International Journal of Reviews in Computing

Welcome to International Journal of Reviews in computing

ISSN : 2076-3328 | E-ISSN : 2076-3336

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Journal receives papers in continuous flow and we will consider articles from a wide range of Computing disciplines including hardware engineering, software engineering, information systems and information technology, encompassing the most basic research to the most innovative and radical ideas. Please submit your papers electronically to our submission system at http://IJRIC.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 IJRIC should be full research / review papers (properly indicated below main title in case of review paper).

International Journal of Reviews in Computing Volume 3 June 2010

Title	RSI RANGE DETERMINATION USING CUBICAL DISTANCE CLASSIFICATION
Authors	Dr. A. CLEMENTKING , S. SASIKALA
Abstract	Information processing and decision support system using data mining techniques is in advance drive for huge availability of remote sensing image (RSI). RSI describe inbuilt properties of objects by recording their supernatural reflectance in the electro-magnetic spectral (ems) region. Information on such objects could be gathered by their color properties or their spectral values in each ems range of pixels Present paper explains a method of such information extraction using cubical distance methods and the results are discussed. This method is one among the simpler in its approach and considers grouping of equal distance of similar from a specified point in the image or selected pixel based on its attributes. The color distance and the occurrence pixel distance are played vital role to determine the similar distance objects in the RSI.
Keywords	Cubical Distance Method, FIS, Color Map
Source	International Journal of Reviews in Computing Vol. 3
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Title	REVIEW OF ROUTING PROTOCOLS IN SENSOR AND ADHOC NETWORKS
Authors	SANJAY KUMAR PADHI, PRASANT KUMAR PATTNAIK, B.PUTHAL
Abstract	The use of wireless sensor networks (WSNs) has foreseen huge changes in data gathering, processing, and dissemination for various environments and specific applications. In current developments, the use of simulations for networks offers a feasible way to deign and improve routing protocols. Grouping sensor nodes into clusters has been used widely in order to achieve the network scalability objectives. Every cluster would have a leader, often referred to as the cluster-head. Although many clustering algorithms have been proposed in the literature for Wireless Networks, the objective was mainly to generate stable clusters in environments with mobile nodes. This paper, gives a review work done on existing protocols in wireless sensor and adhoc networks.
Keywords	Adhoc Network, Sensor Network, Clusters, Routing Protocols
Source	International Journal of Reviews in Computing Vol. 3
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Title	ADAPTIVE RESONANCE THEORY BASED SEDIMENTARY BASINS IDENTIFICATION
Authors	J.ASHOK, M.HUSSAIN, DR.E.G.RAJAN
Abstract	The objective of this paper is to present identification and recognition of Magneto-telluric data for sedimentary basins using Adaptive Resonance Theory (ART). Several sets of data consisting of 17 phases and 17 apparent resistivity values and their respective tag values are given. These sets of data are used for training the network, and other sets of data are used to test the network. The testing will result in the approximate identification of the data patterns with tag value of 1 where there is sediment of hydrocarbon and a tag value of 0 where there is no sediment of hydrocarbon in the given data set. Various techniques used in this experiment are creating the pattern files, normalizing the files, training the neural network, adjustment of weights and parameters, network file creation and finally testing of the field data for the pattern identification. The recognition rate in the proposed system lies between 95% to 100%.
Keywords	Neural Network, Adaptive Resonance Theory
Source	International Journal of Reviews in Computing Vol. 3
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Title	ARP PROTOCOL SEQUENCE ANALYSIS FOR INTRUSION DETECTION SYSTEM
Authors	D. PARAMESWARI, Dr. R.M. SURESH
Abstract	Information and communication technology facilitated the communication system in a sophisticated manner at the same time it challenges are increased from the illegal users. The communication process, user�s connectivity, violations of policy on access of information are handles through intrusion .Intrusion prevention is the process of performing intrusion detection and attempting to stop detected possible incidents. It focused on identifying possible incidents, logging information about them, attempting to stop them, and reporting them to security administrators. However, organizations use Intrusion detection and prevention system (IDPS) for other purposes, such as identifying problems with security policies, documenting existing threats, and deterring individuals from violating security policies. Now a days IDPSs have become a necessary addition to the security infrastructure of nearly every organization. In this paper describes about protocol sequences which is used to detect the intrusion on hybrid network and its attributes and recommend the standardized ARP protocol for the intrusion detection process.
Keywords	Network Intrusion Detection system, Protocol analysis, ARP sequence, ARP-NIDS
Source	International Journal of Reviews in Computing Vol. 3
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Title	SOFTWARE ERROR DETECTION AND CORRECTION (SEDC) USING LAYER BASED APPROACH IN EXPERT SYSTEM
Authors	M.S.JOSEPHINE, Dr. K.SANKARA SUBRAMANIAN
Abstract	An expert system is a computer program that simulates the judgment and behavior of a human or an organization that has expert knowledge and experience in a particular field. Typically, such a system contains a knowledge base containing accumulated experience and a set of rules for applying the knowledge base to each particular situation that is described to the program. Sophisticated expert systems can be enhanced with additions to the knowledge base or to the set of rules. A System called SEDC has been proposed and implemented with an aim to find the errors that encounter during the software development phases in integrated development environment. The main goal of this is to create an application that enables the end-user to use these error solutions in their application program that serves as an error correction mechanism while developing project. The project also comes up with an user-interaction environment which prompts the experts to provide expert solution for a particular error based on their expertise. Thus expert system is initiated with machine learning process of IDE.
Keywords	Expert System, Software Error Detection and Correction, IDE, Knowledge Capturing
Source	International Journal of Reviews in Computing Vol. 3
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Title	OPTIMAL DG PLACEMENT FOR MAXIMUM LOSS REDUCTION IN RADIAL DISTRIBUTION SYSTEM USING ABC ALGORITHM
Authors	M.PADMA LALITHA,N.SINARAMI REDDY, V.C. VEERA REDDY
Abstract	Distributed Generation (DG) is a promising solution to many power system problems such as voltage regulation, power loss, etc. This paper presents a new methodology using a new population based meta heuristic approach namely Artificial Bee Colony algorithm(ABC) for the placement of Distributed Generators(DG) in the radial distribution systems to reduce the real power losses and to improve the voltage profile. A two-stage methodology is used for the optimal DG placement . In the first stage, single DG placement method is used to find the optimal DG locations and in the second stage, ABC algorithm is used to find the sizes of the DGs corresponding to maximum loss reduction. The proposed method is tested on standard IEEE 33-bus test system and the results are presented and compared with different approaches available in the literature. The proposed method has outperformed the other methods in terms of the quality of solution and computational efficiency.
Keywords	DG Placement, Meta Heuristic Methods, ABC Algorithm, Loss Reduction, Radial Distribution System
Source	International Journal of Reviews in Computing Vol. 3
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Title	DEVELOPMENT OF AN ELECTRONIC COURSEWARE SYSTEM
Authors	OJESANMI O.A, OLUWASUSI T.O, AKINWUMI A.O, OMOTOSHO O, AKINPELU J.A
Abstract	In a typical lecture room, the lecturer dictates or gives notes to be photocopied, he does the same for tutorials, sets and gives test questions to students, who in turn write the tests and await their grades or scores. This manual system of classroom learning consumes time, energy, and sometimes money. An Electronic Courseware system can refer to an entire course and any additional material when used in reference an online or 'computer formatted' classroom. The term can also be used to describe the entire package consisting of one course bundled together with the various lecture notes, tests, and other material needed. This project made use of user friendly programming languages and tools such as PHP and HTML with Dreamweaver in the design of a user friendly E-courseware system. In conclusion, the Electronic courseware developed showed that Information Technology is a tool that can aid effective learning.
Keywords	Courseware, Delivery,Lecture Notes, Electronic, Classroom
Source	International Journal of Reviews in Computing Vol. 3
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Title	TEXT MINING: ADVANCEMENTS, CHALLENGES AND FUTURE DIRECTIONS
Authors	MAHESH T R, SURESH M B, M VINAYABABU
Abstract	Text mining, also known as text data mining or knowledge discovery from textual databases, refers to the process of extracting interesting and non-trivial patterns or knowledge from text documents. Regarded by many as the next wave of knowledge discovery, text mining has very high commercial values. Last count reveals that there are more than ten high-tech companies offering products for text mining. Has text mining evolved so rapidly to become a mature field? This article attempts to shed some lights to the question. We first present a text mining framework consisting of two components: Text refining that transforms unstructured text documents into an intermediate form; and knowledge distillation that deduces patterns or knowledge from the intermediate form. We then survey the state-of-the-art text mining products/applications and align them based on the text refining and knowledge distillation functions as well as the intermediate form that they adopt. In conclusion, we highlight the upcoming challenges of text mining and the opportunities it offers.
Keywords	Text Mining, Data Mining, Knowledge Discovery
Source	International Journal of Reviews in Computing Vol. 3
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Title	TAXONOMY OF CELL PLANNING
Authors	L.K.SHARMA , HEMRAJ SAINI , T.C.PANDA , H.N.PRATIHARI
Abstract	An extensive literature survey for cell planning has been provided in the manuscript with certain pros and cons of the discussed architectures. In addition the paper concentrates on the cell planning to reduce the cost of implementing the certain systems in the field of mobile communication with better efficiency and quality of service.
Keywords	Cell Planning, GSM, CDMA, 1G, 2G, 3G, 4G, 5G, BSC, BSS, MS
Source	International Journal of Reviews in Computing Vol. 3
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Title	ARTIFICIAL NEURAL NETWORKS FOR COMPRESSION OF DIGITAL IMAGES: A REVIEW
Authors	VENKATA RAMA PRASAD VADDELLA, KURUPATI RAMA
Abstract	Digital images require large amounts of memory for storage. Thus, the transmission of an image from one computer to another can be very time consuming. By using data compression techniques, it is possible to remove some of the redundant information contained in images, requiring less storage space and less time to transmit. Artificial Neural networks can be used for the purpose of image compression. Successful applications of neural networks to vector quantization have now become well established, and other aspects of neural networks for image compression are stepping up to play significant roles in assisting the traditional compression techniques. This paper discusses various neural network architectures for image compression. Among the architectures presented are the Kohonen self-organized maps (KSOM), Hierarchical Self-organized maps (HSOM), the Back-Propagation networks (BPN), Modular Neural networks (MNN), Wavelet neural Networks, Fractal Neural Networks, Predictive coding Neural Networks and Cellular Neural Networks (CNN). The architecture of these networks, and their performance issues are compared with those of the conventional compression techniques.
Keywords	Neural Networks, Image Compression,Vector Quantization
Source	International Journal of Reviews in Computing Vol. 3
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Title	MULTI AGENT-BASED DISTRIBUTED DATA MINING: AN OVER VIEW
Authors	VUDA SREENIVASA RAO
Abstract	Data mining technology has emerged as a means for identifying patterns and trends from large quantities of data. The Data Mining technology normally adopts data integration method to generate Data warehouse,on which to gather all data into a central site, and then run an algorithm against that data to extract the useful Module Prediction and knowledge evaluation. However, a single data-mining technique has not been proven appropriate for every domain and data set. Data mining techniques involving in such complex environment must encounter great dynamics due to changes in the system can affect the overall performance of the system. Agent computing whose aim is to deal with complex systems has revealed opportunities to improve distributed data mining systems in a number of ways. Multi-agent systems (MAS) often deal with complex applications that require distributed problem solving. In many applications the individual and collective behavior of the agents depends on the observed data from distributed sources. Distributed data mining is originated from the need of mining over decentralized data sources. The field of Distributed Data Mining (DDM) deals with these challenges in analyzing distributed data and offers many algorithmic solutions to perform different data analysis and mining operations in a fundamentally distributed manner that pays careful attention to the resource constraints. Since multi-agent systems are often distributed and agents have proactive and reactive features which are very useful for Knowledge Management Systems, combining DDM with MAS for data intensive applications is appealing. This paper the integration of multi-agent system and distributed data mining, also known as multi agent-based distributed data mining, in terms of significance, system overview, existing systems, and research trends.
Keywords	Distributed Data Mining, Multi-Agent Systems, Multi Agent Data Mining, Agent Based Distributed Data Mining
Source	International Journal of Reviews in Computing Vol. 3
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Title	AFFINE INVARIANT DESCRIPTORS AND RECOGNIZING OF 3D OBJECTS USING STATISTICS METHODS
Authors	M. ELHACHLOUFI , A. EL OIRRAK, D. ABOUTAJDINE , M.N. KADDIOUI
Abstract	The increasing number of objects 3D available on the Internet or in specialized databases which require the establishment of methods to develop description and recognition techniques to access intelligently to the contents of these objects. In this context, our work whose objective is to present the methods of invariant description [1,2,3] and recognition of 3D objects based on statistical methods: analysis of data (AD) and the principal component analysis (PCA). The objective of this studies is to determine an invariant description [4,5] of a 3D object using a coefficients vector of canonical correlations from the data analysis. This vector is invariant against affine transformation of the 3D object and recognize the object (s) of a database (3D objects) similar(s) to a given object (query object) using the descriptor vectors extracted from these 3D objects by the principal component analysis.The 3D objects of this database are transformations of 3D objects by one element of the overall transformation. The set of transformations considered in this work is the general affine group. The measure of similarity between two objects is achieved by a similarity function using the Euclidean distance.
Keywords	Invariants Descriptors, Recognizing, 3D objects, Multiple Regression, Principal Component Analysis, Affine Transformation
Source	International Journal of Reviews in Computing Vol. 3
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