international journal of soft computing and engineering · volume-1 issue-2, may 2011 published by:...
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International Journal of Soft Computing and EngineeringInternational Journal of Soft Computing and EngineeringInternational Journal of Soft Computing and Engineering
n E d n g i na e g e n i r t i n u g p m o C t f o S I n f t eo l r n a a n r t i u o o n J a l
IJSCEIJSCE
Exploring Innovation
www.ijsce.org
EXPLORING INNOVA
TION
ISSN : 2231 - 2307Website: www.ijsce.org
Volume-1 Issue-2, May 2011Volume-1 Issue-2, May 2011
Published by: Blue Eyes Intelligence Engineering and Sciences Publication Pvt. Ltd.
Published by: Blue Eyes Intelligence Engineering and Sciences Publication Pvt. Ltd.
Editor In Chief
Dr. Shiv K Sahu
Ph.D. (CSE), M.Tech. (IT, Honors), B.Tech. (IT)
Director, Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd., Bhopal (M.P.), India
Dr. Shachi Sahu
Ph.D. (Chemistry), M.Sc. (Organic Chemistry)
Additional Director, Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd., Bhopal (M.P.), India
Vice Editor In Chief
Dr. Vahid Nourani
Professor, Faculty of Civil Engineering, University of Tabriz, Iran
Prof.(Dr.) Anuranjan Misra
Professor & Head, Computer Science & Engineering and Information Technology & Engineering, Noida International University,
Noida (U.P.), India
Chief Advisory Board
Prof. (Dr.) Hamid Saremi
Vice Chancellor of Islamic Azad University of Iran, Quchan Branch, Quchan-Iran
Dr. Uma Shanker
Professor & Head, Department of Mathematics, CEC, Bilaspur(C.G.), India
Dr. Rama Shanker
Professor & Head, Department of Statistics, Eritrea Institute of Technology, Asmara, Eritrea
Dr. Vinita Kumari
Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd., India
Dr. Kapil Kumar Bansal
Head (Research and Publication), SRM University, Gaziabad (U.P.), India
Dr. Deepak Garg
Professor, Department of Computer Science and Engineering, Thapar University, Patiala (Punjab), India, Senior Member of IEEE,
Secretary of IEEE Computer Society (Delhi Section), Life Member of Computer Society of India (CSI), Indian Society of Technical
Education (ISTE), Indian Science Congress Association Kolkata.
Dr. Vijay Anant Athavale
Director of SVS Group of Institutions, Mawana, Meerut (U.P.) India/ U.P. Technical University, India
Dr. T.C. Manjunath
Principal & Professor, HKBK College of Engg, Nagawara, Arabic College Road, Bengaluru-560045, Karnataka, India
Dr. Kosta Yogeshwar Prasad
Director, Technical Campus, Marwadi Education Foundation’s Group of Institutions, Rajkot-Morbi Highway, Gauridad, Rajkot,
Gujarat, India
Dr. Dinesh Varshney
Director of College Development Counceling, Devi Ahilya University, Indore (M.P.), Professor, School of Physics, Devi Ahilya
University, Indore (M.P.), and Regional Director, Madhya Pradesh Bhoj (Open) University, Indore (M.P.), India
Dr. P. Dananjayan
Professor, Department of Department of ECE, Pondicherry Engineering College, Pondicherry,India
Dr. Sadhana Vishwakarma
Associate Professor, Department of Engineering Chemistry, Technocrat Institute of Technology, Bhopal(M.P.), India
Dr. Kamal Mehta
Associate Professor, Deptment of Computer Engineering, Institute of Technology, NIRMA University, Ahmedabad (Gujarat), India
Dr. CheeFai Tan
Faculty of Mechanical Engineering, University Technical, Malaysia Melaka, Malaysia
Dr. Suresh Babu Perli
Professor& Head, Department of Electrical and Electronic Engineering, Narasaraopeta Engineering College, Guntur, A.P., India
Dr. Binod Kumar
Associate Professor, Schhool of Engineering and Computer Technology, Faculty of Integrative Sciences and Technology, Quest
International University, Ipoh, Perak, Malaysia
Dr. Chiladze George
Professor, Faculty of Law, Akhaltsikhe State University, Tbilisi University, Georgia
Dr. Kavita Khare
Professor, Department of Electronics & Communication Engineering., MANIT, Bhopal (M.P.), INDIA
Dr. C. Saravanan
Associate Professor (System Manager) & Head, Computer Center, NIT, Durgapur, W.B. India
Dr. S. Saravanan
Professor, Department of Electrical and Electronics Engineering, Muthayamal Engineering College, Resipuram, Tamilnadu, India
Dr. Amit Kumar Garg
Professor & Head, Department of Electronics and Communication Engineering, Maharishi Markandeshwar University, Mulllana,
Ambala (Haryana), India
Dr. T.C.Manjunath
Principal & Professor, HKBK College of Engg, Nagawara, Arabic College Road, Bengaluru-560045, Karnataka, India
Dr. P. Dananjayan
Professor, Department of Department of ECE, Pondicherry Engineering College, Pondicherry, India
Dr. Kamal K Mehta
Associate Professor, Department of Computer Engineering, Institute of Technology, NIRMA University, Ahmedabad (Gujarat), India
Dr. Rajiv Srivastava
Director, Department of Computer Science & Engineering, Sagar Institute of Research & Technology, Bhopal (M.P.), India
Dr. Chakunta Venkata Guru Rao
Professor, Department of Computer Science & Engineering, SR Engineering College, Ananthasagar, Warangal, Andhra Pradesh, India
Dr. Anuranjan Misra
Professor, Department of Computer Science & Engineering, Bhagwant Institute of Technology, NH-24, Jindal Nagar, Ghaziabad,
India
Dr. Robert Brian Smith
International Development Assistance Consultant, Department of AEC Consultants Pty Ltd, AEC Consultants Pty Ltd, Macquarie
Centre, North Ryde, New South Wales, Australia
Dr. Saber Mohamed Abd-Allah
Associate Professor, Department of Biochemistry, Shanghai Institute of Biochemistry and Cell Biology, Yue Yang Road, Shanghai,
China
Dr. Himani Sharma
Professor & Dean, Department of Electronics & Communication Engineering, MLR Institute of Technology, Laxman Reddy Avenue,
Dundigal, Hyderabad, India
Dr. Sahab Singh
Associate Professor, Department of Management Studies, Dronacharya Group of Institutions, Knowledge Park-III, Greater Noida,
India
Dr. Umesh Kumar
Principal: Govt Women Poly, Ranchi, India
Dr. Syed Zaheer Hasan
Scientist-G Petroleum Research Wing, Gujarat Energy Research and Management Institute, Energy Building, Pandit Deendayal
Petroleum University Campus, Raisan, Gandhinagar-382007, Gujarat, India.
Dr. Jaswant Singh Bhomrah
Director, Department of Profit Oriented Technique, 1 – B Crystal Gold, Vijalpore Road, Navsari 396445, Gujarat. India
Technical Advisory Board
Dr. Mohd. Husain
Director, MG Institute of Management & Technology, Banthara, Lucknow (U.P.), India
Dr. T. Jayanthy
Principal, Panimalar Institute of Technology, Chennai (TN), India
Dr. Umesh A.S.
Director, Technocrats Institute of Technology & Science, Bhopal(M.P.), India
Dr. B. Kanagasabapathi
Infosys Labs, Infosys Limited, Center for Advance Modeling and Simulation, Infosys Labs, Infosys Limited, Electronics City,
Bangalore, India
Dr. C.B. Gupta
Professor, Department of Mathematics, Birla Institute of Technology & Sciences, Pilani (Rajasthan), India
Dr. Sunandan Bhunia
Associate Professor & Head,, Dept. of Electronics & Communication Engineering, Haldia Institute of Technology, Haldia, West
Bengal, India
Dr. Jaydeb Bhaumik
Associate Professor, Dept. of Electronics & Communication Engineering, Haldia Institute of Technology, Haldia, West Bengal, India
Dr. Rajesh Das
Associate Professor, School of Applied Sciences, Haldia Institute of Technology, Haldia, West Bengal, India
Dr. Mrutyunjaya Panda
Professor & Head, Department of EEE, Gandhi Institute for Technological Development, Bhubaneswar, Odisha, India
Dr. Mohd. Nazri Ismail
Associate Professor, Department of System and Networking, University of Kuala (UniKL), Kuala Lumpur, Malaysia
Dr. Haw Su Cheng
Faculty of Information Technology, Multimedia University (MMU), Jalan Multimedia, 63100 Cyberjaya
Dr. Hossein Rajabalipour Cheshmehgaz
Industrial Modeling and Computing Department, Faculty of Computer Science and Information Systems, Universiti Teknologi
Malaysia (UTM) 81310, Skudai, Malaysia
Dr. Sudhinder Singh Chowhan
Associate Professor, Institute of Management and Computer Science, NIMS University, Jaipur (Rajasthan), India
Dr. Neeta Sharma
Professor & Head, Department of Communication Skils, Technocrat Institute of Technology, Bhopal(M.P.), India
Dr. Ashish Rastogi
Associate Professor, Department of CSIT, Guru Ghansi Das University, Bilaspur (C.G.), India
Dr. Santosh Kumar Nanda
Professor, Department of Computer Science and Engineering, Eastern Academy of Science and Technology (EAST), Khurda (Orisa),
India
Dr. Hai Shanker Hota
Associate Professor, Department of CSIT, Guru Ghansi Das University, Bilaspur (C.G.), India
Dr. Sunil Kumar Singla
Professor, Department of Electrical and Instrumentation Engineering, Thapar University, Patiala (Punjab), India
Dr. A. K. Verma
Professor, Department of Computer Science and Engineering, Thapar University, Patiala (Punjab), India
Dr. Durgesh Mishra
Chairman, IEEE Computer Society Chapter Bombay Section, Chairman IEEE MP Subsection, Professor & Dean (R&D), Acropolis
Institute of Technology, Indore (M.P.), India
Dr. Xiaoguang Yue
Associate Professor, College of Computer and Information, Southwest Forestry University, Kunming (Yunnan), China
Dr. Veronica Mc Gowan
Associate Professor, Department of Computer and Business Information Systems,Delaware Valley College, Doylestown, PA, Allman
China
Dr. Mohd. Ali Hussain
Professor, Department of Computer Science and Engineering, Sri Sai Madhavi Institute of Science & Technology, Rajahmundry
(A.P.), India
Dr. Mohd. Nazri Ismail
Professor, System and Networking Department, Jalan Sultan Ismail, Kaula Lumpur, MALAYSIA
Dr. Sunil Mishra
Associate Professor, Department of Communication Skills (English), Dronacharya College of Engineering, Farrukhnagar, Gurgaon
(Haryana), India
Dr. Labib Francis Gergis Rofaiel
Associate Professor, Department of Digital Communications and Electronics, Misr Academy for Engineering and Technology,
Mansoura City, Egypt
Dr. Pavol Tanuska
Associate Professor, Department of Applied Informetics, Automation, and Mathematics, Trnava, Slovakia
Dr. VS Giridhar Akula
Professor, Avanthi's Research & Technological Academy, Gunthapally, Hyderabad, Andhra Pradesh, India
Dr. S. Satyanarayana
Associate Professor, Department of Computer Science and Engineering, KL University, Guntur, Andhra Pradesh, India
Dr. Bhupendra Kumar Sharma
Associate Professor, Department of Mathematics, KL University, BITS, Pilani, India
Dr. Praveen Agarwal
Associate Professor& Head, Department of Mathematics, Anand International College of Engineering, Jaipur (Rajasthan), India
Dr. Manoj Kumar
Professor, Department of Mathematics, Rashtriya Kishan Post Graduate Degree, College, Shamli, Prabudh Nagar, (U.P.), India
Dr. Shaikh Abdul Hannan
Associate Professor, Department of Computer Science, Vivekanand Arts Sardar Dalipsing Arts and Science College, Aurangabad
(Maharashtra), India
Dr. K.M. Pandey
Professor, Department of Mechanical Engineering,National Institute of Technology, Silchar, India
Prof. Pranav Parashar
Technical Advisor, International Journal of Soft Computing and Engineering (IJSCE), Bhopal (M.P.), India
Dr. Biswajit Chakraborty
MECON Limited, Research and Development Division (A Govt. of India Enterprise), Ranchi-834002, Jharkhand, India
Dr. D.V. Ashoka
Professor & Head, Department of Information Science & Engineering, SJB Institute of Technology, Kengeri, Bangalore, India
Dr. Sasidhar Babu Suvanam
Professor & Academic Cordinator, Department of Computer Science & Engineering, Sree Narayana Gurukulam College of
Engineering, Kadayiuruppu, Kolenchery, Kerala, India
Dr. C. Venkatesh
Professor & Dean, Faculty of Engineering, EBET Group of Institutions, Kangayam, Erode, Caimbatore (Tamil Nadu), India
Dr. Nilay Khare
Assoc. Professor & Head, Department of Computer Science, MANIT, Bhopal (M.P.), India
Dr. Sandra De Iaco
Professor, Dip.to Di Scienze Dell’Economia-Sez. Matematico-Statistica, Italy
Dr. Yaduvir Singh
Associate Professor, Department of Computer Science & Engineering, Ideal Institute of Technology, Govindpuram Ghaziabad,
Lucknow (U.P.), India
Dr. Angela Amphawan
Head of Optical Technology, School of Computing, School Of Computing, Universiti Utara Malaysia, 06010 Sintok, Kedah, Malaysia
Dr. Ashwini Kumar Arya
Associate Professor, Department of Electronics & Communication Engineering, Faculty of Engineering and Technology,Graphic Era
University, Dehradun (U.K.), India
Dr. Yash Pal Singh
Professor, Department of Electronics & Communication Engg, Director, KLS Institute Of Engg.& Technology, Director, KLSIET,
Chandok, Bijnor, (U.P.), India
Dr. Ashish Jain
Associate Professor, Department of Computer Science & Engineering, Accurate Institute of Management & Technology, Gr. Noida
(U.P.), India
Dr. Abhay Saxena
Associate Professor&Head, Department. of Computer Science, Dev Sanskriti University, Haridwar, Uttrakhand, India
Dr. Judy. M.V
Associate Professor, Head of the Department CS &IT, Amrita School of Arts and Sciences, Amrita Vishwa Vidyapeetham,
Brahmasthanam, Edapally, Cochin, Kerala, India
Dr. Sangkyun Kim
Professor, Department of Industrial Engineering, Kangwon National University, Hyoja 2 dong, Chunche0nsi, Gangwondo, Korea
Dr. Sanjay M. Gulhane
Professor, Department of Electronics & Telecommunication Engineering, Jawaharlal Darda Institute of Engineering & Technology,
Yavatmal, Maharastra, India
Dr. K.K. Thyagharajan
Principal & Professor, Department of Informational Technology, RMK College of Engineering & Technology, RSM Nagar,
Thiruyallur, Tamil Nadu, India
Dr. P. Subashini
Asso. Professor, Department of Computer Science, Coimbatore, India
Dr. G. Srinivasrao
Professor, Department of Mechanical Engineering, RVR & JC, College of Engineering, Chowdavaram, Guntur, India
Dr. Rajesh Verma
Professor, Department of Computer Science & Engg. and Deptt. of Information Technology, Kurukshetra Institute of Technology &
Management, Bhor Sadian, Pehowa, Kurukshetra (Haryana), India
Dr. Pawan Kumar Shukla
Associate Professor, Satya College of Engineering & Technology, Haryana, India
Dr. U C Srivastava
Associate Professor, Department of Applied Physics, Amity Institute of Applied Sciences, Amity University, Noida, India
Dr. Reena Dadhich
Prof.& Head, Department of Computer Science and Informatics, MBS MArg, Near Kabir Circle, University of Kota, Rajasthan, India
Dr. Aashis.S.Roy
Department of Materials Engineering, Indian Institute of Science, Bangalore Karnataka, India
Dr. Sudhir Nigam
Professor Department of Civil Engineering, Principal, Lakshmi Narain College of Technology and Science, Raisen, Road, Bhopal,
(M.P.), India
Dr. S.Senthilkumar
Doctorate, Department of Center for Advanced Image and Information Technology, Division of Computer Science and Engineering,
Graduate School of Electronics and Information Engineering, Chon Buk National University Deok Jin-Dong, Jeonju, Chon Buk, 561-
756, South Korea Tamilnadu, India
Dr. Gufran Ahmad Ansari
Associate Professor, Department of Information Technology, College of Computer, Qassim University, Al-Qassim, Kingdom of
Saudi Arabia (KSA)
Dr. R.Navaneethakrishnan
Associate Professor, Department of MCA, Bharathiyar College of Engg & Tech, Karaikal Puducherry, India
Dr. Hossein Rajabalipour Cheshmejgaz
Industrial Modeling and Computing Department, Faculty of Computer Science and Information Systems, Universiti Teknologi Skudai,
Malaysia
Dr. Veronica McGowan
Associate Professor, Department of Computer and Business Information Systems, Delaware Valley College, Doylestown, PA, Allman
China
Dr. Sanjay Sharma
Associate Professor, Department of Mathematics, Bhilai Institute of Technology, Durg, Chhattisgarh, India
Dr. Taghreed Hashim Al-Noor
Professor, Department of Chemistry, Ibn-Al-Haitham Education for pure Science College, University of Baghdad, Iraq
Dr. Madhumita Dash
Professor, Department of Electronics & Telecommunication, Orissa Engineering College , Bhubaneswar,Odisha, India
Dr. Anita Sagadevan Ethiraj
Associate Professor, Department of Centre for Nanotechnology Research (CNR), School of Electronics Engineering (Sense), Vellore
Institute of Technology (VIT) University, Tamilnadu, India
Dr. Sibasis Acharya
Project Consultant, Department of Metallurgy & Mineral Processing, Midas Tech International, 30 Mukin Street, Jindalee-4074,
Queensland, Australia
Dr. Neelam Ruhil
Professor, Department of Electronics & Computer Engineering, Dronacharya College of Engineering, Gurgaon, Haryana, India
Dr. Faizullah Mahar
Professor, Department of Electrical Engineering, Balochistan University of Engineering and Technology, Pakistan
Dr. K. Selvaraju
Head, PG & Research, Department of Physics, Kandaswami Kandars College (Govt. Aided), Velur (PO), Namakkal DT. Tamil Nadu,
India
Dr. M. K. Bhanarkar
Associate Professor, Department of Electronics, Shivaji University, Kolhapur, Maharashtra, India
Dr. Sanjay Hari Sawant
Professor, Department of Mechanical Engineering, Dr. J. J. Magdum College of Engineering, Jaysingpur, India
Dr. Arindam Ghosal
Professor, Department of Mechanical Engineering, Dronacharya Group of Institutions, B-27, Part-III, Knowledge Park,Greater Noida,
India
Dr. M. Chithirai Pon Selvan
Associate Professor, Department of Mechanical Engineering, School of Engineering & Information Technology, Amity University,
Dubai, UAE
Dr. S. Sambhu Prasad
Professor & Principal, Department of Mechanical Engineering, Pragati College of Engineering, Andhra Pradesh, India.
Dr. Muhammad Attique Khan Shahid
Professor of Physics & Chairman, Department of Physics, Advisor (SAAP) at Government Post Graduate College of Science,
Faisalabad.
Dr. Kuldeep Pareta
Professor & Head, Department of Remote Sensing/GIS & NRM, B-30 Kailash Colony, New Delhi 110 048, India
Dr. Th. Kiranbala Devi
Associate Professor, Department of Civil Engineering, Manipur Institute of Technology, Takyelpat, Imphal, Manipur, India
Dr. Nirmala Mungamuru
Associate Professor, Department of Computing, School of Engineering, Adama Science and Technology University, Ethiopia
Dr. Srilalitha Girija Kumari Sagi
Associate Professor, Department of Management, Gandhi Institute of Technology and Management, India
Dr. Vishnu Narayan Mishra
Associate Professor, Department of Mathematics, Sardar Vallabhbhai National Institute of Technology, Ichchhanath Mahadev Dumas
Road, Surat (Gujarat), India
Dr. Yash Pal Singh
Director/Principal, Somany (P.G.) Institute of Technology & Management, Garhi Bolni Road , Rewari Haryana, India.
Dr. Sripada Rama Sree
Vice Principal, Associate Professor, Department of Computer Science and Engineering, Aditya Engineering College, Surampalem,
Andhra Pradesh. India.
Dr. Rustom Mamlook
Associate Professor, Department of Electrical and Computer Engineering, Dhofar University, Salalah, Oman. Middle East.
Dr. Ramzi Raphael Ibraheem Al Barwari
Assistant Professor, Department of Mechanical Engineering, College of Engineering, Salahaddin University – Hawler (SUH) Erbil –
Kurdistan, Erbil Iraq.
Dr. Kapil Chandra Agarwal
H.O.D. & Professor, Department of Applied Sciences & Humanities, Radha Govind Engineering College, U. P. Technical University,
Jai Bheem Nagar, Meerut, (U.P). India.
Dr. Anil Kumar Tripathy
Associate Professor, Department of Environmental Science & Engineering, Ghanashyama Hemalata Institute of Technology and
Management, Puri Odisha, India.
Managing Editor
Mr. Jitendra Kumar Sen
International Journal of Soft Computing and Engineering (IJSCE)
Editorial Board
Dr. Soni Changlani
Professor, Department of Electronics & Communication, Lakshmi Narain College of Technology & Science, Bhopal (.M.P.), India
Dr. M .M. Manyuchi
Professor, Department Chemical and Process Systems Engineering, Lecturer-Harare Institute of Technology, Zimbabwe
Dr. John Kaiser S. Calautit
Professor, Department Civil Engineering, School of Civil Engineering, University of Leeds, LS2 9JT, Leeds, United Kingdom
Dr. Audai Hussein Al-Abbas
Deputy Head, Department AL-Musaib Technical College/ Foundation of Technical Education/Babylon, Iraq
Dr. Şeref Doğuşcan Akbaş
Professor, Department Civil Engineering, Şehit Muhtar Mah. Öğüt Sok. No:2/37 Beyoğlu Istanbul, Turkey
Dr. H S Behera
Associate Professor, Department Computer Science & Engineering, Veer Surendra Sai University of Technology (VSSUT) A Unitary
Technical University Established by the Government of Odisha, India
Dr. Rajeev Tiwari
Associate Professor, Department Computer Science & Engineering, University of Petroleum & Energy Studies (UPES), Bidholi,
Uttrakhand, India
Dr. Piyush Kumar Shukla
Assoc. Professor, Department of Computer Science and Engineering, University Institute of Technology, RGPV, Bhopal (M.P.), India
Dr. Piyush Lotia
Assoc.Professor, Department of Electronics and Instrumentation, Shankaracharya College of Engineering and Technology, Bhilai
(C.G.), India
Dr. Asha Rai
Assoc. Professor, Department of Communication Skils, Technocrat Institute of Technology, Bhopal (M.P.), India
Dr. Vahid Nourani
Assoc. Professor, Department of Civil Engineering, University of Minnesota, USA
Dr. Hung-Wei Wu
Assoc. Professor, Department of Computer and Communication, Kun Shan University, Taiwan
Dr. Vuda Sreenivasarao
Associate Professor, Department of Computr And Information Technology, Defence University College, Debrezeit Ethiopia, India
Dr. Sanjay Bhargava
Assoc. Professor, Department of Computer Science, Banasthali University, Jaipur, India
Dr. Sanjoy Deb
Assoc. Professor, Department of ECE, BIT Sathy, Sathyamangalam, Tamilnadu, India
Dr. Papita Das (Saha)
Assoc. Professor, Department of Biotechnology, National Institute of Technology, Duragpur, India
Dr. Waail Mahmod Lafta Al-waely
Assoc. Professor, Department of Mechatronics Engineering, Al-Mustafa University College – Plastain Street near AL-SAAKKRA
square- Baghdad - Iraq
Dr. P. P. Satya Paul Kumar
Assoc. Professor, Department of Physical Education & Sports Sciences, University College of Physical Education & Sports Sciences,
Guntur
Dr. Sohrab Mirsaeidi
Associate Professor, Department of Electrical Engineering, Universiti Teknologi Malaysia (UTM), Skudai, Johor, Malaysia
Dr. Ehsan Noroozinejad Farsangi
Associate Professor, Department of Civil Engineering, International Institute of Earthquake Engineering and Seismology (IIEES)
Farmanieh, Tehran - Iran
Dr. Omed Ghareb Abdullah
Associate Professor, Department of Physics, School of Science, University of Sulaimani, Iraq
Dr. Khaled Eskaf
Associate Professor, Department of Computer Engineering, College of Computing and Information Technology, Alexandria, Egypt
Dr. Nitin W. Ingole
Associate Professor & Head, Department of Civil Engineering, Prof Ram Meghe Institute of Technology and Research, Badnera
Amravati
Dr. P. K. Gupta
Associate Professor, Department of Computer Science and Engineering, Jaypee University of Information Technology, P.O. Dumehar
Bani, Solan, India
Dr. P.Ganesh Kumar
Associate Professor, Department of Electronics & Communication, Sri Krishna College of Engineering and Technology, Linyi Top
Network Co Ltd Linyi , Shandong Provience, China
Dr. Santhosh K V
Associate Professor, Department of Instrumentation and Control Engineering, Manipal Institute of Technology, Manipal, Karnataka,
India
Dr. Subhendu Kumar Pani
Assoc. Professor, Department of Computer Science and Engineering, Orissa Engineering College, India
Dr. Syed Asif Ali
Professor/ Chairman, Department of Computer Science, SMI University, Karachi, Pakistan
Dr. Vilas Warudkar
Assoc. Professor, Department of Mechanical Engineering, Maulana Azad National Institute of Technology, Bhopal, India
Dr. S. Chandra Mohan Reddy
Associate Professor & Head, Department of Electronics & Communication Engineering, JNTUA College of Engineering
(Autonomous), Cuddapah, Andhra Pradesh, India
Dr. V. Chittaranjan Das
Associate Professor, Department of Mechanical Engineering, R.V.R. & J.C. College of Engineering, Guntur, Andhra Pradesh, India
Dr. Jamal Fathi Abu Hasna
Associate Professor, Department of Electrical & Electronics and Computer Engineering, Near East University, TRNC, Turkey
Dr. S. Deivanayaki
Associate Professor, Department of Physics, Sri Ramakrishna Engineering College, Tamil Nadu, India
Dr. Nirvesh S. Mehta
Professor, Department of Mechanical Engineering, Sardar Vallabhbhai National Institute of Technology, Surat, South Gujarat, India
Dr. A.Vijaya Bhasakar Reddy
Associate Professor, Research Scientist, Department of Chemistry, Sri Venkateswara University, Andhra Pradesh, India
Dr. C. Jaya Subba Reddy
Associate Professor, Department of Mathematics, Sri Venkateswara University Tirupathi Andhra Pradesh, India
Dr. TOFAN Cezarina Adina
Associate Professor, Department of Sciences Engineering, Spiru Haret University, Arges, Romania
Dr. Balbir Singh
Associate Professor, Department of Health Studies, Human Development Area, Administrative Staff College of India, Bella Vista,
Andhra Pradesh, India
Dr. D. RAJU
Associate Professor, Department of Mathematics, Vidya Jyothi Institute of Technology (VJIT), Aziz Nagar Gate, Hyderabad, India
Dr. Salim Y. Amdani
Associate Professor & Head, Department of Computer Science Engineering, B. N. College of Engineering, PUSAD, (M.S.), India
Dr. K. Kiran Kumar
Associate Professor, Department of Information Technology, Bapatla Engineering College, Andhra Pradesh, India
Dr. Md. Abdullah Al Humayun
Associate Professor, Department of Electrical Systems Engineering, University Malaysia Perlis, Malaysia
Dr. Vellore Vasu
Teaching Assistant, Department of Mathematics, S.V.University Tirupati, Andhra Pradesh, India
Dr. Naveen K. Mehta
Associate Professor & Head, Department of Communication Skills, Mahakal Institute of Technology, Ujjain, India
Dr. Gujar Anant kumar Jotiram
Associate Professor, Department of Mechanical Engineering, Ashokrao Mane Group of Institutions, Vathar, Maharashtra, India
Dr. Pratibhamoy Das
Scientist, Department of Mathematics, IMU Berlin Einstein Foundation Fellow Technical University of Berlin, Germany
Dr. Messaouda AZZOUZI
Associate Professor, Department of Sciences & Technology, University of Djelfa, Algeria
Dr. Vandana Swarnkar
Associate Professor, Department of Chemistry, Jiwaji University Gwalior, India
Dr. Arvind K. Sharma
Associate Professor, Department of Computer Science Engineering, University of Kota, Kabir Circle, Rajasthan, India
Dr. R. Balu
Associate Professor, Department of Computr Applications, Bharathiar University, Tamilnadu, India
Dr. S. Suriyanarayanan
Associate Professor, Department of Water and Health, Jagadguru Sri Shivarathreeswara University, Karnataka, India
Dr. Dinesh Kumar
Associate Professor, Department of Mathematics, Pratap University, Jaipur, Rajasthan, India
Dr. Sandeep N
Associate Professor, Department of Mathematics, Vellore Institute of Technology, Tamil Nadu, India
Dr. Dharmpal Singh
Associate Professor, Department of Computer Science Engineering, JIS College of Engineering, West Bengal, India
Dr. Farshad Zahedi
Associate Professor, Department of Mechanical Engineering, University of Texas at Arlington, Tehran, Iran
Dr. Atishey Mittal
Associate Professor, Department of Mechanical Engineering, SRM University NCR Campus Meerut Delhi Road Modinagar, Aligarh,
India
Dr. Hussein Togun
Associate Professor, Department of Mechanical Engineering, University of Thiqar, Iraq
Dr. Shrikaant Kulkarni
Associate Professor, Department of Senior faculty V.I.T., Pune (M.S.), India
Dr. Mukesh Negi
Project Manager, Department of Computer Science & IT, Mukesh Negi, Project Manager, Noida, India
Dr. Sachin Madhavrao Kanawade
Associate Professor, Department Chemical Engineering, Pravara Rural Education Society’s,Sir Visvesvaraya Institute of Technology,
Nashik, India
Dr. Ganesh S Sable
Professor, Department of Electronics and Telecommunication, Maharashtra Institute of Technology Satara Parisar, Aurangabad,
Maharashtra, India
Dr. T.V. Rajini Kanth
Professor, Department of Computer Science Engineering, Sreenidhi Institute of Science and Technology, Hyderabad, India
Dr. Anuj Kumar Gupta
Associate Professor, Department of Computer Science & Engineering, RIMT Institute of Engineering & Technology, NH-1, Mandi
Godindgarh, Punjab, India
Dr. Hasan Ashrafi- Rizi
Associate Professor, Medical Library and Information Science Department of Health Information Technology Research Center,
Isfahan University of Medical Sciences, Isfahan, Iran
Dr. Golam Kibria
Associate Professor, Department of Mechanical Engineering, Aliah University, Kolkata, India
Dr. Mohammad Jannati
Professor, Department of Energy Conversion, UTM-PROTON Future Drive Laboratory, Faculty of Electrical Enginering, Universit
Teknologi Malaysia,
Dr. Mohammed Saber Mohammed Gad
Professor, Department of Mechanical Engineering, National Research Centre- El Behoos Street, El Dokki, Giza, Cairo, Egypt,
Dr. V. Balaji
Professor, Department of EEE, Sapthagiri College of Engineering Periyanahalli,(P.O) Palacode (Taluk) Dharmapuri,
Dr. Naveen Beri
Associate Professor, Department of Mechanical Engineering, Beant College of Engg. & Tech., Gurdaspur - 143 521, Punjab, India
Dr. Abdel-Baset H. Mekky
Associate Professor, Department of Physics, Buraydah Colleges Al Qassim / Saudi Arabia
Dr. T. Abdul Razak
Associate Professor, Department of Computer Science Jamal Mohamed College (Autonomous), Tiruchirappalli – 620 020 India
Dr. Preeti Singh Bahadur
Associate Professor, Department of Applied Physics Amity University, Greater Noida (U.P.) India
Dr. Ramadan Elaiess
Associate Professor, Department of Information Studies, Faculty of Arts University of Benghazi, Libya
Dr. R . Emmaniel
Professor & Head, Department of Business Administration ST, ANN, College of Engineering & Technology Vetapaliem. Po, Chirala,
Prakasam. DT, AP. India
Dr. C. Phani Ramesh
Director cum Associate Professor, Department of Computer Science Engineering, PRIST University, Manamai, Chennai Campus,
India
Dr. Rachna Goswami
Associate Professor, Department of Faculty in Bio-Science, Rajiv Gandhi University of Knowledge Technologies (RGUKT) District-
Krishna, Andhra Pradesh, India
Dr. Sudhakar Singh
Assoc. Prof. & Head, Department of Physics and Computer Science, Sardar Patel College of Technology, Balaghat (M.P.), India
Dr. Xiaolin Qin
Associate Professor & Assistant Director of Laboratory for Automated Reasoning and Programming, Chengdu Institute of Computer
Applications, Chinese Academy of Sciences, China
Dr. Maddila Lakshmi Chaitanya
Assoc. Prof. Department of Mechanical, Pragati Engineering College 1-378, ADB Road, Surampalem, Near Peddapuram, East
Godavari District, A.P., India
Dr. Jyoti Anand
Assistant Professor, Department of Mathematics, Dronacharya College of Engineering, Gurgaon, Haryana, India
Dr. Nasser Fegh-hi Farahmand
Assoc. Professor, Department of Industrial Management, College of Management, Economy and Accounting, Tabriz Branch, Islamic
Azad University, Tabriz, Iran
Dr. Ravindra Jilte
Assist. Prof. & Head, Department of Mechanical Engineering, VCET Vasai, University of Mumbai , Thane, Maharshtra 401202, India
Dr. Sarita Gajbhiye Meshram
Research Scholar, Department of Water Resources Development & Management Indian Institute of Technology, Roorkee, India
Dr. G. Komarasamy
Associate Professor, Senior Grade, Department of Computer Science & Engineering, Bannari Amman Institute of Technology,
Sathyamangalam,Tamil Nadu, India
Dr. P. Raman
Professor, Department of Management Studies, Panimalar Engineering College Chennai, India
Dr. M. Anto Bennet
Professor, Department of Electronics & Communication Engineering, Veltech Engineering College, Chennai, India
Dr. P. Keerthika
Associate Professor, Department of Computer Science & Engineering, Kongu Engineering College Perundurai, Tamilnadu, India
Dr. Santosh Kumar Behera
Associate Professor, Department of Education, Sidho-Kanho-Birsha University, Ranchi Road, P.O. Sainik School, Dist-Purulia, West
Bengal, India
Dr. P. Suresh
Associate Professor, Department of Information Technology, Kongu Engineering College Perundurai, Tamilnadu, India
Dr. Santosh Shivajirao Lomte
Associate Professor, Department of Computer Science and Information Technology, Radhai Mahavidyalaya, N-2 J sector, opp.
Aurangabad Gymkhana, Jalna Road Aurangabad, India
Dr. Altaf Ali Siyal
Professor, Department of Land and Water Management, Sindh Agriculture University Tandojam, Pakistan
Dr. Mohammad Valipour
Associate Professor, Sari Agricultural Sciences and Natural Resources University, Sari, Iran
Dr. Prakash H. Patil
Professor and Head, Department of Electronics and Tele Communication, Indira College of Engineering and Management Pune, India
Dr. Smolarek Małgorzata
Associate Professor, Department of Institute of Management and Economics, High School of Humanitas in Sosnowiec, Wyższa
Szkoła Humanitas Instytut Zarządzania i Ekonomii ul. Kilińskiego Sosnowiec Poland, India
S.
No
Volume-1 Issue-2, May 2011, ISSN: 2231-2307 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd.
Page
No.
1.
Authors: Shradha Gupta, Neetesh Gupta, Shiv Kumar
Paper Title: Evaluation of Object Based Video Retrieval Using SIFT
Abstract: In Video Retrieval system, each video that is stored in the database has its features extracted and
compared to the features of the query image. The local invariant features are obtained for all frames in a sequence
and tracked throughout the shot to extract stable features. Proposed work is to retrieve video from the database by
giving query as an object. Video is firstly converted into frames, these frames are then segmented and an object is
separated from the image. Then features are extracted from object image by using SIFT features. Features of the
video database obtained by the segmentation and feature extraction using SIFT feature are matched by Nearest
Neighbor Search (NNS). In this paper we have evaluated the proposed video retrieval system. The proposed method
is better than previous video retrieval methods because it is invariant to illumination changes.
Keywords: Video retrieval, segmentation, SIFT, Nearest-neighbor search.
References: 1. John Eakins & Margaret Graham ―Content-based Image Retrieval ―JISC Technology Applications Programme October 1999.
2. Arasanathan Anjulan, Nishan Canagarajah ―Object based video retrieval with local region tracking‖ Signal Processing: Image
Communication 22 (2007) 607–621.
3. Arasanathan Anjulan and Nishan Canagarajah‖ Video Scene Retrieval Based on Local Region Features‖ ICIP 2006. 1-4244-0481-9/06/2006
IEEE. 4. D. G. Lowe. Distinctive image features from scale-invariant keypoints. Int. J. Comput. Vision, 60(2):91-110, 2004.
5. Lili Nurliyana Abdullah, Shahrul Azman Mohd Noah & Tengku Mohd Tengku Sembok,‖ Exploring Video Information: Contents and
Architecture‖.
6. Vaclav Hlavac ,‖ Image Segmentation‖ http://cmp.felk.cvut.cz.
7. Bremner D, Demaine E, Erickson J, Iacono J, Langerman S, Morin P, Toussaint G (2005)."Output-sensitive algorithms for computing
nearest-neighbor decision boundaries". Discrete and Computational Geometry 33 (4): 593–604.
8. http://en.wikipedia.org/wiki/Film_frame.
9. Rahul Choudhury, EE 368 Project Report ―Recognizing pictures at an exhibition using SIFT‖.
10. P. Geetha, Vasumathi Narayanan,‖ A Survey of Content-Based Video Retrieval‖, Journal of Computer Science 4 (6): 474-486, 2008 ISSN
1549-3636 © 2008 Science Publications.
1-6
2.
Authors: Manoj Kumar Meena, Shiv Kumar, Neetesh Gupta
Paper Title: Image Steganography tool using Adaptive Encoding Approach to maximize Image hiding capacity
Abstract: Steganography is the art of hiding the fact that communication is taking place, by hiding information in
other information. Many different carrier file formats can be used, but digital images are the most popular because of
their frequency on the Internet. For hiding secret information in images, there exists a large variety of Steganographic
techniques some are more complex than others and all of them have respective strong and weak points. The Least
Significant Bit (LSB) insertion method is the most common and easiest method for embedding messages in an image.
This paper work intends to give an overview of image Steganography, its uses and techniques along with an attempt
to implement a basic image Steganographic model by using an adaptive encoding algorithm which attempts to
maximize the embedding capacity of each pixel through LSB insertion method. The Implementation is named
StegSan which also uses file compression and data encoding mechanisms to make the image more secure and less
detectable.
Keywords: Steganography, LSB Insertion method, adaptive encoding, StegSan approach.
References: 1. F. A. P. Petitcolas, R. J. Anderson and M. G. Kuhn, "Information hiding-A survey," Proc. IEEE, vol. 87, pp. 1062-1078,1999.
2. H. Wang and S. Wang, "Cyber warfare-Steganography vs. Steganalysis," Commun. ACM, vol. 47, no. 10, pp. 76-82, 2004. 3. X. Zhang and S. Wang, "Steganography using multiplebase notational system and human vision sensitivity," IEEE Signal Processing Letters,
vol. 12, pp. 67-70, Jan. 2005.
4. Masoud Afrakhteh, Adaptive Steganography Scheme Using More Surrounding Pixels, proc IEEE VI-225 Volume I (ICCDA 2010) 5. H. Noda, J. Spaulding, M. N. Shirazi, and E. Kawaguchi, "Application of bit-plane decomposition steganography to JPEG2000 encoded
images," IEEE Signal Processing Lett., vol. 9, no. 12, pp. 410-413, Dec. 2002.
6. D.-C. Wu and W.-H. Tsai, "A steganographic method for images by pixel-value differencing," Pattern Recognit. Lett., vol. 24, pp. 1613-1626,2003.
7. C. K. Chan and L. M. Cheng, "Hiding data in images by simple LSB substitution," Pattern Recognition, pp. 469--474, Mar. 2004.
8. N.!. Wu and M.S. Hwang,"Data Hiding: Current Status and Key Issues," International Journal of Network Security, Vol.4, No.1, PP. 1-9,2007.
9. Y.K. Lee and L. h. Chen, "An Adaptive Image Steganographic Model Based on Minimum-Error LSB Replacement," In Proceedings of the
Ninth National Conference on Information Security. Taichung, Taiwan, 14-15, pp.8-15, 1999. 10. Chandramouli, R.; Memon, N.; , "Analysis of LSB based image steganography techniques," Image Processing, 2001.Proceedings. 2001
International Conference on , vol.3, no., pp.1019-1022 vol.3, 2001 doi: 10.1109/ICIP.2001.958299
URL:http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=958299&isnumber=20708 11. Hengfu YANG ,Xingming SUN , Guang SUN “A High-Capacity Image Data Hiding Scheme Using Adaptive LSB Substitution” VOL. 18,
NO. 4, Dec. 2009.
12. Chandramouli, R., Kharrazi, M. and Memon, N. (2004) "Image Steganography and Steganalysis: Concepts and Practice", In: Kalker, T. and Cox, I. et al. (ed.). Digital Watermarking Springer Berlin / Heidelberg 204-11.
7-11
3.
Authors: R. Angrish, D. Garg
Paper Title: Efficient String Sorting Algorithms: Cache-aware and Cache-Oblivious
Abstract: Sorting is a process of rearranging a sequence of objects into some kind of predefined linear order. String
data is very common and most occurring data type. Sorting a string involves comparison it character by character
which is more time consuming than integer sorting. Also, sorting forms the basis of many applications like data
processing, databases, pattern matching and searching etc. So implementing improvements to make it fast and
efficient will help in reducing the computational time and thus making our applications run faster. This paper briefs
about various fast and efficient string sorting algorithms. The algorithms have been divided into two categories:
cache-aware and cache-oblivious. The various algorithms discussed are: CRadix Sort, Burstsort and cacheoblivious
string sorting algorithm. The improvement in CRadix Sort is achieved by starting the sorting with the most
significant digit and associating a small block of main memory called the key buffer to each key and sorting a portion
of each key into its corresponding key buffer. Burstsort is a trie-based string sorting algorithm that distributes strings
into small buckets whose contents are then sorted in cache. The cacheoblivious string sorting algorithm is a
randomized algorithm for string sorting which uses signature technique (reduces the sequence by creating a set of
“signatures” strings having the same trie structure as the original set) to sort strings.
Keywords: Cache-aware, Cache-oblivious, External string sorting.
References: 1. R. SINHA and A. WIRTH, ―Engineering Burstsort: Towards fast in-place string sorting‖, ACM Journal of Experimental Algorithmics,
Vol. 15, Article No. 2.5, 2010.
2. W.H. Ng and K. Kakehi, ―Cache efficient radix sort for string sorting‖, IEICE TRANS. FUNDAMENTALS, Vol. E90–A, No. 2, 2007.
3. S. Heinz, J. Zobel, and H.E. Williams, ―Burst tries: Afast, efficient data structure for string keys‖, ACM Trans. Inform. Syst, Vol.,20, No.
2, 2002, pages192–223.
4. L. Arge, M. A. Bender, E. D. Demaine, B. Holland- Minkley, and J. I. Munro, ―Cache-oblivious priority queue and graph algorithm
applications‖, In ACM, editor, Proceedings of the 34th Annual ACM Symposium on Theory of Computing (STOC ’02), ACM Press, 2002,
pages 268–276.
5. J. Bentley and R. Sedgewick, ―Fast algorithms for sorting and searching strings‖, In Proceedings of the Annual ACM-SIAM Symposium
on Discrete Algorithms. Society for Industrial and Applied Mathematics, Philadelphia, 1997, pages360–369.
6. L. Arge, P. Ferragina, R. Grossi, and J. S. Vitter, ―On sorting strings in external memory (extended abstract)‖, In ACM, editor, Proceedings
of the 29th Annual ACM Symposium on Theory of Computing (STOC ’97) , ACM Press, 1997, pages 540–548.
7. P.M. Mcilroy, K. Bostic, and M.D. Mcilroy, ―Engineering radix sort‖, Comput. Syst, Vol. 6, No. 1, 1993, pages5–27.International Journal
of Soft Computing and Engineering (IJSCE) ISSN: 2231-2307, Volume-1, Issue-2, May 2011 16
8. A. Andersson and S. Nilsson, ―Implementing radixsort‖, ACM J. Exp. Algorithmics 3, 7, 1998.
9. LaMarca and R.E. Ladner, ―The influence of caches on the performance of sorting,‖ J. Algorithms, vol.31, 1999, pages66–104.
10. Aggarwal and J.S. Vitter, ―The input/output complexity of sorting and related problems‖, Communications of the ACM, 31(9), 1988,
pages1116- 1127.
11. J. S. Vitter and E.A.M. Shrive, ―Algorithms for parallel memory I: Two-level memories‖, Algoritmica 13, 1994, pages110–147.
12. Yale N. Patt, ―The I/O subsystem—a candidate for improvement‖, Guest Editor’s Introduction in IEEE Computer, 27(3) , 1994, pages15-
16.
13. R. Fagerberg, A. Pagh and R. Pagh, ―External string sorting: Faster and cache-oblivious‖.
14. M. Frigo, C. E. Leiserson, H. Prokop, AND S. Ramachandran, ―Cache-oblivious algorithms (extended abstract)‖, Proceedings of
12-16
4.
Authors: Kavita Choudhary
Paper Title: Parametric Estimation of Software Systems
Abstract: Software is characterised by software metrics. Calculation of effort estimation is a type of software
metrics. Software effort estimation plays a vital role in the development of software. In recent years, software has
become the most expensive component of computer system projects. The major part of cost of software
development is due to the human-effort, and most cost estimation methods focus on this aspect and give estimates in
terms of person-month. In this paper, estimation of effort required for the development of software project is
calculated using genetic algorithm approach. Software systems are becoming complex and they desire for new,
effective and optimized technique with limited resources. A solution to this problem lies in nature where
complex species have evolved from simple organisms and constantly become able to adapt to changes in the
environment. In case of species, it takes hundreds of generations and years which are not considerable in the field
of software engineering. With the use of genetic algorithm, it can be done instantly by simulating the results on
various tools of genetic algorithm.
Keywords: Effort estimation, Effort estimation models, Walston-Felix model, COCOMO model, SEL model.
References: 1. Yeong-Seok Seo, Kyung-A Yoon, Doo-Hwan Bae, An Empirical analysis of software effort estimation with outlier elimination, Proceedings
of the 4th International workshop on Predictor models in Software Engineering © ACM 2008 (ISBN: 978-1-60558-036-4/08).
2. Pichai Jodpimai, Peraphon, Advanced Virtual and Intelligent Computing Centre , Analysis of Effort Estimation based on Software Project
Models © IEEE 2009. 3. Parvinder S. Sandhu, Manisha Prashar, Pourush Bassi and Atul Bisht , A model for estimation of efforts in development of software
systems,World Academy of Science and Technology 56-2009.
4. Alaa F Sheta, Estimation of the COCOMO model parameters using genetic algorithm for NASA Software Projects, Journal of Computer Science 2006 ISSN: 1549-3636 © 2006 Science Publications.
5. Andreea Fanea and Laura Diosan, Components execution order using Genetic Algorithm, STUDIA UNIV. BABES BOLYAI, INFORMATICA, 2005.
6. Westley Weimer, ThanhVu Nguyen, Claire Le Goues and Stephanie Forrest, Automatically Finding Patches Using Genetic Programming,
ICSE’09, © IEEE. 7. Mark Harman, The Current State and Future of Search Based Software Engineering, Future of Software Engineering (FOSE'07) © 2007
IEEE.
8. Indrajit Bhattacharyya, Vector GA - A Novel Enhancement of Genetic Algorithms for Efficient Multi-variable or Multi-dimensional Search, November 2009 Volume 34 Number 6, ACM.
9. Anne Martens, Optimising Multiple Quality Criteria of Service-Oriented Software Architectures, QUASOSS’09, August 25, 2009, ACM
Publications.
17-20
10. Yujie Yao and Haopeng Chen, QoS-aware Service Composition Using NSGA, ICIS 2009, November 24-26, 2009 Seoul, Korea © 2009 ACM 978-1-60558-710.
11. Hsin-yi Jiang, Carl Chang, Deriving Evaluation Metrics for Applicability of Genetic Algorithms to Optimization Problems, GECCO'08,
ACM 978-1-60558-130. 12. Outi Raiha, Applying Genetic Algorithms in Software Architecture Design, University of Tampere Department of Computer Sciences,
February 2008.
13. Wasif Afzal, Richard Torkar, Suitability of genetic programming for software reliability growth modeling, Blekinge Institute of Technology. 14. John R. Koza, Introduction to Genetic Programming, GECCO-2008—ATLANTA JULY 12–16, 2008.
15. Hsin-yi Jiang, Can the Genetic Algorithm Be a Good Tool for Software Engineering Searching Problems? Compsac, vol. 2, pp.362-366, 30th
Annual International Computer Software and Applications Conference (COMPSAC'06), 2006. 16. Kavita Choudhary GA based Optimization of Software Development Effort Estimation (ISSN No-0976-8491), Vol 1 Issue 1 (IJCST
0910/963/229), Dec 2010.
5.
Authors: Piyush Lotia, M.R. Khan
Paper Title: Multistage VQ Based GMM For Text Independent Speaker identification System
Abstract: The use of Gaussian Mixture Models (GMM) are most common in speaker identification due to it can be
performed in a completely text independent situation. However, it sounds efficient to speaker identification
application, but it results long time processing in practice. In this paper, we propose a decision function by using
vector quantization (VQ) techniques to decrease the training model for GMM in order to reduce the processing time.
In our proposed modeling, we take the superiority of VQ, which is simplicity computation to distinguish between
male and female speaker. Then, in second phase of classification, decision tree rule are applied to separate out the
similar speaker in same gender into two difference group. While in phase 3, GMM is applied into the subgroup of
speaker to get the accuracy rates. Experimental result shows that our hybrid VQ/GMM method always yielded better
Improvements in accuracy and bring almost 20% reduce in time processing.
Keywords: MFCC, VQ, Cepstrum, LBG Algorithim.
References: 1. Campbell, J.P., "Speaker Recognition: A Tutorial", Proc. of the IEEE, vol. 85, no. 9, 1997, pp. 1437-1462. 2. Sakoe, H.and Chiba, S., "Dynamic programming algorithm optimization for spoken word recognition", Acoustics, Speech, and Signal
Processing, IEEE Transactions on Volume 26, Issue 1, Feb 1978, Page 43 - 49.
3. Vlasta Radová and Zdenek Svenda, "Speaker Identification Based on Vector Quantization", Proceedings of the Second International Workshop on Text, Speech and Dialogue, Vol. 1692, 1999, Pages: 341 -344.
4. Lawrence R. Rabiner., "A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition", Proceedings of the
IEEE,77 (2), 1989, p. 257–286.
5. Reynolds, D. A. and Rose, R. C. "Robust text-independent speaker identification using Gaussian mixture speaker models. IEEE
Trans.Speech Audio Process. 3, 1995, pp 72–83.
6. Solera, U.R., Martín-Iglesias, D., Gallardo-Antolín, A., Peláez-Moreno,C. and Díaz-de-María, F, "Robust ASR using Support Vector Machines",Speech Communication, Volume 49 Issue 4, 2007.
7. J. Pelecanos, S. Myers, S. Sridharan and V. Chandran, "Vector Quantization Based Gaussian Modeling for Speaker Verification",
15thInternational Conference on Pattern Recognition, Volume 3, 2000, p.3298. 8. Qiguang Lin, Ea-Ee Jan, ChiWei Che, Dong-Suk Yuk and lanagan, J,"Selective use of the speech spectrum and a VQGMM method for
speaker identification", Fourth International Conference on Spoken Language, Vol 4, 1996, Pg:2415 - 2418.
9. Davis, S. B. and Mermelstein, P., "Comparison of parametric representations for monosyllabic word recognition in continuouslyspoken sentences", IEEE Trans. on Acoustic, Speech and Signal Processing, ASSP-28, 1980, No. 4.
10. Yu, K., Mason, J., Oglesby, J., ―Speaker recognition using hidden Markov models, dynamic time warping and vector quantization‖ Vision,
Image and Signal Processing, IEE Proceedings, Oct 1995.
11. Vijendra Raj Apsingekar and Phillip L. De Leon; Speaker Model Clustering for Efficient Speaker Identification in Large Population Applications; IEEE transactions on Speech and Audio Signal Processing; Vol. 17, No. 4; May 2009.
12. Aaron. E. Rosenberg, ―New techniques for automatic speaker verification‖, IEEE Transactions on Acoustics, Speech and Signal
Processing, Vol.ASSP-23, No.2, pp.169-176, April 1975
13. Y. Linde, A. Buzo, and R.M. Gray,. "An algorithm for vector quantizer design,". IEEE Trans. Communications, vol. COM-28(1), pp. 84-96,
Jan. 1980.
14. R. Gray. "Vector quantization,". IEEE Acoust., Speech, Signal Process. Mag., vol. 1, pp. 4-29, Apr. 1984.
15. F.K. Soong, A.E. Rosenberg, L.R. Rabiner, and B.H. Juang,. "A Vector quantization approach to speaker recognition,". in Proc. IEEE Int. Conf. Acoust., Speech, Signal Process., vol. 10, Detroit, Michingon, Apr. 1985, pp. 387-90.
16. Sookpotharom Supot, Reruang Sutat, Airphaiboon Surapan, and Sangworasil Manas. Medical Image Compression Using Vector
Quantization and Fuzzy C-Means. [Online] http://www.kmitl.ac.th/biolab/member/sutath/final_paper_iscit02.pdf
17. Rabiner.L.& Juang B.H., ―Fundamentals of speech recognition‖, Prentice Hall, NJ 1993.
18. Wai C. Chu, ―Speech Coding Algorithm‖, Wiley Interscience, New York, NY, 2003.
19. C. Becchetti and Lucio Prina Ricotti, ―Speech Recognition‖, John Wiley and Sons, England, 1999.
20. E. Karpov, ―Real Time Speaker Identification,‖ Master`s thesis, Department of Computer Science, University of Joensuu, 2003
21. J.Y. Hwang , P.M. Schuelthess , ― Block quantization of coreleted Gaussian Random Variables,‖ IEEE Tran. Commu Vol COM 11, pp
289-296 Sep 1963.
22. H. Gish, J.N. Pierce, ― Asympoticaaly efficient Quantizing ,‖ IEEE Tran. Infor Tehory Vol IT-14, pp, 676-683, Sept 1968.
23. AGeirsoi , ―Asympoticaaly optimal block Quantization ,‖ IEEE Tran. Infor Tehory Vol IT-25, pp, 378-380, July 1979.
24. Y. Londe, A. Buzo, R.M. Gray,‖ An Algoii. For vector quantizer design,‖ IEEE Tran. Commun. Vol Comm 28, ppi, 84-95, Jan 1980.
25. P.A. Chou, T. Lookabaugh, and R. M. Gray, ―Entropy Constrained Vector Quantization ,‖ IEEE Tran Acustic speec signal processing. Vol
37, pp, 31-42, Jan 1989.
26. ]N. M. Akrout, C. Diab, R. Prost, and R. Goutte,‖Code Word Orientation an improved subband vector quantization scheme for image
coding,‖ Opt. Engg. VOl. 33 No. 7, pp 2294-2398 July 1994.
27. Poonam Bansal, Amita Dev, Shail Bala Jain, ― Automatic speaker identification using vector Quantization, ― Asian Journal of Information
Technology pp938-942, 2007.
28. S.R.Das, W.S. Mohn, ―A scheme for speech processing in automatic speaker verification‖, IEEE Transactions on Audio And
Electroacoustics, Vol.AU-19, pp.32-43, March 1971.
29. Chulhee Lee, Donghoon Hyun, Euisun Choi, Jinwook Go and Chungyong Lee, ―Optimizing feature extraction for 30. Guorong Xuan, Wei Zhang and Peiqi Chai; EM Algorithms Of GaussianMixture ModelandHidden Markov Model; IEEE Transactions;
2001.
31. D.A.Reynols, R.C.Rose ―A Gaussian mixture modeling approach to text independent speaker recognitions system‖ in Proc. Int. Conf.
Signal Processing Apll. Tech. Nov. 1992 pp. 967-973.
32. A.Revathi and Y.Venkataramani,‖Text independent speaker identification/verification using multiple features‖, Proceedings of IEEE
21-26
International Conference on Computer Science and Information Engineering, April 2009, Los Angeles, USA.
33. P. Li and J. E. Porter, “Normalizations and selection of speech segments for speaker recognition scoring, ‖in Proc. IEEE Int. Conf.
Acoustics, Speech, Signal Processing (ICASSP ’88), vol. 1, pp. 595–598, New York, NY, USA, April 1988.
34. Y. GU and T. Thomas, ―A text-independent speaker verification system using support vector machines classifier,‖ in Proc. European
Conference on Speech Communication and Technology(Euro speech ’01), pp. 1765–1769, Aalborg, Denmark, September 2001. speech
recognition‖, IEEE Transactions on Speech and Audio Processing, Vol.11, No.1, January 2009.
35. J. Koolwaaij and L. Boves, ―Local normalization and delayed decision making in speaker detection and tracking,‖ Digital Signal
Processing, vol. 10, no. 1–3, pp. 113–132, 2000.
36. P. Delacourt and C. J. Wellekens, ―DISTBIC: A speaker based segmentation for audio data indexing,‖ Speech Communication, vol. 32, no.
1-2, pp. 111–126, 2000.
37. R. Auckenthaler,M. Carey, and H. Lloyd-Thomas, ―Score normalization for text-independent speaker verification system, “Digital Signal Processing, vol. 10, no. 1, 2000.
38. Lippman, R.P. "Neural Classifiers Useful for Speech Recognition", IEEEMagazine on Acoustic. Speech and Signal Processing, vo1.4, no.2,
pp. 4-22.
39. K. R. Farrell, R.Mammone, and K. Assaleh, ―Speaker recognition using neural networks and conventional classifiers,‖ IEEE Trans.
Speech, and Audio Processing, vol. 2, no. 1, pp. 194–205,1994.
40. M. D. Richard and R. P. Lippmann, ―Neural network classifiers estimate Bayesian a posteriori probabilities,‖ Neural Computation, vol. 3,
no. 4, pp. 461–483, 1991.
41. Niles, L.T. and Silverman,querque, ―Combining Hidden Markov Model and Neural Classifiers‖, April, 1990 H.F., PIOC. ICASSP-1990,
pp.417-420.
42. D. A. Reynolds, T. F. Quatieri, and R. B. Dunn, ―Speaker verification using adapted Gaussian mixture models,‖ Digital Signal Processing,
vol. 10, no. 1, pp. 19–41, 2000.
43. Peter Varchol, Duston Levicky, ―Optimization of GMM for text Independent Speaker Verification System‖ IEEE transaction on signal
processing 978-1-4244-2088-9/08/2008/IEEE.
6.
Authors: Ritu Ranjani Singh, Neetesh Gupta, Shiv Kumar
Paper Title: To Reduce the False Alarm in Intrusion Detection System using self Organizing Map
Abstract: Intrusion detection systems aim to identify attacks with a high detection rate and a low false alarm rate.
Classification-based data mining models for intrusion detection are often ineffective in dealing with dynamic changes
in intrusion patterns and characteristics. Consequently, unsupervised learning methods have been given a closer look
for network intrusion detection. Traditional instance-based learning methods can only be used to detect known
intrusions, since these methods classify instances based on what they have learned. They rarely detect new intrusions
since these intrusion classes has not been able to detect new intrusions as well as known intrusions. In this paper, we
propose a soft Computing technique such as Self organizing map for detecting the intrusion in network intrusion
detection. Problems with k-mean clustering are hard cluster to class assignment, class dominance, and null class
problems. The network traffic datasets provided by the NSL-KDD Data set in intrusion detection system which
demonstrates the feasibility and promise of unsupervised learning methods for network intrusion detection
Keywords: Data mining, False alarm, Intrusion detection system, neural network, Self organizing map
References: 1. Abirami Muralidharan, J.Patrick Rousche, " Decoding of auditory cortex signals with a LAMSTAR neural network ", Neurological
Research, Volume 27, pp. 4-10, January 2005
2. Srilatha Chebrolu et.al, "Feature deduction and ensemble design of intrusion detection systems", Elsevier Journal of Computers & Security" Vol. 24/4, pp. 295-307, 2005
3. Srilatha Chebrolu et.al, "Feature deduction and ensemble design of intrusion detection systems", Elsevier Journal of Computers & Security"
Vol. 24/4, pp. 295-307, 2005 4. H. Shah, J. Undercoffer, and A. Joshi, “Fuzzy Clustering for Intrusion Detection”, Proc. 12th IEEE Int’l Conf. Fuzzy Systems (FUZZ-IEEE
'03), 2, pp. 1274 – 1278, 2007.
5. Leonid Portnoy, “Intrusion Detection with Unlabeled Data using Clustering'', Undergraduate Thesis, Columbia University, New York, NY, Dec. 2007
6. Wenke Lee, Sal Stolfo, and Kui Mok, “Adaptive Intrusion Detection: A Data Mining Approach”, Artificial Intelligence
7. Michael Sobirey's Intrusion Detection Systems page, http://www.rnks.informatik.tucot. 8. “ NIST Special Publication on Intrusion Detection Systems“, SP 800-31 Computer Security Resource Center (CSRC), National Institute of
Standards and Technology (NIST), Nov. 2008, p.15.
9. P.Lichodzijewski, A. n. Zincir-Heywood and M. I. Heywood, “ Host-based intrusion detection using Neural Gas,” Proceedings of the 2002 IEEE World Congress on Computational Intelligence, 2002 (in press).
10. Z.Muda,w.yassin,MN Seliman & N.I.Udzir. “A K-mean & Naïve Bayes Learing approach for better intrusion Detection”. To appears in
Information Technology journal. Asian network for scientific information .Malaysia 2011
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7.
Authors: Wasim Khan, Shiv Kumar. Neetesh Gupta, Nilofar Khan
Paper Title: A Proposed Method for Image Retrieval using Histogram values and Texture Descriptor Analysis
Abstract: Color and Texture information have been the primitive image descriptors in content based image
retrieval systems. In this article, a method is proposed for image mining based on analysis of color Histogram values
and texture descriptor of an image. For this purpose, three functions are used for texture descriptor analysis such as
entropy, local range and standard deviation. To extract the color properties of an image, histogram values are used.
The combination of the color and texture features of the image provides a robust feature set for image retrieval.
Keywords: content-based image retrieval, color histogram, image texture.
References: 1. Texture Based Image Indexing and Retrieval . N Ganeshwara rao, Dr. V. Vijaya Kumar, V Venkata Krishna.
2. A survey of methods for colour image indexing and retrieval in Image database.Raimondo Schettini , Gianluigi ciocca, Silvia Zuffi. 3. Color Texture Moments For Content – Based Image Retrieval, Hui Yu1, Mingjing Li2, Hong-Jiang Zhang2, Jufu Feng1.
4. Entropy-Based Indexing On Color And Texture In Image Retrieval Anirban Das.
5. Content Based image Retrieval at the End of the Early Years,Arnold W.M. Smeulders IEEE,Marcel Worring ,Simone Santini IEEE,Amarnath Gupta IEEE,Ramesh Jain,IEEE.
33-36
6. Object-Based Image Indexing and Retrieval in DCT Domain using Clustering Techniques, Hossein Nezamabadi-pour and Saeid Saryazdi. 7. Histogram Re nement for Content-Based Image Retrieval, Greg Pass Ramin Zabih.
8. Entropy-Based Indexing On Color And Texture In Image Retrieval, Anirban Das.
8.
Authors: Mukesh Kumar, Kamal Mehta
Paper Title: A Modified Method to Segment Sharp and Unsharp Edged Brain Tumors in 2 D MRI Using
Automatic Seeded Region Growing Method
Abstract: Segmentation of Brain tumor accurately is a challenging task in MRI. The MRI image is an image that
produces a high contrast images indicating regular and irregular tissues that help to distinguish the overlapping in
margin of each limb. But when the edges of tumor is not sharped then the segmentation results are not accurate i.e.
segmentation may be over or under. This may be happened due to initial stage of the tumors [5]. So , in this paper a
modified method of tumor line detection and segmentation is used to separate the irregular from the regular
surrounding tissue to get a real identification of involved and noninvolved area that help the surgeon to distinguish
the involved area precisely. The method used in this paper is seeded region growing method and it was implemented
using MATLAB 7.6.0.324 on 25 Magnetic Resonance Images to detect the tumor boundaries in 2D MRI for different
cases.
Keywords: Gray level, MRI image, Region growing, tumour, segmentation etc.
References: 1. R.B. Dubey, M. Hanmandlu, S.K.Gupta,”Semi-automatic segmentation of MRI Brain tumor”,ICGST-GVIP,ISSN-1687-398X,Volume 9,4
august 2009.
2. Juan shan , H.D. Cheng, Yuxuan wang,”A novel automatic seed point selection algorithm for breast ultra sound images”,IEEE,2008
3. U. sivarajan ,KJ Jayapragasam , YF Abdul Aziz, K Rahmat ,” Dynamic contrast enhancement Magnetic resonanace imaging evaluation of Breast Lesions:A morphological and Quantitive analysis”,J Hk coll Radiol,2009
4. Sukhvinder singh, Sukhbeer singh,”Parallel image processing concepts”,IJCCT vol.1,August 2010.
5. E.Konukoglu,” Monitoring slowly evolving tumors”,IEEE ISBI 2008. 6. Vasant manohar, yuhana gu,”MRI segmentation using fuzzy c means and Finite gaussian mixture models”2003
7. “Digital Image Processing”, 3/E by Rafael C. Gonzalez ,Richard E. Woods, ISBN-10: 013168728X
8. “Skull stripping and automatic segmentation of brain MRI using seed growth and threshold techniques”, Intelligent and Advanced Systems, 2007. ICIAS 2007,page 422 – 426, ISBN: 978-1-4244-1355-3
37-40
9.
Authors: Roli Pradhan, K.K. Pathak , V.P. Singh
Paper Title: Application of Neural Network in Prediction of Financial Viability
Abstract: Bankruptcy prediction is very important for all the organization since it affects the economy and causes a
rise in many social problems with incremental high costs. There are large number of techniques that have been
developed to predict the bankruptcy of firms, which helps the decision makers such as investors and financial
analysts to plan in accordance to the financial position of the firm regarding the terms of credit as well as the
recovery of the lent amount. The Altman Model for prediction of financial bankruptcy has been considered in this
work. The backpropagation neural networks been used to forecast the Z Score for the firms. The research work first
estimates the internal parameters of the Z score for a firm from 2001-2008 to the train the BPNN and uses the
estimates of the year 2009 and 2010 values for the validation process. Finally it dwells to draw predictions for the
period 2011-2015 and emphasizes the growing role of BPNN application based Z Score computation of financial
Bankruptcy.
Keywords: Bankruptcy prediction, financial ratio models, BPNN
References: 1. Artusi and Brandstetter, Radial basis function networks GPU based implementation, IEEE Transactions on Neural networks, 19(12): 2150–
2154, 2008.
2. A.F. Atiya. Bankruptcy prediction for credit risk using neural networks: A survey and new results,Neural Networks, IEEE Transactions on,
12(4):929 – 935, Jul 2001. 3. B Ribeiro, A Vieira, J Duarte, C Silva, J C das Neves, Q Liu, and A H.Sung Learning manifolds for bankruptcy analysis, In M. K¨oppen et
al. (Eds.), editor, Int. Conf. on Neural Information Processing, volume 5506, pages 722–729, Berlin Heidelberg, 2009. Lecture Notes
4. B Ribeiro, C Silva, A Vieira, and J Carvalho das Neves, Extracting discriminative features using non-negative matrix factorization in financial distress dat, In M. Kolehmainen et al. (Eds.), editor, Int Conf on Adaptive and Natural Computing Algorithms, volume 4432, pages
5. E. I. Altman Corporate Financial Distress and Bankruptcy: A Complete Guide to Predicting and Avoiding Distress and Profiting from
Bankruptcy, John Wiley & Sons, 2nd edition, 1993. 6. E. I. Altman ―Financial ratios, discriminant analysis and the prediction of corporate bankruptcy, Journal of Finance, 23(4):589 – 609,
September 1968.
7. G.A. Rekba Pai, R. Annapoorani, and G.A. Vijayalakshmi Pai Performance analysis of a statistical and an evolutionary neural network based classifier for the prediction of industrial bankruptcy, In IEEE Conference on Cybernetics and Intelligent Systems, volume 2, pages
8. J.A. Anderson, C.D. Lorenz, and A. Travesset ― General purpose molecular dynamics simulations fully implemented on graphics
processing units, J. Computational Physics, 227(10):5342–5359, 2008. 9. K.-S. Oh and K. Jun g GPU implementation of neural networks. Pattern Recognition, 37(6):1311–1314, 2004.
10. Noel Lopes and Bernardete Ribeiro ―An efficient gradient-based learning algorithm applied to neural networks with selective actuation
neurons, Neural, Parallel and Scientific Computations, 11:253–272,2003.
11. Noel Lopes and Bernardete Ribeiro ―GPU implementation of the multiple back-propagation algorithm‖, In Proceedings of Intelligent Data
Engineering and Automated Learning, pages 449–456. LNCS, Springer-Verlag, 2009.
12. P. Ravi Kumar and V. Ravi ―Bankruptcy prediction in banks and firms via statistical and intelligent techniques - a review‖, European
Journal of Operational Research, 180(1):1 – 28, July 2007.
13. S. Che, M. Boyer, J. Meng, D. Tarjan, J.W. Sheaffer, and K. Skadron ― A performance study of general-purpose applications on graphics
processors using CUDA, Journal of Parallel and Distributed Computing,68(10):1370–1380, 2008. 14. Huang Fu-yuan A genetic fuzzy neural network for bankruptcy prediction in chinese corporations, In International Conference on Risk
Management & Engineering Management (ICRMEM ’08), pages 542 – 546, Nov. 2008. 15. Sam S. Stone, Haoran Yi, Justin P. Haldar, Wen-Mei W. Hwu,Bradley P. Sutton, and Zhi-Pei Liang ― Accelerating advanced MRI 2215
reconstructions on GPUs, In 5th International Conference on Computing Frontiers, 2008.
41-45
16. V. Volkov and J.W. Demmel. LU, QR and Cholesky factorizations using vector capabilities of GPUs, Technical Report EECS-2008-49, EECS Dept., Univ. of Calif., Berkeley, 2008.
10.
Authors: Ashok Bhansali, H.R. Sharma
Paper Title: An Open Source Framework for PRTF Protocol
Abstract: Social networking websites contain vast amount of data inside them. Volume of data is enormous and
growing at a very fast rate. Social network data can be classified in threemajor categories – user profile data, user
communication data and group communication data. Data mining can be applied effectively to discover the
knowledge and to extract the useful patterns from this gigantic data set, which is called as the social network mining.
Person Related to a Field (PRTF) is a protocol to mine the information across all the social networking data, in
general, and use the extracted pattern to search an expert in particular. It also proposes the mechanism to rank the
searched experts. In this paper we propose an open source implementation of the PRTF (Person related to a Field)
protocol. Using this proposed framework, apart from expert identification, number of useful patterns can be
discovered from social networking data. The proposed framework is implemented using open source technologies
and is explained with the help of an illustrative example.
Keywords: Social network mining, data mining, expert finding, PRTF.
References: 1. Ashok Bhansali and Dr. HR Sharma, “PRTF: Person Related to a Field Protocol for Searching in Social Network Databases”, Journal of
Global Research in Computer Science, Pages: 21-26, Dec’ 2010. 2. I-Hsien Ting , “Web Mining Techniques for On-line Social Networks Analysis”, Service Systems and Service Management, 2008, Page(s): 1
- 5, 2008
3. Duncan J. Watts, Peter Sheridan Dodds, M. E. J. Newman, “Identity and Search in Social Networks”, Vol. 296. no. 5571, pp. 1302 – 1305, Science 17 May 2002
4. Nan Du, Bin Wu, Xin Pei, Bai Wang and Liutong Xu, “Community Detection in Large-Scale Social Networks”, International Conference on Knowledge Discovery and Data Mining archive, Proceedings of the 9th WebKDD and 1st SNA-KDD 2007 workshop on Web mining and
social network analysis table of contents, San Jose, California , Pages: 16-25, 2007
5. Dawit Yimam, “Expert Finding Systems for Organizations: Domain Analysis and the DEMOIR Approach”, ECSCW 99 Beyond Knowledge Management: Management Expertise Workshop, 2000
6. Krisztian Balog Maarten de Rijke, “Finding Experts and their Details in Email Corpora”, In International World Wide Web Conference,
Proceedings of the 15th international conference on World Wide Web. Pages, 1035-1036, ISBN 1595933239, 2006 7. Krisztian Balog and Maarten de Rijke, “Determining Expert Profiles (With an Application to Expert Finding)”, International Joint
Conference On Artificial Intelligence archive, Proceedings of the 20th international joint conference on Artifical intelligence, Pages: 2657-
2662, 2007.
8. Christian Bird, Alex Gourley, Prem Devanbu, Michael Gertz, Anand Swaminathan, “Mining Email Social Networks”, MSR’06, May 22– 23,
2006, Shanghai, China
9. John G. Breslin, Uldis Bojars, Boanerges Aleman-Meza, Harold Boley, Malgorzata Mochol, Lyndon JB Nixon, Axel Polleres, and Anna V. Zhdanova, “Finding experts using Internet-based discussions in online communities and associated social networks”, In Proceedings of the
1st International ExpertFinder Workshop Workshop at Knowledge Web General Assembly 2007, 2007.
10. Jian Jiao, Jun Yan, Haibei Zhao, Weiguo Fan, ExpertRank: An Expert User Ranking Algorithm in Online Communities, 2009 International Conference on New Trends in Information and Service Science, pp. 674 - 679.
11. CM University Data -http://www.cs.cmu.edu/~awm/10701/project/data.html
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11.
Authors: A.M. Agarkar, D.R. Dhabale
Paper Title: Design and Profile Optimization for Dispersion Shifted Fiber (DSF)
Abstract: In designing of SM fibers, dispersion behavior is a major distinguishing feature which limits long
distance and high speed transmission. Dispersion of SMF is lowest at 1.3 um, but the attenuation is minimum at 1.55
um. At 1.55um dispersion is higher. For achieving maximum transmission distance in a high capacity link ,dispersion
null should be at the wavelength of minimum attenuation .This may be achieved by mechanisms like reduction in
fiber core with an accompanying increase in the relative RI to create Dispersion Shifted Fibers (DCF) [3]. In the
proposed work by optimizing the fiber profile a fiber with minimum dispersion slope at the desired wavelength will
be carried out.
Keywords: Optical Fiber, Dispersion, DSF, MFD.
References: 1. Installation of disperslon - shifted fiber in the British telecom trunk network , Electronics Letters , 28th April 1988, vol. 24 no. 9.
2. Relationship between nonlinear effective area and mode field diameter for dispersion shifted fibres, Y. Namihira, Electronics letters, 3rd February, 1994, vol. 30 no. 3.
3. Performance of optical cable composed of dispersion-shifted single-mode fibers, Journal of Light wave technology, vol. Lt-4, no. 10,
October 1986. 4. S. S. Hossain and Alan Couchman, "Design of single mode SMF, NZ-DSF and DCF optical fibers", Proceeding of CCECE05 18th Annual
Canadian Conference on Electrical and Computer Engineering, Saskatoon, Saskatchewan, Canada, May 2005.
5. L. G. Cohen et al., ―Tailoring zero chromatic dispersion into the 1.5 μm-1.6 μm low-loss spectral region of single-mode fibres‖, Electronics
Letters. 15 (12), 334 (1979)
6. M. A. Saifi et al., ―Triangular-profile single-mode fiber Opt. Lett. 7 (1), 43 (1982).
7. B. J. Ainslie et al., ―Mono-mode fibre with ultra-low loss and minimum dispersion at 1.55 μm, Electron. Lett. 18, 842 (1982).
8. V. A. Bhagavatula and M. S. Spitz, ―Dispersion-shifted segmented-core single-mode fibers, Opt. Lett. 9 (5), 186 (1984). 9. A.M. Agarkar , S. Dufare ,Novel Single Mode Fiber (SMF) Ultra Low Loss Design in 1.550 μm window considering PMD, DGD and
various Bending Radii, International Journal of Computer Applications (0975 – 8887),Volume 10– No.7, November 2010.
10. A.M. Agarkar , Prajakta Joharapurkar , PMD & DGD Performance Analysis in SMF due to Fiber Irregularities , International Journal of Computer Applications (0975 – 8887), Volume 12– No.6, December 2010
53-56
12.
Authors: Jaspal Bagga, Neeta Tripathi
Paper Title: Analysis of Digitally Modulated Signals using Instantaneous and Stochastic Features, for
Classification
Abstract: Automatic modulation classification is a procedure performed at the receiver based on the received
signal before demodulation when the modulation format is not known to the receiver. AMR is also believed to play
an important role in the implementation of Software Defined Radio (SDR) of the 4th-Generation (4G)
communication system. The ability to automatically select the correct modulation scheme used in an unknown
received signal is a major advantage in a wireless network This paper describes one application that exploits the
flexibility of a software radio. As compared to the previous work this approach uses stochastic features to distinguish
modulated signals for varying Signal to Noise Ratio (SNR). The proposed method is simple effective and robust. It is
based on the stochastic features derived from instantaneous features to classify digital modulation signals.. This
method is capable of differentiating ASK2, ASK4, FSK2, FSK4, PSK2 and PSK4 signals at the output of a typical
high frequency channel with white Gaussian noise, Unlike most other existing methods, proposed method assumes
no prior information of the incoming signal (symbol rate, carrier frequency, amplitude etc.). Extensive simulation
results demonstrate that this approach is robust in various practical situations in identifying the modulated signals.
When SNR is less than 5 dB, the percentage of correct identification is about 97%which increases to almost 100%
for SNR 20db.
Keywords: Digital signals, Modulation Classification, Signal To Noise Ratio, Stochastic features
References: 1. S. Z. Hsue and S. S. Soliman,1989 “Automatic modulation recognition of digitally modulated signals,” in Proc. IEEE MILCOM, , pp. 645-
649.
2. S.-Z. Hsue and S.S. Soliman, 1990. “Automatic modulation classification using zero crossing,” in IEEE Proceedings (Radar and Signal
Processing), vol. 137, no. 6, pp. 459-464, 3. A.Polydoros and K. Kim,. “On the detection and classification of quadrature digital modulations in broad-band noise,” in IEEE Transactions
on Communications, vol. 38, no. 8, pp. 1199-1211 ,1990
4. B.F. Beidas and C.L.Weber, “Higher-order correlation based approach to modulation classification of digitally modulated signals,” in IEEE Journal on Selected Areain Communications, vol. 13, no.1, pp. 89-101, 1995.
5. E. E. Azzouz and A. K. Nandi, “Automatic Modulation Recognition of Communication Signals”, Kluwer Academic Publishers, 1996.
6. Y.C. Lin and C.-C. Jay Kuo, “Modulation classification using wavelet transform,” in Proceedings SPIE, vol. 2303, pp. 260-271. 1998 7. K.Hassan,1 I. Dayoub,2 W. Hamouda,3 and M. Berbineau1 “AutomaticModulation Recognition Using Wavelet Transform andNeural
Networks inWireless Systems” EURASIP Journal on Advances in Signal Processing Volume 2010
8. O.A.Dobre, A. Abdi, Y. Bar-Ness, and W. Su, “Survey of automatic modulation classification techniques: classical approaches and new trends,” IET Communications, vol. 1, no. 2, pp. 137–156, 2007.
9. W.Wei and J.M.Mendel, “Maximum-likelihood classification for digital amplitude-phase modulations,” IEEE Transactions on
Communications, vol. 48, no. 2, pp. 189–193, 2000. 10. O. A. Dobre and F. Hameed, “Likelihood-based algorithms for linear digital modulation classification in fading CHANNELS,” in
Proceedings of the Canadian Conference on Electrical and Computer Engineering (CCECE ’06), pp. 1347–1350, Ottawa, Canada, 2006. 11. A.Ebrahimzadeh and A. Ranjbar, “Intelligent digital signal type identification,” Engineering Applications of Artificial Intelligence, vol. 21,
no. 4, pp. 569–577, 2008.
12. Y. Zhao, G. Ren, and Z. Zhong, “Modulation recognition of SDR receivers based onWNN,” in Proceedings of the 63rd IEEEVehicular Technology Conference (VTC ’06), pp. 2140–2143,May 2006.
13. M.L.D. Wong and A. K. Nandi, “Automatic digital modulation recognition using artificial neural network and genetic algorithm,” Signal
Processing, vol. 84, no. 2, pp. 351–365, 2004. 14. A.K. Nandi and E. E. Azzouz, “Algorithms for automatic modulation recognition of communication signals,” IEEE Transactions on
Communications, vol. 46, no. 4, pp. 431–436,1998.
15. A.Swami and B. M. Sadler, “Hierarchical digital modulation classification using cumulants,” IEEE Transactions on Communications, vol. 48, no. 3, pp. 416–429, 2000.
16. O.A. Dobre, Y. Bar-Ness, and W. Su, “Robust QAM modulation classification algorithm using cyclic cumulants,” in Proceedings of the
IEEE Wireless Communications and Networking Conference (WCNC ’04), pp. 745–748, 2004. 17. B.G. Mobasseri, “Digital modulation classification using constellation shape,” Signal Processing, vol. 80, no. 2, pp. 251–277, 2000.
18. P. Prakasam and M. Madheswaran, “Modulation identification algorithm for adaptive demodulator in software defined radios using wavelet
transform,” International Journal of Signal Processing, vol. 5, no. 1, pp. 74–81, 2009. 19. K. Maliatsos, S. Vassaki, and P. Constantinou, “Interclass and intraclass modulation recognition using the wavelet transform,” in
Proceedings of the 18th Annual IEEE International Symposium on Personal, Indoor and Mobile Radio communications (PIMRC ’07),
September 2007.
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13.
Authors: Anurag Choubey, Ravindra Patel, J.L. Rana
Paper Title: A Survey of Efficient Algorithms and New Approach for Fast Discovery of Frequent Itemset for
Association Rule Mining (DFIARM)
Abstract: The problem of mining association rules has attracted lots of attention in the research community.
Several techniques for efficient discovery of association rule have appeared. With abundant literature published in
research into frequent itemset mining and deriving association rules, if the question is raised that whether we have
solved most of the critical problems related to frequent itemset mining and association rule discovery. Based on the
scope of the recent literature, the answer will be negative. The most time consuming operation in discovering
association rule, is the computation of the frequency of the occurrences of interesting subset of items (called
candidates) in the database of transactions. Can one develop a method that may avoid or reduce candidate generation
and test and utilize some novel data structures to reduce the cost in frequent pattern mining? This is the motivation of
my study for mining frequent-itemsets and association rules. In this paper we review some existing algorithms for
frequent itemset mining and present a proposal of our new approach.
Keywords: Data mining, Frequent Item-set mining, Association Rule Mining.
References: 1. R. Agrawal, T. Imilienski, and A. Swami, ―Mining Association Rules between Sets of Items in Large Databases,‖ Proc. of the ACM
SIGMOD Int’l Conf. On Management of data, May 1993.
2. R. Agrawal, and R. Srikant, ―Fast Algorithms for Mining Association Rules,‖ Proc. Of the 20th VLDB Conference, Santiago, Chile, 1994.
3. R. Agrawal, J. Shafer, ―Parallel Mining of Association Rules,‖ IEEE Transactions on Knowledge and Data Engineering, Vol. 8, No. 6,
Dec. 1996.
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4. B. Goethals and M. J. Zaki. Advances in frequent itemset mining implementations: report on fimi’03. SIGKDD Explorations, 6(1):109–117, 2004
5. J.S. Park, M.-S. Chen, and P.S. Yu, 1995. ―An effective hash based algorithm for mining association rules‖. In Proceedings of the 1995
ACM SIGMOD International Conference on Management of Data, volume 24(2) of SIGMOD Record, pp. 175–186. ACM Press.
6. Ashok Savasere, Edward Omieinski and Shankant Navathe, 1995. ―An Efficient Algorithm for Mining Association Rules in Large
Databases‖, Proceedings of the 21st International Conference on Very Large Data Bases, pp. 432 – 444.
7. J. Han, J. Pei, and Y. Yin. Mining frequent patterns without candidate generation. In SIGMOD, pages1–12, New York, NY, USA, 2000. ACM
8. Jiawei Han, Jian Pei, Yiwen Yin, Runying Mao. Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree
Approach. Data Mining and Knowledge Discovery, Volume 8, Issue 1, pp. 53 – 87, January 2004 9. Syed Khairuzzaman Tanbeer, Chowdhury Farhan Ahmed, Byeong-Soo Jeong, Young-Koo Lee. Efficient single-pass frequent pattern mining
using a prefix-tree, Elsevier-Information Science 179 (2008) 559-583.
10. C. Agrawal, and P. Yu, ―Mining Large Itemsets for Association Rules,‖ Bulletin of the IEEE Computer Society Technical Committee on
Data Engineering, 1997.
11. A. Freitas and S. Lavington, ―Mining very large databases with parallel processing,‖ Kluwer Academic Pub., 1998.
12. H. Mannila, H. Toivonen, and A. Verkamo, ―Efficient Algorithms for Discovering Association Rules,‖ AAAI Workshop on Knowledge
Discovery in databases (KDD-94), July 1994. 13. M. Zaki, ―Parallel and Distributed Association Mining: A Survey, ―IEEE Concurrency, 7(4), pp. 14-25, 1999.
14. M. Zaki, S. Parthasarathy, M. Ogihara, and W. Li, ―New Algorithms for Fast Discovery of Association Rules,‖ Proc. Of the 3rd Int’l Conf.
On Knowledge Discovery and data Mining (KDD-97), AAAI Press, 1997.
15. Srikant, R. and Agrawal, R., 1996. ―Mining Quantitative Association Rules in Large Relational Tables.‖ In Proc. of ACM SIGMOD Conf.
on Management of Data. ACM Press, pp. 1-12.
16. S. Kotsiantis, D. Kanellopoulos, 2006. ―Association Rules Mining: A Recent Overview‖, ESTS International Transactions on Computer
Science and Engineering, Vol.32, No. 1, pp. 71-82.
17. Erwin, A., Gopalan, R. P., and Achuthan, N. R., 2007. ―CTU-Mine: An Efficient High Utility Itemset Mining Algorithm Using the Pattern
Growth Approach‖, IEEE 7th International Conferences on Computer and Information Technology, pp. 71-76.
18. Khan, M.S. Muyeba, M. Coenen, F., 2008. ―A Weighted Utility Framework for Mining Association Rules‖, Second UKSIM European
Symposium on Computer Modeling and Simulation, pp. 87-92.
14.
Authors: M. Syed Mohamed, T. Kavitha
Paper Title: Outlier Detection Using Support Vector Machine in Wireless Sensor Network Real Time Data
Abstract: Outlier detection has many important applications in sensor networks, e.g., abnormal event detection,
animal behavior change, intruder detection etc. Outliers in wireless sensor networks (WSNs) are sensor nodes that
issue attacks by abnormal behaviours and fake message broadcasting. The probable sources of outliers include noise
and errors, events, and malicious attacks on the network. Wireless sensor networks (WSNs) are more likely to
generate outliers due to their special characteristics, e.g. constrained available resources, frequent physical failure,
and often harsh deployment area. In this project we motivate our technique in the context of the problem of outlier
detection. This paper is going to present the real time network outlier detection method in the wireless sensor
networks. We proposed the technique to classify the sensor node data as local outlier or cluster outlier or network
outlier using Standard Support Vector Machine classification method which is one of the best classification methods
among the various outlier detection methods. If the data is classified as network outlier then it may be due an event
otherwise if it is classified as a cluster outlier then it is an error in the cluster due to some environmental factor or
network otherwise is an error in the sensor node due to some defect in that sensor. Experiments with real data show
that our methodis efficient and accurate to detect the outliers in real time. The real time data are collected from the
Sensor Scope system and implemented using MATLAB.
Keywords: Outliers, Support Vector Machine (SVM), Wireless Sensor Network (WSN)
References: 1. Chandola V, A. Banerjee, and V. Kumar. Outlier detection: A survey. Technical Report, University of Minnesota, 2007
2. M. Syed Mohamed and T. Kavitha. Real Time Outlier Detection in Wireless Sensor Networks. International Journal of Latest Trends in
Computing (E-ISSN: 2045-5364) 114 . Volume 2, Issue 1, March 2011 3. Ding M, D. Chen, K. Xing, and X. Cheng, "Localized fault-tolerant event boundary detection in sensor networks," in Proceedings of IEEE
Conference of Computer and Communications Societies, 2005, pp. 902-913.
4. http: //sensorscope.epfl.ch/index.php/MainP age. 5. Luo X, M. Dong, and Y. Huang, "On distributed fault-tolerant detection in wireless sensor networks", IEEE Transactions on Computers, vol.
55, pp. 58-70, 2006.
6. M.Mohamed Sathik, M.Syed Mohamed and A. Balasubramanian. Fire Detection Using Support Vector Machine in Wireless Sensor Network and Rescue Using Pervasive Devices. International Journal of Advanced Networking and Applications 636 Volume:02, Issue:02, Pages:636-
639 (2010).
7. Rajasegarar S., C. Leckie, M. Palaniswami, and J. C. Bezdek. Quarter sphere based distributed anomaly detection in wireless sensor networks. IEEE International Conference on Communications, June 2007.
8. Tax D.M.Jand R. P. W. Duin. Support vector data description. Machine Learning, 54(1):45-66, 2004.
9. J.Platt, “Fast training of support vector machine using sequential minimal optimization,” Advances in Kernel Methods: support vector machine, MIT Press, Cambridge, MA, 1998
10. Jair Cervantes, Xiaoou Li , Wen Yu “ Multi-Class SVM for Large Data Sets Considering Models of Classes Distribution”
11. http://en.wikipedia.org/wiki/Wireless_sensor_network 12. Zhang Y, N. Meratnia, and P. Havinga. An online outlier detection technique for wireless sensor networks using unsupervised quartersphere
support vector machine. ISSNIP 2008
13. Zhang Y., N. Meratnia, and P. Havinga. Outlier detection techniques for wireless sensor networks: A survey. Technical Report, University of Twente, 2007.
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