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Volume-3 Issue-2: Published on July 10, 2013
45
Volume-3 Issue-2: Published on July 10, 2013

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S. No

Volume-3 Issue-2, July 2013, ISSN:  2278-3075 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.

1.

Authors:

Amitkumar D. Raval, Indrajit N. Patel, Jayeshkumar Pitroda

Paper Title:

Eco-Efficient Concretes: Use Of Ceramic Powder As A Partial Replacement Of Cement

Abstract:   The ceramic industry inevitably generates wastes, irrespective of the improvements introduced in manufacturing processes. In the ceramic industry, about 15%-30% production goes as waste. These wastes pose a problem in present-day society, requiring a suitable form of management in order to achieve sustainable development. In this research study the (OPC) cement has been replaced by ceramic waste powder accordingly in the range of 0%, 10%, 20%, 30% 40%, & 50% by weight for M-25 grade concrete. The wastes employed came from ceramic industry which had been deemed unfit for sale due to a variety of reasons, including dimensional or mechanical defects, or defects in the firing process. The results demonstrate that the use ceramic masonry rubble as active addition endows cement with positive characteristics as major mechanical strength and the economic advantages. Reuse of this kind of waste has advantages economic and environmental, reduction in the number of natural spaces employed as refuse dumps. Indirectly, all the above contributes to a better quality of life for citizens and to introduce the concept of sustainability in the construction sector.  

Keywords:
 Ceramic Waste,Compressive Strength, Eco-Friendly, Industrial Waste, Low Cost, OPC Cement, Sustainable


References:

1.        ASTM C 125, Standard Terminology Relating to Concrete and Concrete Aggregate, 1994 Annual Book of ASTM Standards
2.        A. Piccolroaz, D. Bigoni and A. Gajo, An elastoplastic framework for granular materials becoming cohesive through mechanical densification. Part I - small strain formulation. European Journal of Mechanics A: Solids, 2006, 25, 334-357.

3.        Ceramic Manufacturing Industry, EUROPEAN COMMISSION, August 2007

4.        César Medina1, M.I.Sánchez de Rojas, Moisés Frías and Andrés Juan, “Using Ceramic Materials in Ecoefficient Concrete and Precast Concrete Products”, Spain

5.        C. Medina Martínez, M.I.Guerra Romero, J. M. Morán del Pozo and A. Juan Valdés, “USE OF CERAMIC WASTES IN STRUCTURALS ONCRETES”, 1st Spanish National Conference on Advances in Materials Recycling and Eco – Energy Madrid, 12-13 November 2009

6.        David Pearce and Giles Atkinson, “The concept of sustainable development: an evaluation of its usefulness ten years after brundtland”, CSERGE Working Paper PA 98-02

7.        D. Bigoni, Nonlinear Solid Mechanics: Bifurcation Theory and Material Instability. 2012, Cambridge University Press.

8.        Gérard Valenduc, Patricia VendraminScience, “Technological Innovation and Sustainable Development”,International Conference “Science for a Sustainable Society”Roskilde, 27-29/10/97

9.        Hasnat Dewan, “Re-Defining Sustainable Human Development to Integrate Sustainability and Human Development Goals”Thompson Rivers University, Canada.

10.     İ.B.TOPÇU And M.CANBAZ, “Utilization of crushed tile as aggregate in concrete”, Iranian Journal of Science & Technology, Transaction B, Engineering, Vol. 31, No. B5, pp. 561-565, 2007

11.     Philip J. Vergragt, “How Technology Could Contribute to a Sustainable World”, GTI Paper Series, 2006

12.     P.K. Mehta, Puzzolanic and cementitious by products as mineral admixtures for concrete, fly ash, silica fuÈme, slag and other mineral byproducts in concrete, ACI SP (79)(01)(1983)

13.     Sustainable Development: An Introduction, Internship Series, Volume-I, Centre for Environment Education, 2007

14.     “STRATEGYFOR SUSTAINABLE CONSTRUCTION” HM Government, JUNE 2008

15.     Plan Nacional de Residuos de la Construcción y Demolición 2001 -2006. Resolución de 14 de junio de 2001, de la Secretaría General deMedio Ambiente. BOE n.
166,25305-25313,12 julio (2001 ).

16.     J. Calleja: "Las puzolanas". Ion, Ns. 340,341,343 y 344, noviembre y diciembre ( 1969), febrero y marzo ( 1970), 623-63 8,700-713,81-90,154-160.

17.     Johansson, S; Andresen, P.J. (1990): "Pozzolanic activity of calcined moler clay". Cement and concrete research. V.20,447-452.

18.     Mielenz, R.C. (1983): "Mineral admixtures- History and background". Concrete International, 34-42.

19.     Sánchez de Rojas, M.I., Frías, M. Rivera, J. Escorihuela, M.J., Marín, P.P. (2001) " Investigaciones sobre la actividad puzolánica demateriales de desecho procedentes de arcilla cocida". Materiales de Construcción, 51, N° 261,45-52.

20.     Norma UNE 80301/1996: "Cementos. Definiciones, Clasificación y Especificaciones".

21.     Norma UNE EN 196-1/1994: "Métodos de ensayo de cementos. Parte 1 : Determinación de resistencias mecánicas".(8) Mehta, P.K; Manmohan, D. (1980): "Pore size distribution and permeability of hardened cement pastes". 7^ Inter. Congress on theChemistry of Cement. V. III. París. VII-1-5.

22.     Nyame, B.K., Illston, J.M. (1980): "Capillary pore structure and permeability of hardened cement paste". 7^ Inter. Congress on theChemistry of Cement. V. III. París. VM81-185.

23.     Norma UNE EN 490/1995: "Tejas y accesorios de hormigón. Especificaciones de producto".

24.     Norma UNE EN 491/1995: "Tejas y accesorios de hormigón. Métodos de ensayo".  


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2.

Authors:

Himanshi, Shruti Vashist, M.K.Soni

Paper Title:

Study of Wireless Sensor Network Using LEACH Protocol

Abstract:  Wireless sensor networks (WSNs) have been identified as one of the most important technologies for the 21st century.  A wireless sensor network with a large number of sensor nodes can be used as an effective tool for gathering data in various situations. This paper focuses on study of WSN using a communication protocol called LEACH protocol. LEACH is very effective in enhancing lifetime of the nodes

Keywords:
 Energy efficiency, Wireless sensor network, LEACH,  clustering


References:

1.        Networks,” International Journal of Soft Computing and Engineering (IJSCE), vol. 1, no. 1, pp. 33-42, 2011.
2.        Jun Zheng and Abbas Jamalipour.New Jersey, John Wiley & Sons, 2009

3.        W. Heinzelman, A. Chandrakasan and H. Balakrishnan, “Energy-efficient Communication Protocol for Wireless Microsensor Networks”, Proceeding of the 33rd Hawaii International Conference on System Sciences, January 2000

4.        B. Krishnamachari, D. Estrin, and S. Wicker, “The Impact of Data Aggregation in Wireless Sensor Networks,” 22nd International Conference on Distributed Computing Systems Workshops, pp. 575-578, 2002.

5.        M.Shankar, Dr.M.Sridar, Dr.M.Rajani, “Performance Evaluation of LEACH Protocol in Wireless Network ”, International Journal of Scientific & Engineering  Research, Volume 3, Issue 1, January-2012 1 ISSN 2229-5518.

6.        W. B. Heinzelman, A. P. Chandrakasan, and H. Balakrishnan, “An Application-Specific Algorithm Architecture for Wireless Microsensor Networks,” IEEE Transactions on Wireless Communications, vol no.4, pp. 660-670, 2002.

7.        R. Rajagopalan, and P. Varshney, “Data Aggregation Techniques in Sensor Networks: A Survey,” IEEE Communications Surveys & Tutorials, vol. 8, no. 4, pp. 48-63, 2006.

8.        W. B. Heinzelman, Application-Specific Protocol Architectures for Wireless Networks, PhD thesis, Massachusetts Institute of Technology, June 2000.

9.        Panghal Amanjeet, Mittal Nitin, Singh D.P. & Chauhan R.S. (2010) Improved leach communication protocol for WSN ,National Conference on Computational Instrumentation CSIO Chandigarh, INDIA,177-181.  

 

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3.

Authors:

Chandrasekaran, A, Mukesh, M.V, Anantharaman, P,Tamilselvi, M, Muthukumarasamy, R,  Manivel, T, Rajmohan, R

Paper Title:

Trace Metal Concentration in Sediments of Tamirabarani River in Relationships with Physico Chemical Characteristics - A Study Using Gis Application

Abstract:   A study is carried out to investigate the concentrations and distribution of trace metals to the sediments of Tamirabarani River, south east coast of India. Nearly sixteen soil samples collected from river mouth and tributaries and analyzed for traces elements show high-rate  concentration of Hg (3.52-24.69μg g-1) Cu(2.2-17.82μg g-1), Ni(7.83-15.2μg g-1), Cr(58.3-145.5μg g-1), Pb(3.48-12.93μg g-1), Zn(9.3-74μg g-1) and Cd(1.41-4.92μg g-1). The pH, EC, and TDS values reported as (8.1-9.5) (384-16250) (303-33050) .The abundances of such metals caused by the river contribution of sediments from areas with unplanned agricultural development and from the industrial, activity carried out on the riverbanks. It is concluded that in and around Mukkani area, the concentration of heavy metals is higher due to anthropogenic and industrial effluent in Tamirabarani River.

Keywords:
 Sediments, Trace elements, Tributaries, spatial distribution, Tamirabarani River


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4.

Authors:

Sripriya.B.R, Nataraj.K.R

Paper Title:

Design and Simulation of a Circuit to Predict and Compensate Performance Variability in Submicron Circuit

Abstract:   This paper presents a technique for compensating process, voltage and temperature variations due to manufacturing and environmental variability in submicron circuits using canary flip-flop. This canary flip flop predicts the timing error before it actually occurs and compensate the performance so that the system performance does not get affected. I am going to design a 16-bit Brent-Kung  adder in  45-nm CMOS technology , whose performance will be  controlled by supply voltage scaling. We will show that this technique  can compensate process, supply voltage, and temperature variations and improve the energy efficiency of submicron circuits. We also compare Power dissipation for Worst case design and performance compensate design and show performance design has less power dissipation when compared to worst case design.

Keywords:
 Manufacturing variability, Timing error prediction, Brent-Kung adder, Speed control unit, Canary flip-flop.


References:

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3.        S. Das, C. Tokunaga, S. Pant, W. H. Ma, S. Kalaiselvan, K. Lai, D. M. Bull, and D. Blaauw, “Razor II: In situ error detection and correction for PVT and SER tolerance,” IEEE J. Solid-State Circuits, vol. 44, no. 1, pp. 32–48, Jan. 2009.

4.        H. Fuketa, M. Hashimoto, Y. Mitsuyama, and T. Onoye, “Trade-off analysis between timing error rate and power dissipation for adaptive speed control with timing error prediction,” IEICE Trans. Fund., vol. E92-A, no. 12, pp. 3094–3102, Dec. 2009.

5.        H. Fuketa, M. Hashimoto, Y. Mitsuyama, and T. Onoye, “Adaptive performance compensation with in-situ timing error prediction for subthreshold circuits,” in Proc.Custom Integr. Circuits Conf. (CICC),  pp. 215–218, 2012.

6.        W. Kuzmicz, E. Piwowarska, A. Pfitzner and D. Kasprowicz, “CAD Tools for Analysys of       Process Variability effects in Deep Submicron CMOS Circuits”, IEEE  Region, vol-8, pp. 304–309, Feb. 2008.

7.        Anas Zainal Abidin et al., " 4-bit Brent Kung Parallel Prefix Adder Simulation Study Using  Silvaco EDA tools", IJSSST, vol- 13, pp.51-59, 2009.

8.        Adilakshmi Siliveru and M. Bharathi, " Design of Kogge-Stone and Brent-Kung adder using Degenerate Pass Transistor Logic", IJESE, vol-1, pp.38-41, 2012.
 

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5.

Authors:

Divya A.G, Srividya P

Paper Title:

ASIC Implementation of Switchable Key AES Cryptoprocessor

Abstract:   This paper presents the ASIC implementation of switchable key Advanced Encryption standard algorithm Encryption and decryption with power gating. The implementation supports 128 bits, 192 bits and 256 bits key. The design  is described using verilog HDL , simulated in VCS synopsys. The RTL is Synthesized in Design Compiler (DC) using Nangate 45nm open cell library and  Physical Design is performed in ICC of Synopsys. The  Design was clocked at 125M with a throughput  of  1.14Gbps  and the power consumption of 1.07mw.

Keywords:
 ASIC, AES, 45nm CmosTechnology, Key Expansion.


References:

1.        J.Daemen and V.Rijmen, ―AES Proposal: Rijndael, AES algorithm submission, September 3, 1999, available: http://www.nist.gov/CryptoToolkit.
2.        Draft FIPS for the AES available from: http://csrc.nist.gov/encryption.aes , February 2001.

3.        huang Yin, hedebiao, kang yong and fei Xiande , ―High speed ASIC implementation of AES supporting 128/192/256 bits, International conference on test and Measurement, 2009.

4.        I. Verbauwhede, P. Schaumont and H. Kuo, ―Design and Performance Testing of a 2.29-GB/s Rijndael Processor, IEEE Journal of Solid State Circuits, Vol. 38, No. 3, March 2003, pp. 569-572

5.        T. Ichikawa, T. Kasuya, and M. Matsui, ―Hardware Evaluation of the AES Finalists, in Proc. 3rd AES Candidate Conference, pp. 279-285, New York, April 2000.

6.        A. Hodjat and I. Verbauwhede, ―Minimumarea cost for a 30 to 70 Gb/s AES processor, in Proc. IEEE Comput. Soc. Annu. Symp, Lafayette, LA, Feb. 2004, pp. 83–88.

7.        C.-P. Su, T.-F. Lin, C.-T. Huang, and C.-W. Wu, ―A high-throughput low-cost AES processor, IEEE Commun. Mag., vol. 41, no. 12, pp. 86–91, Dec. 2003


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6.

Authors:

S. M. Rajbhoj, P. B. Mane

Paper Title:

Haar Wavelet Approach of Iris Texture Extraction for Personal Recognition

Abstract:   Iris recognition is one of the fast, accurate, reliable and secure biometric techniques for human identification. As the iris texture pattern is very unique and has no links with the genetic structure of an individual it is used as feature in iris recognition system. Poor quality images, high failure to accept rates (FTE) and high false reject rates (FRR) undermines the performance of iris recognition systems. The selection of subset of feature, its extraction and classification is a crucial step in this system. In this paper a method for iris recognition based on Haar wavelet approach of Iris texture extraction is proposed. Iris recognition system consists of iris localization, normalization, features extraction and matching modules. The feature extraction algorithm extracts haar wavelet packet energies of the normalized iris image (local features) to generate a unique code by quantizing these energies into one bit according to an adapted threshold. Hamming distance measure is used in order to find similarity between the iris images. Results are presented that demonstrate significant improvements in iris recognition accuracy when feature extracted using higher wavelet decomposition through the use of the public iris database CASIA.V4

Keywords:
 Biometrics, Iris recognition, feature extraction, Wavelet Transform.


References:

1.        J. G. Daugman, Recognizing persons by their iris patterns. In A. K. Jain, R. Bolle, and S. Pankanti, editors, Biometrics: Personal Identification in a Networked Society, pages 103–121. Kluwer Academic Publishers, 1999
2.        J. G. Daugman, “High confidence visual recognition of persons by a test of statistical independence”, IEEE Transactions on Pattern Analysis and Machine Intelligence, 15(11), 1993, 1148–1161

3.        J. G. Daugman, "How Iris Recognition Works", In IEEE Transactions on circuits and systems for video technology, vol. 14, no. 1,January 2004

4.        L. Ma, Y. Wang, and T. Tan, “Personal identification based on iris texture analysis,” IEEE Trans. on Pattern Analysis and Machine Intelligence, vol. 25, no. 12, Dec 2003, pp. 1519–1533

5.        R. Wildes. “Iris recognition: an emerging biometric technology.” Proceedings of the IEEE, Vol. 85, No. 9, 1997

6.        R. Wildes, J. Asmuth, G. Green, S. Hsu, R. Kolczynski, J. Matey, & S. McBride, “A Machine vision System for Iris Recognition”, Machine Vision and Applications, 9(1), 1996,1-8

7.        W. W. Boles, & B. Boashah, A Human Identification Technique Using Images of the Iris and Wavelet Transform, IEEE Transaction on Signal Processing, 46(4), 1998, 1185-1188 

8.        Jiali Cui, Yunhong Wang, JunZhou Huang, Tieniu Tan, Zhenan Sun, “An Iris Image Synthesis Method Based on PCA and Super-resolution,” Proceedings of the 17th International Conference on Pattern Recognition (ICPR’04).

9.        Kwanghyuk Bae, Seungin Noh, and Jaihei Kim, “Iris feature extraction using independent component analysis,” Proc. 4th Intl. Conf. on Audio and Video Based Biometric Person Authentication LNCS, vol. 2688, 2003, pp. 838–844

10.     L. Ma, T. Tan,D. Zhang, andY.Wang, “Local intensity variation analysis for iris recognition,” Pattern Recognition, vol. 37, no. 6, , 2005, pp. 1287–1298

11.     Libor Masek, "Recognition of Human Iris Patterns for Biometric Identification", Thesis Report School of Computer Science and Software Engineering, Western Australia, 2003.

12.     Rossani F., Eslava M.T., Ea T., Aml F., Amara A., “Iris Identification and robustness evaluation of wavelet packetsbased algorithm”, IEEE International Conference on image processing, vol.3, pp. III -257-260

13.     Farid Benhammadi, nassima kihal, “Personal Authentication based on Iris Texture analysis”, IEEE International conference on Computer systems and applications 2008,537-543

14.     CASIA Iris Image Database.   


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7.

Authors:

Piyush Saxena, Amarpal Singh, Sangeeta Lalwani

Paper Title:

Use of DNA for Computation, Storage and Cryptography of Information

Abstract:   DNA computing was proposed [1] as a method of solving a group of inflexible computational tribulations in which the computing time can grow up exponentially with respect to the problem size. A DNA can also be used as a next generation Digital Information Storage Medium that has tremendous storage capacity and low maintenance cost. This process of artificial manufacturing and decoding of DNA’s can also be used to encode data by use of an extremely advanced and naturally existing cipher mechanism.

Keywords:
 DNA Computing, DNA Cryptography, Logic gates, DNA chip, DNA Microprocessor.


References:

1.        Lovgren, Stefan (2003-02-24). "Computer Made from DNA and Enzymes". National Geographic. Retrieved 2009-11-26.
2.        Tojanovic, Milan N.; Mitchell, Tiffany Elizabeth; Stefanovic, Darko (2002). "Deoxyribozyme-Based Logic Gates". Journal of the American Chemical Society 124: 3555–3561.doi:10.1021/ja016756v.

3.        J. Gantz, D. Reinsel, “Extracting value from chaos” [International Data Corporation (IDC), Framingham, MA, 2011], www.emc.com/collateral/analyst-reports/idc-extracting-value-from-chaos-ar.pdf.

4.        C. Bancroft, T. Bowler, B. Bloom, C. T. Clelland, Science 293, 1763 (2001).Information on materials and methods is available on Science Online.

5.        Pääbo et al., Annu. Rev. Genet. 38, 645 (2004).

6.        J. Bonnet et al., Nucleic Acids Res. 38, 1531 (2010).

7.        Seelig, G.; Soloveichik, D.; Zhang, D. Y.; Winfree, E. (2006). "Enzyme-Free Nucleic Acid LogicCircuits". Science 314 (5805): 1585. doi:10.1126/science.1132493. PMID 17158324.

8.        http://www.elook.org/computing/dna-computing.htm

9.        http://blogs.discovermagazine.com/80beats/2011/06/03/dna-computerdoes-math-plus-lays-out-building-blocks-for-bigger-circuits/.

10.     Gareth L. Bond, Wenwei Hu, and Arnold J. Levine (2005). "MDM2 is a Central Node in the p53 Pathway: 12 Years and Counting". Current Cancer Drug Targets 5 (1): 3–8.

11.     Towards practical, high-capacity, low-maintenance information storage in synthesized DNA Nick Goldman1, Paul Bertone1, Siyuan Chen2, Christophe Dessimoz1, Emily M. LeProust2, Botond Sipos1 & Ewan Birney1 doi:10.1038/nature11875, Jan 2013 Macmillan Publishers Limited. 


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8.

Authors:

Prathvi Kumari, Ravishankar K

Paper Title:

Measuring Semantic Similarity between Words using Page-Count and Pattern Clustering Methods

Abstract:   Web mining involves activities such as document clustering, community mining etc. to be performed on web. Such tasks need measuring semantic similarity between words. This helps in performing web mining activities easily in many applications. Despite the usefulness of semantic similarity measures in these applications, accurately measuring semantic similarity between two words remains a challenging task.  In this paper to find the semantic similarity between two words it makes use of information available on the web and uses methods that make use of page counts and snippets to measure semantic similarity between two words. Various word co-occurrence measures are defined using page counts and then integrate those with lexical patterns extracted from text snippets. To identify the numerous semantic relations that exist between two given words, a pattern extraction and clustering methods are used. The optimal combination of page counts-based co-occurrence measures and lexical pattern clusters is learned using support vector machine used to find semantic similarity between two words. Finally semantic similarity measure what is got is in the range [0, 1], is used to determine semantic similarity between two given words. If two given words are highly similar it is expected to be closer to 1, if two given words are not semantically similar then it is expected to be closer to 0.  

Keywords:
 Natural Language Processing, Semantic Similarity, Support Vector Machine, Text Snippets, Web Mining


References:

1.        George A. Miller , “WordNet: A Lexical Database for  English”.
2.        D. Lin. Automatic retreival and clustering of similar words.In Proc. of the 17th COLING, pages 768–774 1998.

3.        P. Resnik. Using information content to evaluate semantic similarity in a taxonomy. In Proc. of 14th Internation JoinT Conference on Aritificial Intelligence, 1995.

4.        J.J. Jiang and D.W. Conrath. Semantic similarity based on corpus statistics and lexical taxonomy. In Proc. of the International Conference on Research in Computational Linguistics  ROCLING1998.

5.        D. Lin. An information-theoretic definition of similarity. In Proc. Of the 15th ICML, pages 296–304, 1998.

6.        D. Mclean, Y. Li, and Z.A. Bandar, “An Approach for Measuring SemanticSimilarity between Words Using Multiple Information Sources,” July/Aug. 2003.

7.        R. Cilibrasi and P. Vitanyi, “The Google Similarity  Distance,” IEEE Trans.  Knowledge and Data Eng., vol.19, no. 3, pp. 370-383, Mar.2007.

8.        G. Miller and W. Charles, “Contextual Correlates of Semantic Similarity,” Language and Cognitive Processes,             vol. 6, no. 1, pp. 1-28, 1998.

9.        V.Hemalatha and Mrs .K. Sarojini, “semantic similarity approach using rsvm based on personalized search in web search engine”,vol 1,November 2012
 

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9.

Authors:

Kiran Chhabra, Manali Kshirsagar, A. S. Zadgaonkar

Paper Title:

Effective Congestion Indication for Performance Improvement of Random Early Detection

Abstract:  A congestion avoidance scheme  allows a network to operate in the region of low delay and high throughput. Such scheme prevent a network from entering in to congested state. RED(Random Early Detection), is one such congestion avoidance mechanism used for effectively control  of congestion. In RED, router uses only the average queue size, as a congestion indicator and the average queue length is insensitive to input traffic load variation. Due to this effective incipient congestion becomes difficult to detect and there is no matching between current queue size and average queue size as in [4]. The present paper deals with these two problems and proposed a way in which packet dropping is not only based on average queue size but also on the rate of change of input. The work which is carried out is to find out significant changes in input rate and use this climbing rate as indication of impending congestion for sources to react quickly. Here we have analyzed the performance of   our proposed algorithm using network simulator ns2.

Keywords:
 Average queue size, Congestion Avoidance, Network Simulator (ns), Random Ear ly Detection (RED).


References:

1.        P. Gevros, J. Crowcroft, P. Kirstein, and S.  Bhatti, “Congestion control mechanisms and the best effort service model,” IEEE Network, vol. 15, no. 3 pp 16-26, May2001.
2.        B. Braden, D. Clark, J. Crowcroft, B. Davie, S. Deering, D. Estrin, S.   Floyd, V. Jacobson, G. Minshall, C. Partridge, L. Peterson, K. Ramakrishnan, S. Shenker, J. Wroclawski and L. Zhang RFC 2309:   Recommendations on Queue Management in April 1998

3.        S. Floyd  and V. Jacobson, “Random early  detection gateway for Congestion avoidance, ”IEEE/ACM Transaction on Networking, vol. 1, no.4, pp.397-413, Aug.  1993.

4.        Seunwan Ryu, Christopher Rump, And Chunming Qiao  “Advances in Internet Congestion Control” third quarter 2003, Volume 5, No.1 http://www.comsoc.org/pubs/surveys,

5.        “ns [network simulator]”, 1999 [Online] Available http://www.isi.edu/nsnam/ns,

6.        W. Feng  D. D. Kandlur, D. Saha ,” A Self Configuring  RED gateway”, Proceedings of IEEE INFOCOMM, 1999,Vol 3 pp 1320-1328

7.        D. Lin R. Moris,“ Dynamics of  Random Early Detection”,,Proceedings of ACM SIGCOMM, October 1997

8.        T. J. Ott, T. V, Lakshman and L. Wong, “ SRED : Stablized RED” in IEEE INFOCOM, March 1999

9.        Bing  Zheng, Mogammed Atiquzzaman,” DSRED: An Active Queue Management for Next Generation Networks” Proceedings of 25th IEEE conference on Local Computer Networks LCN 2000,November 2000.

10.     S. Floyd., R .Gummadi, S. Shenkar,”Adaptive RED: An algorithm for  Increasing   the  robustness of RED’s active Queue Management”,Berkely CA, [online] http:www.icir.org/floyd/red.html.

11.     Jinsheng Sun, King-Tim Ko. Guanrong Chen. Sammy Chan, Moshe  sukerman.,”PD RED : To Improve Performance Of RED”, IEEE  COMMUNICATIONS LETTER August 2003.

12.     Tae-Hoo Kim., Kee-Hyun Lee” Refined Adaptive RED in TCP/IP Networks”, IEEE ICASE, October 2006.

13.     Jeong-Hwan, Seol,Ki Young Lee, Yoon Sik Hong “ Performance  Improvement of Adaptive AQM Using the variation of Queue Length”, IEEE Region 10 Conference TENCON, November 2006.

14.     Wu Chung Feng, Kang G Shin, Dilip D Kandlur, Debnanin Saha,” .,“The BLUE Active Queue Management”, IEEE ACM  Transactions on Networking, August 2002.

15.     A.Kamra, S.Kapila,V.Khurana, V.Yadhav H.Saran,”SFED: a rate control based active   queue management discipline”, IBM India research laboratory Research Report, available online from http://www.cse.iitd.ernet.in/srajeev/publications.htm

16.     Srisankar S.Kunniyur., R.Srikant , “ An Adaptive Virtual  Queue [AVQ] for Active Queue Management”., IEEE/ACM Transactions  on Networking, April 2004.

17.     Cheng-Nian long., Bin Zhao., Xin-Ping Guan.,” SAVQ : Stablized Adaptive Virtual Queue Management” IEEE Communications Letters ., January 2005,

18.     Qian Yanping, Li Qi, Lin Xiangze, Ji Wei,” A stable Enhanced Adaptive Virtual Queue Management Algorithm for TCP Networks”, IEEE International Conference on Control and Automation,2007.19.     Chengnian Long., Bin Zhao, Xinping Guan., Jun Wang,” The   Yellow   active   queue   management   algorithm”, Computer Networks, November 2004.

20.     Athuraliya., D.E Lapsley., S.H Low” Random Exponential Marking for internet congestion control” IEEE Transactions on Network, June 2001.

21.     Xidong Deng., Sungwon Yi., George Kesidis., Chita R.Das.,” Stabilised Virtua Buffer [SVB] An Active Queue Mangement Scheme for Internet Quality of Service”, IEEE Globecom November 2002.:

22.     Jaesung Hong., Changhee Joo, Saewoong Bahk” Active queue management algorithm considering queue and load states”, Computer Communications, November 2006.

23.     Jinsheng Sun., Moshe Zukerman,.” “ RaQ: a robust active queue management scheme based on rate and queue length”, Computer Communications, February 2007 


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10.

Authors:

Lavina Jean Crasta, H. Harshavardhan

Paper Title:

Technical Challenges in Mixed Service Systems

Abstract:   A coming together of the technological networks that connect computers on the internet and the social networks that  link humans for millennia has been observed in the past few decades. Even as this has led to the changes in the styles of communication, the media has also remained governed by long standing principles of human social interaction. Web-based collaborations have become vital in today’s business environments. They have paved the way for new type of collaborative system. As collaborative Web-based platforms develop into service oriented architectures (SOA), they promote mixed user enriched services. Due to the availability of various SOA frameworks, Web services emerged as the de facto technology to realize flexible compositions of services. Knowledge-intensive environments clearly demand for provisioning of human expertise along with sharing of computing resources or business data through software-based services. To address the challenges, an adaptive approach allowing humans to provide their expertise through services using SOA standards, such as Web Services Description Language (WSDL) and Simple Object Access Protocol (SOAP) is introduced. The seamless integration of humans in the SOA loop triggers numerous social implications, such as evolving expertise and drifting interests of human service providers.  

Keywords:
 Human Provided Services, Service Avatar, Service Oriented Architecture.


References:

1.        Schall, Daniel. "Human interactions in mixed systems-architecture, protocols, and algorithms." Unpublished Ph. D. thesis, Vienna University of Technology (2009).
2.        Schall, D., Skopik, F., Dustdar, S., "Expert Discovery and Interactions in Mixed Service-Oriented Systems," Services Computing, IEEE Transactions on, vol.5, no.2, pp.233, 245, April-June 2012.

3.        Schall, D., Hong-Linh Truong, Dustdar, S., "The Human-Provided Services Framework," E-Commerce Technology and the Fifth IEEE Conference on Enterprise Computing, E-Commerce and E-Services, 2008 10th IEEE Conference on , vol., no., pp.149,156, 21-24 July 2008.

4.        Florian Skopik, Daniel Schall, Harald Psaier, Schahram Dustdar. Adaptive Provisioning of Human Expertise in Service-oriented Systems SAC’11 Proceedings of the 2011 ACM Symposium on Applied Computing, Pages 1568-1575.

5.        Vasilyeva, Ekaterina, et al. "Feedback adaptation in web-based learning systems." International Journal of Continuing Engineering Education and Life Long Learning 17.4 (2007): 337-357. 


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11.

Authors:

Pande A. M., Kharde Y. R.

Paper Title:

Effect of Pressure Angle on Transmission Efficiency of Helical Gears

Abstract:   In this study, a test methodology for measuring load-dependent (mechanical) power losses of helical gear pairs is developed. A high-speed four-square type test machine is adapted for this purpose. Several sets of helical gears having 3 different pressure angles are manufactured, and their power losses under dip lubricated conditions are measured at various speed and torque levels. A general trend found in the experimental testing was that the higher the pressure angle, the lower the temperature-increase of the lubricant across the gearbox while being tested at identical conditions. This is an indication of the improved efficiency. Finally it was concluded that high-pressure angle helical gears (25°) pressure angle running at high speed provide improved performance over more traditional gear pressure angles (20°).

Keywords:
 load-dependent power losses, helical gear, pressure angle, efficiency.              


References:

1.        Robert F. Handschuh and Andrew J. Zakrajsek, , “High Pressure Angle Gears: Preliminary Testing Results,” NASA/TM—2010-216251, International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, 2010,pp.17-29.
2.        Michlin, Y., Myunster, V., “Determination of Power Losses in Gear Transmissions with Rolling and Sliding Friction incorporated,” Mechanism and Machine Theory, 37, 2002, pp.167-174.

3.        Xu, H., Kahraman, A., Anderson, N.E. and Maddock, D. “Prediction    of Mechanical Efficiency of Parallel Axis Gear Pairs,” Journal of Mechanical Design, 129,  2007,
pp.58-68.

4.        S. Li, A. Vaidyanathan, J. Harianto and A. Kahraman, “Influence of Design Parameters and Micro-geometry on Mechanical Power Losses of Helical Gear pairs,” JSME International Conference on Motion and Power Transmissions, Sendai, Japan, vol-3, No.-2, 2009,  pp.146-158.

5.        Seetharaman and Kahraman, 2009, “Load-Independent Spin Power Losses of a Spur Gear Pair: Model Formulation,” ASME Journal of Tribology, 131, 2009, 022201,pp.01-11.

6.        Shanming Luo and Anhua Chen “Constraint analysis of pressure angle of involute elliptical gears” 12th IFToMM World Congress, Besançon (France), June 18-21, 2007. Pp.54-63

7.        Changenet, C., and Velex, P., “A Model for the Prediction of Churning Losses in Geared Transmissions – Preliminary Results“, ASME Journal of Mechanical Design, 129(1),  2007,pp.128-133.

8.        Heingartner, P., and Mba, D., “Determining Power Losses in the Helical Gear Mesh,” Proceedings of the 2003 ASME Design Engineering Technical Conferences ad Computers and Information in Engineering Conference.2003,pp.127-141

9.        Petry-Johnson, T., Kahraman, A., Anderson, N. E., and Chase, D. R., “An Experimental Investigation of Spur Gear Efficiency,” ASME Journal Machine Design, 130, 2008, 062601,pp.01-10 

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12.

Authors:

A.Sivannarayana, K.Harikishore

Paper Title:

Design and Modeling of Modulo Multipliers Using RNS

Abstract:  The special moduli set,Residue Number System is intended to implement the long and repeated multiplications of cryptographic and signal processing algorithms. In this paper, area and power trade-of of modulo 2n – 1 and modulo 2n + 1  multipliers based on RNS are proposed. The proposed modulo multipliers are based on the radix-8 Booth encoding technique. In the proposed modulo 2n – 1  multipliers, the number of partial products is lowered to └ n/3 ┘ + 1 for n = 32 to 64, which is around 33% reduction over radix-4 Booth encoded multiplier for n = 32 to 64.For modulo 2n + 1multiplier,the aggregate bias is composed of multiplier dependent dynamic bias and multiplier independent static bias due to hard multiple and modulo-reduced partial products generation. The total number of partial products is reduced to └ n/3 ┘ + 6 for modulo 2n + 1 multiplier. From synthesis results for modulo 2n – 1 and modulo 2n + 1 based RNS multipliers constructed from different modulo 2n – 1 and modulo 2n + 1 multipliers.

Keywords:
 Booth algorithm, computer arithmetic, multiplic-ation, residue number system(RNS).


References:

1.        M.A. Soderstrand, W.K. Jenkins, G.A. Jullien, and F.J. Taylor, Residue Number System Arithmetic:   Modern Applications in Digital Signal Processing. New York: IEEE Press,1986.  
2.        R. Conway and J. Nelson, “Improved RNS FIR filter architectures,” IEEE Trans, Circuits and Syst. II, EXP. Briefs, vol. 51, no. 1, pp. 26-28,Jan 2004.

3.        J. Ramirez, U. Meyer-Base, A. Garcia and A. Lloris, “Design and Implementation of RNS-based adaptive filters,” in Proc. 13th Int. Conf. Field Programmable Logic Applications, Lisbon, Spain, Sep. 2003, pp. 1135 – 1138.

4.        H. Nozaki, M. Motoyama, A. Shimbo, and S. Kawamura, “Implementation of RSA algorithm based on RNS montgomery multiplication,”, in Proc. Workshop Cryptographic Hardware Embedded Syst., Paris, France, May 2001, pp. 364-376.

5.        J.C. Bazard and L. Imbart, “A full RNS implementation of RSA, ” IEEE Trans. Comput., vol. 53, no. 6, pp. 769-774, Jun. 2004.

6.        D.M. Schinianakis et al, “An RNS Implementation of an Fp elliptic curve point multiplier,”, IEEE Trans. Circuits Syst. I, Reg. papers, vol. 56, no. 6, pp.1202-1213, Jun. 2009.

7.        Ramya Muralidharan, “Area-Power Efficient Modulo 2n – 1 and Modulo 2n + 1 Multipliers for {2n – 1 , 2n , 2n + 1} Based RNS,”, IEEE Trans. Circuits Syst I., vol. 59,no. 10, Oct  2012.     

8.        V. Paliouras and T. Stouraitis, “Multiplication architectures for RNS processors,” IEEE Trans. Circuits Syst. II, Analog. Digit. Signal Process.,vol. 46, no. 8, pp. 1041-1054, Aug. 1999.

9.        I. Kouretas and V. paliouras, “RNS multi-voltage low power multiply-and unit,” in Proc. 17th IEEE Int. Conf. Electronics, Circuits Systems, Athens, Greece, Dec. 2010, pp. 9-12.

10.     G.C. Cardarilli, A.D. Re, A. Nannarelli, and M, Re, “Low power and low leakage implementation of Rns FIR filters,” in Proc. 39th Asilamar Conf. Signals, Syst. Comput., Pacific Grove, CA, Nov. 2005, pp. 1620-1624.

11.     Z. Wang, G.A. Jullien, and W.C. Miller, “An algorithm for multiplication modulo (2n – 1),” in Proc. 39th IEEE Midwest Symp. Circuits Syst., Ames, 1A, Aug. 1996, pp. 1301-1304.

12.     R. Zimmermann, “Efficient VLSI implementation of modulo (2n ± 1) addition and multiplication,” in Proc. 14th IEEE Symp. Computer Arithmetic, Adelaide, Australia, Apr. 1999, pp. 158 – 167.

13.     C. Efstathiou, H. T. Vergos , and D. Nikolos, “Modified Booth modulo 2n – 1 multipliers,”  IEEE Trans. Comput., vol. 53, no. 3, pp. 370 – 374, Mar. 2004.

14.     Z. Wang, G. A. Jullien, and W. C. Miller, “An efficient tree architecture for modulo 2n + 1 multiplication, ” J. VLSI Signal Process, vol. 14, no. 3, pp. 241 – 248, Dec. 1996.

15.     C. Efstathiou, H. T. Vergos, G. Dimitrakopoulos, and D. Nikolos, “Efficient dimished – 1 modulo 2n + 1 multipliers,” IEEE Trans. Comput., vol. 54, no. 4, pp. 491 – 496, Apr. 2005.

16.     Y. Ma, “A simplified architecture for modulo (2n + 1) multiplication,” IEEE Trans. Comput., vol. 47, no. 3, pp. 333 – 337, Mar. 1998.

17.     L. Sousa and R. Chaves, “A universal architecture for designing efficient modulo 2n + 1 multipliers,” IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 52, no. 6, pp. 1166-1178, Jun. 2005.

18.     J. W. Chen and R. H. Yao, “Efficient modulo 2n + 1 multipliers for diminished-1 representation,” IET Circuits. Divices Syst., vol. 4, no. 4, pp. 291-300, Jun. 2010.

19.     L. Leibowwitz, “A simplified binary arithmetic for the fermat number transform,” IEEE Trans. Acoustics, Speech Signal Process., vol. 24, no. 5, pp. 356-359, Oct. 1976.

20.     H. T. Vergos and C. Efstathiou, “Design of efficient modulo 2n + 1 multipliers,” IET Comput. Digital Tech., vol. 1, no. 1, pp. 49-57, Jan. 2007.

21.     G. W. Bewick, “Fast Multiplication Algorithms and Implimentation,” Ph.D. dissertation, Stanford Univ, Stanford, CA, 1994.

22.     B. S. Cherkauer and E. G. Friedman, “A hybrid radix-4/radix-8 low power signed multiplier architecture,” IEEE Trans. Circuits Syst. II, Analog. Digit. Signal Process, vol. 44, no. 8, pp. 656-659, Aug. 1997.

23.     M. J. Flynn and S. F. Oberman, “Advanced Computer Arithmetic Design,” New York: Wiley, 2001.

24.     R. Muralidharan and C. H. Chang, “Radix-8 Booth encoded modulo 2n – 1 multipliers with adaptive delay for high dynamic range residue number system,” IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 58, no. 5, pp. 982-993,  Jun. 2011.

25.     R. Muralidharan and C. H. Chang, “Hard multiple generator for higher radix modulo 2n – 1 multiplication,” in Proc.12th Int. Symp. Integr. Circuits, Singapore, Dec. 2009, pp. 546-549.

26.     R. Muralidharan and C. H. Chang, “Fast hard multiple generators for radix-8 Booth encoded nodulo 2n-1 and modulo 2n + 1 multipliers,” in Proc. 2010 IEEE Int. Symp. Circuits Syst., Paris, France, May. 2010.

27.     L. K. Kalampoukas et al., “High – Speed parallel – prefix modulo (2n- 1) adders,” IEEE Trans. Comput., vol. 49, no. 7, pp. 673 – 680, Jul. 2000.  

28.     G. Dimitrakopoulos et al., “New architectures for modulo 2n – 1 adders,” in Proc. 12th IEEE Int. Conf. Electronics. Circuits Syst., Gammarth, Tunisia, Dec. 2005, pp. 1 – 4.

29.     H. T. Vergos, C. Efstathiou, and D. Nikolos, “Dimished – one modulo 2n + 1 adder desigh,” IEEE Trans. Comput., vol. 51, no. 12, pp. 1389 – 1399, Dwc. 2002.

30.     H. T. Vergos and C. Efstathiou, “Efficient modulo 2n+ adder architectures,” VLSI J. Integr., vol. 42, no. 2, pp. 149 – 157, Feb. 2009.    

 

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13.

Authors:

Padmini A.K., Abdul Malik K.V., Leena Samuel Panackel

Paper Title:

Forecasting Trip Production Based on Residential Land Use Characteristics

Abstract: Travel demand forecasting models are the key elements for the development of a long-range transportation plan. This paper focuses its study on the formulation of a trip production model using multiple regression technique for the residential land use in medium sized towns of Kerala. The trip production model estimated the number of trips that will be produced from the residential land use of these medium sized towns. The Perinthalmanna, Tirur, and Ponnani towns of Kerala were selected as the study area based on certain criteria. Household interviews were conducted through the administration of questionnaires for data collection on demographic and socio-economic characteristics these areas. The results were then analyzed quantitatively and qualitatively using the correlation and multiple regression analysis. The study showed that the regression model with the independent variables such as the percentage of automobile availability, percentage of persons employed, percentage of students and percentage of pucca type of dwelling with R2 and Adjusted R2 value of 0.878 and 0.859 respectively gives a better estimate of the trips produced. Since most of the work related to traffic and transportation planning requires an effective framework for the analysis of the present and future travel demand pattern, a model forecasting the trip produced based on the above mentioned characteristics shall be advantageous for a speedy travel demand forecast.

Keywords:
 Multiple Linear Regression, Residential Land Use, Socio-Economic Characteristics, Trip Production


References:

1.        Olugbenga Joseph and Oluyemisi Opeyemi, “Regression Model of Household Trip Generation of Ado-Ekiti Township in Nigeria,” European Journal of Scientific Research, ISSN 1450-216X Vol.28 , no.1, EuroJournals Publishing, Inc. 2009, , pp.132-140.
2.        William J. Fogarty, “Trip Production Forecasting Models for Urban Areas,” Transportation Engineering Journal © ASCE, Vol. 102, No. 4, November 1976, pp. 831-845.

3.        Michael G. McNally, “The Four Step Model,” Institute of Transportation Studies University of California, 2007.

4.        Kevin B. Modi, L. B. Zala, T. A. Desai, and  F. S. Umrigar, “Transportation Planning Models,” National Conference on Recent Trends in Engineering & Technology, May 2011.

5.        Charles L. Purvis, Miguel Iglesias, and Victoria A. Eisen, “Incorporating Work Trip Accessibility in Non-Work Trip Generation Models in the San Francisco Bay Area,” Paper submitted to the Transportation Research Board for presentation at the 75th Annual Meeting, January 1996.

6.        Nonito M. Magdayojr, “Study on the Application of Trip Generation Analysis for Residential Condominium Developments in Metro Manila,” Final Paper, Undergraduate Research Program in Civil Engineering, march 2008

7.        John S. Miller, P.E.Lester A. Hoel, P.E. Arkopal K. Goswami, and Jared M. Ulmer, “Borrowing Residential Trip Generation Rates,” Journal of Tansportation Engineering © ASCE, February 2006, pp. 105-113.

8.        Papacostas C.S. and Prevedouros P.D., “Transportation Engineering and Planning,” SI Edition, Prentice-Hall Inc Singapore, 2005.

9.        Abdul Khalik Al-Taei and Amal M. Taher, “Prediction Analysis of Trip Production Using Cross-Classification Technique,” Al-Rafidain Engineering, vol.14, no.4, 2006.

10.     Matthew Femal, “Improving Trip Generation Equations,” Thesis report, School of Engineering and Applied Science, University of Virginia, 2010.

11.     Michael  Anderson and Justin P. Olander, “Evaluation of Two Trip Generation Techniques for Small Area Travel Models,” Journal of Urban Planning and Development © ASCE, vol. 128, no. 2, June 2002, pp. 77-88.

12.     Valerian Kwigizile and Hualiang HarryTeng, “Comparison of Methods for Defining Geographical Connectivity for Variables of Trip Generation Models” ,Journal of Transportation Engineering © ASCE , vol. 135, no. 7, July 2009, pp. 454-466. 


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14.

Authors:

Gymmy Joseph Kattor, Abdul Malik K.V., Pretina George

Paper Title:

Analysis of Trip Attraction Characteristics of Commercial Land Use in Medium Sized Towns in Kerala

Abstract:   Travel demand forecasting is vital for the design of transportation facilities and services, and also for the future development of a town. The study aims to provide a trip attraction model using multiple regression, that is able to predict the trip attracted to any commercial nodes in the medium sized towns in Kerala. This paper also presents an analysis of trip attraction characteristics of the commercial nodes in medium sized towns of Kerala. Using questionnaire survey, the characteristics of the eight selected commercial nodes from the three medium sized towns Tirur, Perinthalmanna, and Ponnani in Kerala are found out. Socioeconomic surveys are conducted for the selected towns for obtaining the origin-destination data. Based on these surveyed data, the characteristics of the selected nodes are studied and correlation and regression analysis are performed. The study showed that the multiple regression model with the independent variables namely the number of employees and percentage of office in the commercial node with the R2 and Adjusted R2 value of 0.999 and 0.9997 respectively gives the better estimate of trip attraction. This model would be very useful for estimating the trips attracted to a new or existing commercial center in any medium sized towns in Kerala, and thus aid to assess the traffic impact of the commercial center on the geometric design of roadways in the surrounding area.

Keywords:
 correlation, multicollinearity, multiple regression, trip attraction


References:

1.        Paquette, R.J., Ashford, N.J., and Wright, P.H., “Transportation Engineering Planning and Design,” John Wiley and Sons, Inc., New York, 1981.      
2.        AASHTO and FHWA. ,”Quick-Response Urban Travel Estimation Techniques and Transferable Parameters,” Users, Guide, National Research Council, Washington, D.C., 1978.            

3.        Institute of Transportation Engineers, “Transportation impact analyses for site development: an ITE proposed recommended practice,” Washington, DC, Institute of Transportation Engineers, 2005.

4.        Alexis M. FILLONE and Michael Ryan TECSON, “Trip Attraction of Mixed-Use Development in Metropolitan Manila,” Proceedings of the Eastern Asia Society for Transportation Studies, Vol.4, October 2003, pp. 860-868.

5.        Budi S. Waloejo, Surjono, and Harnen Sulistio, “The Influence of Trip Attraction on the Road’s Level of Service (LOS) at Traditional Market Land Use,” Journal of Applied Environmental and Biological Sciences, pp. 92-96, February 2012.

6.        J. David Innes, Michael C. Ircha, and Daniel A. Badoe, “Factors affecting automobile shopping trip destinations,” Journal of Urban Planning and Development, vol. 116, no. 3, Dec. 1990.

7.        SCAG Weekend Travel demand Model, Technical Memorandum no.8 - Weekend Trip Attraction Model, Southern california association of Government, June 30, 2008.

8.        Abdul Khalik Al-Taei and Amal M. Taher, “Trip Attraction Development Statistical Model in Dohuk City Residential Area,” Al-Rafidain Engineering, vol.14, no.2, 2006.

9.        Clare Yu and Peter Lawrence, “Trip Generation Model Development for Albany,” in 30th Conference of Australian Institutes of Transport Research (CAITR), December 2008.

10.     Myriam Baumeler, Anja Simma, and Robert Schlich, “Impact of Spatial Variables on Shopping Trips,” STRC 5th Swiss Transport Research Conference March 9-11, 2005.

11.     Barton-Aschman Associates, Inc. and Cambridge Systematics, Inc. “Model Validation and Reasonableness Checking Manual,” February 1997.
 

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15.

Authors:

Anju Jain, Yogesh Chaba

Paper Title:

Design of Efficient and Reliable MAC protocol for Wireless Technologies

Abstract:  In this paper, the performance of IEEE 802.11 MAC protocol is analysed in terms of efficiency and reliability in wireless networks. In the IEEE 802.11, an exponential backoff has been adopted, which means whenever a collision occurs, the contention window (CW) of the station is doubled until it reaches the maximum value. The purpose of increasing CW is to reduce the collision probability by distributing the traffic into a larger time space. In this paper, fixed contention window scheme is used and then correlate the CW size and network size. The interaction of TCP with the MAC protocol is also analysed. For static multi hop network that uses IEEE 802.11 protocol for access, TCP performance is mainly determined by hidden terminal effects ( and not by drop probabilities at buffers) which limits the number of packets that can be transmitted simultaneously in the network. TCP throughput is improved by decreasing the ACKs flows, using delayed ACK, with d=2. Simulation results shows when choosing large maximum window, the delayed ACK considerably outperform standard TCP

Keywords:
 contention window size, MAC protocols, maximum window size, spatial reuse, TCP


References:

1.        IEEE Standard for Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specification, P802.11, November 1999.
2.        Y. Chen, Q-A Zeng, and D. P. Agrawal, "Performance Analysis of IEEE 802.11e Enhanced Distributed Coordination Function," Proceedings of IEEE International Conference on Networking, ISBN: 0-7803-7788-5, pp.573- 578,  August 2003.

3.        M. Kaynia, N. Jindal, and G. Oien, “Improving the performance of wireless ad hoc networks through MAC layer design,” IEEE Trans Wireless Commun, vol. 10 ,no. 1, pp 240-252, jan 2011.

4.        W. Hu, H. Zadeh, X. Li, “Load Adaptive MAC: A Hybrid MAC protocol for MIMO SDR MANETs,”,IEEE,Trans Wireless Commun., vol. 10, no. 11, pp.3924-3933,,Nov 2011

5.        Z. Fu, P. Zerfos, H. Luo, S. Lu, L. Zhang, M. Gerla, “The impact of multihop wireless channel on TCP throughput and loss”, Proc. IEEE INFOCOM, DOI:10.1109, vol. 3 Jan 2003.

6.        P. Garg, R. Doshi, R. Greene, M. Baker, M. Malek, and X. Cheng, "Using IEEE 802.11e MAC for QoS over Wireless," Proceedings of IEEE International Performance, Computing, and Communications Conference, ISSN :1097-2641, pp. 537 -542,April 2003.

7.        Y. Xiao, "Enhanced DCF of IEEE 802.11e to Support QoS," Proceedings of IEEE Wireless Communications and Networking Conference, ISBN: 0-7803-7700-1, pp.1291-1296, vol.2, April 2003.

8.        Y. Chen, Q-A Zeng and D. P. Agrawal. "Performance Analysis and Enhancement of IEEE 802.11 MAC Protocol," Proceedings of IEEE International Conference on Telecommunications, ISBN: 0-7803-7661-7, pp.860 – 867, vol.1, 2003.

9.        “The network simulator - ns-2”, http://www.isi.edu/nsnam/ns/


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16.

Authors:

R.Kayalvizhi, G.Meenakshi

Paper Title:

Growth and Characterization of Pure and Neem Leaves Extract Doped Potassium Dihydrogen Phosphate (KDP) Crystal

Abstract:   KDP-Potassium Dihydrogen Phosphate, slow evaporation technique, organic impurity, NLO

Keywords:
Skin detection, Pixel classification, FPGA, YIQ.


References:

1.        Dmitriev, V.G., Gurzadyan, G.G. and Nicogosyan, D.N., Handbook of Nonlinear Optical Crystals, Spriger-Verlag, New York, (1999).
2.        J.C. Brice, Crystal Growth Processes, Halsted Press, John Wiley and sons, New York (1986).

3.        SA Waksman, ‘What Is an Antibiotic or an Antibiotic Substance?’, Mycologia, 39 (5), (1947) pp. 565–569.

4.        Lindblad WJ, ‘Considerations for Determining if a Natural Product Is an Effective Wound-Healing Agent’, International Journal of Lower Extremity Wounds 7 (2), (2008) pp. 75–81.

5.        Buckley, H.E., Crystal Growth, New York, John Willey sons, Inc, London, Chapman Hall Ltd., (1951) pp. 44.

6.        International Union of Crystallography, Report of the Executive Committee for 1991, Acta Cryst. A, 48(6), (1992) pp.  922.

7.        Krishnaswamy R, Crystal growth and characterization of mixed crystals and doped crystals, Proceedings of the second national seminar on crystal growth (Chennai: Anna University), (1984) pp. 58.

8.        Smith A.L, Applied Infrared Spectroscopy, II Edition, Holden-Day (1977). 


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17.

Authors:

Heenavarshney, Pradeep Kumar

Paper Title:

Secure Communication Architecture Based On “BBCMS” Clustering Algorithm for Mobile Adhoc Network (MANET)

Abstract:   Mobile ad hoc networks are self created and self organized without the support of network infrastructure, consists of mobile devices, such as laptops, cell phones, etc. Security is one of the prime Issues in ad hoc network due to their rapidly change in topology and mobility of nodes. However, the infrastructure less and dynamic natures render them more vulnerable to various types of security attacks than the wired networks. We propose a Secure Communication architecture based on “BBCMS” clustering algorithm. In this algorithm elect cluster head (CH) according to its weight computed by combining a set of system parameters (Stability, Battery, connectivity … etc). It also overcomes some limits in Existed algorithms by defining new mechanisms as cluster dissection, assimilation. In the proposed architecture, the overall network is divided into clusters where the cluster-heads (CH) are connected by virtual networks. For secure data transmission, credential authority (CA) issues a certificate (X.509) to the requested node for authentication. The certificate of a node is renewed or rejected by CH, based on its trust counter value.  

Keywords:
 BBCMS, CertificateX.509, CA, Mobile Ad-Hoc Networks.


References:

1.        Ratish Agarwal, Dr. Mahesh Motwani, “Survey of clustering algorithms for MANET”. International Journal on Computer Science and Engineering Vol.1 (2), 2009,98-104
2.        Mohammad Shayesteh and Nima Karimi, Member, IACSIT,” An Innovative Clustering Algorithm for MANETs Based on Cluster Stability”, International Journal of Modeling and Optimization, Vol. 2, No. 3, June 2012

3.        Yao Yu+, Lincong Zhang “A Secure Clustering Algorithm in Mobile Ad Hoc Networks” IPCSIT vol. 29 (2012).

4.        Salaheddin Dervish, Simon J. E. Taylor and Gheorghita Ghinea “Security Server-Based Architecture for Mobile Adhoc Networks” 2012 IEEE 11th International Conference

5.        B. Kadri, A. M’hamed, M. Feham “Secured Clustering Algorithm for Mobile Ad Hoc Networks” IJCSNS International Journal of Computer Science and Network Security, VOL.7 No.3, March 2007

6.        Nevadita Chatterjee, Anupama Potluri and Atul negi, “Self organizing approach to MANET Clustering”.

7.        Atef Z. Ghalwash, Aliaa A. A. Youssif, Sherif M. Hashad and †Robin Doss “Self Adjusted Security Architecture for Mobile Ad Hoc Networks” 6th IEEE/ACIS International Conference on Computer and Information Science (ICIS 2007).

8.        R. Murugan, A. Shanmugam,” A Cluster Based Authentication Technique for Mitigation of Internal Attacks in MANET” ISSN 1450-216X Vol.51 No.3 (2011), pp.433-441.

9.        Chatterjee, M., Das, S., & Turgut, D. “WCA: A Weighted Clustering Algorithm (WCA) for mobile ad  hoc networks”. Cluster Computing (PP. 193- 204). Kluwer Academic, 2002.

10.     Abdel Rahman H. Hussein, Sufian Yousef, and Omar Arabiyat “A Load-Balancing and Weighted Clustering Algorithm in Mobile Ad-Hoc Network”

11.     R.PushpaLakshmi “Cluster Based Composite Key Management in MobileAd Hoc Networks” International Journal of Computer Applications Volume 4 – No.7, July 2010.

12.     S.Muthuramalingam and R.Rajaram” A TRANSMISSION RANGE BASED CLUSTERING ALGORITHMFOR TOPOLOGY CONTROL MANET” International journal on applications of graph theory in wireless ad hoc networks and sensor networks Vol.2, No.3,Septembe r 2010 


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18.

Authors:

Laukik P. Raut

Paper Title:

Computer Simulation of CI Engine for Diesel and Biodiesel Blends

Abstract:   Among the alternative fuels, biodiesel and its blends are considered suitable and the most promising fuel for diesel engine. The properties of biodiesel are found similar to that of diesel. Many researchers have experimentally evaluated the performance characteristics of conventional diesel engines fuelled by biodiesel and its blends. However, experiments require enormous effort, money and time. Hence, a cycle simulation model incorporating a thermodynamic based single zone combustion model is developed to predict the performance of diesel engine. A comprehensive computer code using “C” language was developed for compression ignition (C.I) engine. Combustion characteristics such as cylinder pressure, heat release, heat transfer and performance characteristics such as work done, brake power and brake thermal efficiency (BTE) were analyzed. On the basis of first law of thermodynamics the properties at each degree crank angle was calculated. The simulated combustion and performance characteristics are found satisfactory with the experimental results.

Keywords:
 Biodiesel, Numerical modeling, simulation.


References:

1.        Carraretto C, Macor A , Mirandola A , Stoppato A , Tonon S. “Biodiesel as alternative fuel: experimental analysis and energetic evaluations”. Energy 20 0 4;29:2195–211.
2.        Reyes JF, Sepulveda MA. PM-10, “ Emissions and power of a diesel engine fueled with crude and refined biodiesel from Salmon oil”. Fuel 2006;85:1714–9.

3.        Labeckas G, Slavinskas S. “The effect of rapeseed oil methyl ester on direct injection diesel engine performance and exhaust emissions”. Energy Conversion and Management 2006; 47:1954–67.

4.        Tsolakis A , Megaritis A , Wyszynski ML, Theinnoi K. “Engine performance and emissions of a diesel engine operating on diesel-RME (rapeseed methyl ester) blends with EGR (exhaust gas recirculation)”. Energy 2007;32:2072–80.

5.        Tsolakis A , Megaritis A , Yap D. “Engine performance and emissions of a diesel engine operating on diesel-RME (rapeseed methyl ester) blends with EGR (exhaust gas recirculation)”. Energy 20 08;33:462–70.

6.        Ramadhas AS, Muraleedharan C, Jayaraj S. “Performance and emission evaluation of a diesel engine fueled with methyl esters of rubber seed oil”. Renewable
Energy 2005;30:1789–800.

7.        Usta N. “An experimental study on performance and exhaust emissions of a diesel engine fuelled with tobacco seed oil methyl ester”. Energy Conversion and Management 2005;46:2373–86.

8.        Neto da Silva F, Prata SA, Teixeira JR. “Technical feasibility assessment of oleic sunflower methyl ester utilization in diesel bus engines”. Energy Conversion and Management 2003;4 4:2857–78.

9.        Hu Z, Tan P, Yan X, Lou D. “Life cycle energy, environment and economic assessment of soybean-based biodiesel as an alternative automotive fuel in China”. Energy 2008;33:1654–8.

10.     Narayana Rao GL, Prasad BD, Sampath S, Rajagopal K. “Combustion analysis of diesel engine fuelled with jatropha oil methyl ester-diesel blend”. International Journal of Green Energy 2007;4:645–58.

11.     Raheman H, Phadatare AG. “Diesel engine emissions and performance from blends of karanja methyl ester and diesel”. Biomass and Bioenergy 2004;27:393–7.

12.     Heywood JB. Internal combustion engine fundamentals. New York: McGrawHill; 1988.
 

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19.

Authors:

Swarna Bajaj, Sumeet Kaur

Paper Title:

Typing Speed Analysis of Human for Password Protection (Based On Keystrokes Dynamics)

Abstract:   Today is an important problem for describe as authentic, you mean that it is such a good imitation that it is almost the same as or good as the original in computer system. Specially those used in e-banking, e-commerce, virtual offices, e-learning, distributed, computing and other services over the internet. Using keystroke dynamics technology we can secure our password. This technology is based on human behavior to type their password. We analysis the human behavior with their typing pattern. Keystroke dynamics are hardware independent, no extra hardware is  used. Only software based technology keyboard is required for password protection. The results provide emphasis with pleasure security that growing in demand in web-based application based on internet.

Keywords:
 Keystroke dynamics, Net bean IDE, Pressing time, secure password.


References:

1.        Mariusz Rybnik, Piotr Panasiuk & Khalid Saeed “User authentication with Keystroke dynamics using Fixed Text” University of Bialystok Marii  Sklodowskiej Curie 14, 15  097,978-07695-3692-  7/09 $25.00 ©  2009 IEEE.
2.        Saurabh Singh, Dr. K.V.Arya “Key Classification: a New Approach in Free Text Keystroke Authentication System” Invertis University Bareilly, India, 978-1-4577-0856-5/11/$26.00 © 2011, IEEE.

3.        Mudhafar M.AL-Jarrah “An Anomaly Detector for Keystroke Dynamics Based on Medians Vector Proximity” Department of Computer Information Systems, Middle East University, Amman, Jordan, VOL 3, NO. 6, © 2009-2012 CIS Journal.

4.        Killourhy, K. & Maxion, R.,”Comparing anomaly-detection algorithms for keystroke  dynamics”,IEEE/IFIP International Conference on Dependable Systems & Networks, 2009.  DSN’09,   pp. 125– 134.2009

5.        Killourhy, K. &  Maxion, R. “Keystroke biometrics with number  pad input”,IEEE/IFIP International Conference on Dependable Systems & Networks, 2010. DSN’10

6.        Hocquet, S. Ramel, J.-Y. & Cardot, H, “Fusion of methods for keystroke dynamic authentication”. autoid, 0, 224–229.2005

7.        Heather Crawford “Keystroke Dynamics: Characteristics and Opportunities” Department of   Computing Science Sir Alwyn Williams BuildingUniversity of Glasgow Glasgow, 978-1- 4244 7550 6/10/$26.00 ©2010 IEEE.

8.        S. J. Shepherd, “Continuous authentication by analysis of keyboard typing characteristics”, Proc. IEEE European Convention on Security and Detection, vol. 16-18, May 1995, pp. 111- 114.

9.        R. V. Yampolskiy, "Motor-Skill Based Biometrics," In Assuring Business processes, Proceedings of the 6th Annual Security Conference, Ed. G. Dhillon. Global Publishing, Las Vegas NV, USA. April 11-12, 2007. 


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20.

Authors:

Zhaorui Wang, Christopher Fortson

Paper Title:

The Design and Test of a Private Cloud Storage System, Part II

Abstract:   Currently, cloud computing is a popular techniques. Many large-scale problems in practice require cloud computing and cloud storage. Even if public cloud is available, many private companies plan to build their private cloud for security reasons. This paper presents testing results of the proposed private cloud architecture in part I of this paper.

Keywords:
 Cloud computing, private cloud and YCSB.


References:

1.        OpenStack. Available: http://www.openstack.org/.
2.        Eucalyptus. Available: http://www.eucalyptus.com/.

3.        K. Ahmed, and M. Gregory, "Integrating Wireless Sensor Networks with Cloud Computing," 2011 Seventh International Conference on Mobile Ad-hoc and Sensor Networks (MSN), pp.364-366, Dec. 2011.

4.        W. Kurschl and W. Beer, “Combining cloud computing and wireless sensor networks”, in Proceedings of the 11th ACM International Conference on Information Integration and Web-based Applications & Services, New York, NY, USA, pp. 512-518.

5.        Z. X. Luo and T. C. Jannett, “Optimal threshold for locating targets within a surveillance region using a binary sensor network,” in Proc. of the International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering, Dec., 2009.

6.        Z. X. Luo and T. C. Jannett, “Energy-based target localization in Multi-hop wireless sensor networks,” in Proc. of the 2012 IEEE Radio and Wireless Symposium, Santa Clara, CA, Jan. 2012.

7.        H. Chen and P. K. Varshney, "Nonparametric quantizers for distributed estimation," IEEE Trans. Signal Process., vol 58, no 7, pp. 3777-3787, July 2010.

8.        Z. X. Luo and T. C. Jannett, “Modeling sensor position uncertainty for robust target localization in wireless sensor networks,” in Proc. of the 2012 IEEE Radio and Wireless Symposium, Santa Clara, CA, Jan. 2012.

9.        H. Chen and P. K. Varshney, “Performance Limit for Distributed Estimation Systems with Identical One-Bit Quantizers," IEEE Transaction on Signal Processing, Vol. 58, No. 1, pp. 466-471, Jan. 2010.

10.     Z. X. Luo and T. C. Jannett, “Performance comparison between maximum likelihood and heuristic weighted average estimation methods for energy-based targetlocalization in wireless sensor networks,” in Proc. of the 2012 IEEE SoutheastCon Conference, Orlando, FL, Mar. 2012.

11.     Q. Cheng, P. K. Varshney, J. H. Michels, and C. M. Belcastro, "Distributed fault detection with correlated decision fusion," IEEE Trans. Aerosp. Electron. Syst., Volume 45, No. 4, pp.1448 – 1465, October 2009.

12.     Z. X. Luo and T. C. Jannett, “A multi-objective method to balance energy consumption and performance for energy-based target localization in wireless sensor networks,” in Proc. of the 2012 IEEE SoutheastCon Conference, Orlando, FL, Mar. 2012.

13.     Lustre. Available: http://lustre.org/.

14.     HDFS. Available: http://hadoop.apache.org/.

15.     MongoDB Available:http://www.mongodb.org/.

16.     Tomcat. Available: http://tomcat.apache.org/.

17.     Nginx. Available: http://nginx.org/.

18.     Yahoo! Cloud Serving Benchmark. Available: http://research.yahoo.com/Web_Information_Management/YCSB.

19.     ParaStor. Available: http://www.sugon.com/product/detail/productid/37.html.

20.     Z. X. Luo, “A censoring and quantization scheme for energy-based target localization in wireless sensor networks,” Journal of Engineering and Technology, vol.2, no.2, Aug. 2012.

21.     K. C. Ho, “Bias reduction for an explicit solution of source localization using TDOA,” IEEE Trans. Signal Processing, vol. 60, pp. 2101-2114, May 2012.

22.     Z. X. Luo, “A coding and decoding scheme for energy-based target localization in wireless sensor networks,” International Journal of Soft Computing and Engineering, vol.2, no. 4, Sept. 2012.

23.     Y. Li, K. C. Ho, and M. Popescu, “A microphone array system for automatic fall detection,” IEEE Trans. Biomedical Engineering, vol. 59, pp. 1291-1301, May 2012.

24.     K. C. Ho and R. Rabipour, “A design and use case for inhibiting the adaptation of echo canceller without using external control,” Contribution C816R1, ITU WP1/SG16 Standard Meeting, Geneva, Switzerland, May 2012.

25.     Z. X. Luo, “Anti-attack and channel aware target localization in wireless sensor networks deployed in hostile environments,” International Journal of Engineering and Advanced Technology, vol. 1, no. 6, Aug. 2012.

26.     Y. Shang, W. Zeng, K. C. Ho, D. Wang, Q. Wang, Y. Wang, T. Zhuang, A. Lobzhanidze, and L. Rui, “NEST: networked smartphones for target localization,” in Proc. IEEE CCNC 2012, Las Vegas, Jan. 2012, pp. 732-736.

27.     Z. X. Luo, “Robust energy-based target localization in wireless sensor networks in the presence of byzantine attacks,” International Journal of Innovative Technology and exploring Engineering, vol. 1, no.3, Aug. 2012.

28.     L. Yang and K. C. Ho, “Alleviating sensor position error in source localization using calibration emitters at inaccurate locations,” IEEE Trans. Signal Processing, vol. 58, pp. 67-83, Jan. 2010.

29.     Z. X. Luo, “A new direct search method for distributed estimation in wireless sensor networks,” International Journal of Innovative Technology and Exploring Engineering, vol. 1, no. 4, Sept. 2012.

30.     T. Glenn, J. N. Wilson, and K. C. Ho, “A multimodal matching pursuits dissimilarity measure applied to landmine/clutter discrimination,” in Proc. IEEE Int. Geoscience and Remote Sensing Symp. IGARSS, Honolulu, July 2010.

31.     M. Popescu, K. E. Stone, T. C. Havens, J. M. Keller, and K. C. Ho, “Anomaly detection in forward-looking infrared imaging using one-class classifiers,” in Proc. SPIE Conf. Detection and Remediation Technologies for Mines and Minelike Targets XV, Orlando, Apr. 2010.

32.     Z. X. Luo, “Distributed estimation and detection in wireless sensor networks,” International Journal of Inventive Engineering and Sciences, vol. 1, no. 3, Feb. 2013.

33.     T. C. Havens, C. J. Spain, K. C. Ho, J. M. Keller, Tuan T. Ton, D. C. Wong, and M. Soumekh, “Improved detection and false alarm rejection using FLGPR and color imagery in a forward-looking system,” in Proc. SPIE Conf. Detection and Remediation Technologies for Mines and Minelike Targets XV, Orlando, Apr. 2010.

34.     George Kousiouris, Tommaso Cucinotta, Theodora Varvarigou, "The Effects of Scheduling, Workload Type and Consolidation Scenarios on Virtual Machine Performance and their Prediction through Optimized Artificial Neural Networks"[19] , The Journal of Systems and Software (2011),Volume 84, Issue 8, August 2011, pp. 1270-1291, Elsevier, doi:10.1016/j.jss.2011.04.013.

35.     Ko, Ryan K. L. Ko; Kirchberg, Markus; Lee, Bu Sung (2011). "From System-Centric Logging to Data-Centric Logging - Accountability, Trust and Security in Cloud Computing". Proceedings of the 1st Defence, Science and Research Conference 2011 - Symposium on Cyber Terrorism, IEEE Computer Society, 3–4 August 2011, Singapore.

36.     Ko, Ryan K. L.; Jagadpramana, Peter; Mowbray, Miranda; Pearson, Siani; Kirchberg, Markus; Liang, Qianhui; Lee, Bu Sung (2011). "TrustCloud: A Framework for Accountability and Trust in Cloud Computing". Proceedings of the 2nd IEEE Cloud Forum for Practitioners (IEEE ICFP 2011), Washington DC, USA, July 7–8, 2011.

37.     Daniel Nurmi, Rich Wolski, Chris Grzegorczyk, Graziano Obertelli, Sunil Soman, Lamia Youseff, Dmitrii Zagorodnov, “The Eucalyptus Open-source Cloud-computing System”, Computer Science Department, University of California - Santa Barbara, Santa Barbara, California 93106.

38.     Mike P. Papazoglou, “Service -Oriented Computing: Concepts, Characteristics and Directions”, Tilburg University, INFOLAB.

39.     Rajiv Ranjan, Rajkumar Buyya, “Decentralized Overlay for Federation of Enterprise Clouds”, Grid Computing and Distributed Systems (GRIDS) Laboratory, Department of Computer Science and Software Engineering, The University of Melbourne, Australia.

40.     Marianne C. Murphy, Marty McClelland, “Computer Lab to Go: A “Cloud” Computing Implementation”, Proc ISECON 2008, v25.


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21.

Authors:

Divyata N. Patel, Jemish V. Maisuria, Milind S. Shah

Paper Title:

Overview of Techniques for Improving MAC over Wireless Sensor Networks

Abstract:   In recent years, sensor networks have transitioned from being objects of academic research interest to a technology that is frequently being deployed in real-life applications and rapidly being commercialized. Wireless sensor networks use battery operated computing and sensing devices. Energy consumption continues to remain a barrier challenge in many sensor network applications that require long lifetimes. However, lower sensing ranges result in dense networks, which bring the necessity to achieve an efficient medium access protocol subject to power constraints. Various MAC protocols with different objectives were proposed for wireless sensor networks. This article surveys several techniques that show promise in addressing and alleviating this MAC improvement challenge. In this paper, we describe several MAC protocols proposed for sensor networks emphasizing their advantages and disadvantages. Finally, we point out conclusion on MAC layer design.

Keywords:
 MAC Protocols, Sensor Networks, Survey, SMAC, duty cycle.


References:

1.        S.S., Kulkarni, “TDMA services for Sensor Networks”, Proceedings of 24th International Conference on Distributed Computing Systems Workshops, Pages:604 – 609, 23-24 March 2004.
2.        W. Ye, J. Heidemann, D. Estrin, “Medium Access Control With Coordinated Adaptive Sleeping for Wireless Sensor Networks”, IEEE/ACM Transactions on Networking, Volume: 12, Issue: 3, Pages:493 - 506, June 2004.

3.        A. El-Hoiydi, “Spatial TDMA and CSMA with preamble sampling for low power ad hoc wireless sensor networks”, Proceedings of ISCC 2002, Seventh International Symposium on Computers and Communications, Pages:685 - 692, 1-4 July 2002.

4.        B. C. Enz, A. El-Hoiydi, J-D. Decotignie, V. Peiris, “WiseNET: An Ultralow-Power Wireless Sensor Network Solution”, IEEE Computer, Volume: 37, Issue: 8, August 2004.

5.        K. Jamieson, H. Balakrishnan, and Y. C. Tay, “Sift: A MAC Protocol for Event-Driven Wireless Sensor Networks,” MIT Laboratory for Computer Science, Tech. Rep. 894, May 2003, http://www.lcs.mit.edu/publications/pubs/pdf/MIT-LCS-TR-894.pdf.

6.        Y.C. Tay, K.Jamieson, H. Balakrishnan, “Collision-minimizing CSMA and Its Applications to Wireless Sensor Networks”, IEEE Journal on Selected Areas in Communications, Volume: 22, Issue: 6, Pages: 1048 – 1057, Aug. 2004.

7.        G. Lu, B. Krishnamachari, C.S. Raghavendra, “An adaptive energyefficient and low-latency MAC for data gathering in wireless sensor networks”, Proceedings of 18th International Parallel and Distributed Processing Symposium, Pages: 224, 26-30 April 2004.

8.        T.V. Dam and K. Langendoen, “An Adaptive Energy-Efficient MAC Protocol for Wireless Sensor Networks”, The First ACM Conference on Embedded Networked Sensor Systems (Sensys‘03), Los Angeles, CA, USA, November, 2003.

9.        Haigang Hu, Jie Min, Xiaodong wang and Yu Zhou, “The Improvement of SMAC based on dynamic duty cycle in wireless sensor network”, IEEE Conference Publication, 978-1-4244-8728-8/11, Pages: 341-345 2011. 


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22.

Authors:

Purnima K. Pandit

Paper Title:

Systems with Negative Fuzzy Parameters

Abstract:   Various primitive Engineering and Sciences applications can be modeled using system of linear equations. In such models it can happen that the values of the parameters are not known or they cannot be stated precisely only their estimation due to experimental data or expert knowledge is available. In such situation it is convenient to represent such parameters by fuzzy numbers (refer [14]). The method and the conditions for obtaining the fuzzy solution for the systems with positive fuzzy parameters is given in [10]. There are applications wherein the model involves even negative fuzzy parameters. In this paper, an algorithm for solving such fuzzy systems is proposed and illustrated.

Keywords:
 negative fuzzy numbers, α-cut, parallel processing, fully fuzzy systems.


References:

1.        S. Abbasbandy S., R. Ezzati and A. Jafarian, LU decomposition method for solving fuzzy system of linear equations, Applied Mathematics and Computation 172 (2006), 633-643.
2.        T. Allahviranloo, M. Ghanbari, A. A. Hosseinzadeh, E. Haghi and R. Nuraei, A note on Fuzzy linear systems, Fuzzy Sets and Systems 177(1) (2011), 87–92.

3.        J. J. Buckley and Y. Qu, Solving linear and quadratic fuzzy equations, Fuzzy Sets and Systems, 38 (1990), 43–49.

4.        M. Dehghan, B. Hashemi and M. Ghatee, Computational methods for solving fully fuzzy linear systems, Applied Mathematics and Computation, 179 (2006), 328–343.

5.        D. Dubois and H. Prade, Fuzzy Sets and Systems: Theory and Applications, Academic Press,New York, 1980.

6.        M. Friedman, M. Ming and A. Kandel, Fuzzy linear systems, Fuzzy Sets and Systems, 96 (1998), 201-209.

7.        G. Klir and B.Yuan, Fuzzy Sets and Fuzzy Logic Theory and Applications, Prentice Hall, 1997.

8.        S. H. Nasseri, M. Abdi and B. Khabiri, An Application of Fuzzy linear System of Equations in Economic Sciences, Australian Journal of Basic and Applied Sciences, 5(7) (2011), 7–14.

9.        S. H. Nasseri and M. Sohrabi, Gram-Schmidt approach for linear System of Equations with fuzzy parameters, The Journal of Mathematics and Computer Science, 1(2) (2010), 80–89.

10.     Pandit Purnima, Fully Fuzzy System of Linear Equations, International Journal of Soft Computing and Engineering, 2(5) (2012) , 159–162.

11.     T. Rahgooy, H. Sadoghi and R. Monsefi, Fuzzy Complex System of linear equations Applied to Circuit Analysis, International Journal of Computer and Electrical Engineering, 1(5) (2009), 535–541.

12.     A. Sadeghi, I. M. Ahmad and A. F. Jameel, Solving Systems of Fuzzy Differential Equation, International Mathematical Forum, 6 (42) (2011), 2087–2100.

13.     M. J. Quinn, Parallel Computing Theory and Practice, Oregon State University, Second Edition. (2002).

14.     L. A. Zadeh, Fuzzy sets, Information and Control, 8 (1965), 338-353. 


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23.

Authors:

Sowmya Lakshmi B S, Sowmya A N Gowda

Paper Title:

A Pair Wise Key Pre-Distribution Scheme for Wireless Sensor Networks

Abstract:   Wireless sensor networks (WSNs) are highly vulnerable to attacks for the limitation of constrained resource and communicating via wireless links, especially running in a hostile environment such as battlefields. In such situation, an adversary may capture any node compromising critical security data including keys used for confidentiality and authentication. Consequently, it is necessary to provide security services to these networks to ensure their survival. In this paper, we propose a new key management technique based on differentiated key pre-distribution, to provide end-to-end secure communication. The core idea is to distribute different number of keys to different sensors to enhance the resilience of certain links. This feature is leveraged during routing, where nodes route through those links with higher resilience. The analysis also shows that the technique can substantially improve the security as well as the performance of existing key pre-distribution techniques.

Keywords:
 Sensor Networks, security, Key Management, Key Pre-distribution


References:

1.        B. Karp and H. Kung, “GPSR: greedy perimeter stateless routing for wireless networks," in Proc. ACM International Conf. Mobile Compute. Netw., Aug. 2000.
2.        C. Intanagonviwat, R. Govindan, and D. Estrin, “Directed diffusion: a scalable and robust communication paradigm for sensor networks," in Proc. ACM International Conf. Mobile Comput. Netw., Aug. 2000.

3.        W. Heinzelman, A. Chandrakasan, and H. Balakrishnan," Energy efficient communication  protocols for wireless micro sensor networks (leach)", Proceedings of the 33rd Hawaii International Conference on System Sciences - 2000.

4.        C. Schugers and M. Srivastava, “Energy efficient routing in wireless sensor networks," in Proc. Milcom, Oct. 2001.

5.        L. Eschenauer and V. D. Gligor, “L. Eschenauer and V. D. Gligor, "A Key-Management Scheme for distributed sensor networks," in Proc. 9th ACM Conf. Comput. Commun.  Security, Nov. 2002.

6.        H. Chan, A. Perrig, and D. Song, “Random key predistribution schemes for sensor networks," in Proc. IEEE Symp. Research Security Privacy, May 2003.

7.        S. Zhu, S. Xu, S. Setia, and S. Jajodia, “Establishing pairwise keys for secure communication in ad hoc networks: a probabilistic approach," in Proc. 11th IEEEInternational Conf. Netw. Protocols, Nov. 2003.

8.        D. Liu and P. Ning, “Establishing pairwise keys in distributed sensor networks," in Proc. 10th ACM Conf. Comput. Commun. Security, Oct. 2003.

9.        S. Tanachaiwiwat, P. Dave, R. Bhindwale, and A. Helmy, “Secure locations: routing on trust and isolating compromised sensors in location aware sensor networks," in Proc. 1st ACM Conf. Embedded Netw. Sensor Syst., Nov. 2003

10.     W. Du, J. Deng, Y. S. Han, and P. K. Varshney, “A pairwise key predistribution scheme for wireless sensor networks," in Proc. 10th ACM Conf. Comput. Commun. Security, Oct. 2003.

11.     D. Liu and P. Ning, “Improving key predistribution with deployment knowledge in static sensor networks," ACM Trans. Sensor Netw., vol. 1, no. 2, pp. 204-239, 2005.

12.     A. D. Wood, L. Fang, J. A. Stankovic, and T. He, “SIGF: a family of configurable, secure routing protocols for wireless sensor networks," in Proc. 4th ACM Workshop Security Ad Hoc Sensor Netw., Oct. 2006.

13.     P. Traynor, H. Choi, G. Cao, S. Zhu, and T. L. Porta, “Establishing pair-wise keys in heterogeneous sensor networks," in Proc. 25th IEEE Conf. Comput. Commun., Apr. 2006.

14.     S. Chellappan, W. Gu, X. Bai, B. Ma, D. Xuan, and K.Zhang, “Deploying  wireless  sensor networks under limited mobility constraints," IEEE Trans. Mobile Comput., vol. 6, no. 10, Oct. 2007.

15.     D. Liu, P. Ning, and W. Du, “Group-based key predistribution for wireless sensor networks," ACM Trans. Sensor Netw., vol. 4, no. 2, pp. 1-30, 2008.

16.     A. Poornima and B. Amberker," Key Management Schemes for Secure Communication in Heterogeneous Sensor Networks", International Journal of Recent Trends in Engineering, Vol 1, No. 1, May 2009.

17.     H. Dai and H. Xu, “Triangle-based key management scheme for wireless sensor networks," Frontiers Electrical Electron. Eng. China, vol. 4, no. 3, pp. 300-306, 2009.

18.     Y. Lee and S. Lee," A new efficient key management protocol for wireless sensor and actor networks", (IJCSIS) International Journal of Computer Science and Information Security, Vol. 6, No. 2, 2009.

19.     N. Canh, P. Truc, T. Hai, Y. Lee, and S. Lee, “Enhanced group-based key management scheme for wireless sensor networks using deployment knowledge," in Proc. 6th IEEE Consumer Commun. Netw. Conf., pp. 1- 5, 2009.

20.     Wenjun Gu, Neelanjana Dutta, Sriram Chellappan, And Xiaole Bai," Providing End-To-End Secure Communications In Wireless Sensor Networks", IEEE Transactions On Network And Service Management, Vol. 8, No. 3, September 2011. 


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24.

Authors:

Shalini.M.G, Punithkumar.M.B, M.B.Anandaraju

Paper Title:

FPGA-Based Implementation of Intelligent Predictor using ANN for Global Solar Irradiation

Abstract:   Global solar irradiation is considered as one of the most important parameter in the design of renewable and solar energy systems. Global solar irradiation is usually represented as time series. Frequently, the measured data are not always available, especially in the remote areas because of the absence of the meteorological stations or measuring instruments. Numerous studies in the literature have shown the possibility to find a correlation between solar irradiation and other meteorological parameters such as air temperature, humidity, sunshine duration etc. The models that are existing so far are based on the probability estimation, which do not always give good generation of data.in order to overcome this problem AI techniques have been applied. In this paper suitable intelligent predictor  is developed  and implemented using a Belgaum region database as the input using ANN for solar irradiation., to develop a hardware board which can be used for real time predictors of solar irradiation in areas where there no stations.

Keywords:
 Global solar irradiation, ANN


References:

1.        Adnan, S., Arcakly´ ogclu, E., Ozalp, M., &Agclar, N. C. (2005). Forecasting based on neural network approach of solar potential in Turkey. Renewable Energy, 30, 1075–1090.
2.        Aguiar, R. J., &Collares-Perreira, M. (1992). T.A.G.A time dependent autoregressive Gaussian model for generating synthetic hourly radiation. Solar Energy, 49(3), 167–174.

3.        Allen, R. G. (1997). Self-calibrating method for estimating solar radiation from air temperature. Journal of Hydraulic Engineering, 2(2), 56–67.

4.        Amos, B., Omondi, C., &Aajapakse, J. (2006). FPGA implementations of neural networks. Springer.

5.        Angstrom, A. (1924). Solar and terrestrial radiation. Quarterly journal of the Royal Meteorological Society, 50, 121–126.

6.        Benghanem, M., Mellit, A., &Alamri, S. N. (2009). ANN-based modelling and estimation of daily global solar radiation data: A case study. Energy Conversion and Management, 50, 1644–1655.

7.        Bristow, K. L., & Campbell, G. S. (1984). On the relationship between incoming solar radiation and daily maximum and minimum temperature. Agricultural and Forest Meteorology, 31, 159–166.

8.        Cao, J. C., & Cao, S. H. (2006). Study of forecasting solar irradiance using neural networks with preprocessing sample data by wavelet analysis. Energy, 3, 3435–3445.

9.        Chandel, S. S., Agarwal, R. K., &Pandey, A. N. (2005). New correlation to estimate global solar radiation on horizontal surfaces using sunshine hour and temperature data for indian sites. Journal of Solar Energy Engineering, 127, 417–420.

10.     David, B. A., &Atsu, S. S. D. (1999). Estimation of solar radiation from the number of sunshine hours. Applied Energy, 63, 161–167.

11.     Gomez, V., & Casanovas, A. (2003). Fuzzy modeling of solar irradiance on inclined surfaces. Solar Energy, 75, 307–315.

12.     Haykin, S. (1999). Neural network: A comprehensive foundation. Neural Network: Macmillan.

13.     Helen, C. (2007). Power estimating clear-sky beam irradiation from sunshine duration. Solar Energy, 71(4), 217–224.

14.     Hontoria, L., Aguilera, J., &Zufiria, P. (2005). An application of the multilayer perceptron: Solar radiation maps in Spain. Solar Energy, 79, 523–530.

15.     Maafi, A., &Adane, A. (1989). A two state Markovian model of global irradiation suitable for photovoltaic conversion. Solar Wind Technology, 6, 247–252.

16.     Mehreen, S., Muneer, G. T., &Kambezidis, H. D. (1998). Models for obtaining solar radiation from other meteorological data. Solar Energy, 64(1–3), 99–108.

17.     Mekki, H., Mellit, A., Salhi, H., &Khaled, B. (2008). FPGA-based implementation of multilayer perceptron for modelling of photovoltaic panel. American Institute of Physics A.I.P Conference Proceedings, 1019, 211–215.

  

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25.

Authors:

Saju Mathew

Paper Title:

Cloud Computing: A New Foundation Towards Health Care

Abstract:   With the development of parallel computing, distributed computing, grid computing a new computing model has appeared that is ‘cloud computing’.  The concept of computing comes from grid, public computing and SaaS.  It is a new method that shares basic framework.  The basic principles of cloud computing is to make the computing be assigned in a great number of distributed computer, rather than local computer or remote computer.  This paper introduces the application of the merit of cloud computing, such as it does not need the user’s high level equipment resulting in cost reduction.  This paper proposes an application of cloud computing to store medical records in cloud minimizing the resources needed.  It provides dependable data storage for the user to store the patient’s data in the cloud.  The uses of the cloud computing can be implemented in health care and can be effectively used to maintain the patient’s records on the cloud.

Keywords:
 Cloud computing, Electronic medical report, IaaS, PaaS, SaaS.


References:

1.        Cloud Security Alliance and Security Guidance for Critical Areas of Focus in Cloud Computing, 2009, V2.1.
2.        P.Patel, A. Ranabahu and A. Sheth, 2009, “Service Level Agreement in Cloud Computing”, Conference on Object Oriented Programming Systems Languages and Application, Orlando, Florida, USA

3.        S. Bertram, M. Boniface, et al., 2010, “On-Demand Dynamic Security for Risk-Based Secure Collaboration in Clouds,” IEEE 3rd International Conference in Cloud Computing, pp. 518-525.

4.        A. Weiss, 2007, BComputing in the clouds, vol. 11, no.4, pp.16-25

5.        B. Hayes, 2008, BCloud Computing, vol.51, no.7,  pp 9-11

6.        Kestler. H.A, Haschka. M, Kartz. W, Schwenker. K, Palm. G, Hombach. V and Hoher. M (1998), “Denoising of High-Resolution ECG-Signals by Combining the Discrete Wavelet Transform with the Wiener Filter”, in proceedings IEEE Conference on Computers in Cardiology, pp 233-236

7.        “An example of colud platform for building applications”,

8.        On cloud computing environment security policy,

9.        http://www.healthcareitnews.com/news/5-ways-cloud-computing-will-transform-healthcare?page=1.

10.     www.Cloud.softlayer.com

11.     www.hamrheadinc.com

12.     www.cloudcomputingzone.com

13.     “Building grep the web in the cloud, part 1: Cloud Architecture”,

14.     Boss G., Malladi P., Quan D., Legregni L., Hall H.; “IBM on  Cloud Computing; High Performance On-Demand Solutions, IBM”; 8th  Oct 2007

15.     Microsoft. (2006, October, 2010). Multi-Tenant Data Architecture. Available: http://msdn.microsoft.com/en-us/library/aa479086.aspx

16.     CDW 2011 Cloud Computing Tracking Poll –

17.     “ How to improve health care with cloud computing”, By Hitachi Data Systems, May 2012 


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26.

Authors:

Zhaorui Wang

Paper Title:

The Design and Test of a Private Cloud Storage System, Part I

Abstract:   Currently, cloud computing in the development stage, and technology is not mature. The core technology tends to be open source software. For security reasons or for mistrust of public cloud, some companies or organizations prefer to build their own private cloud, while reluctant to use public cloud services. In this context, this paper presents a general architecture, which well meets the needs of enterprises or institutions. This private cloud storage system has a highly scalable, high stability and high concurrent processing capability and low cost advantages. The key part of this architecture chooses ParaStor and MongoDB, and performance was tested when they work together and benchmarking tool YCSB was used to do the test. The test results indirectly illustrate the feasibility of the program.

Keywords:
 cloud computing, private cloud and YCSB.


References:

1.        OpenStack. Available: http://www.openstack.org/.
2.        Eucalyptus. Available: http://www.eucalyptus.com/.

3.        K. Ahmed, and M. Gregory, "Integrating Wireless Sensor Networks with Cloud Computing," 2011 Seventh International Conference on Mobile Ad-hoc and Sensor Networks (MSN), pp.364-366, Dec. 2011.

4.        W. Kurschl and W. Beer, “Combining cloud computing and wireless sensor networks”, in Proceedings of the 11th ACM International Conference on Information Integration and Web-based Applications & Services, New York, NY, USA, pp. 512-518.

5.        Z. X. Luo and T. C. Jannett, “Optimal threshold for locating targets within a surveillance region using a binary sensor network,” in Proc. of the International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering, Dec., 2009.

6.        Z. X. Luo and T. C. Jannett, “Energy-based target localization in Multi-hop wireless sensor networks,” in Proc. of the 2012 IEEE Radio and Wireless Symposium, Santa Clara, CA, Jan. 2012.

7.        H. Chen and P. K. Varshney, "Nonparametric quantizers for distributed estimation," IEEE Trans. Signal Process., vol 58, no 7, pp. 3777-3787, July 2010.

8.        Z. X. Luo and T. C. Jannett, “Modeling sensor position uncertainty for robust target localization in wireless sensor networks,” in Proc. of the 2012 IEEE Radio and Wireless Symposium, Santa Clara, CA, Jan. 2012.

9.        H. Chen and P. K. Varshney, “Performance Limit for Distributed Estimation Systems with Identical One-Bit Quantizers," IEEE Transaction on Signal Processing, Vol. 58, No. 1, pp. 466-471, Jan. 2010.

10.     Z. X. Luo and T. C. Jannett, “Performance comparison between maximum likelihood and heuristic weighted average estimation methods for energy-based target localization in wireless sensor networks,” in Proc. of the 2012 IEEE SoutheastCon Conference, Orlando, FL, Mar. 2012.

11.     Q. Cheng, P. K. Varshney, J. H. Michels, and C. M. Belcastro, "Distributed fault detection with correlated decision fusion," IEEE Trans. Aerosp. Electron. Syst., Volume 45, No. 4, pp.1448 – 1465, October 2009.

12.     Z. X. Luo and T. C. Jannett, “A multi-objective method to balance energy consumption and performance for energy-based target localization in wireless sensor networks,” in Proc. of the 2012 IEEE SoutheastCon Conference, Orlando, FL, Mar. 2012.

13.     Lustre. Available: http://lustre.org/.

14.     HDFS. Available: http://hadoop.apache.org/.

15.     MongoDB Available:http://www.mongodb.org/.

16.     Tomcat. Available: http://tomcat.apache.org/.

17.     Nginx. Available: http://nginx.org/.Yahoo! Cloud Serving Benchmark. Available:

18.     http://research.yahoo.com/Web_Information_Management/YCSB.

19.     ParaStor. Available: http://www.sugon.com/product/detail/productid/37.html.

20.     Z. X. Luo, “A censoring and quantization scheme for energy-based target localization in wireless sensor networks,” Journal of Engineering and Technology, vol.2, no.2, Aug. 2012.

21.     K. C. Ho, “Bias reduction for an explicit solution of source localization using TDOA,” IEEE Trans. Signal Processing, vol. 60, pp. 2101-2114, May 2012.

22.     Z. X. Luo, “A coding and decoding scheme for energy-based target localization in wireless sensor networks,” International Journal of Soft Computing and Engineering, vol.2, no. 4, Sept. 2012.

23.     Y. Li, K. C. Ho, and M. Popescu, “A microphone array system for automatic fall detection,” IEEE Trans. Biomedical Engineering, vol. 59, pp. 1291-1301, May 2012.

24.     K. C. Ho and R. Rabipour, “A design and use case for inhibiting the adaptation of echo canceller without using external control,” Contribution C816R1, ITU WP1/SG16 Standard Meeting, Geneva, Switzerland, May 2012.

25.     Z. X. Luo, “Anti-attack and channel aware target localization in wireless sensor networks deployed in hostile environments,” International Journal of Engineering and Advanced Technology, vol. 1, no. 6, Aug. 2012.

26.     Y. Shang, W. Zeng, K. C. Ho, D. Wang, Q. Wang, Y. Wang, T. Zhuang, A. Lobzhanidze, and L. Rui, “NEST: networked smartphones for target localization,” in Proc. IEEE CCNC 2012, Las Vegas, Jan. 2012, pp. 732-736.

27.     Z. X. Luo, “Robust energy-based target localization in wireless sensor networks in the presence of byzantine attacks,” International Journal of Innovative
Technology and exploring Engineering, vol. 1, no.3, Aug. 2012.

28.     L. Yang and K. C. Ho, “Alleviating sensor position error in source localization using calibration emitters at inaccurate locations,” IEEE Trans. Signal Processing, vol. 58, pp. 67-83, Jan. 2010.

29.     Z. X. Luo, “A new direct search method for distributed estimation in wireless sensor networks,” International Journal of Innovative Technology and Exploring Engineering, vol. 1, no. 4, Sept. 2012.

30.     T. Glenn, J. N. Wilson, and K. C. Ho, “A multimodal matching pursuits dissimilarity measure applied to landmine/clutter discrimination,” in Proc. IEEE Int. Geoscience and Remote Sensing Symp. IGARSS, Honolulu, July 2010.

31.     Z. X. Luo, “Parameter estimation in wireless sensor networks based on decisions transmitted over Rayleigh fading channels,” International Journal of Soft Computing and Engineering, vol. 2, no. 6, Jan. 2013.

32.     M. Popescu, K. E. Stone, T. C. Havens, J. M. Keller, and K. C. Ho, “Anomaly detection in forward-looking infrared imaging using one-class classifiers,” in Proc. SPIE Conf. Detection and Remediation Technologies for Mines and Minelike Targets XV, Orlando, Apr. 2010.

33.     Z. X. Luo, “Distributed estimation and detection in wireless sensor networks,” International Journal of Inventive Engineering and Sciences, vol. 1, no. 3, Feb. 2013.

34.     T. C. Havens, C. J. Spain, K. C. Ho, J. M. Keller, Tuan T. Ton, D. C. Wong, and M. Soumekh, “Improved detection and false alarm rejection using FLGPR and color imagery in a forward-looking system,” in Proc. SPIE Conf. Detection and Remediation Technologies for Mines and Minelike Targets XV, Orlando, Apr. 2010.

35.     George Kousiouris, Tommaso Cucinotta, Theodora Varvarigou, "The Effects of Scheduling, Workload Type and Consolidation Scenarios on Virtual Machine Performance and their Prediction through Optimized Artificial Neural Networks,” The Journal of Systems and Software (2011),Volume 84, Issue 8, August 2011, pp. 1270-1291, Elsevier, doi:10.1016/j.jss.2011.04.013.

36.     Ko, Ryan K. L. Ko; Kirchberg, Markus; Lee, Bu Sung (2011). "From System-Centric Logging to Data-Centric Logging - Accountability, Trust and Security in Cloud Computing". Proceedings of the 1st Defence, Science and Research Conference 2011 - Symposium on Cyber Terrorism, IEEE Computer Society, 3–4 August 2011, Singapore.

37.     Ko, Ryan K. L.; Jagadpramana, Peter; Mowbray, Miranda; Pearson, Siani; Kirchberg, Markus; Liang, Qianhui; Lee, Bu Sung (2011). "TrustCloud: A Framework for Accountability and Trust in Cloud Computing". Proceedings of the 2nd IEEE Cloud Forum for Practitioners (IEEE ICFP 2011), Washington DC, USA, July 7–8, 2011.

38.     Z. X. Luo, “Parameter estimation in wireless sensor networks with   normally distributed sensor gains,” International Journal of Soft Computing and Engineering, vol. 2, no. 6, Jan. 2013.

39.     Daniel Nurmi, Rich Wolski, Chris Grzegorczyk, Graziano Obertelli, Sunil Soman, Lamia Youseff, Dmitrii Zagorodnov, “The Eucalyptus Open-source Cloud-computing System”, Computer Science Department, University of California - Santa Barbara, Santa Barbara, California 93106.

40.     Z. X. Luo, “Overview of applications of wireless sensor networks,” International Journal of Innovative Technology and Exploring Engineering, vol. 1, no. 4, Sept. 2012

41.     Mike P. Papazoglou, “Service -Oriented Computing: Concepts, Characteristics and Directions”, Tilburg University, INFOLAB.

42.     Z. X. Luo, “Distributed estimation in wireless sensor networks with heterogeneous sensors,” International Journal of Innovative Technology and Exploring Engineering, vol. 1, no.4, Sept. 2012

43.     Rajiv Ranjan, Rajkumar Buyya, “Decentralized Overlay for Federation of Enterprise Clouds”, Grid Computing and Distributed Systems (GRIDS) Laboratory, Department of Computer Science and Software Engineering, The University of Melbourne, Australia.

44.     Z. X. Luo, P. S. Min, and S. J. Liu, “Target localization in wireless sensor networks for industrial control with selected sensors,” International Journal of Distributed Sensor Networks, 2013.

45.     Marianne C. Murphy, Marty McClelland, “Computer Lab to Go: A “Cloud” Computing Implementation”, Proc ISECON 2008, v25.

46.     Z. X. Luo, “Survey of networking techniques for wireless multimedia sensor networks,” International Journal of Recent Technology and Engineering, vol. 2, no. 2, May 2013.

47.     Z. X. Luo, “Survey of applications of pupil detection techniques in image and video processing,” International Journal of Recent Technology and Engineering, vol. 2, no. 2, May 2013.

48.     Z. X. Luo, “Survey of corner detection techniques in image processing,” International Journal of Recent Technology and Engineering, vol. 2, no. 2, May 2013. 


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27.

Authors:

Kanimozhi .P, Manimegalai.A

Paper Title:

High - Birefringent Nanowire Embedded Photonic Crystal Fiber for Optical Switching

Abstract:   We design a novel waveguide structure of sub-wavelength core diameter called photonic nanowire (PN) and study the different optical properties, namely, dispersion, birefringence and nonlinearity. We design a PN with elliptical core that exhibits a very high birefringence of about ≈0.037049, 0.068264, 0.190803, dispersion of about ≈ 1850, 2300 and 3250 ps/(nm km) and nonlinearity of about ≈ 606,467 and 294 W-1m-1at 0.850,1.06 and1.55 μm wavelengths respectively  and with circular air-holes located in the cladding. This property would highly useful for switching, sensing, etc.

Keywords:
 Photonic Crystal Fiber, Photonic Nanowire, Birefringence, Finite Element Method.


References:

1.        H.Ademgil, S.Haxha and F.AbdleMalek‚“ Bending effects on Highly Birefirngent Photonic Crystal Fibers With Low Chromatic Dispersion and Low Confinement Losses“- March , 2009 .
2.        Daru Chen and Linfang Shen “Ultrahigh Birefringent    Photonic Crystal Fiber with Ultralow Confinement Loss”,    Feb 2007.

3.        Govind P.Agarwal,“Nonlinear Fiber optics“.

4.        W.H.Reeves ,J.C.Knight ,P.S.J.Russell and P.J.Roberts ,”Demonstration of ultra-flattened dispersion in photonics crystal fiber,” Opt.Exp., vol. 10, pp. 609-613-2002.

5.        H. Ademgil and S. Haxha, “Highly birefringent photonic crystal fibers with ultra-low chromatic dispersion and low confinement losses,” J.Lightw. Technol., vol. 26, no. 4, pp. 441–448, Feb. 2008.

6.        K. Suzuki, H. Kubota, S. Kawanishi, M. Tanaka, and M. Fujita, “Optical properties of low loss polarization maintaining photonic crystal fiber,” Opt. Exp., vol. 9, pp. 676–680, 2001. [7] C. Knight, T. A. Birks, and P. S. J. Russell, “All-silica single-mode optical fiber with photonic crystal cladding,” Opt.Lett., vol. 21, pp.1547–1549, 1996.

7.        K. Saitoh and M. Koshiba, “Full-vectorial imaginary-distance beam propagation method based on a finite element scheme: Application to photonic crystal fibers,” IEEE J. Quantum Electron., vol. 38, no. 7, pp. 927–933, Jul. 2002.

8.        N. A. Mortensen, “Effective area of photonic crystal fibers,” Opt. Exp., vol. 10, pp. 341–348, 2002.

9.        Anshu D Varshney and Ravindra K. Sinha*,”Ultrahigh Birefringent Photonic Crystal Fiber: An Improved  Design,” VOL. 4, NO. 5, SEPTEMBER 2009. Available: http://www.(URL)

10.     R. J. Vidmar. (1992, August). On the use of atmospheric plasmas as electromagnetic reflectors. IEEE Trans. Plasma Sci. [Online]. 21(3). pp. 876—880.   Available: http://www.halcyon.com/pub/journals/21ps03-vidmar 


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28.

Authors:

Reena Jindal, Samidha D.Sharma, Manoj Sharma

Paper Title:

A New Technique to Increase the Working Performance of the Ant Colony Optimization Algorithm

Abstract:   The DBSCALE [1] algorithm is a popular algorithm in Data Mining field as it has the ability to mine the noiseless arbitrary shape Clusters in an elegant way. Such meta-heuristic algorithms include Ant Colony Optimization Algorithms, Particle Swarm Optimizations and Genetic Algorithm has received increasing attention in recent years. Ant Colony Optimization (ACO) is a technique that was introduced in the early 1990’s and it is inspired by the foraging behavior of ant colonies.This paper presents an application aiming to cluster a dataset with ACO-based optimization algorithm and to increase the working performance of colony optimization algorithm used for solving data-clustering problem, proposed two new techniques and shows the increase on the performance with the addition of these techniques [5]. We bring out a new clustering initialization algorithm which is scale-invariant to the scale factor. Instead of using the scale factor while the cluster initialization, in this research we determine the number and position of clusters according to the changes of cluster density with the division an agglomeration processes. Experimental results indicate that the proposed DBSCALE has a lower execution time cost than DBSCAN, and IDBSCAN clustering algorithms. IDBSCALE-ACO has a maximum deviation in clustering correctness rate of 95.0% and an error rate of deviation in noise data clustering of 2.62%.This algorithm is proposed to solve combinatorial optimization problem by using Ant Colony algorithm.

Keywords:
 DBSCALE, Ant Colony Optimization Algorithm, Clustering, Large Datasets.


References:

1.        M. H. Dunham, Data Mining: Introductory and Advanced Topics, Prentice Hall, 2003
2.        A. A. Freitas, S. H. Lavington, Mining very large databases with parallel processing. Dordrecht, The Netherlands, Kluwer Academic Publishers,1998

3.        Foster, C. Kesselman, The Grid: Blueprint for a New Computing Infrastructure. Morgan Kaufmann, Elsevier Press, 2004, pp. 593-620

4.        T. G. Dietterich, An experimental comparison of three methods for constructing ensembles of decision trees: Bagging, boosting andrandomization. Machine Learning Vol.40, 2000, pp.139-158

5.        Cheng-Fa Tsai, Chun-Yi Sung, “DBSCALE: An Efficient Density-Based Clustering Algorithm for Data Mining in Large Databases” (PACCS 2010) Second Pacific-Asia Conference on Circuits, Communications and System, 91201 Pingtung, Taiwan, October 2010.

6.        R. Agrawal, J. C. Shafer, Parallel mining of association rules IEEE Transactions on Knowledge and Data Engineering, Vol 8., 1996, pp.962-969

7.        E. Januzaj, H-P. Kriegel, M. Pfeifle, DBDC: Density-Based Distributed Clustering Proc. 9th Int. Conf. on Extending Database Technology(EDBT), Heraklion, Greece 2004, pp. 88-105

8.        N-A. Le-Khac, L. Aouad, and M-T. Kechadi, A new approach for Distributed Density Based Clustering on Grid platform The 24th British National Conference on Databases (BNCOD'07), Springer LNCS 4587, July 3-5, 2007, Glasgow, UK. 2007

9.        C. J. Merz, M. J. Pazzani. A principal components approach to combining regression estimates. Machine Learning Vol. 36, 1999, pp. 9-32

10.     Kivinen, and H. Mannila, “The power of sampling in knowledgediscovery,” Proceedings of the ACM SIGACT-SIGMOD-SIGART,Minneapolis, Minnesota, United States, May 24 - 27, 1994, pp.77-85

11.     K. Sayood, Introduction to Data Compression, 2nd Ed., MorganKaufmann, 2000. 


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29.

Authors:

Tushar Gajame, C.L. Chandrakar

Paper Title:

Face Detection with Skin Color Segmentation & Recognition using Genetic Algorithm

Abstract:   Face recognition in video has gained wide attention as a covert method for surveillance to enhance security in variety of application domains (e.g., airports, traffic, Terrorist attack).A video contains temporal information as well as multiple instances of a face, so it is expected to lead to better face recognition performance compared to still face images. However, faces appearing in a video have substantial variations in pose and lighting. We propose a face recognition system that identifies faces in video. The system utilizes the rich information in video. The description of the proposed method and preliminary results are provided.

Keywords:
 Face detection, Image Enhancement, Skin Color detection, Feature Extraction, Pattern Recognization, Luminance, Color transforms


References:

1.        K. Sandeep, A.N. Rajagopalan,”Human Face Detection in Cluttered Color Images Using Skin Color and Edge Information”, ICVGIP Proceeding, 2002.
2.        H. Deng, L. Jin, L. Zhen, and J. Huang. A new facial expression recognition method based on local gabor filter bank and pca plus lda. International Journal of Information Technology, 11(11):86-96,2005.

3.        L. Shen and L. Bai. Information theory for gabor feature selection for face recognition. Hindawi Publishing Corporation, EURASIP Journal on Applied Signal Processing, Article ID 30274, 2006.

4.        J Essam Al Daoud, ”Enhancement of the Face Recognition Using a Modified Fourier-Gabor Filter”,Int. J. Advance. Soft Comput.Appl., Vol. 1, No. 2, 2009.

5.        Z. Y. Mei, Z. Ming, and G. YuCong. Face recognition based on low dimensional Gabor feature using direct fractional-step lda. In Proceedings of the Computer
Graphics, Image and Vision: New Treds (CGIV'05), IEEE Computer Society, 2005.

6.        B. Schiele, J. Crowley,”Recognition without correspondence using multidimensional receptive field  Histograms”, International Journal on Computer Vision.36:3152, 2000.

7.        Christopher M Bishop, “Neural Networks for Pattern Recognition” London, U.K.: Oxford University  Press, 1995.

8.        H. Martin Hunke, Locating and tracking of human faces with neural network, Master’s thesis, University of Karlsruhe, 1994.

9.        Henry A. Rowley, ShumeetBaluja, and Takeo Kanade. “Neural network based face detection,”IEEE Transactions on Pattern Analysis and Machine Intelligence, 20(I), pp.23-38, 1998.

10.     B. Schiele and J. Crowley.“Recognition without correspondence using multidimensional receptive field histograms”.International Journal on Computer Vision, 36:3152, 2000.

11.     K Messer, J Matas, J Kittler, J Luettin, and Gmaitre, ” Xm2vtsdb: The extended m2vts database”, In  Second International Conference of Audio and Video-based Biometric Person Authentication, March 1999.

12.     L. Sirovich, M. Kirby, Low-dimensional procedure for the characterization of human faces, J. Opt. Soc. Am. A 4 (3) (1987) 519}524.

13.     M. Turk, A. Pentland, Eigenfaces for recognition, J. Cogni-tiveNeurosci. 3 (1) (1991) 71}86.[14] N. Intrator, D. Reisfeld, Y. Yeshurun, Face recognition using a hybrid supervised/unsupervised neural network, Pattern Recognition Lett.17 (1996) 67}76.

14.     B. Moghaddam, A. Pentland, Face recognition using view-based and modular eigenspaces, SPIE: Automat.SystemsIdent. Inspect. Humans 2277 (1994).

15.     R. Brunelli, T. Poggio, Face recognition: features versus template, IEEE PAMI 15 (10) (1993) 1042}1052.

16.     R. Chellappa, C. L. Wilson, S. Sirohey, “Human and machine recognition of faces: a survey”, Proceedings  of the IEEE, Volume 83, No. 5, pp. 705-740, May  1995.

17.     J. Zhang, Y. Yan, M. Lades, “Face recognition: eigenface, elastic matching, and neural nets”, Proceedings of the IEEE, Vol. 85, No. 9, pp. 1423-1435, September
1997.

18.     ISO/IEC JTC1/SC29/WG11. “Overview of the MPEG-7 Standard”, Doc. ISO/MPEG N4031, March 2001, Singapore.

19.     A. Albiol, L. Torres, C.A. Bouman and E. J. Delp, “A simple and efficient face detection algorithm for video database applications”, Proceedings of the IEEE International Conference on Image Processing,Vancouver, Canada, vol. 2, pp. 239-242, September 2000.

20.     L. Torres, L. Lorente and J. Vilà, “Face recognition using self-eigenfaces,” Proceedings of the International Syposium on Image/Video Communications Over Fixed and Mobile Networks, Rabat, Morocco, pp. 44-47, April 2000.

21.     A. Albiol, L. Torres, E. Delp, “An unsupervised color image segmentation algorithm for face detection applications”, IEEE International Conference on Image Processing, Thessaloniki, Greece, October 7-10, 2001.

22.     M. A. Turk, A. P. Pentland, “Face recognition using eigenfaces”, Proceedings of the IEEE Computer Society Conf. on Computer Vision and Patter Recognition, pp. 586-591, Maui, Hawaii 1991. 


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30.

Authors:

Dashrath Mane, Ketaki Chitnis, Namrata Ojha

Paper Title:

The Spring Framework: An Open Source Java Platform for Developing Robust Java Applications

Abstract:   The fundamental concepts of Spring Framework is presented in this paper.Spring framework is an open source Java platform that provides comprehensive infrastructure support for developing robust Java applications very easily and very rapidly. The Spring Framework is a lightweight solution and a potential one-stop-shop for building your enterprise-ready applications.

Keywords:
 Aspect Oriented Programming, Dependency Injection, IoC Container, ORM.


References:

1.        http://www.springsource.org/tutorial
2.        http://www.tutorialspoint.com/spring/index.htm

3.        http://en.wikipedia.org/wiki/Spring_Framework

4.        http://www.theserverside.com/news/1364527/Introduction-to-the-Spring-Framework

5.        http://www.theserverside.com/news/1363858/Introduction-to-the-Spring-Framework

6.        http://www.tutorialspoint.com/spring/spring_dependency_injection.htm

7.        Seth Ladd, Darren Davison, Steven Devijver  and Colin Yates, “Expert Spring MVC and Web Flow”

8.        Gary Mak , “Spring Recipes” 


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31.

Authors:

Sonia Hammami

Paper Title:

Synchronization of Identical Chaotic Systems Using New State Observers Strategy

Abstract:   Throughout this paper, the nonlinear observer-based synchronization problem for two coupled Chen chaotic systems is developed. Initially, complete synchronization conditions of coupled chaotic systems, is provided. The active control law developed is based on the use of aggregation techniques for error dynamics stability study and the arrow form matrix for systems description. Afterwards, by the design of an adequate nonlinear state observer, a new synchronization scheme is formulated for two identical chaotic systems. Numerical simulations are carried out to assess the performance and the efficiency of the proposed contributions.

Keywords:
 Aggregation techniques, Arrow form matrix, Chaotic systems, State observer, Synchronization.

References:

1.        L. M. Pecora and T. L. Carroll, “Synchronization in chaotic systems”, Phys Rev Lett, vol. 64, 1990, pp. 821-824.
2.        M. Ogorzalek, “Taming chaos-I: Synchronization”, IEEE Trans Circ Syst-I, vol. 40, 1993, pp. 693-699.

3.        S. Hammami, K. Ben Saad and M. Benrejeb, “On the synchronization of identical and non-identical 4-D chaotic systems using arrow form matrix”, Chaos, Solitons & Fractals, vol. 42, 2009, pp. 101-112.

4.        M. Hasler, “Synchronization principles and applications”, in IEEE international symposium on circuits and systems, 1994, vol. 3, pp. 314-327, New York.

5.        H. Xiping and Q. Zhang, “Image encryption based on chaotic modulation of wavelet coefficients”, in Congress on IEEE Image and Signal Processing, 2008, vol. 1, pp. 622-626, Sanya, Hainan.      

6.        L. Kocarev and U. Parlitz, “Generalized synchronization, predictability, and equivalence of unidirectionally coupled dynamical systems”, Phys Rev Lett, vol. 76, 1996, pp. 1816-1819.

7.        S. S. Yang and K. Duan, “Generalized synchronization in chaotic systems”, Chaos, Solitons & Fractals, vol. 10, 1998, pp. 1703-1707.

8.        S. Hammami, M. Benrejeb, M. Feki and P. Borne, “Feedback control design for Rössler and Chen chaotic systems anti-synchronization”, Phys Lett A, vol. 374, 2010, pp. 2835-2840.

9.        S. Hammami and M. Benrejeb, “Coexistence of synchronization and anti-synchronization for chaotic systems via feedback control”, Chaotic systems, Croatia: Editions INTECH, 2011, pp. 203-224.

10.     G. H. Li, “Synchronization and anti-synchronization of Colpitts oscillators using active control”, Chaos, Solitons & Fractals, vol. 26, 2005, pp. 87-93.

11.     Ö. Morgül and E. Solak, “Observer-based synchronization of chaotic signals”, Phys Rev E, vol. 54, 1996, pp. 4803-4811.

12.     Ö. Morgül and E. Solak, “On the synchronization of chaotic systems by using state observers”, Int J Bifurcation Chaos, vol. 7, 1997, pp. 1307-1322.

13.     H. Nijmeijer and I. Mareels, “An observer looks at synchronization”, IEEE Trans Circ Syst-I, vol. 44, 1997, pp. 882-890. 


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32.

Authors:

Islabudeen M, Sathiya M

Paper Title:

An Efficient Secure Communication in WLAN Using DH Method

Abstract:   Wireless Local Area Network (WLAN) is one kind of wireless networks and which is a wireless network in limited area where laptop and mobile devices can connect through it freely. WLAN is popular due to its flexibility, mobility and portability and are widely deployed in schools, commercial organizations or in home uses.However, a WLAN suffers from all the constraints of wireless networks including low transmit speed and bandwidth, memory and processing power which limits the implementation of security approaches as can be implemented in wired LANs which includes public-key ciphers. Moreover, due to the feature that signals are transmitted in the air, an adversary can easily monitor and intercept all signals. Thus, robust, efficient and effective security measurements are essential for all WLANs. In this Project, I proposed an efficient encryption technique named Diffie-Hellman  Triple key method to guard the management frames that are disseminated from the Access points.It is used to authenticate as well as protect our messages from tampering.

Keywords:
 Architecture Model, Key Generation, Key Establishment,  Performance.


References:

1.        Mohammad S. Obaidat, Fellow, IEEE, and Tari Guelzim,”ACounterDisassociation Mechanism (CDM) for Wireless LANs and its Performance Simulation Analysis,”IEEE SYSTEMS JOURNAL, VOL. 4, NO. 1, MARCH 2010.
2.        T. Guelzim and M. S. Obaidat, “A novel neurocomputing based scheme to authenticate WLAN users employing distance proximity threshold,”in Proc. IEEE Int. Conf. Security and Cryptography, SCRYPT, Porto,Portugal,  pp. 145–153, Jul. 2008.

3.        M. S. Obaidat and N. Boudriga, Security of e-Systems and ComputerNetworks. Cambridge, U.K.: Cambridge Univ. Press, 2007.

4.        J.-C. Lin, Y.-H. Kao, and C.-W. Yang, “Secure enhanced wireless transfer        protocol,” in Proc. 1st Int. Conf. Availability, Reliability andSecurity (ARES’06), pp. 536–543,Apr. 2006.

5.        X.Wang, Y. L. Yin, and H. Yu, “Finding collisions in the full SHA-1,”CRYPTO 2005.

6.        S. Michelle and Srinivasan, “State based key hop protocol: A lightweight security protocol for wireless networks,” in Proc. 1st ACM Int.Workshop on Performance Evaluation of Wireless Ad Hoc, Sensor, andUbiquitous Networks,  pp. 112–118,Oct. 2004.

7.        C. He and J. C. Mitchell, “Analysis of the 802.11i 4-way handshake,”in ACM Workshop on Wireless Security, pp. 43–50,Oct. 2004.

8.        P. Nicopolitidis, M. S. Obaidat, G. Papadimitriou, and A. S.Pomportsis Wireless Networks. New York: Wiley, 2003.

9.        J. Bellardo and S. Savage, “802.11 Denial-of-service attacks: Real vulnerabilities and practical solutions,” in Proc. USENIX Security Symp.,pp. 15–28.,Aug. 2003.

10.     J. Li and W. Jia, “Traffic analysis ad hoc networks based on location-aware clustering,” in Proc. 23rd Int. Conf. Distributed Computing Systems Workshops (ICDCSW’03), 2003. 


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33.

Authors:

Payal, Sudesh Kumar Jakhar

Paper Title:

TCP Traffic Based Performance Investigations of DSDV, DSR and AODV Routing Protocols for MANET Using NS2

Abstract:   An Ad-hoc network is a dynamically changing network of mobile devices that communicate without the support of a fixed structure. TCP is a connection oriented transport protocol that provides reliable, in-order delivery of data to the TCP receiver. Hence, its use over Mobile Ad-Hoc networks is a certainty. This paper does the comprehensive investigations on routing protocols Dynamic Source Routing (DSR), Ad-hoc On demand distance vector (AODV) and Destination-Sequenced Distance-Vector (DSDV) using ns2 simulator considering TCP as transport protocol and FTP as traffic generator. Simulation results indicate that the performance of proactive routing protocol DSDV is far better than reactive routing protocols. DSR which uses source routing is the best among reactive routing protocols. It is observed that TCP is not appropriate transport protocol for highly mobile multihop wireless networks because TCP protocol is unable to manage efficiently the effects of mobility.

Keywords:
 Ad-hoc Networks, AODV, DSDV, DSR, NS-2, TCP.


References:

1.        Elizabeth M. Royer and C.-K. Toh, A Review of Current Routing Protocols for Ad-Hoc Mobile Wireless Networks, IEEE Personal, Communications Magazine, pp. 46-55, April 1999.
2.        J. Broch, D.A. Maltz, D.B. Johnson, Y.C. Hu, and J. Jetcheva, A Performance Comparison of Multi-Hop Wireless Ad Hoc Network Routing Protocols, Proc. of the ACM/IEEE International Conference on Mobile Computing and Networking MOBICOM ’98, pp. 85-97, October 1998.

3.        S.R. Das, R. Castaneda, J. Yan, and R. Sengupta, Comparative performance evaluation of routing protocols for mobile, ad hoc networks, Proc. of 7th International Conference on Computer Communications and Networks (IC3N), pp. 153–161, October 1998.

4.        Charles E. Perkins and Pravin Bhagwat, Highly dynamic Destination-Sequenced Distance-Vector routing (DSDV) for mobile computers, Proc. SIGCOMM '94 Conference on Communications Architectures, Protocols and Applications, pp. 234-244, August 1994.

5.        David B. Johnson and David A. Maltz, Dynamic Source Routing in Ad Hoc Wireless Networks, In Mobile Computing, Tomasz Imielinski and Hank Korth (Eds.), Chapter 5, pp. 153-181, Kluwer Academic Publishers, 1996.

6.        Charles Perkins and Elizabeth Royer, Ad hoc on demand distance vector routing, Proc. IEEE Workshop on Mobile Computing Systems and Applications, pp. 90–100, February 1999.

7.        C.E. Perkins, E.M. Royer and S.R. Das, Ad hoc on-demand distance vector (AODV) routing, IETF MANET Working Group, Internet-Draft (March 2000).

8.        P. Johansson et al., Scenario-based Performance Analysis of Routing Protocols for Mobile Ad-Hoc Networks, In Proc. IEEE/ACM Mobicom ’99, pp. 195–206, Seattle, WA, Aug. 1999.

9.        Yi Lu, Weichao Wang, Yuhui Zhong, Bharat Bhargava, Study of Distance Vector Routing Protocols for Mobile Ad Hoc Networks, Proc. IEEE International Conference on Pervasive Computing and Communications (Per-Com’2003), 2003.

10.     Azzedine Boukerche, Performance Evaluation of Routing Protocols for Ad Hoc Wireless Networks, Proc. Mobile Networks and Applications 9, pp. 333–342, 2004

11.     P. Chenna Reddy, Dr. P. Chandrasekhar Reddy, Performance analysis of Adhoc network routing protocols, Academic Open Internet Journal ISSN, 1311-4360, Volume 17, 2006.

12.     Geetha Jayakumar and Gopinath Ganapathy, Performance Comparison of Mobile Ad-hoc Network Routing Protocol, IJCSNS International Journal of Computer Science and Network Security, VOL.7 No.11, November 2007

13.     Network Simulator - ns-2. Available at http://www.isi.edu/nsnam/ns/

14.     Suresh Kumar, R.K. Rathy and Diwakar Pandey, “Traffic Pattern Based Performance Comparison of Two Reactive Routing Protocols for Ad-hoc Networks using NS2”, 2nd IEEE International Conference on Computer Science and Information Technology, 2009

15.     Kevin Fall and Kannan Varadhan, editors, ns notes and documentation. The VINT Project, UC Berkeley, LBL, USC/ISI and Xerox PARC, Available from . 


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34.

Authors:

Madhura C, Dheeraj D

Paper Title:

Feature Extraction for Image Retrieval Using Color Spaces and GLCM

Abstract:   Due to the enormous increase in the size of image databases as well as its vast deployment in various applications, the need for Content Based Image Retrieval (CBIR) development arose. This paper describes a hybrid feature extraction approach of our research and solution to the problem of designing a CBIR system manually. Two features are used for retrieving the images such as color and texture. Color feature is extracted by using different color space such as RGB, HSV and YCbCr. Texture feature is extracted by applying Gray Level Co-occurrence Matrix(GLCM). The image is retrieved by combining color and texture feature and the color space which gives the best result as analyzed using precision and recall graph.

Keywords:
 Color Spaces, Euclidean Distance, Image Retrieval, Precision, Recall.


References:

1.        T. Kato. Database architecture for content-based image retrieval. In A. A. Jambardino and W. R. Niblack, editors, Proceedings of SPIE Image Storage and Retrieval Systems, volume 1662, pages 112–123, San Jose, CA, USA, February 1992.
2.        Gauri Deshpande,  Megha Borse, " Image Retrieval with the use of different color spaces and the texture feature", International Conference on Software and Computer Applications, Vol. 9, pp. 273-278, 2011.

3.        M. Flickner, H. Sawhney, W. Niblack, J. Ashley, Q. Huang, B. Dom, M. Gorkani, J. Hafner, D. Lee, D. Petkovic, and P. Yanker, “Query by image and video content: The QBIC system,” IEEE Computer, vol. 28, no 9, pp.23-32, Sep. 1995.

4.        J. Smith and C. Li, “Image Classification and Querying Using Composite Region Templates,” Int. J. Computer Vision and Image Understanding, vol. 75, no. 2, pp.165-174, July 1999.

5.        A. Gupta, and R. Jain, “Visual information retrieval,” Comm. Assoc. Comp. Mach.,vol. 40, no. 5, pp. 70–79, May. 1997.

6.        S. Mukherjea, K. Hirata, and Y. Hara, “AMORE: A World Wide Web Image Retrieval Engine,” Proc. World Wide Web, vol. 2, no. 3, pp. 115-132, June. 1999.

7.        A. Natsev, R. Rastogi, and K. Shim, “WALRUS: A Similarity Retrieval Algorithm for Image Databases,” IEEE Trans. On Knowledge and Data Engineering, vol.16,pp. 301-318, Mar. 2004.

8.        A. Pentland, R. Picard, and S. Sclaroff , “Photobook: Content based manipulation of image databases,” International Journal of Computer Vision, vol.18, no 3,pp.233–254, June 1997.

9.        R. Picard and T. Kabir, “Finding Similar Patterns in Large Image Databases,” Proc. IEEE Int. Conf. Acoustics, Speech and Signal Processing, vol. 5, pp. 161-164, New York 1993.

10.     A. Carson, M. Thomas, S. Belongie, J.M. Hellerstein, and J. Malik, “Blobworld: A System for Region-Based Image Indexing and Retrieval,” Proc. Visual Information Systems, pp. 509-516, June 1999.

11.     J. Smith and S. Chang, “Visualseek: A Fully Automated Content-Based Image Query System,” Proceedings of the 4th ACM international conference on Multimedia table of contents, Boston, Massachusetts, United States, Nov. 1996, pp. 87-98.

12.     W. Ma and B. Manjunath, “Natra: A Toolbox for Navigating Large Image Databases,” Proc. IEEE Int'l Conf. Image Processing, Santa Barbara, 1997, pp. 568- 571.

13.     J. Wang, G. Wiederhold, O. Firschein, and X. Sha, “Content-Based Image Indexing and Searching Using Daubechies' Wavelets,” Int. J. Digital Libraries, vol. 1, no. 4, pp. 311-328, 1998.

14.     J. Yang, W. Lu and A. Waibel, 1998. “ Skin-color modeling and adaptation”, ACCV98.

15.     S. Manimala and K. Hemachandran, “Performance analysis of Color Spaces in Image Retrieval”, Assam University Journal of science & Technology, Vol. 7, Number II 94-104, 2011.

16.     Vladimir Vezhnevets, Vassili Sazonov, and Alla Andreeva,2003. “A Survey on Pixel-Based Skin Color Detection Technique”,In Proceedings of the Graphi Conference, pp.85-92. 

17.     P. Kakumanu, S. Makrogiannis and N. Bourbakis, 2006. “A survey of skin-color modeling and detection methods”. The journal of the pattern recognition society. 

18.     Dong Yin, Jia Pan, et al, "Medical Image Categorization based on Gaussian Mixture Model", IEEE 2008 International Conference on BioMedical Engineering and Informatics, pp. 128-131.

19.     J.Z. Wang, “Wang Database,” [Online], Available at: http://wang.ist.psu.edu/ , last visited June 2013.

20.     Y. Liu, D. Zhang, G. Lu, and W. Ma, “A survey of content based image retrieval with high-level semantics,” Journal of Pattern Recognition, vol. 40, pp. 262–282, Nov. 2007. 

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35.

Authors:

Nitin Kumar Sharma, K.P.Yadav,B.K.Sharma

Paper Title:

Comparative Study of the 64-bit and Apple families of Microprocessors

Abstract:   We live in an era of computers. From the smallest embedded system to the complex servers that take care of the world economy, we need microprocessors to run them. As time passed by, applications needed more processing power and this lead to an explosive era of research on the architecture of microprocessors. As part of our project we are going to present a technical & comparative study of these smart microprocessors. It will include the different software & hardware technical aspects of such devices for instance OS, applications used, hardware study etc. In this report, we study and compare two microprocessor families that have been at the core of the world’s most popular microprocessors of today – 64 bit microprocessor & Apple microprocessor.

Keywords:
 CPU, ALU, AMD, RISC, SIMD etc.

References:

1.        Hadi. “Tablet Ward: Apple iPad vs. BlackBerry Playbook vs. Samsung Galaxy Tab” September 28, 2010
2.        Josh Morse “Apple iPad vs. Tablet PC: A comparison” January 28th,2010

3.        Apple Developer “Start Developing iPad Apps January 2010

4.        Samsung Galaxy Tab Developer Forum "Developing applications for the Samsung Galaxy Tab

5.        Techinsights “Apple-iPad- Redefining the table market”

6.        Android Operating system a complete perspective

7.        Nick Van Elslander, Mario Suppan, Thomas De Roy, Tuan Vu, iPhone Research Paper, MAD intensive programming 2009.

8.        Windows 7 Architecture – Wikipedia,

9.        iOS Developer Community , iOS – Features

10.     Develop for iOS

11.     Samsung Galaxy Tab vs. the iPad Compare for yourself

12.     HTC Android Tablet appearing in CES 2010

13.     HTC rumored to be readying an Android Tablet for Q1 2011   


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36.

Authors:

Ranjana Kumari, Rajesh Mehra

Paper Title:

Space Time Block Code for High Data Rate Using CD Algebra

Abstract:   Multiple antennas at both Transmitter and receiver end of wireless digital transmission channel may increase the data rate and reliability of the communication. Reliability and high data rate transmission over channels can be achieved by proposed Space Time block code. Determinant and Rank code design has been proposed to enhance the diversity and coding gain. Cyclic Division algebras is a new tool for constructing space time block code, this is non-commutative algebras that naturally yield fully diverse codes. The CDA based construction method usually consists of two steps. First steps are to construct a degree-n cyclic extension over a base field. Second steps are used to find a non-norm algebra integer in base field. Proposed STBC for 4X2, 4X3, 4X4, 8X1 at code rate ‘3/4’ and 16QAM modulation technique are used. This proposed STBC code is compared with Generalized silver codesilver code ,golden code. Simulation results of symbol error rate for 4 Tx and 8 Tx shows proposed STBC code is good in error performance at offering one dimensional lower decoding complexity by using sphere decoding.

Keywords:
 Cyclic algebras; division algebras; full diversity; golden code; silver code;  non-vanishing determinant; sphere decoding.


References:

1.        V. Tarókh, H. Jafarkhani, and A. R. Calderbank, “Space-time block codes from orthogonal designs,” IEEE Transaction Information Theory, vol. 45, no. 5,  pp. no.1456–1467, July 1999.
2.        “Correction to ‘Space-time block codes from orthogonal designs,” IEEE Transaction  Information  Theory, vol. 46, no. 1, pp. no.314, January 2000.

3.        O. Tirkkonen and A. Hottinen, “Square-matrix embeddable space-time block codes for complex signal constellations,” IEEE Transaction in Information Theory, vol. 48, no. 2, pp. no. 384–395, February   2002.

4.        Siavash M. Alamouti “A Simple Transmit Diversity Technique for   Wireless Communication” ,IEEE Journal on Select Areas in     Communications, Vol. 16, no. 8, pp.no.1451-1458 ,October 1998

5.        K. P. Srinath and B. S. Rajan, “Low ML-decoding complexity, largecoding gain, full-rate, full-diversity STBCs for 2x2 and 4x2MIMO systems,” IEEE J. Select. Topics Signal Processing., vol. 3, no. 6, pp.no. 916–927, December  2009.

6.        M. O. Sinnokrot and J. Barry, “Fast maximum-likelihood decoding of the golden code,” IEEE Wireless Communication., vol. 9, no.  1, pp. no. 26–31, January  2010.

7.        C. Hollanti, J. Lahtonen, K. Ranto, R. Vehkalahti, and E. Viterbo, “On the algebraic structure of the silver code: A 2x2 perfect space-time code with non-vanishing determinant,” in Processing of IEEE Information Theory Workshop, Porto, Portugal, May 2008.

8.        O. Tirkkonen and R. Kashaev, “Combined information and    Performance optimization of linear MIMO modulations,” in Processing  ISIT  2002.

9.        Z. A. Khan and B. S. Rajan, “Single symbol maximum likelihood   decodable linear STBCs,” IEEE Transaction  Information. Theory, vol. 52, no. 5, pp.no.2062–2091, May 2006.

10.     Srinath, K.P and Ranjan , “ Generalized Silver Code” , IEEE Transaction on Information Theory,vol.57,pp.no.6134-6147, September  2011.

11.     F. Oggier, J.-C. Belfiore and E. Viterbo“ Foundations and Trends in     Communications and Information Theory”  Vol. 4,  No. 1   pp. no 1–95. 2007.

12.     J. Jalden and B. Ottersten, "On the Complexity of Sphere Decoding in Digital Communications," IEEE Transaction  Signal Processing, vol. 53,  no. 4, pp. no. 1474-1484, April 2005

13.     Dia ,XG  “ A new family of linear Dispersion codes for fast sphere Decoding   ”, Canadian conference on Electrical and Computer  Engineering , pp. no. 314-317,May 2009 .

14.     Jalden , J. , Elia P,“ The complexity of sphere decoding perfect codes under a vanishing gap to ML performance  ”, IEEE information symposium on information theory ,pp. no. 2836-2840 , 2011 


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37.

Authors:

Sowmya A N Gowda, Bhaskar Rao N

Paper Title:

Congestion Control with Explicit Feedback for Time Varying Capacity Media

Abstract:   XCP is a serious candidate to replace TCP congestion control in the internet. TCP, despite performing end-to-end congestion remarkably well degrades network performance due to unstable throughput, limited fairness and limited fairness. In XCP the routers provides the explicit feedback about the link capacity to the source. In time varying capacity media such as IEEE 802.11 knowing this value is difficult as it depends on many variables. We explore three algorithms for time varying capacity media which maintain efficiency under such conditions. Finally we compare our proposal with TCP new Reno and how such algorithm outperforms in terms of efficiency.

Keywords:
 Congestion, Wireless Communication, XCP, Blind, ErrorS, MAC.


Refererces:

1.        H. Balakrishnan, N. Dukkipati, N. McKeown, and C. Tomlin, “Stability Analysis of Explicit Congestion Control Protocols,” Technical Report SUDAAR 776, Dept. of Aeronautics and Astronautics, Stanford Univ., Sept. 2005
2.        D. Katabi, M. Handley, and C. Rohrs, “Congestion Control for High Bandwidth-Delay Product Networks,” Proc. ACM SIGCOMM, 2002

3.        F. Kelly and T. Voice, “Stability of End-to-End Algorithms for Joint Routing and Rate Control,” SIGCOMM Computer Comm. Rev., vol. 35, no. 2, pp. 5-12, 2005

4.        P. Wang and D. Mills, “Simple Analysis of XCP Equilibrium Performance,” Proc. IEEE Conf. Information Sciences and Systems (CISS), 2006

5.        Y. Zhang and T. Henderson, “An Implementation and Experimental Study of the Explicit Control Protocol (XCP),” Proc. IEEE INFOCOM, Mar. 2005.

6.        Jianxin Wang; Jie Chen; Shigeng Zhang; Weiping Wang, “An explicit congestion protocol based on bandwidth estimation,” IEEE 2011

7.        F. Abrantes and M. Ricardo, “XCP for shared-access multi-rate media,” ACM SIGCOMM Computer Communication Review, vol. 36, pp. 27–38, July 2006.

8.        K. Ramakrishnan, S. Floyd, and D. Black, “The Addition of Explicit Congestion Notification (ECN) to IP.” RFC 3168, September 2001.

9.        Filipe Abrantes,Jao Taveria Araujo, “Explicit Congestion Control for Time Varying Capacity media “ IEEE Transaction on mobile computing Jan 2011

10.     Y. Zhang and M. Ahmed, “A Control Theoretic Analysis of XCP,” in Proc. of IEEE GLOBECOM, March 2005.

11.     Yang Su and Thomas R. Gross. WXCP: Explicit Congestion Control for Wireless Multi-hop Networks. In Proc. of IEEE IWQoS, pages 313–326, 2005.

12.     Aaron Falk, Dina Katabi, Yuri Pryadkin "Specification for the Explicit Control Protocol (XCP)", draft-falk-xcp-03.txt (work in progress), July 2007. [html], [txt]

13.     Aman Kapoor, Aaron Falk, Ted Faber, Yuri Pryadkin, "Achieving Faster Access to Satellite Link Bandwidth", 8th IEEE Global Internet Symposium, Miami, FL, March 2005. [pdf]

14.     Dina Katabi, Mark Handley, and Charles Rohrs, "Internet Congestion Control for Future High Bandwidth-Delay Product Environments." ACM Sigcomm 2002, August 2002. [ pdf]

15.     Dina Katabi, "Decoupling Congestion Control and Bandwidth Allocation Policy With Application to High Bandwidth-Delay Product Networks," Ph.D. Dissertation, Massechussetts Institute of Technology, March 2003. [ ps]

16.     Y. Zhang and M. Ahmed, “A Control Theoretic Analysis of XCP,” Proc. IEEE INFOCOM, Mar. 2005.

17.     A. Falk and D. Katabi. Specification for the explicit control protocol (XCP). Internet Draft (draft-falk-xcp-spec-01), work in progress, October 2004
 

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38.

Authors:

S. Venkateswaran, S. Vediappan

Paper Title:

Assessment of Groundwater Quality for Irrigation Use and Evaluate the Feasibility Zones through Geospatial Technology in Lower Bhavani Sub Basin, Cauvery River, Tamil Nadu, India

Abstract:   The present work is employed in Lower Bhavani sub-basin (study area 2424.19 sq.km), major portion of the study area fall in Erode District and small portion in Coimbatore District, Tamil Nadu and India. The 50 groundwater samples were collected from during pre monsoon (May) 2011 and were analysed for major cations and anions EC, pH and TDS. The irrigational parameters like; EC, Kelley’s ratio, SAR values, Mg-hazards, HCO3 and RSC have been worked out to know the suitability of the groundwater for irrigational purpose. Wilcox diagram indicates that out of 50 samples, 33 samples belong to good to permissible category and Doneen diagram revealed that 100% of the groundwater samples fall in Class I. The plotting of SAR values in USSL diagram indicates that all the samples have low SAR value. Out of 50 samples 41 samples in C3-S1 field. This implies that no alkali hazard is anticipated to the crops. 41 Location (82%) samples occurred within C3–S1 category. This category is suitable for irrigations purposes. However, the concentration of bicarbonate was in significant amount showing 54% of sites under “increasing problem” and the 44% sites under “Severe Problem” zones. Finally above said results are taken into GIS platform. To understand the spatial distribution of unsuitable zones, ArcGIS was employed. The present work reveals that groundwater in the Lower Bhavani sub-basin area is of good quality and is suitable for all uses including interbrain water transfer in the region.

Keywords:
 Irrigation; Sodium Absorption Ratio (SAR); Sodium Percentage; Doneen’s diagram; Geographic Information System (GIS); Spatial Distribution Map; Cauvery River


References:

1.        BAKER THOMAS R., and CASE STEVEN B. (2000). Let GIS be your guide. The Science Teacher 67, no. 7: 24-26. http://kangis.org/learning/publications/science_teacher/print/tst 0010_24. pdf.
2.        BIS. (1991) Indian standards specifications for drinking water. Bureau of Indian Standards, New Delhi. IS: 10500.

3.        DONEEN, L.D., (1961) Notes on water quality in Agriculture. Published as a water science and Engineering Paper 4001, Department of Water Sciences and Engineering. University of California.

4.        DONEEN, L.D., (1964) Notes on Water Quality in Agriculture, Water Science and Engineering.

5.        DURBUDE D. G., and VARARRAJAN, N. (2007) Monitoring and mapping of groundwater quality. Journal of Applied Hydrology, v.xx, No. 1&2,  pp.22–30.

6.        EATON, E.M., (1950) Significance of carbonate in irrigation water.  Soil. Sci., Vol.69, pp.123-133.

7.        FRAPE, S.K., FRITZ, P., and MCNUTT, R.H. (1984) Water rock interaction and chemistry of groundwaters from the Canadian Shield. Geochem. Cosmochim. Acta, v.48, pp.1617–1627.

8.        GARRELS, R.M., and CHRIST, C.L. (1965) Solutions, Minerals and Equilibria. Harper and Row, New York, N.Y., 450p.

9.        HEM, J.D. (1985) Study and interpretation of the chemical characteristics of natural water. US Geol. Surv. Water Supply pp.254, 263, USGS, Washington.

10.     HERCZEG, A.L., TORGERSEN, T., CHIVAS, A.R., and HABERMEHL, M.A. (1991) Geochemistry of groundwater from the Great Artesian Basin, Australia. Jour. Hydrology, v.126, pp.225–245.

11.     KELLEY, W.P., BROWN, S.M. and LEIBIG, G.I. Jr. (1940) Chemical effects of Saline Irrigation water on soils.  Soil Science, Vol.49, pp. 95-107.

12.     KIMBLIN, R.T., (1995) The chemistry and origin of groundwater in Triassic sandstone and Quaternary deposits, Northwest England and some U.K. comparisons. Jour. Hydrology, v.172. pp.293–311.

13.     LONGLEY PAUL, A., (2000) The academic success of GIS in geography: Problems and prospects. Journal of Geographical Systems, 2 no. 1: pp.37 – 42.

14.     MANDEL, S. and Z.L. SHIFTAN, (1981). Ground Water Resources Investigation and Development, Academic Press Inc., New York.

15.     MICHAEL, A.M., (1990) Irrigation: Theory and Practice, Vikas Publishing House Pvt. Ltd., New Delhi, 801p.

16.     OPENSHAW, S.A., (1991) view on the crisis in geography, or using GIS to put humpty-dumpty back together again. Environment and Planning, A 23, no. 5: pp.621-628.

17.     PANDIAN, K., and SANKAR, K. (2007) Hydrogeochemistry and groundwater quality in the Vaippar river basin, Tamil Nadu Jour. of GSI, Vol.69, pp.970-982.

18.     PAWAR, N. J. (1993) Geochemistry of carbonate precipitation from the grounwaters in basaltic aquifers, An equilibrium thermodynamic approach, Jour. Geol. Soc. India, v.41, pp.119–131.

19.     RAJU, K.C.B. (1998) Importance of recharging depleted aquifers, State of the art of artificial recharge in India. Jour. Geol. Soc. India, v.51, pp.429–454.

20.     RICHARDS, L.A., (1954) Diagnosis and improvement of saline and alkali soils, U.S.D.A handbook, Vol.60, 160p.

21.     SALEH, A., AL-RUwaih, F. and SHEHATA, M. (1999) Hydrogeochemical processes operating within the main aquifers of Kuwait. J. Arid Env. V.42, pp.195-209.

22.     SARAF, A.K., GUPTA, R.P., JAIN, R.K., and SRIVASTAVA, N.K. (1994) GIS based processing and interpretation of ground water quality data, Proceedings of Regional workshop on Environmental Aspects of Ground water Development, Oct. 17-19, Kurukshetra, India.

23.     SOM. S.K., and BHATTACHARYA, A.K. (1992) Groundwater geochemistry of recent weathering at Panchpatmali bauxite bearing plateau, Koraput district, Orissa. Jour. Geol. Soc. India, v.40, pp.453–461.

24.     STUMM, W., and MORGAN, J.J. (1970) Aquatic Chemistry, Wiley, New York, N.Y. 1022p.

25.     SUI DANIEL, and RICHARD MORRILL. (2004) Computers and geography: From automated geography to digital earth. In Geography and Technology, edited by STANLEY, D., BRUNN SUSAN, L., CUTTER, and J.W. HARRINGTON, JR. DORDRECHT, NL: KLUWER.

26.     SWAINE, S., and SCHNEIDER, P. J., (1971) The chemistry of surface water in prairie ponds. Am. Chem. Soc. Adv. Chem. Ser., v.106, pp.99–104.

27.     TODD, D.K. (1980) Groundwater Hydrology. 2nd Edn. John Wiley & sons, Inc, New York.

28.     WICKS, C.M., and HERMAN, J.S. (1994) The effect of a confining unit on the geochemical evolution of groundwater in the Upper Floridan aquifer system. Jour. Hydrology, v.153, pp.139–155.
29.     WILCOX L.V (1955) Classification and use of irrigation waters. US Department of Agriculture, Arc 969, Washington DC

  

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39.

Authors:

M.I. Ramli, M.F. Basar, N.H.A. Razik

Paper Title:

Natural Energy Water Pump: Revisit the Water Sling Pump

Abstract:   Most people who live in rural areas come from the low income families. One reason for this is that the revenue generation is limited to certain domestic economic activities due to poor access to electricity. As a result, it limits the productivity of the people in these particular areas. By using this new pump where sling pump concept is adopted, it is believe that the people in rural areas could have more access to electricity and simultaneously grow the income related activities. This new pump is capable of providing water supply to the domestic agriculture areas. Sling pump is the enhancement of the coil pump where it powered by the water flow. This pump is driven by a propeller which finally resulting the entire pump to rotate the water and turns it into stream. Water and air enter the rear side of the pump and are forced to flow through a coil of plastic tubes while the pump is rotating. Water will be channeled through a hose and into stock tank or reservoir. The pump is applicable for low head and low flow river. From the experiment, this pump is capable to deliver up to 0.5m3 in a minute for stream water with flow rate 5L/s.

Keywords:
 Low head, low flow, natural energy, pico hydro, water sling pump.


References:

1.        M. F. Basar, A. Ahmad, N. Hasim and K. Sopian, “Introduction to the Pico Hydropower and the status of implementation in Malaysia,” IEEE Student Conference on Research and Development (SCOReD), pp. 283-288, ISBN: 978-1-4673-0099-5, Cyberjaya, Malaysia, 19-20 December 2011.
2.        Martin Anyi, Brian Kirke, and Sam Ali, “Remote Community Electricfication in Sarawak, Malaysia,” Renewable Energy 35 (2010), Volume 35, Issue 7, pp. 1609-1613, July 2010.

3.        P. Maher, and N. Smith, “Pico Hydro Village Power : A Practical Manual for Schemes Up to 5 kW in Hilly Areas”, 2nd Edi., Intermediate Technology Publications, May 2001.

4.        A.A. Williams, and R. Simpson, “Pico Hydro – Reducing Technical Risks for Rural Electrification,” Renewable Energy 34 (2009), Volume 34, Issue 8, pp. 1986-1991, August 2009.

5.        R.K. Sharma, and T.K. Sharma, “A Textbook of Water Power Engineering”, S. Chand & Company Ltd., First Edition, ISBN : 81-219-2230-5, 2003.

6.        Dan New, “Intro to Hydropower, Part 1 : Systems Overview,” Home Power 103, p.p 14 – 20, October & November 2004. Available at: http://www.homepower.com

7.        Sling Water Pump, http://www.riferam.com/river/, 2012 ‎     


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40.

Authors:

Tejaswini. R

Paper Title:

Resonant Boost Dc-Dc Converter for a High Frequency Operation

Abstract:   With different versions of inverters available, a control of VHF resonant boost dc-dc converter is described in detailed in this paper. Though, a classical Class- Φ inverter is well documented in the literature, this is a new version and coupled to resonant rectifier. The twin aspect of any design of resonant boost topology is to mainly feature low device voltage stress and to have high efficiency over wide range of loads. Increased switching frequency allows smaller size of the passive components, allowing one to use air-core magnetic, and thereby reducing core loss. The output is regulated by MPPT controller. The performance analysis was carried out on MATLAB/Simulink platform and performance characteristics are presented along with the values of components.

Keywords:
 Class- Φ inverter, resonant rectifier, MPPT controller, Zero-Voltage-Switching (ZVS).


References:

1.        Anthony D. Sagneri, Et.al., “Very-High-Frequency Resonant Boost Converters,” June 2009.
2.        R. Gutmann, “Application of RF circuit design principles to distributed Power Converters,” IEE Trans. Ind. Electron. Control Instrum,vol. IEC-127, no.3, pp. 156-164, Jun.1980.

3.        J. Rivas, J Jackson, O. Leitermann, A. Sagneri, Y. Han, and D. Perreault. “Design considerations for very high frequency dc-dc converters,” in Proc. 37th Annu. IEE Power Electron. Spec. Conf., Jun. 18-22, 2006.pp.1-11.

4.        J. Rivas, J Jackson, O. Leitermann, A. Sagneri, Y. Han, and D. Perreault. “Design considerations for very high frequency dc-dc converters,” in Proc. 37th Annu. IEE Power Electron. Spec. Conf., Jun. 18-22, 2006.pp.1-11.

5.        W. Tabisz and F. Lee, “Zero-Voltage-Switching multiresonant technique-a novel approach to improve Performance of high-frequency quasi-resonant converters,” IEE Trans. Power Electron, vol.4, no.4,pp.450-458, oct,1989.

6.        W. Bowman, J. Balicki, F. Dickens, R. Honeycutt, W. Nitz, W. Strauss, W. Suiter, and N.zeisse, “A resonant dc-dc converter operating at 22 megahertz,” in Proc. 3rd Annu. Appl. Power Electron.conf. 1988,pp.3-11.

7.        J.W.Phinney, D.J.Perreault, and J.H.Lang, “Radio-frequency inverters with transmission-line input nrtworks,” IEE Trans. Power Electron., vol.22, no.44, pp. 1154-1161, Jul.2007.

8.        J.M.Rivas, Y.Han, O. Lietermann, A.Sagneri, and D.J.Perreault, “A high-frequency resonant inverter topology with low voltage stress,” in Proc. IEE Power Electron.spec. conf.,2007.

9.        W.Nitz, w.Bowman, F.Dickens, F.Magalhees, W.Strauss, W.Suiter, and N.Zeisse, “A New family of resonant rectifier circuits for high frequency DC-DC converter
applications,” in Proc.3rd Annu. IEE Appl. Power Electron.conf., 1988, pp.12-22.

10.     S. Birca Galateanu and J.L.Cocqureue, “class e half-wave low dv/dt rectifier operating in a range of frequencies around resonance,” IEE Trans. Circuits Syst.I, Fundam. Theory Appl., vol.42, no.2, pp.83-94, Feb.1995.

11.     David Sanz Morales, “Maximum Power Point Tracking Algorithms for Photovoltaic Applications,” 2010. 


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41.

Authors:

S .Venkateswaran, P. Jayapal

Paper Title:

Geoelectrical Schlumberger Investigation for Characterizing the Hydrogeological Conditions Using GIS in Kadavanar Sub-basin, Cauvery River, Tamil Nadu, India

Abstract:   The increasing demand for fresh water has necessitated the exploration for new sources of groundwater, particularly in hard rock terrain, where groundwater is a vital source of fresh water. A fast, cost effective and economical way of exploration is to study and analyze geophysical resistivity survey data. The present study area Kadavanar sub-basin, Cauvery River, Tamil Nadu, India, is overlain by Archaean crystalline metamorphic complex. The study area is a characteristic region of unconfined aquifer system. The potential for occurrence of groundwater in the study areas was classified as very good, good, moderate and poor by interpreting the sub-surface geophysical investigations, namely vertical electrical soundings, were carried out to delineate potential water bearing zones. The studies reveal that the groundwater potential of shallow aquifers is due to weathered zone very low resistivity and very high thickness and the potential of deeper aquifers is determined by fracture zone very low resistivity and very high thickness area. By using conventional GIS method, the spatial distribution maps for different layer (Top soil, weathered zone, first fracture zone and second fracture zone) thicknesses were prepared. The geoelectrical approach was successfully applied in the study area and can be therefore easily adopted for similar environments.  

Keywords:
 Aquifer; Vertical Electrical Sounding (VES); spatial distribution map; hard rock terrain.


References:

1.        Baker, Thomas R., and Case, Steven B. (2000). Let GIS be your guide. The Science Teacher 67, no. 7: 24-26. http://kangis.org/learning/publications/science_teacher/print/tst 0010_24. pdf.
2.        Bernard, J., and Valla, P., (1991). Groundwater Exploration in fissured media with electrical and VLF methods. Geoexploration 27, 81-91.

3.        Christensen, N.B., Sorensen, K.I., (1998). Surface and borehole electric and electromagnetic methods for hydrogeological investigations. European Journal of Environmental and Engineering Geophysics 31, 75–90.

4.        De Lima, O.A.L., Niwas, S., (2000). Estimation of hydraulic parameters of shaly sandstone aquifers from geological measurements. Journal of Hydrology 235, 12–26.

5.        Fitterman, D.V., Stewart, M.T., (1986). Transient electromagnetic sounding for groundwater. Geophysics, 51, 995– 1005.

6.        Flathe, H., (1955). Possibilities and limitations in applying geoelectrical methods to hydrogeological problems in the coastal areas of North West Germany. Geophysical Prospecting, 3, 95–110.

7.        Huntley, D., (1986). Relations between permeability and electrical resistivity in granular aquifers. Groundwater 24 (4), 466–474.

8.        Kaikkonen, P., and Sharma, S.P., (1997).Delineation of near-surface structures using VLF and VLF-R data-an insight from the joint inversion result. The Leading Edge 16 (11), 1683-1686.

9.        Karous, M., and Mares, S., (1988). Geophysical methods in studying fracture aquifers. Charlse university, prague. 93 pp. (ER, EMI, SP, SRR, borehole).

10.     Kelly, W., 1977. Geoelectric sounding for estimating aquifer hydraulic conductivity. Groundwater 15 (6), 420–425.

11.     Kelly, W.E., (1977). Geoelectrical sounding for estimation hydraulic conductivity. Groundwater 15, 420-425.

12.     Krishnamurthy, N.S., Kumar, D., Rao Anand, V., Jain, S.C., and Ahmed, S., (2003). Comparison of surface and sub-surface geophysical investigations in delineatingfracture zones. Current Science 84 (9), 1242- 1246. 

13.     Longley, Paul A. (2000). The academic success of GIS in geography: Problems and prospects. Journal of Geographical Systems, 2 no. 1: 37 – 42.

14.     Mazac, O., Cislerova, M., Vogel, T., 1988. Application of geophysical methods in describing spatial variability of  saturated hydraulic conductivity in the zone of aeration. Journal of Hydrology 103, 117–126.

15.     Mazac, O., Kelly, W.E., Landa, I., (1985). A hydrogeophysical model for relations between electrical and hydraulic properties of aquifers. Journal of Hydrology 79, 1–19.

16.     McNeil, J.D., (1980). Electrical conductivity of soil and rocks. Technical Note TN-5, Geonics Limited, Mississauga, Ont., Canada, p. 22.

17.     Niwas, S., Gupta, P.K., de Lima, O.A.L., (2006). Nonlinear electrical response of saturated shaley sand reservoir and its asymptotic approximations. Geophysics 71 (3), 129–133.

18.     Openshaw, S. A view on the crisis in geography, or using GIS to put humpty-dumpty back together again. Environment and Planning, 1991, A 23, no. 5: 621-628.

19.     Porsani, J.L., Elis, V.R., Hiodo, F.Y., (2005). Geophysical investigations for the characterization of fractured rock aquifers in Itu, SE Brazil. Journal of Applied Geophysics 57, 119-128.

20.     Ramtek, R.S., Venugopal, K., Ghish, N., Krishnaiah, C., Panvaikar, G.A., and Vaidya. S.D., (2001). Remote sensing and surface geophysical techniques in the exploration of groundwater at Usha Ispat Ltd., Sindhurg Dist., Maharastra, India. Journal of IGU 5 (1), 41-49.

21.     Ronning, Jan S., Lauritsen, and T., Mauring, E., (1995). LocatiNG bedrock fractures beneath alluvium using various geophysical methods. Journal of Applied Geophysics 34, 137 – 167.

22.     Rubin, Y., Hubbard, S.S., 2005Hydrogeophysics, Water Science and Technology Library, 50. Springer, p. 521.

23.     Shahid, S., Nath, S.K., (2002). GIS integration of remote sensing and electrical sounding data for hydrogeological exploration. Journal of Spatial Hydrology 2 (1), 1–12.

24.     Sharma, S.P, Baranwal, V.C., 2005, Delineation of groundwater bearing fracture zones in a hard rock area integrating very low frequency electromagnetic and resistivity data.  Journal of Applied Geophysics 57, 155, 166.

25.     Srivastava, P.K., Bhattacharya, A.K., (2006). Groundwater assessment through an integrated approach using remote sensing, GIS and resistivity techniques: a case study from a hard rock terrain.

26.     Sui, Daniel and Richard Morrill. Computers and geography: From automated geography to digital earth. In Geography and Technology, 2004, edited by Stanley D. Brunn, Susan L. Cutter, and J.W. Harrington, Jr. Dordrecht, NL: Kluwer.

27.     Teeuw, R.M., (1999). Groundwater exploration using remote sensing and a low-cost geographical information system. Hydrogeology Journal 3, 21–30.

28.     W.E., Mares, S., 1993. International Journal of Remote Sensing 27 (20/20), 4599–4620. Kelly, Applied Geophysics in Hydrogeological and Engineering Practice. Elsevier Science Publisher, Amsterdam, p. 289.

29.     Zohdy, A.A.R., (1969). The use of Schlumberger and equatorial soundings in ground-water investigations near El Paso, Texas. Geophysics, 34, 713–728.


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42.

Authors:

Gabriel Nyame, Francis Ohene Boateng, Nana Kwame Gyamfi, and Nana Yaw Asabere

Paper Title:

ICTs and Supply Chain: The Competitiveness of Small and Medium Scale Enterprises (SMEs)

Abstract:   The number of Small and Medium Enterprises (SMEs) operating in the Adum Central Business District (CBD) of Kumasi, Ghana continues to grow at an increasing rate, but still they do not conform to the right standards and appropriate parameters. No matter what business activities they embark on some Information and Communication Technologies (ICTs) can be effectively used to enhance their operations. This paper finds out the adequacy of dissemination of ICTs and its level of deployment in the operations of SMEs of trade businesses in the Adum CBD and establishes the level of awareness of computers and their related technologies among owner-managers. In order to do an in-depth assessment of the situation, the CBD was put into zones A, B, and C and enterprises were selected at random. Interview procedures and administered questionnaires were used to obtain data for analysis. In effect, the study established that though the level of awareness is high, only 23% of these SMEs use computers whilst 49% use mobile phones to support their businesses. Also, 54% of these enterprises do not have access to the Internet. Thus, the exploitation and deployment of ICTs remain a greater challenge to these enterprises. It is recommended that the Ministry of Trade and Industry and other stakeholders organize programmes to enlighten owner-managers on the prospects of using ICTs to gain competitive advantage. In addition, the ICT industry must be revamped and freed from bottlenecks surrounding access to hardware and software.

Keywords:
 Awareness, Competitiveness, Digital Enterprise ICTs, Owner-Managers, SMEs, Supply Chain.


References:

1.        J. Tang, “Competition and Innovation Behaviour,” Research Policy, Vol. 35 pp. 68-82, 2006.
2.        D. Stokes and N. Wilson, “Small Business Management & Entrepreneurship,” 5th edition, 2006.

3.        V. Kotelnikov, “Small and Medium Enterprises and ICT,” United Nations Development Programme – Asia-Pacific Development Information Programme (UNDP-APDIP) and Asian and Pacific Training Centre for Information and Communication Technology for Development (APCICT), 2007.

4.        G.S. Kushwaha, “Competitive Advantage through Information and Communication Technology (ICT) Enabled Supply Chain Management Practices,” International Journal of Enterprise Computing and Business Systems, 1:2, p. 3, 2011.

5.        DFID Report on Digital Opportunity Task Force (DOT Force) Action Plan, G8 Summit, Geneva, 1992.

6.        M. Kuppusamy, M. Raman and G. Lee, “Whose ICT Investment Matters to Economic Growth: Private or Public? The Malaysian Perspective,” The Electronic Journal on Information Systems in Developing Countries, Vol. 37, No. 7, pp. 1-19, 2009.

7.        J. Abor and P. Quartey, “Issues in SME Development in Ghana and South Africa,” International Research Journal of Finance and Economics, Vol. 39, pp. 218-228, 2010.

8.        K.C. Laudon and J.P. Laudon, “Management Information Systems: Managing the Digital Firm,” 10th edition, Pearson Prentice Hall, New Jersey, 2007.

9.        A.L. Popoola, “Development of a Multi-Channel Personal Computer (PC) Based Data Logger,” Journal of Science and Technology, Vol 27. No. 3 pp. 122-130, 2007.

10.     A. Papastathopoulos, “Organizational Forms Based on Information & Communication Technologies (ICTs) Adoption,” Research in Business and Economics Journal, Vol. 32, No. 3, pp. 4-6, 2010.

11.     R. Ramakrishnan, “Database Management Systems,” WCB/McGraw-Hill Companies, Madison, USA, 1998.

12.     P. Marker, M. Kerry, and L. Wallace, “The Significance of Information and Communication Technologies for Reducing Poverty,” DFID: Fuller Davies, 2002.

13.     O. Thompson, “Business Intelligence Success, Lessons Learned,” Technology, 2004.

14.     H. Shiels, R. McIvor and D. O'Reilly, “Understanding the Implications of ICT Adoption: Insights from SMEs,” Logistics Information Management, Vol. 16, Issue 5, pp.312 – 326, 2003.

15.     T.H. Davenport and J.G.  Harris, “Automated Decision Making Comes of Age,” MIT Sloan Management Review, Vol. 46, No. 4, pp. 83-89, 2005.

16.     K. Sevrani and R. Bahiti “ICT in Small and Medium Enterprises: (Case of Albania),” ICBS, 2008.

17.     A. Bryman and E. Bell, “Business Research Methods,” 2nd edition, Oxford University Press Inc., New York, 2007.

18.     R.K. Yin, “Case Study Research: Design and Method,” 3rd edition, London, Sage, 2003.

19.     R.A. Krueger and M.A. Casey, “Focus Groups: A Practical Guide for Applied Research,” 3rd edition, Thousand Oaks, CA, Sage, 2000.

20.     M. Hall, “Decision Support Systems,” Computerworld, Vol. 36, No. 27, 2002.

21.     J. Hoffer, M. Prescott, and F. McFadden, “Modern Database Management,” 6th edition, Upper Saddle River, Prentice Hall, New Jersey, 2002. 


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43.

Authors:

Hemant Sharma, Jasvir Singh

Paper Title:

Run off River Plant: Status and Prospects

Abstract:   Most of the small hydro power plants are based on Run of River scheme, implying that they do not have any water storage capability. The power is generated only when enough water is available from the river. When the stream flow reduces below the design flow value, the generation will reduce as the water does not flow through the intake structure into the turbine. Small hydro plants may be stand alone system in isolated areas but could also be grid connected. The connection to the grid has the advantage of the easier control of the electrical system frequency of the electricity. In this research paper i discussed about the run off river plant, comparison of runoff river plant and small hydro power plants. And what type of turbine is suitable for small hydro power plant and run off river plant. 

Keywords:
 hydropower, runoff river power plant, water power.

References:

1.        Jiaqi Liang, Ronald G. Harley “Pumped storage hydro-plant models for system transient and long-term dynamic studies” IEEE  2009.
2.        Mukhtiar Singh, and Ambrish Chandra “Modelling and control of isolated micro-hydro power plant with battery storage system” IEEE 2012.

3.        H.K. Verma and Arun Kumar “Performance testing of small hydropower plant”International Conference on Small Hydro power 2007.

4.        Oliver Paish, “Small Hydro Power- Technology and Current Status: Elseiver Journal Renewable and Sustainable Energy Reviews.

5.        Vineesh V, A. Immanuel Selvakumar “ Design of micro hydel power plant” IJEAT 2012.

6.        Pankaj kapoor, Lobzang Phunchok, Sunandan Kumar “Frequency control of micro hydro power plant using electronic load controller” IJERA 2012.

7.        Viktor Iliev, Predrag Popovski, Zoran Markov “Transient phenomena analysis in hydroelectric power plants at off-design operating conditions” IJERA 2012.

8.        Arun Varughese, Prawin Angel Michael “Electrical characteristics of micro-hydro power plant proposed in valara waterfall” IJITEE 2013.

9.        Okonkwo, G N, Ezeonu S O “Design and Installation of Mini Hydro Electric Power Plant”, Scholar Journal of Engineering Research April 2012. 


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44.

Authors:

K Raja Sekhar, V Srinivasa Kalyan, B Phanindra Kumar

Paper Title:

Training Of Artificial Neural Networksin Data Mining

Abstract:   Companies have been collecting data for decades, building massive data warehouses in which to store it. Even though this data is available, very few companies have been able to realize the actual value stored in it. The question these companies are asking is how to extract this value. The answer is Data mining. There are many technologies available to data mining practitioners, including Artificial Neural Networks, Regression, and Decision Trees. Many practitioners are wary of Neural Networks due to their black box nature, even though they have proven themselves in many situations. This paper is an overview of artificial neural networks and questions their position as a preferred tool by data mining practitioners.

Keywords:
 Artificial Neural Network (ANN), neural network topology, Data mining, back propagation algorithm, Advantages.


References:

1.        Agrawal, R., Imielinski, T., Swami, A., “Database Mining: A Performance Perspective”, IEEE Transactions on Knowledge and Data Engineering, pp. 914-925, December 1993
2.        Berry, J. A., Lindoff, G., Data Mining Techniques, Wiley Computer Publishing, 1997 (ISBN 0-471-17980-9).

3.        Berson, “Data Warehousing, Data-Mining & OLAP”, TMH

4.        Bhavani,Thura-is-ingham, “Data-mining Technologies,Techniques tools & Trends”, CRC Press

5.        Bradley, I., Introduction to Neural Networks, Multinet Systems Pty Ltd 1997.

6.        Fayyad, Usama, Ramakrishna “ Evolving Data mining into solutions for Insights”, communications of the ACM 45, no. 8

7.        Fausett, Laurene (1994), Fundamentals of Neural Networks: Architectures, Algorithms and Applications, Prentice-Hall, New Jersey, USA.

8.        Haykin, S., Neural Networks, Prentice Hall International Inc., 1999

9.        Khajanchi, Amit, Artificial Neural Networks: The next intelligence

10.     Zurada J.M., “An introduction to artificial neural networks systems”, St. Paul: West Publishing (1992) 

  

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