Volume-2 Issue-6

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Volume-2 Issue-6, January 2013, ISSN: 2231-2307 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd.

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Moiz A. Hussain, G. U. Kharat

Paper Title:

Robust Human Motion Detection and Tracking In Dynamic Background

Abstract: Background subtraction is very important part of surveillance applications for successful segmentation of moving objects from video sequences. We present a novel & robust algorithm, for human motion detection and tracking in dynamic scenes based on background modelling technique to analyze the illumination change for detection & tracking of moving objects. Successive frame difference is taken and compared for the required set threshold for the changing pixel detection. Experimental result shows the high performance of the proposed method for human tracking in noisy backgrounds.

object detection, tracking, video survelliance, backgoround model, illumination change.


1. W. Hu, T. Tan, L.Wang, and S. Maybank, “A survey on visual surveillance of object motion and behaviors,” IEEE Trans. Syst., Man, Cybern. C, Appl. Rev., vol. 34, no. 3, pp. 334–352, Aug. 2004.
2. M.J. Hossain, J. Lee, and O. Chae. An Adaptive Video Surveillance Approach for Dynamic Environment. Proc. Int’l Symposium on Intelligent Signal Processing and Communication Systems: 2004. 84 – 89, 2004.

3. Y. Dhome, N. Tronson, A. Vacavant, T. Chateau, C. Gabard, Y. Goyat, and D. Gruyer. A Benchmark for Background Subtraction Algorithms in Monocular Vision: a Comparative Study. In International Conference on Image Processing Theory, Tools and Applications (IPTA 2010). 7–10 July 2010,

4. Madhur Mehta, Chandni Goyal, M.C. Srivastava and R.C.Jain, “ Real time object detection and tracking: Histogram matching and kalman filter approach,” IEEE 2010, 978-1-4244-5586-7.

5. J. Lou, T.Tan, W. Hu, H. Yang,and S. H. Maybank, “3D Model-based Vehicle Tracking”, IEEE Trans.on Image Processing, vol. 14, pp. 1561-1569, October 2005.

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8. G. B. Yang, W. W. Chen, Q. Y. Zhou, and Z. Y. Zhang, “Optical flow approximation based motion object extraction for MPEG-2 video stream,” Journal of Real-Time Image Processing, vol. 4, pp. 303-316, Nov 2009.

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12. W. Q. Wang, J. Yang, and W. Gao, “Modeling background and segmenting moving objects from compressed video,” IEEE Transactions on Circuits and Systems for Video Technology, vol. 18, pp. 670-681, May 2008.

13. M. Mason and Z. Duric. Using histograms to detect and track objects in color video. Applied Imagery Pattern Recognition Workshop, pages 154-159, 2001.

14. Y. Chen, C. Chen, C. Huang, Yi-Ping Hung: Efficient hierarchical method for background subtraction. Pattern Recognition 40(10): 2706–2715, 2007.

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17. Shaopeng Tang, Satoshi Goto, “Human Detection Using Motion and Appearance based Feature”,978-1-4244-4657-5/09/$25.00 ©2009 IEEE, May 2009






S Chandrashekhar Reddy, P.V.N.Prasad, A. Jaya Laxmi

Paper Title:

Reliability Improvement of Distribution System: A Hybrid Approach Based on GA and NN

Abstract: Due to high power demand, modern utilities are continuously planning the expansion of the electrical networks. One of the methods used for the expansion of electrical networks is connecting distributed generator (DG) in the distribution system. The main function of DG is to generate power based on the load condition or any fault occurs in the electrical network. By connecting DG in the distribution system, the power demand of the system can be satisfied and also it improves the reliability of the electrical network. The major problem in DG is, identifying the optimal location for fixing DG in the system and also computing the optimal number of DG to be connected in the system. By considering the abovementioned problem, here a hybrid technique is proposed, which includes genetic algorithm and neural network to identify the optimal number & location of DG to be connected in the system. The proposed method also computes the amount of power to be generated by each DG for various load conditions. By connecting DGs, the number of generators in the network increases and so that different generator states are possible for a particular load condition. From the possible generator states, the best state is selected based on some reliability parameters. Here, the reliability parameters that are considered for identifying the best generator states are loss of load probability (LOLP), loss of load expectation (LOLE), expected energy not supplied (EENS) and system expected outage cost (ECOST). The above reliability parameters are computed for different load conditions and also for the optimal number of DG identified using the proposed method. By using this method, the best generator state for different load conditions and also for different number of generators is computed. The result obtained shows the development in system reliability due to connecting optimal number of DG in the system.

Reliability, ECOST, EENS, LOLP, LOLE, DG, Distribution system.


1. Hadi Zayandehroodi, Azah Mohamed, Hussain Shareef and Marjan Mohammadjafari, “Impact of distributed generations on power system protection performance”, International Journal of the Physical Sciences Vol. 6, No. 16, pp. 3999-4007, Aug 2011
2. Sebastian Rios. M, Victor Vidal. P and David L. Kiguel, “Bus-Based Reliability Indices and Associated Costs in the Bulk Power System”, IEEE Transactions on
Power Systems, Vol. 13, No. 3, pp. 719-724, Aug 1998

3. A. A. Chowdhury, Sudhir Kumar Agarwal and Don O. Koval, “Reliability Modeling of Distributed Generationin Conventional Distribution SystemsPlanning and Analysis”, IEEE Transactions on Industry Applications, Vol. 39, No. 5, pp. 1493-1498, Oct 2003.

4. F. Gharedaghi, M. Deysi, H. Jamali, A khalili, “Investigation of Power Quality in Presence of Fuel Cell Based Distributed Generation”, Australian Journal of Basic and Applied Sciences, Vol. 5, No. 10, pp. 1106-1111, 2011

5. Akash T. Davda, M. D. Desai and B. R. Parekh, “Impact of Embedding Renewable Distributed Generation on Voltage Profile of Distribution System: A Case Study”, ARPN Journal of Engineering and Applied Sciences, Vol. 6, No. 6, pp. 70-74, June 2011

6. Moein Moeini-Aghtaie, Payman Dehghanian and Seyed Hamid Hosseini, “Optimal Distributed Generation Placement in a Restructured Environment via a Multi-Objective Optimization Approach”, 16th Conference on Electrical Power Distribution Networks (EPDC), Iran, pp. 1-6, 2011

7. R. Yousefian and H. Monsef, “DG-Allocation Based on Reliability Indices by Means of Monte Carlo Simulation and AHP”, 10th International Conference on Environment and Electrical Engineering (EEEIC), Iran, pp. 1-4, 2011.

8. Limbu, Tika R. and Saha, Tapan K., “Investigations of the impact of powerformer™ on composite power system reliability”, Proceedings of the IEEE Power Engineering Society General Meeting, United States, pp. 406-413, 2005.

9. Lingfeng Wang and Chanan Singh, “Adequacy Assessment of Power-generating Systems Including Wind Power Integration Based on Ant Colony System Algorithm”, IEEE Power Tech, Lausanne, pp. 1629-1634, 2007.

10. Saket R K, Bansal and R C, Singh G, “Generation capacity adequacy evaluation based on peak load consideration”, The South Pacific Journal of Natural Science Vol. 24 , pp. 38–44, 2006.

11. Bindeshwar Singh, K.S. Verma, Deependra Singhand S.N. Singh, “A Novel Approach for Optimal Placement of Distributed Generation & FACTS Controllers In Power Systems: An Overview and Key Issues”, International Journal of Reviews in Computing, Vol. 7, pp. 29-54, 2011.

12. Fariba Gharedaghi, Hanieh Jamali, Mansoureh Deisi and Atefeh Khalili, “Investigation of a new islanding detection method for distributed power generation systems”, International Journal of the Physical Sciences Vol. 6, No. 23, pp. 5540-5549, Oct 2011.

13. Seyed Ali Mohammad Javadian and Maryam Massaeli, “Impact of Distributed Generation on Distribution System’s Reliability Considering Recloser-Fuse Miscoordination-A Practical Case Study”, Indian Journal of Science and Technology, Vol. 4, No. 10, pp. 1279-1284, Oct 2011.

14. Wenping Qin, Peng Wang, Xiaoqing Han, and Xinhui Du, “Reactive Power Aspects in Reliability Assessment of Power Systems”, IEEE Transactions ON Power Systems, Vol. 26, No. 1, pp. 85-92, Feb 2011.

15. Mohammad Mohammadi and M. Akbari Nasab, “PSO Based Multiobjective Approach for Optimal Sizing and Placement of Distributed Generation”, Research Journal of Applied Sciences, Engineering and Technology, Vol. 2, No. 8, pp. 832-837, 2011

16. Morteza heydari, Amin Hajizadeh and Mahdi Banejad, “Optimal Placement of Distributed Generation Resources”, International Journal of Power System Operation and Energy Management, Vol. 1, Issue. 2, pp. 2231–4407, 2011

17. Satish Kansal, B.B.R. Sai, Barjeev Tyagi and Vishal Kumar, “Optimal placement of distributed generation in distribution networks”, International Journal of Engineering, Science and Technology, Vol. 3, No. 3, pp. 47-55, 2011.

18. Mohammad Mohammadi and M. Akbari Nasab, “DG Placement with Considering Reliability Improvement and Power Loss Reduction with GA Method” Research Journal of Applied Sciences, Engineering and Technology, Vol. 3, No. 8, pp. 838-842, 2011

19. Priyanka Paliwal and N.P. Patidar, “Distributed Generator Placement for Loss Reduction and Improvement in Reliability”, World Academy of Science, Engineering and Technology, Vol. 69, pp. 809-813, 2010.

20. H. Shayeghi, H. Hosseini, A. Shabani and M. Mahdavi, “GEP Considering Purchase Prices, Profits of IPPs and Reliability Criteria Using Hybrid GA and PSO”, World Academy of Science, Engineering and Technology, Vol. 44, pp. 888-894, 2008.

21. S. Chandrashekhar Reddy, P. V. N. Prasad, A. Jaya Laxmi, “Power Quality Improvement of Distribution System by Optimal Placement and Power Generation of DGs using GA and NN”, European Journal of Scientific Research, Vol.69, No.3, pp. 326-336, 2012

22. Qing-Shan, Min XIE and Felix F.WU, “Ordinal Optimization Based Security Dispatching in Deregulated Power Systems”, Joint 48th IEEE Conference on Decision and Control and 28th Chinese Control Conference, Shanghai, P.R.China, December 16-18, 2009, FrA 15.4.

23. Samuel Raafat Fahim, Walid Helmy, Hany M.Hasanien and M.A.L.Badr, “ Optimal Study of Distributed Generation Impact on Electrical Distribution Networks using GA and Generalized Reduced Gradient”, Recent Researches in Communications, Electrical & Computer Engineering, pp. 77-82, 2001, ISBN: 978-960-474-286-8.






Remica Aggarwal

Paper Title:

Selection of IT Personnel through Hybrid Multi-attribute AHP-FLP approach

Abstract: The personnel evaluation and selection is an important problem that can considerably affect the future competitiveness and performance of an organization. This paper presents a comprehensive hierarchical structure for selecting and evaluating a right personnel and proposes a new approach called “Analytical Hierarchy Process Weighted Fuzzy Linear Programming Model (AHP-FLP)” for personnel selection based on multiple attributes or criteria. The weights of the various criteria, taken as local weights from a given judgment matrix, are calculated using Analytical Hierarchy Process (AHP) that are also considered as the weights of the fuzzy linear programming model. This new model is compared with the classical AHP method. The study concluded that the AHP-FLP method outperforms the AHP method for selection of personnel with respect to restricted selection criteria. An example demonstrates the feasibility of the presented framework. Drawing on a real case of an Indian company from IT industry, the approach has been used to analyze the selection criteria used in recruitment for different IT roles which differed significantly in professional skills required.

Analytic Hierarchy Process, Decision making, Fuzzy linear programming.


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Sujatha.B, Chandra Sekhar Reddy, P Kiran Kumar Reddy

Paper Title:

Texture Classification Using Texton Co-Occurrence Matrix Derived From Texture Orientation

Abstract: The present paper derived a new co-occurrence matrix based on textons and texture orientation for rotation invariant texture classification of 2D images. The new co-occurrence matrix is called as Texton and Texture Orientation Co-occurrence Matrix (T&TO-CM). The Co-occurrence Matrix (CM) characterizes the relationship between the values of neighboring pixels, while the histogram based techniques have high indexing performance. If the CM is used to represent image features directly, then the dimension will be high and the performance is decreased. On the other hand, if histogram is used to represent image features, the spatial information will be lost. Texture Classification based on T&TO-CM, integrates color, texture and edge features of an image. The proposed T&TO-CM is used to describe the spatial correlation of textons and texture orientation for texture classification. T&TO-CM can capture the spatial distribution of edges, and it is an efficient texture descriptor for images with heavy textural presence. The proposed method is computationally attractive as it computes different features with limited number of selected pixels. The experimental results indicate the efficacy of the present method over the various other methods.

Co-occurrence Matrix;Texton, Texture Orientation


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Mohamed Bahaj, Abdellatif Soklabi, Ilias Cherti

Paper Title:

Load Balancing Management by Efficient Controlling Mobiles Agents

Abstract: Load balancing is a computer networking methodology which allows the distribution of the workload across multiple computers or computing devices, such as central processing units, disk drives, or other resources, to reach optimal resource utilization, reduce response time, maximize throughput and circumvent overload. The Use of multiple computers with load balancing, instead of a single computer, may increase reliability through redundancy. Our contribution outlines the adaptation of the Shadow approach used to control mobiles agents for developing a load balancing management algorithm in distributed systems. This approach does not only distribute the loads on the nodes and collect its running result, but it also manages the tasks execution places during all the execution time. Thereby, we get a self-organized load balancing infrastructure.

distributed computing, load balancing, mobiles agents.


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M Sripathy, K V Sharma, M Krishna

Paper Title:

Effect of Cyclic Compression Loading On Crushing Response of Polymer Based Composites Sandwich Panels

Abstract: The objective of work was focused to investigate microstructure of polyurethane foam and cyclic crushing strength of its sandwich structure which made of sisal / coir / bamboo / glass fabrics as reinforcement with polyester resin to form composites skin. The tested sandwich panels were constructed four type of FRP faceplates made of sisal / coir / bamboo / glass fiber reinforcements impregnated in polyester resin in four different material combinations. Each specimen subjected ten cyclic compression loading upto 40% maximum strain. The results indicate that the foams initially harden after the first cycle and then soften in subsequent cyclic loading. The hysteresis loops tend to shrink and approach asymptotically to a steady state before failure both the foam and the skin. The considered damage is in a form of through-width zone of crushed foam core accompanied by a residual crushing in the foam. It is shown that such damage causes a significant reduction of compressive strength. Glass/polyester and bamboo/polyester skin based sandwich structures have superior compressive strength. Coir /polyester based sandwich structure shows next to glass/polyester sandwich structures.

The hysteresis loops tend to shrink and approach asymptotically to a steady state before failure both the foam and the skin.


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3. Flavio de Andrade Silva, Nikhilesh Chawla, Romildo Dias de Toledo Filho, Tensile behavior of high performance natural (sisal) fibers, Composites Science and Technology, Volume 68, Issues 15-16, December 2008, Pages 3438-3443

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5. A. Awal, G. Cescutti, S.B. Ghosh, J. Müssig, Interfacial studies of natural fibre/polypropylene composites using single fibre fragmentation test (SFFT), Composites Part A: Applied Science and Manufacturing, Volume 42, Issue 1, January 2011, Pages 50-56

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8. Amin Ajdari, Hamid Nayeb-Hashemi, Ashkan Vaziri, Dynamic crushing and energy absorption of regular, irregular and functionally graded cellular structures, International Journal of Solids and Structures, Volume 48, Issues 3-4, February 2011, Pages 506-516.






G.Ajay, M.Suneel, K.Kiran Kumar, P.Siva Prasad

Paper Title:

Quality Evaluation of Rice Grains Using Morphological Methods

Abstract: In this paper we present an automatic evaluation method for the determination of the quality of milled rice. Among the milled rice samples the quantity of broken kernels are determined with the help of shape descriptors, and geometric features. Grains are said to be broken kernels whose lengths are 75% of the grain size. This proposed method gives good results in evaluation of rice quality.

Rice, Morphological Processing, Parameters, broken rice.


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6. Yadav, B. K., & Jindal, V. K. ‘Monitoring milling quality of rice by image analyses. Computers and Electronics in Agriculture, 33(1), 19–33.2001.

7. Yanagihara, T. ‘Measurement of the visual characteristics of cooked rice using image analysis’. Nippon Shokuhin Kagaku Kaishi, 47(7), 516–522Cereal Chemistry, 75(5), 738–741.2001.

8 Dalen G.V.”Determination of the size rice distribution and percentage of broken kernels of using flatbed scanning and image analyses:”Food research International(37)51,2004 Elsevier






C. Saravanan, M. Surender

Paper Title:

Enhancing Efficiency of Huffman Coding using Lempel Ziv Coding for Image Compression

Abstract: Compression is a technology for reducing the quantity of data used to represent any content without excessively reducing the quality of the picture. The need for an efficient technique for compression of images ever increasing because the raw images need large amounts of disk space seems to be a big disadvantage during transmission & storage. Compression is a technique that makes storing easier for large amount of data. It also reduces the number of bits required to store and transmit digital media. In this paper, a fast lossless compression scheme is presented and named as HL which consists of two stages. In the first stage, a Huffman coding is used to compress the image. In the second stage all Huffman code words are concatenated together and then compressed with Lempel Ziv coding. This technique is simple in implementation and utilizes less memory. A software algorithm has been developed and implemented to compress and decompress the given image using Huffman coding techniques in MATLAB software.

Lossless image compression, Huffman coding, Lempel Ziv coding.


1. http://www.TheLZWcompressionalgorithm.html
2. http://en.wikipedia.org/wiki/huffmancoding

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

4. J.Ziv and A.Lempel “A Universal Algorithm for Sequential data compression”, IEEE Transaction on Information theory, May 1977.

5. Introduction to Data Compression, Khalid Sayood, Ed Fox (Editor), March 2000.

6. Kuo-Kun Tseng, JunMin Jiang, Jeng-Shyang Pan, Ling Ling Tang, Chih-Yu Hsu, and Chih-Cheng Chen, “Enhanced Huffman Coding with Encryption for Wireless Data Broadcasting System”, International Symposium on Computer, Consumer and Control, 2012.

7. Mamta Sharma, “Compression Using Huffman Coding”, International Journal of Computer Science and Network Security, Vol.10, No.5, May 2010.

8. C. Saravanan and R. Ponalagusamy, “Lossless Grey-scale Image Compression using Source Symbols Reduction and Huffman Coding”, International Journal of Image Processing (CSC Journals), Vol.3, Iss.5, pp.246-251, 2009.

9. M.J.Weinberger, G.Seroussi, and G. Saprio. “LOCO-1 Lossless, Image Compression Algorithm: Principles and Standardization into JPEG-LS”, IEEE trans. Image Processing, pp.1309 – 1324, August 2000.

10. Martin DVORAK, Martin SLANINA, “Educational Video Codec”, 22nd International Conference Radioelektronika 2012, www.radioelektronika.cz.

11. R.C. Gonzales, R.E. Woods, Digital Image Processing, pp. 525-626, Pearson Prentice Hall, Upper Saddle River, New Jersey, 2008.

12. D. A. Huffman, “A method for the construction of minimum Redundancy codes,” in Proc. IRE, Sep. 1952, Vol. 40, pp. 1098–1101.

13. G. Lakhani and V. Ayyagari, “Improved Huffman code tables for JPEG’s encoder,” IEEE Trans. Circuits Syst. Video Technol., Vol. 5, No. 6, pp. 562–564, Dec. 1995.

14. Adina Arthur, V. Saravanan, “Efficient Medical Image Compression Technique for Telemedicine Considering Online and Offline Application”, International Conference on Computing, Communication, and Applications, 2012.

15. Yu-Ting Pai, Fan-Chieh Cheng, Shu-Ping Lu, and Shanq-Jang Ruan, “Sub-Trees Modification of Huffman Coding for Stuffing Bits Reduction and Efficient NRZI Data Transmission”, IEEE Transactions on Broadcasting, vol. 58, no. 2, June 2012.

16. S.B. Choi and M.H. Lee, “High speed pattern matching for a fast Huffman decoder,” IEEE Trans. Consum. Electron., vol. 41, no. 1, pp. 97–103, Feb. 1995.

17. Huang-Chih Kuo and Youn-Long Lin,”A Hybrid Algorithm for Effective Lossless Compression of Video Display Frames”, IEEE Transactions on Multimedia, vol.14, no.13, June 2012.





Zhenxing Luo

Paper Title:

Parameter Estimation in Wireless Sensor Networks Based on Decisions Transmitted over Rayleigh Fading Channels

Abstract: In this paper, we present a distributed estimation method in wireless sensor networks (WSNs) based on decisions transmitted over Rayleigh fading channels. The fusion centre can uses either coherent receiver or non-coherent receiver to acquire decisions transmitted over Rayleigh fading channels. The estimation method using coherent receiver and the estimation method using non-coherent receiver are presented and the Cramer-Rao lower bounds (CRLBs) are derived. Simulation results showed that in ideal situations, the RMS errors given by the distributed estimation method were close to the CRLB. Moreover, simulation results highlighted the importance of the number of sensors, channel SNR, and accurate channel SNR information known to the fusion centre on estimation performance.

Wireless sensor networks, maximum likelihood estimation, distributed estimation, Cramer-Rao lower bound, Rayleigh fading channel.


1. D. Li, K. D. Wong, Y.H.Hu, and A. N. Sayeed, “Detection, Classification, and Tracking of Targets”, IEEE Signal Processing Magazine, vol.19, no. 3, pp. 17-29, Mar. 2002.
2. Z. X. Luo and T. C. Jannett, “Optimal Threshold for Locating Targets within a Surveillance Region Using a Binary Sensor Network”, in Proceedings of the International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering (CISSE 09), Dec. 2009.

3. Z. X. Luo and T. C. Jannett, “A Multi-Objective Method to Balance Energy Consumption and Performance for Energy-Based Target Localization in Wireless Sensor Networks”, in Proc. of the 2012 IEEE Southeastcon, Orlando, FL, Mar. 2012.

4. X. Sheng and Y. H. Hu, “Maximum Likelihood Multiple-Source Localization Using Acoustic Energy Measurements with Wireless Sensor Networks”, IEEE Transactions on Signal Processing, vol.53, no.1, pp. 44-53, Jan. 2005.

5. 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 Proceedings of the 2012 IEEE Southeastcon, Orlando, FL, Mar. 2012.

6. Z. X. Luo and T. C. Jannett, “Modelling Sensor Position Uncertainty for Robust Target Localization in Wireless Sensor Networks”, in Proceedings of the 2012 IEEE Radio and Wireless Symposium, Santa Clara, CA, Jan. 2012.

7. Z. X. Luo and T. C. Jannett, “Energy-Based Target Localization in Multi-Hop Wireless Sensor Networks”, in Proceedings of the 2012 IEEE Radio and Wireless Symposium, Santa Clara, CA, Jan. 2012.

8. Z. X. Luo, “A censoring and quantization scheme for energy-based target localization in wireless sensor networks,” Journal of Engineering and Technology 2012, no 2, pp. 69-74.

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

10. 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.

11. 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.

12. 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.

13. R. X. Niu and P. K. Varshney, “Target Location Estimation in Sensor Networks with Quantized Data”, IEEE Transactions on Signal Processing, vol. 54, pp. 4519-4528, Dec. 2006.

14. O. Ozdemir, R. X. Niu, and P. K. Varshney, “Channel Aware Target Localization with Quantized Data in Wireless Sensor Networks,” IEEE Trans. Signal Process., vol. 57, pp. 1190-1202, 2009.

15. A. Ribeiro, and G. B. Giannakis, “Bandwidth-constrained Distributed Estimation for Wireless Sensor Networks-part I: Gaussian case,” IEEE Trans. Signal
Process., vol. 54, no. 3, pp.1131-43, March 2006.

16. A. Ribeiro, and G. B. Giannakis, “Bandwidth-constrained Distributed Estimation for Wireless Sensor Networks-part II: Unknown Probability Density Function,” IEEE Transactions on Signal Process., vol. 54, no. 7, pp. 2784-96, July 2006.

17. C. Hao and P. K. Varshney, “Nonparametric One-Bit Quantizers for Distributed Estimation,” IEEE Transactions on Signal Processing, vol. 58, pp. 3777-3787, 2010.

18. C. Hao and P. K. Varshney, “Performance Limit for Distributed Estimation Systems With Identical One-Bit Quantizers,” IEEE Transactions on Signal Processing, vol. 58, pp. 466-471, 2010.

19. G. Liu, B. Xu, M. Zeng, and H. Chen, “Distributed estimation over binary symmetric channels in wireless sensor networks,” IET Wireless Sensor Systems, vol. 1, pp. 105-109, 2011.






Zhenxing Luo

Paper Title:

Parameter Estimation in Wireless Sensor Networks with Normally Distributed Sensor Gains

Abstract: Wireless sensor networks (WSN) have attracted significant attention recently. The distributed estimation problem is an important research topic in WSNs. In the distributed estimation problem, the fusion center estimates an unknown parameter based on information gathered from sensors. Usually, it is assumed that sensors have identical gains. However, this may not be true due to manufacture errors or environmental influence. In this paper, we assume sensor gains follow normal distribution and present a maximum likelihood estimation (MLE) approach for distributed estimation in WSNs with normally distributed sensor gains. Moreover, the Cramer-Rao lower bound (CRLB) corresponding to this MLE approach is also derived. Simulation results showed that the root square mean (RMS) estimation errors given by this MLE approach were close to the CRLB if the variance of the sensor gains is small. If the variance of the sensor gains was large, the RMS estimation errors were not close to the CRLB.

Distributed estimation, maximum likelihood estimation, Gaussian distribution, wireless sensor networks.


1. D. Li, K. D. Wong, Y.H.Hu, and A. N. Sayeed, “Detection, Classification, and Tracking of Targets”, IEEE Signal Processing Magazine, vol.19, no. 3, pp. 17-29, Mar. 2002.
2. Z. X. Luo and T. C. Jannett, “Optimal Threshold for Locating Targets within a Surveillance Region Using a Binary Sensor Network”, in Proceedings of the International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering (CISSE 09), Dec. 2009.

3. Z. X. Luo and T. C. Jannett, “Energy-Based Target Localization in Multi-Hop Wireless Sensor Networks”, in Proceedings of the 2012 IEEE Radio and Wireless Symposium, Santa Clara, CA, Jan. 2012.

4. 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 Proceedings of the 2012 IEEE Southeastcon, Orlando, FL, Mar. 2012.

5. 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 Proceedings of the 2012 IEEE Southeastcon, Orlando, FL, Mar. 2012.

6. Z. X. Luo and T. C. Jannett, “Modeling Sensor Position Uncertainty for Robust Target Localization in Wireless Sensor Networks”, in Proceedings of the 2012 IEEE Radio and Wireless Symposium, Santa Clara, CA, Jan. 2012.

7. Z. X. Luo, “A censoring and quantization scheme for energy-based target localization in wireless sensor networks”, Journal of Engineering and Technology, 2012, no 2, pp. 69-74.

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

9. 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.

10. 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.

11. Z. X. Luo, “Distributed Estimation in Wireless Sensor Networks with Heterogeneous Sensors”, International Journal of Innovative Technology and Exploring Engineering, vol. 1, no. 4, Sept. 2012.

12. Z. X. Luo, “A New Search Method for Distributed Estimation in Wireless Sensor Networks,” International Journal of Innovative Technology and Exploring Engineering, vol.1, no.4, Sept. 2012.

13. X. Sheng and Y. H. Hu, “Maximum Likelihood Multiple-Source Localization Using Acoustic Energy Measurements with Wireless Sensor Networks”, IEEE Transactions on Signal Processing, vol.53, no.1, pp. 44-53, Jan. 2005.

14. R. X. Niu and P. K. Varshney, “Target Location Estimation in Sensor Networks with Quantized Data”, IEEE Transactions on Signal Processing, vol. 54, pp. 4519-4528, Dec. 2006.

15. A. Ribeiro, and G. B. Giannakis, “Bandwidth-constrained Distributed Estimation for Wireless Sensor Networks-part I: Gaussian case,” IEEE Trans. Signal Process., vol. 54, no. 3, pp.1131-43, March 2006.

16. A. Ribeiro, and G. B. Giannakis, “Bandwidth-constrained Distributed Estimation for Wireless Sensor Networks-part II: Unknown Probability Density Function,” IEEE Transactions on Signal Process., vol. 54, no. 7, pp. 2784-96, July 2006.

17. G. Liu, B. Xu, M. Zeng, and H. Chen, “Distributed Estimation over Binary Symmetric Channels in Wireless Sensor Networks,” IET Wireless Sensor Systems, vol. 1, pp. 105-109, 2011.

18. A. Papoulis and S. U. Pillai, Probability, random variables, and stochastic processes. New York: McGraw-Hill, 4th edition, 2002.






R. L. Bhargavi, M.Merlin Moses, V.Karthikeyan and C.Karthikeyan

Paper Title:

Design of a High-Speed Matrix Multiplier Based on Balanced Word-Width Decomposition and Karatsuba Multiplication

Abstract: This paper presents a flexible 2×2 matrix multiplier architecture. The architecture is based on word-width decomposition for flexible but high-speed operation. The elements in the matrices are successively decomposed so that a set of small multipliers and simple adders are used to generate partial results, which are combined to generate the final results. Balanced word-width decomposition scheme is discussed, which support 2’s complement inputs, and its overall functionality is verified and designed with a field-programmable gate array (FPGA). The architecture can be easily extended to a reconfigurable matrix multiplier. The objective is to propose a flexible and energy efficient matrix multiplier, which can be extended to reconfigurable high speed processing implementation, using word width decomposition technique. This technique is based on divide and conquers approach. The Karatsuba multiplication is proposed in this basic approach. This Karatsuba multiplication is an efficient procedure for multiplying large numbers, which gives high speed performance than the booth multiplier.

Balanced word-width decomposition. Field-programmable gate array (FPGA) implementation, matrix multiplier, Reconfigurable architecture.


1. K.Li,Y.Pan,and S.Q.Zheng,“Fast and processor efficient parallel matrix multiplication algorithms on a linear array with a reconfigurable pipelined bus system,”IEEE Trans.Parallel Distrib.Syst.,vol.9,no. 8,pp.705–720,Aug.1998.
2. C.I.Brown and R.B.Yates,“VLSI architecture for sparse matrix mul-tiplication,” Electron.Lett.,vol.32,no.10,pp.891–893,May 1996.

3. O.Mencer,M.Morf,and M.Flynn,“PAM-Blox: High performance FPGA design for adaptive computing,”in Proc.IEEE Symp.FPGAs Custom Computing Machines,1998,pp.167–174.

4. A.Amira,A.Bouridane,and P.Milligan,“Accelerating matrix product on reconfigurable hardware for signal processing,”in Proc.11th Int. Conf.Field-Programmable Logic Appl.(FPL),2001,pp.101–111.

5. J.Jang,S.Choi, and V.K.Prasanna, “Energy-efficient matrixmulti-plication on FPGAs,”in Proc.Int.Conf.Field Programmable Logic Appl.,2002,pp.534–544.

6. V.K.Prasanna and Y.Tsai,“On synthesizing optimal family of linear systolic arrays for matrix multiplication,”IEEE Trans.Comput.,vol. 40,no.6,pp.770–774,Jun.1991.

7. J.-W.Jang,S.Choi,and V.K.Prasanna,“Area and time efficient im-plementations of matrix multiplication on FPGAs,”in Proc.IEEE Int. Conf.Field Programmable Technol.,2002,pp.93–100.

8. R.Lin,“Bit-matrix decomposition and dynamic reconfiguration:Uni-fied arithmetic processor architecture,design,and test,”in Proc.Re-configurable Arch.Workshop (RAW),2002,p.83.

9. R.Lin,“Bit-matrix decomposition and dynamic reconfiguration: Uni-fied arithmetic processor architecture,design,and test,”in Proc.Re- configurableArch.Workshop (RAW),2002,p.83.

10. R.Lin,“Reconfigurable parallel inner product processor architectures,” IEEE Trans. Very Large Scale Integr.(VLSI)Syst.,vol.9,no.2,pp. 261–272,Apr.2001.

11. S.Choi,R.Scrofano, V.K.Prasanna, and J.-W.Jang,“Energy-effi-cient signal processing using FPGAs,”in Proc.ACM/SIGDA Int.Symp. Field-Programmable Gate
Arrays, 2003, pp.225–234.

12. J.M.Rabaey, A.Chandrakasan and B.Nikolic ´,Digital Integrated Cir-cuits: A Design Persepective, 2nd ed.Englewood Cliffs,NJ: Pren-tice- Hall,2003.

13. C.R.Baugh and B.A.Wooley,“A t wo’s complement parallel array multiplication algorithm, ”IEEE Trans.Comput., vol.C-22,no. 1–2, pp.1045–1047,Jan.193.






Jayasanthi Ranjith, NJR.Muniraj

Paper Title:

Novel Evolutionary Algorithm for ICA Processor for FPGA Implementation

Abstract: Evolutionary programming (EP) has been applied to many numerical and combinatorial optimization problems in recent years. Independent component analysis (ICA) is a statistical signal processing technique for separation of mixed signals, voices and images. The need for evolutionary algorithm for ICA lies in the fact that it needs contrast function optimization which enables the estimation of the independent components. Independent component analysis (ICA) decomposes observed mixed random vectors into statistically independent variables. It aims at finding the underlying independent components in the mixture by searching a linear or nonlinear transformation. It is also more efficient when the cost function, which measures the independence of the components, is optimized. ICA algorithm for contrast function optimization is developed in VHDL .The use of low complexity evolutionary computation with additional operations of mutation and crossover resolves the permutation ambiguity to a large extent. This also ensures the convergence of the algorithm to a global optimum and VLSI implementation results in reduced complexity of algorithms. IEEE single-precision representation, which fits in thirty-two bits, is used for all the manipulations for covering large range of real values.

ICA, Evolutionary optimization algorithm, FPGA , Statistical signal processing, VLSI


1. Hyvarinen and E. Oja, “A fast fixed-point algorithm for independent component analysis,” Neural Comput., vol. 9, no. 7, pp. 1483–1492,Oct. 1997.
2. Amit Acharyya and Koushik “hardware Efficient Fixed-Point VLSI Architecture for 2D Kurtotic FastICA”

3. H. Du, H. Qi and X. Wang, “Comparative Study of VLSI Solutions to Independent Component Analysis”, IEEE Trans. Industrial Electronics, vol. 54, no. 1, February, 2007.

4. K. K. Shyu, M. H. Lee, Y. T. Wu and P. L. Lee, “Implementation of Pipelined FastICA on FPGA for Real-Time Blind Source Separation”, IEEE Trans. Neural Networks, vol. 19, no. 6, pp. 958-970, June, 2008.

5. Hyvarinen, “Fast and Robust Fixed-Point Algorithms for Independent Component Analysis”, IEEE Trans. Neural Networks, vol. 10, no. 3, May, 1999.

6. E.Bingham and A. Hyvarinen, A Fast fixed-point algorithm for independent component analysis of complex valued signals, International Journal of Neural Systems, Vol. 10, No. 1, pp.1-8, February, 2000.

7. Alan Paulo , Ana Maria ,”FPGA hardware design, simulation and synthesis for a Independent component analysis algorithm using system-level design software”

8. Y.Tan and J.Wang, “Nonlinear Blind Source Separation Using Higher Order Statistics and a Genetic Algorithm”, IEEE Trans. On Evolutionary Computation, vol.5, No.6, pp.600-611, Dec. 2001.

9. Xuehai Pan,” The Study on the Shuffled Frog Leap Algorithm and Its Applications”Advances in information Sciences and Service Sciences (AISS),Volume4, Number1, January 2012

10. Xia Li, Jianping Luo,” An improved shuffled frog-leaping algorithm with external optimisation for continuous optimization”, 2010 Elsevier

11. Yamin Li and Wanming Chu”A New Non-Restoring Square Root Algorithm and Its VLSI Implementation” IEEE-2009

12. N. Shirazi, A. Walters and P. Athanas, “Quantitative analysis of floating point arithmetic on FPGA based custom computing machines”in Proc. IEEE Symposium on FPGAs for Custom Computing Machines, 1995, pp. 155-162.

13. Hongtao Du and Hairong Qi A Reconfigurable FPGA System for Parallel Independent Component Analysis, Hindawi Publishing Corporation EURASIP Journal on Embedded Systems Volume 2006, Article ID 23025, Pages 1–12

14. Mohammadreza Farahani1, Saber Bayat Movahhed1 , Seyyed Farid Ghaderi,” A hybrid meta-heuristic optimization algorithm based on SFLA”,2nd International Conference on Engineering Optimization September 6 – 9, 2010, Lisbon, Portugal

15. Xin Yao, Senior Member, IEEE, Yong Liu, Student Member, IEEE, and Guangming Lin,” Evolutionary Programming Made Faster”,IEEE transactions on evolutionary computation, VOL. 3, NO. 2, JULY 1999

16. Emad Elbeltagi, Tarek Hegazy, and Donald Grierson,” Comparison among five evolutionary-based optimization algorithms”, Advanced Engineering Informatics, volume 19, issue 1 , 43-53, January 2005

17. Jayasanthi Ranjith and Dr.N.J.R.Muniraj “Implementation of Optimized Floating Point Independent Component Analysis Processor on FPGA for EEG Separation,”Journal of Signal Processing Theory and Applications, (2012) 1: 36-43

18. Jayasanthi Ranjith and Dr.N.J.R. Muniraj,” VLSI Implementation of Memory Efficient Single Bit Processor for Industrial Control Applications”, Int. J. of Recent Trends in Engineering and Technology, Vol. 4, No. 4, Nov 2010






Monica N. Agu

Paper Title:

Application of ICT in Agricultural Sector: Women’s Perspective

Abstract: Agriculture is the mainstay of most third world economies and occupies a pivotal position in the development of these countries. Despite the importance of agriculture, improvements in this sector have been uneven and, on the whole, disappointing. In any farming system, it is important to recognize the various roles of women. Many women experience a life that is a complex web of multi roles and multi-tasks which requires the average woman to conduct different things in a bid to fulfil her family needs. Women in rural communities are extensively involved in arduous farm operations and agricultural activities, from planting to harvesting and other post harvesting operations. These women have been using and managing natural resources, collecting food etc for their livelihood. In Nigeria, women provide 60 – 80 percent of labour in agriculture through production, processing and marketing of food. They assist on family farms and are farmers in their own right. So the Nigerian women are in an important position to contribute to food supply. This sector faces major challenges for enhancing production in a situation of dwindling natural resources necessary for production. ICT plays an impotant role in addressing these challenges. The paper analyzes the problems facing women in the agricultural sector-and suggests ways to solve these problems. Furthermore the paper surveys the information needs of rural women and how ICT can be used to meet their information needs.

Agriculture, information and communication technology, women.


1. Blumberg, R. L.( 1992). African women in agriculture: farmers, students, extension agents, chiefs. Winrock International Institute for Agricultural Development, Morrilton, AR, USA. Development Studies Paper. 43 pp.
2. Blackden, Mark and Bhanu Chitra(1999) Gender Growth and Poverty Reduction. The World Bank Technical paper 428.

3. Dunn, K. 1995. The busiest people in the world. Ceres, 27(4), 48-50

4. GenARDIS, http://genardis.apcwomen.org/en

5. GrameenPhone , www.grameenpphone.com/

6. Hilda Munyua (2000) Application of ICTs in Africa’s Agricultural Sector: A Gender Perspective: Gender and the Information http://www.idrc.ca/en/ev-32947-201-1-DO_TOPIC.html

7. IFAD (International Fund for Agricultural Development). 1989. Women: the roots of rural development. IFAD, Rome, Italy, 22pp.

8. Lewis, Barbara(1984) The Impact of Development Policies on Women.In Hay and Stichter eds. African Women south of the sahara, New York:Longmans.

9. Nidhi Tandon (2006). ICTs to help Women Organic Farmers in the Caribbean.

10. United Nations(2000) the World’s Women 2000. Trends and Statistics. United Nations: New York






Monica N. Agu

Paper Title:

Need to Empower Nigerian Children and Youths through Information Technology

Abstract: Technology has become the driving force of change in the modern world. It has altered our economic structures and ways we communicate. Information is only one of our needs. Email, satellites can not be sustituted for drugs; neither can they provide clean water. Massive access to the Internet and ICT can accelerate awareness of these needs and will also facilitate development of solutions to tackle these needs effectively by empowering the youth of this country that are our future hopes. The information highways is leaving the African youth (Nigeria not excluded) poorer in ICT knowledge, skills and global reach. Thousands of young people in Nigeria leave school with the hope of developing a career and sustainable life that often turns into an illusion. The paper looks at the benefits of youth empowering, takes a review of youth empowerment initiatives in other developing countries and presents an approach of empowering Nigeria youths that are future leaders of tomorrow. With this we will move from the realm of educational inadequacy to that of unlimited resources.

Information Technology, Youth, Empowerment, Information and Communication Technology.


1. Agu M. N. (2008). An Integrated Framework for Poverty Reduction Via IT Empowerment. An unpublished Ph.d Thesis. Ebonyi State University.
2. Ajialcom-Empowering Youth through Technology. www.microsoft.com/about/corporatecitizenship/citizenship/giving/programs/up/casestudies/ajialcom.mspx.
3. Bernice Yeung (2008) Digital Equality: Empowering Underprivileged Youth in India with Information and Technology. www.edutopia.org/global-education-india

4. Edalat Abbas (1999) Empowering the Youthh of our Homeland. Information Technology and the Internet for Education in Iran. www.stanford.edu/group/psa/events/1990-00/saf-talk.utf8.html.

5. Itir Akdogan (2007)Technology empowers youth, youth will empower Turkey. Common Ground News Service www.commongroundnews.org/article.php?id=22091&lan=en&sid=l&sp=0=20k

6. ILO,Global Employment Trends for youth(Geneve,2004).

7. Information & Communications technology-Empowering Palestinian Children and Youth Through Digital Media. web.worldbank.org/…/EXTINFORMATIONAND COMMUNICATIONAN…-51K

8. Njideka Ugwuegbu (2002) Owerri Digital Village: A grassroots approach to empowering Nigerian youth and their communities, Digital Divide Network. www.digitaldivide.net/articles/view.php?ArticleID






Mohamed Bahaj, Jamal Bakkas

Paper Title:

Automatic Conversion Method of Class Diagrams to Ontologies Maintaining Their Semantic Features

Abstract: In this paper, we propose a new conversion’s method from UML class diagram to ontology in order to serve the Semantic Web. The ontology which results from the conversion is expressed in OWL / XML. This method allows us to preserve semantic of some feature’s UML diagram such as inheritance, encapsulation, types of associations (composition, aggregation, or simple association), constraints of integrity, class identifier…etc.

UML, ontology, mapping, OWL.


1. G. Antoniou, F. van Harmelen “Web Ontology Language: OWL”. pages 76-92 Springer-verlag .2003
2. D. L. McGuinness, F. van Harmelen, http://www.w3.org

3. M. R. Jensen, T. H. Møller Torben, B. Pedersen “Converting XML Data to UML Diagrams For Conceptual Data Integration”. Data & Knowledge Eng., vol. 44, no. 3, pp. 323-346, 2003

4. J. Fong, F. Pang, C. Bloor “Converting Relational Database into XML Document”. DEXA Workshop, pp 61-65. 2001

5. N. GHERABI, K. ADDAKIRI, M. BAHAJ “Mapping relational database into OWL Structure with data semantic preservation”. CoRR abs/1205.5922. 2012

6. J. Seidenberg, A. Rector “Web Ontology Segmentation: Analysis, Classification and Use”. IW3C 2006. ACM, 2006

7. M. Arnoux, T. Despeyroux “ Multi-représentation d’une ontologie : OWL, bases de données, systèmes de types et d’objets”. CoRR abs/1104.2982. 2011

8. D. Gasevic, D. Djuric, V. Devedzic, V. Damjanovi “Converting UML to OWL ontologies”. In Proceedings of the 13 th International World Wide Web Conference, NY, USA, pp. 488-489. 2004

9. M. Šeleng, M. Laclavík, Z. Balogh, L. Hluchý “RDB2Onto: Approach for creating semantic metadata from relational database data”. In INFORMATICS´ 2007: proceedings of the ninth international conference on informatic, Bratislava Slovak Society for Applied Cybernetics and Informatics, 113–116. 2007

10. C. Nyulas, M. O’Connor, S. Tu “DataMaster – a Plug-in for Importing Schemas and Data from Relational Databases into Protégé” In Proceedings of 10 th International Protégé Conference, Budapest, Hungary, 2007

11. J. Barrasa, Ó. Corcho, A. Gómez-Pérez “R2O, an Extensible and Semantically Based Database to ontology Mapping Language”. In Proceedings of the 2nd Workshop on Semantic Web and DatabasesSWDB2004Springer, p. 1069-1070, 2004





Oguike, O.E., Agu, M.N., Echezona, S.C.

Paper Title:

Modeling Variation of Waiting Time of Distributed Memory Heterogeneous Parallel Computer System Using Recursive Models

Abstract: In a heterogeneous parallel computer system, the computational power of each of the processors differs from one another. Furthermore, with distributed memory, the capacity of the memory, which is distributed to each of the processors, differs from one another. Using queuing system to describe a distributed memory heterogeneous parallel computer system, each of the heterogeneous processors will have its own heterogeneous queue. The variation of waiting time of heterogeneous parallel computer system with distributed memory needs to be modeled because it will help designers of parallel computer system to determine the extent of variation of the waiting time. It will also help users to know when to realize minimum variation of the waiting time. This paper models the variation of the waiting time of distributed memory heterogeneous parallel computer system using recursive models. It also uses the statistical method of Z-Transform to verify and validate the recursive model.

distributed memory, heterogeneous parallel computer, parallel computer system, queuing network, recursive models, variation, waiting time, Z-Transform.


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Karthikeyan.C, Karthikeyan.V, Jerin Sajeev.C.R, Merlin Moses.M

Paper Title:

Active Timing Based Approach for Tracking Anonymous Peer-to-peer Network in VoIP

Abstract: Peer-to-peer VoIP calls are popular due to their low cost and convenience. When these calls are encrypted and anonymized the network becomes a secured one. Tracing of the anonymous VoIP call users are important and the traced information about them should be sent to the server to know how long the users are in communication. The key challenge in tracking encrypted VoIP calls across anonymous communication system is to identify the correlation between the VoIP flows of the caller and the callee. Since all the traffic of the peer-to-peer VoIP calls are encrypted, the best way to track anonymous VoIP calls across the internet is using the Active timing based correlation. It is done by embedding a unique watermark into the inter-packet timing domain. The analysis shows that it only takes several milliseconds time adjustment to make normal VoIP flows highly unique and the embedded delay value could be preserved across the low latency anonymizing network. In this proposal, tracking of anonymous VoIP calls across internet was successfully achieved by using active time based correlation method and the results demonstrate that tracing of anonymous peer-to-peer VoIP calls on the internet is feasible and low latency anonymizing networks are susceptible to timing attacks.

It is done by embedding a unique watermark into the inter-packet timing domain.


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4. Shiping Chen, Xinyuan Wang, and Sushil Jajodia, George Mason University. “On the Anonymity and Traceability of Peer-to-Peer VoIP Calls” IEEE Network, September/October 2006 page (32-37)

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7. S. J. Murdoch and G. Danezis. “Low-Cost Traffic Analysis of Tor”. In Proceedings of the 2005 IEEE Symposium on Security and Privacy, IEEE, 2005.

8. X. Wang, S. Chen, and S. Jajodia, “Tracking Anonymous Peer-to-Peer VOIP Calls on the Internet,” Proc. 12th ACM Conf. Comp. and Commun. Sec., Nov. 2005, Page. 81–91.

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13. Matthew Wright, Micah Adler, Brian Neil Levine, and Clay Shields. “Defending anonymous communication against passive logging attacks”. In Proceedings of the 2003 IEEE Symposium on Security and Privacy, May 2003.

14. X. Wang and D. Reeves. “Robust Correlation of Encrypted Attack Traffic Through Stepping Stones by Manipulation of Interpacket Delays”. In Proceedings of the 10th ACM Conference on Computer and Communications Security (CCS 2003), pages 20-29. ACM, October 2003.

15. Marc Rennhard and Bernhard Plattner. Introducing MorphMix: “Peer-to-Peer based Anonymous Internet Usage with Collusion Detection”. In Proceedings of the Workshop on Privacy in the Electronic Society (WPES 2002), Washington, DC, USA, November 2002.





M. Jabbari Ghadi, A. Baghramian

Paper Title:

A New Heuristic Method for Solving Unit Commitment Problem in Competitive Environment

Abstract: In a restructured power market, traditional scheduling of generating units needs modification. The classical unit commitment problem aims at minimizing the operation costs by satisfying the forecasted electricity load. However, under new structure, Generation companies (GENCOs) schedule their generators with an objective to maximize their own profit by relaxation of the demand fulfillment constraint and without any regard for system social profit, to match the competitive market. A Unit Commitment algorithm with capability of profit maximization plays a significant role in successful development bidding strategies of a competitive generator. In such an environment, power price turns into an important factor in decision process. In this paper the authors utilized a new heuristic technique called Imperialistic Competitive Algorithm (ICA) to exert Profit Based Unit Commitment (PBUC) problem. In fact, the presented approach assists GENCOs to make a decision, how to schedule generators in order to gain the maximum profit by selling adequate amounts of power in power market. The effectiveness of the proposed method to solve generation scheduling optimization problem in a day-ahead deregulated electricity market is validated on 10 generating unit systems available in the literature. Comparison of results obtained from simulation verifies the ability of proposed method.

Deregulation, Electricity Market, Profit Based Unit Commitment, Imperialistic Competitive Algorithm, Competitive Environment.


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Lourthu Hepziba Mercy.M, Balamurugan.K, Vijayaraj.M

Paper Title:

Maximization of Lifetime and Reducing Power Consumption in Wireless Sensor Network Using Protocol

Abstract: This paper is to avoid duplicate transmission, node reconfiguration and power consumption in Wireless Sensor Networks (WSN). Wireless sensor network requires robust and energy efficient communication protocols to minimize the energy consumption as much as possible. However, the lifetime of sensor network reduces due to the adverse impacts caused by radio irregularity and fading in multi-hop WSN. The scheme extends High Energy First (HEF) clustering algorithm and enables multi-hop transmissions among the clusters by incorporating the selection of cooperative sending and receiving nodes. The work proposed focuses to develop any node to act as cluster head (CH) instead of affected CH because we need to get a data from CH continuously. To reduce energy consumption, proposed scheme extends with the help of S-MAC layer to get the efficient energy saving. The performance of the proposed system is evaluated in terms of energy efficiency and reliability. Simulation results show that tremendous energy savings can be achieved by adopting hard network lifetime scheme among the clusters. Many routing protocols are developed, but among those protocols cluster based routing protocols are energy efficient, scalable and prolong the network lifetime .The network simulator 2 (NS2) is used to verify the proposed network lifetime predictability model, and the results show that the derived bounds of the predictability provide accurate estimations of the energy saving and network lifetime.

cluster head selection, network lifetime, schedulability, timing constraints, wireless sensor networks, AODV.


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Ugwuishiwu B. O., Obi O. F. and Ugwuishiwu, C. H.

Paper Title:

Information and Communication Technologies: Benefits and Challenges to the Environment

Abstract: The issue of Information and Communication Technology (ICT) and the environment is a complex and multifaceted one. ICT can play both positive and negative roles in sustainable environment. This study shows the important linkages between ICTs, ICT-enabled innovation and the environment. It analyses the environmental impacts of ICTs in different stages of the life cycle and also as an enabling technology for mitigation of environmental impacts across all economic sectors. Direct environmental impacts were noted to be considerable in areas such as energy use, materials throughput and end-of-life treatment. ICT usage could also generate new activities and wastes with grave implications on efficient environmental resource management. The contribution of ICTs to systemic changes to achieve more sustainable environment was discussed. It was concluded that it is important that the environmental impacts of ICT products and operations be minimized through improved research and development, implementation of innovative ICT systems and government ICT policies.

Benefits, Challenges, Environment, ICT, Wastes.


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Muhammad Tanveer, Amir Habib, Muhammad Bilal Khan

Paper Title:

The Inverted Double Heterojunction Organic Photovoltaic Devices using Electrospun TiO2 Nanofibers

Abstract: The introduction of electrospun TiO2 nanofibers has improved the performance of inverted poly (3- hexylthiophene) (P3HT) and (6, 6)- phenyl-C61– butyric acid methyl ester (PCBM) solar cells by providing efficient charge generation and collection through double heterojunction. Electrospun TiO2 nanofibers increased the charge separation and collecting capability of the devices both from P3HT and PCBM by providing interfaces between P3HT-TiO2 and PCBM-TiO2 nanofibers. The resulting devices have reached to maximum power conversion efficiency (PCE) of 4.25±0.03% contributed by increased short circuit current (Jsc).

Heterojunction, inverted, nanofibers, organic


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12. M.S. White, D.C. Olson, S.E. Shaheen, N. Kopidakis, D.S. Ginley, “Inverted bulk-heterojunction organic photovoltaic device using a solution-derived ZnO underlayer”, Appl. Phys. Lett., 2006, 89, 143517-143513.

13. C. Waldauf, M. Morana, P. Denk, P. Schilinsky, K. Coakley, S.A. Choulis, C.J. Brabec, “Highly efficient inverted organic photovoltaics using solution based titanium oxide as electron selective contact”, Appl. Phys. Lett., 2006, 89, 233517-233513.

14. J.Y. Kim, S.H. Kim, H.H. Lee, K. Lee, W. Ma, X. Gong, A.J. Heeger, “New Architecture for High-Efficiency Polymer Photovoltaic Cells Using Solution-Based Titanium Oxide as an Optical Spacer”, Adv. Mater., 2006, 18, 572-576.

15. M.-S. Su, C.-Y. Kuo, M.-C. Yuan, U.S. Jeng, C.-J. Su, K.-H. Wei, “Improving Device Efficiency of Polymer/Fullerene Bulk Heterojunction Solar Cells Through Enhanced Crystallinity and Reduced Grain Boundaries Induced by Solvent Additives”, Adv. Mater., 2011, 23, 3315-3319.

16. M.K. Siddiki, J. Li, D. Galipeau, Q. Qiao, “A review of polymer multijunction solar cells”, Energy Environ. Sci., 2010, 3, 867-883.

17. J.H. Park, A.R. Carter, L.M. Mier, C.-Y. Kao, S.A.M. Lewis, R.P. Nandyala, Y. Min, A.J. Epstein, “Organic photovoltaic cells with nano-fabric heterojunction structure”, Appl. Phys. Lett., 2012, 100, 073301-073304.

18. Y. Zhou, M. Eck, C. Men, F. Rauscher, P. Niyamakom, S. Yilmaz, I. Dumsch, S. Allard, U. Scherf, M. Krüger, “Efficient polymer nanocrystal hybrid solar cells by improved nanocrystal composition”, Sol. Energy Mater. Sol. Cells, 2011, 95, 3227-3232.

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21. C.-F. Lin, M. Zhang, S.-W. Liu, T.-L. Chiu, J.-H. Lee, “High Photoelectric Conversion Efficiency of Metal Phthalocyanine/Fullerene Heterojunction Photovoltaic Device”, International Journal of Molecular Sciences, 2011, 12, 476-505.

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31. Y. Zheng, J. Xue, “Organic Photovoltaic Cells Based on Molecular Donor-Acceptor Heterojunctions”, Polymer Reviews, 2010, 50, 420 – 453.

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34. M. Al-Ibrahim, H.K. Roth, U. Zhokhavets, G. Gobsch, S. Sensfuss, “Flexible large area polymer solar cells based on poly(3-hexylthiophene)/fullerene”, Sol. Energy Mater. Sol. Cells, 2005, 85, 13-20.

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42. D.W. Zhao, P. Liu, X.W. Sun, S.T. Tan, L. Ke, A.K.K. Kyaw, “An inverted organic solar cell with an ultrathin Ca electron-transporting layer and MoO[sub 3] hole-transporting layer”, Appl. Phys. Lett., 2009, 95, 153304-153303.

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60. Y. Long, “Effects of metal electrode reflection and layer thicknesses on the performance of inverted organic solar cells”, Sol. Energy Mater. Sol. Cells, 2010, 94, 744-749.

61. J.C. Wang, W.T. Weng, M.Y. Tsai, M.K. Lee, S.F. Horng, T.P. Perng, C.C. Kei, C.C. Yu, H.F. Meng, “Highly efficient flexible inverted organic solar cells using atomic layer deposited ZnO as electron selective layer”, J. Mater. Chem., 2010, 20, 862-866.






G.Banupriya, C.R.Jerinsajeev

Paper Title:

Optimal Image Upscaling Using Pixel Classification

Abstract: Image magnification generally results in loss of image quality. Therefore image magnification requires interpolation to read between the pixels. Generally the enlarged images suffer from imperfect reconstructions, pixelization and jagged contours. The proposed system provides error-free high resolution for real images. The basic idea behind the system comprises two basic steps: Fast Curvature Based Interpolation (FCBI) which involves the filling of missing values after zooming and Iterative Curvature Based Interpolation (ICBI) which involves the modification of the filled values. The results obtained from the simulation shows that the proposed interpolation algorithm improves the quality of the image both subjectively and objectively compared to the previous conventional techniques.

Image enhancement, image processing, Image magnification, interpolation, jagged contours, NEDI, FCBI, ICBI, nvidia CUDA.


1. Andrea Giachetti and Nicola Asuni, “Real-Time Artifact-Free Image Upscaling”.IEEE Transactions on Image Processing, Vol. 20, No. 10, October 2011
2. Battiato. S, Gallo. G, and Stanco. F, “A locally-adaptive zooming algorithm for digital images,”Image Visual Computing. , vol. 20, 2002, pp. 805–812.

3. Chen. M. J, Huang. C. H, and Lee. W. L, “A fast edge-oriented algorithm for imageinterpolation,” Image Visual Computing. , vol. 23, 2005, pp.791–798.

4. Fattal.,R,“Image upsampling via imposed edge statistics”,ACMTransactionsonGraph.,vol.26,no.3,2007,pp.95-1-95 8.

5. Freeman. W. T, T. R. Jones, and E. C. Pasztor,”Example-basedsuper-resolution,”IEEE computer Graphic application,vol.22,no.2,Mar./Apr. 2002,pp.56-65.

6. Gilad Freeman and Raanan Fattal, “Image and video upscaling from Local self-Examples”,in proceedings of 12th International conference computer vision,2009,pp.349-356.

7. Glasner.D,Bagon. S, and Irani. M,”Super-resolution from a single image,” in proceedings of 12th International conference on computer vision., 2009,pp.349-356.

8. kim. K.I and Kwon. Y,”Example-based learning for single – image super- resolution,”in proceedings of 30th DAGM SymposiumonPatternRecognition,Berlin,Heidelberg,2008,pp.456-465

9. Li. X and orchard. M. T,”New edge-directed interpolation,” IEEE Transaction on Image processing, vol. 10, no. 10,oct. 2001,pp. 1521-1527.

10. Morse. B. S and schwartzwald.D,”Image magnification using level set reconstruction”, in proceedings of IEEE conference on Computer vision and pattern recognition ,2001,vol. 3,pp.333-340.

11. Su.D and willis. P,”Image interpolation by pixel level data-dependent triangulation,” computer Graphics Forum,vol.23,2004,pp.189-201.

12. Sun Jian, Z.B.Xu, and H.Y .shum,”Image super-resolution using gradient profile prior,”in proceedings of IEEE on computer vision and pattern recognition(CVPR),2008,pp. 1-8







Paper Title:

Low Power and Area-Efficient Carry Select Adder

Abstract: Carry Select Adder (CSLA) is one of the fastest adders used in many data-processing processors to perform fast arithmetic functions. From the structure of the CSLA, it is clear that there is scope for reducing the area and power consumption in the CSLA. This work uses a simple and efficient gate-level modification to significantly reduce the area and power of the CSLA. Based on this modification 8-, 16-, 32-, and 64-b square-root CSLA (SQRT CSLA) architecture have been developed and compared with the regular SQRT CSLA architecture. The proposed design has reduced area and power as compared with the regular SQRT CSLA with only a slight increase in the delay. This work evaluates the performance of the proposed designs in terms of delay, area, power, and their products by hand with logical effort and through custom design and layout in 0.18-m CMOS process technology. The results analysis shows that the proposed CSLA structure is better than the regular SQRT CSLA.

Application-specific integrated circuit (ASIC), area efficient, CSLA, low power.


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2. B. Ramkumar, H.M. Kittur, and P. M. Kannan, “ASIC implementation of modified faster carry save adder,” Eur. J. Sci. Res., vol. 42, no. 1, pp. 53–58, 2010.

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5. J. M. Rabaey, Digtal Integrated Circuits—A Design Perspective. Upper Saddle River, NJ: Prentice-Hall, 2001.

6. Y. He, C. H. Chang, and J. Gu, “An area efficient 64-bit square root carry-select adder for lowpower applications,” in Proc. IEEE Int. Symp. Circuits Syst., 2005, vol. 4, pp. 4082–4085.






Rashmi Agrawal, Mridula Batra

Paper Title:

A Detailed Study on Text Mining Techniques

Abstract: Text Mining is an important step of Knowledge Discovery process. It is used to extract hidden information from not-structured or semi-structured data. This aspect is fundamental because most of the Web information is semi-structured due to the nested structure of HTML code, is linked and is redundant. Web Text Mining helps whole knowledge mining process in mining, extraction and integration of useful data, information and knowledge from Web page contents. Web Text Mining process able to discover knowledge in a distributed and heterogeneous multi-organization environment. In this paper, our basic focus is to study the concept of Text Mining and various techniques. Here, we are able to determine how to mine the Plain as well as Structured Text. It also describes the major ways in which text is mined when the input is plain natural language, rather than partially-structured Web documents.

Plain, Structured, Text Mining, Web Documents.


1. Agrawal, R. and Srikant, R. (1994) “Fast algorithms for mining association rules.” Proc Int Conf on Very Large Databases VLDB-94, Santiago, Chile, pp. 487-499.
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6. Blum, A. and Mitchell, T. (1998) “Combining labeled and unlabeled data with co-training.” Proc Conf on Computational Learning Theory COLT-98. Madison, Wisconsin, pp. 92-100.

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Nalina.P, Muthukannan.K

Paper Title:

Survey on Image Segmentation Using Graph Based Methods

Abstract: The main goal of this paper is to survey the high quality of image segmentation with improved speed and stability. In this paper to segment the image using three different graph based segmentation algorithms. These are Isoperimetric Segmentation Normalisd Cut Segmentation, and Spectral Segmentation. Apply these algorithms in the image and find out segmentation result. Using the segmentation results the performance will be analyzed with speed and stability. To determine stability of image by adding the Additive Noise, Multiplicative Noise, Shot Noise

Isoperimetric, Normalized Cut, Performance Evaluation, Spectral, Segmentation.


1. Pedro F. Felzenszwalb and Daniel P. Huttenlocher. “Efficient Graph-Based Image Segmentation” International Journal of Computer Vision, Volume 59: 167–181, Number 2, September 2004.
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3. L. Grady and E. L. Schwartz, “Isoperimetric partitioning: A new algorithm for graph partitioning,” SIAM Journal on Scientific Computing, vol. 27, no. 6, pp. 1844–1866, June 2006.

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10. Weiss,Y. “Segmentation using eigenvectors: A unifying view” In Proceedings of the International Conference on Computer Vision, pp. 975–982, 1999.

11. Ratan, A.L., Maron, O., Grimson, W.E.L., and Lozano-Perez, T “A framework for learning query concepts in image classification” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp. 423–431, 1999.

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14. J. Ning,L. Zhang, D. Zhang and C. Wu “Interactive Image Segmentation by Maximal Similarity based Region Merging” In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, vol. 43, pp. 445-456, Feb, 2010.

15. Tranos Zuva, Oludayo O. Olugbara, et.al., “Image Segmentation, Available Techniques, Developments and Open Issues” Canadian Journal on Image Processing and Computer Vision Vol. 2, No. 3, March 2011

16. Ming Zhang, Reda Alhajj, “Improving the Graph-Based Image Segmentation Method” Proceedings of the 18th IEEE International Conference on Tools with Artificial Intelligence (ICTAI’O6), 2006, IEEE.

17. L. Grady and E. L. Schwartz, “Isoperimetric graph partitioning for image segmentation,” IEEE Trans. on Pat. Anal. and Mach. Int., vol. 28, no. 3, pp. 469–475,March 2006.

18. Yoram Gdalyahu, Daphne Weinshall, and Michael Werman, .Self-organization in vision: Stochastic clustering for image segmentation, perceptual grouping and image database organization,. IEEE Pattern Anal. and Mach. Int., vol. 23, no. 10, pp. 1053.1074, October 2001, 288.

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Smriti joshi, Anant Kr. Jaiswal, Pushpendra Kr. Tyagi

Paper Title:

A Novel Analysis of T Mac and S Mac Protocol for Wireless Sensor Networks Using Castalia

Abstract: Wireless sensor networks have been kept evolving due to the advancements in various technologies like radio, battery and operating systems in sensor elements but mac protocols are still most important in wsn because the exact implementation of communication among sensors is derived by the mac protocols. Battery consumption, network lifetime, communication latency, packet collisions are some very important factors those depends on mac protocols used in a wireless sensor networks. T Mac and S Mac have been two landmark protocols in wireless sensor networks protocols because of their utility and ease of implementation along with simplicity.

T Mac, protocol, S Mac, Castalia, Omnetpp, wsn.


1. www.omnet.org
2. A. Varga, The OMNeT++ discrete event simulation system, in: European Simulation Multiconference (ESM’2001) (Prague, Czech Republic,

3. http://castalia.npc.nicta.com.au/

4. Yuri Tselishchev, Athanassios Boulis, Lavy Libman, “Experiences and Lessons from Implementing a Wireless Sensor Network MAC Protocol in the Castalia Simulator,” submitted to IEEE Wireless Communications & Networking Conference 2010 (WCNC 2010), Sydney, Australia.

5. Wei Ye, John Heidemann, Deborah Estrin “An Energy-Efficient MAC Protocol for Wireless Sensor Networks”, INFOCOM 2002. Twenty-First Annual Joint Conferences of the IEEE Computer and Communications Societies. Proceedings. IEEE.

6. www.ecilipse.org

7. T. van Dam and K. Langendoen, An adaptive energy-efficient MAC protocol for wireless sensor networks, in: 1st ACM Conf. on Embedded Networked Sensor Systems (SenSys 2003), (Los Angeles, CA,November 2003)

8. A. Varga. The OMNeT++ discrete event simulation system. In European Simulation Multiconference (ESM’2001), Prague, Czech Republic, June 2001.






Mukesh Kumar Jha, Debanjan Pakhira, Baisakhi Chakraborty

Paper Title:

Diabetes Detection and Care Applying CBR Techniques

Abstract: Diabetes is a lifelong (chronic) disease increase at a rapid rate because of sedate life style, changes into urban culture, unhealthy foods and lacking of physical activity. It is an incurable chronic disease, but through true diabetes screening and advanced sugar monitoring can prevent risky complications. A little information, Precaution and absolute care plan can go a long way to dealing with diabetes. It is very hard to make an excellent care plan and maintaining healthy blood glucose level for patients and their health care providers. In this research work we proposed a case base decision support system for patients with diabetes. Case based reasoning is an artificial intelligence technique to detect diabetes and its type, its seriousness and giving the appropriate care plan. This system helps doctors and patients to check, analyze and repair solutions. A case consists of a problem description (e.g. symptoms) and a solution (e.g. a care plan and a therapy). Cases are stored in a database of cases called case bases. To solve an actual problem a notion of similarity is used to retrieve similar cases from case bases. The solutions of these found similar cases are used as starting points for solving the actual problems at hand. The system analyzes the symptoms of the patients and gives the exact types of diabetes, its seriousness level and the appropriate care plan for appropriate patients. If it is not found then system generates basic care plan by ontology. After that system modified that case and stored in its ever expanding database for future use. The learning process of CBR is retaining the modified solved case in the data base is gives a big scope to solve new problems in future.

Case-Based Reasoning, Detection, Diagnosis, Ontology.


1. Samaresh Deyashi, Debrup Banerjee, Baisakhi Chakraborty , D.Ghosh, Joyati Debnath, “Application Of CBR On Viral Fever Detection System(VFDS)”, 978-1-4577-0434-5/11/$26.00 ©2011 IEEE.
2. Department of Health, “What is diabetes “, http://www.doh.gov.tw/C HT2006/service/QnA.aspx?FAQ)D=193.(accessed 04124/2010)

3. I. Watson, F. Marir, “Case-Based reasoning: a review,” The Knowledge Engineering Review, vol. 9, no. 4, 1994. pp. 355-381.

4. T. R. Gruber, “Ontolingua: A translation approach to portable ontology specifications,” Knowledge Acquisition, Vol. 5, No. 2, 1993, pp. 199-200.

5. Jian-xun Chen, Shih-Li Su, Che-Ha Chang, “Diabetes care Decision Support System”, 2nd International Conference on Industrial and information Systems, 2010.

6. Cindy Marling, Matthew Wiley and Razvan Bunescu, Jay Shubrook and Frank Schwartz, “Emerging Applications for Intelligent Diabetes Management”, Proceedings of the Twenty-Third Innovative Applications of Artificial Intelligence Conference.

7. Cindy Marling, Jay Shubrook, And Frank Schwartz, “Toward Case-Based Reasoning for Diabetes Management: A Preliminary Clinical Study and Decision Support System Prototype”, Computational Intelligence, Volume 25, Number 3, 2009.

8. Frank L. Schwartz, Jay H. Shubrook, and Cynthia R. Marling, “Use of Case-Based Reasoning to Enhance Intensive Management of Patients on Insulin Pump Therapy”, Journal of Diabetes Science and Technology Volume 2, Issue 4, July 2008.

9. A. Bonzano, P. Cunningham, and C. Meckiff, “ISAC: A CBR System for Decision Support in Air Traffic Control”, Advances in Case-Based Reasoning, LNCS, Vol. 1168, , Springer Heidelberg, pp.44-57, 1996.

10. Agnar Aamodt, Enric Plaza, “Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches”, AI Communications. IOS Press, Vol. 7: 1, pp. 39-59, 1994.

11. Baisakhi Chakraborty, D.Ghosh, Ranjan Kumar Maji, Saswati Garnaik, Narayan Debnath,” Knowledge Management with Case-Based Reasoning Applied on Fire Emergency Handling”, 2012.

12. http://en.wikipedia.org/wiki/Diabetes_mellitus

13. http://www.nlm.nih.gov/medlineplus/diabetes.html

14. http://www.medicinenet.com/diabetes_mellitus

15. http://www.who.int/diabetes/en/index.html

16. http://www.hhs.gov/asl/testify/t990908a.html






Sarvesh Tanwar, Prema K.V.

Paper Title:

Threats & Security Issues in Ad hoc network: A Survey Report

Abstract: With the advancement in radio technologies like Bluetooth, IEEE 802.11, a new concept of networking has emerged; this is known as ad hoc networking where potential mobile users arrive within the range for communication. As network is becoming an increasingly important technology for both military and commercial distributed and group based applications, security is an essential requirement in mobile ad hoc network (MANETs). Compared to wired networks, MANETs are more vulnerable to security attacks due to the lack of a trusted centralized authority and limited resources. Attacks on ad hoc networks can be classified as passive and active attacks or internal attack and external attacks, the security services such as confidentiality, authenticity and data integrity are also necessary for both wired and wireless networks to protect basic applications. One main challenge in design of these networks is their vulnerability to security attacks. In this paper, we study the threats an ad hoc network faces and the security goals to be achieved.

MANET, Security, IEEE802.11, vulnerability, authenticity, threats, ad hoc networks.


1. T. Karygiannis and L. Owens, “Wireless Network Security, 802.11, Bluetooth and Handheld Devices,” NIST Publication, p. 800(48), November 2002.
2. S. A. Razak, S. M. Furnell, P. J. Brooke, Attacks against Mobile Ad Hoc Networks Routing Protocols”

3. Abhay Kumar Rai, Rajiv Ranjan Tewari & Saurabh Kant Upadhyay, “Different Types of Attacks on Integrated MANET-Internet Communication,” International Journal of Computer Science and Security (IJCSS) Volume: 4 Issue: 3.

4. H. Deng, W. Li, Agrawal, D.P., “Routing security in wireless ad hoc networks”, Cincinnati Univ., OH, USA; IEEE Communications Magazine, Oct. 2002, Volume: 40, page(s): 70- 75, ISSN: 0163-6804.

5. H.Deng, H.Li, and D.P.Ararwal, “Routing security in wireless Ad hoc networks”, IEEE Communication magazine. Vol. 40, No.10. Oct.2002.

6. S. Murphy, “Routing Protocol Threat Analysis,” Internet Draft, draft-murphy-threat-00.txt, October 2002.

7. Douceur, John: The Sybil Attack, 2002 http://www.cs.rice.edu/Conferences/IPTPS02/101.pdf

8. V. Gayraud and B. Tharon. Securing Wireless Ad Hoc Networks. ISS Master, MP 71 project, March 2003.

9. K. Sanzgiri, D. Laflamme, B. Dahill, B. Levine, C. Shields and E. Royer. An Authenticated Routing for Secure Ad Hoc Networks. Journal on Selected Areas in Communications special issue on Wireless Ad hoc Networks, March 2005.

10. Pradip M. Jawandhiya et. al. / International Journal of Engineering Science and Technology Vol. 2(9), 2010, 4063-4071

11. Charles P. Pfleeger, Shari Lawerence Pfleeger (2003), Security in Computing, Pearson Education, Singapore.

12. Abhay Kumar Rai, Rajiv Ranjan Tewari & Saurabh Kant Upadhyay International Journal of Computer Science and Security (IJCSS) Volume (4): Issue (3)

13. L. Zhou and Z. J. Haas. “Securing Ad Hoc Networks”. IEEE Network Magazine, Volume. 13, no. 6, Pages 24-30, December 1999.

14. C. E. Perkins and E. M. Royer. “Ad Hoc On-Demand Distance Vector Routing”. Proceedings of IEEE Workshop on Mobile Computing Systems and Applications, Pages 90-100, February 1999.






Manju, Ranjana Thalore, Jyoti, M.K Jha

Paper Title:

Performance Evaluation of Bellman-Ford, AODV, DSR and DYMO Protocols using QualNet in 1000m×1000m Terrain Area

Abstract: Wireless sensor networks (WSNs) offer much promise for target tracking and environmental monitoring. While many WSN routing protocols have been proposed to date, most of these focus on the mobility of observers and assume that targets are fixed. In addition, WSNs often operate under strict energy constraints, and therefore reducing energy dissipation is also an important issue. In this paper we discuss various protocols like Bellman-Ford, Ad-Hoc on-Demand Routing (AODV), Dynamic Source Routing (DSR), Dynamic MANET On-demand Protocol (DYMO) and compare various parameters like Average End-to-End Delay (sec.), Residual Battery Capacity (mAhr), and Throughput (bits/sec.), Output Received at CBR Server.

Wireless sensor networks, Routing Protocols, Energy efficiency, Qualnet 5.2.


1. Kadivar, M., Shiri, M. E., & Dehghan, M. (2009). Distributed topology control algorithm based on one-and two-hop neighbors information for ad hoc networks. Computer Communications, 32(2), 368– 375.
2. Dimokas, N., Katsaros, D., & Manolopoulos, Y. (2010). Energy-efficient distributed clustering in wireless sensor networks. Journal of Parallel and Distributed Computing, 70(4), 371–383.

3. Song, C., Liu, M., & Cao, J. (2009). Maximizing network lifetime based on transmission range adjustment in wireless sensor networks. Computer Communications, 32(11), 1316–1325.

4. Xu, Y., Hendemann, J., & Estrin, D. (2000). Adaptive energy-conserving routing for multihop ad hoc networks. Technical report TR-2000-527, USC/Information Sciences Institute.

5. Li, J. P. (2008). A mobile ECG monitoring system with context collection. Master’s thesis, Dublin Institute of Technology.

6. P. Hu, R. Robinson, M. Portmann, and J. Indulska, “Context-Aware Routing in Wireless Mesh Networks,” In Proceedings of the 2nd ACM International Workshop on Context-Awareness for Self-Managing Systems (CASEMANS), (Pervasive’08 Workshop), May 22, 2008, Sydney, Australia.

7. Vicaire, P., et al. (2009). Achieving long-term surveillance in vigilNet. ACM Transactions on Sensor Netowkrs, 5(5), 626–648.

8. P Kuosmanen – “Classification of Ad Hoc Routing Protocols” Finnish Defence Forces, Naval Academy, Finland, 2002 – netlab.tkk.fi.

9. Hadi Sargolzaey, Ayyoub Akbari Moghanjoughi and Sabira Khatun, – A Review and Comparison of Reliable Unicast Routing Protocols For Mobile Ad Hoc Networks, IJCSNS International Journal of Computer Science and Network Security, VOL.9 No.1, pp. 186-196, January 2009.

10. Beigh Bilal Maqbool, Prof.M.A.Peer (2010) Classification of Current Routing Protocols for Ad Hoc Networks – A Review International Journal of Computer Applications (0975 – 8887) Volume 7– No.8.

11. Charles Perkins and Elizabeth Royer. Ad hoc on demand distance vector (AODV) routing.http://www.ietf.org/internet-drafts/draft-ietfmanet- aodv-02.txt, November 1998. IETF Internet Draft.

12. D. Johnson and D. Maltz. Dynamic source routing in ad hoc wireless networks. In T. Imielinski and H. Korth, editors, Mobile computing. Kluwer Academic,1996.

13. Parma Nand, Dr. S.C. Sharma, “Performance study of Broadcast based Mobile Adhoc Routing Protocols AODV, DSR and DYMO,” International Journal of Security and Its Applications Vol. 5 No. 1, January, 2011.

14. Scalable Network Technologies, “Qualnet simulator”, Software Package, 2003. http:// www.scalable-networks.com.

15. T.V. P. Sundararajan, Dr. A. Shanmugam “Selfish avoidance routing protocol for Mobile Adhoc Network” International journal of wireless and Mobile Networks (IJWMN), Vol. 2, No. 2, may 2010.






Anil Saroliya, Upendra Mishra and Ajay Rana

Paper Title:

Secure transaction on the Peer to Peer based Virtual Network

Abstract: Distributed Hash Tables or the DHT is a very crucial and attention seeking topic as far as the field of P2P network overlays is concerned; since the latter has set a new benchmark in the arena of file sharing. The use of DHTs in P2P network involves the cause of file searching within the network. The DHT protocol works by assigning a key to a single P2P function and finds the node or nodes associated to this key thereby completing the request for file search. Other functions involving the retrieval of information and its storage are facilitated by certain higher layers in the P2P network. Through the research made out in the paper, the goal is to find out various security issues related to the process and resolve them according to the routing protocols of the network. The Chord which is a DHT protocol has been taken as the target for research in this paper for certain reasons that will consequently be covered in the following.

Structured P2P networks, distributed hash tables, routing, security, backtracking.


1. Dehui Liu, Feng Chen, Gang Yini, HuaiMin Wangl, Peng Zoul: LSB-Chord:Load Balancing in DHT based P2P systems under Churn. In:Proc. IEEE ICCSIT’10, Changsha, China (2010)
2. Heinbockel, W., and Kwon, M.: Phyllo: A peer-to-peer overlay security framework. The First Workshop on Secure Network Protocols (NPSec), Boston, MA (2005)

3. Ratnasamy, S., Francis, P., Handley, M., Karp, R., Shenker, S.: A scalable content addressable network. In: Proc. ACM SIGCOMM’01, San Diego, CA (2001)

4. Stoica, I., Morris, R., Karger, D., Kaashoek, M.F., Balakrishnan, H.: Chord: A scalable peer-to-peer lookup service for Internet applications. In: Proc. ACM SIGCOMM’01, San Diego, California (2001)

5. Wallach, D.: A survey of peer-to-peer security issues, International Symposium on Software Security, Tokyo, Japan (2002)

6. Gurari, Eitan, Backtracking algorithms “CIS 680: Data Structures: Chapter 19: Backtracking Algorithms” (1999)

7. Mariem Thaalbi, Nabil Tabbane, Tarek Bejaoui, Ahmed Meddahi: Enhanced Backtracking Chord protocol for mobile Ad hoc networks. In: Proc. IEEE ICCIT’12, Ariana, Tunisia (2012)






V.Selvi, R.Umarani

Paper Title:

Comparative Study of GA and ABC for Job Scheduling

Abstract: In the field of computer science and operation’s research, Artificial Bee Colony (ABC) is an optimization algorithm relatively new swarm intelligence technique based on behaviour of honey bee swarm and Meta heuristic. It is successfully applied to various paths mostly continuous optimization problems. Swarm intelligence systems are typically made up of a population of simple agents or boids interacting locally with one another and with their environment. The job scheduling problem is the problem of assigning the jobs in the system in a manner that will optimize the overall performance of the application, while assuring the correctness of the result. ABC algorithm, is proposed in this paper, for solving the job scheduling problem with the criterion to decrease the maximum completion time. In this paper, modifications to the ABC algorithm is based on Genetic Algorithm (GA) crossover and mutation operators. Such modifications applied to the creation of new candidate solutions improved performance of the algorithm.

Artificial Bee Colony, Genetic algorithm, Job scheduling.


1. Dror G. Feitelson, Larry Rudolph and Uwe Schwiegelshohn, “Parallel Job Scheduling -A Status Report”, In Proeedings of the Conference on JSSPP, pp.1-16, 2004.
2. Ivan Rodero, Francesc Guim and Julita Corbalan, “Evaluation of Coordinated Grid Scheduling Strategies”, In Proceedings of 11th IEEE International Conference on High Performance Computing and Communications, Seoul, pp. 1-10, 2009.

3. Oliner, Sahoo, Moreira, Gupta and Sivasubramaniam, “Fault-aware Job Scheduling for BlueGene/L Systems”, In Proceedings of 18th International Parallel and Distributed Processing Symposium, 2004.

4. Grudenic and Bogunovi, “Computer Cluster Scheduling Algorithm Based on Time Bounded Dynamic Programming”, In Proceedings of the 34th International Convention on MIPRO, 2011, Opatija, pp. 722-726, 2011

5. Abdelrahman Elleithy, Syed S. Rizvi and Khaled M. Elleithy, “Optimization and Job Scheduling in Heterogeneous Networks “, International Joint Conferences on Computer, Information, and Systems Sciences, and Engineering, 2008

6. Zhang, Franke, Moreira and Sivasubramaniam, “A Comparative Analysis of Space- and Time-Sharing Techniques for Parallel Job Scheduling in Large Scale Parallel Systems”, pp. 1-33, 2008.

7. Surekha and Sumathi, “Solution to the Job Shop Scheduling Problem using Hybrid Genetic Swarm Optimization Based on (λ, 1)-Interval Fuzzy Processing Time”, European Journal of Scientific Research, Vol. 64, No. 2, pp. 168-188, 2011.

8. Bin Cai, Shilong Wang and Haibo Hu, “Hybrid Artificial Immune System for Job Shop Scheduling Problem”, World Academy of Science, Engineering and Technology, Vol. 59, No. 18, pp. 81-86, 2011.

9. Mohammad Akhshabi, Mostafa Akhshabi and Javad Khalatbari, “Parallel Genetic Algorithm to Solving Job Shop Scheduling Problem”, Journal of Applied Sciences Research, Vol. 1, No. 10, pp. 1484-1489, 2011.

10. Manish Gupta, Govind sharma, “An Efficient Modified Artificial Bee Colony Algorithm for Job Scheduling Problem”, International Journal of Soft Computing and Engineering (IJSCE), Vol. 1, No. 6, pp. 291-296, January 2012.

11. Hadi Mokhtari, “Adapting a Heuristic Oriented Methodology for Achieving Minimum Number of Late Jobs with Identical Processing Machines”, Research Journal of Applied Sciences, Engineering and Technology, Vol. 4, No. 3, pp. 245-248, 2012.

12. Elnaz ZM, Amir MR, Mohammad R, Feizi D (2008). Job Scheduling in Multiprocessor Architecture Using Genetic Algorithm. Proc. IEEE, pp. 248-250.

13. Thanushkodi K, Deeba K (2009). An Evolutionary Approach for Job Scheduling in a Multiprocessor Architecture. CiiT Int. J. Artif. Intell. Syst. Mach. Learn., 1(4).

14. Tung-Kuan L, Jinn- Tsong T, Jyh-Hong C (2005). Improved genetic algorithm for the job-shop scheduling problem. International Journal Advanced Manufacture Technology (Spiringer), pp. 1021-1029.






CH.Appala Narayana, D.V.N. Ananth, K.D. Syam Prasad, CH. Saibabu, S.Sai Kiran, T. Papi Naidu

Paper Title:

Application of STATCOM for Transient Stability Improvement and Performance Enhancement for a Wind Turbine Based Induction Generator

Abstract: Voltage stability is a key issue to achieve the uninterrupted operation of wind farms equipped with squirrel cage induction generators (SCIG) during grid faults. A Static Synchronous Compensator (STATCOM) is applied to a power network which includes a SCIG driven by a wind turbine, for steady state voltage regulation and transient voltage stability support. The STATCOM is controlled by using PQ controller technique with voltage regulation as basic scenario. The system is implemented using MATLAB/ SIMULINK. Results illustrate that the STATCOM improves the transient voltage stability and therefore helps the wind turbine generator system to remain in service during grid faults. The time to reach steady state torque and speed without using vector control or direct torque control can also be achieved by using this STATCOM control technique.

Keywords: STATCOM, PQ control theory, induction machine, PWM.


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2. K.S Hook, Y. Liu, and S. Atcitty, “Mitigation of the wind generation integration related power quality issues by energy storage,” EPQU J., vol. XII, no. 2, 2006.

3. R. Billinton and Y. Gao, “Energy conversion system models for adequacy assessment of generating systems incorporating wind energy,” IEEE Trans. on E. Conv., vol. 23, no. 1, pp. 163–169, 2008,Multistate.

4. D. Tziouvaras, “Relay Performance during Major System Disturbances,” in Proc. Protective Relay Engineers, 2007. 60th Annual Conference, College Station, TX, 27-29 March 2007, pp. 251-270.

5. J. Manel, “Power electronic system for grid integration of renewable energy source: A survey,” IEEE Trans. Ind. Electron., vol. 53, no. 4, pp. 1002–1014, 2006, Carrasco.

6. M. Tsili and S. Papathanassiou, “A review of grid code technology requirements for wind turbine,” Proc. IET Renew.power gen., vol. 3,pp. 308–332, 2009.

7. S. Heier, Grid Integration of Wind Energy Conversions. Hoboken, NJ: Wiley, 2007, pp. 256–259.

8. J. J. Gutierrez, J. Ruiz, L. Leturiondo, and A. Lazkano, “Flicker measurement system for wind turbine certification,” IEEE Trans. InstrumMeas., vol. 58, no. 2, pp. 375–382, Feb. 2009.

9. Indian Wind Grid Code Draft report on, Jul. 2009, pp. 15–18, C-NET.

10. P. Kundur, Power System Stability and Control, McGraw Hill, 1994.

11. Charles Mozina, “Power Plant Protection and Control Strategies for Blackout Avoidance,” in Proc. IEEE PES Advanced Metering, Protection, Control, Communication, and Distributed Resources Conference, March 14-17, 2006, pp. 200-218.

12. W. Elmore, Protective Relaying Theory and Applications, CRC Press, 2nd Edition, 2004.






CH.AppalaNarayana, D.V.N.Ananth, T. PapiNaidu, B. Santosh Kumar, S. Saikiran, I. Prasanna Kumar, Y.Naveen Kumar, K.V.Ramana

Paper Title:

Application of STATCOM and CROWBAR for Transient Stability Improvement and Performance Enhancement for A Wind Turbine Based Doubly Fed Induction Generator

Abstract: This paper presents a robust control of Doubly Fed Induction Generator (DFIG) wind turbine in a sample power system. DFIG consists of a common induction generator with slip ring and a partial scale power electronic converter. Indirect field-oriented controller is applied to rotor side converter for active power control and voltage regulation of wind turbine. On grid side PQ control scheme is applied. Wind turbine and its control units are described in details and also for STATCOM control. All power system components are simulated in MATLAB/ SIMULINK software. For studying the performance of controller, different abnormal conditions are applied even the worst case. Simulation results prove that the performance of STATCOM and DFIG control schemes as improving power quality and stability of wind turbine.

STATCOM, PQ control theory, induction machine, PWM, crowbar, rotor side controller, grid side controller, DFIG, wind turbine.


1. Sannino, “Global power systems for sustainable development,” in IEEE General Meeting, Denver, CO, Jun. 2004.
2. K.S Hook, Y. Liu, and S. Atcitty, “Mitigation of the wind generation integration related power quality issues by energy storage,” EPQU J., vol. XII, no. 2, 2006.

3. R. Billinton and Y. Gao, “Energy conversion system models for adequacy assessment of generating systems incorporating wind energy,” IEEE Trans. on E. Conv., vol. 23, no. 1, pp. 163–169, 2008,Multistate.

4. D. Tziouvaras, “Relay Performance during Major System Disturbances,” in Proc. Protective Relay Engineers, 2007. 60th Annual Conference, College Station, TX, 27-29 March 2007, pp. 251-270.

5. J. Manel, “Power electronic system for grid integration of renewable energy source: A survey,” IEEE Trans. Ind. Electron., vol. 53, no. 4, pp. 1002–1014, 2006, Carrasco.

6. M. Tsili and S. Papathanassiou, “A review of grid code technology requirements for wind turbine,” Proc. IET Renew.power gen., vol. 3,pp. 308–332, 2009.

7. S. Heier, Grid Integration of Wind Energy Conversions. Hoboken, NJ: Wiley, 2007, pp. 256–259.

8. J. J. Gutierrez, J. Ruiz, L. Leturiondo, and A. Lazkano, “Flicker measurement system for wind turbine certification,” IEEE Trans. InstrumMeas., vol. 58, no. 2, pp. 375–382, Feb. 2009.

9. Indian Wind Grid Code Draft report on, Jul. 2009, pp. 15–18, C-NET.

10. P. Kundur, Power System Stability and Control, McGraw Hill, 1994.

11. Charles Mozina, “Power Plant Protection and Control Strategies for Blackout Avoidance,” in Proc. IEEE PES Advanced Metering, Protection, Control, Communication, and Distributed Resources Conference, March 14-17, 2006, pp. 200-218.

12. W. Elmore, Protective Relaying Theory and Applications, CRC Press, 2nd Edition, 2004.

13. Holdsworth, L., X.G. Wu, J.B. Ekanayake and N. Jenkins, 2003. Comparison of fixed speed and doubly-fed induction wind turbines during power system disturbances. IEE Proc. Gener. Transm. Distrib., 150 (3): 343-352.

14. W. Zhang, P. Zhou, and Y. He, “Analysis of the by-pass resistance of an active crowbar for doubly-fed induction generator based wind turbines under grid faults,” in Proc. Int. Conf. Electr. Mach. Syst. (ICEMS), Oct.,2008, pp. 2316–2321.

15. G. Pannell, D. Atkinson, and B. Zahawi, “Minimum-threshold crowbar for a fault-ride-through grid-code-compliant dfig wind turbine,” IEEE Trans. Energy Convers., vol. 25, no. 3, pp. 750–759, Sep. 2010.

16. J. Morren and S. de Haan, “Short-circuit current of wind turbines with doubly fed induction generator,” IEEE Trans. Energy Convers., vol. 22, no. 1, pp. 174–180, Mar. 2007.

17. J. Yang, J. Fletcher, and J. O’Reilly, “A series-dynamic-resistor-based converter protection scheme for doubly-fed induction generator during various fault conditions,” IEEE Trans. Energy Convers., vol. 25, no. 2, pp. 422–432, Jun. 2010.

18. A. Causebrook, D. Atkinson, and A. Jack, “Fault ride-through of large wind farms using series dynamic braking resistors (march 2007),” IEEE Trans. Power Syst., vol. 22, no. 3, pp. 966–975, Aug. 2007.

19. P. Flannery and G. Venkataramanan, “Unbalanced voltage sag ride-through of a doubly fed induction generator wind turbine with series grid-side converter,” IEEE Trans. Ind. Appl., vol. 45, no. 5, pp. 1879–1887, Sep./Oct. 2009.

20. J. Liang,W. Qiao, and R. Harley, “Direct transient control of wind turbine driven dfig for low voltage ride-through,” in Proc. IEEE Power Electron. Mach. Wind Appl. (PEMWA), Jun. 2009, pp. 1–7.






T. D. Dongale, S. R. Ghatage, R. R. Mudholkar

Paper Title:

Application Philosophy of Fuzzy Regression

Abstract: The uncertainties and its prediction normally tend to be complex phenomena. The randomness and fuzziness are two kinds of uncertainties possible in real time. The randomness deals with the general uncertainties whereas; the fuzzy logic addresses the linguistic uncertainties. The fuzzy logic and its allied field deal with the every part of uncertainties in fuzzy way. For a situation where, complex predictions are to tackle then statistical regression methodology is used from many years. The next step in this scenario for dealing with uncertainties is the ‘Fuzzy Regression’. This paper presents the elementary theory of fuzzy regression and the philosophy behind its potential application.

Fuzzy Logic, Fuzzy Regression, Uncertainties, Computational Intelligence


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32. Yun-Hsi O. Chang, Bilal M. Ayyub, Fuzzy regression methods- a comparative assessment, Fuzzy Sets and Systems 119, 2001, pp. 187-203.

33. Dongale, T. D., Kulkarni, T. G., & Mudholkar, R. R. Fuzzy Modelling of Voltage Standing Wave Ratio using Fuzzy Regression Method., International Journal of Emerging Technology and Advanced Engineering, ISSN 2250-2459, Volume 2, Issue 6, 2012, pp. 21-26.





Sanjivani Shantaiya, Kesari Verma, Kamal Mehta

Paper Title:

Study and Analysis of Methods of Object Detection in Video

Abstract: Object detection is generally performed in the context of higher-level applications that require the location and/or shape of the object in every frame. In the recent years various object detection methods have been proposed over by many researchers and both the apprentice and the proficient can be confused about their benefits and restrictions. In order to overcome this problem, this paper presents an analysis of some important methods and presents innovative classification based on time, memory requirements and accuracy. Results of Such an analysis can efficiently guide the researcher to select the most suitable method for a given application in a proper way. This research paper includes various approaches that have been used mostly by different researchers for object detection.

frame difference, approximate median, mixture of Gaussian.


1. Alok K. Watve, Dr. Shamik Sural “Object tracking in video scenes”, seminar at IIT Kharagpur, 1998
2. Yiwei Wang and John F. Doherty, Robert E. Van Dyck “Moving Object Tracking in Video,” 1999

3. Dong Kwon Park, Ho Seok Yoon and Chee Sun Won, “fast object tracking in digital video”, IEEE Transactions on Consumer Electronics, Vol. 46, No. 3, AUGUST 2000

4. Shanik Tiwari, Deepa Kumari, Deepika Gupta, Raina,” Enhanced Military Security Via Robot Vision Implementation Using Moving Object Detection and Classification Methods “,IOSR Journal of Engineering (IOSRJEN), Vol. 2 Issue 1, Jan.2012, pp.162-165

5. Robert Bodor, Bennett Jackson, Nikolaos Papanikolopoulos,” Vision-Based Human Tracking and Activity Recognition”,2000

6. Paul Viola,Michael Jones,Daniel Snow,” Detecting Pedestrians Using Patterns of Motion and Appearance “,Proceedings of the International Conference on Computer Vision (ICCV),October 13, 2003, Nice, France.

7. Alper Yilmaz, Omar Javed, Mubarak Shah,” Object Tracking: A Survey “ACM Comput. Surv. 38, 4, Article 13 (Dec. 2006), 45 pages. doi = 10.1145/1177352.1177355

8. Lan Wu,” Multiview Hockey Tracking with Trajectory Smoothing and Camera Selection “,2005

9. Massimo Piccardi, “Background subtraction techniques: a review “,2004 IEEE International Conference on Systems, Man and Cybernetics 0-7803-8566-7/04/$20.00 @ 2004 IEEE

10. Arnab Roy, Sanket Shinde and Kyoung-Don Kang,” An Approach for Efficient Real Time Moving Object Detection “,2009

11. Sivabalakrishnan.M and Dr.D.Manjula,” An Efficient Foreground Detection Algorithm for Visual Surveillance System “IJCSNS International Journal of Computer Science and Network Security, VOL.9 No.5, May 2009

12. Shireen Y. Elhabian*, Khaled M. El-Sayed* and Sumaya H. Ahmed,” Moving Object Detection in Spatial Domain using Background Removal Techniques – State-of-Art” Recent Patents on Computer Science 2008, 1, 32-54 , 1874- 4796 /08 $100.00+.00 © 2008 Bentham Science Publishers Ltd.

13. Young Min Kim,” Object Tracking in a Video Sequence”,2007

14. Sourabh Khire & Jochen Teizer,” Object Detection and Tracking “,2008

15. Prof. William H. Press,”Gaussian Mixture Models and EM Methods”, The University of Texas at Austin, CS 395T, Spring 2008, Prof. William H. Press

16. Jiyan Pan, ,BoHu, and Jian Qiu Zhang,” Robust and Accurate Object Tracking Under Various Types of Occlusions “,IEEE Transactions On Circuits And
Systems For Video Technology, Vol. 18, No. 2, February 2008

17. Vibha L, Chetana Hegde, P Deepa Shenoy, Venugopal K R, L M Patnaik,” Dynamic Object Detection, Tracking and Counting in Video Streams for Multimedia Mining “,IAENG International Journal of Computer Science,35:3,IJCS_35_3_16,21 august 2008

18. S. Saravanakumar, A. Vadivel and C.G. Saneem Ahmed,” Human object tracking in video sequences “ICTACT Journal On Image And Video Processing, August 2011, Volume: 02, Issue: 01






D. David NeelsPon Kumar, Praveen David, S.Rimlon Shibi, K.Arun Kumar

Paper Title:

Security Enhancement for Mobile WiMAX Network

Abstract: Security in wireless networks has traditionally been considered to be an issue to be addressed at the higher layers of the network.IEEE 802.16, known as WiMAX, is at the top of communication technology drive because it is gaining a great position in the next generation of wireless networks. Due to the evolution of new technologies wireless is not secured as like others networking technologies. A lot of security concerns are needed to secure a wireless network.Secure communication can only be provided after successful authentication and a robust security network association is established. By keeping in mind the importance of security, the WiMAX working groups has designed several security mechanisms to provide protection against unauthorized access and threats, but still facing a lot of challenging situations. WiMAX security architecture deals with all of the basic wireless security requirements like authentication, authorization, access control, data integrity, confidentiality and privacy.This paper examines the threats which are associated with MAC layer and physical layer of WiMAX and also proposes some enhancements to the existing model for improving the performance of the encryption algorithm and proposes some techniques in the existing model to enhance its functionality and capability.

WiMAX, Authentication, Authorization, Access control, Data integrity, Confidentiality


1. Dr. S.A.M Rizvi, Neeta Wadhwa, Dr. Syed ZeeshanHussain, “Performance Analysis of AES and TwoFish Encryption Schemes”, Commn Sys & Network Tech’s, IEEE, 2011.
2. C. Xenakis, N. Laoutaris, L. Merakos and I. Stavrakakis, “A generic characterization of the overheads imposed by IPsec and associated cryptographic algorithms”, Elsevier Computer Networks, 2006.

3. Alex Biryukov, Dmitry Khovratovich, IvicaNikolic. “Distinguisher and Related-Key Attack on the Full AES-256”, University of Luxembourg, 2009.

4. TrungNguyen,Prof. Raj Jain, “A survey of WiMAX security threats”, www1.cse.wustl.edu/ jain/cse571 09/ftp/wimax2/index.html, 2010.

5. Bruce Schneier, John Kelsey, Doug Whiting, David Wagner, Chris Hall, Niels Ferguson, “Twofish: A 128-Bit Block Cipher”, Counterpane Systems, 2000.

6. AamerNadeem, Dr M. YounusJaved, “A Performance Comparison of Data Encryption Algorithms”, IEEE 2005.

7. D. S. Abdul. Elminaam, H. M. Abdul Kader, M. M. Hadhoud, “Performance Evaluation of Symmetric Encryption Algorithms”, Communications of the IBIMA, Vol 8, 2009.

8. Rakesh Kumar Jha, DrUpena D Dalal, “A Journey on WiMAX and its Security Issues”, IJCSIT, Vol. 1 (4) , 2010.

9. Mathieu Lacage, “Experimentation with ns-3”, Trilogy Summer School, 27th august 2009.

10. “www.nsnam.org\ ns-3 Tutorial” Release ns-3.12, 2011.

11. Elias Weingrtner, Hendrikvom Lehn and Klaus Wehrle, “A performance comparison of recent network simulators”, RWTH Aachen University, 2009.

12. NaganandDoraswamy, Dan Harkins, “IPSec: The New Security Standard for the Internet, Intranets, and Virtual Private Networks”, Prentice Hall PTR, 2003.

13. Víctor A. Villagra, “Security Architecture for the Internet Protocol: IPSEC”, DIT-UPM, 2002.

14. Ibikunle F.A., Jamshedhasan, “Security Issues in Mobile WiMAX (802.16e)”, Mobile WiMAX Symposium, pp. 117 – 122, 2009.

15. E. B. Fernandez and M. VanHilst, ‘‘An overview of WiMAX security,’’ in WiMAX Standards and Security, M. Ilyas, Ed. Boca Raton, FL: CRC Press, 2008, pp. 197–204.

16. Andrey Bogdanov, Dmitry Khovratovich, and Christian Rechberger, “Biclique Cryptanalysis of the Full AES”, in Crypto 2011 Cryptology conference in Santa Barbara, California.

17. RFC1321 – The MD5 Message-Digest Algorithm http://www.faqs.org/rfcs/ rfc1321.html.

18. Rivest, R., “The MD4 Message Digest Algorithm”, RFC 1320, MIT and RSA Data Security, Inc., April 1992.






Pradip P.Patel, Sameena Zafar

Paper Title:

New E-Shape Rectangular Antenna Using the Square and Giuseppe Peano Fractals for Ultra Wide Band Application

Abstract: In this paper, a compact design and construction of microstrip Ultra Wide Band (UWB) antenna is proposed. The proposed antenna has the capability of operating between 3.2 GHz to 10 GHz. The antenna parameter in frequency domain analysis has been investigated to show its capability as an effective radiating element. The fractal antenna is preferred due to small size, light weight and easy installation. A fractal micro strip antenna is used for Ultra Wide Band application in this paper provides a simple and efficient method for obtaining the compactness. A New E-Shape Rectangular fractal antenna is designed for Ultra Wide Band. It should be in compactness and less weight is the major point for designing an antenna. This antenna is providing better efficiency.



Keywords: Component, New E-Shape Rectangular fractal antenna, Giuseppe peano fractal.


1. Pramendra Tilanthe and P. C. Sharma, “Design of a single layer multiband microstrip square ring antenna” IEEE explore-www.ieee.org, Applied Electromagnetic Conference (AEMC), year: 2009, PP: 1– 4.
2. Duixian Liu and Brian Gaucher, “A New multiband Antenna for WLAN/Cellular Applications”, Vehicular Technology Conference, 2004;VTC2004-Fall; IEEE 60th, Year: 2004, Vol: 1, PP: 243 – 246.

3. C. Puente, J. Romeu, R. Pous, A. Cardama, “On the behavior of the Sierpinski multiband antenna,”IEEE Trans. Antennas Propagat., vol. 46, pp. 517-524, Apr. 1998

4. D. H. Werner, S. Ganguly, “An overview of Fractal Antenna Engineering Research”, IEEEAntennas and Propagation Magazine, vol. 45, pp.38-57, 2003.

5. D. H. Werner and R. Mittra, Frontiers in Electromagnetics Piscataway,NJ: IEEE Press, 2000, pp. 48–81.

6. C. P. Baliarda, J. Romeu, and A. Cardama, “The kochmonopole: A small fractal antenna,” IEEE Trans Antennas Propagate., vol. 48, no.11, Nov. 2000.

7. T. Mustafa Khalid, “Combined fractal dipole wire antenna,” in Proc.2nd Int.ITG Conf. Antenna, Munich,Germany, Mar. 2007, pp.76–180.





P.Vamsi Krishna, D.Yugandhar

Paper Title:

An Enhanced Railway Transport System using FPGA through GPS & GSM

Abstract: Travel time information is a vital component of many intelligent transportation systems (ITS) applications. In recent years, the number of passengers travels in train & number of trains in India has increased tremendously. Due to the increase in number of trains the train times may be delayed and the passengers have to wait at railway stations. A desirable strategy to deal with such issues is to provide better service (comfort, convenience and so on) the notification of location of time through GSM. One such application provides accurate information about train arrivals to passengers, leading to reduced waiting times at railway stations. This needs a real-time data collection technique, a quick and reliable data and informing the passengers regarding the same. The scope of this proposed system is to use global positioning system data collected from trains in the city in India, to show the location. The system consists of three modules: Vehicle section Module, BASE Station section Module, User mobile section Module. Equipped with PC and GSM modem, BASE Station Module sends the initialization information containing the train number to Vehicle section Module using SMS. The microcontroller based vehicle section Module consisting mainly of a GPS receiver and GSM modem then starts transmitting its location to BASE Station Module. BASE Station Module equipped with a microcontroller unit and GSM modems interfaced to PCs is designed to keep track record of every train, processes user request about a particular train location out of BASE Station and updates trains location at stations. GPS Module is installed at every station and consists of a GSM modem, memory unit and dot matrix display all interfaced to a microcontroller. This module receives trains location information coming towards that station from BASE Station module and displays the information on a dot matrix display. The performance of the proposed system is found to be promising and expected to be valuable in the development of advanced public transportation systems (APTS) in India. The work presented here is one of the first attempts at real-time short-term prediction of arrival time for ITS applications in India.

GPS;GSM; Intelligent transportation systems;Base Station Module; Vehicle section Module; User mobile section Module; rush statistical analysis


1. P & D Department Punjab and Dainichi Consultants Inc., “Urbantransport policy study for five cities of PunjabProvinc,” Nov 2008.
2. Available [online]: www.garmin.com/products/gps35

3. Available [online]: www.d-d-s.nl/fotos-nokia/n12i_datasheet_a4_v2.pdf

4. Available [online]: www.alldatasheet.com

5. M. A. Mazidi, J. C. Mazidi, R. D. Mckinaly, The 8051Microcontroller and Embedded Systems, PearsonEducation, 2006.

6. Available [online]: www.mathworks.com





Mihir Gandhi, Jwalant Baria

Paper Title:

SQL INJECTION Attacks in Web Application

Abstract: Databases are the first target of the attackers in Web Application Once your ID and PASSWORD are out there may be several misuse of it. These paper discuss about Advance SQL Injection (ASQLIA) first of all it identifies which type of attacks according to that prevention measures are suggested .Some New features are added to it Web Crawling ,Web Services and Advance SQL Injection (ASQLA)which will emphases more Security of Web Application. In short enhancing database security with the aspect of web developer is main aim of my paper.

Cybercrime, hash function, encryption algorithm.SQL Injection, Tautology, SQLIA, Blind injection, piggy backing, PSIAW.


1. By1Prasant Singh Yadav, 2 Dr pankajYadav, 3Dr. K.P.Yadav “A Modern Mechanism to Avoid SQL Injection Attacks in Web Applications”,IJRREST: International
Journal of Research Review in Engineering Science and Technology ,Volume-1 Issue-1, June 2012.

2. By MayankNamdev *, FehreenHasan, GauravShrivastav “Review of SQL Injection Attack and Proposed Method for Detection and Prevention of SQLIA”Volume 2, Issue 7, July 2012.

3. By AtefehTajpour ,Suhaimi Ibrahim, Mohammad SharifiWeb Application Security by SQL Injection DetectionTools.IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 2, No 3, March 2012






Nidhi Saxena, Vipul Saxena, Neelesh Dubey, Pragya Mishra

Paper Title:

HAND GEOMETRY: A New Method for Biometric Recognition

Abstract: This research method demonstrates a study about personal verification and identification using hand geometry. Hand geometry used in this research consists of the lengths and widths of fingers and the width of a palm. Users can place their hands freely without the need for pegs to fix the hand placement. In this method, six dierent distance functions were tested and compared. Test data obtained were from different users. Among the six dierent distance functions, S1 gives the best results in both verification and identification.

Biometric, Hand geometry, Recognition, Identification


1. K. Jain, A. Ross, and S.Prabhakar,“An Introduction to Biometric Recognition,” IEEE Transactions on circuits and Systems for Video Technology, Special Issue on Image- and Video-Based Biometrics, Vol. 14, No. 1, pp. 4-20, Jan. 2004.
2. John Chirillo, and Scott Blaul,Implementing Biometric Security, John Wiley & Sons, Apr. 2003.

3. R. Sanchez-Reillo, C. Sanchez-Avila, and A.Gonzalez- Marcos,“Biometric Identification Through Hand Geometry Measurements,” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 22, No. 10, pp. 1168-1171, 2000

4. Alexandra L.N. Wong and Pengcheng Shi,“Peg Free Hand Geometry Recognition Using Hierarchical Geometry and Shape Matching,” IAPR Workshop on Machine Vision Applications, Nara, Japan, pp. 281- 284, Dec. 2002.

5. Linda G. Shapiro, and George C. Stockman, Computer Vision, Prentice Hall, Jan. 2001.

6. Sezgin, M., Sankur, B., “Survey over image thresholding techniques and quantitative performance evaluation”, Journal of Electronic Imaging, 13 (1), 2004, pp.146–156.

7. A. K. Jain and N. Duta,“Deformable Matching of Hand Shapes for Verfication,” IEEE International Conference on Image Processing, pp. 857- 861, Oct.1999.

8. R.Sanchez-Reillo,“Hand Geometry Pattern Recognition Through Gaussian Mixture Modeling,” 15th, International Conference on Pattern Recognition, Vol. 2, pp. 937-940, Sep. 2000

9. Öden, A. Erçil, and B. Büke, “Combining implicit polynomials and geometric features for hand recognition,” Pattern Recognit. Lett.,Vol. 24, 2003, pp. 2145–2152.

10. D.P.Sidlauskas, “3D hand profile identification apparatus”, US Patent No.4736203, 1988.

11. Y. A. Kumar, and A. K. Jain,“Personal verification using palmprint and hand geometry biometric”, in Proc. 4th Int. Conf. Audio Video-Based Biometric Person Authentication, Guildford, U.K., Jun. 9–11, 2003, pp.668–678.

12. C. Han, H.L. Cheng,C. L. Lin, and K C.Fan, “Personal authentication using palm printfeatures,” Pattern Recognit., Vol. 36, 2003, pp. 371–381.

13. N. Otsu,“A Threshold Selection Method From Gray-scale Histogram,” IEEE Transaction Syst., Man, Cybern., Vol. 8, pp. 62-66, 1978.

14. Otsu, N., “A threshold selection method from gray-level histograms”, IEEE Transactions on Systems, Man, and Cybernetics, Vol. SMC-9 (1), 1979, pp. 62–66.






Roop Singh Takur, E.Ramkumar

Paper Title:

Embedded Systems and Robotics that Improving Security Model with 2D and 3D of Face -Recognition Access Control System Using Neural Networks

Abstract: Recognition and Sensor monitor Control are the basic tasks performed by Artificial Neural Networks. In this paper we present new technology for Security reasons. That is Robots and Embedded systems Using Camera inside the devices. By using sensor controls we can captures the photos and videos of the crimes and terrorists activities performing by human beings. Embedded Systems devices such as LED TV, Car, Air conditioners where we are using in Airports and Markets, Bus stations, Railway stations so on. Especially in public places. By using these method crimes will be reduced greater Extent. Some countries are using robots for security purpose and in other countries we are using embedded systems for Entertainments, announcements, air, travelling purpose. They are using embedded applications inside. I am going to show by keeping cameras inside into that we can also performs Face recognition in 2D and 3D.Here in this paper using Back propagation algorithm is used to detect the face in proper manner and right direction without any errors and transferred images into memories in micro controller chip.

Artificial Neural Networks, Back propagation, 3D-Model-Face recognition, Robots, Embedded systems.


1. Recognition of Human Face by Face Recognition System using 3D Bayan Ali Saad Al-Ghamdi* Sumayyah Redhwan Allaam* Yanbu University College, Saudi Arabia.
2. Robust face recognition using posterior union model based neural networks J. Lin1,2 J. Ming2 D. Crookes2

3. High-speed face recognition using self-adaptive radial basis function neural networks Jamuna Kanta Sing Æ Sweta Thakur Æ Dipak Kumar Basu Æ Mita Nasipuri Æ Mahantapas Kundu

4. Face Recognition: A Literature Review A. S. Tolba, A.H. El-Baz, and A.A. El-Harby

5. Face Recognition under Occlusions and Variant Expressions with Partial Similarity Xiaoyang Tan, Member Songcan Chen, Zhi-Hua Zhou, Senior Member, Jun Liu

6. Film Colorization, Using Artificial Neural Networks and Laws Filters Mohammad Reza Lavvafi Department Computer, Islamic Azad University of Mahallat Mahallat, Arak, Iran S. Amirhassan Monadjemi and Payman Moallem Department of Computer Engineering, Department of Electrical Engineering Faculty of Engineering, University of Isfahan

7. Reconstruction and recognition of face and digit images using autoencoders Chun Chet Tan • C. Eswaran

8. A Neural Network-Based Intelligent Image Target Identification Method And Its Performance Analysis Xiaofang Li 1, Yanhong Sun1,Ming Tang2, Xijun Yan1, Yanping Kang1 1College of Computer and Information Engineering Hohai University Nanjing,China Dept. of Information Technology Communication University of China, Nanjing

9. Image Compression using Multilayer Feed Forward Artificial Neural Network and DCT Fatima B. Ibrahim Information and communication engineering, Baghdad University, Baghdad, Iraq

10. Cerebrovascular Accident Attack Classification Using Multilayer Feed Forward Artificial Neural Network with Back Propagation Error 1Olatubosun Olabode and 2Bola Titilayo Olabode 1Department of Computer Science, Federal Universityof Technology, Akure, Nigeria 2Department of Mathematical Sciences, Olabodebola Federal University of Technology, Akure, Nigeria

11. Appearance-based face detection with artificial neural networks 1 Ioanna-Ourania Stathopoulou and George A. Tsihrintzis University of Piraeus, Department of Informatics, Piraeus 185 34, Greece





P. Ajith, B. Tejaswi, M.S.S.Sai

Paper Title:

Rule Mining Framework for Students Performance Evaluation

Abstract: Academic Data Mining used many techniques such as Decision Trees, Neural Networks, Naïve Bayes, K- Nearest neighbor, and many others. Using these techniques many kinds of knowledge can be discovered such as association rules, classifications and clustering. The discovered knowledge can be used for prediction and analysis purposes of student patterns. Prior approaches used decision tree classifications optimized with ID3 algorithms to obtain such patterns. Among sets of items in transaction databases, Association Rules aims at discovering implicative tendencies that can be valuable information for the decision-maker which is absent in tree based classifications. So we propose a new interactive approach to prune and filter discovered rules. First, we propose to integrate user knowledge in the post processing task. Second, we propose a Rule Schema formalism extending the specifications to obtain association rules from knowledge base. Furthermore, an interactive framework is designed to assist the user throughout the analyzing task. Applying our new approach to discover the likelihood of students deviations / requiring special attention is organized and efficient providing more insight by considering more information. Compared to tree based classifications the results are better to understand and can be applied to real time use. An implementation of the proposed system validates our claim.

Association Rules, Knowledge base, Prediction, and Rule Schema.


1. Al-Radaideh, Q., Al-Shawakfa, E. and Al-Najjar, M. (2006) ‘Mining Student Data Using Decision Trees’, The 2006 International Arab Conference on Information Technology (ACIT’2006) – Conference Proceedings.
2. Ayesha, S. , Mustafa, T. , Sattar, A. and Khan, I. (2010) ‘Data Mining Model for Higher Education System’, European Journal of Scientific Research, vol. 43, no. 1, pp. 24-29.

3. Baradwaj, B. and Pal, S. (2011) ‘Mining Educational Data to Analyze Student s’ Performance’, International Journal of Advanced Computer Science and Applications, vol. 2, no. 6, pp. 63-69.

4. Chandra, E. and Nandhini, K. (2010) ‘Knowledge Mining from Student Data’, European Journal of Scientific Research, vol. 47, no. 1, pp. 156-163.

5. El-Halees, A. (2008) ‘Mining Students Data to Analyze Learning Behavior: A Case Study’, The 2008 international Arab Conference of Information Technology (ACIT2008) – Conference Proceedings, University of Sfax, Tunisia, Dec 15- 18.

6. Romero, C. and Ventura, S. (2007) ‘Educational data Mining: A Survey from 1995 to 2005’, Expert Systems with Applications (33), pp. 135-146.

7. Shannaq, B. , Rafael, Y. and Alexandro, V. (2010) ‘Student Relationship in Higher Education Using Data Mining Techniques’, Global Journal of Computer Science and Technology, vol. 10, no. 11, pp. 54-59.

8. S. T. Hijazi, and R. S. M. M. Naqvi, “Factors affecting students performance: A Case of Private Colleges”, Bangladesh e-Journal of Sociology, Vol. 3, No. 1, 2006.

9. U. K. Pandey, and S. Pal, “A Data mining view on class room teaching language”, (IJCSI) International Journal of Computer Science Issue, Vol. 8, Issue 2, pp. 277-282, ISSN:1694-0814, 2011.

10. Shaeela Ayesha, Tasleem Mustafa, Ahsan Raza Sattar, M. Inayat Khan, “Data mining model for higher education system”, Europen Journal of Scientific Research, Vol.43, No.1, pp.24-29, 2010.






T. Kalai Chelvi, P.Rangarajan

Paper Title:

Criterion based Two Dimensional Protein Folding Using Extended GA

Abstract: In the dynamite field of biological and protein research, the protein fold recognition for long pattern protein sequences is a great confrontation for many years. With that consideration, this paper contributes to the protein folding research field and presents a novel procedure for mapping appropriate protein structure to its correct 2D fold by a concrete model using swarm intelligence. Moreover, the model incorporates Extended Genetic Algorithm (EGA) with concealed Markov model (CMM) for effectively folding the protein sequences that are having long chain lengths. The protein sequences are preprocessed, classified and then, analyzed with some parameters (criterion) such as fitness, similarity and sequence gaps for optimal formation of protein structures. Fitness correlation is evaluated for the determination of bonding strength of molecules, thereby involves in efficient fold recognition task. Experimental results have shown that the proposed method is more adept in 2D protein folding and outperforms the existing algorithms.

classification, CMM, criterion analysis, EGA, protein folding, sequence gaps


1. Yudong Zhang, Lenan Wu, Yuankai Huo and Shuihua Wang, “Chaotic Clonal Genetic Algorithm for Protein folding model,” In the Proceedings of International Conference on Computer Application and System Modeling, 2010, Vol. 3, pp. 120-124.
2. Yudong Zhang and Lenan Wu, “Bacterial Chemotaxis Optimization for Protein Folding Model,” In the Proceedings of Fifth International Conference on Natural Computation, 2009, Vol. 4, pp. 159-162.

3. Md. Tamjidul Hoque, Madhu Chetty and Laurence S Dooley, “A New Guided Genetic Algorithm for 2D Hydrophobic-Hydrophilic Model to Predict Protein Folding,” In the Proceedings of Congress on Evolutionary Computation, 2005, Vol. 1, pp. 259-266.

4. D. Bouchaffra and J. Tan, “Protein Fold Recognition using a Structural Hidden Markov Model,” In the Proceedings of 18th International Conference on Pattern Recognition, 2006, Vol. 3, pp. 186-189.

5. Piotr Berman and Bhaskar DasGupta, “The Inverse Protein Folding Problem on 2D and 3D Lattices,” Journal on Discrete Applied Mathematics, 2007, Vol. 155, Issue. 6-7, pp. 719-732.

6. Guang Song and Nancy M. Amato, “A Motion Planning Approach to Folding: From Paper Craft to Protein Folding,” IEEE Transactions On Robotics And Automation, 2004, Vol. 20, Issue. 1, pp. 60-71.

7. Md Tamjidul Hoque, Madhu Chetty, Andrew Lewis, and Abdul Sattar, “Twin-Removal in Genetic Algorithms for Protein Structure Prediction using Low Resolution Model,” IEEE/ACM Transactions On Computational Biology And Bioinformatics, 2011, Vol. 8, Issue. 1, pp. 234-245.

8. R. F. Mansour, “Applying an Evolutionary Algorithm for Protein Structure Prediction,” American Journal of Bioinformatics Research, 2011, Vol. 1, Issue. 1, pp. 18-23.

9. Yudong Zhang, LenanWu, “Artificial Bee Colony for Two Dimensional Protein Folding,” Advances in Electrical Engineering Systems, Vol. 1, Issue. 1, pp. 19-23.

10. Md Tamjidul Hoque, Madhu Chetty and Abdul Sattur, “Protein folding prediction in 3D FCC HP lattice model using genetic algorithm,” In the Proceedings of IEEE Conference on Evolutionary Computation, 2007, pp. 4138 – 4145.

11. Trent Higgs, Bela Stantic, Md Tamjidul Hoque, and Abdul Sattar, “Hydrophobic-Hydrophilic Forces and their Effects on Protein Structural Similarity,” Supplementary Proceedings [of the] Third IAPR International Conference on Pattern Recognition in Bioinformatics, 2008.

12. Md Tamjidul Hoque, Madhu Chetty, Andrew Lewis, Abdul Sattar and Vicky M Avery, “DFS generated pathways in GA crossover for protein structure prediction,” In ScienceDirect Journal of Neurocomputing, 2010, Vol. 73, Issue. 13-15, pp. 2308-2316.

13. Heitor Silv´erio Lopes, “Evolutionary Algorithms for the Protein Folding Problem: A Review and Current Trends,” Journal on Computational Intelligence in Biomedicine and Bioinformatics, 2008, Vol. 151, pp. 297-315.

14. Luca Bortolussi, Alessandro Dal Palu, Agostino Dovier and Federico Fogolari, “Protein Folding Simulation in CCP,” In the Proceedings of 20th International Conference on Logical Programming, 2004, Vol. 20, pp. 1-19.

15. Benhui CHEN, Long LI and Jinglu HU, “A Novel EDAs Based Method for HP Model Protein Folding,” IEEE Congress on Evolutionary Computation, 2009, pp. 309-315.

16. Swagatam Das, Ajith Abraham and Amit Konar, “Swarm Intelligence Algorithms in Bioinformatics,” Journal of Computational Intelligence in Bioinformatics, 2008, Vol. 94, pp. 113-147.

17. Jan Kubelka, James Hofrichter and William A Eaton, “The protein folding ‘speed limit’,” Journal of Current Opinion in Structural Biology, 2004, Vol. 14, Issue. 1, February 2004, pp. 76-88.

18. Arvind Ramanathan and Christopher J. Langmead, “Dynamic Invariants in Protein Folding Pathways Revealed by Tensor Analysis,” In the Proceedings of 8th Annual International Conference on Computational Systems Bioinformatics, 2009.

19. Tamjidul Hoque, Madhu Chetty and Abdul Sattar, “Extended HP Model for Protein Structure Prediction,” Journal of Computational Biology, 2009, Vol. 16, Issue. 1, Pp. 85–103.

20. Shawna Thomas Nancy M. Amato, “Parallel Protein Folding with STAPL,” Journal of Concurrency and Computation: Practice and Experience, 2005, Vol. 17, Issue. 14.

21. Torsten Thalheim, Daniel Merkle, Martin Middendorf, “A Hybrid Population based ACO Algorithm for Protein Folding,” Proceedings of the International MultiConference of Engineers and Computer Scientists, 2008, Vol. 1, pp. 19-21.

22. Julia Hockenmaier, Aravind K. Joshi and Ken A. Dill, “Routes Are Trees: The Parsing Perspective on Protein Folding,” Journal of Proteins: Structure, Function, and Bioinformatics, 2006, Vol. 66, Issue. 1, pp. 1-15.

23. L. Lo Conte, B. Ailey, T. hubbard, S. Brenner, A. G. Murzin, and C. Chothia, “Scop: a structural classification of proteins database,” Journal of Nucleic Acids Research, 2000, Vol. 28, pp. 257-259.






Tahere Panahi, Saideh Naderi, Tahere Heidari, Elham Zeidabadi nejad , Peiman Keshavarzian

Paper Title:

New Ternary Logic Subtractor Using Carbon Nanotube Field-Effect Transistors

Abstract: In this paper, we present a new Ternary logic Subtractor (TLS) that is implemented by CNTFET. In addition, we investigate the design of two Novel subtractors based on the proposed TLS. Ternary results are better than the Binary ones. Results show large decrements in delay time. Further, the second presented circuit with its Simulation results has demonstrated significant development in speed, area and power consumption. In the past extensive design techniques, Multiple-Valued Logic (MVL) circuits (especially ternary logic inverters) have been proposed by CMOS Technology. Here, the new TLS based on CNTFETs is presented, and wide simulation results have been done by HSPICE.

CNTFET, Subtractor, Multiple-Valued Logic.


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26. Y. Ohno, S. Kishimoto, T. Mizutani, T. Okazaki, H. Shinohara,2004 .“Chirality assignment of individual single-walled carbon nanotubes in carbon nanotube field-effect transistors by micro photo current spectroscopy”. Applied Physics Letters, Vol. 84, no.8.






Om Prakash Sharma, M. K. Ghose, Krishna Bikram Shah, Benoy Kumar Thakur

Paper Title:

Recent Trends and Tools for Feature Extraction in OCR Technology

Abstract: This paper presents a recent trends and tools used for feature extraction that helps in efficient classification of the handwritten alphabets. Numerous models of feature extraction have been defined by different researchers in their respective dissertation. It is found that the use of Euler Number in addition to zoning increases the speed and the accuracy of the classifier as it reduces the search space by dividing the character set into three groups.

Handwritten Character Recognition, Feature Extraction, Zoning, Euler Number, Classification.


1. J Pradeep, E Shrinivasan and S.Himavathi, “Diagonal Based Feature Extraction for Handwritten Alphabets Recognition System Using Neural Network”, International Journal of Computer Science & Information Technology (IJCSIT), vol . 3, No 1, Feb 2011.
2. M. Alata — M. Al-Shabi, “ Text Detection And Character Recognition Using Fuzzy Image Processing”, Journal of Electrical Engineering, vol. 57, no. 5, 2006, 258–267

3. R. Plamondon and S. N. Srihari, “On-line and off- line handwritten character recognition: A comprehensive survey,”IEEE. Transactions on Pattern Analysis and Machine Intelligence, vol. 22, no. 1, pp. 63-84, 2000.

4. N. Arica and F. Yarman-Vural, “An Overview of Character Recognition Focused on Off-line Handwriting”, IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 2001, 31(2), pp. 216 – 233.

5. U. Bhattacharya, and B. B. Chaudhuri, “Handwritten numeral databases of Indian scripts and multistage recognition of mixed numerals,” IEEE Transaction on Pattern analysis and machine intelligence, vol.31, No.3, pp.444-457, 2009.

6. U. Pal, T. Wakabayashi and F. Kimura, “Handwritten numeral recognition of six popular scripts,” Ninth International conference on Document Analysis and Recognition ICDAR 07, Vol.2, pp.749-753, 2007.

7. Devinder Singh and Baljit Singh Khehra, “Digit Recognition System Using Back Propagation Neural Network”, International Journal of Computer Science and Communication Vol. 2, No. 1, January-June 2011, pp. 197-205

8. VENTZAS, DIMITRIOS 1, NTOGAS, NIKOLAOS , “A BINARIZATION ALGORITHM FOR HISTORICAL MANUSCRIPTS”, 12th WSEAS International conference on Communications, Heraklion, Greece, July 23-25, 2008.

9. Bindu Philip, R. D. Sudhaker Samuel and C. R. Venugopal, Member, IACSIT, “A Novel Segmentation Technique for Printed Malayalam Characters”, International Journal of Computer and Electrical Engineering, Vol. 2, No. 4, August, 2010 1793-8163 Printed Malayalam Characters.

10. Anil Kumar Jain and Torfinn Taxt, “Feature extraction Methods for Character Recognition- A Survey”, Pattern Recognition, Vol.29, No.4, pp. 641-662, 1996.

11. S.V. Rajashekararadhya, and P.VanajaRanjan, “Efficient zone based feature extraction algorithm for handwritten numeral recognition of four popular south-Indian scripts,” Journal of Theoretical and Applied Information Technology, JATIT vol.4, no.12, pp.1171-1181, 2008.

12. Anita Pal & Dayashankar Singh, “ Handwritten English Character Recognition Using Neural Network”, International Journal of Computer Science & Communication”, Vol. 1, No.2, July-December 2010, pp. 141-144

13. G. Vamvakas, B. Gatos, I. Pratikakis, N. Stamatopoulos, A. Roniotis, S.J. Perantonis, “Hybrid Off-Line OCR for Isolated Handwritten Greek Characters”, The Fourth IASTED International Conference on Signal Processing, Pattern Recognition and Applications (SPPRA’07), pp. 197-202, Innsbruck, Austria, February 2007.

14. G. Vamvakas, B. Gatos, S. Petridis and N. Stamatopoulos, ”An Efficient Feature Extraction and Dimensionality Reduction Scheme for Isolated Greek Handwritten Character Recognition”, Proceedings of the 9th International Conference on Document Analysis and Recognition, Curitiba, Brazil, 2007, pp. 1073-1077.

15. Dinesh Acharya U, N V Subba Reddy and Krishnamurthy, “Isolated handwritten Kannada numeral recognition using structural feature and K-means cluster,” IISN-2007, pp-125 -129.

16. M Arijit Bishnu, Bhargab B. Bhattacharya, Malay K. Kundu b C.A. Murthy, Tinku Acharya, “A pipeline architecture for computing the Euler number of a binary image”, Journal of Systems Architecture 51 (2005) 470–487.

17. Om Prakash Sharma, M. K. Ghose, Krishna Bikram Shah, “An Improved Zone Based Hybrid Feature Extraction Model using Euler Number”, Innternationa Journal on Soft Computing and Engineering (IJSCE’12), ISSN 2231-2307, Volume -II, Issue- II, Article no-96, pp. 154-158.

18. Bishnu Chaulagain, Brizika Bantawa Rai, Sharad Kumar Raya, “Final Report on Nepali Optical Character Recognition NepaliOCR”, Submitted On July 29, 2009.

19. 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






Kapil Bhagchandani, Yatendra Mohan Sharma

Paper Title:

Exploration of VANET Mobility Models with New Cluster Based Routing Protocol

Abstract: Vehicular ad-hoc network (VANET) is high dynamic wheeled networks in which moving vehicles that can move in any direction at varying speed are behave as network nodes and router for data exchange. The frequently changes in topology and mobility pattern in VANET pose many unique networking research challenges which make crucial the designing of an new suit of efficient routing protocol for VANET. Recently, several approaches proposed by some authors in order to overcome the problem of discovering and maintaining the efficient and effective route for the data transmission over the wireless network but still there is scope of modernization. In this paper we are presenting cluster based routing approach for VANET and compare their performances with existing routing protocols. This new routing approach will have an aim of increasing the overall network throughput and minimize end to end delay. This paper, considering the mobility models like: random way point mobility model and group mobility model. Simulation studies are conducted using NS2.

VANET, Clustering, Routing, Mobility, AODV, DSR.


1. Hang Dok, Huirong Fu, Ruben Echevarria, and Hesiri Weerasinghe, “Privacy Issues of Vehicular Ad-Hoc Networks”, International Journal of Future Generation Communication and Networking Vol. 3, No. 1, March , 2010
2. Yun-Wei Lin, Yuh-Shyan Chen, And Sing-Ling Lee, “ Routing Protocols in Vehicular Ad Hoc Networks: A Survey and Future Perspectives”, JISE-2009-1

3. Xiong Wei , Li Qing-Quan, “Performance Evaluation Of Data Disseminations For Vehicular Ad Hoc Networks In Highway Scenarios”, The International Archives of
the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B1. Beijing 2008

4. D.Rajini Girinath, S.Selvan, “A Novel Cluster based Routing Algorithm for Hybrid Mobility Model in VANET” International Journal of Computer Applications (0975 – 8887) Volume 1 – No. 15, 2010

5. Martin Koubek, Olivia Brickley, Susan Rea, Dirk Pesch, “ Application Driven Routing for Vehicular Ad Hoc Networks – A Necessity”, ISVCS 2008, July 22 – 24, 2008, Dublin, Ireland. ISBN 978-963-9799-27-1

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8. C.E. Perkins and E.M. Royer, “Ad hoc on demand distance vector (AODV) routing,” in 2nd IEEE Workshop on Mobile Computing Systems and Applications, Feb. 1999.

9. James Bernsen, D. Mnivannan, “Unicast routing protocols for vehicular ad hoc networks: A critical comparison and classification”, in journal of Pervasive and Mobile Computing 5 (2009) 1-18

10. Jagadeesh Kakarla, S Siva Sathya, B Govinda Laxmi, Ramesh Babu B.” A Survey on Routing Protocols and its Issues in VANET” International Journal of Computer Applications (0975 – 8887) Volume 28– No.4, August 2011

11. Uma Nagaraj, Dr. M. U. Kharat, Poonam Dhamal “Study of Various Routing Protocols in VANET” IJCST Vol. 2, Issue 4, Oct . – Dec. 2011

12. Rakesh Kumar, Mayank Dave “ A Comparative Study of Various Routing Protocols in VANET” IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 4, No 1, July 2011

13. Yatendra Mohan Sharma, Dr. Saurabh Mukherjee “ A Contemporary Proportional Exploration of Numerous Routing Protocol in VANET” International Journal of Computer Applications (0975 – 8887) Volume 50– No.21, July 2012

14. Zhan Haawei and Zhou Yun.Comparison and analysis AODV and OLSR Routing Protocols in Ad Hoc Network, 2008, IEEE.

15. D. Johnson, B.D.A. Maltz, and Y.C.Hu, “The Dynamic Source Routing Protocol for Mobile Ad Hoc Networks (DSR)”, draft-ietf-manet-dsr-10.txt, 2004.

16. C.E.Perkins and E. M. Royer. Ad-Hoc On Demand Distance Vector Routing, Proceedings of the 2nd IEEE Workshop on Mobile Computing Systems and Applications (WMCSA), pp. 90-100, 1999.

17. J. Blum,”Mobility management in IVC networks,” 2003.

18. R. A. Santos, “Performance evaluation of routing protocols in vehicular ad hoc networks,” 2005.

19. Tao Song,” A Cluster-Based Directional Routing Protocol in VANET”.

20. Ajay Kumar, Ashwani Kumar Singla “Performance evaluation of Manet routing protocols on the basis of tcp traffic pattern” International Journal of Information Technology Convergence and Services (IJITCS) Vol.1, No.5, October 2011

21. S H Manjula, C N Abhilash, Shaila K, K R Venugopal, L M Patnaik, “Performance of AODV Routing Protocol using group and entity Mobility Models in Wireless Sensor Networks,” Proceedings of the International Multi Conference of Engineers and Computer Scientists (IMECS 2008), vol. 2, 19-21 March 2008, Hong Kong, pp. 1212-1217






Manas Kumar Parai, Banasree Das, Gautam Das

Paper Title:

An Overview of Microcontroller Unit: From Proper Selection to Specific Application

Abstract: It is very difficult to choose a particular Microcontroller for specific application. Success or failure of any project largely depends on proper selection of the Microcontroller Unit. In this paper a brief overview of the unit is described as far as the right selection for particular application is concerned. So many manufactures are producing microcontroller in bulk amount. Comparison is based on products of few leading manufactures. System requirements, availability, performance, size, power dissipation, flexibility, Reliability, Maintainability, Environmental constraints, software support, correctness, safety, Cost, manufacturer’s history and track records are the vital factors to be considered whenever a system is to be implemented using a microcontroller which is the heart of the device. In this paper several factors are focused and follow up of those factors leads to success of the project.

Assembler, Compiler, Debugger, IDE, In-System-Programming, Microcontroller, On-Chip ROM.


1. M. A. Mazidi, J.G. Mazidi, R.. D. Mckinlay, “The 8051 Microcontroller and Embedded Systems: using Assembly and C”, Pearson Education, Inc., 2nd edition 1999.
2. Takawira F., Dawoud D.S., “Selecting the Right Microcontroller Unit”, Zimb. J. Sci. Technol., Vol. 4, no. 1, p 39-46

3. Gonzales D.R., “Understanding the Key Architectural Features of a Microcontroller” , Available at : http://www.dedicatedsystem.com

4. Gajski, Daniel D., Principles of Digital Design. Englewood Cliffs, NJ: Prentice-Hall, 1997.

5. “Selecting the Microcontroller Unit”, Freescale Semiconductor, Application Note Available at: http://www.freescale.com/files/microcontrollers/doc/app_note/AN1057.pdf

6. Technical Guide to Microcontroller Selection, “Microcontrollers: options and trends in today’s applications”, Wednesday, January 25, 2006 Available at website: http://fr.farnell.com/images/en/ede/pdf/micro_tech.pdf

7. Types of Microcontroller: Application note available at: http://my.safaribooksonline.com/book/electrical-engineering/semiconductor-technology/9788131759905/types-selection-and-applications-of-microcontrollers/ch001#X2ludGVybmFsX0h0bWxWaWV3P3htbGlkPTk3ODgxMzE3

8. Selection of a microcontroller: http://my.safaribooksonline.com/book/electrical-engineering/semiconductor-technology/9788131759905/types-selection-and-applications-of-microcontrollers/ch001#X2ludGVybmFsX0h0bWxWaWV3P3htbGlkPTk3ODgxMzE3NTk5MDUlM

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Alpa K. Oza

Paper Title:

Data Visualization for University Research Papers

Abstract: Quite many publications are being published either in form of Theses, essays or Research papers at various levels of scientists, research scholars or Ph.D students. This is a big jargon. They are required to be segregated under various Topics. Topic modeling is a set of tool that provides a solution. Topic modeling discovers a hidden thematic structure in collection of documents. Topic models are high level statistical tools. A user must scrutinize numerical distribution to understand and explore their results. Latent Dirichlet Allocation LDA has been used to generate automatically topics of text corpora and also to subdivide the corpus words among those topics. Topic models also fall in the same line of functioning. This model (topic model) has proven remarkably powerful for information retrieval tasks. Information visualization technologies when used in conjunction with data mining and text analyses tools can be of great value for various types of tasks. For this reason various visualizations have been designed. Quite laborious work has been done and still being labored at various levels of scholars. Here our aim is to present a brief description to the topical method of visualization under data mining.

Topic Models, Text Visualization, Visual analysis, Text, Statistical model


1. J. Chuang, C. D. Manning, and J. Heer, “Interpertation and Trust: Designing model-driven visualizations for text analysis”, In CHI, 2012.
2. J. Chuang, C. D. Manning, and J. Heer, “Termite: Visualization Techniques for assessing textual topic models”, In ACM, 2012.

3. Allison J. B. Chaney and D. M. Blei. “Visualizing Topic Models”, In AAAI, 2012.

4. Y. Chen, L. Wang, M. Dong and J. Hua. “Exemplar-based Visualization of Large Document Corpus”, 2009. . IEEE Transactions on Visualization and Computer Graphics 15(6): 1161-1168.

5. N. Cao, J. Sun, Y-R. Lin, D. Gotz, S. Liu and H. Ou. “FacetAtlas: Multifaceted Visualization for Rich Text Corpora”, 2010. IEEE Transactions on Visualization and Computer Graphics 16(6): 1172-1181.

6. D. M. Blei, A. Y. Ng and M. I. Jordan. “Latent Dirichlet Allocation”, J Machine Learning Research, 3:993-1022, 2003.

7. L. Alsumait, D. Barbara, J. Gentle and C. Domeniconi. “Topic Significant ranking of LDA generative models”, In ECML, 2009.

8. J. Chang, J. Bod-Graber, C. Wang, S. Gerrish and D. M. Blei. “Reading tes leaves: How Humans interpret topic models”, In NIPS, pages 288-296, 2009.






N. Gwangwava, S. Mhlanga and W. Goriwondo

Paper Title:

Implementation Of A Computerized Balanced Scorecard (BSC) System In A Manufacturing Organisation In Zimbabwe

Abstract: This modern era’s high technological improvements present manufacturers and other organizations with a plethora of Management Information Systems (MISs) which makes them face challenges when choosing a corporate information system. High initial investment in setting up the information systems make it very difficult for companies to adopt new systems as they come into market before realizing a reasonable return from the previous system. In line with these concerns, a methodology for building a Balanced Scorecard module as a strategic management platform that can be integrated smoothly into already existing information system such as MRP/ERP is presented. The paper uses a case study of a manufacturing company based in Zimbabwe. Various manufacturing based metrics are reviewed with the main intent of showing how these can be tracked in a computerized platform. Sample data extracted from the production system is used to test the built system. The paper shows a methodology for software design, setting up and adopting a BSC system. The proposed approach is used to design a computerized BSC system for the case study company, which incorporates a BSC dashboard for the four main perspectives derived from various operational metrics.

Balanced Scorecard (BSC), Metrics, MRP/ERP, Management Information System (MIS).


1. K. J. Fernandes, V. Raja and A. Whalley, Lessons from Implementing the balances scorecard in a small and medium size manufacturing organisation, Technovation, 26, 2006, pp 623-634
2. L. Garvin, A. Henrik and C. Ian, Balanced scorecard implementation in SMEs: reflection in literature and practice. 2GC working paper, 2006, 2GC Limited.

3. R. S. Kaplan and D. P. Norton, Translating strategy into action: the balanced scorecard, Harvard Business School press, 2000.

4. M. Torbacka and W. Torbacki, BSC methodology for determining strategy of manufacturing enterprises of SME sector, Journal of Achievements in
Materials and Manufacturing Engineering, Vol 23 Issue 2, 2007, pp 99-102.

5. M. S. Seyedhosseini and A. Soloukdar, Modelling for World Class Manufacturing at Iran Khodro Company: A dynamic system approach, American Journal of Scientific Research, Issue 26 (2011), pp.48-58.- available: http://www.eurojournals.com/ajsr.htm

6. CIMA Technical Briefing, Developing and Promoting Strategy, 2002, CIMA Publishing.

7. A. Grobler, An Exploratory System Dynamics model of strategic capabilities in Manufacturing, Journal of Manufacturing Technology Management, 21(6): 2010, pp 651-669.

8. P R. Niven, Balanced Scorecard Step-By-Step: Maximizing Performance and Maintaining Results, Second Edition, 2006, Wiley.

9. R. S. Kaplan, and D. P. Norton, Strategy Maps: Converting Intangible Assets into Tangible Outcomes. Harvard Business School Press, 2004.






Le Hoang Son, Nguyen Dinh Hoa

Paper Title:

A Novel Stochastic-Based Algorithm for Terrain Splitting Optimization Problem

Abstract: This paper deals with the problem of displaying large Digital Elevation Model data in 3D GIS. Current approaches relate to the splitting algorithms by 2D Polygonal Vector Data such as Particle Swarm Optimization (PSO-TSA) and Genetic Algorithm (GA-TSA). We will, herein, present another method based on stochastic optimization for the considered problem. It also employs some ideas of Wife-Selection scenario and Stick Procedure. The new method allows us to quickly find the optimal saving threshold. The comparison with the state-of-the-art method will be made to verify the efficiency of the proposed method.

Digital Elevation Model, Geographic Information Systems, Stochastic Optimization, Terrain Splitting.


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2. Holland, J. H., “Adaptation in natural and artificial system”. Ann Arbor: The University of Michigan Press, 1975.

3. Kennedy, J., Eberhart, R. C., “Particle swarm optimization”, In: Proceedings of IEEE International Conference on Neural Networks, Piscataway, NJ, 1995, pp. 1942-1948.

4. Son, L. H., Thong, P. H., Linh, N. D., Hoa, N. D., Cuong, T. C., “Some Results of 3D Terrain Splitting By 2D Polygonal Vector Data”, International Journal of Machine Learning and Computing, vol.1, no. 3, 2011, pp. 253-262.

5. Son, L. H., Thong, P. H., Linh, N. D., Cuong, T. C., Hoa, N. D., “Developing JSG Framework and Applications in COMGIS Project”, International Journal of Computer Information Systems and Industrial Management Applications, vol. 3, 2011, pp. 108-118.

6. Thien, N. D., Son. L. H., Lanzi, P. L., Thong, P. H., ”Heuristic Optimization Algorithms For Terrain Splitting and Mapping Problem”, International Journal of Engineering and Technology, vol. 3, no. 4, 2011, pp. 376-383.






T.Revathi, P.Sumathi

Paper Title:

Distributed Data Mining based on Random Projection with Optimal Communication

Abstract: Distributed data mining discovers hidden useful information from data sources distributed among several sites. Privacy of participating sites becomes great concern and sensitive information pertaining to the individual sites needs high protection when data mining occurs among several sites. Different approaches for mining data securely in a distributed environment have been proposed but in the existing approaches, collusion among the participating sites may reveal sensitive information about other participating sites and they suffer from the intended purposes of maintaining privacy of the individual participating sites, reducing computational complexity and minimizing communication overhead. The proposed method finds global frequent itemsets in a distributed environment with minimal communication among sites and ensures higher degree of privacy with randomized site selection. The experimental analysis shows that proposed method generates global frequent itemsets among colluded sites without affecting mining performance and confirms optimal communication among sites.

Distributed data mining, privacy, secure multiparty computation, frequent itemsets.


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Amitha P L, Geethu Joy, Geethu S Pillai, Tharakrishnan L, Soman K P

Paper Title:

Innovative Use of What if Analysis for Visualization

Abstract: The novelty of this paper is aimed at simplifying the tasks in Spreadsheet using a feature called what if analysis, which fires up the performance of the task we are working on. The use of spreadsheet helped us save time, perform many operations such as sorting, searching, classifying and comparing easily and to solve a problem without any programming knowledge. What if or sensitivity analysis is one of the most powerful and valuable concepts in Spreadsheet, the potential of which is not well exploited. The advantage of what if analysis is that if we show one computation in excel, the remaining part of the process will be computed by its own for a given range of variable values. It can be used to solve many problems other than the conventional managerial applications. Two Dimensional function evaluation and graphing, creating Pascal triangles, enumerating Pythagorean triplets in a given range, error function evaluation are some of the real applications. These types of applications can be exploited to enhance computational thinking of children in high schools. Computational thinking brings about a neoteric approach in problem-solving and model simulation.

Computational Thinking, Excel Computation, What if Analysis.


1. Aravind H, C Rajgopal, Soman K P, “A Simple Approach to Clustering in Excel”, International Journal of Computer Applications, Volume 11- No.7, December 2010.
2. Soman K P, Manu Unni V G, Praveen Krishnan, Sowmya V,” Enhancing Computational Thinking with Spreadsheet and Fractal Geometry: Part 1”, International Journal of Computer Applications 55(14):1-8, October 2012.

3. K P Soman, Manu Unni V G, Praveen Krishnan, Sowmya V,” Enhancing Computational Thinking with Spreadsheet and Fractal Geometry: Part 2- Root-finding using Newton Method and Creation of Newton Fractals”, International Journal of Computer Applications, 55(14):9- 15, October 2012.

4. K P Soman, Manu Unni V G, Praveen Krishnan, Sowmya V,” Enhancing Computational Thinking with Spreadsheet and Fractal Geometry: Part 3- Mandelbrot and Julia Set “, International Journal of Computer Applications, 55(14):16- 23, October 2012.

5. K P Soman, Manu Unni V G, Praveen Krishnan, Sowmya V,” Enhancing Computational Thinking with Spreadsheet and Fractal Geometry: Part 4- Plant Growth modeling and Space Filling Curves “, International Journal of Computer Applications, 55(14):24- 29, October 2012.

6. Anand R, Pinchu Prabha, Sikha O K, Suchithra M, Sukanya P, Sowmya V, Soman K P ,” Visualization Of OFDM Using Microsoft Excel Spreadsheet In Linear Algebra Perspective”, International Conference on Advances Computing and Communication(ICACC),pg-58-64,Aug 2012.

7. J M Wing,” Computational Thinking” , CACM viewpoint, vol. 49 no. 3, March 2006, pp. 33-35.

8. Ozar, Mirac,” Spreadsheets in Education”, Hacettepe Journal of Education, No.13, pp.81-83.

9. S A OKE,”Spreadsheet Applications in Engineering Education: A Review”, International. Journal of Engineering Education. Vol. 20, No. 6, pp. 893-901, 2004.

10. Paul Cornell, “Synthetic Beginning Excel What-If Data Analysis Tools: Getting Started with Goal Seek, Data Tables, Scenarios, and Solver” Apress; 1 edition, December 13, 2005.

11. K P Soman, Sachin Kumar S, Soumya V, Shajeesh K U,” Computational Thinking with Spreadsheet: Convolution, High-Precision Computing and Filtering of Signals and Images”, International Journal of Computer Applications 60(19):1-7, December 2012.

12. Committee for the Workshops on Computational Thinking; National Research Council, “Report of a Workshop Pedagogical Aspects of Computational Thinking”, Washington DC, 2011.

13. Pinchu Prabha, Sikha O K, Suchithra M, Sukanya P, Sowmya V, Soman K P” Computation Of Continuous Wavelet Transform Using Microsoft Excel Spreadsheet “, International Conference on Advances in Computing and Communication(ICACC),pg-73-77, Aug 2012.

14. Indukala P K, Lakshmi K, Sowmya V, Soman K P,” Implementation Of L1 Magic And One Bit Compressed Sensing Based On Linear Programming Using Excel”, International Conference on Advances in Computing and Communication(ICACC),pg-69-72,Aug 2012.






Hari Prasada Rao Pydi, Balamurugan Adhithan, A.Syed Bava Bakrudeen

Paper Title:

Microstructure Exploration of the Aluminum-Tungsten Carbide Composite with different Manufacturing circumstances

Abstract: In the last decade, as demand for high quality materials are increased, the development of lightweight aluminum (Al) also increased especially in aerospace and automotive industries. It has been well known that Al based metal matrix composites (MMCs) offers a very low thermal expansion coefficient, high specific strengths, wear and heat resistance as compared to conventional Al alloys. In order to combine all these properties, MMCs have become a very attractive method for various industrial applications. The interest in Tungsten Carbide (WC) as reinforcements for aluminum (Al) has been growing considerably. Efforts have been largely focused on investigating their contribution to the enhancement of the mechanical performance of the composites. The uniform dispersion of Tungsten Carbide in the Al matrix has been identified as being critical to the pursuit of enhanced properties. In this present research paper emphasis, the effect of Tungsten Carbide content on the Physical properties of the composites like SEM, XRD was investigated. The improvement of physical properties for composites of Al/WC has been compared with pure aluminum.

MMC, SEM, Tungsten Carbide, XR.D.


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Fayçal Messaoudi, Mimoun Moussaoui, Ahmed Bouchboua, Aziz Derouich

Paper Title:

Modeling Approach to a Learner Based on Ontology

Abstract: A new generation of advanced systems of learning has to integrate new educational approach giving to the learner an active role to learn and build his knowledge and so allowing to integrate a vision more centered on the learner . The systems adaptive hypermedia in the field of distance education (e-learning) propose solutions of these problems. The objective of these systems is to adapt the presentation of the knowledge and to help the learner to navigate through the graph consisted by all the pages and the links.

Modeling teaching, ontology, model of the domain, CEHL.


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6. A. Derouich, M. Karim, E. K. Hachem, “Automatic treatment of the learner’s productions,” International Journal of Computer Science and Network Security, Vol. 9, No. 12, pp. 96-100, 2009.

7. M. Trella, R. Conejo, D. Bueno, E. Guzmn, “An autonomous component architecture to develop WWW-ITS, Proceedings of the Workshops on Adaptive Systems for Web-Based Education, ” Malaga, 2002.

8. M. Laroussi, “Conception et réalisation d’un système didactique hypermédia adaptatif :” CAMELEON, Thèse de Doctorat, Université Manouba, Tunisie, 2001.

9. G. Webb, M. Pazzani, D. Billsus, “Machine Learning for User Modeling, User Modeling and User-Adapted Interaction,” Vol.11, pp. 19-29, 2001.

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11. A. Behaz & all, “Approche de modélisation d’un apprenant à base d’ontologie pour un hypermédia adaptatif pédagogique,” Vol.12, pp.3-4.

12. C. R. Todd, Myers-Briggs Type Indicator. The Skeptic’s Dictionary. http://skepdic.com/myersb.html. (Consulté Octobre 2008).

13. V. Psyché, O. Mendes, J.Bourdeau, “Apport de l’ingénierie ontologique aux environnements de formation à distance,” Vol 10, 2003.

14. PROTÉGÉ was developed by Stanford Center for Biomedical Informatics Research. Protege 3.4.8 released!. 12 Jan 2012






Jyoti Mahajan, Simmi Dutta

Paper Title:

COREAN: A proposed Model for Predicting Effort Estimation having Reuse

Abstract: The estimation accuracy has been focused in various formal estimation models in recent research initiatives. The formal estimation models were developed to measure lines of code and function points in the software projects but most of them failed to improve accuracy in estimation. The concept of reusability in software development in estimating effort using artificial neural network is focused in this paper. Incorporation of reusability metrics in COCOMO II may yield better results. In COCOMO II it is very difficult to find the values of size parameters. A new model called COREAN has been proposed in this paper for better effort estimation accuracy and reliability. The proposed model has focused on two components of COCOMO II. First, instead of using RUSE cost driver, three new reuse cost drivers are introduced. Second, In order to reduce the project cost, three cost drivers such as PEXE, AEXE, LTEX are combined into single cost driver Personnel Experience (PLEX). Finally, this proposed model accuracy is more improved with the help of Enhanced RPROP algorithm and simulated annealing optimization technique.

Effort Estimation, Software Reuse, COCOMO II, Artificial Neural Network, Simulated Annealing.


1. K. Molokken-Ostvold and M. Jorgensen, “A Review of Surveys on Software Effort Estimation,” Proc. 2003 ACM-IEEE Intternational Symposium on Empirical Software Eng, pp. 220-230, 2003.
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3. Chao-Jung Hsu, Nancy Urbina Rodas, Chin-Yu Huang and Kuan-Li Peng “A Study of Improving the Accuracy of Software Effort Estimation Using Linearly Weighted Combinations”, 34th Annual IEEE Computer Software & Application Conference Workshops, 2010

4. B. Boehm, B. Clark, E. Horowitz, C. Westland, R. Madachy, and R. Selby, “Cost Models for Future Software Life Cycle Processes: COCOMO 2. 0,” Annals of Software Engineering: Special Volume on Software Process and Product Measurement, Science Publishers, vol. 1, pp. 45-60, 1995.

5. Boehm, B. COCOMO II Model Definition Manual. Center for Software Engineering, University of Southern California. 1997.

6. Balda, D,. M. and D. A. Gustafson, “Cost Estimation Models for the Reuse and Prototype Software Development Life-Cycles”, ACM Sigsoft Software Engineering Notes, 15 (3), pp. 4250, 1990.

7. A.Windsor Brown url: http://csse.usc.edu/publications/TECHRPTS/KBSA_Tech_Report/app5.pdf, 1999

8. Barry Boehm, A.Winsor Brown, http://csse.usc.edu/publications/TECHRPTS/KBSA_Tech_Report/volumeI.pdf, 1999

9. Sunita Chulani, Barry Boehm “Modeling Software Defect Introduction Removal: COQUALMO (COnstructive QUALity MOdel)”, Technical Report USC-CSE-99-510, 1998

10. C.Abst, B.Boehm, E.Clark. “COCOTS: A COTS Software Integration Lifecycle Cost Model – Model Overview and Preliminary Data Collection Findings”, Technical report USC-CSE-2000-501, USC Center for Software Engineering, 2000.

11. Heiat A, “Comparison of artificial neural network and regression models for estimating software development effort,” Journal of Information and Software Technology, Volume 44, Issue 15, Pages 911-922, 2002.

12. Wittig, G., Finnie, G., “Estimating software development effort with connectionist models”, Information and Software Technology, 39 (7), 469–476, 1997

13. Karunanithi, N., D. Whitely, Y. K. Malaiya, “Using neural networks in reliability prediction”, IEEE Software, pp. 53-59, 1992.

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16. Lionel C. Briand, Sandro Morasca, and Victor R. Basili, “An Operational Process for Goal-Driven Definition of Measures”, IEEE Transactions On Software Engineering, Vol. 28, No. 12, 2002.

17. V. Basili, “Software Modeling and Measurement: The Goal/Question/Metric Paradigm” University of Maryland, Department of Computer Science, Tech. Rep. CS-TR-2956, 1992.

18. L. Briand, K. El Emam, S. Morasca, “Theoretical and Empirical Validation of Software Product Measures”, Technical Report ISERN-95-03, Fraunhofer Institute for Experimental Software Engineering, Germany, 1995.

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22. Mitat Uysal, “Estimation of the Effort Component of the Software Projects Using Simulated Annealing Algorithm”, World Academy of Science, Engineering and Technology, 2008





Garima Bhardwaj, Vasudha Vashishtha

Paper Title:

Energy – Efficient MAC Protocol (EE-MAC Protocol)

Abstract: Because of the difficulty in recharging or replacing the batteries of each node in a Wireless Sensor Network, the energy efficiency of the system is a major issue in the area of network design. Other critical parameters such as delay, adaptability to traffic conditions, scalability, system fairness, and throughput and bandwidth utilization are mostly dealt as secondary objectives. Some sensor network applications adopt IEEE 802.11-like MAC protocol, which is however, not a good solution for sensor network applications because it suffers from energy inefficiency problem. The adaptive Sensor-MAC (S-MAC) proposes enhanced schemes such as periodic sleep and overhearing avoidance to provide a better choice for different sensor network applications. In this research paper we propose an energy efficient MAC (EE-MAC) protocol, which is based on adaptive S-MAC with added transmission power control techniques. The main contribution of our work is to introduce a controlled power transmission of RTS, CTS, DATA and ACK frames according to the adaptive S-MAC protocol. We simulate our proposed protocol i.e., EE-MAC protocol using ns-2.33 simulator for two parameters energy consumption and throughput, for determining the behavior of the proposed protocol. The simulation results show that our proposed EE-MAC protocol performs better than adaptive S-MAC protocol in terms of energy consumption and throughput.

IEEE802.11, S-Mac Protocol, Transmission Power Control, Wireless Sensor Network


1. J. Yick, B. Mukherjee, and D. Ghosal, “Wireless sensor network survey,” Copyright © 2008 Elsevier, pp. 2292-2330.
2. C. Shiva Ram Murthy, and B. S. Manoj, “Ad-hoc Wireless Networks: Architectures and Protocols,” Copyright © 2004 by Pearson education, Inc.

3. S. S. Kulkarni, “TDMA Services for Sensor Networks,” Proc. 24th Int’l. Conf. Distrib. Comp. Sys. Wksps., Mar. 2004, pp. 604-09.

4. Wei Ye, John Heidmann, “Medium Access Control in Wireless Sensor Networks” USC/ISI TECHNICAL REPORT ISI-TR-580, OCTOBER 2003.

5. I. Demirkol, C. Ersoy, F. Alagoz. “MAC protocols for Wireless Sensor Networks: A Survey” IEEE communication magazine, pages 115-121, April 2006.
6. Koen Langendoen, “Medium access control in wireless sensor networks,” Vol. II: Practice and Standards edited by H. Wu and Y. Pan, published by Nova Science Publishers © 2007.

7. P. Naik, K. Sivalingam, “A Survey of MAC Protocols for Wireless Sensor Networks,” in: C. Raghavendra, K. Sivalingam, T. Znati (Eds.), Wireless Sensor Networks, Kluwer Academic Publishers, 2004.

8. W. Ye, J. Heidemann, and D. Estrin, “An energy efficient MAC protocol for Wireless Sensor Networks,” in Proceedings of the 21st International Annual Joint Conference of the IEEE Computer and Communication Societies (INFOCOM 2002), New York, USA, June 2002, pp. 1567-1576.

9. IEEE 802.11, Wireless LAN media access controls (MAC) and physical layer (PHY) specifications, 1999.

10. W. Ye, J. Heidemann, and D. Estrin, “Medium Access Control with Coordinated Adaptive Sleeping for Wireless Sensor Networks,” in IEEE/ACM Transactions on Networking, June 2004, pp. 493-506.

11. Jian Xiao, and Fengqi Yu, “An Efficient Transmission Power Control Algorithm in Wireless Sensor Networks,” in Proceedings of, 2007, pp. 2767-2770.

12. H. W. Tseng, S. H. Yang, P. Y. Chuang, E. H. Kuang Wu and G. H. Chen, “An Energy Consumption Analytic Model for A Wireless Sensor MAC Protocol”, in Proceedings of the IEEE Vehicular Technology Conference (VTC’2004), September 2004, pp. 4533-4537.

13. T. Ezzedine, M. Miladi, and R. Bouallegue, “An Energy-Latency-Efficient MAC Protocol for Wireless Sensor Networks,” in Proceedings of International Journal of Electronics, Communications and Computer Engineering, January 2009, pp. 30-35.

14. J. Gomez and A.T. Campbell, M. Naghshineh, and C. Bisdikian, “Conserving Transmission Power in Wireless Ad Hoc Networks,” in ICNP’01, November 2001.

15. S. Agarwal, S. Krishnamurthy, R. H. Katz, and S. K. Dao, “Distributed Power Control in Ad-hoc Wireless Networks,” in PIMRC, 2001.






Priyanka Sharma, Urvashi Mutreja

Paper Title:

Analysis of Satellite Images using Artificial Neural Network

Abstract: Data from Remote Sensing Satellites are used for various applications of resources survey and management. For collection and analysis of remotely sensed data, Artificial Neural Network(ANN) have become a popular tool. As we know Remotely Sensed images are major sources of data & information which is used in various fields such as Environmental impact analysis, Forest survey, rural to urban change detection(Urban Planning), Mineral Prospecting etc. Although many neural network based Methods has been developed for image classification but some issues still remain to be fixed. Digital interpretation (quantitative analysis) is one of the main approaches for extracting information from remotely sensed image. ‘Classification’ is one of the most common digital technique used as information extraction method from remotely sensed data. In pattern recognition two techniques are used which are supervised classification & unsupervised classification. Supervised Classification is done using Supervised Learning technique according to which the networks know the target and changes accordingly to get the required output corresponding to the input sample data. Already a lot of work has been done in the field of supervised classification. This paper examines remotely sensed data analysis with neural network and unsupervised classification method of ANN for classification of satellite images.

ANN, LVQ, Satellite Images, SOFM, SOM.


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7. Archana Mangal, Pratistha Mathur and Rekha Govil. Trend Analysis in satellite Imagery Using SOFM. Apaji Institute of Mathematics & Computer Technology, Banasthali Vidhyapith, Rajasthan, India.






Saurabh Kumar Gaur, S.K.Tyagi, Pushpender Singh

Paper Title:

“VANET” System for Vehicular Security Applications

Abstract: Today the vehicular security and passenger safety is an alarming issue in the field of automobile industry. The technocrats of the companies are very much varied about this issue. Ad hoc network (VANETs) is becoming the mostsuitable solution for this purpose. It provides vehicle to vehicle connectivity. A vehicular Ad hoc network (VANETs) can be used as an alert system. By this we get the alert about the traffic jam. It helps to create balance in traffic load to reduce travelling time. This system is also useful to broadcast emergency signal to the driver of the vehicle behind the accident. It also helps to send message to ambulance and traffic police in the case of traffic emergency. In this paper, we take the position that VANETs would indeed turn out to be the networking platform that would support the future vehicular applications. We analyze the critical factors in deciding the networking framework over which the future vehicular Applications would be deployed. A reactive research effort is needed for making VANETs a reality in the near future.

LPGs, VANETs, VANETs architecture, V2V.


1. Z. Li, Z. Wang, and C. Chigan, “Security of Vehicular Ad Hoc Networks in Intelligent Transportation Systems,” in Wireless Technologies for Intelligent Transportation Systems, Nova Science Publishers, 2009 (in press)
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6. “Enhancing location privacy in wireless lan through disposable interface identifiers- a quantitative analysis,” pp. 315–325, 2005.

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10. M. Raya, P. Papadimitratos, and J.-P. Hubaux, “Securing vehicular communications.”

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13. en.wikipedia.org/wiki/Intelligent_vehicular_ad-hoc_network

14. ArunkumarTangavelu “Location Identification and Vehicle Tracking using VANET (VETRAC)” IEEE-ICSN 2007, Feb 22-24, 2007pp 112-116

15. Tamer Nadeem, Pravin Shankar, Liviu Iftode “A Comparative Study of Data Dissemination Models for VANETs”






Mukta, Balwinder Singh Surjan

Paper Title:

Grid Stability of Interconnected System with Fuzzy-logic controller & HVDC in Deregulated Environment

Abstract: This paper investigates the effects of integral controller, fuzzy controller,HVDC on an interconnected two area power system in a deregulated environment. The system is simulated using Matlab-Simulink along with controllers. The frequency deviation responses are studied using Matlab-simulink. Robustness of the controller is thus checked and we get a new proposed system with better results i.e. lesser deviation for reliable and quality power supply.

Frequency Control, Interconnected Power System, Integral Controller, Fuzzy logic Controller,HVDC, Deregulated Environment, Wind Turbine Generator.


1. Yogendra Arya, Narender Kumar, Hitesh Dutt Mathur, “Automatic Generation Control in Multi Area Interconnected Power System by using HVDC Links” IJPEDS( International Journal of Power Electronics and Drive System) Vol.2,No.1, March 2012, pp.67~75, ISSN :2088-8694.
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10. http://nptel.iitm.ac.in/courses/Webcourse-ontents/IIT%20Bombay/Power%20System%20Operation%20and%20Control/Module%207/L01-Introduction%20to%20Deregulation-1.pdf

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13. Peter Meisen, “ Cross-Border Interconnections on Every Continent” Report by Global Energy Network Institute (GENI), June 2010.

14. Ngamroo, “A Stabilization of frequency oscillation in a parallel ac-dc interconnected power system via an HVDC Link,” Science Asia, vol. 28, pp. 173-180, 2002

15. R. Thottungal, P. Anbalagan, T. Mohanaprakash, A. Sureshkumar and G.V. Prabhu, “Frequency stabilisation in multi area system using HVDC link,” in Proc. of IEEE International Conference on Industrial Technology, 15-17, December, 2006. pp. 590-595.

16. K.R.Padiyar, “HVDC Power Transmission Systems”, New Age International(P) Limited Publishers, Second Edition,2012.






Sonal Dubey, R.K. Pandey, S.S. Gautam

Paper Title:

Literature Review on Fuzzy Expert System in Agriculture

Abstract: Agriculture constitutes the backbone of the Indian economy. Farmer need advance expert knowledge to take decision during land preparation, sowing, fertilizer management, irrigation management, integrated pest management, storage etc. for higher crop production. Expert systems are being used in agriculture which assists the farmers to make right decisions. Expert systems for pest management and crop protection constitute a very significant class of agricultural expert systems. Knowledge of entomology, plant pathology, nematology, weeds and nutritional disorders and various number of techniques used are included in integrated pest management and crop protection.Uncertainty is confronted during time of sowing, weed management, diagnosis of insect, disease and nutritional disorders, storage, marketing of the produce etc. This uncertainty is compounded by the fact that many agricultural decision- making activities are often vague or based on intuition. Fuzzy logic is used to handle imprecision, vagueness and insufficient knowledge. Fuzzy logic lets expert systems perform optimally with uncertain or ambiguous data and knowledge. Fuzzy expert systems use fuzzy logic instead of classical Boolean logic. They are oriented towards numerical processing The paper presents a review of various fuzzy expert systems in agriculture over the last two decades.

Agriculture, Integrated Pest management, fuzzy expert system, rules.


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3. G. Delgado, V. Aranda, J. Calero, M. Sánchez-Marañón, J. M. Serrano, D. Sánchez and M. A. Vila “Building a fuzzy logic information network and a decision-support system for olive cultivation in Andalusia” Spanish Journal of Agricultural Research 2008 6(2), 252-263.

4. Harvinder S. Saini, Raj Kamal and A. N. Sharma (2002), “Web Based Fuzzy Expert System For Integrated Pest Management in Soyabean”, International journal Of Information technology, Vol 8, No. 2, 2002.

5. Nureize Arbaiy, Azizul Azhar Ramli, Zurinah Suradi,Mustafa Mat Deris “Pest Activity Prognosis in the Rice Field” , www.igi-global.com/chapter/pest-activity-prognosis-rice-field/17171.

6. Philomine Roseline,Clarence J. M Tauro, N. Ganesan ” Design and Development of Fuzzy Expert System for Integrated Disease Management in Finger Millets “ International Journal of Computer Applications (0975 – 8887) Volume 56– No.1, October 2012


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9. Savita Kolhe, Raj Kamal, Harvinder S. Saini and G.K. Gupta , “A web-based intelligent disease-diagnosis system using a new fuzzy-logic based approach for drawing the inferences in crops”, Journal of Computers and Electronics in Agriculture, year 2011, volume 76, pp 16–27

10. Virparia P.V. A Web Based Fuzzy Expert System For Insect Pest Management In Groundnut Crop ‘Prajna’ – Journal Of Pure & Applied Sciences, 15 (2007) 36-41

11. Zadeh, L.A. (1965): Fuzzy sets, Information and Control 8(3):338–353.

12. Ajith Abraham “Rule-based Expert Systems” Handbook of Measuring System Design, edited by Peter H. Sydenham and Richard Thorn 2005 John Wiley & Sons, Ltd.






Rinky D. Patel, Dheeraj Kumar Singh

Paper Title:

Credit Card Fraud Detection & Prevention of Fraud Using Genetic Algorithm

Abstract: Companies and institutions move parts of their business, or the entire business, towards online services providing e-commerce, information and communication services for the purpose of allowing their customers better efficiency and accessibility. Payment card fraud has become a serious problem throughout the world. Companies and institutions loose huge amounts annually due to fraud and fraudsters continuously seek new ways to commit illegal actions. In this we will try to detect fraudulent transaction through the with the genetic algorithm. Genetic algorithm are used for making the decision about the network topology, number of hidden layers, number of nodes that will be used in the design of neural network for our problem of credit card fraud detection.

Credit cards; Credit card fraud detection; Artificial neural networks; Genetic algorithm.


1. Ganesh Kumar.Nune, and P.Vasanth Sena, and T.P.Shekhar, “Novel Artificial Neural Networks and Logistic Approach for Detecting Credit Card Deceit”, In IJCSMR Vol 1 Issue 3 October 2012 ISSN 2278-733X October 2012.
2. Raghavendra Patidar, and Lokesh Sharma, “Credit Card Fraud Detection Using Neural Network”, In IJSCE ISSN: 2231-2307, Volume-1, Issue-NCAI2011, June 2011.

3. Khyati Chaudhary, and Jyoti Yadav, and Bhawna Mallick, “A review of Fraud Detection Techniques: Credit Card”, In IJCA Volume 45– No.1, May 2012.

4. K.RamaKalyani, and D.UmaDevi, “ Fraud Detection of Credit Card Payment System by Genetic Algorithm”, In IJSER Volume 3, Issue 7, July 2012.

5. Mehzabin Shaikh and Mrs. Gyankamal J. Chhajed, “ Review on Financial Forecasting using Neural Network and Data Mining Technique”,In Global Journals Inc. Volume 12 Issue 11, 2012.

6. Alejandro Correa, Banco Colpatria, Andres Gonzalez, Banco Colpatria, camilo Ladino, Banco Colpatria, “Genetic Algorithm Optimization for Selecting the Best Architecture of a Multi-Layer Perceptron Neural Network: A Credit Scoring Case” ,SAS Global Forum, 2011.

7. Khyati Chaudhary, Bhawna Mallick, “Exploration of Data mining techniques in Fraud Detection: Credit Card”, In IJECSE ISSN 277-1956/V1N3-1765-1771.

8. Sushmita Mitra, Sankar K. Pal, Pabitra Mitra, “Data Mining in Soft Computing Framework: A Survey”, IEEE Transactions On Neural Networks, VOL. 13, NO. 1, January 2002.

9. S.Benson Edwin Raj, A. Annie Portia, ―Analysis on Credit Card Fraud Detection Methods, IEEE International Conference on Computer, Communication and Electrical Technology, IEEE March 2011.

10. Genetic algorithms for credit card fraud detection by Daniel Garner, IEEE Transactions May 2011.





R.Harikumar, T.Vijayakumar

Paper Title:

A Comparison of Elman and Radial Basis Function (RBF) Neural Networks in Optimization of Fuzzy outputs for Epilepsy Risk Levels Classification from EEG Signals

Abstract: In this paper; we investigate the optimization of fuzzy outputs in the classification of epilepsy risk levels from EEG (Electroencephalogram) signals using two categories (Recurrent &Non Recurrent) of neural networks. The fuzzy techniques are applied as a first level classifier to classify the risk levels of epilepsy based on extracted parameters like energy, variance, peaks, sharp and spike waves, duration, events and covariance from the EEG signals of the patient. Elman neural network (with error Back propagation training) & Radial Basis Function (RBF) neural network are identified as post classifiers on the classified data to obtain the optimized risk level that characterizes the patient’s epilepsy risk level. The Performance Index (PI) and Quality Value (QV) are calculated for the above methods. A group of ten patients with known epilepsy findings are used in this study. High PI such as 97.87 %, and 98.92% was obtained at QV’s of 23.31, and 23.98 in Elman and RBF neural network optimization when compared to the value of 40% and 6.25 through fuzzy techniques respectively. We find that the RBF (Non Recurrent) neural network out performs Elman Network in optimizing the epilepsy risk levels.

EEG Signals, Epilepsy Risk Levels,Fuzzy Logic, RBF, Elman Neural Networks, Back propagation.


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10. Mark van Gils, Signal processing in prolonged EEG recordings during intensive care, IEEE EMB Magazine November/December 1997,16(6): 56-63.

11. R.Harikumar, Dr.(Mrs). R.Sukanesh, P.A. Bharthi, Genetic Algorithm Optimization of Fuzzy outputs for Classification of Epilepsy Risk Levels from EEG signals,I.E . India Journal of Interdisciplinary panels, May 2005, 86(1):9-17.

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14. Joel.J etal, Detection of seizure precursors from depth EEG using a sign periodogram transform, IEEE Transactions on Bio Medical Engineering, April 2004,51 (4):449-458.

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17. Drazen.S.etal., Estimation of difficult –to- Measure process variables using neural networks, Proceedings of IEEE MELECON 2004,May 12-15, 2004, Dubrovnik, Croatia, 387-390.

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21. H.Demuth and M..Beale, Neural network tool box: User’s guide, Version 3.0 the math works, Inc., Natick,MA, 1998.

22. G.Fung etal, Fault Detection In Inkjet Printers Using Neural Networks, Proceedings of IEEE SMC, 2002.

23. Guoqiang Peter Zhang , Neural Networks for Classification: A Survey ,IEEE Transactions on Systems Man Cybernetics- Part C: Applications and Reviews, November 2000,30(4): 451-462.

24. Jonathan lee etal., A Neural Network Approach to Cloud Classification, IEEE Transactions on Geosciences and Remote Sensing, September 1990,28 (5): 846-855.

25. S.Haykin, Neural networks a Comprehensive Foundation, Prentice- Hall Inc. 2nd Ed. 1999.

26. Meng Joo Er,Shiqian Wu,Juwei Lu, Face Recognition with Radial Basis Function (RBF) Neural Network, IEEE Transactions on Neural Networks, May 2002,13 (3): 697-710.

27. Mu-chun Su, Chien –Hsing Chou, A modified version of the k-means clustering algorithm with a distance based on cluster symmetry, IEEE Transactions on Pattern Analysis and Machine Intelligence June 2001, 23 (6): 674-680.

28. Masaaki Tsujitani, Takashi Koshimizu, Neural Discriminant Analysis, IEEE Transactions on Neural Networks, November 2000,11 (6):1394-1401.

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31. K.Sriramamurty and B.Yegnannarayana, Combining Evidence from Residual Phase and MFCC Features for Speaker Recognition, IEEE Signal Processing Letters, January 2006,13 (1): 52-55.






Devesh D. Nawgaje, Rajendra D. Kanphade

Paper Title:

Hardware Implementation of Genetic Algorithm for Ovarian Cancer Image Segmentation

Abstract: Imaging plays an important role in the diagnosis and treatment of ovarian cancer. An accurate segmentation is critical, especially when the ovarian tumor morphological changes remain subtle, irregular and difficult to assess by clinical examination. Traditionally, segmentation is performed manually in clinical environment that is operator dependent and very tedious and time consuming labor intensive work. In this paper genetic algorithm for selecting the optimal threshold in image segmentation is proposed. In the computational process, the GA adjusts crossover probability and mutation probability automatically according to the variance between the target and background. Moreover, the complete algorithm is implemented using Digital Signal Processor TMS320C6713 which decreases the run time greatly.

Genetic algorithm, Ovarian Cancer, Digital Signal Processor, Segmentation.


1. American Cancer Society. Cancer Facts and Figures 2011. Atlanta, GA: American Cancer Society; 2011.
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8. J.E. Koss, F. D. Newman, T. K. Johnson and D. L. Kirch: “Abdominal organ segmentation using texture transforms and a hopfield neural network”, IEEE Trans.
Med. Imag., vol. 18, no. 7, July, 1999.

9. Payel Ghosh, M. Mitchess, “ Automatic segmentation of the prostate using a genetic algorithm for prostate cancer treatment planning”, IEEE proceeding of ICMLA 2010.

10. Liu Jianli, Zuo Baoqi, “The segmentation of skin cancer image based on genetic neural network”, IEEE proceeding of CSIE 2008.

11. Texas Instruments, TMS320C6713, Floating-Point Digital Signal Processors, Data Sheet, Dallas, TX, 2002.






Abhay Mundra, Poonam Tomar, Deepak Kulhare

Paper Title:

Rapid Update in Frequent Pattern form Large Dynamic Database to Increase Scalability

Abstract: Association rule mining is a popular data mining technique which gives us valuable relationships among different items in a dataset. In dynamic databases, new transactions are appended as time advances. This may introduce new association rules and some existing association rules would become invalid [1]-[2]. Thus, the maintenance of association rules for dynamic databases is an important problem. Several incremental algorithms, is proposed to deal with this problem. In this paper we proposed algorithm RUPF (Rapid Update in Frequent Pattern). This algorithm reduces a number of times to scan the database (old and new) to generate frequent pattern. As a result, the algorithm has execution time faster than that of previous Algorithms. This paper also conducts experiments to show the performance of the proposed algorithm. The result shows that the proposed algorithm has a good performance.

Association rule, frequent pattern for Dynamic maintenance, incremental algorithms.


1. Rahman, Mohammad.M AL-Widyan “Reduce Scanning Time Incremental Algorithm (RSTIA) of Association rules” Academic Research International2, September Volume 1, Issue 2, September 2011 University, Amman, JORDAN
2. N.L. Sarda N. V. Srinivas “an Adaptive Algorithm for Incremental Mining of Association Rules “Computer Science and Engineering Indian Institute of Technology Bombay Mumbai.

3. Siddharth Shah, N. C. Chauhan, S. D. Bhander “Incremental Mining of Association Rules: A Survey “International Journal of Computer Science and Information Technologies, Vol. 3 , 2012,

4. Wei-Guang Teng and Ming-Syan Chen “Incremental Mining on Association Rules” Department of Electrical Engineering National Taiwan University Taipei, Taiwan.

5. Animesh Tripathy, Subhalaxmi Das “An Association Rule Based Algorithmic Approach to Mine Frequent Pattern in Spatial Database System” International Journal of Computer Science & Communication Vol. 1, No. 2, July-December 2010,

6. Sandhya Rani Jetti, Sujatha D “Mining Frequent Item Sets from incremental database: A single pass approach “International Journal of Scientific & Engineering Research, Volume 2, Issue 12, December-2011,

7. Chelliah Balasubramanian*, Karuppaswamy ”A mining method for tracking changes in temporal association rules from an encoded database” International Journal on Computer Science and Engineering Vol.1(1), 2009,

8. Nibedita Panigrahi “An Efficient Algorithm for Mining Of frequent items using incremental model” Konark Institute of Science and Technology International Journal of Computer Science & Informatics, Volume-1,

9. Wuzhou Dong, Juan Yi, Haitao He, and Jiadong Ren “An incremental algorithm for frequent pattern mining based on bit-sequence (IJACT)” Volume3, Number9, October 2011

10. Ahmed Taha1, Mohamed Taha1, Hamed Nassar2, and Tarek F. Gharib3 “DARM: Decrement Association Rules Mining “Journal of Intelligent Learning Systems and Applications,

11. Romans Tumasonis, Gintautas Dzemyda “A probabilistic algorithm for mining frequent sequences “

12. Jia-Dong Ren and Xiao-Lei Zhou Yanshan “A New Incremental Updating Algorithm for Mining Sequential Patterns “University, , China Journal of Computer Science 2

13. F.A. Dafa-Alla, Ho Sun Shon and Khalid E.K. Saeed “IMTAR: Incremental Mining of General Temporal Association Rules “ Journal of Information Processing Systems, Vol.6, No.2, June 2010

14. Vasile Parvan 2, Timisoara, Romania “A Comparative Study of Association Rules Mining Algorithms”Computer & Software Engineering Department, Politehnica University of Timisoara, Bd.






Namita Jain and Neeraj Jain

Paper Title:

Study of Energy Efficient Time Synchronization Algorithm for the development of Smart Wireless Sensor Network

Abstract: Time Synchronization algorithm guarantees the connectivity, coverage, reliability and security of networking operations for a maximized period of time. We propose energy efficient time synchronization algorithm for deployment of Underwater Wireless Sensor Network (UWSN) for the purpose of monitoring phenomenon of our interest in the coverage region. This paper describes a prototype of a synchronization protocol which is suitable for UWSN considering the effects of both propagation delay and movement. In the algorithm, no time synchronization is necessary if the time stamps of the received data packets are within the tolerance. In this context, the network underwater neither performs global time synchronizations frequently nor periodically and it reduces the time used to synchronize clocks among sensor nodes.

Algorithm, Protocols, Time Synchronization, Underwater Wireless sensor Network (UWSN).


1. Li Liu, 2010, “Time Synchronization of Underwater Wireless Sensor Networks”, Smart Wireless Sensor Networks.
2. Romer, K., 2001, “Time synchronization in ad hoc networks”, in: Proceedings of ACM Symposium on Mobile Ad Hoc Networking and Computing (MobiHoc’01), pp. 173–182.

3. Elson, J., Girod L., and Estrin D., 2002, “Fine¬grained network time synchronization using reference broadcasts”, in: Proceedings of Fifth Symposium on Operating Systems Design and Implementation (OSDI 2002), 36, pp. 147–163.

4. Gautam Gopal, Sharma Teek, 2011, “A Comparative Study of Time Synchronization Protocols in Wireless Sensor Network” in International Journal of Applied Engineering Research Dindigul Volume 1, No 4, 2011.

5. Su, W., and Akyildiz, I.F., 2005, “Time¬diffusion synchronization protocol for wireless sensor networks”, Networking, IEEE/ACM Transactions on, 13(2), pp. 384¬ 397.

6. Mingxia Xu, Minjian Zhao, and Shiju Li, 2005, “Lightweight and energy efficient time synchronization for sensor network,” in proceedings of International Conference on Wireless Communications, Networking and Mobile Computing, 2005, 2, pp. 947¬ 950.

7. Lamport,L. & Melliar-Smith, P.(1985). Synchronizing clocks in the presence of faults. Journal of the Association for Computing Machinery, Vol. 32, No. 1,(1985) 52-78,ISSN 0004-5411.

8. Mar’oti, M. ; Kusy, B. ; Simon, G. & L’edeczi, A. (2004). The flooding time synchronization protocol, Proceedings of Sensys 2004,pp. 39-49, ISBN 1-58113-879-2,Baltimore, MD, USA, November 2004, ACM Press, New York, NY, USA.






G. Balasubramanian, S. Singaravelu

Paper Title:

Fuzzy Controller for StandAlone Hybrid PV-Wind Generation Systems

Abstract: This paper proposes a fuzzy logic based voltage controller for hybrid generation scheme using solar and wind energy for the stand alone applications. The fuzzy logic controller is designed to vary the duty-cycle of the DC-DC converter automatically such that to maintain the load voltage constant. The hybrid scheme inherently adapts to the changes in wind speed or load on generator. A dynamic and steady-state mathematical model and simulations for the entire scheme is presented. The model is implemented in the MATLAB/Simulink platform. Results from the simulations and laboratory tests bring out the suitability of the proposed hybrid scheme in remote areas.

DC-DC converter, Fuzzy logic, Induction generator, PV array, Single-phase and Wind energy.


1. S.Meenakshi, K.Rajambal, C.Chellamuthu, and S.Elangovan, “Intelligent Controller for Stand-Alone Hybrid Generation System”, Power India Conference IEEE, pp 8-15, 2006.
2. Ashraf A.Ahmed, Li Ran, Jim Bumby, “Simulation and control of a Hybrid PV-Wind System”, Power Electronics Machines & Drives, PEMD 4th IET conference, pp 421-425, 2008.

3. Meenakshmisundaram Arutchelvi, Samuel Arul Daniel, “Grid Connected Hybrid Dispersed Power Generators Based on PV Array And Wind Driven Induction Generator”, Journal of Electrical Engineering , Vol., 60, pp 313-320, 2009.

4. T.Ahmed, N. Katsumi, N.Mutsuo, “Advanced control of PWM converter with variable-speed induction generator”, IET Electr.Power Appl, pp 239-247, 2007.

5. S.Bhim, K.Gaurav kumar, “Solid state voltage and frequency controller for a stand- alone wind power generating system”,IEEE Trans.Power Electron, pp 1170-1177, 2008.

6. B.Venkatesa perumal, K.Jayanta, “Voltage and frequency controller of a stand- alone brushless wind electric generation using generalized impedance controller” IEEE Trans. Energy Convers, pp 632-641, 2008.

7. S.Bhim, K.Gaurav kumar, “Voltage and frequency controller for three phase four wire autonomous wind energy conversion system”, IEEE Trans.Energy Convers,pp 509-518, 2008.

8. M.G.Villalva, J.R.Gazol, and E.R.Filho, “Comprehensive Approach to Modeling and Simulation of Photovoltaic Arrays”, IEEE trans. on Power Electronics, vol.24, no.5, pp.1198-1208, 2009.

9. H. Patel, and V. Agarwal, “MATLAB based modeling to study the effects of partial shading on PV array characteristics”, IEEE trans. on energy conv., vol. 23, no.1, pp. 302-310, 2008.

10. Bhim singh, L.B. Shilpakar, S.S Murthy, A.K. Tiwari, “Improved steady state and transient performance with optimum excitation of single phase self-excited induction generator”, Electric machines and power system, 2000.

11. A.Karthikeyan, C.Nagamani, G.Saravana Illango, A.Sreenivasulu, “Hybrid, open-loop excitation system for a wind turbine –driven stand-alone induction generator”, IET Renewable Power Generation, Vol.5, no.2,pp.184-193,2011.

12. Timothy and Ross J, Fuzzy logic with engineering applications, McGraw hill international editions, Electrical engineering series, New York, 1997.






Supriya Jana, Bipadtaran Sinhamahapatra, Sudeshna Dey, Arnab Das, Bipa Datta, Moumita Mukherjee, Santosh Kumar Chowdhury, Samiran Chatterjee

Paper Title:

Single Layer Monopole Hexagonal Microstrip Patch Antenna for Satellite Television

Abstract: A single layer monopole hexagonal patch antenna is thoroughly simulated in this paper. Resonant frequency has been reduced drastically by cutting two equal slots which are the combinations of two triangular and one rectangular slot at the upper right and lower left corner and middle point symmetrical Y-junction slot located from the conventional microstrip patch antenna. It is shown that the simulated results are in acceptable agreement. More importantly, it is also shown that the differentially-driven microstrip antenna has higher gain of simulated 3.19 dBi at 9.12GHz and -0.62 dBi at 13.71GHz and beam width of simulated 162.910 at 9.12GHz and 64.470at 13.71GHz of the single-ended microstrip antenna. Compared to a conventional microstrip patch antenna, simulated antenna size has been reduced by 56.55% with an increased frequency ratio.

Compact, Patch, Slot, Resonant frequency, Bandwidth.


1. I.Sarkar, P.P.Sarkar, S.K.Chowdhury “A New Compact Printed Antenna for Mobile Communication”, 2009 Loughborough Antennas& Propagation Conference, 16-17 November 2009, pp 109-112.
2. S. Chatterjee, U. Chakraborty, I.Sarkar, S. K. Chowdhury, and P.P.Sarkar, “A Compact Microstrip Antenna for Mobile Communication”, IEEE annual conference. Paper ID: 510

3. J.-W. Wu, H.-M. Hsiao, J.-H. Lu and S.-H. Chang, “Dual broadband design of rectangular slot antenna for 2.4 and 5 GHz wireless communication”, IEE Electron. Lett. Vol. 40 No. 23, 11th November 2004.

4. U. Chakraborty, S. Chatterjee, S. K. Chowdhury, and P. P. Sarkar, “A comact microstrip patch antenna for wireless communication,” Progress In Electromagnetics Research C, Vol. 18, 211-220, 2011 http://www.jpier.org/pierc/pier.php?paper=10101205

5. Rohit K. Raj, Monoj Joseph, C.K. Anandan, K. Vasudevan, P. Mohanan, “ A New Compact Microstrip-Fed Dual-Band Coplaner Antenna for WLAN Applications”, IEEE Trans. Antennas Propag., Vol. 54, No. 12, December 2006, pp 3755-3762.

6. Zhijun Zhang, Magdy F. Iskander, Jean-Christophe Langer, and Jim Mathews, “Dual-Band WLAN Dipole Antenna Using an Internal Matching Circuit”, IEEE Trans. Antennas and Propag.,VOL. 53, NO. 5, May 2005, pp 1813-1818.

7. J. -Y. Jan and L. -C. Tseng, “ Small planar monopole Antenna with a shorted parasitic inverted-L wire for Wireless communications in the 2.4, 5.2 and 5.8 GHz. bands” , IEEE Trans. Antennas and Propag., VOL. 52, NO. 7, July 2004, pp -1903-1905.

8. Samiran Chatterjee, Joydeep Paul, Kalyanbrata Ghosh, P. P. Sarkar and S. K. Chowdhury “A Printed Patch Antenna for Mobile Communication”, Convergence of Optics and Electronics conference, 2011, Paper ID: 15, pp 102-107

9. C. A. Balanis, “Advanced Engineering Electromagnetics”, John Wiley & Sons., New York, 1989.

10. Bipa Datta, Arnab Das, Samiran Chatterjee, Bipadtaran Sinhamahapatra, Supriya Jana, Moumita Mukherjee, Santosh Kumar Chowdhury, “Design of Compact Patch Antenna for Multi-Band Microwave Communication”, National Conference on Sustainable Development through Innovative Research in Science and Technology (Extended Abstracts), Paper ID: 115, pp 155, 2012

11. Arnab Das, Bipa Datta, Samiran Chatterjee, Bipadtaran Sinhamahapatra, Supriya Jana, Moumita Mukherjee, Santosh Kumar Chowdhury, “Multi-Band Microstrip Slotted Patch Antenna for Application in Microwave Communication,” International Journal of Science and Advanced Technology, (ISSN 2221-8386), Vol. 2, Issue-9, 91-95, September 2012.

12. Zeland Software Inc. IE3D: MoM-Based EM Simulator. Web: http://www.zeland.com/






Sandip Bhattacharya, Subhajit Das, Debaprasad Das

Paper Title:

Analysis of Stability in Carbon Nanotube and Graphene Nanoribbon Interconnects

Abstract: This paper analyzes the stability of carbon nanotube (CNT) and graphene nanoribbon (GNR) based interconnects for future VLSI technology node. We have analyzed both Bode and Nyquist stability of single-wall CNT, multi-wall CNT, GNR, and copper based interconnect systems. The stability analysis is performed for different interconnect systems for 16nm ITRS technology node. It is shown that densely packed single-wall CNT bundle based interconnect has highest gain margin for a wide range of interconnect length (1 m to 100 m) as compared to the other interconnect systems.

Carbon nanotube (CNT), graphene nanoribbon (GNR), stability.


1. International Technology Roadmap for Semiconductors (ITRS) reports, 2006. [Online]. Available: http://www.itrs.net/reports.html
2. Debaprasad Das and Hafizur Rahaman, “Crosstalk overshoot/ undershoot analysis and its impact on gate oxide reliability in multi-wall carbon nanotube interconnects”, Journal on Computational Electronics, Springer, vol. 10, no. 4, pp. 360-372, Dec. 2011.

3. Debaprasad Das and Hafizur Rahaman, “Analysis of Crosstalk in Single- and Multiwall Carbon Nanotube Interconnects and Its Impact on Gate Oxide Reliability”, IEEE Transactions on Nanotechnology, vol. 10, no. 6, Nov. 2011.

4. Debaprasad Das and Hafizur Rahaman, “Crosstalk and Gate Oxide Reliability Analysis in Graphene Nanoribbon Interconnects”, in Proc. 2nd International Symposium on Electronic System Design (ISED), 19-21 Dec. 2011, pp. 182-187.

5. Sandip Bhattacharya, Subhajit Das, Debaprasad Das, “Analysis of Stability in Carbon Nanotube Interconnects”, in Proc. National Conference on Recent Advances in Applied Mathematics (NCRAAM), 18th Feb. 2012, pp. 34-39.

6. R. C. Dorf, R. H. Bishop, Modern Control System, 11th Ed., Englewood Cliffs, NJ: Prentice-Halls, 2008.

7. http://en.wikipedia.org/wiki/Nyquist_plot.

8. http://www.facstaff.bucknell.edu/mastascu/econtrolhtml/Freq/Freq6.html






Jagannath Samanta, Mousam Halder, Bishnu Prasad De

Paper Title:

Performance Analysis of High Speed Low Power Carry Look-Ahead Adder Using Different Logic Styles

Abstract: A carry look-ahead adder improves speed by reducing the amount of time required to resolve carry bits. It is widely used in any electronic computational devices. In this paper a 4 bit & 8 bit CLA has been implemented using different static and dynamic logic styles such as Standard CMOS, DCVS Pseudo NMOS, PTL & Domino logic style. The performance of the CLA has been measured by comparing the results in terms of propagation delay, power dissipation and their Power Delay Product. The simulation is done with the help of Tanner EDA tool considering the different feature sizes of 150nm, 200nm & 250nm. Result analyses are also carried out for intrinsic and extrinsic load capacitances. This work will helpful for any circuit designer to build any system.

Carry Look-Ahead Adder, TSpice, Standard CMOS, DCVS, Pseudo NMOS, PTL and Domino logic.


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5. K. Ueda, H. Suzuki, K. Suda, H. Shinohara, K. Mashiko,et.al., “A 64-bit Carry Look Ahead Adder Using Pass.” IEEE Journal of Solid-Stale Circuits, vol. 31, no. 6, pp. 810-818, 1996.

6. M.C.B. Osorio, C.A. Sampaio, A. I. Reis, R.P. Ribas., et.al. “Enhanced 32-bit Carry Lookahead Adder using Multiple Output Enable-Disable CMOS Differential Logic”. SBCCI, pp. 181-185, 2004.

7. Y. T. Pai and Y. K. Chen., “The Fastest Carry Lookahead Adder.” IEEE, Proceedings of the Second IEEE International Workshop on Electronic Design, Test and Applications (DELTA), 2004.

8. J. M. Rabey, Digital Integrated Circuits, A Design Perspective. Prentice-Hall, 1996.

9. N. H. E. Weste and K. Eshraghian, “Principles of CMOS VLSI Design”, Addison Wesley: New York, NY, 1985.

10. Sung-Mo Kang and Yusuf Leblebici. “CMOS Digital Integrated Circuits Analysis and Design”, Mcgraw-Hill, 2002.

11. R. Zlatanovici, S. Kao, B. Nikolic ´et.al., “Energy–Delay Optimization of 64-Bit Carry-Lookahead Adders with a 240 ps 90 nm CMOS Design Example.” IEEE
Journal of Solid-Stale Circuits, vol. 44, no. 2, pp569-583, February 2009.

12. J Samanta and B P De, “Comprehensive analysis of delay in UDSM CMOS circuits”, Proceeding of IEEE explore, ICECCT’11, Tamil Nadu, India, 978-1-4577-1894-6/11, pp:29-32, Nov-2011.






S.De, P.Samaddar, S.Sarkar, S.Biswas, D.Sarkar, P.P.Sarkar

Paper Title:

Compact High Gain Multi-frequency Microstrip Antenna

Abstract: In this paper, an antenna has been designed with some slots on the ground plane and a T slot on the radiating patch which shows five resonant frequencies. The size of the designed slotted antenna is reduced by more than 92% compared to the reference antenna. Omni-directional good radiation pattern and as well as Return Loss characteristics are done by Ansoft Designer software The gain of the antenna is also remarkable.

Keywords: microstrip antenna, compactness, high gain, multfrequency.


1. Handbook of Microstrip Antennas, J. R. James and P. S. Hall, Eds., Peter Peregrinus, London, U.K., 1989.
2. S. C. Gao and S. S. Zhong, “Analysis and design of dual-polarized microstrip arrays,” Int. J. RF Microwave CAE, vol. 9, no. 1, pp. 42–48, 1999.

3. “Dual-polarized microstrip antenna array with high isolation fed by coplanar network,” Microwave Opt. Technol. Lett., vol. 19, no. 3, pp.214–216, Oct. 1998.

4. S. C. Gao, Dual-Polarized Microstrip Antenna Elements and Arrays for Active Integration, Shanghai, China: Shanghai Univ. Press, 1999.

5. S. A. Long and M. D. Waton, “A dual-frequency stacked circular-disc antenna,” IEEE Trans. Antennas Propagat., vol. AP-27, no. 3, pp. 281–285, 1979.

6. J. S. Dahele, K. F. Lee, and D. P. Wong, “Dual-frequency stacked annular- ring microstrip antenna,” IEEE Trans. Antennas Propagat., vol.AP-35, no. 11, pp. 1281–1285, 1987.

7. J.Wang, R. Fralich, C.Wu, and J. Litva, “Multifunctional aperture-coupled stacked antenna,” Electron. Lett., vol. 26, no. 25, pp. 2067–2068, 1990.

8. F. Croq and D. M. Pozar, “Multifrequency operation of microstrip antennas using aperture coupled parallel resonators,” IEEE Trans. Antennas Propagat., vol. 40, no. 11, pp. 1367–1374, 1992.






P. Samaddar, S. De, S. Sarkar, S. Biswas, D.C. Sarkar, P.P. Sarkar

Paper Title:

Study on Dual Wide Band Frequency Selective Surface for Different Incident Angles

Abstract: This paper deals with single layer Frequency selective surface (FSS) which acts as a double band reject filter. The two stop bands are really broad with percentage bandwidth of 26.67% and 14.53%. The maximum and minimum band separation for this proposed design is around 45 dB and frequency ratio is more than 1.9.This results are almost same for different incident angles.. This design is investigated theoretically by ANSOFT® Designer software and practically by standard microwave test bench and the both results show a good agreement.

Frequency Selective Surface; Band reject filter, Band separation, Frequency ratio.


1. H. Zhou, S. Qu, Z. Pei, J. Zhang, B. Lin, J. Wang, H. Ma and C. Gu, Narrowband Frequency Selective Surface Based on Substrate Integrated Waveguide Technology, Progress In Electromagnetics Research Letters, Vol. 22, 19-28, 2011, pp 19-28.
2. N.D. Agrawal and W.A. Imbraile, Design of a dicroic Cassegrain subreflector, IEEE Trans Antennas Propagat AP-27 Ž1979, pp. 466-473.

3. S.W. Lee et al., Design for the MDRSS tri band reflector Antenna, IEEE Int AP-S Symp, Ontario, Canada, 1991, pp. 666-669.

4. G.H. Schennum, Frequency selective surfaces for multiple frequency antennas, Microwave J 16, 1973, pp. 55-57.

5. Michael E. MacDonald,Angelos Alexanian, Robert A. York, Zoya Popovic and Erich N. Grossman, Spectral Transmittance of Lossy Printed Resonant-Grid Terahertz Band pass Filters, IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, VOL. 48, NO. 4, APRIL 2000, pp 712-718.

6. J. Huang and S.W. Lee,”Tri-Band Frequency Selective Surface with Circular Ring Elements” IEEE Int. AP- Symp., London, Ontario, Canada, June 24-28, 1991.

7. A.E. Martynyuk and J.I. Martinez Lopez, Frequency-selective surfaces based on shorted ring slots, ELECTRONICS LETTERS 7st March 2007 Vol. 37 No. 5.

8. T.K. Wu, K. Woo, S.W. Lee, Multi-ring element Frequency Selective Surface for multi-band application, IEEE, vol- 4, page- 1775-1778, 1992.

9. Parker, E.A.; Hamdy, S.M.A.; Langley, R.J.; , “Arrays of concentric rings as frequency selective surfaces,” Electronics Letters , vol.17, no.23, pp.880-881, November 12 1981.






Surajit Mondal, Sourav Nandi, Sushanta Sarkar, Shuvodip Majumdar, Partha Pratim Sarkar

Paper Title:

Design of Compact-Broadband Frequency Selective Surface (FSS) by Modifying the Dimension of Slot and Periodicity

Abstract: This paper deals with the theoretical investigation on a reduced sized Frequency Selective Surface (FSS). The FSS is designed by cutting a unique shaped slot into square patch. It has been shown, how the variation of the dimension of the slot and periodicity results in shifting of resonant frequency. Compared to conventional square patch FSS the designed FSS can provide reduction in resonant frequency resulting in size reduction up to 91.32% with the bandwidth of 39.54% corresponding to resonant frequency of 3.54GHz. Theoretical investigations have been done by Ansoft Designer® software.

Frequency Selective Surface, Multi frequency, Size Reduction, slot.


1. N.D. Agrawal and W.A. imbraile,”Design of a Dichroic Cassegrain Sub Reflector” IEEE Trans, AP- 27(4), pp. 466-473(1979)
2. Sung, G.H. –h, Sowerby, K.W. Neve, M.J.Williamson A.G, “A Frequency selective wall for Interface Reduction In Wireless Indoor Environments” Antennas and Propagation Magazine, IEEE,Vol 48, Issue 5, pp 29-37 (Oct 2006).

3. A Novel Dual-Band Frequency Selective Surface (FSS)Xiao- Dong Hu 1, Xi- Lang Zhou 1, Lin- Sheng Wu1, Liang Zhou1, and Wen- Yan Yin 2,1 Center for Microwave and RF Technologies, Shanghai Jiao Tong University, Shanghai 200240, CHINA2 Center for Optics and EM Research, State Key Lab of MOI, Zhejiang University, Hangzhou 310058, CHINA.

4. R.Ray, A.Ray, S.Sarkar, D.Sarkar, P.P.sarkar, Reduction of Resonant Frequencies of Frequency Selective Surface by Introducing Different Types of Slots, IJCA Special Issue on “2nd National Conference- Computing, Communication and Sensor Network” CCSN,2011

5. PhD Thesis of P.P.Sarkar, Some Studies on FSS, Jadavpur University 2002.






S. Singh, P.P. Sarkar, D. Sarkar, S. Bhunia, S. Biswas

Paper Title:

Design of a Miniaturized Dual Wide Band Frequency Selective Structure

Abstract: This paper deals with the frequency selective property of a structure comprising of a two dimensional array of patches. This frequency selective surface (FSS) acts like a dual band reject filter. The proposed design has been investigated theoretically using Ansoft Designer® software in which the reflection and transmission band have been predicted by the method known as Method of Moment which is most complicated but its accuracy is best. Efforts have been given to achieve dual high band reject filtering with high band ratio (approx 3.18).

Bandwidth (BW), Band Ratio, Dual Band, Frequency Selective Surface (FSS), Resonating Frequency.


1. N.D. Agrawal and W.A. imbraile,”Design of a Dichroic Cassegrain Sub Reflector” IEEE Trans, AP- 27(4), pp. 466 473(1979)
2. Sung, G.H. –h, Sowerby, K.W. Neve, M.J.Williamson A.G, “A Frequency selective wall for Interface Reduction In Wireless Indoor Environments” Antennas and Propagation Magazine, IEEE,Vol 48, Issue 5, pp 29-37 (Oct 2006).

3. D.H. Werner and D. Lee, “A Design Approach for Dual-Polarised Multiband Frequency Selective Surface using Fractal Elements” IEEE International Symposium on Antennas and Propagation digest vol. 3, Salt Lake City Utah,pp. 1692-1695( July 2000).

4. D.H.Lee, Y.J.Yeo, R.Mitra, W.S.Parl, “Design of novel thin Frequency Selective Surface superstrates for dual-band directivity enhancement”, IET Microw. Antennas Propag., pp. 248-254, 2007

5. P.P Sarkar, D. Sarkar, S.Sarkar, S.Das, S.K. Chowdhury.”Experimental investigation of the Frequency selective property of an array of dual tuned printed dipoles, Microwave Opt. Technol lett.31 (2001), 189-190

6. Hsing-Yi Chen and Yu Tao, “Bandwidth Enhancement of a U-Slot Patch Antenna Using Dual-Band Frequency-Selective Surface With Double Rectangular Ring Elements”, MOTL Vol. 53 No. 7, pp 1547-1553, (July 2011).

7. PhD Thesis of P.P.Sarkar, Some Studies on FSS, Jadavpur University, 2002.






S. Mondal, S. Sarkar, S. De, P. Samaddar, S. Bhunia, P.P. Sarkar

Paper Title:

Studies on a Modified CPW Feed Planar Monopole Antenna

Abstract: This paper presents a shorted planar quasi semicircular monopole antenna (SPQSMA) for wideband wireless communication application. The shorting strip reduces the size of the antenna. A modified CPW feed is designed to match with 50Ω input impedance. Simulations have been performed to investigate the different characteristics of the antenna. This antenna has desirable characteristics such as very wide dual band (865 MHz to 1.42 GHz and 2.17 GHz to 20 GHz), low cost, ease of manufacture, compact size, bidirectional radiation pattern. The magnetic field distribution of the antenna is shown and a slot of semicircular shaped is introduced at the centre of radiator to reduce the weight, volume and cost of the antenna. The proposed antenna is suitable specially for GSM band and ultrawideband (UWB) applications.

shorting strip, dual band, CPW, ultrawideband.


1. Seong-Youp Suh, Stutzman, W.L., Davis, W.A., “A new ultrawideband printed monopole antenna: the planar inverted cone antenna (PICA),” Antennas and Propagation, IEEE Transactions on, Volume: 52, Issue: 5 Digital Object Identifier: 10.1109/TAP.2004.827529, Publication Year: 2004, pp. 1361 – 1364.
2. Li Tianming, Rao Yuping, Niu Zhongxia, “Analysis and Design of UWB Vivaldi Antenna,” Microwave, Antenna, Propagation and EMC Technologies for Wireless Communications, 2007 International Symposium on, Digital Object Identifier: 10.1109/MAPE.2007.4393685, Publication Year: 2007, pp. 579 – 581.

3. Junho Yeo; Yoonjae Lee; Mittra, R.; “Design of a wideband planar volcano-smoke slot antenna (PVSA) for wireless communications,” Antennas and Propagation Society International Symposium, 2003. IEEE Volume: 2, Digital Object Identifier: 10.1109/- APS.2003.1219321, Publication Year: 2003, pp. 655 – 658.

4. Agarwall, N. P., Kumar G., and Ray K. P., “Wide-Band Planar Monopole Antennas,” IEEE Trans. Antennas Propagation, Vol. 46, No. 2, 1998, pp. 294 – 295.

5. Sharma, M.M., Shrivastava, V., “Printed fractal elliptical monopole antenna for UWB application”, Recent Advances in Microwave Theory and Applications, 2008. MICROWAVE 2008. International Conference on Digital Object Identifier: 10.1109/AMTA.2008. 4763208, Publication Year: 2008, pp. 374 – 376.

6. Chen, Z.N., Ammann, M.J., Chia, M.Y.W., See, T.S.P.; “Annular planar monopole antennas,” Microwaves, Antennas and Propagation, IEE Proceedings, Volume: 149, Issue: 4, Digital Object Identifier: 10.1049/ip-map:20020701, Publication Year: 2002, pp. 200 – 203.

7. Evans, J.A., Amunann, M.J., “Planar trapezoidal and pentagonal monopoles with impedance bandwidths in excess of 10:1,” Antennas and Propagation Society International Symposium, 1999. IEEE, Digital Object Identifier: 10.1109/APS.1999.788241, Issue Date: Aug 1999, vol.3, pp. 1558 – 1561.

8. Zhi Ning Chen, “Impedance characteristics of planar bow-tie-like monopole antennas,” Electronics Letters, Volume: 36, Issue: 13, Digital Object Identifier: 10.1049/el: 20000816, Publication Year: 2000, pp. 1100 – 1101.

9. Tipsawate, T., Phongcharoenpanich, C., Kosulvit, S., “A wideband bidirectional antenna using truncated circular sector fed by rectangular monopole,” Electrical Engineering/ Electronics, Computer, Telecommunications and Information Technology, 2009. ECTI-CON 2009. 6th International Conference on, Volume: 02 Digital Object Identifier: 10.1109/ECTIC- ON.2009.5137163, Publication Year: 2009, pp. 782 – 785.

10. Lamultree, S., Phongcharoenpanich, C., Torrungrueng, D., “Design of UWB Bidirectional Rectangular Ring Antenna Fed by Stepped Monopole,” Microwave Conference, 2007. APMC 2007. Asia-Pacific, Digital Object Identifier: 10.1109/APMC.2007.4555121, Publication Year: 2007, pp. 1 – 4.

11. G. P. Gao, M. Li, S.F., Niu, X. J. Li; B. N. Li, “Study of a novel wideband circular slot antenna having frequency band-notched function,” Progress In Electromagnetics Research, volume: 96, 2009, pp. 141-154.

12. Jianxin Liang, Chiau, C.C., Xiaodong Chen, Parini, C.G., “Study of a printed circular disc monopole antenna for UWB systems,” Antennas and Propagation, IEEE Transactions on, Volume: 53, Issue: 11, Digital Object Identifier: 10.1109/TAP.2005.858598 Publication Year: 2005, pp. 3500-3504.

13. Qi Wu, Jin, R., Geng, J., “Ultra-wideband quasi-circular monopole antennas with rectangular and trapezoidal grounds,” Microwaves, Antennas & Propagation, IET, Volume: 3, Issue: 1, Digital Object Identifier: 10.1049/iet-map: 20070215, Publication Year: 2009, pp. 55 – 61.

14. Mondal S., P.P. Sarkar, “Wideband bidirectional planar shorted circular monopole antenna, ” 2nd International conference on computer, control, communication and information Technology (C3IT), Procedia Technology, Vol-4, 2012, pp. 421-426.






Pampa Debnath, Snehasis Roy

Paper Title:

An Analysis of Wave Guide E-Plane Tee as 3dB splitter at X Band Using HFSS Software

Abstract: In this paper, HFSS simulation software has been used to design X band E-plane Tee to study the power distribution between port 1 and 2 along with distribution of electric and magnetic fields. Phase of transmission coefficient between collinear arms is observed 180 degree and the power at collinear arms reflect the nature of 3 dB splitter of E plane tee. Simulation results also show the field analysis in collinear, and side arm. The analysis is helpful for designing magic tee and waveguide components using tee structure.

HFSS, E Plane TEE, E-port, Collinear arm, Transmission coefficient, X band.


1. M.Liu, Z.Feng, A novel hybrid planar SIW magic Tee, , pp. 1-4, APMC 2008.
2. L.Z.You, W.B.Dou, Design and Optimization of Planar Waveguide Magic Tee at W-band, pp. 1- 4, ICMMT-2007.

3. Pampa.Debnath,Snehasis,Roy, An Analysis of Wave guide Magic Tee at X band using HFSS, IJETAE,ISSN 2250-2459, Volume 2, Issue 5,May 2012.

4. P.Dawar, Design and Simulation of Magic Tee and Ring Hybrid Coupler using Ansoft HFSS, IJCST, vol 2, issue1,2011.

5. T.Sieverding and F. Arndt, Modal analysis of the magic tee, IEEE Microwave Guided Wave Lett., Vol. 3,150–152,1993.

6. Z.X.Shen, C.L. Law and C. Qian, Hybrid finite-element-modal-expansion method for matched magic T-junction, IEEE Trans. Magnetics, Vol. 38,385–388, 2002.

7. HFSS: High Frequency Structure Simulator based on the Finite Element Method, v. 9.2.1, Ansoft Corporation, 2004.

8. A.Das and S.K.Das, Microwave Engineering,2nd edition, New Delhi,Tata McGraw Hill,2009.

9. D.M.Pozar, Microwave Engineering, 2nd Edition, and New York: John Wiley &sons Inc,1998.

10. R.E.Collin, Foundation of Microwave Engineering, 2nd Edition McGraw-Hill Book Co, New York,1996.

11. M.L.Sisodia, G.S. Raghuvanshi, Microwave circuits and Passive Devices,2003.






Ujjwal Mondal, Parthasarathi Satvaya, Sourav Kumar Das

Paper Title:

Real-Time Speed Control of a DC Motor using Open Source Code Tools

Abstract: The presented work envisaged to explore the possibility of developing ultra-low cost experimental setup for teaching and learning Real-Time systems. The presented work demonstrates, in steps, the development of a real-time control system with free open source code softwares. The free suite utilized and experimented within the present work composed by Linux operating system and the Real Time Application Interface (RTAI) add-on, the Scilab Computer Aided Control System Design (CACSD) software and the Control & Measurement Device Interface (COMEDI) drivers. Scilab/Scicos, a free scientific software package for numerical computations and control system simulation is used with RTAI to provide hard real-time extensions in to Linux environment. The development and deployment platform are the same and consisted of the (i) Linux, (ii) Scilab/ Scicos (iii) RTAI and (iv) COMEDI drivers running in a PC. The investment is reduced to the hardware as well as in software cost, which consists of a standard PC, dc motor and a COMEDI compatible acquisition board. The most obvious advantage of the proposed solution is that all the software or codes are free & available in the web. The whole idea is demonstrated by real time speed control of a dc motor using Pulse Width Modulation (PWM).



1. R. Bucher and L. Dozio, Paolo Mantegazza, “Rapid Control Prototyping with Scilab/Scicos and Linux RTAI”, The Vlsi Journal (2004) pp. 739-744
2. J. Jang, C. K. Ahn, S. Han, and W. H. Kwon, “Rapid Control Prototyping for Robot Soccer System using SIMTool,” in ProcSICE-ICASE International Joint Conference 2006, Busan, Korea, Oct. 2006, vol. 2, pp. 3035–3039.

3. R. Bucher and L. Dozio, “CACSD with Linux RTAI and RTAI-Lab,” in Real Time Linux Workshop, Valencia, 2003.

4. Giovanni Racciu and Paolo Mantegazza. RTAI 3.3 User Manual, 2006. URL www.rtai.org.

5. “RTAI-Lab Tutorial” by Roberto Bucher, Simone Mannori and Thomas Netter, 2006

6. Ramine Nikoukhah and Serge Steer, SCICOS – A Dynamic System Builder and Simulator, User’s Guide, 1998. http://www.scilabsoft.inria.fr/doc/scicos/scicos.htm

7. Stephen L. Campbell, Jean-Philippe Chancelier, and Ramine Nikoukhah. Modeling and Simulation in Scilab/Scicos. Springer, Berlin, Germany, 2006. URL www.scicos.org

8. Roberto Bucher and Silvano Balemi “Scilab/Scicos and Linux RTAI –A unified approach” 2005 IEEE Conference on Control Applications Toronto, Canada, August 28-31, 2005.






R. K. Maity, A. Roy, S. Mukherjee, T. K. Barik, S. Bhunia

Paper Title:

Effects of Array Parameters on FSS Structure of Dipole Array

Abstract: This paper focuses on the study of the effects of the array parameters such as array spacing, length and width of the array element on the characteristics such as transmission coefficient, bandwidth of a Frequency Selective Surface (FSS) structure formed by uniform dipole array used in microwave frequency for communication. In this paper FSS structure of 20X20 half-wave dipole elements has been studied. Electromagnetic wave equations are solved by Method of Moment (MoM) and mathematical formulation has been programmed using MATLAB.

Frequency Selective surface, Half-Wave dipole, Periodic Array.


1. R. Ulrich, “Far-infrared Properties of Metallic Mesh and its Complementary Structure,” Infrared Phys. 7, 1967, pp. 37-55.
2. S.W.Lee, G. Zarrilo, and C. L. Law, “Simple Formulas for Transmission Through Periodic Metal Grids or Plates,” IEEE Trans. Antennas Propag. AP-30, 1982 pp. 904-909.

3. R. Mittra, C.Chan, and T. Cwik, “Techniques for Analysing Frequency Selective Surfaces—a Review,” IEEE Proc. 76 (23), 1988, pp. 1593-1615.

4. G. H. Schennum, “Frequency-Selective Surfaces for Multiple Frequency Antennas,” Microwave J. 16(5), 1973, pp. 55-57.

5. P. P. Sarkar, D. Sarkar, S. Das, S. Sarkar, and S. K. Chowdhury, “Experimental investigation of the frequency-selective property of an array ofdual tuned printed dipoles,” Microwave Opt. Tech. Lett., vol. 31, no. 3, pp.189–190, Nov. 5, 2001.

6. D. Sarkar, P. P. Sarkar, S. Das and S. K. Chowdhury, “An array of stagger-tuned printed dipoles as a broadband frequency selective surface”, MOTL, Vol. 35, No. 2, 2002, pp. 138 – 140.

7. John P. Gianvittorio et al., “Self-Similar Pre fractal Frequency Selective Surfaces for Multiband and Dual-Polarized Applications” IEEE Transactions on Antennas and Propagation, Vol. 51, No.11, pp 3088-3096, November 2003.

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9. Douglas J. Kern et al., “The Design Synthesis of Multiband Artificial Magnetic Conductors Using High Impedance Frequency Selective Surfaces” IEEE Transactions on Antennas and Propagation, Vol. 53, No.1,pp 8-17, January 2005.

10. B.A. Munk, “Frequency Selective Surfaces, Theory and Design” John Willey & Sons, 2000.

11. T.K.Wu “Frequency Selective Surface and Grid Array” John Willey & Sons, 1995

12. Raj Mittra, R.C. Hall, C. H. Tsao “Spectral domain analysis of circular patch frequency selective surfaces”, IEEE Trans., Antenna Propagat., vol 32, May, 1984, pp. 533-536.

13. R.F.Harrington, “Time-Harmonic electromagnetic Fields”, McGraw-Hill, New York, 1961, pp. 130 and pp. 365.






D. Mondal, S. Maity,R. Bera, S.Kumar, A. Ghosh M. Mitra

Paper Title:

Integrated Position & Velocity Measurement for Smart Vehicle Link

Abstract: This paper addresses the development efforts towards realization of radar based Smart vehicle. Commercial Vehicles with multiple radars has the limitation of more false detection as the detection technology is based on ‘ Skin’ mode of radar[1] operation and the radar receives its transmitted energy after reflection from the body of the target vehicles. The ‘Transponder’ mode of radar operation will definitely improve the false detection leading to CAWAS system (Collision Avoidance and Warning System)[2][3]. The Vehicles will be the ‘friends’ to each other by integrating the local radar mounted on each vehicle with Vehicular Communication. Furthermore, IHCS makes use of facilities to carry out traffic control and transmits the information to drivers and concerned departments, and implements traffic management measures, such as vehicle count, vehicle speed, vehicle range, speed control and so on.

Intelligent Highway Control system (IHCS), radar, RADCOM, DAR (Digital Array Radar), STAP (Space Time Adaptive Processing), collision, LFM, OFDM, CFAR .


1. Skolnik MI.Radar handbook.McGraw-Hill.
2. A. Barrientos et al, ‘CAWAS: Collision Avoidance and Warning system for Automotives based on Satellite’, 8th International IEEE Conference on Intelligent Transportation Systems Vienna, Austria, September 13-16, 2005.

3. Blake, L. V., A Guide to Basic Pulse-Radar Maximum Range Calculation Part-I Equations, Definitions, and Aids to Calculation, Naval Res. Lab. Report 5868, 1969.

4. ECC REPORT 56, ‘Compatibility of Automotive collision warning short range radar operating at 79 GHz with radio communication services’, Stockholm, October 2004.

5. N.B.Sinha, Dipak Mondal,M.Mitra ,and R.Bera “Prediction of Vehicle Classification And Channel Modelling For Intelligent Transportation ” JOURNAL OF ELECOMMUNICATIONS, VOLUME 5, ISSUE 1, OCTOBER 2010

6. Marcum, J. I., A Statistical Theory of Target Detection by Pulsed Radar, IRE Transactionson Information Theory. Vol IT-6, pp 59-267. April 1960.

7. Swerling, P., Probability of Detection for Fluctuating Targets, IRE Transactions on Information Theory. Vol IT-6, pp 269-308. April 1960.






Supriyo De, Subijit Mondal, Dibyendu Chowdhury

Paper Title:

Digital Watermarking with Secret Audio Sharing

Abstract: In today’s society with the increased use of computers, internet, and wireless communications, the need for safety and security has raised dramatically. The phenomenal growth of E-communication and new technologies has furnished to the need of secured communication and secure data transmission. The information can be a confidential document, it may be in form of image, audio, text etc. Some of the information transmitted can be intercepted illegally, such as personal information and private or secure messages. In this paper, implementation of secret sharing scheme is used to achieve the goal. We have proposed a technique to hide shared data into a digital image using the basics of cryptography to prepare a cipher key and meanwhile using the definition of digital watermarking to hide the fact that data is hidden. This helps to prevent the participant from incidental or intentional provision of a false or tampered stego-image. Consequently, the proposed scheme offers a high secure and cost effective mechanism for secret sharing.

Image processing, Secret sharing, Secure message transfer, Security watermarking, Steganography.


1. J. Cox, M. L. Miller and J. A. Bloom. Digital Watermarking,Research Report, New York: Academic Press, 2002.
2. Adelson, E., 1990. Digital signal encoding and decoding apparatus, US Patent no. 4,939,515, 1990.

3. Hsu, C.T., Wu, J.L., 1999. Hidden digital watermarks in images. IEEE Transactions of Image Processing 8, 58–68.

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6. Chang-Chou Lin, Wen-Hsiang Tsai, “Secret image sharing with steganography and authentication”, Journal of Systems and software, vol. 73, no. 3, pp. 405-414, 2004.

7. P.K. Naskar, A. Chaudhuri, A. Chaudhuri, “Image Secret Sharing with Steganography”, Proc. of Second National Conference on Computing and Systems – 2012, pp. xv-xix.

8. S De, D Choudhury, S Ghosh, P Maity, “A New Digital watermarking Scheme for Secret Audio Message Transmission”, Proc. of National Conference on Advanced Communication Systems and Design Techniques, 2011, pp. 118-122.

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Debasis Giri and Arpita Mazumdar

Paper Title:

A Secure Off-line Electronic Payment System Based on Bilinear Pairings and Signcryption

Abstract: In this paper, we have designed an off-line e-cash payment system based on bilinear pairings for low-value transaction. We use the concept of proxy signcryption for communication among the entities. In our system, the token is issued & authenticated by Bank. Customer delegates the signing capability to Merchant. Bank verifies the original signer (customer) and proxy signer (Merchant) and ensures the originality of the transaction. Unlike the existing e-payment system question of double spending of e-cash arises because each transaction is made uniquely identifiable. Hence, no separate protocol is needed to check double spending. The proposed scheme provides anonymity, authenticity, confidentiality and fairness.

Off-line; Proxy Signature; Security; Electronic Payment; Bilinear pairings.


1. Kevin Cattell and Shujlan Zhang, “Minimal cost one-dimensional linear hybrid cellular automata of degree through 500”. Journal of Electronic Tsting: Theory and Applications, 6:255-258, January 1995.
2. H. Oros, C. Popescu Horea Oros, Constantin Popescu Department of Mathematics and Computer Science, University of Oradea Str. Universitatii 1, Oradea, Romania, “A Secure and Efficient Off-line Electronic Payment System forWireless Networks”.Int. J. of omputers, Communications & Control, Vol. V , No. 4, pp. 551-557, 2010

3. Fangguo Zhang and Kwangjo Kim International Research center for Information Security (IRIS) Information and Communications University(ICU), 58-4 Hwaam-dong Yusong-ku, Taejon, 305-732 KOREA, “Efficient ID-Based Blind Signature and Proxy Signature from Bilinear Pairings”

4. Debasis Giri, Prithayan Barua, P. D. Srivastava and Biswapati Jana “A Cryptosystem for Encryption and Decryption of Long Confidential Messages”,ISA 2010,CCIS 76, PP 86-96,2010

5. Florian Hess,“Efficient Identity Based Signature Schemes Based on Pairings”,LNCS, Volume 2595/2003, 310-324,2003.

6. K. Cattell and J.C. Muzio, “Synthesis of one-dimensional linear hybrid cellular automata,” Submitted to IEEE Transactions on Computer- Aided Design, April 1994.

7. M. Serra, T. Slater, J.C. Muzio, and D.M. Miller, “The analysis of one-dimensional linear cellular automata and their aliasing properties,” IEEE Transactions on Computer-AidedDesign, vol. 9, pp. 767-778, July 1990.

8. Sukanta Das , “Theory and Applications of Nonlinear Cellular Automata In VLSI Design”, 2006

9. Yuliang Zheng, “Digital Signcryption or how to achieve ost(Signature \& Encryption)$ <<$ Cost (Signature) + Cost( Encryption)”- Monash University, Melbourne, Australia, CRYPTO ’97 Proceedings of the 17th Annual International Cryptology Conference on Advances in Cryptology,(LNCS 1294, Springer-Verlag, 1997), pp. 165-179.

10. R. Sai Anand and CE Veni Madhavan, “Online Transferable Ecash Payment System”, INDOCRYPT 2000, LNCS 1977, pp. 93-103, 2000.

11. Steve Glassman,Mark Manasse,Martín Abadi,Paul Gauthier and Patrick Sobalvarro, “Millicent Protocol for inexpensive E.commerce”.World Wide Web Journal, 4th WWW Conference Proceedings, p 603-618, December 1995.

12. W H He and TC- Wu, “Cryptanalysis and improvement of Peterson-Michels signcryption scheme”,IEE Proc.-Comput. Digit. Tech., Vol. 146, No. 2, 1999.

13. Min-Shiang Hwang and Pei-Chen Sung “A Study of Micro-payment Based on One-Way Hash Chain”, International Journal of Network Security, Vol.2, No.2, PP.81–90, Mar. 2006.






Avisankar Roy, P. P. Sarkar, Sunandan Bhunia

Paper Title:

Compact and Broadband Monopole Triangular Microstrip Patch Antenna with Shorting Pin

Abstract: A monopole triangular shaped, broadband, compact microstrip patch antenna with shorting pin is presented in this paper. By defecting the ground plane bandwidth of 38.7% with respect to center frequency of a Microstrip patch antenna has been achieved which can be used for WLAN application. 82.4% size reduction has also been achieved by using shorting pin of a microstrip patch antenna with inset feed. The simulation is done by using the Method of Moment based commercially available standard software.

Microstrip antenna, shorting pin, compact, broad band, defected ground


1. Garg, Bhatia, Bahl, Ittipiboon, “Micristrip Antenna Design Handbook”, Artech House INC, Norwood, NA 2001.
2. Zhi Ning Chen, “Antennas for Portable Devices”, John Wiley & Sons Ltd., 2007.

3. Kin-Lu Wong, “Planer Antennas for Wireless Communications”, John Wiley & Sons Ltd, 2003.

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7. Mahmoud N. Mahmoud, Reyhan Baktur, “A Dual Band Microstrip-Fed Slot Antenna”, IEEE Transactions on Antennas and Propagation, Vol. 59, NO. 5, MAY 2011, pp 1720-1724.

8. S. Sarkar, A. Das Majumdar, S. Mondal, S. Biswas, D. Sarkar, P. P. Sarkar, “Miniaturization of Rectangular Microstrip Patch Antenna using Optimized Single-Slotted Ground Plane”, Microwave and Optical Technology Letters, Vol. 53, No. 1 January 2011, pp 111-115.

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11. R. Porath, “Theory of miniaturized shorting-post micro-strip antennas,” IEEE Transactions, Antennas and Propagation, Vol. 48, No. 1, pp. 41-47, 2000.

12. Debatosh Guha, Yahia M. M. Antar, “Circular Microstrip Patch Loaded With Balanced Shorting Pins for Improved Bandwidth”, IEEE Antennas And Wireless Propagation Letters, Vol. 5, 2006, pp 217-219.

13. Wenquan Cao, Bangning Zhang, Hongbin Li, Tongbin Yi, Aijun Liu, “A Broadband Microstrip Dipole Antenna Loaded with Shorted Pin”, International Conference on Microwave and Millimeter Wave Technology (ICMMT), 2010, pp 1035-1037.

14. Yikai Chen, Shiwen Yang, and Zaiping Nie, “Bandwidth Enhancement Method for Low Profile E-Shaped Microstrip Patch Antennas”, IEEE Transactions on Antennas and Propagation, vol. 58, no. 7,July 2010, pp 2442-2447.

15. E. A´ vila-Navarro, J. Anto´ n, Jose´ M. Blanes, C. Reig, “Broadband Printed Dipole With Integrated Via-Hole Balun for WIMAX Applications”, Microwave and Optical Technology Letters, Vol. 53, No. 1 January 2011, pp 52-55.

16. Gaojian Kang, Zhengwei Du, “A Novel Compact Broadband Printed Monopole Antenna for Mobile Handsets”, Microwave and Optical Technology Letters, Vol. 53, No. 1 January 2011, pp 118-121.

17. W. Chen, K. F. Lee, and J. S. Dahele, “Theoretical and experimental studies of the resonant frequencies of the equilateral triangular microstrip antenna,” IEEE Trans. Antennas Propagation, vol. 40, pp. 1253-1256, 1992.

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23. J-S. Hong and S. Li, “Theory and experiment of dual mode microstrip triangular patch resonators and filters,” IEEE Trans. Microwave Theory Tech., vol. 52, pp. 1237-1243, 2004.

24. C. A. Balanis, “Advanced Engineering Electromagnetics”, John Wiley & Sons., New York, 1989.






Dibyendu Chowdhury, Sunandan Bhunia, Tarun Kumar Barik

Paper Title:

Study the Liquid Surface Capillary Wave Profile by Optical Method

Abstract: In this article, we describe a simple optics-based non-destructive experimental technique devised with the necessary background theoretical formulation to study the liquid properties like surface tension and surface capillary wave profile like wavelength and phase velocity of pure and impure water. Experimentally, we have estimated the surface tension of pure water using this optical method is (73.6+ 1.5) dyne/cm. We have also studied the variation of surface tension of water with adding organic and inorganic impurities using this same method. Finally we estimate the wavelength and phase velocity of capillary wave using the measured values of surface tensions of the above liquids.

Fraunhofer diffraction, Surface tension, Capillary wave profile


1. R. Bahadur, L. M. Russell and S. Alavi, “Surface Tensions in NaCl-Water-Air Systems from MD Simulations”, J. Phys. Chem. B, vol. 111, July 30, 2007, pp. 11989-11996.
2. J. Vanhanen, A. P. Hyvarinen, T. Anttila, T. Raatikainen, Y. Viisanen, and H. Lihavainen, “Ternary solution of sodium chloride, succinic acid and water; surface tension and its influence on cloud droplet activation” Atmos. Chem. Phys., vol. 8, 6 August 2008, pp. 4595–4604.

3. T. Mukhim and K. Ismail, “Micellization of Cetylpridinium Chloride in Aqueous Lithium Chloride, Sodium Chloride and Potassium Chloride Media”, International Conference on Soft Matter (ICSM 2004), Kolkata, India, Nov. 18 – 20, 2004, Vol. 21, No. 3-4, pp. 113-127.

4. P. A. Kralchevsky, K. D. Danov, C. I. Pishmanova, S. D. Kralchevska, N. C. Christov, K. P. Ananthapadmanabhan and A. Lips, “Effect of the Precipitation of Neutral-Soap, Acid-Soap, and Alkanoic Acid Crystallites on the Bulk pH and Surface Tension of Soap Solutions”, American Chemical Society, Langmuir, Vol. 23, No. 7, January 4, 2007, pp. 3538-3553.

5. F. Garbay, G. Weisbuch, “Light scattering by surface tension waves” American Journal of Physics, vol. 47, 1979, pp. 355-356.

6. Runcai Miao, Zongli Yang, Jingtao Zhu and Changyu Shen “Visualization of low-frequency liquid surface acoustic waves by means of optical diffraction”, Applied Physics letters, Vol. – 80, No. – 17, 29 April, (2002), pp. 3033-3035.

7. David Walkenhorst “Determining Surface Tension by Light scattering” Physics Department, The College of Wooster, Wooster, Ohio 44691, April 30, (1998).

8. Klemens, P. G. “Dispersion relations for waves on liquid surfaces” American Journal of Physics, vol. 52, 451-452 (1984).

9. J. W. Goodman, Introduction of Fourier optics (McGraw-Hill, San Francisco, (1968), pp. 61-63.

10. T. K.. Barik, A. Roy, and S. Kar “A simple experiment on diffraction of light by interfering liquid surface waves” Am. J. Phys., Vol. 73, No. 8, August 2005 ,
pp. 725 – 729.

11. T. K.. Barik, P. Roy Chaudhuri, A. Roy, and S. Kar, “Probing liquid surface waves, liquidproperties and liquid films with light diffraction”, Meas. Sci. Technol., vol. 17, 8 May, 2006, pp. 1553–1562.

12. K. Y. Lee, T. Chou, D. S. Chung, and E. Mazur, ‘‘Direct measurement of the spatial damping of capillary waves at liquid–vapor interfaces,’’ J. Phys. Chem. , vol. 97, 1993, pp. 12876–12878.

13. W. Heller, M. H. Cheng, and B. W. Greene, “Surface tension measurements by means of the “microcone tensiometer””, J. Colloid Interface. Sci., vol. 22, 1966, 179-194.

14. A. G. Gaonkar, and R. D. Neuman, “The surface tension of water”, Colloids Surf. , vol. 27, 1987, pp. 1-3.

15. J. J. Jasper, “The surface tension of pure liquid compounds”, J. Phys. Chem. Ref. Data , vol. 1, 1972, pp. 841-1009.

16. H. Fujii, T. Matsumoto, T. Ueda, and K. Nogi, “A new method for simultaneous measurement of surface tension and viscosity”, J. Mater. Sci., vol. 40, 2005, pp. 2161-2166.

17. A. A. Abramzon, and R. D. Gauberk, “Surface Tension of Salt Solutions”, Zh. Prikl. Khim. (St. Petersburg), vol. 66, 1993, pp. 1428-1430.

18. A. W. Adamson, Physical Chemistry of Surfaces; Wiley: NewYork, 1990.

19. W. Wu, and G. H. Nancollas, “Determination of interfacial tension from crystallization and dissolution data: a comparison with other methods.”, Adv. Coll. Interface Sci., , vol. 79, 1999, pp. 229-279.

20. http://wiki.answers.com/Q/Does_vegetable_oil_have_more_surface_tension_than_water.






Anindya Sundar Das, Satyajit Das and Jaydeb Bhaumik

Paper Title:

Design of RS (255, 251) Encoder and Decoder in FPGA

Abstract: Detection and correction of errors in digital data is an important issue for the modern communication systems. Therefore an efficient error control code is needed to protect the digital data. In high speed communication system Reed-Solomon codes are widely used to provide error protection especially against the burst errors. Reed-Solomon codes are cyclic, non-binary codes. In this paper RS(255, 251)encoder and decoder have been designed and implemented on an FPGA platform.

Reed-Solomon codes, Galois field, RS encoder, RS decoder.


1. S. Lin and D. J. Costello, Error Control Coding: Fundamentals and Applications. Englewood Cliffs, NJ: Prentice-Hall, 1983.
2. R. E. Blahut, Theory and Practice of Error Control Codes. Addison- Wesley, 1983

3. S. B. Wicker and V. K. Bhargava, Reed Solomon Codes and Their Applications, IEEE Press, 1994.

4. T. K. Matsushima, T. Matsushima, and S. Hirasawa, “Parallel architecture for high-speed Reed-Solomon codec,” in Proc. IEEE Int. Telecommunication. Symposium. 1998, pp. 468–473.

5. D. V. Sarawate and N. R. Shanbhag, “High-speed architectures for Reed-Solomon decoders,” IEEE Trans. on VLSI Systems, vol. 9, no. 5, Oct. 2001, pp. 641-655.

6. E. Mastrovito. “VLSI Architectures for Computations in Galois Fields,” Ph. D. Dissertation, Dept. of Electrical Engineering, Linkoping University, Linkoping, Sweden, 1991.

7. L. Song, K. K. Parhi, I. Kuroda. and T. Nishitani. “Hardware/software codesign of finite field datapath for low-energy Reed-Solomon codecs,” IEEE Trans. on VLSI Systems, vol. 8. no. 2, Apr. 2000, pp. 160-172.

8. C. Y. Lee, Y. H. Chen, C. W. Chiou and J. M. Lin, “Unified Parallel Systolic Multipliers over GF(2m),”Journal of Computer Science and Technology, vol. 22, Jan. 2007, pp. 28-38.






Jaydeb Bhaumik, Anindya Sundar Das and Jagannath Samanta

Paper Title:

Architecture for Programmable Generator Polynomial Based Reed-Solomon Encoder and Decoder

Abstract: Reed-Solomon Codes are popularly used for error correction in many applications like storage devices (CD, DVD), wireless communications, high speed modems and satellite communications. In this paper, a modified scheme for programmable generator polynomial based Reed-Solomon encoder and decoder has been proposed. The works reported in this paper corrects errors in derived equations and decoder architecture proposed by Shayan et al. Moreover, modified architectures for programmable generator polynomial based Reed-Solomon encoder and decoder are reported.

Reed-Solomon Code, Finite Field, Encoder and Decoder Architectures


1. Reed and G. Solomon, “Polynomial codes over certain finite fields,”Journal of the Society for Industrial and Applied Mathematics, vol. 8, no. 2, Jun 1960, pp. 300-304.
2. J. Bhaumik and D. Roy Chowdhury, “An Integrated ECC-MAC Basedon RS Code,” Transactions on Computational Science, vol. IV, LNCS5430, Apr. 2009, pp. 117-135.

3. Y. R. Shayan and T. Le-Ngoc, “Decoding Reed- Solomon codes generated by any generator polynomial,” Electronics Letters, vol. 25, no. 18, Aug. 1989, pp. 1223-1224.

4. Y. R. Shayan, T. Le-Ngoc and V. K. Bhargava, “A versatile time-domain Reed-Solomon decoder,” IEEE Journal on Selected Areas in Communications archive, Vol. 8 no. 8, Sept. 2006, pp. 1535-1542.

5. H. Y. Hsu and A. Y. Wu, “VLSI Design of a Reconfigurable Multimode Reed-Solomon Codec for High Speed Communication Systems,” in IEEE Asia-Pacific Conference on ASIC, 2002, pp. 359-362

6. S. B. Wicker and V. K. Bhargava, Reed Solomon Codes and Their Applications. IEEE Press, 1994.

7. H. Krawczyk, “LFSR-based hashing and authentication,” in Proc. Advances in Cryptology-CRYPTO, 1994, vol. LNCS 0839, pp. 129-139.

8. C. C. Y. Lam, G. Gong and S. Vanstone, “Message authentication codes with error correcting capabilities,” in 4th Int. Conf. on Information and Communications Security, 2002, vol. LNCS 2513, pp. 354-366

9. D. V. Sarawate and N. R. Shanbhag, “High-speed architectures for Reed- Solomon decoders,” IEEE Trans. on VLSI Systems, vol. 9, no. 5, Oct. 2001, pp. 641-655.

10. V. Rijmen, J. Daemen, B. Preneel, A. Bosselaers and E. De Win, “The cipher SHARK,” in Fast Software Encryption, 1996, vol. LNCS 1039, pp. 99-111.

11. S. Lin and D. J. Costello, Error Control Coding: Fundamentals and Applications. Englewood Cliffs, NJ: Prentice-Hall, 1983.

12. R. E. Blahut, Theory and Practice of Error Control Codes. Addison- Wesley, 1983.






Snigdha Madhab Ghosh, Partha Mitra, Sunandan Bhunia

Paper Title:

In search of Emotional Manifestation in ECG Signal

Abstract: Emotion detection recognition in physiological signal and categorization their of, is very challenging. There are many methods for detecting the emotional features from physiological and ECG is one of them. In this paper we have analyzed sixteen ECG signals of two different groups and tried to find some similarities among the same group and also between these two groups based on two parameters viz mean instantaneous frequency(MIF) and correlation coefficient, with an aim to classify their emotion.

Electrocardiogram, emotion, empirical mode of decomposition, intrinsic mode function, mean instantaneous frequency.


1. Panagiotis C. Petrantonakis, and Leontios J. Hadjileontiadis“Emotio Recognition From EEG Using Higher Order Crossings” IEEE Transactions on Information Technology in Biomedicine ,Vol . 14, No. 2, March 2010.
2. P. SaloVey and J. D. Mayer, “Emotional intelligence,” Imagination, Cognition Pers., vol. 9, no. 3, pp. 185–211, 1990.

3. D. Goleman, Emotional Intelligence. New York: Bantam Books, 1995.

4. “Emotions in Humans and Artifacts” edited by Robert Trappl Paolo Petta Sabine Payr, Apr 2003 ISBN 0262201429, http://cs5937.userapi.com/u11728334/ docs/fc9aa0f94f61/Robert_ Trappl _Emotions_in_Humans_and_Artifact.pdf.

5. What is Emotion? http:// knowledgerush. com/kr/ encyclopedia/ Emotion .

6. S. Valins, “Cognitive Effects of False Heart-Rate Feedback,” Journal of Personality and Social Psychology, 4, 400-408

7. Joris H. Janssen, Jeremy N. Bailenson, Wijnand A. IJsselsteijn, and Joyce H.D.M. Westerink, “Intimate Heartbeats: Opportunities for Affective Communication Technology” IEEE Transaction on affective computing vol1. No 2July-December2010

8. N E Huang, Z Shen, R.R Long M.L Wu, Q Zheng, N C Yen and C. C Tung, “The Empirical Mode Decomposition and Hilbert Spectrum for Nonlinear and Nonstationary Time Series Analysis”, proc. Royal Soc London vol. 454,pp 903-995,1998.

9. Po-Hong Wu , National Taiwan University, Taipei, Taiwan“Hilbert Huang transform for Climate Analysis” http://djj.ee.ntu.edu.tw/HHT_Climate.pdf






Shreyash Srivastava, Shaurya Ahuja, Shivam Tyagi

Paper Title:

Determining Keirsey Temperament Class of a Person Based on his GPS Data

Abstract: The smart phone market has steadily gone up in the recent years. The technologies have taken a further leap and immensely improved. The Global Positioning System (GPS) is one location acquisition technology that is present in almost every smart phone that we use. The dataset obtained from the location acquisition technologies can in some way be used to determine various useful results and conclusions from the movement patterns of a person. The places a person visits and the frequency of visits, to some extent describe his personality. This paper presents one such innovative idea to determine the Keirsey Temperament class of a person by processing his collected GPS data.

Global Positioning System, location acquisition, temperament, data mining, reverse geocoding.


1. David Keirsey and Marilyn Bates, Please Understand Me: Character and Temperament Types, 5th edition, Gnosology Books Ltd., 1984.
2. Isabel Briggs Myers and Mary H. McCaulley, Manual: A guide to the development and use of the Myers-Briggs Type Indicator, Consulting Psychologists Press, 1985.

3. Myers, Isabel Briggs with Peter B. Myers (1980, 1995). Gifts Differing: Understanding Personality Type. Mountain View, CA: Davies-Black Publishing. pp. xi–xii. ISBN 0-89106-074-X

4. Olaf Isachsen and Linda V. Berens, Working Together: A Personality Centered Approach to Management, Networld Management Press, 1991.

5. Jung, Carl (1976). Campbell, Joseph. ed. The Portable Jung. New York, NY: Penguin Books. pp. 178.

6. Yu Zheng, Quannan Li, Yukun Chen and Xing Xie. “Understanding Mobility Based on GPS Data”. In Proc. Ubicomp 2008. ACM Press: 312-321, Sept. 2008.

7. Yu Zheng, Lizhu Zhang, Xing Xie and Wei-Ying Ma. “Mining Interesting Locations and Travel Sequences from GPS Trajectories”. In Proc. WWW 2009, April 2009.

8. Yu Zheng, Lizhu Zhang, Zhengxin Ma, Xing Xie and Wei-Ying Ma. “Recommending Friends and Locations Based on Individual Location History”. In Proc. TWEB. Vol. 5 Issue 1 Article 8, Feb. 2011.

9. G. Agamennoni, J. Nieto and E. Nebot. “Mining GPS Data for Extracting Significant Places”. In Proc. ICRA ’09, IEEE, 855-862, May 2009.

10. Kathryn Jo-Ann McPhail, (2002),”The nursing profession, personality types and leadership”, Leadership in Health Services, Vol. 15 Iss: 1 pp. 7 – 10

11. GeoLife GPS Trajectories (2011), Available: http://research.microsoft.com/en-us/downloads/b16d359d-d164-469e-9fd4-daa38f2b2e13/default.aspx

12. Xin Cao, Gao Cong and Christian S. Jensen “Mining Significant Semantic Locations from GPS Data”. In Proc. VLDB Endowment, Vol. 3, Issue 1-2. 1009-1020,
Sept. 2010.

13. Vincent W. Zheng, Yu Zheng, Xing Xie, Qiang Yang. “Collaborative Location and Activity Recommendations with GPS History Data”. In Proc. WWW ’10.

14. S. Srivastava, S. Ahuja, A. Mittal, Determining Most Visited Locations Based on Temporal Grouping of GPS Data, Advances in Intelligent and Soft Computing,
Volume 131, 2012, DOI 0.1007/978-81-322-0491-6:

15. New World Encyclopedia – http://newworldencyclopedia/entry/Myers-Briggs Type Indicator

16. Wikimapia – http://www.wikimapia.org

17. Personality Page – http://www.personalitypage.com






Mohd Shoab, Kamal Jain, M Shashi

Paper Title:

Development and Implementation of Web Service for Logging and Retrieving Real Time Train Location Information

Abstract: Global Positioning System (GPS) is widely used for vehicle tracking, navigation and also used for tracking Trains. Transmitting the location information of a moving train is challenging work. In this paper a Web Service is proposed to store location and navigation information in to a central server for monitoring the trains. Remote GPS device call this web service for transmitting location and navigation information to the central server. This web service is a bidirectional web service by which you can send and receive train location and navigation information. Remote GPS device can be a PDA, Smartphone or a dedicated GPS device. This web service is developed in c# .net using Visual Studio 2010.

GPS, Navigation, Web Service.


1. Abbasali Jandaghi Alaei and Mahmoud Reza Delavar, “Integration of GPS and GIS for Railway Accident Management” Preceding Conference Simtect’s, Adelaide, Australia, June, 2003.
2. Ankur Chandra, Shashank Jain and Mohammed Abdul Qadeer, “GPS Locator: An Application for Location Tracking and Sharing using GPS for JAVA Enabled Handhelds” in International Conference on Computational Intelligence and Communication Systems. 2011
3. G. Goulas, V. Barkayannis, S. Gianoulis, C. Gogos, P. Alefragis, P. Foundas, C. Valouxis, S. Koubias and E. Housos,“ ERMIS: A Helicopter Taxi Company Software Support System based on GPS, GSM and Web Services” in IEEE Conference on Emerging Technologies and Factory Automation, 2006. ETFA ’06.
4. Hakan Guler, Murat Akad and Murat Ergun “Railway Asset Management System in Turkey: A GIS Application” in FIG Working Week 2004 Athens, Greece, May 22-27, 2004.
5. Iman M. Almomani, Nour Y. Alkhalil, Enas M. Ahmad and Rania M. Jodeh, “Ubiquitous GPS Vehicle Tracking and Management System” in IEEE Jordan Conference on Applied Electrical Engineering and Computing Technologies (AEECT). 2011
6. Introduction to Web Service by
7. http://www.w3schools.com/webservices/ws_intro.asp
8. Luqun Li, Minglu Li, Changqin Ji and Dong Wang, “The Study on Mobile Web Service Computing for Data Collecting” in International Conference on Communications, Circuits and Systems, 2004. ICCCAS 2004.
9. Types of Web Services by
10. http://xml.indelv.com/rpc-soa-rest-the-most-well-known-types-of-web-services.html
11. Web Service Architecture by
12. http://www.w3.org/TR/2002/WD-ws-arch-20021114/
13. Web Services by






Ashwani Jain, Nitish Puri

Paper Title:

Consolidation Characteristics of Highly Plastic Clay Stabilised With Rice Husk Ash

Abstract: One-dimensional consolidation tests have been conducted to study the effect of addition of various percentages of rice husk ash on compressibility characteristics of highly plastic clay soil. Statically compacted soil specimens have been prepared at optimum moisture content and maximum dry density by adding 4, 8, 12, 16 and 20% by weight of rice husk ash to the parent soil. Specimens have been subjected to increments of vertical pressure of 0.25, 0.50, 1.00, 2.00 and 4.00 kg/cm2 in a fixed ring consolidometer. It has been observed due to the addition of rice husk ash to the parent clay, the optimum moisture increases and maximum dry density decrease with increase in percentage of rice husk ash. Coefficient of compressibility (av) and coefficient of volume compressibility (mv) show no significant trend for variation in values with change in proportion of rice husk ash in the soil at a particular effective stress. It has been observed that there is decrease in the values of these parameters with increase in effective stress for a particular percentage of rice husk ash. Compression index (Cc) has been found to decrease significantly with increase in percentage of rice husk ash, hence decreasing consolidation settlement of parent material. It has also been observed that the time required for achieving a given degree of consolidation decreases with increase in the percentage of rice husk ash at a particular effective stress. Overall, it has been observed that rice husk ash effectively increase one-dimensional stiffness and therefore, reduce settlement.

Rice husk ash (RHA), stabilization, compressibility, characteristics, maximum dry density and optimum moisture content.


1. Eberemu, Adrian O. (2011), “Consolidation Properties of Compacted Lateritic Soil Treated with RHA”, Geomaterals, 1, 70-78.
2. Giddel, M.R. and Jivani, A.P. (2007), “Waste to Wealth – Potential of Rice Husk in India – A Literature Review”, Proceedings of the International Conference on Cleaner Technologies and Environmental Management, PEC, Pondicherry, India.

3. Handy, R.L. and Spangler, M.G. (2007), “Geotechnical Engineering: Soil and Foundation Principles and Practice”, McGraw-Hill, Fifth Edition.

4. IS: 1498 (1970),”Indian Standard Methods of Test for Soils: Classification and Identification of Soil for General Engineering Purposes”, Bureau of Indian Standards.

5. IS: 2720 (Part 7) (1974), “Indian Standard Methods of Test for Soils: Determination of Moisture Content-Dry Density Relation using Light Compaction”, Bureau of Indian Standards.

6. IS: 2720 (Part 15) (1986), “Indian Standard Methods of Test for Soils: Determination of Consolidation Properties”, Bureau of Indian Standards.

7. Rao, D. Koteswara, Raju, G.V.R. Prasada and Kumar, K. Ashok (2011), “Consolidation Characteristics of Treated Marine Clay for Foundation Soil Beds”, International Journal of Engineering Science and Technology (IJEST), Vol. 2, No.3, 788-796.

8. Ranjan, Gopal and Rao, A.S.R. (2000), “Basic and Applied Soil Mechanics”, New Age International (P) Ltd., New Delhi.

9. Singh, Alam and Chowdhary, G.R. (1994), “Soil Engineering in Theory and Practice”, Geotechnical Testing and Instrumentation, Vol. 2, CBS Publishers and Distributors, Delhi.






M.Thamarai, R.Shanmugalakshmi

Paper Title:

Multi objective Particle Swarm Optimization in video coding

Abstract: Particle Swarm Optimization (PSO) is a global optimization technique based on swarm intelligence. It simulates the behavior of bird flocking. It is widely accepted and focused by researchers due to its profound intelligence and simple algorithm structure. Currently PSO has been implemented in a wide range of research areas such as functional optimization, pattern recognition, neural network training and fuzzy system control etc., and obtained significant success. In this paper the application of Particle swarm optimization for video coding is analyzed The application of multi objective optimization using PSO for optimal subband selection of the dualtree discrete wavelet transform is proposed and analyzed. The results are compared with the standard techniques. The video coding using PSO and Dualtree wavelet transform provides better PSNR values when compared to the PSO based Block based coders. The performance variation of the PSO based coder in various aspects such as swarm size variation and threshold value variation for frame rates are also measured.

Dualtree Discrete Wavelet Transform, Multi objective Particle Swarm Optimization, Noise Shaping and MSE


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2. J. Kennedy ., R.C Eberhart, “A discrete binary version of the particle swarm optimization algorithm”, in IEEE International Conference on Neural Networks, Perth, Australia, 1997, 4104-4108.

3. Eduardo Asbun, “Improvements in Wavelet based rate scalable video compression”, Ph.D. Thesis December 2000.

4. J.-R. Ohm, “Advances in scalable video coding,” Proceedings of the IEEE, vol. 93, ,2005,pp. 42-56.

5. S-T Hsiang and J. W. Woods, “Embedded video coding using invertible motion compensated 3-D subband/wavelet filter bank”, Signal Processing: Image Communications, vol. 16, 2001 pp. 705-724.

6. Ivan.w.Selesnick,Ke. Yong Li, “ Video denoising using 2D and 3D Complex dual tree wavelet transform,Proceedings,Wavelet applications in signal and image processing 2003,,XSPIE ,5207.

7. B. Wang, Y. Wang, I. Selesnick, and A. Vetro,. “An investigation of 3D dual-tree wavelet transform for video coding, in Proceedings of the International Conference on Image Processing, 2004, vol. 2, Singapore, pp. 1317–1320.

8. T. H. Reeves , Kingsbury N. G., “Over complete image coding using iterative projection- based noise shaping, Signal Processing Group University of Cambridge 2002,U.K.ICIP 02, Rochester, New York

9. B. Wang, Y. Wang, I. Selesnick, and A. Vetro,. “ Video coding using 3- D dual- tree wavelet transform,” EURASIP Journal on Image and Video Processing, , 2007 article ID 42761.

10. K.U.Parsopoulos, M.N.Varahatis,, “Particle swarm optimization method in multi objective problems”, Proceedings of the ACM Symposium on applied Computing Madrid, Spain, ACM Press,2002, pp.603-607.

11. Abdullak Konak,David W.Coit,Alice E.Smith,“Multi objective optimization using genetic algorithms –a tutorial” journal on Reliability Engineering in system safety pp. 2006,992-1007.

12. Bong Chin-Wei, Mandhava Rajeswari, Multi objective optimization approaches in Image segmentation-The directions and challenges” International journal of advance soft computing applications 2010,Vol.2, No.1.

13. A.Boukhobza, Optimization design of orthogonal filter banks for image coding via multi objective genetic algorithm UHBC University, Chlef Algeria.

14. Charos A. Cello Cello, Gregorio Toscano Pulido, Maximino Salazar, “Handling multi objectives with Particle Swarm Optimization”,IEEE.Transactions on Evolutionary Computation 2004,Vol.No.8.

15. Chunjuan Ouyang, Xia Li,Na Wang,”A best wavelet packet basis image compression algorithm based on PSO” Proceedings of the fourth international conference on Genetic E






Firas Ajil Jassim

Paper Title:

Image Denoising Using Interquartile Range Filter with Local Averaging

Abstract: Image denoising is one of the fundamental problems in image processing. In this paper, a novel approach to suppress noise from the image is conducted by applying the interquartile range (IQR) which is one of the statistical methods used to detect outlier effect from a dataset. A window of size kk was implemented to support IQR filter. Each pixel outside the IQR range of the kk window is treated as noisy pixel. The estimation of the noisy pixels was obtained by local averaging. The essential advantage of applying IQR filter is to preserve edge sharpness better of the original image. A variety of test images have been used to support the proposed filter and PSNR was calculated and compared with median filter. The experimental results on standard test images demonstrate this filter is simpler and better performing than median filter.

Image enhancement, Noise Removal, Image filter, IQR filter.


1. A. A. Gulhane and A. S. Alvi, “Noise Reduction of an Image by using Function Approximation Techniques”, International Journal of Soft Computing and Engineering (IJSCE) Volume-2, Issue-1, March 2012
2. C. Liu, R. Szeliski, S. B. Kang, C. L. Zitnick, and W. T. Freeman, “Automatic Estimation and Removal of Noise from a Single Image Noise from a Single Image”, IEEE Transactions on Pattern Analysis And Machine Intelligence, Vol. 30, No. 2, February 2008

3. D. Shekar and R. Srikanth, “Removal of High Density Salt & Pepper Noise in Noisy Images Using Decision Based UnSymmetric Trimmed Median Filter (DBUTM)”, International Journal of Computer Trends and Technology, vol. 2, Issue 1, 2011

4. F. M. Dekking, C. Kraaikamp, H.P. Lopuhaa, L.E. Meester, A Modern Introduction to Probability and Statistics: Understanding Why and How, Springer-Verlag, London Limited, 2005, pp:236

5. G. Hanji and M. V. Latte, “A New Impulse Noise Detection and Filtering Algorithm”, International Journal of Scientific Research and Publications, Vol. 2, Issue 1, 2012.

6. H. Hosseini, F. Marvasti, “Fast Impulse Noise Removal from Highly Corrupted Images”, Available:

7. H. Hwang and R. A. Haddad, “Adaptive Median Filters: New Algorithms and Results”, IEEE Transactions on Image Processing, Vol. 4, No. 4, 1995 http://arxiv. org/ftp/arxiv/papers/1105/11052899. pdf

8. J. M. C. Geoffrine and N. Kumarasabapathy, “Study And Analysis Of Impulse Noise Reduction Filters”, Signal & Image Processing : An International Journal(SIPIJ), Vol.2, No.1, March 2011

9. J.S. Marcel, A. Jayachandran, G. K .Sundararaj, “An Efficient Algorithm for Removal of Impulse Noise Using Adaptive Fuzzy Switching Weighted Median Filter”, International Journal of Computer Technology and Electronics Engineering (IJCTEE), Vol 2, Issue 2, 2012

10. K. R. Castleman, Digital Image Processing, Prentice Hall, 1996, pp:414

11. M. S. Nair, K. Revathy, and R. Tatavarti, “Removal of Salt-and Pepper Noise in Images: A New Decision-Based Algorithm”, Proceedings of the International MultiConference of Engineers and Computer Scientists IMECS, 19-21 March, Hong Kong, Vol I, 2008

12. R. C. Gonzalez and R. E. Woods. Digital Image Processing, Prentice Hall, New Jersey 07458, second edition, 2001, pp: 222.

13. R. H. Chan, C.-W. Ho, and M. Nikolova, “Salt-and-Pepper Noise Removal by Median-Type Noise Detectors and Detail-Preserving Regularization”, IEEE Transactions on Image Processing, Vol. 14, No. 10, October 2005

14. S. S. Al-Amri, N.V. Kalyankar, and Khamitkar S.D, “A Comparative Study of Removal Noise from Remote Sensing Image”, International Journal of Computer Science Issues, Vol. 7, Issue. 1, No. 1, January 2010

15. S.-S. Ieng, J.-P. Tarel and P. Charbonnier, “Modeling Non-Gaussian Noise For Robust Image Analysis”, In proceeding of: VISAPP 2007: Proceedings of the Second International Conference on Computer Vision Theory and Applications, Barcelona, Spain, March 8-11, 2007 – Volume 1

16. T. Gebreyohannes, and K. Dong-Yoon, “Adaptive Noise Reduction Scheme for Salt and Pepper”, Signal & Image Processing: An International Journal, Vol. 2 Issue 4, Dec2011 p47

17. V. Jayaraj , D. Ebenezer, and K. Aiswarya, “High Density Salt and Pepper Noise Removal in Images using Improved Adaptive Statistics Estimation Filter”, International Journal of Computer Science and Network Security, Vol.9 No.11, November 2009

18. V. R. Vijay Kumar, S. Manikandan, P. T. Vanathi, P. Kanagasabapathy, and D. Ebenezer, “Adaptive Window Length Recursive Weighted Median Filter for Removing Impulse Noise in Images with Details Preservation”, ECTI Transactions on Electrical Eng., Electronics, and Communications, Vol.6, No.1 February 2008

19. W. K. Pratt, Digital Image Processing, Fourth Edition, John Wiley & Sons, Inc., Publication, 2007, pp:267.

20. W. W. Daniel, Biostatistics: A Foundation for Analysis in the Health Sciences, eighth edition, John Wiley & Sons Inc., 2005, pp: 44-47.






Naila Rozi, Nasir uddin khan, Zuhair Hasnain

Paper Title:

Principal of Repeated DNA

Abstract: DNA sequences in the nuclear diploid genome usually exist as two allelic copies ( on paternal and maternal homologous chromosomes . in addition to this degree of repetition , approximately 40 % of the human nuclear genome in both haploid and diploid cells is composed of sets of closely related nonallelic DNA sequences (DNA sequences families or repetitive DNA).within the considerable variety of different repetitive DNA sequences are DNA sequence families whose individual members include functional genes (multigene families)& also many examples of nongenic repetitive DNA sequence families.

DNA, Multigene families, homologous chromosomes


1. Naila Rozi, Nasir Uddin Khan,2nd ABRC 2009Conference of Comsat Institute Lahore on 22-23 october,2009(Geometric Patterns of DNA Help In Signal Processing
2. Naila Rozi and Nasir Uddin khan, Journal of Life Sciences, U.S.A(ISSN-1934-7391),Termination of DNA replication and role of enzymes in recombination Vol#5,Number2,February2011.

3. Naila Rozi, Nasir Uddin Khan, ISSN# 2073 7122.JournalofIJCRB,Jan.2011,vol#2,page#528 Improve Hidden Markov Model In DNA SequencesHMM).

4. Naila Rozi, Nasir Uddin Khan2ND ICECS Conferenc,28-30DEC2009Proceeding IEEE,DUBAI,U.A.E,Number Patterns Geometric representation of DNA, ISBN978- 7695-3937-9,page#343-344G.






P. Samundiswary, M. Raj Kumar Naik

Paper Title:

Performance Analysis of Deterministic Energy Efficient Clustering Protocol for WSN

Abstract: Recently, there has been an increase in the use of ad hoc wireless sensor networks for monitoring environmental information (temperature, sound levels, humidity etc) across an entire physical space. In sensor networks, sensor nodes are used to gather local data and communicate with other nodes. Wireless sensor network (WSN) is built of several “nodes” from a few to several hundreds or even thousands, where each node is connected to one (or sometimes several) sensors. The main challenging task in this network is routing. There are different types of protocols in WSN used to route the packets from source to destination. They are data centric, hierarchical, location–based and QoS aware. Low-Energy Adaptive Clustering Hierarchy (LEACH) protocol is one of the best hierarchical protocols utilizing the probabilistic model to manage the energy consumption of WSN. However LEACH offers unguaranteed election of cluster head and election is not guaranteed to be optimal. In this paper, Deterministic Energy-efficient Clustering protocol (DEC), a deterministic model is developed to analyse the network performance. A deterministic energy-efficient clustering protocol promises a better election of cluster-heads and is dynamic, distributive, self-organizing and more energy efficient than the existing conventional LEACH protocols. Then the performance parameters such as number of rounds and energy dissipation of LEACH and DEC protocols are determined and analyzed by varying coverage area, packet length and nodes. The simulation is done by using MATLAB. The simulation results shows that DEC protocol has better performance than the existing LEACH protocol.

Energy efficiency, DEC, LEACH, Wireless Sensor Networks.


1. F. A. Aderohunmu, J. D. Deng, and M. K. Purvis, “Enhancing Clustering in Wireless Sensor Networks with Energy Heterogeneity”. International Journal of Business Data Communications and Networking, vol.7, no.4, pp.18-31, 2011.
2. W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, “An Application-Specific Protocol Architectures for Wireless Networks”, IEEE Transactions on Wireless Communications, vol.1,no.4, pp.660-670, 2002.

3. G. Smaragdakis, I. Matta, and A. Bestavros, “SEP: A Stable Election Protocol for clustered heterogeneous wireless sensor networks”, Proceedings of the International Workshop on Sensor and Actor Network Protocols and Applications, Boston, MA, pp.121-129, Aug 2004.

4. O. Younis and S. Fahmy, “HEED: A Hybrid, Energy-Efficient, Distributed Clustering Approach for Ad Hoc Sensor Networks”, IEEE Transactions on Mobile Computing, vol.3, no.4 pp.366–379, December 2004.

5. L. Qing, Q. Zhu, and M. Wang, “Design of a Distributed Energy-efficient Clustering algorithm for heterogeneous wireless sensor networks”, Computer Communication, vol. 29, pp. 2230–2237, August 2006.

6. Aderohunmu F.A., Deng J.D., Purvis M.K., “A deterministic energy-efficient clustering protocol for wireless sensor networks”, Proceedings of Seventh IEEE International Conference on Intelligent Sensors, Sensor Networks and Information Processing, pp.341 – 346, 2011.

7. I. F. Akyildiz, W. Su, Y. Sankara subramaniam, and E. Cayirci, “Wireless sensor networks: a survey”, Computer Networks, vol.38, no.4, pp.393-422, 2002.

8. Shio Kumar Singh , M P Singh , and D K Singh “Routing Protocols in Wireless Sensor Networks- A Survey” International Journal of Computer Science & Engineering Survey, vol.1, no.2, pp.63-83, Nov 2010.

9. M. Haase and D. Timmermann, “Low energy adaptive clustering hierarchy with deterministic cluster-head selection”, Proceedings of IEEE Conference on Mobile and Wireless Communications Networks, pp.368–372, Sweden, 2002.

10. Rajashree. V.Biradar,V.C .Patil, Dr. S. R. Sawant, Dr. R. R. Mudholkar “Classification And Comparison Of Routing Protocol In Wireless Sensor Networks” ,Special Issue on Ubiquitous Computing Security Systems, vol.4, pp.701-711, 2012.

11. F. Comeau, “Optimal Clustering in Wireless Sensor Networks Employing Different Propagation Models And Data Aggregation Techniques”, Ph.D. Thesis, Dalhousie University, Halifax, Nova Scotia, 2008.

12. C. Li, M. Ye, and G. Chen, “An Energy-Efficient Unequal Clustering Mechanism for Wireless Sensor Networks”, Proceeding of IEEE International Conference on Mobile Ad-hoc and Sensor System, pp.597–604, Washington DC,USA, November 2005.

13. W. R. Heinzelman, A. Chandrakasan, and H. Balakrishnan. “Energy efficient communication protocol for wireless micro sensor networks”, Proceedings of 33rd Hawaii International Conference on System Sciences, vol. 8, pp.8020, USA, 2000.

14. F. Xiangning and S. Yulin, “Improvement on LEACH Protocol of Wireless Sensor Network”, Proceedings of the IEEE International Conference on Sensor Technologies and Applications, pp.260–264, Washington, DC, 2007.






Raj Anand, Vishnu Pratap Singh Kirar, Kavita Burse

Paper Title:

K-Fold Cross Validation and Classification Accuracy of PIMA Indian Diabetes Data Set Using Higher Order Neural Network and PCA

Abstract: Neural network techniques have been successfully applied for diagnosis of Type II diabetes. We propose a K-Fold cross validation method for classification of PIMA Indian diabetes data set. The classification accuracy is computed with PCA preprocessing and higher order neural network. The problem of missing data in the analysis and decision making process is handled through PCA. PCA also scales the data in the same range of values.

Type II diabetes, Pima Indian data set, higher order neural networks, data pre-processing, K cross validation, PCA.


1. P.J.G. Lisboa, “A review of evidence of health benefit from artificial neutral networks in medical intervention, Neural Network,” pp. 11-39, 2002.
2. M. Shanker, M.Y. Hu, and M.S. Hung, “Estimating probabilities of diabetes mellitus using neural network”, “SAR and QSAR in Environment Research,” vol. 2, pp. 133-147, 2000.

3. G. Guo , H. Wang , D.Bell ,Y. Bi and K. Greer,” KNN model-based approach in classification”, Springer-Verlag Berlin, 2888, 2003, 986-996.

4. M. Lee , T M Gatton and Lee K-K. “A monitoring and advisory system for diabetes patient management using rule based method and KNN, Sensors”, 10, 2010, 3934-3953.

5. T Jayalakshmi and A Sahthakumaran”, “Improved gradient descent back propagation neural network for diagnosis of type II diabetes mellitus”, “Global journal of Computer Science and Technology”, 9, 5 (Ver. 2.0), 2010, 94-97.

6. K.Polat and S.Güneş”, “An expert system approach based on principal component analysis and adaptive neuro-fuzzy inference system to diagnosis of diabetes disease”, “Digital image processing”, 17, 4, 2007, 702-710.

7. F. Tang, and H.Tao, “Fast linear discriminant analysis using binary bases”, “Proc. of the 18th International Conference on Pattern Recognition (ICPR06)”,

8. R. N. Yadav, P. K. Kalra and J. John,” Time series prediction using single multiplicative neuron model,” Applied Soft Computing, Vol 7, pp 1157-1163, 2007.

9. A. Frank and A. Asuncion, “UCI Machine Learning Repository [http://archive.ics.uci.edu/ml]. Irvine, CA: University of California, School of Information and Computer Science,” 2010.
10. http://www.cs.cmu.edu/~schneide/tut5/node42.html






Gihan Kuruppu, S. R. Kodituwakku, U. A. J. Pinidiyaarachchi

Paper Title:

High Speed Motion Tracking for Weightlifting based on Correlation Coefficient Template Matching

Abstract: Tracking of motion in weightlifting is a challenging task. This paper presents a method for tracking Weightlifting bar movement of an athlete. The proposed method uses three different template creation techniques for tracking and applies Wilcoxon Signed rank test to evaluate the results. The method was tested with normally captured data (30fps) and data captured in slow motion (100fps) separately. For the normally captured data, combined dynamic templates method has the highest accuracy of 95% in tracking the trajectory. For slow motion data Wilcoxon Signed Rank generated equal results for all three template creation methods.

Tracking Algorithms, Block Matching Algorithms, Fast Motion Tracking.


1. Shahram Lenjan Nejadian, Mostafa Rostami and Farzad Towhidkhah ,Optimization Of Barbell Trajectory During The Snatch Lift Technique By Using Optimal Control Theory , Biomedical Engineering Faculty, Amirkabir University Of Technology (aut), Journal Of Applied Sciences 5 (5): 524-531, 2008,issn 1546-9239
2. Brian K. Schilling, Michael H. Stone, Harold S. O’bryant,andrew C. Fry, Robert H. Coglianese and Kyle C. Pierce Snatch Technique Of Collegiate National Level Weightlifters,journal of strength and conditioning research, 2002, 16(4), 551–555.

3. Bai, X. And H. Wang. Three-Dimension Kinematics Simulation And Biomechanics Analysis Of Snatch Technique. Proceedings of 1st Joint International Pre-Olympic Conference Of Sports Science & Sports Engineering volume i: Computer Science in Sports (2008): 291-296.

4. Chettibi, T., H.E. Lehtihet, M. Haddad And S.Hanchi, 2004. Minimum Cost Trajectory Planning For Industrial Robots. European Journal Of Mechanics A/Solids, 23: 703-715.

5. Y.W. Huang, C.Y. Chen, C.H. Tsai, C.F. Shen, L.G. Chen, Survey On Block Matching Motion Estimation Algorithms And Architectures With New Results, J. VLSI Signal Process. 42 (3) (2006) 297–320.

6. S. Zhu, K. Ma, A new diamond search algorithm for fast block- matching motion estimation, IEEE Trans. Image Process. 9 (2) (2000) 287–290

7. Lam, S. K., Yeong, C. Y., Yew, C. T., Chai, W. S., Suandi, S. A. A Study on Similarity Computations in Template Matching Technique for Identity Verification. IJCSE) International Journal on Computer Science and Engineering Vol. 02, No. 08, 2010, 2659-2665

8. Buchwalder, T., and B. Huber-Eicher. 2004. Effect of increased floor space on aggressive behaviour in male turkeys (Melagris gallopavo). Appl. Anim. Behav. Sci. 89: 207-214.

9. Ho, W.K., W.I. Wei, and K.F. Chung. 2004. Managing disturbing snoring with palatal implants: a pilot study. Arch. Otolaryngology Head and Neck Surg. 130: 753-758.






Utpal Bhattacharjee, Kshirod Sarmah

Paper Title:

Development of a Speech Corpus for Speaker Verification Research in Multilingual Environment

Abstract: Automatic Speaker Verification (ASV) refers to the task of verifying the claimed identity of a speaker based on speech data. The decision made by a Speaker Verification system is basically a binary decision returns either “Yes” or “No” based on the credibility of the claim, determined by some scoring techniques. The output of an automatic speaker verification system is highly dependent on database used for training and testing the system. The results obtained by the speaker verification system are meaningless if recording specifications and environment for training and testing data are not known. This paper describes methodology and experimental setup used for the development of a speech corpus for the evaluation of text-independent speaker verification system in multilingual environment. Four major languages of Arunachal Pradesh (a North-Eastern frontier state of India, boarding with China) Nyishi, Adi, Galo and Apatani along with English and Hindi have been considered for the developing of the speech corpus. Each speaker has been recoded for three languages – English, Hindi and a local language which must be the mother tongue of the informant. A basic characteristic of this corpus is the presence of both native and non-native speaker. English and Hindi languages have been considered as non-native languages for the speaker. Though the corpus is basically developed for the speaker and language recognition research, it can also be used for various studies including the influence of non-nativeness on speaker and language recognition and accent recognition.

Speaker Verification, Speech corpus, Multilingual, Non-native.


1. B.R. Wildermoth and K. K. Paliwal, GMM based speaker recognition on readily available databases, Proc Microelectronic Engineering Research Conf. 2003.
2. D.A. Reynolds, An overview of automatic speaker recognition technology, Acoustics, Speech, and Signal Processing (ICASSP), 2002, Vol. 4.

3. Wikipedia URL: http://en.wikipedia.org/wiki/ Arunachal_Pradesh

4. J.P.Campbell, Jr. and D.A. Reynolds, Corpora for the evaluation of speaker recognition systems, In Proceedings of International Conference on Acoustics, Speech and Signal Processing(ICASSP’99), 1999, Vol. 2, pp. 829–832.

5. Linguistic Data Consortium. URL: http:// www.ldc.upenn.edu/

6. European Lang Resources Assoc. http:// www.icp.grenet.fr/ELRA/

7. Oregon Graduate Institute URL: http:// cslu.cse.ogi.edu/

8. J.B. Millnar, J.P. VonWiller, J.M. Harrington and P.J. Dermody, The Austrakian national database of spoken language, in Proc. Inter. Conf. on Acoustics, Speech & Signal Processing (ICASSP’94), 1994, Vol. 1, pp. 97-101.

9. G. R. Doddington, CSR Corpus Development, In Proceedings of the workshop on Speech and Natural Language, 1992, pp. 363-366

10. H.A. Patil and T.k. Basu, Development of speech copora for speaker recognition research and evaluation in Indian languages, Int J Speech Technol, 2008, Vol. 11, pp. 17-32.






B.Veeramallu, Ch.LavanyaSusanna, S.Sahitya

Paper Title:

Survey on an Image Quality Assessment Metric Based on Early Vision Features

Abstract: Evaluating the image perceptual quality is a fundamental problem in image and video processing, and various methods have been proposed for image quality assessment(IQA).This letter presents IQA metrics such as Conventional IQA indices ( mean squared error (MSE), signal-to-noise ratio (SNR) and peak signal-to-noise ratio (PSNR)), state-of-the-art IQA metrics(structural similarity based image quality assessment (SSIM),multi-scale-SSIM, non shift edge based ratio (NSER) and their limitations . In the non shift edge based ratio (NSER) method the procedures involved include computing the response of classical receptive fields, zero-crossing detection, and non-shift edge based ratio (NSER) calculation. This IQA metric is very simple but very effective and performs much better than most state-of-the-art IQA metric.

Image quality assessment, structural similarity, non-shift edge, zero-crossing.


1. Z. Wang, A.C. Bovik, H.R. Sheikh, and E.P. Simon celli, “Image quality assessment: from error visibility to structural similarity”, IEEE Trans. Image Process., vol. 13, no. 4, pp. 600-612, Apr. 2004.
2. J. L. Mannos and D. J. Sakrison, “The effects of a visual fidelity criterion on the encoding of images,” IEEE Trans. Information Theory, vol. 4, pp. 525–536, 1974

3. Z. Wang, Rate scalable foveated image and video communications. PhD thesis, Dept. of ECE, The University of Texas at Austin, Dec. 2001

4. Z. Wang, A. C. Bovik, and L. Lu, “Why is image quality assessment so difficult,” in Proc. IEEE Int. Conf. Acoust., Speech, and Signal Processing, vol. 4, (Orlando), pp. 3313–3316, May 2002.

5. Min Zhang, Xuanqin Mou, and Lei Zhang, “Non-Shift Edge Based Ratio (NSER): An Image Quality Assessment Metric Based on Early Vision Features”, IEEE Trans. Image Process vol. 18, NO. 5, MAY 2011

6. N. Ponomarenko, M. Carli, V. Lukin, K. Egiazarian, J. Astola, and F. Battisti, “Color image database for evaluation of image quality metrics,” in Proc. MMSP, Cairns, Australia, 2008, pp. 403–408.

7. H. R. Sheikh, A. C. Bovik, and G. de Veciana, “An information fidelity criterion for image quality assessment using natural scene statistics,” IEEE Trans. Image Process, vol. 14, no. 12, pp. 2117–2128, Dec. 2005

8. H. R. Sheikh and A. C. Bovik, “Image information and visual quality,” IEEE Trans. Image Process., vol. 15, no. 2, pp. 430–444, Feb. 2006.

9. Z. Wang, A. C. Bovik, H. R. Sheikh, and E. P. Simon celli, “Image quality assessment: From error measurement to structural similarity,” IEEE Trans. Image Process., vol. 13, no. 4, pp. 600–612, 2004.

10. Z.Wang and A. C. Bovik, “A universal image quality index,” IEEE Signal Process. Lett. vol. 9, no. 3, pp. 81–84, Sep. 2002.

11. Z. Wang, E. P. Simon celli, and A. C. Bovik, “Multi-scale structural similarity for image quality assessment,” in Proc. IEEE Conf. Signals, Systems, and Computers, 2003, pp. 1398–1402

12. N. Damera-Venkata, T. D. Kite, W. S. Geisler, B. L. Evans, and A. C. Bovik, “Image quality assessment based on a degradation model,” IEEE Trans. Image
Process., vol. 4, no. 4, pp. 636–650, Apr. 2000

13. D. M. Chandler and S. S. Hemami, “VSNR: A wavelet-based visual signal-to-noise ratio for natural images,” IEEE Trans. Image Process., vol. 16, no. 9, pp. 2284–2298, Sep. 2007.

14. H. R. Sheikh, A. C. Bovik, and G. de Veciana, “An information fidelity criterion for image quality assessment using natural scene statistics,” IEEE Trans. Image Process, vol. 14, no. 12, pp. 2117–2128, Dec. 2005.

15. Z.Wang and A. C. Bovik, “A universal image quality index,” IEEE Signal Process. Lett., vol. 9, no. 3, pp. 81–84, Sep. 2002

16. D. Marr, Vision. New York: W. H. Freeman, 1980.






Kapil Jain, Ashish Garg, Rajkumar Rajoria, Pradyumn Chatuvedi

Paper Title:

Simulation & Performance Analysis of Two Level AC-DC-AC Converter with IM

Abstract: The main features of multilevel Converter are the low harmonics content of output voltages and switches experience a voltage stress that is fraction of total dc bus voltage. In this paper, we discussed the AC-DC-AC converter performance with different load. First we describe, the Multilevel Inverter fundamental then the control technique for AC-DC converter, and Control technique for DC-AC converter. Performance of proposed converter is measured by different load at output end.

SPWM, Multilevel Inverter, PI Controller.


1. J. S. Lai and F.Z. Peng “Multilevel Converters – A new breed of power converters” IEEE Trans. Ind Applicant, Vol. 32, May/June 1996.
2. Jose Roderiguez, Jih-Sheng Lai and Fang Zheng Reng, “Multilevel Inverters” A survey of topologies ,control, and applications “,IEEE Trans. On Ind. Electronics, vol No. 4. August 2002.

3. A. Nabae, I Takashashi, and H. Akagi, “A new neutral –point clamped PWM inverter,” IEEE Trans. Ind Application Vol. No. IA-17, PP 518-523, Sept/oc 1981.

4. P.K.Chaturvedi, S. Jain, Pramod Agrawal “ Modeling , Simulation and Analysis of Three level Neutral Point CLAMPED inverter using Matlab/Simulink/Power System Blockst”

5. Bor-Ren Lin & Hsin – Hung Lu “A Novel Multilevel PWM Control Scheme of the AC/DC/AC converter for AC Drives”IEEE Trans on ISIE, 1999.

6. B. R. Lin & H- H Lu “multilevel AC/DC/AC Converter for AC Drives” IEEE Proceding electronics Power application, Vol 146, No. 4, July 1999.

7. Y. Minari, K Shinohara, R. Ueda “ PWM rectifier/voltage inverter without DC link components for induction motor drive” IEEE Proceeding-B,Vol 140, No. 6,November 1993.

8. DAI Bin “ A new control scheme for voltage Source Inverter Without DC Link Capacitor Under Abnormal Input Voltage Conditions” IEEE Tran.2009.

9. K. Arab tehrani, H. Andriasioharana, I. Rasonarivo & F.M. Sargos “ A Multilevel Inverter Model” IEEE Trans. 2008.

10. Siriroj Sirisukprasert, Jih- Sheng Lai & Tina – Hua Liu “Optimum harmonics Reduction With A wide Range Of Modulation Indexes for Multilevel Converters” IEEE Trans Ind Application Electronics ,Vol 49 , No. 4, August 2002.

11. G.Bhuvaneshwari and Nagaraju “ Multilevel inverters – a comaparative study” vol.51 No.2 march – april 2005.

12. Siriroj Sirisukprasert “ Optimum harmonics reduction”.

13. A. M. Massoud, S.J. Finney and B.W. Williams “Control Techniques for Multilevel Voltage Source Inverters” IEEE proce. 2003.

14. B.R. Lin and H.H. Lu “Multilevel AC/DC/AC converter for AC drives” IEE Proc.—Electr. Power Application, Vol. 146, No. 4, July 1999.






Mehran Amiri, Mahdi Eftekhari, Farshid Keynia

Paper Title:

Using Naïve Bayes Classifier to Accelerate Constructing Fuzzy Intrusion Detection Systems

Abstract: A Bayesian classifier is one of the most widely used classifiers which possess several properties that make it surprisingly useful and accurate. It is illustrated that performance of Bayesian learning in some cases is comparable with neural networks and decision trees. Bayesian theorem suggests a straight forward process which is not based on search methods. This is the major point which satisfies the marvelous time complexity of Bayesian classifier. At the other hand, constructing phase of fuzzy intrusion detection systems suffer from time consuming processes which are based on search methods. In this paper we propose a novel method to accelerate such processes using Bayesian inference. Experimental results show meaningful time reduction.

Fuzzy intrusion detection systems, Naïve Bayes classifier, Rule`s consequent class, Time complexity.


1. El-Semary, A., Edmonds, J., Gonzalez, J., Papa, M., “A framework for hybrid fuzzy logic intrusion detection systems”, in: The 14th IEEE International Conference on Fuzzy Systems (FUZZ’05), Reno, NV, USA, 25–25 May 2005, IEEE Press, 2005, pp. 325–330.
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Patel Nimisha R., Sheetal Mehta

Paper Title:

A Survey on Mining Algorithms

Abstract: Data mining is a process that discover the knowledge or hidden pattern from large databases. In the large database using association rules throughfind meaningful relationship between large amount of itemsets and this itemset through create frequent itemset. Association rule mining is the most paramount application in the large database. Most of the Association rule mining algorithm are improved and derivative. The traditional algorithms scan databases many times so, time complexity and space complexity is very high of some of association rule mining . The Latest Researcher are focused on data mining to reduce the scanning time of the large database and increased the mining efficiency. In This paper we are cover the most of the latest algorithm based on association rule mining based on frequent itemsets.

Association rule, Maximal frequent itemsets,Mining algorithm, Data Mining


1. Hu, Y., & Han, R. X.“An improved algorithm for mining maximal frequentpatterns,” In Proceedings of international joint conference on artificial intelligence,2009, pp. 746–749.
2. Grahne, G., & Zhu, J. F,“Fast algorithms for frequent itemset mining using FPtrees”, IEEE Transactions on Knowledge and Data Engineering, 17(10), 2005, pp. 1347–1362.

3. Chen, E. H., Cao, H. H., Li, Q., &Qian, T. Y,“Efficient strategies for toughaggregate constraint-based sequential pattern mining. Information Sciences” 2008,pp.178(6), 1498–1518.

4. Bayardo, R. J. “Efficiently mining long patterns from databases,” In Proceeding of the ACM SIGMOD international conference on management of data, 1998, pp. 85–93.

5. Lin, D., &Kedem, Z. M. “Pincer-Search: an efficient algorithm for discovering the maximum frequent set.” IEEE Transactions on Knowledge and DataEngineering, 2002, pp.14 (3), 553–566.

6. Agarwal, R. C., Aggarwal, C. C., & Prasad, V. V. V. “ Depth first generation of long patterns,” In Proceedings of the 6th ACM SIGKDD international conference on knowledge discovery and data mining , 2000,pp. 108–118.

7. Zhou, Q. H., Wesley, C., & Lu, B. J. “SmartMiner: A depth 1st algorithm guided by tail information for mining maximal frequent itemsets.” In Proceedings of IEEE international conference on data mining ,2002,pp. 570–577.

8. Gouda, K., &Zaki, M. J,“Efficiently mining maximal frequent itemsets,”InProceedings of 1st IEEE international conference on data mining,2001, pp. 163–170.

9. Burdick, D., Calimlim, M., &Gehrke, J,“Mafia: A maximal frequent itemsetalgorithm for transactional databases” In Proceedings of 17th internationalconference on data engineering ,2001,pp. 443–452 .

10. Baralis, E., Cerquitelli, T., &Chiusano, S. “IMine: Index support for item set mining” IEEE Transactions on Knowledge and Data Engineering, 2009,pp.21(4), 493–506.

11. Chen, E. H., Cao, H. H., Li, Q., &Qian, T. Y.“ Efficient strategies for toughaggregate constraint-based sequential pattern mining. Information Sciences”,2008,pp.178(6), 1498–1518.

12. RupaliHaldulakar and Prof. JitendraAgrawal, “Optimization of Association Rule Mining through Genetic Algorithm”, International Journal on Computer Science and Engineering (IJCSE), Vol. 3 No. 3 , 2011, pp. 1252-1259.

13. Zaki, M. J.; Parthasarathy, S.; Ogihara, M.; and Li, W, “New Algorithms for Fast Discovery of association Rules,”InProc. of the Third Int’l Conf. on Knowledge Discovery inDatabases and Data Mining,1997,pp.283-286

14. Song, Y. Q., Zhu, Y. Q., & Sun, Z. H., “An algorithm and its updating algorithmbased on FP-tree for mining maximum frequent itemsets”, Journal of Software, 14(9),2003 pp-1586–1592

15. Grahne, G., & Zhu, J. F.“High performance mining of maximal frequentitemsets,” In Proceedings of the 6th SIAM international workshop on highperformance data mining,, 2003,pp. 135–143.

16. Qin, L. X., & Shi, Z. Z,“SFP-Max: a sorted FP-tree based algorithm for maximalfrequent patterns mining”, Journal of Computer Research and Development, 2005,pp.42(2),217–223.

17. Yan, Y. J., Li, Z. J., & Chen, H. W. “ A depth-first search algorithm for miningmaximal frequent itemsets” Journal of Computer Research and Development,, 2005,pp. 462–467.






Aruna Rani, R. K. Singh

Paper Title:

Fractal Antenna and Nano Technology Uniforms

Abstract: This paper presents the latest technology of making a patch antenna using fractals which can be used for making the nano technology uniforms. This Paper is the theoretical analysis and implementation of fractal Antennas.

Fractal Antennas, Nano technology, Koch, Sierpinski.


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3. N. Cohen:, “Fractal and shaped dipoles,” Commun. Quart., pp. 25–36, Spring 1996.

4. Nemanja POPRŽEN1, Mićo GAĆANOVIĆ2: “FRACTAL ANTENNAS: DESIGN, CHARACTERISTICS AND APPLICATION”, regular paper, University of Banjaluka, Patre 5,

5. Carles Puente Baliarda Member, IEEE, Jordi Romeu, Member, IEEE, and Angel Cardama, Member, IEEE: “ The Koch Monopole: A Small Fractal Antenna” IEEE TRANSACTIONS ON ANTENNAS AND ROPAGATION, VOL. 48, NO. 11, NOVEMBER 2000.






B.Veeramallu, A.Raghuveer, U.Sairam

Paper Title:

Analyzing the Generations of Mobile Technology

Abstract: In my research paper, I will be defining the distinguish between mobile generations basically 2G and 3G wireless. It will have some of the history for both 2G, 3G network. 2G networks were built mainly for voice data and slow transmission. Due to some changes in user expectations they do not meet today’s the wireless needs. That Cellular mobile telecommunications networks are being upgraded for the use of a 3G technologies from 1999 to 2010. Japan was the first country that introduces the 3G nationally, and in Japan the transition 3G largely completed in 2006. Korea then adopted the 3G Networks soon after and the transition was done as early as 2004. 2.5G (and even 2.75G) and the technologies such as camera phones , high-speed circuit-switched data (HSCSD) and General packet radio service (GPRS) that provide some of the functionalities like 3G networks, where without the full transition to 3G network. They are taken to introduce the possibilities of wireless technology for the end consumers, so increase the demand for 3G services. When we are converting a GSM network to the UMTS network, we first new technology is General Packet Radio Service (GPRS).



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5. Proceedings of the 11th IEEE International Symposium

6. on Personal, Indoor and Mobile Radio Communications,

7. London, UK, September 2000.

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B.Veeramallu, S.Sahitya, Ch.Lavanya Susanna

Paper Title:

Confidentiality in Wireless sensor Networks

Abstract: While much research has focused on making sensor networks that feasible and useful security has received little attention. We present a set of security protocols optimized for sensor networks: they are confidentiality and authentication, data freshness, data integrity. By using the Sensor Network Encryption Protocol we explains the basic primitives for providing confidentiality, authentication between the two nodes, data integrity and message freshness present in a wireless sensor network. That was designed as base component of Security Protocols for Sensor Networks. Here mainly two security properties are checked: authenticity and Confidentiality of similar messages components. That the first case is the communication between the networks nodes and base station in order to retrieve node Confidential information. In the second case is a key distribution protocol in a sensor network using SNEP (sensor network encryption protocol) for securing messages.

Sensor networks, secure communication protocols, mobile ad hoc networks, authentication of wireless communication.


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Shivali Tyagi, Sachin Singh

Paper Title:

Image Inpainting By Optimized Exemplar Region Filling Algorithm

Abstract: This paper discusses removing objects from digital images and fills the hole that is left behind. Here, we present a novel and effective algorithm that combines the advantages of these two approaches. We first note that exemplar-based texture synthesis contains the essential process required to replicate both texture and structure; the success of structure propagation, however, is highly dependent on the order in which the filling proceeds. The existing algorithms are combined to improve the efficiency for finding the line association in selected region (like solid objects). Main focus is on data term and confidence term to find line association in selected region which is to be inpainted. The region filling is done from that line associated to other section in selected region.

Confidence term, data term, exemplar-based texture, image inpainting, region based algorithm synthesis.


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7. Mohiy M. Hadhoud, Kamel. A. Moustafa and Sameh. Z. Shenoda “Digital Images Inpainting using Modified Convolution Based Method” in proceeding SPIE 7340, 73400S, 2009.

8. Muthukumar S, Dr. Krishnan N, Pasupati P, Deepa S “Analysis of Image Inpainting Techniques with Exemplar, Poisson, Successive Elimination and 8 Pixel Neighborhood Methods”, in proceeding vol. 9, no. 11, 2010.






S.Sivagamasundari, D.Sivakumar

Paper Title:

A New Methodology to Compensate Stiction in Pneumatic Control Valves

Abstract: Industrial surveys reported that, almost one third of poorly performing control loops are caused by nonlinearities present in the control valves, one of which is static friction. The effect of this nonlinearity is usually observed as oscillations in process variable. Since industrial plants include numerous interacting loops, the oscillations will be propagated to the entire system. Doubtlessly, repairing the faulty valves will be the only solution to this problem, which is possible only during process shut down. But, as shutting down the process to isolate the faulty valve for maintenance purposes is not economical, this solution does not count as the primary one. So, there is a need for a method to compensate the destructive effect of the stiction phenomenon in the control valve, especially when maintenance is not available. This paper focuses on existing compensation issues, followed by a proposal of a new model-based compensation approach for the stiction nonlinearity present in control valves. Performance of this method is validated by both simulation and laboratory data.

Pneumatic control valve, stiction, Stick band, stiction compensation, knocker.


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4. M.A.A.S.Choudhury, M. Jian and S.L. Shah, Definition, mdelling, detection and quantification, Journal of Process Control, 2008,Vol.18, pp.232-243.

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6. Hagglund T, A friction compensator for pneumatic control valves, J Proc Control, 2002 Vol.12, pp.897–904.

7. Z.X. Ivan and S. Lakshminarayanan, A new unified approach to valve stiction, quantification and compensation, Industrial and Engineering chemistry research, 2009, Vol.48, pp.3474-3483.

8. Ranganathan Srinivasan and Raghunathan Rengaswamy, Techniques for Stiction Diagnosis and Compensation in Process Control Loops, Proceedings of the American Control Conference, Minneapolis, Minnesota, USA 2006.

9. Srinivasan R, Rengaswamy R, Approaches for efficient stiction compensation in process control valves. Comput Chem Eng, 2008 vol.32, pp.218–229.

10. Srinivasan R, Rengaswamy R, Integrating Stiction diagnosis and Stiction Compensation in Process Control Valves, 16th European Symposium on Computer Aided Process Engineering and 9th International Symposium on Process Systems Engineering, 2006.

11. Srinivasan R, Rengaswamy R, Stiction compensation in control loops: a framewok for integrating stiction measure and compensation, Industrial and Engineering Chemistry Research, 2005 , Vol.44, pp.9164–9174.






Hota H.S., Sirigiri Pavani, P.V.S.S. Gangadhar

Paper Title:

Evaluating Teachers Ranking Using Fuzzy AHP Technique

Abstract: Teachers are the backbone of any educational institution and responsible for quality education, a good teacher can produce good student but Indian institutions are very poor in terms of quality teachers, in spite of having well qualified faculty members in their institutions. There is always a question mark about quality teaching. A teacher with good academic records may not necessarily be a good teacher hence there should be a reliable technique to evaluate teachers quality for financial and administrative decision making .An institute management can take proper decision about teachers after choosing best teacher in their institution and also assign new responsibilities based on their quality. Fuzzy AHP is a multi criteria decision making technique which is frequently used to find out ranking and can be applied to find out teachers ranking ,the quality of teacher is fuzzy in nature hence fuzzy AHP approach can better deal with this situation and finally decide ranking of the teachers based on the multiple conflicting criteria of the teachers. A teacher may have many qualities like communication ability, knowledge level ,interaction with students etc. but all these qualities are qualitative not quantitative which is little bit difficult to deal with traditional theory .Fuzzy logic can be used to deal this type of problem . In this research work fuzzy logic based MCDM method: fuzzy AHP is used to decide the ranking of teacher for further decision making. Data of small sample size of teachers are collected from educational institution.

Fuzzy analytical hierarchy process (FAHP), Multi criteria decision making (MCDM).


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Mirzaei H., Jafari M., Mirshahi A.

Paper Title:

Considering the effect of using JPEG images on accuracy results of radiology images and application programs

Abstract: With hardware and software algorithms development, necessity of methods with accuracy and velocity are more attention. For example edge detection is one of the most important operations in machine vision and the main purpose of edge detection is reducing the volume of data with preserving main structure and original form of images. For these purpose the accuracy of edge detection with retrieval edges by minimum position error rate and losing edges is one of more important approach in recent decades. It is clear those raw images because of no losing many features than JPEG images have better results. In this research consider a simulation neural network program and compare three famous edge detection “Sobel, Prewitt, Canny” with raw images and shows efficiency on results.

Medical image processing, Edge detection, Raw image, Neural network.


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Ekta Tiwari, Suchita Varade

Paper Title:

Transmit Beamforming for Performance Enhancement of IEEE 802.16e Mobile WiMAX

Abstract: This paper aims at performance evaluation of mobile WiMAX system which uses multiple antenna technique such as space time block coding space time trellis coding with and without transmit beamforming for multiple transmit and multiple receive antennas. The mobile WiMAX system has been analyzed for modulation scheme such as mPSK along with different combination of multiple transmit and receive antenna. Computer simulations are done using MATLAB 7.10.The performance of the proposed system has been analyzed in terms of bit error rate (BER). Simulation results shows that the multiple antenna technique in combination with transmit beamforming improves the performance of mobile WiMAX system in terms of BER as number of transmitting antenna increases without increasing the transmit power and bandwidth.

Mobile WiMAX, Multiple Input Multiple Output (MIMO),Space Time Block Code(STBC), Space Time Trellis Code(STTC), Transmit Beamforming.


1. Md. Ashraful Islam,Riaz Uddin Mondal,Md. Zahid Hasan,University of Rajshahi, Rajshahi, Bangladesh,’Performance Evaluation of Wimax Physical Layer Under Adaptive Modulation Techniques and Communication Channels’,(IJCSIS) International Journal of Computer Science and Information Security,Vol. 5, No.1, 2009.
2. Mountassir, J.; Balta, H.; Oltean, M.; Kovaci, M.; Isar, A.; Dept. of Commun., Univ. “Politeh.” of Timisoara, Timisoara, Romania ,’ A physical layer simulator for WiMAX in Rayleigh fading channel ‘, Applied Computational Intelligence and Informatics (SACI), 2011 6th IEEE International Symposium ,2011.

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Kavitha Sirasani, S.Y. Kamdi

Paper Title:

Solar Wind Hydro Hybrid Energy System Simulation

Abstract: The importance of hybrid systems has grown as they appeared to be the right solution for a clean and distributed energy production. So that new implementations of hybrid systems require special attention on analysis and modeling. This paper deals theoretical study of hybrid systems, based on renewable energy is the availability of models, which can be used to study the behavior of hybrid systems and most important, software simulation environments. In this paper we present several models which can be used for the simulation purposes of hybrid power systems.

Hybrid energy system; Micro-hydro; Solar; Wind; Modeling; Simulation.


1. S. Ashok “ Optimized model for community-based hybrid energy system” Renewable Energy 32 (2007) 1155-1164, ScienceDirect.
2. Cristian Dragos Dumitru, Adrian Gligor “ Software Development for Analysis of Solar-Wind Hybrid Systems Supplying Local Distribution Networks” 2ND International Conference on Modern Power Systems MPS 2008, 12-14 November 2008, Cluj-Napoca, Romania.

3. Dorin Bica, Cristian Dumitru, Adrian Gligot, Adrian-Vasile Duka “ Isolated hybrid solar-wind-hydro renewable energy systems”

4. Furat Abdal Rassul Abbas and Mohammed Abdulla Abdulsada “Simulation of Wind-Turbine Speed Control by MATLAB” International Journal of Computer and Electrical Engineering, Vol.2, No.5, October 2010

5. Richard Gagnon, Gilbert Turmel, Christian Larose , Jacques Brochu, Gilbert Sybille, Martin Fectrau “ Large –Scale Real-Time Simulation of Wind Power Plants into Hdro-Quebec Power System”

6. Geoff Walker “ Evaluating MPPT converter topologies using a matlab PV model”