergency message dissemination.
Keywords:	Vehicular Networks, Data Dissemination, Clustering.
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	LTE STANDARD: CHANNEL ESTIMATION ALGORITHMS FROM THE BASE STATION TO THE TERMINAL
Author:	ABDELHAMID LARAKI & DRISS EL OUADGHIRI, ABDELLAH JAMAL
Abstract:	This report deals with the LTE downlink transmission scheme, from the base station to the terminal (the mobile phone), which is based on multicarrier modulation: OFDM (Orthogonal Frequency Division Multiplexing). LTE also supports the use of multiple antennas at both the base station and the terminal to improve communication performance: Multiple Input – Multiple Output (MIMO) antenna processing. The project focuses on the different methods for estimating the time-varying channel between the transmitter and the receiver: to carry out coherent demodulation, the mobile terminal requires estimates of the downlink channel, and to allow this, known symbols are inserted in the transmitted signal.
Keywords:	Analog Baseband - Orthogonal Frequency-Division Multiplexing (OFDM) - End Module - LTE
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	AN APPROACH FOR IMAGE DENOISING USING NLM IN TERMS OF ANISOTROPIC DIFFUSION
Author:	GANESH NAGA SAI PRASAD V , HABIBULLA KHAN , E.GOPINATHAN
Abstract:	In a traditional single view photograph, dynamic objects or cameras cause motion noise. Digital image denoising is a prominent field in signal processing, focusing on improving the quality of images suffering from various degradation effects such as noise . To perform the denoising usually requires modelling the image content in order to separate the true image content from the degradation effects and restoring the degradation-free content. Restoration of image sequences can obtain better results compared to restoring each image individually, provided the temporal redundancy is adequately used. However in denoising of image sequence, the estimation of motion patterns between the frames in order to be able to merge the data from various frames are very complex and as a result motion estimation, a severely under-determined problem, tends to be error-prone and inaccurate. In this paper, for image denoising we are suggesting an algorithm which will give better result than the basic NLM algorithm.
Keywords:	Denoising, NLM, Ansitropic Diffusion, Degradation, PSNR.
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
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Title:	OCCURRENCE BASED CATEGORICAL DATA CLUSTERING USING COSINE AND BINARY MATCHING SIMILARITY MEASURE
Author:	S. ANITHA ELAVARASI1, J. AKILANDESWARI
Abstract:	Clustering is the process of grouping a set of physical objects into classes of similar object. Objects in real world consist of both numerical and categorical data. Categorical data are not analyzed as numerical data because of the absence of inherit ordering. This paper describes about occurrence based categorical data clustering (OBCDC) technique based on cosine similarity measure and simple binary matching similarity measure. The OBCDC system consists of four modules, such as data pre-processing, similarity matrix generation, cluster formation and validation. Similarity matrix generation uses three functions, namely FrequencyComputation, OccurranceBasedCosine and OccurranceBasedSBMS. The time complexity of various algorithms are discussed and its performance on real world data are measured using accuracy and error rate
Keywords:	Clustering, Unsupervised Learning, Categorical Data, Cosine Similarity, Simple Binary Matching Similarity
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
Full Text

Title:	EMBEDDED ZERO TREE WAVELET AND ORTHOGONAL POLYNOMIAL BASED TRANSFORM CODING
Author:	T.KARTHIKEYAN , B.PRABURAJ , K.KESAVAPANDIAN
Abstract:	In this paper, a new and effective mode for transform coding of images depends on orthogonal polynomials has been recommended. The proposed orthogonal polynomials be contingent on transform coding system has the encoder, comprising of a polynomial transform operation tracked by quantization of transform coefficients and the entropy coding of quantized measurements. Embedded Zerotree of Wavelet transforms is a lossy image compression algorithm. At low bit rates most of the coefficients bent by a subband transform will be zero, or very close to zero. It provides extensive improvement in picture quality at privileged compression ratio. After the encoded bit stream of an input image is transferred over the channel, the decoder rears all the functionalities applied in the encoder and tries to reconstruct a decoded image that looks as close as possible to the inventive input image. The result of the proposed coding are compared with Embedded Zero Tree Wavelet and Discrete Wavelet Transform coding. The new image coding algorithm results in a considerable reduction in computation time and provides better reconstructed picture quality. The experimental results of the proposed technique also show that the efficient bit rate decline is achieved, when equated with existing techniques.
Keywords:	Orthogonal Polynomials, Quantized Coefficients, EZW, Lossy Image Compression, Compression Ratio.
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
Full Text

Title:	APPLYING THE FVSI-GENERATION TRACING AND HYBRID ANT COLONY ALGORITHM FOR EFFECTIVE STATIC GENERATION POWER DISPATCH
Author:	Z. HAMID, I. MUSIRIN
Abstract:	This paper proposes the latest application of power tracing technique for voltage stability improvement. Instead of solving losses charge allocation problem in deregulated power market as performed by many researchers, the proposed technique can be implemented for effective static generation power dispatch; that is, by determining suitable generating units involved in re-dispatching with the aim of providing a more economical and effective power generation. Using power tracing approach, the determination of suitable generating units can be done by means of stability index tracing or specifically termed as Fast Voltage Stability Index-Generation Tracing (FVSI-GT). After deriving a ranking list of generator buses via FVSI-GT, the real and reactive power of the selected generators are sized using a new hybrid algorithm; the Blended Crossover Continuous Ant Colony Optimization (BX-CACO). Simulation and experiment on IEEE 57-Bus reliability test system (RTS) justified the reliability of FVSI-GT for precise selection of suitable generators besides other conventional ranking methods. In addition, the proposed BX-CACO showed a tremendous performance in terms of convergence speed and solution quality.
Keywords:	BX-CACO, FVSI-GT, Generation Power Dispatch, Stability Index Tracing
Source:	Journal of Theoretical and Applied Information Technology 10^th October 2014 -- Vol. 68. No. 1 -- 2014
Full Text