		FeedBack \| Contact Us \| Links \| Site Map

Welcome to Journal of Theoretical and Applied Information Technology

Submit Paper / Call for Papers

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
September 2014 | Vol. 67 No.2

Title:	SURVEY ON INFORMATION EXTRACTION FROM CHEMICAL COMPOUND LITERATURES: TECHNIQUES AND CHALLENGES
Author:	MUAWIA ABDELMAGID, MUBARAK HIMMAT, ALI AHMED
Abstract:	Chemical documents, especially those involving drug information, comprise a variety of types – the most common being journal articles, patents and theses. They typically contain large amounts of chemical information, such as PubMed-ID, activity classes and adverse or side effects. Techniques are used to extract information from a huge number of documents and it is presented in a useful structurally prepared format that can be applied to structured, semi-structured and unstructured texts. Numerous information extraction methods and techniques have been proposed and implemented. In principle, there are two main approaches to information extraction, the knowledge engineering approach and the learning approach. In this survey study, we ﬁrst provide the historical background on information extraction approaches applied to chemical documents and discuss several kinds of information extraction tasks that have emerged in recent years. Then, we discuss the metrics used for evaluating information extraction systems, and finally the survey outlines the main issues that will shape future research in this area of study.
Keywords:	Information Extraction, Information Retrieval, Chemical Extraction, Extraction Methods
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	FLOW BASED ANALYSIS TO IDENTIFY BOTNET INFECTED SYSTEMS
Author:	R.KANNAN, A.V.RAMANI
Abstract:	Botnet most widespread and occurs commonly in today’s cyber-attacks, resulting in serious threats to our network assets and organization’s properties hence there is a high need to detect and prevent the adverse effects of bots. Botnets are collections of compromised computers (Bots) which are remotely controlled by its originator (Bot-Master) under a common Command-and-Control (C&C) infrastructure. This paper focuses on classifying the bots and the regular hosts in the network through the classification based on their behavior. The goal is to develop a live version of the botnet detection system which identifies a botnet activity in a network, based on traffic behavior analysis and flow intervals which does not depend on packet pay load i.e., they can work on encrypted network communication protocol. The approach is to classify packets based on source IP, destination IP, number of packet, etc., using decision tree which is a classification technique in machine learning. The attribute selection is mainly based on packet attribute and does not consider the data part. The feasibility of the approach is to detect botnet activity without having seen a complete network flow by classifying behavior based on time intervals.
Keywords:	Botnet, Machine learning, Malicious, Intrusion, Network flow.
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	REAL TIME VIDEO SEGMENTATION BASED ON MODIFIED MULTISCALE MORPHOLOGICAL RECONSTRUCTION
Author:	NITHYA. A, KAYALVIZHI R
Abstract:	Video Segmentation is used in many practical applications such as medical imaging, computer-guided surgery, machine vision, object recognition, digital entertainment, surveillance, content-based browsing and augmented reality applications. In the proposed technique video segmentation is performed using modified gradient based multiscale morphological operation. Both gradient and grey scale method used to segment the object from the frame. Also K-Mean Clustering algorithm is applied to segment object by removing the background in each frame. Segmented object will be obtained by refining the combined gradient k-means segmented frame and the gray-scale k-means segmented frame. Accuracy of the segmentation is evaluated by comparing proposed algorithm and existing algorithm with different threshold value.
Keywords:	Video Segmentation, Multiscale Morphological Operation, Gradient, K-Means Clustering, Accuracy.
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	PROPAGATION DELAY BASED COMPARISON OF PARALLEL ADDERS
Author:	THEMOZHI.G, THENMOZHI.V
Abstract:	An intelligent full adder circuit is simulated using Cadence Virtuoso Analog Design version 6.0. The complementary property between sum and carry for most of the input combination is considered for reducing the number of transistors in the full adder circuit. The parameters such as the Power consumption, Delay and Power Delay Product (PDP) are improved in the proposed CMOS full adder than the conventional CMOS full adder. The size of the chip and the number of transistors are greatly reduced with the proposed circuit. From the single bit full adder module, other parallel adder circuits such as Ripple carry Adder, Carry Look Ahead Adder, Carry Save Adder, Carry Increment adder, Carry Skip Adder, Carry Select Adder and Carry By-pass Adder are simulated. The worst-case gate delay in each case is measured and compared with other adders.
Keywords:	Full Adder, CMOS, Gate Delay, PDP (Power Delay Product), Parallel Adders.
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	TUNING OF NONLINEAR MODEL PREDICTIVE CONTROL FOR QUADRUPLE TANK PROCESS
Author:	P.SRINIVASARAO, DR.P.SUBBAIAH
Abstract:	Multi Input Multi Output (MIMO) interactive process is more complex than Single Input Single Output (SISO) systems. We consider two inputs and two outputs for four tank process, which is also called Quadruple Tank Process (QTP). It consists of two inputs as voltages fed to motor pumps and water levels in the lower tanks are the two outputs. The inputs are manipulated by setting of valves. It has four tank interactive loop operation consisting of two lower tanks and two upper tanks. The Model Predictive Control (MPC) technique is more suitable and gives optimized operational control in calculating present and future values of output. It tunes output and inputs simultaneously to provide more stable (optimized) output within the permissible limits of tolerance / error. MPC can stabilize all linear processes effectively and efficiently. It can also work with nonlinear processes under extreme conditions. It offers an optimized result under Predictive control “P” and Horizon control “M”, by tuning P and M and its application to QTP as a Nonlinear Model Predictive Control.
Keywords:	Nonlinear Model Predictive Control, Optimized, QTP, Predictive Control P, Horizon Control M
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	PERSONALIZING USER DIRECTORIES THROUGH NAVIGATIONAL BEHAVIOR OF INTERESTING GROUPS AND ACHIEVING MINING TASKS
Author:	MS.R.KOUSALYA, DR. V. SARAVANAN
Abstract:	Web directory is a collection of web pages with links. A grouping or organizing web content into thematic hierarchies are known as Web Directories which are correspond to topics listed are easily visualize by the people. The key focus on our methodology is that is personalizing web directories using navigation patterns prepared for user profiles. A user profiles containing the information about a user or group of user’s previous visits categories. Patterns are generated based on navigational behavior and interest of the individual user or a group of user. Our work provides a set of mining tasks and personalization techniques to customize the organization of user directory based on corresponding pattern behavior.
Keywords:	Personalization, User Directory, User Profile, Navigation Patterns, Clustering
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	NOVEL MODIFIED FPCM FOR WEB LOG MINING BY REMOVING GLOBAL NOISE AND WEB ROBOTS
Author:	P.NITHYA, DR.P.SUMATHI
Abstract:	Nowadays, internet is a useful source of information in everyone’s daily activity. Hence, this made a huge development of World Wide Web in its quantity of interchange and its size and difficulty of websites. Web Usage Mining (WUM) is one of the main applications of data mining, artificial intelligence and so on to the web data and forecast the user’s visiting behaviors and obtains their interests by investigating the samples. Since WUM directly involves in large range of applications, such as, e-commerce, e-learning, Web analytics, information retrieval etc. Web log data is one of the major sources which contain all the information regarding the users visited links, browsing patterns, time spent on a particular page or link and this information can be used in several applications like adaptive web sites, modified services, customer summary, pre-fetching, generate attractive web sites etc. There are varieties of problems related with the existing web usage mining approaches. Existing web usage mining algorithms suffer from difficulty of practical applicability. So, a novel research is very much necessary for the accurate prediction of future performance of web users with rapid execution time. The main aim of this paper to remove the noise and web robots by novel approach and provide faster and easier data processing and it also helps in saving time and it resource. In this paper, a novel pre-processing technique is proposed by removing local and global noise and web robots. Anonymous Microsoft Web Dataset and MSNBC.com Anonymous Web Dataset are used for evaluating the proposed preprocessing technique. An Effective Web User Analysis and Clustering are analyzed using Modified FPCM. Then results are evaluated using Hit Rate and Execution time.
Keywords:	Preprocessing, Data Cleaning. Modified Fuzzy Possibilistic C Means, Fuzzy C Means, Hit Rate, Execution Time.
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	FUTURE LOAD AWARE SERVICE BROKER POLICY FOR INFRASTRUCTURE REQUESTS IN CLOUD
Author:	A.RADHAKRISHNAN, V.KAVITHA
Abstract:	Cloud computing is a new computing paradigm, which offers resources for solving complex problem in fast and lower cost under pay per usage through internet. This feature is great boon to software companies to reduce their infrastructure setup and maintenance cost. IaaS service is one of the fundamental service models of cloud provider that offers entire computing environment as Virtual Machine (VM) to customers. The VM is created on cloud provider datacenter physical server. The provider deployed multiple datacenters in geographically different location to cater the needs of IaaS customers. The customers are much concerned about reducing their computation time and VM rental cost. The cloud service brokers are playing vital role in this regard, one of their responsibility is to direct the user request to appropriate datacenter. The selection of datacenter is a challenging task for service broker. Our proposed approach aims to enrich the intelligence of service broker during datacenter selection. Our novel algorithm makes the service broker to aware about the future load of every datacenter during request forwarding. It would facilitate the broker to route the IaaS request in right destination. The performance of our novel methodology is tested in Cloud Analyst tool. The result shows that our methodology reduces task time of customer applications compare to existing broker policies.
Keywords:	Virtual Machine (VM), Infrastructure as a Service (IaaS), Datacenters Classification Algorithm (DCA), Datacenter Load Aware Service broker Algorithm (DLASA), Neural Networks (NN).
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	PERFORMANCE ANALYSIS OF ADAPTIVE MODULATION FOR HIGH MOBILITY FOR LTE
Author:	LENIN, Dr. S. MALARKKAN
Abstract:	The demand of high data rate and affirmation to the real-time communications (network). LTE is well placed to fulfill the demands of next generation mobile networks. It delivers beneficial features such as high mobility transmission and scalability of bandwidth using both TDD and FDD duplexing methods, for the time varying and frequency selective wireless channel within one OFDM sub-carrier. For the exact estimation of wireless channel, some of OFDM subcarrier used as a reference signal while other subcarrier are either used to transmit data symbols are set as unused. The weighted time-domain interpolation computed from the channel based on the Doppler spread information and Parallel Interference Cancellation scheme jointly with Decision Statistical Combining (PIC-DSC) technique is used to reduce the ICI and to improve the data symbol detection. Here the adaptive modulation technique is used additionally to adopt the channel condition that maximizes the spectral efficiency and to meet higher throughput instead of retransmission, the transition rate can be cut down, when the channel condition is miserable. So the Quality of Service (QOS) in the time varying wireless channel is maintained.
Keywords:	Adaptive Modulation, ICI, MIMO-OFDM, PIC, DSC
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	JOSE MEASURE BASED HIGH DIMENSIONAL DATA CLUSTERING FOR REAL WORLD CONDITIONS
Author:	M.SUGUNA, Dr.S.PALANIAMMAL
Abstract:	The modern real world data has more number of dimensions with varying arguments. Different organization maintains customer or product information in different forms which is difficult to perform clustering. Each data point has different in size and properties, but has to be clustered in meaningful and efficient way to get some knowledge from that. Many strategies have been proposed for clustering high dimensional data but suffer with the problem of overlapping and retrieval efficiency. We propose a new measure called JOSE (Joint optimum similarity eccentric), which represents the distance between points in multiple forms of data. Jose measure, which shows the relationship between two data points at their junction points with eccentric data points. The Jose measure shows the closeness of particular data point with set of data points in a cluster. The proposed approach computes distance between data points with available attributes of data points with remaining data points from the cluster. The proposed approach has produced higher efficient clustering with negligible overlapping. We have used Enron data set for the evaluation of the proposed approach and the results shows that the proposed method has produced efficient result than others.
Keywords:	High dimensional data, Clustering, JOSE Measure.
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	SEMANTIC ANALYSIS OF SOFTWARE SPECIFICATIONS WITH LINKED DATA
Author:	MARTIN DOSTAL, MICHAL NYKL, KAREL JEŽEK
Abstract:	Software development life cycle is the process involved in the design, development and improvement of a software application. Nowadays especially component systems are used due to possibility of implementing reusable independent modules. The individual module, known as a software component, can be implemented in a form of a software package, a web service or a web resource that encapsulates a set of related functions. Software products are derived in a configuration process by composing different components. Moreover a software product line enables stakeholders to derive a different software products based on their needs. This fact and need for validation of the software product and its components requires methods for software specification processing and matching with concrete sw properties. In this article we will propose an approach for semantic analysis of software specifications with Linked Data.
Keywords:	Software Specifications, Linked Data, Semantic Analysis
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	A COMPARATIVE ANALYSIS OF AN OCDMA SYSTEM BASED ON SINGLE-PHOTO-DIODE (SPD) AND SPECTRAL DIRECTION DETECTION (SDD) SCHEMES
Author:	SARAH G. ABDULQADER, HILAL A. FADHIL, S. A. ALJUNID
Abstract:	In this paper, a comparative study to evaluate the performance of spectral-amplitude coding optical code-division multiple-access (SAC-OCDMA) systems based on single photo-diode (SPD) detection and spectral direct detection (SDD) schemes. In our work, we utilized Modified Double weight (MDW) code as one of the SAC codes for evaluated both detection techniques. The results characterizing the bit-error-rate (BER) of 10-12 with respect to the data rate show that the SDP offers a significant improved performance for long haul applications over SDD technique. Furthermore, the SPD detection has higher signal –to-noise ratio (SNR) than SDD technique utilizing different types of optical filters. Finally, for the same quality of service (QoS) for a bit error rate (BER) of 10-12 and data rate of 622 Mbps, SPD allows higher transmission distance of 30 km than SDD technique.
Keywords:	OCDMA, PIIN, MAI, SDD, SPD.
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	PRIMITIVE STRUCTURAL METHOD FOR HIGH CAPACITY TEXT STEGANOGRAPHY
Author:	NUUR ALIFAH ROSLAN, RAMLAN MAHMOD, NUR IZURA UDZIR, ZURIATI AHMAD ZURKARNAIN
Abstract:	High capacity for hiding secret information is typically the main concern in text steganography, as well as robustness and perceptual invisibility in a perfect steganography algorithm. The major issue in text steganography is the difficulty of using a large amount of redundant information to hide secret bits (1 and 0) in perceptible appearance. We propose a Primitive Structural algorithm for Arabic text steganography to encounter this issue. This algorithm hides the secret bits in the primitive structure (i.e. sharp edges, dots, typographical proportion) for the Arabic character. Therefore, this new algorithm presents a high data-embedding capacity since each character has more than one potential place to hide the secret information. The main processes involved are the preparation of the secret message as a binary process, identifying the Primitive Structural for each character in the cover-text process, and finally the bit hiding process. The experiments have shown that the data-embedding capacity percentage is increased up to 4% for our first experiment and for the second experiment the results show the increase in capacity up to 21% compared to the our previous method, thus resolving the capacity issue.
Keywords:	Information Hiding, Data Embedding, Text Steganography, Arabic Text Steganography, High Capacity
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	PERFORMANCE ANALYSIS OF MULTI-CARRIER AGGREGATION WITH ADAPTIVE MODULATION AND CODING SCHEME IN LTE-ADVANCED SYSTEM
Author:	IBRAHEEM SHAYEA, MAHAMOD ISMAIL ROSDIADEE NORDIN HAFIZAL MOHAMAD
Abstract:	Although LTE-Advanced system is targeted at enhancing the users’ throughput and increasing connection reliability, however user’s mobility tends to degrade the efficiency of the services and applications in terms of throughput degradation and outage probability reduction. Particularly this is during the handover from the source to the target eNBs. Therefore, the Carrier Aggregation (CA) technique is based on different numbers of Components Carrier (CCs) utilizing AMC scheme is implemented in this paper in order to further enhance the system performance. A simple mathematical formulation for user’s throughput and outage probability evaluation are derived and then used in the simulation for random mobility. It has shown that, the integration of CA and AMC (CA-AMC) on the downlink significantly outperforms systems either by employing CA with common Modulation and Coding Schemes (MCSs) or that by implementing Non-CA technique with MCSs or AMC scheme in terms of throughput and outage probability. The total throughput gains achieved by CA-AMC integration are 50 to 80% over non-CA employed AMC when between 2 to 5 CCs are used respectively with AMC integration. Similarly, the total user’s outage probability is improved when the number of CCs is increased with AMC integration.
Keywords:	Carrier Aggregation, AMC, Throughput, Outage Probability, LTE-Advanced.
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	PARAMETER MAPPING OF FEATURE SELECTION VIA TAGUCHI METHOD ON EMAIL FILTERING
Author:	NOORMADINAH ALLIAS, MEGAT NORULAZMI MEGAT MOHAMED NOOR, MOHD NAZRI ISMAIL
Abstract:	In spam filtering, the use of machine learning as a filtering method is prone to a high dimensionality of features space. In order to overcome the problem, a lot of feature selection methods have been introduced. Besides, the number of features used as an input to machine learning classifier is still high, thus it will delay the delivery of incoming emails to user’s inbox. Therefore, two stages of feature selection by using Taguchi method to reduce a high dimensionality of features and obtained a good result are introduced. Firstly, we used Gini Index to reduce a high dimensionality and selecting the best subset of features, while Taguchi method is applied to assist Gini Index and PSO-SVM in selecting the best combination of parameter settings. Apart from this, the impact of population size on different classifier is investigated as it brings a high impact on the classifier performances. This method is trained and tested on Ling-spam email dataset. The experimental result shows that a hybrid Gini PSO- SVM feature selection with Taguchi method is able to produce a good classification result even when the population size is less than 10.
Keywords:	Spam Email, High Dimensionality, Feature Selection, Orthogonal Array, and Population Size.
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	DESIGN OF PRIVACY MODEL FOR STORING FILES ON CLOUD STORAGE
Author:	AMBIKA VISHAL PAWAR, DR. AJAY A. DANI
Abstract:	Cloud Storages like Google drive, Dropbox are popular for personal and institutional file storage. Cloud storage is beneficial in terms of scalability, availability and economy. But cloud storage has privacy challenges due to which many users are reluctant to use it for personal data storage. Storage of personal or sensitive files should be done carefully. Since cloud storage is third party storage and also has many other possibilities like files can be shifted from one server to another cloud server. Cloud storage needs special solution than traditional third party storages. The data can be encrypted for security purpose but this will further raises issues like key management and key distribution. Encryption also requires more computation cost and time on client/user. This paper introduces the design of novel privacy model for storing files in cloud storage, proposes architecture and algorithms for cloud storage. Paper also discusses about the proof of privacy and proposed system’s performance evaluation parameters for future work.
Keywords:	Cloud Storage, Files, Privacy, Multicloud, Splitting, Information Dispersal Algorithm, Security, Randomization
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	CLASSIFICATION MODELS BASED FORWARD SELECTION FOR BUSINESS PERFORMANCE PREDICTION
Author:	EDI NOERSASONGKO, PURWANTO, GURUH FAJAR SHIDIK
Abstract:	This paper proposes a classification model to improve the accuracy of prediction for business performance. The proposed model uses a combination of forward selection method to select the optimum attributes and classification models. Business performance data set is used to evaluate the accuracy of the proposed model. From results of experiments show that the combination of forward selection and Naïve Bayes model can improve the prediction accuracy of business performance compared to the other classification models, namely Logistic Regression, k-NN, Naïve Bayes, C4.5 and Support Vector Machine models significantly. The proposed model also yields better result compared to the other attribute selection using backward elimination method.
Keywords:	Forward Selection, Naïve Bayes, Entrepreneur, Business performance, Classification Models
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	AREA OPTIMIZED BALANCED MULTIWAVELETS FOR WIRELESS COMMUNICATION
Author:	G.ASWINI, K.ANITHA, Dr.Dharmishtan.K.Varughese
Abstract:	New technologies are emerging to take the challenges in the wireless communication. According to the requirements for the next generation technologies have led to unparalleled insist for high speed architectures for complex signal processing applications. In this paper, we propose a modified DMWT architecture based on CardBal filter. The DMWT coefficients that are fractions are converted to integers and are modified to reduce the number of multiplications and additions. The reduced CardBal filter coefficients are used to process the data, thus reducing the computation complexity and making it suitable for FPGA implementation. The design operates at maximum frequency of 300MHz and consumes less than 1% resources and thus is suitable for real time applications optimizing area, speed and power. The model is tested for its functionality using HDL code and is synthesized using Xilinx ISE targeting FPGA.
Keywords:	Cardinal Multiwavelets, CardBal Filter, Balanced Multiwavelets, DMWT, FPGA
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	A PREDICTIVE USERS PREFERENCE IDENTIFICATION TECHNIQUE TO IMPROVE WEB USERS QUERY RELATIONAL PROCESSING
Author:	D. MADHUSUBRAM, DR. S.P. SHANTHARAJAH
Abstract:	One of the major challenges in the web is accessing relevant information according to the needs of the user. With each user having different information needs in relation to his/her query, the search results should be personalized according to the information needs of the users. Personalized ontology model for knowledge representation and reasoning over user profiles fails to match the local instance repository queries (i.e.,) users with global information base (i.e.,) web database. Although the application of ontology model has been underway for many years and many algorithms related to ontology have been developed, it is not applicable to the majority of the existing web documents. Query planning for Weighted Additive Aggregation Queries (WAAQ) obtained optimal set of sub queries with incoherency bounds and least number of refresh messages were sent from aggregators to the client. But WAAQ is not effective in developing the cost model for complex queries. To overcome the issues related to complex queries, Predictive User Preference Identification (PUPI) technique is developed based on the relational users and stored queries. PUPI technique searches the results according to each user’s need based on their relevant information with little effort from the side of the user, followed by it the effectiveness with complex queries are verified. PUPI then extends to Condition Redefine Query which redefines the queries according to the user relational profile and stored query context. In order to learn user’s preference, PUPI make use of both semantic and lexical information. PUPI take into account the web queries for the current user task and engender a new query language model for redefining based on the user query model and the considering the user profile. PUPI technique performed experiment on Weka tool using the MSNBC.com Anonymous Web Data. By analyzing the results, PUPI technique is better than using the state-of-art methods. Experiments were conducted on the factors such as execution time, micro averaged accuracy, query user relationship ratio, query frequency similarity and true positive rate to reveal the efficiency of the technique, query frequency similarity and true positive rate.
Keywords:	Ontology Model, Predictive User Preference Identification, Semantic Information, Condition Redefine Query, User Relational Profile, Stored Complex Queries
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	EVALUATION OF EMPLOYEES AWARENESS AND USAGE OF INFORMATION SECURITY POLICY IN ORGANIZATIONS OF DEVELOPING COUNTRTIES: A STUDY OF FEDERAL INLAND REVENUE SERVICE, NIGERIA
Author:	WADZANI A. GADZAMA, JATAU ISAAC KATUKA, YUSUF GAMBO, ALIYU M. ABALI, MUHAMMED JODA USMAN
Abstract:	Information security policy has become an integral part of today’s organizational operations. It is a set of rules that guides computer resource users to ensure confidentiality, integrity and availability of organization information resources. Federal Inland Revenue Service of Nigeria is a government organization that is responsible for collecting revenues to the government. Due to its nature, it is concerned with how to protect and manage its information resource. This can only be achieved through implementation of an effective information security policy. This policy will help to ensure the confidentiality, integrity and availability of its information assets are protected. The purpose of the study is to find out the precise nature of existing information security policy and also to access the level of IT staffs awareness and usage of the policy in organizations of developing countries using Federal Inland Revenue service, Nigeria as a study area. Questionnaires were distributed which consist of both open and closed ended questions. The data collected were analyzed and presented. The study reveals that the IT staffs are aware of the existence and usage of the information security policy to the success of the organization. It was also revealed that the lack of adequate management support has affected the use of the policy. The study recommends that the management support in terms of staff training and awareness programs, continuous monitoring, enforcement and periodic review of the policy should be made to ensure the effectiveness of the organization information security policy.
Keywords:	Federal Inland Revenue, Service, Information Security Policy, Models, Information and Communication Technology.
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	A NOVEL CLASSIFICATION SCHEME FOR NON-INVASIVE HEMOGLOBIN MEASUREMENT METHODS
Author:	KUMAR R Dr RANGANATHAN H
Abstract:	Hemoglobin (Hb) is an imperative constituent of red blood cells (RBC). Assessment of individual physiological status is accomplished by measuring Hb concentration in human blood. The limitations associated with invasive methods are distress during sample collection, wide analysis time and disability to provide real time monitoring. These limitations were addressed by a gamut of non-invasive schemes. The decision scheme for different blood samples associated with non-invasive schemes exhibits intrinsic intricacies. This paper proposes a classification scheme for diverse blood samples by criterion based identification and association to an existing data set. The scheme was implemented and tested on three samples with different testing conditions. Accuracy was identified as the performance metric for this scheme and the results shows that the proposed schemes displays accuracy ranging from 99% to 72% for a range of 0 dB to 10dB Signal to Noise Ratio (SNR).
Keywords:	Hemoglobin (Hb), Red Blood Cell (RBC), Invasive, Non-Invasive, Signal to Noise Ratio (SNR)
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	IMPROVED GENETIC ALGORITHM FOR GROUP-BASED JOB SCHEDULING IN MOBILE GRIDS
Author:	G.SARAVANAN, Dr.V.GOPALAKRISHANAN
Abstract:	In mobile grids, the existing job scheduling scheme causes increased job processing time. The increased processing time and overhead may results in system degradation. Also mobility and resource availability parameters are not considered during job scheduling. Hence in this paper, we propose an improved genetic algorithm for group-based job scheduling in mobile grids. In this technique, the jobs are grouped according to the resource availability. Then the jobs are scheduled based on the parameters such as mobility, resource availability and job completion time using enhanced genetic algorithm. By simulation results, we show that the proposed technique minimizes the job completion time, thus enhancing the system performance and minimizing the overhead time.
Keywords:	Genetic Algorithm, Job Scheduling, Mobile Grids, Simulation, Overhead Time
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	WIRELESS IMPLEMENTATION SELECTION IN HIGHER INSTITUTION LEARNING ENVIRONMENT
Author:	IHAB AHMED NAJM, MAHAMOD ISMAIL, ABD AL-RAZAK TAREQ RAHEM
Abstract:	The limitation of WiFi coverage and free frequency create problems as well as weaken security and degrade quality of services. Therefore, a complementary wireless technology, WiMAX, is required. WiMAX and WiFi are chosen as both technology are the most highly popular by wireless network protocols usage in Iraq. Simulation on both of the network environments will be used to imitate the real situation in Tikrit University. This study provides a comprehensive field survey on wireless networking in Tikrit University of Iraq. Suitable wireless protocol, expanding coverage, performance of network will be included after the application of this study. The major benefits that have achieved as the outcome of this study are packet delivery ratio and throughput. Both WiFi scenarios achieved packet delivery ratios of 97.2% and 96.012% respectively, while WiMAX scenario scored 98.0% on packet delivery ratio. On the other hand, the throughput was found to produce interesting results and increased with packet size. WiMAX throughput had been discovered to be increasing linearly to the throughput. The maximum throughput achieved by WiMAX was 22.12 Mbps while the WiFi obtained throughputs of 22.46 Kbps and 11.61 Kbps for the different scenarios.
Keywords:	WiFi, WiMAX, Interference, Expand Coverage.
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	A SURVEY ON NEURAL NETWORK MODELS FOR HEART DISEASE PREDICTION
Author:	SELVAKUMAR.P, DR.RAJAGOPALAN.S.P
Abstract:	The healthcare organization (hospitals, medical centers) should provide quality services at affordable costs. Quality of service implies diagnosing patients accurately and suggesting treatments that are effective. To achieve a correct and cost effective treatment, computer-based information and/or decision support Systems can be developed to full-fill the task. The generated information systems typically consist of large amount of data. Health care organizations must have ability to analyze these data. The Health care system includes data such as resource management, patient centric and transformed data. Data mining techniques are used to explore, analyze and extract these data using complex algorithms in order to discover unknown patterns. Many data mining techniques have been used in the diagnosis of heart disease with good accuracy. Neural Networks have shown great potential to be applied in the development of prediction system for various type of heart disease. This paper investigates the benefits and overhead of various neural network models for heart disease prediction.
Keywords:	Artificial Neural Network, Data Mining, Heart Diseases, Knowledge Discovery, Heart Disease Prediction System
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	EXPERIMENTAL EVALUATION OF FUZZY- BASED FUNCTION POINT ANALYSIS FOR SOFTWARE EFFORT ESTIMATION
Author:	M. SENTHIL KUMAR, Dr.B. CHIDAMBARA RAJAN
Abstract:	Accurate Effort Estimation is a significant task in software development, which is helpful in the scheduling and tracking of the project. A number of estimation models are available for effort calculation. However, a lot of newer models are still being proposed to obtain more accurate estimation .This paper attempts to propose a hybrid technique which incorporates both quality factors and fuzzy based technique in function Point Analysis. Fuzzy logic has the capability of tackle the uncertainty issues in the estimation. The goal of this paper is to evaluate the accuracy of fuzzy analysis for software effort estimation. In this approach, fuzzy logic is used to control the uncertainty in the software size with the help of a triangular fuzzy set, and de-fuzzification through the weighted average method. The experimentation is done with different project data on the proposed model, and the results are tabulated. The measured effort of the proposed model is compared with that of the existing model, and finally, the performance evaluation is done based on parameters in terms of MMRE and VAF.
Keywords:	Effort Estimation, Function Point, Fuzzy-based Function Point, Triangular Fuzzy Set, Accuracy
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	THE RELATIONSHIPS BETWEEN WIRELESS NETWORK COMMUNICATION, IT FLEXIBILITY, IT ARCHITECTURE, AND STRATEGIC ALIGNMENT: AN EMPIRICAL STUDY
Author:	A.HAMEED, ALI OUDAH
Abstract:	Strategic alignment and wireless communication network are two important areas that receive considerable attention in two last decades, for this reason, we try to evaluate the relation between these two important concepts. This study discussed and empirically tested the most important factors that affect strategic alignment and wireless network communication. The objective of this paper is to analysis and provides a model for the effect of wireless network connectivity on strategic alignment in the case of Iraqi firms. For this purpose, we consider the relationship between information technology flexibility and strategic alignment and also we involve three important dimension of flexibility in our research. Connectivity is voice and data Communication infrastructure of networks. We empirically tested our model using data collected from executives of 55 Iraqi firms. The results show that strategic alignment is not positively correlated with wireless network communication; so successful communication in a wireless network indicates good connectivity.
Keywords:	Strategic Alignment, Wireless Communication Network, Connectivity, IT, IT Architecture
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	IDENTITY BASED ATTACK DETECTION AND MANIFOLD ADVERSARIES LOCALIZATION IN WIRELESS NETWORKS
Author:	UDHAYA SANKAR S.M , V.VIJAYA CHAMUNDEESWARI , JEEVAA KATIRAVAN
Abstract:	Wireless spoofing attacks are easy to launch in wireless network due to openness of wireless network. Although the identity of a node can be detected through cryptographic authentication, conservative security approaches are not always possible because of their overhead requirements. Source sends a Data to the destination, Data is forwarded to the intermediate nodes in between source and destination, with respect to Received Signal Strength(RSS). In this paper to detect the identity based attacks and multiple adversaries as well as localizing the adversaries. Detect the position of multiple adversaries even when the adversaries vary their transmission power level. We propose to use the spatial correlation of received signal strength(RSS) inherited from wireless nodes to detect the attacks. We are also using primary key and encrypting the data packets during transmission for security purpose. By encrypting the data packets the intermediate nodes are not able to view the data presented in the data packets. Experiments using an 802.11 (Wi-Fi) network, We use network simulation to analyse the performance of the results.
Keywords:	Wireless Networks, Identity Attacks, Primary Keys, Attack Prevention
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	FLOW BASED MULTI FEATURE INFERENCE MODEL FOR DETECTION OF DDOS ATTACKS IN NETWORK IMMUNE SYSTEM
Author:	S.VASANTHI, S.CHANDRASEKAR
Abstract:	Network immune systems have been developed in many ways but differ with the feature set used and suffer with identifying network threats in efficient manner. We propose a multi feature inference model which uses various parameters of network flow. Unlike earlier approaches, the proposed method infers valuable knowledge from the packet flow and packet details to detect DDOS attacks. The proposed method uses, hop count, hop details, payload, Time to live with time variant information’s. The network packets are monitored about their traversal, through which they forwarded towards destination. We consider the botnet attacks, which is supported by dedicated nodes distributed throughout intermediate network. Whenever a new packet received at the network various features are extracted and we compute the probability of genuine value according to the features. The proposed immune system maintains packet trace for each of the packet received at various time domains. At each time window, for each distinct traversal path an probability value is computed using the features extracted from traffic trace. The inferred results are applied do denial the service for the malicious nodes. The result will be inferred using computed probability value to allow or deny the packet into the network.
Keywords:	Intrusion Detection System, Network Immune System, Botnet, Flow Based Inference Model, Denial of Service Attacks.
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	MODIFIED MFCC METHODS BASED ON KL- TRANSFORM AND POWER LAW FOR ROBUST SPEECH RECOGNITION
Author:	JOHN SAHAYA RANI ALEX, NITHYA VENKATESAN
Abstract:	This paper presents robust feature extraction techniques, called Mel Power Karhunen Loeve Transform Coefficients (MPKC), Mel Power Coefficients (MPC) for an isolated digit recognition. This hybrid method involves Stevens’ Power Law of Hearing and Karhunen Loeve(KL) Transform to improve noise robustness. We have evaluated the proposed methods on a Hidden Markov Model (HMM) based isolated digit recognition system with TIDIGITS data for clean speech and also with noisy speech data. An increase in the recognition accuracy rate is observed with the proposed methods compared to conventional Mel Frequency Cepstral Coefficients (MFCC) technique.
Keywords:	Feature extraction; Stevens’ power law; MPKC; KL Transform; CMN; MFCC; HMM
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text

Title:	NEW TECHNIQUE FOR SIZING OPTIMIZATION OF A STAND-ALONE PHOTOVOLTAIC SYSTEM
Author:	NUR IZZATI ABDUL AZIZ, SHAHRIL IRWAN SULAIMAN, SULAIMAN SHAARI, ISMAIL MUSIRIN
Abstract:	This paper presents a method for sizing optimization in Stand-Alone Photovoltaic (SAPV) system. Evolutionary Programming (EP) was integrated in the sizing process to maximize the technical performance of the system. It is used to determine the optimal PV module, charge controller, inverter and battery such that the expected Performance Ratio (PR) of the SAPV system could be maximized. Two EP models, i.e. the Classical Evolutionary Programming (CEP) and Fast Evolutionary Programming (FEP) were tested in determining the best EP model for the EP-based sizing algorithm. In addition, an iterative-based sizing algorithm was developed to determine the optimal solution for benchmarking purposes. The results showed that CEP had outperformed the FEP by producing higher PR despite having almost similar computation time. However, the sizing algorithm using both EP models was also found to be much faster when compared to the iterative-based sizing algorithm, thus justifying the needs for incorporating EP in the sizing algorithm.
Keywords:	Photovoltaic (PV), Stand-Alone Photovoltaic (SAPV), Evolutionary Programming (EP), Sizing, Optimization
Source:	Journal of Theoretical and Applied Information Technology 20 September 2014 -- Vol. 67. No. 2 -- 2014
Full Text