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S. No
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Volume-1 Issue-6, January 2012, ISSN: 2231-2307 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd.
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Page No.
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1.
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Authors:
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C.K.Sarumathy, J.Gokulraj, P.Selvaperumal
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Paper Title:
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Integration of Online Ontologies Using Combined Ranking Algorithm
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Abstract: In the Semantic Web, knowledge representation is largely based on ontologies. Ontology should be constructed in a way such that it should meet the requirements of the users. The main difficulty involved in the construction of ontologies is the high cost incurred in building them. Gathering complete knowledge about a specific domain requires more time and it doesn’t guarantee that the resulting ontology will be better than the existing ontologies. Hence, an approach for reusing the existing ontologies to build new ontologies has been proposed. This process makes use of the following steps: identification of existing ontologies, use of combined ranking algorithm (OntoRank+AKTive), segmentation and integration. As a result, best quality ontology can be obtained.
Keywords: AKTive Rank, Extraction, Fragmentation, Onto Rank, Reusability.
References:
1. An Ontology Approach to creating a New Recipe by Reusing Parts of the Existing Recipe,IEEE,2009,Rie Makino, Ichiro Kobayashi, Noriaki Izumi and Koiti Hasida.
2. Harith Alani. Position Paper: Ontology construction from online ontologies. In Proc. 5th International World Wide Web Conference, Edinburg, 2006
3. Content-based Ontology Ranking, Matthew Jones, Harith Alani
4. Ranking ontologies with AKTive Rank, Harith Alani, Christopher Brewster and Nigel Shadbolt.
5. http://swoogle.umbc.edu
6. http://wordnet.priceton.edu
7. J. Seidenberg and A. Rector. Techniques for segmenting large description logic ontologies. In Workshop on Ontology Management: Searching, Selection, Ranking, and Segmentation. 3rd Int. Conf. Knowledge Capture (K-Cap), pages 49–56, Banff, Canada, 2005.
8. N. F. Noy and M. A. Musen. Specifying ontology views by traversal. In 3rd Int. Semantic Web Conf. (ISWC’04), Hiroshima, Japan, 2004. [9] M. Bhatt, C. Wouters, A. Flahive, W. Rahayu, and D. Taniar. Semantic completeness in sub-ontology extraction using distributed methods. In Proc. Int. Conf. on Computational Science and its Applications (ICCSA), pages 508–517, Perugia, Italy, 2004. LNCS, Springer Verlag.
9. H. Alani, S. Harris, and B. O’Neil. Ontology winnowing: A case study on the akt reference ontology. In Proc. Int.Conf. on Intelligent Agents, Web Technology and Internet Commerce
10. M. A. Musen, R. W. Fergerson, W. E. Grosso, N. F. Noy, M. Y. Grubezy, and J. H. Gennari. Component-based support for building knowledge-acquisition systems. In Proc. Intelligent Information Processing (IIP 2000) Conference of the International Federation for Processing (IFIP), World Computer Congress (WCC’2000), pages 18–
22, Beijing, China, 2000.
11. N. F. Noy and M. A. Musen. The prompt suite: Interactive tools for ontology merging and mapping. International Journal of Human-Computer Studies, 59(6): 983–1024, 2003.
12. N.Guarino & C.Welty. Evaluating ontological decisions with Ontoclean. Communications of the ACM, 45(2):61–65, 2002.
13. J. Volker, D. Vrandecic, and Y. Sure. Automatic evaluation of ontologies (aeon). In Proc. 4th Int. Semantic Web Conf. (ISWC), Galway, Ireland, 2005.
14. Ding L, et al Finding and Ranking Knowledge on the Semantic Web. In the Proceedings of the 4th International Semantic Web Conference.
15. Ding L, et al. Swoogle: a search and metadata engine for the semantic web. In : Proceedings of the Thirteenth ACM Conference on Information and Knowledge Management, 2004, 652-659.
16. Alani H, Brewster C. Ontology ranking based on the analysis of concept structures. Proceedings of the 3rd International Conference on Knowledge Capture, 2005,51-58.
17. OWL Web ontology Language Overview. http://www.w3.org/TR/owl-features/
18. P.C.Weinstein and W.P.Birmingham. Comparing concepts in differentiated ontologies. In Proceedings of 12th Workshop on Knowledge Acquisition.
19. A.Maedche and S.Staab. Measuring similarity between ontologies. In Proc. European Conf. On Knowledge Acquisition and Management (EKAW), pages 251-263 , Madrid, 2002.
20. A Language and Algorithm for Automatic merging of ontologies, Alma Delia Cuevas Rasgado and Adolfo Guzman Arenas, In Proceedings of the 15th International Conference on Computing (CIC'06) , 2006. Modeling and Management (KAW’ 99), Banff, Alberta, Canada, 1999.
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1-4
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2.
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Authors:
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Anilkumar T, M.V.Vijayasaradhi
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Paper Title:
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Mpt Technique In Unifacial And Bi Directional Peer To Peer Wlan For Efficient Downlink Performance
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Abstract: This paper proposes Multiple Packet Transmission (MPT) to multiple nodes in unidirectional and bi directional peer to peer wireless LAN for efficient downlink performance. This gives users the mobility to move around within a local coverage area and still be connected to the network. In this paper, we study a novel Multiple-Input, Multiple-Output (MIMO) technique called Multiple Packet Transmission (MPT) in unidirectional peer to peer WLAN, with which the sender can send more than one packet to distinct users simultaneously. The existing system was based on the sequence packet transmission method but this will not reduce the downloading time. It depends upon the client-server architecture that network cannot be expanded. The access point can send two packets to two users simultaneously. It depends upon the system hardware requirements. Paper proposes MPT- that is multiple transmission packets. This suggests sending packets to multiple systems simultaneously. In Bi directional P2P WLAN networks are typically used for connecting nodes, largely ad hoc connections. Data, including digital formats such as audio files, and real time data such as telephony traffic, is passed using P2P technology. The security issues in P2P network can be overcome with help of firewalls and TCP ports.
Keywords: Unifacial, MI MO, MPT, MAC, Switching, Collide, Encompassing, Napster.
References:
1. Zhenghao Zhang, Yuanyuan Yang, Miao Zhao,”Enhancing Downlink Performance in Wireless Networks by Simultaneous Multiple Packet Transmission”, IEEE transactions on computers, vol. 58, no. 5, may 2009.
2. S. Fluhrer, I. Martin, and A. Shamir, "Weaknesses in the Key Scheduling Algorithm of RC4", in Proceedings of the 8th Annual Workshop on Selected Areas in Cryptography, 2001.
3. D. Tse and P. Viswanath, “Fundamentals of Wireless Communication”, Cambridge Univ. Press, May 2005.
4. Allen Ka Lun Miu, “Improving Packet Delivery Efficiency Using Multi-Radio Diversity in Wireless LANs”, Massachusetts Institute of Technology,June 2006.
5. H.N. Gabow, “An Efficient Implementation of Edmonds’ Algorithm for Maximum Matching on Graphs,” J. ACM.
6. S. Saroiu, P.K. Gummadi, and S.D. Gribble, "A Measurement Study of P2P File Sharing Systems", in Proceedings of Multimedia Conferencing and Networking, San Jose, 2002.
7. IEEE Std 802.11, "Wireless LAN Medium Access Control (MAC) and Physical Layer Specifications", ISO/IEC 8802-11:1999(E).
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5-9
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3.
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Authors:
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K.Gupta, P.C. Jana, A.K.Meikap
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Paper Title:
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High Magnetoresistance of the Composite of Polyaniline Nanotubes with La0.67Sr0.33MnO3. Determination of Stiffness Constant and Range Of Interaction of this composite
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Abstract: We have synthesized composite of polyaniline nanotubes with Lanthanum strontium manganite (La0.67Sr0.33MnO3, LSMO) nanoparticles. A huge increase in magnetoresistance (~73%) is obtained in the nanocomposite containing highest amount of LSMO. This increase in magnetoresistance may be explained by evaluating stiffness constant and average range of interaction of the nanocomposite. Average range of interaction among magnetic ions increases from 5 to 7.736 and value of stiffness constant decreases from 2.75 x 10-5 to 0.74 x 10-5 eV(A0 )2 with increase in LSMO content in the nanocomposites. Increase in average range of interaction and decrease in stiffness constant may be the cause of observed increase in magnetoresistance.
Keywords: LSMO, Magnetoresistance, Polyaniline, Range of interaction, Stiffness constant
References:
1. J.S. Zhou, J.B. Goodenough, A. Asamitsu, Y. Tokura Phys. Rev. Lett. 79 (1997) 3234
2. R. A. Rao, D. Lavric, T. K. Nath, C.B. Eom, L.Wu, F. Tsui Appl. Phys. Lett.73 (1998) 3294.
3. Y. Tokura, Colossal Magnetoresistive Oxides, Gordon and Breach, New York, (2000)
4. P. Raychaudhuri, K. Sheshadri, P. Taneja, S. Bandyopadhyay, P. Ayyub, A.K.Nigam, R. Pinto, Phys. Rev. B 59(1999)13919.
5. P. Raychaudhuri, T.K. Nath, A.K. Nigam, R. Pinto, J. Appl. Phys. 84 (1998) 2048
6. P. Dey, T.K. Nath, U. Kumar, P.K. Mukhopadhyay, J. Appl. Phys. 98 (2005) 014306.
7. J. H. Kim, F. F. Fang, H. J. Choi, Y. Seo, Mat. Lett. 62 (2008) 2897.
8. T. A. Skotheim, R. L. Elsenbaumer, J. R. Reynolds (Eds.), Hand Book of Conducting Polymers, Marcel Dekker Inc.,New York (1998, p.945).
9. H. S. Nalwa, Handbook of organic Conductive Molecules and polymers, Wiley, (1997, Vol-2, Chapter 12)
10. L. Xia, Y. Gao, X. Zhang, J. Gong, Y. Sun, X. Zheng, L. Qu, Mater. Lett. 62 (2008) 2237.
11. F. Huang, C.W.Lin, Polymer 50 (2009) 775
12. J. Stejskal, M. Trchova, N. V. Blinova, E. N. Konyushenko, S. Reynaud, J. Prokes, Polymer 49(2008) 180
13. J. Bhadra, D. Sarkar, Mater. Lett. 63 (2009) 69.
14. J. Stejskal, I. Sapurina, M. Trchova , E. N. Konyushenko, P. Holler, Polymer 47(2006)8253
15. S. Ding, H. Mao, W. Zhang, J. App. Polym. Sci. 109 (2008) 2842
16. K. Gupta, P. C. Jana, A. K. Meikap, T. K. Nath, J. Appl. Phys. 107(2010) 073704
17. K. Gupta, G. Chakraborty, S. Ghatak, P. C. Jana, A. K. Meikap, R Babu, J. Applied Physics 108 (2010) 073701
18. K. Gupta, P. C. Jana, A. K. Meikap, Synth. Met. 160 (2010)1566
19. P. Dey, T. K. Nath, Appl. Phys. Lett. 87 (2005)162501
20. K. R. Reddy, K. P. Lee, A. I Gopalan, Coll. and Surf. A Physico. Eng. Aspets. 320 (2008) 49.
21. C.W.Chen, Magnetism and metallurgy of soft magnetic material, North Holland, Amsterdam, (1977)
22. W. F. Brown, Phys. Rev. 60(1941)139.
23. L. Neel, J. Phys. Radium 9(1941)184.
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10-14
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4.
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Authors:
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J.Emmanual Robin, G.Prabu
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Paper Title:
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Comparative analysis of TOFEL IBT result rate among students using K-Means Clustering
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Abstract: Data mining technology that blends traditional data analysis methods with sophisticated algorithms for processing large volumes of data. This paper reveals the comparative analysis of the students with UG, PG, Other Students community. Before getting into the picture we have to know the basic concept of clustering technique. What is clustering analysis? Clustering analysis divides data into the groups (clusters) that are meaningful or useful or both. If meaningful groups are the goal, then the clusters should capture natural structure of data. This paper focuses to discover the comparative analysis of reading, writing, speaking, listening skills over the student’s dataset such as (a) PercentileMarkUG (b) PercentileMarkPG (c) PercentileMarkOther
Keywords: K-Means Clustering, IBT(Internet Based Test),TOEFL(Test of English as a Foreign Language)
References:
1. Berry, Michael J. A. and Gordon Linoff, (1997), Data Mining Techniques, New York: John Wiley & Sons, Inc. .
2. Mendenhall, William and Richard L. Schaeffer, (1973), Mathematical Statistics with Applications. North Scituate, Massachusetts.
3. Introduction to Data Mining, Vipin Kumar,Ping-Pang,Michael Stein bench
4. www.ets.org
5. K. Pakhira, Malay, “A Modified k-means Algorithm to Avoid Empty Clusters,” International Journal of Recent Trends in Engineering, Vol 1,No. 1, May 2009.
6. R. Salman, V. Kecman, Q. Li, R. Strack and E. Test, “Two-Stage Clustering with k-means Algorithm,” WIMO 2011 Conference, Ankara,Turky, June 2011 (in press).
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15-19
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5.
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Authors:
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Geeta Nagpal, Moin Uddin, Arvinder Kaur
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Paper Title:
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A Hybrid Technique using Grey Relational Analysis and Regression for Software Effort Estimation using Feature Selection
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Abstract: Software Estimation Techniques present an inclusive set of directives for software project developers, project managers and the management in order to produce more accurate estimates or predictions for future developments. The estimates also facilitate allocation of resources’ for Software development. Estimations also smooth the process of re-planning, prioritizing, classification and reuse of the projects. Various estimation models are widely being used in the Industry as well for research purposes. Several comparative studies have been executed on them, but choosing the best technique is quite intricate. Estimation by Analogy (EbA) is the method of making estimations based on the outcome from k most analogous projects. The projects close in distance are potentially similar to the reference project from the repository of projects. This method has widely been accepted and is quite popular as it impersonates human beings inherent judgment skill by estimating with analogous projects. In this paper, Grey Relational Analysis (GRA) is used as the method for feature selection and also for locating the closest analogous projects to the reference project from the set of projects. The closest k projects are then used to build regression models. Regression techniques like Multiple Linear Regression, Stepwise Regression and Robust regression techniques are used to find the effort from the closest projects.
Keywords: Estimation by Analogy, Feature Selection, Grey relational Analysis, Regression.
References:
1. B.W. Boehm and R.Valerdi. "Achievements and Challenges in Software Resources Estimation", CSSE Tech Report,2005
2. J L Deng “Control problems of grey system”. System and Control Letters, 1:288–94,1982
3. J Deng “Introduction to grey system theory”. Journal of Grey System 1:1–24,1989
4. J Deng “Grey information space”. Journal of Grey System 1:103–117,1989
5. C J Hsu, C Y Huang “Improving Effort Estimation Accuracy by Weighted Grey relational Analysis During Software development”. 14th Asia-Pacific Software Engineering Conference,534-541,2007
6. S J Huang , N H Chiu , L W Chen “Integration of the grey relational analysis with genetic algorithm for software effort estimation”. European Journal of operational and research 188:898-909,2007
7. M. Shepperd, C. Schofield,B. Kitchenham. “Effort Estimation using Analogy”. In Proceedings of the 18th International Conference on Software Engineering,170-178,1996
8. M. Shepperd,C. Schofield.“Estimating Software Project Effort Using Analogies”. IEEE Transactions on Software Engineering,23(12):736-743,1997
9. L. Angelis,I. Stamelos.“A simulation tool for efficient analogy based cost estimation”. Empirical Software Engineering, 5 :35–68,2000
10. Q. Song, M. Shepperd, C. Mair,“Using Grey Relational Analysis to Predict Software Effort with Small Data Sets”. Proceedings of the 11th International Symposium on Software Metrics (METRICS’05), 35-45,2005
11. J. Li, G. Ruhe, A. Al-Emran, M. M. Richter. “A flexible method for software effort estimation by analogy”, Empirical Software Engineering,12:65–106,2007
12. N.Mittas, M.Athanasiades, Angelis. “Improving analogy-based software cost estimation by a re sampling Method”. Journal of Information & software technology,50,2008
13. J. Jorgenson , Shepperd. “A Systematic Review of Software Development Cost Estimation Studies”. IEEE Transactions on Software Engineering,33(1),2007
14. C. J. Hsu and C. Y. Huang, “Improving Effort Estimation Accuracy by Weighted Grey relational Analysis During Software development”. 14th Asia-Pacific Software Engineering Conference,534-541,2007
15. N.Mittas, L.Angelis,“LSEbA: least squares regression and estimation by analogy in a semi-parametric model for software cost estimation”. Empirical Software Engineering,15(5):523-555,2010
16. M. Azzeh, et al., “Analogy-based software effort estimation using Fuzzy numbers”. Journal of Systems and Software,84:270-284,2011
17. J.S.Pahariya, V. Ravi, M. Carr, M.Vasu, “Computational Intelligence Hybrids Applied to Software Cost Estimation”. International Journal of Computer Information Systems and Industrial Management Applications, 2:104-112,2010
18. N.Mittas, L.Angelis.“Comparing cost prediction models by resampling techniques”, Journal of Systems and Software, 81:616–632,2008
19. J. H. Wu, C. B. Chen. “An alternative form for Grey Relational Grade”. Journal of Grey System,11(1):7–11,1999
20. K.H.Hsia, J.H.Wu. “A study on the data preprocessing in Grey Relation Analysis”. Journal of Chinese Grey System,1:47-53,1998
21. J.H.Wu, M.L.You and K.L.Wen. “A Modified Grey Relational Analysis”,The Journal of Grey System,11(3):287-292,1999
22. P.J. Huber, Robust regression: Asymptotics, conjectures and Monte Carlo, The Annals of Statistics, 1, 799–821, 1981.
23. P.J. Huber, “Robust Estimation of a Location Parameter”. Annals of Mathematical Statistics, 35:73–101, 1964
24. MATLAB®Documentation, http://www.mathworks.com/help/techdoc/
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20-27
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6.
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Authors:
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Hamdy A. Morsy, Zaki B. Nossair, Alaa M. Hamdy, Fathy Z. Amer
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Paper Title:
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JPEG Steganography System with Minimal Changes to the Quantized DCT Coefficients
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Abstract: Steganography is the science of invisible communications over an innocuous cover medium. Most steganographic systems defeat both visual and first order statistical attacks however they offer only low capacity embedding. In this paper, a new steganographic system is introduced for message embedding by inverting the LSB of DCT coefficients of JPEG image. This algorithm offers high capacity compared to existing steganographic system.
Keywords: JPEG hiding, steganography, steganalysis, information hiding.
References:
1. Hamdy A. Morsy, Zaki B. Nossair, Alaa M. Hamdy, and Fathy Z. Amer, "Utilizing Image Block Properties to Embed Data in the DCT Coefficients with Minimum MSE," International Journal of soft computing and Engineering vol. 1, no. 4, pp. 449-453 , 2011.
2. Hamdy A. Morsy, Zaki B. Nossair, Alaa M. Hamdy, and Fathy Z. Amer, " Optimum segment length for embedding in the LSB of JPEG images with Minimum MSE," International Journal of Computer and Electrical Engineering vol. 3, no. 3, pp. 72-77 , 2011.
3. A. Kerckhoffs, “La Cryptographie Militaire”, Journal des Sciences Militaires, 9th series, IX pp 5–38; Feb. pp 161–191, Jan. 1883.
4. R. J. Anderson, and F.A. Petitcolas, “ On the limits of Steganography,” J. Selected Areas in Comm., vol.16, no. 4, pp. 474–481, 1998.
5. Mehdi Kharrazi, Husrev T. Sencar, and Nasir Memon " Image Steganography: Concepts and Practice," WSPC/Lecture Notes Seriesm, April 22, 2004.
6. A. Westfeld, “F5—A Steganographic Algorithm High Capacity Despite Better Steganalysis,” Springer-Verlag Berlin Heidelberg, 2001.
7. N. Provos, and P. Honeyman, “Detecting Steganographic Content on the Internet,” CITI Technical Report 01-11, 2001.
8. N. Provos, and P. Honeyman, “Hide and Seek: An introduction to steganography,” IEEE Computer security 15407993/03, 2003
9. A. Westfeld, “Detecting Low Embedding Rates, “, 5th Information Hiding Workshop. Nooerdwijkerhout, Netherlands, Oct. 7−9, 2002
10. A. Westfeld, and A. Pfitzmann, “Attacks on Steganographic Systems,” in Andreas Pfitzmann (ed) Information Hiding. Third International Workshop, LNCS 1768, Springer- Verlag Berlin Heidelberg. pp. 61–76. 289, 291, 293, 299, 2000.
11. C. Hung, “PVRG-JPEG Codec, 1.1,” Stanford niversity, 1993. http://archiv.leo.org/pub/comp/os/unix/graphics/jpeg/PVRG 291.
12. Manoj Kumar Meena, Shiv Kumar, Neetesh Gupta “ Image Steganography tool using Adaptive Encoding Approach to maximize Image hiding capacity” IJSCE Volume-1, Issue-2, May 2011
13. C. Cachin,” An Information-Theoretic Model for Steganography,” Cryptology ePrint Archive, 2002.
14. N. Memon, and M. Kharrazi, “Performance study of common image steganography,” Journal of Electronic Imaging 15(4), 041104 (Oct-Dec), 2006.
15. G. Cancelli, and M. Barni, “New techniques for steganography and steganalysis in the pixel domain, “, Ph.D. dissertation - Ciclo XXI. Report 2000 /028, 2009. www.zurich.ibm.com/˜cca/papers/stego.pdf.
16. T. Pevn'y, J. and Fridrich, “Benchmarking for Steganography,” Information Hiding.10th International. Workshop, Santa Barbara, CA, LNCS vol. 5284, 2008.
17. D. Upham, “Steganography software for Windows,” 1997, http: //members.tripod.com/steganography/stego/ software.html
18. J. Fridrich, M. Goljan, and D. Hogea, “new methodology for breaking steganographic techniques for JPEGs,” in Proc. of SPIE: Security and Watermarking of Multimedia Contents, vol. 5020, pp 143–155, 2003.
19. Jan Kodovský, Jessica Fridrich ”Quantitative Steganalysis of LSB Embeddingin JPEG Domain” MM&Sec’10, September 9–10, 2010, Roma, Italy.2010 ACM 978-1-4503-0286-9/10/09
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28-33
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7.
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Authors:
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GauravChheda, NiketGajra, ManalChhaya, JiteshDeshpande, SayleeGharge
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Paper Title:
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Real Time Bus Monitoring and Passenger Information System
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Abstract: The Real Time Bus Monitoring and Passenger Information bus tracking device is a standalone system designed to display the real-time location(s) of the buses in Mumbai city. This system will enable the tracking device to obtain GPS data of the bus locations, which it will then transfer it to centralized control unit and depict it by activating LEDs in the approximate geographic positions of the buses on the route map. Specific softwares will be used to interface the data received to the map.
Keywords: GPS, LEDs
References:
1. (16/10/11) http://www.nextbus.com/corporate
2. (18/10/11)http://www.sparkfun.com/datasheets/Components/LM7805.pdf
3. (17/10/11)http://en.wikipedia.org/wiki/Serial_Peripheral_Interface_Bus
4. (20/10/11)http://en.wikipedia.org/wiki/Global_Positioning System
5. (20/10/11)http://www.microchip.com/wwwproducts/Devices.aspx?dDocName=en010297
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34-38
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8.
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Authors:
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Monika Arora, Uma Kanjilal, Dinesh Varshney
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Paper Title:
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Efficient and Intelligent Information Retrieval using Support Vector machine (SVM)
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Abstract: The information access is the rich data available for information retrieval, evolved to provide principal approaches or strategies for searching and browsing. The search has become the leading paradigm to find the information on World Wide Web. For building the successful information retrieval, there are a number of prospects that arise at the different levels where techniques can be considered. The present investigations explore the Support vector machine identified its level and classifies the documents on web. This paper attempts to develop a model for the efficient and intelligent retrieval. This paper attempts to propose the implement model for efficient and intelligent retrieval. In model it attempted to figure out the important factors for the successful efficient and intelligent retrieval. The proposed model is designed to collate all the differing views on information retrieval so as to construct a holistic theoretical which is considered to be the source of a system. This paper considers the application of Support Vector Machine for designing the model for efficient and intelligent retrieval. This will also consider a proposed model for developing successful retrieval.
Keywords: Information Retrieval, Web Information Retrieval, Support vector machine.
References:
1. Quek C. Y. Classification of World Wide Web Documents.” 1997. Senior Honors Thesis, Carnegie Mellon University 1997.
2. Boser B. E., Guyon I., and Vapnik V. A training algorithm for optimal margin classifiers. In Proceedings of the Fifth Annual Workshop on Computational Learning Theory, pages 144-152. ACM Press, 1992.
3. Cortes C. and Vapnik V. Support-vector network. Machine Learning, vol 20 pp 273-297,1995.
4. Lin H.-T. and Lin C.-J., “A study on sigmoid kernels for SVM and the training of non-PSD Kernels by SMO-type methods”, March 2003.
5. Chen S., Cowan C. F. N., and Grant P. M., "Orthogonal Least Squares Learning Algorithm for Radial Basis Function Networks", IEEE Transactions on Neural Networks, Vol 2, No 2 (Mar) , 1991.
6. Cross, R. A bird’s-eye view: Using social network analysis to improve knowledge creation and sharing, IBM Corporation , 2002
7. Keerthi, S.S., Lin, C.-J., 2003. Asymptotic behaviors of support vector machines with Gaussian kernel. Neural Comput. 15 (7), 1667–1689.
8. Chang C.-C. and Lin C.-J. LIBSVM: a library for support vector machines, 2001.Software available at http://www.csie.ntu.edu.tw/~cjlin/libsvm.
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39-43
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9.
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Authors:
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Parveen Dabur, Naresh Kumar Yadav, Ram Avtar
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Paper Title:
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Matlab Design and Simulation of AGC and AVR For Single Area Power System With Fuzzy Logic Control
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Abstract: This paper deals with the combination of automatic generation control (AGC) of thermal system with automatic voltage control (AVR). In this particular work thermal unit is considered with single area concept. The primary purpose of the AGC is to balance the total system generation against system load and losses. Any mismatch between generation and demand causes the system frequency to deviate from scheduled value. Thus high frequency deviation may lead to system collapse. Further the role of automatic voltage regulator is to hold terminal voltage magnitude of synchronous generator at a specified level. The interaction between frequency deviation and voltage deviation is analyzed in this paper. System performance has been evaluated at various loading disturbances. This paper describes the design, implementation and operation performance of fuzzy controller as part of the combined loop of AGC & AVR for single area power system. The fuzzy controller is implemented in the control of ACE calculation in the case of AGC & excitation in case of AVR, which determines the shortfall or surplus generation that has to be corrected. In the case of AVR, fuzzy with PID has been implemented.
Keywords: Automatic Generation Control (AGC), Automatic Voltage Regulator (AVR), Area Control Error (ACE), Frequency Response, Voltage Response, Govemor Action, Power System Operation, Fuzzy logic, Fuzzy control.
References:
1. Yao Zhang, Lili Dong, Zhiqiang Gao; “Load Frequency Control for Multiple-Area Power Systems”, 2009 American Control Conference Hyatt Regency Riverfront, St. Louis, MO, USA June 10-12, 2009.
2. Nasser Jaleeli, Donald N. Ewart, Lester H. Fink; “Understanding automatic generation control”, IEEE Transaction on power system, Vol. 7, No. 3, August 1992. Pages: 1106-1122.
3. G. V. Hicks, B Jeyasurya, P. Eng; “An investigation of automatic generation control for an isolated transmission system”, IEEE Canadian Conference on Electrical and Computer Engineering, Vol. 2, May 1997. Pages: 31- 34.
4. Jyant Kumar, Kh- Hoi Ng, Gerald Shevle; “AGC simulator for price based operation”, IEEE transaction in power system, Vol.12, No- 2, May 1997. Pages: 527- 532.
5. Jayant Kumar, Kh- Hoi Ng, Gerald Shevle; “AGC simulator for price based operation Part- 2”, IEEE transaction in power system, Vol.12, No- 2, May 1997. Pages: 533- 538.
6. T. C. Yang, H. Cimen, Q.M. Zhu; “Decentralized load – frequency Controller design based on structured singular values”, IEE proc. Gener, Transm, Distrib. Vol. 145 No. 1, January 1998.
7. Vaibhav Donde, M.A.Pai, and Ian A.Hiskens; ”Simulation and Optimization in an AGC system after Deregulation”, IEEE transactions on power systems, Vol.16, No -3, August 2001.
8. Li Pingkang Beijing and Ma Yongzhen; “Some New Concepts in Modem Automatic Generation Control Realization”, IEEE 1998,pp1232-1236.
9. M.S. Anower , MR.I Sheikh, M.F. Hossain, M.G. Rabbani , A.B.M. Nasiruzzaman; “FUZZY GAIN SCHEDULING OF AN AGC IN A SINGLE AREA POWER SYSTEM”, 4th International Conference on Electrical and Computer Engineering ICECE 2006, 19-21 December 2006, Dhaka, Bangladesh.
10. Zulfatman, M. F. Rahmat; “APPLICATION OF SELF-TUNING FUZZY PID CONTROLLER ON INDUSTRIAL HYDRAULIC ACTUATOR USING SYSTEM IDENTIFICATION APPROACH”, International Journal On Smart Sensing And Intelligent Systems, VOL. 2, NO. 2, JUNE 2009.
11. Huang S. H, Chen Y. H. C. 2006. Adaptive Sliding Control with Self-Tuning Fuzzy Compensation for Vehicle Suspension Control. Mechatronics, Vol. 16: 607-622.
12. Loukianov A. G., Sanchez E., Lizarde C. 2007. Force Tracking Neural Block Control for an Electro-Hydraulic Actuator via Second-Order Sliding Mode. Int. Journal of Robust and Nonlinear Control, Wiley InterScience, 20, June : 319-332.
13. Q.P. Ha, H. Trinh, A Variable Structure- Based Controller with Fuzzy Tuning for Load Frequency Control, International Journal of Power and Enenrgy Systems, Vol. 0,No.0,2001.
14. Y.L. Karnavas, D.P. Papadopoulos, AGC for autonomous power system using combined intelligent techniques, Electric Power Systems Research 62 (2002), pp-225-239.
15. Shao J., Chen L., Sun Z. 2005. The Application of Fuzzy Control Strategy in Electro-hydraulic Servo System. In Proceedings of the IEEE International Conference on Mechatronics & Automation, 2010-2016. Niagara Falls, Canada.
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44-49
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10.
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Authors:
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G R Rajkumar, M Krishna, H N Narasimha Murthy, S C Sharma, K R Vishnu Mahesh
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Paper Title:
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Investigation of Repeated Low Velocity Impact Behaviour of GFRP /Aluminium and CFRP /Aluminium Laminates
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Abstract: The objective of this research was to investigate esponse of repeated low velocity impact tests on glass fibre/ epoxy-Al metal laminates (GEAML) and carbon fibre/epoxy-Al metal laminates (CEAML) at the same location using drop-weight tester. CEAML, GEAML as well as monolithic Al panels of the same thickness were impacted repeatedly up to four impacts. The effect of repeated impacts on specimen is studied on peak load, absorbed energy, decelerated velocity and impact time with respect to deflection at impactor load of 5.2 kg under gravity fall. The result shows the Al plates, GEAML and CEAML exhibit different behaviour for both loading bearing capacity and damage pattern. The maximum load bearing capacity is higher in case of monolithic aluminium but damage spread throughout the specimen, which contribute to the energy-absorbing capacity of these Al plates. In the case of GEAML and CEAML the damage is concentrated only at impact area hence lower energy-absorbing capacity.
Keywords: FML, Low velocity impact, Epoxy, Glass fibre, Carbon fibre.
References:
1. J.G.Carrillo, W.J.Cantwell, “Mechanical properties of novel fibre metal laminate based on a polypropylene composite”, Mechanics of Materials, vol.41 (2009) pp.828-838.
2. Edson Cocchiere botelho, Rogerio Almedia Silva, Luiz Cladio Pardini, Mirabel Cerqueira Rezende “A review on the development and properties of continuous fibre/epoxy/aluminium Hybrid composites for Aircraft structures”, Material Research, vol.9(3) (2006) pp.247-256.
3. G.Reyes, H.Kanf, “Mechanical behaviour of lightweight thermoplastic fibre metal laminates”, Journal of Materials Processing Technology, vol. 186 (1-3), (2007) pp284-289.
4. J.J.Homan, “Fatigue initiation in Fiber metal laminates”. International journal of Fatigue, vol. 28 (4), (2006) pp 366-374
5. Guocai Wu J.M.Yang. “The mechanical behaviour of GLARE laminates for aircraft Structures”, Journal of Minerals, Metals and Materials society, Vol.57,no.1(2005) pp.72-79.
6. G.Caprino,G.Spataro,S.Del Luongo “Low impact behaviour of fibreglass-aluminium laminates”, Composites part A,vol 35(2004),pp605-616.
7. P.Cortes,W.J.Cantwell, “The fracture properties of a fiber metal laminates based on magnesium alloy”,Composites: Part B:Engineering, vol.37 (2006)No.2-3, pp.163-170
8. Jeremy Laliberte, P.V.Straznicky,Cheung Poon. “Numerical modelling of low velocity impact damage in fiber metal laminates”, ICAS 2002 Congress, pp.1-10.
9. M.R.Abdullah,W.J.Cantwell “Impact resistance of polypropylene based fibre-metal Laminates”. Composites science and technology,vol.66, No.11-12,(2006) pp.1682-1693.
10. S.L.Lemanski, G.N.Nurich, G.S.Langdon, M.C.Simmons,W.J Cantwell, G.K.Schleyer “Behaviour of fiber metal laminates subjected to localised blast loading- Part II: Quantitative analysis”. International Journal of Impact Engineering vol.34 No.7(2007) pp.1223-1245
11. ASTM D7136, “Standard test method for Measuring the damage Resistance of a Fiber-Reinforced-Polymer matrix Composites to a Drop Weight Impact event”, Book of standards, Vol 15.03,(2005)
12. M.V.Hosur, M.R.Karim, S.Jeelani “Experimental investigations on the response of stitched/unstitched woven S2-glass/SC15 epoxy composites under single and repeated low velocity impact loading”. Composite structures, vol.61,No.1-2 (2003)pp. 89-102.
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50-58
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11.
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Authors:
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C K Bhensdadia, Y P Kosta
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Paper Title:
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An Efficient Algorithm for Mining Frequent Sequential Patterns and Emerging Patterns with Various Constraints
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Abstract: In many cases, sequential pattern mining still faces tough challenges in both effectiveness and efficiency. On the one hand, there could be a large number of sequential patterns in a large database. A user is often interested in only a small subset of such patterns. Presenting the complete set of sequential patterns may make the mining result hard to understand and hard to use. On the other hand, although efficient algorithms have been proposed, mining a large amount of sequential patterns from large data sequence databases is very expensive task. If we can focus on only those sequential patterns interesting to users, we may be able to save a lot of computation cost by those uninteresting patterns. Many types of constraints can be pushed in sequential pattern mining like item constraint, aggregate constraint, length constraint, gap constraint, duration to enhance the performance.
Keywords: Sequential Pattern, Constraints.
References:
1. Xiaogang Wang, Yan Bai, Yue Li,”An Information Retrieval method based on sequential access pat terns” in 2010 Asia-Pecificconference on Wearable computing system, 2010.
2. Erich Allen Peterson, Peiyi Tang, “A Hybrid approach to mining frequent sequential patterns”, ACMSE, CLEMSON, SC, USA, 2009, Unpublished.
3. Jean Francois Boulicaut, “If constraint based mining is the answer: what is the constraint? (Invited Talk)”, IEEE International conference on data mining workshops, 2008.
4. Incrementally Fast Updated Sequential Pattern Trees, Proceedings of the Seventh International Conference on Machine Learning and Cybernetics, Kunming, 12-15 July 2008
5. Shigeaki Sakurai, Youichi Kitahata and Ryohei Orihara , “Discovery of Sequential Patterns based on Constraint Patterns”, international journal of computational intelligence,2008
6. An Efficient Frequent Item set Mining Algorithm, Proceedings of Sixth International Conference on Machine Learning Cybernetics, Hong K-ong, 19-22 August 2007.
7. Jian Pei, Jiawei Han, Wei Wang, “Constraint-based sequential pattern mining : the pattern growth methods”, J Intell Inf Syst , Vol. 28, No.2, pp. 133 –160 , 2007.
8. Yen-Liang Chen, Ya-Han Hu, “The consideration of recency and compactness in sequential pattern mining”, In Proceedings of the second workshop on Knowledge Economy and Electronic Commerce, Vol. 42, Iss. 2 ,pp. 1203-1215, 2006.
9. Yu Hirate, Hayato Yamana, “Generalized Sequential Pattern Mining with Item Intervals”, Journal of Computers, Vol. 1, No. 3, June 2006.
10. Mining Sequential Patterns by Pattern-Growth: The PrefixSpan Approach Jian Pei, Jiawei Han, Behzad Mortazavi-Asl, Jianyong Wang, Helen Pinto, Qiming Chen, Umeshwar Dayal, and Mei-Chun Hsu, IEEE Transactions on Knowledge and Data Engineering, Vol. 16, No. 10, October 2004.
11. N Ju-Dong Ren, Yin-Bo Cheng, Lung-Lung Yang, “An Algorithm for Mining Generalized Sequential Patterns”, Proceedings of the Third International Conference on Machine Learning and Cybernetics, Shanghai, 26-29 August 2004.
12. Ron Kohavi, Rajesh Parekh, “Visualizing RFM Segmentation”, In Proceedings of the Fourth SIAM International Conference on Data Mining, San Mateo, CA, 2004.
13. Ming-Yen Lin and Suh-Yin Lee, “Incremental update on sequential patterns in large databases by implicit merging and efficient counting”, Information Systems, Vol. 29, No. 5, pp. 385-404, 2004.
14. Show-Jane Yen and Yue-Shi Lee, “Mining Sequential Patterns with Item Constraints”, DaWaK 2004: data warehousing and knowledge discovery: International conference on data warehousing and knowledge discovery, Zaragoza, ESPAGNE, vol. 3181, pp. 381-390, 2004.
15. Wang, J., & Han J., “BIDE: Efficient Mining of Frequent Closed Sequences”, Proceedings of the 20th International Conference of Data Engineering, Boston, USA, 2004, pp. 79-90.
16. C. Antunes, A. L. Oliveira, “Generalization of Pattern-growth Methods for Sequential Pattern Mining with Gap Constraints”, Machine Learning and Data Mining in Pattern Recognition, Third International Conference, MLDM 2003, Leipzig, Germany, July 5-7, 2003, Proceedings.
17. Y. L. Chen, M. C. Chiang, and M. T. Kao, “Discovering time-interval sequential patterns in sequence databases”, Expert Systems with Applications, Vol. 25, No. 3, pp. 343-354, 2003.
18. M. J. Zaki, “SPADE: an efficient algorithm for mining frequent sequences”, Machine Learning Journal, Vol. 42, Iss. (1-2), pp. 31-60, 2001.
19. Sahista Machchhar, C.K. Bhensdadia and A.M. Ganatra, “Scientific Understanding, Comprehensive Evolution and More Informed Evaluation of Various Sequential Pattern Mining Algorithms”,CiiT International journal of Data Mining & Knowledge engineering,pp. - Jan-2011
20. Helen Pinto, and Jiawei Han , “Multidimensional Sequential Pattern Mining”, In Proceedings of the 10th International Conference on Information and Knowledge Management, pp 81 - 88 , Atlanta, Georgia, USA , 2001.
21. Ching-Yao-Wang, Tzung-Pei Hong, S.S.T. 2001 “Maintainance of sequential pattern for record deletion”, International conference on data mining pp. 536-541.
22. A. Mortazavi, Q. Chen, U. Dayal, M. Hsu, J. Han and T. Pei, FREESPAN: Frequent Pattern Projected sequential pattern mining” Proc ACM SIGMOD, 2000.
23. M. N. Garofalakis, R. Rastogi, K. Shim, “SPIRIT: Sequential Pattern Mining with Regular Expression Constraints”, In Proceedings of 25th VLDB Conference, pp. 223-234, San Francisco, California, 1999.
24. R. Agrawal and R. Srikant, “Mining sequential patterns: generalizations and performance improvements”, In Proceedings of the 5th International Conference on Extending Database Technology, pp. 3-17, Avignon, France, 1996.
25. R. Agrawal and R. Srikant, “Mining sequential patterns”, In Proceedings of the 1995 International Conference on Data Engineering, pp. 3-14, 1995.
26. Agrawal, R. and Srikant, R. 1994. “Fast algorithms for mining association rules”, In Proceeding of 20th international conferenceon very large databases, VLDB, J.B. Bocca, M. Jarke, and C. Zaniolo.. Eds. Morgan Kauffman pp. 487-499.
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59-65
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12.
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Authors:
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Amit Ganatra, Y P Kosta
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Paper Title:
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In depth Coverage and Analysis of Information Fusion Technique (with Enhanced Algorithm for Feature Selection with Multiple Classifier System) for Data Mining
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Abstract: The main objective of Information Fusion techniques in Data Mining is to show that final information generated to be of superior quality and more meaningful, than the information available from the actual (primary) sources. Fusion, by definition, requires a qualitative difference between the final output and the output of the original sources. Information fusion is the process of acquisition, filtering, correlation and integration of relevant information from various sources into one representational format that is appropriate for deriving decisions regarding the interpretation of the information. In theory, the fusion of redundant information from different sources can reduce redundancy and overall uncertainty and thus increase the accuracy of the system. The fusion can be performed on three levels: raw data level, feature level, or decision level. This paper presents a novel idea of a multiple (ensemble) classification (classifier) system with feature selection where Neural Networks (Multilayer Feed-forward Networks with Back Propagation learning) are boosted for scalable (High Dimensional) datasets. The method uses Genetic Algorithms for Feature Selection with various Evaluation Techniques (Evaluators) like subset evaluation, consistency subset evaluation and wrapper subset approaches to enhance the performance of the feature selection and overall system.
Keywords: Classification, Multiple Classifier Pre-processing, Training, Testing, Feature Selection, AttributeSelectedClassifier (ASC)
References:
1. Pei-Yong Xia, Xiang-Qian Ding, Bai-Ning Jiang, “A Ga-Based Feature Selection And Ensemble Learning For High-Dimensional Datasets”, IEEE 2009, Proceedings of the Eighth International Conference on Machine Learning and Cybernetics, Baoding, 12-15 July 2009.
2. Laura Emmanuella A Santana, Diogo F de Oliveira, Anne M P Canuto and Marcilio C P de Souto, “A Comparative Analysis of Feature Selection Methods for Ensembles with Different Combination Methods”, IEEE 2007, Proceedings of International Joint Conference on Neural Networks, Orlando, Florida, USA, August 12-17, 2007.
3. Lin Yu Tseng and Shiueng Bien Yang, “Genetic Algorithms for Clustering, Feature Selection and Classification”, IEEE 1997.
4. Faten Hussein, Nawwaf Kharma, and Rabab Ward, “Genetic Algorithms for Feature Selection and Weighting, a Review and Study”, IEEE 2001.
5. Daming Shi & Wenhao Shu and Haitao Liu, “Feature Selection for Handwritten Chinese Character Recognition Based on Genetic Algorithms”, IEEE 1998.
6. Laura E A Santana, Ligia Silva and Anne M P Canuto, “Feature Selection in Heterogeneous Structure of Ensembles: A Genetic Algorithm Approach”, IEEE 2009, Proceedings of International Joint Conference on Neural Networks, Atlanta, Georgia, USA, June 14-19, 2009.
7. Jihoon Yang and Vasant Honavar, “Feature Subset Selection Using a Genetic Algorithm”, IEEE Intelllgent Systems, 1998.
8. Michael L. Raymer, William F. Punch, Erik D. Goodman, Leslie A. Kuhn, and Anil K. Jain, “Dimensionality Reduction Using Genetic Algorithms”, IEEE Transactions On Evolutionary Computation, Vol. 4, No. 2, July 2000. (Journal Paper).
9. N. Srinivas and Kalyanmoy Deb, “Multiobjective Optimization Using Nondominated Sorting in Genetic Algorithms”, Journal of Evolutionary Computation, Vol. 2, No. 3. (Journal Paper).
10. Mr. Kashif Waqas, Dr. Rauf Baig1and, Dr. Shahid Ali, “Feature Subset Selection Using Multi-Objective Genetic Algorithms”, IEEE 2009.
11. L. S. Oliveira, R. Sabourin, F. Bortolozzi, and C. Y. Suen, “Feature Selection for Ensembles: A Hierarchical Multi-Objective Genetic Algorithm Approach”, IEEE, 2003.
12. Kushan Ahmadian, Abbas Golestani, Nasser Mozayani, and Peyman Kabiri, “A New Multi-Objective Evolutionary Approach for Creating Ensemble of Classifiers”, IEEE, 2007.
13. Abdullah Konaka, David W. Coitb and Alice E. Smith, “Multi-objective optimization using genetic algorithms: A tutorial”, Reliability Engineering and System Safety, Available at www.ElsevierComputerScience.com.
14. Christm Emmanouilidis, Andrew Hunter, John Machtyre, and Chris Cox, “Multiple - Criteria Genetic Algorithms for Feature Selection in Neurofuzzy Modeling”, IEEE, 1999.
15. L. S. Oliveira, R. Saburin, F. Bortolozzi, and C. Y. Suen, “Feature Selection Using Multi-Objective Genetic Algorithms for Handwritten Digit Recognition”, IEEE, 2002
16. Pier Luca Lanzi & Politecnico di Milano, “Fast Feature Selection with Genetic Algorithms: A Filter Approach”, IEEE 1997.
17. Huan Liu and Rudy Setiono, “A Probabilistic Approach to Feature Selection – A Filter Solution”.
18. Hussein Almuallim and Thomas G. Dietterich, “Learning Boolean concepts in the presence of many irrelevant features”, Artificial Intelligence 69 (1994) 279-305, Available at www.ElsevierComputerScience.com.
19. Mark A. Hall, “Correlation based Feature Selection for Machine Learning”, Thesis submitted in partial fulfilment of the requirements for the degree of Doctor of
Philosophy at The University of Waikato.
20. Nigel Williams, Sebastian Zander, Grenville Armitage, “A Preliminary Performance Comparison of Five Machine Learning Algorithms for Practical IP Traffic Flow Classification”, ACM SIGCOMM Computer Communication Review , Volume 36, Number 5, October 2006. (Journal Paper).
21. Frans Coenen and Paul Leng, “Obtaining Best Parameter Values For Accurate Classification”, IEEE, 2005.Alden H. Wright, “Genetic Algorithms for Real Parameter Optimization”.
22. Zhang Dezhen and Yang Kai, “Genetic Algorithm based Optimization for AdaBoost”, International Conference on Computer Science and Software Engineering, 2008.
23. Dragos D. Margineantu and Thomas G. Dietterich, “Pruning Adaptive Boosting”, ICML, 1997.
24. Simon Thompson, “Genetic Algorithms as Post Processors for Data Mining”, AAAI Technical Report WS-99-06, 1999.
25. Janaki Gopalan, Reda Alhajj and Ken Barker, “Discovering Accurate and Interesting Classification Rules Using Genetic Algorithm”.
26. Karina Gibert, Joaquín Izquierdo, Geoff Holmes, Ioannis Athanasiadis, Joaquim Comas, Miquel Sànchez-Marrè, “On the role of pre and post-processing in environmental data mining”, International Congress on Environmental Modelling and Software Integrating Sciences and Information Technology for Environmental Assessment and Decision Making, 2008.
27. Manoranjan Dash and Huan Liu, “Consistency-based search in feature selection”, Artificial Intelligence 151 (2003) 155–176.
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66-73
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13.
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Authors:
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R. Hari Kumar, B. Vinoth Kumar, G. Karthick
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Paper Title:
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Performance Analysis for Quality Measures Using K means Clustering and EM Models in Segmentation of Medical Images
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Abstract: The main objective of this paper is to compare the performance of quality measures towards the segmentation of medical images using K-means clustering and EM models. Three types of medical images such as MRI, X-rays and Ultrasonic images are studied. The K-means clustering shows that the non intactness of the clusters. As cluster size increases the edges are brittle and compactness of the clusters get altered. Hence expectation maximization models are utilized to segment the images for better edge perseverance and compactness of clusters at larger size. The quality measures like PSNR, average difference, structural content, image fidelity and normalize coefficients are calculated for both methods. The EM models shows one dB increase in PSNR values than the K-means clustering. At less number of clusters AD value of EM models mitigates the compactness of the cluster centers.
Keywords: Segmentation, K-means clustering, EM models, Quality measures
References:
1. S. Li, T. Fevens, A. Krzyzak and S. Li Automatic: clinical image segmentation using pathological modeling, PCA and SVM, Engineering Applications of Artificial Intelligence, Volume 19, Issue 4, June 2006, pp. 403-410. .
2. A. Schwaighofer, V. Tresp, P. Mayer, A.K. Scheel and G. Muller, The RA scanner: prediction of rheumatoid joint inflammation based on laser imaging, IEEE Trans. Biomed. Imaging 50 (2003), pp. 375-382.
3. Y. Zheng, H. Li and D. Doermann, Machine printed text and handwriting identification in noisy document images, IEEE Trans. Pattern Anal. Mach. Intell. 26, 2004, pp. 337-345.
4. W.Y. Ma and B. S. Manjunath,, 1997. Edge flow; A framework of boundary detection and image segmentation. In: IEEE Conference on Computer Vision and Pattern Recognition, San Juan, Puerto Rico, pp. 744-749.
5. Chenyang Xu. and L.P. Jerry , 1998. Snakes, shapes and gradient vector flow, IEEE trans. Image Process. 73, pp. 359-369.
6. Song Chun Zhu and Alan. Y, 1996, Region competition: Unifying snakes, region growing and Bayes/MDL for multiband image segmentation, IEEE Trans. Pattern Anal. Mach. Intell. 189, pp. 884-900.
7. Gatica-Perez. D and Ruiz Correa, 2001, Extensive partition operators, gray-level connected operators, and region merging/classification segmentation algorithms; Theoretical links. IEEE Trans. Image Process. 109, pp. 1332-1345.
8. Shah.P.K and Udupa.J.K., 2001, Optimum image thresholding via class uncertainty and region homogeneity, IEEE Trans. Pattern Recog. Mach. Intell. 237, pp. 689-706.
9. Jia-Ping Wang, 1998, Stochastic relaxation on partions with connectd components and its application to image segmentation, IEEE Trans. Pattern Anal. Mach. Intell. 206, pp. 619-636.
10. J. Xie, and H. T. Tsui, Image segmentation based on maximum-likelihood estimation and optimum entropy-distribution (MLE-OED), Pattern Recognition Letters, Volume 25, Issue 10, 16 July 2004, pp. 1133-1141.
11. Deng.Y. and Manjunath, B.S., 2001, unsupervised segmentation of color-texture regions in images and video, IEEE Trans. Pattern Anal. Mach. Intell. 238, pp. 800-810.
12. R. Xu, D. Wunsch II, “Survey of clustering algorithms”, IEEE Transcations on Neural Networks, 16, 2005, 645-678.
13. A. Jain, M. Murty, P. Flynn, “Data Clustering: A review”, ACM Computing Surveys, 31, 1999, 264-323.
14. O. Hall, I. Barak, J.C. Bezdek, “Clustering with a genetically optimized approach”, IEEE Trans. Evo. Computation, 3, 1999, 103-112.
15. G. Hamerly, C. Elkan, “Alternatives to the k-means algorithm that find better clusterings”, Proc. Of the ACM Conference on Information and Knowledge Management, CIKM-2002, 2002, 600-607.
16. G. H. Omran, A. Salman, A.P. Engelbrecht, “Dynamic clustering using particle swarm optimization with application in image segmentation”, Pattern Anal Applic., 8, 2006, 332-344.
17. M. Halkidi, M. Vazirgiannis, I. Batistakis, “Quality scheme assessment in the clustering process”. In Proc. Of the 4th European Conf. on Principles of Data Mining and Knowledge Discovery, LNCS 1910, 2000, 265-267.
18. M. Halkidi et al., “Clustering validity checking methods: PartII” SIGMOD Rec., 31, No. 3, 2002, 19-27.
19. Stephen J Redmond and Conor Heneghan,” A method for initializing the k-means clustering algorithm using kd-trees”, Pattern Recogintion 28(2007), 965-973.
20. Ujjwal Maulik, Sanghamitra Bandyopadhyay, “ Genetic algorithm based clustering technique”, Pattern Recognition 33(2000), 1455-1465.
21. Mc. Culloch, C.E, Maximum likelihood algorithm for generalized linear mixed models. Journal of the American Statistical Association, 92, 1997, pp162-170.
22. Ahmet M. Eskicioglu and Paul S. Fisher “Image Quality Measures and their performance” IEEE Transactions on Communications, Vol.43, No.12, December 1995.
23. Marta Mrak, Sonja Grgic and Mislav Grgic “ Picture Quality Measures in Image Compression Systems” EUROCON 2003, Ljuijana, Slovenia..
24. Ismail Avicibas, Bulent Sankur, Khalid Sayood “ Statistical Evaluation of Image Quality Measures” Journal of Electronic Imaging 11(2), 206-223 (April 2002).
25. N. M. Nasrabadi and R. A. King, “ Image coding using vector quantization: A review, “IEEE Trans. Communications, vol.36, no.8,pp. 957-971, August 1988..
26. Zhou Wang, Alan Conrad Bovik., et.al. “ Image Quality Assessment: From Error Visibility to Structural Similairty” IEEE Transactions on Image processing, vol. 13, no.4, April 2004.
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74-80
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14.
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Authors:
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Pituk Bunnoon, Kusumal Chalermyanont, Chusak Limsakul
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Paper Title:
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Wavelet and Neural Network Approach to Demand Forecasting based on Whole and Electric Sub-Control Center Area
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Abstract: Whole and electric sub-control area load demand forecasting based on a wavelet transform and a neural network method that are very significant technique for a load prediction. The research used wavelet transform method in preprocessing stage; furthermore, a neural network is used to predict in forecasting stage for whole and sub-control areas prediction. The comparison results show that sub-control area forecasting has a good prediction than that the whole area forecasting based on two levels of wavelet transform. An accuracy of forecast is an essential activity for fuel reserve planning in a power system.
Keywords: Whole area, electric sub-control area, wavelet transform, neural network, forecasting.
References:
1. Qi Wu, “Hybrid model based on wavelet support vector machine and modified genetic algorithm penalizing Gaussian noises for power load forecasts,” International journal of expert systems with applications pp.379-385, 2011.
2. Ying Chen, Peter B. Luh, Che Guan, Yige Zhao, Laurent D. Michel et.al., “Short-term load forecasting: Similar day-based wavelet neural networks,” IEEE Trans.on power syst., vol.25, pp.322-330, 2010.
3. Ajay Shekhar Pandey, Devender Singh, and Sunil Kumar Sinha, “Intelligent hybrid wavelet models for short-term load forecasting,” IEEE Trans.on power syst., vol. 25, pp.1266-1273, 2010.
4. N. Amjady, and F. Keynia, “Short-term load forecasting of power systems by combination of wavelet transform and neuro-evolutionary algorithm,” International journal of energy, vol.34, pp.46-57, 2009.
5. N. M. Pindoriya, S. N. Singh, and S. K. Singh, “An adaptive wavelet neural network based energy price forecasting in electricity markets,” IEEE Trans.on power syst., vol.23, pp.1423-1432, 2008.
6. D. Benaouda, F. Murtagh, J.-L. Starck, and O. Renaud, “Wavelet-based nonlinear multi-scale decomposition model for electricity load forecasting,” International journal of neuro computing, vol.70, pp.139-154, 2006.
7. Tai Nengling, Jurgen Stenzel, and Wu Hongxiao, “Techniques of applying wavelet transform into combined model for short-term load forecasting,” International journal of electric power systems research, vol.76, pp.525-533, 2006.
8. Bai-Ling Zhang, and Zhao-Yang Dong, An adaptive neural-wavelet model for short term load forecasting,” International journal of electric power systems research, vol.59, pp.121-129, 2001.
9. Tongxin Zheng, Adly A. Girgis, and Elham B. Makram, “A hybrid wavelet-Kalman filter method for load forecasting,” International journal of electric power systems research, vol.54, pp.11-17, 2000.
10. S. J. Yao, Y. H. Song, L. Z. Zhang, and X. Y. Cheng, Wavelet transform and neural network for short-term electrical load forecasting, International journal of energy conversion and management, vol.41, pp.1975-1988, 2000.
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81-86
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15.
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Authors:
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Gunjan Manik, Alka Kalra, Sanjeev Kalra
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Paper Title:
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Performance Analysis of STBC- OFDM System Under Multipath Fading Channel
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Abstract: In current 4G systems growing demand of multimedia services and the growth of Internet related contents lead to increasing interest to high speed communications. Recently, space time block codes (STBC) have gained much attention as an effective transmit diversity technique to provide reliable transmission with high peak data rates to increase the capacity of wireless communication systems. In this paper, performance of STBC-OFDM is analyzed under different constraints in Rayleigh fading channels. We have studied the effect of modulation order, antenna selection techniques, slow and fast fading conditions and power conditions on the performance of STBC-OFDM.
Keywords: MIMO, OFDM, STBC, Multipath, fading
References:
1. S. M. Alamouti, “A simple transmitter diversity scheme for wireless communications,” IEEE J. Select. Areas Commun., vol. 16, pp. 1451–1458, Oct. 1998.
2. B. Lu and X. Wang, "Space-time code design in OFDM systems," in IEEE Conference on Global Telecommunications, vol.2, pp. 1000-1004, 2000.
3. Wei, X. Xia and K. Ben Letaief, "Space-Time/Frequency Coding for MIMO-OFDM in Next Generation Broadband Wireless Systems," IEEE Wireless Communications, vol. 14, pp.32-43, 2007.
4. 3GPP TR 25.996 V6.1.0, “Spatial Channel Model for Multiple Input Multiple Output (MIMO) Simulations.”
5. S. M. Alamouti, “A Simple Transmit Diversity technique for Wireless Communications,” IEEE JSAC, vol. 16, no. 8, Oct. 1998, pp. 1451–58.
6. W. Huiming, X. Xiang-Gen, Y. Qinye and L. Bin, "A family of space-time block codes achieving full diversity with linear receivers," IEEE Transactions on Communications, vol. 57, pp. 3607-3617, 2009.
7. A. Slaney and Y. Sun, "Space-time coding for wireless communications: an overview," IEE Proceedings in Communications, vol. 153, pp. 509-518, 2006.
8. S. N. Diggavi, N. Al-Dhahir, A. Stamoulis and A. R. Calderbank, "Great expectations: the value of spatial diversity in wireless networks," Proceedings of the IEEE, vol. 92, pp. 219-270, 2004.
9. D. Agrawal, V. Tarokh, A. Naguib and N. Seshadri, "Space-time coded OFDM for high data-rate wireless communication over wideband channels," in IEEE Conference on Vehicular Technology, vol.3, pp. 2232-2236, 1998.
10. D. Torrieri and M. C. Valenti, "Efficiently decoded full-rate space-time block codes," IEEE Transactions on Communications, vol. 58, pp. 480-488, 2010.
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87-90
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16.
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Authors:
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S.V. Saboji, C. B. Akki
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Paper Title:
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Congestion-aware Proactive Vertical Handoff Decision Using Coalition Game
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Abstract: In 4G wireless networks, when a mobile host (MH) with multiple wireless interfaces changes its location or needs a network service, the MH will require a switch between different wireless networks (vertical handoff). Proposed congestion-aware proactive vertical handoff scheme uses coalition game. Its main objective is to decide source and target networks for handoff at minimum congestion in 4G wireless networks. Our mechanism is based on the coalition game formulation. It aims at maximizing the utilization of the resources available and meeting QoS requirement of users as much as possible by initiating vertical handoff. This will reduce congestion level. The performance of proposed scheme is evaluated through numerical analysis.
Keywords: congestion, vertical handoff, Heterogeneous networks, and fairness.
References:
1. S. V. Saboji, C.B. Akki “A survey of fourth generation (4G) wireless network models” Journal of Telecommunications Management, Vol. II, No. 1, Henary Stewart publications (2009), pp 77-91
2. S.V.Saboji, C.B.Akki “A Review of Vertical Handoff In 4G Wireless Networks” in proceedings of National Conference on Computer Networks, 20-21st Feb 2009, Banglore, India.
3. Janise Mcnair, Fang Zhu, “Vertical Handoffs In Fourth – Generation Multinetwork Environment”,IEEE Wireless Communications, June 2004, pp 8-16.
4. Enrique Stevens-Navarro, Yuxia Lin, Vincent W. S. Wong “An MDP-Based Vertical Handoff Decision Algorithm for Heterogeneous Wireless Networks” IEEE Transaction On Vehicular Technology, Vol. 57, No. 2, March 2008, pp 1243-1255.
5. M. N. Birje , S. S. Manvi , M. S. Kakkasageri , S. V. Saboji “Prediction Based Handover for Multiclass Traffic in Wireless Mobile Networks : An Agent Based Approach” proceedings of Sixth international conference on information communication and signal processing (ICICS 2007),10th –13th Dec 2007, Singapore
6. Kai Xu, Ye Tain, Nirwan Ansari “TCP-Jersy for Wireless IP Communications” IEEE Journal On selected Areas in Communications, VOL. 22, NO. 4, May 2004, pp. 747-756.
7. H. J. Byun, J.T. Lim “Fair TCP congestion control in heterogeneous networks with explicit congestion notification” IEE Proc.-Commun., Vol. 152, No. 1, February 2005, pp. 13-21.
8. Pyung-Soo Kim ,Yong-Jin Kim “Recognizing Handover Situation for Vertical Handovers using Mobile IPv6 Signaling” IJCSNS International Journal of Computer Science and Network Security, VOL.7 No.4, April 2007,pp 173-179
9. Fei Hu, Neeraj K. Sharma “The Quantitative Analysis of TCP Congestion Control Algorithm in Third-Generation Cellular Networks Based on FSMC Loss Model and its Performance Enhancement” proceedings of IEEE INFOCOM 2002, pp 407-417.
10. Lei Ying, G. E. Dullerud, R. Srikant “Global Stability of Internet Congestion Controllers with Heterogeneous Delays” Proceeding of the 2004 American Control Conference Boston, Massachusetts June 30. July 2,2004, pp 2948-2954.
11. Filipe Abrantes, Manuel Ricardo “On Congestion Control for Interactive Real-time Applications in Dynamic Heterogeneous 4G Networks” proceedins of IEEE 16th International Symposium on Personal, Indoor and Mobile Radio Communications 2005, pp 1796-1801.
12. Kun Tan, Feng Jiang, Qian Zhang, Xuemin Shen “Congestion Control in Multihop Wireless Networks” IEEE Transactions on Vehicular Technology, Vol. 56, No. 2, Mar. 2007, pp 863-874.
13. Haijie Huang and Jianfei Cai “Adding Network-Layer Intelligence to Mobile Receivers for Solving Spurious TCP Timeout During Vertical Handoff”, IEEE Network •
November/December 2006, pp 24-32.
14. Xiaojun Lin, Ness B. Shroff “The impact of imperfect scheduling on cross-layer congestion control in wireless networks” IEEE/ACM Transactions on Networks, VOL. 14, NO.2, April 2006, pp. 302-315.
15. Mung Chiang “Balancing transport and physical layers in wireless multihop networks: Jointly optimal congestion control and power control”
16. Ben-Jye Chang, Jun-Fu Chen “Cross-Layer-Based Adaptive Vertical Handoff With Predictive RSS in Heterogeneous Wireless Networks” IEEE Transaction on Vehicular Technology, Vol. 57, No. 6, Nov. 2008, pp 3679-3693.
17. Jinan Lou, Shashidhar Thakur, Shankar Krishnamoorthy, Henry S. Sheng “Estimating Routing Congestion Using Probabilistic Analysis” IEEE Transaction on Computer –Aided Design of Integrated Circuits and Systems, vol. 21, No. 1, Jan 2002, pp 32-42.
18. Rupesh S. Shelar, Sachin S. Sapatnekar, Prashant Saxena, Xinning Wang “A Predictive Distributed Congestion Metric With Application to Technology Mapping” IEEE Transaction on Computer –Aided Design of Integrated Circuits and Systems, vol. 24, No. 5, May 2005, pp. 696-701.
19. Maogang Wang, Xiaojian Yang, Majid Sarrafzadeh “Congestion Minimization During Placement” IEEE Transaction on Computer –Aided Design of Integrated Circuits and Systems, vol. 19, No. 10, Oct. 2000, pp 1140-1149.
20. Mesut E. Baran, Venkat Banunarayanan, Kenneth E. Garren “Equitable Allocation of Congestion Relief Cost to Transactions” IEEE Transactions on Power Systems, Vol. 15, No. 2, May 2000, pp.579-586.
21. Z.Q. Wu, Y.N. Wang, H.S. Qing ,Y.X. Ou Yang “Continuous integration congestion cost allocation based on sensitivity” IEEE Proc.-Gener. Transm. Distrib., Vol. 151, No. 4, July 2004, pp 421-427.
22. Qing-Hui Zeng, Jian-Ping WU, Yi-Lin Zeng, Ji-Long Wang, Rong-Hua Qin “Research on controlling Congstion In Wireless Mobile Internet Via Satellite Based On Multi-Information & Fuzzy Identification Technologies” Proceedings of 1ST International conference on Machine Learning and Cybernetics, Bejing, 4-5th Nov 2002, pp 1698-1702.
23. Jiang Hu and Sachin S. Sapatnekar “A Timing-Constrained Simultaneous Global Routing Algorithm” IEEE Transaction on Computer –Aided Design of Integrated Circuits and Systems, vol. 21, No. 9, Sep. 2002, pp 1025-1037.
24. Sneha Kumar Kasera, Member, Ramachandran Ramjee, Sandra R. Thuel, Xin Wang, Member “Congestion Control Policies for IP-Based CDMA Radio Access Networks” IEEE Transactions on Mobile Computing, Vol. 4, No. 4, July/August 2005, pp. 349-363.
25. Tarek Bejaoui, Lynda Mokad “Adaptive Hybrid Call admission Control Policy for UMTS with underlying Tunnel-WLANs Heterogeneous Networks” Proc. of IEEE International Conference on Communication on 14-18 June 2009, pp.1-5.
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91-97
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17.
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Authors:
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Basil Hamed
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Paper Title:
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Design & Implementation of Smart House Control Using LabVIEW
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Abstract: Smart home is a house that uses information technology to monitor the environment, control the electric appliance and communicates with the outer world. Smart home is a complex technology, at the same time it is developing. A smart home automation system has been developed to automatically achieve some activities performed frequently in daily life to obtain more comfortable and easier life environment. A sample house environment monitor and control system that is one branch of the Smart home is addressed in this paper. The system is based on the LabVIEW software and can act as a security guard of the home. The system can monitor the temperature, humidity, lighting, fire & burglar alarm, gas density of the house and have infrared sensor to guarantees the family security. The system also has internet connection to monitor and control the house equipment’s from anywhere in the world. This paper presents the hardware implementation of a multiplatform control system for house automation using LabVIEW. Such a system belongs to a domain usually named smart house systems. The approach combines hardware and software technologies. Test results of the system have shown that it can be easily used for the smart home automation applications.
Keywords: Smart House, LabVIEW, PIC16F877A, Data Acquisition Card, Remote Control.
References:
1. http://depts.washington.edu/dmgftp/publications/html/smarthouse98-mdg.html
2. Sleman, A.; Alafandi, M.; Moeller,”Integration of Wireless Fieldbus and Wired Fieldbus for Health Monitoring”; R.;Consumer Electronics, 2009. ICCE '09. Digest of
Technical Papers International Conference on 10-14 Jan. 2009 Page(s):1 - 2
3. Van Nguyen, T.; Jin Gook Kim; Deokjai Choi, "ISS: The Interactive Smart home Simulator," Advanced Communication Technology, 2009. ICACT 2009. 11th International Conference on , vol.03, no., pp.1828- 1833, 15-18 Feb. 2009
4. Escoffier, C.; Bourcier, J.; Lalanda, P.; Jianqi Yu, "Towards a Home Application Server," Consumer Communications and Networking Conference, 2008. CCNC 2008. 5th IEEE, vol., no., pp.321-325, 10-12 Jan. 2008.
5. Salvador, Z.; Jimeno, R.; Lafuente, A.; Larrea, M.; Abascal, J.;”Architecture for ubiquitous enviroments” Wireless And Mobile Computing, Networking And Communications, 2005. (WiMob'2005), IEEE International Conference on, Volume 4, 22-24 Aug. 2005 Page(s):90 - 97 Vol. 4.
6. Patricio, G.; Gomes, L., "Smart house monitoring and actuating system development using automatic code generation," Industrial Informatics, 2009. INDIN2009. 7th IEEE International Conference on, vol., no., pp.256-261, 23-26 June 2009
7. LabVIEW for Everyone: Graphical Programming Made Easy and Fun, Jeffrey Travis, Jim Kring, Third Edition. Prentice Hall Professional, 2007 ISBN-10: 0131856723.
8. http://zone.ni.com/devzone/cda/pub/p/id/1141
9. Chance Elliott, Vipin Vijayakumar, Wesley Zink, and Richard Hansen: National Instrument LabVIEW: A programming environment for laboratory automation and measurement, the association for Laboratory Automation, 2007.
10. Bitter, Rick, Taqi Mohiuddin, and Matt Nawrocki “LabVIEW Advanced Programming Techniques “Boca Raton: CRC Press LLC, 2001
11. LabVIEW User Manual, April 2003 Edition, National Instruments
12. http://www.ni.com/labview/
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98-106
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18.
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Authors:
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Suchita Varade, Kishore Kulat
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Paper Title:
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BER Comparison of Rayleigh Fading, Rician Fading and AWGN Channel using Chaotic Communication based MIMO-OFDM System
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Abstract: This paper proposes, a technique which uses chaotic communication system combined with adaptive beamforming, for secure communications and to improve the system performance by mitigating interference. For secure communications, chaotic sequences are used. Many chaotic communication systems have been proposed, but most of them show a poor performance under realistic channel conditions (i.e. noise and multipath fading).This paper proposes a wireless communication structure based on two coupled chaotic systems. In order to enhance the error-rate performance of MIMO-OFDM system, adaptive beamforming is used. Evaluation and comparison of the performances of MIMO- OFDM system in the AWGN (Additive White Gaussian Noise) channel, Rician fading channel and the Rayleigh fading channel are provided. Results are verified and analyzed for two cases, one when adaptive beamforming is used in the proposed system and second when adaptive beamforming is not used in the proposed system. Computer simulations are done to verify the performance of the proposed approach. A simulation tool with a Graphical User Interface (GUI) which implements these algorithms is also developed to provide ease in the execution.
Keywords: Chaotic Communication System, Adaptive Beamforming, LMS (Least Mean Squares), LMS-LMS (LLMS).
References:
1. Jiang and Hanzo ,White paper on “MIMO & Smart antenna for 3G & 4G Wireless systems-practical aspects & deployment considerations”, May-2010
2. M. Ali Akbar, Hamza Bin Tila, M. Zulkifl Khalid and Muhammad Asim Ajaz “Bit Error Rate Improvement using ESPRIT based Beamforming and RAKE receiver”, 978-1-4244-4873-9/09/©2009 IEEE
3. M. P. Kennedy, R. Rovatti, and G. Setti “Special Issue on Applications of Nonlinear Dynamics to Electronic and Information Engineering”, Proceedings of the IEEE, May 2002, vol. 90,no. 5., Eds., Chaotic Electronics in Telecommunications. CRC Press, 2000.
4. F. C. M. Lau and C. K. Tse, ‘ Chaos-Based Digital Systems’ Berlin: Springer-Verlag, 2003
5. V.Nagarajan and P..Dananjayan “Performance Enhancement Of MC-DS/CDMA System Using Chaotic Spreading Sequence"
6. T. Athanasiadis, K. H. Lin, and Z.M. Hussain. “Transmission of compressed multimedia data over wireless channels using space-time OFDM with adaptive beamforming”, In Proc. IEEE TENCON., pages 1–5, Nov. 2005.
7. A. J. Paulraj, D. A. Gore, R. U. Nabar, and H. Bolcskei.”An overview of MIMO communications - a key to gigabit wireless”, In Proc. of the IEEE, Feb. 2004.
8. B. Vucetic and J. Yuan. Space-time Coding. John Wiley & Son Ltd, 2003.
9. Datacomm Research Company, “Using MIMO-OFDM Technology to Boost Wireless LAN Performance Today”, White Paper, St. Louis, MO, Jun. 2005
10. H. Sampath, S. Talwar, J. Tellado, V. Erceg, and A. J. Paulraj, “A fourth-generation MIMO-OFDM broadband wireless system:Design, performance, and field trial results”,[ IEEE Commun. Mag., vol. 40, no. 9, pp. 143–149, Sep. 2002.
11. H. Liu, and Q. Feng, “Post-IDFT Multidimensional Beamforming for STC-OFDM Systems,” IEEE Asia-Pacific Microwave Conf., pp. 2110-2113, Dec 2006, doi:10.1109/APMC.2006.4429829.
12. P. Xia, S. Zhou, and G. Giammakis, “Adaptive MIMO-OFDM based on Partial Channel State Information,” IEEE Trans. on Signal Processing, vol. 52, no. 1, pp. 202-213, Jan 2004,doi:10.1109/TSP.2003.819986.
13. T. Athanasiadis, K. H. Lin and Z. M. Hussain, “Transmission of Compressed Multimedia Data over Wireless Channels using Space-time OFDM with Adaptive Beamforming,” IEEE Technology Education and Networking Conf., pp.1-5, Nov 2005,doi:10.1109/TENCON.2005.301344.
14. K. Li and M. A. Ingram, “Space-time Block-Coded OFDM Systems with RF Beamformers for High-speed Indoor Wireless Communications,” IEEE Trans. on Communications, vol. 50, no.12, pp. 1899-1902, Dec 2002, doi:10.1109/VETECF.2000.883306.
15. J. Li, K. B. Letaief and Z. Cao, “Co-channel Interference Cancellation for Space-time Coded OFDM Systems,” IEEE Trans. On Wireless Communications, vol. 2, no. 1, pp. 41-49, Jan 2003,doi:10.1109/TWC.2002.806361.
16. D. Agrawal, V. Tarokh, A. Naguib, and N. Seshadri, “Space time coded OFDM for high data-rate wireless communications over wideband channels,” IEEE Conf. on Vehicular Technology, pp. 2232-2236, May 1998, doi:10.1109/VETEC.1998.686154.
17. Hang-Hong Kuo, Teh-Lu Liao, Jui-Sheng Lin & Jun-Juh Yan “A new structure of chaotic secure communication in wireless AWGN channel” 2009 International Workshop on Chaos-Fractals Theories and Applications
18. A.N. Miliou, I.P. Antoniades, S.G. Stavrinides, and A.N. Anagnostopoulos, “Secure communication by chaotic synchronization: Robustness under noisy conditions”, Nonlinear analysis, p.p. 1003–1012, 2008.
19. M. Hännikäinen, T.D. Hämäläinen, M. Niemi, and J. Saarinen, “Trends in personal wireless data communications“,Computer Communications, p.p.84–99, 2002.
20. Jalal Abdul sayed SRAR, Kah-Seng CHUNG and Ali MANSOUR “Adaptive Array Beamforming using a Combined LMSLMSAlgorithm” IEEEAC paper#1606, Version 2, Updated 2009:12:27
21. N. Erasala, and David C. Yen, “Bluetooth technology: a strategic analysis of its role in global 3G wireless communication era”, Computer Standards & Interfaces,p.p.193–206, 2002
22. E.S. Nadimi, H.T. SogaardG.Jongren,M.Skoglund and B. Ottersten, “Combining beamforming and orthogonal space-time block coding,” IEEE Trans. Inf. Theory, vol. 48, pp. 611–627, Mar. 2002.
23. V. Tarokh, H. Jafarkhani, A.R. Calderbank,“Space-time block coding for wirelesscommunications: Performance results”, IEEE Journal on Selected Areas in Communication,vol.17, pp. 451-460, Mar.
24. S.W.Varade & K.D.Kulat “Robust Algorithms for DOA Estimation and Adaptive Beamforming for Smart Antenna Application” International Conference on Emerging Trend in Engineering & Technology (ICETET 2009) at G.H.Raisoni College of Engg.,Nagpur,16-18 Dec.2009
25. S.W.Varade & K.D.Kulat “Performance Analysis of MVDR Beamformer for Smart Antenna Applications” International Conference on VLSI and Communication(ICVCom-09),Kerela April 16-18, 2009
26. E. G. Larsson and P. Stoica, Space-Time Block Coding for Wireless Com-munications. Cambridge, U.K.: Cambridge Univ. Press, 2003.
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107-115
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19.
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Authors:
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J.Hamidi
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Paper Title:
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Control System Design Using Particle Swarm Optimization (PSO)
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Abstract: The main purpose of this paper is to select the appropriate weighting matrices for designing of optimal controller using Particle Swarm Optimization (PSO) algorithm as an intelligent procedure. Generally speaking, it is not easy to determine the optimal weighting matrices for a high-dimension control system via analytical methods. There is no direct relation between the elements of weighting matrices and desirable control system characteristics and selecting these weights is performed using time-consuming trial and error method and based on designer experiences. Superior features of PSO method are fast tuning of the parameters, rapid convergence, less computational burden and capability to avoid from local optima. Simulation results demonstrate that our proposed method is more efficient and robust compared with other heuristic method, i.e., the Genetic Algorithm (GA) method.
Keywords: Weighting matrices, Particle Swarm Optimization (PSO), Genetic Algorithm (GA).
References:
1. Kirk, Donald E., Optimal control theory: an introduction, Carmel/ California, 1937.
2. Kalman, R. E., “When is a linear control system optimal?,” J. Basci Eng. Trans., ASME-86D:51-56,1964.
3. Wang Yaoqing, “The determination of weighting matrices in LQ optimal control system,” ACTA Automatic Sinica, 1992.
4. Gheng-Chung Sung, Gong Chen, “Optimal control systems design associated with genetic algorithm,” Proceedings of 2006 CACS Automatic Control Conference St. John's University, Tamsui, Taiwan, Nov. 10-11, 2006.
5. C. P. Bottura and J. V. da Fonseca Neto, “Rule based decision making unit for eigenstructure assignment via parallel genetic algorithm and LQR design,” Proceeding of the American Control Conference, Chicago, Illinois, Vol. 1, pp. 467- 471, 2000.
6. C. P. Bottura and J. V. da Fonseca Neto, “Parallel eigenstructure assignment via LQR design and genetic algorithms,” Proceeding of the American Control Conference, San Diego, Vol. 4, pp. 2295-2299, 1999.
7. Iraj Hassanzadeh, Saleh Mobayen and Abbas Harifi, “Input-output feedback linearization cascade controller using genetic algorithm for rotary inverted pendulum,” American Journal of Applied Sciences, 5 (10), pp: 1322-1328, 2008.
8. Iraj Hassanzadeh and Saleh Mobayen, “Optimum design of PID controller for 5-bar-linkage manipulator using particle swarm optimization,” Proceeding of the 4th International Symposium on Mechatronics and its Applications (ISMA07), Sharjah, U.A.E. March 26-29, 2007.
9. J. Kennedy and R. Eberhart, “Particle swarm optimization,” in Proc. IEEE Int.Conf. Neural Networks, vol. IV, Perth, Australia, 1995, pp. 1942-1948.
10. Eberhart, R. C., and Kermedy, J. “A New Optimizer Using Particles Swarm Theory,” Proc. Sixth International Symposium on Micro Machine and Human Science(Nagoya, Japan), IEEE Service Center, Pkcataway, NJ, 39-43, 1995.
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116-119
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20.
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Authors:
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H. P. Sinha, Nidhi Syal
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Paper Title:
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Design of Fault Tolerant Reversible Multiplier
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Abstract: In the recent years, reversible logic has emerged as a promising technology having its applications in low power CMOS, quantum computing, nanotechnology, and optical computing. The classical set of gates such as AND, OR, and EXOR are not reversible. This paper proposes a novel 4x4 bit reversible fault tolerant multiplier circuit which can multiply two 4-bit numbers. It is faster and has lower hardware complexity compared to the existing designs. In addition, the proposed reversible multiplier is better than the existing counterparts in terms of delay & power. It is based on two concepts. The partial products can be generated in parallel using Fredkin gates and thereafter the addition is done by using reversible parallel adder designed from IG gates. Thus, this paper provides the initial threshold to building of more complex system which can execute more complicated operations using reversible logic.
Keywords: Reversible logic, Parity, Fredkin gate, IG gate, Constants, Garbage, Delay.
References:
1. R. Landuer, IBM, Irreversibility and heat generation in the computing process, J. Res. Develop., 5 (1961) 183.
2. C. H. Bennet, Logical reversibility of computation, IBM J. Res. Dev., 6 (1973) 525.
3. M. Nielsen and I. Chuang, Quantum computation and quantum information, Cambridge University Press, New Delhi (2002).
4. A. De Vos et al, Design of reversible logic circuits by means of control gates, PATMOS 2000: LNCS, 1918 (2000) 255.
5. B. Desoete and A. De Vos, A reversible carry-look-ahead adder using control gates, Integration, VLSI J., 33 (2002) 88.
6. P. Kerntopf, A new heuristic algorithm for reversible logic synthesis, In Proceedings of the IEEE Design Automation Conference (2004) 834.
7. A. Agarwal and N. K. Jha, Synthesis of reversible logic, Proceedings of IEEE, Design, Automation and Test in Europe Conference and Exhibition, 2 (2004) 1384.
8. A. De Vos and Y. V. Rentergem, Reversible computing: from mathematical group theory to electronical circuit experiment. In Proceedings of the 2nd Conference on Computing Frontiers (2005).
9. V. V. Shende, I.L. Markov, and S.S. Bullock, Synthesis of quantum logic circuits, IEEE Trans. Comput.-Aided Des. Integr. Circuits Syst., 25 (2006) 1000.
10. M. Mohammadi and M. Eshghi, Heuristic methods to use dont cares in automated design of reversible and quantum logic circuits, Quantum Inform. Process. J., 7 (2008) 172.
11. D. M. Miller, D. Maslov, G. W. Duek, A Transformation based algorithm for reversible logic synthesis, Proceedings of 40th Design Automation conference (DAC'03), Anaheim, Califomia (2003) 318.
12. M. Mohammadi and M. Eshghi, On _gures of merit in reversible and quantum logic designs, Quantum information Process, 8 (2009) 297.
13. D. P. Vasudevan, Reversible-logic design with online testability, IEEE Trans. Instru. and Meas., 55 (2006) 406.
14. G. Schrom, Ultra-low-powerCMOStechnology. PhD thesis, Technischen Universitat Wien (1998).
15. R. C. Merkle, Two types of mechanical reversible logic. Nanotech, 4 (1993) 114.
16. E. Knill, R. La_amme and G. J. Milburn, A scheme for efficient quantum computation with linear optics, Nature, 409 (2001) 46.
17. H. Wood and D. Junghuei Chen, Fredkin gate circuits via recombination enzymes, Proceedings Evolutionary Computation 2004 (CEC2004), 2 (2004) 1896.
18. M. P. Frank, "Reversibility for efficient computing" Ph.D. dissertation, Dept. Elect. Eng. Comput. Sci., Mass. Inst. Tech.,Cambridge, Jun.1999.
19. E. Fredkin and T Toffoli, "Conservative logic," Int. 1. Theor. Phys., vol. 21, no. 3-4, pp. 219-253, 1982.
20. P G upta, A. Agrawal, N. K. Jha, "An Algorithm for synthesis of reversible logic circuits", IEEE Transactions on computer-Aided Design ofintegrated Circuits and Systems, Vol. 25, No. II, pp.2317-2330, November 2006.
21. Saiful Islam, M.D. and M.D. Rafiqul Islam."Minimizing of reversible adder circuits", Asian journal, Inform. Tech., 4(12): 1146-1151, 2005.
22. Thapliyal Himanshu, and M.B. Srinivas, "Novel reversible TSG gate and its application for designing reversible carry look ahead adder and other adder architectures", Asia-pacific computer systems architecture conference(ACSAC 05).3740-2005.
23. H. H. Babu and A. R Chowdhury, "Design of a compact reversible binary coded decimal adder circuit", Journal of Systems Architecture, 52 (2006) 272
24. H. Thapliyal and M. B. Srinivas, "Novel reversible TSG gate and its application for designing reversible carry look ahead adder and other adder architectures", Proceedings of the 10th Asia-Paci_c Computer Systems Architecture Conference (ACSAC 05), 3740 (2005) 805.
25. M. Haghparast and K. Navi, "A Novel Reversible Full Adder Circuit for Nanotechnology Based Systems". J. Applied Sci., 7 (2007) 3995.
26. M. Haghparast and K. Navi, "Design of a novel reversible multiplier circuit using HNG gate in nanotechnology", Am. 1. Applied Sciences, 5 (2008) 282
27. H. Thaplyal and M. B. Srinivas, "Novel reversible multiplier architecture using reversible TSG gate", IEEE Int. Conf Computer Systems and Applications (2006) 100.
28. M. Shams, M. Haghparast and K. Navi, "Novel reversible multiplier circuit in nanotechnology", World App!. Sci. 1., 3 (2008) 806.
29. M. Haghparast, S. J. Jassbi, K. Navi and O. Hashemipour, "Design of a novel reversible multiplier circuit using HNG gate in nanotechnology", World Appl. Sci. 1., 3 (2008) 974.
30. M.S. Islam et a!.,"Low cost quantum realization of reversible multiplier circuit", Information technology journal, 8 (2009) 208.
31. M. S. Islam, and M. Rafiqul Islam, “Minimization of reversible adder circuits”, Asian Journal of Information Technology, vol. 4, no. 12, pp. 1146-1151, 2005.
32. B. Parhami , “Fault tolerant reversible circuits”, in Proceedings of 40th Asimolar Conf. Signals, Systems, and Computers, Pacific Grove, CA, pp. 1726-1729, October 2006.
33. D. Maslov, G. W. Dueck, and D. M. Miller, "Synthesis of Fredkin-Toffoli reversible networks," IEEE Trans. VLSI Systems, vol. 13, no. 6, pp. 765-769, 2005.
34. R. Feynman, “Quantum mechanical computers”, Optical News, vol. 11, 1985, pp. 11-20.
35. A. Peres, “Reversible logic and quantum computers”, Physical Review: A, vol. 32, no. 6, pp. 3266-3276, 1985.
36. T. Toffoli, “Reversible computing”, In Automata, Languages and Programming, Springer-Verlag, pp. 632-644, 1980.
37. Islam, S.; Rahman, M.M.; Begum, Z.; Hafiz, Z.; Al Mahmud, A.; , "Synthesis of Fault Tolerant Reversible Logic Circuits," Testing and Diagnosis, 2009. ICTD 2009. IEEE Circuits and Systems International Conference on , vol., no., pp.1-4, 28-29 April 2009.
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120-124
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21.
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Authors:
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Santanu Mondal
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Paper Title:
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Two Element Superdirective Array Of Shorted Planar Inverted Cone Antenna
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Abstract: The proposed wideband shorted planar inverted cone antenna (SPICA) has been described as a two element antenna array in this paper. The two element array by this antenna with proper phase of excitation and spacing between the elements provide superdirective array characteristic. This array gives peak endfire directivity from 3.502 dBi to 10.3 dBi and radiation efficiency above 98% in the operating frequency band. Also in radiation pattern characteristic, the farfield pattern of the array is more directional than single element array. Thus the proposed SPICA is suitable for wideband antenna array applications.
Keywords: SPICA, wideband, superdirective array
References:
1. A. I. Uzkov, “An approach to the problem of optimum directive antennae design,” Comptes Rendus (Doklady) de l’Academie des Sciences de l’URSS, vol. 53, pp. 35–38, 1946.
2. Altshuler, E.E., O'Donnell, T.H., Yaghjian, A.D., Best, S.R., “A Monopole Superdirective Array,” Antennas and Propagation, IEEE Transactions on, Volume: 53, Issue: 8 , Part: 2, Digital Object Identifier: 10.1109/TAP.2005.851810, Publication Year: 2005, pp. 2653 – 2661.
3. Sungkyun Lim, Hao Ling, “Design of a Closely Spaced, Folded Yagi Antenna,” Antennas and Wireless Propagation Letters, IEEE, Volume: 5, Issue: 1, Digital Object Identifier: 10.1109/ LAWP.2006.878892, Publication Year: 2006, pp. 302 – 305.
4. Best, S.R., “Improving the performance properties of a dipole element closely spaced to a PEC ground plane,” Antennas and Wireless Propagation Letters, IEEE, Volume: 3, Issue:1, Digital Object Identifier: 10.1109/LAWP. 2004.840722, Publication Year: 2004, pp. 359 – 363.
5. T. Kokkinos, T. Rufete-Martinez, and A. P. Feresidis, “Electrically small superdirective endfire arrays of low-profile folded monopoles,” presented at the 2nd Int. Congress on Advanced Electromagnetic Materials in Microwaves and Optics, Pamplona, Spain, 2008.
6. K. Buell, H. Mosallaei, and K. Sarabandi, “Metamaterial Insulator Enabled Superdirective Array,” IEEE Trans. Antennas Propag., vol. 55, no. 4, pp. 1074–1085, Apr. 2007.
7. Agarwall, N. P., Kumar G., and Ray K. P., “Wide-Band Planar Monopole Antennas,” IEEE Trans. Antennas Propagation, Vol. 46, No. 2, 1998, pp. 294-295.
8. Mazinani, S. Maryam, Hassani, Hamid Reza, “Two element wideband Planar plate Monopole superdirective array,” Electrical Engineering (ICEE), 2010 18th Iranian Conference on, Digital Object Identifier: 10.1109/IRANIANCEE.2010.5507521, Publication Year: 2010, pp. 80 - 85.
9. Mazinani, S.M., Hassani, H.R., “Superdirective Wideband Array of Planar Monopole Antenna With Loading Plates,” Antennas and Wireless Propagation Letters, IEEE, Volume: 9, Digital Object Identifier: 10.1109/LAWP.2010.2087411, Publication Year: 2010, pp. 978 – 981.
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125-128
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22.
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Authors:
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Subir Kr. Maity, Himadri Sekhar Das
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Paper Title:
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FPGA Based Hardware Efficient Digital Decimation Filter for ∑-∆ ADC
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Abstract: This paper focuses on the design of a FPGA based off chip digital decimation filter for single bit sigma-delta A/D converter with medium oversampling ratio for the processing of audio signal. A second-order single-stage sigma-delta (∑-∆) modulator with single bit quantizer with oversampling ratio 96 from FALCON Instrument is used in this work as a reference modulator. To reduce hardware requirement, multiplier less FIR filter architecture used. Total three cascaded comb type filter are used for decimation and filtering purpose. Those filters are designed and simulated with MATLAB Filter Design Toolbox and finally mapped into XILINX SPARTAN-II XC2S50PQ208 series FPGA. The overall ADC gives 14 bit resolution.
Keywords: Oversampling, quantization, SNR, Sigma-Delta, Decimation, CIC Filter, FPGA.
References:
1. George I Bourdopoulos, Aristodemos Pnevmatikakis, Vassilis Anastassopoulos, Theodore L Deliyannis: Delta sigma Modulators, Modeling, Design & simulation. Imperial college press,2006
2. S. R. Norsworthy, R. Schreier and G. C. Temes, Delta-sigma Data Converters: Theory, Design, and Simulation, IEEE Press, 1996
3. N. H. E. Weste and D. Harris, CMOS VLSI Design- A Circuits and Systems Perspective, 3rd edition, Addison Wisley, NY, 2005.
4. Sangil Park, Principles of Sigma Delta Modulation for Analog to Digital Converters .Motorola Digital Signal Processors.
5. Modern Digital and Analog Communication Systems , B.P. Lathi , oxford press , Third edition
6. Geerts, Y., Steyaert, M.S.J., Sansen, W.M.: A 3.3-V, 15-bit delta-sigma ADC with a signal bandwidth of 1.1 MHz for ADSL applications. IEEE J. Solid-State Circuits 34(7), 927–936 July (1999)
7. J. C. Candy, “Decimation for sigma delta modulation,” IEEE Transactions on Communications, Vol. COM-34, No.1, January 1986
8. Rusu, A., “Sigma-delta modulation using filters with non monotonic transfer functions. Modeling and analysis” , IEEE International Conference on Electronics, circuits and systems ,Cyprus, Sept.- 1999 , pp. 1361-63
9. Understanding CIC compensation Filters, Application Note 455 “ http://www.altera.com/literature/an/an455.pdf”
10. www.xilinx.com/support/documentation/data_sheets/ds001.pdf
11. http://www.lynx-india.com/index.php?productID=5570
12. www.falconindia.biz/Download/DCS-I.pdf
13. G.Ritchie, “Higher order interpolation analog to digital converter”, Ph.D Dissertation, University of Pennsylvania, 1977
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129-133
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23.
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Authors:
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Gurjit Singh Walia, Gajraj Kuldeep, Rajiv Kapoor, A K Sharma, Navneet Gaba
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Paper Title:
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FPGA Based Secure System Design-an Overview
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Abstract: The implementation of cryptographic algorithm on FPGA is highly addressed in different forums due to its paramount advantages over the other platforms. Most of the secure systems are designed using SRAM based FPGAs with additional security features provided by the manufactures. In this paper, firstly, attempts are made to address different security problems of FPGA based secure systems. The difficulty levels that an attacker may face while implementing an attack are also tabulated. Finally, some constructive recommendation for tackling these security issues are proposed for designing secure systems.
Keywords: Cryptography, FPGA, Secure system, Security, ASIC, SRAM
References:
1. T. Wollinger and C. Paar. How Secure Are FPGAs in Crypto-graphic Applications?(Long Version).Report 2003/119,IACR,2003.
2. A. Elbirt, W.Yip, B. Chetwynd, and C. Paar.An FPGA-based performance Evaluation of the AES block cipher candidate algorithm finalists. IEEE Transactions on VLSI Design, 9(4):545{557, August 2001.
3. Jr. Kaliski , B. S. Koc , C. K. and C. Paar , Eds. 2002. Workshop on Cryptographic Hardware and Embedded Systems — CHES 2002. Vol. LNCS 2523. Springer-Verlag, Berlin, Germany.
4. T. Wollinger, J. Guajardo and C. Paar “ Security on FPGAs: State of the Art Implementations and Attacks” ACM Special Issue Security and Embedded Systems Vol. No. March 2003.
5. K. K Parhi, VLSI Digital Signal Processing Systems: Design andImplementation, John Wiley & Sons, Inc.1999.
6. T. Kean. Cryptographic rights management of FPGA intellectual property cores. In Field Programmable Gate Arrays Symposium, pages 113-118, New York, NY, USA, 2002. ACM Press.
7. Actel Corporation www.actel.com ,“Design Security in Nonvolatile Flash and Antifuse FPGAs”, Security Backgrounder ©2002.
8. D.G Abraham, G.M. Dolan, G.P. Double and J.V. Stevens. 1991.Transaction Security System. IBM Systems Journal vol. 30 no. 2NewYork: International Machines Business Corporation: 206-229.
9. P. Vikram. Embedded systems challenge faq. Information Systems And Internet Security Laboratory,Department of Computer Science, NYU- Polytechnic University.
10. D.P. Wilt, R.C. Meitzler, and J.P. DeVale. Metrics for TRUST in Integrated Circuits, 2008
11. A. Ross. Security Engineering, A Gudie to Building Dependable Distributed Systems. Wiley, New York, second edition edition, 2008.
12. http://www.bltinc.com/services .fpga-reverseengineering.htm. FPGA Reverse Engineering Services.
13. E. J. Chikofsky and J. H. Cross, II, “Reverse Engineering and Design Recovery,” IEEE Software, vol. 7, no. 1, pp. 13-17, January 1990.
14. P. Kocher, “Timing attacks on implementations of Diffie-Hellman, RSA, DSS and other systems,” in Advances in Cryptology: Proceedings of CRYPTO’96, N. Koblitz, Ed., 1996, vol. 1109 of LNCS, pp. 104– 113,Springer- Verlag.
15. P. Kocher, J. Jaffe, and B. Jun, “Differential power analysis,” in Advances in Cryptology: Proceedings of CRYPTO’99, M. Wiener, Ed.1999, vol. 1666 of LNCS, pp. 388–397, Springer-Verlag
16. J. G. Proakis and D. G. Manolakis – Digital Signal Processing – Principles, Algorithms and Applications; Third Edition; Prentice Hall of India, 2003.
17. Xilinx Inc., www.xilinx.com. "Using Bitstream Encryption", in Chapter 2 of the Virtex II Platform FPGA.
18. T. Kean, “Secure Configuration of Field Programmable Gate Arrays”, Proceedings of FPL 2001, Belfast, UK. Published as Springer LNCS.
19. Algotronix Ltd., “Method of Protecting Intellectual Property Cores on Field Programmable Gate Array”, unpublished pending patent application.
20. D Mukhopadyay et al., “ Cryptoscan: A Secured Scan Chain Architecture”, IEEE @ 2005 Proceedings of the 14th Asian Test Symposium(ATS ’05).
21. A Baumgarten et al “A case study of hardware Trojan design and implementation” Springer-Verlag 2010
22. Xiaoxiao Wang; Tehranipoor, M.; Plusquellic, J “Detecting malicious inclusions in secure hardware: Challenges and solutions” 2008 IEEE international workshop on hardware-oriented security and trust (HOST)
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134-138
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24.
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Authors:
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D. Mondal, A. Chakrabarti, A. Sengupta
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Paper Title:
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LMI Based Wide Area TCSC Controller in Mitigating Small Signal Oscillations
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Abstract: This paper proposes a Linear Matrix Inequality (LMI) based robust controller design employing Wide Area Measurement (WAM) based stabilizing signals as generator speed. A Three-input, Single-output (TISO) controller is designed for a Thyristor Controlled Series compensator (TCSC) in order to mitigate small signal oscillations in a multimachine power system. The controller design has been carried out based on the mixed-sensitivity formulation in a LMI framework with pole-placement constraint. The small signal performance of the test system has been examined employing eigenvalue analysis as well as time domain response. The designed controller is found to be robust against disturbances like varying generations as well as load power demand.
Keywords: H∞ Robust Controller, Linear Matrix Inequality, Small Signal Oscillations, Thyristor Controlled Series Compensator, Wide Area Measurement
References:
1. P. Kundur, Power System Stability and Control. New York: McGraw-Hill; 1994.
2. P. Kundur, M. Klein, G. j. Rogers and M. S. Zywno, “Application of power system stabilizers for enhancement of overall system stability,” IEEE Trans. on Power Systems, vol. 4, no. 2, 1989, pp. 614-626.
3. N. G. Hingorani and L. Gyugyi. Understanding FACTS: Concepts and technology of Flexible AC Transmission System. IEEE Press; 2000.
4. M. O. Hassan, Z. A. Zakaria and S. J. Cheng, “Impact of TCSC on enhancing power system stability,” IEEE Power and Energy Conference, APPEEC 2009; pp. 1-6.
5. M. E. Aboul-Ela, A. A Sail am, J. D. McCalley and A. A. Fouad, “Damping controller design for power system oscillations using global signals,” IEEE Trans. on Power
System, vol. 11, no.2, May 1996, pp. 767-773.
6. J. Chow, J. Sanchez-Gasca, H. Ren, and S. Wang, “Power system damping controller design using multiple input signals,” IEEE Contr. Syst. Mag., vol. 20, Aug. 2000, pp. 82–90.
7. B. C. Pal, A. A. Coonick, I. M. Jaimoukha, and H. El-Zobaidi, “A Linear Matrix Inequality Approach to Robust Damping Control Design in Power Systems with Superconducting Magnetic Energy Storage Device,” IEEE Transactions on power systems, vol. 15, no. 1, Feb. 2000, pp. 356-362.
8. B. Chaudhuri and B. C. Pal, “Robust damping of multiple swing modes employing global stabilizing signals with a TCSC,” IEEE Trans. on power systems, vol. 19, no. 1, Feb. 2004, pp. 499-506.
9. I. Kamwa, R. Grondin and Y. Hebert, “Wide-area measurement based stabilizing control of large power systems—A decentralized/hierarchical approach,” IEEE Trans. Power Syst., vol. 16, Feb. 2001, pp. 136–153.
10. F. Okou, L. A Dessaint and O. Akhrif, “Power system stability enhancement using a wide-area signals based hierarchical controller,” IEEE Trans. on Power System, vol. 20, Aug. 2005, pp. 1465-1477.
11. H. Wu, S. Tsakalis and G.T. Heydt, “Evaluation of time delay effects to wide-area power system stabilizer design,” IEEE Transactions on power systems, vol. 10, no. 4, Nov. 2004, pp. 1935-1941.
12. P. W. Sauer and M. A. Pai, Power system dynamics and stability; Pearson Education Pte. Ltd.: Singapore, 1998.
13. C. R. Fuerte-Esquivel, E. Acha and H. Ambriz-Pe'rez, “A thyristor controlled series compensator model for the power flow solution of practical power networks,” IEEE Trans on power systems, vol. 15, no. 1, 2000, pp. 58-64.
14. S. Skogestad and I. Postlethwaite, Multivariale Feedback Control Analysis and Design: John Wiley and Sons. 1996.
15. K. Zhou, J. Doyle and K. Glover, Robust and Optimal Control: Prentice Hall, 1995.
16. P. Gahinet and P. Apkarian, “A linear matrix inequality approach to H∞ control,” Int. J. Robust Nonlinear Contr., vol. 4, no. 4, Apr. 1994, pp. 421–448.
17. Y. Nesterov and A. Nemirovski, Interior Point Polynomial Methods in Convex Programming; Theory and Applications. Philadelphia, PA: SIAM, 1994.
18. M. Chilali and P. Gahinet, “H∞ design with pole placement constraints: An LMI approach,” IEEE Transaction on Automatic Control, vol. 41, no. 3, Mar. 1996, pp, 358-367.
19. C. Scherer, P. Gahinet and M. Chilali, “Multiobjective output-feedback control via LMI optimization,” IEEE Trans. on Automatic Control, vol. 42, no. 7, July 1997, pp. 896-911.
20. E. Z. Zhou, O. P. Malik and G. S. Hope, “A reduced-order iterative method for swing mode computation,” IEEE Trans. on Power Systems, vol. 6, no. 3, 1991, pp. 1224-1230.
21. Matlab Users Guide, The Math Works Inc., USA, 1998.
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139-144
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25.
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Authors:
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Arpan Deyasi, Swapan Bhattacharyya
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Paper Title:
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Numerical Evaluation of Junction Temperature Effect on Negative Resistivity at Different Current Densities of Si DDR IMPATT Device at Sub-millimeterwave Region
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Abstract: Negative resistivity profile for Si DDR IMPATT device is numerically computed by double-iterative method with incorporation of modified Runge-Kutta method at different junction temperatures and bias current densities for different operating frequency bands in sub-millimeterwave region. Profiles are obtained throughout the depletion layer width for 1-D model consideration and assuming independence of carrier velocities over electric field in avalanche and drift regions; whereas both conduction and displacement current densities are taken into account. Analysis is helpful for comparative study of device performance with different heat sink materials.
Keywords: Current density, Junction temperature, Negative resistance, Small-signal analysis.
References:
1. W.T.Read, “A Proposed High-Frequency Negative Resistance Diode”, Bell System Technical Journal, Vol.37, pp. 401-446, 1958.
2. H.C.Bowers, “Space-Charge-Induced Negative Resistance in Avalanche Diodes”, IEEE Transactions on Electron Devices, Vol. ED 15, No.6, June 1968.
3. T.E.Seidel, R.E.Davis and D.E.Iglesias, “Double-Drift-Region Ion-Implanted Millimeter-Wave IMPATT Diodes”, Proceedings of the IEEE, Vol.59, No.8, pp-1222-1228, 1971.
4. S.K.Roy, J.P.Banerjee and S.P.Pati, “A Computer analysis of the distribution of high frequency negative resistance in the depletion layer of IMPATT Diodes”, NASECODE-IV, p. 494, 1985.
5. M.Mukherjee, S.Banerjee and J.P.Banerjee, “Dynamic Characteristics of III-V and IV-IV Semiconductor Based Transit Time Devices in the Terahertz Regime: A Comparative Analysis”, Terahertz Science and Technology, Vol.3, pp 97-109, 2010.
6. M.Mukherjee and J.P.Banerjee, “DDR Pulsed IMPATT Sources at MM-Wave Window Frequency: High-Power Operation Mode”, International Journal of Advanced Science and Technology, Vol. 19, pp 1-11, 2010.
7. S.Banerjee, M.Mukherjee and J.P.Banerjee, “Bias current optimization of Wurtzite-GaN DDR IMPATT diode for high power operation at THz frequencies”, International Journal of Advanced Science and Technology, Vol. 16, pp 11-20, 2010.
8. M.Mukherjee, S.Banerjee and J.P.Banerjee, “Mobile space-charge effect on Terahertz properties of Wz-GaN based DDR IMPATT oscillators”, CODEC 2009.
9. M.Mukherjee, S.Banerjee and J.P.Banerjee, “MM-wave performance of DDR IMPATT’s based on cubic SiC”, XVth IWPSD-2009.
10. S.Banerjee, M.Mukherjee and J.P.Banerjee, “Studies on the performance of Wz-GaN DDR IMPATT diode at optimum bias current for THz frequencies”, 3rd IEEE MiNDSS-2010.
11. M.Mukherjee and N.Mazumder, “Modeling of high power 0.3 THz IMPATT oscillator based on 3C-SiC and growth of 3C-SiC on Si <100> substrate for possible IMPATT fabrication”, ICMMT 2008.
12. M.Mukherjee and N.Mazumder, “Effects of Charge Bump on High-Frequency Characteristics of α-SiC-based Double-drift ATT Diodes at Millimeter-wave Window Frequencies”, IETE Journal of Research, Vol. 3, pp. 118-127, 2009.
13. X.Bi, J.R.East, U.Ravaioli and G.I.Haddad, “Analysis and Design of Si Terahertz Transit-Time Diodes”, 16th International Symposium on Space Terahertz Technology, pp 271-275, 2005.
14. M.Mukherjee, P.Tripathi and S.P.Pati, “Effects of Mobile Space-Charge on Dynamic Characteristics and Parasitic Resistance of InP Terahertz IMPATT Oscillator Operating at Elevated Junction Temperature, Applied Science Research, Vol. 2(3), pp 42-52, 2010.
15. M.Mukherjee, J.Mukherjee, J.P.Banerjee and S.K.Roy, “MM-wave properties of photo-illuminated double drift Indium Phosphide IMPATT’s at elevated temperature”, Proceedings of Int. Conf. IEEE-ICMMT, 2008.
16. U.C.Ray, A.K.Gupta and M.N.Sen, “Frequency response of W-band pulsed IMPATT’s operating over extended ambient temperature”, International Journal of Infrared and Millimeter Waves, Vol. 10, pp 1165-1179, 1989.
17. S.P.Pati and P.R.Tripathy, “Design Consideration for Sub-mm Wave Silicon DDR’s including Drift, Diffusion and Tunnel Currents”, XIIIth IWPSD, 2005.
18. H.K.Gummel and J.L.Blue, “A Small Signal Theory of Avalanche Noise on IMPATT Diodes”, IEEE, Transaction Electron Devices, Vol. 14, pp. 569-580, 1967.
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145-148
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26.
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Authors:
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Snigdha Madhab Ghosh, Anindya Sundar Dhar, Sunandan Bhunia
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Paper Title:
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Direct Digital Frequency Synthesizer Design With Modified Parabolic Method Approximation Method
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|
Abstract: The efficiency of the traditional DDFS is greatly depends on the large size of memory. The ROM less architecture for generating sine wave and its necessary corrective measure based on parabola has already been developed. This paper proposes a modified parabola by adding a triangular wave to achieve a sine wave with less distortion. This architecture gives better performance.
Keywords: Direct Digital Frequency Synthesizer, Parabolic approximation.
References:
1. A Digital Frequency Synthesizer- J.Tierney, C.M.Radre, and B.Gold IEEE Transactions on Audio and Electroacoustics, March 1971
2. Avanindra Madisetti, Alan Y kwentus, Alan N Willson “A 100-MHz, 16-b, Direct Digital Frequency Synthesizer with a !00-dBc Spurious-Free Dynamic Range”.IEEE Journal of solid-state circuits, vol 34, 8 August 1999,pp1034-1043.
3. D. Soudris, M. Kesoulis, C. Koukourlis, A. Thanailakis, and S. Blionas“Alternative Direct Digital Frequency Synthesizer Architectures with Reduced Memory Size”
4. K.I Palomaki and J Niittylahti, “A Low-Power, Memoryless direct Digital Frequency Synthesizer Architecture” P.O. Box 553,FIN- 33101,Tampere Finland.
5. David J. Betowski, Daniel Dwyer and Valeriu Beiu “A Novel Segmented Parabolic Sine Approximation for Direct Digital Frequency Synthesizers”
6. Amir M. Sodagar and G. Roientan Lahiji “A Pipelined ROM-Less Architecture for Sine-Output Direct Digital Frequency Synthesizers Using the Second-Order Parabolic Approximation”IEEE Transactions on Circuits and Systems-II: Analog and Digital Signal Processing, Vol48 No 9, September 2001.
7. H T Nicholas and H Samueli, “A 150 MHz direct digital frequency synthesizer in 1.25- CMOS with – 90 dBc spurious performance,” IEEE j. Solid –State Circuits vol. 26, pp.1959-1969, Dec.1991.
8. Harris HSP45106 datasheet, Jan 1999.
9. Stanford Telecommunications 1178A datasheet, Mar. 1994.
10. “Qualcomm 2368,” Synthesizer Data Book, 80-24127-1A, Aug. 1997.
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149-153
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27.
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Authors:
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Avisankar Roy, Sunandan Bhunia
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Paper Title:
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Compact Broad Band Dual Frequency Slot Loaded Microstrip Patch Antenna with Defecting Ground Plane for Wi-MAX and WLAN
|
|
Abstract: A dual frequency, compact microstrip patch antenna with enhanced bandwidth is presented in this paper. Microstrip antenna with bandwidth of 31% is also been designed for Wi-MAX application by defecting the ground plane The single layered antenna has been designed to resonate in dual frequencies for Wi-MAX and WLAN with enhanced bandwidth of more than 12%. Microstrip patch antenna with inset feed is simulated with the method of Moment based standard software.
Keywords: Microstrip antenna, dual-frequency, compact, broad band, Wi-MAX, WLAN.
References:
1. Zhi Ning Chen, “Antennas for Portable Devices”, John Wiley & Sons Ltd, 2007.
2. Kin-Lu Wong, “Planer Antennas for Wireless Communications”, John Wiley & Sons Ltd, 2003.
3. Norbahiah Misran, Mohammad Tariqul Islam, Mohammed Nazmus Shakib and Baharudin Yatim, “Design of Broadband Multi-Slotted Microstrip Patch Antenna for Wireless System”, Proceedings of International Conference on Microwave-08, 2008, pp 23-25.
4. S.Bhunia, D.Sarkar, S,Biswas, P.P.sarkar, B.Gupta,, K.Yasumoto “Reduced Size Small Dual and Multi-Frequency Microstrip Antenna” Microwave & optical Technology Letters. Vol. 50, No.4, pp.961-965, April 2008.
5. S. Bhunia, M.-K. Pain, S. Biswas, D. Sarkar, P. P. Sarkar, and B. Gupta, “Investigations on Microstrip Patch Antennas with Different slots and Feeding Points” , Microwave .and Optical Technology Letters, VOL 50, NO. 11, November 2008, pp 2754-2758.
6. Sarkar, I.; Sarkar, P. P.; Chowdhury, S. K., “A new compact printed antenna for mobile communication”, IEEE Antennas & Propagation Conference, 2009. LAPC 2009. Loughborough University, 16-17 Nov. 2009 Page(s):109 - 112.
7. Mahmoud N. Mahmoud and Reyhan Baktur, “A Dual Band Microstrip Fed Slot Antenna”, IEEE Transaction on Antennas and Propagation, Vol. 59,No. 5, pp 1720-1724, may 2011,.
8. Wen-Chung Liu, Chao-Ming Wu, and Yang Dai, ”Design of Tripple Frequency Microstrip Fed Monopole Antenna Using Defected Ground Structure”, IEEE Transaction on Antennas and Propagation, Vol. 59,No. 7, pp 2457-2463, july 2011.
9. E.O. Hammerstad, “Equations for Microstrip Circuit Design”, Proc. Fifth European Microwave Conf. Pp 268-272, September 1975.
10. C. A. Balanis, “Advanced Engineering Electromagnetics”, John Wiley & Sons., New York, 1989.
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154-157
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28.
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Authors:
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Dibyendu Chowdhury, Souvik Singha
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Paper Title:
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A Coding based Approach to Load Flow Analysis using Krylov Subspace Methods for well conditioned systems
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|
Abstract: In this work, we propose to apply the conjugate gradient algorithm to the sparse systems; we encounter these in the system admittance matrices, and we will search for a numerical solution to this system using the locally optimal steepest descent method. The system admittance matrices for an IEEE 30-bus or 57-bus system(s) are too large to be handled by direct methods like the Cholesky decomposition method. Hence, we will make use of the flexible preconditioned conjugate-gradient method, which makes use of sophisticated preconditioners, leading to variable preconditioning that change between successive iterations. The Polak–Ribière formula, a highly efficient preconditioner, is applied to the system, to yield drastic improvements in convergence.
Keywords: Krylov subspace methods, conjugate gradient algorithm, preconditioners, Polak–Ribière formula, assured convergence.
References:
1. James W. Daniel, “Convergence of the Conjugate Gradient Method with Computationally Convenient Modifications” Numerische Mathemati (1967), pp125–131.
2. J. Grainger and W. Stevenson, “Power System Analysis” McGraw-Hill, New York, 1994, ISBN 0-07-061293-5.
3. R. Fletcher and M. J. D. Powell, “A Rapidly Convergent Descent Method for Minimization” Computer Journal 6 (1963), pp163–168.
4. R. Fletcher and C. M. Reeves, “Function Minimization by Conjugate Gradients”, Computer Journal 7(1964), pp149–154.
5. L. Fox, H. D. Huskey, and J. H. Wilkinson, “Notes on the Solution of Algebraic Linear Simultaneous Equations”, Quarterly Journal of Mechanics and Applied Mathematics 1 (1948), pp149–173.
6. Jean Charles Gilbert and Jorge Nocedal, “Global Convergence Properties of Conjugate Gradient Methods for Optimization”, SIAM Journal on Optimization 2 (1992), no. 1,pp 21–42.
7. Gene H. Golub and Dianne P. O’Leary, “Some History of the Conjugate Gradient and Lanczos Algorithms”:1948–1976, SIAM Review 31 (1989), no. 1, pp50–102.
8. Magnus R. Hestenes, “Iterative Methods for Solving Linear Equations”, Journal of Optimization Theory And Applications 11 (1973), no. 4, pp323–334.
9. Web links: http://en.wikipedia.org
10. Lynn Powell, Power System Load Flow Analysis, McGraw Professional Engineering Series.
11. Onoda Pessanha, Jose Eduardo; Portugal, Carlos Enrique; and Saavedra, Osvaldo R. (2011) "An Efficient Reordering Technique for Incomplete Factorization GMRES Preconditioning: Application in Load Flow Problems," International Journal of Emerging Electric Power Systems: Vol. 12: Iss. 2, Article 4.
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158-161
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29.
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Authors:
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Jagannath Samanta, Bishnu Prasad De, Banibrata Bag, Raj Kumar Maity
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Paper Title:
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Comparative study for delay & power dissipation of CMOS Inverter in UDSM range
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|
Abstract: Delay and power are two major issues in design and synthesis of VLSI circuits which depends on different design parameters. In this paper, the relative study of propagation delay and power consumption of UDSM CMOS inverter is found considering the channel length below 100nm. The simulation results are taken for different technology (32nm, 45nm, 65nm and 90nm) with the help of Tanner (T-spice) simulation tool. The values of model parameters are used from current Berkeley Predictive Technology Model (PTM). Also the results are analyzed by varying load capacitance, supply voltage & transistor widths.
Keywords: UDSM, T-Spice, BPTM, Delay, Power dissipation, PDP, CMOS Inverter.
References:
1. A. Ghosh, D. Ghosh, “Optimization of Static Power, Leakage Power and Delay of Full Adder Circuit Using Dual Threshold MOSFET Based Design and T-Spice Simulation” IEEE Computer society, Advances in Recent Technologies in Communication and Computing, 2009, PP-903-905.
2. T. Sakurai and A.R. Newton, “Alpha-power Law MOSFET Model and its applications to CMOS Inverter Delay and Other Formulas”, IEEE J. Solid-state circuits, vol. 25, no.2, pp. 584-594, April 1990.
3. T. Sakurai, A. R. Newton, “Delay analysis of series-connected MOSFET circuits”, IEEE J. Solid-State circuits, vol. 26, pp. 122-131, Feb. 1991.
4. S. H. K. Embabi, R. Damdaran, “Delay Models for CMOS, BiCMOS, BiNMOS circuits and their applications for timing simulations”, IEEE trans. Computer-Aided Design, vol. 13, pp. 1132- 1142, Sept. 1994.
5. L. Bisdounis, S. Nikolaidis and O. Koufopavlou, “Analytical Transient Response and Propagation Delay Evaluation of the CMOS inverter for short-channel Devices”, IEEE J. Solid-state Circuits, vol. 33, no. 2, pp. 302-306, February 1998.
6. V. Adler and E. G. Friedman, “Delay and Power Expressions for a CMOS Inverter driving a Resistive-Capacitive Load”, Proc. of IEEE Int. Symp. On Circuits and systems (ISCAS), pp. 101-104, 1996.
7. F. Dartu, N. Menezes, J. Qian, and L.e T. Pillage,” A Gate-Delay model for High-Speed CMOS circuits”, Proc. ACM/IEEE Design Automation Conference, pp. 576-580, 1994.
8. ASU, Berkeley Predictive Technology Model (BPTM) Dept. of EE, Arizona State Univ., Tempe, AZ, 2006 [Online].
9. W. Liu et al., BSIM3v3.2.2 MOSFET Model – User Manual, Department of Electrical and Computer Engineering, University of California, Berkeley, 1999.
10. X. Xi et al., BSIM4.6.1 MOSFET Model – User Manual, Department of Electrical and Computer Engineering, University of California, Berkeley, 2007.
11. S. Dutta, Shivaling S. M Shetti, and Stephen L. Lusky, “A Comprehensive Delay Model for CMOS Inverters” IEEE Journal of Solid-State Circuits, Vol. 30, No. 8,
August 1995.
12. T. Sakurai. and R. Newton. "A simple short-channel MOSFET model and its application to delay analysis of Inverters and series-connected MOSFETs," Proceedings of IEEE International Conference on Circuits and Systems, pp. 105-108. 1990.
13. A.I. Kayssi, K.A. Sakallah, and T. M. Burks, “Analytical Transient Response of CMOS Inserters,” IEEE transactions on Circuits and Systems-I CAS I-39, 42 (1992).
14. C. Datta, M. Datta, S. Sahoo, R. Kar, “A Closed Form Delay Estimation Technique for High Speed On-Chip RLC Interconnect Using Balanced Truncation Method”, IEEE International Conference on Devices and Communications (ICDeCom-11), Feb 24-25, 2011, pp. 1-4, BIT Mesra, India.
15. Makram M. Mansour, Mohammad M. Mansour, Amit Mehrotra, “Modified Sakurai-Newton Current Model and its applications to CMOS Digital Circuit Design”, Proceedings of the IEEE Computer Society Annual Symposium on VLSI (ISVLSI’03).
16. Hamoui and N. Rumin, “An analytical model for current, delay and power analysis of submicron CMOS logic circuits, “IEEE Trans. Circuits Syst.-II: Analog and Digital Signal_Processing, vol. 47, pp. 999-1007, Oct. 2000.
17. L. Bisdounis, S. Nikolaidis, and O. Koufopavlou, “Analytical transient response and propagation delay evaluation of the CMOS for short-channel devices,” IEEE Journal of Solid State Circuits, vol. 33 ,pp. 302-306, Feb. 1998.
18. B Amelifard, M Taherzadeh Sani, H Iman-Eini and A. Kush, “Delay and power estimation of CMOS inverters” 11th ICEE, May 2003, Vol. 1, pp-458-464.
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162-167
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30.
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Authors:
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S. K. Mandal, G. K. Mahanti, Rowdra Ghatak
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Paper Title:
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Genatic Algorithm for Reducing the Side Lobe Level of Main Beam of Uniformly Excited Time Modulated Linear Array Antenna
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Abstract: The Side Lobe Level (SLL) of the main beam of a uniformly excited time modulated antenna array is reduced to less than -55 dB by using Genetic Algorithm (GA). For a uniformly excited linear antenna array the maximum side lobe level is ~ -13.5 DB. In this work the uniformly excited antenna array is first time modulated and then the on-time sequences of each of the array elements are optimized by applying GA to get the desired result.
Keywords: Time Modulated Linear Array (TMLA), Side lobe level (SLL), Side band radiation (SBR), Genetic Algorithm (GA).
References:
1. Constantine A. Balanis,”Antenna Theory Analysis and Design”, A John Wiley & Sons, Inc., Publication, 3rd edition.
2. Shanks H. E., “A New Technique for Electronic Scanning”, IEEE Trans.on Antennas and Prop., March, 1961, vol -9, pp.162–166.
3. Kummer W.H., Villeneuve A.T., Fong T.S., Terrio F.G., “Ultra-low side-lobes from time-modulated arrays”, IEEE Trans. Antennas Prop., 1963, 11, (6), pp. 633–639.
4. Yang S., Gan Y.B., Qing A, “Sideband suppression in time-modulated linear arrays by the differential evolution algorithm”, IEEE Antennas Wireess. Prop. Lett., 2002, 1, pp. 173–175
5. Fondevila J., Bre´ Gains J.C., Ares F., Moreno E., “Optimizing uniformly excited linear arrays through time modulation”, IEEE Antennas and Prop. vol. 56, No. 6, June 2008, pp. 1799–1804
6. Bregains J. C., Fondevila – Gomez J., Franceschetti G., and Ares F.,”Signal Radiation and Power Losses of Time Modulated Arrays, IEEE Trans. Antennas Prop., 2005, 53, (7), pp. 2337–2339
7. L. Manica, P. Rocca, L. Poli, and A. Massa, “Almost time-independent performance in time-modulated linear arrays,” IEEE AntennasWireless Propag. Lett., vol. 8, pp. 843–846, 2009.
8. Tong Y and Tennant A., “Simultaneous control of side lobe level and harmonic beam steering in time modulated linear arrays”, Electronics Letters, 4th February 2010, vol. 46, No.3
9. Ertugrul Aksoy and Erkan Afacan, “Thinned Nonuniform Amplitude Time-Modulated Linear Arrays,” IEEE Antennas and Wireless Prop. Lett., vol. 9, 2010.
10. Li G., Yang S., Chen Y., and Nie Z., “A Novel Electronic Beam Steering Technique in Time Modulated Antenna Arrays”, Progress In Electromagnetics Research, PIER 97, 391 – 405, 2009.
11. A. Tennant,”Experimental Two-Element Time-Modulated Direction Finding Array”, IEEE Antennas and Prop. vol. 58, No. 3, March -2010, pp. 986–988.
12. David E. Goldberg, Genetic Algorithms in Search, Optimization & Machine Learning, Pearson Education Asia, Fourth edition.
13. R. L. Haupt, “An Introduction to Genetic Algorithms for Electromagnetics”, IEEE AP Magazine, vol. 37, No. 2, April 1995.
14. Y. J. Cao and Q. H. Wu,”Teaching Genetic Algorithm Using MATLAB”, Int. J. Elect. Enging Educ., vol. 36, pp 139 – 153.
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168-172
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31.
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Authors:
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Subhajit Das, Sandip Bhattacharya, Debaprasad Das
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Paper Title:
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Design of Digital Logic Circuits using Carbon Nanotube Field Effect Transistors
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Abstract: The work in this paper designs the basic logic circuits using the carbon nanotube field effect transistor (CNTFET). CNTFET is a novel device that is projected to outperform scaled CMOS technologies. CNTFET-based devices offer high mobility for near-ballistic transport, high carrier velocity for fast switching, as well as better electrostatic control due to the quasi one-dimensional structure of carbon nanotubes. CNTFET utilizes a semiconducting carbon nanotube (CNT) channel controlled by isolated electrostatic gates. It demonstrates p-type or n-type switching behavior depending upon the polarity-gate voltage. In this paper ambipolar CNTFETs are used to design basic logic circuits. The datapath logic blocks like half and full-adders are designed and their performances have been investigated.
Keywords: Carbon nanotube (CNT), CNT field-effect transistor (CNTFET), Transmission gate (TG), Verilog-AMS.
References:
1. International Technology Roadmap for Semiconductors (ITRS) reports, http://www.itrs.net/reports.html
2. Hong Li, Chuan Xu, Navin Srivastava, and Kaustav Banerjee, “Carbon Nanomaterials for Next-Generation Interconnects and Passives: Physics, Status, and Prospects”, IEEE Trans. Electron Devices, vol. 56, no. 9, Sep, 2009.
3. Ali Javey, Jing Guo, Qian Wang, Mark Lundstrom, and Hongjie Dai, “Ballistic carbon nanotube field-effect transistor,” Nature, vol. 424, pp. 654-657, 2003.
4. J. Guo, A. Javey, H. Dai, and M. Lundstrom, “Performance analysis and design optimization of near ballistic carbon nanotube FETs,” IEDM Tech. Digest, pp. 703-706, 2004.
5. R. Saito, G. Dresselhaus, and M. S. Dresselhaus, Physical Properties of Carbon Nanotubes. London: Imperial College Press, 1998.
6. Y.-M. Lin, J. Appenzeller, and P. Avouris, “Novel carbon nanotube FET design with tunable polarity,” Proc. Electron Devices Meeting, pp. 687– 690, 2004.
7. Yu-Ming Lin, J. Appenzeller, J. Knoch, and P. Avouris, “High-performance carbon nanotube field-effect transistor with tunable polarities,” IEEE Trans. Nanotechnology, vol. 4, no. 5, pp. 481–489, Sep. 2005.
8. A. Raychowdhury, S. Mukhopadhyay, and K. Roy, “A circuit-compatible model of ballistic carbon nanotube field-effect transistors”, IEEE Trans. Computer-Aided Design of Integrated Circuits and Systems, vol. 23, no. 10, pp. 1411–1420, Oct. 2004.
9. J.W. Mintmire and C.T. White, “Universal density of states for carbon nanotubes,” Phys, Rev. Lett., vol.81, no.12, pp. 2506-2509, 1998.
10. I. O’Connor, et al., “CNTFET modeling and reconfigurable logic-circuit design,” IEEE Trans. Circuits and Systems I: Regular Papers, vol. 54, no. 11, pp. 2365–2379, Nov. 2007.
11. S. Das, S. Bhattacharya and D. Das, “Modeling of carbon nanotube based device and interconnect using VERILOG-AMS”, Proc. Int. Conf. on Advances in Recent Technologies in Communication and Computing, pp. 51-55, Sep. 2011.
12. S. Das, S. Bhattacharya, D. Das, “Design of Transmission Gate Logic Circuits using Carbon Nanotube Field Effect Transistors”, Proc. National conference on Advanced Communication Systems and Design Techniques, pp. 75-78, Nov. 2011.
13. S. Das, S. Bhattacharya, D. Das, “Performance Evaluation of CNTFET-based Logic Gates using Verilog-AMS”, Proc. National Conference on Electronics, Communication and Signal Processing, pp. 85-88, Sep. 2011.
14. Verilog-AMS language reference manual.
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173-178
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32.
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Authors:
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Niladri Mandal, Souragni Ghosh
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Paper Title:
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A Modified Fast FFT Algorithm for OFDM Based Future Wireless Communication System
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|
Abstract: The limited available spectrum and the inefficiency in the spectrum usage in a fixed spectrum assignment policy, demands a new communication prototype to exploit the existing wireless spectrum opportunistically. This new networking paradigm is referred to as next generation networks as well as Dynamic Spectrum Access (DSA) and cognitive radio networks. The Fast Fourier Transform (FFT) and its inverse (IFFT) are very important algorithms in signal processing, software-defined radio, and the most promising modulation technique i.e. Orthogonal Frequency Division Multiplexing (OFDM). From the standard structure of OFDM we can find that IFFT/FFT modules play the vital role for any OFDM based transceiver. So when zero valued inputs/outputs outnumber nonzero inputs/outputs, then general IFFT/FFT algorithm for OFDM is no longer efficient in term of execution time. It is possible to reduce the execution time by “pruning” the FFT. In this paper we have implemented a novel and efficient input zero traced FFT pruning (IZTFFTP) algorithm based on DIF radix-2 technique. Compare to other algorithms, the results of IZFFTP shows that it is independent of the position of the zero valued input and also maintaining a good trade-off between time and space complexity of any system by not only reducing the number of complex multiplication as well as complex additions also. The proposed algorithm is implemented in high level computer program i.e. in C++and this is similar to the Cooley-Tukey radix-2 FFT algorithm, retaining all the key features such as simplicity and regularity, by making some alternation and programming modification.
Keywords: Cognitive radio, OFDM, FFT, Pruning Techniques, Execution time.
References:
1. J. Mitola, III, "Cognitive Radio: An Integrated Agent Architecture for Software Defined Radio," Thesis (PhD), Dept. of Teleinformatics, Royal Institute of Technology (KTH), Stockholm Sweden, May 2000.
2. J. D. Poston and W. D. Horne, “Discontinuous OFDM considerations for dynamic spectrum access in idle TV channels,” inProc. IEEE Int. Symp. New Frontiers Dynamic Spectra. Access Networks, vol. 1, (Baltimore, MD, USA), pp. 607–610, Nov.
3. R. Rajbanshi, A. M. Wyglinski, and G. J. Minden, Cognitive Radio Communication Networks, ch. 5. Springer-Verlag, 2007.
4. J. D. Markel, “FFT Pruning,” IEEE Trans. Audio Electroacoust., vol. 19, pp. 305 – 311, Dec. 1971.
5. D. P. Skinner, “Pruning the Decimation in time FFT algorithm,” in Proc. IEEE Int. Conf.Acoust., Speech, Signal Process., vol. 24, Apr. 1976, pp.193 – 194
6. T. V. Sreenivas and P. Rao, “FFT algorithm for both input and output Pruning,” in Proc.IEEE Int. Conf. Acoust., Speech, Signal Process, vol. 27, June 1979, pp. 291 – 292.
7. R. G. Alves, P. L. Osorio, and M. N. S. Swamy, “General FFT Pruning Algorithm,” in Proc.43rd IEEE Midwest Symp. Circuits and Systems, vol. 3, Aug. 2000, pp. 1192 – 1195.
8. H. V. Sorensen and C. S. Burrus, “Efficient computation of the DFT with only a subset of input or output points,” IEEE Trans. Signal Processing, vol. 41, pp. 1184 – 1200, Mar. 1993.
9. E. Oran. Brigham, "The Fast Fourier Transform and Its Applications" Prentice Hall Publication, 1988, ISBN: 0133075052.
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179-184
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33.
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Authors:
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Tamasi Moyra, Susanta Kumar Parui, Santanu Das
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Paper Title:
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Design of High Quality Factor and Harmonic Reduced Bandpass Filter Using Coupled Resonators and Defected Ground Structures
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|
Abstract: Design of good quality factor and high selective Band pass filter (BPF) is an emerging challenge of microwave engineers in modern RF, microwave and millimeter wave communication systems. Front end of the receiver in a communication system demands high performance BPF to select the required signal from the unwanted adjacent signals with improved selectivity. In this paper one end coupled Band pass filter with centre frequency 2GHz and 30% Fractional Bandwidth (FBW) at -20 dB has been designed with rectangular split ring coupled resonators forming with conventional Microstrip transmission line. This designed BPF has been simulated with the help of MoM besed IE3D electromagnetic simulation software. The proposed BPF provides first unwanted harmonic or spurious nearer to the twice of its passband centre frequency and some other higher harmonics at different higher frequencies. Therefore, in this paper attention also has been given towards the suppression of harmonics with the help of Defected Ground Structures (DGS) in addition with the proposed coupled microstrip BPF. Finally, one novel BPF has been designed for Satellite, GPS and Bluetooth applications of modern wireless communication systems.
Keywords: Microstrip, coupled resonator, defected ground structure, elliptical, bandpass filter, Q-factor, selectivity.
References:
1. C.S.Kim, J.S.Park, D.Ahn and J.B. Lim, “A novel one dimensional periodc defected ground structure for planar circuits,” IEEE Microwave and Guided wave Letters, vol. 10, No. 4, pp.131-133, 2000.
2. D. Ahn, J.S.Park, C.S.Kim, J.Kim, Y Qian and T. Itoh, “A design of the lowpass filter using the novel microstrip defected ground structure,” IEEE Trans. on Microwave Theory and Techniques, vol. 49, no. 1, pp. 86-93, 2001
3. Lim J., Kim C., Lee Y., Ahn D., and Nam S., “Design of lowpass filters using defected ground structure and compensated microstrip line,” Electronics Letter, vol. 38, no. 25, pp. 1357-1358, 2002
4. A. Abdel-Rahman, A.K. Verma, A. Boutejdar, and A.S. Omar, “Control of bandstop response of Hi-Lo microstrip lowpass filter using slot in ground plane,” IEEE Trans. On Microwave Theory Tech., vol .52, no. 3, pp. 1008-1013, March 2004
5. M.K.Mandal and S.Sanyal, “A novel defected ground structure for planar circuits,” IEEE Microwave and Wireless Comp. Lett., vol. 16, no. 2, pp.93-95, Feb. 2004
6. Chen J.-X., Li J.-L., Wan K.-C. and Xue Q., “Compact quasi-elliptic function filter based on defected ground structure,” IEE Proc.-Microwave Antennas propagation, vol . 153, no. 4, pp. 320-324, Aug. 2006
7. Susanta Kumar Parui, Santanu Das “Performance enhancement of microstrip open-loop resonator bandpass filter by defected ground structures,” Proc. of International Workshop on Antenna Technology, Cambridge, U.K. (iWAT-07), pp.483-486, March, 2007
8. Susanta Kumar Parui, Santanu Das ‘An asymmetric defected ground structure with elliptical response and its application as a lowpass filter’ Int. J. Electron. Commun. (AEÜ) vol. 63 ,pp.483 – 490, 2009
9. Parui, Susanta Kumar, Moyra, Tamasi and Das, Santanu “Quasi-elliptic filter characteristics of an asymmetric defective ground structure,” International Journal of Electronics, Vol.-96, No.-9, PP-915-924. September 2009.
10. Tamasi Moyra, Susanta Kumar Parui and Santanu Das “Application of a Defected Ground Structure and Alternative Transmission Line for Designing a Quasi-elliptic Lowpass Filter and Reduction of Insertion Loss” International Journal of RF and Microwave Computer-Aided Engineering , Vol.-20, No.-6, PP-882-888 November 2010.
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185-188
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34.
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Authors:
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S. Sarkar, A. Ray, M. Kahar, S. Biswas, D. Sarkar, P. P. Sarkar
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Paper Title:
|
Study of Frequency Tuning Characteristic of a Micro-strip Patch Antenna Operating at Dual Resonant Frequency, by Modifying the Slot, Loaded in the Ground Plane
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|
Abstract: In this paper, the tuning characteristic of a rectangular microstrip patch antenna has been studied. It has been shown, how the variation of length of the slot embedded in the ground plane results in shifting of resonant frequency. The antenna mentioned in this paper operates at two resonant frequencies. By modifying the length of the embedded slot, the ratio of the higher resonant frequency to the lower frequency can be varied from 2.03 to 1.In actual case it has been found that one of the resonant frequency remains fixed irrespective of the slot length. If the ratio of this fixed frequency to the tunable resonant frequency is considered, then the ratio can be varied from 2.03 to 0.7 by varying the slot length.
Keywords: Antenna, frequency tuning, microstrip, multiband.
References:
1. Kin-Lu Wong; Kai-Ping Yang; , "Small dual-frequency microstrip antenna with cross slot," Electronics Letters , vol.33, no.23, pp.1916-1917, 6 Nov 1997
2. Kin-Lu Wong; Kai-Ping Yang; , "Compact dual-frequency microstrip antenna with a pair of bent slots ," Electronics Letters , vol.34, no.3, pp.225-226, 5 Feb 1998
3. Lau, K.L.; Kong, K.C.; Luk, K.M.; , "A Miniature Folded Shorted Patch Antenna for Dual-Band Operation ," Antennas and Propagation, IEEE Transactions on , vol.55, no.8, pp.2391-2398, Aug. 2007
4. Kan, H.K.; Waterhouse, R.B.; Lee, A.Y.J.; Pavlickovski, D.; , "Investigation of small dual-frequency spiral-like printed antennas for mobile communication," Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, 2005. MAPE 2005. IEEE International Symposium on , vol.1, no., pp.254-257 Vol.
1, 8-12 Aug. 2005
5. Boccia, L.; Amendola, G.; Di Massa, G.; , "A dual frequency microstrip patch antenna for high-precision GPS applications," Antennas and Wireless Propagation Letters, IEEE , vol.3, no.1, pp.157-160, Dec. 2004.
6. Xiaoxiang He; Sheng Hong; Huagang Xiong; Qishan Zhang; Tentzeris, E.M.M.; , "Design of a Novel High-Gain Dual-Band Antenna for WLAN Applications," Antennas and Wireless Propagation Letters, IEEE , vol.8, no., pp.798-801, 2009.
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189-191
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35.
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Authors:
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Somnath Maiti, Abhik Roy, Tirtha Sankar Das, Subir Kumar Sarkar
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Paper Title:
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OFDM Based High Capacity Information Hiding in Grey Scale Image
|
|
Abstract: This paper proposes a robust information hiding method by utilizing the spectrum efficient OFDM technique applied on gray scale image onto another gray carrier image. For simplicity, the data mapping in complex domain we have used 4-QAM. A modified QIM technique for data embedding is used for improving robustness. But the robustness analysis is not a common practice for QIM based data hiding. The result shows a large amount of information hiding capability along with substantial improvement in robustness against intentional impairments. But the possibility of using OFDM technique in robust high capacity data hiding has drawn a very little attention to the researchers even today.
Keywords: OFDM, QIM, QAM, Capacity, Robustness.
References:
1. I.J. Cox, J. Kilian, F.T. Leighton et al, “Secure Spread Spectrum Watermarking for Multimedia”, IEEE Transactions on Image Processing, 1997 6 (12):167321687.
2. B.Chen and G.W.Ornell, “Quantization Index Modulation Methods for Digital Watermarking & Information Embedding of Multimedia”, Journal of VLSI Signal Processing 27, 7-33, 2001.
3. B. Chen and G. W. Wornell, “Quantization index modulation: A class of provably good methods for digital watermarking and information embedding”, IEEE Trans. Inform. Theory.
4. Ahmed R.S. Bahai, Burton R. Saltzberg, Mustafa Ergan, “Multicarrier Digital Communications Theory and Applications of OFDM”, Springer Science & Buisness Media, 2004, ISBN: 0-387-22575-7.
5. D.K. Arrowsmithv and C.M.Place, “An Introduction to Dynamical systems”, Cambridge Univ.Press (1990).
6. C.S. Lu, “Multimedia Security: Steganography and Digital Watermarking Techniques for Protection of Intellectual Property”, 1st Edn., Idea Group Publishing, Taiwan, ROC, ISBN: 10: 1591401925, pp: 350, 2005..
7. Fan Tie-sheng, Xue Jian-sheng, Xuan Wei-hong, Qu Da-peng, “OFDM Information Hiding Method by Preposition Embedded QIM”, CIMCA 2008, IAWTIC 2008 and ISE 2008.
8. Anamitra Makur, S. SethuSelvi, “Variable dimension vector quantization based image watermarking”, Signal Processing 81 (2001) 889-893.
9. Hsien-Chu Wu, Chin-Chen Chang, “A Novel Digital Image Watermarking Scheme based on The Vector Quantization Technique”, Computers & Security (2005) 24, 460-471.
10. Hideki Noda, MichiharuNiimi and Eiji Kawaguchi, “High-Performance JPEG Steganography using Quantization Index Modulation in DCT Domain, , Pattern Recognition Letters 27 (2006) 455–461.
11. A. Ouled Zaid, A. Makhloufi, A. Bouallegue and C. Olivier, “Improved QIM-based Watermarking Integrated to JPEG2000 Coding Scheme”, SIViP (2009) 3:197–207, DOI 10.1007/s11760-008-0094-z
12. Chin-Chen Chang and Wen-Chuan Wu, “Reversible Quantization-Index Modulation Using Neighboring Correlation”, IWDW 2007, LNCS 5041, pp. 222–232, 2008.
13. Mahalingam Ramkumar, Ali N. Akansu and A Aydan Alatan, “A Robust Data Hiding Scheme for Images using DFT”, In Proceedings of ICIP (2)'1999. pp. 211-215.
14. Jinhua Liu, Kun She, and William Zhu, “Using Wavelets and Independent Component Analysis for Quantization Index Modulation Watermarking”, Springer-LNCS 5589, pp. 555–562, 2009.
15. Xianfeng Zhao, Bingbing Xia, and Yi Deng, “Strengthening QIM-based Watermarking by Non-uniform Discrete Cosine Transform”, LNCS 5284,pp.309–324,2008
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192-195
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36.
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Authors:
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Raj Kumar Maity, Jagannath Samanta
|
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Paper Title:
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Construction and Performance Studies of a Pseudo-Orthogonal Code for Fiber Optic CDMA Lan
|
|
Abstract: A pseudo-orthogonal prime sequence code and a modified prime sequence code using the elements of Galoi’s Field (GF) for a particular prime number have been developed. Bit-error rate performances using Gaussian approximation technique have been made. The capacities of the prime sequence codes are determined. Detailed simulation results on the performance of the codes are presented. The codes are useful for medium access in fiber optic CDMA LAN.
Keywords: Galoi’s Field, Prime Code, OOC , CDMA, FO-CDMA , S/CDMA.
References:
1. P. R. Prucnal, et al. "Spread spectrum fiber-optic local area network using optical processing," J. Lightwave Technol., vol. LT-4, pp. 547-554, May 1986.
2. P. R. Prucnal, et al. "Ultra-fast all-optical synchronous multiple access fiber networks," IEEE J. Select. Areas Com.., vol. SAC-4, pp. 1484-1493, Dec. 1986.
3. J. A. Salehi, "Code division multiple-access techniques in optical fiber networks"-Part I & Part-II: IEEE Trans. Com., vol. 37, pp. 824-833, 834- 842 Aug. 1989.
4. P. A Perrier and P. R. Prucnal, ''Wavelength-division integration of services in fiber optic networks,'' Int. J. Digital Analog Cabled Syst.., vol. 1, no. 3, pp. 149-157, Aug. 1988.
5. F. R. K. Chung, et al "Optical orthogonal codes: Design, analysis, and applications," IEEE Trans. inform. Theory, vol. 37, pp. 595-604, May1989.
6. W C Kwong et al '' Performance comparison of asynchronous and synchronous code division multiple access techniques for fiber optic local area networks'', IEEE Trans. Com., vol. 39, No. 11, pp. 1625-1634, Nov 1991.
7. M. Azizog et al "Optical CDMA via temporal codes," IEEE Trans. Com., vol. 40, pp. 1162-1170, July 1992.
8. S. Zahedi and J.A. Salehi, Analytical comparison of various fiber- optic CDMA receiver structures," IEEE J. Lightwave Technol., vol. 18, pp. 1718-1727, Dec. 2000
9. Tung-Wah et al., "Optimizing Spectral Efficiency in Multiwavelength Optical CDMA System " IEEE Trans. On Comm. Vol.51,No.9,Sep-2003.
10. E.S.Shivaleela,et al.,,"Two dimensional optical orthogonal codes for?ber-optic CDMA networks," .Lightwave Technol.,vol.23,no.2,pp.647-654,Feb2005.
11. Chao-Chin Yang, "Optical CDMA Passive Optical Network Using Prime Code" , IEEE Photonics Tech. letter, Vol-19 No-7, pp. 516-518, April-2007.
12. Chien-Hung Hsieh et al. "Multilevel Prime Codes for Optical CDMA Systems" , Journal of Optical Comm. & net., Vol-1, No-7, pp.-600-607, 2009
13. H Fadhil et al. "Performance of OCDMA Systems Using Random Diagonal Code for Different Decoders Architecture Schemes " The International Arab Journal of Information Technology, Vol. 7, No. 1, January 2010.
14. Cho-Cheng Sun et al. "Extended Multilevel Prime Codes for Optical CDMA", IEEE Trans. On Comm.Vol. 58 No. 5, pp. 1344-1350, May -2010.
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196-201
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37.
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Authors:
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D.R.Godara, S.K.Modi, Rupesh Kumar Rawat
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Paper Title:
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Study of Millimeter Wave Scattering from Ground & Vegetation at 35 GHz
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|
Abstract: In the present work, a measurement study is undertaken to quantify the attenuation caused due to tree canopies, at 35 GHz. Now when the frequency is increased the attenuation is increased but there is a less attenuation atmosphere window at 35 GHz. So if the devices having the working frequency near about 35 GHz is taken then communication will be effective. It becomes necessary to study the microwave attenuation & Scattering due to Desert foliage & ground. In this investigation, the behavior of wave propagation through coniferous tree, ground & obstacles stands at 35 GHz is characterized Both theoretically and experimentally. An outdoor measurement system will be setup and used for characterizing the channel behavior at 35 GHz.
Keywords: 35 GHz.
References:
1. Anderson, 1. Rappaport, T.; and Yoshida, S. "Propagation Measurements and Models for Wireless Communications Channels." IEEE Communications Magazine, January 1995.
2. Propagation study of Millimeter Wave Based on Rain Attenuation at 35 GHz Measured in Western Rajasthan, ICRS-2010, Jodhpur by Dr. M.M.Sharma, D.R.Godara, Sandeep Rankawat.
3. CCIR, Influences of terrain irregularities and vegetation on troposphere propagation," CCIR Report, 235-236, Geneva, 1986.
4. Koh, I. S., F. Wang, and K. Sarabandi, Estimation of coherent ¯eld attenuation through dense foliage including multiple scattering," IEEE Trans. Geosci. Remote Sensing, Vol. 41, No. 5, 1132-1135, 2003.
5. Wang, F. and K. Sarabandi, An enhanced millimeter-wave foliage propagation model," EEE Trans. Antennas Propag. Vol. 53, No. 7, 2138-2145, 2005.
6. Wang, F. and K. Sarabandi, A physics-based statistical model for wave propagation through foliage," IEEE Trans. Antennas Propag. Vol. 55, No. 3, 958-968, 2007.
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202-204
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38.
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Authors:
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Kamini Maheshwar, Sapna Bagde, Deshraj Ahirwar
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Paper Title:
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Application Based Detection Technique for Secure Mobile Ad-hoc Network
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|
Abstract: An ad-hoc network is often defined as an infrastructure less network, meaning a network without the usual routing infrastructure like fixed routers and routing backbones. Typically, the ad-hoc nodes are mobile and the underlying communication medium is wireless. In mobile ad-hoc networks, the data tends to be intercepted by malicious node when using a single path for transmission. Also, the wireless channel in a mobile ad-hoc network is accessible to both legitimate network users and malicious attackers. So, the task of finding good solutions for these challenges plays a critical role in achieving the eventual success of mobile ad-hoc networks. In this paper, we proposed an efficient monitoring technique that uses readily available information from different layers of the protocol stack to detect “malicious packet-dropping”, where a faulty node silently drops packets destined for some other node. A key source of information for this technique is the messages used by the special ad-hoc routing protocols. This technique can be deployed on any single node in the network without relying on the cooperation of other nodes, easing its deployment. Our simulation results show that proposed technique has good detection effectiveness across a wide variety of network mobility models.
Keywords: MANET, Secure Routing Protocol, Monitoring Detection Technique.
References:
1. S.Tamilarasan and Dr.Aramudan, “A Performance and Analysis of Misbehaving node in MANET using Intrusion Detection System”, IJCSNS International Journal of Computer Science and Network Security, VOL.11 No.5, May 2011, pp 258-264.
2. Vijay Kumar, “BEHAVIORAL STUDY OF DYNAMIC ROUTING PROTOCOLS FOR MANET”, International Journal of Computing and Business Research Volume 2 Issue 2 May 2011.
3. G. Rajkumar and K. Duraisamy, “A Fault Tolerant Multipath Routing Protocol to Reduce Route Failures in Mobile Adhoc Networks”, European Journal of Scientific Research, Vol.50 No.3 (2011), pp.394-404
4. Wenchao Huang, Yan Xiong, Depin Chen, “DAAODV: A Secure Ad-hoc Routing Protocol based on Direct Anonymous Attestation”, IEEE 2009 International Conference on Computational Science and Engineering, Issue Date : 29-31 Aug. 2009, Volume : 2 , On page(s): 809.
5. A.H Azni, Azreen Azman, Madihah Mohd Saudi, AH Fauzi, DNF Awang Iskandar, “Analysis of Packets Abnormalities in Wireless Sensor Network” , IEEE 2009 Fifth International Conference on MEMS NANO, and Smart Systems, pp 259-264.
6. Cuirong Wang, Shuxin Cai, “AODVsec: A Multipath Routing Protocol in Ad-Hoc Networks for Improving Security”, IEEE 2009 International Conference on Multimedia Information Networking and Security, pp 401-404.
7. A Nagaraju and B.Eswar, “Performance of Dominating Sets in AODV Routing protocol for MANETs”, IEEE 2009 First International Conference on Networks & Communications, pp 166-170.
8. Sheng Cao and Yong Chen, “AN Intelligent MANet Routing Method MEC”, 2009 Eighth IEEE International Conference on Dependable, Autonomic and Secure Computing, pp 831-834.
9. Zeyad M. Alfawaer and Saleem Al_zoubi, “A proposed Security subsystem for Ad Hoc Wireless Networks”, IEEE 2009 International Forum on Computer Science-Technology and Applications, pp 253-256.
10. Shayesteh Tabatabaei, “Multiple Criteria Routing Algorithms to Increase Durability Path in Mobile Ad hoc Networks”, IEEE 2009 by the Institute of Electrical and Electronics Engineers, Issue Date : 9-12 Nov. 2009, On page(s): 1 , Print ISBN: 978-1-4244-5647-5, INSPEC Accession Number: 11135758.
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205-211
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39.
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Authors:
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Samreen Amir, Manzoor Hashmani, B.S. Chowdhry
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Paper Title:
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A Novel Approach to Change the Breech Presentation of Fetus through Ultrasound
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Abstract: Breech presentation is one of the reasons for infant mortality and neurological disorders. Many conventional methods are being used to address the problem with different success rates and side effects, like External Cephalic Version, Elective C-Section, Moxibustions, gravity manipulation, acupressure, homeopathy, slant board exercise, visualization etc. The most regular way to deliver a breech baby in developed countries like USA, Australia, and Great Britain is Caesarean section and similar to any major surgery, it engross risks that may increase the maternal mortality. To avoid such risks, one solution is to stimulate unborn baby’s reflex action to make him/her change its position. This paper presents a hypothesis to stimulate the fetal movement using ultrasound beam. The radiation force exerted by the ultrasound beam generates an acoustic vibration and the resulting sound can be used as a stimulus to the baby. The critical part in this approach is the transducer design, in this paper a linear ultra-sonic transducer design is studied as a stimulus source. The results show that the platform developed for this study can be effectively used to simulate and select the optimum design of the transducer. Moreover, the field strength plots given in the paper can be used to select the optimum number of transducer element given the required pressure and the focal depth.
Keywords: Breech presentation, Ultrasound transducer
References:
1. Shocking Maternal death rate for women in Pakistan, October 25, 2009 by Baby Chums , Filed under: Baby Health, News, Pregnancy
2. S. Begum, A. Nisa, and I. Begum , “Analysis of Maternal Mortality in A Tertiary Care Hospital to determine causes and Preventable factors,” Journal of Ayub Medical College Abbottabad, Vol. 15(2), 2003, Ayub Medical College, Abbottabad
3. S. Demol, “Breech presentation is a risk factor for intra-partum and neonatal death in preterm delivery’” European Journal of Obstetrics & Gynecology and Reproductive Biology, Vol. 93, Issue 1, Pages 47-51
4. G.J. Hofmeyr and M. Hannah, “Planned caesarean section for term breech delivery,” Cochrane Database of Systematic Reviews 2001, Issue 1. Art. No.: CD000166. DOI: 10.1002/14651858.CD000166
5. F.Golfier, “Planned vaginal delivery versus elective caesarean section in singleton term breech presentation :a study of 1116 cases”, European Journal of Obstetrics & Gynecology and Reproductive Biology, Vol. 98, Issue 2, Pages 186-192
6. “Maternal Newborn and Child Health Program”, Ministry of Health, Government of Pakistan, www.mnch.gov.pk/indicators.php
7. L.R. Gavrilov, “Use of focused ultrasound for stimulation of nerve structures,” Ultrasonics, 22(3), 132–138, 1984.
8. Gavrilov LR, Tsirulnikov EM, Davies I. Application of focused ultrasound for the stimulation of neural structures. Ultrasound Med Biol. 1996;22:179
9. M. Fatemi, A. Alizad, and J. F. Greenleaf, “Characteristics of the audio sound generated by ultrasound imaging systems,” Journal of Acoustical Society of America,
Vol . 117 (3), Pt. 1, March 2005.
10. J.C. Birnholz, and B. R. Benacerraf, “The development of human fetal hearing,” Science, Vol 222, Issue 4623, 516-518, 1983.
11. Bethesda, “Exposure Criteria for Medical Diagnostic Ultrasound: II. Criteria Based on All Known Mechanisms,” National Council on Radiation Protection and Measurements, NCRP Report No. 140 – 2002.
12. S. Arulkumaran, D.G. Talbert, M. Westgren, H.S. Su, and S. Ratnam, “Audible in-utero sound from ultrasound scanner.” Lancet Vol. 338, 704–705. 1991
13. S. Arulkumaran, D.G. Talbert, M. Nyman, M. Westgren, H.S. Su, and S. Ratnam, “Audible in utero sound caused by the ultrasonic radiation force from a real-time scanner,” Journal of Obstetrics and Gynecology Research, Vol. 22(6), 523–527. 1996
14. M. Fatemi, P.L. Ogburn, Jr., and J.F. Greenleaf, ‘‘Fetal stimulation by pulsed diagnostic ultrasound,’’ Journal of Ultrasound in Medcine. Vol. 20, 883–889, 2001.
15. “Nervous System” http://universe-review.ca/R10-16-ANS.htm
16. James, “Physics of hearing” www.antonine-education.co.uk /Physics%20A%20level/Options/Module_6/Topic_3/Topic_3.htm
17. “Refraction artefact”, Ultrasound Technology Information Portal”, http://www.us-tip.com
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212-217
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40.
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Authors:
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Nimisha Singla, Deepak Garg
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Paper Title:
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String Matching Algorithms and their Applicability in various Applications
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Abstract: In this paper the applicability of the various strings matching algorithms are being described. Which algorithm is best in which application and why. This describes the optimal algorithm for various activities that include string matching as an important aspect of functionality. In all applications test string and pattern class needs to be matched always.
Keywords: Databases, Dynamic programming, Search engine, String matching algorithms.
References:
1. Dany Breslauer, Livio Colussi and Laura Toniolo, ‘Tight Comparison Bounds for the String Prefix Matching Problem’, Stiching Mathematisch Centrum, Amsterdam, 1-9, 1992.
2. Richard S. Bird, ‘Polymorphic String Matching’, 110-115, Haskell’05 2005, Tallin, Estonia.
3. C. Jason Coit, Stuart Staniford and Joseph McAlerney, ‘Towards Faster String Matching for Intrusion Detection or Exceeding the Speed of Snort’, 1-7.
4. S. Chen, S. Diggavi, S. Dusad and S. Muthukrishnan, ‘Efficient String Matching Algorithms for Combinatorial Universal Denoising’,1-10.
5. Narendra Kumar, Vimal Bibhu, Mohammad Islam and Shashank Bhardwaj, ‘Approximate string matching Algorithm’, International Journal on Computer Science and Engineering, Vol. 02, No. 03, 2010, 641-644.
6. Yu-lung Lo Chien-Chi Huang, ‘Fault Tolerant Music Retrieval by similar String Matching’, National Science Council of ROC Grant NSC98-2221-E-324-027,1-10.
7. S. Viswanadha Raju and A. Vinayababu. ‘Optimal Parallel algorithm for String Matching on Mesh Network Structure’, International Journal of Applied Mathematical Sciences ISSN 0973-0176 Vol.3 No.2 2006, 167-175.
8. Ahmad Fadel Klaib, Zurinahni Zainol, Nurul Hashimah Ahamed, Rosma Ahmad, and Wahidah Hussin, ‘Application of Exact String Matching Algorithms towards SMILES Representation of Chemical Structure’, World Academy of Science, Engineering and Technology 34 2007,36-40.
9. Venkata Padmavati Metta, Kamala Kritivasan, Deepak Garg, "On String Languages Generated by SN P Systems with Anti-Spikes", International Journal of Foundations in Computer Science, World Scientific May 2011.
10. www.cs.biu.ac.il.
11. Venkaesan T. Chakaravarthy, Rajasekar Krishnamurthy, ‘The Problem of Context Sensitive String Matching’, 1-12
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218-222
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41.
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Authors:
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Mohini Ratna Chaurasia, Nitin Naiyar
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Paper Title:
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Stepper Motor Controller using XC9572 CPLD through Mobile As a Remote
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Abstract: The theory of motion control has evolved since the late 18th century. Simply, motion control is defined as accurately controlling the movement of an object based on speed, distance, load, inertia or a combination of all these factors. Due to high system complexity and difficult software language implementation, the traditional programmable logic controller based motion control systems have gradually been replaced by CPLD based control systems. In my project, the control to a stepper motor system is accomplished from a mobile and an intuitive and easy to use graphical user interface is designed by using VHDL. My paper presents, a hardware implementation of circuit which is designed for a programmable rotational stepper motor using VHDL as a design tool and the CPLD as a target technology. The design is implemented on a XC9572 kit. The advantage of using reconfigurable hardware (CPLD) instead of a PLC, Microprocessor & Microcontroller is that the designer can make modifications to the design easily and quickly, and the total design represents an embedded system. The total programmable hardware design that make control on the stepper motor movement, occupy an area that did not exceed 12% of the chip resources.
Keywords: CPLD, DTMF decoder, PLC, Stepper Motor, VHDL.
References:
1. Zoonubiya Ali and R.V.Kshirsagar “development of a CPLD based novel open loop Stepper motor controller for high performances using VHDL’’ ,978-1-4244-7652-7/10/$26.00©2010 IEEE.
2. Zoonubiya Ali and R.V.Kshirsagar “An open loop stepper motor controller based on CPLD” International Journal of Electronic Engineering Research ISSN 0975 - 6450 Volume 2 Number 2 (2010) pp. 219–228© Research India Publications http://www.ripublication.com/ijeer.htm
3. J. Petrov and S. Strmik, “A Microcomputer-Based Speed Controller for Lift Drives”, IEEE Transactions on Applications, Vol. 24, No. 3, pp. 487 - 498, 1988.
4. T. Kenjo and A. Sugawara, “Stepping Motors And Their Microprocessor Controls Second Edition”, Oxford University Press, 1994.
5. Bae and Krishnan (1996) H. K. Bae and R. Krishnan, “A Study of Current Controllers and Development of a Novel Current Controller for High Performance SRM Drivers,” IEEE Industry Applications Conference, vol. 1, pp. 68-75, Oct.1996.
6. D. O. Carrica, S. A. González, and M. Benedetti, “A high speed velocity control algorithm of multiple stepper motors”, Elsevier, Mechatronics, Vol. 14, Issue 6, pp. 675 – 684, 2004.
7. Xiaoyin Shao and Dong Sun, “Development of an FPGA-BasedMotion Control ASIC for Robotic Manipulators,” IEEE Proceedings of The Sixth World Congress on Intelligent Control and Automation, vol. 2, pp. 8221-8225, Jun. 2006.
8. Ngoc Quy Le and Jae Wook Jeon An Open-loop Stepper Motor Driver Based on FPGA, International Conference on Control, Automation and Systems 2007, Oct. 17-20, 2007 in COEX, Seoul, Korea, 1322-1326
9. Brown and Rose, (1996) Architecture of FPGAs and CPLDs: A Tutorial , Survey published by University of Toronto.
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223-225
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42.
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Authors:
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Dilip Kumar Sarker, Md. Mortuza Ali, Diponkar Kundu, Pallab Kanti Podder, Md. Galib Hasan
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Paper Title:
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Effect of Waveguide Parameters on the Growth Rates in a Solid Beam Driven Plasma Loaded Backward Wave Oscillator
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Abstract: This paper contains results of analytical investigation of a solid beam driven plasma loaded backward wave oscillator. Here, an instability leading to microwave generation involves a process of three-wave interaction. The theory of approximate cubic dispersion equation valid near resonance for annular beam driven vacuum backward wave oscillator (BWO), was derived earlier. In this paper, by extending and modifying this theory is used for investigating the effect of variation of SWS size parameters on the oscillation frequency and growth rates for solid beam driven plasma loaded BWO.
Keywords: BWO, SWS, instability, plasma-loaded, dispersion, corrugated structure.
References:
1. John A. Swegle, “Approximate treatment near resonance of backward and traveling wave tubes in the Comton regime”, Phys. Fluids 28 (12), December 1985, pp. 3696-3702.
2. K. Minami, W. R. Lou, W. W. Destler, R. A. Kehs, V. L. Granatstein and Y. Carmel, “Observation of resonance enhancement of microwave radiation from a gas-filled backward wave oscillator”,Appl. Phys. Lett. 53, 559 (1988).
3. Y. Carmel, K. Minami, R. A. Kehs, W. W. Destler, V. L. Granatstein, D. Abe, and W. R. Lou, “Demonstration of efficiency enhancement in a high power backward wave oscillator by plasma injection”, Phys. Rev. Lett. 62, 2389 (1989).
4. R. Sawhney, “Effect of Plasma on Efficiency Enhancement in a High Power Relativistic Backward Wave Oscillator”, IEEE Trans. on Plasma Science, 1993, vol.21, pp. 609-613.
5. Douglas Yong, Osmu Ishihara, C. Grabowski, J. Gahl, and E. Schamiloglu, “Study of Power Enhancement and Frequency Shifting of Microwave Emission in a Plasma Filled Non-Uniform Backward Wave Oscillator”, IEEE Conference Record-Abstracts, 1998 IEEE ICOPS (June, 1998).
6. B. S. Sharma and N. K. Jaiman, “Numerical investigations on the effect of geometrical parameters on free electron laser instability”, Journal of Plasma Phys. 74: 741-747, Cambridge University Press, July, 2008.
7. Kosuke Otubo, Kazuo Ogura, Mitsuhisa Yamakawa and Yusuke Takashima, “Numerical Analysis of Slow-wave Instabilities in an Oversized Sinusoidally Corrugated Waveguide Driven by a Finitely Thick Annular Electron Beam”, Jpn Soc. of Plasma Sci. & Nuclear Fusion Research, 2010,Vol. 5, S1047.
8. M. M. Ali, K. Ogura, K. Minami, T. Watanabe, W. W. Destler and V. L. Granatstein, “Linear Analysis of a Finite Length Plasma-Filled Backward Wave Oscillator”, Phys. Fluids B4 (4), April, 1992.
9. K. Minami, Y. Carmel, V. L. Granatstein, W. W. Destler, W. R. Lou, D. K. Abe, R. A. Kehs, M. M. Ali, T. Hosokawa, K. Ogura, and T. Watanabe, “Linear Theory of Electromagnetic Wave Generation in a Plasma-Loaded Corrugated-Wall Resonator”, IEEE Trans. Plasma Sci. 18 (1990) 537.
10. M. M. Ali, K. Minami, K. Ogura, T. Hosokawa, H. Kazama, T. Ozawa, T. Watanabe, Y. Carmel, V. L. Granatstein, W. W. Destler, R. A. Kehs, W. R. Lou, and D. K. Abe, “Absolute Instability for Enhanced Radiation from a High-Power Plasma-Filled Backward-Wave Oscillator”, Phys. Rev. Lett. 65 (1990) 855
11. M. M. Ali, K. Minami, S. Amano, K. Ogura, and T. Watanabe, “Linear Analysis of a Localized Plasma-Loaded Backward Wave Oscillator Driven by an Annular Intense
Relativistic Electron Beam”, Journal of Phys. Sci. of Japan, vol.60, no.8, August, 1991, pp. 2655-2664..
12. Kazuo Ogura, Md. Mortuza Ali, Kazuo Minami, SouichiWatanabe, Yoshinori Kan, Yasushi Aiba, Akira Sugawara and Tsuguhiro Watanabe, “Absolute Instability of Low-Frequency Electromagnetic Waves in a Plasma Waveguide with Periodic Boundaries”, Journal of the Physical Society of Japan, vol.61, No.11, November, 1992, pp. 4022-4032.
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226-231
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43.
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Authors:
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CheeFai Tan, Ranjit Singh Sarban Singh, Mohd. Rizal Alkahari
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Paper Title:
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Water Pressure Loss Analysis of Mobile Machine for Fire Fighting Purpose
|
|
Abstract: Fire fighting is risky profession. They are not only extinguishing fires in tall buildings but also must drag heavy hoses, climb high ladders and carry people from buildings and other situations. There are many fire fighters lost their lives in the line of duty each year throughout the world. The statistics of the fire fighter fatalities are still maintain at high level every year and it may continue to increase if there is no improvement in fire fighting techniques and technology. The paper describes the water pressure loss analysis of mobile fire fighting machine prototype.
Keywords: Fire Fighting, Mobile Machine, Pressure Loss Analysis.
References:
1. International Association of Fire Fighters (IAFF), 2000, “Death and Injury Survey, Washington,”Available from: http://www.iaff.org/ HS/PDF/ 2000%20D&I.pdf. Accessed on 5th September 2008.
2. Kyle, S.N. 2007, “NFPA Releases Firefighter Death Study, U.S.A,” Available from: http://cms.firehouse.com/content/section/news. Accessed on 5th September 2008.
3. Rosmuller, N. and Ale, B.J.M., “Classification of fatal firefighter accidents in the Netherlands: Time pressure and aim of the suppression activity,” Journal of Safety Science, No. 46, 2008, pp. 282 –290.
4. Shanghai Qiangshi Fire-fighting Equipment Co. Ltd., 2007, “Qiangshi Fire Fighting Robot, China,” Available from: www.qs119.com/en/ showpro.asp?id=530. Accessed on 5th September 2008.
5. Sofge, E. 2007, “First Firefighting Robots Deployed, Could Spark Autonomous Dept. Las Vegas,” Available from: http://www.popularmechanics.com/science/roboticsl. Accessed on 5th September 2008.
6. Konda, A. “The Fire Fighting Snake Robot. Europe,” Available from: http://www.sintef.com. Accessed on 4th September 2008.
7. HKFSD, “Mobile Fire Fighting Supporting Machine LUF 60R. China,” Available from: http://www.hkfsd.gov.hk/home/images/ equipment/fire/e_luf60.html. Accessed on 13th September 2008.
8. NEVA, “Mobile Fire Fighting Robot. Russia,” Available from: http://www.neva.ru/CNII-RTC/Firemen/html. Accessed on 13th September 2008.
9. Amano, H. “Present Status and Problems of Fire Fighting Robots,” SICE 2002. Proceedings of the 41st SICE Annual Conference, Vol. 2, 2002, page 880- 885.
10. Manual of Firemanship Book 7: Hydraulics, pumps and pump operation, Second Edition, Home Office, Fire Policy Unit, United Kingdom. February 1987.
11. Sturtevant, T.B. “Introduction to Fire Pump Operations”, 2nd Edition, Thompson Delmar Learning Publishing, 2004.
12. Fire Protection Handbook, 19th Edition, Volume 1, National Fire Protection Association, 2003
13. Cote, A.E. “Organizing for Fire and Rescue Services”, Jones & Bartlett Publishers; 1st Edition, Jan. 2003
14. Kemmpler, J. “Fire Fighting Pump and Operation,” Lecture Notes, http://home.honolulu.hawaii.edu/ ~jkemmler/chapter6.htm. Accessed on 13th September 2009.
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232-235
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44.
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Authors:
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C.Kumar, T.Alwarsamy
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Paper Title:
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Solution of Economic Dispatch Problem using Differential Evolution Algorithm
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Abstract: Economic Dispatch is the process of allocating the required load demand between the available generation units such that the cost of operation is minimized. There have been many algorithms proposed for economic dispatch out of which a Differential Evolution (DE) is discussed in this paper. The Differential Evolution (DE) is a population-based, stochastic function optimizer using vector differences for perturbing the population. The DE is used to solve the Economic Dispatch problem (ED) with transmission loss by satisfying the linear equality and inequality constraints. The proposed method is compared with Genetic Algorithm (GA), Particle Swarm Optimization (PSO) and Simulated Annealing (SA).
Keywords: Differential Evolution, Economic Dispatch, Genetic Algorithm, Particle Swarm Optimization, Simulated Annealing.
References:
1. J. Wood and B. F. Wollenberg, Power Generation, Operation and Control, 2nd Edition, New York: John Wiley & Sons, 1996.
2. J. B. Park, K. S. Lee, J. R. Shin and K. Y. Lee, “A particle swarm optimization for economic dispatch with nonsmooth cost functions”, IEEE Trans. on Power Systems, Vol. 8, No. 3, pp. 1325-1332, Aug. 1993.
3. Z. X. Liang and J. D. Glover, “A zoom feature for a dynamic programming solution to economic dispatch including transmission losses”, IEEE Trans. on Power Systems, Vol. 7, No. 2, pp. 544-550, May 1992.
4. K. Deb, “An efficient constraint handling method for genetic algorithms”, Computer Methods in Applied Mechanics and Engineering, Elsevier, Netherlands, 186(2- 4):311–338, 2000.
5. Po-Hung Chen and Hong-Chan Chang, “Large Scale Economic Dispatch by Genetic Algorithm”, IEEE transactions on power systems, vol. 10, no. 4, November 1995.
6. S. O. Orero and M. R. Irving, “Economic dispatch of generators with prohibited operating zones: a genetic algorithm approach”, IEE Pro.- Gener. Transm. Distrib., vol. 143, no. 6, November 1996.
7. J. Kennedy and R. C. Eberhart, “Particle Swarm Optimization”, In Proceedings of 1995 IEEE International Conference on Neural Networks, 4: 1942–1948, Perth, Western Australia, 1995.
8. Zwe-Lee Gaing, “Particle Swarm Optimization to Solving the Economic Dispatch Considering the Generator Constraints”, IEEE transactions on power systems, Vol. 18, No. 3, August 2003.
9. A. Immanuel Selvakumar and K. Thanushkodi, “A New Particle Swarm Optimization Solution to Nonconvex Economic Dispatch Problems”, IEEE transactions on power systems, Vol. 22, No. 1, February 2007.
10. K. P. Wong and C. C. Fung, “Simulated Annealing based Economic Dispatch Algorithm”, Proc. Inst. Elect. Eng., Gen. Transm. and Distrib., vol. 140, no. 6, pp. 509–515, November 1993.
11. Kit Po Wong, “Solving Power System Optimization Problem using Simulated Annealing”, Engineering Applications of Artificial Intelligence, Vol 8, No.6, December 1995.
12. J. Sasikala and M. Ramaswamy, “Optimal λ based Economic Emission Dispatch using Simulated Annealing”, International Journal of Computer Applications, Vol.1,
No.10, 2010.
13. R. Storn and K. Price, “Differential evolution: a simple and efficient adaptive scheme for global optimization over continuous spaces”, Technical Report TR-95-012, Berkeley, USA: International Computer Science Institute, 1995.
14. K. Vaisakh and L. R. Srinivas, “Differential Evolution Approach for Optimal Power Flow Solution”, Journal of Theoretical and Applied Information Technology.
15. Archana Gupta and Shashwati Ray, “Economic Emission Load Dispatch using Interval Differential Evolution Algorithm”, 4th International Workshop on Reliable Engineering Computing (REC 2010), Published by Research Publishing Services.
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236-241
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45.
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Authors:
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J.Hamidi
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Paper Title:
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Application of Multi-Layered Perceptron Neural network (MLPNN) to Combined Economic and Emission Dispatch
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|
Abstract: This paper presents a multi-layered perceptron neural network (MLPNN) method to solve the combined economic and emission dispatch (CEED) problem. The harmful ecological effects caused by the emission of particulate and gaseous pollutants like sulfur dioxide (SO2) and oxides of nitrogen ( NOx ) can be reduced by adequate distribution of load between the plants of a power system. However, this leads to a noticeable increase in the operating cost of the plants. This paper presents the (MLPNN) method applied for the successful operation of the power system subject to economical and environmental constraints. The proposed MLP NN method is tested for a three plant thermal power system and the results are compared with the solutions obtained from the classical lambda iterative technique and simple genetic algorithm (SGA) refined genetic algorithm (RGA) method.
Keywords: Economic dispatch, Emission dispatch, the multi-layered perceptron neural network.
References:
1. Zwe-Lee Gaing, “ Particle swarm optimization to solving the economic dispatch considering the generator constraints, ” IEEE Transactions on Power Systems, vol.18, No.3, pp. 1187-1195, Aug. 2003
2. Ching-Tzong Su, Chien-Tung Lin, “ New Approach with a Hopfield Modeling Framework to Economic Dispatch, ” IEEE Trans.On Power Syst, vol. 15,No. 2, 2000.
3. M. Basu, “ Fuel Constrained Economic Emission Load Dispatch Using Hopfield Neural Networks, ” Electric Power Systems Research 63, 2002 , 51-57.
4. T.Yalcinoz, B.J.Cory, M.J.Short, “ Hopfield Neural Network Approaches To Economic Dispatch Problem, ” Electrical Power and Energy Systems, Vol. 23,No. 6, August 2001 , pp. 435-442(8).
5. T.Yalcinoz, U.Hassan, “ Environmentally Constrained Economic Dispatch via Neural Networks, ” Nigde University, and Nigde 51100, Turkey.
6. H. Altun, T. Yalcinoz, “ Implementing soft computing techniques to solve economic dispatch problem in power systems, ” Expert Systems with Applications in Press, 2007.
7. Y. S. Haruna, “ Comparison of Economic Load Dispatch Using Genetic Algorithm and Other Optimization Methods, ” M. Eng. Degree Thesis, A.T. B. University, Bauchi, Nigeria, 2003.
8. Yalcinoz T., Altun H. and Uzam M., “Economic dispatch solution using a genetic algorithm based on arithmetic crossover, ” IEEE Porto PowerTech2001, Porto, Portugal, 2001.
9. S.M.R Slochanal, Dr M Sudhakaran, “ Application of Refined Genetic Algorithm to Combine Economic and Emission Dispatch, ”, IE (I) Journal.ELvol 85, September 2004.
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242-246
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46.
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Authors:
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Amit Thakkar, Y P Kosta
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Paper Title:
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Survey of Multi Relational Classification (MRC) Approaches & Current Research Challenges in the field of MRC based on Multi-View Learning
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|
Abstract: An increasing number of data mining applications involve the analysis of complex and structured types of data and require the use of expressive pattern languages. Many of these applications cannot be solved using traditional data mining algorithms. This observation forms the main motivation for the multi-disciplinary field of Multi-Relational Data Mining (MRDM). Unfortunately, existing “upgrading” approaches, especially those using Logic Programming techniques, often suffer not only from poor scalability when dealing with complex database schemas but also from unsatisfactory predictive performance while handling noisy or numeric values in real-world applications. However, “flattening” strategies tend to require considerable time and effort for the data transformation, result in losing the compact representations of the normalized databases, and produce an extremely large table with huge number of additional attributes and numerous NULL values (missing values). As a result, these difficulties have prevented a wider application of multi relational mining, and post an urgent challenge to the data mining community. To address the above mentioned problems, this article introduces a multiple view approach—where neither “upgrading” nor “flattening” is required— to bridge the gap between propositional learning algorithms and relational databases and current research challenges in the field of Multi relational classification based on Multi View Learning.
Keywords: Multi Relational Data Mining, Propositional Learning, Multi Relational Classification, Relational Learning.
References:
1. Dr. M. Thangaraj, A Study on Classification Approaches across Multiple Database Relations, International Journal of Computer Applications (0975 –8887) Volume 12– No.12, January 2011.
2. Jing-Feng Guo, An Efficient Relational Decision Tree Classification Algorithm, Third International Conference on Natural Computation (ICNC 2007).
3. Yin, X., Han, J., Yang, J., and Yu, P.S., CrossMine: Efficient Classification across Multiple Database Relations, in Proceedings of the 2004 International conference on Data Engineering (ICDE'04), Boston, MA, 2004.
4. Hongyan Liu, Xiaoxin Yin, and Jiawei Han, “d” , MRDM-2005, Chicago, 2005
5. Arno Jan Knobbe, A Ph.D Theis on Multi relational Data Mining SIKS Dissertation Series No. 2004-15.
6. Amir Netz, Integration of Data Mining and Relational Databases, Proceedings of the 26th International Conference on Very Large Databases, Cairo, Egypt, 2000
7. Andreas Heß and Nick Kushmerick, Iterative Ensemble Classification for Relational Data: A Case Study of Semantic Web Services, 2007
8. Anneleen Van Assche, Improving The Applicability Of Ensemble Methods In Data Mining, PhD Thesis, ISBN 978–90–5682–896–7, Katholieke University Leuven – B-3001 Heverlee (Belgium) 2008.
9. Guo, H., Herna, L., Viktor.. Multirelational classification: a multiple view approach, Knowl. Inf. Systems, vol.17, pp.287–312, Springer-Verlag London. 2008
10. PAN Cao, WANG Hong-yuan,,Multi-relational classification on the basis of the attribute reduction twice, Journal of Communication and Computer, ISSN 1548-7709, USA, Nov. 2009, Volume 6, No.11 (Serial No.60)
11. Christophe Giraud-, Relationships among Learning Algorithms and Tasks, A dissertation submitted to the faculty of Brigham Young University in partial fulfillment of the requirements for the degree of Doctor of Philosophy Brigham Young University, 2011
12. Christine Preisach and Lars Schmidt-Thieme, Relational ensemble classification. In ICDM Conference on Data Mining, pages 499–509,Washington, DC, USA, 2006. IEEE Computer Society..
13. Hongyu Guo, Member, IEEE, and Herna L. Viktor, Member, IEEE, Multi-view ANNs for Multi-relational Classification, 2006 International Joint Conference on Neural Networks Sheraton Vancouver Wall Centre Hotel, Vancouver, BC, Canada,July 16-21, 2006
14. Hongyu Guo and Herna L. Viktor, Mining Relational Data through Correlation based Multiple View Validation, KDD’06, August 20–23, 2006, Philadelphia, Pennsylvania, USA.Copyright 2006 ACM
15. Yun Li, Luan Luan, Multi-relational Classification Based on the Contribution of Tables, International Conference on Artificial Intelligence and Computational Intelligence,2009.
16. Zhen Peng and Lifeng Wu, Research on Multi-Relational Classification Approaches, International Conference on Computational Intelligence and Natural Computing, 2009
17. Miao Zou, Tengjiao Wang,A General Multi-relational Classification Approach Using FeatureGeneration & Selection, Advanced Data Mining & Applications, Lecture Notes in Computer Science,2010,Vol 6441/2010,21-33.
18. Jun He,Hongyan Liu, SELECTING EFFECTIVE FEATURES AND RELATIONS FOR EFFICIENT MULTI-RELATIONAL CLASSIFICATION, International Journal of Computational Intelligence, Volume 26,Issue 3,pages 258-281,2010, Wiley Periodicals, Inc
19. Geeta Manjunath,M Narasimha,Dinkar Sitaram, A heterogeneous Naive Bayesian classifier for relational databases, International Conference on Pattern Recognition, pp 3316-2219,2010.
20. Guo, H., Herna, L., Viktor, Learning from Skewed Class Multi-relational Databases, Fundamenta Informaticae - Progress on Multi-Relational Data Mining Volume 89 Issue 1, January 2009
21. Werner Uwents Neural networks for relational learning: an experimental comparison, Journal Machine Learning Volume 82 Issue 3, March 2011.
22. Sarah Daniel Abdelmessih, Classifiers' Accuracy Prediction based on Data Characterization, Multimedia Analysis and Data Mining Competence Center German Research Center for Artificial Intelligence (DFKI GmbH) Kaiserslautern, Germany, August, 2010.
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247-252
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47.
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Authors:
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S.Muthukrishnan, A.Nirmalkumar
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Paper Title:
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Comparison and Simulation of Open Loop System and Closed Loop System Based UPFC used for Power Quality Improvement
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Abstract: This paper deals with digital simulation of power system using open loop system and closed loop based UPFC to improve the power quality. The UPFC is capable of improving transient stability in a power system. It is the most complex power electronic system for controlling the power flow in an electrical power system. The real and reactive powers can be easily controlled in a power system with a UPFC. The circuit model is developed for UPFC using rectifier and inverter circuits with the help of IGBT and MOSFET. The control angle of the converters is varied to vary the real and reactive powers at the receiving end. The Matlab simulation results are presented to validate the model. The experimental results are compared with the simulation results.
Keywords: UPFC, Power Quality, Statcom, Compensation and matlab simulink
References:
1. C.D. Schaulder et al., “Operation of unified power flow controller (UPFC) under practical constraints’, IEEE Trans.Power Del., vol.13, no.2. pp. 630-639, Apr1998.
2. R.Mihalic et al., “Improvement of transient stability using unified power flow controller’ IEEE Trans.Power Del., vol. 11, no. 1, pp. 485-492, Jan 1996 .
3. J.Machowski et al., Power System Dynamics and Stability. New York: Wiley, 1998.
4. M. Noroozian et al., “ Improving power system dynamics by series-connected FACTS devices,” IEEE trans. Power Del., vol. 139, no.4, pp. 689-694, Oct. 1997.
5. Gyugyi, “ Unified power-flow control concept for flexible AC transmission system,” Proc. Inst. elect. Eng.C, vol. 139, no.4, pp. 323-331, Jul, 1992.
6. N.G. Hingorani and L. Gyugyi, Understanding FACTS. New York: IEEE Press, 2000.
7. E. Gholipour and S.Saadate, “ A new method for improving transient stability of power systems by using UPFC,” in Proc. European Power Electronics, Toulouse, France, Sep. 2003.
8. Z. Huang et al.,”Application of UPFC in interconnected power systems- Modeling, interface, control strategy, and case study, “ IEEE Trans. Power Syst., vol. 15, no. 2, pp. 817-824, May 2000.
9. K. Schoder, A, hasanovic, and A. feliachi, “ Enhancing transient stability using fuzzy control scheme for the unified power flow controller (UPFC) within the power system toolbox (PST),” in proc. Midwest Symp. Circuits Systems, vol. 3, lansing, MI, Aug, 2000, pp. 1382-1385.
10. K.K. Sen and A.J.F. Keri, “Comparison of field results and digital simulation results of voltage-sourced converter-based FACTS controller,” IEEE Trans. Power Del., vol. 18, no. 1, pp. 300-306, Jan. 2003.
11. R.Mohan and R.K.Varma, “ Thyristor based FACTS controllers for electrical systems transmission “, IEEE press, 2000.
12. S.Fakuda, Y.Kubo, “ Introduction to series connected multi converter system ”, IEEE, 2002
13. S. Tara Kalyani, G. Tulasiram Das, (2008) ‘Simulation of real and reactive power flow with UPFC connected to a transmission line’, Journal of Theoretical and Applied Information Technology.
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253-258
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48.
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Authors:
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M Anul Haq, Kamal Jain, KPR Menon
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Paper Title:
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Change Monitoring of Gangotri Glacier using Remote Sensing
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Abstract: Himalayas has one of the largest resources of snow and ice, which act as a freshwater reservoir for all the rivers originating from it. Monitoring of these resources is important for the assessment of availability of water in the Himalayan Rivers. The mapping of Glaciers is very difficult task because of the inaccessibility and remoteness of the terrain. Remote sensing techniques are often the only way to analyze glaciers in remote mountains and to monitor a large number of glaciers in multitemporal manner. This paper presents the results obtained from the analysis of a set of multitemporal Landsat MSS, TM and ETM+ images for the monitoring and analysis of Gangotri Glacier main trunk change. The investigation has shown an overall reduction in glacier area from 63.227 sq km to 62.412 sq km between 1972 and 2010, an overall deglaciation of 1.3% percent. To monitor seasonal snow cover, NDSI based algorithm was used to monitor the Gangotri glacier main trunk.
Keywords: Ablation, Digital Elevation Model, Glacier, NDSI, Snow.
References:
1. Dyurgerov, M.B. and Meier, M.F. 2000.Twentieth century climate change: Evidence from small glaciers. Proceedings of the National Academy of Sciences 97(4):1406-1411.
2. G PHILIP* and K V RAVINDRAN 1998,Glacial Mapping Using Landsat ThematicMapper Data : A Case Study in Parts of Gangotri Glacier, NW Himalaya, Journal of the Indian Society of Remote Sensing, Vol. 26, No. l&2
3. GSI. (1999). Inventory of the Himalayan glaciers. Special publication, vol. 34 (p. 165). Lucknow’ Geological Survey of India.
4. Haeberli, W., 1990. Glacier and permafrost signals of 20th century warming. Annals of Glaciology, 14, p 99-101International Conference on Water, Environment, Energy and Society. New Delhi, 12-16 January 2009. Hydrologic and Hydraulic Modelling, 1, p. 366-371.
5. IPCC WGII Fourth Assessment Report Singh, P., Polglase, L. and Wilson, D., 2009. Role of Snow and Glacier melt runoff modeling in Hydropower projects in the Himalayan Region. In (WEES -2009),
6. Vohra C P (1981). Himalayan Glaciers. In: The Himalaya: Aspects of Change. (Eds. J.S. Lall and Moddie), Oxford University Press, New Delhi, 138-151.
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259-261
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49.
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Authors:
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Rajeshwar Lal Dua, Himanshu Singh, Neha Gambhir
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Paper Title:
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2.45 GHz Microstrip Patch Antenna with Defected Ground Structure for Bluetooth
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Abstract: In this paper, a rectangular microstrip patch antenna with DGS has been analyzed and simulated for the wireless applications. The proposed antenna has been simulated at 2.45 GHz frequency. This compact antenna fed by Quarter Transformer feeding. This type of feeding is mostly used for impedance matching purposes. The antenna is simulated by the software HFSS. HFSS, high frequency structure simulator is employed to analyze the proposed antenna and simulated results on return loss, the E and H plane radiation pattern and polar plot gain is presented. The resultant antenna with Defected Ground Structure has improved in parameters performance.
Keywords: DGS, HFSS, Microstrip, Quarter.
References:
1. Ashwini K. Arya, M. V. Kartikeyan, A .Patnaik, “Defected Ground Structure in the perspective of Microstrip antenna,” Frequenz, Vol.64, Issue5-6, pp.79-84 , Oct 2010.
2. L. H. Weng, Y. C. Guo, X.W. Shi , X. Q. Chen,“ An overview on defected ground structure,” Progress in electromagnetic Research B, Vol.7, pp.173-189, July 2008.
3. “Microstrip patch antenna,” www. electronicshome.com, Jan 2007.
4. H. M. Chen, “Microstrip fed dual frequency printed triangular monopole antenna,” Electron Letter, Vol.38, pp.619-620, June 2002.
5. W. L. Stutzman and G. A. Thiele, Antenna Theory and design ,second edition John Wiley & Sons,1998,pp.172-173.
6. C. A. Balanis, “Antenna Theory and Analysis,” Second Edition, John Wiley & Sons, 1997.
7. Keith R. Carver, James W. Mink, “Microstrip Antenna Technology,” IEEE Transactions on Antenna and Propagation Vol.29, No.1, Jan1981.
8. Jong –Sik Lim, Jun-SeokPark,Young-Taek, Dal Ahn,Sangwook Nam, “Applications of Defected ground structures in Reducing the size of Amplifiers,” IEEE Microwave and Wireless Components Letters ,Vol.12,No.7, July 2002
9. R.B.Waterhouse, “Microstrip patch antenna, a designer guide,” Kluwer Academic publishers 2003.
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262-265
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50.
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Authors:
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Vinay Kumar.S.B, Manjula N Harihar
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Paper Title:
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Diameter-based Protocol in the IP Multimedia Subsystem
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Abstract: The Diameter protocol was initially developed by the Internet Engineering Task Force (IETF) as an Authentication, Authorization, and Accounting (AAA) framework intended for applications such as remote network access and IP mobility. Diameter was further embraced by the Third Generation Partnership Project (3GPP) as the key protocol for AAA and mobility management in 3G networks. The paper discusses the use of Diameter in the scope of the IP Multimedia Subsystem (IMS) as specified by 3GPP. This paper presents a solution for the problem of how to provide authentication, authorization and accounting (AAA) for multi-domain interacting services by referring open diameter. We have studied the case of ‘FoneFreez’, a service that provides interaction between different basic services, like telephony and television. The involvement of several parties like television provider, telephony provider etc., secure interaction between multiple domains must be assured. A part of this security issue can be resolved using AAA. In this paper the AAA protocol Diameter is used for that purpose, which is the successor of the RADIUS protocol. The authors have taken a look at open diameter can be used for AAA in multi-domain service interaction.
Keywords: Diameter protocol, IP Multimedia Subsystem, AAA, CSCF, HSS, SIP
References:
1. G. Camarillo, M. A. García-Martín, The 3G IP Multimedia Subsystem: Merging the Internet and the Cellular Worlds, John Wiley and Sons, Ltd., England, UK, 2004.
2. P. Calhoun, J. Loughney, E. Guttman, G. Zorn, J. Arkko, Diameter Base Protocol, IETF RFC 3588, September 2003.
3. http://www.fer.unizg.hr/images/50010415/Mipro_2006.pdf.
4. IP Multimedia (IM) Subsystem Cx and Dx interfaces; Signaling flows and message contents, The 3rd Generation Partnership Project; Technical Specification Group Core Network and Terminals; TS 29.228, 2005.
5. Cx and Dx interfaces based on the Diameter protocol; Protocol details, The 3rd Generation Partnership Project; Technical Specification Group Core Network and Terminals; TS 29.229, 2005.
6. J. Loughney, Diameter Command Codes for Third Generation Partnership Project (3GPP) Release 5, IETF RFC 3589, September 2003.
7. Open Diameter Website, http://www.opendiameter.org/
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266-269
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51.
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Authors:
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Pallavi Sharma, Vijay Singh Rathore
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Paper Title:
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Regulating Bandwidth Flow Estimation and Control for Wired/Wireless Networks
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Abstract: In this topic, an analysis will be made on the problems faced by bandwidth constrained applications which comes under networking domain. For bandwidth constrained applications, a proper monitoring of available bandwidth is an important factor to avoid degradation in performance while execution. Such application example could be video or voice chat on Internet , which consumes more bandwidth and its overall performance is bandwidth constraint. After the implementation of 802.11e Wireless Sensor Networks are capable to provide good level of QoS but research works are not much for improving performance of bandwidth constraint applications by checking sufficiency of bandwidth available in transmission route. We propose to design and develop a system for 802.11 based ad-hoc networks, which estimate the network traffic bandwidth and control the flow of traffic on given channels. Our research would be capable to work on both wired and wireless ad-hoc network, On top of it, It would be able to show the simulation results on multiple computers.
Keywords: Bandwidth, Estimation, Control, Wired/Wireless Networks
References:
1. Prasad, R., Murray, M., Dovrolis, C., Cla_y, K.: Bandwidth estimation: Metrics, Measurement techniques, and tools. In: IEEE Network. (2003).
2. Lowekamp, B.B., Tierney, B., Cottrell, L., Hughes-Jones, R., Kielmann, T., Swany, M. Enabling network measurement portability through a hierarchy of characteristics. In: Proceedings of the 4th Workshop on Grid Computing (GRID). (2003).
3. R. Prasad, M. Murray, C. Dovrolis, and K. Claffy, “Bandwidth Estimation: Metrics, Measurement Techniques, and Tools,” IEEE Network, vol. 17, no. 6, pp. 27-35, Nov. 2003.
4. M. Jain and C. Dovrolis, “End-to-End Available Bandwidth: Measurement Methodology, Dynamics, and Relation with TCP Throughput,” IEEE/ACM Trans. Networking (TON ’03), vol. 11, no. 4, pp. 537-549, Aug. 2003.
5. B. Melander, M. Bjorkman, and P. Gunningberg, “A New Endto-End Probing Analysis Method for Estimating Bandwidth Bottlenecks,” Proc. Fifth Global Internet Symp. (Global Internet) held in conjunction with Global Comm. Conf. (GLOBECOM ’00),Nov. 2000.
6. F.Y. Li, M. Haugea, A. Hafslund, O. Kure, and P. Spilling, “Estimating Residual Bandwidth in 802.11-Based Ad Hoc Networks: An Empirical Approach,” Proc. Seventh Int’l Symp. Wireless Personal Multimedia Comm. (WPMC ’04), Sept. 2004.
7. A. Johnsson, B. Melander, and M. Bjo¨rkman, “Bandwidth Measurement in Wireless Network,” technical report, Ma¨lardalen Univ., Mar. 2005.
8. http://www.ssmrae.com/admin/images/3c5b309affe7fad36ed07079cb9b4.pdf
9. K. Xu, K. Tang, R. Bagrodia, M. Gerla, and M. Bereschinsky, “Adaptive Bandwidth Management and QoS Provisioning in Large Scale Ad Hoc Networks,” Proc. Military Comm. Conf. (MILCOM '03), Oct. 2003.
10. Atsushi Fujiwara, “Analysis and evaluation of Spectral Ffficiency in Multi hop Transmission “ NTT DoCoMo Technical journal Vol.7 No 4.
11. Mitigating Performance degradation in congested Sensor Networks: http://www.scribd.com/doc/46473110/Document
12. http://www.antd.nist.gov/wctg/aodv_kernel/aodv_guide.pdf
13. http://docs.oracle.com/javase/1.4.2/docs/api/java/awt/package-summary.html
14. http://en.wikipedia.org/wiki/Swing_(Java)
15. http://www.oracle.com/technetwork/java/javase/jdbc/index.html
16. K. Mohideen Vahitha Banu,” Discussion on Improving Quality of Service through Available Bandwidth Estimation in Mobile Ad Hoc Networks” International Journal of Computer Applications (0975 – 8887) Volume 11– No.8, December 2010.
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270-274
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52.
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Authors:
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Sanjeev Kumar, Somnath Chattopadhyaya, Vinay Sharma
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Paper Title:
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Green Supply Chain Management: A Case Study from Indian Electrical and Electronics Industry
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Abstract: This study aims to investigate the green supply chain management practices likely to be adopted by the manufacturing industry of electrical and electronics products in India. The approach of the present research includes a literature review, in depth interviews and questionnaire surveys. The relationship between green supply chain management practices and environmental performance is studied. The industries in the electrical and electronics products industry in India were sampled for empirical study. The data were then analyzed using “mean score”. The results indicate that performance of eco procurement, eco accounting, eco logistics design, eco product design, eco manufacturing, economic performance, etc practices in response to the current wave of national & international green issues and also environmental performances of the electrical and electronics industry.
Keywords: Indian industry, electrical and electronics, green supply chain, environmental performance, case study.
References:
1. Chetan Kumar M. Sedani, Ramesh R. Lakhe 2011, ISO certification and business performance: empirical findings of Indian SMEs, International Journal of Business Excellence, Vol.4, No. 6, pp715-730.
2. G. Kannan , P. Sasikumar and K. Devika 2010, A genetic algorithm approach for solving a closed loop supply chain model: A case of battery recycling, Applied Mathematical Modelling, volume 34, issue 3, pp655-670.
3. Handfield, R., Walton, S., Sroufe, R., 2002. Applying environmental criteria to supplier assessment: A study of the application of the analytical hierarchy process. European Journal of Operational Research 141, pp70–87.
4. K.C.Shang, C.S.Lu, S.Li 2010, A taxonomy of green supply chain management capability among electronic related manufacturing firms in Taiwan, Journal of environmental management, 91, pp1218-1226.
5. Lamming, R.; Hampson, J., 1996. The environment as a supply chain management issue. Brit. J. Manage., 7 (Special issue 1), pp45-62.
6. Qinghua Zhu, Joseph Sarkis, Kee-hung Lai, 2008, Confirmation of a measurement model for green supply chain management practices implementation, Int. J. Production Economics ,111, pp261–273.
7. Ramudhin A., Chaabane, A.2010, Carbon market sensitive sustainable supply chain network design, International Journal of Management Science and Engineering Management, 5 (1), pp30-38.
8. Seok Jin Lim, Suk Jae Jeong , Kyung Sup Kim , MyonWoong Park, 2006, Hybrid approach to distribution planning reflecting a stochastic supply chain, Int J Adv Manuf Technol, 28: pp618–625.
9. Walton, S.V., Handfield, R.B., Melnyk, S.T., 1998, The green supply chain: Integrating suppliers into environmental management process, International Journal of Purchasing and Materials Management, Spring,pp 2–11.
10. Zhu, Q.; Sarkis, J., 2006. An inter-sectoral comparison of green supply chain management in China: Drivers and practices, J. Clean. Prod., 14, pp472-486.
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275-281
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53.
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Authors:
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M Anul Haq, Kamal Jain, KPR Menon
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Paper Title:
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Development of New Thermal Ratio Index for Snow/Ice Identification
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|
Abstract: Existing methods and newly developed method of monitoring snow-covered areas by optical remote sensing were evaluated using the ASTER Satellite data of Satopanth and Bhagirathi Kharak Glaciers, and Landsat satellite data of Gangotri glacier, one of the largest ice bodies in the Indian Himalayas. Snow-covered areas were identified using two methods: (1) Normalized Difference Snow Index (NDSI) which uses visible and shortwave-infrared reflectance’s, and (2) a newly proposed snow index called NDSTI which uses visible, thermal-infrared reflectance’s. NDSTI can be achieved by the ratioing of significantly distinguishing bands and normalizing those values to a standardized range will provide a sensitive and comparable test of thermal character. The NDSTI is useful for the identification of snow and ice and for separating snow/ice and most water bodies. The NDSTI is a measure of the relative magnitude of the characteristic reflectance difference between the visible and TIR reflectance of snow. A comparison between NDSI vs. NDSTI has been attempted in current investigation.
Keywords: Accumulation, Classification, processing, Snow, Thermal
References:
1. MAURER, E.P., RHOADS, J.D., DUBAYAH, R.O. and LETTENMAIER, D.P., 2003, Evaluation of the snow-covered area data product from MODIS. Hydrological Processes, 17, pp.59–71.
2. ROMANOV, P., GUTMAN, G. and CSISZAR, I., 2000, Automated monitoring of snow cover over North America with multispectral satellite data. Journal of Applied Meteorology, 39, pp. 1866–1880.
3. ROSENTHAL, W. and DOZIER, J., 1996, Automated mapping of montane snow cover at subpixel resolution from the Landsat Thematic Mapper. Water Resources Research,32, pp. 115–130
4. DOZIER, J., 1989, Spectral signature of alpine snow-cover from the Landsat Thematic Mapper. Remote Sensing of Environment, 28, pp. 9–22.
5. HALL, D.K., RIGGS, G.A. and SALOMONSON, V.V., 1995, Development of methods for mapping global snow-cover using moderate resolution spectroradiometer data. Remote Sensing of Environment, 54, pp. 127–140.
6. Anul Haq and Kamal Jain.2011. Change Detection of Himalayan Glacier Surface Using Satellite Imagery. In Regional Conference on Geomatics for G-governance from 13 – 14 September, 2011.
7. H. C. Nainwal, B. D. S. Negi, M. Chaudhary, K. S. Sajwan and Amit Gaurav” Temporal changes in rate of recession: Evidences from Satopanth and Bhagirath Kharak glaciers, Uttarakhand, using Total --Station Survey ”, CURRENT SCIENCE, VOL. 94, NO. 5, 10 MARCH 2008.
8. Rees, W.G., 2006. "Remote Sensing of Snow and Ice".
9. JOHAN P. M. HENDRIKS AND PETRI PELLIKKA, HELSINKI (2008) Semi-automatic glacier delineation from Landsat imagery over Hintereisferner in the Austrian Alps. ZEITSCHRIFT FÜR GLETSCHERKUNDE UND GLAZIALGEOLOGIE, Universitätsverlag Wagner, Innsbruck.
10. Keshri, A. K., Shukla, A. and Gupta, R. P.(2009) 'ASTER ratio indices for supraglacial terrain mapping', International Journal of Remote Sensing, 30: 2, 519 — 524
11. Anil V. Kulkarni (2010),Monitoring Himalayan cryosphere using remote sensing techniques, Jour nal of the Indian Inst itute of Science VOL 90:4 Oct De c 2010
12. Hall, D. K., Riggs, G. A., Salomonson, V. V, DiGirolanno, N. E., and Bayr, K. J., 2002. MODIS snow-cover products. Remote Sensing QfEnvironment, 83, 181-194.
13. CONGALTON, R.G., 1991, A review of assessing the accuracy of classifications of remotely sensed data. Remote Sensing of Environment, 37, pp. 35–37.
14. Rezaei, Y., 2004. "Investigation of Chale Khersan Glacier using Remote Sensing Data and GIS” M.S. Thesis, Khaje Nasire Toosi, Iran.
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282-285
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54.
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Authors:
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R.Madhubala
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Paper Title:
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An Illustrative study on Cloud Computing
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Abstract: “Cloud” computing – a relatively recent term, defines the paths ahead in computer science world. Being built on decades of research it utilizes all recent achievements in virtualization, distributed computing and utility computing. This paper is about the definition of cloud, architecture and security issues of cloud.
Keywords: Cloud, virtualization, security, infrastructure .
References:
1. S. M. Metev and Michael Armbrust, Armando Fox, Rean Griffith, Anthony D. Joseph, Randy Katz, A Berkeley View of Cloud Computing, February 10, 2009
2. Andy Bechtolsheim, Chairman & Co-founder, Arista Networks, Cloud Computing, November 12th, 2008
3. Introduction to Cloud Computing Architecture, Sun Microsystems, Inc.
4. An Oracle White Paper in Enterprise Architecture, August 2009 Architectural Strategies for Cloud Computing .
5. David Chappell, a short introduction to cloud Platforms, An enterprise- oriented view, august 2008,
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286-290
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55.
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Authors:
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Manish Gupta, Govind Sharma
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Paper Title:
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An Efficient Modified Artificial Bee Colony Algorithm for Job Scheduling Problem
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Abstract: Swarm intelligence systems are typically made up of a population of simple agents or boids interacting locally with one another and with their environment. Particle swarm, Ant colony, Bee colony are examples of swarm intelligence. In the field of computer science and operations research, Artificial Bee Colony Algorithm (ABC) is an optimization algorithm based on the intelligent foraging behavior of honey bee swarm. The job scheduling problem is the problem of assigning the jobs in the system in a manner that will optimize the overall performance of the application, while assuring the correctness of the result. In this paper, An Efficient artificial bee colony (ABC) algorithm, where we have used additional mutation and crossover operator of Genetic algorithm (GA) in the classical ABC algorithm. We have added crossover operator after the employed bee phase and mutation operator after onlooker bee phase of ABC algorithm, is proposed in this paper, for solving the job scheduling problem with the criterion to decrease the maximum completion time. The simulated results show that ABC proves to be a better algorithm when applied to job scheduling problem.
Keywords: Artificial Bee Colony, ABC, Genetic Algorithm, GA, Mutation, crossover.
References:
1. Dervis Karaboga • Bahriye Basturk, “A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm” J Glob Optim (2007), pp 459-471
2. C.A. Silvaa, lM.C. Sousaa, T.A. Runkler, "Rescheduling and optimization of logistic processes using GA and ACO," Engineering Applications of Artificial Intelligence., vol. 21, pp. 343-352, 2008.
3. L.-P. Wong, M.Y. Hean Low, C.S. Chong, "A Bee Colony Optimization Algorithm for Traveling Salesman Problem," Second Asia International Conference on Modelling & Simulation, 2008, pp. 818-823.
4. D. Karaboga, "An idea based on honey bee swarm for numerical optimization," Erciyes University, Engineering Faculty, Computer Engineering Department, Turkey, Technical Report-TR06, 2005.
5. D. Karaboga, B. Akay, "A Survey: Algorithms Simulating Bee Swarm Intelligence," Artificial Intelligence Review., vol. 31, pp. 68-85, 2009.
6. G-. G. Jin, S-. R. Joo, “A Study on a Real-Coded Genetic Algorithm,” Journal of Control, Automation, and Systems Engineering, vol. 6, no. 4, pp. 268-274, April 2000.
7. le. Biesmeijer, T.D. Seeley, "The use of waggle dance information by honey bees throughout their foraging careers," Behav. Ecol. Sociobiol., vol. 59, pp. 133-142, 2005.
8. Wright, A. “Genetic Algorithms for Real Parameter Optimization, Foundations of Genetic Algorithms”, G. Rswlins(Ed.), Morgen Kaufmann publishers, CA, pp.205-218, 1991.
9. L. Davis, “Handbook of Genetic Algorithms”, Von Nostrand Reinhold, N.Y., 1991
10. C. 2. Janikow and Z. Michalewicz, “An Experimental Comparisonof Binary and Floating Point Representations in Genetic Algorithms,”Pmc. 4th Int. Con$ on Genetic Algorithm, Morgan Kaufiann F’ublishers, CA, 1991
11. H. Miihlenbein and D. Schlierkamp-Voosen,“Predictive Models for the Breeder Genetic Algorithm: I. Continuous Parameter Optimization”, Evolutionary Computation, vol. 1, pp. 25-49, I993
12. Z. Michalewicz, “Genetic algorithm + data structure = evolution program”, Springer-Verlag, Inc., Heidelberg, Berlin, 1996.
13. L. J. Eshelman, R. A. Caruana, and J. D. Schaffer, “Bases in the crossover landscape,” Pmc. 3rd Int. Con$ on Genetic Algorithms, J. Schaffer(Ed.), Morgan Kaufmann Publishers, LA, pp.10-19, 1989.
14. Yazdani M, Amiri M, Zandieh M (2010) Flexible job-shopscheduling with parallel variable neighborhood search algorithm.Expert Sys Appl 37(1):678–687.
15. Moradi E, Fatemi Ghomi SMT, Zandieh M (2010) An efficient architecture for scheduling flexible job-shop with machine availability constraints. Int J Adv Manuf Tech 51(1–4):325–339.
16. Defersha FM, Chen M (2010) A parallel genetic algorithm for a flexible job-shop scheduling problem with sequence dependent setups. Int J Adv Manuf Tech 49(1–4):263–279.
17. Zhang GH, Gao L, Shi Y (2011) An effective genetic algorithm for the flexible job-shop scheduling problem. Experts Sys Appl 38 (4):3563–3573.
18. Li JQ, Pan QK, Suganthan PN, Chua TJ (2011) A hybrid tabu search algorithm with an efficient neighborhood structure for the flexible job shop scheduling problem. Int J Adv Manuf Tech 52(5–8):683–697.
19. Moslehi G, Mahnam M (2011) A Pareto approach to multi-objective flexible job-shop scheduling problem using particle swarm optimization and local search. Int J Product Econ 129(1):14–22.
20. Wang XJ, Gao L, Zhang CY, Shao XY (2010) A multi-objective genetic algorithm based on immune and entropy principle for flexible job-shop scheduling problem. Int J Adv Manuf Tech 51 (5–8):757–767.
21. Pan QK, Tasgetiren MF, Suganthan PN, Chua TJ (2011) A discrete artificial bee colony algorithm for the lot-streaming flow shop scheduling problem. Inf Sci 181(12):2455–2468.
22. Karaboga D, Akay B (2009) A comparative study of artificial bee colony algorithm. Appl Math Comput 24(1):108–132.
23. Wong LP, Low MYH, Chong CS (2008) Bee colony optimization with local search for traveling salesman problem. In: Proc. of 6th IEEE International Conference on Industrial Informatics, pp 1019–1025.
24. Karaboga, D.; Basturk, B. On the performance of artificial bee colony (ABC) algorithm. Appl.Soft Comput. 2008, 8, 687–697.
25. Karaboga, D.; Akay, B. A survey: algorithms simulating bee swarm intelligence. Artif. Intell.Rev. 2009, 31, 61–85.
26. Lei, D. Simplified multi-objective genetic algorithms for stochastic job shop scheduling. Appl.Soft Comput. 2011, doi:10.1016/j.asoc.2011.06.001.
27. Akay, B.; Karaboga, D. Artificial bee colony algorithm for large-scale problems and engineering design optimization. J. Intell. Manuf. 2011, doi:10.1007/s10845
010-0393-4.
28. Pezzella, F.; Morganti, G.; Ciaschetti, G. A genetic algorithm for the flexible job-shop scheduling problem. Comput. Oper. Res. 2008, 35, 3202–3212.
29. Xing LN, Chen YW, Wang P, Zhao QS, Xiong J (2010) A knowledge-based ant colony optimization for flexible job shop scheduling problems. Applied Soft Com 10(3):888–896.
30. Gao J, Sun LY, Gen M (2008) A hybrid genetic and variable neighborhood descent algorithm for flexible job shop scheduling problems. Com Oper Res 35(9):2892–2907.
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291-296
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56.
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Authors:
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Govind Sharma, Manish Gupta
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Paper Title:
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Black Hole Detection in MANET Using AODV Routing Protocol
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Abstract: Mobile Ad-hoc network (MANET) has become an individual part for communication for mobile device. Therefore, interest in research of Mobile Ad-hoc network has been growing since last few years. Due to the open medium, dynamic network topology, autonomous terminal, lack of centralized monitoring and lack of management point Mobile Ad-hoc network are highly vulnerable to security attacks compared to wired network or infrastructure-based wireless network. In this paper, we analyze the black hole attack. In this attack, a malicious node falsely advertise shortest path to the destination node. The intension of malicious node could be to intercept all data packets being sent to the destination node concerned. We proposed our approach to detect the black hole attack in Mobile Ad-hoc network. This approach is based on the AODV (ad-hoc on demand distance vector) routing algorithm. In this paper we are enhancing the secured AODV routing algorithm. Here we are making more secure AODV routing algorithm and using promiscuous mode of the node in promiscuous mode node can learn about the neighbouring routes traversed by data packets if operated in the promiscuous mode.
Keywords: Secured Routing, AODV, Ad-hoc network, Black Hole Attack, Malicious node,MANET.
References:
1. C. Siva Ram Murthy and B.S. Manoj, “Ad Hoc Wireless Networks: Architectures and Protocols,” Prentice Hall (2004).
2. Loay Abusalah, Ashfaq Khokhar and Mohsen Guizani, “A Survey of Secure Mobile Ad Hoc Routing Protocols,” IEEE Communications Surveys & Tutorials, Vol 10, No. 4 pp. 78-93 (2008).
3. D. P. Agrawal and Q.-A. Zeng, Introduction to Wireless and Mobile Systems, Brooks/Cole Publishing, Aug. 2002.
4. C. E. Perkins and P. Bhagwat, “Highly Dynamic Destination-Sequenced Distance-Vector (DSDV) for Mobile Computers,”Proc. ACM Conf. Commun. Architectures and Protocols (SIGCOMM’94), London, UK, Aug. 1994, pp. 234–44.
5. T. Clausen et al., “The Optimized Link State Routing Protocol: Evaluation Through Experiments and Simulation,” Proc. 4th Int’l. Symp. Wireless Pers. Multimedia Commun., Aalborg, Denmark,Sept. 2001.
6. D. B. Johnson, D. A. Maltz, and J. Broch, “DSR: The Dynamic Source Routing Protocol for Multi-Hop Wireless Ad hoc Networks,”Ad Hoc Net., C. E. Perkins, ed., Addison-Wesley, 2001, pp. 139–72.
7. J. Lundberg, “Routing Security in Ad Hoc Networks,”Helsinki University of Technology, http://citeseer.nj.nec.com/400961.html
8. J.-F. Raymond, “Traffic Analysis: Protocols, Attacks, Design Issues and Open Problems,” Proc. Wksp. Design Issues in Anonymity and Unobservability, Berkeley, CA, July 2000, pp. 7–26.
9. Songbai Lu, Longxuan Li, Kwon-Yan Lam and Lingvan Jia “SAODV: A MANET Routing Protocol that can Withstand Black Hole Attack,” International Conference on Computational Intelligence and Security, pp 421-425 (2009).
10. Devid Cerri, Alessandro Ghioni, CEFRIEL-Politecnico di Milano “Securing AODV: The A-SAODV secure Routing Prototype,” IEEE Communication Magzine, pp 120-125 (2008).
11. N. Bhalaji, A. Shanmugam, “Association between nodes to combat black hole attack in DSR based MANET,” Wireless and Optical communication Networks, pp 1-5 (2009).
12. M. Sayee Kumar, S. Selvarajan, S. Balu, “ANODR based anomaly detection for black hole and route disrupt attacks,” International Conference on Computing, Communication and Networking , pp 1-5 (2008).
13. Nidhi Sharma, Sanjeev Rana and R.M. Sharma, “Provisioning of Quality of Se Service in MANETs Performance Analysis & Comparison (AODV AND DSR), ” International Conference on Computer Engineering and Technology, pp 243-248 (2010).
14. Yibeltal Fantahun Alem and Zhao Cheng Xuan, “Preventing Black Hole Attack in Mobile Ad-Hoc Networks Using Anomaly Detection,” International Conference on Future Computer and Communication, pp 672-676 (2010).
15. Martuja Ahmad, Rima Pal and Md. Abu Naser Bikas, “PIDS: A packet based approach to network intrusion detection and prevention,” International Conference on
Information Management and Engineering, pp 124-127 (2009).
16. Patroklos G. Argyroudis and Donal O’Mahony, “Secure Routing for Mobile Ad-hoc Network,” IEEE Communication Surveys & Tutorials, pp 2-21 (2005).
17. Hongmei Deng, Wei Li and Dharma P. Agrawal, “Routing Security in Wireless Ad Hoc Networks,” IEEE Communication Magazine, Vol. 40 pp 70-75 (2002).
18. Satyabrata Chakrabarti and Amitabh Mishra, “QoS Issues in Ad Hoc Wireless Networks,” IEEE Communications Magazine, Vol. 39, pp 142-148 (2001).
19. A. Menaka Pushpa, “Trust Based Secure Routing in AODV Routing Protocol,” IEEE, (2009).
20. H. Weerasinghe and H. Fu. “Preventing cooperative black hole attacks in mobile ad-hoc networks: simulation, implementation and evaluation,” International Journal of Software Engineeringand its Applications. Vol.2, No. 3 pp. 362-367 (2008).
21. A. Raja Mahmood and A.I. Khan, “A Survey on Detecting Black Hole Attack in AODV-based Mobile Ad Hoc Networks,”, pp. 1-6 (2007).
22. Scalable Network Technologies (SNT). QualNet.http://www.qualnet.com/.
23. Sonja Buchegger and Jean-Yves Le Boudec: “Performance analysis of the CONFIDANT protocol” Proceedings of the 3rd ACM international symposium on Mobile ad hoc networking & computing’02. p.p:226 –236.http://doi.acm.org/10.1145/513800.513828.
24. E. M. Royer and C.-K. Toh, “A Review of Current Routing Protocols for Ad hoc Mobile Wireless Networks,” IEEE Pers. Commun.,vol. 2, no. 6, Apr. 1999, pp. 46–55.
25. L. Zhou and Z. J. Haas, “Securing Ad hoc Networks,” IEEE Net. Mag., vol. 6, no. 13, Nov./Dec. 1999, pp. 24–30.
26. tools.ietf.org/html/draft-perkins-manet-aodvbis-00
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297-303
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57.
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Authors:
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Manish Gupta, Govind sharma
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Paper Title:
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An Efficient Face Recognition System Based on Sub-Window Extraction Algorithm
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Abstract: In this paper, an efficient face recognition system based on sub-window extraction algorithm and recognition based on principal component analysis (PCA) and Back propagation algorithm is proposed. Our proposed method works on two phases: Extraction phase and Recognition phase. In extraction phase, face images are captured from different sources and then enhanced using filtering, clipping and histogram equalization. Enhanced images are converted into edge images using Sobel operator and then converted into binary images. Finally sub windows from extracted using proposed sub windows extraction algorithm and extract different features (mouth, eyes, nose etc.) from these sub windows. In recognition phase, back propagation algorithm (BPA) and PCA algorithm is used. The experiments are carried out using IIIM_Gwalior database, IIT_Kanpur database and Face_94 database.
Keywords: Sub-windows extraction, principal component analysis (PCA), Back propagation algorithm (BPA), Face recognition, Neural Network.
References:
1. Jain, R. Bolle, S. Pankanti Eds, "BIOMETRIC - Personal Identification in Networked Society", Kluwer Academic Publishers, Boston/ Dordrecht/ London, 1999.
2. D.L. Swets and J.J. Weng, "Using Discriminant Eigen features for image retrieval", IEEE Trans. Pattern Anal. Machine Intel, vol. 18, PP. 831-836, Aug. 1996.
3. P.N. Belhumeur, J.P. Hespanha, and D. J. Kriegman, "Eigen faces vs. Fisher faces: Recognition using class specific linear projection", IEEE Trans. Pattern Anal. Machine Intel, vol. 19, PP. 711-720, may 1997.
4. M. Turk, A. Pentland, "Eigen faces for face recognition", Journal cognitive neuroscience, Vol. 3, No.1, 1991.
5. W. Zhao, R. Chellappa, A, Krishnaswamy, "Discriminant analysis of principal component for face recognition", .IEEE Trans. Pattern Anal. Machine Intel, Vol 8, 1997.
6. M.J.Er, W.Chen, S.Wu, "High speed face recognition based on discrete cosine transform and RBF neural network", IEEE Trans. On Neural Network, Vol. 16, No. 3, PP. 679,691, 2005.
7. D. Ramaeubramanian, y. Venkatesh, "Encoding and recognition of Faces based on human visual model and DCT", Pattern recognition, Vol 34, PP. 2447-2458, 2001.
8. X. Y. Jing, D. Zhang, "A face and palm print recognition approach based on discriminant DCT feature extraction", IEEE trans. on Sys. Man & Cyb., Vol. 34, No. 6, PP. 2405-2415, 2004."
9. Mohammed Alwakeel, Zyad Shaaban," Face Recognition Based on Haar Wavelet Transform and Principal Component Analysis via Levenberg-Marquardt Back propagation Neural Network", European Journal of Scientific Research ISSN 1450-216X Vol.42 No.1 (2010), pp.25-31.
10. P.Latha, Dr.L.Ganesan, Dr.S.Annadurai, "Face Recognition using Neural Networks" An International Journal (SPIJ) Volume (3) : Issue (5).
11. Dipti Patra, Member IEEE, Manab Kumar Das, Smita Pradhan, "Integration of FCM, PCA and Neural Networks for Classification of ECG Arrhythmias ",computer Science, 36:3, IJCS_36_3_05, 2010.
12. Anupam shukla, Ritu Tiwari, Chandra prakash, Dhirendra Sharma, Rishi kumar Anand and Sourav Sharma, "Face Recognition Based On PCA, R-LDA And SUPERVISED NEURAL NETWORKS", International J. of Engg. Research & Indu. Appls. (IJERIA). ISSN 0974-1518, Vol.2, No. III (2009), pp 243-255.
13. Chang Jyh-Yeong, Chen Jia Lin, Automated Facial Expression Recognition System Using Neural Networks, Journal of the Chinese Institute of Engineers, Vol. 24, No.3, pp.345-356, 2001
14. P. Ekman, W.V. Friesen, The Facial Action Coding System: A Technique for measurement of facial movement, Consulting Psychologists Press, PaloAlto, CA, 1978
15. M. Pantic, L, Rothkrantz, Automatic Analysis of Facial Expression: the state of the art, IEEE Transaction on Pattern Analysisi and Machine Intelligence 22 (12)(2000), pp.1424-1445, 2000
16. M. Turk and A. Pentland, "Eigenfaces for recognition," Journal of Cognitive Neuroscience, vol. 3, no. 1, pp. 72-86, 1991.
17. P. N. Belhumeur, J. Hespanda and D. Kriegeman, "Eigenfaces vs. Fisherfaces: Recognition Using Class Specific Linear Projection," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 19, no. 7, pp. 711-720, July 1997.
18. Liu and H. Wechsler, "Enhanced Fisher Linear Discriminant Models for Face Recognition," Proc. Int'l Conf.Pattern Recognition, vol. 2, pp. 1368- 1372, 1998.
19. K. Fukunaga, Introduction to Statistical Pattern Recognition, Academic Press, New York, 1990.
20. S.Anila, N. Devarajan, "Simple and fast face detection system based on edges" international journals of Universal Computer Sciences, Vol. 1/Iss.2, pp. 54-58, 2010.
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304-310
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58.
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Authors:
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Sarin CR, Manu R Krishnan
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Paper Title:
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Growing Self Organized Maps for Radiographic Non Destructive Testing of Metallic Products
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Abstract: Manual inspection of metallic products can only be a time-consuming and is less reliable to find microscopic and internal defects, therefore is an expensive task; it can also suffer from operator performance. The proposed system apply image processing techniques to automatically inspect radiographic images and evaluate the data to find faults and is based on Improved Growing Self organized Maps Segmentation. The number of false detections is still high and will be addressed in future research. Monitoring the defect or damage at an early stage is a very important as it allows to implement operations to classify and correct defects and improves the safety, reliability, accuracy, and high throughput of the structure. This paper presents an improved intelligent methodology for Radiographic automated visual quality inspection and, which provides many advantages over traditional methods. The accuracy of conventional systems is very much depending on the selected features, which are extracted from defect images. Growing Self Organized Maps for Radiographic Non Destructive Testing is an advanced method suitable for crack detection, which gives a smoothed image to obtain uniform brightness, followed by removing isolated points to remove noise and morphological operations with fast operation.
Keywords: Automatic Quality Inspection, GSOM, NDT, Object detection
References:
1. Juran, J. M., Godfrey, A. B., Juran’s Quality Handbook, 7th ed. McGraw Hill, New York, NY (2006)
2. Kisil’ I.S., Karpash M.O., Vashchyshak I.R. Device for Evaluation of Mechanical Properties of Steel FMH-1 - Methods and Devices of Quality Control, 2005, No.14, 77-80.
3. Charola, A.E., E. De Witte, and M. Laurenzi Tabasso. Establishing International Standards for the Quality Control of Conservation Materials and for Qualifying Practioners Applying Them. In Saving Our Architectural Heritage. 1996. Berlin: Wiley; p. 245–254.
4. Hands, G., Nath, R. H., “Nondestructive Testing of Metal Castings,” Materials Evaluation, vol 62, No 2, pp 111–115 (2004).
5. Artificial Intelligence: A Modern Approach, Stuart J. Russell and Peter Norvig, Prentice Hall, Englewood Cliffs, ISBN 0-13-080302-2.
6. Dario Floreano, Toshifumi Kato, Davide Marocco, and Eric Sauser. Automaitic vision and feature selection. Biological Cybernetics, 90:218–228, 2004
7. S.W. Lawson. Automatic defect detection in industrial radioscopic and ultrasonic images. PhD. thesis, University of Surrey, 1996.
8. S. Edelman; Representation and Recognition in Vision, MIT Press, 1999, ISBN 0-262-05057-9.
9. Ultrasonic and Advanced Methods for Nondestructive Testing and Material Characterization, World Scientific Publishing Co. Pte. Ltd,2005.
10. Digital Image Processing,Rafael C. González, Richard Eugene Woods,Prentice Hall, 2008 - Computers - 954 pages
11. Computer vision, graphics and image processing: fourth Indian conference, ICVGIP 2004, Kolkata, December 16-18, 2004. Proceedings Chanda, B., ed., Chandran, S., ed. & Davis, L., ed. 006.37 CHA 019131
12. F. Brandt, 2000. The use of X-ray inspection techniques to improve quality and reduce costs. The e-Journal of Nondestructive Testing & Ultrasonics, 5(5).
13. A. Besbes 2009] N. Paragios A. Besbes N. Komodakis and G. Langs. Discrete MRFs for Knowledge-based Segmentation. IEEE Conference in Computer Vision and Pattern Recognition, 2009. 103
14. Amberg 2007] B. Amberg, S. Romdhani and T. Vetter. Optimal Step Nonrigid ICP Algorithms for Surface Registration. IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2007. 114
15. Kohonen, T.;Dept. of Comput. Sci., Helsinki Univ. of Technol., Espoo, Sep 1990, On page(s): 1464 – 1480 ISSN: 0018-9219 Volume: 78 Issue: 9,
16. A novel self-organizingmap (SOM) neural network for discrete groups of data clustering Applied Soft Computing, Volume 11, Issue 4, June 2011, Pages 3771-3778 M.H. Ghaseminezhad, A. Karami.
17. N. Ampazis and S. J. Perantonis. Evaluation of dimensionality reduction techniques for SOM clustering of textual data. In Proceedings of the Second-Iasted International Conference. Artificial Intelligenceand Applications. 2002: 216-21, 2002. [17].
18. R. Amarasiri, D. Alahakoon, and K. A. Smith. HDGSOM: a modified growing self-organizing map for high dimensional data clustering. In M. Ishikawa, S. Hashimoto, M. Paprzycki, E. Barakova, K. Yoshida, M. Koppen, D. W. Corne, and A. Abraham, editors, Fourth International Conference on Hybrid Intelligent Systems, pages 216–221. IEEE Comput. Soc, Los Alamitos, CA, USA, 2004.
19. Romeu R. da Silva, Marcio H.S. Siqueira, Marcos Paulo Vieira de Souza, João M.A. Rebello and Luiz P. Calôba. Estimated accuracy of classification of defects detected in welded joints by radiographic tests. NDT & E International, Volume 38, Issue 5, July 2005, Pages 335-343.
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311-317
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59.
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Authors:
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D.Kishore Babu, Y.Nagasatish, P.M.Prasuna
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Paper Title:
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Mining Train Delays by Using Frequent Itemsets
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Abstract: The Indian railway network has a high traffic density with Vijayawada as its gravity center. The star-shape of the network implies heavily loaded bifurcations in which knock-on delays are likely to occur. Knock-on delays should be minimized to improve the total punctuality in the network. Based on experience, the most critical junctions in the traffic flow are known, but others might be hidden. To reveal the hidden patterns of trains passing delays to each other, we study, adapt and apply the state-of-the-art techniques for mining frequent episodes to this specific problem.
Keywords: Train delays, Data Analysis, Pattern mining, frequent itemsets, Hidden trains.
References:
1. Flier, H., Gelashivili, R., Graffagnino, T., and Nunkesser, M., “Mining Railway Delay Dependencies in Large-Scale Real-World Delay Data”, Robust and Online Large- Scale Optimization, Lecture Notes in Computer Science, vol. 5868, 354–36, 2009.
2. Agrawal,R.and Srikant,R.,“Mining sequential patterns”, Proc. of the 11th International Conference on Data Engineering, vol. 0, 3–14, 1995.
3. Goethe’s,B.,“Frequent Set Mining”, The Data Mining and Knowledge Discovery Handbook, chap. 17, 377–397, Springer, 2005.
4. Gunopulis, D., Khardon, R., Labbuka, H., Saluja, S., Toivonen, H., and Sharma, R.S., “Discovering all most specific sentences”, ACM Transactions on Database Systems, vol. 28(2), pp. 140–174, 2003.
5. Mirabadi, A. and Sharifian, S., “Application of Association rules in Iranian Railways (RAI) accident data analysis”, Safety Science, vol. 48, 1427–1435, 2010.
6. Mannila, H., Toivonen, H., and Verkamo, A.I., “Discovery of Frequent Episodes in Event Sequences”, Data Mining and Knowledge Discovery, vol. 1, 259–298, 1997.
7. Tan, P.-N., Steinbach, M., and Kumar. Introduction to Data Mining, Pearson Addi- son Wesley, 2006.
8. Tatti, N., and Cule, B., “Mining Closed Strict Episodes”, Proc. of the IEEE International Conference on Data Mining, 2010.
9. Wang, J. T.-L., Chirn, G.-W., Marr, T.G., Shapiro, B., Shasha, D., and Zhang, K., “Combinatorial pattern discovery for scientific data: some preliminary results”, ACM SIGMOD Record, vol. 23, 115–125, 1994.
10. Data Mining Concepts and Techniques - J.Han & amp; M.Kamber. ptpg_sit_2005.
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318-323
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60.
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Authors:
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R. HariKumar, V.K. Sudhaman, C.Ganesh Babu
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Paper Title:
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FPGA Synthesis of Fuzzy (PD and PID) Controller for Insulin Pumps in Diabetes Using Cadence
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Abstract: This paper emphasizes on a FPGA synthesis of Fuzzy PD and PID Controller in biomedical application. We aim at identifying a proper methodology for the infusion process of insulin to diabetic patients using an automated fuzzy logic PD and PID controller. A synthesis of FPGA model of the above automatic controller is analyzed and synthesized. In Type I and Type II diabetes the patient is dependent on an external source of insulin to be infused at an appropriate rate to maintain blood glucose concentration. Hypoglycemia has short term effects which can lead to diabetic coma and possibly death, while hyperglycemia has a long term impact that has been linked to nephropathy, retinopathy and other tissues damage. In this process insulin is administrated through an infusion pump as a single injection. The pump is controlled by the automatic control Fuzzy PD Controller which is more efficient compared to the conventional PD Controller. This is of primary importance where the processes are too complex to be analyzed using the conventional one. The designed controller is implemented with low power multiplier and Fuzzy controller architecture. In case of non- linear inputs, Fuzzy PD Controller performs better compared to the conventional controller and consumes lesser power. The blood glucose level is monitored from Photo Plethysmography of pulse Oximeter. This fuzzy controller model will surely be a boon to the diabetic patients.
Keywords: Fuzzy PD and PID controller, FPGA synthesis, Photo Plethysmography, Insulin pump, Diabetes.
References:
1. Harikumar.R and Selvan.S, “Fuzzy Controller for Insulin Pumps in Diabetes”, Proceedings of International Conference on Bio medical Engineering, Anna University, Chennai, India, pp.73-76, January 24-26, 2001.
2. Paramasivam.K and R.Harikumar and R. Sundararajan, “Simulation of VLSI Design Using Parallel Architecture for Epilepsy Risk Level Diagnosis in Diabetic Neuropathy”, IETE Journal of Research, Vol.50, no.4, pp. 297-304, August 2004.
3. Baogang Hu, George K.I. Mann, and Raymond G.Gosine, “New Methodology for Analytical and Optimal Design of Fuzzy PID Controllers” IEEE Transactions on Fuzzy Systems, Vol. 7,no.5,pp.521-539,October 1999.
4. K.H.Kienitz and T.Yoneyama “A Robust Controller for Insulin Pumps based on H-Infinity Theory” IEEE Transactions on Bio Medical Engineering, Vol.40, no.11, pp. 1133-1137, November 1993.
5. C.C.Lim and K.L.Teo “Optimal Insulin Infusion Control via a Mathematical Blood Glico Regulator Model with Fuzzy Parameters” Cybernetics and Systems, Vol.22, pp.1-16, 1991.
6. H.A.Malki,H.Li and G.Cheng “New Design and Stability Analysis of Fuzzy Proportional-Derivative Control Systems” IEEE Transactions on Fuzzy Systems, Vol. 2, no.4, pp.245-254, November 1994.
7. C.-L.Chen and F.-C.Kuo, “Design and Analysis of a Fuzzy Logic Controller,” Int.J. Syst. Sci., Vol.26, pp.1223-1248, 1995.
8. C.C.Lee, “Fuzzy Logic in Control Systems: Fuzzy Logic Controller- Part 1 and Part 2,” IEEE Transactions on Syst., Man,Cybern., Vol. 20, pp.404-435 ,1990.
9. Altera- FPGA Reference Manual, 2006.
10. A. E. Gamal, et al., “An Architecture for Electrically Configurable Gate Arrays,” IEEE Journal of Solid-state Circuits, Vol. 24, no. 2, pp. 394-398, April 1989.
11. Palo Magni, and Riccardo Bellazzi, “A Stochastic Model to Assess the Variability of Blood Glucose Time Series in Diabetic Patient Self- Monitoring,” IEEE Transactions on Bio Medical Engineering, Vol.53, no.6, pp. 977-985, June 2006.
12. Ackerman, E., L.C. Gatewood, J.W. Rosevear, and G.D. Molnar, “Model Studies of Blood Glucose Regulation,” Bull. Math. Biophys., Vol. 27, pp.21-37,1965.
13. Spencer, W.J. “A Review of Programmed Insulin Delivery Systems,” IEEE Transaction on Bio Medical Engineering, Vol. 28, no.3, pp.237-251,1981.
14. Cadence Documentation Cadence EDA 1514,2010
15. www.EDAforum.com
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324-331
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61.
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Authors:
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Naveen Choudhary
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Paper Title:
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Network-on-Chip: A New SoC Communication Infrastructure Paradigm
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Abstract: As the feature size in deep-submicron domain is continuously shrinking and the bandwidth requirements is increasing, traditional shared-bus architecture will no longer be able to meet the requirements of System-on-Chip (SoC) implementations. Specially, inherently non-scalable nature of the shared-bus architecture as well as its power hungry nature will become the communication bottleneck in most practical applications. Network-on-Chip (NoC) communication architectures have emerged as a promising alternative to address the problems associated with on-chip buses by employing a packet-based micro-network for inter-IP communication. Some of the most important phases in designing the NoC are the design of the topology or structure of the network and setting of various design parameters (such as frequency of operation, link-width, etc). This paper surveys the various topological structures for NoC proposed in the research domain
Keywords: NoC. SoC, Topology, Routing, Buffers, Virtual Channel.
References:
1. P. Guerrier, A. Greiner, "A generic architecture for on-chip packet-switched interconnections", in Proceedings of the Automation and Test in Europe Conference and Exhibition, pp. 250-256, 2000.
2. International Technical Roadmap for Semiconductors website. [online] Available: http://public.itrs.net/.
3. W. J. Dally, B. Towles, "Route packets, not wires: on-chip interconnection networks", in Proceedings DAC, pp. 684-689, June 2001.
4. M. Millnerg, E. Nilsson, R. Thid, A. Jantsch, “Guaranteed bandwidth using looped containers in temporally disjoint networks within the nostrum network-on-chip,” in Proceedings of Design, Automation and Testing in Europe Conference (DATE). IEEE, pp. 890–895, 2004.
5. S. Kumar, A. Jantsch, J.-P. Soininen, M. Forsell, M. Millberg, J. Oberg, K. Tiensyrja, and A. Hemani, “A network on chip architecture and design methodology,” in Proceedings of VLSI Annual Symposium (ISVLSI 2002), pp. 105–112, 2002.
6. D. Wiklund and D. Liu, “SOCBUS: switched network on chip for hard real time embedded systems,” in Proceedings of the Int. Parallel and Distributed Processing Symposium, Apr.2003.
7. L. Natvig, “High-level architectural simulation of the torus routing chip,” in Proceedings of the International Verilog HDL Conference, California, pp. 48–55, Mar. 1997
8. L. Benini, G. DeMicheli., “Networks on Chips: a new SoC paradigm,” IEEE Computer Vol. 35, No. 1 pp. 70–78, January 2002.
9. P. Guerrier, A. Greiner, “A generic architecture for on-chip packet-switched interconnections,” in Proceedings of the Automation and Test in Europe Conference and Exhibition, pp. 250–256, 2000.
10. M. Taylor, W. Lee, S. Amarasinghe, A. Agarwal, “Scalar operand networks,” in IEEE Transactions on Parallel and Distributed Systems, vol. 16, no. 2, pp. 145-162, Feb 2005.
11. F. KARIM et al., “An interconnect architecture for networking systems on chips”, IEEE Micro 22, pp. 36–45, 2002.
12. W. Zhang, L. Hou, J. Wang, S. Geng, W. Wu, “Comparison research between XY and odd-even routing algorithm of a 2-dimension 3 imes3 mesh topology network-on-chip,” in GCIS’09, pp. 329–333, 2009.
13. J. Duato, S. Yalamanchili, L. Ni, Interconnection Networks : An Engineering Approach, Elsevier, 2003.
14. G. M. Chiu, “The odd-even turn model for adaptive routing,” in IEEE Transactions on Parallel and Distributed Systems, vol. 11, no. 7, pp. 729–738, Jul 2000.
15. S. Kumar, A. Jantsch, J.P. Soininen, M. Forsell, M. Millberg, J. Öberg, K. Tiensyrjä, A. Hemani, “A Network on Chip Architecture and Design Methodology”, In IEEE Annual Symposium on VLSI, April 2002.
16. R. Holsmark, S. Kumar, “Design Issues and Performance Evaluation of Mesh NoC with Regions”, In IEEE NorChip, Oulu, Finland, pp. 40-43, Nov. 2005.
17. e. a. M. D. Schroeder, “Autonet: A High-Speed Self-Configuring Local Area Network Using Point-to-Point Links”, In Journal on Selected Areas in Communications, vol. 9, Oct. 1991.
18. A. Jouraku, A. Funahashi, H. Amano, M. Koibuchi, “L-turn routing: An Adaptive Routing in Irregular Networks”, In the International Conference on Parallel Processing, pp. 374-383, Sep. 2001.
19. Y.M. Sun, C.H. Yang, Y.C Chung, T.Y. Hang, “An Efficient Deadlock-Free Tree-Based Routing Algorithm for Irregular Wormhole-Routed Networks Based on Turn Model”, In International Conference on Parallel Processing, vol. 1, pp. 343-352, Aug. 2004.
20. J. Wu, L. Sheng, “Deadlock-Free Routing in Irregular Networks Using Prefix Routing”, DIMACS Tech. Rep. 99-19, Apr. 1999.
21. B. Black and et al., Die stacking (3d) microarchitecture. In MICRO 39, pages 469–479, 2006.
22. N. Choudhary, M. Gaur, V. Laxmi, “Irregular NoC simulation Framework: IrNIRGAM”, in proceeding of the international conference ETNCC 2011, pp. 1-5, April 2011.
23. L. Jain, B. M. Al-Hashimi, M. S. Gaur, V. Laxmi, A. Narayanan, “NIRGAM: A Simulator for NoC Interconnect Routing and Application Modelling”. DATE 2007, 2007.
24. J. Hu, R. Marculescu, “Energy-Aware Mapping for Tile-based NOC Architectures Under Performance Constraints”. In ASP-DAC 2003, Jan 2003.
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232-235
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62.
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Authors:
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K.V.Satyanarayana, B.Bhaskar Rao
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Paper Title:
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Implementation Of A New Binary Tree Using Huffman Encoder
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Abstract: Lossless compression of a sequence of symbols is important in Information theory as well as today’s IT field. Huffman coding is lossless and is most widely used. However, Huffman coding has some limitations depending on the stream of symbols appearing in a file. In fact, Huffman coding generates a code with very few bits for a symbol that has a very high probability of occurrence and a larger number of bits for a symbol with a low probability of occurrence [1]. In this paper, we present a novel technique that subdivides the original symbol sequence into two or more subsequences. We then apply Huffman coding on each of the subsequences. This proposed scheme gives approximately 10-20% better compression in comparison with that of straightforward usage of Huffman coding.
Keywords: Huffman decoding, Table lookup
References:
1. D. Huffman, “A method for the construction of minimum redundancy code”, Proc. IRE, vol. 40, pp. 1098-1101, 1952.
2. S. Choi, and M. Lee, “ High Speech Pattern Matching for a Fast Huffman Decoder”, IEEE Transactions on Consumer Electronics, vol. 41, pp. 97-103, February 1995. [3] S. Cho, T. Xanthopoulos, and A. Chandrakasan, “A lowpower Variable Length Decoder for MPEG-2 Based on Non uniform Fine-Grain Table Partitioning”, IEEE Transactions on VLSI systems, vol. 7, no. 2, pp. 249-257, June 1999.
3. S. Lei, and M. Sun, “ An entropy coding system for digital HDTV applications”, IEEE Transactions on Circuits and Systems for Video Technology, vol. 2, No. 1, pp. 147- 155, March 1991.
4. ISO/iec 11172-3:1993 “Information Technology – coding of Moving Pictures and associated audio for Digital Storage Media at up to about 1.5 Mbit/s –part 3 : Audio ”
5. A. Gersho, and A. Gray, “Vector Quantization and Signal Compression”, Kluwer Academic Publications, 1991.
6. CCITT Recommendation T.81, “Digital compression and coding of continuous-tone still images”, 1992.
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336-339
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63.
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Authors:
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Panchakshari H.V., Girish D.P., M Krishn
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Paper Title:
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Effect of Deep Cryogenic Treatment on Microstructure, Mechanical and Fracture Properties of Aluminium-AL2O3 Metal Matrix Composites
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Abstract: The aim of this research work was to focus on the effect of deep cryogenic treatment on the microstructure, mechanical and fracture properties of Al6061/Al2O3 metal matrix composites (MMCs) at -196 °C for different time duration. Al/Al2O3 metal matrix composites containing 5, 10, 15 and 20% of Al2O3 are produced by liquid metallurgy technique. After deep cryogenic treatment of samples at liquid nitrogen temperature, the microstructure of specimens shows the change in distribution of precipitates. The precipitate particles almost dissolved in the matrix and obtained very fine grain boundaries. The modification of microstructure of MMCs due to cryogenic treatment shows significant improvement in mechanical properties of the MMCs. The preferred orientation of grains was sufficiently corroborated by XRD results of Al/Al2O3 composite before and after cryogenic treatment.
Keywords: Metal Matrix Composites, Cryogenic treatment, microstructure, microhardness.
References:
1. Jun Wang, Ji Xiong, Hongyuan Fan, Hong-Shan Yang, Hao-Huai Liu, Bao-Luo Shen Effects of high temperature and cryogenic treatment on the microstructure and abrasion resistance of a high chromium cast iron, Journal of Materials Processing Technology, vol. 209(7) (2009), pp. 3236-3240
2. Hong-xiao CHI, Dang-shen MA, Qi-long YONG, Li-zhi WU, Zhan-pu ZHANG, Yong-wei WANG, Effect of Cryogenic Treatment on Properties of Cr8-Type Cold Work Die Steel, Journal of Iron and Steel Research, International, vol. 17(6), (2010), pp. 43-46,59
3. P. Poza, J. Llorca, Fracture toughness and fracture mechanisms of Al-Al2O3 composites at cryogenic and elevated temperatures, Materials Science and Engineering: A, vol. 206 (2), (1996), pp.183-193.
4. Joel Hemanth, Tribological behavior of cryogenically treated B4Cp/Al–12% Si composites, Wear, vol 258(11-12), (2005), pp. 1732-1744
5. K.H.W. Seah, J. Hemanth, Cryogenic effects during casting on the wear behavior of aluminum-alloy/glass MMCs, Composites Part A: Applied Science and Manufacturing, vol.38(5), (2007),pp. 1395-1402
6. Kaveh Meshinchi Asla, Alireza Tari, Farzad Khomamizadeh, Effect of deep cryogenic treatment on microstructure, creep and wear behaviors of AZ91 magnesium alloy Materials Science and Engineering A, vol.523 (2009) vol. 27–31
7. D.S. Mehta, S.H. Masood, W.Q. Song, Investigation of wear properties of magnesium and aluminum alloys for automotive applications, Journal of Materials Processing Technology, vol.155-156, (2004),pp. 1526-1531
8. Kaveh Meshinchi Asl, Alireza Tari, Farzad Khomamizadeh, Effect of deep cryogenic treatment on microstructure, creep and wear behaviors of AZ91
magnesium alloy, Materials Science and Engineering: A, vol.523, (1-2), (2009), pp. 27-31
9. P.K Govindan Potti, B Nageswara Rao, V.K Srivastava, Residual strength of aluminum–lithium alloy center surface crack tension specimens at cryogenic temperatures, Cryogenics, Volume 40, Issue 12, 2000, Pages 789-795
10. A.R Kennedy, S.M Wyatt, The effect of processing on the mechanical properties and interfacial strength of aluminium / TiC MMCs, Composites Science and Technology, vol 60(2), (2000), pp.307-314
11. K.H.W Seah, J Hemanth, S.C Sharma, Mechanical properties of aluminum/quartz particulate composites cast using metallic and non-metallic chills, Materials & Design, vol. 24 (2), (2003),pp. 87-93
12. B. Dutta, M.K. Surappa, Microstructure evolution during multidirectional solidification of Al-Cu-SiC composites Composites Part A: Applied Science and Manufacturing, vol. 29,( 5-6), (1998), pp.565-573
13. Jiang Xian-Quan, Ning Li, Hong He, Zhang Xiu-Jin, Hao Yang, Effect of Cryogenic Treatment on Mechanical Properties and Microstructure of 3102 Al alloy, Materials Science Forum, vol. 546-49 (2), pp.845-848.
14. Olivier Beffort, Siyuan Long, Cyril Cayron, Jakob Kuebler, Philippe-André Buffat, Alloying effects on microstructure and mechanical properties of high volume fraction SiC-particle reinforced Al-MMCs made by squeeze casting infiltration, Composites Science and Technology, vol. 67, (3-4), (2007), pp.737-745.
15. K. Mahadevana, K. Raghukandanb, B.C. Pai , U.T.S. Pillai, Influence of precipitation hardening parameters on the fatigue strength of AA 6061-SiCp composite, Journal of Materials Processing Technology, vol. 198(2008), pp.241–247
16. Guozhi Ma, Ding Chen, Zhenhua Chen, Wei Li Effect of cryogenic treatment on microstructure and mechanical behaviors of the Cu-based bulk metallic glass matrix composite, Journal of Alloys and Compounds, Vol. 505,(1) (2010) pp. 319-323
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340-346
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64.
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Authors:
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Naveen Choudhary
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Paper Title:
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Bursty Communication Performance Analysis of Network-on-Chip with Diverse Traffic Permutations
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Abstract: To satisfy the increasing communication demands of complex VLSI circuits, Network on Chip (NoC) has been introduced as a new paradigm, where processing and communication can be independently catered by communication infrastructure design. Network on Chip proposes to establish a communication infrastructure for the complex VLSI circuit in such a way that communication between any nodes in the circuit is possible even if the circuit blocks are not directly connected by a direct channel. Each circuit block of the whole circuit can be assumed as an Intellectual Property (IP) which may be a microprocessor, memory or ASIC, etc. In this paper the performance of standard 2D mesh NOC is analyzed for bursty communication traffic for various traffic or topology mapping patterns such as butterfly, transpose etc over a NOC simulation framework. The routing for the NoC is assumed to be XY and OE.
Keywords: NoC, Simulation, VLSI, Transpose, Traffic latency
References:
1. W. J. Dally, B. Towles, "Route packets, not wires: on-chip interconnection networks", in Proceedings DAC, pp. 684-689, June 2001.
2. L. Benini, G. DeMicheli., “Networks on Chips: A New SoC Paradigm”, In IEEE Computer Vol. 35, No. 1 pp. 70–78, January 2002.
3. S. Kumar, A. Jantsch, J.-P. Soininen, M. Forsell, M. Millberg, J. Oberg, K. Tiensyrja, and A. Hemani, “A Network on Chip Architecture and Design Methodology”, In Proceedings of VLSI Annual Symposium (ISVLSI 2002), pp. 105–112, 2002
4. M. Millnerg, E. Nilsson, R. Thid, A. Jantsch, “Guaranteed bandwidth using looped containers in temporally disjoint networks within the nostrum network-on-chip,” in Proceedings of Design, Automation and Testing in Europe Conference (DATE). IEEE, pp. 890–895, 2004.
5. J. Duato, S. Yalamanchili, L. Ni, Interconnection Networks : An Engineering Approach, Elsevier, 2003.
6. L.-S. Peh, W. J. Dally, “A delay model for router microarchitectures,” in IEEE Micro 21, pp. 26–34, 2001.
7. P. Poplavko, T. Basten, M. Bekooij, J. van Meerbergen, B. Mesman, “Task level timing models for guaranteed performance in multiprocessor networks-on-chip,” in CASES ’03: Proceedings of the 2003 International Conference on Compilers, Architecture and Synthesis for Embedded systems, New York, USA, pp. 63-72, ACM, 2003.
8. A. Hansson et al., “Applying data flow analysis to dimension buffers for guaranteed performance in networks on chip,” in Proceedings of the International Symposium on Networks-on-Chip (NOCS), April 2008.
9. A. Hansson, M. Coenen, and K. Goossens, “Undisrupted quality-of-service during reconfiguration of multiple applications in networks on chip,” in Proceedings of Design, Automation & Test in Europe Conference & Exhibition, pp. 1–6, DATE 16-20, April 2007.
10. A. Hansson and K. Goossens, “Trade-offs in the configuration of a network on chip for multiple use-cases,” 1^{ ext{st}} International Symposium on NoC (NOCS 2007), pp. 233–242, 7-9May 2007.
11. S. Murali, M. Coenen, A. Radulescu, K. Goossens, and G. De Micheli, “A methodology for mapping multiple use-cases onto networks on chips,” in Proceedings Design, Automation and Test in Europe, 2006 (DATE ’06), vol. 1, pp. 1–6, 6-10 March 2006.
12. W. Zhang, L. Hou, J. Wang, S. Geng, W. Wu, “Comparison research between XY and odd-even routing algorithm of a 2-dimension 3 imes3 mesh topology network-on-chip,” in GCIS’09, pp. 329–333, 2009.
13. G. M. Chiu, “The odd-even turn model for adaptive routing,” in IEEE Transactions on Parallel and Distributed Systems, vol. 11, no. 7, pp. 729–738, Jul 2000.
14. Lavina Jain et al., “NIRGAM: A Simulator for NoC Interconnect Routing and Application Modelling, Proc. DATE 2007, 2007
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347-351
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65.
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Authors:
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Gururaja M N, A N Hari Rao
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Paper Title:
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A Review on Recent Applications and Future Prospectus of Hybrid Composites
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Abstract: Hybrid composite Materials have extensive engineering application where strength to weight ratio, low cost and ease of fabrication are required. Hybrid composites provide combination of properties such as tensile modulus, compressive strength and impact strength which cannot be realized in composite materials. In recent times hybrid composites have been established as highly efficient, high performance structural materials and their use is increasing rapidly. Hybrid composites are usually used when a combination of properties of different types of fibres have to be achieved, or when longitudinal as well as lateral mechanical performances are required. The investigation of the novel applications of hybrid composites has been of deep interest to the researchers for many years as evident from reports. This paper presents a review of the current status of hybrid composite materials technology, in terms of materials available and properties, and an outline of some of the trends, obvious and speculative, with emphasis on various applications including some details of smart hybrid composites.
Keywords: Hybrid composites, strength, stiffness, tensile modulus, smart hybrid composites
References:
1. Hayashi, T. 'On the improvement of mechanical properties of composites by hybrid composition', Proceedings of the Eighth International Reinforced Plastics Conference (October 1972) paper 22
2. Hofer,.K.E., Rao, N. and Stander, M. 'Fatigue behaviour of graphite-glass-epoxy composites', Proceedings of the Second International Carbon Fibers Conference (February 1974) paper 31
3. Tetlow, R. - Carbon Fibres in Engineering, Chap. 4, Ed. M. Langley McGraw Hill Sept, 1973.
4. Tetlow, R. - Design and Testing of Some Reinforced Plastic Components "Fibre Reinforced Materials" Inst. Of Civil Eng. 1977.
5. P. Sittner and R. Stalmans, “Developing Hybrid Polymer Composites with Embedded Shape-Memory Alloy Wires”, Journal of Materials October, 2000.
6. D.A. Griffin, T.D. Aswill: Proceedings of the 48 International SAMPE Symposium and Exhibition. Long Beach, CA (2003).
7. D.A. Griffin: SAND 2004-0073, vol. II, Sandia National Laboratories (2004).
8. M.J. Boone, V. Caccese, R. Bragg and K.A. Berube, “Mechanical Testing of Epoxy Adhesives for Naval Applications,” UMMACH- RPT-01-03, April 2003
9. J.L. Grenestedt, “Steel to Composite Joints in Hybrid Ships,” Proc. International Conference of Sandwich Construction, Fort Lauderdale, March 31-April 2, 2003
10. S.M. Walsh, B.R. Scott, D.M. Spagnuolo, “The Development of Hybrid Thermoplastic Ballistic Material with Application to Helmets”, Army Research Labs, Aberdeen, MD, December 2005.
11. D.Thomas Campbell, David R Cramer, “Hybrid Thermoplastic Composite Ballistic Helmet Fabrication Study” Advancement of Materials & Process Engineering, 2008.
12. Keller, T. Use of Fiber Reinforced Polymers in Bridge Construction. International Association for Bridge and Structural Engineering. Zurich,(2003).
13. Hiroshi Mutsuyoshi1, Thiru Aravinthan, “Development of New Hybrid Composite Girders Consisting of Carbon and Glass Fibers”, Saitama University, & Toray Industries, Inc., Japan
14. Pramod Srivastava, Pravin Ahire, Milind S Chavan, Girish Sharma, P. Narsingh, “New hybrid Composite Cable for Power transmission, Critical Signaling, & Telecom application” Sterlite Optical Technologies Ltd. Silvassa. UT of Dadara & Nagar Haveli, INDIA.
15. Wood, A.S. 'Hybrid reinforcement: low cost route to premium performance' Mod Plastics 55 No 3, March 1978, pp 48-50
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352-355
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66.
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Authors:
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Pratibhadevi Tapashetti, A.S Umesh, Ashalatha Kulshrestha
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Paper Title:
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Design and Simulation of Energy Efficient Full Adder for Systolic Array
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Abstract: Full adder is an essential component for the design and development of all types of processors viz. digital signal processors (DSP), microprocessors, Microcontrollers, ARM processors etc. Full adder is the basic building block for all arithmetic and logical operations. For the speed improvement the systolic array using the full adders is involved in almost all the processors. Adders are the core elements of complex arithmetic operations like addition, subtraction, multiplication, division, exponentiation etc. In most of these systems adder lies in the critical path that affects the overall speed of the system. So enhancing the performance of the 1-bit full adder cell is a significant goal. The present study proposes an efficient full adder cell design and simulation using the simulation software Edvin XP which considerably increases the speed.
Keywords: Auto Sequencing Memory (ASM), Central processing Units (CPU), Data Processing Units (DPU).
References:
1. Jonathan Break, “Systolic Arrays & Their Applications”
2. M. Kunde, H.W. Lang, M. Schimmler, H. Schmeck, H. Schröder: The Instruction Systolic Array and its Relation to Other Models of Parallel Computers. Parallel Computing 7, 25-39 (1988)
3. H.W. Lang: The Instruction Systolic Array, a Parallel Architecture for VLSI. Integration, the VLSI Journal 4, 65-74 (1986)
4. Sung Burn Pan, Seung Soo Chae and Rae-Hong Park, VLSI Architecture for Block Matching Algorithms using Systolic Array, IEEE Transactions on Circuits and Systems for Video Technology, Vol. 6, No. 1, February 1996.
5. M. Shams, T. K. Darwish and M. A. Bayoumi, “Performance Analysis of Low-Power 1-Bit CMOS Full-Adder Cells,” IEEE Trans. on VLSI Systems, vol. 10, Feb. 2002.
6. N. Zhuang and H. Wu, “A New Design of the CMOS Full-Adder,” IEEE J. Solid-State Circuits, pp. 840- 844, May 1992.
7. Samir Palnitkar, “Verilog HDL, A Guide to Digital Design and Synthesis", Pearson Education,ISBN: 81-7758-918-0
8. M. Shams and M. A. Bayoumi, “A Novel High Performance CMOS 1-Bit Full-Adder Cell,” IEEE Trans. on Circuits and Systems II: Analog and Digital Signal Processing, pp. 478-481, May 2000.
9. Abu Shama, A. Elechouemi, S. Sayed and M. Bayoumi, “An Efficient Low Power Basic Cell for Adders,” Proc. 38th Midwest Symposium on Circuits and Systems, pp. 306-309, 1996.
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356-360
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67.
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Authors:
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R . Jayanthi, I.A.Chidambaram
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Paper Title:
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Power System Restoration Index for Load Frequency Control Assessment Using Artificial Bee Colony Algorithm in a Two-Area Reheat Interconnected Power System Co-ordinated with SMES Units
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Abstract: This paper proposes evaluation of Restoration Indices for the Load-Frequency Control assessment of a Two-Area Two Unit Interconnected Power System (TATURIPS) coordinated with Superconducting Magnetic Energy Storage (SMES) units. As Proportional Integral (PI) type controller is still widely used for the solution of the Load Frequency Control (LFC) problem, in this paper also PI controllers are used. The optimal gain tuning of PI controllers for various case studies for the LFC problem is proposed and obtained using Artificial Bee Colony (ABC) algorithm. These controllers are designed and implemented in a TATURIPS coordinated without and with SMES units. The system was simulated and the frequency deviations, tie-line power deviation, control input deviations and additional mechanical power generation required for step load disturbance of 0.01 p.u.MW and 0.04 p.u.MW without and with outage condition in area-1 are presented. The simulation results and the evaluation of the Restoration Indices shows that the TATURIPS coordinated with SMES units ensures a better transient and steady state response and improved Restoration Indices than that of TATURIPS without SMES Units.
Keywords: Load Frequency Control (LFC), Proportional Integral (PI) Controller, Super Conducting Magnetic Energy Storage (SMES) device, Restoration Index (RI).
References:
1. H. Shayeghi, H.A. Shayanfar, A. Jalili, “Load Frequency Control Strategies: A state-of the-art survey for the researcher”, Energy Conversion and Management, Vol.50, No.2, pp.344-353, 2009.
2. Ibraheem, P. Kumar, D.P. Kothari, “Recent philosophies of automatic generation control strategies in power systems” IEEE Transactions on Power System, Vol.20, No.1, pp. 346-357, 2005.
3. Howard F.Illian, “Expanding the requirements for Load Frequency Control” 06GM0675, pp 1-7, IEEE Transactions, 2006.
4. R.Roy, P.Bhatt and S.P.Ghoshal, “Evolutionary Computation based Three-Area Automatic Generation Control”, ExpertSystems with Applications, Vol 37, Issue 8, pp.5913–24, 2010.
5. Chidambaram, I.A and S.Velusami, “Design of Decentralized Biased Controllers for Load Frequency Control of Interconnected Power Systems” Electric Power Components and Systems, Vol. 33, No.12, pp. 1313-1331, 2005.
6. Demiroren A., “Application of a self-tuning to power system with SMES”, European Transactions on Electrical Power (ETEP), Vol. 12, N0.2, pp.101-109, 2002.
7. A.Demiroren, E.Yesil, “Automatic generation control with fuzzy logic controllers in the power system including SMES units”, Electrical Power and Energy Systems, Vol: 26, pp.291–305, 2004.
8. R.J. Abraham, D. Das and A. Patra, “Automatic Generation Control of an Interconnected Hydrothermal Power System Considering Superconducting Magnetic Energy Storage”, Electrical Power and Energy Systems; 29, pp. 271-579, 2007.
9. S.C.Tripathy, R.Balasubramania and P.S.Chandramohanan Nair, “Adaptive Automatic Generation Control with Super Conducting Magnetic Energy Storage in
Power System”, IEEE Transactions On Energy Conversion, Vol.7, No.3, pp. 134-141, 1992.
10. D.Karaboga and B.Akay, “A Comparative Study of Artificial Bee Colony Algorithm”, Applied Mathematics and Computation, Vol. 214, pp. 108-132, 2009.
11. S.N.Omkar, J.Senthil Nath, R.Khandelwal, G.N.Naik and S.Gopalakrishnan, “Artificial Bee Colony (ABC) for Multi-Objective Design Optimization of Composite Structures”, Applied Soft Computing, Vol. 11, Issue 1, 2011.
12. D.Karaboga, B.Basturk, Artificial Bee Colony (ABC) Optimization Algorithm for Solving Constrained Optimization Problems, LNCS: Advances in Soft Computing: Foundations of Fuzzy Logic and Soft Computing, Vol.4529/2007springer-verlag, pp.789-798, 2007
13. M. Shanthakumar, Computer Based Numerical Analysis, Khanna Publishers, New Delhi, 1999.
14. Katsuhiko Ogata, Modern Control Engineering, Prentice Hall of India, New Delhi, 1986.
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361-370
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68.
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Authors:
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S. Rajkumar, V. Narayani, S. P. Victor
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Paper Title:
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Epidemic Analysis of uncertainty in Deception Detection under Fuzzified Anomalies
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Abstract: Nowadays in this competitive world of job seekers, the necessity of job makes many recruiters to provide more cautious on their selection process. The recruitment process is definitely a fuzzified anomaly for all the components available in the environment. The art of deception also changes its face with a modern artistic fashion. This paper deals with the uncertainty features which play the major role of Deception in a fuzzified environment of Recruitment process. We deal with the impacts of uncertainty in deception detections and also with the underlying environment of fuzzification. In this paper we proposed a Research Model which considers the linkage of fuzzification and uncertainty in Deception Detection. In this paper we implement our proposed model with an experiment which includes warning and lack of warning to the recruiters upon the competitors. Enumerated results and discussions mould the impact of uncertainty and fuzziness in Deception Detection.
Keywords: Deception, Fuzzy logic, Randomization, Uncertainty.
References:
1. Steve Woznaik, Kevin D.Mitnick, Willaim L.Simon,2002. “The art of deception: controlling the human element of security”. Wiley; 1 edition.
2. Zuckerman, M.,DePaulo, B.M. and Rosenthal, R.”Verbal and Nonverbal Communication of Deception”.In L.Berkowitz(Ed)(1981)
3. Burgoon, J.K., and Qin,T. “The Dynamic Nature of Deceptive Verbal Communication”. Journal of Language and Social Psychology, 2006, vol25(1), 1-22.
4. Bond,c.,F. “A world of lies: the global deception research team”, Journal of Cross-culture Psychology, 2006, Vol.37(1), 60-74.
5. Pennebaker,J.W,Mehl,M.R.&Niederhoffer,K. ”Psychological aspects of natural language use: our words, ourselves”. Annual Review of Psychology, 2003, 54,547-577
6. Whissell,C., Fournier,M.,Pelland,R., Weir, D.,& Makaree,K. ”A comparison of Classfiifcation methods for predicting deception in computer-mediated communication”. Journal of Management Information systems, 2004,20(4),139-165.
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371-376
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69.
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Authors:
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R.Valli, P.Dananjayan
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Paper Title:
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Power Control with MIDRS Codes in VMIMO WSN Using Game Theoretic Approach
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Abstract: Improvements in electronic and computer technologies have tiled the path for explosion of wireless sensor networks (WSN). A fundamental component of resource management in WSN is transmitter power control and an efficient power control technique is essential to support system quality and efficiency. The data transmitted from the sensor nodes is highly susceptible to error in a wireless environment which increases the transmit power. Error control coding (ECC) schemes can improve the system performance and has an impact on energy consumption. Further the adverse impacts caused by radio irregularities and fading increases the energy consumption and thereby reduces the WSN lifetime. To reduce the fading effects in wireless channel, multi-input multi-output (MIMO) scheme is utilised for sensor network. This paper proposes a power control solution considering Multivariate Interpolation Decoding RS (MIDRS) Code in Virtual MIMO (VMIMO) WSN using game theoretic approach. The game is formulated as a utility maximizing distributed power control game while considering the pricing function. VMIMO utilising space time block code (STBC) along with MIDRS code enables to achieve higher energy savings and longer network lifetime by allowing nodes to transmit and receive information jointly. The performance of the proposed power control scheme with MIDRS code for the virtual MIMO wireless sensor network is evaluated in terms of utility, power efficiency, energy consumption and network lifetime.
Keywords: Game theory, MIDRS code, Space time block code, Virtual MIMO, Wireless sensor network
References:
1. L.Akyildiz, W.Su, Y.Sankarasubramanian, E.Cayirci, “A survey on sensor networks,” IEEE Communications Magazine, vol.40, no.8, 2002, pp.102-114.
2. Shraddha Srivastava, Christian Spagnol, Emanuel Popovici, “Ananlysis of a set of error correcting schemes in multi-hop wireless sensor networks,” Proceedings of IEEE PRIME 2009, Ireland. pp.1-4
3. S. Buchegger, and J. Le Boudec, “Performance Analysis of the CONFIDANT Protocol,” Proceedings of Third ACM International Symposium on Mobile AdHoc Networking & Computing, 2002, pp.226-232.
4. L. Buttyan, and J.P. Hubaux, “Nuglets: A Virtual Currency to Stimulate Cooperation in Self organized Mobile Ad-Hoc Networks,” Technical Report DSC/2001/001, Swiss Federal Institute Of Technology, January 2001.
5. W. Wang, M. Chatterjee, and K.Kwiat, “Enforcing Cooperation in Ad Hoc Networks with Unreliable Channel,” Proceedings of Fifth IEEE International Conference on Mobile Ad-Hoc and Sensor Systems (MASS), 2008, pp.456-462.
6. V. Srinivasan, P. Nuggehalli, C.Chiasserini, and R.Rao, “Cooperation in Wireless Ad Hoc Networks,” Proceedings of IEEE INFOCOM, April
7. 2003, pp. 808-817.
8. S.Cui, A.J.Goldsmith, A.Bahai, “Energy-efficiency of MIMO and cooperative MIMO techniques in sensor networks,” IEEE Journal on Selected Areas in Communications, vol 22, no.6, 2004, pp. 1089-1098.
9. S. K.Jayaweera, “Energy analysis of MIMO techniques in wireless sensor networks,” Proceedings of Annual Conference on Information Sciences and Systems, Princeton, NJ, 2004; pp. 1-6.
10. F. Parvaresh and A. Vardy, “Multivariate Interpolation Decoding Beyond the Guruswami Sudan Radius,” 42nd Annual Allerton Conference on Communications, Control, and Computing, Illinois, September 2004.
11. R.Valli, A.Sharmila and P.Dananjayan “Utility based power control with pricing using MIDRS codes in Wireless Sensor Networks,” Proceedings of IEEE International Symposium on Humanities, Science and Engineering Research, Kualalumpur, Malaysia, 5-7 June 2011.
12. D.Fudenberg and J.Tirole, Game Theory, MIT Press, Cambridge, MA, 1991
13. Shamik Sengupta, Mainak Chatterjee, and Kevin A. Kwiat, “A Game Theoretic Framework for Power Control in Wireless Sensor Networks,” IEEE Transactions on Computers, vol 59, no.2, February 2010, pp.231-242.
14. W.Heinzelman, A.Chandrakasan, and H.Balakrishnan, “An application-specific protocol architecture for wireless microsensor networks,” IEEE Transactions on Wireless Communication. vol.1, no.4, 2002, pp. 660-670.
15. Xiaohua Li, Mo Chen and Wenyu Liu, “Application of STBC encoded cooperative transmissions in wireless sensor networks,” IEEE Signal Processing Letters, vol.12, no.2, February 2005, pp.134-137.
16. R.Valli, P.Dananjayan, “A Non-Cooperative Game Theoretical Approach for Power Control in Virtual MIMO Wireless Sensor Network,” International Journal of UbiComp (IJU), vol.1 no.3, 2010, pp.44-55.
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377-381
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70.
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Authors:
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B.Siva kumar, K.Tharani, S.Venkatasen
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Paper Title:
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Power – Aware Routing In Manet Using Randomized Casting
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Abstract: In a typical wireless mobile ad hoc network (MANET) using a shared communication medium, every node receives or overhears every data transmission occurring in its vicinity. However, this technique is not applicable when a power saving mechanism (PSM) such as the one specified in IEEE 802.11 is employed, where a packet advertisement period is separated from the actual data transmission period. When a node receives an advertised packet that is not destined to it, it switches to a low-power state during the data transmission period, and thus, conserves power. However, since some MANET routing protocols such as Dynamic Source Routing (DSR) collect route information via overhearing, they would suffer if they are used with the IEEE 802.11PSM. Allowing no overhearing may critically deteriorate the performance of the underlying routing protocol, while unconditional overhearing may offset the advantage of using PSM. This paper proposes a new communication mechanism, called Random Cast or Rcast, via which a sender can specify the desired level of overhearing in addition to the intended receiver by using(Adhoc On-demand Distance Vector) AODV protocol. Therefore, it is possible that only a random set of nodes overhear and collect route information for future use. Rcast improves not only the energy efficiency, but also the energy balance among the nodes, without significantly affecting the routing efficiency.
Keywords: Energy balance, energy efficiency, mobile ad hoc networks, network lifetime, overhearing, power saving mechanism.
References:
1. NS-2, The ns Manual (formally known as NS Documentation) available at http: //www. isi.edu/nsnam/ns/doc.
2. Samyak Shah, Amit Khandre, Mahesh Shirole and Girish Bhole,”Performance Evaluation of Ad Hoc Routing Protocols Using NS2 Simulation” International Conference on Mobile and Pervasive Computing (CoMPC–2008), pp 167-171.
3. Z.J. Hass, J.Y. Halpern, and L. Li, “Gossip-Based Ad Hoc Routing,” Proc. IEEE INFOCOM, pp. 1707-1716, 2002.
4. D.B. Johnson and D.A. Maltz, “Dynamic Source Routing in Ad Hoc Wireless Networks,” Mobile Computing, pp. 153-181, Kluwer, 1996.
5. S. Lim, C. Yu, and C. Das, “Rcast: A Randomized Communication Scheme for Improving Energy Efficiency in Mobile Ad Hoc Networks,” Proc. 25th IEEE Int’l Conf.
Distributed Computing Systems (ICDCS ’05), pp. 123-132, 2005.
6. S. Singh, M. Woo, and C.S. Raghavendra, “Power-Aware Routing in Mobile Ad Hoc Networks,” Proc. ACM MobiCom, pp. 181-190, Oct. 1998.
7. J.-H. Chang and L. Tassiulas. Energy Conserving Routing in Wireless Ad-hoc Networks. In Proc. IEEE INFOCOM, pages 22–31, 2000.
8. S. R. Das, C. E. Perkins, and E. M. Royer. Performance Comparison of Two On-demand Routing Protocols for Ad Hoc Networks. In Proc. IEEE INFOCOM, pages 3–12, 2000.
9. Y. Hu and D. B. Johnson. Caching Strategies in On-Demand Routing Protocols for Wireless Ad Hoc Networks. In Proc. ACM MOBICOM, pages 231–242, 2000.
10. D. B. Johnson and D. A. Maltz. Dynamic Source Routing in Ad Hoc Wireless Networks. In Mobile Computing, pages 153–181, Kluwer 1996.
11. C. Perkins and E. M. Royer. Ad-hoc On-Demand Distance Vector Routing. In 2nd IEEE workshop on Mobile Computing Systems and Applications, pages 90–100, 1999.
12. Y.-C. Tseng, C.-S. Hsu and T.-Y. Hsieh. Power-Saving Protocol for IEEE 802.11-Based Multi-Hop Ad Hoc Networks. In Proc. IEEE INFOCOM, pages 200–209, 2002.
13. H. Woesner, J. Ebert, M. Schlager, and A. Wolisz. Power- Saving Mechanisms in Emerging Standards for Wireless LANs: The MAC Level Perspective. IEEE Personal Communications, 5(3):40–48, Jun 1998.
14. R. Zheng and R. Kravets. On-Demand Power Management for Ad Hoc Networks. In Proc. IEEE INFOCOM, pages 481–491, 2003.
15. Sunho Lim, Chansu Yu, Chita R.Das. “Random Cast: An Energy-Efficient Communication Scheme for Mobile Ad Hoc Networks,” Proc.IEEE Transaction on Mobile Computing, Vol.8, No .8, August 2009.
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382-387
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71.
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Authors:
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D. Sreenivasa Rao, Y. Gangadhar, V.S. Giridhar Akula
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Paper Title:
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Fuzzy Based Adaptive Filters in Color Image Processing
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Abstract: Noise reduction is the very important stage of image processing and pattern reorganization. Many researches find new tools and filters for noise reduction. This paper proposed a fuzzy based adaptive filter. The proposed filter is composed with the existing filter like VDF, VMF and VRF with Gaussian noise, impulse noise and mixed Gaussian Noise. The proposed method is proved to be a best suitable one with a P value of 0.23.
Keywords: Rectangular Window, Rational Functions, Fuzzy Logic, Color Space, Trapezoid Fuzzy Subsets, Fuzzy Membership Function, Distances Function Sub Filters, Power Parameter.
References:
1. J. Astola, P. Haavisto, Y. Neuvo, Vector median filter, Proc. IEEE 78 (1990) 678–689.
2. L. Khriji, F. Alaya Cheikh, M. Gabbouj, High resolution digital resampling using vector rational filters, J. Opt. Eng. SPIE 38 (5) (1999) 893–901
3. P.E. Trahanias, D. Karakos, A.N. Venetsanopoulos, Directional processing of color images: theory and experimental results, IEEE Trans. Image Process. 5 (6)(1996) 868–880.
4. L. Khriji, M. Gabbouj, Vector median-rational hybrid filters for multichannel image processing, IEEE Signal Process. Lett. 6 (7) (1999) 186–190.
5. M. J. Swain, D. H. Ballard, “Color indexing", IJCV, vol. 7, no. 1, pp. 11-32, 1999.
6. B. Bouchon-Meunier, La Logique Floue et ses Applications, Addison-Wesley, 1995.
7. W.K. Pratt, Digital Image Processing, Wiley, New York, NY, 1991.
8. Lazhar Khriji, Moncef Gabbouj “Adaptive fuzzy order statistics - rational hybrid filters for color image processing” Fuzzy sets and systems 128(2002) 35-46.
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388-390
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72.
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Authors:
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G. Sunil Kumar, C.V.K Sirisha, Kanaka Durga.R, A.Devi
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Paper Title:
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Robust Preprocessing and Random Forests Technique for Network Probe Anomaly Detection
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Abstract: During the past few years, huge amount of network attacks have increased the requirement of efficient network intrusion détection techniques. Different classification techniques for identifying various real time network attacks have been proposed in the literature. But most of the algorithms fail to classify the new type of attacks due to lack of collaborative filtering technique and robust classifiers. In this project we propose a new collaborating filtering technique for preprocessing the probe type of attacks and implement a hybrid classifiers based on binary particle swarm optimization (BPSO) and random forests (RF) algorithm for the classification of PROBE attacks in a network. PSO is an optimization method which has a strong global search capability and is used for fine-tuning of the features whereas RF, a highly accurate classifier, is used here for Probe type of attacks classification.
Keywords: Random forest, self organizing map, intrusion detection, filtering, Normalization.
References:
1. D.S Bauer, M.E Koblentz,. NIDX- an expert system for real-time network intrusion detection, Proceedings of the Computer Networking Symposium, 1988. pp. 98-106.
2. Herv Debar, Marc Dacier, and Andreas Wespi, "Towards a Taxonomy of Intrusion Detection Systems", IBM Technical Paper, Computer Networks, Vol.39, Issue 9, pp. 805-822, April 1999.
3. S. Chebrolu, A. Abraham, J. P. Thomas, Feature Deduction and Ensemble Design of Intrusion Detection Systems, Computer & Security, 2004.
4. A.Sundaram, "An introduction to intrusion detection, Crossroads": The ACM student magazine, 2(4), April 1996.
5. D. Denning, "An intrusion-detection model", In IEEE computer society symposium on research in security and privacy, 1986, pp. 118- 131.
6. Zhang Jianpei, Liu Jiandong, Yang Jing. Data Preprocessing Method Research for Web Usage Mining [J]. Computer Engineering and Applications, 2003, (10):191-193(In Chinese).
7. Yu kai,Xu Xiao-wei,Martin Ester,et al.Collaborative Filtering and Algorithms:Selecting Relevant Instances for Efficient and Accurate Collaborative Filtering[C]//Proceedings of the Tenth International Conference on Information and Knowledge Management. 2001:239-246.
8. Huang Z,Chen H,Zeng D.Applying Associative Retrieval Techniques to Alleviate the Sparsity Problem in Collaborative Filtering [J].ACM Transactions on Information Systems, 2004, 22(1):116-142.
9. Herlocker J,Konstan J,Terveen L,et al.Evaluating Collaborative Filtering Recommender Systems.ACM Trans.on Information Systems(TOIS),2004,22(1):5-53
10. KDD’99 datasets,The UCI KDD Archive,http://kdd.ics.uci.edu/databases/kddcup99/kddcup99.html, Irvine, CA, USA, 1999.
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391-395
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73.
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Authors:
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G. Sunil Kumar, C.V.K Sirisha, Kanaka Durga.R, A.Devi
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Paper Title:
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Web Users Session Analysis Using DBSCAN and Two Phase Utility Mining Algorithms
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Abstract: One of the important issues in data mining is the interestingness problem. Typically, in a data mining process, the number of patterns discovered can easily exceed the capabilities of a human user to identify interesting results. To address this problem, utility measures have been used to reduce the patterns prior to presenting them to the user. A frequent itemset only reflects the statistical correlation between items, and it does not reflect the semantic significance of the items. This proposed approach uses a utility based itemset mining approach to overcome this limitation. This proposed system first uses Dbscan clustering algorithm which identifies the behavior of the users page visits, order of occurrence of visits. After applying the clustering technique High Two phase utility mining algorithm is applied, aimed at finding itemsets that contribute high utility.Mining web access sequences can discover very useful knowledge from web logs with broad applications. Mining useful Web path traversal patterns is a very important research issue in Web technologies. Knowledge about the frequent Web path traversal patterns enables us to discover the most interesting Websites traversed by the users. However, considering only the binary (presence/absence) occurrences of the Websites in the Web traversal paths, real world scenarios may not be reflected. Therefore, if we consider the time spent by each user as a utility value of a website, more interesting web traversal paths can be discovered using proposed two-phase algorithm. User page visits are sequential in nature. In this paper MSNBC web navigation dataset is used to compare the efficiency and performance in web usage mining is finding the groups which share common interests General Terms Web session mining, log analysis.
Keywords: Webusage Mining, Itemset, DBScan, Association rules.
References:
1. Agrawal .R and Srikant .R (1994) : Fast algorithm for mining association rules in large databases, The 20th International Conference on Very Large Data Bases, pp. 487-99.
2. Lan G.C., Hong T.P., and Vincent S. Tseng. (2009): A two-phased mining algorithm for high on-shelf utility itemsets, The 2009 National Computer Symposium, pp. 100-5.
3. D.N.V.S.L.S. Indira, Jyotsna Supriya .P, and Narayana .S(July 2011): A Modern Approach of On-Shelf Utility Mining with Two-Phase Algorithm on Web Transactions, IJCSNS International Journal of Computer Science and Network Security, VOL.11 No.7
4. Lan G.C., Hong T.P., and Vincent S. Tseng (2011) : Reducing Database Scans for On-shelf Utility Mining, IETE Tech Rev 2011, vol 28,no. 2, pp.103-12.
5. Tseng V.S., Chu C.J., Liang T.(2006) : Efficient Mining of Temporal High Utility Itemsets from Data streams Proceedings of Second International Workshop on Utility-Based Data Mining, August 20, 2006.
6. Yao H., Hamilton H.J., and Butz C.J, (2004) : A foundational approach to mining itemset utilities from databases, Proceedings of the 3rd SIAM International Conference on Data Mining, pp. 482-486.
7. Yu-Cheng Chen and Jieh- Shan Yeh.(2010) : Preference utility mining of web navigation patterns, IET International Conference on Frontier Computing. Theory, Technologies & Applications (CP568) Taichung, Taiwan, pp.49-54.
8. Chang, C.C., Lin, C.Y.: Perfect hashing schemes for mining association rules. The Computer Journal 48(2), 168–179 (2005)
9. Grahne, G., Zhu, J.: Fast algorithms for frequent itemset mining using fp trees. IEEE Transactions on Knowledge and Data Engineering 17(10), 1347-1362 (2005).
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396-401
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74.
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Authors:
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S.Kokila, R.Shankar, P.Dananjayan
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Paper Title:
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Analysis of Call Admission Control Schemes for WLAN Coupled to 3G Network
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Abstract: Convergence of wireless local area network (WLAN) and third generation (3G) wireless network is expected to create new markets for service providers and tender enhanced services to the integrated network users. In this paper, call admission control (CAC) schemes viz., throughput (TP) based CAC and dynamic partitioning (DP) CAC with service differentiation for WLAN coupled to 3G network have been analysed. The 3G/WLAN convergence network with TP based admission control is developed for loose, tight and hybrid coupled network. DP scheme, a resource allocation mechanism is also implemented, in which the differentiation between the data and voice calls are made by using different thresholds. The performance parameters such as delay, throughput, voice and data call blocking probabilities are analysed for different coupled networks.
Keywords: 3G/WLAN convergence network, call admission control, inter-networking.
References:
1. Duk Kyung Kim, Griffith D and Golmie, N., “A new call admission control scheme for heterogeneous wireless networks”, IEEE Transactions on Wireless Communications,vol. 9 ,no. 10, pp. 3000 – 3005, October 2010.
2. TarekBejaoui and Nidal Nasser, “Hybrid Call Admission Control Scheme for Next Generation mobile networks”,. Proceedings of IEEE/ACS International Conference on Computer Systems and Applications, pp. 373 - 380, March 31 -April 4, Crete Island, Greece 2008
3. ProdromosMakris and CharalabosSkianis,” Multi-scenario based call admission control for coexisting heterogeneous wireless technologies”, Proceedings of IEEE "GLOBECOM", New Orleans, Nov. 30 -Dec. 4 ,2008.
4. Skehill, R., Barry, M., Kent, W., Callaghan, M., Gawley, N. and Mcgrath, S., “ The common RRM approach to admission control for converged heterogeneous wireless networks”, IEEE Transactions on Wireless Communications, vol. 14, no. 2 , pp. 48 – 56, April 2007.
5. Racha Ben Ali and Samuel Pierre, “On the impact of soft vertical handoff on optimal voice admission control in PCF-based WLANs loosely coupled to 3G networks”, IEEE Transactions on Wireless Communications, vol. 8, no. 3, March 2009
6. Wei Song, Yu Cheng, and WeihuaZhuang, “Improving voice and data services in Cellular/WLAN integrated network by admission control”, IEEE Transactions on Wireless Communications , vol. 6, no.11, pp.4025-4037, Nov. 2007.
7. Yang Xiao, Kin K. Leung and Yi Pan, “Architecture, mobility management and quality of service for integrated 3G and WLAN networks”, Published inJournal on Wireless Communications & Mobile Computing archive, vol. 5, no. 7, November 2005.
8. Xiang Chen, HongqiangZhai, XuejunTian, and Yuguang Fang,” Supporting QoS in IEEE 802.11e wireless LAN’s”, IEEE Transactions On Wireless Communications, vol. 5, no. 8, pp.2217-2227, August 2006.
9. Huan Chen, Chih-Chuan Cheng and Hsi-HsunYeh, “Guard-Channel-Based Incremental and Dynamic Optimization on Call Admission Control for Next- Generation QoS-Aware Heterogeneous Systems”, IEEE Transactions on Vehicular Technology,vol.57,no.5,pp.3064–3082,September2008.
10. H. Holma and A. Toskala, ”WCDMA for UMTS Radio Access for Third Generation Mobile Communications,” John Wiley & Sons, 3rd edition, 2004
11. Yu Zhou, YanxiaRong, Hyeong-Ah Choi, Jae-Hoon Kim, Jung KyuSohn, and Hyeong In Choi., ”Utility-based load balancing in WLAN/UMTS internetworking systems”, IEEE Transactions on Mobile Computing, vol. 6, no. 3, pp. 567-571, May 2007.
12. Qi Liu, Jian Yuan, Xiuming Shan, YueWangand and Wei Su, “ Dynamic load balance scheme based on mobility and service awareness in integrated 3G/WLAN networks”, Proceedings of Global Mobile Congress (GMC), Shanghai, China, Oct. 2010
13. S. Malarkkan and V.C. Ravichandran “Performance Analysis of Call Admission Control in WCDMA Systems with Mobility based Interference Margin Reservation” Journal of Computer Science, vol. 2, no. 10, pp 789-793, October 2006.
14. Bin Li, Lizhong Li, Bo Li, Sivalingam, K.M., and Xi-Ren Cao, “ Call Admission control for Voice/Data Integrated Cellular Networks: Performance Analysis and Comparative Study”, IEEE Journal on Selected Areas in Communications, vol. 22,no. 4, pp. 706 – 718, May2004.
15. I. C. Panoutssopoulos and S. Kotsopoulos, “Handover and new call admission policy optimization for 3G systems,” Journal of Wireless Networks, vol. 8, no. 3, pp. 381–389, November 2002.
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402-408
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75.
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Authors:
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G.Akhilesh, V.Suresh, P.Anvesh
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Paper Title:
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Power Flow Controller/Short Circuit Current Limiter
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Abstract: This paper presents the various advantages of Thyristor Controller Series Capacitor (TCSC), both as a Power Flow Controller, as well as a Short Circuit limiter during faults. The results have been derived and verified from the software PSCAD, and the graphs and calculations are included in the paper. The results and information included in the paper are sufficiently accurate.
Keywords: Modelling, power system dynamic stability.
References:
1. Dragan Jovcic and G. N. Pillai, “Analytical Modelling of TCSC Dynamics”, IEEE Transactions on Power Delivery, VOL 20, No.2, APRIL 2005
2. S. G. Jalali, R. A. Hedin, M. Pereira, and K. Sadek, “A stability model for the advanced series compensator (ASC),” IEEE Trans. Power Del., vol. 11, no. 2, pp. 1128–1137, Apr. 1996.
3. R. Fuerte-Esquivel, E. Acha, and H. Ambriz-Perez, “A thyristor con- trolled series compensator model for the power flow solution of practical power networks,” IEEE Trans. Power Syst., vol. 9, no. 15, pp. 58–64,Feb. 2000.
4. Jovcic, N. Pahalawaththa, M. Zavahir, and H. Hassan, “SVC dynamic analytical model,” IEEE Trans. Power Del., vol. 18, no. 4, pp.1455–1461, Oct. 2003.
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409-415
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76.
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Authors:
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S.Javeed Hussain,T. Satya Savithri, P.V. Sree Devi
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Paper Title:
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Segmentation of Tissues in Brain MRI Images using Dynamic Neuro-Fuzzy Technique
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Abstract: In this paper, an efficient technique is proposed for the precise segmentation of normal and pathological tissues in the MRI brain images. The proposed segmentation technique initially performs classification process by utilizing Fuzzy Inference System (FIS) and FFBNN. Both classifiers are utilizing the extracted image features as an input for the classification process. The features that are extracted in two ways from the MRI brain images. The FIS are used to make the classification process by generating the fuzzy rules using extracted features. Five features are extracted from the MRI images: they are two dynamic statistical features and three 2D wavelet decomposition features. In Segmentation, the normal tissues such as WM (White Matter), GM (Gray Matter) and CSF (Cerebrospinal Fluid) are segmented from the normal MRI images and pathological tissues such as Edema and Tumor are segmented from the abnormal images. The non-cortical tissues in the normal images are removed by the preprocessing stage. The implementation result shows the efficiency of proposed tissue segmentation technique in segmenting the tissues accurately from the MRI images. The performance of the segmentation technique is evaluated by performance measures such as accuracy, specificity and sensitivity. The performance of segmentation process is analyzed using a defined set of MRI brain image and compared against K-means clustering and Fuzzy ANN based segmentation methods.
Keywords: MRI, FFBNN, FIS
References:
1. Chaozhe Zhu and Tianzi Jiang, "Multicontext Fuzzy Clustering for Separation of Brain Tissues in Magnetic Resonance Images", NeuroImage, Vol.18, No. 3, pp. 685-696, 2003
2. Shan Shen, William Sandham, Malcolm Granat and Annette Sterr, "MRI Fuzzy Segmentation of Brain Tissue Using Neighborhood Attraction With Neural-NetworkOptimization", IEEE Transactions On Information Technology In Biomedicine, Vol. 9, No. 3, pp. 459-467, September 2005
3. Senthilkumaran and Rajesh, "Brain Image Segmentation using Granular Rough Sets", International Journal of Arts and Sciences, Vol. 3, No. 1, pp. 69 - 78, 2009
4. Pradipta Maji, Malay K. Kundu and Bhabatosh Chanda, "Second Order Fuzzy Measure and Weighted Co-Occurrence Matrix for Segmentation of Brain MR Images", Journal of Fundamenta Informaticae, Vol. 88, No. 1-2, pp. 161-176, 2008
5. Jzau-Sheng Lin, Kuo-Sheng Cheng, and Chi-Wu Mao, "Segmentation of Multispectral Magnetic Resonance Image Using Penalized Fuzzy Competitive Learning Network", Journal of Computers and Biomedical Research, Vol. 29, No. 4, pp. 314–326, 1996
6. Mostafa G. Mostafa, Mohammed F. Tolba, Tarek F. Gharib and Mohammed A-Megeed, "A Gaussian Multiresolution Algorithm For Medical Image Segmentation", In Proceedings of IEEE International Conference On Intelligent Engineering Systems, Assiut-Luxor, Egypt, 2003
7. Jagath C. Rajapakse, Jay N. Giedd and Judith L. Rapoport, "Statistical Approach to Segmentation of Single-Channel Cerebral MR Images", IEEE Transactions on Medical Imaging, Vol. 16, No. 2, pp. 176-186, April 1997
8. W.Wells, W.Grimson, R. Kikinis, F.A. Jolesz, “Adaptive Segmentation of MRI Data”, IEEE Transaction on Medical Imaging ,Vol.15, No. 4, pp. 429-442, August 1992
9. Nicolaos B. Karayiannis and Pin-I Pai, "Segmentation of Magnetic Resonance Images Using Fuzzy Algorithms for Learning Vector Quantization", IEEE Transactions on Medical Imaging, Vol. 18, No. 2, pp. 172-180, February 1999
10. Fitsum Admasua, Stephan Al-Zubia, Klaus Toenniesa, Nils Bodammerb and Hermann Hinrichsb, "Segmentation of Multiple Sclerosis Lesions from MR Brain Images Using the Principles of Fuzzy-Connectedness and Artificial Neuron Networks", In Proceedings of International Conference on Image Processing, Barcelona, Spain, Vol. 3, 2003
11. N. K. Subbanna, M. Shah, S. J. Francis, S. Narayanan, D. L. Collins, D. L. Arnold and T. Arbel, "MS Lesion Segmentation using Markov Random Fields", In Proceedings of International Conference on Medical Image Computing and Computer Assisted Intervention, London, UK, September 2009
12. Kenneth Revett and Aurangzeb Khan, "An On-Line (Real-Time) Automated MRI Based Pathology Detection System Using Selforganised Maps", In Proceedings of Virtual Multi Conference on Computer Science and Information Systems, pp. 213-216, 2005
13. Nahla Ibraheem Jabbar and Monica Mehrotra, "Application of Fuzzy Neural Network for Image Tumor Description", World Academy of Science, Engineering and Technology, Vol. 44, pp. 575-577, 2008
14. Manisha Sutar and Janwe, "A Swarm-based Approach to Medical Image Analysis", Global Journal of Computer Science and Technology, Vol. 11, No. 3, pp. 23-26, March 2011
15. Pradipta Maji, Malay K. Kundu and Bhabotosh Chanda, "Segmentation of Brain MR Images Using Fuzzy Sets and Modified Co-Occurrence Matrix", In Proceedings of IET International Conference on Visual Information Engineering, Bangalore, India, pp. 327-332, 2006
16. Forghani, Forouzanfar and Forouzanfar, Tehran "MRI Fuzzy Segmentation of Brain Tissue Using IFCM Algorithm with Particle Swarm Optimization", In Proceedings of International Symposium on Computer and Information Sciences, Ankara, pp. 1-4, 2007
17. Nicolaos B. Karayiannis, "A Methodology for Constructing Fuzzy Algorithms for Learning Vector Quantization”, IEEE Transactions on Neural Networks, Vol. 8, No. 3, pp. 505-518, May 1997
18. Zhiqiang Lao, Dinggang Shen, Dengfeng Liu, Abbas F. Jawad, Elias R. Melhem, Lenore J. Launer, R. Nick Bryan and Christos Davatzikos, "Computer-Assisted Segmentation of White Matter Lesions in 3D MR Images Using Support Vector Machine", Academic Radiology, Vol. 15, No. 3, pp. 300-313, March 2008
19. Zhang, Wang, and Wu, "A Novel Method for Magnetic Resonance Brain Image Classification Based On Adaptive Chaotic PSO", Progress In Electromagnetics Research, Vol. 109, pp. 325-343, 2010
20. Mina Rafi Nazari and Emad Fatemizadeh, "A CBIR System for Human Brain Magnetic Resonance Image Indexing", International Journal of Computer Applications, Vol. 7, No.14, pp. 33-37, October 2010
21. Shafaf Ibrahim, Noor Elaiza Abdul Khalid and Mazani Manaf, "Seed-Based Region Growing (SBRG) vs Adaptive Network-Based Inference System (ANFIS) vs Fuzzy c-Means (FCM): Brain Abnormalities Segmentation", International Journal of Electrical and Computer Engineering, Vol. 5, No. 2, pp. 94-104, 2010
22. Nandita Pradhan and Sinha, "Development of a Composite Feature Vector for the Detection of Pathological and Healthy Tissues in FLAIR MR Images of Brain", Journal of ICGST-BIME , Vol. 10, No. 1, pp. 1-11, December 2010
23. Jayashri Joshi and Phadke, "Feature Extraction and Texture Classification in MRI", In Proceedings of International Conference on Computer Technology, Vol. 2, No. 2, 3, 4, pp. 130-136, 2010
24. Frank Y. Shih and Shouxian Cheng, "Automatic seeded region growing for color image segmentation", Journal of Image and Vision Computing, Vol. 23, pp. 877–886, 2005
25. Soumya Maitra, "Morphological Edge Detection Using Bit-Plane Decomposition in Gray Scale Images", In Proceedings of INDIACom, New Delhi, 2011.
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416-423
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77.
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Authors:
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SK Dwivedi, NK Shukla, Sudhakar Pandey
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Paper Title:
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A Hybrid Wireless Network Model For Post Disaster Relief Operations
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Abstract: In the event of large scale natural disaster, most of the public utility services like communication, power and roads get disrupted. Post disaster relief operations need quick but reliable restoration of these services. Rapid and reliable deployment of communication setup is highly crucial to commence rescue and relief operations. Mobile Ad-hoc Networks (MANETs) can be built quickly but suffer from problems due to nodes mobility; on the other hand, Static Ad-hoc Networks (SANETs) can provide better performance but takes longer time to establish. This paper presents a Hybrid Network model having features like scalability, robustness, speedy deployment, portability, cost effective and desired QoS. The proposed Hybrid Ad-hoc Network (HANET) topology is a combination of static nodes of grid topology of SANET and the mobile nodes of random topology of MANET. In the recent past, many researchers have shown interest in the development of directional antenna based MAC protocols. Although directional antenna brings in advantages of higher transmission range, spatial reuse and so on but equally suffers from typical problems of hidden/exposed terminals, head-of-line blocking and deafness etc. In this paper, we have proposed a novel protocol based on the directional smart antenna to exploit the advantage of spatial reuse in terms of multiple concurrent transmissions while ensuring collision avoidance. Simulation results demonstrated that the throughput and end-to-end delay performances of the proposed MAC protocol with HANET model is significantly better than the legacy MANETs with IEEE 802.11-MAC.
Keywords: (MANETs), (HANET).
References:
1. Ansari, N., Chao Zhang, Rojas-Cessa R., Sakarindr P., and Hou E. S. H.,’Networking for critical conditions’, Wireless Communications, IEEE, volume 15, April, page (s): 73-81.
2. Naudts, D., Bouckaert, S., Bergs, J., Schouttcet, A., Blondia, C., Moerman, I., Demeester, P., “A Wireless Mesh Monitoring and Planning Tool for Emergency
3. C. Ng, and S. C. Liew, “Offered load control in IEEE 802.11 Multi-hop Ad hoc
4. G. Bianchi, “Performance analysis of the IEEE 802.11 distributed coordination function,” IEEE journal on Selected Areas in Communications, vol.18, no. 3, pp. 535-547, March 2000.
5. R. Ramanathan, “On the performance of ad hoc networks with beamforming antennas,” in Proceedings of the IEEE international Symposium on Mobile Ad hoc Networking and Computing - MobiHoc, Long Beach, USA, pp. 95-101, October 2001.
6. L. Bao and J. Gracia-Luna-Aceves, “Transmission scheduling in ad hoc
7. D. Lal, V. Jain, Q. A. Zeng, and D. P. Agrawal, “Performance evaluation of medium access control for multiple-beam antenna nodes in a wireless LAN,” IEEE Transactions on Parallel and Distributed Systems, vol. 15, no. 12, pp. 48-58, 2002.
8. V. Jain, A. Gupta, D. Lal, and D. P. Agrawal, “A cross layer MAC with explicit synchronization through intelligent feedback for multiple beam antennas,” in Proceedings of IEEE GlobeCom, December 2005.
9. V. Jain, A. Gupta, D. Lal, and D. P. Agrawal, “IEEE 802.11 DCF based MAC protocols for multiple beam antennas and their limitations,” in Proceedings of IEEE MASS, November 2005.
10. A. Kalis and T. Antonakopoulos, “Direction finding in IEEE 802.11 wireless networks,” IEEE Transactions on Instrumentation and Measurement, vol. 51, no. 5, pp. 940-948, October 2002.
11. J. C. Liberti and T. S. Rappaport, “Smart antennas for wireless communication: IS-95 and third generation CDMA applications,” Prentice Hall, 1999.
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424-428
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78.
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Authors:
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Santanu Roy
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Paper Title:
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Some New Type of Fuzzy I-Convergent Double Difference Sequence Spaces
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Abstract: In this paper we introduce some new classes of double difference sequence spaces of fuzzy numbers. We study different topological properties of these sequence spaces like completeness, solidity etc. Also we obtain some inclusion relation involving these sequence spaces.
Keywords: Fuzzy real number, Difference sequence, Solid space, Monotone, Sequence algebra.
References:
1. G. A. Anastassiou, Fuzzy approximation by fuzzy convolution type operators, Comput. Math. Appl., 48, 2004, pp. 1369-1386.
2. L. C. Barrors, R. C. Bassanezi, and P. A.nTonelli, Fuzzy modelling in population dynamics, Ecol. Model., 128, 2000, pp. 27-33.
3. T. J. Ia. Bromwich, An Introduction to the Theory of Infinite Series, New York, MacMillan and Co Ltd, 1965.
4. M. A. Erceg, Metric spaces in fuzzy set theory, J. Math. Anal. Appl., 69, 1979, pp. 205- 230.
5. M. Et, and R. Colak, On some generalized difference sequence spaces, Soochow J. of Math.21, 1995, pp. 337-386.
6. M. Et, Y. Altin, and H. Altinok, On almost statistical convergence of generalized difference sequences of Fuzzy numbers, Math. Model. Anal., 10(4), 2005, pp. 345-352.
7. A. Esi, and M. Isik, Some generalized difference sequence spaces, Thai Journal of Mathematics, 3(2), 2005, pp.241-247.
8. A. L. Fradkow, and R. J. Evans, Control of chaos: Methods and applications in engineering, Chaos, Solution & Fractals, 29, 2005, pp. 33-56.
9. R. A. Giles, computer program for fuzzy reasoning, Fuzzy Sets Syst., 1980, pp. 221- 234.
10. G. H. Hardy, On the convergence of certain multiple series, Proc. Camb.Phil. Soc., 19, 1917, pp. 86–95.
11. L. Hong, and J. Q. Sun, Bifurcations of fuzzy nonlinear dynamical systems, Commun. Nonlinear Sci. Numer. Simul., 2006, pp. 1-12.
12. P. K. Kamthan, and M. Gupta, Sequence Spaces and Series, Marcel Dekker, 1980.
13. Khan, A new type of difference sequence space, Appl. Sci. 12, 2010, pp. 102-108.
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