archive-org.com » ORG » I » IJORCS.ORG Total: 231 Choose link from "Titles, links and description words view": Or switch to
"Titles and links view". |

- A Comparative Study on Distance Measuring Approaches for Clustering

distance measures for clustering and present a comparison between them based on application domain efficiency benefits and drawbacks This comparison helps the researchers to take quick decision about which distance measure to use for clustering We conclude this work by identifying trends and challenges of research and development towards clustering References Cited By Ankita Vimal Satyanarayana R Valluri Kamalakar Karlapalem An Experiment with Distance Measures for Clustering Technical Report IIIT TR 2008 132 John W Ratcliff and David E Metzener Pattern Matching The Gestalt Approach DR DOBB S JOURNAL 1998 p 46 Martin Ester Hans Peter Kriegel Jrg Sander and Xiaowei Xu A Density Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise AAAI Press 1996 pp 226 231 Bar Hilel A Hertz T Shental N Weinshall D 2003 Learning distance functions using equivalence Fukunaga K 1990 Statistical pattern recognition San Diego Academic Press 2nd edition Rui Xu Donald Wunsch Survey of Clustering Algorithms IEEE Transactions on Neural Networks VOL 16 NO 3 MAY 2005 doi 10 1109 TNN 2005 845141 http en wikipedia org wiki Data clustering http en wikipedia org wiki K means http en wikipedia org wiki DBSCAN http en wikipedia org wiki Jaccard index http en wikipedia org wiki Dice coefficient Kekre H B Tanuja K Sarode and Jagruti K Save Effect of Distance Measures on Transform Based Image Classification International Journal of Engineering Science and Technology 4 8 2012 Zhang Yu et al Encoding local binary descriptors by bag of features with hamming distance for visual object categorization Advances in Information Retrieval Springer Berlin Heidelberg 2013 630 641 Seitzer Phillip Tu Anh Huynh and Marc T Facciotti JContextExplorer a tree based approach to facilitate cross species genomic context comparison BMC bioinformatics 14 1 2013 18 Paskaleva Biliana and Pavel Bochev A vector space

Original URL path: http://www.ijorcs.org/manuscript/id/11/shraddha-pandit/distance-measuring-approaches-for-clustering (2016-05-01)

Open archived version from archive - Simulation of Generation of High Pressure and Temperature in Metals under Shock Loading

doi 10 7815 ijorcs 21 2011 009 Singh Dr V P Simulation of Generation of High Pressure and Temperature in Metals under Shock Loading International Journal of Research in Computer Science 2 1 2011 7 10 Web 1 May 2016 Singh Dr V P Simulation of Generation of High Pressure and Temperature in Metals under Shock Loading International Journal of Research in Computer Science 2 no 1 2011 7 10 doi 10 7815 ijorcs 21 2011 009 Close Abstract Pressure and Temperature in different metals including radioactive materials behind converging shock waves is simulated using generalized form of equation of state Tait s equation of state of metals is valid for pressures of the range of few mega bars and takes into account only elastic pressures At such high pressures metal undergo phase change and normal equation of state no more is valid At such pressures temperature in metals becomes very high and thermal and excitation pressures dominate over elastic pressure It is observed that as shock approaches the center of sphere excitation pressure dominates elastic as well as thermal pressure References Cited By H S Yadav and V P Singh Pramana 18 No 4 331 338 April 1982 Ya B Zeldovich et al Physics of shock waves and high temperature hydrodynamic phenomena Academic Press New York 1967 Ray Kinslow High velocity impact phenomena Academic Press New York 1970 R G Mcqueen S P Marsh et al The Equation of state of solids from shock wave studies page no 294 415 V N Zharkov et al Equations of state for solids at high pressures and temperatures Consultants Bureau New York 1971 V P Singh and Renuka DV Study of phase change in materials under high pressure J Appl Physics 86 no 9 1st Nov 99 pp 4881 4 V P

Original URL path: http://www.ijorcs.org/manuscript/id/9/dr-vp-singh/simulation-of-generation-of-high-pressure-and-temperature-in-metals-under-shock-loading (2016-05-01)

Open archived version from archive - Network Security using Linux Intrusion Detection System

The tool GRANT Global Real time Analysis of Network Traffic being a Linux based Intrusion Detection System LIDs takes the advantage of the security of a Linux box and secures the other nodes in the perimeter of the network It is capable of detecting intrusions and probes as and when they occur and capable of responding to already successful attacks thus causing minimal or no damage to the entire network For better performance this Linux Intrusion Detection System should be part of a defense in depth strategy such as Firewall and Intrusion Prevention References Cited By Rebecca Bace and Peter Mell Intrusion Detection System NIST special publication on Intrusion Detection System 2001 Jeff Reinhard Network Intrusion Detection System PenTele Data Palmerton Grant Users Manual GrantRelease 1 8 1 Hexa Bytes Pvt Ltd Harley Kozushko Intrusion Detection Host Based and Network Based Intrusion Detection Systems Independent Study 2003 Giovanni Vigna and Christopher Kruegel Host Based Intrusion Detection System WL041 Bidgoli WL041 Bidgoli cls June 15 2005 Vipin Das et al Network Intrusion Detection System Based On Machine Learning Algorithms International Journal of Computer Science Information Technology IJCSIT Vol 2 No 6 December 2010 Rafeeq Ur Rehman Intrusion Detection Systems with Snort Library of Congress Cataloging in Publication Data ISBN 0 13 140733 3 Tejinder Aulakh Intrusion Detection and Prevention System CGI Attacks The Faculty of the Department of Computer Science San Jose State University 2009 Sebastian Elbaum and John C Munson Intrusion Detection through Dynamic Software Measurement Proceedings of the Workshop on Intrusion Detection and Network Monitoring Santa Clara California USA April 9 12 1999 Taylor Merry Linux Kernel Hardening SANS Institute 2003 J R Winkler A Unix Prototype for Intrusion and Anomaly Detection in Secure Networks Proc 13th National Computer Security Conference pp 115 124 Washington D C Oct 1990

Original URL path: http://www.ijorcs.org/manuscript/id/12/arul-anitha/network-security-using-linux-intrusion-detection-system (2016-05-01)

Open archived version from archive - Introductory Approach on Ad-Hoc Networks and its Paradigms

Adhoc Network Protocols IJECT VOL 2 Issue 4 Oct Dec 2011 Online Available http www iject org vol2issue4 pra deep1 pdf Tseng Yu Chee Hsieh Ten Yueng Fully power aware and location aware protocols for wireless multi hop ad hoc networks proceedings of Eleventh International Conference on Computer communications and networks 2002 Kunagorn Kunavut Teerapat Sanguankotchakorn QoS aware routing for Mobile Ad hoc Networks Based on Multiple Metrics Connectivity Index CI and Delay ECTI CON 2010 Online Available http ieeexplore ieee org Xplore login jsp url http 3A 2F 2Fieeexplore ieee org 2Fiel5 2F5483296 2F5491394 2F05491536 pdf 3Farnumber 3D5491536 authDecision 203 Thriveni J Alekhya V L Deepa N Uma B Alice A Prakash G L K R Venugopal L M Patnaik QoS Preemptive Routing with Bandwidth Estimation for Improved Performance in Ad Hoc Networks 2008 IEEE doi 10 1109 ICIAFS 2008 4784005 Young Bae Ko and Nitin H Vaidya Location Aided Routing LAR in mobile ad hoc networks Wireless Networks 6 2000 J C Baltzer AG Science Publishers pp 307 321 Bevan Das Vaduvur Bharghavan Routing in Ad Hoc Networks Using Minimum Connected Dominating Sets 1997 IEEE p p376 doi 10 1109 ICC 1997 605303 Shigang Chen and Klara Nahrstedt Distributed Quality of Service Routing in Ad Hoc Networks IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS VOL 17 NO 8 AUGUST 1999 doi 10 1109 49 780354 Young Bae Ko and Nitin H Vaidya Location Aided Routing LAR in mobile ad hoc networks Wireless Networks 6 2000 307 321 J C Baltzer AG Science Publishers Lianggui Liu and Guangzeng FengL A Novel Ant Colony Based QoS Aware Routing Algorithm for MANETs Wang K Chen and Y S Ong Eds ICNC 2005 LNCS 3612 pp 457 466 2005 Springer Verlag Berlin Heidelberg 2005 Mohammad Reza EffatParvar Mehdi EffatParvar and Mahmoud Fathy Improvement of on Demand Multicast Routing Protocol in Ad Hoc Networks to Achieve Good Scalability and Reliability O Gervasi et al Eds ICCSA 2008 Part II LNCS 5073 pp 446 457 2008 Springer Verlag Berlin Heidelberg 2008 doi 10 1007 978 3 540 69848 7 37 Chi Hsiang Yeh DEAR An Extension of Traffic Engineering for Routing and Resource Management in Ad Hoc Wireless Networks VTC 2002 0 7803 7484 3 02 17 00 02002 IEEE Dong Lu Haitao Wu Qian Zhang Wenwu Zhu PARS Stimulating Cooperation for Power Aware Routing in Ad Hoc Networks 0 7803 8938 7 05 20 00 C 2005 IEEE Kai Zeng Kui Ren and Wenjing Lou Geographic On Demand Disjoint Multipath Routing in Wireless Ad Hoc Networks RADHIKA D JOSHI PRITI P REGE Distributed Energy Efficient Routing in Ad Hoc Networks 978 1 4244 3328 5 08 25 00 2008 IEEE L Boukhalfa P Minet and S Midonnet QoS Support in a MANET Based on OLSR and CBQ Proceedings of the Sixth International Conference on Networking ICN 07 April 2007 doi 10 1109 ICN 2007 77 Myung Jong Lee Jianling Zheng Xuhui Hu Hsin hui Juan Chunhui Zhu Yong Liu June Seung Yoon and

Original URL path: http://www.ijorcs.org/manuscript/id/20/mehtab-singh-kahlon/introductory-approach-on-ad-hoc-networks-and-its-paradigms (2016-05-01)

Open archived version from archive - Unification of Randomized Anomaly in Deception Detection using Fuzzy Logic under Uncertainty

V Narayani and Dr S P Victor Unification of Randomized Anomaly in Deception Detection using Fuzzy Logic under Uncertainty International Journal of Research in Computer Science 2 no 2 2012 7 14 doi 10 7815 ijorcs 22 2012 016 Close Abstract In the recent era of computer electronic communication we are currently facing the critical impact of Deception which plays its vital role in the mode of affecting efficient information sharing system Identifying Deception in any mode of communication is a tedious process without using the proper tool for detecting those vulnerabilities This paper deals with the efficient tools of Deception detection in which combined application implementation is our main focus rather than with its individuality We propose a research model which comprises Fuzzy logic Uncertainty and Randomization This paper deals with an experiment which implements the scenario of mixture application with its revealed results We also discuss the combined approach rather than with its individual performance References Cited By Alan Ryan Professional liars Truth Telling Lying and Self Deception Social Research Fall 1996 Bond c F A world of lies the global deception research team JournalofCrossculturePsychology 2006Vol 37 1 60 74 Burgoon J K and Qin T The Dynamic Nature of Deceptive Verbal Communication Journal of Language and Social Psychology 2006 vol25 1 1 22 doi 10 1177 0261927X05284482 Gupta Bina 1995 Perceiving in Advaita Vedanta Epistemological Analysis and Interpretation Delhi Motilal Banarsidass pp 197 ISBN 81 208 1296 4 Pennebaker J W Mehl M R Niederhoffer K Psychological aspects of natural language use our words ourselves Annual Review of Psychology 2003 54 547 577 Steve Woznaik L Simon 2002 The art of deception controlling the human element of security Wiley 1 edition Whissell C Fournier M Pelland R Weir D Makaree K A comparison of Classfiifcation methods for

Original URL path: http://www.ijorcs.org/manuscript/id/16/srajkumar/unification-of-randomized-anamoly-in-deception-detection-using-fuzzy-logic-under-uncertainty (2016-05-01)

Open archived version from archive - Multiple Linear Regression Models in Outlier Detection

databases is important both for improving the quality of original data and for reducing the impact of anomalous values in the process of knowledge discovery in databases Such anomalous values give useful information to the data analyst in discovering useful patterns Through isolation these data may be separated and analyzed The analysis of outliers and influential points is an important step of the regression diagnostics In this paper our aim is to detect the points which are very different from the others points They do not seem to belong to a particular population and behave differently If these influential points are to be removed it will lead to a different model Distinction between these points is not always obvious and clear Hence several indicators are used for identifying and analyzing outliers Existing methods of outlier detection are based on manual inspection of graphically represented data In this paper we present a new approach in automating the process of detecting and isolating outliers Impact of anomalous values on the dataset has been established by using two indicators DFFITS and Cook sD The process is based on modeling the human perception of exceptional values by using multiple linear regression analysis References Cited By Hawkins D Identification of Outliers Chapman and and Hall London 1980 Barnett V and Lewis T 1994 Outliers in Statistical Data John Wiley Sons 3rd edition Grubbs F E 1969 Procedures for detecting outlying observations in samples Technometrics 11 1 21 doi 10 1080 00401706 1969 10490657 Rousseeuw P and Leroy A 1996 Robust Regression and Outlier Detection John Wiley Sons 3rd edition Cook R D and Weisberg S T 1982 Residuals and influence in New York Chapman and Hall Abraham B and A Chuang Outlier Detection and Time Series Modelling Technometrics 1989 doi 10 1080 00401706 1989 10488517

Original URL path: http://www.ijorcs.org/manuscript/id/18/smakhaleelur-rahman/multiple-linear-regression-models-in-outlier-detection (2016-05-01)

Open archived version from archive - Adoption of Parallel Genetic Algorithms for the Solution of System of Equations

require modeling the system as set of simultaneous linear non linear equations and generating solutions to satisfy the system of equations Analytical approach towards solving the system of equations remains practical so long as considerable constraints are imposed on the modeled system to bring in significant simplicity so as to retain the system model within the scope of defined algorithms for solving system of equations The current work adopts the concept of genetic algorithm towards evolving a solution to a system of equations The fundamental strength of genetic algorithms lies in the fact the solution generation is practically unconstrained permitting the methodology to become the superset for all possible realizable problems One of the oft repeated and highlighted drawbacks of genetic algorithm i e requirements of huge initial population and corresponding extended number of computations and hence time is addressed by exploiting multi processing capabilities of the current generation hardware as well as system software Adopted strategy for selecting the best population implementation flow chart along with a case study is presented References Cited By Wang D and Zhiming Z Differential equations with symbolic computation Birkhauser Basel 2005 doi 10 1007 3 7643 7429 2 Versteeg H and Malalasekara W An introduction to computational fluid dynamics The finite volume method Pearson 2008 Smith I M and Griffiths D V Programming the finite element method John Wiley Sons 2004 Hayt W H Kemmerly J E and Durbin S M Engineering Circuits Analysis Tata McGraw Hill Education 2006 Chapra S and Canale R Numerical Methods for Engineers McGraw Hill Higher Education 2009 Hamming R W Numerical methods for scientists and engineers Dover Publications 1973 Sarkar T Siarkiewicz K and Stratton R Survey of numerical methods for solution of large systems of linear equations for electromagnetic field problems IEEE Transactions on Antennas and

Original URL path: http://www.ijorcs.org/manuscript/id/15/shilpa-s-babalad/adoption-of-parallel-genetic-algorithms-for-the-solution-of-system-of-equations (2016-05-01)

Open archived version from archive - Image Denoising using Wavelet Transform and various Filters

Signal Processing Letters IEEE Volume 10 Issue 11 Nov 2003 265 Vol 3 doi 10 1109 LSP 2003 818225 Wavelet Shrinkage and W V D A 10 minute Tour Donoho D L David L Donoho s website William K Pratt Digital Image Processing Wiley 1991 Image Denoising using Wavelet Thresholding and Model Selection Shi Zhong Image Processing 2000 Proceedings 2000 International Conference on Volume 3 10 13 Sept 2000 Pages 262 doi 10 1109 ICIP 2000 899345 Charles Boncelet 2005 Image Noise Models in Alan C Bovik Handbook of Image and Video Processing doi 10 1016 B978 012119792 6 50087 5 R C Gonzalez and R Elwood s Digital Image Processing Reading MA Addison Wesley 1993 M Sonka V Hlavac R Boyle Image Processing Analysis AndMachine Vision Pp10 210 646 670 Raghuveer M Rao A S Bopardikar Wavelet Transforms Introduction To Theory And Application Published By Addison Wesley 2001 pp1 126 Arthur Jr Weeks Fundamental of Electronic Image Processing Jaideva Goswami Andrew K Chan Fundamentals Of Wavelets Theory Algorithms And Applications John Wiley Sons Portilla J Strela V Wainwright M Simoncelli E P Image Denoising using Gaussian Scale Mixturesin the Wavelet Domain TR2002 831 ComputerScience Dept New York University 2002 Martin Vetterli S Grace Chang Bin Yu Adaptive wavelet thresholding for image denoising and compression IEEE Transactions on Image Processing 9 9 1532 1546 Sep 2000 doi 10 1109 83 862633 Zhou Wang Member IEEE Alan Conrad Bovik Fellow IEEE Hamid Rahim Sheikh Student Member IEEE and Eero P Simoncelli Senior Member IEEE Image Quality Assessment From error visibility to structural similarity IEEE transactions on image processing vol 13 no 4 April 2004 doi 10 1109 TIP 2003 819861 Tinku Acharya Ajoy K Ray IMAGE PROCESSING Principles and Applications Hoboken New Jersey A JOHN WILEY SONS MC Publication 2005 doi 10 1002 0471745790 S Poornachandra Wavelet based denoising using subband dependent threshold for ECG signals Digital Signal Processing vol 18 pp 49 55 2008 Rioul O and Vetterli M Wavelets and Signal Processing IEEE Signal Processing Magazine October 1991 pp 14 38 doi 10 1109 79 91217 Ingrid Daubechies Ten Lectures on Wavelets CBMS NSF Regional Conference Series in Applied Mathematics Vol 61 SIAM Philadelphia 1992 doi 10 1137 1 9781611970104 Ruskai M B et al Wavelet and Their Applications 1992 M Antonini M Barlaud P Mathieu and I Daubechies Image coding using wavelet transform IEEE Trans Image Process vol 1 no 2 pp 205 220 Apr 1992 doi 10 1109 83 136597 J Woods and J Kim Image identification and restoration in the sub band domain in Proceedings IEEE Int Conference on Acoustics Speech and Signal Processing San Francisco CA vol III pp 297 300 Mar 1992 doi 10 1109 ICASSP 1992 226242 T L Ji M K Sundareshan and H Roehrig Adaptive Image Contrast Enhancement Based on Human Visual Properties IEEE Transactions on Medical Imaging VOL 13 NO 4 December 1994 IEEE doi 10 1109 42 363111 M R Banham Wavelet Based Image Restoration Techniques Ph D Thesis

Original URL path: http://www.ijorcs.org/manuscript/id/17/gurmeet-kaur/image-denoising-using-wavelet-transform-and-various-filters (2016-05-01)

Open archived version from archive