International Journal of Recent Technology and...
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ISSN : 2277 - 3878 Website: www.ijrte.org Technology and Engineering Technology and Engineering International Journal of Recent International Journal of Recent Volume-2 Issue-2, May 2013 Volume-2 Issue-2, May 2013 Published by: Blue Eyes Intelligence Engineering and Sciences Publication Pvt. Published by: Blue Eyes Intelligence Engineering and Sciences Publication Pvt. n E d a n g i y n g e o e l r o i n n g h c e T t n e c e R I n f t o e l r n a n a t r i u o o n J l a Ijrte Ijrte Exploring Innovation www.ijrte.org E X P L O R I N G I N N O V A T ION
Transcript of International Journal of Recent Technology and...
ISSN : 2277 - 3878Website: www.ijrte.org
Technology and EngineeringTechnology and EngineeringInternational Journal of Recent International Journal of Recent
Volume-2 Issue-2, May 2013Volume-2 Issue-2, May 2013
Published by: Blue Eyes Intelligence Engineering and Sciences Publication Pvt.
Published by: Blue Eyes Intelligence Engineering and Sciences Publication Pvt.
n E d a n g i y n g e o e l r o i n n g h c e T t n e c e R I n f t o e l r na n at r i u o o n J l a
IjrteIjrte
Exploring Innovation
www.ijrte.org
EXPLORING INNOVA
TION
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 Recent Technology and Engineering (IJRTE)
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
Dr. Umakant Vyankatesh Kongre
Associate Professor, Department of Mechanical Engineering, Jawaharlal Darda Institute of Engineering and Technology, Yavatmal,
Maharashtra, India
Dr. Niranjana S
Associate Professor, Department of Biomedical Engineering, Manipal Institute of Technology (MIT) Manipal University, Manipal,
Karnataka, India
Dr. Naseema Khatoon
Associate Professor, Department of Chemistry, Integral University Lucknow (U.P), India
Dr. P. Samuel
Associate Professor, Department of English, KSR College of Engineering Tiruchengode – 637 215 Namakkal Dt. Tamilnadu, India
Dr. Mohammad Sajid
Associate Professor, Department of Mathematics, College of Engineering Qassim University Buraidah 51452, Al-Qassim Saudi
Arabia
Dr. Sanjay Pachauri
Associate Professor, Department of Computer Science & Engineering, IMS Unison University Makkawala Greens Dehradun-248009
(UK)
Dr. S. Kishore Reddy
Professor, Department of School of Electrical & Computer Engineering, Adama Science & Technology University, Adama
Dr. Muthukumar Subramanyam
Professor, Department of Computer Science & Engineering, National Institute of Technology, Puducherry, India
Dr. Latika Kharb
Associate Professor, Faculty of Information Technology, Jagan Institute of Management Studies (JIMS), Rohini, Delhi, India
Dr. Kusum Yadav
Associate Professor, Department of Information Systems, College of Computer Engineering & Science Salman bin Abdulaziz
University, Saudi Arabia
Dr. Preeti Gera
Assoc. Professor, Department of Computer Science & Engineering, Savera Group of Institutions, Farrukh Nagar, Gurgaon, India
Dr. Ajeet Kumar
Associate Professor, Department of Chemistry and Biomolecular Science, Clarkson University 8 Clarkson Avenue, New York
Dr. M. Jinnah S Mohamed
Associate Professor, Department of Mechanical Engineering, National College of Engineering, Maruthakulam.Tirunelveli, Tamil
Nadu, India
Dr. Mostafa Eslami
Assistant Professor, Department of Mathematics, University of Mazandaran Babolsar, Iran
Dr. Akram Mohammad Hassan Elentably
Professor, Department of Economics of Maritime Transport, Faculty of Maritime Studies, Ports & Maritime Transport, King Abdul-
Aziz University
Dr. Ebrahim Nohani
Associate Professor, Department of Hydraulic Structures, Dezful Branch, Islamic Azad University, Dezful, Iran
Dr. Aarti Tolia
Faculty, Prahaldbhai Dalmia Lions College of Commerce & Economics, Mumbai, India
Dr. Ramachandra C G
Professor& Head, Department of Marine Engineering, Srinivas Institute of Technology, Valachil, Mangalore-574143, India
Dr. G. Anandharaj
Associate Professor, Department of M.C.A, Ganadipathy Tulsi's Jain Engineering College, Chittoor- Cuddalore Road, Kaniyambadi,
Vellore, Tamil Nadu, India
S.
No
Volume-2 Issue-2, May 2013, ISSN: 2277-3878 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd.
Page
No.
1.
Authors: B. Shankar, D.Vidhya
Paper Title: Transitioning Residential Neighbourhoods: A Case Study of Jayalaximpuram, Mysore, India
Abstract: In India, large cities are experiencing rapid population and spatial growths. The rising land costs are
making the construction of reasonably priced. Local and Planning Authorities are encouraging to transition to
commercial retail establishments or higher-density residential uses that supports the need to supply housing
apartments by designating streets and areas. Many streets in residential areas have altered into commercial, public
and semi public activity and apartments. Transition of land uses is inevitable in large cities like Mysore. Thus, the
residential areas are affected greatly in terms of increasing density and overloading the existing infrastructure
facilities by changing dynamics of land use. With a result of this, the residential areas are transforming into mixed
land use. The City of Mysore is on the large and emerging metropolitan cities in the State of Karnataka.
Jayalaxmipuram residential neighbourhood is one among many residential areas which was developed immediately
after Independence. The neighbourhood is experiencing rapid land use transformation. The paper presents the
residential neighbourhood transformation due changing dynamics of land use in Jayalaxmipuram, Mysore and
proposes planning strategies for addressing the transitioning of residential land use.
Keywords: Transitioning, Diversity, Residential, Neighbourhood, Mixed Land Use
References: 1. Aurand, A. (2010). Density, Housing Types and Mixed Land Use: Smart Tools for Affordable Housing? Urban Studies 47(5): 1015-1036.
2. Briassoulis, E., 2000. Analysis of Land Use Change: Theoretical and Modeling Approaches. In The Web Book of the Regional Science. S.
Loveridge (Ed.). West Virginia University, Regional Research Institute, Morgantown, WV. 3. Britaldo, S. S., C. C. Gustavo, L. P. Cassio, 2001. DINAMICA – A Stochastic Cellular Automata Model Designed to Simulate the Landscape
Dynamics in an Amazonian Colonization Frontier. Ecological Modeling. 154: Pp 217-235. 4. Burnell, J.D. (1985). Industrial Land Use, Externalities, and Residential Location. Urban Studies, 22(5): 399-408.
5. Cao, T.V. And Cory, D. (1981). Mixed Land Uses, Land-Use Externalities, and Residential Property Values: A Re-Evaluation. Annals of
Regional Science 16, 1-24. 6. Cervero, R. (1989). Jobs-Housing Balance And Regional Mobility
7. Ligtenberg, A., A. K. Bregt, R. V. Lammeren, 2001. Multi Actor Based Land Use Modeling: Spatial Planning Using Agents. Land Use and
Urban Planning. 56: Pp. 21-33. 8. Planning. University Of North Carolina. Batty, M. (2007), 'Model Cities', Town Planning Review, 78(2): 125-178.
9. Post. R. B. (1 964) Criteria for Theories of Urban Spatial Structure: An Evaluation of Current Research M.A. Thesis. Chape1 Hill:
Department Of City And Regional 10. Spatial Logic of Morphological transformation, A Paradigm Of Planned - Unplanned Areas In Dhaka City, Nayma Khan, Ref 052.
11. Verburg, P. H., W. Soepboer, A. Veldkamp, R.Limpiada, V. Espaldon, S. S. A. Mastura,2002. Modeling the Spatial Dynamics of Regional
Land Use: The CLUE-S Model, Environnemental Management. 30 (3): Pp. 391–405. 12. Wang, Y., and Zhang, X., 2001. A Dynamic Modeling Approach to Simulating Socioeconomic Effects on Landscape Changes. Ecological
Modelling. 140: Pp. 141-162.
13. Xiang W-N, Clarke K C, 2003, "The Use of Scenarios in Land-Use Planning" Environment and Planning B: Planning And Design 30(6) 885 – 909
1-5
2.
Authors: K.Mohan, K.Ramanaiah, S.A.K.Jilani
Paper Title: An Enhanced Feature Selection Tool for Face Detection using Genetic Algorithm
Abstract: Various face detection techniques has been proposed over the past decade. Generally, a large number of
features are required to be selected for training purposes of face detection system. Often some of these features are
irrelevant and does not contribute directly to the face detection algorithm. This creates unnecessary computation and
usage of large memory space. In this paper we propose to enlarge the features search space by enriching it with more
types of features. With an additional seven new feature types, we show how Genetic Algorithm (GA) can be used,
within the Adaboost framework, to find sets of features which can provide better classifiers with a shorter training
time. The technique is referred as GABoost for our face detection system. The GA carries out an evolutionary search
over possible features search space which results in a higher number of feature types and sets selected in lesser time.
Experiments on a set of images from BioID database proved that by using GA to search on large number of feature
types and sets, GA Boost is able to obtain cascade of boosted classifiers for a face detection system that can give
higher detection rates, lower false positive rates and less training time but gives higher detection rates.
Keywords: Genetic Algorithm, cascade of classifiers, Adaboost, rectangle features.
References: 1. P. Viola, M. Jones, Rapid object detection using a boosted cascade of simple features, IEEE Proceedings of the Computer Vision and Pattern
Recognition Conference (CVPR), December 11-13, Hawaii, USA, 2001.
2. R. Lienhart, A. Kuranov and V. Pisarevsky. Empirical analysis of detection cascades of boosted classifiers for rapid object detection. In
DAGM'03, 25th Pattern Recognition Symposium, pages 297-304, Germany, 2003. 3. Treptow & A. Zell, Combining Adaboost Learning and Evolutionary Search to select Features for Real-Time Object Detection, Proceedings
Of the Congress on Evolutionary Computational CEC 2004, Vol. 2, 2107-2113, San Diego, USA, 2004.
4. H. Rowley, S. Baluja and T. Kanabe. Neural Network-based Face Detector, IEEE Trans. on Pattern Analysis and Machine Intelligence, 20(1), page 23-28, 2000.
5. K. Sung and T. Poggio. Example-based Learning For View-based Face Detection, IEEE Transaction on Pattern Analysis and Machine
Intelligence, 20, page 39-51, 1998. 6. H. Schneiderman and T. Kanabe. A Statistical method for object detection applied to faces and cars, International Conference on Computer
Vision and Pattern Recognition, page 1746-1759, 2000.
7. D. Roth, M. Yang and N. Ahuja. A Snowbased Face Detector, Advances in Neural Information Processing Systems 12 (NIPS 12), volume
6-11
12, 2000. 8. S.Z. Li, Z.Q. Zhang, H. Shum and H. J. Zhan. Floatboost Learning for Classification, 16th Annual Conference on Neural Information
Processing Systems (NIPS), 2002.
9. J. S. Jang and J. H. Kim. Evolutionary Prunning for Fast and Robust Face Detection, IEEE Congress on Evolutionary Computation CEC 2006, pages 1293- 1299, Vancouver, Canada, July 2006.
10. Y. Freund and R. E. Schapire. A Short Introduction to Boosting, Journal of Japanese Society for Artificial Intelligence, Vol. 14(5), pages
771-780, September 1999. 11. T. L. Seng, M. Khalid and R. Yusof. Tuning of A Neuro-Fuzzy Controller by Genetic Algorithm With An Application to A Coupled-Tank
Liquid-Level Control System, International Journal of Engineering Applications on Artificial Intelligence, Vol. 11, pages 517-529, 1998.
12. Areibi, S., Moussa, M., and Abdullah, H., A Comparison of Genetic/Memetic Algorithms and Other Heuristic Search Techniques, International Conference on Artificial Intelligence, pages 660-666, Las Vegas, Nevada, 2001.
3.
Authors: Sagar M. Gawande
Paper Title: Water Quality Assessment of “River Morna” Through Akola
Abstract: Akola is growing industrial city and also the pilgrim place in Vidarbha region of Maharashtra State
popularly known as cotton city, spreading on an area of 10 Sq.km. It is situated on the bank of “River Morna”. Nearly
65 MLD of waste water is flowing through the drainage system to the river water. Major part of the waste water is
directly discharged into the “River Morna” and further many villages on the downstream side are using the river
water for drinking and for irrigation purposes. The higher BOD, COD and other chemical and biological contents are
polluting the river water and affecting quality of soil by lowering its fertility and health effect to people of Akola. It
was intended to carry out the analysis of waste water of “River Morna”. The sampling points were decided for
collection of waste water from the “River Morna” and analysis is carried out and the results are discussed in the
paper.
Keywords: Genetic Algorithm, cascade of classifiers, Adaboost, rectangle features.
References: 1. Abbasi, S.A., Khan, F.I. and Sentilvelan, K. (1999) “Modelling of Buckingham Canal Water Quality”Indian Journal of Environmental
Health; Vol. 41, No.3, Page: 176-183. 2. Abbasi, S.A. and Vinithan, S. (1999) “Water Quality in and around an industrialization suburb of Pondicherry” Indian Journal of
Environmental Health, Vol. 41, No.4, Page: 253-263.
3. Bhatia, M.S. and Jaiswal, L. (1999)“Water quality of river Adyar in Chennai city – The River a Boon or Bane” Indian Journal of Environmental Protection, Vol. 19, No.6, Page: 412-415.
4. Borkar, P.B. and Khedkar, S.K. (2000) “Assessment of drinking water quality in Kalleru lake area with reference to Pesticides” Indian
Journal of Environmental Protection, Vol.20, No.9, Page: 668-673.
5. Dara, M.M. and Roy, N.N. (1987) “Investigation of water quality of Subarnarekha River of irrigation” Indian Journal of Environmental
Health, Vol. 29, No.4, Page: 292-298.
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4.
Authors: Umogbai, V. I.
Paper Title: Development of a Farm Level Paddy Rice Parboiling Device
Abstract: The need to improve on parboiling techniques by rural farmers in Nigeria has led to the development of a
parboiling device at the Department of Agricultural and Environmental Engineering, University of Agriculture,
Makurdi. Design and construction of a paddy rice parboiler was carried out using an empty 200 litres metal drum. It
has a soaking chamber of 0.1378 m3 with perforated floor of 570 m3 and a steaming chamber of 0.0919 m3. The
steaming chamber is directly below the soaking chamber and it is provided with two drain plugs to drain water off
from the paddy mass and the steaming chamber. A rotating grid is incorporated to serve as a stirrer. The parboiler is
mounted on a titling frame for ease of evacuation of the paddy after parboiling. Firewood was used as the source of
fuel. The evaluation of the parboiler was done using 50 kg of the long grain rice (SIPPI). The performance of the
developed parboiler was compared with the traditional method of parboiling using empty drums and the industrial
method. A water uptake test was carried out for the products of the developed parboiler, traditional and industrial
methods. Panel subjective test was used to compare the quality of the rice parboiled with the developed parboiler, the
traditional and industrial parboiler. The developed parboiler, parboiled 50 kg of rice in 30mins. The quantity of fuel
(firewood) used in parboiling was 3.6 kg at a parboiling temperature of 950C. The traditional parboiler parboiled 50
kg of rice in 3 hours and the quantity of fuel (firewood) used in parboiling was 9.8 kg at a temperature of 105 0C.
Panels’ assessment showed that the quality of rice produced by the developed parboiler is good when compared to the
traditional and industrial methods of parboiling. Overall results show a significant improvement, less time of
operation and a cheaper cost using the developed parboiler. A 0.05 significant level used to test the null hypothesis
concluded that there is no significant difference in the water uptake of the rice parboiled using the developed,
industrial and traditional parboilers at varying temperatures. With a production cost of N15,750:00 (fifteen thousand,
seven hundred and fifty naira only) and an operating cost of N400:00 (four hundred naira) which is equivalent to an
average of 4.2 tons/month capacity of 35 tons of parboiled paddy per year, the developed parboiler gives a higher
economic benefit than the traditional parboiler which cost N3,500:00 (three thousand, five hundred naira) with an
average output of 10 tons of parboiled rice per year, which is equivalent to an average of 0.83 tons/month.
Keywords: Device, Paddy, Parboiling, Rice.
References: 1. Ali, N. and Ojha, T.P. (1973) Postharvest Rice Technology: Parboiling Technology of Paddy, Paper Presented at the Regional Training
Course, University of Philipines, and Los Banos. 2. United States Agricultural Industrial Development (USAID, 2005) in partnership to increase rice production in Nigeria.
3. Rice:Wikipediaorg (2010), the Free Encyclopedia. http//www.en.wikipedia.org/wiki/Rice
4. Raghavendra, R. and Juliano, B.O. (1970) Effect of Parboiling on some Physico-Chemical Properties of Rice, Food Chem. Pp 18,289. 5. Shaheen, A.B, El Dash A.A and El Shirbeeny A.E (1975) Effect of Parboiling of Rice on the Rate of Lipid Hydrolysis and Deterioration of
16-21
Rice Bran, Cereal Chem., Pp 52,1. 6. United States Department of Agriculture (USDA 2010) National Nutrient Database for Standard Reference . Nutritional value of rice per 100
g. US annual bulleting on diet.
7. Gariboldi, F. and Houston, D.F. (1972) Parboiled Rice, in Rice: Chemistry and Technology, Amer. Assoc. Cereal Chemist, St. Paul, Minn. P 358
8. Gariboldi, .F. (1984) Rice Parboiling; an FAO Agricultural Services Bulletins, No. 56
9. Ali, N. and Ojha, T.P. (1975). Soaking characteristics of paddy. Journal of Agric. Engineering. Res(20)4, 358.8 10. en.wikipedia.org (2010)
11. Chakraverty, A. and De, D.C. (1981) Postharvest Technology of Cereals and Legumes, Oxford and IBH, New Delhi, p 331.
12. Ituen, E.U. and Ukpakha, A.C (2011). Improved method of parboiling paddy for better quality rice. World Journal of Applied Science and Technology, Vol.3 No 1.
13. www.immi.gov.an (2009)
14. Field Report (2011) Investigation carried out by the researcher. 15. Obobi, A.A. and Anazodo U.O. (1987) Development of a Rice Parboiling Machine. Agricultural Mechanization in Asia, Africa and Latin
America, vol. 18 No. 2 Spring.
16. National Cereals Research Institute (NCRI, 1994) Rice Processing, Advisory Leaflet No. 16 of NCRI Badeggi, Nigeria. 17. National Centre for Agricultural Mechanization (NCAM, 1999) Low cost Farming Equipment Technologies Brochures.
18. Ozumba, I.C. and Obiakor, S.I. (2004). Farm Level Paddy Parboiling Equipment: An improved version. National Centre for Agricultural
Mechanization(NCAM). Ilorin, Kwara State, Nigeria 19. Microsoft Excel 2007
5.
Authors: J.Alla Bagash, T.Prathap, G.Karthik
Paper Title: Power Control of a Hybrid Wind Generator for Distributed Power Generation and Grid Integration
Abstract: In this paper A dc-coupled wind/hydrogen/super capacitor hybrid power system is proposed is control the
system and is to coordinate these different sources, particularly their power exchange, in order to make controllable
the generated power. The generated power does not depend on the grid requirement but entirely on the fluctuant wind
condition. As a result, an active wind generator can be built to provide some ancillary services to the grid. The control
system should be adapted to integrate the power management strategies. Two power management strategies are
presented and compared experimentally. We found that the “source-following” strategy has better performances on
the grid power regulation than the “grid-following” strategy.
Keywords: Distributed power, energy management, hybridpower system (HPS), power control, wind generator
(WG).
References: 1. W. Li, G. Joos, and J. Belanger, “Real-time simulation of a wind turbine generator coupled with a battery supercapacitor energy storage
system,”IEEE Trans. Ind. Electron., vol. 57, no. 4, pp. 1137–1145, Apr. 2010. 2. [Online]. Available: http://www.eurobserv-er.org/
3. G. Delille and B. Francois, “A review of some technical and economic features of energy storage technologies for distribution systems
integration,” Ecol. Eng. Environ. Prot., vol. 1, pp. 40–49, 2009. 4. C. Abbey and G. Joos, “Supercapacitor energy storage for wind energy applications,” IEEE Trans. Ind. Electron., vol. 43, no. 3, pp. 769–
776, May 2007.
5. G. Taljan, M. Fowler, C. Cañizares, and G. Verbiˇc, “Hydrogen storage for mixed wind-nuclear power plants in the context of a Hydrogen Economy,” Hydrogen Energy, vol. 33, no. 17, pp. 4463–4475, Sep. 2008.
6. M. Little, M. Thomson, and D. Infield, “Electrical integration of renewable energy into stand-alone power supplies incorporating hydrogen
storage,” Hydrogen Energy, vol. 32, no. 10, pp. 1582–1588, Jul. 2007. 7. T. Zhou, D. Lu, H. Fakham, and B. Francois, “Power flow control in different time scales for a wind/hydrogen/super-capacitors based
activehybrid power system,” in Proc. EPE-PEMC, Poznan, Poland, Sep. 2008, pp. 2205–2210.
22-28
6.
Authors: Vandana Choudhary, Rajesh Mehra
Paper Title: 2-Bit CMOS Comparator by Hybridizing PTL and Pseudo Logic
Abstract: In this paper an area and power efficient hybrid comparator is proposed by hybridizing PTL and Pseudo
logic design. This hybrid comparator is proposed to improve area and power in 120 nm technology and compared
with the previous work. To improve area and power minimum number of transistor logic is used in the proposed
hybrid comparator. The proposed comparator has been designed and simulated using DSCH 3.1 and Microwind 3.1
on 120nm. Also the simulation of layout and parametric analysis has been done for the proposed comparator design.
Power and current variation with respect to the supply voltage and temperature has been performed on BSIM-4 and
LEVEL-3 on 120nm. Results show that area consumed by the proposed hybrid comparator is 40.99% on 120nm
technology. At 1.2V input supply voltage the proposed adder has shown an improvement of 42.69% in power on
BSIM-4 120nm technology
Keywords: Magnitude comparator; Binary Comparator; High speed; Low power; Hybrid PTL/PSEUDO NMOS
logic
References: 1. M. M. Mano(1991), Digital Design. Englewood Cliffs, NJ: Prentice-Hall, ch. 5.
2. N. West and K. Eshraghian(1993), Principles of CMOS VLSI Design. Reading, MA: Addison-Wesley, ch. 8.
3. C.-C. Wang, C.-F. Wu and K.-C. Tsai(1998), “1-GHz 64-b high-speed comparator using ANT dynamic logic with two- phase clocking,” Proc. Inst.Elect. Eng. Comput. Digital Techn., vol. 145, no. 6, pp. 433–436.
4. R. X. Gu and M. I. Elmasry(1996), “All-N-Logic high-speed true-single-phasedynamic CMOS logic,” IEEE J. Solid- State Circuits, vol.
31, pp.221–229, Feb. 5. S. Furber(1997), ARM System Architecture. Reading, MA: Addison-Wesley.
6. J.-S. Wang and C.-H. Huang(2000), “High-speed and low-power CMOS priorityencoders,” IEEE J. Solid-State Circuits, vol. 35, pp. 1511–
1514. 7. S. Kang and Y. Leblebici(2003), “CMOS Digital Integrated Circuit, Analysis and Design” (Tata McGraw-Hill).
8. M.Morris Mano(2002) “Digital Design” (Pearson Education Asia. 3rd Ed).
9. Bellaouar and Mohamed I. Elmasry(1995), “Low Power Digital VLSI Design: Circuits and Systems” (Kluwer Academic Publishers, 2nd
29-32
Ed). 10. Anantha P. Chandrakasan and Robert W. Brodersen(2009), “Minimizing Power Consumption in CMOS circuits”. Department of EECS,
University of California, pp.1-64.
11. S. Salivahanan and S. Arivazhagan (2004)“Digital Circuits and Design” (2nd Ed). 12. Dinesh Sharma, Microelectronics group(2010), EE Department IIT Bombay, “Logic Design”,pp.1-34
13. N. Weste and K. Eshraghian(1993) “Principles of CMOS VLSI Design: A system Perspective” (Addison- Wesley, 2nd Ed).
14. John P. Uyemura(2002) “Introduction to VLSI Circuit and Systems” (John Wiley India, ISBN: 978-81-265-0915-7). 15. R. Zimmermann and W. Fichtner(1997), “Low Power Logic Styles: CMOS Versus Pass Transistor Logic” IEEE Journal of Solid State
Circuits, Vol.32, No.7, pp1079-1090.
7.
Authors: Aditi Sandhu, Prashant Priyadarshi, Shalini Tiwari
Paper Title: GSM Based Engine & A.C Control System for Vehicles
Abstract: The main objective of this paper is to focus on a system which is developed using GSM module, KEIL
software and PROTEUS software to work as a wireless vehicle engine igniter for various vehicle engine based
application. Through this application we can take control over every module inside the vehicle which depends upon
the ignition of engine .One of the application focused in this paper is ignition of Air Conditioning system using GSM
module. The A.C inside the car usually takes ten to fifteen minutes to maintain the normal temperature. By using this
GSM module we turn ON the Vehicle A.C before a required specific time. This is done in two simple steps-Firstly
ignition of vehicle engine and Secondly ignition of A.C inside the vehicle by sending SMS by owner’s mobile. The
proceeding content will reveal a general outlook to achieve the foresaid objectives.
Keywords: GSM, Microcontroller, Relay, Proteus , Keil.
References: 1. SMS Send/Receive At Command Set. Available at: http://www.cellular.co.za/sms_at_commands.htm. 2. "Cell phone bus tracking applications developed".
3. Metro Magazine. April 2009. Retrieved 2009-11-26.
4. Mazidi Muhammad Ali; Mazidi Janice Gillispie; Rolin D. McKinlay,”The 8051Microcontroller and Embedded Systems:Using Assembly and C”, 2nd edition, published by Pearson Education,Inc, pp-237-270.
5. Robert L.Boylestad Louis Nashelsky,”Electronic Devices and Circuit Theory”,6th edition, pp-821.
6. Raj Kamal,”Architecture,Programming,Interfacing and System Design”,1st edition,published by Pearson Education,pp-83-88. 7. Vijay K.Garg; Joseph E.Wilkes, ”Principals and Applications of GSM”, 1stedition, published by Pearson Education, Inc, pp-137-175, pp-
195-209.
8. http://www.tutorialspoint.com/gsm/gsm_architecture.html dated:02/03/2013
33-38
8.
Authors: Sumedha B. Hallale, Geeta D. Salunke
Paper Title: Twelve Directional Feature Extraction for Handwritten English Character Recognition
Abstract: Directional features have been successfully used for the recognition of both machine printed as well as
handwritten characters. Selection of feature extraction method is probably the single most important factor in
achieving high performance in pattern recognition. In this paper, twelve directional features are used for the
recognition of handwritten English alphabets and numerals. The properties of similarity measure are analysed with
directional pattern matching. Then the comparison is made between recognition rate of conventional and twelve
directional feature extraction techniques. The experiment shows that directional feature extraction techniques are
better than conventional one.
Keywords: Feature extraction, Pattern recognition, Directional pattern matching, Recognition rate.
References: 1. Dayashankar Singh, Sanjay Kr. Singh, Dr. (Mrs.) Maitreyee Dutta, “Hand written character recognition using twelve directional feature input
and neural network”, ©2010 International Journal of Computer Applications (0975 – 8887) Volume 1 – No. 3.
2. Cheng-Lin Liu “Handwritten Chinese character recognition: effects of shape normalization and feature extraction”, inria 00120408, Dec
2006. 3. Bindu S Moni,G Raju “Modified quadratic classifier and directional features for handwritten Malayalam character recognition”,
Computational Science-New Dimensions and Perspectives, NCCSE, 2011.
4. M. Amrouch, Y. es-saady, “Handwritten Amazigh character recognition system based on continuous HMMs and directional features”, IJMER, vol. 2, issue 2, 2012, pp-436-411.
5. Hiromachi Fujisawa, Cheng-Lin Liu, “Directional pattern matching for character recognition revisited”, proceedings of the ICDAR 2003, 0-
7695-19601/03©2003 IEEE. 6. M. Ziaratban, K. Faez, F. Faradji, “Language-based feature extraction using template-matching in Farsi/Arabic handwritten numeral
recognition”, Ninth International Conference on Document Analysis and Recognition, pp. 297 - 301, 2007.
7. Cheng-Lin Liu, “Normalization-cooperated gradient feature extraction for handwritten character recognition”, IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 29, no. 8, August 2007.
8. Kartar Singh Siddharth, Mahesh Jangid, Renu Dhir, Rajneesh Rani, “Handwritten Gurmukhi character recognition using statistical and
background directional distribution features”, International Journal on Computer Science and Engineering (0975-3397), Vol. 3 No. 6 June 2011.
9. Weipeng Zhang, Yuan Yan Tang, Yun Xue, “Handwritten character recognition using combined gradient and wavelet feature” ,1-4244-0605-
6/06/$20.00 ©2006 IEEE 10. Anita Pal, Dayashankar Singh, “Handwritten English character recognition using neural network”, International Journal of Computer Science
& Communication Vol. 1, No. 2, July-December 2010, pp. 141-144
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9.
Authors: Ravi Kumar B
Paper Title: HVS Based Steganography
Abstract: The main aim of the project carried is to produce an efficient steganography method which can be
avoided by identified through anti-detecting agents ,the project is combination of the two method ,First method is
visual criteria and it is followed by data encryption method ,the visual criteria is the method which provide the
embedded impact values of the cover image by means of this values stegno image can avoids the pixel distortion of
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the cover image will embedding the secret message into the cover image, the experimental results later show that the
proposed information hiding system can perform well in different types of images.
Keywords: Contrast masking, Embedding, Embedding impact, Steganography.
References: 1. Willems F. and Dijk M., “Capacity and codes for embedding information in Gray-Scale Signals,” IEEE Trans. Information Theory, 2005,
pp. 1209-1214.
2. Zhang X and Wang S, “Efficient Steganographic Embedding by Exploiting Modification Direction,”IEEE Communications Letters, 2006,
pp. 781-783. 3. Fridrich J. and Filler T., “Practical methods for minimizing embedding impact in steganography, ” Proc. SPIE, 2007, pp. 650502.1-15.
4. Zhang W., Zhang X., and Wang S., “Maximizing steganographic embedding efficiency by combining hamming codes and wet paper
codes,” Proc.10th Information Hiding Conf., 2008, pp. 60-71. 5. Fridrich J., “Asymptotic behavior of the ZZW embedding construction,” IEEE Transactions on Information Forensics and Security, 2009,
pp.
6. Filler T., Judas J., and Fridrich J., “Minimizing embedding impact in steganography using trellis-coded quantization,” Proc. SPIE, Electronic Imaging, Media Forensics and Security XII, San Jose, CA,January 17, 2010, pp. 501-514.
10.
Authors: Ketki Muzumdar, Ravi Mante, Prashant Chatur
Paper Title: Neural Network Approach for Web Usage Mining
Abstract: Web usage mining attempts to discover useful knowledge from the secondary data obtained from the
interactions of the users with the Web. Web usage mining has become very critical for effective Web site
management, business and support services, personalization, and network traffic flow analysis and so on. Previous
study on Web usage mining using a concurrent Clustering, Neural based approach has shown that the usage trend
analysis very much depends on the performance of the clustering of the number of requests. In this paper, a novel
approach Self Organizing Map is introduced, which is a kind of neural network, in the process of Web Usage Mining
to detect user’s patterns. We are going to analyze the traditional K-Means algorithm result with comparison to SOM.
The process details the transformations necessaries to modify the data storage in the Web Servers Log files to an
input of SOM.
Keywords: Clustering, K-Means, SOM, Web Server Log File, Web Usage Mining
References: 1. R. Kosala, H. Blockeel, “Web Mining Research: A Survey”, SIGKKD Explorations, vol. 2(1), July 2000.
2. Magdalini Eirinaki , Michalis Vazirgiannis, “Web Mining for Web Personalization”, ACM Transactions on Internet Technology, Vol. 3, No. 1, February 2003.
3. J. Srivastava, R. Cooley, M. Deshpande, P.-N. Tan, “Web Usage Mining: Discovery And Applications Of Usage Patterns From Web Data”,
SIGKKD Explorations, vol.1, Jan 2000. 4. Vinita Shrivastava, “Web Usage Data Clustering Using Neural Network Learning”, IJRIM Vol. 1, No. 2 , June, 2011.
5. Navin Kumar Tyagi, A.K. Solanki& Sanjay Tyagi, “An Algorithmic Approach To Data Preprocessing In Web Usage Mining” International
Journal of Information Technology and Knowledge Management, Vol. 2, No. 2, July-December 2010, pp.: 279-283. 6. Masseglia, F., Poncelet, P., And Cicchetti, R. (1999). “WebTool: An integrated framework for data mining”, In Proceedings of the Ninth
International Conference on Database and Expert Systems Applications (DEXA’99) (Florence, Italy, August1999, pp.: 892–901.
7. Spiliopoulou, M. And Faulstich, L. C.. “WUM: A web utilization miner”, Proceedings of the International Workshop on the Web and Databases (Valencia, March) 1998.
8. Perkowitz, M. And Etzioni, O. 2000. “Towards adaptive web sites: Conceptual framework and case study”, In Artif. Intell. 118, 1–2,pp.:
245–275. 9. Mobasher, B., Dai, H., Luo, T., Sung, Y., And Zhu, J. 2000c. “Integrating web usage and content mining for more effective
personalization”, In Proceedings of the International Conference on Ecommerce and Web Technologies (ECWeb2000). (Greenwich, UK, Sept.).
10. Paola Britos, Damián Martinelli, Hernán Merlino, Ramón García-Martínez, “Web Usage Mining Using Self Organized Maps”, IJCSNS
International Journal of Computer Science and Network Security, VOL.7 No.6, June 2007. 11. A.M. Mora, C.M. Fernandes, J.J. Merelo, V. Ramos, J.L.J. Laredo, A.C. Rosa, “Kohonants: A Self-Organizing Ant Algorithm For
Clustering And Pattern Classification”, Artificial Life XI 2008.
12. Santhi, S.Shrivasan.P ,“An improved Usage Mining using Back Propagation Algorithm With Functional Update” , Advance computing Conference, IACC 2009.
13. Prakash S Raghavendra, Shreya Roy Chowdhury, Srilekha Vedula Kameswari, “Web Usage Mining Using Statistical Classifiers And Fuzzy
Artificial Neural Networks”, International Journal Multimedia and Image Processing (IJMIP), Volume 1, Issue 1, March 2011. 14. A. Jirayusakul, S. Auwatanamongkol, “A Supervised Growing Neural Gas Algorithm for Cluster Analysis”, International Journal of Hybrid
Intelligent Systems 3 2006.
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11.
Authors: Alok Kumar, Surya Bhushan Dubey
Paper Title: Enhancement of Transient Stability in Transmission Line Using SVC Facts Controller
Abstract: This paper will discuss and demonstrate how Static Var Compensator (SVC) has successfully been
applied to control transmission systems dynamic performance for system disturbance and effectively regulate system
voltage. SVC is basically a shunt connected static var generator whose output is adjusted to exchange capacitive or
inductive current so as to maintain or control specific power variable; typically, the control variable is the SVC bus
voltage. One of the major reasons for installing a SVC in transmission line is to improve transient stability of a line.
Static VAR Compensator is a shunt connected FACTS devices, and plays an important role as a stability aid for
dynamic and transient disturbances in power systems. UPFC controller is another FACTS device which can be used
to control active and reactive power flows in a transmission line. The damping of power system oscillations after a
three phase fault is also analyzed with the analyzation of the effects of SVC on transient stability performance of a
power system. A general program for transient stability studies to incorporate FACTS devices is developed using
modified partitioned solution approach. The modeling of SVC for transient stability evaluation is studied and tested
on a 10-Generator, 39 - Bus, New England Test System.
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Keywords: SVC Facts Controller, Transient stability, Matlab.
References: 1. R.Mihalic, P. Zunko and D.Povh, “Improvement of Transient Stability using Unified Power Flow Controller”, IEEE Transactions on Power
Delivery, Vol. 11, No.1, Jan.1996, pp.485-491 2. K.R.Padiyar, “Power System Dynamics: Stability and Control”, Second Edition, BS Publications, Hyderabad, 2002.
3. Igor Papic, Peter Zunko “Mathematical Model and Steady- State Operational Characteristics of a Unified Power Flow Controller”, Electro
technical Review 2002, Slovenija, 69 (5), pp. 285-290 4. N.G. Hingorani and L.Gyugyi, “Understanding FACTS”, IEEE press, 1999
5. K.R. Padiyar and A.M. Kulakarni, “Control Design and Simulation of Unified Power Flow Controler”, IEEE Trans. On Power Delivery, pp:
1348-1354, Oct- 1, 1997 6. N.Mithulananthan, Claudio A.Canizares, John Reeve and Graham J.Rogers, “Comparison of PSS, SVC and STATCOM Controllers for
Damping Power system Oscillations”, IEEE transactions on Power system, October 2002.
7. Nang Sabai, and Thida Win (2008) “Voltage control and dynamic performance of power transmission system using SVC” World Academy of Science, Engineering and Technology 42 Pp. 425-429
8. [S. Sankar (2010),”Simulation and comparison of various FACTS Devices in power system” International journal of Engg Science And
Technology Vol.2 (4),Pp. 538-547 9. D. Murali (October 2010),”Comparison of FACTS devices for power system stability enhancement “. International Journal of Computer
Applications (0975 – 8887) Volume 8– No.4, Pp. 30-35
10. H. Yazdanpanahi ,”Application of FACTS devices in transmission expansion to overcome the problems related to delays”.
11. Bindeshwar singh, N.k Sharma and A.N Tiwari (2010),” A comprehensive survey of coordinated control techniques of FACTS controllers
in multi machine power system environments “International Journal of Engineering Science and Technology Vol. 2(6), 1507-1525.
12. Christian Rehtanz April (2009) ,”New types of FACTS devices for power system security and efficiency” Pp-1-6 13. M.A Abibo ,”Power System stability enhancement using FACTS controllers “The Arabian Journal for Science and Engineering Volume 34,
Pp. 153-161
14. Edris Abdel, “Series Compensation Schemes Reducing the Potential of Sub synchronous Resonance, “IEEE Trans. On power systems, vol. 5 No. 1. Feb1990. Pp. 219-226
15. Hatziadoniu C. J. and Funk A. T., “Development of a Control Scheme for Series- Connected Solid-State Synchronous Voltage Source,”
IEEE Transactions on Power Delivery, Vol. 11, No. 2, April 1996, pp. 1138–1144. 16. Kimbark I W.’Direct Current Transmission Vol-I.’Wiley, New York, 1971.
17. Liu Y. H., Zhang R. H., Arrillaga J., and Watson N. R., “An Overview of Self-Commutating Converters and Their Application in
Transmission and Distribution”, 2005 IEEE/PES Transmission and Distribution Conference and Exhibition: Asia and Pacific, Dalian, China, 2005.
18. Litzenberger Wayne H., (ed.), An Annotated Bibliography of High-Voltage Direct-Current Transmission and Flexible AC Transmission
(FACTS) Devices, 1991-1993. Portland, OR, USA: Bonneville Power Administration and Western Area Power Administration, 1994. 19. Padiyar K. R., Pai M. A., and Radhakrishna C., “Analysis of D.C. link control for system stabilization,” in Proc. Inst. Elect. Eng. Conf. Publ
. No. 205, London, U.K., 1981.
20. PSCAD/EMTDC, User’s Guide, Manitoba-HVDC Research Centre. Winnipeg, MB, Canada, Jan. 2003.[21] Padiyar K.R.’HVDC Power
Transmission System.’ Wiley Eastern, New Delhi, 1993).
21. Rudervall Roberto, Johansson Jan, “Interconexion de sistemas eléctricos con HVDC”. Seminario internacional de interconexiones regionales CIGRE, Santiago de Chile, Noviembre 2003.
22. Stella M., Dash P. K., and Basu K. P. “A neuro-sliding mode controller for STATCOM,” Elect. Power Compon. Syst., vol. 32, pp. 131–
147, Feb. 2004. 23. Szechtman M., Wees T., and Thio C. V., “First benchmark model for HVDC control studies,” Electra, no. 135, pp. 54–67, Apr. 1991.
24. Sen K. K., “SSSC—Static Synchronous Series Compensator: Theory, Modelling, and Applications,” IEEE Transactions on Power Delivery,
Vol. 13, No. 1, January 1998.
12.
Authors: S.M.Mehzabeen, I.Manju
Paper Title: Efficient Optimization Of FPGA On-Chip Memory For Image Processing Algorithm
Abstract: This paper is concerned with efficient optimization and low power implementation of FPGA on-chip
memories in image processing algorithms. In recent years on chip memories are expected to increase continuously
which depends upon the application for future generation portable devices and high performance processors. Memory
plays a major role in image processing applications more than 90% of the consumed power in the system is by the
memory part. This paper provides a novel approach by making SPSRAM to function like a DPSRAM. It supports
most of the access schemes for Image processing algorithms and also when the readout changes the memories need
not to be redesigned. It achieves high throughput, less hardware requirement and high bandwidth utilization. The
full bandwidth utilization has been achieved by splitting the on-chip memory into four sub banks. The Optimization
of power can be done by making any two banks active at a time.It is well suited for various image coding algorithms
when compared to the typical SPSRAM and TDP SRAM.It finds applications in most of the parallel processing
fields.GENERAL TERMS Design, measurement, performance, theory
Keywords: Bandwidth utilization, Field programmable gate array, Power optimization, SRAM, access schemes in
image processing, TDP SRAM.
References: 1. K.Compton, S.Hauck, Reconfigurable computing: a survey of systems and software, ACM Comput. Surv. 34(2002)171–210.
2. Ranjith kumar volkankursun, Temperature adaptive voltage scaling for enhanced energy efficiency in subthreshold memory arrays
,Microelectron J.40(2009) 1013-1025.
3. Altera corporation,Embedded Design Hand book,Chapter 7,Memory System Design (2010).
4. F. Francisco, F. Mariano, C. Enrique, Run-time self-reconfigurable 2D convolver for adaptive image processing, Microelectron. J. 42 (2011) 204–217.
5. ARM Architecture Reference Model, ARM DDI 0100l (2005).
6. P.Deepa,C.vasanthanayaki,FPGA based efficient on-chip memory or image processing algorithm.Microelectron.J(2012). 7. Yan Wang, Shoushun Chen and Amine Berma k smart,Novel VLSI implementation of Peano-Hilbert curve Address Generator,Sensory
Integrated Systems Lab Electronic and Computer Engineering Department,Hong kong University of science and technology. 8. G.S. Sohi, M. Franklin, High-bandwidth data memory systems for superscalar processors, SIGOPS Oper. Syst. Rev. 25 (Special Issue)
(1991) 53–62.
9. S. Heithecker, A. do Carmo Lucas, R. Ernst, A mixed QoS SDRAM controller for FPGA-based high-end image processing, in: SIPS, IEEE
57-61
Workshop Signal Process. Syst. 2003 (2003) 322–327. 10. Muhammad M.Khellah,Member,IEEE and Mohamed I.Elmasry,Fellow,IEEE,A Low power High performance current mode multiport
SRAM,IEEE Transactions on VLSI,Vol.9,No .5,October 2004.
11. Houman Homayoun, member, IEEE, Avesta Sasan, Member, IEEE, Alexander V.Veidenbaum, member, IEEE,Hsin Cheng Yao, Shahin Golsan,and Payam Heydari, senior Member, IEEE MZZ-HVS Multiple sleep modes Zig-zag horizontal and vertical sleep transistor sharing
to reduce leakage power in on-chip SRAM peripheral circuits,IEEE transactions on VLSI systems,Vol.19,No.12,December 2011.
12. Srinivas R.Sridhara,Member, IEEE,Michael Direnzo, Member, IEEE, Srinivas Lingam, Member, IEEE,Seok-Jun Lee, Member, IEEE, Raul Blazquez, Member, IEEE,Jay Maxey, Member, IEEE, Samer Ghanem,Yu-Hung Lee,Rami Abdallah, PrashantSingh, Member,IEEE, and
Manish Goel, Member, IEEE, Microwatt Embedded Processor Platform for Medical System-on-Chip Applications,IEEE Journal of Solid-
state circuits,Vol.46,No.4,April,2011. 13. P. Ranganathan, S. Adve, N.P. Jouppi, Reconfigurable caches and their application to media processing, Proceedings of the 27th
International Symposium on Computer Architecture, USA. (2000) pp. 214–224.
14. Q. Liu, G. Constantinides, K. Masselos, P. Cheung, Automatic on-chip memory minimization for data reuse, in: 15th Annual IEEE Symposium on Field- Programmable Custom Computing Machines. (2007) pp. 251–260.
15. S.S. Ang, G.A. Constantinides, W. Luk, P.Y.K. Cheung, Custom parallel caching schemes for hardware accelerated image compression, J.
Real-Time Image Proc. 3 (2008) 289–302. 16. ARM Architecture Reference Model, ARM DDI 0100l (2005).
13.
Authors: Mehboob Ul Amin, Randhir Singh, Javaid.A.Skeikh
Paper Title: A New Method for PAPR Reduction in MIMO- OFDM Using Combination of OSTBC Encoder and
DCT Matrix
Abstract: Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) is an
attractive air-interface solution for next generation wireless local area networks (WLANs), wireless metropolitan area
networks (WMANs), and fourth generation mobile cellular wireless systems. However one of the main disadvantage
associated with MIMO-OFDM systems is the high peak-to-average power ratio (PAPR) of the transmitter’s output
signal on different antennas. High Peak to Average Power Ratio (PAPR) for MIMO-OFDM system is still a
demanding area and difficult issue. So far numerous techniques based on PAPR reduction have been proposed. In this
paper a new technique based on the combination of Orthogonal Space Time Block Code (OSTBC) Encoder and
Discrete Cosine Transform based Selective Level Mapping as method of PAPR reduction technique has been
proposed and simulated. The results have been verified in terms of various graphs and plots and are compared with
earlier results of embedded transform techniques. Simulations show that better results are obtained in the proposed
technique
Keywords: Multiple Input Multiple Out (MIMO), Peak to Average Power Ratio (PAPR) ,Orthogonal Space Time
Block (OSTBC) Encoder, Discreet Cosine Transform (DCT), Complementary Cumulative Distribution Function
(CCDF).
References: 1. A.J Paulraj, R.U Nabar, and D.A.Gore, “ Introduction to Space-Time wireless communications, Cambridge, UK Cambridge, univ
press,2003 2. N.Chan and G.T.Zhou, “Peak-to-average power ratio reduction in OFDM with blind selected pilot tone modulation,” Proc.IEEE
Intl.Conference on Acoustics,Speech, and siginal processing, Mar 2005
3. H.Ochiai and H.Imai, “Performance analysis of deliberately clipped OFDM signals,” IEEE Trans commum,vol.50, pp 89-101, Jan 2002 4. Mehboob ul Amin,et al, “Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) Based Image
Transmission Using Hadamard Transform as PAPR Reduction Technique,” International Journal of Engineering and advanced Technology
(IJEAT) vol 2, Issue 4,pp 550-553,April 2013 5. V.Taron, N Seshadri, and A.R Calderbank, “Space-Time codes for High Data Rates wireless communication : Performance critorian and
code construction.” IEEE Trans.Info.Theory,Vol.44 no.2, Mar-1998, pp 744-65.
6. L.Zheng and D.N.C.Tsc, “Diversity and Multipexing: A Fundamental Trade Off in Multiple Antenna channels,” IEEE Trans.Info theory, vol 49,no.5, May 2003, pp 1073-96
7. M.Borgmann and H Bolckei, “Interpolation-Based Efficient Matrix Inversion for MIMO-OFDM receivers,” Proc. 38th Asilomar conf.
signals,syst,and computers,Pacific Grove, C.A.Nov.2004,pp 1941-47
8. G.Caire, G.Taricco,and E.Biglien, “Bit-Interleaved Coded Modulation”, IEEE Trans.Info.Theory, vol.44,no.3,May 1998,pp 927-46
9. H.Boclcskei and A.J Paulraj, “Space-Frequency coded Broadband OFDM systems,” Proc IEEE wireless commum.and Networking conf. ,
Chicago, Sept 2000, pp 1-6 10. T Rouphael, RF and Digital Processing for Softwere Defined Radio,Ist Edition Print Book,Nov 2008
11. K.yong, S.chang, “Peak-to-Average power control in OFDM using standard Arrays of linear Block codes,”IEEE communication letters,
vol,7 no 4,April 2003 12. C.Tellamura, Computation of Continous-Time PAR of an OFDM signal with BPSK subcarriers,IEEE communication letter,vol 5,no.5,may
2000.
13. S.M.Alamouti, “A simple transmit diversity technique for wireless communication,” IEEE journal on selected Areas in communications, vol 16,no.8,pp-1451-1458,oct,1998
14. V.Tarokh, H.Jafarkhami and A.R.Calderbank, “Space-time block codes from orhogonal designs,” Information Theory, vol.45,no.5,
pp.1456-1467,jul,1999 15. M.Jankiraman, Space-Time codes and MIMO systems.Artech House Publishers,2004.
16. M. E. Gärtner and H. Bölcskei, “Multi-User Space-Time/Frequency Code Design,” Proc. IEEE ISIT, Seattle,WA, July 2006.
17. Yong soo Cho, Jeakwonkin,Won Young Yang,” MIMO – OFDM wireless Communication with MATLAB,” Joh Wilong and Sons (Asia) PVT Ltd. 2010
18. G.L Stuber, JR Barry, S.W.mclaughlin, M.A.Ingram, T.G Pratt, “BroadBAND MIMO-OFDM wireless Communications,” Proceedings of
the IEEE, VOL .92 No.2, Februry 2004
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14.
Authors: R.Murali, P. Nagasekhara Reddy, B. Asha Kiran
Paper Title: Power Quality Enhancement of Distributed Network fed with Renewable Energy Sources based on
Interfacing Inverter
Abstract: Renewable energy technologies such as photovoltaics, solar thermal electricity using dish-stirling systems,
and wind turbine power are environmentally advantageous sources of energy that can be considered for electric
power generation. The expenses of renewable energy technologies have decreased in recent years, so that an
ever-increasing number of applications can be economically justified by utilities. The integration of generation
from renewable energy sources into electric power distribution systems is a reasonable way for electric utilities
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to apply renewable energy resources, since it places the sources near the load with more efficient operation. The
interfacing inverter is controlled to perform as a multi-function device by incorporating active power filter
functionality and this inverter is used to inject power generated from Renewable Energy Sources to the grid. The
objectives of this paper is to develop an assessment methodology for renewable energy electric generation and
energy storage facilities integrated into electric power distribution systems which addresses the distributed
benefits of electricity generation from renewable sources and their true value to the system, and to apply the
methodology in case studies. The renewable energy sources which are interconnected to distributed network with
interfacing power electronic inverter is analyzed for power quality enhancement by using MATLAB/SIMULINK
software.
Keywords: Renewable Energy Sources (RES), interfacing inverter, Power Quality, Active power filter .
References: 1. . S. Shugar, “Photovoltaics in the Utility Distribution System: The Evaluation of System and Distribution Benefits,” IEEE Trans. on
Power Apparatus and Systems, Paper No. 0160-8371/90/0000-0836, 1990.
2. A.Ananda Kumar, J.Srinivasa Rao “Power Quality Improvement of Grid Interconnected 3-phase 4-wire Distribution System using Fuzzy logic control” “International Journal of Engineering Research & Technology (IJERT), Vol. 1 Issue 4, June - 2012 .
3. Yongning Chi, Yanhua Liu, Weisheng Wang, “Voltage Stability Analysis of Wind Farm integration into Transmission Network” IEEE
Trans. Energy Conversion, vol. 21, issue 1, pp. 257-264, March. 2006.
4. J. M. Guerrero, L. G. de Vicuna, J. Matas, M. Castilla, and J. Miret,“A wireless controller to enhance dynamic performance of parallel
inverters in distributed generation systems,” IEEE Trans. Power Electron., vol. 19, no. 5, pp. 1205–1213, Sep. 2004.
5. Bhim Singh, Kamal Al-Haddad, Senior Member, IEEE, and Ambrish Chandra, Member, IEEE "A Review of Active Filters for Power Quality Improvement",” IEEE Trans.Iind. Elec-tron., vol. 46, no. 5, Sep. 1999.
6. AswathyB.Raj , B. Shyam, Robins Anto“Simulation of Distributed Generation Power Inverter as Active Power Filter using
MATLAB/Simulink.” International Journal on Recent Trends in Engineering and Technology ,Vol.6, No.2,Nov 2011. 7. R. Karki and P. Hu, “Wind power simulation model for reliability evaluation,” in Electrical and Computer Engineering, 2005. Canadian
Conference on, Los Alamitos, CA, 2005, pp. 541–544.
8. P. Jintakosonwit, H. Fujita, H. Akagi, and S. Ogasawara, “Implementation and performance of cooperative control of shunt active filters for harmonic damping throughout a power distribution system,” IEEE Trans. Ind. Appl., vol. 39, no. 2, pp. 556–564, Mar./Apr. 2003.
9. U. Borup, F. Blaabjerg, and P. N. Enjeti, “Sharing of nonlinear load in parallel-connected three-phase converters,” IEEE Trans. Ind. Appl.,
vol. 37, no. 6, pp. 1817–1823, Nov./Dec. 2001. 10. J. H. R. Enslin and P. J. M. Heskes, “Harmonic interaction between a large number of distributed power inverters and the distribution
network,” IEEE Trans. Power Electron., vol. 19, no. 6, pp. 1586–1593, Nov. 2004.
15.
Authors: Rajni Bala, Jaswinder Singh
Paper Title: Effect on Multiband Behavior of Square Fractal Dipole Antenna with the Variation of Angle between
Square Fractals
Abstract: In this paper the design of square shape multiband dipole antenna using fractal geometry is described. The
fractal antenna has been designed on substrate FR-4 having thickness h=1.4mm, ∈_r= 4.4 with dimension 70×35mm.
Ansoft HFSS software has been used to design and simulate the antenna. The antenna exhibit multiband resonances
due to the self similarity in its structure. Firstly antenna was designed up to fourth iteration by keeping angle of 450
between adjacent squares. The experimental result indicates that the antenna resonates at six frequencies 0.75GHz,
2.15 GHz, 3.35 GHz, 4.65 GHz, 5.95 GHz and 7.25 GHz. It is observed that the multiband behavior of antenna is
affected by the variation in angle between adjacent square fractals. In same design when angle between adjacent
square fractals is reduced up to 100 the resonance frequencies also get reduced up to three, but at these three resonant
frequencies the percentage of bandwidth get increased which means antenna shows wideband behavior.
Keywords: Multiband antenna, Fractal, Resonant frequency
References: 1. B.B. Madelbrot, “The Fractal Geometry of Nature” New York: W.H. Freeman, 1983.
2. Brendt Wohlberg and Gerhard de Jager, “A Review of the Fractal Image Coding Literature”, IEEE Transactions on Image Processing, Vol.
8, No. 12, December 1999. 3. Alexandru Bogdan, “The Fractal Pyramid with application to Image coding” IEEE Conf. ICASSP-95.May 1995.
4. Akhlesh Lakhtaiua, Neal S. Holter, Vuay K.Varadan, “Self-Similarity in Diffraction by A Self-Similar Fractal Screen” IEEE Transactions on
Antennas Propagation, Vol. Ap-35, No. 2, February 1987. 5. Aleksandr Nikolaevich Bogolyubov, Artem Aleksandrovich Koblikov, and Natalia Evgenievna Shapkina “Fractal Electrodynamics: Analysis
and Synthesis of Fractal Antenna Radiation Pattern” Progress in Electromagnetics Research Symposium Proceedings, Moscow, Russia,
August 2009. 6. George Palasantzas,” Roughness spectrum and surface width of self affine fractal surfaces via the K correlation model” Physical review,
Volume 48 No.19 november1993.
7. Yongping Chen, Chengbin Zhang, Mingheng Shi, and G. P. Peterson, “Role of surface roughness characterized by fractal geometry on laminar flow in microchannels” Physical Review E 80, 026301 _2009.
8. Douglas H. Werner' and Suman Gangul, “An Overview' of Fractal Antenna Engineering Research” IEEE Antennas and Propagation
Magazine, Vol. 45, NO. I Februarv 2003. 9. N. Cohen, “Fractal antenna applications in wireless telecommunications,” in Professional Program Proc. of Electronics Industries Forum of
New England, 1997,IEEE, pp. 43-49, 1997.
10. C. Puente, J. Romeu, R. Pous, Ramis and A. Hijazo, “Small but long Koch fractal monopole”, Electronics Letters 8th January 1998 Vol. 34 No. 7.
11. Aggarwal and M. V. Kartikeyan, “Pythagoras Tree: A Fractal Patch Antenna for Multi Frequency and Ultra-Wide Bandwidth operations”
Progress in Electromagnetics Research C, Vol. 16, 25-35, 2010. 12. Raj Kumar1 and P. Malathi2, “On the Design of Wheel Shape Fractal Antenna” International Journal of Recent Trends in Engineering, Vol 2,
No. 6, November 2009.
13. Kuem C. Hwang, “A Modified Sierpinski Fractal Antenna for Multiband Application” IEEE Antennas and Wireless Propagation Letters, Vol. 6, 2007.
72-75
16. Authors: Niketa Vishwanath Patil, S.U.Kadam
Paper Title: Thermal Recognition in Biometrics Approach
Abstract: Humans recognize each other according to their various characteristics for ages. We recognize others by
their face when we meet them and by their voice as we speak to them. Identity verification (authentication) in
computer systems has been traditionally based on something that one has (key, magnetic or chip card) or one knows
(PIN, password). Things like keys or cards, however, tend to get stolen or lost and passwords are often forgotten or
disclosed. To achieve more reliable verification or identification we should use something that really characterizes the
given person. Biometrics offer automated methods of identity verification or identification on the principle of
measurable physiological or behavioural characteristics such as a fingerprint or a voice sample. The characteristics
are measurable, unique and these characteristics should biometrics not be duplicable. Proper design and
implementation of the biometric system can indeed increase the overall security; especially the smartcard based
solutions seem to be very promising. Making a secure biometric systems is, however, not as easy as it might appear.
The word biometrics is very often used as a synonym for the perfect security
Keywords: Biometrics, Facial Recognition, Fingerprint Matching, Palm Geometry, Thermal face recognition,
Thermal recognition
References: 1. D. A. Socolinsky and A. Selinger, “A comparative analysis of face recognition performance with visible and thermal infrared imagery,”
in Proceedings ICPR, Quebec, Canada, August 2002. 2. D.A. Socolinsky and A. Selinger, “Face recognition with visible and thermal infrared imagery,” Computer Vision and Image
Understanding, July - August 2003. [3] Joseph Wilder, P. Jonathon Phillips, Cunhong Jiang, and Stephen Wiener, “Comparison of Visible
and Infra-Red Imagery for Face Recognition,” in Proceedings of 2nd International Conference on Automatic Face & Gesture Recognition, Killington, VT, 1996, pp. 182
3. X. Chen, P. Flynn, and K. Bowyer, “Visible-light and infrared face recognition,” in Proceedings of the Workshop on Multimodal User Authentication, Santa Barbara, CA, December 2003, to appear.
4. B. Abidi, “Performance comparison of visual and thermal signatures for face recognition,” in The Biometrics Consortium Conference,
Arlington, VA, September 2003. 5. F. J. Prokoski, “History, Current Status, and Future of Infrared Identification,” in Proceedings IEEE Workshop on Computer Vision Beyond
the Visible Spectrum: Methods and Applications, Hilton Head, 2000.
6. P. Jonathon Phillips, Hyeonjoon Moon, Syed A Rizvi, and Patrick J. Rauss, “The FERET Evaluation Methodology for Face-Recognition Algorithms,” Tech. Rep. NISTIR 6264, National Institiute of Standards and Technology, 7 Jan. 1999.
7. X. Chen, P. Flynn, and K. Bowyer, “PCA-based face recognition in infrared imagery: Baseline and comparative studies,” in International
Workshop on Analysis and Modeling of Faces and Gestures, Nice, France, October 2003. 8. Yael Adini, Yael Moses, and Shimon Ullman, “Face Recognition: The Problem of Compensating for Changes in Illumination Direction,”
IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 721–732, July 1997.
9. P. J. Phillips, D. Blackburn, M. Bone, P. Grother, R. Micheals, and E. Tabassi, “Face recognition vendor test 2002 (FRVT 2002),” Available at
10. http://www.frvt.org/FRVT2002/default.htm, 2002.
11. Authors, “Thermal face recognition in an operational scenario,” in Submitted to CVPR 2004. 12. A. Ross and A. Jain,”Information fusion in biometrics. Pattern Recognition Letters”, 2003.
76-79
17.
Authors: P. Sumitra
Paper Title: A New, Fast and Efficient Wavelet Based Image Compression Technique Using JPEG2000 with
EBCOT versus SPIHT
Abstract: A wavelet is a function like a small wave and a ripple of baseline. The Wavelet Transform (WT) is a
technique for analyzing signals. It was developed as an alternative to the Short Time Fourier Transform (STFT) to
overcome the problems related to its frequency and time resolution properties. Wavelet can be used to represent data
as diverse as heart beats and television signals, in a way that reduces redundancy within the signal. Therefore it can
be used for image compression. This paper focuses important features of wavelet transform in compression of still
images, including the extent to which the quality of image is degraded by the process of wavelet compression and
decompression. The techniques used are Set Partitioning In Hierarchical Trees (SPIHT) and Embedded Block Coding
Optimal Truncation Code (EBCOT). These techniques are more efficient and provide a better quality in the image. In
compression, wavelets have shown a good adaptability to a wide range of data, while being of reasonable complexity.
The above techniques have been successfully used in many applications. The techniques are compared by using the
performance parameters PSNR. Images obtained with those techniques yield very good results.
Keywords: EBCOT, JPEG2000, SPIHT, DWT, VQ, SQ
References: 1. Ronald A. DeVore, Bjorn Jawerth and Bradley J.Lucier, “ Image Compression Through Wavelet Transform Coding”, IEEE Transactions on
Information Theory, Vo.38, pp. 719-746,March 1992.
2. Othman O. Khalifa, Sering Habib Harding and Aisha-Hassan A. Hashim,” Compression using Wavelet Transform”, Signal Processing: An
International Journal (SPIJ) , Volume(2), Issue(5) pp. 17-26. October 2008. 3. Harmanpreet kaur , Ramanpreet kaur, “Speech compression and decompression using DWT and DCT”, International Journal of Computer
Technology & Applications, Vol 3(4), pp. 1501-1503, July-August 2012.
4. Manik Groach and Dr. Amit Garg, “ DCSPIHT: Image Compression Algorithm”, International Journal of Engineering Research and Applications(IJERA), Vol.2, Issue 2, pp. 560-567, Mar-Apr 2012.
5. Bibhuprasad Mohanty, Abhishek Singh and Dr. Sudipta Mahapatra,” A High Performance Modified SPIHT for Scalable Image
Compression”, International Journal of Image Processing (IJIP), Vol. 5, pp. 390-402, 2011. 6. V. Rehna, J. S. Shubhangi and S. Vasanthi, “Improving the performance of wavelet based image compression using SPIHT algorithm”,
IRNet Transactions on Electrical and Electronics Engineering (ITEEE) , Vol-1, Issue-2, pp. 2319-2577, 2012. 7. Adeel Abbas and Trac D. Jran,”Rational Coefficient Dual-Tree Complex Wavelets Transform: Design and Implementation”, IEEE
Transactions on Signal Processing, Vol. 56, pp. 3523-3531,2008.
8. Tinku Acharya and Chaitali Chakrabarti, “A Survey on Lifting-base Discrete Wavelet Transform Architectures “, Journal of VLSI Signal Processing, Vol. 42, pp. 321-339, 2006.
9. Chengyi Xiong, Tiawen Tian and Jian Liu, “Efficient Architectures for Two-Dimensional Discrete Wavelet transform Using Lifting
80-84
Scheme”, IEEE Transactions on Image Processing, Vol. 16, pp. 607-614, 2007. 10. Shirpra Gupta and Chirag Sharma,” A Novel Technique in SPIHT for Medical Image Compression’, Vol. 4, issue 1, pp. 01-08,January –
April 2013,
11. Meng Wang and Qi-rui Han,” An Improved Algorithm of SPIHT based on the Human Visual Characteristics”, World Academy of Science, Engineering and Technology 17, pp. 1134-1137, 2008.
12. Sadashivappa Mahesh Jayakar, K.V.S Anand Babu and Dr. K. Srinivas, “ Color Image Compression using SPIHT Algorithm”,
International Journal of Computer Applications, Vol. 16, No.7, February 2011. 13. Said and A. Pearlman, “Image compression using Spatial-orientation tree”, in Proceedings IEEE International Symp. Circuits and Systems,
Chicago, IL, pp. 279-282, May 1993.
14. Said and W. Pearlman, “A New, fast and Efficient Image Codec based on Set Partitioning in Hierarchical Trees”, IEEE Transactions of Circuits and Systems for Video technology, Vol.6, No. 3, pp. 243-250, June 1996.
15. Andrew P. Bradley and Fred W.M. Steniford ,” JPEG2000 and Region of Interest Coding”, DICTA2002:Digital Image Computing
Techniques and Applications, pp. 1- 6, January 2002, Melbourne, Australia. 16. David S. Taubman and Michael W. Marcellin, “JPEG2000: Standard for Interactive Imaging”, Proceedings of the IEEE, Vol. 90, No. 8,
pp.1336-1357, August 2002.
18.
Authors: Mercy Nesa Rani and Thangaswamy Rajesh
Paper Title: Comparative Analysis on Software’s used in Expert System with Special Reference to Agriculture
Abstract: The expert system developed by various experts clearly indicate that different software’s were used to
develop computer based expert system for different applications. There are two ways of building expert system: one
is to develop from scratch i.e. to code the expert system as a normal computer programme for each domain using
programming languages like CLIPS, PROLOG, LISP, VB 6.0, VB.Net, ASP.Net, PHP etc as front end, MS Access,
MySQL, ORACLE etc as back end and the other is to use an expert system shell i.e. to build an expert system with
the help of specially designed programmes that are commercially available which may be used for a particular
domain. The shell enables the user to build their own expert system with or without the help from knowledge
engineers. Thus shells can make considerable saving on programming time. Because of this, building expert system
can be faster and more commercial. This paper discuss about different softwares used for the development of expert
system.
Keywords: Agriculture, Expert System, Software, Information and Farmers
References: 1. Patil ,S.S., Dhandra , B. V., Angadi , U.B., Shankar, A. G. and Joshi, N.,2009. Web based Expert System for Diagnosis of Micro Nutrients
Deficiencies in Crops, Proceedings of the World Congress on Engineering and Computer Science , San Francisco, USA Vol I. WCECS.
2. Riely, G., 2006. CLIPS: A tool for building expert system, available http://www.ghg.net/clips/CLIPS. html, Accessed on:12 July
2006.Building Expert Systems in Prolog by Dennis Merritt available in http://www.inf.fu-berlin.de/lehre/SS08/KI/merritt.pdf.
3. Prasad, R., Ranjan, K.R. and Sinha, A. K.,2006. AMRAPALIKA: An expert system for the diagnosis of pests, diseases, disorders in Indian
mango, Knowl.-Based Syst. 19(1), 9-21. 4. Sarma, S. K., Singh, K .R. and Singh, A. 2010. An Expert System for diagnosis of diseases in Rice Plant, International Journal of
Artificial Intelligence 1 (1), 1-6.
5. ESTA (Expert System Shell for Text Animation) version 4.1. 1993. Prolog Development Center, Atlanta, Georgia. 6. Balasubramani, N., 2004. Designing and testing the effectiveness of computer –based expert system on cognitive and conative domains of
rubber growers, TNAU, Coimbatore,2004.
7. Kumar,V., Lehri,S., sharma, A.K., Meena, P.D. and Kumar,A. 2008. Image Based Rapeseed-Mustard Disease Expert System: An Effective Extension Tool, Indian Res.J. Ext. Edu. 8 (2&3).
8. Babu, M.S.P., Murty, N. V. R and Narayana, S. V. N. L., 2010. A web based tomato crop expert information system based on artificial
intelligence and machine learning algorithms, International Journal of Computer Science and Information Technologies 1 (1), 6-15. 9. Palmer, R.G., 1986.How Expert System can improve Crop Production.Agric.Eng.,67(6):28-29.
10. Bennett, T.B. and Sneed, R.E., 1988. An Expert System for irrigation Planning and Design. ASAE paper No.88-5021.American Society of
Agriculture Engineers, St. Joseph, MI. 11. Folris, V., Simon, D. and Simon,R., 1988.Development of an Expert System for Mark Twain Reservoir Operation. In: Computerized
Decision Support System for water Managers .American Society of civil Enginneers,NY,USA.
12. Getfort,G. and Macvicer, T., 1988. AN operation’s Advisor for Regional water Management. In: Critical Water issues and Computer Application. America Society of civil Engineers, NY, USA.
13. Haie, N. and Irwin, R.W., 1988. Diagnostic Expert Systems for land drainage decisions. Irrigation and Drainage Systems, 2(2):139-146.
14. Stone, N.D and Toman, T.W., 1989. A Dynamically Linked Expert-Data base system for Decision Support in Texas Cotton Production. Computers and Electronics in Agriculture, 4:139-148.
15. Bachelor, W. D., Wetzstein, M.E. and Mc Clendon, R.W.,1989. Economic Theory and Expert System Information Technologies in
Agriculture European Review of Agriculture Economics 18(2): 245-261. 16. McClendon, R.W., Bachelor, W.D. and Hook, J.E.,1989. An Expert Simulation System for Irrigation Management .Proc. Int Winter Meet
American Society of Agriculture Engineers, New Orleans, LA, 12-15 December 1989.
17. Hart, W.E., Ekholt, B.A. and Kim, T.G., 1989. Irrigation system Selection. ASAE paper No.89-7042. American Society of Agriculture Enginners, St Joseph,MI.
18. Hershaeur, J., Karim, A., Owens, H. and Philipakis, A., 1989. A Field Observation Study of an Expert System Prototype Development
.Inform. Manage. 17:107-116. 19. Bhatty, M., 1990. Hybrid Expert System and Optimization Model for Multi-purpose Reservoir Operation. Ph.D. Thesis, Dept. of Civil
Engineering, Colorado State University, Ft.Collins Co.
20. McGregor, M.J and Thornton, P.K., 1990. Information Systems for crop Management: Prospects and problems. Journal of Agricultural Economics, 41(2):172-183.
21. Oswald, O., 1990. An Expert System for the Diagnosis of Tank Irrigated Systems: A Feasibility Study. Ph.D.Thesis, Center for water
Resources, Anna University, Madras,India. 22. Hasbini, B.A., Buchleiter, G.W. and Duke, H.R., 1991 .Expert System for Improved Irrigation Management. Proc. Int. Summer Meet
American Society of Agriculture Engineers, Albuquerque, New Mexico, June 23-26, 1-17.
23. King, J.P., Broner, I., Croissant, R.L. and Basham, C.W., 1991. Malting Barley water and Nutrient Management Knowledge- based system. Transaction of ASAE, 34(6): 2622-2630.
24. Srinivasan, R., Engel, B.A. and Pandyal. G.N.,1991. Expert System for irrigation Management (ESIM). Agricultural Systems, 36:297-314. 25. Clarke ,N. D., Tan, C. S. and Stone, J.A.,1992. Expert System for scheduling Supplement Irrigation for Fruits and Vegetable Crops in
Ontario. Can. Agric.Eng., 34:27-31.
26. Plant, R.E., Horrocks, R. D., Grimes, D. W. and Zelinski, L.J ., 1992.CALEX/Cotton: An Expert System Application for irrigation Scheduling .American Society of Agricultural Engineers,35(6):1833-1838.
27. Raman, H., Mohan, S. and Rangacharya, N.C.V., 1992.Decision Support for Crop Planning During Droughts.Journal of Irrigation and
85-89
Drainage Engineering ,118(2):229=241. 28. Nevo, A., Oad, R. and Padmore, T.,1994. An Integrated Expert System for Optimal Crop Planning. Agriculture Systems., 45:73-92.
19.
Authors: D. S. Monisha, R. Shantha Selva Kumari
Paper Title: Implementation of RNG in FPGA using Efficient Resource Utilization
Abstract: Computers’ required random numbers initially, for simulations and numerical computations like Monte
Carlo calculations. Random number generators offer an important contribution to many communication systems for
security. They are critical components in computational science. However the tradeoff between quality and
computational performance is an issue for many numerical simulations. FPGA optimized RNGs are efficient in terms
of resources than other types of software-based RNGs which means that they can take advantage of bitwise
operations and FPGA based specific features. One of the types of FPGA based RNG called a LUT-SR RNG is
illustrated using an algorithm. Shift registers are used to improve mixing rate between numbers. Results will be
misleading when correlations exist between the random numbers and hence permutations are used. The LUTs are
configured into shift registers. The algorithm is simplified based on the architecture such that it ensures longer
periods. A generator with a period of 2^(r )-1 can be implemented and provides r random output bits. This provides a
good quality balance compared to previous generators. The critical path between all registers is a single LUT. The
program is run in ModelSim 6.4a and implementation is done using Xilinx PlanAhead Virtex5 kit.
Keywords: random number generator (RNG), field programmable gate arrays (FPGA), SIMD, Look up table,
Shift Register (LUT SR).
References: 1. . B. Thomas and W. Luk, “The LUT-SR Family of Uniform Random Number Generatorsfor FPGA Architectures,” IEEE Transactions on
Very Large Scale Integration (VLSI)Systems, March 2012.
2. D. B. Thomas and W. Luk, “FPGA-optimized uniform random number generators using lut and shift registers,” in Proc. Int. Conf. Field Program. Logic Appl., 2010, pp. 77–82.
3. D. B. Thomas and W. Luk, “FPGA- optimized high - quality uniform random number generators,” in Proc. Field Program. Logic
Appl. Int.Conf., 2008, pp. 235-244. 4. D. B. Thomas and W. Luk, “High quality uniform random number generation using LUT optimized state-transition matrices,” J. VLSI
Signal Process., vol. 47, no. 1, pp. 77–92, 2007.
5. F. Panneton, P. L’Ecuyer, and M. Matsumoto, “Improved long period generators based on linear recurrences modulo 2,” ACM Trans. Math. Software, vol. 32, no. 1, pp. 1–16, 2006.
6. P. L’Ecuyer, “Tables of maximally equidistributed combined LFSR generators,” Math.Comput., vol. 68, no. 225, pp. 261– 269, 1999.
7. M. Saito and M. Matsumoto, “SIMD-oriented fast mersenne twister: A 128-bit Pseudo random number generator,” in Monte-Carlo and
Quasi- Monte Carlo Methods. NewYork: Springer-Verlag, 2006, pp. 607–622.
8. M. Matsumoto and T. Nishimura, “Mersenne twister: A 623- dimensionally equidistributed uniform pseudo-random number generator,”
ACM Trans. Modeling Comput. Simulat.,vol.8, no. 1, pp. 3–30, Jan. 1998. 9. F. Panneton, P. L’Ecuyer, and M. Matsumoto, “Improved long-period generators based on linear recurrences modulo 2,” ACM Trans. Math.
Software, vol. 32, no. 1, pp. 1–16, 2006.
10. K. H. Tsoi, K. H. Leung, and P. H. W. Leong, “Compact FPGA-based True Random Number Generators”, in IEEE Symposium on FPGAs for Custom Computing Machines, IEEE Computer Society, Washington, DC, 2003,p. 51.
11. M. Matsumoto and Y. Kurita, “Twisted GFSR generators II,” ACM Trans. Modeling Comput. Simulat., vol. 4, no. 3, pp. 254–266, 1994.
12. D. Wang and A. Compagner, On the use of reducible polynomials as random number generators, Mathematics of Computation 60 (1993), 363{374}. MR 93e:65012
13. P. L’Ecuyer and R. Simard, “TestU01 Random Number Test Suite”, (2007).
14. V. Sriram and D. Kearney, “A high throughput area time efficient pseudo uniform random number generator based on the TT800 algorithm,” in Proc. Int. Conf. Field Program. Logic Appl., 2007, pp. 529–532.
15. S. Konuma and S. Ichikawa, “Design and evaluation of hardware pseudorandom number generator MT19937,” IEICE Trans. Inf. Syst.,
vol. 88, no. 12, pp. 2876–2879, 2005. 16. Y. Li, P. C. J. Jiang, and M. Zhang, “Software/hardware framework for generating parallel long-period random numbers using the well
method,”in Proc. Int. Conf. Field Program. Logic Appl., Sep. 2011, pp. 110–115.
90-95
20.
Authors: Milind U. Nemade, Satish K. Shah
Paper Title: Beamforming based Speech Recognition using Genetic Algorithm for Real-time Systems
Abstract: The speech based applications have been always important in communication for the humans. There are
in various essential applications like speech recognition, voice-distance-talk and other forms of personal
communications. Most recently, speech based interface has been tried to be employed in almost all the mobile and
stationary devices. However, these attempts could not give ultimate response due to variations in surrounding noises,
changes in person to person speech and also intra person variation. This scenario leads to further research that will
make speech recognition more robust and general and can be applied upcoming electronic devices to be sued for
gaming, entertainment, cellular phones. The broad categories of speech enhancement techniques can be listed as
speech filtering techniques, beam forming techniques and active noise cancellation methods. In this paper, we have
improved the performance of beamforming based speech recognition system using evolutionary computational
algorithms (Genetic algorithm, GA). Additionally, the system is made to be working in real-time as time required for
classifier has been reduced dramatically. This is particularly achieved by including the zeros at random places and in
random amount in initial population chromosomes, which were generated randomly in the range of 0 to 1. This
results in the reduction of feature elements in feature descriptor and have feature vector length. The experiments were
performed for 20 words including numbers and commands, 10 words of numbers only and 10 words of commands
only for different values of filter bank parameters. The results show the effectiveness of the GA optimization in all
the subsets of experiments with different parameters of beamforming.
Keywords: Delay and sum beamformer, HMM based classifier, Least Mean Square, MFC, Nearest Neighbor
Classifier
96-104
References: 1. O. L. Frost, III, “An algorithm for linearly constrained adaptive array processing,” Proc. IEEE, vol. 60, pp. 926–935, Jan. 1972. 2. Griffiths, L.; Jim, C.; , "An alternative approach to linearly constrained adaptive beamforming,", IEEE Transactions on Antennas and
Propagation, vol.30, no.1, pp. 27- 34, Jan 1982.
3. Van Compernolle, D , "Switching adaptive filters for enhancing noisy and reverberant speech from microphone array recordings," ICASSP-
90, International Conference on Acoustics, Speech, and Signal Processing, 1990, vol.2, pp.833-836, 3-6 Apr 1990.
4. Gannot, S.; Burshtein, D.; Weinstein, E., "Signal enhancement using beamforming and nonstationarity with applications to speech," IEEE
Transactions on Signal Processing, vol.49, no.8, pp.1614-1626, Aug 2001. 5. Grbic, N.; Nordholm, S.; Cantoni, A., "Optimal FIR subband beamforming for speech enhancement in multipath environments," IEEE
Signal Processing Letters, vol.10, no.11, pp. 335- 338, Nov. 2003.
6. Xianxian Zhang; Hansen, J.H.L., "CSA-BF: a constrained switched adaptive beamformer for speech enhancement and recognition in real car environments," IEEE Transactions on Speech and Audio Processing, vol.11, no.6, pp. 733- 745, Nov. 2003.
7. Seltzer, M.L.; Raj, B.; Stern, R.M., "Likelihood-maximizing beamforming for robust hands-free speech recognition," IEEE Transactions on Speech and Audio Processing, vol.12, no.5, pp. 489- 498, Sept. 2004.
8. Yermeche, Z.; Grbic, N.; Claesson, I., "Blind Subband Beamforming With Time-Delay Constraints for Moving Source Speech
Enhancement," IEEE Transactions on Audio, Speech, and Language Processing, vol.15, no.8, pp.2360-2372, Nov. 2007. 9. Guangji Shi; Parham Aarabi; Hui Jiang; "Phase-Based Dual-Microphone Speech Enhancement Using A Prior Speech Model," IEEE
Transactions on Audio, Speech, and Language Processing, vol.15, no.1, pp.109-118, Jan. 2007.
10. Maganti, H.K.; Gatica-Perez, D., McCowan, I, "Speech Enhancement and Recognition in Meetings With an Audio–Visual Sensor Array," IEEE Transactions on Audio, Speech, and Language Processing, vol.15, no.8, pp.2257-2269, Nov. 2007.
11. Hai Huyen Dam; Hai Quang Dam; Nordholm, S., "Noise Statistics Update Adaptive Beamformer With PSD Estimation for Speech
Extraction in Noisy Environment," IEEE Transactions on Audio, Speech, and Language Processing, vol.16, no.8, pp.1633-1641, Nov. 2008.
12. Han, S.; Hong, J.; Jeong, S.; Hahn, M., "Robust GSC-based speech enhancement for human machine interface," IEEE Transactions on
Consumer Electronics, vol.56, no.2, pp.965-970, May 2010.
13. John J. Shynk, “Frequency-domain and multirate adaptive filtering,” IEEE Signal Processing Magazine, vol. 9, pp. 14–37, 1992. 14. Jan Mark de Haan, Nedelko Grbic, Ingvar Claesson, and Sven Erik Nordholm, “Filter bank design for subband adaptive microphone
arrays,” IEEE Trans. Speech Audio Proc., vol. 11, no. 1, pp. 14–23, Jan. 2003.
15. Kumatani, K.; McDonough, J.; Schachl, S.; Klakow, D.; Garner, P.N.; Weifeng Li, "Filter bank design based on minimization of individual aliasing terms for minimum mutual information subband adaptive beamforming," IEEE International Conference on Acoustics, Speech and
Signal Processing, ICASSP 2008 , vol., no., pp.1609-1612, March 31 2008-April 4 2008.
16. P. P. Vaidyanathan, “Multirate Systems and Filter Banks”, Prentice Hall, Englewood Cliffs, 1993. 17. Kenichi Kumatani, Tobias Gehrig, Uwe Mayer, Emilian Stoimenov, John McDonough, and MatthiasW¨olfel, “Adaptive beamforming with
a minimum mutual information criterion,” IEEE Transactions on Audio, Speech and Language Processing, vol. 15, no. 8, pp. 2527–2541,
2007. 18. L. Rabiner and Biing-Hwang Juang, “Fundamentals of Speech Recognition”, Prentice Hall PTR, 1993.
19. Joseph W. Picone, “Signal Modeling Techniques in Speech Recognition”, Proceedings of the IEEE, vol. 81, No. 9, pages 1215--1247, 1993.
20. Steven B. Davis and Paul Mermelstein, “Comparison of Parametric Representations for Monosyllabic Word Recognition in Continuously Spoken Sentences”, IEEE Transactions on Acoustics, Speech, and Signal Processing ASSP-28, vol., No. 4, August 1980.
21. Nemade M. U., Shah S.K., “Improvement in Speech Recognition Performance using Beamforming based Speech Enhancement”,
International Journal of Electronics Communication and Computer Engineering (IJECCE), ISSN: 2249-071X (Online, http://ijecce.org) Volume 3 Issue 4, July 2012.
22. Chan, K.Y.; Low, S.Y.; Nordholm, S.; Yiu, K.F.C.; Ling, S.H.; , "Speech Recognition Enhancement Using Beamforming and a Genetic
Algorithm," Third International Conference on Network and System Security, 2009. NSS '09. , pp.510-515, 19-21 Oct. 2009. 23. Chmulik, M.; Jarina, R., "Bio-inspired optimization of acoustic features for generic sound recognition," 19th International Conference on
Systems, Signals and Image Processing (IWSSIP), 2012, pp. 629-632, 11-13 April 2012.
24. Harrag, A.; Saigaa, D., Boukharouba, K.; Drif, M.; Bouchelaghem, A., "GA-based feature subset selection: Application to Arabic speaker recognition system," 11th International Conference on Hybrid Intelligent Systems (HIS), 2011, pp.383-387, 5-8 Dec. 2011.
25. Gao Wen-xi; Yu Feng-qin, "Feature dimension reduction based on genetic algorithm for mandarin digit recognition," 4th International
Congress on Image and Signal Processing (CISP), 2011, vol.5, pp.2737-2740, 15-17 Oct. 2011. 26. Aggarwal, R.K.; Dave, M., "Application of genetically optimized neural networks for hindi speech recognition system," 2011 World
Congress on Information and Communication Technologies (WICT), pp.512-517, 11-14 Dec. 2011.
27. Selouani, S., "Evolutionary discriminative speaker adaptation," IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU), 2011, pp.164-168, 11-15 Dec. 2011.
28. Shing-Tai Pan; Ching-Fa Chen; Jian-Hong Zeng, "Speech recognition via Hidden Markov Model and neural network trained by genetic
algorithm," International Conference on Machine Learning and Cybernetics (ICMLC), 2010, vol.6, pp.2950-2955, 11-14 July 2010. 29. Oudelha, M.; Ainon, R.N., "HMM parameters estimation using hybrid Baum-Welch genetic algorithm," 2010 International Symposium in
Information Technology (ITSim), vol.2, pp.542-545, 15-17 June 2010.
30. Yuan Yujin; Zhou Qun; Zhao Peihua , "Vector Quantization Codebook Design Method for Speech Recognition Based on Genetic Algorithm," 2nd International Conference on Information Engineering and Computer Science (ICIECS), pp.1-4, 25-26 Dec. 2010.
21.
Authors: V.J.K.Kishor Sonti, V.Kannan
Paper Title: Noise Analysis of Novel Design of MODFET Low Noise Amplifier
Abstract: In this paper, Noise analysis of a novel MODFET LNA was done that is designed using Micro strip
based design methodology. A novel design has been proposed for MODFET LNA Load and stability has been
obtained. A comparative analysis has been done for different values of drain voltages. Noise analysis has also been
done and the design is carried out at a centre frequency of 2.4 GHz and the noise bandwidth considered is 6GHz. In
this paper the work is carried out using ADS simulation software. Scattering parameter S11 and S22 are obtained.
Noise figure and gain of Cascaded LNA is also obtained. Variation of noise figure and gain with respect to frequency
has been obtained. From the results the effect of drain voltage on the design performance is explored. Layout of the
proposed design has been obtained. Results obtained are in greater coherence with the theoretical observations.
Keywords: MODFET, Noise, LNA, Micro Strip
References: 1. Hasina F. Huq, Syed K. Islam.(2005), “Self-Aligned AlGaN/GaN MODFET with Liquid Phase Deposited Oxide Gate for Microwave Power
Applications”, IEEE, Department of Electrical and Computer Engineering, The University of Tennessee. 2. B.VanZeghbroeck, Principles of semiconductor devices, 2011, ecee.colorado.edu/~bart/book/book/chapter3/pdf/ch3_6.pdf.
3. Mark C. Lau, Virginia Polytechnic Institute and State University, Small Signal Equivalent Circuit Extraction From A Gallium Arsenide
Mesfet Device, 1997. 4. ZHANG Hualiang, The Design of Low Noise Amplifier Using ADS, December 22, 2004
5. www.wikipedia.org
105-108
6. L.Aucoin, HEMTs and PHEMTs, parts.jpl.nasa.gov/mmic/3-IV.pdf 7. Peter J. Rudge, Robert E. Miles, Michael B. Steer, Fellow, IEEE, andC Christopher M. Snowden, Fellow, IEEE, “Investigation Into
Intermodulation Distortion in HEMTs Using a Quasi-2-D physical model”, IEEE transactions
8. Noise in Electronic and Photonic Devices, K. K. Ghosh, www.intechopen.com
22.
Authors: D. M. Awze, A. K. Mahalle
Paper Title: Design of Steam Pipe Layout and Hanger Support in Thermal Power Station
Abstract: Steam piping layout in thermal power station is used to transfer steam from one area to another area to
perform the work. The present paper is related to steam piping layout between Boiler outlet & Turbine inlet i.e. main
steam line. The steam piping layout directly impacts the drop in pressure of the steam. The ideal condition is that the
pressure require at turbine inlet should be equal to boiler super heater out let pressure. But due to various factors there
is 7 to 9 Kg/cm2 pressure drop. By changing the steam piping layout pressure drop can be minimized. The slight
change in pressure drop result less power require to increase the pressure of steam (i.e. Boiler feed Pump) throughout
life cycle of power plant. It means auxiliary consumption can be reduce by doing modification in steam piping layout.
The change in piping layout also changes the hanger support position.
Keywords: Steam piping layout, main steam line, Pressure drop, Hanger support
References: 1. ASME, 2007: ASME B31.1-2007. Power piping. The American Society of Mechanical Engineers, New York. 2. H. Griem, W. Kohler, H. Schmidt Heat Transfer, Pressure Drop and stresses in Evaporator Water Walls. VGB Power Tech 79 (1999) 1, pp.
26-35.
3. Hanger & Supports for Piping’ by M. Rajagopal, 4. Pipe Design Engineering
5. ‘Cold Spring of Retained Piping System’ by L. C. Peng, Peng Engineering, Houston, Texas 6. www.powerplantengineering.in
7. Introduction to piping Engineering by Gerald H. May, P.E.
8. www.suncam.com 9. Process Piping Design & Engineering per ASME B 31.3’ Institute of piping Engineering & Building services, Hyderabad. www.ipebs.in
10. Hydraulic Institute, Pipe Friction Manual, New York 1954
11. Hydraulic Institute, Engineering Data Book, 2nd ed, 1991
109-113
23.
Authors: N.Kiran Babu, P.S.Srinivas Babu
Paper Title: Design of Physical Coding Sublayer using 8B/10B Algorithm
Abstract: In order to resolve the problem of base-line offset and unbalanced code flow during the fiber data
transmission, thesis give a simple and practical solution 8B/10B encoder. This solution taking a method which
integrate checking scheme and logic operation, through Verilog HDL description language, realize the design of
encoder. The proposed circuit is simulated in Xilinx and Cadence. The results obtained in various tools are presented
in this paper.
Keywords: Physical coding sub layer, 8B/10B algorithm, Synchronization, Verilog HDL, Cadence Encounter
References: 1. IEEE standard P802.3z/o5. 2.1998.06
2. PCS design Spec$cation version. I, Rocket chips Inc. 1998. 3. Samir palnitkar, Verilog HDL: A Guide to Digital Design and Synthesis, Sunsoft press, 1996.
4. Verilog – XL Reference Manual Ver. 2.2 cadence design systems, 1995.
5. Spectre HDL Reference Manual Ver. 4.3.4 cadence design systems, 1995. 6. VSC713.5 Preliminary Data Sheet, VITESSE Semiconductor Corporation, 1997.
7. Edward A. LEE, DIGITAL COMMUNICATION, kluwer Academic Publishers, 1994.
8. Simon Haykin, Communication Systems, John Willey & Sons, Inc, 1994. 9. Andrew S. Tanenbaum, COMPUTER NETWORKS, Prentice-Hall, Inc, 1996.
10. Behzad Razavi, Design of monolithic Phase-Locked Loops and Clock Recovery Circuits – A Tutorial IEEE Press, 1994
114-117
24.
Authors: Matilda.S, B.Palaniappan, Thambidurai.T
Paper Title: Performance Analysis of Adaptive Queuing Techniques for Streaming Real-Time Video
Abstract: Wireless communication today is a mixture of real time traffic whic is expeced to ocuppy over 70%
by 2016 [1]. The challenge lies in integrating the age old wired network with the new-born 4G networks to provide
better user experience. Excessive delay is observed in the Base stations and WiMax networks due to difference in
available bandwidth between the fixed network and the wireless link. The main reason attributed to the failure in
streaming of real-time video, is lack of proper buffer design, which has resulted in bufferbloat across the Internet.
This increases the delay across the network eventually leading to packet loss. If QOS is configured correctly in the
network, time sensitive packets get priority and playout is smooth. Many techniques such as Active Queue
Management and Controlled Delay tend to reduce the effects of bufferbloat. The random drop of packets and static
value of queue size adopted in these methods do not support real-time traffic. In this paper Adaptive Controlled delay
algorithm has been proposed to overcome the drawbacks of the existing methods and provide a better Quality of
Service for real-time video.
Keywords: Real-time video, Bufferbloat, Controlled Delay, Adaptive Controlled Delay
References: 1. Cisco Visual Networking Index: Global Mobile Data Traffic Forecast Update- 2011-2016. White Paper, February 2012
2. Y. Zhang and D. Loguinov, “ABS: Adaptive buffer sizing for heterogeneous networks,” Proc. IEEE International Workshop on Quality of
Service (IWQoS), Enschede, The Netherlands, Jun 2008
118-123
3. R. Stanojevic, R. Shorten and C. Kellet, “Adaptive tuning of drop-tail buffers for reducing queueing delays,” IEEE Communications Letters, vol.10, no. 7, pp. 570-572, Jul 2006
4. Du Li; Qiu Zhen-Yu; Guo Yong-le, "An Improved Queue Management Algorithm in DiffServ Networks," Information and Computing
Science, 2009. ICIC '09. vol.1, no., pp.123,126. 5. Y. Zhang and D. Loguinov., “ABS: Adaptive buffer sizing for Heterogeneous Networks” Proceedings of IEEE International Workshop on
Quality of Service (IWQoS), Enschede, The Netherlands, Jun 2008.
6. R. Stanojevic, R. Shorten and C. Kellet., “ Adaptive tuning of drop-tail buffers for reducing Queueing Delays” IEEE Communications Letters, vol. 10, no. 7, pp. 570-572, Jul 2006.
7. R.S.Prasad, C. Dovrolis and M. Thottan.,“Router buffer sizing revisited:The role of the output/input capacity ratio,”Proceedings of the
ACM Conference CoNEXT, New York, USA, Dec 2007. 8. Lakshmikantha, R. Srikant and C. Beck, “Impact of file arrivals and departures on buffer sizing in core routers,” Proc. IEEE
INFOCOM,Phoenix, Arizona, USA, Apr. 2008.
9. Dhamdhere and C. Dovrolis, “Open issues in router buffer sizing,”ACM SIGCOMM Computer Communications Review, vol. 36, no. 1, pp.87-92, Jan 2006.
10. G.Vu-Brugier, R. S. Stanojevic, D.J.Leith and R.N.Shorten, “A critique of recently proposed buffer-sizing strategies,” ACM SIGCOMM
Computer Communications Review, vol. 37, no. 1, pp. 43-47, Jan. 2007. 11. M. Wang and Y. Ganjali, “The effects of fairness in buffer sizing,” Proc.IFIP NETWORKING, Atlanta, USA, May 2007.
12. Arun Vishwanath, Vijay Sivaraman and George N. Rouskasz, “Considerations for Sizing Buffers in Optical Packet Switched Networks ,”
Citeseer, 2009. 13. Jim Gettys, Kathleen Nichols, “Bufferbloat: Dark Buffers in the Internet,” in ACMQueue, Vol. 9 No. 11 – November 2011, pp. 15–
64.
14. Haiqing Jiang, Zeyu Liu, Yaogong Wang, Kyunghan Lee and Injong Rhee, “Understanding Bufferbloat in Cellular Networks,” CellNet '12
Proceedings of the 2012 ACM SIGCOMM workshop on Cellular networks: operations, challenges, and future design, pp 1-6.
15. Lakkakorpi, J.; Sayenko, A.; Karhula, J.; Alanen, O.; Moilanen, J., "Active Queue Management for Reducing Downlink Delays in
WiMAX," Vehicular Technology Conference, 2007. VTC-2007 Fall. 2007 IEEE 66th , vol., no., pp.326,330, Sept. 30 2007-Oct. 3 2007. 16. W.-c. Feng, M. Fisk, M. K. Gardner, and E. Weigle. “Dynamic Right-Sizing: An Automated, Lightweight, and Scalable Technique for
Enhancing Grid Performance” Proceedings of the 7th IFIP/IEEE International Workshop on Protocols for High Speed Networks (PIHSN),
pages 69–83, 2002. 17. Kathleen Nichols and Van Jackobson, “Controlling Queue Delay” Communications of the ACM, Volume 55, Issue 7, pages 42-50, 2012
18. Richard Chirgwin, “Researchers propose solution to Bufferbloat” http://www.theregister.co.uk/2012/05/09/bufferbloat_and_codel, , 9th
May 2012. 19. netalyzr.icsi.berkeley.edu
20. www.pingplotter.com
21. www.wireshark.org 22. Matilda, S., Palaniappan, B., Cross Layered Hybrid Transport Layer Protocol Approach To Enhance Network Utilisation For Video Traffic.
ICTACT Journal on Communication Technology. Volume1 Issue 1, March 2010, pp. 54-60.
25.
Authors: Namitha Sona, Shantharama Rai.c
Paper Title: Fuzzy Logic Controller for the Speed Control of an IC Engine using Matlab \ Simulink
Abstract: the use of graphical dynamic system simulation software is becoming more popular as engines try to
reduce the time to develop new control system. Dynamic system simulation software is an important tool and
developing advanced reliable and high quality products and systems. This paper explains about one of the a tool
MATLAB/SIMULINK used and the study of system dynamics of a four stroke IC engine which will give clear idea
about speed control of IC engine using fuzzy logic. A Fuzzy Logic controller is thereby developed to control the
speed of the IC Engine with variable load conditions.
Keywords: internal combustion(IC) engine, fuzzy logic controller. Matlab /simulink
References: 1. C.A. Rabbath, H. Desira and K. Butts,“Effective Modeling and Simulation of Internal Combustion Engine Control System,” Proc. the
American Control Conf. Arlington, VA June 25-27,2001. 2. P.R. Crossley and J.A. Cook, “A Nonlinear Engine Model for Drive Train System Development,” IEE International Conf.’Control 91’, Vol. 2,
pp. 921-925, March 25-28, 1991,Edinburgh, U.K.
3. J. J. Moskwa and J. K. Hedrick, "Automotive Engine Modeling for Real Time Control Application," Proc.1987 ACC, pp. 341-346.
124-127
26.
Authors: Sachin Goyal, Mukul Gaur, Sulata Bhandari
Paper Title: Power Regulation of a Wind Turbine Using Adaptive Fuzzy- PID Pitch Angle Controller
Abstract: This paper considers power generation control in variable pitch wind turbines, using an adaptive fuzzy-
PID controller. The pitch angle control system was simulated using MATLAB/ SIMULINK tool to test the control
strategy and performance evaluation of the system. To test the controller’s performance, a wind profile has been
simulated and results are validated to show that the proposed controllers are effective for power regulation. To
highlight the improvements of the method the proposed controller are compared to the conventional PID controller.
Keywords: Adaptive control, Fuzzy controller, PID- controller, Pitch control, Wind turbine
References: 1. Vladislav Akhmatov, “Variable-Speed Wind Turbines with Doubly-Fed Induction Generators--Part 1: Modelling in Dynamic Simulation
Tools”. Wind Engineering, 2002,vol 26.2, pp 85-108. 2. Francoise Mei, “Small Signal Modeling and Analysis of Doubly Fed Induction Generator in Wind Power Applications,” Ph.D.
dissertation, Control and Power Group Dept of Electrical and Electronic Engineering Imperial College London, University of London.
3. Bijaya Pokharel, “Modeling, Control And Analysis of a Doubly Fed Induction Generator Based Wind Turbine System With Voltage Regulation” M.S. dissertation, Deptt. of Electrical and Computer Engineering, The Faculty of Graduate school, Tennessee Technological
University . Dec-2011.
4. Jajun Xi, Bin Sun and Huaqi Zhao, “Adaptive PID Controller based on Single Neuron for Permanent Magnet Synchronous Machine”, Electrical Power Automation Equipment, Vol.23, No. 10, 2003, pp. 59-61.
5. Xingjia Yao, Z. Zhang and C. Zhang, “The Study of Adaptive Independence Electrical Drive Blade Pitch Control Technology”, Proceeding
of International Conference on Electrical Machines and Systems, 2007, pp. 828-833. 6. Linjing Hu, Dongmin Xi and Tao Liu, “Research of Wind Generation Pitch System Bases on Fuzzy Adaptive PID”, 2nd International
conference on intelligent control and Information Processing, 2011, pp. 97-100.
128-132
7. Danish Wind Industry Association. Know How: Guided tour [online]. Available: http://www.windpower.org. 8. Wind Energy Background [Online]. Available: http://www.dolcera.com.
9. Asynchronous Generators [Online]. Available: http://www.windturbines.net.
10. Jainguang Qi and Yongxin Liu, ”PID Control in Adjustable-pitch Wind Turbine System Based on Fuzzy Control.” Proceedings of 2nd International conference on Industrial Mechatronics and Automation, 2010, pp 341-344.
27.
Authors: Mukul Gaur, Sachin Goyal, Sulata Bhandari,
Paper Title: Effect of Time Delay on Robust PID Controllers for a Transfer Function
Abstract: A controller designed for a nominal process model generally works fine for the nominal plant model, but
may fail even by a slight change in it. Robust control deals with system analysis and control design for such
imperfectly known process models. Robust control has been a recent addition to the field of control engineering that
primarily deals with obtaining system robustness in the presence of uncertainties. A lot of research has been done and
many approaches are available for robust design of the plants. In this paper, a graphical technique introduced in [1] to
find all proportional integral derivative (PID) controllers that satisfy the robust stability constraint of a given single
input-single-output (SISO) linear time-invariant (LTI) system with time delay[1], is followed and effects of change of
time-delay in the nominal plant model is discussed..
Keywords: H∞ control, Robust stability, small gain theorem, time-delay.
References: 1. Emami, T. and J.M. Watkins, “Robust stability design of PID controllers for arbitrary-order transfer functions with uncertain time delay,”
Southeastern Symposium on System Theory University of Tennessee Space Institute, March 2009.
2. Qing-Chang Zhong, Robust stability of time delay systems, Springer-Verlag London Limited 2006. Chapters 1,2 pp. 1-40. Available: http://pcwww.liv.ac.uk/~zhongqc/delay/Contents.pdf
3. Peter Dorato, “A historical review of robust control”, control systems magazine (volume 7, issue 2), april 1987. 4. G. Zames, “Functional Analysis Applied to Nonlinear Feedback Systems,” IEEE Trans.. Circuit Theory. Vol. CT-10, pp. 392-4134, Sept.
1963.
5. R. E. Kalman, “When is a linear control system optimal?” Trans. ASME, Ser. D,J. Basic Engr, vol. 86, pp. 5 1-60, March 1964. 6. Dorf Richard C. and Robert H. Bishop, Modern Control Systems, 9th ed., Prentice–Hall Inc., New Jersey-07458, USA, 2001, Chapters 1, 5,
pp. 1-23, pp. 173-206.
7. Skogestad, S. and I. Postlethwaite, Multivariable Feedback Control, John Wiley & Sons Ltd., Baffins lane, Chicester, West Sussex PO19 1UD, England, 2001, Chapters 2, 7, pp. 15-62, pp. 253-290.
8. Doyle, J., Bruce Francis,and Allen Tannenbaum, Feedback control theory, macmillan Publishing Co., 1990. Available:
:http://www.control.utoronto.ca/people/profs/francis/dft.pdf 9. Bhattacharyya, S.P., Chapellat, H., and L.H. Keel, Robust Control: The Parametric Approach, Prentice Hall, N.J., 1995.
10. Sujoldzic, S. and J.M. Watkins, “Stabilization of an arbitrary order transfer function with time delay using PI and PD controllers,” Proc. of
American Control Conference, June 2006, pp. 2427-2432. 11. Sujoldzic S. and J.M. Watkins, “Stabilization of an arbitrary order transfer function with time delay using PID controller,” Proc. of IEEE
Conf. on Decision and Control, Vol. 45, December 2005.
12. Emami, T. and J.M. Watkins, “Weighted sensitivity design of PID controllers for arbitrary-order transfer functions with time-delay,” Proc. of the IASTED International Conf. on Intelligent Systems and Control, November 2008, pp 20-25.
13. Emami, T. and J.M. Watkins, “Complementary sensitivity design of PID controllers for arbitrary-order transfer functions with time delay,”
Proc. of 2008 ASME Dynamic Systems and Control Conf., October 2008. 14. Emami, T. and J.M. Watkins, “Robust performance characterization of PID controllers in the frequency domain,” WSEAS Transactions
Journal of Systems and Control, Vol. 4, No. 5, May 2009, pp. 232-242.
15. Manoj Gogoi,“PID controllers design for robust stability of arbitrary order plant with time delay and additive uncertainty”. Available: http://engineering.wichita.edu/esawan/gogoi.pdf.
16. “Basics of electrical machines”. Available: http://www.reliance.com/mtr/mtrthrmn.htm.
17. TreurnichtJ.,Robust Control Systems—Usingthe Matlab toolbox.Available:http://courses.ee.sun.ac.za/Robuuste_Beheerstelsels_813/images/robustexample32007.pdf..
133-137
28.
Authors: Kunatsa T, Mufundirwa A
Paper Title: Biogas Production from Water Hyacinth Case of Lake Chivero - Zimbabwe A review
Abstract The purpose of this study was to review the energy situation in Zimbabwe as well as the possibility of
producing biogas from water hyacinth. Zimbabwe faces a shortage of electrical energy owing to internal generation
shortfalls and the country imports all its petroleum fuels at a huge cost.The majority of people in Zimbabwe as a
developing country are dependent on traditional and inefficient energy services that constrain their ability to enhance
economic productivity and quality of life. The water hyacinth weed has invaded approximately all rivers, lakes and
dams in Zimbabwe and government authorities are relying on research institutions to come up with solutions to deal
with this invasive weed. The costs connected with elimination and maintenance control of water hyacinth are quite
considerable. This study found out that the option of biogas production as a way of energy exploration using water
hyacinth may not only sustain the energy availability but also improve environmental sustainability by improving the
social, economic and physical well being of the environment.
Keywords: Biogas, Lake Chivero, Renewable energy, Water Hyacinth
References: 1. Kidunda RS, Osarya J (2005). Potential of water hyacinth (Eicchornia crassipes) in ruminant nutrition in Tanzania. Livest. Res. Rural Dev.
5: 17.
2. A.Jagadeesh, 2012. Invasive Water Hyacinths for Renewable Energy in China
3. Ali N, Chaudhary BL, Khandelwal SK (2004). Better use of water hyacinth for fuel, manure and pollution free environment. Indian J. Environ. Prot., 24: 297–303.
4. Barrett S.C.H. 1980a. Sexual reproduction in Eichhornia crassipes (water Hyacinth). 1. Fertility of clones from diverse regions. Journal of
Applied Ecology 17:101-112. 5. Barrett S.C.H. 1980b. Sexual reproduction in Eichhornia crassipes (water hyacinth). II. Seed production in natural populations. The Journal
of Applied Ecology 17:113-124.
6. Bartodziej W. & Weymouth G. (1995) Waterbird abundance and activity on water-hyacinth and Egeria in the St-Marks River, Florida.
138-142
Journal of Aquatic Plant Management, 33, 19-22. 7. Brendonck L., Maes J., Rommens W., Dekeza N., Nhiwatiwa T., Barson M., Callebaut V., Phiri C., Moreau K., Gratwicke B., Stevens M.,
Alyn N., Holsters E., Ollevier F. & Marshall B. (2003) The impact of water hyacinth (Eichhornia crassipes) in a eutrophic subtropical
impoundment (Lake Chivero, Zimbabwe). II. Species diversity. Archiv Fur Hydrobiologie, 158, 389-405. 8. Center T.D. (ed.) (1994) Biological Control of weeds: water hyacinth and water lettuce. Intercept, Andover.
9. Chatterji, A.C , (2005). Introduction to Environmental Biotechnology.
10. Chigbo F.E. Smith, R.W, F.L. (1982), Environmental Pollution 11. Chikwenhere G.P, Phiri G, 2010. History of water hyacinth and its control efforts on Lake Chivero in Zimbabwe
12. de Casabianca M.-L. and T. Laugier. 1995. Eichhornia crassipes production on petroliferous wastewaters: effects of salinity. Bioresource
Technology 54:39-43. 13. Elias Jigar (2010) Study on Renewable Biogas Energy Production from Cladodes of
14. Farrell, A.E., Plevin, R.J., Turner, B.T., Jones, A.D., O’Hare, M., Kammen, D.M. 2006. Ethanol can contribute to energy and environmental
goals. 15. Gibbons M., Gibbons Jr. H. & Sytsma M. (1994) A Citizen's Manual for Developing Integraed Aquatic Vegetation Management Plans. in
Water Environmental Services. Available Water Environmental Services.
16. Gopal, B., (1987). Water Hyacinth, Aquatic Plant Studies Series Elsevier Amsterdam. 17. Gopal, B., 1987. Water Hyacinth. Elsevier, New York.
18. Goswami T, Saikia CN (1994). Water hyacinth—a potential source of raw material for greaseproof paper. Bioresour. Technol., 50: 235–
238. 19. Holm LG, Plucknett DL, Pancho JV, Herberger JP. 1977. The world's worst weeds: Distribution and biology. Honolulu: University Press of
Hawaii.
20. International Atomic Energy Agency Vienna (IAEA). 2005
21. Jigisha Parikh, S.A. Channiwala and G.K. Ghosal (2004). A correlation for calculating HHV from proximate analysis of solid fuels.
22. Kittiphop Promdee, Tharapong Vitidsant, and Supot Vanpetch, (2012). Comparative Study of Some Physical and Chemical Properties of
Bio-Oil from Manila Grass and Water Hyacinth Transformed by Pyrolysis Process 23. Lu JB, Fu ZH, Yin ZZ (2008) Performance of a water hyacinth (Eichhornia crassipes) system in the treatment of wastewater from a duck
farm and the effects of using water hyacinth as duck feed.
24. Malik A (2007). Environmental challenge vis a vis opportunity: The case of water hyacinth. Environ. Int., 33: 122-138. 25. Mangas-Ramirez E. & Elias-Gutierrez M. (2004) Effect of mechanical removal of water hyacinth (Eichhornia crassipes) on the water
quality and biological communities in a Mexican reservoir. Journal of Aquatic Health and Management, 7 161-168.
26. Mitchell D.S. 1976. The growth and management of Eichhornia crassipes and Salvinia spp. In their native environment and in alien situations.
27. Mshandete A, Kivaisi A, Rubindamayugi M, Mattiasson BO (2004). Anaerobic batch codigestion of sisal pulp and fish wastes. Bioresour.
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29. Oudhia P (1999b). Studies on allelopathy and medicinal weeds in chickpea fields. Int Chickpea Pigeonpea Newsl. 6: 29–33.
30. Parisi, F., 1989. Advances in lignocellulosics hydrolysis and in the utilization of the hydrolysates. 31. Pinto, C.R.L.R., Carconia, A. and Souza, M.M. (1987)
32. Sajn SA, Bulc TG, Vrhovsek D (2005). Comparison of nutrient cycling in a surface flow constructed wetland and in a facultative pond
treating secondary effluent. Water Sci. Technol., 51: 291–298.
33. Shoeb F, Singh HJ(2002) Kinetic studies of biogas evolved from water hyacinth 2nd International Symposium on New Technologies for
Environmental Monitoring and Agro – Applications pp 138 34. Szczeck MM (1999). Suppressiveness of vermicompost against fusarium wilt of tomato. J. Phytopathol. Phytopathologische Zeitschrift 47:
155–161.
35. UNIDO, Energy, Development and Security: Energy issues in the current macroeconomic context. 2008 36. Wolverton, B.C and McDonald, R.C. (1979), Journal of Water Pollution Control.
37. http://www.worldlakes.org/shownews.asp?newsid=518 ,Thursday, September 12, 2002. Water hyacinth problem creating controversy in
Zimbabwean lakes; weevils, toxic chemicals or inaction? 38. Zimbabwe National Energy Policy (NEP), 2012
39. Zimbabwe, Ministry of Energy and Power Development (MoEPD), Energy balance, 2009
29.
Authors: Radhamani R, Keshaveni
Paper Title: FPGA implementation of Efficient and High Speed Template Matching Module
Abstract Template Matching is a digital image processing technique used in classifying objects .Due to changing
intensity and template size the computational complexity increases. In our project we have simplified the original
normalized cross-correlation (NCC) algorithm and designed a parallel processing pipelined architecture circuit to
improve the computational speed and accuracy .This template matching module can be used in all types of vision
applications, pattern recognition and elastic matching.
Keywords: Image processing, mean, Normalized cross-correlation, template matching
References: 1. C. WANG, "HUMAN RELIABILITY IN VISUAL INSPECTION," QUALITY, SEPT. 1974.
2. Nikolić D, Muresan RC, Feng W, Singer W (2012) Scaled correlation analysis: a better way to compute a cross-correlogram. European
Journal of Neuroscience, pp. 1–21, 3. Real time FPGA based template matching module for Visual Inspection Application. Jiun-Yan Chen,Kuo-Feng Hung,Chin-Chia Wu
4. Chin, Automated Visual Inspection: A Survey IEEE PAMI 1982
5. Tsai, D.-M., Chiang, C.-H., 2002. Rotation-invariant pattern matching using wavelet decomposition. Pattern Recognition Lett. 23, 191–201. Wakahara, T., Kimura, Y., Tomono, A., 2001. Affine-invariant recognition of gray-scale characters using global affine
transformationcorrelation. IEEE Trans. Pattern Anal. Machine Intell. 23, 384–395.
6. Kim, J.H., Cho, H.S., Kim, S., 1996. Pattern classification of solder joint images using a correlation neural network. Eng. Appl. Artif. Intell9, 655–669.
7. Cai, X.Y., Kvasnik, F., Blore, R.W., 1994. Wafer fault measurement bycoherent optical processor. Appl. Opt. 33, 4487–4496.
8. Stefano, “An Efficient Algorithm for exhaustive template matching based on normalized cross correlation”. IEEE ICIAP03 9. Xiaotao Wang, Xingbo Wang, "FPGA Based Parallel Architectures fo Normalized Cross-Correlation", The 1st International Conference on
Information Science and Engineering (ICISE2009), pp. 225 - 229
10. Nisheeth Gupta, Nikhil Gupta, "A VLSI Architecture for Image Registration in Real Time," IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS, VOL. 15, NO. 9SEPTEMBER 2007
11. "Robot vision system with a correlation chip for real time tracking, optical flow, and depth map generation", 1992 IEEE Conference on
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143-146
30.
Authors: Arvind Yadav, Jagdish Kumar
Paper Title: Harmonic Reduction in Cascaded Multilevel Inverter
Abstrac: This paper presents method of selecting switching angles of a cascaded multilevel inverter so as to produce
required fundamental voltage along with improved staircase waveform in terms of harmonics. Cascaded multilevel
inverter uses number of DC sources, for k sources number of levels will be 2k+1 and leads to k number of non-linear
equations to be solved. Many approaches can be made regarding the solution but this paper focuses on Specific
Harmonic Elimination (SHE) technique for angle optimization. Newton-Raphson method is used and the difficulty
with this method is a closed initial guess. Variation of angles with modulation index is observed and THD is
calculated for selected modulation indexes and all attempts are made so as to get lowest THD. Results are simulated
in MATLAB/Simulink environment.
Keywords: Cascaded multilevel inverter, SHE, Switching angles, THD.
References: 1. C. Schauder et al., “Development of a 100 MVAR static condenser for voltage control of transmission systems,” presented at the IEEE PES
Summer Power Meeting, San Francisco, CA, July 24–28, 1994, Paper 94SM479-6PWRD.
2. F. Z. Peng and J. Lai, “Application considerations and compensation characteristics of shunt active and series active filters in power
systems,” in Proc. 7th Int. Conf. Harmonics and Quality Power, Las Vegas, NV, Oct. 16–18, 1996, pp. 12–20.
3. F. G. Turnbull, “Selected harmonic reduction in static DC-AC inverters,”IEEE Trans. Commun. Electron., vol. 83, no. 73, pp. 374–378, Jul.
1964.
4. The Math Works, MATLAB User’s Manual Optimization Toolbox/SIMULINK Power SystemBlock Set v7, Natick, MA: Author, 2006. 5. J. Chiasson, L. M. Tolbert, K. McKenzie, and Z. Du, “Harmonic elimination in multilevel converters,” in Proc. 7th IASTED Int. Multi-Conf.
Power and Energy System (PES), Palm Springs, CA, Feb. 2003, pp. 284–289.
6. N. A. Azli and S. N. Wong, “Development of a DSP-based fuzzy PI controller for an online optimal PWM control scheme for a multilevel inverter,” in Proc. Int. Conf. Power Electron. Drives Syst. (PEDS), Nov.2005, vol. 2, pp. 1457–1462.
7. J. Holtz and J. O. Krah, “Adaptive optimal pulse-width modulation for the line-side converter of electric locomotives,” IEEE Trans. Power
Elecron., vol. 7, no. 1, pp. 205–211, Jan. 1992. 8. B. Ozpineci, L. M. Tolbert, and J. N. Chiasson, “Harmonic optimization of multilevel converters using genetic algorithms,” IEEE Power
Electron. Lett., vol. 3, no. 3, pp. 92–95, Sep. 2005.
9. M. S. A. Dahidah and V. G. Agelidis, “Selective harmonic elimination PWM control for cascaded multilevel voltage source converters: A generalized formula,” IEEE Trans. Power Electron., vol. 23, no. 4, pp. 1620– 1630, Jul. 2008.
147-149
31.
Authors: Swati Mishra, Siddharth Bali
Paper Title: Harmonic Reduction in Cascaded Multilevel Inverter
Abstrac: Cryptography is an imperative tool for protecting and securing data. Security provides safety and
reliability. Genetic Algorithm (GA) is typically used to obtain solution for optimization and search problems. This
paper presents application of GA in the field of cryptography. Key Selection in public key cryptography is a selection
process in which keys can be categorized on the basis of their fitness, making GA a good candidate for key
generation. Primary goals of our algorithm was to provide fast and improved performance results having practical and
feasible implementation. GA correlates nature to a great extent and produce population of keys such that keys with
higher fitness value is replicated often. Good Fitness function helps in exploring search space more efficiently and
effectively while bad fitness function traps GA operating in local optimum solution and losing its discovery power.
Pearson’s Coefficient of auto-correlation was used to calculate the fitness of keys. Ranking of keys was performed to
find the best fit key. The private key generated cannot be derived from public key. The key samples satisfy gap and
frequency test. Thus, purely random and non-repeating final keys were obtained by application of GA which
increased the keys strength and security.
Keywords: About four key words or phrases in alphabetical order, separated by commas.
References: 1. Omran, S.S.; Al-Khalid, A.S.; Al-Saady, D. M., "A cryptanalytic attack on Vigenère cipher using genetic algorithm," Open Systems (ICOS),
2011 IEEE Conference on, vol., no., pp.59,64, 25-28 Sept. 2011.
2. Goyat, S., “Cryptography Using Genetic Algorithms (GAs). ” IOSR Journal of Computer Engineering (IOSRJCE), Volume 1, Issue 5 , Volume 1, Issue 5 , June 2012.
3. Delman, B., “Genetic Algorithms in Cryptography.” Master of Science in Computer Engineering, Rochester Institute of Technology,
Rochester, New York, July 2004. 4. Som, S.; Chatergee, N.S.; Mandal, J.K., "Key based bit level genetic cryptographic technique (KBGCT)," Information Assurance and Security
(IAS), 2011 7th International Conference on , vol., no., pp.240,245, 5-8 Dec. 2011.
5. Goyat, S., “GENETIC KEY GENERATION FOR PUBLIC KEY CRYPTOGRAPHY.” International Journal of Soft Computing and Engineering (IJSCE), Volume 2, Issue 3, July 2012.
6. Sharma, L.; Pathak, B. K.; Sharma, R., “Breaking of Simplified Data Encryption Standard Using Genetic Algorithm ”, Global Journal Of
Computer Science And Technology, Volume 12, Issue 5, Version 1.0, March 2012. 7. Khan F. U.; Bhatia, S., “A NOVEL APPROACH TO GENETIC ALGORITHM BASED CRYPTOGRAPHY ”, International Journal of
Research in Computer Science, Volume 2, Issue 3, pp. 7-10, 2012.
8. Bhasin, H.; Bhatia, S., “Application of Genetic Algorithms in Machine learning”, IJCSIT, Vol. 2 (5), 2011. 9. Goldberg, D E., Genetic Algorithms in Search, Optimization, and Machine Learning. Reading, MA. : Addison-Wesley, 1989. Stallings, W.,
“Cryptography and Network Security : Principles and Practice”, 3rd Edition. Prentice Hall. Boston Columbus Indianapolis
150-154
32.
Authors: Niketa N, Shantharama Rai.C
Paper Title: Design and Modeling of Fuzzy Logic Based Voltage Controller for an Alternator
Abstrac: Wide range of electrical apparatus used in industrial application require automatic voltage regulator for
stability purpose. As the loud on an alternator is varied, its terminal voltage is also found to vary. This variation
terminal voltage is due to voltage drop in armature and armature reaction, therefore this paper aims to design voltage
regulator to maintain the terminal voltage of alternator at constant value at load condition. The armature voltage of a
155-158
synchronous generator is controlled by varying the field voltage using fuzzy logic based control method. Voltage
difference between the immediate output voltage and the rated voltage of the generator is used to process the rate of
change of voltage error. The amount of armature voltage that has to be applied to the alternator is varied by the
controller to keep the output of alternator at its rated value. The system is designed and simulated using MATLAB
simulink.
Keywords: alternator, fuzzy logic controller (FLC), voltage control.
References: 1. Brock J. LaMeres.,” Design and implementation of a fuzzy logic based voltage regulation of a synchronous generator”, Montana
state university. 2. Hasan, Abul R., Martis, Thomas S., Sadrul, A.H.M, “Design and Implementation of a Fuzzy Controller Based Automatic Voltage Regulator
for a Synchronous Generator”,IEEE Transactions on Electrical Machinery, Vol.9, No.6, Sep. 1994
3. Spoljaric, Zeljko ; Miklosevic, Kresimir & Jerkovic, Vedrana, “Synchronous Generator Modeling Using Matlab.
33.
Authors: Vijaykumar Kulkarni , Pradip Katti
Paper Title: Policies and Strategies for the Improvement in Energy Efficiency in Industries – Indian Experience
Abstrac: Energy has become the basic need of human beings. With technological advancements the supply-demand
gap is alarmingly increasing globally. This causes burden on the nation like increase in generation capacity or energy
import. Energy policies and regulations are framed by various nations. Majority of energy is consumed by industrial
sector. An effort in energy conservation by improving the energy efficiency in industries in the light of these policies
and strategies formed for industries to improve the energy efficiency can be effective. In this paper, the energy
policies of some nations including India are discussed. Energy saving strategies for industries are proposed. Energy
efficiency can be improved by these strategies. A sample case study in an industry and the results show that the
operation of the equipment and machineries in accordance with the policies and regulations has resulted in 12% of
average saving in energy with less or no investments.
Keywords: Energy conservation, energy policies, energy strategies, energy saving
References: 1. V. A. Kulkarni and P. K. Katti , Energy Strategies for India under Perspective Energy Scenario ’, International Journal of Energy Science
IJES IJES Vol.2 Iss.4 2012 pp.133-140 www.ijesci.org World Academic Publishing .
2. Challenges in meeting increasing power demand of developing economics without damaging the environment - Siong Lee Koh and
YunSeng Lim, 2010 IEEE Int. Conf. on Power and energy (PECon2010) 29Nov-1Dec 2010 Malaysia, pp923
3. ‘ Policies for the future 2011 Assessment of country energy and climate policies’ World Energy Council(WEC) publication, 2011.
4. Understanding China’s Energy Policy - Economic Growth and Energy Use, Fuel Diversity, Energy/Carbon Intensity, and International Cooperation’ Background Paper Research Centre for Sustainable Development, Chinese Academy of Social Sciences, China
5. ‘Energy in Australia 2011 ‘ Department of Resources, GPO Box 1563 Energy and Tourism, Government of Australia, 2011.
6. ’World Energy Assessment: Overview 2004 Update’ United Nations Development Programme, 2004. 7. ‘WWF the energy report 100% renewable energy ‘ WWF International pub. 2011
8. V. A.Kulkarni and. P.K.Katti, ‘ Efficient Utilization of Energy In Industry – Energy Management Perspective’ IEEE International
Conference on ‘ Power Systems Technology (POWERCON2010) China, 24- 28 Oct 2010 pp. 259. 9. V. A.Kulkarni and. P.K.Katti, ‘ Improvement of Energy Efficiency In Industries By Facility Based Energy Management’ IEEE
International Conference on Energy, Automation and Signals(ICEAS2011), Bubaneshwar India, 28-30 Dec2011
10. WWF the energy report 100% renewable energy ‘ WWF International pub. 2011 11. Electricity and energy policy’ IEEE www.electripedia.us
12. ‘Policies for the future 2011 Assessment of country energy and climate policies’ World Energy Council(WEC) publication, 2011.
13. Ram Ganesh Yadav, Anjan Roy, S A Khaparde and Polgani Pentayya ,‘India’s fast growing power sector’ IEEE Power and energy magazine July/Aug2005, pp.39
14. ‘The Brookings Foreign Policy Studies Energy Security Series: India—Executive Summary’,Tanvi Madan, The Brookings Institutions,
USA publication, November 2006 15. ‘Energy in India’s future – insights’ , Jacques Lesourne and William C. Ramsay The Institute Français des Relations Internationales
(IFRI), Paris, France, 2009
16. India National Electricity Policy , Electricity act2003(EA2003) and Energy conservation act 2001(EC2001), Government of India
159-163
34.
Authors: Shashikant Pandey, Suman Kant, Vinod Mishra, Neha Khatri, Sarepaka.V.Ramagopal
Paper Title: Parametric Optimization of Ball End Magneto Rheological Finishing Process on EN-31
Abstrac: This work is concerned to explore the effect of process parameters of the ball end magnetorheologial
finishing on the magnetic work piece to achieve nanofinishing. Magnetizing Current, working gap and Nozzle speed
have been considered as input parameters; however percent improvement in surface roughness considered as an
outcome of the process. In Present work the experiments have been carried out with above mentioned input process
parameters with the help of the standard L9 orthogonal array of Taguchi .The measurement of the surface roughness
is taken with the help of contact type Contact Mechanical Profiler PGI 120. Experimental data has been analyzed by
using pooled anova for finding the contribution of input parameters, and further searching best input values to obtain
optimal/near optimal output value. In the end a generic input-output relation has been developed using regression
analysis to predict output value for newer input values.
Keywords: Magneto rheological finishing, Surface roughness, Taguchi method, ANOVA, Regression model
References: 1. R.S. Malik, and P.M. Pandey, “Magnetic abrasive finishing of hardened AISI 52100 steel’ V. K. Jain Advanced machining processes. Allied
Publisher Pvt. Ltd., New Delhi, 2004.
2. K. Singh, Sunil Jha, P.M. Pandey “Improved ball end magnetorheological finishing process” Proceedings of the ASME 2011 3. T. Shinmura, K. Takazawa, E. HatanoMatsunaga, M., (1990), “Study on Magnetic Abrasive Finishing,”Annals of ClRP., 39(1) pp. 325-328
4. D. Golini, S. Jacobs, W. Kordonski, P. Dumas,” PrecisionOptics Fabrication Using Magnetorheological Finishing”, SPIE CR 67: Advanced
164-169
Materials for Optics and Precision Structures, (1997) 251 -274. 5. J.D. Carlson, Catanzarite., D. M Clair (1996), “Commercial magnetorehological fluid divices”, Int. J. of Modern Physics B, vol. 10, 2857-
2865.
6. E.M. Furst, and A.P. Gast, “Micromechanics of Magnetorheological Suspensions”, Physics Rev. E., vol.61, pp. 6732-6739, 2000. 7. M. Das, V.K. Jain, and P.S. Ghoshdastidar (2009). “Parametric study of process parameters and characterization of surface texture using
rotational- magnetorehological abrasive flow finishing(R-MRAFF).” Proceeding of the ASME 2009 International manufacturing science
and engineering conference, MSEC 2009 October 4-7, 2009 West Lafayette, IN . 8. W. L. Song, C.Q. Chai, , S.b. Choi and Lee C.H. “A study of finishing process of magneto- rheological fluid on steel surface.” International
Journal of Civil Engineering and Building Materials (ISSN 2223-487X) Vol.1No.1 (2011)
9. Taguchi G, “Introduction to quality engineering”, (Asian Productivity Organization, Tokyo, (1990). 10. .H. Yang, Y.S. Tarng, “Design optimization of cutting parameters for turning operations based on the Taguchi method, ” Journal of
Material Processing Technology, 84, (1998), 122–129.
35.
Authors: Thumpi.R, Manjula R.B, Sunilkumar S.Manvi
Paper Title: A Survey on Routing Protocols for Underwater Acoustic Sensor Networks
Abstrac: Underwater communication in recent times has gained great importance owing to reasons varying from
predicting natural disasters to formulating strategic defence systems. Underwater communication systems face
challenges ranging higher propagation delays to frequency related constraints like bandwidth limitations, Doppler
spread, multipath propagation and is greatly affected by distance between nodes and link orientation. This call for the
formation of most appropriate routing protocol for UASN. This paper explores the significant advantages,
disadvantages and applications of different existing routing protocols
Keywords: Underwater Acoustic Sensor Networks (UASNs), Acoustic Communication
References: 1. Ocean Engineering at Florida Atlantic University,Available online at :http//www.oe.fau.edu/research/ams.html
2. X.Yang, K.G.Ong , W.R.Dreschel, K.Zeng, C.S.Mungle and C.A.Grimes, Design of a wireless sensor network for long-term, monitoring of an aqueous environment, pp 455-472,Sensors 2 Vol.11,2002
3. J.H.Cui,J.Kong .M.Gerla and S.Zhou,Challenges : Building scalable mobile underwater wireless sensor networks for aquatic applications,
IEEE Network, Special issue on wireless sensor networking,pp. 12-18,2006 4. Akyildiz IF, Pompili D, Melodia T. Underwater acoustic sensor networks: research challenges. Ad Hoc Networks 2005;3(3):257–79.
5. Akyildiz IF, Pompili D, Melodia T. State-of-the-art in protocol research for underwater acoustic sensor networks. In: Proceedings of the 1st
ACM international workshop on underwater networks. ACM: Los Angeles (CA, USA); 2006. 6. Ayaz M, Abdullah A. Underwater wireless sensor networks: routing issues and future challenges. In: Proceedings of the 7th international
conference on advances in mobile computing and multimedia. ACM: Kuala Lumpur (Malaysia); 2009.
7. Manjula R.B, Sunilkumar S.Manvi,Issues in UASNs,International Journal of Computer and Electrical Engineering,Vol 3,No.1 February,2011
8. Mohd.Ehmer khan , Farmeena khan , An Empirical study of UASN and Terrestrial network, IJCSI International journal of Computer Science
issues, Vol.9,Issue 1,No.1,January 2012
9. Pompili D. Efficient communication protocols for underwater acoustic sensor networks. School of Electrical and Computer Engineering, Georgia Institute of Technology; 2007.
10. Heidemann J, et al. Research challenges and applications for underwater sensornetworking. In: Proceedings of the IEEE wireless
communications and networking conference, WCNC; 2006. 11. Quazi A, Konrad W. Underwater acoustic communications. Commun Mag, IEEE 1982;20(2):24–30.
12. Ovaliadis K, N.S.a.V.K. Energy efficiency in underwater sensor networks: a research review. J Eng Sci Technol Rev 2010;3(1):151–6.
13. Xie P, Cui J-H, Lao L. VBF: vector-based forwarding protocol for underwater sensor networks.Networking 2006. Networking technologies, services, and protocols;
14. performance of computer and communication networks; mobile and wireless communications systems. Berlin/Heidelberg: Springer; 2006a.
p.1216–1221 15. Nikolaou N, et al. Improving the robustness of location-based routing for underwater sensor networks. In: Proceedings of the OCEANS.–
Europe; 2007.
16. Jornet JM, Stojanovic M, Zorzi M. Focused beam routing protocol for underwater acoustic networks. In: Proceedings of the third ACM international workshop on Underwater Networks. San Francisco (California, USA): ACM; 2008.
17. Jinming C, Xiaobing W, Guihai C. REBAR: a reliable and energy balanced routing algorithm for UWSNs. In: Proceedings of the seventh
international conference on grid and cooperative computing, GCC ’08; 2008. 18. Chirdchoo, N, Wee-Seng S, Kee Chaing C. Sector-based routing with destination location prediction for underwater mobile networks. In:
Proceedings of the international conference on advanced information networking and applications workshops, WAINA ’09; 2009.
19. Daeyoup H, Dongkyun K. DFR: directional flooding-based routing protocol for underwater sensor networks. In: Proceedings of the OCEANS; 2008.
20. Carlson EA, Beau jean PP, An E. Location-aware routing protocol for underwateracoustic networks. In: Proceedings of the OCEANS; 2006.
21. Yan H, Shi ZJ, Cui J-H. DBR: depth-based routing for underwater sensor networks. In: Proceedings of the 7th international IFIP-TC6 networking conference on adhoc and sensor networks, wireless networks, next generation internet. Singapore: Springer-Verlag; 2008.
22. Uichin L, et al. Pressure routing for underwater sensor networks. In: Proceedings of the IEEE, INFOCOM; 2010.
23. Zheng G, et al. Adaptive routing in underwater delay/disruption tolerant sensor networks. In: Proceedings of the fifth annual conference on wireless on demand network systems and services, WONS; 2008.
24. Domingo MC, Prior R. A distributed clustering scheme for underwater wireless sensor networks. in personal, indoor and mobile radio
communications. In: Proceedings of the IEEE 18th International Symposium on PIMRC; 2007. 25. Pu W, Cheng L, Jun Z. Distributed minimum-cost clustering protocol for underwater sensor networks (UWSNs). In: Proceedings of the IEEE
international conference on communications, ICC ’07; 2007.
26. Ayaz M, Abdullah A, Low Tang J. Temporary cluster based routing for Underwater Wireless Sensor Networks. In: Proceedings of the International Symposium in Information Technology (ITSim); 2010.
27. Chitre M, et al. Underwater acoustic communications and networking: recent advances and future challenges. In: Proceedings of the
OCEANS; 2008. 28. Basagni S, et al. Choosing the packet size in multi-hop underwater networks.In: Proceedings of the IEEE, OCEANS. Sydney; 2010
29. Basagni S, et al. Optimizing network performance through packet fragmentation in multi-hop underwater communications. In: Proceedings of
the IEEE, OCEANS.Sydney; 2010. 30. Bin Z, Sukhatme GS, Requicha AA. Adaptive sampling for marine microorganism monitoring. In: Proceedings of the 2004 IEEE/RSJ
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36. Ethem M, Sozer MS, Proakis John G. Underwater acoustic networks. IEEE J Oceanic Eng 2000;25(1).
37. Harris AR, Zorzi M. On the design of energy-efficient routing protocols in underwater networks. In: Proceedings of the 4th annual IEEE communications society conference on sensor, mesh and ad hoc communications and networks, SECON ’07; 2007.
38. Heinzelman WB, Chandrakasan AP, Balakrishnan H. An application-specific protocol architecture for wireless microsensor networks.
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43. Jun-Hong C, et al. The challenges of building mobile underwater wirelessnetworks for aquatic applications. Network, IEEE 2006;20(3):12–8.
44. Kai Chen YZ, He Jianhua. A localization scheme for underwater wireless sensor networks. Int J Adv Sci Technol 2009;4. 45. Liu G, Li Z. Depth-based multi-hop routing protocol for underwater sensor network. In: Proceedings of the 2nd international conference on
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36.
Authors: Swati Singh, Gaurav Dubey
Paper Title: Finding Interest of People in Purchasing Real Estate by Using Data Mining Techniques
Abstrac: Data mining is the extraction of hidden predictive information from large databases; it is a powerful
technology with great potential to help organizations focus on the most important information in their data
warehouses. Data mining tools predict future trends and behaviours, helps organizations to make proactive
knowledge-driven decisions. Hence by using data mining techniques we predict the interest of people in real estate
and their pattern of purchasing them. The data has collected by moving the questionnaire among the people. We used
two data mining techniques that classify the data based on certain attributes, are classification (Zeror classifier) and
clustering (simple k means). And then based on their result several bar charts have been drawn.
Keywords: Data mining tools predict future trends and behaviours, helps organizations to make proactive
knowledge-driven decisions.
References: 1. Jiawei Han and Micheline Kamber (2006), Data Mining Concepts and Techniques, published by Morgan Kauffman,2nd ed.
2. Agrawal R, Imilienski T, Swami A (1993). Mining association rules between sets of items in large databases, In Proceedings of the ACM SIGMOD international conference on management of data.
3. Basaltoa N, Bellottib R, De Carlob F, Facchib P, Pascazio S (2005). Clustering stock market companies via chaotic map synchronization,
Physica A. 4. Berry MJA, Linoff GS (2000). Mastering data mining, New York: Wiley.
5. Boris K, Evgenii V (2005). Data Mining for Financial Applications, the Data Mining and Knowledge Discovery Handbook.
6. Data mining: Ford, C.W.; Chia-Chu Chiang; Hao Wu; Chilka, R.R.; Talburt,J.R.; Information Technology: Coding and Computing, 2005. ITCC 2005 International Conference Volume: Digital Object Identifier: 10.1109/ITCC.2005.270 Publication Year: 2005 , Page(s): 122 - 127
Vol. 1
176-179
37.
Authors: Zhenxing Luo
Paper Title: Survey of Applications of Pupil Detection Techniques in Image and Video Processing
Abstrac: This paper presents a variety of applications of the pupil detection techniques in image and Video
processing. Moreover, the robust pupil detection techniques are also discussed. The purpose of this paper is to
provide some background knowledge for new researchers in pupil detection area. .
Keywords: Pupil detection, robust techniques, Iris recognition system, and Diabetic retinopathy. .
References: 1. L. Lin, P. Lin, L. Wei, and L. Yu, "A robust and accurate detection of pupil images," in Proc. of the 3rd International Conference on
Biomedical Engineering and Informatics (BMEI), pp.70-74, 16-18 Oct. 2010.
2. G. Gomai, A. El-Zaart, H. Mathkour, "A new approach for pupil detection in iris recognition system," in Proc. of the 2nd International
Conference on Computer Engineering and Technology (ICCET), pp.V4-415, 16-18 April 2010. 3. R. Kheirolahy, H. Ebrahimnezhad, and M. H. Sedaaghi, "Robust pupil boundary detection by optimized color mapping for iris recognition,"
in Proc. of the 14th International CSI Computer Conference (CSICC'09), pp.170-175, 20-21 Oct. 2009.
4. G. Akinci, E. Polat, and O. M. Kocak, "Neuropsychiatric disorders classification using a video based pupil detection system," in Proc. of International Symposium on Innovations in Intelligent Systems and Applications (INISTA), pp.1-5, 2-4 July 2012.
5. Ektesabi and A. Kapoor, "Exact pupil and iris boundary detection," in Proc. of the 2nd International Conference on Control,
Instrumentation and Automation (ICCIA), pp.1217-1221, 27-29 Dec. 2011. 6. W. Aryaputera, X. Gao, W. Damon, Y. Sun, and Y. Wong, "Automatic pupil detection on retro-illumination lens images from a population-
based study," in Proc. of 7th IEEE Conference on Industrial Electronics and Applications (ICIEA), pp.1772-1777, 18-20 July 2012.
7. H. Xinyu, T. Changpeng, Q. Hou, A. Tokuta, and R. Yang, "An experimental study of pupil constriction for liveness detection," in Proc. of IEEE Workshop on Applications of Computer Vision (WACV), pp.252-258, 15-17 Jan. 2013.
8. Y. Ebisawa, “Robust pupil detection by image difference with positional compensation”, in Proc. of IEEE Conference on Virtual
180-181
Environments, Human-Computer Interfaces and Measurement Systems (VECIMS 2009), May 2009, Hong Kong, China. 9. Yan, J. Li, S. Liu and H. Yuan, “A robust algorithm for pupil center detection,” in Proc. of 6th IEEE Conference on Industrial Electronics
and Applications (ICIEA), 21-23 June 2011, Beijing, China.
10. S. Goni, J. Echeto, A. Villanueva, and R. Cabeza, "Robust algorithm for pupil-glint vector detection in a video-oculography eyetracking system," in Proceedings of the 17th International Conference on Pattern Recognition (ICPR 2004), pp.941-944, 23-26 Aug. 2004.
11. Z. X. Luo, “Distributed Estimation in Wireless Sensor Networks with Heterogeneous Sensors”, International Journal of Innovative
Technology and Exploring Engineering, Vol. 1, no.4, Sept. 2012 12. Z. X. Luo, “Overview of Applications of Wireless Sensor Networks”, International Journal of Innovative Technology and Exploring
Engineering, Vol. 1, no. 4, Sept. 2012
13. Z. X. Luo, “Parameter Estimation in Wireless Sensor Networks with Normally Distributed Sensor Gains”, International Journal of Soft Computing and Engineering, vol. 2, no. 6, Jan. 2013.
14. Z. X. Luo, “Parameter Estimation in Wireless Sensor Networks Based on Decisions Transmitted over Rayleigh Fading Channels”,
International Journal of Soft Computing and Engineering, Vol. 2, No. 6, Jan. 2013. 15. Z. X. Luo, “Distributed Estimation and Detection in Wireless Sensor Networks”, International Journal of Inventive Engineering and
Sciences, vol. 1, no. 3, Feb. 2013.
16. Z. X. Luo, “Anti-attack and Channel Aware Target Localization in Wireless Sensor Networks Deployed in Hostile Environments,” International Journal of Engineering and Advanced Technology, vol. 1, no. 6, Aug. 2012.
17. Z. X. Luo, “A New Direct Search Method for Distributed Estimation in Wireless Sensor Networks,” International Journal of innovative
technology and exploring engineering, vol. 1, no. 4, Sept. 2012. 18. Z. X. Luo and T. C. Jannett, “Optimal threshold for locating targets within a surveillance region using a binary sensor network,” in Proc. of
the International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering (CISSE 09), Dec. 2009.
19. Z. X. Luo and T. C. Jannett, “A multi-objective method to balance energy consumption and performance for energy-based target
localization in wireless sensor networks,” in Proc. of the 2012 IEEE SoutheastCon, Orlando, FL, Mar. 2012.
20. Z. X. Luo and T. C. Jannett, “Performance comparison between maximum likelihood and heuristic weighted average estimation methods for
energy-based target localization in wireless sensor networks,” in Proc. of the 2012 IEEE SoutheastCon, Orlando, FL, Mar. 2012. 21. Z. X. Luo, “A censoring and quantization scheme for energy-based target localization in wireless sensor networks,” Journal of Engineering
and Technology, Vol.2, no.2, 2012.
22. Z. X. Luo, “A coding and decoding scheme for energy-based target localization in wireless sensor networks”, International Journal of Soft Computing and Engineering, Vol.2, no. 4, Sept. 2012
38.
Authors: Zhenxing Luo
Paper Title: Survey of Networking Techniques for Wireless Multimedia Sensor Networks
Abstrac: This paper discusses some interesting aspects of wireless multimedia sensor networks, such as security,
energy consumption and QoS. It can serve as an introductory material for new researchers. .
Keywords: wireless multimedia sensor networks, Quality of Service, energy consumption, and security .
References: 1. D. Ru, W. Pu, and I. F. Akyildiz, "Correlation-Aware QoS Routing for Wireless Video Sensor Networks," in Proc. of 2010 IEEE Global
Telecommunications Conference (GLOBECOM 2010), pp. 6-10 Dec. 2010. 2. M. Younis, K. Akkaya, M. Eltoweissy, and A. Wadaa, "On handling QoS traffic in wireless sensor networks," in Proceedings of the 37th
Annual Hawaii International Conference on System Sciences, pp. 5-8, Jan. 2004.
3. S. Guo and T. D. Little, "QoS-enabled Video Streaming in Wireless Sensor Networks," in Proc. of 9th IEEE International Symposium on Network Computing and Applications, pp.214-217, 15-17 July 2010.
4. M. A. Hamid, M. Alam, and H. Choong-seon, "Design of a QoS-Aware Routing Mechanism for Wireless Multimedia Sensor Networks," in
Proc. Of IEEE Global Telecommunications Conference (GLOBECOM), pp.1-6, Nov. 30 2008-Dec. 4 2008. 5. H. Pei, X. Yang, and T. Yongdong, "A Robust and Energy-Efficient Approach for Image/Video Dissemination in WSNs," in Proc. of the 5th
IEEE Conference on Consumer Communications and Networking Conference (CCNC 2008), pp.665-669, 10-12 Jan. 2008.
6. H. Wang, D. Peng, W Wang, H. Sharif, and H. Chen, "Energy-Aware Adaptive Watermarking for Real-Time Image Delivery in Wireless Sensor Networks," in Proc. of IEEE International Conference on Communications (ICC '08), pp.1479-1483, 19-23 May 2008.
7. H. Wang and D. Peng, W. Wang, H. Sharif, and H. Chen, "Image transmissions with security enhancement based on region and path diversity
in wireless sensor networks," IEEE Transactions on Wireless Communications, vol.8, no.2, pp.757-765, Feb. 2009. 8. J. F. Mingorance-Puga, G. Macia-Fernandez, A. Grilo, and N. Tiglao, "Efficient multimedia transmission in wireless sensor networks," in
Proc. of 6th EURO-NF Conference on Next Generation Internet (NGI), pp.1-8, 2-4 June 2010.
9. S. Qaisar, and H. Radha, "A reliability framework for visual sensor networks," in Proc. of Picture Coding Symposium, (PCS 2009), pp.1-4, 6-8 May 2009.
10. Z. X. Luo, “Parameter Estimation in Wireless Sensor Networks with Normally Distributed Sensor Gains”, International Journal of Soft
Computing and Engineering, vol. 2, no. 6, Jan. 2013. 11. Z. X. Luo, “Parameter Estimation in Wireless Sensor Networks Based on Decisions Transmitted over Rayleigh Fading Channels”,
International Journal of Soft Computing and Engineering, Vol. 2, No. 6, Jan. 2013.
12. Z. X. Luo, “Distributed Estimation and Detection in Wireless Sensor Networks”, International Journal of Inventive Engineering and Sciences, vol. 1, no. 3, Feb. 2013.
13. Z. X. Luo, “Anti-attack and Channel Aware Target Localization in Wireless Sensor Networks Deployed in Hostile Environments,”
International Journal of Engineering and Advanced Technology, vol. 1, no. 6, Aug. 2012. 14. Z. X. Luo, “A New Direct Search Method for Distributed Estimation in Wireless Sensor Networks,” International Journal of innovative
technology and exploring engineering, vol. 1, no. 4, Sept. 2012.
15. Z. X. Luo and T. C. Jannett, “Performance comparison between maximum likelihood and heuristic weighted average estimation methods for energy-based target localization in wireless sensor networks,” in Proc. of the 2012 IEEE SoutheastCon, Orlando, FL, Mar. 2012.
16. Z. X. Luo, “A censoring and quantization scheme for energy-based target localization in wireless sensor networks,” Journal of Engineering
and Technology, Vol.2, no.2, 2012 17. Z. X. Luo, “A coding and decoding scheme for energy-based target localization in wireless sensor networks”, International Journal of Soft
Computing and Engineering, Vol.2, no. 4, Sept. 2012
18. Z. X. Luo, “Distributed Estimation in Wireless Sensor Networks with Heterogeneous Sensors”, International Journal of Innovative Technology and Exploring Engineering, Vol. 1, no.4, Sept. 2012
19. Z. X. Luo, “Overview of Applications of Wireless Sensor Networks”, International Journal of Innovative Technology and Exploring
Engineering, Vol. 1, no. 4, Sept. 2012 20. Z. X. Luo, and T. C. Jannett, “Modeling Sensor Position Uncertainty for Robust Target Localization in Wireless Sensor Networks,” in
Proceedings of the 2012 IEEE Radio and Wireless symposium, Santa Clara, CA, Jan. 2012. 21. Z. X. Luo, “Robust Energy-based Target Localization in Wireless Sensor Networks in the Presence of Byzantine Attacks,” International
Journal of Innovative Technology and exploring Engineering, vol. 1, no.3, Aug. 2012.
22. Z. X. Luo, and T. C. Jannett, “Energy-Based Target Localization in Multi-Hop Wireless Sensor Networks, in Proceedings of the 2012 IEEE Radio and Wireless symposium, Santa Clara, CA, Jan. 2012.
23. Z. X. Luo and T. C. Jannett, “Optimal threshold for locating targets within a surveillance region using a binary sensor network,” in Proc. of
182-183
the International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering (CISSE 09), Dec. 2009. 24. Z. X. Luo and T. C. Jannett, “A multi-objective method to balance energy consumption and performance for energy-based target localization
in wireless sensor networks,” in Proc. of the 2012 IEEE SoutheastCon, Orlando, FL, Mar. 2012.
39.
Authors: Zhenxing Luo
Paper Title: Survey of Corner Detection Techniques in Image Processing
Abstrac: Corner detection is important in many applications, such as image registration, mobile robots, and
computer vision. This paper discusses several important corner detectors. More recent developments in corner
detection techniques are also presented.
Keywords: Corner detector, Harris corner detector, SUSAN corner detector, and Contour-based corner detector .
References: 1. G. Xinting, Z. Wenbo, F. Sattar, R. Venkateswarlu, and E. Sung, "Scale-space Based Corner Detection of Gray Level Images Using Plessey
Operator," in Proc. of the Fifth International Conference on Information, Communications and Signal Processing, 2005, pp. 683-687.
2. G. Xinting, F. Sattar, and R. Venkateswarlu, "Multiscale Corner Detection of Gray Level Images Based on Log-Gabor Wavelet Transform,"
IEEE Transactions on Circuits and Systems for Video Technology, vol. 17, pp. 868-875, 2007. 3. C. Harris and M. Stephens, “A combined corner and edge detector,” in Proceedings of the 4th Alvey Vision Conference, pp. 147–151, 1988.
4. Willis and S. Yunfeng, "An algebraic model for fast corner detection," in Proc. of the IEEE 12th International Conference on Computer
Vision, 2009, pp. 2296-2302.
5. S. M. Smith and J. M. Brady, “Susan - a new approach to low level image processing,” International Journal of Computer Vision, vol. 23, no.
1, pp. 45–78, 1997.
6. Z. Li-hui, C. Jie, Z. Juan, and D. Li-hua, "The Comparison of Two Typical Corner Detection Algorithms," in Proc. of the Second International Symposium on Intelligent Information Technology Application, 2008, pp. 211-215.
7. Z. Ding and A. Ma, "Harris corner detection based on the multi-scale topological feature," in Proc. of the 2011 International Conference on
Computer Science and Network Technology, pp.1394-1397, Dec. 2011. 8. B. Sirisha and B. Sandhya, "Evaluation of distinctive color features from harris corner key points," in Proc. of the 2013 IEEE 3rd
International Advance Computing Conference, pp.1287-1292, Feb. 2013.
9. S. Kim, I. Kweon and W. Lee, "Orientation based multi-scale corner detection for mobile robot application," in Proc. of the 12th International Conference on Control, Automation and Systems, pp.466-468, Oct. 2012.
10. M. Awrangjeb, G. Lu, and C. S. Fraser, "Performance Comparisons of Contour-Based Corner Detectors," IEEE Transactions on Image
Processing, vol.21, no.9, pp.4167-4179, Sept. 2012. 11. Z. X. Luo, “Distributed Estimation in Wireless Sensor Networks with Heterogeneous Sensors”, International Journal of Innovative
Technology and Exploring Engineering, Vol. 1, no.4, Sept. 2012
12. Z. X. Luo, “Overview of Applications of Wireless Sensor Networks”, International Journal of Innovative Technology and Exploring Engineering, Vol. 1, no. 4, Sept. 2012
13. Z. X. Luo, “Parameter Estimation in Wireless Sensor Networks with Normally Distributed Sensor Gains”, International Journal of Soft
Computing and Engineering, vol. 2, no. 6, Jan. 2013. 14. Z. X. Luo, “Parameter Estimation in Wireless Sensor Networks Based on Decisions Transmitted over Rayleigh Fading Channels”,
International Journal of Soft Computing and Engineering, Vol. 2, No. 6, Jan. 2013.
15. Z. X. Luo, “Distributed Estimation and Detection in Wireless Sensor Networks”, International Journal of Inventive Engineering and Sciences, vol. 1, no. 3, Feb. 2013.
16. Z. X. Luo, “Anti-attack and Channel Aware Target Localization in Wireless Sensor Networks Deployed in Hostile Environments,”
International Journal of Engineering and Advanced Technology, vol. 1, no. 6, Aug. 2012. 17. Z. X. Luo, “A New Direct Search Method for Distributed Estimation in Wireless Sensor Networks,” International Journal of innovative
technology and exploring engineering, vol. 1, no. 4, Sept. 2012.
18. Z. X. Luo and T. C. Jannett, “Optimal threshold for locating targets within a surveillance region using a binary sensor network,” in Proc. of the International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering (CISSE 09), Dec. 2009.
19. Z. X. Luo and T. C. Jannett, “A multi-objective method to balance energy consumption and performance for energy-based target localization
in wireless sensor networks,” in Proc. of the 2012 IEEE SoutheastCon, Orlando, FL, Mar. 2012. 20. Z. X. Luo and T. C. Jannett, “Performance comparison between maximum likelihood and heuristic weighted average estimation methods for
energy-based target localization in wireless sensor networks,” in Proc. of the 2012 IEEE SoutheastCon, Orlando, FL, Mar. 2012. 21. Z. X. Luo, “A censoring and quantization scheme for energy-based target localization in wireless sensor networks,” Journal of Engineering
and Technology, Vol.2, no.2, 2012.
22. Z. X. Luo, “A coding and decoding scheme for energy-based target localization in wireless sensor networks”, International Journal of Soft Computing and Engineering, Vol.2, no. 4, Sept. 2012.
184-185
40.
Authors: M. Aziz, Vinod Kumar, Aasha Chauhan, Bharti Thakur
Paper Title: Power Quality Improvement by Suppression of Current Harmonics Using Hysteresis Controller
Technique
Abstrac: Recently wide spread of power electronic equipment has caused an increase of the harmonic disturbances
in the power systems. The nonlinear loads draw harmonic and reactive power components of current from ac mains.
Current harmonics generated by nonlinear loads such as adjustable speed drives, static power supplies and UPS. Thus
a perfect compensator is required to avoid the consequences due to harmonics. To overcome problems due to
harmonics Shunt Active Power Filter (SAPF) has been considered extensively. SAPF has better harmonic
compensation than the other approaches used for solving the harmonic related problems. The performance of the
SAPF depends upon different control strategies. This paper presents the performance analysis of SAPF under most
important control strategy namely instantaneous real active and reactive power method (p-q) for extracting reference
currents of shunt active filters under unbalanced load condition. Detailed simulations have been carried out
considering this control strategy and adequate results were presented. These simulation results validate the
significance of instantaneous real active and reactive power (p-q) control strategy in achieving an effective harmonic
compensation under unbalanced load conditions. In this paper, harmonic control strategy is applied to compensate the
current harmonics in the system. A detailed study about the harmonic control method has been used using shunt
active filter technique
Keywords: Hysteresis Current control, Instantaneous power (p–q) theory, PI Controller, Shunt Active Power Filter
References:
186-191
1. .H, 1996. “New Trends in Active Filters for Power Conditioning”, IEEE Transaction on Industrial Applications, vol. 32, No 6, Dec., pp 1312-1322.
2. Akagi.H, 2006. “Modern active filter and traditional passive filters”, Bulletin of the polish academy of sciences technical sciences
vol.54.No.3 3. Ali Ajami and Seyed Hossein Hosseini, 2006. “Implementation of a Novel Control Strategy for Shunt Active Filter”, ECTI Transactions on
Electrical Eng., Electronics, And Communications Vol.4, No.1
4. .Akagi, Hirofumi. Active Filters for Power Conditioning. In Timothy L.Skvarenina. The Power Electronics Handbook: Industrial Electronics Series. United State of America: CRC Press. Chap. 17:30-63. 2002.
5. .Peng, F. Z., Akagi, H. and Nabae, A. A Novel Harmonics Power Filter.IEEE Transactions on Power Electronics Specialists Conference.
April 11-14. PESC ’88 Record: IEEE. 1988. 1151-1159. 6. Grady, W. M., Samotyi, M. J. and Noyola, A. H. Survey of Active Line Conditioning Methodologies. IEEE Transactions on Power
Delivery.1990. 5 (3): 1536-1542.
7. Bhattacharya S. and Divan D., “Synchronous frame based controller implementation for a hybrid series active filter system,” IEEE Conf. On Industry applications, vol.4,(1995):pp. 2531–2540
8. Lin C. E., Su W. F., Lu S. L, Chen C. L., and Huang C. L., “Operation strategy of hybrid harmonic filter in demand-side system,” IEEE-IAS
Annul. Meeting, Industry applications, (1995):pp. 1862–1866. 9. Dahono P.A, “New hysteresis current controller for single-phase bridge inverters” IET journal on [10] Power electronics, vol.2
(2009):pp. 585-594
10. Casaravilla, G, Salvia, A., Briozzo, C. and Watanabe, E. Control Strategies of Selective Harmonics Current Shunt Active Filter. IEE Proc.- Generation, Transmission and Distribution. 2002. 149 (6): 689-694.
11. Grady, W. M., Samotyi, M. J. and Noyola, A. H. Survey of Active Line Conditioning Methodologies. IEEE Transactions on Power
Delivery.1990. 5 (3): 1536-1542.
12. Bhattacharya S. and Divan D., “Synchronous frame based controller implementation for a hybrid series active filter system,” IEEE Conf. On
Industry applications, vol.4,(1995):pp. 2531–2540
13. Lin C. E., Su W. F., Lu S. L, Chen C. L., and Huang C. L., “Operation strategy of hybrid harmonic filter in demand-side system,” IEEE-IAS Annul. Meeting, Industry applications, (1995):pp. 1862–1866.
14. Dahono P.A, “New hysteresis current controller for single-phase bridge inverters” IET journal on Power electronics, vol.2 (2009):pp. 585-
594. 15. Hongyu Li., Fang Zhuo, Zhaoan Wang, Lei W. and Wu L., “A novel time domain current detection algorihm for shunt active power
filters” IEEE Trans. power systems, vol.20, (2005):pp. 644–651.
16. Buso S., Malesani L., Mattavelli P. and Veronese R., “Design and fully digital control of parallel active filter for thyristor rectifier to comply with ICE 1000-3-2 standard” IEEE Trans. Ind. Applicat., vol. 34, (1998):pp. 508-517
41.
Authors: Prabhat Kumar Sinha, Raisul Islam, Chandan Prasad, Mohd. Kaleem
Paper Title: Analysis of Residual Stresses and Distortions in Girth-Welded Carbon Steel Pipe
Abstrac: This article, the weld joint suffers various types of weld-induced residual stress fields (hoop and axial)
and deformation patterns (axial shrinkage, radial shrinkage). In this paper Three-dimensional finite element
modeling of residual stresses in a girth-welded carbon steel pipe is presented with an emphasis on modeling
procedures for the global residual stress characteristics. To precisely capture the distortions and residual stresses,
computational methodology based on three-dimensional finite element model for the simulation of gas tungsten arc
welding in thin-walled pipe is presented. Butt-weld geometry with single "V" for a 300 mm outer diameter cylinder
of 3 mm thick is used. The complex phenomenon of arc welding is numerically solved by sequentially coupled
transient, non-linear thermo-mechanical analysis. The accuracy of both the thermal and structural models is validated
through experiments for temperature distribution, residual stresses and distortion. The simulated result shows close
correlation with the experimental measurements.
Keywords: FEM; welding simulations; Distortions; Residual Stresses; Girth Weld.
References: 1. Rybicki, E. F., Schmueser, D. W., Stone-sifer, R. W., Groom, J. J., Mishler, H. W. 1978. A finite-element model for residual stresses
and deflections in girth-butt welded pipes. Journal of Pressure Vessel Technology, Vol. 100, pp. 256-262.. [2]. Brust, F. W.,
Stonesifer, R. B. 1981. Effect of weldingarameters on residual stresses in BWR piping systems. EPRI NP-1743, Project 1174-1, Final
Report 2. Karlsson, C. T. 1989. Finite element analysis of temperatures and stresses in a single-pass butt-welded pipe-influence of mesh
density and material modeling. Engineering Computations, Vol. 6, pp. 133-141..
3. Fujita, Y., Nomoto, 1., Hasegawa, H. 1980. Deformations and residual stresses in butt welded pipes and shells. Nav. Archit. a.OceanEngng. (Soc. of Nay. Archit. of Jap.) 18, pp. 164-174, and IIW-Doc. X-963-80
4. Josefson, B. L. 1983. Stress redistribution [12] Y. Dong, J. Hong, C. Tsai and P. Dong. Finite Element modeling of residual stresses in
austenitic stainless steel pipe girth welds, Welding Journal, Weld Research Supplement,442 (1997) 449-444. 5. Yaghia, T. H. Hydea, A. A. Becker, W. Suna and J. A. Williams, Residual stress simulation in thin and thick-walled stainless steel pipe
welds including pipe diameter effects, International Journal of Pres-sure Vessels and Piping,83 (11-12) (2006) 864-874.
6. D. Deng and H. Murakawa, Numerical simulation of temperature field and residual stress in multi-pass welds in stainless steel pipe and comparison with experimental measurements, Computational Material Science,37 (3) (2006) 269-277
7. B. Brickstad and B. L. Josefson, A parametric study of residual stresses in multi-pass butt-welded stainless steel pipes, International Journal
of Pres-sure Vessels and Piping,75 (1) (1998) 11-25. 8. E. F. Rybicki, D. W. Schmueser, R. W. Stonesifer, J. J. Groom and H. W. Mishaler, A Finite Element model for residual stresses and
deflections in girth-butt welded pipes, ASME Journal of Pressure Ves-sel Technology,100 (1978) 256-262.
9. E. F. Rybicki, P. A. McGuire, E. Merrick and J. Wert, The effect of Pipe thickness on residual stresses due to girth welds. ASME Journal of Pres-sure Vessel Technology, 104 (1982) 204-209
10. E. F. Rybicki and R. B. Stonesifer, Computation ofresidual stresses due to multi-pass welds in piping system. ASME Journal of Pressure
Vessel Technology, 101 (1979) 49-54. 11. Y. Dong, J. Hong, C. Tsai and P. Dong. Finite Element modeling of residual stresses in austenitic stainless steel pipe girth welds, Welding
Journal, Weld Research Supplement,442 (1997) 449-444.
12. R. I. Karlsson and B. L. Josefson, Three- dimensional Finite Element analysis of temperature and stresses in single-pass butt-welded pipe. ASME Journal of Pressure Vessel Technology,112 (1990) 76-84.
13. M. Jonsson and B. L. Josefson, Experimentally determined transient and residual stresses in the butt-welded pipes, Journal of Strain Analysis,23 (1) (1988) 25-31.
14. L. Karlsson, M. Jonsson, L. E. Lindgren, M. Näss-tröm and L. Troive, Residual stresses and deforma-tions in a welded thin-walled pipe,
Proc. ASME Pressure Vessel and Piping Conf. (Hawaii, July 1989)PVP-173 (1989) 7-11. 15. S. Fricke, E. Keim and J. Schmidt, Numerical weld modeling-a method for calculating weld-induced residual stresses, Nuclear Engineering
and Design,206 (2-3) (2001) 139-150.
192-199
16. ANSYS-10.0 user manual. 17. J. Goldak, A. Chakravarti and M. Bibby, A new Finite Element model for welding heat source. Metallurgical Transactions B. 15B (1984)
299-305
18. L. F. Anderson, Residual stresses and deformations in steel structures, PhD. Thesis, Technical University of Denmark,(2000) 19. Vishay Group, Measurement of residual stresses by the hole drilling strain gage method, Technical Note No.TN-503.
(www.vishay.com/brands/measurements_group/guide/tn/tn503/503index.htm).
20. P.J. Bouchard, D. George, J.R. Santisteban, G. Bruno, M. Dutta, L. Edwards, E. Kingston,D.J. Smith, Measurement of the residual stresses in a stainless steel pipe girth weld containing long and short repairs, International Journal of Pressure Vessels and Piping, 82,(4), (
2005),299–310
21. W.C. Jiang,B.Y. Wang,J.M. Gong,S.T. Tu, Finite element analysis of the effect of welding heat input and layer number on residual stress in repair welds for a stainless steel clad plate, Materials & Design, 32(5), (2011), 2851–2857
22. Chin-Hyung Lee, Jeong-HoonBaek, Kyong-Ho Chang, Bending capacity of girth-welded circular steel tubes, Journal of Constructional
Steel Research,75 (2012), 142–151 23. Chin-Hyung Lee, Kyong-Ho Chang, Jeong-Ung Park, Three-dimensional finite element analysis of residual stresses in dissimilar steel pipe
welds, Nuclear Engineering and Design256, (2013),160–168
42.
Authors: Meghna B. Patel, Ashok R. Patel
Paper Title: Performance Improvement by Classification Approach for Fingerprint Identification System
Abstrac: In the world of Information Technology, Information Security is an important factor. For Information
Security, authentication plays a vital role. And for Secure Authentication now a days biometric based authentication
(‘who you are’, e.g. Fingerprint) replace the Knowledge Based (‘what you know’, e.g. Password) and Object Based
Authentication (‘what you have’, e.g. Token). Biometric authentication is the method which identifies or verifies the
person based on his/her physiological or behavioral characteristics. The fingerprint is most widely used in biometric
world. In Fingerprint Authentication different three levels (The Global or Galton level, The Local Level, The Very
Fine Level) of Feature extraction techniques are used at the time of Fingerprint Identification and Verification. In
Global or Galton Level identify the flow of ridges and valleys and also extract delta and core point features which
classify the fingerprint in different pattern group like arch, tented arch, whorl, left loop and right loop. In tradition
biometric recognition approach, the fingerprint template is match with all the template of the database. So, it will take
long time for the individual’s authentication. In this paper present an approach which speed up the matching process
by classifying the fingerprint template database on various fingerprint pattern group. So, instead of matching process
done on whole database it will be done on specific fingerprint pattern group and reduce the no. of matches and
improve the performance 3 time faster than the traditional approach.
Keywords: Biometrics, classification, identification, verification, minutiae points, singular points. .
References: 1. Integration of Biometrics with Cryptographic Techniques for Secure Authentication of Networked Data Access by Abanti Cyrus Makori. 2. Jinwei Gu, Jie Zhou, and Chunyu Yang, “Fingerprint Recognition by Combining Global Structure and Local Cues”, IEEE Transactions on
Image Processing, vol. 15, no. 7, pp. 1952 – 1964, (2006).
3. Arpita Gopal, Chandrani Singh, e-World: Emerging Trends in Information Technology, Excel Publication, New Delhi (2009). 4. Fingerprint Patterns based on Henry Classification System
5. http://www.crimescene-forensics.com/Fingerprints.html “Basic Fingerprint Pattern”
6. http://www.slideshare.net/juroc26/fingerprint-classification-slide-1#btnNext 7. K. Jain, L. Hong, and R. Bolle, “On-line fingerprint verification”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(4),
1997, pp. 302–314.
8. Roli Bansal, Priti Sehgal, and Punam Bedi, “Minutiae Extraction from Fingerprint Images - a Review”, IJCSI (International Journal of Computer Science Issues, Volume 8, Issue 5 No 3, September 2011.
9. D.R. Ashbaugh. Quantitative-Qualitative Friction Ridge Analysis: “An Introduction to Basic and Advanced Ridgeology”. CRC Press, 1999.
10. A.K. Jain, Y. Chen, and M. Demirkus. “Pores and Ridges: High-Resolution Fingerprint Matching Using Level 3 Features”, PAMI, 29(1):15-27, January 2007.
200-203
43.
Authors: Vini Malik, Aakanksha Gautam, Aditi Sahai, Ambika Jha, AnkitaRamvir Singh
Paper Title: Satellite Image Classification Using Fuzzy Logic
Abstrac: The intent of the classification process is to categorize all pixels in a digital image into one of several
land cover classes, or "themes". In this paper, fuzzy inference system is developed for classifying the satellite image
of (472x546x7 pixel).The input image from the satellite was in form of 7 bands which were then reduced to 3 bands.
Keywords: classification, fuzzy logic,if-then rules, land cover, remote sensing .
References: 1. Rafael C. Gonzalez, Richard E. Woods and Steven L.Eddins “Digital Image Processing Using Matlab,” Pearson Education, Second
Impression,2007. 2. www.sjsu.edu/faculty/watkins/fuzzysets.htm.
3. Fuzzy set available (online) en.wikipedia.org/wiki/Fuzzy_set
4. Mario. I. Chacon. M “Fuzzy logic for image processing,” Advanced Fuzzy logic Techniques in industrial applications, 2006. 5. Foody G. M., “Approaches for the production and evaluation of fuzzy land cover classification from remotely-sensed data”, International
Journal of Remote Sensing, 17, pp. 1317–1340, 1996.
6. Fuzzy Mathematics -Wikipedia 7. Supervised Classification and Unsupervised classification
available(online)http://academic.emporia.edu/aberjame/student/banman5/perry3.html
8. MATLAB Functions in Fuzzy Logic Toolbox www.mathworks.in/help/fuzzy/functionlist.html 9. Fuzzy Logic Toolbox available (online)http://www.mathworks.in/products/fuzzy-logic/description3.htm
10. Image Classification and Analysis available (online)www.nrcan.gc.ca/earth-sciences/geography-boundary/remote.../1920
204-207
44.
Authors: Haval Sardar Kamil
Paper Title: Analysis of Self Excited Induction Generator Driven By Wind Turbine System Using Current Source
Inverter Technology
Abstrac: This paper describes the simulation model and the harmonics analysis of Current Source Inverters fed RL
load. The SEIG fed PWM Current Source Inverter for variable speed wind energy conversion systems are considered
for various stand-alone applications. In this paper, the SEIG fed IGBT PWM Inverter for RL load system are clearly
explained with the help of MATLAB/SIMULINK models. The generated voltage of wind driven self-excited
induction generator (SEIG) is mainly depending on the wind velocity fluctuations, suitable capacitance magnitude
and load conditions. The PWM Inverter has interface with the wind driven self-excited induction generator. The main
objective of this paper is to extract maximum power from the generator to the grid connected wind energy conversion
system. The variable magnitude, variable frequency voltage of the generator can be controlled by choosing the proper
modulation index. The simulation analysis of the proposed inverter will be discussed and the total harmonic distortion
will be evaluated.
Keywords: Self-Excited induction generator (SEIG), Current Source Inverter, Pulse Width Modulation (PWM),
Wind Turbine, Wind Energy Conversion Application (WECs), Isolated load.
References: 1. Harish Kumar, Neel Kamal, “Steady State Analysis of Self-Excited Induction Generator”, International Journal of Soft Computing and
Engineering (IJSCE) ISSN: 2231-2307, Volume-1, Issue-5, November 2011. 2. Swati Devabhaktuni1* S.V.Jayaram Kumar2, “Modeling and Analysis of Wind turbine Driven Self-Excited Induction Generator Connected
to Grid Interface with Multilevel H-Bridge Inverter”, Journal of Energy Technologies and Policy ISSN 2224-3232 (Paper) ISSN 2225-0573
(Online) Vol.2, No.2, 2012. 3. Palle, M.G. Simoes, F.A. Farret: Dynamic Simulation and Analysis of Parallel Self-Excited Induction Generators for Islanded Wind Farm
Systems, IEEE Trans. on Industry Applications, Vol. 41, No. 4, 2005, pp. 1099–1106.
4. Seyoum, C. Grantham and F. Rahman, “Novel Analysis and Modeling of an Isolated Self-ExcitedInduction Generator Taking Iron Loss into Account”, IEE Proc. B, Vol. 136, No. 2, pp. 61-68, March 1989.
5. D. Basset, F.M. Potter: Capacitive Excitation of Induction Generators: Trans. Amer. Inst. Electric. Eng., 54, 1935, pp. 540–545.
6. S. Subramanian and R. Bhuvaneswari, “Optimal Design of Self-excited Cage Induction Generator Using Particle Swarm Optimization”, Iranian Journal of Electrical and Computer Engineering, VOL. 6, NO. 1, WINTER-SPRING 2007.
7. Rohin M. Hilloowala and Adel M. Sharaf, “A Rule-Based Fuzzy Logic Controller for a PWM Inverter in a Stand-alone Wind Energy
Conversion Scheme” IEEE, Transaction on Industry Applications, Vol. 32.No.1 January/February 1996, pp 57- 65. 8. Dawit S Eyaum Colin Grantham, and Muhammed Fazlur Rahman,”The dynamic characteristics of an isolated self-excited induction
generator driven by a wind turbine”, IEEE, Transaction on Industry applications, Vol. 39.No.4, July/August 2003 pp 936 - 944.
9. T.F. Chan.” Capacitance requirements of self-excited induction generators “, IEEE Transactions on Energy Conversion, Vol. 8, No. 2, June 1993 pp 304-311.
10. Andrew Miller, Edward Muljadi and Donald S. Zinger, “A Variable Speed Wind Turbine Power Control”, IEEE, Transaction on Energy
Conversion, Vol. 12.No.2 June 1997, pp – 181- 186. 11. M.Sasikumar,S.ChenthurPandian"Implementation and Characteristics of Induction Generator fed Three Level ZSI for Wind Energy
Conversion Scheme" (IJAEST) International Journal of Advanced Engineering Science and Technologies Vol No. 1, Issue No. 1, 052 –
057. 12. K. Al Jabri and A. I. Alolah, "Capacitance requirements for isolated self-excited induction generators", IEEE Proc., B, Vol. 137, No. 3,
1990, pp.154-159
208-211
45.
Authors: Mustafa Jawad Kadhim, D.S.Chavan
Paper Title: Improvement Fault-ride Through of DFIG Based Wind Turbines by Using a Series Compensation
Technology with Emphasis Put on the Mitigation of Voltage Dips
Abstrac: Low Voltage Ride Through is an important feature for wind turbine systems to fulfill grid code
requirements. In case of wind turbine technologies using doubly fed induction generators the reaction to grid voltage
disturbances is sensible. Hardware or software protection must be implemented to protect the converter from tripping
during severe grid voltage faults. In this paper the Dynamic Voltage Restorer (DVR) solution for LVRT of DFIG
wind turbines is investigated by simulation results using a detailed converter model considering the switching and
appropriate 2 MW wind turbine system parameter. To show the effectiveness of the proposed method the results are
compared to a conventional fault ride through of the DFIG using a crowbar circuit. Measurement results on a 22 kW
laboratory DFIG test bench show the effectiveness of the proposed control technique.
Keywords: Doubly fed induction generator (DFIG), dynamic voltage restorer (DVR), fault ride-through and wind
energy.
References: 1. M. Tsili and S. Papathanassiou, “A review of grid code technical requirements for wind farms,” Renewable Power generation, IET, vol. 3,
no. 3, pp. 308–332, Sept. 2009.
2. S. Seman, J. Niiranen, and A. Arkkio, “Ride-throughanalysis of doubly fed induction wind-power generatorunder unsymmetrical network disturbance,” Power Systems, IEEE Transactions on, vol. 21, no. 4,pp. 1782–1789, Nov. 2006.
3. S. Foster, L. Xu, and B. Fox, “Behaviour and protection of doubly-fed induction generators during networkfaults,” in Power & Energy
Society General Meeting, 2009. PES ’09. IEEE, July 2009, pp. 1–8. 4. L. Peng, B. Francois, and Y. Li, “Improved crowbar control strategy of dfig based wind turbines for gridfault ride-through,” Applied Power
Electronics Conference and Exposition, 2009. APEC 2009. Twenty-Fourth Annual IEEE, pp. 1932–1938, Feb. 2009.
5. W. Zhang, P. Zhou, and Y. He, “Analysis of the by-pass resistance of an active crowbar for doublyfedinductiongenerator based wind
turbines under grid faults,” Electrical Machines and Systems, 2008.ICEMS 2008. International Conference on, pp. 2316–2321, Oct. 2008.
6. J. Morren and S. de Haan, “Short-circuit current of wind turbines with doubly fed induction generator,”EnergyConversion, IEEE
Transactions on, vol. 22, no. 1, pp. 174–180, March 2007. 7. J. Yang, J. Fletcher, and J. O’Reilly, “A series-dynamic-resistor-basedconverter protection scheme for doubly-fed induction generator
duringvarious fault conditions,” IEEE Trans. Energy Convers., vol. 25, no. 2,pp. 422–432, Jun. 2010.
8. L. H. Hansen, L. Helle, F. Blaabjerg, E. Ritchie, S. Munk-Nielsen, H. Bindner, P. Sørensen, and B. Bak-Jensen, “Conceptual survey of generators and power electronicsfor wind turbines,” Risø National Laboratory, Roskilde, Denmark, Tech. Rep.Risø-R-1205(EN), ISBN 87-
550-2743-8, Dec. 2001.
9. W. Leonhard, Control of Electrical Drives, 2nd ed. Berlin, Germany: Springer-Verlag, 1996. 10. T. Thiringer and J. Luomi, “Comparison of reduced-order dynamic models of inductionmachines,” IEEE Trans. Power Syst., vol. 16, no. 1,
pp. 119–126, Feb. 2001.
11. J. Nielsen and F. Blaabjerg, “A detailed comparison of system topologiesfor dynamic voltage restorers,” IEEE Trans. Ind. Appl., vol. 41,
212-216
no. 5,pp. 1272–1280, Sep./Oct. 2005. 12. M. H. J. Bollen, Understanding Power Quality Problems Voltage Sags andInterruptions. New York: Wiley, 2000.
13. S. Mahesh,M.Mishra, B. Kumar, and V. Jayashankar, “Rating and designissues of dvr injection transformer,” in Proc. 23rd Annu. IEEE
Appl. PowerElectron. Conf. Expo. (APEC), Feb. 2008, pp. 449–455.
46.
Authors: Nadiya G. Mohammed
Paper Title: Overview of Existing Solutions for Fault Ride through Capability Improvement of DFIG used in
Wind Turbines
Abstrac: The growing of wind generation gives arise for new challenges for its integration to the network tripping
of large amount of wind power will lead to serious consequence to the grid . in this paper DFIG performance used in
wind turbine during voltage dip due to fault. Wind turbines equipped with doubly-fed induction generators (DFIG)
can regulate easily the reactive power generated in steady state. However, challenges appear when reactive power has
to be generated during voltage dips. A survey of the problems associated with voltage dips and solutions for Ride
Through operation of this type of system are given. an overview of different alternatives for Low Voltage Ride
Through are presented in this paper.
Keywords: Doubly-Fed induction Generator, Low Voltage Ride Trough, Voltage Dip
References: 1. ELTRA, “Specificatons for connecting wind farms to the transmission network”, 2000. 2. E.on Netz, “Ergänzede netzansschlussregeln für windenergieanlagen”. Technical report E.on Netz, 2001.
3. J. Matevosyan, T. Ackermann, S. Bolik, L.Söder “Comparison of International Regulations for Connection of Wind Turbines to the
Network” Nordic Wind Power Conference, 1-2 march, 2004 4. C. Jauch, P. Sørensen, B. Bak-Jensen “International Review of Grid Connection Requirements for Wind Turbines” Nordic Wind Power
Conference, 1-2 march, 2004
5. M.H.J. Bollen , G. Olguin, M. Martins, “Voltage Dips at the Terminals of Wind Power Installations” Nordic Wind Power Conference, march 1-2, 2004
6. J. Niiranen “Voltage Dip Ride Through of a doublyfed system” World Wide Energy Conference, 2004
7. T. Thiringer, A. Petersson, T. Petru, “Grid disturbance response of wind turbines equipped with induction generator and doubly-fed induction generator”, Power engineering society annual meeting, Toronto, Canada july, 2003
8. J. M. Rodriguez, J. L Fernandez, D. Beato, R. Iturbe, J. Usaola, P. Ledesma, j. R. Wilhelmi, “Incidence on power system dynamics of high
penetration of fixed speed and doubly fed wind energy systems: study of the Spanish case”, IEEE Trans. in Power Systems., vol. 17,nº 4 pp. 1089–1095, November 2002.
217-119
47.
Authors: P. Kaveri, G.R.K. Prasad, Fazal Noorbasha
Paper Title: Router Design Using Cadence Encounter
Abstrac: As the technology is going on increasing rapidly the electronic component units are also increasing. The
initial innovation for the technology growth is the internet communications and also the rapid growth in the chip
density slashed the power limits. As there is no advancement in the power storage devices like batteries .so there is a
need for the low power design. In all of this innovations router plays a major role in diverting the information from
one to many channels, now a days it became the essential thing The concept of reconfigurable router to contribute to
the creation of the next-generation energy-efficient Internet infrastructure. Through enhancement of the router
architectural design, it is expected to reduce average power consumption during network operation. Depending on the
traffic there is feasibility for adjusting the frequency. This project has been done in the cadence 90nm technology.
System verilog for verification has been done using Synopsys tools
Keywords: Low power, Routing, power or phrases in alphabetical order, separated by commas.
References: 1. Akella, S. Seshan, and A. Shaikh, “An empirical evaluation of widearea internet bottlenecks,” in Proc. ACM SIGCOMM Conf. Internet
Measure. (IMC), M. Crovella, Ed., New York, 2003, pp. 101–114.
2. N. Hopper, E. Y. Vasserman, and E. Chan-tin, “How much anonymity does network latency leak,” in Proc. 14th ACM Conf. Comput
Commun. Secur. ACM (CCS ’07), 2007. 3. G. Bissias, M. Liberatore,D. Jensen, and B. Levine, “Privacy vulnerabilities in encrypted HTTP streams,” Privacy Enhancing Technol., pp.
1–11, 2006 [Online]. Available: http://dx.doi.org/10.1007/11767831_1
4. M. Liberatore and B. N. Levine, “Inferring the source of encrypted HTTP connections,” in Proc. 13th ACM Conf. Comput. Commun.Secur. (CCS ’06), New York, 2006, pp. 255–263 [Online]. Available: http://dx.doi.org/10.1145/1180405.1180437
5. D. X. Song, D. Wagner, and X. Tian, “Timing analysis of keystrokes and SSH timing attacks,” in Proc. USENIX Security Symp. , 2001. [6]
C. V.Wright, L. Ballard, S. E. Coull, F.Monrose, and G. M. Masson, “Spot me if you can: Uncovering spoken phrases in encrypted VOIP conversations,” in Proc. 2008 IEEE Symp. Secur. Privacy( SP ’08),Washington, DC, 2008, pp. 35–49, IEEE Computer Soc
6. Susrutha Babu Sukhavasi, Suparshya Babu Sukhavasi Lakshmi Narayana Thalluri , S R Sastry Kalavakolanu Harikishore K, Fazal Noor
Bhasha,“ Implementation of new slant for efficient power saving in digital design by using automatic clock gating technique”,IJERA, Vol. 2,
Issue 2, Mar-Apr 2012, pp.884-889.
220-224
48.
Authors: Naveen Kumar Malik
Paper Title: Cognitive Amplifier: A New Approach for Cable Television
Abstrac: Intelligent, Cognitive and Conscious Machines are considered as the future of design in system
engineering. These are used in every field of engineering. In this concept paper, a new idea of cognitive amplifier is
introduced. Its application in cable television is discussed. The steps of cognitive cycle are discussed. The pictorial
diagram of traditional amplifier and cognitive amplifier with its responses is shown to explain the concept. The gain
control capability of cognitive amplifier for signal transmission system is shown pictorially. This concept provides
flat response for the good quality picture and sound response at all channels.
Keywords: Amplifier, Cognitive amplifier,
225-228
References: 1. Haoxi Zhang, Cesar Sanin, Edward Szczerbicki (2010), “Towards Decisional DNA – based Cognitive Embedded Systems”, IEEE. 2. J.Mitolla (2000), “Cognitive Radio – An Integrated Agent Architecture for Software Defined Radio,” Ph.D. Dissertation, KTH Royal
Institute of Technology, Stockholm, Sweden.
3. www.en.wikipidiaorg/wiki/amplifier
4. www.hdtvprimer.com/antennas/basics.html
5. Shipra Kapoor,SVRK Rao,Ghanshyam Singh (2011), “Opportunistic Spectrum Sensing by Employing matched Filter in cognitive Radio
Network” IEEE. 6. J.H.Reed (2002), “Software Radio : A modern Approach to Radio Engineering” Prentice Hall, Englewood Cliffs, N J.
7. S. Haykin(2005) , “Cognitive Radio : Brain – Empowered Wireless Communications” IEEE J,Select. Area in Commun, vol.23, no.2,
pp.201-220. 8. B.A.Fette (2006), “Cognitive Radio” 1st ed. Newnes.
9. J.O.Neel (2006), “Analysis and design of cognitive radio networks and distributed radio resource management algorithms” Ph.D. dissertation , Virginia Polytechnic Institute and State University.
10. R.Rubenstein (2007), “Radios get smart” IEEE Spectrum, Consumer Electronics, pp.46-50.
11. Paul Baxter and Will Browne (2009), “Perspectives on Robotic Embodiment from a Developmental Cognitive Architecture” IEEE Conference.
12. Kopetz, Hermann (2008), “The Complexity Challenge in Embedded System Design” Object Oriented Real-Time Distributed Computing
(ISORC), 11th IEEE International Symposium. 13. Ashwin Amanna, Jeffrey H. Reed (2010), “Survey of Cognitive Radio Architectures” IEEE.
14. V.K.Bhargava and E. Hossain (2007), “Cognitive Wireless Communication Networks, 1st ed. Springer.
15. J.Mitola (1999), “Cognitive Radio: Making Software Radio More Personal” IEEE Personal Communication, vol. 6, no. 4, pp. 13-18,.
16. Siddavatm (2011), “Mapping of cognitive radio as intelligent agent architecture”Wireless VITAE , IEEE Conference Publication.
17. Anna T. Lawniczak, Bruno N. Di Stefano(2010), “Computational intelligence based architecture for cognitive agents” ICCS, Science
Direct. 18. Tevfik Yucek and Huseyin Arslan (2009), “A Survey of Spectrum Sensing Algorithms for Cognitive Radio Applications” IEEE
Communications Surveys & Tutorials ,Vol.11, no. 1, First Quarter.
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WRAN Applications”.
21. J.Mitola III (2006), “Cognitive Radio Architecture” John Wiley & Sons, Ltd., New York. 22. Gaurav Bansal, Md. Jahangir Hossain, Praveen Kaligineedi, Hugues Mercier, Chris Nicola, Umesh Phuyal, Md.Mamunur Rashid, Kapila C.
Wavegedara, Ziaul Hasan, Majid Khabbazian, and Vijay K. Bhargava (2007), “Some Research Issues in Cognitive Radio Networks” IEEE.
23. Nicola Baldo and Michele Zorzi (2008), “Learning and Adaptation in Cognitive Radios using Neural Networks” IEEE CCNC proceedings.
24. Li Zhu, Huaibei Zhou (2008), “A New Architecture for Cognitive Radio Networks Platform” IEEE.
25. Shixian Wang, Lunguo Xie, Hengzhu Liu, Botao Zhang, and Heng Zhao (2010), “ACRA: An Autonomic and Expandable Architecture for Cognitive Radio Nodes” IEEE.
26. Irfan, Siddavatm (2011), “Mapping of Cognitive Radio as Intelligent Agent Architecture” IEEE.
27. Q.Mahmoud (2007), “Cognitive Networks : Towards Self –Aware Networks” New York : Wiley – Interscience,. 28. William Browne, Kazuhiko Kawamura, Jeffrey Krichmar, William Harwin, and Hiroaki Wagatsuma (2009) “Cognitive Robotics: New
Insights into Robot and Human Intelligence by Reverse Engineering Brain Functions” IEEE Robotics & Automation Magazine.
29. John-Thones Amenyo, “Engineering Computer Architectures for Cognitive Robotics - The CR/SARAMA Model” IEEE (ICCI'09). 30. Frederick Ackers and Darush Davani (2011), “Engineering a Cognitive Robotics Platform” Ninth International Conference on Software
Engineering Research, Management and Applications.
31. Catalin Buiu (2008),“Hybrid Educational Strategy for a Laboratory Course on Cognitive Robotics” IEEE Transactions on Education, vol. 51, no. 1.
32. Emil Vassev, Mike Hinchey (2012), “Knowledge Representation for Cognitive Robotic Systems” IEEE 15th International Symposium on
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Evolutionary Psychology, Artificial life, and Cognitive Robotics” Proc. 11th IEEE Int. Conf. on Cognitive Informatics & Cognitive
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49.
Authors: V. Pranava Jyothy, K. Padmavathi
Paper Title: Removal of High Density Salt and Pepper Noise in Videos through MDBUTMF
Abstrac: A modified decision based unsymmetrical trimmed median filter (MDBUTM) algorithm for the restoration
of gray scale, and color video’s that are highly corrupted by salt and pepper noise is proposed in this paper. In the
Transmission of Videos over channel, Video frames are corrupted by salt and pepper noise (Impulse Noise), due to
faulty communication systems. The objective of this paper is to implement a better filtering technique that makes the
noisy video frames to noise free video frames. The proposed algorithm replaces the noisy pixel by trimmed median
value when 0’s and 255’s are present in the selected window and when all the pixel values are 0’s and 255’s then the
noise pixel is replaced by mean value of all the elements present in the selected window. This proposed algorithm
shows better results than the Standard Median Filter (MF), Decision Based Algorithm (DBA), Modified Decision
Based Algorithm (MDBA), and Progressive Switched Median Filter (PSMF). The proposed algorithm is tested
against different gray scale and color video frames and it gives better Peak Signal-to-Noise Ratio (PSNR) and Image
Enhancement Factor (IEF).
Keywords: Median filter, salt and pepper noise, unsymmet--rical trimmed median filter.
229-234
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