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ISSN : 2319 - 6386ISSN : 2319 - 6386Website: www.ijisme.orgWebsite: www.ijisme.org
n E r e n g d o i n M e e rd i n n ga e c n e i c S e v i t a v o n n I f o I l n a t e n r r n u a o tJ o i l n a
Exploring Innovation
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Volume-4 Issue-10, April 2017Volume-4 Issue-10, April 2017
Published by: Blue Eyes Intelligence Engineering and Sciences Publication Pvt.
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
Advisory Chair
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
Technical Chair
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
Managing Chair
Mr. Jitendra Kumar Sen
International Journal of Innovative Science and Modern Engineering (IJISME)
Reviewer Chair
Dr. Ashu Gupta
Assoc. Professor, Department of Computer Applications, Apeejay Institute of Management Technical Campus, Jalandhar, Punjab,
India
Dr. T.Logeswari
Associate Professor, Department of MCA, Dr.N.G.P. – Kalapatti Road Coimbatore - 641048 India
Dr. Nurul Fadly Habidin
Department of Management, Faculty of Management and Economics, Universiti Pendidikan Sultan Idris, 35900 Tanjung Malim,
Perak
Dr. S.Manikandan
Department of ECE, Dean,VKS College of Engineering and Technology, Karur,Tamilnadu, India
Dr. S.Sasikumar
Department of ECE, Jayaram College of Engineering and Technology, India
Dr. Mojtaba Moradi
Assoc. Professor, Department of Statistics, Faculty of Mathematical Sciences, University of Guilan, Rasht, Iran
Dr. Neeraj Kumar
Assoc. Professor, Department of Applied Sciences & Humanities, IIMT Engineering.College, Meerut (U.P.), India
Dr. T.V.Suryanarayana
Assoc. Professor, Department of ECM, K L University, Green Fields,Vaddeswaram, Guntur District, A.P., India
Dr. Yaswanth Kumar Avulapati
Department of Computer Science, S.V.U.Collge of CM&CS, S.V.University, Tirupati, India
Dr. Yu Qi
Department of Computer Science, 30 Montgomery Street, Suite 1250, Jersey City, NJ, USA
Dr. N Dinesh Kumar
Professor, Department of Electronics & Instrumentation, VITS, Vignan Hills, Deshmukhi, Pochampalli Mdl,Nalogonda Dist, India
Dr. Deepshikha Bhargava
Assoc. Professor & Head, Department of Information Technology, Amity University, Jaipur (Rajasthan), India
Dr. Dinesh Sharma
Assoc. Professor, Department of ECE, DAVCET, Kanina (HR), India
Dr. Aginam, Chukwurah Henry
Department of Civil Engineering/Structural Engineering, Nnamdi Azikiwe University, Awka, Anambra, Nigeria
Dr. Messaouda AZZOUZI
Associate Professor, Department of Sciences and Technologies, Cite Porte Charef (02) Nr 14/798, Djelfa, Algeria
Dr. Remica Aggarwal
Assoc. Professor, Department of Management, BITS Pilani, Rajasthan, India
Dr. Dinesh Chandra Jain
Assoc. Professor, Department of Computer Science & Engineering,S.V.I.T.S – Indore (M.P.), India
Dr. Vu Truong Vu
Department of Civil Engineering, Ho Chi Minh City University of Transport, Faculty of Civil Engineering, No. 2, D3 Street, Ward 25,
Binh Thanh District, Ho Chi Minh City, Viet Nam
Dr. Muhammad Farhan
Department of Mathematical Models & Travel Demand Forecasting,Wasatch Front Regional Council North Jimmy Doolittle Road
Salt Lake City, Utah
Dr. S.Sumathi
Professor, Department of Electrical and Electronics Engineering,V.M.K.V. Engineering College, salem
Dr. G. Subramanya Nayak
Assoc. Professor, Department of Electronics & Communication Engineering, Manipal Institute of Technology, Manipal University,
Manipal Karnataka, India
Dr. R.Balamurugan
Professor, Department of Electrical and Electronics Engineering, KSR College of Technology,Tiruchengode Tamilnadu, India
Dr. Ganesh Kumar T
Department of Computer Science and Engineering, Research Scholar, Manonmaniam Sundaranar University,Tirunelveli, India
Dr. K.Siva Rama Krishna
Assoc. Professor, Department of Civil Engineering, Gitam University Visakhapatnam, India
Dr. P.Sanjeevikumar
Assoc. Professor, Department of Electrical Engineering, Bharathi Street, Jeevanandhapuram, Lawspet, Puducherry, India.
S.
No
Volume-4 Issue-10, April 2017, ISSN: 2319–6386 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd.
Page No.
1.
Authors: Purvi Kapoor, Manish K.R. Singh, Shashikant
Paper Title: A Review on Distributed Generation Definitions and DG Impacts on Distribution System
Abstract: Rapidly growing the power consumption and decrease in generating and transmission capacities have
set the trend towards the Distributed Generation (DG) sources. Still there is not a univer sal definition of DG.
This paper discusses the different definitions proposed in the literature. For DG system to become a major part of
the current power scenario it needs to be connected with the existing grid system. This integration will cause some
technical, operational and economic impacts on distribution systems. This paper also summarizes these different
impacts of DG on distribution system.
Keywords: Distributed Generation, Impacts of DG, Islanding, Economic Impacts of DG, Power Quality, Voltage
Regulation, Islanding, Dispatched Operation
References: 1. The US Department of Energy, Office of Distributed Energy Resources, online publications available at:
http://www.eere.energy.gov/der/, 2003.
2. Distributed Generation in Liberalised Electricity Markets. International Energy Agency, 2002. 3. T. Ackerman, G. Anderson, and L. Soder, “Distributed generation: a definition,” Electric Power System Research, vol. 57, pp. 195–204,
2001.
4. Gas Research Institute, Distributed Power Generation: A Strategy for a Competitive Energy Industry, Gas Research Institute, Chicago, USA 1998
5. D. Sharma, R. Bartels, Distributed electricity generation in competitive energy markets: a case study in Australia, in: The Energy Journal
Special issue: Distributed Resources: Toward a New Paradigm of the Electricity Business, The International Association for Energy Economics, Clevland, Ohio, USA, 1998, pp. 17–40
6. J. Cardell, R. Tabors, Operation and control in a competitive market: distributed generation in a restructured industry, in: The Energy Journal Special Issue: Distributed Resources: Toward a New Paradigm of the Electricity Business, The International Association for
Energy Economics, Clevland, Ohio, USA, 1998, pp. 111–135.
7. The Electric Power Research Institute, online publications available at: http://www.epri.com/, 2002. 8. B. M. Balmat and A. M. Dicaprio, “Electricity market regulations and their impact on distributed generation,” in Proc. Conf. on Electric
Utility Deregulation and Restructuring and Power Technologies (DRPT 2000), London, pp. 608–613.
9. “Impact of increasing contribution of dispersed generation on the power system,” CIGRE study Committee no 37, Final Report, Tech. Rep., 2003.
10. IEEE, Institute of Electrical and Electronics Engineers, http://www.ieee.org
11. International Energy Agency (IEA). Distributed Generation in Liberalized Electricity Markets. OECD/IEA, Paris, France, 2002. 12. American Gas Association, “What is Distributed Generation?” Full article at:
http://www.aga.org/Content/ContentGroups/Newsrom/Issue_Focus/Distributed_Generation.htm
13. California Energy Commission. “Distributed Energy Resources: Guide”. http://www.energy.ca.gov/distgen/index.html 14. Dondi P., Bayoumi, D., Haederli, C., Julian, D., Suter, M.,“ Network integration of distributed power generation” Journal of Power
Sources, pp. 1–9, 2002.
15. Chambers, A., “Distributed generation: a nontechnical guide.” Penn Well, Tulsa, OK, p. 283, 2001. 16. Pepermans, J. Driesen, D. Haeseldonckx, R. Belmans, W. D‟haeseleer, "Distributed generation: definition, benefits and issues", Energy
Policy Vol. 33, p.p. 787–798, 2005.
17. A.A. Bayod Rújula, J. Mur Amada, J.L. Bernal Agustín, J.M. Yusta Loyo, J.A, Domínguez Navarro1, “ Definitions for Distributed Generation: a review” ICREPQ-05, Zaragoza 16,17,18 of March, 2005
18. Distributed Generation: Understanding the Economics, Arthur D. Little, Inc. Full white paper at:
www.eren.doe.gov/distributedpower/pdfs/library/adlgecon.pdf 19. Gonzalez-Longatt, C. Fortoul, “Review of the Distributed Generation Concept: Attempt of Unification” paper no 275, ICREPQ'05
20. F. Ochoa, A. Padilha-Feltrin, and G. P. Harrison, “Evaluating distributed generation impacts with a multiobjective index,” IEEE Trans.
Power Delivery, vol. 21, no. 3, pp. 1452-1458, July 2006. 21. Gil and G. Joos, “Models for quantifying the economic benefits of distributed generation,” IEEE Trans. Power Systems, vol. 23, no. 2,
pp. 327-335, May 2008.
22. Philip P. Barker, R. W., “Determining the Impact of Distributed Generation on Power Systems: Part 1 - Radial Distribution Systems” from IEEE,12 IEEE, Feb 2011.
23. Yiming and, K.N. Miu, “Switch placement to improve system reliability for radial distribution systems with distributed generation,”
IEEE Trans.\ Power Systems, vol. 18, no. 4, pp. 1346-1352, Nov. 2003. 24. B. Delfino, “Modeling of the integration of distributed generation into the electrical system,” in Proc. IEEE Conf. Power Engineering
Society Summer Meeting, USA, 2002, pp. 170-175
25. Gaudenz Koeppel, “Distributed Generation: Literature Review and Outline of the Swiss Situation” eeh power system laboratory internal report 2003. 26. Pehnt, M., Schneider, L., “Embedding Micro Cogeneration in the Energy Supply System”, in Pehnt, M., Cames, M.,
Fischer, C., Praetorius, B., Shneider, L., Schumacher, K., Voss, J.P. Micro cogeneration towards decentralized energy systems, Berlin:
Springer, pp. 197-218, 2006. 26. Angel Fernández Sarabia, “Impact of distributed generation on distribution system” A Dissertation Submitted to the Department of
Energy and Technology, Faculty of Engineering, Science and Medicine, Aalborg University, June 2011
27. Jeremi Martin, “Distributed vs. centralized electricity generation: are we witnessing a change of paradigm?” May 2009
28. Khan, U. N. ,“Impact of Distributed Generation on Distributed Network”, Wroclav, University of Technology, Poland, 2008
29. IEEE Standards Association, “IEEE Standard for Interconnecting Distributed Resources With Electric Power Systems,” IEEE Std.
1547-2003 (Issued 2003, Reaffirmed 2008), doi:10.1109/ IEEESTD.2003.94285. 30. P. P. Barker and R. W. De Mello, “Determining the Impact of Distributed Generation on Power Systems,” presented at IEEE Power
Engineering Society Summer Meeting, Seattle, WA, July 16–20, 2000.
31. Subcontractor Report on DG Power Quality, Protection and Reliability Case Studies Report, NREL Colorado, 2003. Available electronically at http://www.osti.gov/bridge.
1-6
2.
Authors: Purwono Hendrad, Harry Budi Santoso, Zainal A Hasibuan
Paper Title: Use Clustering Data of Student High School for Placement in Personalization E-Learning on Higher
Education
Abstract: Personalize the e-learning begins after students interact with the system by utilizing the functions and 7-12
features to collect data and process it so that the resulting information from students who used to organize further
activities. In another study, the educational background of the student (and types of SMA) also affects the success
in education at the university. In this study developed a personalized e-learning design of the early, which is when
the new students will interact with the system. The system will be a kind of student placement test. The case
studies used subjects Program Building which is one of the core subjects in the study program Engineering
Informatics. As the methods used Knowledge Data Discovery (KDD) using background data combined with a high
school student math scores on the National Exam as an ingredient on the stage of Data Mining. This study will
measure the extent of the student's educational background above can be used as a system of placement of students
in personalized e-learning.
Keywords: high school background, data mining, placement, personalized e-learning.
References: 1. Yayah Karyanah, "Hubungan Asal Jurusan dengan Prestasi Belajar Mahasiswa Program Sstudi Ilmu Keperawatan Universitas Esa
Unggul," Forum Ilmiah, vol. 12, no. 2, pp. 156-163, May 2015. 2. C., Romero, C., & Ventura Marquez-Vera, "Predicting School Failure Using Data Mining," in Proceedings of the 4th international
conference on educational data mining, 2011, pp. 271– 275.
3. Swarnalatha P, D. Ganesh Gopal Ramanathan.L, "Mining Educational Data for Students' Placement Prediction using Sum of Difference Method," International Journal of Computer Applications, vol. 99, no. 18, pp. 36-39, August 2014.
4. Romero C. AND Ventura, "Educational Data mining: A Review of the State of the Art.," IEEE Transactions on Systems. Man, and
Cybernetics., vol. 40, no. 6, pp. 601-618, 2010. 5. Bertan Y. Badur Osman N. Darcan, "Student Profiling on Academic on Academic Performance Using Cluster Analysis," Journal of e-
Learning & Higher Education, vol. 2012, p. 8, 2012.
6. Narwati, "Pengelompokan Siswa Menggunakan Algoritma K-Means," Dinamika Informatika, pp. 12-16, 2010. 7. Zainal A. Hasibuan, Harry Budi Santoso Mira Suryani, "Personalisasi Konten Pembelajaran Berdasarkan Pendekatan Tipe Belajar Triple-
Factor Dalam Student Centered E-Learning Environment," in KNSI , Makasar, 2014.
8. Zainal A Hasibuan Sfenrianto, "Triple Characteristic Model (TCM) in E-Learning System," Proceedings of 4th International Conference on Computer Science and Information Technology. IEEE, Chengdu, 2011.
9. Zainal A Hasibuan, Heru Suhartanto Sfenrianto, "An Automatic Approach for Identifying Triple-Factor in e-Learning Process,"
International Journal of Computer Theory and Engineering, vol. 5, no. 2, pp. 371-376, April 2013. 10. Zainal. A. Hasibuan and H. B. Santoso., "The Use of E-Learning towards New Learning Paradigm: Case Study Student Centered E-
Learning Environment at Faculty of Computer Science - University of Indonesia," in Proc. IEEE International Conference on Advanced
Learning Technologies (ICALT 05), Kaohsiung, Taiwan, 2005, pp. 1026-1030. 11. Rajan Vohra Praveen Rani, "Generating Placement Intelligence in Higher Education Using Data Mining," (IJCSIT) International Journal
of Computer Science and Information Technologies, vol. Vol. 6, no. 3, pp. 2298-2302, May 2015.
12. Howard Hamilton. (2012, June) Howard J. Hamilton. [Online]. http://www2.cs.uregina.ca/~dbd/cs831/notes/kdd/1_kdd.html
13. Daniel T Larose, Data Mining Methods and Models. Hoboken, New Jersey: Jhon Wiley & Sons, Inc, 2006.
14. Daniel T Larose, Discovering Knowledge in Data: An Introduction to Data Mining: John Willey & Sons. Inc, 2005.
15. T. Kanungo and D. M. Mount, "An Efficient K-means Clustering Algorithm: Analysis and Implementation," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 24, no. 7, pp. 35-39, 2002.
3.
Authors: Jishnu M Thampan, Femitha Mohammed, Tijin M S, Pratibha S Prabhu, Rince K. M.
Paper Title: Eye Based Tracking and Control System
Abstract: An eye based tracking and control system is primarily used to track the human eye movements and in
turn control appliances as well as a replacement for mouse. Eye movements could be tracked by tracking the
position of the pupil. Real time video processing is carried out with the help of a camera which samples the images
constantly and a processor. The images taken by the camera are sent to a single board computer / PC where image
processing is done to identify the location of the pupil. The necessary calibration is then carried out by which
cursor tracking and appliance control could be made possible. For appliance control a separate unit is fed with the
control signals which select the appliance to be controlled. In order to achieve cursor, control the control signals
are fed to a computer and proper calibration would help to achieve the desired output results.
Keywords: proper calibration, computer / PC , image, possible,identify, tracking
References: 1. K.M.Lam, H.Yan,, “ Locating and extracting eye in human face images”, Pattern Recognition, 29, [5], 771-779, [1996].
2. K.-N. Kim and R. S. Ramakrishna, “Vision-based eye gaze tracking for human computer interface”, Proceedings of the IEEE International
Conference on Systems, Man, and Cybernetics, 2, 324-329, [1999]. 3. Shafi. M, Chung. P. W. H, “A Hybrid Method for Eyes Detection in Facial Images”, International Journal of Electrical, Computer, and
Systems Engineering, 231-236,[2009].
4. Ito, Nara, “Eye movement measurement by picture taking in and processing via a video capture card, an Institute of Electronics”, Information and Communication Engineers Technical Report, 102, 128, 31-36, [2002]
5. Bradski, G. and Kaehler, A. „‟Learning OpenCV’’. Cambridge, MA: O‟Reilly Media, Inc., 2008.
6. Principi E ; Dept. of Inf. Eng., Univ. Politec. delle Marche, Ancona, Italy, Colagiacom V. ; Squartini, S. ; Piazza, F.,” Low Power High Performance computing on the BeagleBoard Platfotm”, Education and Research Conference, 5° European DSP, 35 - 39 ,[2012]
7. Huang Ying, W. Z.and Xuyan, T. A real-time compensation strategy for non-contact gaze tracking under natural head movement. Chinese
Journal of Electroncis (July 2010). 8. Wilson, P. I., and Fernandez, J. Facial feature detection using haar classifiers. J. Comput. Sci. Coll. 21, 4 (Apr. 2006), 127-133.
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4.
Authors: Aashish Jaiswal, Garima Sikka
Paper Title: Future Scope and Potential of Solar Energy in India An Overview
Abstract: After the oil crisis in 1973, the world has to think about the alternative resource of energy apart from
conventional energy resources (coal, gas and petroleum etc.). Solar energy is the most important alternative
resource of the world and has a large potential of green energy. India has a huge potential for generating green
electricity from the renewable energy sources. To promote the green energy, government of India launching many
18-23
schemes for the renewable energy resources. The Jawaharlal Nehru National Solar Mission was launched on the
11th January, 2010 by the Prime Minister. The Mission has set the ambitious target of deploying 20,000 MW of
grid connected solar power by 2022 is aimed at reducing the cost of solar power generation in the country through
(i) long term policy; (ii) large scale deployment goals; (iii) aggressive R&D; and (iv) domestic production of
critical raw materials, components and products, as a result to achieve grid tariff parity by 2022. Mission will
create an enabling policy background to achieve this objective and make India a global leader in solar energy. This
paper provides an overview on solar energy in India. It reviews the current status of solar energy in terms of
existing capacity, along with historical trends of solar energy and future potential of different form of solar energy
in India.
Keywords: Solar Energy, Solar policy and Renewable policy in India, policy; management.
References: 1. Kapoor K, Pandey KK, Jain AK and Nandan A, “Evolution of solar energy in India: A review” Renewable and Sustainable Energy
Reviews, 40(2014)475–487.
2. Veeraboina P and Ratnam GY, “Analysis of the opportunities and challenges of solar water heating system (SWHS) in India: Estimates from the energy audit surveys & review” Renewable and Sustainable Energy Reviews, 16 (2012) 668– 676.
3. Load Generation and Balance Report, Central Electricity Authority, Ministry of Power, Government of India, 2015–16.
4. Renewable Energy in India: Growth and Targets, Ministry of New and Renewable Energy (MNRE), Government of India, May 2015.
5. Power Sector at a Glance all India, Ministry of Power, Government of India, on 8 Oct. 2015 [Online]. Available
http://powermin.nic.in/power-sector-glance-all-india
6. Savita Lolla and Somnath Baidya Roy, “Wind and Solar Resources in India”, Energy Procedia, vol. 70, pp 187-192, 2015. 7. Ashok Upadhyay and Arnab Chowdhury, “Solar Energy Fundamentals and Challenges in Indian restructured power sector”, International
Journal of Scientific and Research Publications, vol. 4, issue 10, pp 1-13, Oct. 2014.
8. Pandey S, Singh VS, Gnagwar NP and Vijayvergia MM,“Determinants of success for promoting solar energy in Rajasthan, India” Renewable and Sustainable Energy Reviews 16 (2012) 3593– 3598.
9. Sharma NK, Tiwari PK and Sood YR, “Solar energy in India: Strategies, policies, perspectives and future potential” Renewable and
Sustainable Energy Reviews 16 (2012) 933–941. 10. Ministry of New and Renewable Energy source(MNRE),http://www.mnre.gov.in/achievements.htm; 2015.
11. http://www.solarindiaonline.com/solar-india.html#present.
12. Akshay Urja. Newsletter of the Ministry of New and Renewable Energy, Government of India 2010;4(November–December (2–3)). 13. Jawaharlal Nehru National Solar Mission (MNRE) Website of Ministry of New & Renewable Energy, Government of India,
http://mnre.gov.in/; 2015.
14. http://www.eai.in/ref/ae/sol/sol.html 15. http://en.wikipedia.org/wiki/Solar_power_India.
5.
Authors: Ankita Singh, Nar Singh
Paper Title: Analysis of Wireless Mac 802.11 and 802.11Ext in NS-2
Abstract: The major issues with increasing of wireless networks are throughput, packet delivery ratio, average
delay and MAC specifications. IEEE 802.11 standard is a set of media access control (MAC) and physical layer
(PHY) for implementing wireless MAC. New modeling of IEEE 802.11 have been developed in NS-2, which
introduces two new modules: Mac802_11Ext and Wireles Phy Ext for aiming at a significantly higher level of
simulation accuracy. In this paper, we analysis the throughput, packet delivery ratio and average delay for
Mac802_11 and 802_11Ext. Simulation results are evaluated by NS-2 using different no. of nodes for both Mac
802_11 and 802_11Ext based networks. After analysis of results from NS-2 the Mac 802_11Ext is better perform
to compare Mac802_11 of IEEE 802.11in wireless network.
Keywords: IEEE802.11, Mac802_11, Mac802_11Ext, NS2.
References: 1. Manjusha Methew, Mary John, “Performance Analysis of IEEE 802.11 Modified Distributed Coordination Function for Wireless LANs
based on data rate”, IOSR Journal of Computer Engineering (IOSR-JCE), Vol 16, Issue 6 (Nov-Dec 2014). PP: 08-13, e-ISSN: 2278-
0661, p-ISSN: 2278-8727. 2. Jin-Uk Jung, Kyo-Hong Jin, “Modification of Extended Version of IEEE 802.11 in ns-2 and Performance Analysis with Error Rate Using
Computer Simulation”, Changwon National University Electronics, 2009.
3. IEEE Std. 802.11TM-2012 IEEE Standard for Information Technology—Telecommunications and Information Exchange Between Systems—Local and Metropolitan Area Networks— Specific Requirements. Part 11: WirelessLAN Medium Access Control (MAC) and
Physical Layer (PHY) Specifications, IEEE, New York, 2012.
4. Qi Chen, Felix Schmidt-Eisenlohr, Daniel Jiang, “Overhaul of IEEE 802.11 Modeling and Simulation in NS-2 (802.11Ext)”, University of Karlsruhe (TH), 2008.
5. UC Berkeley, LBL, USC/ISI, and Xerox PARC, “The ns Manual (formerly ns Notes and Documentation)1”,
www.isi.edu/nsnam/ns/doc/ns_doc.pdf . 6. Tritva Jyothi K P and Kavitha Athota, “Performance Analysis of IEEE 802..11e over WMNs”, 2012 World Congress on Information and
Communication Technologies, IEEE 2012.
7. http://www.isi.edu/nsnam/ns/index.html 8. “ns-allinone-2.34.tar.gz-OSDN”, en.osdn.jp/projects/.../allinone/ns-allinone-2.34/ns-allinone-2.34.tar.gz/
9. Heidemann, Tom Handerson, “nsnam”, http://sourceforge.net/project/showfiles.php?group id=149743&package id=169689&release
id=588643 10. Cali F, Conti M, Gregori E, “IEEE 802.11 protocol: design and performance evaluation of an adaptive backoff mechanism”, IEEE Journal
on Selected Areas in Communications, 1774-1786, 2000.
11. Cali F, Conti M, Gregori E, “IEEE 802.11 wireless LAN: capacity analysis and protocol enhancement”, In Proceedings of IEEE INFOCOM’ 1998, March 1998.
12. Hongqiang Zhai, Younggoo Kwon, Yuguang Fang, “ Performance analysis of IEEE 802.11 MAC protocols in wireless LANs”, wireless
communications and mobile computing, PP: 917-931, 2004.
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6. Authors: M. Vidhya, G. Zayaraz
Paper Title: Object Oriented Design Refactoring for Enhancing the Technical Debt
Abstract: Code Refactoring is a process of changing the internal behavior without changing its external
behavior or functionality. Manual refactoring is hard to modify changes, if we automate refactoring there are much
more benefits possible. Software refactoring is a valuable process in software development and is often aimed at
repaying technical debt. The automated refactoring techniques, software metrics and Metaheuristic Search and
automated refactoring tool are combined to improve the quality of software without affecting its functionality. The
four different refactoring approaches are compared using automated refactoring tool. The more number of metrics
are added to improve the quality and reduce the complexity. Metrics are combined to measure Abstraction,
coupling, inheritance and technical debt. This will improve the quality of software and also reduces technical debt
by maintenance cost and time.
Keywords: Search based techniques; refactoring; Software metrics; software quality; design level metric;
Technical debt.
References: 1. Mel Ó Cinnéide, Laurence Tratt , Mark Harman, Steve Counsell , Iman Hemati Moghadam. Experimental Assessment of Software
Metrics Using Automated Refactoring. ESEM’12, September 19–20, 2012, Lund, Sweden Copyright 2012 ACM 978-1-4503-1056-
7/12/09.
2. Michael Mohan , Des Greer , Paul McMullan. Technical debt reduction using a search based automated refactoring, The Journal of Systems and Software 0 0 0 (2016) 1–12.
3. Gomathi. S and Edith Linda. P. An overview of Object Oriented Metrics A complete Survey. International Journal of Computer Science
& Engineering Technology (IJCSET). Vol. 4 No. 09 Sep 2013. ISSN : 2229-3345. 4. Muktamyee Sarker. An overview of Object Oriented Design Metrics. Master Thesis Department of Computer Science, Umeå University,
Sweden June 23, 2005. 5. Sonia Chawla. Review of MOOD and QMOOD metric sets. International Journal of Advanced Research in Computer Science and
Software Engineering. Volume 3, Issue 3, March 2013 ISSN: 2277 128X .
6. Safwat M. Ibrahim, Sameh A. Salem, Manal A. Ismail, and Mohamed Eladawy. Identification of Nominated Classes for Software Refactoring Using Object-Oriented Cohesion Metrics. IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 2, No 2,
March 2012. ISSN (Online): 1694-0814. www.IJCSI.org
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