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Volume-1 Issue-5, June 2012, ISSN: 2249-8958 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.



Salil Batra, Chandra Prakash

Paper Title:

Commanding Computer Using Gesture Based Patterns

Abstract:   Gesture recognition is one of the popular methods for Human computer Interaction. This paper is mainly focused on the applications of this technology in the computing environment. The idea is to construct such a system which can take gesture inputs and on the basis of that controlling and commanding of the computer is performed. In doing so, such a module is presented which is based on the finger tracking through which different types of applications can be started. This module basically performs the finger counting and then on the basis of which actions are performed. Further these actions are used to control various functions of operating systems. Results reveal that the proposed technique works well in the robust conditions

  Gesture Recognition,  Human computer Interaction, Finger Tracking, Convex Hull Algorithm Coefficient of Correlation.


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2.        Bhuyan M. K.,Ghosh D. and  Bora P.K. (2005) “Threshold Finite State      Machine for Vision Based Gesture Recognition”, IEEE  Indicon  2005Conference,Chennai,India.

3.        Kumar Rajesh, Kumar Anupam (2008) “Black Pearl: An Alternative for Mouse and Keyboard”, ICGST-GVIP, ISSN 1687-398X, Volume (8), Issue (III).

4.        Vo Nam,  Tran Quang,  Ba Dinh Thang, Ba Dinh Tein, Nguyen Quan M.(2009-2010)  “An  Efficient  Human-Computer  Interaction  Framework Using  Skin  Color  Tracking  and  Gesture  Recognition”,  A  part  of  the KC.01/06-10 project supported by the Ministry of Science and Technology.

5.        Pang Yee Yong ,Ismail Nor Azman ,Gilbert Phuah Leong Siang  (2010) “A  Real  Time  Vision-Based  Hand   Gesture  Interaction”,  Fourth  Asia International   Conference on Mathematical /Analytical Modeling and Computer Simulation.

6.        Jilin Tu, Hai Tao, Thomas Huang, “Face as Mouse through Visual Face   Tracking”.

7.        Charles J. Cohen, Glenn Beach, Gene Foul “A Basic  Hand Gesture  Control System for PC Applications” .

8.        Hummels  Caroline,  Stappers Pieter Jan  ,  “Meaningful  Gestures for Human Computer Interaction beyond Hand Postures”

9.        Acharya Tinku, Image Processing and Applications,Wiley Publications.

10.     T. Young Ian, J. Gerbrands Jan, Lucas J. van Vliet, Fundamentals of Image Processing.

11.     Dimitrios Tzovaras, Thierry Pun, and Alice Caplier, Image and Video  Processing for Disability, Euracip Journal.

12.     Bradski   gary,Kaehler   Adrian   (2004),Learning   openCV   ,ORilly publications





Maya Yadav, Pradeep Baniya, Ganesh Wayal

Paper Title:

Comparison Between Inheritance & interface UML     Design Through the Coupling Metrics

Abstract:    In this paper we have applied various coupling metrics for measuring the comparison between object oriented class inheritance and interface.  In this we have applied metrics on class design diagram and evaluate the metrics values. The coupling metrics presented identifies complexity between inheritance and interface programming In this paper we want to show which concept is good to use and beneficial for software developer.

   measurement of metrics, object oriented technology ,CBO, NOC , DIT, C K metrics.


1.        Krishnapriya, V., Dr. Ramar, K.: Exploring the Difference between Object Oriented Class Inheritance and Interfaces Using Coupling Measures. International Conference on Advances in Computer Engineering, 978-0-7695-4058-0/10, IEEE (2010)
2.        Rene Santaolaya Salgado, Olivia G. Fragosco Diaz, Manuel A. Valdes Marrero, Issac M. Vaseuqz Mendz and Shiela L. delfin Lara,”Object Oriented Metric to Measure the Degree of Dependency Due to Unused Interfaces”, ICCSA 2004, LNCS 3046, P.No:808-817,2004 @ Springer, Verlag Berlin HeidelBerg.

3.        El Hachemi Alikacem, Houari A. Sahraoui, “Generic Metric Extraction Framework”,IWSM/Metrickon, Software Measurement Conference 2006.

4.        Stephen R. Schach, ”Object Oriented and Classical Engineering”, 5th Edition,Tata McGraw Hill,2002.

5.        Carlo Ghezzi, Mehdi Jazayeri, Dino Manddrioli,”Fundamentals of software Engineering, P.No: 366, 2nd Edition, Prentice Hall India, 2003

6.        Christopher L. Brooks, Chrislopher G. Buell, “A Tool for Automatically Gathering Object-Oriented Metrics”, IEEE, 1994.

7.        Lorenz, Mark & Kidd Jeff, Object-Oriented Software Metrics, Prentice Hall, 1994.

8.        Tegarden, D., Sheetz, S., Monarchi, D., “Effectiveness of Traditional Software Metrics for Object-Oriented Systems”, Proceedings: 25th Hawaii International Conference on System Sciences, January, 1992, pp. 359-368.

9.        McCabe and Associates, Using McCabe QA 7.0, 1999, 9861 Broken Land Parkway 4th Floor Columbia, MD 21046.

10.     Rosenberg, L., and Hyatt, L., “Software Quality Metrics for Object-Oriented System Environments”, Software Assurance Technology Center, Technical Report SATC-TR-95-1001, NASA Goddard Space Flight Center, Greenbelt, Maryland 20771.

11.     FriedRich Steimann, Philip Mayer, Andreas MeiBner,"Decoupling Classes with Inferred Interfaces ", Proceedings of 2006 ACM, Symposium on Applied Computing, Pg.No:1404-1408.

12.     Matthew Cochran,"Coding Better: Using Classes Vs. Interfaces", January 18th, 2009.

13.     Markus Mohenen, "Interfaces with Default Implementations in Java", Aachen University of Technology.

14.     Khan R.A., K.Mustafa And S.A.Ahson, "Software    Quality - Concepts And Practices", P.No:140.

15.     Fried Stiemann, Wolf Siberski and Thomas Kuhne, “ Towards the Systematic Use of Interfaces in Java Programming”, 2nd Int. Conf. on  The Principles and practice of Programming in Java PPJ 2003,   P.No 13-17

16.     Ken Pugh,” Interface Oriented Design”, Chapter 5, 2005

17.     Dirk Riehle and Erica Dubach,”Working With Java Interfaces and Classes-How to Separate Interfaces from Implementations”, P.No:35-46, Published in Java Report 4, 1999.

18.     Pradeep Kumar Bhatia, Rajbeer Mann, “ An Approach to Measure   Software Reusability of OO Design”, Proceedings of 2nd International Conference on Challenges & Opportunities in Information Technology(COIT-2008),RIMT-IET,Mandi Gobindgarh, March 29,2008

19.     Rajib Mall,”Fundamentals of Software Engineering”, Chapter 1, Pg.No:1-18,2nd Edition, April 2004.

20.     Rene Santaolaya Salgado, Olivia G. Fragosco Diaz, Manuel A. Valdes Marrero, Issac M. Vaseuqz Mendez and Shiela L. Delfin Lara,  “Object Oriented Metric to Measure the Degree of Dependency Due  to Unused Interfaces”, ICCSA 2004, LNCS 3046, P.No: 808-  817,2004 @ Springer, Verlag Berlin Heidelberg.

21.     Rudiger Lincke, Jonas Lundberg and Welf Lowe,”Comparing   Software Metrics Tools”, ISSTA’08, July 20-24, 2008, ACM 978-1- 59593-904-3/07.

22.     Santonu Sarkar, Member, IEEE, Avinash C. Kak, and Girish Maskeri  Rama,“ Metrics for Measuring the Quality of Modularization of Large-Scale Object-Oriented Software, IEEE Transactions on  Software Engineering, Vol. 34, No. 5, Sep-Oct 2008.

23.     Shyam R. Chidamber, Chris F. Kemrer,”A Metrics Suite for Object  Oriented Design. M.I.T., Sloan School Of Management, 1993.

24.     Terry .C. and Dikel .D.,”Reuse Library Standards Aid Users in  Setting up Organizational Reuse Programs”,Embedded System Programming Product News,1996.





Vaishali M. Chavan, V.V. Gohokar

Paper Title:

Speech Emotion Recognition by using SVM-Classifier

Abstract:    Automatic emotion recognition in speech is a current research area with a wide range of applications in human-machine interactions. This paper uses the support vector machine (SVM), to classify five emotional states: anger, happiness, sadness, surprise and a neutral state. The classification performance of the selected feature subset was done with that of the Mel frequency cepstrum coefficients (MFCC), Periodicity Histogram and Fluctuation Pattern. Within the method based on SVM, a new method by using Multi-class SVM is used as a classifier. Experiments were conducted on the Danish Emotion Speech (DES) Database. The recognition rates by using SVM classifier were 68 %, 60 %, 55.40 % and 60 % for Linear, Polynomial, RBF, and Sigmoid Kernel Function respectively. The recognition rates by Multiclass SVM using Linear, Polynomial, RBF and Sigmoid kernel function for Danish database for Periodicity Histogram are 64.77 %, 78.41 %, 79.55 % and 78.41% respectively.

   Emotion recognition, Mel frequency cepstrum coefficients (MFCC), Support Vector Machine.

1.        Proceedings of the Fourth International Conference on Machine Learning and Cybernetics, Guangzhou, 18-21 August 2005, “SPEECH EMOTION RECOGNITION BASED ON HMM AND SVM” by YI-LIN LIN, GANG WEI.
2.        “HIDDEN MARKOV MODEL-BASED SPEECH EMOTION RECOGNITION” by Björn Schuller, Gerhard Rigoll, and Manfred Lang, Institute for Human-Computer Communication, 2003 IEEE.

3.        “Timing Levels in Segment-Based Speech Emotion Recognition”, by Björn Schuller and Gerhard Rigoll of Institute for Human-Machine Communication in 2006.

4.        “A NEURAL NETWORK APPROACH FOR HUMAN EMOTION RECOGNITION IN SPEECH”, by Muhammad Waqas Bhatti, Yongjin Wang and Ling Guan in 2006.

5.        “Comparison Between Fuzzy and NN Method for Speech Emotion Recognition”, by Aishah Abdul Razak, Ryoichi Komiya, Mohamad Izani Zainal Abidin, in 2005 IEEE.

6.        2005 IEEE International Workshop on Robots and Human Interactive Communication, “Fuzzy Emotion Recognition in Natural Speech Dialogue”, by Anja Austermann, Natascha Esau, Lisa Kleinjohann and Bernd Kleinjohann.

7.        “Emotion Recognition on the Basis of Human Speech”, by Zygmunt Ciota Technical University of Lodz, Department of Microelectronics and Computer Science.

8.        SICE-ICASE International Joint Conference 2006, Oct. 18-21, 2006 in Bexco, Busan, Korea, “Robust Speech Emotion Recognition Using Log Frequency Power Ratio”, by Kyung-Hak Hyun, Eun-Ho Kim and Yoon-Keun Kwak.

9.        “Speech Emotion Recognition Based on Rough Set and SVM”, by Jian Zhou, Guoyin Wang, Yong Yang, Peijun Chen, 2006 IEEE.

10.     “GMM SUPERVECTOR BASED SVM WITH SPECTRAL FEATURES FOR SPEECH EMOTION RECOGNITION”, by Hao Hu, Ming-XingXu, and Wei Wu, Tsinghua University, Beijing, 2007 IEEE.

11.     “SPEECH EMOTION RECOGNITION USING GAUSSIAN MIXTURE VECTOR AUTOREGRESSIVE MODELS”  by Moataz M. H. El Ayadi, Mohamed S. Kamel, and Fakhri Karray, Pattern Analysis and Machine Intelligence Lab, Electrical and Computer Engineering, University of Waterloo,2007 IEEE.

12.     IMACS Multi-conference on "Computational Engineering in System Applications"(CESA), October 4-6, 2006, Beijing, China.” Emotion-detecting Based Model Selection for Emotional Speech Recognition”, by Y. C. Pan,  M. X. Xu, L. Q. Liu, P. F. Jia.

13.     “Speech Emotion Recognition in E-learning System Based on Affective Computing” by Wu Li, Yanhui Zhang, Yingzi Fu, Third International Conference on Natural Computation (ICNC 2007).

14.     2007 IEEE International Conference on Control and Automation FrBP-27 Guangzhou, CHINA - May 30 to June 1, 2007. Research on “Speech Emotion Recognition in E- learning By Using Neural Networks Method”, by Qian Zhang, Yan Wang, Lan Wang and Guoqiang Wang, 2007 IEEE.

15.     16th IEEE International Conference on Robot & Human Interactive Communication August 26 - 29, 2007 / Jeju, Korea, “Speech Emotion Recognition Using Eigen-FFT in Clean and Noisy Environments”, Eun Ho Kim ,Kyung Hak Hyu, Soo Hyun Kim and Yoon Keun Kwak, 2007 IEEE.

16.     “Speech Emotion Recognition using Auditory Cortex”, Abdul Wahab, Chai Quek, and Sussan De, 1-4244-1340-0/07/$25.00 c-2007 IEEE.


18.     “Adaptive and Optimal Classification of Speech Emotion Recognition”, by Ying Wang, Shoufu Du , Yongzhao Zhan. 2008 IEEE, DOI - 10.1109/ICNC.2008.713.

19.     “Efficient Speech Emotion Recognition Based on Multisurface Proximal Support Vector Machine”, by Chengfu Yang, Xiaorong Pu, Xiaobin Wang, 2008 IEEE

20.     “Speech Emotion Recognition Using Canonical Correlation Analysis and Probabilistic Neural Network”, by Ling Cen, Wee Ser, Zhu Liang Yu. 2008 Seventh International Conference.

21.     2009 World Congress on Computer Science and Information Engineering, “Multi-Level Speech Emotion Recognition based on HMM and ANN” by Xia Mao, Lijiang Chen, Liqin Fu, 2008 IEEE.

22.     “Recognition of emotions in speech by a hierarchical approach”, by Zhongzhe Xiao and Emmanuel Dellandrea and Liming Chen, Weibei Dou, 2009 IEEE.

23.     “Speech emotion recognition using both spectral and prosodic features”, by Yu Zhou and Yanqing Sun and Jianping Zhang and Yonghong Yan, 2009 IEEE.

24.     2009 International Conference on Advances in Computing, Control, and Telecommunication Technologies, “Automatic Emotion Recognition from Speech using Artificial Neural Networks with Gender-Dependent Databases”, by Firoz Shah. A, Raji Sukumar. A, Babu Anto. P, 2009 IEEE.

25.     2010 International Conference on Measuring Technology and Mechatronics Automation, “Speech Emotion Recognition Based on Principal Component Analysis and Back Propagation Neural Network”, by Sheguo Wang,Xuxiong Ling,Fuliang Zhang,Jianing Tong, 2010 IEEE

26.     “SVM - MLP - PNN Classifiers on Speech Emotion Recognition Field -A Comparative Study”, by Theodoros Iliou, Christos-Nikolaos Anagnostopoulos, 2010 IEEE. DOI 10.1109/ICDT.2010.8

27.     “Speech Emotion Recognition Based on Data Mining Technology”, by Ying SHI, Weihua SONG, 2010 IEEE.

28.     2010 International Conference on Electrical and Control Engineering, “Fuzzy multi-class support vector machine based on binary tree in network intrusion detection”,  by Lei L, Zhi-ping GA ,Wen-yan Dinl.

29.     “Speech emotion recognition using segmental level prosodic analysis”, by Shashidhar G. Koolagudi, Nitin Kumar and K. Sreenivasa Rao, 2011 IEEE.

30.     2011 International Conference on Electronic & Mechanical Engineering and Information Technology, “Automatic Speech Emotion Recognition Using Support Vector Machine”, by Peipei Shen, Zhou Changjun, Xiong Chen.

31.     2011 International Conference on Image Information Processing (ICIIP 2011) “Statistical Estimation of Emotions in Speech Notes”, by Featured Term Analogy, Sita Kumari K., Suhasini S., Zaheer Parvez Shaik Mohd.

32.     Sixth International Conference on Spoken Language Processing (ICSLP 2000), “EMOTION RECOGNITION IN SPEECH SIGNAL: EXPERIMENTAL STUDY, DEVELOPMENT, AND APPLICATION”, by Valery A. Petrushin.

33.     “HIDDEN MARKOV MODEL-BASED SPEECH EMOTION RECOGNITION” by Björn Schuller, Gerhard Rigoll, and Manfred Lang, 2003 IEEE.





Nagesh Potdar, Dipak Pawar, Sachin Jain, Bhumil Haria, Seema Shrawne

Paper Title:

Indoor Navigation Using Smartphones

Abstract:  This project is for implementation and analysis of the usage of smart phone sensors for indoor navigation, without the use of Global Positioning Systems. This is to extend advantages of outdoor navigation for indoor navigation, by making use of existing technologies and devices to facilitate navigation for achieving this, without the use of extra/expensive hardware.

   Navigation, local positioning system, motion tracking, smart-phone, GPS alternative


1.       Silke Feldmann, Kyandoghere Kyamakya, Ana Zapater, and Lue Zighuo, "An indoor Blutooth-based positioning system: concept,  Implementation and experimental evaluation," Institute of Communications Engineering, Hanover,.
2.       Changdon Kee et al., "Centimeter-Accuracy Indoor Navigation," GPS World, November 2001.

3.       Kamol Kaemarungsi and Prashant Krishnamurthy, "Modeling of Indoor Positioning Systems Based on Location Fingerprinting," 2004.

4.       Vasileios Zeimpekis, George M. Giaglis, and George Lek, "A taxonomy of indoor and outdoor positioning techniques for mobile location services," sigecom Exchange, 2003.

5.       E. W. Dijkstra, "A Note on Two Problems in Connexion with Graphs," Numerische Mathematlk 1, pp. 269-271, 1959.





Mamta Kamath, Disha Punjabi, Tejal Sabnis, Divya Upadhyay, Seema Shrawne

Paper Title:

Improving Content Based Image Retrieval using Scale Invariant Feature Transform

Abstract:    Content-Based Image Retrieval (CBIR) is a challenging task. Common approaches use only low-level features. Notwithstanding, such CBIR solutions fail on capturing some local features representing the details and nuances of scenes. Many techniques in image processing and computer vision can capture these scene semantics. Among them, the Scale Invariant Features Transform (SIFT) has been widely used in a lot of applications. This approach relies on the choice of several parameters which directly impact its effectiveness when applied to retrieve images. In this paper, we attempt to evaluate the application of the SIFT to refine CBIR.

   Content Based Image Retrieval (CBIR), Difference Of Gaussian (DOG), Nearest Neighbour Search (NNS), Scale Invariant Feature Transform (SIFT).


1.       David G. Lowe , Distinctive Image Features from Scale-Invariant KeypointsComputer Science Department,University of British Columbia, Vancouver, B.C., Canada, lowe@cs.ubc.ca
2.       Xu Wangming, Wu Jin, Liu Xinhai, Zhu Lei, Shi Gang, Application of Image SIFT Features to The Context of CBIR, Engineering Research Center of Metallurgical Automation and Measurement Technology,Ministry of Education, College of Information Science and Engineering, Wuhan University of Science and Technology Wuhan, China

3.       P.S.Suhasini, Dr. K. Sri Rama Krishna,  Dr.  I.V.  Murali Krishna , Cbir Using Color Histogram Processing , Asst. Professor in ECE , DMSSVH College of Engineering , Machilipatnam, A.P., India -521001 Professor & Head, ECE Department, VR Siddhartha Engineering College, Vijayawada, A.P., India–520007

4.       Ajay B. Kurhe, Suhas S. Satonka, Prakash B. Khanale,  Color Matching Of Images By Using Minkowski- Form Distance , University Grant Commission





Preeti Singh, Charu Pujara

Paper Title:

Comparative study of various Techniques Employ in Image Steganography

Abstract:    The staggering growth in communication technology and the usage of internet allows the huge transfer of data over it but because of various security threats data can be tampered by the intruders. Various cryptography techniques are developed for secure transmission over the internet, another practical approach of hiding secret information from intruders over the web is Steganography. Steganography is a technique of hiding covert data inside an image. Various techniques are discussed below for hiding data and each of them have some of their own limitations. This paper comprises of four sections. Section 1 gives a brief introduction about Steganography. Section 2 Steganograpy Techniques, Section 3 Analysis of Steganography Techniques, Section 4  Conclusion and future scope.

   Steganography, Techniques, technology usage of internet.


1.       .Neil F. Johnson and Sushi1 Jajodia, “Steganalysis:The Investigation of Hidden Information, ”IEEEInformation Technology Conference,Syracuse,NewYork,USA,September 1st - 3rd, 1998.
2.       Steganography by Khan, Mohammed Minhajuddin.

3.       T.Morkel, J.H.PEloff ,M.S.Olivir ,”An overviewofimagesteganography”,Information and Computer Security Architecture (ICSA) Research Group Department of Computer Science University of Pretoria, 0002, Pretoria, South Africa.

4.       .Souvik Bhattacharyya*1,Indradip Banerjee2 and Gautam Sanyal3,”A Survey of Steganography and Steganalysis Technique in Image, Text, Audio and Video as Cover Carrier”,Ajounal of global research in computer science,ISSN-2229-371X.,Volume 2, No. 4, April 2011.

5.       L. M. Marvel, C. G. Boncelet, Jr. and C. T. Retter, "Spread spectrum image steganography," IEEE Trans. on Image Processing, 8(8), 1075-1083 (1999).

6.       .R.Chandramouli,NasirMemon,”Analysis of LSB Based Image Steganography Techniques ,” , Proc. IEEE ICIP, 2001.

7.       .Kevin Curran, Kran Bailey,” An Evaluation of Image Based Steganography Methods,” International Journal of Digital Evidence, Fall  2003.

8.       .Ross J. Anderson and Fabien A.P. Petitcolas,"On the limits of steganography," IEEE Journal on Selected Areas in Communications (J-SAC), Special Issue on Copyright & Privacy Protection, vol. 16 no. 4, pp 474-481, May 1998.

9.       N. F. Johnson and S. Jajodia, "Steganography: seeing the unseen," IEEE Computer., Feb., 26-34 (1998).

10.     SouvikBhattacharyya,Indradip Banerjeeand Gautam Sanyal,”A Survey of Steganography and Steganalysis Technique in Image, Text, Audio and Video as Cover Carrier”,Ajounal of global research in computer science,ISSN-2229-371X, Volume 2, No. 4, April 2011

11.     .Mamta Juneja, Parvinder S. Sandhu, and Ekta Walia”Application of LSB Based Steganographic Technique for 8-bit Color Images ,” World Academy of Science, Engineering and Technology 50, 2009.

12.     .ImageRosziati Ibrahim and Teoh Suk KuanFaculty of Computer Science and Information Technology, University Tun Hussein Onn Malaysia (UTHM), Batu Pahat 86400,Johor, Malaysia received “Steganography Algorithm to Hide Secret Message inside an image,” Computer Technology and Application 2 (2011) 102-108 November 25, 2010 / Accepted: January 10, 2011 / Published: February 25, 2011.

13.     ShrikantS.Khaire,Dr.BabasahebAmbedkand Dr Sanjay L Nalwarbar Steganography,” Bit Plane Complexity Segmentation Technique , International Journal of Engineering Science and TechnologyVol. 2(9), 2010, 4860-4868.

14.     ShoTanaka,MichiharuNiimi and Hideki Noda” A Study on Reversible Information Hiding using Complexity Measure for BinaryImages” Kyushu Institute of Technology,680–4 Kawazu, Iizuka, 8208502Japan{tanaka,niimi,noda}@mip.ces.kyutech.ac.jp

15.     Bui Cong Nguyen, Sang Moon Yoon, and Heung-Kyu ,”Multi Bit Plane Image Steganography” Y.Q. Shi and B. Jeon (Eds.): IWDW 2006, LNCS 4283, pp. 61–70, 2 Springer-Verlag Berlin Heidelberg 2006





Modh Jigar S, Shah Brijesh, Shah Satish k

Paper Title:

A New K-mean Color Image Segmentation with Cosine Distance for Satellite Images

Abstract:    This paper represents unsupervised method of k-means segmentation which is new adaptive technique of color-texture segmentation. With the progress in satellite images, the image segmentation technique for generating and updating geographical information are become more and more important. This algorithm first enhance the image then applying clustering based k-means segmentation technique ,using L*a*b color space and using cosine distance matrices instead of  sqeuclidean distance. With this it is possible to reduce computational time and calculation for every pixel in the image .Although colors are not frequently used in image segmentation; it gives high discriminative power to the regions present in image.

   K-means segmentation, cosine distance ,Euclidean distance,


1.       He, Xiaoling; Hodgson, W. Jeffrey,”Research Image Processing Technology hot issue”, IEEE Transactions on Intelligent Transportation Systems, 3(4): Dec., 244-251, 2002.
2.       Amanpreet Kaur, et al, “Color image Segmentation Using K-Means Clustering Algorithm” ,International journal on emerging technologies 1(2):18-20,2010.

3.       Ricardo Dutra da Silva et al ”Satellite Image Segmentation Using Wavelet transform Based On color and Texture Features”, ISVC 2008,part II,LNCS 5359,pp 113-122,2008

4.       H C Chen et al,”Visible Color Difference-Based Quantitative of Color Segmentation “, IEEE proceeding, Vis image signal Process Vol.153 No. 5 , pp 598-609.oct 2006.

5.       Ahmed Darwish ,et al, ”Image Segmentation for the Purpose of Object-Based Classification”,IEEE, pp 2039-2041,2003

6.       Anil Z Chitade, “Color Based Image Segmentation using K-mean Clustering”, International journal of Engineering Science and technology, Vol. 2(10), 5319-5325,2010.

7.       W.Woelker,”Image Segmentation Based on an Adaptive 3D Analysis of thecae-L*a*b* Color Space.” proc. of SPIE’96-Visual Communication and Image Processing ’96, Vol.2727, pp.1197-1203, 1996. 

8.       J. B. Macqueen, “Some Methods for Classification and Analysis of Multivariate Observations”, proceedings of 5-th Berkeley symposium on mathematical statistics and probability, Berkeley, university of California press, 1:281-297,1967.

9.       Anna Huang, ”Similarity Measures for Text Document Clustering” The university of waikato, Hamilton ,

10.     R. B. Yates and B. R. Neto.”Modern Information Retrieval.”, Addison-Wesley , newyork,1999.

11.     A. K. Jain, M. N. Murty, and P. J. Flynn.”Data clustering: a review.”ACM computing surveys (CSUR) , 31 (3) :264-323, 1999.

12.     P. N. Tan, M. Stenbach & V. kumar, ”Introduction to Data Mining” ,Addison-Wesely,ch.-8,2005.

13.     L.jin and D.Li”A switching Vector median Based on the CIELAB color space for Color Image Restoration”, Signal Processing, Vol. 87, pp 1345, 2007.





A.Jeraldine Viji, M Sudhakaran

Paper Title:

Reduction of THD in Single Phase PAF With PSD Method for Reference Current Generation

Abstract:  In this paper Single phase parallel active filter (PAF) with a control algorithm of power synchronous detection method for reference current generation is proposed .The current waveform injected by the active filter is able to compensate the reactive power and the load current harmonics and to balance asymmetrical loads. The active filter designed in PSIM software and control of active filter is done in Simulink environment. PSIM and MATLAB software is linked by Sim coupler.The capacitor voltage is maintained constant by using PI controller. Simulation results with PSIM software show that the designed active filter is very effective in improvement of quality of power.

   Active filter, Hysteresis Band controller, Power Synchronous detection (PSD), current harmonics, Pulse Width Modulation, PSIM software


1.        F. Z. Peng and D. J. Adams, “Harmonics sources and filtering approaches,” in Proc. Industry Applications Conf., Oct. 1999, vol. 1, pp. 448–455.
2.        J. C. Das, “Passive filters-potentialities and limitations,” IEEE Trans. Ind. Appli., vol. 40, no. 1, pp. 232–241, Jan. 2004.

3.        H. L. Ginn, III and L. S. Czarnecki, “An optimization based method for selection of resonant harmonic filter branch parameters,” IEEE Trans. Power Del., vol. 21, no. 3, pp. 1445–1451, Jul. 2006.

4.        J. A. Pomilio and S. M. Deckmann, “Characterization and  compensation of harmonics and reactive power of residential and commercial loads,” IEEE Trans. Power Del., vol. 22, no. 2, pp. 1049–1055, Apr. 2007.

5.        S.A. Gonzalez, R. Garcia-Retegui, M. Benedetti, “Harmonic computation technique suitable for active power filters”, IEEE Transactions on Industrial Electronics 54 (October) (2007) 2791–3279.

6.        G.W. Chang, C.M. Yeh, “Optimisation-based strategy for shunt active power filter control under non-ideal supply voltages” IEE Proceedings Electric Power Applications 152 (March (2)) (2005) 182–190.

7.        S. George, V. Agarwal, “A DSP based optimal algorithm for shunt active filter under nonsinusoidal supply and unbalanced load conditions”, IEEE Transactions on Power Electronics 22 (March) (2007) 593–601.

8.        M.P. Kazmierkowski, L. Malesani, “Current control techniques for three-phase voltage source PWM converters”: a survey, IEEE Transactions on Industrial Electronics 45 (5) (1998) 691–703.

9.        M.Montero, E.R. Cadaval, F. Gonzalez,”Comparison of control strategies for shunt active power filters in three-phase four-wire systems”, IEEE Transactions on Power Electronics 22 (January) (2007) 229–236.

10.     Review of Harmonic Current Extraction Techniques for an Active Power Filter A. M. Massoud, S.  J. Finney, and B. W. Williams.

11.     T.C. Green, J.H. Marks, “Control techniques for active power filters”, IEE Proceedings Electric Power Applications 152 (March (2)) (2005) 369–381.

12.     M.P. Kazmierkowski, L. Malesani, “Current control techniques for three-phase voltage source PWM converters”: a survey, IEEE Transactions on Industrial Electronics 45 (5) (1998) 691–703.

13.     B. Singh, K. Al-Haddad, and A. Chandra, “A review of active filters for power quality improvement,” IEEE Trans. Ind. Electron., vol. 46,no. 5, pp. 960–971, Oct. 1999.





Mayur S. Burange, S. V. Dhopte

Paper Title:

Neuro Fuzzy Model for Human Face Expression Recognition

Abstract:    This paper present an approach to recognize human face expression and emotions based on some fuzzy pattern rules. Facial features for this specially eye and lips are extracted an approximated into curves which represents the relationship between the motion of features and change of expression. This paper focuses the concepts like face detections, skin color segmentation, face features extractions and approximation and fuzzy rules formation. Conclusion based on fuzzy patterns never been accurate but still our intension is to put more accurate results.

   Face Detection, Skin Color Segmentation, Face Futures, Curve Formation and Approximation, Fuzzy Patterns

1.        Y. Yacoob and L.S. Davis, “Recognizing human facial expressions from long image sequences using optical flow”, IEEE Trans. Pattern Analysis & Machine Intelligence, Vol. 18, No 6, pp. 636-642, 1996.
2.        P. Ekman and W. Friesen, “Facial Action Coding System”, Consulting Psychologists Press, 1977.

3.        K. Aizawa and T. S. Huang, “Model-based image coding: Advanced video coding techniques for very low bit-rate applications”, Proc. IEEE, Vol. 83, No. 2, pp. 259-271,

4.        S. Kimura and M. Yachida, “Facial expressionrecognition and its degree estimation”, Proc.Computer Vision and Pattern Recognition, pp.295-300, 1997.

5.        K. Ohba, G. Clary, T. Tsukada, T. Kotoku, and K. Tanie, “Facial expression communication with FES”, Proc. International Conference on Pattern Recognition, pp. 1376-1378, 1998.

6.        M.A. Bhuiyan and H. Hama, “Identification of Actors Drawn in Ukiyoe Pictures”, PatternRecognition, Vol. 35, No. 1, pp. 93-102, 2002.

7.        M. B. Hmid and Y.B. Jemaa, Fuzzy Classification, Image Segmentation and Shape Analysis for Human Face Detection. Proc. Of ICSP, vol. 4, 2006.

8.        M. Wang, Y. Iwai, M. Yachida, “Expression Recognition from Time-Sequential Facial Images by use of Expression Change Model”, Proc. Third IEEE International Conference on Automatic Face and Gesture Recognition, pp. 324 – 329, 1998.

9.        M. I. Khan and M. A. Bhuiyan, “Facial Expression recognition for Human-Machine Interface”, ICCIT, 2006.





Priyanka Satish Tekadpande, Ramnivas Giri

Paper Title:

Recent Developments in Traffic Signs Recognition Techniques

Abstract:    The traffic signs play a vital role for accident free and smooth fast driving. If the recognition of traffic signs done by the accurate and fast automated systems, it provides the extra edge in efficient navigation. Thus automatic traffic signs recognition is an important task, particularly in intelligence transportation system. Automated recognition system collects useful information about traffic signs, helps the driver to make timely decisions, and increases driving safety and comfort. This paper presents an overview of the different methods and techniques used in traffic sign detection and recognition. It describes the physical properties and characteristics of the road signs, potential difficulties and problems that occur during detection of real-time images. The detection and recognition techniques are classified into three stages i.e. Color-based filtering, shape-based analysis and final recognition. Thus, we have chronologically discussed some of the referred previous work theme-wise with respect to the different approaches and techniques used in these stages. In future, new techniques should be involved to increase the robustness, and to get faster systems for real-time applications.

   Artificial intelligence, Driver assistance system, Thresholding, hough Transform.


1.       Arturo de la Escalera and Miguel Angel Salichs, "Road Traffic Sign Detection and Classification," IEEE Transactions on Industrial Electronics, Vol. 44, Issue 6, 1997, pp 848 - 859.
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4.       Ritter, W., Stein, F., Janssen, R.: Traffic sign recognition using colour information. Math. Comput. Model. 22(4-7), 149–161 (1995)

5.       A. Ruta, Y. Li, and X. Liu, “Real-time traffic sign recognition from video by class-specific discriminative features,” vol. 43, no. 1, pp. 416–430, 2010.

6.       Gareth Loy and Nick Barnes, "Fast Shape-based Road Sign Detection for a Driver Assistance System," in Proc. of the IEEEIRSJ Int. Conf. on Intelligent Robots and Systems, Vol. 1, 2004, pp. 70 - 75.

7.       D. M. Gavrila, "Traffic Sign Recognition Revisited," in Proceedings of the 21st DAGM Symposium fur Mustererkennung, Springer Verlag, Bonn, Germany, 1999, pp. 86-93

8.       Y. Aoyagi and T. Asakura, "A study on traffic sign recognition in scene image using genetic algorithms and neural networks," in Proc. of the 22nd Int. Conf On Industrial Electronics, Control, and Instrumentation, Taipeis, 1996. pp. 1838-43.

9.       L. Estevez and N. Kehtarnavaz, "A real-time histographic approach to road sign recognition," in Proc. of the IEEE Southwest Symposium on Image Analysis and Interpretation, 1996, pp. 95-100.

10.     S. Escalera and P. Radeva, "Fast Greyscale Road Sign Model Matching and Recognition," Recent Advances in Artificial Intelligence Research and Development, J. Vitria et.al. (Eds.) IOS Press, 2004, pp. 69-76.

11.     Pavel Paclik and Jana Novovicova, "Road Sign Classification without Colour Information," in Proc. of 6th Conf. of Advaced School of Imaging and Computing, ASCI, Lommel, Belgium, 2000

12.     Piccioli, G., De Micheli, E., Parodi, P., Campani, M.: Robust method for road sign detection and recognition. Image Vis. Comput. 14(3), 209–223 (1996)

13.     S. Vitabile, G. Pollaccia, G. Pilato, and F.Sorbello, "Road signs recognition using a dynamic pixel aggregation technique in the HSV colour space," in Proc. Int. Conf. on Image Analysis and Processing, Italy, 2001, pp. 572-577

14.     Priese, L., Klieber, J., Lakmann, R., Rehrmann, V., Schian, R.: New results on traffic sign recognition. In: IEEE Proceedings of the Intelligent Vehicles Symposium, pp. 249–254 (1994)

15.     Gao, X.W., Podladchikova, L., Shaposhnikov, D., Hong, K., Shevtsova, N.: Recognition of traffic signs based on their colour and shape features extracted using human vision models. J. Vis. Commun. Image Represent. 17((4), 675–685 (2006)

16.     Fleyeh, H.: Color detection and segmentation for road and traffic signs. Proc. IEEE Conf. Cybern. Intell. Syst. 2, 809–814 (2004)

17.     Paclik, P., Novovicova, J., Duin, R.: Building road-sign classifiers using a trainable similarity measure. IEEE Trans. Intell. Transp. Syst. 6(3), 309–321 (2006)

18.     Douville, P.: Real-time classification of traffic signs. Real-Time Imaging, 6(3), 185–193 (2000)

19.     Cyganek, B.: Circular road signs recognitionwith soft classifiers.Computer-Aided Eng. 14((4), 323–343 (2007)

20.     Krumbiegel, D., Kraiss, K.-F., Schrieber, S.: A connectionist traffic sign recognition system for onboard driver information. In: Proceedings of the Fifth IFAC/IFIP/IFORS/IEA Symposium on Analysis, Design and Evaluation of Man-Machine Systems, pp. 201–206 (1992)





Fawzi Elias Bekri, A. Govardhan

Paper Title:

EMA-QPSO based Feature Selection and Weighted Classification by LS-SVM for Diabetes diagnosis

Abstract:    In accordance to the fast developing technology now a days, every field is gaining it’s benefit through machines other than human involvement. Many changes are being made much advancement is possible by this developing technology. Likewise this technology is too gaining its importance in bioinformatics especially to analyse data. As we all know that diabetes is one of the present day deadly diseases prevailing. With the motivation of our earlier model OFW-ITS-LSSVM, here in this paper we introduce weighted classification with LSSVM to diagnose the diabetes in given blood sample datasets. We derived and proposed a swarm intelligence technique called Escalated Mediocre Agent based Quantum Particle Swarm Optimization EMA-QPSO for feature selection. The feature weights will be identified using a technique DFWQ (dynamic feature weight quantization) that derived from HITS algorithm, which uses in web mining. In contrast to our earlier model OFW-ITS-LSSVM the proposed model is not using pre defined ontology. Further, considering the patient’s details we can predict where he has a chance to get diabetes, if so measures to cure or stop it.

   machine learning, SVM, Feature reduction, feature optimization, tabu search, Tabu search.


1.        Polat, K., Güneş, S., 2007. An expert system approach based on principal component analysis and adaptive neuro-fuzzy inference system to diagnosis of diabetes disease. Digital Signal Processing 17, 702-710.
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3.        Çalişir, D., Doğantekin, E., 2011. An automatic diabetes diagnosis system based on LDA-Wavelet Support Vector

4.        Übeyli, E.D., 2007. Comparison of different classification algorithms in clinical decision-making. Expert Systems 24, 17-31.

5.        Acır, N., Özdamar, Ö., Güzeliş, C., 2006. Automatic classification of auditory brainstem responses using SVM-based feature selection algorithm for threshold detection. Engineering Applications of Artificial Intelligence 19, 209-218

6.        Lin, M., Oki, T., Holloway, T., Streets, D.G., Bengtsson, M., Kanae, S., 2008. Long-range transport of acidifying substances in East Asia—Part I: model evaluation and sensitivity studies. Atmospheric Environment, in press,  doi:10.1016/j.atmosenv.2008.04.008

7.        Valentini, G., Muselli, M., Ruffino, F., 2004. Cancer recognition with bagged ensembles of support vector machines. Neurocomputing 56, 461-466.

8.        Zhang, Y.L., Guo, N., Du, H., Li, W.H., 2005. Automated defect recognition of C- SAM images in IC packaging using Support Vector Machines. The International Journal of Advanced Manufacturing Technology 25, 1191-1196.

9.        Lei Zhang , Zhichao Wang “Ontology-based clustering algorithm with feature weights”,2010Journal of  Computational Information Systems 6:9 (2010) 2959-2966.

10.     Karabatak, M., Ince, M.C., 2009. An expert system for detection of breast cancer based on association rules and neural network. Expert Systems with Applications 36, 3465-3469.

11.     Mehmet Fatih, A., 2009. Support vector machines combined with feature selection for breast cancer diagnosis. Expert Systems with Applications 36, 3240-3247.

12.     Polat, K., Güneş, S., Arslan, A., 2008. A cascade learning system for classification of diabetes disease: Generalized Discriminant Analysis and Least Square Support Vector Machine. Expert Systems with Applications 34, 482-487.

13.     Pardo, M., Sberveglieri, G., 2005. Classification of electronic nose data with support vector machines. Sensors and Actuators B: Chemical 107, 730-737.

14.     Fred Glover, Tabu search fundamentals and uses, http://leeds-faculty.colorado.edu/glover/TS%20-%20Fundamentals&Uses.pdf, 1995

15.     Xing, H.-j., Ha, M.-h., Hu, B.-g., Tian, D.-z., 2009. Linear feature-weighted support vector machine. Fuzzy Information and Engineering 1, 289-305.

16.     Asuncion, A., Newman, D. J. (2007) Pima Indians Diabetes Data Set, UCI Machine Learning Repository, http://archive.ics.uci.edu/ml/datasets/Pima+Indians+Diabets, Irvine, CA: University of California, School of Information and Computer Science.

17.     Cios, K. J., Pedrycz, W., Swiniarski, R.W., Kurgan, L. A. (2007) Data Mining: A Knowledge Discovery  Approach, New York: Springer.

18.     Vapnik, V.; Statistical Learning Theory, John Wiley: New York, 1998.

19.     Sun J, Xu W, Feng B, A Global Search Strategy of Quantum- Behaved Particle Swarm Optimization. In Proc. of the 2004 IEEE Conf. on Cybernetics and Intelligent Systems, Singapore: 291 – 294, 2004.

20.     Suykens, J. A. K.; Vandewalle, J.; Neural Process. Lett. 1999, 9, 293.

21.     Suykens, J. A. K.; van Gestel, T.; de Brabanter, J.; de Moor, B.; Vandewalle, J.; Least-Squares Support Vector Machines, World Scientifics: Singapore, 2002.

22.     Zou, T.; Dou, Y.; Mi, H.; Zou, J.; Ren, Y.; Anal. Biochem. 2006, 355, 1.

23.     Ke, Y.; Yiyu, C.; Chinese J. Anal. Chem. 2006, 34, 561.

24.     Niazi, A.; Ghasemi, J.; Yazdanipour, A.; Spectrochim. Acta Part A 2007, 68, 523.

25.     Varewyck, M.; Martens, J.-P.; , "A Practical Approach to Model Selection for Support Vector Machines With a Gaussian Kernel," Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on , vol.41, no.2, pp.330-340, April 2011   doi: 10.1109/TSMCB.2010.2053026

26.     I. Steinwart. Sparseness of support vector machines - some asymptotically sharp bounds. In NIPS, pages 169–184, 2004.

27.     A. Tikhonov and V. Arsenin. Solution of Ill-posed Problems. Winston & Sons, 1977.

28.     Tikhonov and V. Arsenin. Solution of Ill-posed Problems. Winston & Sons, 1977.

29.     Tikhonov and V. Arsenin. Ill-Posed Pproblems: Theory and Applications. Kluwer Academic Publishers, 1994.

30.     F. Glover and M. Laguna. Tabu search. Kluwer Academic Publishers, 1997.

31.     R. Collobert and S. Bengio. SVMTorch: Support vector machines for large-scale regression problems. In Journal of Machine Learning Research, volume 1, pages 143–160, 2001.

32.     Least Squares Support Vector Machines for Classification and nonlinear modelling  PASE 2000 (2000) by J. A. K. Suykens posted to classification lssvm pattern_recognition regression svm by Borelli on 2006-01-18

33.     Davar Giveki, Hamid Salimi, GholamReza Bahmanyar, Younes Khademian, Automatic Detection of Diabetes Diagnosis using Feature Weighted Support Vector Machines based on Mutual Information and Modified Cuckoo Search, arXiv:1201.2173v1, ARXIV, 01/2012

34.     Fawzi Elias Bekri, Dr. A. Govardhan "OFW-ITS-LSSVM: Weighted Classification by LS-SVM for Diabetes diagnosis", (IJACSA) International Journal of Advanced Computer Science and Applications, Vol. 3, No. 3, 2012





Vishal B. Padole, D. S. Chaudhari

Paper Title:

Detection of Brain Tumor in MRI Images Using Mean Shift Algorithm and Normalized Cut Method

Abstract:    This paper introduces an efficient method for detection of brain tumor from Magnetic Resonance Images (MRI). In the process of detection of tumor from MRI, segmentation plays vital role for partitioning an image into different subregion with homogeneous properties. The methodology introduced here consist of combination of two conventional algorithms i.e. Mean shift algorithm and Normalized cut (Ncut) Method which provides automatic detection of exact surface area of brain tumor in MRI. By incorporating the advantages of the mean shift segmentation and Ncut method, Magnetic Resonance image (MRI) will be preprocessed first by using the mean shift algorithm to form segmented regions, then Ncut method will be used for region nodes clustering after this connect component extraction analysis is used to locate the exact tumorous area in MRI Images.

   Mean shift, Normalized cut (NCut), tumor.


1.       Shi J and Malik J. , ‘Normalized cuts and image segmentation’, IEEE Trans. on PAMI, Vol. 22, no. 8, pp. 888-905, 2000.
2.       Cheng Y., ‘Mean shift, mode seeking, and clustering’, IEEE Trans. on Pattern Analysis and Machine Intelligence, Vol. 17, no. 8, pp. 790-799, 1995.

3.       Qiu-Bo Xi, ‘An Improved Image Segmentation Algorithm Base on Normalized Cut’, 2nd International Conference on Computer Eng. & Tech., Vol (7), pp. 293-296, 2010.

4.       V.Chen and S. Ruan.‘Graph Cut Based Segmentation of Brain Tumor from MRI Images, IJSTA, Vol (3), pp. 1054-1063, 2009.

5.       Kharrat A., Mohamed Ben Messaoud, Nacera Benamrane, Mohmed Abid ‘Detection of brain tumor in medical images’ IEEE ICSC and S pp. 1 – 6, 2009.

6.       Comannicau D. ‘Mean Shift: A Robust Approach Toward Feature Space Analysis’,IEEE Transactiuons on pattern analysis and machine intelligence, Vol.24, No. 5 May 2002.

7.       Xie Mei, Zhen Zheng, Wu Bingrong, Li Guo ‘The Edge detection of Brain Tumor’ IEEE  pp. 477 – 479, 2009.

8.       Thilagamani S.and Shanthi N.  ‘A Survey on image segmentation through clustering’ International journal of research and Information sciences Vol 1 No. 1, March 2011

9.       Bhat S.  ‘A Mixed model based on watershed and active contour algorithm for brain tumor segmentation’ 2010 International conference on advances in recent technologies in communication and computing

10.     Badran E. F, Esraa G. Mahmoud, and N.Hamdy ‘ An algorithm for detecting brain tumors  in MRI’, IEEE pp. 368 - 373, 2010

11.     Wu Z,.Leahy R. ‘An Optimal Graph Theoretic Approach to Data Clustering: Theory and Its Application to Image Segmentation’ IEEE Transaction on pattern analysis and machine intelligence Vol. 15, NO. 11, pp. 1101 – 1113, Nov 1993





M. J. Pawar, V. S. Jadhav

Paper Title:

Finite Elemental Analysis of Influence of Shape and Profile of Cutting Edge of Twist Drill on Drilling Process

Abstract:    The aims of the investigations presented in this paper were to measure the tool load under conditions of drilling and to analyze if changes of the cutting edge shape and profile significantly influence the edge stresses. The described methods to analyze the influences of edge shape modifications will contribute to the optimization of drilling tools. Based on a specific cutting edge shape of a drill, systematic changes to the edge were made. Forces and temperatures on the cutting edge were measured as well as the heat flow into the chips and the workpiece. Using a quick-stop device, length and type of chip for the different drills under various machining parameters were observed. It could be shown that the modification of the transition from the chisel to the cutting edge influences the stress developed, heat in chip and chip formation. Machining with a rounded cutting edge shape compared to a sharp edge reduces the mechanical load but slightly increases thermal tool load. The presented experimental and FEA method show the possibility of determining influences of modified cutting edge shapes and to adapt the drill to the needs of the drilling process. The cutting force and stress developed during drilling processes has direct influence on the generation of heat, tool wear, quality of machined surface and accuracy of workpiece. Due to complex tool geometry, cutting conditions and some unknown factors theoretical cutting force and stress calculation failed to produce accurate results. To see the behavior of drill either experimental or Finite Elemental Analysis can be used. By using both the methods validation of results can be possible.

   Finite Elemental Analysis, Cutting edge, Chip formation 


1.       Ashkan Sahraie Jahromi, K. Habeeb Ur Rahman, R. Bassi, B. Bahr,2007 “Investigation of the effect of different parameters in the drilled hole quality in composite materials”, Proceedings of the 3rd Annual GRASP Symposium, Wichita State University, pp.219-220.
2.       W. Grzesik, P. Niestony, 2008, “FEM–based thermal modelling of the cutting process using power law temperature dependent concept”, Materials Science and Engineering International Scientific Journal published monthly by the World Academy of Materials and Manufacturing Engineering, Volume 29, Issue 2 ,Pages 105-108.

3.       Dong-Woo Kim, Myeong-Woo Cho,

4.       Tae-Il Seo and Eung-Sug Lee,2008, “Application of Design of Experiment Method for Thrust Force Minimization in Step-feed Micro Drilling”, Sensors, 8, pp. 211-221.

5.       Azlan Abdul Rahman, Azuddin Mamat, Abdullah Wagiman, 2009, “ Effect of Machining Parameters on Hole Quality of Micro Drilling for Brass”, Modern Applied Science, Vol 03, pp.221-230.

6.       Athulan Vijayaraghavan, David A. Dornfeld, 2007 “Automated Drill Modeling for Drilling Process Simulation” , Journal of computer and information Science in Engineering, Transaction of ASME,  Vol. 7,  pp. 276-282.

GENERAL PURPOSE TWIST DRILLS”, Computer assisted analysis, pp.04-07.

8.       Raviraj Shetty, Laxmikant K., R. Pai and S. S. Rao, 2008, “FINITE ELEMENT MODELING OF STRESS DISTRIBUTION IN THE CUTTING PATH IN MACHINING OF DISCONTINUOUSLY REINFORCED ALUMINIUM COMPOSITES”, ARPN Journal of Engineering and Applied Sciences, Vol 03, pp. 25-31.

9.       W. Grzesik, P. Niestony, 2008, “FEM–based thermal modelling of the cutting process using power law temperature dependent concept”, Materials Science and Engineering International Scientific Journal published monthly by the World Academy of Materials and Manufacturing Engineering, Volume 29, Issue 2 ,Pages 105-108.t

10.     K. Kadirgama, M.M. Noor, W.S.W. Harun and C.H.C. Haron, 2009, “Finite Element Analysis and Statistical Method to Determine Temperature Distribution on Cutting Tool in End-Milling”, European Journal of Scientific Research ISSN 1450-216X Vol.30 No.3 (2009), pp.451-463





Namrata Rajendra Shah, Aishwarya Vishwakarma

Paper Title:

Review on Text Document Watermarking

Abstract:    Digital watermarking is the concept of hiding digital signal into digital document such that it cannot be detected and removed easily. That digital signal is called watermark. Text document watermarking is the process of hiding digital data into text document such that it preserves ownership of document. This paper focuses on watermarking process and various techniques including their benefits and limitations.

   DWTC, Text Document, Watermarking.


1.       Zunera Jalil and Anwar M. Mirza, “A Review of Digital Watermarking Techniques for Text Documents”, IEEE International Conference on Information and Multimedia Technology, pp. 230-234, 2009.
2.       Yanqun Zhang, “Digital Watermarking Technology: A Review”, IEEE International Conference on Future Computer and Communication, 2009.

3.       L.Robert and T. Shanmugapriya, “A Study On Digital Watermarking Techniques”, International Journal of Recent Trends in Engineering, Vol. 1, No. 2, pp. 223-225, May 2009.

4.       Huijuan Yang, Alex, and C. Kot, "Text Document Authentication by Integrating Inter Character and Word Spaces Watermarking", IEEE Inter-national Conference on Multimedia and Expo., Vol. 2, pp. 955 – 958, June 26-30, 2004.

5.       Zhichao Yu and Xiaojun liu, “A New Digital Watermarking Scheme Based on Text”, IEEE Inter-national Conference on Multimedia Information Networking and Security, Vol. 2, pp. 138-140, 2004.

6.       Nighat Mir and Sayed Afaq Hussain, “Web Page Watermarking: XML files using Synonyms and Acronyms”, World Academy of Science, Engineering and Technology, Issue 49, Jan 2011.

7.       He Lu, Fang Ding Yi, Gui Xiao Lin, Chen Xiao Jiang , Xu Xin Bai, and Liu Jin “A New Chinese Text Digital Watermarking for Copyright Protecting Word Document”, Vol. 3, pp. 435-439, 2009.

8.       Mussarat Abdullah, Quaid Avenue and Fazal Wahab, “Key Based Text Watermarking of E-Text Documents in an Object Based Environment Using Z-Axis for Watermark Embedding”, World Academy of Science, Engineering and Technology 2008 , BAHRIA University Islamabad campus.

9.       Zhang, “DWTC: A Dual Watermarking Scheme Based on Threshold Cryptography for Web Document”, International Conference on Computer Application and System Modeling (ICCASM ) ,Vol. 8, pp. v8 510 – v8 514, 2010.





Almabrouk W. Ibrahim, Mahdi Alhaji Musa, Nor Zairah Ab.Rahim

Paper Title:

Application of Computer Supported Cooperative Work in Sebha University in Student Affairs Unit

Abstract:    Computer Supported Cooperative Work (CSCW) is the study of how people use technology, with relation to hardware and software, to work together in shared time and space. The nature of computer-supported cooperative work (CSCW) is to facilitate work using technology in such a way that supports human interaction in cooperative work situations. This study was conducted in order to investigate on application of CSCW in Sebha University, in particular, in students’ affairs unit. The proposed application system would be the tools that will facilitate and automate workflow in this organization. This study was also proposed an outline policy for the organization based on the use of the automated system. For this study, the researcher designed a survey and distributed organization to 40 employees of this organization. Besides that, since the study is about current workflow, an observation was conducted to see how process is done. Findings revealed that most of the participants replied positively that they are seriously in need to use up-to date automated technology to ease their interaction in that unit.

   CSCW, current work flow, new work flow, Sebha University, automated system.


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3.        Aqeel-ur-Rehman, Zubair A. Shaikh.. Intelligent Workflow: A Step towards Intelligent Agent based Academic Workflow System. Shah Latif Town, Karachi, Pakistan, 2006. Page 45-47

4.        Agostini, Alessandra, Giorgio De Michelis, Maria Antonietta Grasso, Wolfgang Prinz and Anja Syri Contexts, Work Processes, and Workspaces in Computer Supported Cooperative Work : The Journal of Collaborative Computing, Kluwer Academic Publishers, 1996, pp. 223-250.

5.        Baecker, R.M. Readings in Groupware and Computer Supported Cooperative Work: assisting human-human collaboration. 2004. Page 2-6

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7.        Baker, S., Green, H., Blogs Will Change Your Business, BusinessWeek, 2006, page 67-69

8.        Barber, P. Putting Your Organization on the Internet. THE Grantsmanship Center.. 1996

9.        Bentley,R.  Horstmann, T., and Trevor, J..The World Wide Web as enabling technology for CSCW: The case of BSCW. The Journal of Collaborative Computing: Special issue on CSCW and the Web, 1997, 2-3, 1997, Kluwer Academic Publishers, Amsterdam.

10.     Berghel, H. The Client’s Side of the World Y& D Web, ACM, 1996,  39, 12, 30-40.

11.     Berners-Lee, T., Cailliau, R., Luotonen, A., Frystyck Nielsen, H., and Secret, A. the Wide Web, in Communications of the ACM, 37(8), August, 1994,  pp 76-82.).

12.     Best, M. H. The New Competition - Institutions of Industrial Restructuring Polity Press, Cambridge. 1998, page 7-23

13.     Bowers, J.  Conceptual Framework for Describing Organizations COMIC D-1.2, Lancaster University. 1994

14.     Blackmore, P. “The development of an intranet within a college of further and higher education”, ASLIB Proceedings, 1997, Vol. 49 No. 3, pp. 67-72.

15.     Campbell, J.D Instant messages: a framework for reading between the lines, CSCW 2004.

16.     Castells, M.  The Rise of the Network Society Blackwell, Oxford. 1994, page 34-36

17.     Christensen, U. CSCW in Organizations: A perspective on workflow, awareness and organizational context, center for Tele-Information Technical University of Denmark. 2000

18.     Curry, A. & Stancich, L. The intranet - an intrinsic component of strategic information management [Electronic version]. International Journal of Information Management, 2000, 20(4), 249-268.

19.     Dix, A.J., Finley,J., Abowd,G.D., Beale,R.  Human-Computer Interaction. New York: Prentice Hall. 1993.

20.     Ellis, C. A., S. J. Gibbs and G. L.  Rein Groupware: Some issues and experiences in Communications of the ACM, 1991, vol. 34, no. 1, pp. 38-58.

21.     Fichter, D. Recipes for intranet standards [Electronic version]. Online (Weston, Conn.), 2004, 28(1), 51-53.

22.     Fisher, D., McDonald, D.W., Brooks, A.L., Churchill, E.F. Terms of Service, Ethics and Bias. Tapping the Social Web for CSCW Research. Great America Parkway. 2004

23.     Fitzpatrick, G., Tolone, W.J. and Kaplan, S.: M.  Work, Locales and Distributed Social Worlds. Proceedings of the 1995 European Conference on Computer Supported
Cooperative Work (ECSCW ’95), 1995,  pp. 1-16.

24.     Gerson, Elihu M. and Susan Leigh Star : Analyzing due process in the workplace. ACM Transactions on Office Information Systems, vol. 4, no. 3, July 1986, pp. 257-270.

25.     Greif, I. “Computer-Supported Cooperative Work: A Book of Readings,” Morgan Kaufmann, San Mateo, CA.1980, page 4-8

26.     G.M. Olson, D.E. Atkins.  Supporting collaboration with advanced multimedia electronic mail: The NSF EXPRES  Project, in: J. Galegher, R.E. Kraut, C. Egido (Eds.), Intellectual Teamwork: Social and Technological Foundations  of Co operative Work, Lawrence Erlbaum Associates, Hillsdale, 1990, page 429-451.





Ali Hussein Hsan Sabeen, Ahmed Elmugtaba Anwar, Zainura Z. Noor

Paper Title:

Sustainable Public Transportation in Malaysia

Abstract:    The sustainable public transportations represent one of the civilization implements in the development countries including Malaysia.  The increase of the automobile vehicles in the Malaysian cities represents the civilization challenge in   Malaysian Infrastructure development.  Depending on the estimations conducted in 2005 for the number of automobile vehicles will increase to 15, 0000 million vehicles by 2020. Furthermore, it has been estimated that the motorcycles number is higher than the other types of the vehicles. The implications of the crucial increasing of street vehicles will disrupt widely the environment and human rather than the other types of the Malaysian infrastructure built. Therefore, the scientists suggest the Malaysian government to encourage the sustainable public transportation by reducing the costs and the ground fuel elimination. In addition, facilitation of manufacturing of   the free fuel vehicles may contribute the dilemma reduction.

   volatile organic compounds vocs , United Nations Environment Program UNEP, global environment monitoring System GEMS


1.        C. A. Briceno-Garmendia, A. Estache, N. Shafik, “Infrastructure services in developing countries: access,     quality, costs, and policy reform” World Bank Publications. 2004.
2.        J. K. P. Chan, "Travel Demand Management: Lessons for Malaysia." Journal of Public Transportation. Vol.  11, 3, 2008.

3.        Japan International Cooperation Agency (JICA), The A TC Feasibility Study in Penang and Kuala Lumpur. 1986. 

4.        K. Gwilliam, "Urban transport in developing countries." Transport Reviews. Vol. 23, 2,pp. 197-216. 2003.

5.        W. Harrington, and V. Mcconnell, 5. Motor vehicles and the environment. The international yearbook of environmental and resource economics 2003/2004: a survey of current issues, 190. (2): 197-216. 2003.

6.        D. Mage, G. Ozolins, P. Peterson, A. Webster, R Orthofer, V. Vandeweerd, and M. Gwynne, Urban air pollution in megacities of the world. Atmospheric Environment, vol. 30, pp. 681-686. 1996.

7.        D. T. Mage, and O. Zali, “Motor vehicle air pollution: public health impact and control measures”. 1992

8.        J., Mohamad, and A.T. Kiggundu. “The rise of private car in Kuala Lumpur,  Malaysia: Assessing the policy options”  IATSS Research. Vol.  31. 1, pp 69–77. 2007.

9.        M. Sharifi, L. Boerboom, K. Shamsudin, and L.Veeramuthu, Spatial multiple criteria decision analysis in integrated planning for public transport and land use development study in Klang Valley, Malaysia.  ISPRS Technical Commission II Symposium, Vienna, 12 – 14, July, pp.125-130. 2006.

10.     State Government of Penang, Penang Public Transport Study (Bus and Taxis), Penang. 1995





Pushpalata Verma, K. K. Mehta

Paper Title:

Implementation of an Efficient Multiplier based on Vedic Mathematics Using EDA Tool

Abstract:    A high speed processor depends greatly on the multiplier as it is one of the key hardware blocks in most digital signal processing systems as well as in general processors. This paper presents a high speed 8x8 bit Vedic multiplier architecture which is quite different from the Conventional method of multiplication like add and shift. The most significant aspect of the proposed method is that, the developed multiplier architecture is based on Vertical and Crosswise structure of Ancient Indian Vedic Mathematics. It generates all partial products and their sum in one step.  This also gives chances for modular design where smaller block can be used to design the bigger one. So the design complexity gets reduced for inputs of larger no of bits and modularity gets increased. The proposed Vedic multiplier is coded in VHDL (Very High Speed Integrated Circuits Hardware Description Language), synthesized and simulated using EDA (Electronic Design Automation) tool - XilinxISE12.1i. Finally the results are compared with Conventional multipliers to show the significant improvement in its efficiency in terms of path delay (speed). The  high  speed  processor requires  high  speed  multipliers  and  the  Vedic  Multiplication  technique  is  very  much  suitable  for this purpose.

   Architecture, Ripple Carry (RC) Adder, Multiplication, Vedic Mathematics, Vedic Multiplier (VM), Urdhava Tiryakbhyam Sutra


1.       Jagadguru Swami, Sri Bharati Krisna, Tirthaji Maharaja, “Vedic Mathematics or Sixteen Simple Mathematical Formulae from the Veda, Delhi (1965)”, Motilal Banarsidas, Varanasi, India, 1986.
2.       M. Morris Mano, “Computer System Architecture”, 3rd edition, Prientice-Hall, New Jersey, USA, 1993, pp. 346-348.

3.       H. Thapliyal and H.R Arbania. “A Time-Area-Power Efficient Multiplier and Square Architecture Based On Ancient Indian Vedic Mathematics”, Proceedings of the 2004 International Conference on VLSI (VLSI’04), Las Vegas, Nevada, June 2004, pp. 434-439.

4.       P. D. Chidgupkar and M. T. Karad, “The Implementation of Vedic Algorithms in Digital Signal Processing”, Global J. of Engg. Edu, Vol.8, No.2, 2004, UICEE Published in Australia.

5.       Thapliyal H. and Srinivas M.B, “High Speed Efficient NxN Bit Parallel Hierarchical Overlay Multiplier Architecture Based on Ancient Indian Vedic Mathematics”, Transactions on Engineering, Computing and Technology, 2004, Vol.2.

6.       Harpreet Singh Dhillon and Abhijit Mitra, “A Reduced– Bit Multipliction Algorithm for Digital Arithmetics”, International Journal of Computational and Mathematical Sciences 2.2 @ www.waset.orgSpring2008.

7.       Honey Durga Tiwari, Ganzorig Gankhuyag, Chan Mo Kim and Yong Beom Cho, “Multiplier design based on ancient Indian Vedic Mathematician”, International SoC Design Conference, pp. 65- 68, 2008.

8.       Parth Mehta and Dhanashri Gawali, “Conventional versus Vedic mathematics method for Hardware implementation of a multiplier”, International conference on Advances in Computing, Control, and Telecommunication Technologies, pp. 640-642, 2009.

9.       Ramalatha, M.Dayalan, K D Dharani, P Priya, and S Deoborah, “High Speed Energy Efficient ALU Design using Vedic Multiplication Techniques”, International Conference on Advances in Computational Tools for Engineering Applications (ACTEA) IEEE, pp. 600-603, July 15-17, 2009.

10.     Sumita Vaidya and Deepak Dandekar, “Delay-Power Performance comparison of Multipliers in VLSI Circuit Design”, International Journal of Computer Networks & Communications (IJCNC), Vol.2, No.4, pp. 47-56, July 2010.

11.     S.S.Kerur, Prakash Narchi, Jayashree C N, Harish M Kittur and Girish V A “Implementation of Vedic Multiplier For Digital Signal Processing” International conference on VLSI communication & instrumentation (ICVCI), 2011.

12.     Asmita Haveliya, “A Novel Design for High Speed Multiplier for Digital Signal Processing Applications (Ancient Indian Vedic mathematics approach)”, International Journal of Technology and Engineering System (IJTES), Vol.2, No.1, pp. 27-31, Jan-March, 2011.

13.     Prabha S., Kasliwal, B.P. Patil and D.K. Gautam, “Performance Evaluation of Squaring Operation by Vedic Mathematics”, IETE Journal of Research, vol.57, Issue 1, Jan-Feb 2011.

14.     Aniruddha Kanhe, Shishir Kumar Das and Ankit Kumar Singh, “Design and Implementation of Low Power Multiplier Using Vedic Multiplication Technique”, (IJCSC) International Journal of Computer Science and Communication Vol. 3, No. 1, pp. 131-132, January-June 2012.

15.     Umesh Akare, T.V. More and R.S. Lonkar, “Performance Evaluation and Synthesis of Vedic Multiplier”, National Conference on Innovative Paradigms in Engineering & Technology (NCIPET-2012), Proceedings published by International Journal of Computer Applications (IJCA),  pp. 20-23, 2012





Anil Kumar Sharma, Anuj Kumar Ojha

Paper Title:

A Study on Micro-Electro-Mechanical Systems (MEMS) Sensors & their Applications

Abstract:    Continued demands for better control of the operating conditions of structures and processes have led to the need for better means of measuring temperature (T), pressure (P), and relative humidity (RH). One way to satisfy this need is to use MEMS technology to develop a sensor that will contain, in a single package, capabilities to simultaneously measure T, P, and RH of its environment. Because of the advantages of MEMS technology, which include small size, low power, very high precision, and low cost, it was selected for use in this paper. Although MEMS sensors that individually measure T, P, and RH exist, there are no sensors that combine all three measurements in a single package. In this paper we present overview of microelectromechanical system (MEMS) sensors and its application, is the technology of very small mechanical devices driven by electricity. The critical physical dimensions of MEMS devices can vary from well below one micron on the lower end of the dimensional spectrum, all the way to several millimeters, it merges at the nano-scale into nanoelectromechanical systems (NEMS) and nanotechnology. MEMS are also referred to as micromachines (in Japan), or micro systems technology – MST (in Europe).



1.       Byunghoon Bae1, Bruce R Flachsbart, Kyihwan Park and Mark A Shannon, “ Design Optimization Of A Piezoresistive Pressure Sensor Considering The Output Signal-To-Noise Ratio,” Institute Of Physics Publishing Journal Of Micromechanics And Microengineering J. Micromech. Microeng. Vol. 14, 2004, pp. 1597–1607.
2.       David S. Eddy And Douglas R. Sparks “Application of MEMS Technology in Automotive Sensors and Actuators” Proceedings Of The IEEE, VOL. 86, NO. 8, August 1998.

3.       J Courbat1, M Canonica, D Teyssieux, D Briand and N F de Rooij “ Design and fabrication of micro-hotplates made on a polyimide foil: electrothermal simulation and characterization to achieve power consumption in the low mW range” IOP Publishing Journal Of Micromechanics And Microengineering J. Micromech. Microeng. Vol. 21 , 2011.

4.       Bingleiwang, Shenjie Zhou, Junfeng Zhao And Xi Chen “Size-Dependent Pull-In Instability Of Electrostatically Actuated Microbeam-Based MEMS” IOP Publishing Journal Of Micromechanics And Microengineering J. Micromech. Microeng. Vol.21, 2011.

5.       Kwan Kyu Parka, Hyunjoo Leea, Mario Kupnikb, Ömer Oralkana, Jean-Pierre Ramseyerc, Hans Peter Langc, Martin Hegnerc, Christoph Gerberc, Butrus T. Khuri-Yakuba, “Capacitive micromachined ultrasonic transducer (CMUT) as a chemical sensor for DMMP detection” Contents lists available at SciVerse ScienceDirect Sensors and Actuators , 2011.

6.       Tzu-Yuan Chao, M C Hsu, C-D Lin and Y T Cheng “SU-8 serial MEMS switch for flexible RF Applications” Iop Publishing Journal Of Micromechanics And Microengineering J. Micromech. Microeng. Vol.21, 2011.

7.       Mekhater, K Vummidi, E M Abdel-Rahman, A H Nayfeh And S Raman “Dynamic Actuation Methods For Capacitive MEMS Shunt Switchesiop” Publishing Journal Of Micromechanics And Microengineering, J. Micromech. Microeng. Vol.21, 2011. 

8.       Akhatar J., Dixit B.B, Pant B.D. and Deshwal, V.P.(2003a), “Polysilicon piezoresistive pressure sensors     based on MEMS technology”, IETE Journal of Research, Vol. 49 No. 6,2003,  pp. 365-77.

9.       Akhtar J., Dixit, B.D and Deshwal, V.p(n.d), “Poly silicon piezoresistive pressure sensor based on MEMS technology ”, IETE Technical review, 2011 

10.     Chang,P.Z. and Yang,L.J.), “A method using V grooves to monitor the thickness of silicon membrane with μm resolution”, Journel of micromachine & Microengineering,Vol.8, 1988, pp.182-187.

11.     Clark,S.K. and Wise , K.D “Pressure sensitivity on anisotropically etched thin-diapharam pressure sensors ”, IEEE Trans on Electron Devices Vol.26 No. 12, 1979, pp. 1187-1196.

12.     Kendall, D.L.) , “A new theory for the anisotropic etching of silicon and some underdeveloped chemical micromachining concepts”, J.Vac.Sci. Technol., Vol.A8 No. 4, 1990, pp.3598-3605.

13.     M. Mehregany and S. Roy, Introduction to MEMS, 2000, Microengineering Aerospace Systems, El Segundo, CA, Aerospace Press, AIAA, Inc., 1999.

14.     M. Mehregany, K. J. Gabriel, and W. S. N. Trimmer, Integrated fabrication of polysilicon mechanisms, IEEE Transactions on Electron Devices ED-35, June 1988, pp. 719-723.

15.     L. S. Fan, Y. C. Tai, and R. S. Muller, Integrated movable micromechanical structures for sensors and actuators, IEEE Transactions on Electron Devices ED-35, June 1988, pp. 724-730.

16.     Yang Z, Wang R N, Jia S, Wang D, Zhang B S, Lau K M and Chen K J 2006 Mechanical characterization of suspended GaN microstructures fabricated by GaN-on-patterned-silicon technique Appl. Phys. Lett.

17.     Wang Y, Hu F and Hane K 2010 Freestanding GaN slab fabricated on patterned silicon on an insulator substrate J. Micromech. Microeng.

18.     Wang Y, Hu F, Wakui M and Hane K 2009 Freestanding circular GaN grating fabricated by fast atom beam etching Appl. Phys.

19.     Wang Y, Hu F, Kanamori Y, Sameshima H and Hane K 2010 Fabrication and characterization of subwavelength nanostructures on freestanding GaN slab Opt. Express

20.     Ono T, Orimoto N, Lee S, Simizu T and Esashi M 2000 RF-plasma-assisted fast atom beam etching Japan. J. Appl.Phys.

21.     Manh C H and Hane K 2009 Vacuum operation of comb-drive micro display mirrors J. Micromech. Microeng.

22.     Sasaki M, Yuki S and Hane K 2007 Performance of tense thin-film torsion bar for large rotation and low-voltage driving of micromirror IEEE J. Sel. Top. Quantum Electron.





Shobha Sharma

Paper Title:

22nm Ptm Model Low Power yet High Speed CMOS High K Metal Gate Strained Silicon Technology Inverter

Abstract:   This paper analysis four inverter configuration with low power and high performance PTM  models of Arizona State University, USA at 22nm technology with High K metal gate strained silicon technology. The  effect of stacked transistor is analysed to show the reduced average and peak power dissipation. This stack effect is utilized in combination with forward biasing of a transistor to have low power but high speed inverter without loosing the maximum and minimum voltage swing at the output. Average power dissipated by low power stacked forward biased inverter is reduced by 4% compared to HP inverter. Peak power reduction is 64% in case of this new inverter compared to traditional High Performance  inverter. The propagation delay is more compared to a HP inverter but is reduced by  almost 18.2% compared to Low Power stacked inverter.

   About four key words or phrases in alphabetical order, separated by commas.


1.        BSIM470 manual , Univ of Cal, Berkeley
2.        www.itrs.net

3.        B doris, IEDM 2006

4.        K wang et al,SiGe based engg for MOS, cmos,J of Material Sc,vol6,oct1995

5.        R bate,”prospectus of Quantam Integrated circuits”, Proc of SPICEmarch 1987

6.        Bohr et al, “nanotechnology goals and challenges for electronics applications, “IEEE transactions on nanotechnology, vol1, no1, pp.56-62, March2002

7.        S Borkar et al, ‘Design Challenges in scaling”. IEEE Micro, Vol19 Aug1999

8.        K roy et al, “Low power VLSi Design”, John wiley, inc 2000

9.        Borkar et al, “Obeying Moore’s law beyond. 18micron’, Proceedings of IEEE intl ASIC sept 2000

10.     Usami et al, “automated low power techniques, “IEEE Journal of Solid State circuits, Vol 33, March 1998.





Saurabh P.Bahurupi, D.S.Chaudhari

Paper Title:

Principal Component Analysis for Face Recognition

Abstract:    Face recognition is a biometric technology with a wide range of potential applications such as access control, banking, information security, human computer interaction, virtual reality, database retrieval etc. This paper addresses the building of   face recognition system by using Principal Component Analysis (PCA) method. PCA is a statistical approach used for reducing the number of variables in face recognition. While extracting the most relevant information (feature) contained in the images (face). In PCA, every image in the training set can be represented as a linear combination of weighted eigenvectors called as “Eigenfaces”. These eigenvectors are obtained from covariance matrix of a training image set called as basis function. The weights are found out after selecting a set of most relevant Eigenfaces. Recognition is performed by projecting a new image (test image) onto the subspace spanned by the eigenfaces and then classification is done by distance measure methods such as Euclidean distance. A number of experiments were done to evaluate the performance of the face recognition system.

   Face Recognition, Principle Component Analysis (PCA), Eigenface, Covariance matrix, Face database.


1.       W.Zhao, R.Chellappa, P.J..Phillips and A. Rosennfeld, “Face Reconition: A literature Survey. ACM Comput.Surv., 35(4): 399-458, 2003.
2.       M.A.Turk and A.P. Pentaland, “Face Recognition Using Eigenfaces”, IEEE conf. on Computer Vision and Pattern Recognition, pp. 586-591, 1991.

3.       B.Poon , M. Ashraful Amin , Hong Yan “Performance evaluation and comparison of PCA Based human face recognition methods for distorted images” International Journal of Machine Learning and Cybernetics, , Vol 2, No. 4,pp. 245–259, July 2011. Springer-Verlag 2011.

4.       G. J. Alvarado , W. Pedrycz ,M. Reformat ,Keun-Chang Kwak “Deterioration of visual information in face classification using Eigenfaces and Fisherfaces” Machine Vision and Applications, Vol.17, No. 1, pp. 68-82. Springer-Verlag 2006.

5.       G. Jarillo, W.Pedrycz , M. Reformat “Aggregation of classifiers based on image transformations in biometric face recognition” Machine Vision and Applications (2008) Vol . 19,pp. 125–140, Springer-Verlag 2007.

6.       Ling-Zhi Liao, Si-Wei Luo, and Mei Tian “”Whitenedfaces” Recognition With PCA and ICA” IEEE Signal Processing Letters, Vol. 14, No. 12, pp1008-1011, Dec. 2007.

7.       Kwan-Ho Lin, Kin-Man Lam, and Wan-Chi Siu   “A New Approach using ModiGied Hausdorff Distances with EigenFace for Human Face Recognition” Seventh international Conference on Control, Automation, Robotics And Vision (ICARCV’O2), Singapore, Dec 2002.

8.       Shermina.J “Illumination Invariant Face Recognition Using Discrete Cosine Transform And Principal Component Analysis”  International conference on Emerging Trendes in Electrical and Computer Technology(ICETECT)-2011.

9.       A.Eleyan and H. Demirel “Face Recognition using Multiresolution PCA” IEEE International Symposium on Signal Processing and Information Technology-2007.

10.     W.Zuo, David Zhang, Jian Yang, and Kuanquan Wang “BDPCA Plus LDA: A Novel Fast Feature Extraction Technique for Face Recognition” IEEE Trans. On Systems, Man, and Cybernetics—Part B: Cybernetics, vol. 36, no. 4, pp. 946-953Aug. 2006

11.     L.Wiskott,Jean-Marc Fellous “Face Recognition by Elastic Bunch Graph Matching” In Intelligent Biometric Techniques in Fingerprint and Face Recognition, eds. L.C. Jain et al., publ. CRC Press, ISBN 0-8493-2055-0, Chapter 11, pp. 355-396, (1999).

12.     Indian face database (2002) www.cs.umass.edu/*vidit/Indian

13.     FaceDatabase

14.     Dr Libor Spacek, Faces Directories, Faces 94 Directory,http://cswww.essex.ac.uk/mv/allfac





S.Vasanthi, M.Gopila, I.Gnanambal

Paper Title:

Fuzzy And Pid Excitation control System With AVR In Power System Stability Analysis

Abstract:    This works aims to develop a controller based on PID and Fuzzy Logic Controller to simulate an automatic voltage regulator in transient stability power system analysis. It was simulated a one machine control to check if the Fuzzy and PID controller implementation was possible. After that the controller developed was applied in field excitation system to show its behavior, which results were compared to the results obtained with the AVR itself.

   Fuzzy and PID controller, system to show its behavior.


1.        Clerc,M.and Kennedy,J., “The Particle Swarm Explosion,Stability, and Convergence in a Multidimentional Complex Space,” IEEE Transactions on Evolutionary Computation, (2002)
2.        Gaing,Z.L., “ A Particle Swarm Optimization Approach for Optimum Design of PID Controller in AVR System,” IEEE Transactions on Energy Conversion, (2004)

3.        P.M. Anderson and A.A. Fouad, “ Power System  Control and Stability”, IEEE press (1995)

4.        Hadi Saadat. 1999. “Power System Analysis”, Tata McGraw-Hill

5.        C.L. Brasca & M.A. Johnson, “ On Automatic Voltage Regulator Design for Synchronous Generator”, IEEE International Conference on control and Appilications, (1994)

6.        E.H Mamdani and S.Assilian, “ An experiment in linguistic synthesis with a fuzzy logic controller”, Int.J.Man Mach. Studies,vol.7, no 1,pp 1- 13, 1975.

7.        C.C. Lee, “ Fuzzy logic in control systems”, IEEE transactions on systems, Man and cybernetics, vol. 20, no 2, MARCH/APRIL 1990.

8.        L.A. Zadeh, " Fuzzy Sets”, Informat Control, vol. 8, pp. 338-353 , 1965,





Chitra.M, A.R Ashwath, Roopa.M

Paper Title:

Design and Implementation of Viterbi Encoder and Decoder Using FPGA

Abstract:    In this paper, we present an implementation of the Viterbi algorithm using the Hardware Description Language and Implemented on FPGA. We begin with a description of the algorithm. Included are aspects of design specifications that must be considered when implementing the Viterbi algorithm as well as properties of Verilog HDL that can be used to simplify or optimize the algorithm. Finally, we evaluate the performance of the Viterbi algorithm implemented on FPGA.

   HDL-Hardware Descriptive Language, FPGA- Field Programmable Gate Array.


1.       Implementation of the viterbi algorithm using functional programming languages: By Tristan Bull, Department of Electrical Engineering & Computer Science, University of Kansas, Lawrence.[An IEEE paper].
2.       IEEE transactions on magnetics, vol. 44, no. 1, January 2008: “Viterbi Detector for Non-Markov Recording Channels” by Sam Gratrix, Robert Jackson, Tom Parnell, and Oleg Zaboronski..

3.       Y. K. P.Cheung, G. A. Constantinides, J.T. D. Sousa (2003) Field programmable logic and applications: 13th International Conference, FPL 2003, Lisbon, Portugal. New York:Springer.

4.       Y. K. P.Cheung, G. A. Constantinides, J.T. D. Sousa (2003) Field programmable logic and applications: 13th International Conference, FPL 2003, Lisbon, Portugal. New York:Springer.

5.       Shung, C.B. on his paper: “VLSI Architecture for Metric Normalization in the Viterbi Decoders”, Proceeding ICC, Vol.4; 1990.





K.Sivakumar, N. Krishna Mohan, B. Sivaraman

Paper Title:

Automation of 10 KW Biomass Gasifier and its effectiveness on saw dust briquettes with binder cow dung.

Abstract:    India is very rich in biomass. It has a potential of 19,500 MW (3,500 MW from bagasse based cogeneration and 16,000 MW from surplus biomass). Currently, India has 537 MW commissioned and 536 MW under construction.(GENI). On the other hand rural biomass gasification projects for power generation are facing lot of practical difficulties on operational effectiveness of gasification due to shortage of man power and knowledge worker for the operation of gasifier. Preparation of briquettes and starting and stopping of gasifier is a difficult task in many rural areas. So many rural power projects are failed to take momentum on implementation. This paper is focus on experimental investigation on effectiveness of automation of rural 10 KW biomass gasifier and its effectiveness. PLC based SCADA system was introduced in the programme controlled gasification of bio mass gasifier was experimentally tested. The results reveal that it improved gasification efficiency and less dependent of human man power.  This experiment was tested with saw dust briquette with cow dung as binder having 75:25 ratio at 800* C. This ratio is selected because of higher gas composition than any other ratio’s.  it is investigated in manual mode operation and Automation mode operation for its effectiveness in a 10 KW down  draft gasifier  The experimental result reveals that, the gasification effectiveness is high due to complete combustion and its efficiency is improved around 10%. Automation leads to complete combustion and it helps to improve the reduction process of gasification. it increases in the production  of Methane and CH4 in producer gas.. Quality of product gas produced is comparatively better in automation of gasifier.

   Programmable Logic Controller, Combustion. , Manual mode, Auto mode, gasifier efficiency, gas composition, Product gas


1.       Operation manual of Bio mass gasifier by Ankur Scientific Energy Technologies.
2.       M.Simone, F.Barontini, C. Nicolella, L. Tognotti (2011). “Experimental characterization of the performance of a downdraft biomass gasifier”. Proceedings of the European Combustion Meeting .

3.       Felix Fonseca Felfli (2011).” Biomass briquetting and its perspectives in Brazil”. Biomass and bio energy 35,   236 -242.

4.       David E.Clarke (1989).”Influence of coal/binder interactions on mechanical strength of briquettes”.fuel processing Technology, 68, , 1023-1030.

5.       Ayhan Demirbas (1998). “Evaluation of biomass residue 1. Briquetting waste paper and wheat strawmixtures”. Fuel Processing Technology, 55, 175–183.

6.       Harwin Saptoadi(2008).”The best Biobriquette Dimension and its Particle Size”.Asian journal of energy Environment 9, 161-175.

7.       H.V.Sridhar,G.Sridhar Experience of using various biomass Briquettes in IBG (IISC  BIORESIDUE GASIFIER) ,Indian Institute of science,Bangalore.

8.       (Prokash C.Roy,Amitava Datta, Niladri chakraborty(2010). “Assessment of cow dung as a supplementary fuel in a downdraft biomass gasifier”. Renewable Energy 3,379





Roopashree.S, Sachin Saini, Rohan Ranjan Singh

Paper Title:

Enhancement and Pre-Processing of Images Using Filtering

Abstract:    The field of Digital Image Processing refers to processing digital images by means of digital computer. One of the main application areas in Digital Image Processing methods is to improve the pictorial information for human interpretation. Most of the digital images contain noise. This can be removed by many enhancement techniques. Filtering is one of the enhancement techniques which is used to remove unwanted information (noise) from the image. It is also used for image sharpening and smoothening. The aim of this project is to demonstrate the filtering techniques by performing different operations such as smoothening, sharpening, removing the noise etc. This project has been developed using Java language because of its universal acceptance and easy understandability. Interest in digital image processing methods stems from two principal application areas:- improvement of pictorial information for human interpretation; and processing of image data for storage, transformation, and representation for autonomous machine perception

   Digital Image processing, Filltering techniques, Image enhancement.


1.        Brinkman B.H., Manteca A and Robb R.A. (2011) journal on Medical imaging, vol.17.
2.        Lee International journal on pattern Analysis and ma-chine intelligence, pp. 165

3.        Nagao M and Matsuyama T. (1997) Computer Graphics and Image Processing, vol. 9, pp. 394-407.

4.        Handley D.A. and Green W.B. (1972) IEEE, vol. 60, no. 7, pp.. 821-8280.

5.        Lee J (1983) Graphics and Image Processing, vol. 24, pp. 255- 269.

6.        Aghagolzadeh S. and Ersory O.K. (1992) Transform image Enhancement, Optical Engineering, vol.31,pp.614-626.

7.        Polesel A (2000) IEEE Transaction on Image Processing, vol.9, pp. 505-510.

8.        Buades A., Coll B. and Morel J.

9.        M Ozaki, Y. Adachi, Y. Iwahori, and N. Ishii, Application of fuzzy theory to writer recognition of Chinese characters, International Journal of Modelling and Simulation, 18(2), 1998, 112-116.





Sanjaydeep Singh Lodhi, Ghanshyam Rathore, Premnarayan Arya

Paper Title:

Performance based Frequent Itemset Mining Techniques for Data Mining

Abstract:    Data mining tasks that try to find interesting patterns from databases, such as association rules, correlations, sequences, episodes, classifiers, clusters and many more of which the mining of association rules is one of the most popular problems. There is a large body of research on Frequent Itemset Mining (FIM) but very little work addresses FIM in uncertain databases. Most studies on frequent itemset mining focus on mining precise data. However, there are situations in which the data are uncertain. This leads to the mining of uncertain data. There are also situations in which users are only interested in frequent itemsets that satisfy user-specified aggregate constraints. This leads to constrained mining of uncertain data. Moreover, floods of uncertain data can be produced in many other situations. This leads to stream mining of uncertain data. In this paper, we propose algorithms to deal with all these situations. We first design a tree-based mining algorithm to find all frequent itemsets from databases of uncertain data. We then extend it to mine databases of uncertain data for only those frequent itemsets that satisfy user-specified aggregate constraints and to mine streams of uncertain data for all frequent itemsets. Our experimental results show the more effectiveness than existing methods.

   Data Mining, Frequent Itemset Mining, Apriori Algorithm.


1.        C.C. Aggarwal, Y. Li, J. Wang, and J. Wang, “Frequent pattern mining with uncertain data”,  In Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pages 29–38, Paris, France, 2009.
2.        T. Bernecker, H.P. Kriegel, M. Renz, F. Verhein, and A. Zuefle, “Probabilistic frequent itemset mining in uncertain databases”, In Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pages 119–128, Paris, France, 2009.

3.        M. Chau, R. Cheng, B. Kao, and J. Ng, “Uncertain data mining: an example in clustering location data”, In Proceedings of the 10th Pacific Asia Conference on Knowledge Discovery and Data mining (PAKDD), pages 199–204, Singapore, 2006.

4.        G. Cormode and M. Hadiieleftheriou, “ Finding frequent items in data streams”, In Proceedings of the 34th International Conference on Very Large Data Bases (VLDB), pages 1530–1541, Auckland, New Zealand, 2008.

5.        C.K. Chui and B. Kao, “ A decremental approach for mining frequent itemsets from uncertain data”, In Proceedings of the 12th Pacific-Asia Conference on Knowledge Discovery and Data mining (PAKDD), pages 64–75, Osaka, Japan, 2008.

6.        D.Y. Chiu, Y.H. Wu, and A.L. Chen, “Efficient frequent sequence mining by a dynamic strategy switching algorithm”, The International Journal on Very Large Data Bases (VLDB Journal), 18(1):303–327, 2009.

7.        C. Giannella, J. Han, J. Pei, X. Yan, and P.S. Yu, “ Mining frequent patterns in data streams at multiple time granularities”, In Data Mining: Next Generation Challenges and Future Directions. AAAI/MIT Press, 2004.

8.        N. Jiang and L. Gruenwald, “Research issues in data stream association rule mining”, ACM SIGMOD Record, 35(1):14–19, 2006.

9.        C.C. Aggarwal, “On density based transforms for uncertain data mining”, In Proceedings of the 23rd IEEE International Conference on Data Engineering (ICDE), pages
866–875, Istanbul, Turkey, 2007.

10.     H.P. Kriegel and M. Pfeifle, “Density-based clustering of uncertain data”, In Proceedings of the 11th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pages 672–677, Chicago,  IL, USA, 2005.

11.     C.K. Leung and D.A, “Brajczuk. Efficient algorithms for mining constrained frequent patterns from uncertain data”, In Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pages 9–18, Paris, France, 2009.

12.     Z. Li, Z. Chen, and Y. Zhou, “Mining blocks correlations to improve storage performance” ACM Transactions on Storage (TOS), 1(2):213–245, 2005.

13.     Mohamed Anis Bach Tobji, Boutheina Ben Yaghlane, and Khaled Mellouli, “A New Algorithm for Mining Frequent Itemsets from Evidential Databases”, Proceedings of IPMU'08, pp. 1535{1542 Torremolinos (M_alaga), June 22{27, 2008.

14.     L. Manikonda, A. Mangalampalli1, V. Pudi, “UACI: Uncertain Associative Classi¯er for Object Class Identification in Images”, 2010 IEEE.





Surendra Kumar Shukla, Romil Rawat, Cns Murthy

Paper Title:

Web Attacking Parameters Filtration: A Approach For Attack Signature Verification

Abstract:    Web site is the global needs for business, study and government sectors, but the usage of web application has addicted the peoples. There is no proficiency for the user at several levels such as security, context management, web applications and related information. Attacker has also been activated to steal or destroy the confidential and most secured data. In past various attacks has been notified with severe disastrous result. For stopping and detecting these attacks, various techniques and tools have been manufactured, but they are not 100% result oriented. In this paper we have presented various types of web attack and also different methods and techniques to detect and prevent them, finally we have evaluated these web attacks by different approaches.

   In past various attacks has been notified with severe disastrous result. For stopping and detecting these attacks,


1.        Thomas Heumann, J¨org Keller, Sven T¨urpe; “Quantifying the Attack Surface of a Web Application”. OWASP Top 10 – 2010. available   online,
2.        http://www.owasp.org/index.php/,Category: OWASP_ Top_Ten_Project, 2010.

3.        Peter Mell, Karen Scarfone, and Sasha Romanosky. “A Complete Guide to the Common Vulnerability Scoring System”, http://www.first.org/cvss/cvss-guide.pdf, June 2007.”

4.        Andrew Bortz, Dan Boneh, Palash Nandy. “Exposing Private Information by Timing Web Applications”. WWW 2007, May 8–12, 2007,  Banff, Alberta, Canada. ACM 9781595936547/07/0005.

5.        SecurityFocus, “Microsoft IIS IDC Extension Cross Site Scripting  Vulnerability ”http://online.securityfocus. com/bid/5900/info/

6.        Aditya K Sood, SecNiche Security. “PDF Silent HTTP Form Repurposing Attacks Web Penetration Testing” Mitja Kolšek, ACROS Security. “Session Fixation Vulnerability in Web-based Applications” Version 1.0  revision 1. December 2002 (Revised February 2007 –  The Acknowledgments section).

7.        Gabrilovich E. and Gontmakher A., “The Homograph Attack, Communications of the ACM” 45(2), pp.128,2002

8.        Anthony Y. Fu Wan Zhang Xiaotie Deng Liu Wenyin. “Safeguard against Unicode Attacks: Generation and  Applications of UC-SimList” Duerst M., Suignard M., “RFC 3987: Internationalized Resource Identifiers (IRIs)”, The Internet Society, 2005.

9.        Fu A. Y., Deng X., Liu W., “A Potential IRI based Phishing Strategy”, WISE2005, LNCS Vol. 3806,pp.618-619, 2005

10.     Liu W., Deng X., Huang G, Fu Y., “An Anti-Phishing Strategy based on Visual Similarity Assessment”, IEEE Internet Computing (2), pp.    58-65, Mar/Apr. 2006.

11.     Matt Blaze. Simple UNIX time quantization package. Previously available on the web.Martin Szydlowski, Christopher Kruegel, Engin Kirda.“Secure Input for Web Applications”.

12.     Jarrett Rosenberg. “Some Misconceptions About Lines of Code”. In Fourth International Software Metrics Symposium (METRICS’97),   volume 0, pages 137–142, Los Alamitos, CA, USA, November 1997. IEEE Computer Society.

13.     Carnegie Mellon University. The CAPTCHA Project. http://www.captcha.net.

14.     Gabrilovich E. and Gontmakher A., “The Homograph Attack, Communications of the ACM” 45(2), pp.128,2002

15.     http://www.owasp.org/index.php/,Category: OWASP_ Top_Ten_Project, 2011





Kavya Cheraukula, Chowdam Venkata Sudhakar

Paper Title:

Design and Implementation of A Memory For Joint Improvement Of Error Tolerance And Access Efficiency

Abstract:    The on-chip memory becomes increasingly exposed to the dual challenges of device-level reliability degradation and architecture-level performance gap. We propose to exploit the inherent memory soft redundancy for on-chip memory design. Due to the mismatch between fixed cache line size and runtime variations in memory spatial locality, many irrelevant data are fetched into the memory thereby wasting memory spaces. The proposed soft-redundancy allocated memory detects and utilizes these memory spaces for jointly achieving efficient memory access and effective error control. We design an CRC & ECC with error correction techniques by making use of standard Ethernet (004C11DB7H) polynomial and compare with each other, which will be implemented in FPGA proposed system design which take care of the Cache and memory by re-checking the cache when a miss is identified and help in effective functionality of the system and finally we compare which method will give good results in terms of cost and reliability.

   cache memory, ECC, soft error, URL.


1.        The International Technology Roadmap for Semiconductors, 2003 at     http://public.itrs.net/Files/2003ITRS/Home2003.htm.
2.        R. W. Keyes, “Fundamental limits of silicon technology”, Proceedings of the IEEE, vol. 89, no. 3, pp. 227-239, 2001.

3.        A. Mupid, M. Mutyam, N. ijaykrishnan, Y. Xie, and M. J. Irwin,“Variation analysis of CAM cells,” International Symposium on Quality Electronic Design, pp. 333-338, 2007.

4.        Agarwal, B. C. Paul, S. Mukhopadhyay, and K. Roy, “Process variation in embedded memories: failure analysis and variation aware architecture,”IEEE Journal of Solid-State Circuits, vol. 40, no. 9, pp. 1804-1814, 2005.

5.        R. C. Baumann, “Radiation-induced soft errors in advanced semiconductor technologies,” IEEE Transactions on Device and Materials Reliability,vol. 5, no. 3, pp. 305-316, 2005.

6.        S. S. Mukherjee, J. Emer, and S. K. Reinhardt, “The soft error problem: an architectural perspective,” International Symposium on High-Performance Computer Architecture, pp. 243-247, 2005.

7.        H. L. Hughes and J. M. Benedetto, “Radiation effects and hardening of MOS technology: devices and circuits,” IEEE Trans. on Nuclear Science,vol. 50, pp. 500-521, June 2003.                                                                                                

8.        Q. Zhou and K. Mohanram, “Gate Sizing to Radiation Harden combinational Logic,” IEEE Trans. on computer-aided design of integrated circuitsand systems, vol. 25, pp. 155-166, Jan 2006.

9.        K. Chakraborty, S. Kulkami, M. Bhattacharya, P. Mazumder, and A.   Gupta, “A physical design tool for built-in self-repairable RAMs,”IEEETrans. on VLSI, vol. 9, pp. 352-364, April 2001.

10.     M. Horiguchi, “Redundancy techniques for high-density DRAMS,”   IEEE Innovative Systems Silicon, pp. 22-29, Oct. 1997.

11.     M. Biberstein and T. Etzion, “Optimal codes for single-error correction,double-adjacent-error detection,” IEEE Trans. on Information Theory, vol.46, pp. 2188-2193, Sept. 2000.

12.     T. Suzuki, Y. Yamagami, I. Hatanaka, A. Shibayama, H. Akamatsu, and H. Yamauchi, “A Sub-0.5-V Operating Embedded SRAM Featuring a Multi-Bit-Error-Immune Hidden-ECC Scheme,” IEEE Journal of Solid- State Circuits, vol. 41, pp. 152-160, Jan. 2006.

13.     S. K. Reinhardt and S. S. Mukherjee, “Transient fault detection via simultaneous multithreading,” Proc. International Symposium on Computer Architecture, pp. 25-36, 2000.

14.     R. D. Fellman, R. T. Kaneshiro, and K. Konstantinides, “Design and   evaluation of an architecture for a digital signal processor for instrumentation applications,” IEEE Transaction on Acoustics, Speech, and Signal Processing, vol. 38, no. 3, pp. 537-546, 1990.

15.     A. V. Veidenbaum, W. Tang, R. Gupta, A. Nicolau, and X. Ji, “Adapting cache line size to application behavior,” International Conference on Supercomputing, pp. 145-154, 1999.

16.     P. Pujara and A. Aggarwal, “Increasing the cache efficiency by eliminating noise,” International Symposium on High Performance Computer Architecture, pp. 145-154, 2006.





K Mahesh Dutt, H.K.Shivanand

Paper Title:

Investigation of Modal parameters of Carbon & Kevlar Fiber composite Laminates using FFT Analyzer

Abstract:   Composite Materials are known for their excellent combinations of High Structural Stiffness & Low Weight. They allow the Design Engineer to tailor the material in order to achieve the desired performance requirements because of their anisotropic properties. Therefore, it has become very necessary for Engineers to develop tools which allow the Design Engineer to obtain Optimized designs considering the structural requirements. Based on these requirements, this work considers the Dynamic behavior of Components manufactured from Fiber- reinforced Composite Materials. Towards this, Specimens of Carbon & Kevlar fibers were manufactured using the Hand Lay-up process followed by cutting to the required dimension. Experimental Dynamic Tests were carried out using specimens of different thickness. From the results obtained, the influence of the fiber orientations as well as the stacking sequences on the modal parameters like Natural frequency, Damping etc., were investigated. Also, Validation of the results of Theoretical and from the FEA was done. Good Agreement was obtained between the finite – element predictions and experimentalresults

   Composite Materials, FEA, Modal Analysis, Fibers.


1.       Gentle, C.R. and Lacey, M.R (1999). Design of a Novel Insulated Construction Material, Material and Design, 20(6): pp.311–315.
2.       [Kosmatka, J.B. and Liguore, S.L. (1993). Review of Methods to Study Constrained Layer Damping, ASCE Journal of Aerospace Engineering, 6: 268–283.

3.        Maly, R. Joseph and Johnson, Conor, D. (1998). Cocured Viscoelastic  Composites, In: SPIE Proceedings on Smart Structures and Materials, pp.365 –  376, San Diego CA.

4.       Qunli Liu and Yi Zhao, Prediction of Natural Frequencies of a Sandwich Panel Using Thick Plate Theory”, Journal of sandwich structures and   Materials 2001, 3;289

5.       Raville, M.E., Ueng, E.-S. and Lei, M.-M. (September 1961). Natural      Frequencies of Vibration of Fixed-Fixed Sandwich Beams, Journal of Applied  Mechanics, pp367-371.

6.       Markus, S. and Vala kova´,O. (1972).On Eigenvalue Boundary Problems of Transversely Vibrating Sandwich Beams, Journal of Sound and Vibration, 23(4).

7.       Silverman, I.K. (1995). Natural Frequencies of Sandwich Beams Including Shear and Rotary Effects, Journal of Sound and Vibration, 183(3): 547–561.

8.       Marur, S.R. and Kant, T. (1996). Free Vibration Analysis of Fiber Reinforced Composite Beams Using Higher Order Theories and Finite Element Modeling,      Journal of Sound and Vibration, 194(3): 337–351.

9.       Maheri, M.R. and Adams, R.D. (1998). On the Flexural Vibration of  Timoshenko Beams, and the Applicability of the Analysis to a Sandwich Configuration, Journal of Sound and Vibration, 209(3): 419–442.

10.     Sakiyama, T., Matsuda, H. and Morita, C. (1996). Free Vibration Analysis of Sandwich Beam with Elastic or Viscoelastic Core by Applying the Discrete Green Function, Journal of Sound and Vibration, 191(2): 189–206.

11.     Dow M.B., Dexter H.B., Development of stitched, braided and woven composite structures in the ACT program and at Langley Research Center (1985 to 1997): summary and bibliography. NASA/TP-97-206234, 1997.

12.     C.Y.Son, I.T.Kim & J.S.Paik, Experimental Study on Structural Behaviour and Vibrational Characteristics of Sandwich Plate with Aluminum Honey comb core, International Journal of Offshore and Polar Engineering, Vol 8, No.2 June 1998.





Pravin R. Kubade, V. S. Jadhav

Paper Title:

An Experimental Investigation of Electrode Wear Rate (EWR), Material Removal Rate (MRR) and Radial Overcut (ROC) in EDM of High Carbon-High Chromium Steel (AISI D3)

Abstract:    This study investigates the influence of EDM parameters on EWR, MRR and ROC while machining of AISI D3 material. The parameters considered are pulse-on time (Ton), peak current (Ip), duty factor (t) and gap voltage (Vg). The experiments were performed on the die-sinking EDM machine fitted with a copper electrode. The experiments planned, conducted and analyzed using Taguchi method. It is found that the MRR is mainly influenced by (Ip); where as other factors have very less effect on material removal rate. Electrode wear rate is mainly influenced by peak current (Ip) and pulse on time (Ton), duty cycle (t) and gap voltage (Vg) has very less effect on electrode wear rate. Peak current (Ip) has the most influence on radial overcut then followed by duty cycle (t) and pulse on time (Ton) with almost very less influence by gap voltage (Vg).

   AISI D3; EDM; Radial overcut, duty factor


1.       C. J. Luis, I.Puertas, G. Villa “Material removal rate and electrode wear study on the EDM of silicon carbide”. Journal of Materials Processing Technology 164-16     (2005) 889- 896.
2.       A.A. Khan “Electrode wear and material removal rate during EDM of aluminium and mild steel using copper and brass electrodes”.  Int. Journal of Adv. Manuf.  Tech. (2008) 39:482-487.

3.       I. Puertas, C.J. Alvarez, ‘Analysis of the influence of EDM parameters on surface quality, MRR and EWR of WC-Co’. Journal of Materials Processing Technology 153-154 (2004) 1024-1032.

4.       S.H. Tomadi, M.A. Hassan, Hamedon, “Analysis of the influence of EDM parameters on Surface quality, Material Removal rate and Electrode wear of Tungsten Carbide”. Proceedings of International Multi Conference of Engineers and computer Scientists. Vol. II March 2009.

5.       K. M. Patel, Pulak M. Pandey, and P. Venkateswara Rao “Determination of an Optimum Parametric Combination Using a Surface Roughness Prediction Model for EDM of Al2O3/SiCw/TiC Ceramic Composite.” Dept. of Mech. Engg., IIT Delhi, India. Mtls. and Mfg. Processes, 24: 675–682, 2009

6.       S. Dhar and R. Purohit “Mathematical modeling and statistical analysis for Electric Discharge Machining machine (EDM) of AL-20% SI-CP cast metal matrix composite”. Department of Mfg. Processes and Automation Engg., Netaji Subhash Institute of Tech., Dwarka, New Delhi, India.- 110087

7.       P. M. George, B.K.Raghunath, L. M. Manocha, Ashish M. Warriern “EDM machining of carbon– carbon composites – a Taguchi approach”. Journal of Materials processing Technology. 145(2004) 66-71.





Mohammad Eyni Kangavar

Paper Title:

Seismic Propensity of Knee Braced Frame (KBF) As Weighed Against Concentric Braced Frame (CBF) Utilizing ETABS and OPENSEES

Abstract:    Steel braced frame is one of the structural systems used to resist earthquake loads in structures. Many existing reinforced concrete structures need retrofitting to overcome deficiencies and to resist seismic loads. The use of steel bracing systems for strengthening or retrofitting seismically in adequate reinforced concrete frames is a viable solution for enhancing earthquake resistance. Steel bracing is economical, easy to erect, occupies less space and has flexibility to design for meeting the required strength and stiffness. In the present study, seismic propensity of knee braced frames as weigh against concentric braced frames was investigated. These investigations were based on stiffness and ductility. Single - bay reinforced concrete frames in two levels which are a 1- story and a 10- story with three modes which are reinforced concrete frame without brace and reinforced concrete frame with concentric brace system and reinforced concrete frame with knee brace system were considered. Displacement analysis were performed using the  Extended 3D Analysis of Building Systems (ETABS) software for investigating stiffness of these system and pushover analysis were performed through Open System for Earthquake Engineering Simulation (OPENSEES) software for investigating ductility of these system. Finally, analysis of cyclic loading was done by using again the OPENSEES software for the completion of the investigations. The results of these outputs indicated that concentric bracing can provide a stiffer bracing system but reduces the ductility of the reinforced concrete frame. Knee bracing can be employed to provide the desired ductility level for reinforced concrete frame. It is concluded that both concentric bracing and knee bracing systems may be used to design or to retrofit for a damage-level earthquake. However, when designing or retrofitting for a collapse-level earthquake, knee bracing is a more effective system.

   concentric braced frame, ductility, knee braced frame, stiffness


1.        ACI Committee 318. (2002) Building code requirements for reinforced concrete (ACI 318-02).  American Concrete Institute, Detroit, MI.
2.        AISC.(2002) Seismic provisions for structural steel buildings. ( Chicago (IL): American Institute of Steel Construction.Aristizabal-Ochoa, J.D. (1986). Disposable knee bracing: improvement in seismic design of steel frames. Journal of Structural Engineering, 112 (7): 1544-1552.

3.        Abou-Elfath, H. & Ghobarah, A. (2000). Behaviour of reinforced concrete frames rehabilitated with concentric steel bracing. Canadian Journal of Civil Engineering., 27 433-444.

4.        Balendra, T., Yu, C.Y., & Xiao, Y. (2001). An economical structural system for wind and earthquake loads. Engineering Structures, 23: 491-501.

5.        Badoux, M. & Jirsa, O. (1990). Steel bracing of RC frames for seismic retrofitting. Journal of Structural Enineering. ASCE, No. 1, 116, 55-74.

6.        Bush, TD, Jones, EA, & Jirsa, JO. (1991). Behaviour of RC frame strengthened using structural steel bracing. Proc. ASCE, Journal of Structural Enineering. No. 4, 117, 1115-1126.

7.        Bourahla N. (1990). “Knee bracing system for earthquake resisting steel frames”, PHD-thesis. Department of Civil Engineering University of Bristol, UK.

8.        Balendra T, Sam M-T & Lee C-Y. (1990). “Diagonal brace with ductile knee anchor for a seismic steel frame”, Earthquake Engineering & Structural Dynamics, 19, 847-858.

9.        Balendera T, Sam M-T & Lee C-Y. (1991). “Preliminary studies into the behaviour of knee braced frames subject to seismic loading”, Engineering stractures, 13, 67-74.

10.     Baledra, T, Lim E-L & Liaw C-Y. (1994). “ Ductile knee braced with shear yielding knee for seismic resistant structures “, Engineering Structures, 16(4), 263-269.

11.     Balendra, T & Liaw, C-Y. (1995). “Earthquake-resistant steel frame with energy dissipating knee element”, Engineering Structures, 17(5), 334-343.

12.     Balendra, T, Lim E-L & Liaw C-Y. (1997). “Large-Scale Seismic Testing of Knee braced frame”, Journal of Structural Engineering, 1(1), 11-19.

13.     Building and Housing Research Centre. (2005). Iranian Code of Practice for Seismic Resistant  Design of Buildings (Standard 2800). Tehran.

14.     Chopra, A. (2005). Dynamics of structures: Theory and Applications to Earthquake Engineering. 2nd  Ed. New Delhi: Prentice-Hall of India,Del Valle Calderon, E.,Foutch, A., Hjelmstad, KD., Figueroa-Gutierrez, E. & Tena-Colunga A. Seismic retrofit of a RC building: a case study. Proceeding. of 9th World Conference. on Earthquake Engineering, Japan, 3 (1988) 451-456.

15.     Ghobarah, A. & Abou-Elfath H. (2001).  Rehabilitation of a reinforced concrete frames using eccentric steel bracing. Engineering Structures, 23, 745-755

16.     Hjelmstad, K. Foutch D., Del Valle, E., Downs, R. Forced vibration studies of an RC building retrofit with steel bracing. Proceeding of 9th World Conference on Earthquake Engineering. Japan, 3(1988) 469-474.

17.     Mofid, M. & Khosravi, P.(2000). Non-linear analysis of disposable knee bracing. Computers & Structures, 75: 65-72.

18.     Maheri, M. R. & Sahebi, A. (1997). Use of steel bracing in reinforced concrete frames. Engineering Structures, No.12, 19, 1018-1024.

19.     Mylonakis, G. & Gazetas, G. (2000). “Seismic Soil-structure interaction: beneficial or detrimental.” Journal of earthquake engineering; 4(3): 277-301.

20.     McKenna, F. (1997). “Object-oriented finite element programming: Frameworks for analysis, algorithms and parallel computing.” PhD thesis, University of California, Berkeley, CA.

21.     McKenna, F. & Fenves, G. (2002). “http://opensees.berkeley.edu. The OpenSees command language primer.” Department of Civil and Environmental Engineering, University of California, Berkeley, CA.

22.     Nateghi-Alahi F. (1995). Seismic strengthening of eight-story building using steel braces. Engineering Structures, No. 6, 17, 455-461.

23.     Sam, M.T., Balendra, T., & Liaw, C.Y. (1995). Earthquake-resistant steel frames with energy dissipating knee elements. Engineering Structure, 17(5):334-343.

24.     Schodek, D. (2004). Structures, fifth edition. Upper Saddle River, NJ: Pearson Education, Inc., INDEERS. ( University of Bristol ).

25.     Sekiguchi, I., (1998). Seismic strengthening of an existing steel reinforced concrete city office building in Shizuoka, Japan. Proceeding of 9th World Conference on Earthquake Engineering. Japan, 3 (1998)

26.     Sugano, S. & Fujimura, M., Seismic strengthening of existing reinforced concrete buildings. Proceeding of 7th World Conference on Earthquake Engineering., Turkey, No. 1, 4(1980)449-456.

27.     Tagawa, Y., Aoki, H., Huang, T. & Masuda H. (1992). Experimental study of new seismic strengthening method for existing RC structure. 10th World Conference on Earthquake Engineering, Rotterdam, 5193-5198.

28.     Tasnimi, A. & Masoomi, A. (1990) Evaluation of response reinforced concrete frames strengthened with steel bracing. Proceeding of 3rd International Conference on Seismic and Earthquake Engineering. Iran (in Persian).

29.     William, M., Blakeborough, A., Clement, D., & Bourahla, N. (2002). Seismic behavior of knee braced frames. Proceedings of the Institution of Civil Engineers: Structures and Buildings, 152(2):147-155.

30.     Wylli, L., Dal Pino, J. & Cohen, J. (1991). Seismic upgrade preserves architecture. Modern Steel Construction 20-23.





Nitish Agarwal

Paper Title:

Fragile Watermarking Scheme for Images in Transform Domain

Abstract:    Watermarking had an explosive amount of work done in the past decade. The field has diverse application areas, and a large number of fields amalgamate to ensure different requirement in different circumstances is being met by watermarking. We will be focusing in this paper mainly on the techniques which come under authenticating an image as to see if the image which is being used as a proof is not tampered in any way. This comes as the subset named as fragile watermarking in the field of watermarking techniques. We propose a novel method which focuses mainly on JPEG format of images and takes the lossy compression into consideration. The method works for both grayscale as well as the color images.

   Watermarking, Fragile Watermarking, Image Authentication, Transform Domain, JPEG, Hash, MD5, Digital Signature Algorithm, HMAC.


1.        M. U. Celik, Gaurav Sharma, E. Saber, and A. M. Tekalp. Hierarchical watermarking for secure image authentication with localization. IEEE Transactions on Image Processing, June 2002.
2.        R. Chandramouli, N. Memon, and M. Rabbani. Digital watermarking. Encyclopedia of Imaging Science and Technology, 2002.

3.        B. Chen and G. W. Wornell. Quantization index modulation methods: A class of provably good methods for digital watermarking and information embedding, May 2001.

4.        D. Coppersmith, F. Mintzer, C. Tresser, Chai Wah Wu, and M. M. Yeung. Fragile imperceptible digital watermark withprivacy control. SPIE conference on Security and      Watermarking of Multimedia Contents, January 1999.

5.        I. J. Cox, J. Killian, F. T. Leighton, and T. Shamoon. Secure spread spectrum watermarking for multimedia, December1997.

6.        F.Minitzer, G.W. Braudaway, and A. E. Bell. Opportunities for watermarking standards. Communications of ACM, July 1998.

7.        J. Fridrich, M. Goljan, and Arnold C. Baldoza. New fragile authentication watermark for images. Proc. IEEE International Conference Image Processing, September 2000.

8.        J. Fridrich, M. Goljan, and N. Memon. Further attacks on yeung-mintzer watermarking scheme. Proc. SPIE Electronic Imaging, January 2000.

9.        G. L. Friedman. The trustworthy digital camera: Restoring credibility to the photographic image. IEEE Transactions on Consumer Electronics, November 1993.

10.     M. Holliman and N. Memon. Counterfeiting attacks on oblivious block-wise independent invisible watermarking scheme. IEEE Trans. Image Processing, pages 432–441, March 2000.

11.     J. Hwang, J. Kim, and J. Choi. A reversible watermarking based on histogram shifting. Springer-Verlag IWDW, pages 348–361, 2006.

12.     R. Du J. Fridrich, M. Goljan. Invertible authentication watermark for jpeg images. Proc. SPIE Photonics West, Security and Watermarking of Multimedia Contents III, pages 197–208, Janurary 2001.

13.     N. F. Johnson and S. Jajodia. Exploring steganography: Seeing the unseen. IEEE Computer, pages 26–34, 1998.

14.     H. Lu, R. Shen, and Fu-Lai Chung. Fragile watermarking scheme for image authentication. Electronics Letters, June 2003.

15.     C. Paar and et al. Understanding Cryptography. Springer, 2010.

16.     Christine I. Podilchuk and Edward J. Delpi. Digital watermarking: Algorithms and applications. IEEE Signal Processing Magazine, 2001.

17.     P. W. Wong. A public key watermarking for image verification and authentication. Proc. IEEE International Conference Image Processing, pages 425–429, October 1998.

18.     J. Wu, B. B. Zhu, S. Li, and F. Lin. Efficient oracle attacks on yeung-mintzer and variant authentication schemes. Proc. Of International Conf. on Multimedia and Expro. Taiwan, pages 301–306, 2004.

19.     M. Wu and B. Liu. Watermarking for image authentication. IEEE Proc. of ICIP, October 1998.

20.     Minerva M. Yeung and F. Mintzer. An invisible watermarking technique for image verification. Proc. IEEE Int. Conf. Image Processing, October 1997.





Rashi Bais, K.K.Mehta

Paper Title:

Biometric Parameter Based Cryptographic Key Generation

Abstract:    A method is proposed for generation of unique cryptographic key which is generated using biometrics of the user, which are stable throughout person's lifetime. The proposed approach reduces the cost associated with lost keys, addresses non-repudiation issues and provides increased security of digital content. This approach has reduced the complicated sequence of the operation to generate crypto keys as in the traditional cryptography system. The key is derived directly from the biometric data and is not stored in the database, since it creates more complexity to crack or guess the cryptographic keys. We evaluated our technique using 50 different fingerprint samples, and found that an error-free key can be reproduced reliably with a 99.5% success rate. This approach is implemented in MATLAB and can generate variable size cryptographic key, with minimum amount of time complexity, which is aptly suited for any real time cryptography.

Keywords:   Cryptography, Biometrics, Minutiae points, Morphological Operation, Histogram Equalization, Crossing Number


1.        Umut Uludag, Sharath Pankanti, Salil Prabhakar, Anil K.Jain “Biometric Cryptosystems Issues and Challenges” Proceedings of the IEEE 2004.
2.        P.Arul, Dr.A.Shanmugam “Generate a Key for AES Using Biometric For VOIP Network Security” Journal of Theoretical and Applied Information Technology 2009.107-112.

3.        Je-Gyeong Jo, Jong-Won Seo, and Hyung-Woo Lee Div Biometric Digital Signature Key Generation and Cryptography Communication Based on Fingerprint. Computer Information of Software, Hanshin University               

4.        N.Lalithamani, K.P.Soman “Irrevocable Cryptographic Key Generation from Cancelable Fingerprint Templates: An Enhanced and Effective Scheme”. European Journal of Scientific Research ISSN 1450-216X Vol.31 No.3 (2009), pp.372-387

5.        Víctor  López Lorenzo, Pablo Huerta Pellitero, José Ignacio Martínez Torre, Javier Castillo Villar, “Fingerprint Minutiae Extraction Based On FPGA and MatLab”, http://www.escet.urjc.es/~phuerta/pdf/dcis_ 2005.pdf

6.        Jain, A.K.; Prabhakar, S.; Hong, L.; Pankanti, S., "Filterbank-based fingerprint matching",IEEE Transactions on Image Processing, vol. 9, no. 5, pp: 846-859, May 2000, Doi:10.1109/83.841531.

7.        Sang Keun Oh, Joon Jae Lee*, Chul Hyun Park, BumSoo Kim, Kil Houm Park School of Electrical Engineering, Kyungpook National University, SEOUL 702-701,Daegu ,
Korea,“New Fingerprint Image Enhancement Using DirectionalFilterBank”
8.        A. Goh, D.C.L. Ngo, “Computation of cryptographic keys from face biometrics, “International Federation for Information Processing 2003, Springer-Verlag, LNCS 2828, pp. 1–13, 2003.

9.        Y. Seto, “Development of personal authentication systems using fingerprint with smart cards and digital signature technologies,” the Seventh International Conferenceon Control, Automation, Robotics and Vision, Dec 2002.





Sowjanya Sunkara, T.Ravi Sekhar

Paper Title:

High Speed Codec Design for Crosstalk Avoidance

Abstract:    The cross talk is dependent on the data transition patterns on the bus, patterns can be classified based on the severity of the crosstalk they impose on the bus. The general idea behind techniques that improve on-chip bus speed is to remove undesirable patterns that are associated with certain classes of crosstalk. Different schemes incur different area  overheads since they requires additional wires, spacing between wires or both. We analyze the properties of the FPF-CAC and show that mathematically, a mapping scheme exists between the data words and code words. Our proposed CODEC design offers a near-optimal area overhead performance. An improved version of the CODEC is then presented, which achieves theoretical optimal performance. We also investigate the implementation details of the CODECs, including design complexity and the speed. Optimization schemes are provided to reduce the size of the CODEC and improve its speed.

   CODEC, FPF-CAC, pruning,shielding.


1.         Duane .C, Cordero. V and Khatri. S. P. “Efficient On-Chip Crosstalk Avoidance CODEC Design”, IEEE Transactions on VLSI Systems, April 2009, pp 551 – 560.
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3.         Madhu Mutyam, ”Preventing Crosstalk Delay using Fibonacci Representation”, Intl Conf. on VLSI Design, 2004, pp 685-688.

4.         S.R. Sridhara, A. Ahmed, and N. R. Shanbhag, ”Area and Energy- Efficient Crosstalk Avoidance Codes for On-Chip busses”, Proc. of ICCD,2004, pp 12-17.

5.         C. Duan, A. Tirumala and S. P. Khatri, “Analysis and Avoidance of Crosstalk in On-chip Bus”, HotInterconnects, 2001,pp 133-138.

6.         Bret Victor and K. Keutzer,”Bus Encoding to Prevent Crosstalk Delay”,ICCAD, 2001, pp 57-63.

7.         T. Gao and C.L. Liu, “Minimum Crosstalk Channel Routing,” IEEE Transactions on Computer-Aided Design, vol. 15, no. 5, pp. 465-474, 1996.

8.         K. Hirose and H. Yasuura, “A Bus Delay Reduction Technique Considering Crosstalk,” Proceedings. Design, Automation and Test in Europe Conference and Exhibition 2000, pp. 441-445, 2000.

9.         H.-P. Tseng, L. Scheffer, and C. Sechen, “Timing and crosstalk Driven Area Routing,” Proceedings. 35th Design Automation Conference, pp. 378-381, 1998.

10.       A. Vittal and M. Marek-Sadowska, “Crosstalk Reduction VLSI,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems, vol. 16, no., pp. 290-298, 1997.

11.       T. Xue, E. Kuh, and D. Wang, “Post Global Routing Crosstalk Synthesis,” IEEE Transactions on Computer Aided Design, vol. 16, no. 12, pp. 1418-1430, 1997.

12.       T. Sakurai, “Closed-Form Expressions for Interconnection Delay          Coupling, and Crosstalk in VLSI’s,” IEEE Transactions on Electron Devices, vol. 40, no. 12, pp. 118-124, 1993.

13.       H. Zhou and D.F. Wong, “Global Routing with Crosstalk      Constraints,” Proceedings. 35th Design Automation Conference, pp. 374-377, 1998.

14.       B. Victor and K. Keutzer, “Bus Encoding to Prevent Crosstalk Delay,” Proceedings. ICCAD-2001 International Conference on Computer-Aided Design 2001, pp.57-64, 2001.

15.       K. Kim, K. Baek, N. Shanbhag, C. Liu, and S.-M.Kang, Coupling driven signal encoding scheme for low-power interface design, Proc. Of IEEE/ACM International Conference on Computer-Aided Design, Nov 2000.

16.       H. Kaul, D. Sylvester and D. Blauuw, ”Active shielding of RLC global interconnects”, Proc. of the 8th ACM/IEEE international workshop on Timing issues in the specification and synthesis of digital systems, 2002, pp 98-104.

17.       D. Li, A. Pua, P. Srivastava, and U. Ko, “A Repeater Optimization      Methodology for Deep Sub- Micron, High-Performance Processors,” Proceedings. International Conference on Computer Design, VLSI in   Computers and Processors, pp. 726-731, 1997.

18.       A.B. Kahng, S. Muddu, E. Sarto, and R. Sharma, “Interconnect Tuning Strategies for High-Performance ICs,”Proceedings. Design, Automation and Test in Europe Conference and Exhibition 1998, pp. 471-478, 1998.

19.       A. Apostolico and A.S. Fraenkel, “Robust Transmission of Unbounded Strings Using Fibonacci Representations,” IEEE Transactions on Information Theory, IT- 33, pp. 238-245, 1987.

20.       H.B. Bakoglu, Circuits, Interconnections and Packaging for VLSI, Addison-Wesley, 1990.

21.       A.S. Fraenkel, “Systems of Numeration,” The American Mathematical Monthly, vol. 92, pp. 105-114, 1985.





Brajesh Mishra, Sudeep Baudha, Amit Gupta

Paper Title:

Data Rate Comparison during Handoff in GSM with Wireless ATM Networks

Abstract:    Wireless GSM  has emerged as an important component of the broadband wireless network infrastructure. While GSM supports for different traffic characteristics and QOS requirements, WATM networks provide wireless extension to the ATM-based B-ISDN networks by adding mobility support functions. The implementation of WATM poses several problems like mobility management, radio access to network etc. This paper presents the literature survey of GSM and its handoff related issues. Handoff is basically related with GSM so that we can understand the required bandwidth and data rate. These parameters are compared with traditional and advance data rate bandwidth. The paper reviews ATM fundamentals and its benefits. It deals with GSM features, requirements, protocol architectures and the global activities AS per the requirement of higher access network user needs high speed that will surly increase with GSM network. The focus is made on the handoff related aspects of WATM and GSM. The handoff management operation, requirements, protocols, proposed solutions and open issues for research.

   GSM, ATM. Hand-Off, Data Rate


1.        R. Handel, M. N. Huber, S. Schroder: ATM Networks- concepts, protocols and applications 7e. Pear- son Education Ltd; India (2004)
2.        D. Raychaudhuri: Wireless ATM Networks-Architecture, System Design and Prototyping. IEEE Per- sonal Communications. 3 (4), 42-49 (1996)

3.        B. Kraimeche:  Wireless ATM- Current Standards and Issues. IEEE Wireless Communications and Networking Conference. 1, 56-60 (1999)

4.        D.Raychaudhuri, N. D. Wilson: ATM-Based Transport Architecture for Multi services Wireless Per- sonal Communication Networks. IEEE Journal On Selected Areas in
Communications. 12 (8), 1401-1414 (1992)

5.        T. Nadeem, R. Miller: Survey on Wireless and Mobile ATM Networks. Wireless and ATM Networks. (2002)

6.        E. Ayanoglu, K.Y. Eng, M. J. Karol: Wireless ATM- Limits, Challenges and Proposals. IEEE Personal Communications. 3 (4), 18-34 (1996)

7.        Hakan Mitts: Architectures for wireless ATM. Helsinki University of Technology. (June 1996). http://lib.tkk.fi/HUTpubl/publications/mitts96.html.

8.        Xinri Cong: Wireless ATM - An Overview. Ohio state. (Aug. 1997)http://www.cs.wustl.edu/˜jain/cis788-97/ftp/wire atm.pdf.

9.        D. Raychaudhuri, N. Wilson: Multimedia Personal   Communication Networks- System Design Issues. Proc. 3rd WIWLAB Workshop on 3rd Generation Wireless Information Networks. 259-288 (1992)

10.     Ayse Yasemin Seydim:  Wireless ATM (WATM) An Overview. Southern Methodist University, EE8304 Spring 2000, Section 799. (2000) http://www.engr.smu.edu/˜yasemin/watm.pdf.

11.     R. R. Bhat and K. Rauhala: Draft Baseline Text for Wireless ATM Capability Set 1 Specification. BTD WATM-01, ATM Forum. (Dec. 1998)

12.     L. Dellaverson: Reaching the New Frontier. The ATM Forum Newsletter. 4 (3), (Oct.1996) .http://www.atmforum.org/atmforum/library/53bytes/backissues/v4-3/article-08.html

13.     Damian Gilmurray, Alan Jones, Oliver Mason, John Naylon, John Porter: Wireless ATM Radio Access       Layer Requirements. ATM Forum/96-1057/WATM. (Aug. 1996)

14.     C. Chrysostomou1, A. Pitsillides, F. Pavlidou: A Survey of Wireless ATM Handover Issues. Proc. of the Int. Symposium of 3G Infrastructure and Services. 2 (3), 34-39 (2001)

15.     A. T. Campbell, K. Rauhala: Mobile ATM- State of the Art and Beyond. IEEE Networks. 12 (1), 10-11 (1998)

I.         Akhyldiz: Mobility Management in Next generation Wireless System. Proceedings of the IEEE. 87 (8), 1347-1384 (1999)

16.     Upkar Varshney: Supporting Mobility with Wireless ATM. IEEE Computers Magazine. 30(1), 131-133 (1997)

17.     A. Kaloxylos, G. Dravopoulos, H. Hansen: Mobility Management Extensions in the Wireless ATM Network Demonstrator. Proceedings of the ACTS-98 Summit, Rhodes, Greece. (1998)

18.     A. Kaloxylos, G. Alexiou, S. Hadjiefthymiades, L. Merakos :   Design and Performance Evaluation of a Mobility Management Protocol for Wireless ATM Networks. Proceedings of PIMRC-98, Boston USA. (1998)

19.     Alex Kaloxylos, S. Hadjiefthymiades, and Lazciros Merakos: Mobility management and control pro- tocol for Wireless ATM Networks, IEEE Networks, 19-27 (Jul./Aug.-1998)





N.P. Zinjad, S. S. More

Paper Title:

Energy Efficiency in Data Centers: How to Reduce Power Consumption in Data Centers by Optimum UPS Loading

Abstract:    Computation and data center has a huge value to modern enterprise. This has resulted in the installation of millions of data centers in business around the globe. Historically, the cost to power and cool these facilities was small relative to the investment in servers, storage units and other equipments. Today, however, the annual power and cooling costs of typical data centers are almost equal to the cost of hardware. In the past decade, India has witnessed an exponential increase in the demand for digital storage, from 1 petabyte in 2001 to more than 34 petabytes by 2007. They also continue to grow at a compounded rate of 25-30%. Datacenter growth is basically driven by increasing requirements from the sectors such as financial institutions, telecom operators, manufacturing and services. While large financial institutions and telecom companies are likely to build captive Datacenters for hosting their growing data storage needs. Datacenter service providers are expected to invest significantly to multiply their capacities, so as to fulfill the demand arising from small and midsize users. Datacenter is highly energy intensive. With the increasing energy cost, the increase in operational cost is inevitable. Therefore it becomes necessary to reduce the energy consumption to offset the increasing operational cost and to maintain competitiveness. Existing Datacenters need to adopt the best practices in design, operation and maintenance to achieve operational excellence. The increasing IT business process outsource from foreign countries has resulted in phenomenal growth of Datacenters in India. The total datacenter capacity in India is growing at a rapid pace and is expected to exceed 5.1 million square feet by 2012. The primary scope of this paper is to provide a framework in which data centers, large and small, could analyze and reduce their power consumption. This paper provides a quantitative approach to understanding energy efficiency within a server and within a data center. A panorama for power minimization and energy efficiency beginning with the basics of dual in line memory modules (DIMM) selection, configuring processors with reduced power states, options for constantly spinning disks, power management features in operating systems and other internal equipments.

   Loading optimization, Harmonics, Flywheel plus converter, Loading, Efficiency, Five “nines”, MTTF, MTBR, MTBF.


1.       Datacenter book; Publisher: BEE India
2.       Energy Efficiency in Data Centers; Publisher: Intel

3.       www.leonardo energy.com

4.       APC journals

5.       www.schneider electricals.com

6.       www.cockvalley.com

7.       Configuring your UPS; Publisher: EAMS





Deepak Kumar Dakate, Pawan Dubey

Paper Title:

Blowfish Encryption: A Comparative Analysis using VHDL

Abstract:    Data security has always been important in all aspects of life. Data may contain several form of information that we want to secure from any unauthorized access. It can be all the more important as technology continues to control various operations in our day to day life Reprogrammable devices are highly attractive options for hardware implementations of encryption algorithms as they provide cryptographic algorithm agility, physical security, and potentially much higher performance, therefore this paper investigates a hardware design to efficiently implement a special type block ciphers in VHDL and its comparative analysis in different parameter variation . This hardware design is applied to the new secret and variable size key block cipher called Blowfish designed to meet the requirements of the previous known standard and to increase security and to improve performance. The proposed algorithm will be used a variable key size.



1.       B. Schneier, Description of a New Variable-Length Key, 64-Bit Block Cipher (Blowfish),Fast Software Encryption, Cambridge Security Workshop Proceedings (December 1993), Springer-Verlag, 1994.
2.       M. Thaduri, S.-M. Yoo, An efficient VLSI implementation of IDEA encryption algorithm using VHDL, Sciencedirect ,5 JUNE 2004.

3.       Afaf M. Ali Al-Neaimi, New Approach for Modifying Blowfish Algorithm by Using Multiple Keys, IJCSNS, March 2011
4.       Krishnamurthy G.N , V. Ramaswamy , Leela G.H and Ashalatha M.E,” Blow-CAST-Fish: A New 64-bit Block Cipher”, IJCSNS International Journal of Computer Science and Network Security, VOL.8 No.4, p. 282,April 2008.

5.       P. Karthigai Kumar, K. Baskaran , An ASIC implementation of low power and high throughput blowfish crypto algorithm, Sciencedirect, 6 April 2010.

6.       Sushanta Kumar Sahu, Manoranjan Pradhan, FPGA Implementation of RSA Encryption System, International Journal of Computer Applications, April 2011.





Veeraiah Kumbha, N. Sumathi, K. Siva Naga Raju

Paper Title:

Power Quality Improvement of Grid Connected Wind Energy System having Balanced and Unbalanced Non-linear Loads

Abstract:    A Power quality problem is an occurrence manifested as a nonstandard voltage, current or frequency that results in a failure or a mis-operation of end user equipments. Utility distribution networks, sensitive industrial loads and critical commercial operations suffer from various types of outages and service interruptions which can cost significant financial losses. With the restructuring of power systems and with shifting trend towards distributed and dispersed generation, the issue of power quality is going to take newer dimension. Injection of the wind power into an electric grid affects the power quality. The performance of the wind turbine and thereby power quality are determined on the basis of measurements and the norms followed according to the guideline specified in International Electro-technical Commission standard, IEC-61400. The influence of the wind turbine in the grid system concerning the power quality measurements are-the active power, reactive power, variation of voltage, flicker, harmonics, and electrical behavior of switching operation and these are measured according to national/international guidelines. The paper study demonstrates the power quality problem due to installation of wind turbine with the grid. In this proposed scheme STATIC COMPENSATOR (STATCOM) is connected at a point of common coupling with a battery energy storage system (BESS) to mitigate the power quality issues.. The STATCOM control scheme for the grid connected wind energy generation system for power quality improvement is simulated using MATLAB/SIMULINK in power system block set. Finally the proposed scheme is applied for both balanced and unbalanced linear non- linear loads.

   International electro-technical commission (IEC), power quality, wind generating system (WGS).


1.        A.E. Hammad, Comparing the Voltage source capability of Present and future Var Compensation Techniques in Transmission System, IEEE Trans, on Power Delivery .volume 1. No.1 Jan 1995.
2.        G.Yalienkaya, M.H.J Bollen, P.A. Crossley, “Characterization of Voltage Sags in Industrial Distribution System”, IEEE transactions on industry applications, volume 34, No. 4, July/August, PP.682-688, 1999.

3.        Haque, M.H., “Compensation Of Distribution Systems Voltage sags by DVR and D-STATCOM”, Power Tech Proceedings, 2001 IEEE Porto, Volume 1, PP.10-13, September 2001.

4.        Anaya-Lara O, Acha E., “Modeling and Analysis Of Custom Power Systems by PSCAD/EMTDC”, IEEE Transactions on Power Delivery, Volume 17, Issue: 2002, Pages: 266-272.

5.        Bollen, M.H.J.,”Voltage sags in Three Phase Systems”, Power Engineering Review, IEEE, Volume 21, Issue :9, September 2001, PP: 11-15.

6.        M.Madrigal, E.Acha., “Modelling OF Custom Power Equipment Using Harmonics Domain Techniques”,IEEE 2000.

7.        R.Meinski, R.Pawelek and I.Wasiak, “Shunt Compensation For Power Quality Improvement Using a STATCOM controller Modelling and Simulation”, IEEE Proce, Volume 151, No. 2, March 2004.

8.        J.Nastran , R. Cajhen, M. Seliger, and P.Jereb,”Active Power Filters for Nonlinear AC loads, IEEE Trans.on Power Electronics Volume 9, No.1, PP: 92-96, Jan 2004.

9.        L.A.Moran, J.W. Dixon , and R.Wallace, A Three Phase Active Power Filter with fixed Switching Frequency For Reactive Power and Current Harmonics Compensation, IEEE
Trans. On Industrial Electronics. Volume 42, PP:402-8, August 1995.

10.     L.T. Moran ,P.DZiogas, and G.Joos , Analysis and Design Of Three Phase Current source solid State Var Compensator, IEEE Trans, on Indutry Applications. Volume 25, No.2, 1989, PP:356-65.





S. Drishya, I. Nancy Jeba Jingle

Paper Title:

Efficient Method for De-Duplication and Periodicity Mining In Time Series Databases

Abstract:    Periodic pattern mining or periodicity detection has a number of applications, such as prediction, forecasting, detection of unusual activities, etc. The problem is not trivial because the data to be analyzed are mostly noisy and differentperiodicity types(namely symbol, sequence, and segment) are to be investigated. Noise is the duplication of data from differentdatabases when they are used for same purpose in different places. So it should be removed. Time series is a collection of data values gathered generally at uniform interval of time to reflect certain behavior of an entity. Real life has several examples of time series such as weather conditions of a particular location, transactions in a superstore, network delays, power consumption, earthquake prediction. A time series is mostly characterized by being composed of repeating cycles. Identifying repeating (periodic) patterns could reveal important observations about the behavior and future trends of the case represented by the time series, and hence would lead to more effective decision making. The goal of analyzing a time series is to find whether and how frequent a periodic pattern (full or partial) is repeated within the series. There is a need for a comprehensive approach capable of analyzing the whole time series or in a subsection of it to effectively handle different types of noise (to a certain degree) and at the same time is able to detect different types of periodic patterns; combining these under one umbrella is by itself a challenge. In this paper, we present an algorithm which can detect symbol, sequence (partial), and segment (full cycle) periodicity in time series. The algorithm is noise resilient; it has been successfully demonstrated to work with replacement, insertion, deletion, or a mixture of these types of noise.

   Time series, periodicity detection, suffix tree, symbol periodicity, segment periodicity, sequence periodicity, noise resilient.


1.        M. Ahdesma¨ki, H. La¨hdesma¨ki, R. Pearson, H. Huttunen, and O. Yli-Harja, “Robust Detection of Periodic Time Series Measured from Biological Systems,” BMC Bioinformatics, vol. 6, no. 117, 2005.
2.        C. Berberidis, W. Aref, M. Atallah, I. Vlahavas, and A.Elmagarmid, “Multiple and Partial Periodicity Mining in Time Series Databases,” Proc. European Conf. Artificial Intelligence, July

3.        J. Han, Y. Yin, and G. Dong, “Efficient Mining of Partial Periodic Patterns in Time Series Database,” Proc. 15th IEEE Int’l Conf. Data  Eng., p. 106, 1999.

4.        Y. Tian, S. Tata, R.A. Hankins, and J.M. Patel, “Practical Methods for Constructing Suffix Trees,” VLDB J., vol. 14, no. 3, pp. 281-299, Sept. 2005.

5.        K.-Y. Huang and C.-H. Chang, “SMCA: A General Model for Mining Asynchronous Periodic Patterns in Temporal Databases,” IEEE Trans. Knowledge and Data Eng., vol. 17, no. 6, pp. 774-785, June 2005.





Ashish P. Waghmare, S. S. Pimplikar

Paper Title:

Financial Analysis of Infrastructure Project - A Case Study on Built-Operate-Transfer Project in India

Abstract:   The build operate transfer scheme can be advantageously adopted by administrations in India for implementing transport infrastructure projects, such as the construction of bridges, road without undue strain on their declining budgetary resources relating to the toll structure, toll revision schedule, extent of the grant, and duration of the concession period. Feasibility report is prepared during the initial phase or definition phase of the project. Updating and validation of the feasibility report is required for implementation of the project. the project can be implemented as per techno economics stipulation made in the feasibility report. A feasibility report is prepared to present an in-depth techno economic analysis carried out on the project and contain result of technical as well as economic evaluation of the project so that the owner can take investment decision and the project can be properly planned and implemented . The viability of any project mainly depend on the technical analysis, financial analysis, economic analysis, ecological analysis. Hence it can be very well understood that feasibility study is the base for the success of a project and the major part of this success lies in proper financial analysis. Financial analysis is useful for every business entity to enhance their performance, competitive strength and access their financial stability and profitability of the firm. This paper investigates the financial analysis of the BOT project

   BOT Infrastructure projects, profitability statement, cash flow statement, DSCR, payback period.


1.       ‘A Guide to the Project Management Body of Knowledge’, Third Edition, (PMBOK® Guide), an American National Standard ANSI/PMI 99-001-2004
2.       ‘Financial Management’, Prasanna Chandra (2001 ),Tata McGraw-Hill Publishing Company Ltd., New Delhi

3.       ‘Financial Management’, Rustagi. R. P. (2002), Galgotia publishing company, New Delhi.

4.       “Projects Planning, Financing, Implementation and Review”, Chandra Prasanna, Tata McGraw-Hill, New Delhi, 2002.

5.       ‘Feasibility Studies for Public Sector Projects’, Planning Commission, Govt. of India, 1966





Amrita Chakraborty, Avinash Gaur

Paper Title:

Signaling Technique for Free Space Optics

Abstract:    A new efficient method to implement orthogonal frequency division multiplexing (OFDM) on intensity modulated direct detection (IM/DD) channels is presented and termed auto-correlated optical OFDM. It is shown that a necessary and sufficient condition for a band limited periodic signal to be positive for all time is that the frequency coefficients form an autocorrelation sequence. Instead of sending data directly on the subcarriers, the autocorrelation of the complex data sequence is performed before transmission to guarantee non-negativity. In contrast to previous approaches, auto-correlated optical OFDM is able to use the entire bandwidth for data transmission and does not require reserved subcarriers. Using a sub-optimal design technique with 1024 subcarriers, auto-correlated optical OFDM has a better BER than the existing techniques.

   Auto-correlation, IM/DD,OFDM.


1.        J. Grubor, S. Randel, K.D. Langer and J.W. Walewski, “Broadband information broadcasting using LED-based interior lighting”, IEEE/OSA J. Lightw. Technol., vol. 26, no. 24, pp. 3883-3892, Dec. 15, 2008.
2.        J.M. Cioffi, “A Multicarrier Primer,” November 1991, ANSI Contribution T1E1.4/91-157, Clearfield, Fla, USA.

3.        J.B. Carruthers and J.M. Kahn, “Multiple-subcarrier modulation for nondirected wireless infrared communication,” IEEE J. Select. Areas Commun., vol. SAC-14, pp. 538-546, Apr. 1996.

4.        J. Armstrong and A.J. Lowery, “Power efficient optical OFDM,” Electron. Lett., vol. 42, pp. 370-372, 2006.

5.        S.C.J. Lee, S. Randel, F. Breyer and A.M.J. Koonen, “PAM-DMT for intensity-modulated and direct-detection optical communication systems,” IEEE Photon. Technol. Lett., vol. 21, pp. 1749-1751, 2009.

6.        S. Wu, S Boyd and L. Vandenberghe, “FIR filter design via spectral factorization and convex optimization,” in Applied and Computational Control, Signals and Circuits, B.Datta, Ed., Boston, MA: Birkhauser, 1999, vol.1.





A. Bhogayata, K. D. Shah, B. A.vyas, N. K. Arora

Paper Title:

Feasibility of Waste Metallised Polythene Used As Concrete Constituent

Abstract:    Utilising fibres in concrete was introduced in early 1900s. Since then large variety of fibres are experimented and being practiced effectively around the world. The prime concern was the improvisation of concrete properties. With time, the scenario gets diverted towards utilisation of wastes and by products from industry and municipal wastes especially the plastic wastes were in concern. The most stable form of plastic wastes made them non biodegradable and somewhat difficult to recycle. In last ten years, large range of various wastes are added to concrete as dual solution towards mitigation of waste management problems and reducing natural material use as concrete constituent. This paper presents the experimental investigation of feasibility of polyethylene post consumer waste used for food packaging along with fly ash as another by product of thermal power stations. The ample numbers of samples were prepared in M10 concrete mix with two different water/ cement ratio. Plastic waste was converted in fibre form and added from 0% to 1.5% of volume along with variation of fly ash from 0% to 30% of volume. Different curing conditions were used to note the effect of chemical attack and corresponding change in the compressive strength of the concrete mix.

  metallised polyethylene, land filling, compressive strength, acid curing, sulphate curing,  water/cement ratio.


1.        Ankur Bhogayata and Narendra K. Arora, “Green concrete from the post consumer plastic wastes: Indian scenario”, ICTSET proceedings, ISBN: 978-81-906377-9-4, pages: 437-440, April, 2011.
2.        C. Meyer,“The greening of the concrete industry”,Cement & Concrete Composites 31 (2009) 601–605

3.        F. Mahdi a, H. Abbas b, A.A. Khan c “Strength characteristics of polymer mortar and concrete using different compositions of resins derived from post-consumer PET bottles”, Construction and Building Materials 24 (2010) 25–36.

4.        F. Pacheco-Torgal a,⇑, Yining Ding b, Said Jalali a “Properties and durability of concrete containing polymeric wastes (tyre rubber and polyethylene terephthalate bottles): An overview”, Construction and Building Materials 30 (2012) 714–724.

5.        Luiz A. Pereira de Oliveira , João P. Castro-Gomes “Physical and mechanical behaviour of recycled PET fibre reinforced mortar”, Construction and Building Materials 25 (2011) 1712–1717.                                        

6.        M.Sivaraja, S. Kandasamy and A. Thirumurugan, “Mechanical strength of fibrous concrete with waste rural materials”, Journal of engineering and applied science, vol. 69, April, page: 308 – 312, 2010.                                                         

7.        M. Sivaraja and Kandasamy, “Reinforced concrete beams with rural composites under cyclic loading”, Journal of engineering and applied science 2 (11), page: 1620 -1626, 2007.           

8.        Marzouk OY, Dheilly RM, Queneudec M. “Valorisation of Post Consumer Waste Plastic  in Cementitious Concrete Composites”, PubMed, U.S.National Library of Medicine, National Institute of Health, vol. 27 (2), Issue-12, 310- May, 2006.

9.        Priya Narayan, “Analysing Plastic Waste in India- Case Study of PET bottles and poly bags”, Lund University, Sweden, September, 2001. 

10.     Prvinkumar and S.K. Kaushik, “Some trends in the use of concrete: Indian Scenario”, The Indian concrete Journal, December, page: 1503 –1508, 2003.         
11.     T.R.Naik, S.S. Singh, C.O.Huber, and B.S.Brodersen, “Use of  Post Consumer Plastics in Cement Based Composites”, Cement and Concrete Research, Science Direct, Vol. 26, Issue 10, October, page: 1489 – 1492, 1996.

12.     Zainab Z. Ismail, Enas A. Al – Hashmi, “ Use of Waste Plastic in Concrete Mixture as Aggregate Replacement”, Waste Management, Science Direct, Vol. 28, Issue 11, November, page: 2041 – 2047, 2008.      





B.Rajani, P.Sangameswara Raju

Paper Title:

Pi & Fuzzy Logic Controller Based Multi Converter Unified Power Quality Conditioner

Abstract:    A  new unified power-quality conditioning system  (MC-UPQC) ,  is proposed in this paper as a new custom power device for a two-bus/two-feeder distribution system. The response of the Multi converter unified power quality conditioner, for different types of controllers are studied. This paper capable of simultaneous   compensation for voltage and current in multibus/multifeeder systems. In this configuration, one shunt voltage-source converter (shunt VSC) and two or more series VSCs exist. The system can be applied to adjacent feeders to compensate for supply-voltage and load current imperfections on the main feeder and full compensation of supply voltage imperfections on the other feeders. In the proposed configuration, all converters are connected back to back on the dc side and share a common dc-link capacitor. Therefore, power can be transferred from one feeder to adjacent feeders to compensate for sag/swell and interruption. In order to regulate the dc-link capacitor voltage, Conventionally, a proportional controller (PI) is used to maintain the dc-link voltage at the reference value. The transient response of the PI dc-link voltage controller is slow. So, a fast acting dc-link voltage controller based on the energy of a dc-link  capacitor  is proposed. The transient response of this controller is very fast when compared to that of the conventional dc-link voltage controller. By using fuzzy logic controller instead of the PI  controller the transient response is improved. The detailed simulation studies are carried out to validate the proposed controller. The performance of the proposed configuration has been verified through simulation studies using MATLAB/SIMULATION on a two-bus/two-feeder system.

   Power quality (PQ),MATLAB/SIMULATION unified power-quality conditioner (UPQC), voltage-source converter (VSC), fuzzy logic controller.


1.        Hamid Reza Mohammadi, Ali Yazdian Varjani, and Hossein Mokhtari,“Multiconverter Unified Power-Quality Conditioning System: MC- UPQC” IEEE TRANSACTIONS ON POWER   DELIVERY, VOL. 24, NO. 3, JULY 2009.
2.        R.Rezaeipour and A.Kazemi, “Review of Novel  control strategies for UPQC” Internal Journal of Electric and power Engineering 2(4) 241-247,  2008.

3.        S. Ravi Kumar and S.Siva Nagaraju“Simulation of DSTATCOM and DVR in power systems” Vol. 2, No. 3, June 2007 ISSN 1819-6608 ARPN Journal of Engineering and Applied Sciences.

4.        M.V.Kasuni Perera” Control of a Dynamic Voltage Restorer to compensate single phase voltage sags” Master of Science Thesis  Stockholm, Sweden 2007.

5.        M. Basu, S. P. Das, and G. K. Dubey, “Comparative evaluation of two models of UPQC  for suitable interface to enhance power quality,”    Elect.Power Syst. Res., pp. 821– 830, 2007.  

6.        A. K. Jindal, A. Ghosh, and A. Joshi, “Interline   unified power quality conditioner,” IEEE Trans.  Power Del. vol. 22, no. 1, pp. 364–372, Jan. 2007.

7.        P.Hoang, K.Tomosovic, “Design and an analysis an adaptive fuzzy  power  system  stabilizer”,Vol. 11, No. 2.June 1996.
8.  Momoh, X. W. Ma, “Overview and Literature   survey of Fuzzy set theory in power systems”,IEEE   Trans.on Power Systems, Vol. 10, No.3, Aug. 1995. pp. 1676-1690.





Aditya Goyal, Akhilesh Bijalwan, Pradeep Kumar, Kuntal Chowdhury

Paper Title:

Image Enhancement using Guided Image Filter Technique

Abstract:    In this paper we study and implement image enhancement aspect of guided image filtering. Principle objective of Image enhancement is to process an image so that result is more suitable than original image for specific application. Digital image enhancement techniques provide a multitude of choices for improving the visual quality of images. Guided image filter is an explicit image filter, derived from a local linear model; it generates the filtering output by considering the content of a guidance image, which can be the input image itself or another different image. Moreover, the guided filter has a fast and non-approximate linear-time algorithm, whose computational complexity is independent of the filtering kernel size. This paper will provide an overview of underlying concepts, along with algorithms commonly used for image enhancement.

   Digital Image Processing, Explicit image filter, Guided Image Filtering, Image Enhancement, Kernel.


1.        Bhabatosh Chanda and Dwijest Dutta Majumder, 2002, Digital Image Processing and Analysis.
2.        R.W.Jr. Weeks,(1996). Fundamental of Electronic Image Processing. Bellingham: SPIE Press.

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7.        Xing-fang huang; jiang-she zhang.: Edge-Preserving Filtering for Grey and Color Image. In Proc. of the IEEE / Computer Science and Information Engineering, (2009), vol. 5, pp. 139-143.

8.        R Hummel, “Histogram modification techniques“, Computer Graphics and Image Processing, Vol. 4, pp. 209-224, 1975.

9.        S. E. Umbaugh, “Computer Vision & Image Processing,”Prentice Hall PTR, 1998

10.     Rafael C. Gonzalez and Richard E. Woods. Digital Image Processing. Addison-Wesley Publishing Company, 2010, chapter 4.

11.     Pablo Bauszat, Martin Eisemann and Marcus Magnor.: Guided Image Filtering for Interactive High-quality Global Illumination.  In The Eurographics Association and Blackwell Publishing Ltd.(2011) volume 30 number 4.





Akhilesh Bijalwan, Aditya Goyal, Nidhi Sethi

Paper Title:

Wavelet Transform Based Image Denoise Using Threshold Approaches

Abstract:    This paper deals with the threshold estimation method for image denoising in the wavelet transform domain. The proposed technique is based upon the discrete wavelet transform analysis where the algorithm of wavelet threshold is used to calculate the value of threshold. The proposed method is more efficient and adaptive because the parameter required for calculating the threshold based on sub band data. The threshold value is computed by xσ2w0 /σ where x is the scale parameter which depends upon the sub band size and number of decomposition and σw0 is the noise variance estimation. σ are the wavelet coefficient variance estimation in various sub bands. Experimental results on several test images are compared with popular denoise technique from three aspects (PSNR, RMSE and CoC).

   Wavelet Thresholding, Image Denoising, Discrete Wavelet Transform.


1.        Wavelet domain image de-noising by thresholding and Wiener filtering. Kazubek, M. Signal Processing Letters IEEE, Volume: 10, Issue: 11, Nov. 2003 265 Vol.3.
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3.        S. Grace Chang, Bin Yu and M. Vattereli, Adaptive Wavelet Thresholding for Image Denoising and Compression, IEEE Trans. Image Processing, vol. 9, pp. 1532-1546, Sept. 2000.

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5.        C. Valens. A really friendly guide to wavelets. eBook, 2004. http://perso.wanadoo.fr.

6.        D.L.Donono, I.M.Johnstone. Adaptive to unknown smoothness via wavelet shrinkage [J]. Journal of the American Statistical Association. Vol.90, No.432, pp.1200-1224, 1995.

7.        Chen juan, Chen qian-hui, Shi lu-huan. Edge detection technology in image tracking[J]. Chinese Journal of Optics and Applied Optics. Vol.2. No.1,pp.46-53.february 2009.

8.        Maarten Jansen, Noise Reduction by Wavelet Thresholding, Springer– Verlag New York Inc.- 2001.

9.        D.L. Donoho and I.M. Johnstone, Ideal spatial adaptation via wavelet shrinkage, Biometrica, Vol. 81, pp. 425-455,1994.

10.     D.L. Donoho and I.M. Johnstone, Wavelet shrinkage: Asymptopia?, J.R. Stat. Soc. B, ser. B, Vol. 57, no. 2, pp. 301-369, 1995.

11.     Xu Bao Guo,Wng ji. A new adaptive edge detection algorithm based on mathematic morphology [J].Journal of China Application, Vol.29,No.4,pp.997-1002,April 2009.

12.     Yan-lei Xu, Ji-yin Zhao, Yu-bin Jiao. Gray-scale Image Edge Detection Based on Order Morphology Transformation.  Proceedings of the 7th world Congress on Intelligent
Control and Automation. 5970-5975, June 25 - 27, 2008. (WCICA08)





Ashish Jaiswal , Santhosha Rao, Kumara Shama

Paper Title:

Application Aware Energy Efficient Geographic Greedy Forwarding in Wireless Multimedia Sensor Networks

Abstract:    Finding maximum number of node-disjoint paths for transmission has always been a prime aim to achieve reliability, security, load balancing and improved performance. Finding paths that lead to maximum network lifetime is the other extreme that is desired. Algorithm that aims at one of the requirements tends to oppose the other. In this paper, we propose an Application Aware Energy Efficient Geographic Greedy Forwarding (AAEEGF) routing algorithm for Wireless Multimedia Sensor Networks (WMSNs) that is a trade- off between finding maximum number of node disjoint paths and finding paths with maximum network lifetime. AAEEGF takes into account both the requirements of real time multimedia transmission and the realistic characteristics of WMSNs. It finds list of node-disjoint routing paths with improved lifetime with path delays less than time constraint of the application. AAEEGF supports three features: (1) hole-bypassing, (2) explore maximum number of node disjoint path, and (3) lifetime improvement of paths, at the same time. AAEEGF is a pure geographic greedy forwarding routing algorithm and is an extension to Two-Phase geographic Greedy Forwarding (TPGF) [1]. Exploring paths in AAEEGF is time constraint dependent. All the paths obtained as a result have path delay less than time constraint of application. Unnecessary paths, whose end-to-end delays may exceed time constraint, are not formed, thereby making such nodes to be available for other useful path formation. This point allows more nodes to be available for AAEEGF to explore more routing paths, and enables AAEEGF to be different from many existing geographic routing algorithms like TPGF. AAEEGF improves lifetime of the found paths within the time constraint. Both theoretical analysis and simulation comparison in this paper indicate that AAEEGF is highly suitable for multimedia transmission in WMSNs.

   node-disjoint path,  NetTopo, TPGF, Wireless Mutimedia Sensor Networks


1.       L. Shu, Y. Zhang, L. T. Yang, Y. Wang, N. Xiong, and M., Hauswirth, “TPGF: Geographic Routing in Wireless Multimedia Sensor Networks.” Telecommunication Systems, Nov,2009..
2.       Holman R, Stanley J, O zkan-Haller, “ Applying video sensor networks to near shore environment monitoring”, IEEE Pervasive Computing 2(4):1421, doi:10.1109/MPRV.2003.1251165.

3.       Chu M, Reich J, Zhao, “ Distributed attention in large scale video sensor networks”, In: Proceedings of the second IEE workshop on intelligent distributed surveillance systems, London, UK, , February 2004.

4.       Qin M, Zimmermann, “Maximizing video sensor network lifetime through genetic clustering”, USC Technical Report USC-CS-TR05-84, University of Southern California.

5.       Agathangelou D, Lo BPL, Wang JL, Yang, “Self configuring video-sensor networks”, In: Proceedings of the 3rd international conference on pervasive computing (Pervasive 2005), Munich, Germany, May 2005, pp 2932.

6.       Karp, B.,& Kung, H. T. , “GPSR: Greedy Perimeter Stateless Routing for wireless networks”. In Proceedings of the annual international conference on mobile computing and networking (Mobi-Com 2000), Boston, USA, August. 2000.

7.       Kuhn, F., Wattenhofer, R., & Zollinger, A., “Worst-case optimal and average-case efficient geometric Ad-hoc routing”, In Proceedings of the 4th ACM international symposium on mobile Ad-hoc networking and computing (MobiHoc 2003), Annapolis, MD, USA, June, 2003.

8.       Kuhn, F.,Wattenhofer, R., Zhang, Y., & Zollinger, A, “Geometric ad-hoc routing:  theory and practice”, In Proceedings of the 22nd ACM international symposium on the principles of distributed computing, Boston, Massachusetts, USA, July, 2003.

9.       Leong, B., Mitra, S., & Liskov, B. , “GPath vector face routing: geographic routing with local face information”, In Proceedings of the 13th IEEE international conference on network protocols (ICNP 2005), Boston, Massachusetts, USA, November 69, 2005.

10.     Lei Shu and Chun Wu and Manfred Hauswirth, “NetTopo:Beyond Simulator and Visualizer for Wireless Sensor Networks”, Digital Enterprise Research Institute, Galway, Jul,2008





R.Lokesh Kumar, T.Gopalakrishnan, P.Sengottuvelan

Paper Title:

A Relational Based Fuzzy Clustering To Mine User Profiles for Web Directory Personalization

Abstract:    The log data at a search engine can be used to analyze users’ search behavior and to develop search technologies to improve users’ search experiences. Web usage mining performs mining on web usage data or web logs. A web log is a listing of page reference data/clickstream data. The behavior of the web page readers is imprint in the web server log files.  By using the sequence of pages a user accesses, a user profile could be developed thus used in personalization. With personalization, web access or the contents of web page are modified to better fit the desires of the user and also to identify the browsing behavior of the user can improve system performance, enhance the quality and delivery of Internet Information services to the end user, and identify the population of potential customers. For this purpose a new clustering based approach is used, The proposed algorithm finds the meaningful behavior patterns extracted by applying efficient clustering algorithm, to log data. It is proved that performance of the proposed system is better than that of the existing algorithm. The proposed algorithm can provide popular information from web page visitors for web personalization.

   User profiles, web log data, clustering, Web Personalization.


1.       B. Mobasher, R. Cooley, and J. Srivastava, “Automatic Personalization Based on Web Usage Mining,” Comm. ACM, vol. 43, no. 8, pp. 142-151, 2000.
2.       J. Srivastava, R. Cooley, M. Deshpande, and P.T. Tan, “Web Usage Mining: Discovery and Applications of Usage Patterns from Web Data,” SIGKDD Explorations, vol. 1,
no. 2, pp. 12-23, 2000.

3.       D. Pierrakos, G. Paliouras, C. Papatheodorou, and C.D. Spyropoulos, “Web Usage Mining as a Tool for Personalization: A Survey,” User Modeling and User-Adapted Interaction, vol. 13, no. 4, pp. 311-372, 2003.

4.       G. Paliouras, C. Papatheodorou, V. Karkaletsis, and C.D. Spyropoulos, “Discovering User Communities on the Internet Using Unsupervised Machine Learning Techniques,” Interacting with Computers J., vol. 14, no. 6, pp. 761-791, 2002.

5.       G. Xu, Y. Zhang, and Y. Xun, “Modeling User Behaviour for Web Recommendation Using lda Model,” Proc. IEEE/WIC/ACM Int’l Conf. Web Intelligence and Intelligent Agent Technology, pp. 529-532, 2008.

6.       W. Chu and S.-T.P. Park, “Personalized Recommendation on Dynamic Content Using Predictive Bilinear Models,” Proc. 18th Int’l Conf. World Wide Web (WWW), pp. 691-700, 2009.

7.       A.L.N. Fred and A.K. Jain, “Combining Multiple Clusterings Using Evidence Accumulation,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 27, no. 6, pp. 835-850, June 2005.

8.       S. Monti, P. Tamayo, J.P. Mesirov, and T.R. Golub, “Consensus Clustering: A Resampling-Based Method for Class Discovery and Visualization of Gene Expression Microarray Data,” Machine Learning, vol. 52, nos. 1/2, pp. 91-118, 2003.

9.       N. Iam-On, T. Boongoen, and S. Garrett, “Refining Pairwise Similarity Matrix for Cluster Ensemble Problem with Cluster Relations,” Proc. Int’l Conf. Discovery Science, pp. 222-233, 2008.

10.     T. Boongoen, Q. Shen, and C. Price, “Disclosing False Identity through Hybrid Link Analysis,” Artificial Intelligence and Law, vol. 18, no. 1, pp. 77-102, 2010.

11.     N. Nguyen and R. Caruana, “Consensus Clusterings,” Proc. IEEE Int’l Conf. Data Mining (ICDM), pp. 607-612, 2007.

12.     A.P. Topchy, A.K. Jain, and W.F. Punch, “Clustering Ensembles: Models of Consensus and Weak Partitions,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 27, no. 12, pp. 1866-1881, Dec. 2005.

13.     C. Boulis and M. Ostendorf, “Combining Multiple Clustering Systems,” Proc. European Conf. Principles and Practice of Knowledge Discovery in Databases (PKDD), pp. 63-74, 2004.

14.     B. Fischer and J.M. Buhmann, “Bagging for Path-Based Clustering,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 25, no. 11, pp. 1411-1415, Nov. 2003.

15.     Domeniconi and M. Al-Razgan, “Weighted Cluster Ensembles: Methods and Analysis,” ACM Trans. Knowledge Discovery from Data, vol. 2, no. 4, pp. 1-40, 2009.

16.     Z. Fern and C.E. Brodley, “Solving Cluster Ensemble Problems by Bipartite Graph Partitioning,” Proc. Int’l Conf. Machine Learning (ICML), pp. 36-43, 2004.

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18.     Ayad and M. Kamel, “Finding Natural Clusters Using Multiclusterer Combiner Based on Shared Nearest Neighbors,” Proc. Int’l Workshop Multiple Classifier Systems, pp. 166-175, 2003.

19.     N. Fred and A.K. Jain, “Combining Multiple Clustering Using Evidence Accumulation,” IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 27, no. 6, pp. 835-850, June 2005.

20.     S. Monti, P. Tamayo, J.P. Mesirov, and T.R. Golub, “Consensus Clustering: A Resampling-Based Method for Class Discovery and Visualization of Gene Expression Microarray Data,” Machine Learning, vol. 52, nos. 1/2, pp. 91-118, 2003.

21.     N. Iam-On, T. Boongoen, and S. Garrett, “Refining Pairwise Similarity Matrix for Cluster Ensemble Problem with Cluster Relations,” Proc. Int’l Conf. Discovery Science, pp. 222-233, 2008.

22.     Olfa Nasraoui, Maha Soliman, Esin Saka “A Web Usage Mining Framework for Mining Evolving User Profiles in Dynamic Web Sites” IEEE transactions on knowledge and data engineering, vol. 20, no. 2, February 2008.

23.     Dimitrios Pierrakos, Georgios Paliouras, Personalizing Web Directories with the Aid of Web Usage Data” IEEE transactions on knowledge and data engineering, vol. 22, no. 9, September 2010.

24.     A UCI machine Learning Repository http://archive.ics.uci.edu/ml/datasets.html





Reena Dadhich, Bhavesh Mathur

Paper Title:

Measuring Reliability of an Aspect Oriented Software Using Fuzzy Logic Approach

Abstract:    Aspect Oriented Programming (AOP) refers to the programming approach which isolates secondary and supporting functions from the main program’s business logic.  The application’s modularity increased in that way and its maintenance becomes significantly easier. Apart from the functional requirements while developing any software, we should also consider some non functional requirements like Reliability, Adaptability, and Suitability etc. In this paper an attempt has been made to quantifying the reliability of aspect oriented software using ISO/IEC 9126 Model. Due to the unpredictable nature of software quality attributes, the fuzzy multi criteria approach has been used to evolve the quality of the software.

   Aspect Oriented Programming (AOP), Cross Cutting Concerns, ISO/IEC9126 Model, Reliability


1.        ISO/IEC 9126-1:2001, “Software Engineering-Product Quality—Part 1: Quality Model”, Int’l Organization for Standardization, 2001, Available at www.iso.org
2.        R. Laddad, “Aspect Oriemted Programming will improve Quality”,2003,published by IEEE Computer Society 0740-745

3.        B. W. Boehm, J. R. Brown and M. L. Lipow, “Quantitative Evaluation of Software Quality,” Proceedings of the 2nd International Conference on Software Engineering, San Francisco, CA, USA, October,1976, pp.592-605.

4.        J. A. McCall, P. K. Richards, and G. F. Walters, Factors in Software Quality, 1977, Vol.I, II, and III, US Rome Air Development Center Reports - NTIS AD/A-049 014, NTIS AD/A-049 015 and NTIS AD/A-049 016, U. S. Department of Commerce.

5.        R. G. Dromey, “A model for software product quality,” IEEE Transactions on Software Engineering, Vol.21, No.2, February, 1995, pp.146-162.

6.        P. R. Srivastava and K. Kumar, “An Approach towards Software Quality Assessment,” Communications in Computer and Information Systems Series (CCIS Springer Verlag), Vol.31, No.6, 2009, pp.345-346.

7.        P. R. Srivastava, A. P. Singh, K.V. Vageesh, “Assessment of Software Quality: A Fuzzy Multi – Criteria Approach,” Evolution of Computationand Optimization Algorithms in Software Engineering:Applications and Techniques, IGI Global USA, 2010, chapter - 11, pp.200-219.

8.        A. Sharma, R. Kumar and P.S. Grover, “Estimation of Quality for Software Components - an Empirical Approach,” ACM SIGSOFT Software Engineering Notes, Vol.33, No.5, November, 2008, pp.1-10.

9.        S.A. Slaughter, D. E. Harter, & M. S. Krishnan, “Evaluating the Cost of Software Quality,” Communications of the ACM, Vol.41, No.8, August, 1998, pp.67-73.

10.     M. Agarwal, & K. Chari, “Software Effort, Quality, and Cycle Time: A Study of CMM Level 5 Projects,” IEEE Transactions on Software Engineering, Vol.33, No.3, March, 2007, pp.145-156.

11.     O. Maryoly, M.A. Perez and T. Rojas, “Construction of a Systemic Quality Model for Evaluating Software Product,” Software Quality Journal, Vol.11, No.3, July, 2003, pp.219-242.

12.     O. Lamouchi, A.R. Cherif, and N. Lévy, “A framework based measurements for evaluating an IS quality,” Proceedings of the fifth on Asia-Pacific conference on conceptual modelling, Wollongong, NSW, Australia, January, 2008, pp.39-47.

13.     Y.Kanellopoulos, P.Antonellis, D. Antoniou, C.Makris, E.Theodoridis, C. Tjortjis and N.Tsirakis, “Code Quality Evaluation Methodology Using The Iso/Iec 9126 Standard,” International Journal of Software Engineering & Applications (IJSEA), Vol.1, No.3, July, 2010, pp.17-36.

14.     I.Heitlager, T.Kuipers, J.Visser, “A Practical Model for Measuring Maintainability - a preliminary report,” 6th International Conference on Quality of Information and Communications Technology (QUATIC), September, 2007, pp.30-39.

15.     R. Fitzpatrick and C. Higgins, “Usable Software and its Attributes:A synthesis of Software Quality European Community Law and Human-Computer Interaction”, Proceedings of the HCI'98 Conference, Springer, London, United Kingdom. 1998, pp.1-19.

16.     IEEE Standard Glossary of Software Engineering terminology, IEEE Std 610.12-1990.

17.     Markus Voelter, voelter at acm dot org ,”Aspect oriented Programming in Java”.

18.     Jiantao Pan, “Software Reliability” Carnegie Mellon University, 18-849b ,Dependable Embedded Systems  Spring 1999





Pushpaja V. Saudagare, D. S. Chaudhari

Paper Title:

Human Facial Expression Recognition using Eigen Face and Neural Network

Abstract:    In many face recognition systems the important part is face detection. The task of detecting face is complex due to its variability present across human faces including color, pose, expression, position and orientation. A face detection system based on principal component analysis algorithm and neural network techniques. Facial expression as a natural and efficient way of communication, it can also be considered as a special case of pattern recognition and also many techniques are available. In principal component analysis algorithm, eigenvector and Eigenfaces are identified the initial face image set and these faces are projected onto the Eigenfaces for calculating the weights. These weights created a face database to recognize the face by using neural network. Classification of face detection and token matching can be carried out any neural network for recognizing the facial expression.

   Eigen face, Eigenvector, face recognition, facial expression recognition and neural network


1.        Rheja J. L. and Kumar U., ‘Human Facial Expressio Recognition from Detected in Captured Image Using Back Propagation Neural Network’, International Journal of Computer Science and Information Technology, February 2010.
2.        Agrwal M., Jail N., Kumar M. and Agrawal H., ‘Face Recognition using Eigen Faces and Artificial Neural Network’, International Journal of Computer Theory and Engineering, August 2010

3.        Gonzalez and Woods, Digital Image Processing, Third Edition Pearson Education, 2009

4.        Ren Y., Facial Expression Recognition System, Electrical and Computer Engineering, University of Waterloo, 2008

5.        Paknikar G., Facial Image Based Expression Classification System Using Committee Neural Network, University of Akron, August 2008.

6.        Nagesh-Nilchi A. R. and Roshanzamir M., ‘An Efficient Algorithm for Motion Detection Based Facial Expression Recognition using Optical Flow’, International Journal of Engineering and Applied Science 2006

7.        Mohanad N., Facial Expression Recognition using Back-propagation Network, Unrvisity Teknology MARA, October 2004.

8.        Akalin, Volkan., Face Recognition using Eigenfaces and Neural Network, M.S.,The Department of Electrical and Electronocs Enigineering, December 2003.

9.        Chibelushi C.C. and Bourel F., Facial Expression Recognition: A Brief Tutorial overview, 2002.

10.     Sulistijono I. A., Darojah Z., Dwijotomo A., Pramdihanto D., Facial Expression  Recognition using Backpropagation,200
 11.     Chang J. and Chen J., ‘Automated Facial Expression Recognition System using Neural Networks’, Journal of the Chinese Institute of Engineers, pp. 345-356 (2001).

12.     Feitosa R. Q., Vellasco M. M. B., Facial Expression Classification using RBF and Back Propagation Neural Network,2001

13.     Brimblecombe P, Face Detection using Neural  Network, Meng Electronic  Engineering School of Electronics and Physical Sciences, University of Surrey.

14.     Haykin S., Neural Network: A Comprehensive Foundation, 1999.





Ravi Jon, Charlie Eapen, A.Ashhok, Nishita Sahoo, Anil Kumar

Paper Title:

Performance Analysis of Wireless Power Transfer to the Implantable Drug Delivery System using Helical Antenna with Inductive Coupling

Abstract:    In this paper, we explore the feasibility of wireless power transfer(WPT) to the drug delivery system(DDS) using helical antenna .We investigated the efficiency through different parameters of helical antenna. Helical Antenna (HA) is used here as a primary and secondary coil which works based on the inductive coupling. Through this technology we can reduce the wires or we eliminate the complications and infections caused by the wires. The aim of the system is transfer the power efficiently to the drug delivery system implanted in human body. We studied the inductive coupling and coupling coefficient of the primary and secondary coil and we studied the electrical characteristics of the antenna with equivalent circuit. Inductive power transfer is the most common method of wireless power transfer to the implantable drug delivery system. For good inductive coupling and better efficiency the inductors should have high inductance.

   Wireless power transfer, Helical antenna, Inductive coupling.


1.        Andre Kurs, Aristeidis Karalis, Robert Mofatt, J.D. Joannopoulos, Peter Fisher, Marin Soljacic, “Wireless Power Transfer via Strongly Coupled Magnetic Resonance”, Science Express, 7 June 2007, Vol. 3.17 no.5834,pp.83-86
2.        Takehiro Imura, Hiroyuki Okabe, Yoichi Hori, “Basic Experimental Study on Helical Antennas of Wireless Power Transfer for Electric Vehicles by using Magnetic Resonant Couplings”, Vehicle Power and Propulsion Conference, 2009. IEEE Pages 936-940

3.        Edelman E.R. et al Journal of Biomedical Materials Research 1985, 67-83.

4.        Amer S. & Badawy W. Current Pharmaceutical Biotechnology 2005, 57-64.

5.        R. Puers and G. Vandevoorde, "Recent progress on transcutaneous energy transfer for total artificial heart systems," Artificial Organs, Vol. 25, Issue 5, pp. 400-405, May 2001.

6.        P. Si, A. P. Hu, D. Budgett, S. Malpas, J. Yang and J. Gao, "Stabilizing the operating frequency of a resonant converter for wireless power transfer to implantable biomedical sensors," in Proc. 1st International Conference on Sensing Technology, Palmerston North, New Zealand, 2005.

7.        S. I. Babic, C. Akyel, “Calculating Mutual Inductance Between Circular Coils with Inclined Axes in Air,” IEEE Trans. Magnetics, vol. 44, no. 7, pp. 1745, July 2008 .

8.        P. Si, A. P. HuJ. W. HsuM. Chiang, Y. Wang, S. Malpas, and D. Budgett, “Wireless Power Supply for Implantable Biomedical Device Based on Primary Input Voltage Regulation”.





Sophia Comaneci.J, K.John Peter

Paper Title:

Optimal Denoising Of an Image Using Anscombe Transformation Based Image Stabilization

Abstract:    This paper proposes an effective inversing of the anscombe transformation with the help of adaptive bilateral image denoising algorithm. The Poisson noise removal is carried out into three steps. They are First, Image pre-processin,. Second, image denoising and Third, Image retrieval. In image pre-processing the images of any format can be got as input they are then converted into gray scale images for ease of functions and this paper uses anscombe transform to stabilize the image to a constant intensity level. This is very helpful in determining the noise at low counts. For image denoising, Multiscale variance stabilizing transform is the technique that is proposed to denoise the image. Now the noisy pixels in the images are removed. This paper also proposes a similar neighborhood function that is essential for filling the noisy pixels with the help of non-local means of similar neighbors. This is suitable for overall adjustment of the image. But in the case of texture images this technique is not applicable and in that condition the technique proposed is bilateral transformation of texture images. For this we use Bilateral image denoising and PCA analysis. This paper also proposes an approach to determine the best among the two processes in terms of performance and efficiency. Next step is very crucial because the application of inverse transformation is an critical factor. The inverse transform that is proposed in this paper is minimum mean square error method. This results in retrieval of an image with efficient filtering and inversing functions.

   Anscombe transform, MS-VST, Bilateral denoising, PCA analysis, MMSE


1.       B.Zhang, J.M.Fadili, and J.-L.Starck, “Wavelets, ridgelets, and curvelets for Poisson noise removal,” IEEE Trans. Image Process., vol. 17, no.7, pp.1093–1108, Jul.2008.
2.       S.Lefkimmiatis, P.Maragos, and G.Papandreou, “Bayesian inference on multiscale models for Poisson intensity estimation: Applications top hot on limited image denoising,”IEEE Trans. Image Process., vol.18, no.8, pp.1724–1741, Aug. 2009.

3.       S.Ramani, T.Blu, and M.Unser, “Monte-Carlo SURE: A black- box optimization of regularization parameters for general denoising algorithms,”IEEE Trans. Image Process., vol.17, no.9, pp.1540–1554, Sep.2008.

4.       M.Mäkitaloand A. Foi,“On the inversion of the Anscombe transformation in low count Poisson image denoising,”in Proc.Int. Workshop Local and Non –Local Approx. Image Process, Tuusula, Finland, Aug. 2009, pp.26–32.

5.       K.Dabov, A.Foi, V.Katkovnik, and K. Egiazarian, “Color image denoising via sparse 3D collaborative filtering with grouping constraint in luminance chrominance space,” presented at the IEEE Int. Conf. Image Process., SanAntonio, TX,Sep.  2007.

6.       V.Katkovnik, K.Egiazarian, and J.Astola, “Local Approximation Techniques in Signal and Image Process.”  Bellingham, WA: SPIE, 2006, vol.PM157.

7.       M.Jansen, “Multiscale Poisson data smoothing,” J.Roy Statist.Soc.B, vol. 68, no.1, pp.27–48, 2006.





S. Shiny, Agnes Anto

Paper Title:

Proximal Interpolation in Image Zooming Using Advanced Neighborhood Algorithm

Abstract:    Image zooming, the process of enlarging the image is a direct application of image interpolation procedures. Image interpolation is the process of determining the unknown values of an image at positions lying between some known values. The existing system used the PDE-based curvature interpolation method for image zooming by edge-detection. The proposed work also includes the neighborhood regions. The basic interpolation technique i.e. Proximal or nearest-neighbor interpolation is applied. In this technique, the output pixel is assigned the value of the pixel that the point falls within and no other pixels are considered. This is achieved using the advanced neighborhood algorithm for image zooming. Here the input image can be a grayscale, RGB, or binary image. This algorithm computes each output pixel by taking the value of each input pixel and distributes it to the corresponding output pixel's 3-by-3 neighborhood. The proposed algorithm performs median filtering for the image matrix using the 3-by-3 neighborhood as a smoothing procedure to reduce the artifacts like blurring, jagging and ghosting. The proposed zooming algorithm works with different image types.

  Curvature interpolation method, Edge-detection, Image zooming, Median filtering, Proximal interpolation.


1.     B.Zhang, J.M.Fadili, and J.-L.Starck, “Wavelets, ridgelets, and curvelets for Poisson noise removal,” IEEE Trans. Image Process., vol. 17, no.7, pp.1093–1108, Jul.2008.
2.     S.Lefkimmiatis, P.Maragos, and G.Papandreou, “Bayesian inference on multiscale models for Poisson intensity estimation: Applications top hot on limited image denoising,”IEEE Trans. Image Process., vol.18, no.8, pp.1724–1741, Aug. 2009.

3.     S.Ramani, T.Blu, and M.Unser, “Monte-Carlo SURE: A black- box optimization of regularization parameters for general denoising algorithms,”IEEE Trans. Image Process., vol.17, no.9, pp.1540–1554, Sep.2008.

4.     M.Mäkitaloand A. Foi,“On the inversion of the Anscombe transformation in low count Poisson image denoising,”in Proc.Int. Workshop Local and Non –Local Approx. Image Process, Tuusula, Finland, Aug. 2009, pp.26–32.

5.     K.Dabov, A.Foi, V.Katkovnik, and K. Egiazarian, “Color image denoising via sparse 3D collaborative filtering with grouping constraint in luminance chrominance space,” presented at the IEEE Int. Conf. Image Process., SanAntonio, TX,Sep.  2007.

6.     V.Katkovnik, K.Egiazarian, and J.Astola, “Local Approximation Techniques in Signal and Image Process.”  Bellingham, WA: SPIE, 2006, vol.PM157.

7.     M.Jansen, “Multiscale Poisson data smoothing,” J.Roy Statist.Soc.B, vol. 68, no.1, pp.27–48, 2006.





Varsha Karambelkar, A.A.Shinde

Paper Title:

Testing Digital Signals by Low Cost ARM Based Logic Analyzer

Abstract:    Due to the fast development of electronic devices, the digital circuit designing takes up more and more percentage in total electronic developments thus in the process of debugging and doing validation in a digital system, one of the common task a designer need to do is the acquisition of digital waveforms. The waveforms can be captured  by the device  Logic Analyzer. As digital circuit is too fast to be observed by a human being, the basic idea to capture waveforms at higher speed is to implement the design using ARM controller which internally uses RISC Machine unlike simple processors. ARM based embedded systems, providing a low-cost solution to meet the request of flexibility and testability Logic analyzer is a dedicated application The main objective is to use module as powerful Lab equipment to check and verify the design under test (digital circuit) for design and verification engineers with smaller size and less expensive.

   Logic analyzer, ARM, RISC.


1.        Article Sources and Contributors Logic analyzer Source: http://en.wikipedia.org/w/index.php?oldid=382892919
2.        “Logic Analyzer manual version 1.00” issued by Guangzhou ZHIYUAN electronics  co. Pvt Ltd.   

3.        ”The XYZs of Logic analyzer ”  issued by Tektronix

4.        www.embeddedtools.com

5.        Embedded logic analyzer

6.        Tegra T2, dual core&display, FullHD 12 MPix Camera Interface, Cortex A9

7.        The Design of a Rapid Prototype Platform for ARM Based Embedded System RuiWang and Shiyuan Yang, Senior Member, IEEE

8.        The ARM Architecture Leonid Ryzhyk leonidr@cse.unsw.edu.au June 5, 2006

9.        David Brash, “The ARM Architecture Version”, ARM White Paper, January 2002

10.     Brian W. Kernigan and Dennis M.Ritchie, “The C Programming Language (ANSI)”, Prentice Hall, second edition, 2001

11.     http://www.st.com ,(August 2007)

12.     http://www.arm.com (December 2007) © 2009 ACADEMY PUBLISHER

13.     ARM System Developer‟s Guide Designing and Optimizing System    Software by A. N. Sloss, D. Symes, C. Wright, J. Rayfield, Elsevier 2004.

14.     http://www.cse.unsw.edu.au/~cs9244/06/seminars/08-leonidr.pdf

15.     Kolek K., Turnau A.: Architecture of a High Speed Logic Analyser, Proceedings of the ISMM Intermational Conference MICRO'90, s68-71, Montrela, 1990, Canada

16.     ARM Agilent Debug Interface User Guide

17.     http://www.linkinstruments.com/logic%20analyzer%20software.htm





Vishnu Vardhan

Paper Title:

Formation of Virtual Lenses with the Help of Puissance Radio Telescopic Satellites around the Planets

Abstract:    The technological development of humans has successfully faced all the brutal difficulties it came across. Today’s world has almost nothing which it cannot achieve, yet the thirst for innovation has not decreased. We have the most puissance telescopes located at different parts of the world which can track pretty much information regarding the changes that occur in the celestial bodies in the outer space with in no time, but the changes that occur in them is much faster than the captivity speed of the telescopes . This is the point where we need to throw some light, to build something which is capable of capturing the fastest changes that happen in outer space. This paper deals with launching of radio telescopic satellites in orbits around the planets of our solar system. By launching radio telescopic satellites around some of the worthy planets in our solar system, the view of the multiverse will be improved beyond our imagination. This kind of placement of radio telescopic satellites around the planets will aid in taking a dynamic look at the changes that occur in the outer space and leaves us enough time to be on safe side before the actual disaster happens, more over this arrangement of telescopic satellites will help us to predict the change of path of  celestial object in due course of time and also to track the most distant celestial bodies in the outer space.



1.        "Significant Achievements in Space Communications and Navigation, 1958-1964". NASA-SP-93. NASA. 1966. pp. 30–32. Retrieved 2009-10-31.
2.        F. Ananasso, F. Delli Pricoli, "The Role of Satellites in Personal Communications Services," IEEE Journal on Selected Areas in Communications," V 13, N 2, (February 1995), pp.180-195.

3.        M.H. Hadjitheodosiou, F.P. Coakley and B.G. Evans, "Multiacess Protocols for a Multiservice VSAT Network. Center for Satellite Engineering Research, University of Surrey, Guildford, UK.

4.        A. Guntsch. Analysis of the ATDMA/PRMA++ Protocol in a Mobile Satellite Environment.In Proceedings 46th IEEE Vehicular Technology Conference '96, pp. 1225-1229, Atlanta, U.S.A., April 1996.

5.        Bruce R. Elbert, "Ths Satellite Communication applications handbook",1997 Artech House, Inc, MA.

6.        Elbert, Bruce R, The satellite communication applications handbook, Boston, MA: Artech House, 1997.

7.        Feldman, Phillip M., An overview and comparison of demand assignment multiple access (DAMA) concepts for satellite communications networks Santa Monica, CA: RAND, 1996. Student Project Report, 2000.

8.        Wertz, James R. and Wiley J.Larson, Space Mission Analysis and Design, Microcosm Press, El Segundo CA 1999, pg 533-586. [9] Daniel E. Friedman, Masters Thesis: "Error Control for Satellite and Hybrid Communication Networks", directed by Daniel E. Friedman, 1995

9.        John S. Baras, ATM in Hybrid Networks, Center for Satellite and Hybrid Communication Networks, 1996

10.     Vivek Arora, Narin Suphasindhu, John S. Baras, Douglas Dillon, "Effective Extensions of Internet in Hybrid Satellite-Terrestrial Networks", University of Maryland at College Park & Hughes Network Systems, Inc., 1996

11.     Tom Logsdon, "Mobile Communication Satellites", McGraw Hill Text, February 1995 Dennis Roddy, "Satellite Communications", McGraw Hill Text, 1995m TIA/SCD/CIS - WATM WG Meeting Overview, 3/26/97Satellite Comunications Pelton, Joseph N., "Wireless & Satellite Telecommunications: The Technology, the Market, & the Regulations", Prentice Hall 1995

12.     Cochetti, Roger, "Mobile Satellite Communications Handbook", Quantum Publishing, Incorporated 1995





Chandu Kumari, T. Ravi Sekhar

Paper Title:

SOC Implementation of Soft-Error Tolerance in Asynchronous Burst Mode Circuits

Abstract:    The problem of soft errors in asynchronous burst-mode machines (ABMMs), and we propose the solution is an error tolerance approach, which leverages the inherent functionality of Muller C- elements, along with a variant of duplication, to suppress all transient errors. The proposed method is more robust and less expensive than the typical triple modular  redundancy  error  tolerance  method  and often even less expensive than previously proposed concurrent error detection methods, which only provide detection but no correction The   solution is an error tolerance approach, which leverages the inherent functionality of Muller C-elements, along with a variant of duplication, to suppress all transient errors, which leverages a newly devised soft- error susceptibility assessment method for ABMMs, along with partial duplication, to suppress a carefully chosen subset of transient errors. Progressively more powerful options for partial duplication select among individual gates, complete state/output logic cones or partial state/output logic cones and enable efficient exploration of the tradeoff between the achieved soft- error susceptibility reduction and the incurred area overhead. Furthermore, a gate-decomposition method is developed to leverage the additional soft-error susceptibility reduction opportunities arising during conversion of a two-level ABMM implementation into a multilevel one. Extensive experimental results on benchmark ABMMs assess the effectiveness of the proposed methods reducing soft-error susceptibility, and their impact on area, performance, and offline testability.

   Asynchronous burst-mode circuits, soft errors,soft-error mitigation, soft-error susceptibility, soft-error tolerance.


1.        K. Mohanram and N. A. Touba, “Cost-effective approach for reducing soft error rate in logic circuits,” in IEEE Int. Test onf., 2003, pp.893–901.
2.        M. Nicolaidis, “Design for soft error  mitigation,”IEEE Trans. Device Mater. Rel., vol. 5, no. 3, pp. 405–418, Sep. 2005.

3.        S. Almukhaizim, Y. Makris, Y.-S. Yang, and A. Veneris, “Seamless integration of SER in rewiring- based design space exploration,” in  IEEE Int. Test Conf., 2006, pp. 29.3.1–29.3.9.

4.        Q. Zhou and K. Mohanram, “Gate sizing to radiation harden combinational logic,”  IEEE  Trans.  Comput.-Aided Design  Integr. Circuits Syst.,vol. 25, no. 1, pp. 155–166, Jan. 2006.

5.        ARM Ltd.,“ARM996HS Processor,” Jan. 18, 200 [Online]. Available http://www.handshakesolutions.com/products_services/ARM996HS/Index.htm

6.        W.  Jang  and  A.  Martin,  “SEU-tolerant  QDI circuits,” in Proc. IEEE Int.Symp. Asynchronous Circuits Syst., 2005, pp.156–165

7.        Y. Monnet, M. Renaudin, and R. Leveugle, “Designing resistant circuits against            malicious faults  injection using asynchronous logic,”IEEE Trans. Comput., vol. 55, no. 9, pp. 1104–1115, Sep. 2006.

8.        R. Baumann, “Technology scaling trends and accelerated  testing  for  soft  errors  in  commercial silicon devices,” in Proc. Int. On-Line Testing Symp., Kos Island, Greece, 2003, p. 4.

9.        M. P. Baze and S. P. Buchner, “Attenuation of single event induced pulses in CMOS combinational logic,” IEEE Trans. Nucl. Sci., vol. 44, no. 6, pp.2217–2223, Dec. 1997.

10.     Y. Cao et al., “New paradigm of predictive MOSFET and interconnect modeling for early circuit design,” in Proc. Custom Integrated Circuits Conf., Orlando, FL, 2000, pp. 201–204.





Gagandeep, Aashima, Pawan Kumar

Paper Title:

Analysis of Different Security Attacks in MANETs on Protocol Stack A-Review

Abstract:    A MANET is an infrastructure-less type network, which consists of number of mobile nodes with wireless network interfaces In order to make communication among nodes, the nodes dynamically establish paths among one another. The nature and structure of such networks makes it attractive to various types of attackers. In this paper we discuss various types of attacks on various layers under protocol stack. Different types of attacker attempts different approaches to decrease the network performance, throughput. In this paper the principal focus is on routing and security issues associated with mobile ad hoc networks which are required in order to provide secure communication. On the basis of the nature of attack interaction, the attacks against MANET may be classified into active and passive attacks. Attackers against a network can be classified into two groups: insider and outsider. Whereas an outsider attacker is not a legitimate user of the network, an insider attacker is an authorized node and a part of the routing mechanism on MANETs.



1.        Mohammad Ilyas, “The Handbook of Ad Hoc Wireless Networks”,
2.        Amitabh Mishra, “SECURITY AND QUALITY OF SERVICE IN AD HOC WIRELESS NETWORKS” (chapter 1, 3), ISBN- 13 978-0-521-87824-1 Handbook.

3.        Zubair Muhammad Fadlullah, Tarik Taleb, and Marcus Schöller, “Combating against Security Attacks against Mobile Ad Hoc Networks (MANETs)”.

4.        Vikrant Gokhale, S.K.Gosh, and Arobinda Gupta, “Classification of Attacks on Wireless Mobile Ad Hoc Networks and Vehicular Ad Hoc Networks a Survey”.

5.        Kamanshis Biswas and Md. Liakat Ali, “Security Threats in Mobile Ad Hoc Network”.

6.        Wenjia Li and Anupam Joshi, “Security Issues in Mobile Ad Hoc Networks - A Survey”.

7.        PRADIP M. JAWANDHIYA, MANGESH M. GHONGE “A Survey of Mobile Ad Hoc Network Attacks”. International Journal of Engineering Science and Technology Vol. 2(9), 2010, 4063-4071

8.        K.P. Manikandan, Dr. R .Satyaprasad, Dr. Rajasekhararao. “Analysis and Diminution of Security Attacks on Mobile Ad hoc Network”.IJCA Special Issue on “Mobile Ad-hoc Networks “MANETs, 2010

9.        Kisung Kim and Sehun Kim, “A Sinkhole Detection Method based on Incremental Learning in Wireless Ad Hoc Networks”.

10.     Ad hoc network specific attacks held by Adam Burg.

11.     Akanksha Saini, Harish Kumar, “Effect of Black Hole Attack on AODV Routing Protocol in MANET”.

12.     Sevil ¸ Sen, John A. Clark, and Juan E. Tapiador, “Security Threats in Mobile Ad Hoc Networks”.

13.     Panagiotis Papadimitratos and Zygmunt J. Haas “Securing Mobile Ad Hoc Networks”.

14.     Dan Zhou “Security Issues in Ad Hoc Networks”.

15.     C. Siva Ram Murthy and B. S. Manoj, “Ad Hoc Wireless Networks: Architectures and Protocols”.





Sukhdeep Kaur

Paper Title:

Document Categorization Using Reinforcement Learning

Abstract:    Automatic categorization of documents has become an important research issue since the explosion of digital and online text information. The text information is stored in the form of files and documents and to extract this particular information, a well-defined process is followed. The organization of documents is not so easy task. So there is need to present these documents in a categorized form. A particular text document is categorized, on the basis of high frequency words. So, the main idea is to convert the unstructured documents into structured form. The final goal is to achieve high accuracy in the formation of categories by following particular steps.

   Document Categorization, Data Mining, Pre-processing.


1.        Arzucan augur (2002), “supervised and unsupervised Learning approaches to text   Categorization”.
2.        Debnath Bhattacharya “unstructured document Categorization” , international journal of Information  Science.-30697 Korea.

3.        Dina Goren-Bar and Tsvi Kuflik (2005)“ User subjective categorization using learning vector Organization and self organizinmaps,56(4):345–355, 2005.

4.        Eui-Hong (Sam) Han and George Caryopsis “Centroid based technique for document Classification”. [5] G.S Thakur (2008), “Framework for document Categorization”, International Journal of Information Technology.

5.        Hang lie, kanji Yamanishi (2006), “Document Classification using finite mixture model”.

6.        Heide Britiicher, grehard knolmayer, Marc-Andre Mittermayer (2008) “document classification methods for organizing the explicit knowledge”.

7.        Ken Williams and Rafael A. Calve in 2006, “New Framework for document categorization” , New York, Yorktown Heights, NY 10598, USA.

8.        Manhood soltani, Mohammad taher (2009) “Classification of textual document using learning Vector organization”,978-1-4244-4538-7.

9.        Muhammad Fahad Umer and M.Sikander Hayat (2007) “classification of textual documents by  using learning vector organization”, information Technology journal 6 (1):154-159.

10.     Marcel Rusinol and josep Lead’s (2009) “logo Spotting by Bag-of-words approach for document Categorization”.

11.     Philip S. Yu, Bing Liu Wee Sun Lee, “partially Supervised technique for the Categorization of text Documents”.

12.     Quire Zhang and jinghua (2008), “Research on medical document categorization”,International Journal of Information Technology.

13.     Riel.A, boonyasopon (2009)”Knowledge mining approach to document classification” AIJSTPME (2009) 2(3): 1-10.

14.     S.R.Suresh, T.Karthikeyan, D.B.Shanmugam, J.Dhilipan” Text categorization

15.     Zhihang Chen (2006), “Neural network approaches to text documents categorization” july16-21(2006).





Chhaya Dalela

Paper Title:

Radio Measurements in the WiMAX Band of 2.3 GHz, in Coastal Zone for Different Transmitting Antenna Heights

Abstract:    In this paper, comparison of propagation prediction models for WiMAX at 2.3 GHz for different transmitting antenna height is presented and path loss for different models such as COST-231 Hata model, SUI model, the ECC model, ITU-R(NLOS) model for different transmitting antenna height is computed.  The obtained path losses are graphically plotted for the better conclusion using the MATLAB. The paper studies the path loss models of the wideband channels at 2.3GHz for WiMAX.

   Pathloss; path loss exponent; propagation model; WiMAX, propagation.


1.       Abhayawardhana, V. S., Wassell, I. J., Crosby, D., Sellars and Brown, M. G., “Comparison of Empirical Propagation Path loss Models for Fixed Wireless Access Systems” IEEE conference on Vehicular Technology, Stockholm, Sweden, vol. 1, pp.  73-77 , Jun 2005
2.       Rial, V., Kraus, H., Hauck, J., & Buchholz, M., “Measurements and analysis of aWiMAX field trial at 3.5GHz in an urban environment”  IEEE International Symposium on Broadband, 2007.

3.       Belloul, B., Aragon-Zaval, A., Saunders, S. R.,  “ Measurements and comparison of WiMAX radio coverage at 2.5GHz and 3.5GHz”  EuCAP 2009, 3rd European Conference on Antennas and Propagation, 2009.    

4.       Joe,Hazra,Toh and Shankar, “Path loss measurements in sea port for WiMAX,” WCNC 2007 proceedings, 2007.

5.       COST Action 231, “Digital Mobile Radio. Towards Future generation systems - Final report”, Tech. Report. European Communities, EUR 18957. Ch. 4, 1999.

6.       Electronic Communication Committee (ECC) within the European Conference of Postal and Telecommunications Administration (CEPT), “The analysis of the coexistence of FWA cells in the 3.4 - 3.8 GHz band,”tech. rep., ECC Report 33, May 2003.

7.       V. Erceg, K. V. S. Hari, et al., “Channel models for fixed wireless applications,” IEEE 802.16 Broadband Wireless Access Working Group, January 2001.

8.       Recommendation ITU-R P.1411-1, “Propagation data and prediction methods for the planning of short-range outdoor radio communication systems and radio
local area networks in the frequency range 300 MHz to 100 GHz” tech. rep., International Telecommunication Union, 2001

9.       http://www.twin-antennas.com/omni-antenna.html#2-3ghz-omni-antenna

10.     http://www.bvsystems.com     

11.     Okumura, Y., Ohmori, E., Kawano, T. and Fukuda, K. (1968).  Field strength and its variability in the VHF and UHF land mobile service, Review Electronic Communication Laboratories, 16(9/10), pp. 825–873.

12.     Okumura, Y., Ohmori, E., Kawano, T. and Fukuda, K. (1968).  Field strength and its variability in the VHF and UHF land mobile service, Review Electronic Communication Laboratories, 16(9/10), pp. 825–873.

13.     Ekpenyong, Isabone, Josheph and Elcong, Etim (2010), On Propagation path Loss Models For 3-G Based Wireless networks: A Comparative Analysis, Georgian Electronic Scientific journal: Computer Science and Telecommunications, vol. 2, no. 25.

14.     Chhaya Dalela, M. V. S. N. Prasad, P. K. Dalela,  Rajeev Saraf,  “WiMAX Radio Measurements and Comparison of Propagation Models in Mixed Urban Environments of Western India at 2.3 GHz,” ICEIT National Conference on Advances in Wireless Cellular Telecommunications, 14 -15 Apr 2011, New Delhi, India.





Pradeep Kumar, Rajat Chaudhary, Ambika Aggarwal, Prem Singh, Ravi Tomar

Paper Title:

Improving Medical Image Segmentation Techniques Using Multiphase Level Set Approach Via Bias Correction

Abstract:    In this paper, we present a new variational formulation for geometric active contours that forces the level set function to be close to a signed distance function, and therefore completely eliminates the need of the costly re-initialization procedure. Our variational formulation consists of an internal energy term that penalizes the deviation of the levelset function from a signed distance function, and an external energy term that drives the motion of the zero level set toward the desired image features, such as object boundaries. The resulting evolution of the level set function is the gradient flow that minimizes the overall energy functional.

   image segmentation, level set formulation, Gradient, bias field and MRI


1.        Y. Boykin and V. Kolmogorov. An experimental comparison of min-cut/max-flow algorithms for energy minimization in vision. submitted IEEE Trans. Pattern Anal. and Machine Intel., 2004.
2.        C. Carson,  S. Belongie,  H. Greenspan,  and J. Malik.   Blobworld:   Image segmentation using expectation-maximization and its application to image querying. IEEE Trans. Pattern Anal. and Machine Intell. , 24(8):1026–1038, 2002.

3.        C. M. Christoudias, B. Georgescu, and P. Meer.    Synergism in low level vision.   In 16th Inter-   national Conference on Pattern Recognition., Quebec City, Canada, volume IV, pages 150–155, 2002.

4.        D. Comaniciu and P. Meer.  Mean shift: A robust approach toward feature space analysis. IEEE Trans. Pattern Anal. and Machine Intell., 24:603–619, 2002.

5.        T. Cour, S. Yu, and J. Shi. Normalized cuts matlab code.    Computer and Information Science, Penn State University. Code available at                   http://www.cis.upenn.edu/˜jshi/software/.

6.        F.J. Estrada,  A.D. Jepson,  and C. Chennubhotla.   Spectral embedding and min-cut for image segmentation. In British Machine Vision Conference, 2004.

7.        P.F. Felzenszwalb and D.P. Huttenlocher.  Efficient graph-based image segmentation.     Int. J. of Comp. Vis., 59(2):167–181, 2004.

8.        J. Malik, S. Belongie, T. Leung, and J. Shi. Contour and texture analysis for image segmentation. Int. J. of Computer Vision , 43(1):7–27, 2001.

9.        D.  Martin   and   C.  Fowlkes.      The   Berkeley   Segmentation   DatasetandBenchmark. http://www.cs.berkeley.edu/projects/vision/grouping/segbench/.

10.     D. Martin, C. Fowlkes, and J. Malik.   Learning to detect natural image boundaries using local   brightness, color, and texture cues.  IEEE Trans. Pattern Anal. and Machine Intell. , 26(5):530–  549, 2004.

11.     D. Martin, C. Fowlkes, D. Tal, and J. Malik.    A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics. In  Proc. 8th Int’l Conf. Computer Vision, volume 2, pages 416–423, July 2001.

12.     J. Shi, C. Fowlkes, D. Martin, and E. Sharon.  Graph based image segmentation tutorial. CVPR 2004. http://www.cis.upenn.edu/˜jshi/GraphTutorial/.





Manoj. B, Manjula N Harihar

Paper Title:

Image Encryption and Decryption using AES

Abstract:    In today’s world most of the communication is done using electronic media. Data Security is widely used to ensure security in communication, data storage and transmission. We have Advanced Encryption Standard (AES) which is accepted as a symmetric cryptography standard for transferring block of data securely. The available AES algorithm is used for text data and it is also suitable for image encryption and decryption to protect the confidential image data from an unauthorized access. This project proposes a method in which the image data is an input to AES Encryption to obtain the encrypted image, and the encrypted image is the input to AES Decryption to get the original image. In this paper, we implement the 128 bit AES for image encryption and decryption which is synthesized and simulated on FPGA family of Spartan-6 (XC6SLX25) using Xilinx ISE 12.4 tool in Very high speed integrated circuit Hardware Description Language (VHDL) and shall be verified with the help of its simulation result.

   Cryptography, AES, Image Encryption, Decryption, FPGA, S-box, Cipher Text, NIST, FIPS.


1.        National Institute of Standards and Technology, “Federal Information Processing Standard Publication 197, the Advanced Encryption Standard (AES),” Nov. 2001.
2.        William Stalling, Cryptography and Network Security: Principles and Practices, Principles and Practices, 4th ed. Prentice Hall, 2006.

3.        Charles H Roth, Jr. Digital Systems Design Using VHDL, Thomson, India Edition 2007.

4.        Atul Kahate, Cryptography and Network Security, Second Edition, Tata McGraw-Hill Edition 2008.

5.        Abdulkarim Amer Shtewi, Bahaa Eldin M. Hasan,  Abd El Fatah .A. Hegazy “An Efficient Modified Advanced Encryption Standard (MAES) Adapted for Image Cryptosystems” IJCSNS International Journal of Computer Science and Network Security, VOL.10 No.2,pp.226-232 February 2010.

6.        P.Karthigaikumar, Soumiya Rasheed “Simulation of Image Encryption using AES Algorithm” IJCA Special Issue on “Computational Science - New Dimensions & Perspectives” NCCSE, pp166-172, 2011.

7.        Mr. Atul M. Borkar, Dr. R. V. Kshirsagar, Mrs. M. V. Vyawahare “FPGA Implementation of AES Algorithm” IEEE, pp.401-405, 2011.

8.        Xinmiao Zhang,  Keshab K. Parhi, Fellow, “High-Speed VLSI Architectures for the AES Algorithm” IEEE Transactions on vlsi systems, vol. 12, no. 9, pp.957-966, September 2004.





Raghuwar Sharan Soni, Deepak Asati

Paper Title:

Development of Embedded Web Server Configured on FPGA Using Soft-core Processor and Web Client on PC

Abstract:    A soft processor is an Intellectual Property (IP) core that is implemented using the logic primitives of the FPGA. Key benefits of having a soft FPGA-based processing system are re programmability and re-configurability. There are various soft-core processors provided by different vendors such as Microblaze (Xilinx), NiosII (Altera), OpenRISC (developed by OpenCores) etc. Microblaze processor is one of those soft-core processor developed by Xilinx which models specific processor using HDL and can be customized (and synthesized) for any application. The Microblaze soft processor is a soft 32-bit RISC processor. FPGA with soft core processor has wide variety of applications mainly in automobiles, medical field, entertainment electronics and industrial control system.  In this project, a  soft processor (Microblaze) based embedded system is developed with RS-232 serial interface, Ethernet interface, 32MB SDRAM,  4MB PROM (platform flash), 16x2 LCD interface,  8 digital inputs and 8 digital outputs. The embedded systems is connected to the internet and remotely controlled and monitored. The TCP/IP stack is ported on Microblaze and Embedded Webserver is developed on FPGA board using HTTP communication protocol. A Web browser based interface (client) is developed in VB.NET (with HTML and AJAX Controls) on Personal Computer (PC) to communicate with the FPGA board using HTTP through TCP/IP protocol. Ethernet connectivity is tested between Embedded Web server on Microblaze and Web client on PC. Messages sent from the client side can be displayed over LCD on Webserver. Client can send commands to board for controlling IO’s, for reading from RAM and for writing on RAM. Status check command sent by the client computer to Webserver updates the browser on PC to show status of IO’s.  It can also be used as slave processor to provide Ethernet connectivity to any 8- bit, 16-bit and 32- bit processors. TFTP server is also deployed in the Embedded Webserver Card so as to provide file transfer access to/from the client (Computer / Other Processor)

   Embedded Webserver, Ethernet, FPGA, Intellectual Property (IP), Microblaze, Soft-core Processor and TFTP Server.


1.        Bryan H. Fletcher, “FPGA Embedded Processor Revealing True System Performance”, Embedded Training Program, Embedded Systems Conference and San Francisco, ETP-367, 2005.
2.        “Getting Started with Embedded System Development using MicroBlaze processor & Spartan-3A FPGAs”, www.xilinx.com.

3.        Franjo Plavec, Blair Fort, Zvonko G. Vranesic, Stephen D. Brown “Experiences with Soft-Core Processor Design”,19th IEEE International Parallel and Distributed Processing Symposium (IPDPS’05)

4.        Petar Borisov Minev (Technical University of Gabrovo) and Valentina Stoianova Kukenska (Technical University of Gabrovo) “Implementation Of Soft-Core Processors In Fpgas”,  In “International Scientific Conference” 23 – 24 November 2007, Gabrovo

5.        Stephen MacMahon, Nan Zang, Anirudha Sarangi “LightWeight IP (lwIP) Application Examples”, XAPP 1026 (V3.1) , April 21, 2011





Amit Gupta, Sudeep Baudha, Brajesh Mishra

Paper Title:

RFID (NFC) Antenna Design for Dedicated Mobile Applications at 88 MHz Frequency

Abstract:    Near field communication (NFC) is a set of standards for smart phones and similar devices to establish radio communication with each other by touching them together or bringing them into close proximity, usually no more than a few centimeters. Present and anticipated applications include contactless transactions, data exchange, and simplified setup of more complex communications such as Wi-Fi Communication is also possible between an NFC device and an unpowered NFC chip, called a "tag"  Later part of paper discuss about the RFID antenna which is tuned on 88 MHz frequency, this frequency is not yet allotted for any mobile application, so if allotted on such frequency the communication might become revolutionary. New designs with new results and all other parameters to describe the antenna design in detail.

   Wi-Fi Communication is also possible between an NFC device and an unpowered NFC chip, called a "tag"   


1.     Near Field Communication-White paper, ECMA International, Jan. 2004.
2.     International standard ISO/IEC 18092, International Standardization Organization, April 2004.

3.     Standard ECMA-340, “Near Field Communication - Interface and Protocol (NFCIP-1)”, ECMA International, December 2002.

4.     Standard ECMA-352, “Near Field Communication Interface and Protocol -2 (NFCIP-2)”, ECMA International, December 2003.

5.     Short Form Specification, “Near Field Communication PN531- μC based Transmission module”, Philips Semiconductors, February 2004.

6.     David M. Pozar, Microwave Engineering 3rd ed, Publishing House of Electronics Industry , pp. 223-235, September 2006.

7.     Antenna Theory and Design by Balanis, 3rd edition. antum Publishing, Incorporated 1995





Priti Trivedi, Sudeep Baudha

Paper Title:

Development, Integration and Verification of VHDL code for FPGA based Beam Position Measurement Board

Abstract:    Continuous increase in FPGA capacity, architectural features and performance, along with decrease in cost, results in an ideal solution to hardware system designers. The embedded designer who is serious about increasing performance must consider the FPGAs ability to accelerate the processor performance with dedicated hardware. Although this technique consumes FPGA resources, the performance improvements can be extraordinary. Thus FPGA based VME Bus compatible four channels ADC card is used to acquire the Beam Position Indicator (BPI) electrode data, and calculate the beam position using an intelligence device (FPGA) on board. This card is having on-board 4-channel ADC (with signal conditioning electronics) and 8-channel Opto-coupler inputs. Additionally there is a memory available on-board to save calculated beam position. In all, the system is VME based so this card is a VME slave board where VME CPU card will be able to control the card and read the calculated beam position whenever it is available in memory.

   FPGA, VME, 4-channel ADC, e-beam position and BPI.


1.       John Rynearson, “VME bus [Basic description of the world's]”.
2.       Russell Tessier, Member, IEEE, Vaughn Betz, Member, IEEE, David Neto, Aaron Egier, Member, IEEE, and Thiagaraja Gopalsamy “Power-Efficient RAM Mapping Algorithms for FPGA Embedded Memory Blocks” IEEE Transactions on Computer-Aided Design of Circuits and Systems, 2006.

3.       Dominique Breton1, Eric Delagnes and Michael Houry “Very High Dynamic Range and High Sampling Rate VME Digitizing Boards for Physics Experiments” published in "IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC - 2004).

4.       Nasri Sulaiman, Zeyad Assi Obaid, M. H. Marhaban and M. N. Hamidon, “Design and Implementation of FPGA-Based Systems” Australian Journal of Basic and Applied Sciences, 3(4): 3575-3596, 2009ISSN 1991-8178 © 2009, INSInet Publication

5.       J. Bhasker, “A VHDL Primer (3rd Edition)”, Prentice Hall India Publisher, 1999.

6.       Sun JiangFeng Chen Feng, “The IP Soft Core Design of ADC and PLd Verification”, Proceedings of the Third International Symposium on Electronic Commerce and Security Workshops(ISECS ’10) Guangzhou, P. R. China, 29-31,July 2010, pp. 014-017





Chitra M, Roopa M

Paper Title:

A High Performance Binary Data Compression Technique Using Low Puncturing Turbo Codes

Abstract:    In this paper, we present a distributed coding technique for binary data compression. The performance of the proposed architecture is higher when compared with the existing techniques. The complexity of the traditional encoder is distributed to the decoder. Thus the proposed architecture can be used for the applications where the complexity of decoder can be more than that of an encoder.

  Distributed coding, Binary compression, side information, encoder.


1.        J. D. Slepian and J. K. Wolf, “Noiseless coding of correlated information sources,” IEEE Transactions on Information Theory, vol.    IT-19, pp. 471–480, July 1973.
2.        A. D. Wyner, “Recent Results in the Shannon Theory,” IEEE Transactions on Information Theory, vol. 20, no. 1, pp. 2–10, Jan.      1974.

3.        S. S. Pradhan and K. Ramchandran, “Distributed source coding using syndromes (DISCUS): Design and construction,” in Proc. IEEE Data Compression Conference, Snowbird, UT, Mar. 1999, pp. 158 –167.

4.        “Distributed source coding: Symmetric rates and applications to sensor networks,” in Proc. IEEE Data Compression Conference, Snowbird, UT, Mar. 2000, pp. 363 –372.

5.        “Group-theoretic construction and analysis of generalized coset codes for symmetric/asymmetric distributed source coding,” in Proc.Conference on Information Sciences and Systems, Princeton, NJ, Mar.2000.

6.        “Geometric proof of rate-distortion function of Gaussian sources with side information at the decoder,” in Proc. IEEE International Symposium on Information Theory (ISIT), Sorrento, Italy, June 2000, p. 351.

7.        S. S. Pradhan, J. Kusuma, and K. Ramchandran, “Distributed compression in a dense microsensor network,” IEEE Signal Processing Magazine, vol. 19, no. 2, pp. 51–60, Mar. 2002.

8.        X. Wang and M. Orchard, “Design of trellis codes for source coding with side information at the decoder,” in Proc. IEEE Data Compression Conference, Snowbird, UT, Mar. 2001, pp. 361–370.





Parvez Mahmud, Shahjadi Hisan Farjana

Paper Title:

Design and Construction of Refrigerant Charge Level Detecting Device in HVAC/R System with Microcontroller

Abstract:    A charge level detecting device in residential and light commercial heating, ventilation, and air-conditioning (HVAC) systems and in refrigeration systems is used to detect the sufficiency of refrigerant or charge level whether it is proper or not. The most common problems affecting residential and commercial HVAC/R systems are slow refrigerant leaks, improper refrigerant charge and charging device. The usual methods for charge level detection are sight glass method and system high side and low side pressure measurement method. The limitation of sight glass method is it works only if a predictable amount of refrigerant remains in one part of system or constant flow of refrigerant is maintained throughout the system. Pressure of any HVAC/R system cannot be measured in a running system, and charge leaks occur in case of pressure method. Refrigerant charge level detecting device employs a method of determining if the refrigerant charge is within an acceptable range, including the steps of measuring the superheat and subcool temperatures at compressor inlet and condenser outlet. Actual superheat and actual subcooling values are calculated and these values are thus compared with target superheat and target subcool values in microcontroller device, thus obtained from manufacturers chart for particular type of refrigerant, which values depends on outdoor dry bulb temperature and indoor wet bulb temperature on system operating situation and shows the charge status result. The refrigerant charge indicator is based on the fact that when refrigerant starts to leak, the evaporator coil temperature starts to drop and the level of liquid sub cooling drops. An over charge in this system results in compressor flooding, damaging to the motor and mechanical components. Inadequate refrigerant charge can lead to increased power consumption, thus reducing system capacity and efficiency.

   Superheat, subcooling, refrigerant charge level, microcontroller.


1.        American Society of Heating, Refrigeration and Air conditioning Engineers  (ASHRAE), www.ashrae.org.
2.        Bureau of Energy Efficiency, Ministry of Power, India. HVAC and Refrigeration Systems. In:  Energy Efficiency in Electrical Utilities, chapter 4. 2004.

3.        Stocker.F.W “Refrigeration and Air conditioning”, The Good heart –Wilcox Company, inc.1968.

4.        Khurmi.S.R, “Refrigeration and Air Conditioning”, McGraw- ill Book Company, International Edition.

5.        Arora.C.P,”Refrigeration and Air conditioning”, McGraw –Hill Book Company, Delhi,2nd edition, 2002.                                                                 

6.        Ballaney.L.P, “Refrigeration & Air Conditioning”, Khanna Publishers, Delhi, 3rdedition. 2002.

7.        www.fluke.com

8.        www.energybooks.com/pdf/342346.pdf

9.        www.answers.com/topic/refrigerant-charge-1

10.     www.ftc.gov/os/comments/energylabeling/519870-00003.pdf

11.     en.wikipedia.org/wiki/Air_conditioning

12.     Jan Axelson, The Microcontroller Idea Book Circuits, Programs, & Applications featuring the 8052-BASIC Microcontroller, Lakeview Research,2209 Winnebago St.,Madison, WI 53704,USA Phone: 608-241-5824.

13.     Prof. Prabhat Ranjan(prabhat_ranjan@da-iict.org), DA-IICT,Gandhinagar,Programming Atmel AVR series Microcontroller.

14.     Bibin John, My Experience In Programming Avr Microcontroller Using  WINAVR/AVRGCC.

15.     www.davidwinscoe.com/Programming in BASCOM-AVR.

16.     Braun II; Robert J,” Refrigerant charge Adequacy gauge”,US7712319, May11,2010.

17.     Bush; James W,” Refrigerant charge storage”, US20100050668,March 4,2010.

18.     Concha,et al ,” Detection of refrigerant charge adequacy based on multiple temperature measurements”, 7386985,June 17,2008.

19.     Galante,et al ,” Dual thermochromic liquid crystal temperature sensing for refrigerant charge indication”, 7552596,June 30,2009.

20.     Kang,et al.,” Refrigerant charge status indication method and device”, 7610765, November3,2009

21.     Schuster,Don A,” Method for determining refrigerant charge”, US20100088046,April 8,2010.





M. A. Parvez Mahmud, Shahjadi Hisan Farjana

Paper Title:

Wind Power Technology Schemes as Renewable Energy in Bangladesh

Abstract:    Wind energy is one of the renewable means of electricity generation that is a part of the worldwide discussion on the future of energy generation and use. Usage of wind energy has been increased in recent times especially because it is a running demand to use alternative energy sources and reduce fossil fuels consumption. This paper presents the schemes to use this technology in Bangladesh because it has a 724 km long coastline and many small islands in the Bay of Bengal, where strong southwesterly wind and sea breeze blow in the summer season and there is gentle northeasterly wind and breeze in winter months. It could produce 2,000 MW of power in the coastal belt installing 30 windmills per square km. The windmills that can be installed in the coastal belts can sustain 250 km per hour cyclonic storm. The scope of setting large scale power plant in coastal areas will be discussed in this paper.

   Wind Power, Renewable Energy, Wind Turbines, Pressure Difference, Alternative Energy Sources, Cost Analysis, Wind Farm


1.        Power Plant Engineering - G.R.Nagpal
2.        “Wind renewable energy - Wind energy-How Wind Power Works” http://www.solarpowernotes.com

3.        “Wind Turbines Principle” http://www.solarnavigator.net

4.        “Wind & Water Power Program” http://www1.eere.energy.gov/windandhydro/hydro_technologies.html

5.        “Wind Turbine Cost” http://www.windustry.org

6.        “Electricity Generation Using Small Wind Turbines” - http://www.omafra.gov.on.ca

7.        “Wind power”- http://en.wikipedia.org

8.        Mohammad Golam Kibria Khan, Talha Rahman and M.M. Alam “Wind energy in bangladesh: prospects and utilization Initiatives”. pp 474-477,ICECE 2004, 28-30 December 2004, Dhaka, Bangladesh.

9.        “Condition of Wind Energy in Bangladesh” http://people.com.cn

10.     Wind Battery Hybrid Power plant- Energy Bangla, Bangladesh.





Pooja Kannadas, S.Joshua Daniel

Paper Title:

Energy Efficient Conflict Free Query Scheduling For Wireless Sensor Networks

Abstract:    There is an increase in demand of high performance query services, with the emergence of high data rate applications. To meet this challenge we propose Dynamic Conflict-free Query Scheduling (DCQS), a novel scheduling technique for queries in wireless sensor networks. In contrast to earlier Time Division Multiple Access (TDMA) designed for query services in wireless sensor networks. DCQS has several unique features. First, it optimizes the query performance through conflict-free transmission scheduling based on the temporal properties of queries in wireless sensor networks. Second, it can adapt to workload changes without explicitly reconstructing the transmission schedule. Furthermore, DCQS also provides predictable performance in terms of the maximum achievable query rate. The nodes operate over the time-varying wireless channel whose quality significantly fluctuates over time due to fading and interference. Such time-varying nature of wireless channel imposes many constraints in designing an energy-efficient transmission scheme. In this work, we derive a tight bound on the maximum query rate achieved under DCQS. Such a bound is of practical importance since it can be used to prevent network overload. NS2 simulations demonstrate that energy efficient DCQS significantly outperforms 802.11 in terms of energy efficiency, over head, query latency, and throughput, thereby increasing the network life time.



1.        T.F. Abdelzaher, S. Prabh, and R. Kiran, “On Real-Time Capacity Limits of Multihop Wireless Sensor Networks,” Proc.25th IEEE  Int’l Real-Time Systems Symp. (RTSS). (2004),
2.        S.R. Madden, M.J. Franklin, J.M. Hellerstein, and W. Hong, “Tiny DB: An Acquisitional Query Processing System for Sensor Networks,” ACM  Trans. Database Systems, vol. 30, no. 1, pp. 122-173, (2005).

3.        A. Mainwaring, D. Culler, J. Polastre, R. Szewczyk, and J. Anderson, “Wireless Sensor Networks for Habitat Monitoring,” Proc. First ACM   Int’l Workshop Wireless Sensor Networks and Applications (WSNA), (2002).

4.        R. Maheshwari, J. Cao, and S.R. Das, “Physical Interference Modeling for Transmission Scheduling on Commodity WiFi Hardware,” Proc. IEEE INFOCOM, (2009).

5.        L. Krishnamurthy, R. Adler, P. Buonadonna, J. Chhabra, M. Flanigan, N. Kushalnagar, L. Nachman, and M. Yarvis, “Design and Deployment of Industrial Sensor Networks: Experiences from a Semiconductor Plant and the North Sea,” Proc. Third Int’l Conf. Embedded Networked Sensor  Systems (SenSys), (2005).

6.        R. Maheshwari, J. Cao, and S.R. Das, “Physical Interference Modeling for Transmission Scheduling on Commodity WiFi Hardware,” Proc. IEEE INFOCOM, (2009).

7.        V. Rajendran, K. Obraczka, and J.J. Garcia-Luna-Aceves, “Energy-Efficient Collision-Free Medium Access Control for Wireless Sensor  Networks,” Proc. First Int’l Conf. Embedded Networked Sensor Systems (SenSys), (2003)





K. P. Shashikala, K. B. Raja

Paper Title:

Palmprint Identification Based On DWT, DCT And QPCA 

Abstract:    An individual can be identified effectively using palmprints. In this paper we propose palmprint identification based on DWT, DCT and QPCA (PIDDQ). Histogram equalization is used on palmprint to enhance contrast of an image. The DWT is applied on Histogram equalized image to generate LL, LH, HL and HH bands. The LL band is converted into DCT coefficients using DCT. QPCA is applied on DCT coefficients to generate features. The test and database palmprint features are compared using Euclidean Distance (ED). It is observed that the proposed method gives better performance compared to existing method.

   Palmprint Identification, DWT, DCT, QPCA, ED.


1.     Vieira V S and Salomao J M, “Use of Wavelet Transforms and Neural Networks for Identifying Individuals through Extracted Features of the Palm Hand.”  International Conference on Bio-signals and Bio-robotics Conference, pp 1 – 5, 2011 
2.     Zhenhua Guo, Lei Zhang and David Zhang, “Feature Band Selection for Multispectral Palmprint Recognition.”International Conference on Pattern Recognition, pp 1136-1139, 2010

3.     Jifeng Dai and Jie Zhou, “Multifeature Based High Resolution Palmprint Recognition.” IEEE Transactions on pattern analysis and Machine Intelligence, Vol. 33, No 5, pp 945-957, May 2011

4.     Naidu, Chemudu Satish, Vaddi Seshu Satyanarayana, Pillem Ramesh kumar, Naresh Hanuma Bhuma and C H Himabindu, “New Palm print Authentication System by Using Wavelet Based Method.”  International Journal on Signal & Image Processing Vol.2, No.1, pp 191-203, March 2011

5.     Abdallah Meraoumia , Salim Chitroub and Ahmed Bouridane, “Fusion of Multispectral Palmprint Images For Automatic Person Identification.” International Conference on Electronics Communications and Photonics, PP 1-6, 2011

6.     Murat Aykut and Murat Ekinci, “An Application of Gabor Based Kernel Fisher Discriminants to the Online Palmprint Verification System.”Nineteenth IEEE Conference on Signal Processing and Communications Applications, pp 303-306, 2011

7.     Tunkpien P, Phimoltares S and Panthuwadeethorn S, “Palmprint identification system using shape matching and K Nearest neighbor algorithm.” IEEE International Conference on Imaging Systems and Techniques, pp 327-330, 2011

8.     Ningbo Zhu, Fu Yu and Qinglong Tian, “Combining Feature Level and Matching Score Level Fusion Strategies for Multi-Biometrics.” International Conference on Remote Sensing, Environment and Transportation Engineering, PP 3930 – 3933, 2011

9.     Yong Jian Chin, Thian Song Ong, Teoh A B J and Goh M K O, “Multimodal Biometrics Based Bit Extraction Method for Template Security.” Sixth IEEE Conference on Industrial Electronics and Applications, pp 1971 – 1976, 2011 

10.  Xingpeng Xu and Zhenhua Guo, “Multispectral Palmprint Recognition Using Quaternion Principal Component Analysis.” International Workshop on Emerging Techniques and Challenges for Hand-Based Biometrics, pp 1-5,  2010

11.  Lu Leng, Jiashu Zhang, Muhammad Khurram Khan, Xi Chen, Ming Ji and  Khaled Alghathbar, “Cancelable PalmCode Generated From Randomized Gabor Filters For Palmprint Template Protection.” Scientific Research and Essays Vol. 6(4), pp 784-792,  2011

12.  Liu Yu-qin, Yuan Wei-qi and Guo Jin-yu, “Analysis of Relationship between Size of Image Resolution and Recognition Performance. ” International Conference on Electric Information and Control Engineering, PP 3991 – 3994, 2011

13.  Zohaib Khan, AjmalMian and Yiqun Hu, “Contour Code: Robust and Efficient Multispectral Palmprint Encoding for Human Recognition.” International Conference on Computer Vision, pp 1935-1942,  2011

14.  Vivek Kanhangad, Ajay Kumar and David Zhang   ,“Contactless and Pose Invariant Biometric Identification Using Hand Surface.” IEEE Transactions on Image Processing, Vol. 20, No. 5, pp 1415-1424, May 2011

15.  Trabelsi R B, Kallel I K, Imasmoudi D S, “Multimodal Biometric System Based Palmprint and Iris.”8th International Multi-Conference on Systems, Signals and
Devices, pp 1 – 5, 2011

16.  Meraoumia A Chitroub and S Bouridane A, “Fusion of Finger-Knuckle-Print and Palmprint for an Efficient Multi-Biometric System of Person Recognition.” IEEE International Conference on Communications, pp 1 – 5, 2011

17.  Yanqiang Zhang, Dongmei Sun and Zheng ding    Qiu, “Hand-Based Feature Level Fusion for Single Sample Biometrics Recognition”. Emerging Techniques and Challenges for Hand-Based Biometrics, Istanbul, pp 1 - 4, August 2010

18.  Jie Wu, Zhengding Qiu, “A Hierarchical Palmprint Identification Method Using Hand Geometry and Grayscale Distribution Features.” Eighteenth IEEE International Conference on Pattern Recognition Vol. 00, Issue c, pp 409-412, 2006,

19.  Yanqiang Zhang Zhengding Qiu and   Dongmei Sun, “Experimental Evaluation of Different Intensity Distributions for Palmprint Identification.” International Conference on Information Security and Assurance,   pp 102 – 105, 2008,

20.  Xiang-Qian Wu, Kuan-Quan Wang, David Zhang, “Fusion of Multiple Features for Palmprint Authentication”. Proceedings of the Fifth International Conference on Machine Learning and Cybernetics, pp 3260-326, August 2006

21.  ShuangXu, JidongSuo, JiYin Zhao and Jifeng Ding, “A Bi-Directional Compressed 2DPCA for Palmprint recognition based on Gabor wavelets”. Sixth International Conference on Natural Computation, pp-958-961, 2010

22.  Runbin Cai and Dewen Hu, “Image fusion of palmprint and palm vein: Multispectral palm image fusion.” IEEE International Congress on Image and Signal Processing, Vol. 6, pp 2778 – 2781, Oct 2010

23.  K B Nagasundara and D S Guru, “ Multi Algorithm based Feature Palmprint Indexing” International Journal of Computer Applications,  pp 7-12,  2012,

24.  Ashutosh Kumar and Ranjan Parekh, “Palmprint Recognition in Eigen Space” International Journal of  Computer Science and Engineering, Vol 4, pp 788-794, 2012

25.  Xiang Peng Xu,Zhenhua Guo, Chang Jiang Song and Yafeng LI,“Multispectral Palmprint Recognition using Quaternion Matrix” Sensors , Vol 12, pp 4633-4647,2012

26.  K.Vaidehi,T S Subhashini,V Ramalingam,S Palanivel and M Kalaimamani, “Transform based Approaches for Palmprint Identification” International Journal of Computer Applications, Vol  41,PP1-5, 2012

27.  Linlin Shen, Shipei Wu, Songhao Zheng and ZhenJi, “ Embedded palmprint recognition system using OMAP 3530” Sensors, Vol. 12 (2), PP 1482-1493, 2012.





Priyanka Pitale, Asha Ambhaikar

Paper Title:

Sensitive Region Prediction using Data Mining Technique

Abstract:    Surveys provide huge amounts of healthcare data which, unfortunately, are not used to discover hidden information for effective decision making. Discovery of hidden patterns and relationships can provide a powerful prediction technique for predicting regions which are sensitive for several diseases. Advanced data mining techniques can help to predict future number of cases of a disease. This research has developed a prototype, Sensitive Region Prediction System (SRPS), using data mining technique, called Linear Regression. Using historical data from various sources such as regional surveys and health reports, it can predict the number of cases of malaria disease. SRPS is user-friendly, platform independent, scalable, portable and expandable. It is implemented on the Java platform.

   Decision Making, Hidden Patterns, Java, Linear Regression, SRPS


1.       http://www.who.int
2.       www.cs.waikato.ac.nz/ml/weka/arff.html

3.       http://www.cs.waikato.ac.nz/

4.       http://www.cs.waikato.ac.nz/~ml/weka/

5.       www.java.com/en/about/

6.       www.jfree.org/jfreechart/

7.       Takashi Kimoto, Kazuo Asakawa ,Morio Yoda and Masakazu Takeoka, “Stock Market Prediction System with Modular Neural Networks ”,1990,  IJCNN International Joint Conference on Neural Networks, Vol-1, San Diego, CA , USA  pp. 1-6.

8.       Sayan Mukherjee ,Edgar Osuna,Federico Girosi,  “Nonlinear Prediction of Chaotic Time Series Using Support Vector Machine ” , Proceeding of IEEE NNSP'97, Amelia Island, FL, 24-26 Sep., 1997

9.       Jaehyun Sim , Seung-Yeon Kim  and Julian Lee, “Prediction of protein solvent accessibility using fuzzy k -nearest neighbor method ”, Oxford Journals ,Vol. 21 no. 12 2005, pages 2844–2849 .

10.     Kari Laasonen, “Prediction of Mobile User Routes from Cellular Data”, 9th European Conference on Principles and Practice of Knowledge Discovery in Databases, Porto, Portugal, October 3-7, 2005. Proceedings, Springer Berlin / Heidelberg, Monday, November 07, 2005 ,pp-569-576.

11.     Steven Rovnyak , Stein Kretsinger ,  James Thorp , Donald Brown , “Decision Trees For Real-Time Transient Stability Prediction ” , IEEE Transactions on Power Systems, Vol. 9, No. 3. August 1994 , pp-1417-1426.

12.     Kiryung Lee, Dong Sik Kim,  Taejeong Kim,  “Regression-based prediction for blocking artifact reduction in JPEG-compressed images ”, IEEE Transactions on Image Processing, Electron. & Telecommun. Res. Inst., Daejeon, South Korea,14  Issue: 1,pp-36 - 48 .

13.     Hongyu Sun, Henry X Liu, Heng Xiao, Bin Ran, “Short Term Traffic Forecasting Using the Local Linear Regression Model”, Center for Traffic Simulation Studies, Institute of Transportation Studies, UC Irvine, 07-01-2002.

14.     C C Toner, C J Broomhead, I H Littlejohn,G S Samra    “Prediction of postoperative nausea and vomiting using a logistic regression model”, British Journal of Anaesthesia. 1996, pp-347-351.

15.     Panagiotis Sentas, Lefteris Angelis, “Categorical missing  data imputation for software cost estimation by multinomial logistic regression”  Journal of Systems and Software, Volume 79, Issue 3, March 2006, Pages 404-414.

16.     Xiaobo Zhou, Xiaodong Wang, Edward R. Dougherty, “Gene prediction using multinomial probit regression with Bayesian gene selection”, EURASIP Journal on Applied Signal Processing, Volume 2004, 1 January 2004, pp- 115-124.

17.     F.J. Nogales, J Contreras,   A.J Conejo,   R. Espinola, “Forecasting next-day electricity prices by time series models”, IEEE Transactions on Power Systems, Volume 17Issue:2, pp- 342 – 348.

18.     Douglas C. Montgomery , David J. Friedman, “prediction using regression models with multicollinear predictor variables”, IIE Transactions, Volume 25, Issue 3, 1993, pp- 73-85.





Tripti Sharma, Sarang Pitale

Paper Title:

Chapter extraction from research documents using Meta-Content Framework

Abstract:    Automatic chapter extraction from electronic documents has always been an interesting task for researchers who are continuously engaged in subjective answering systems. Researchers are agreed on the fact that chapter extraction is one of the key processes to generate the model answers. The proposed paper presents a framework to extract the chapter contents from the research documents. The framework is implemented using Java technology and iText library , It takes research document of PDF format as an input and extracts the chapter contents in simple HTML format so that it can be easily rendered in web browser.

   PDF, Java, iText, Html.


1.       Adobe Systems Incorporated, http://www.adobe.com/pdf/
2.       Oracle Corporation,  http://www.java.com/en/

3.       iText ®- Free / Open Source PDF Library for Java and C#, http://www.itextpdf.com/

4.       Sarang Pitale and Tripti sharma, “Information Extraction tools for portable document format”, International journal of computer technology and applications,Vol 2 (6), 2047-2051

5.       César García-Osorio,Carlos Gómez-Palacios,Nicolás García-Pedrajas, “A Tool for Teaching LL and LR Parsing Algorithms”, Proceedings of the 13th annual conference on Innovation and technology in computer science education, ACM New York, NY, USA ©2008, pp-317-317 M. Young, The Technical Writer's Handbook. Mill Valley, CA: University Science1989.





Shruti Wadalkar, S.S. Pimplikar

Paper Title:

Role of Project Manager from the Client’s Side on the Performance of a Construction Project

Abstract:    In the developing Country like India there are various small construction companies involved in building and real estate sector. In such company project management team plays a very important role in success of the project from Preformulation to the completion stage of the project. Such project management team mainly consists of project manager and project engineer or supervisor. As the project manager is the leader of this team, it is required by him to acquire all the skills required for the better performance of his role. In the present work, the correlation coefficient between delay in the work, project manager and contractor is determined. On the basis of value of the coefficient of correlation, required project manager skills and classification of skills are stated.

   Coefficient, competency, Correlation, Project lifecycle.


1.       Amin Akhavan Tabassi, A.H. Abu Bakar (2008) “Training, motivation, and performance: The case of human resource management in construction projects in Mashhad, Iran” International Journal of Project Management 27 (2009) 471–480 available online at www.sciencedirect.com
2.       Eddie W. L. Cheng and Heng Li (2006) “Job Performance Evaluation for Construction Companies: An Analytic Network Process Approach” available at Journal Of construction engineering and management © ASCE / AUGUST 2006.

3.       G.L. Narayanappa (2009) “Human Resource Management (Text and Case Studies)” 1st ed. Scitech publications (India) pvt. Ltd.

4.       Juri L. De Coi, Eelco Herder, Arne Koesling, Christoph Lofi, Daniel Olmedilla, Odysseas  Papapetrou, and Wolf Siberski (2007)  “ A model for competence gap analysis” available on http://dspace.ou.nl/bitstream/1820/1119/1/model_for_competence_gap_analysis.pd

5.       National Skill Development Corporation, India NSDC (2010) “Study on mapping of human resource skill gaps in India till 2022”  available at  http://www.nsdcindia.org

6.       V.P. Michael (1998) “Human Resources Management and Human Relations” 5th ed. Himalaya publishing house, Mumbai.

7.       Sadi A. Assaf1, Member, ASCE, Mohammed Al-Khalil2, and Sheldon M. Ross “Introduction to Probability and Statistics for Engineering and Scientists Third edition”

8.       http://www.surveysystem.com/correlation.htm





Shalem Raj Meduri, P. S. Bramhanandam

Paper Title:

Comparison of Dilution of Precision (DOP) in Multipath and Error free Environment using Single Frequency Global Positioning System

Abstract:    Global Positioning System (GPS) is a satellite based radio navigation system intended to provide highly accurate three dimensional positions and precise time on a continuous global basis. Usually, GPS accuracy is limited by several factors such as atmospheric, receiver and satellite based errors. Among them, Dilution of Precision (DOP) and multipath errors are very important to investigate the error for improving positional accuracy. In this paper, single frequency receiver data analysis in static mode is carried out. Using the GPS data, Horizontal Dilution of Precision (HDOP) results were presented. The presented preliminary results would be useful for developing suitable techniques for improving single frequency GPS positional accuracy by taking the HDOP errors into the consideration.

   GPS, NMEA and HDOP.


1.        Kai Orre, and Gilert Strang, "Linear Algebra Geodesy And Gps",  Wellesely Camridge Press, USA, 1997
2.        Misra P And Per Enge, "Global Postioning System-Signals, Measurements And Performance", Ganga-Jamuna Press, Lincoln,  Massachussets, USA, 2001

3.        Hofmann wellenhof B., Lichtenegger H., and collins J., "Global Positioning system-Theory and Practice", Springer wein, New york, fifth Edition, 2001

4.        Parkinson B. W and Spilker J. J, “Global Positioning System: Theory and Applications”, Vol.1, American Institute of Aeronautics and Astronautics, Washington, 1996. 

5.        Quddusa sultana, Dhiraj Sunehra, A. D. Sharma and P. V. D. Somasekhara Rao “Comparitive Analysis of the Techniques for Estimation of GPS DOP over Indian Region”





Rahul Singh Rathore,  Sudeep Baudha, Neha Shrivastave

Paper Title:

Design and Simulation of Triangular Arm Antenna for WLAN Application

Abstract:    In this paper, A newly design technique for enhancing Bandwidth that improves the performance of a conventional microstrip patch antenna is proposed. This paper presents a novel wideband triangular arm antenna. The design adopts contemporary techniques; A triangular arm patch antenna structure. The effect of these techniques and by introducing the novel single shaped patch, offer a low profile, broadband, high gain, and compact antenna element. The result showed satisfactory performance with maximum achievable return loss –19db and a fractional impedance bandwidth of 2.32GHZ-2.72GHZ. The design is suitable for WLAN, mobile communication, satellite communication & WPAN.

  2.32GHZ-2.72GHZ. The design is suitable for WLAN, mobile communication, satellite communication & WPAN.


1.        Luis Brás, Nuno Borges Carvalho and Pedro Pinho, “Pentagonal Patch-Excited Sectorized Antenna for Localization Systems”, Transactions on antennas and propogation,  IEEE March 2012   Vol. 60, NO. 3,
2.        Amit Kumar Srivastava, Saswati Ghosh and Binay Kumar Sarkar, “Analysis of Circular Patch Antenna as an Electromagnetic Interference Sensor”, IEEE  2012 Vol. 978-1-4673-1515-9/12 

3.        S.K. Podilchak, M. Caillet, D. Lee and Y.M.M. Antar, ” Compact Antenna for Microsatellite        Using Folded Shorted Patches and an Integrated Feeding Network”, IEEE 2011   Vol. 978-1-4577-0919-7/12 

4.        Linxi Zhang, Qi Zhang, “The Influence of Dielectric Constant on  Bandwidth of U-notch Microstrip Patch Antenna”, International Conference on Ultra-Wideband       IEEE,  2010.

5.        Aditi sharma G. Singh, “ Rectangular micro strip patch antenna design at THz frequency for        short distance wireless communication systems” ,  infrared milli TeraHz Waves,  2009.

6.        D. N. Elsheakh, Student Member, IEEE, H. A. Elsadek, E. A. Abdallah, H. Elhenawy, and          M. F. Iskander, Member, IEEE, “Enhancement of Microstrip Monopole Antenna Bandwidth by Using EBG Structures”, Antennas and wireless propogation letters, IEEE  2009   VOL8.

7.        M.A. Matin, B.S. Sharif. C.C. Teesimenidis, “Broadband stacked Microstrip Antennas with Different Radiating patch”, Springer LLC, 2009.

8.        C.F. Yang, W.C. Tzou, J.H. Tsai, H.M. Chen and Y.F.Lin, “Enhance Antenna Bandwidth by UsingHigh Permittivity Ceramic and FR4 Stacked Structure”, IEEE, 2007 IEEE, 2007 Vol. 1-4244-0878-4/07 

9.        Wang jain   Zhang Hou Huang Wenli Huang  Xueyu, “A novel wide band circular  patch antenna”, Journal of electronics (CHINA), Nov ’2005  Vol.22 No.6

10.     Indra Surjati and Eko Tjipto Rahardjo and  Djoko Hartanto, “Increasing  Bandwidth Dual Frequency Triangular Microstrip Antenna Feed By Coplanar Waveguide”, IEEE, 2/06 /2006 Vol.I     1-4244-0574

11.     Y. J. Sung', B.Y. Kim, T. U. Jang, and Y.-S.Kim, “Swithchable Triangular Microstrip Patch Antenna for Dual-Frequency Operation”, IEEE 8/04/2004 Vol.0-7803-8302

12.     Jui-Han Lu, Member, IEEE, Chia-Luan Tang, and Kin-Lu Wong, Senior Member, IEEE,” Novel Dual-Frequency and Broad-Band Designs of Slot-Loaded Equilateral Triangular Microstrip Antennas”, IEEE Transactions on antennas and propogation,IEEE, July 2000 Vol. 48, NO. 7

13.     Vinode kumar Singh aAshok mittal, “Design of wide band micro strip antenna arry at millimeter wave nd frequencies”, International journal of infrared and millimeter waves, Oct’1999 vol.21.No.2

14.     Ting-Hua Liu & Wen-Xun Zhang, “Compound techniques for broadening the bandwidth of microstrip patch antenna”, Asia Pacific Microwave Conference 1997.





Kaushik Sanganabhatla

Paper Title:

Comparison of Security Algorithms in a Distributed Monitoring Environment

Abstract:    In a Real time wireless environment like WIFI, we send the data in the form of packets from one location to other. While sending the data to destination safely, we maintain some security algorithms for the confidentiality of the data. We use the knowledge of many pre- existing algorithm mechanisms for the smooth flow of the data packets in a timely & secured manner. Here, the main objective is to compare the various security algorithms in ganglia distributed monitoring system. The research stimulates that comparing the constant algorithms (1-point/minimal & 10-point/maximal) with the variable (optimal) algorithms. From these it can be concluded that the CPU memory usage is less in optimal algorithm in terms of against high load, bytes- in, bytes-out characteristics.

  1-point or minimal, 10point or maximal, optimal algorithms and ganglia.


1.        The ganglia distributed monitoring system: design, implementation, and experience Matthew L. Massie Available online 15 June 2004
2.        Improving Security of Real-Time Wireless Networks through Packet Scheduling by Xiao Qin, Mohamed Alghamdi in IEEE Transaction on wireless communication, VOL.7, and NO. 9, September 2008.

3.        Dynamic Task Scheduling with Security Awareness in Real-Time Systems by Andrew Sung in High Performance Computing and Networking, Vol. 1, Nos. 1/2/3, 2004

4.        Integrating Intelligent Anomaly Detection Agents into Distributed Monitoring Systems by German Florez-Larrahondo in Journal of Information Assurance and Security 1 (2006) 59–77.

5.        Job oriented monitoring of clusters by vijaya lakshmi in IJCSE.

6.        802.11 security issues and solutions by D.M.Garge in IJCSC Vol. 2, No. 2, July-December 2011, pp. 587-591

7.        S. Lu, V. Bharghavan, and R. Srikant, “Fair scheduling in wireless packet networks,” IEEE Transaction Networking Aug 1999.

8.        Text book: The complete reference “Network security” by Roberta Bragg and Keith strassberg.

9.        GradyBooch, Object oriented Analysis and design with applications, the benjimin/cummings, 1994.

10.     T. Karygiannis and L. Owens, IEEE journal on” wireless network security 802.11, Bluetooth and Handheld Devices”.

11.     Scheduler based qos analysis by kumaran sharma IJRTE 2009.

12.     SPD (Static Priority with Deadline Considerations) Packet Scheduling Algorithm for achieving better QoS by Tamer Dag in Third International Conference on Networking and Services(ICNS'07) IEEE2007.





Penchalababu.V, Chandrakala.B, Gopal Krishna

Paper Title:

A Survey on Modified PWM Techniques for Z-Source Inverter

Abstract:    The proposed work presents a Z-source inverter which can be proposed as an alternative power conversion concept for variable speed AC drives. It has both buck and boost capabilities as they allow operation of the inverter in the shoot through state. It uses an exclusive Z-source network (LC component) to DC-link in between inverter and the DC source. By controlling the shoot-through duty cycle of IGBTs in inverter system, reduces the line harmonics, improves power factor, and extends output voltage range..This Paper presents different switching techniques such as Simple boost pwm, Constant boost pwm, Maximum boost pwm, Sine carrier pwm and Modified SVPWM.

   pulse width modulation, Modified SVPWM, z-source inverte

1.        F.Z.Peng; "Z-source inverter"; IEEE Transactions on Industry Applications, vol. 39, pp. 504-510, 2003
2.        P.C.Loh, D. M. Vilathgamuwa, Y. S. Lai, C. Geok Tin, Y. Li; "Pulse width modulation of Z-source inverters"; IEEE Transactions in Power Electronics, vol. 20, pp. 1346-1355,2005.

3.        A.H.Rajaei, S.Kaboli, A.Emadi; “Sliding-Mode Control of Z-source inverter”; Industrial Electronics,. IECON 2008. 34th Annual Conference of IEEE.

4.        R.Strzelecki ,G.S. Zinoviev; “Power Electronics in Smart Electrical Energy Networks”; Springer, 2008.

5.        F.Z.Peng, S. Miaosen, Q. Zhaoming; "Maximum boost control of the Z-source inverter"; IEEE Transactions in Power Electronics, vol. 20,  pp. 833-838, 2005.

6.        S.Thangaprakash, A.Krishnan; “Comparative evaluation of modified pulse width modulation schemes of Z-source inverter for various applications and demands”; IJEST, vol 2, pp. 103-115.

7.        S. Miaosen, W.Jin, A.Joseph, F.Z.Peng, L.M.Tolbert, D.J.Adams; "Constant boost control of the Z-source inverter to minimize current ripple and voltage stress"; IEEE Transactions in Industry Applications, vol.40, pp. 770-778, 2006.

8.        T.Meenakshi, K.Rajambal; “Identification of an effective control scheme for z-source inverter”; Asian Power Electronics Journal, vol.4, no.1, pp. 22-28, 2010.

9.        P.C.Loh, D. M. Vilathgamuwa, C.J.Gajanayake, L.T.Wong, C.P.Ang; “Z-source curren-type inverters: Digital modulation and logic implementation”; IAS, pp. 940-947, 2005.

10.     Q.V.Tran, T.W.Chun, H.G.Kim, E.C.Nho; “Minimization of voltage stress across switching devices in the z-source inverter by capacitor voltage control”; Journal of Power Electronics, vol.9, no.3, pp. 335 - 342, 2009.

11.     J.W.Jung, A.Keyhani, “Control of a fuel cell based z-source converter”; IEEEE Transaction of Energy Conversion, vol. 22, no.2, pp. 467-476, 2007.

12.     Zare, F., Firouzjaee, J.A., “Hysteresis band current control for a single phase z-source inverter with symmetrical and asymmetrical network”; Power Conversion Conference, pp. 143-148, 2007.

13.     U.Shajith.Ali, V.Kamaraj, “Since carrier for fundamental fortification in three phase z-source PWM inverters”; Modern Applied Science, vol.4, no.1, pp. 73-81, 2010.





D.Preethi, A.M Vijaya Prakash

Paper Title:

A Low Power VLSI Architecture for Image Compression System Using DCT and IDCT

Abstract:    Image compression is an important topic in digital world. It is the art of representing the information in a compact form. This paper deals with the implementation of low power VLSI architecture for image compression system using DCT. Discrete Cosine Transform (DCT) is the most widely used technique for image compression of JPEG images[5] and is a lossy compression method.. The architecture of DCT is based on Lo-effler method[1] which is a fast and low complexity algorithm. In the proposed architecture of DCT multipliers are replaced with adders and shifters. Low power approaches like Canonic signed digit representation for constant coefficients and sub-expression elimination methods has been used. The 2D DCT is performed on 8x8 image matrix using two 1D DCT blocks and a transposition block. Similar to DCT, the IDCT is also implemented using the Lo.effler algorithm for IDCT. Verilog HDL is used to implement the design. ISIM of XILINX is used for the simulation of the design. CADENCE RTL compiler is used to synthesize and obtain the detailed power and area reports of the design. MATLAB is used as the support tool to obtain the input pixel values of the image and the results from both ISIM and MATLAB are compared.

   Discrete Cosine Transform (DCT), Low Power, Canonic Signed Digit (CSD), Common Sub expression Elimination (CSE), JPEG, VLSI.


1.        Vimal P. Singh Thoudam, Prof.B.Bhaumik, Dr. s. Chatterjee, “Ultra Low Power Implementation Of 2D DCT For Image/Video Compression,” presented in International Conference on Computer Applications and Industrial Electronics.
2.        M. Jridi, A. Alfalou, “Low Power, High-Speed DCT Architecture For Image Compression: Principle And Implementation”, 18th IEEE/IFIP International Conference on VLSI and System on Chip.

3.        Christoph Loeffler, Adriaan Ligtenberg, George S. Moschytz “Practical fast 1D DCT algorithm with 11 multiplications,” 1989 IEEE.

4.        Jeffrey O. Coleman, Arda Yurdakul “Fractions in The Canonical Signed Digit Number Systems,”  Conference On Information Science And Systems.

5.        Gregory K.Wallace, “The JPEG Still Picture Compression Standards”, 1991 publication in IEEE transactions on consumer electronics.

6.        Ricardo Castellanos, Hari Kalva, Ravishankar, “Low Power DCT Using Highly Scalable Multipliers”.

7.        Ankita Singla, A.P.Vinod, Deepu Rajan, Edmund M.K.Lai, “Low Power DCT Implementation Using Differential Pixels For On-Board Satellite Image Processing.”

8.        Muhammed Yusuf Khan, Ekram Khan, M.Salim Beg, “Performance Evaluation Of 4x4 DCT Algorithms For Low Power Wireless Applications,” First International Conference on Emerging Trends in Engineering and Technology.

9.        M. El Aakif, S.Belkouch, N.Chabini, M.M.Hassani, “Low Power and Fast DCT Architecture Using Multipliers-Less Method”, 2011 Faible Tension Consommation.

10.     Vijay Kumar Sharma, K.K.Mahapatra, Umesh C. Pati, “An Efficient Distributed Arithmetic based VLSI Architecture for DCT”, 2011 IEEE.

11.     A. Pradini, T.M.Roffi, R.Dirza, T.Adiono, “VLSI Design of a High Throughput Discrete Cosine Transform for Image Compression Systems”, 2011 International Conference on Electrical Engineering and Informatics, Indonesia.

12.     S.V.V Sateesh, R.Sakathivel, K.Nirosha, Harish M.Kittur, “An Optimized Architecture to Perform Image Compression And Encryption Simultaneously Using Modified DCT Algorithms”, Proceedings of 2011 International Conference On Signal Processing, Communication, Computing And Networking Technologies.





Sandeep Kaur

Paper Title:

Mouse Movement using Speech and Non-Speech Characteristics of Human Voice

Abstract:    In the modern era, mouse control has become an important part of human computer interaction which is difficult for physically disabled people. This research paper presents a system called as Vocal Mouse (VM). This device will allow users to continuously control the mouse pointer using words as well as sounds by varying vocal parameters such as vowel quality, loudness and pitch. Traditional method of using only standard spoken words was inefficient for performing continuous tasks and they are often recognized poorly by automatic speech recognizers. Now, VM will allow users to work on both continuous and discrete motion control. This includes commands given as words or regular sounds consisting of vowels and consonants. Low-level acoustic features are extracted in real time using LPC (Linear Predictive Coding). Pattern recognition is performed using a new proposed technique called “minimum feature distance technique”. This proposed technique is based on calculating distances between the spoken word and each stored word in the library during training process. Features from pattern recognition module are processed to produce output in the form of cursor’s 2-D movement. VM can be used by novice users without extensive training and it presents a viable alternative to existing speech-based cursor control methods.

   acoustic features, continuous speech recognition, minimum feature distance, motor impairment, vocal sounds.


1.        Susumu Harada, “Harnessing the Capacity of the Human Voice for Fluidly Controlling Computer Interface”, University of Washington, 2010
2.        James R Evans, Wayne A Tjoland and Lloyd G Allred, “Achieving a Hands-Free Computer Interface using Voice Recognition and Speech Synthesis “,IEEE AES Systems Magazine, 2000

3.        Susumu Harada and James A Landay, “The Vocal Joystick: Evaluation of Voice-based Cursor Control Techniques”, Portland, Oregon, USA: ASSETS, 2006

4.        M Abdeen, H Moshammad and M C E Yagoub, “An Architecture for Multi-Lingual Hands Free Desktop Control System for PC Windows”, Niagara Falls, Canada : IEEE , 2008

5.        R Maskeliunas, K Ratkevicius and V Rudzionis, “Voice-based Human-Machine Interaction Modeling for Automated Information Services”, ISSN 1392-1215 Electronics and Electrical Engineering, 2011

6.        R Norma Conn and Michael McTear, “Speech Technology: A Solution for People with Disabilities”, Savoy Place, London WCPR OBL, UK: IEE, 2000

7.        Minh TU Vo and Alex Waibel “A Multi-Lingual Human-Computer Interface: Combination of Gesture and Speech Recognition”, Carnegie Mellon University Pittsburgh, U.S.A, 2009

8.        Susumu Harada, Jacob O Wobbrock, Jonathan Malkin, Jeff A Bilmes and James A Landay,“Longitudinal Study of People Learning to Use Continuous Voice-Based Cursor Control”, Boston, MA: Conf. on Human Factors in Computing Systems

9.        M Rahmani, N Yousefian and A Akbari, “Energy-based speech enhancement technique for hands-free communication”, ELECTRONICS LETTERS Vol. 45 No. 1, 2009





Ketki Ram Bhakare, R.K.Krishna, Samiksha Bhakare

Paper Title:

Distance Distribution Approach of Minimizing Energy Consumption in Grid Wireless Sensor Network

Abstract:   A wireless Sensor Network (WSN) is a wireless network consisting of several tiny sensing nodes.Wireless Sensor Network (WSN) is an emerging technology. It is predicted that in future, WSN will change the human life totally. Energy minimization in Wireless Sensor Network (WSN)is one of the challenging issue. The sensor nodes are continuously sense and transmit the data. WSN have a wireless nature, due to this has a limited lifetime. So increase the lifetime of Wireless Sensor Network and Minimize energy cost in wireless sensor network are an important problem. To solve this problem clustering technique are always used, among the entire clustering technique grid based clustering is more efficient. Most of the work uses the average distance within the grid & between neighboring grids for calculating the average energy consumption; by using this average distance model we found that it underestimate the actual value of average energy consumption. So we propose a better model for energy consumption i.e.  Distance distribution model, this model gives the accurate estimation of energy consumption. Distance distribution model can be used to optimize grid size and minimize energy consumption.

   Average Energy Consumption, Clustering, Distance Distribution Sensor,Grid based Clustering, power consumption, WSN


1.       Ameer Ahmed Abbasi and Mohamed Younis, “A survey on clustering algorithms for wireless sensor networks,” Computer Communications 30 (2007) 2826–2841.
2.       Chin-Ling Chen  and I-Hsien Lin, “Location-Aware Dynamic         Session-Key Management for Grid-Based Wireless Sensor Networks particles, thin films and exchange anisotropy,” Sensors 2010, 10, 7347-7370; doi:10.3390/s 100807347.

3.       Adeel Akhtar, Abid Ali Minhas, and Sohail Jabbar , “Energy Aware Intra         Cluster Routing for Wireless Sensor Networks,” International Journal of  ybrid Information Technology Vol.3, No.1, January, 2010.

4.       Y. Zhuang, J. Pan and G. Wu, “Energy-optimal gridbased clustering in wireless microsensor networks,” IEEE ICDCS Workshop on Wireless Adhoc and Sensor Networking (WWASN), 2009.

5.       R. Vidhyapriya and P. T. Vanathi, “Energy efficient grid-based routing in wireless sensor networks,” International Journal of Intelligent Computing and Cybernetics, vol. 1, no. 2, pp. 301–318, Jan. 2008.

6.       K. Akkaya, M. Younis, “A survey on routing protocols for wireless sensor networks,” Ad Hoc Networks, vol. 3, no. 3, pp. 325–349, May 2005.

7.       Sylvain Ranvier , “Path loss models,” Radio Laboratory TKK 23 November 2004.

8.       Yanyan Zhuang ,Jianping Pan  and Lin Cai, “Minimizing Energy Consumption with Probabilistic Distance Models in Wireless Sensor Networks,” IEEE INFOCOM 2010.





Rajeswar Lal Dua, Anjali Nigam, Pooja Yadav

Paper Title:

A  Method for Fine Tuning Of Resonance Frequency of Patch Antenna

Abstract:    When a patch antenna is fabricated, size of the as-fabricated resonant patch may be slightly different from its designed value due to tolerances in the fabrication operations. This will alter the resonance frequency. To overcome this problem this paper presents a new method for fine tuning the resonance frequency by dielectric engineering. This approach is especially suited to LTCC and similar processes where the antenna dielectric is composed of several layers. Composite dielectric constant of this multilayer structure is altered in such away that the resonant frequency is set back to the designed value. A cavity is cut below the patch in one or more dielectric layers. This paper investigates the effect of cavity size on shift in resonance frequency. HFSS software has been used for simulations. Three different dielectric materials were investigated for several resonant frequencies. f/f0 was plotted against Area Ratio (AR) to generalize the findings. Area Ratio is the ratio of area of cavity to the area of the patch,  f is the resonance frequency for a given cavity area and f0 is its value without any cavity. Depth of the cavity may be equal to either one or two dielectric layer thickness in a four layered dielectric structure. Very interesting results have been obtained. For all ε and all f/f0 the curve can be described by the equation of the form f/f0 = R2+R+1 where R is the area ratio. This mathematical model is true up to R=1.27. After this saturation effects set in and the curve changes to a straight line f/f0 = mR+. Further work is being carried out.

   LTCC ,Composite Dielectric Constant,area ratio, multilayer structure.


1.        M.Olyphant, Jr. and J.H. Ball, "Stripline method for dielectric measurements at microwavefrequency", IEEE Trans. Elec. Insul., Vol.EI-5, pp.26-32, March,1970.
2.        L.S. Napoli and J.J. Hughes, "A simple technique for the accurate determination of the microwave dielectric constant for microwave integrated circuit substrates", IEEE Trans.  Microwave Theory Tech., Vol.MTT-19, pp.664-665, July 1971.

3.        T. Itoh, "Anew method for measuring properties of dielectric materials using a micro strip cavity", IEEE Trans. Microwave Theory Tech., Val-MTT-22, pp. 572-576, May 1974.

4.        D. Shimin, "A new method for measuring dielectric constant using the resonant Frequency of a patch antenna", IEEE Trans. Microwave Theory Tech., Vol.MTT-34, pp.923-931, Sept. 1986.

5.        Ranjit Singh, Asok De, R.S. Yadav, “A simple method for measuring dieledtric constant at microwave frequency", IEEE Trans. Microwave Theory Tech., Vol.MTT-22,pp.1-5, Jan. 1990.

6.        Jiri Svacina, “Analysis of Multilayer Microstrip Lines by a Conformal Mapping Method”, IEEE Trans. Microwave Theory Tech., vol. 40,no.4, pp. 769., 1992.

7.        A.K. Verma, et al., “Unified Dispersion Model for Multilayer Microstrip Line”, IEEE Trans. Microwave Theory Tech. vol. 40.No.7, pp. 1587, 1992.

8.        R. H. Jansen, “ A novel CAD tool ad concept compatible with the requirement of multilayer GaAs MMIC technology”, IEEE MTT-S Microwave Symp. Dig.,  pp. 711, 1980.

9.        M. Y. Frankel, et al., “ Coplanar Transmission Lines on Thin Substrate for High Speed Low Loss Propagation”, IEEE Trans. Microwave Theory Tech., vol. 42, no. 3, pp. 396, 1994.

10.     Kin-Lu Wong, Fellow, IEEE, Yu-weiChang“Bandwidth enhancement of small size planer tablet computer anteena using a parallel resonant spiral slit” IEEE Trans.onanteena and propagation, vol. 60 , no.4,april 2012.

11.     Y.Sung“Bandwidth enhancement of a microstrip line fed printed wide slot anteena with a parasitic center patch” IEEE Trans.,on anteena and propagation vol. 60, no. 4april 2012.





Nikunj V. Patel, R. K. Patel, U. J. Patel, B. P. Patel

Paper Title:

A Novel Approach for Selection of Tool Insert in CNC Turning Process Using MADM Methods

Abstract:    In modern decision science the Multiple attribute decision making (MADM) is playing an important role for selection of best from number of alternative. It has been applicable in various areas such as society, economics, military, management, manufacturing, etc., and has been receiving more and more attention over the last decades. To date, however, most research has focused on single-period multi-attribute decision-making in which all the original decision information is given at the same period, and a number of methods have been proposed to solve this kind of problems. In this research work we have considered a novel approach for optimum cutting tool insert selection strategy. In this approach, two well-known Multiple Attribute Decision- Making (MADM) methods such as Simple Additive Weighting (SAW) and Weighted Product Method (WPM) use for a case study of tool insert selection for better surface finish in CNC (Computer Numerical Control) turning operation. In these methods their relative performance are compared with respect to ranking of alternative and from ranking we have selected best tool insert for better surface quality during turning operation on alloy steel using CNC  turning centre.

   MADM, SAW, WPM, Surface roughness


1.       M. A. Manan, R. M. Arunachalam, A.C. Spowage, Surface integrity when machining age hardened Inconel 718 with coated carbide cutting tools, International Journal of Machine Tools & Manufacture, 44 (2004), 1481–1491.
2.       Hasan Go kkaya a, Muammer Nalbant, The effects of cutting tool geometry and processing parameters on the surface roughness of AISI 1030 steel, Materials
and Design, 28 (2007), 717–721.

3.       Suleyman Neseli, Suleyman Yaldız , Erol Turkes, Optimization of tool geometry parameters for turning operations based on the response surface methodology, Measurement, 44 (2011), 580–587.

4.       M. Dogra,V. S. Sharma, J. Dureja , Effect of tool geometry variation on finish turning – A Review Journal of Engineering Science and Technology Review, 4 (1), (2011), 1-13.

5.       J. Guddat, R. M’Saoubia, P. Alma, D. Meyer Hard, Turning of AISI 52100 using PCBN wiper geometryinserts and the resulting surface integrity , Procedia Engineering, 19, (2011), 118 – 124.

6.       Vijay Manikrao Athawale, Shankar Chakraborty, A TOPSIS Method-based Approach to Machine Tool Selection, Proceedings of the 2010 International Conference on Industrial Engineering and Operations Management Dhaka, Bangladesh, (2010), 9 – 10,.

7.       Dr. D. Nageswara Rao, K. Suresh Babu N. V. Subba  Raju M. Srinivasa Reddy, The Material Selection For Typical Wind Turbine Blades Using  A MADM Approach & Analysis of Blades, MCDM, Chania, Greece, (2006), 19-23,.

8.       Manshadi B. D., Mahmudi H., Abedian A., Mahmudi R., A novel method for materials selection in mechanical design: combination of non-linear normalization and a modified digital logic method. Materials & Design, 28, (2007), 8–15.

9.       Vishram B. Sawant, Suhas S. Mohite, Rajesh Patil, A Decision-Making Framework using a Preference Selection Index Method for Automated Guided Vehicle Selection Problem. International Conference on Technology Systems and Management (ICTSM) 2011 Proceedings published by International Journal of Computer Applications (IJCA), (2011), 12-16.

10.     Abhang, L.B.*& Hameedullah, M* Selection of Lubricate Using Combine Multiple Attribute Decision Making Method, Advance in Production Engineering & Management 7 (1), (2012), 39-50.

11.     R. Venkata Rao "Decision Making in Manufacturing Environment Using Graph Theory and Fuzzy   Multiple Attribute Decision Making Methods", Springer Series in Advanced Manufacturing, Springer Landon, 2007.





Alaknanda Mane, S.S.Pimplikar

Paper Title:

Dispute – A Case Study

Abstract:    One of the greatest challenge facing the construction industry during the last couple of decades has been how to resolve disputes arising in construction contracts' in a timely and efficient manner with minimal financial costs, without hindering the pre-planned end results on a construction project. Wide scale adoption of Dispute Review Boards (DRBs), sometimes also called Dispute Adjudication Boards (DABs), in large size engineering projects construction contracts is just more than a decade old in the advanced world. During this period, DRBs have been found ideally suited to dispute resolution process in large size projects involving sophisticated technology and Intricate construction techniques such as in tunnels & underground construction, heavy industrial & process buildings, hydro engineering power projects, bridges & highways and marine works.

   Wide scale adoption of Dispute Review Boards (DRBs), sometimes also called Dispute Adjudication Boards (DABs),


1.        Ministry of Statistics and Programme Implementation, Government of India, Standard general conditions for domestic contracts.
2.        FIDIC Conditions of Contract for Construction, For building and engineering works, May 2005.

3.        Actual Project Execution Site.





V.Radhika, K.Baskaran, N.Krithika

Paper Title:

A Survey - Power Management in Multicore System On-a-Chip (SOC)

Abstract:    Multi core systems running multiple process, needs a power management technique which is able to provide tradeoff between power and performance. Power management refers to the generation and control of regulated voltages required to operate an electronic system. With growing power management concern there is necessity to develop an efficient voltage regulation technique to improve the performance of any system. In the present scenario power supply design must be integrated within the system to improve the efficiency. Integrated components like switching regulator, linear regulators, and voltage reference are typical elements of power management.

   Linear regulator, power management, power converters, switching regulator.


1.       Jonathan Rosenfled and Eby G.Friedman “Linear and Switch-Mode Conversion in    3-D Circuits” IEEE J.Very Large scale Integration (VLSI) Systems.,vol.19,no.11,  November 2011 .
2.       Jonathan Rosenfled and Eby G.Friedman “A Distributed Filter Within a Switching Converter for Application to 3-D Integrated Circuits” IEEE J.Very Large scale Integration (VLSI) Systems,   vol.19,no.6,  June 2011.

3.       Juliana Gjanci,Masud.H.Chowdhury, “A Hybrid Scheme for On–Chip Voltage Regulation in System –On-a-Chip(SOC)” IEEE J.Very Large scale Integration (VLSI) Systems,   vol.19,no .11,November 2011 .

4.       W. Kim, et. El, “Enabling On-Chip Switching Regulators for Multi-Core Processors using Current Staggering,” Workshop on Architectural Support for Giga scale Integration 2007, held in conjunction with ISCA 2007.

5.       R. Bergamaschi, et.El, “Exploring Power Management in Multi-Core Systems”, Design Automation Conference, Asia and South Pacific, pp. 708–713, 2008.

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Padmini Sahu, Anurag Singh Tomer

Paper Title:

Speed control of PMBLDCM drive using Power Factor Correction (PFC) Convertor

Abstract:    This paper aims at  an improve speed quality employing buck half-bridge DC-DC converter is used as a single-stage power factor correction (PFC) converter for feeding a voltage source inverter (VSI) based permanent magnet brushless DC motor (PMBLDCM) driven air condition. This PFC converter is front end diode bridge rectifier (DBR) fed from single-phase AC mains and connected to a three phase voltage source (VSI) feeding the permanent magnet brushless DC motor (PMBLDCM). The PMBLDCM is used to drive a compressor load of an air conditioner through a three-phase VSI fed from a controlled DC link voltage. The speed of the compressor is controlled to achieve energy conservation using a concept of the voltage control at DC link proportional to the desired speed of the PMBLDCM. Therefore the VSI is operated only as an electronic commutator of the PMBLDCM. The stator current of the PMBLDCM during step change of reference speed is controlled by a rate limiter for the reference voltage at DC link. The proposed PMBLDCM drive with voltage control based PFC converter is designed, modeled and its performance is simulated in Matlab- Simulink environment for an air conditioner compressor driven PMBLDC motor.

   PFC, PMBLDCM, Air Conditioner, Buck Half Bridge Converter, Voltage Control, VSI.


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2.       M. V. Ramesh1, J. Amarnath2, S. Kamakshaiah and G. S. Rao3. “ Speed control  of  BRUSHLESS  DC  MOTOR  by  using  fuzzy  logic  PI  controller” 2009.

3.       Y.H.  Bharathi1, B.R. Rekha1, P. Bhaskar2, C.S.  Parvathi2 and A.B. Kulkarni1. “Multi-input  Fuzzy  Logic  Controller  for  Brushless  dc  Motor Drives”, 2008

4.       Deepak Batra1, Sanjay Sharma2 and Rajeev Ratan3.  “Axis  controlled movement  of  robot  using  brushless  DC  motor  drive” ,2009.

5.       Bhim Singh and Sanjeev Singh,” Half Bridge Boost Converter for Power Quality Improvement in PMBLDCM Drive”, ICETET-09.

6.       B. Singh, B. N. Singh, A. Chandra, K. Al-Haddad, A. Pandey and D. P.Kothari, “A review of single-phase improved power quality AC-DC converters,” IEEE Trans. Industrial Electron., vol. 50, no. 5, pp. 962 –981, oct. 2003.

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8.       A. Halvaei Niasar', A. Vahedi2, H. Moghbelli3Speed Control of a Brushless DC Motor Drive via Adaptive Neuro-Fuzzy Controller Based on Emotional Learning Algorithm.

9.       T.V.NARMADHA,” Speed control of PMBLDCM with gate control method using conventional and fuzzy controller” Vol. 2(11), 2010, 6663-6674.

10.     Vinatha U, Research Scholar, Swetha Pola, Asst. Software Engg., TCS, Dr K.P.Vittal, Simulation of Four Quadrant Operation & SpeedControl of BLDC Motor on MATLAB / SIMULINK





I.Diana Jeba Jingle, Elijah Blessing Rajsingh, P.Mano Paul

Paper Title:

Distributed Detection of DoS Using Clock Values in Wireless Broadband Networks

Abstract:    Wireless broadband networks are most vulnerable to denial-of-service attacks where attackers can disrupt legitimate communication between hosts in a network by flooding unwanted traffic between legitimate hosts. Flooding attack at the transport layer affects the TCP’s 3-way handshake process, thereby denying the services of TCP. It also denies the services of UDP. This paper proposes a novel flooding attack, the most severe denial-of-service attack that occurs at the transport layer of the internet. The main objective of this approach is to install local and global monitoring agents at various points in order to monitor and filter real-time TCP traffic and UDP traffic thereby allowing legitimate traffic to flow in the network during attack traffic filtration process and to avoid buffer overflow at the monitoring agents. Also, a novel algorithm has been proposed by taking the clock values of each node into account for effective detection of the attack. This distributed defense mechanism reduces the burden on a single global monitoring agent thereby introducing local monitoring agents at various points in the network. The performance results show that this approach effectively and accurately detects and filters DOS attacks within a short period.

   DOS, Flooding, Handshake, Spoofing.


1.       Jelena Mirkovic, Peter Reiher, “D-WARD: A Source-end Defense Against Flooding Denial-of-service Attacks,” IEEE Transactions On Dependable And Secure Computing, Vol. 2, No. 3, July - September 2005.
2.       Sudip Misra, P. Venkata Krishna, Kiran Isaac Abraham, Navin Sasikumar, S. Fredun, “An Adaptive Learning Routing Protocol For The Prevention Of Distributed Denial Of Service Attacks In Wireless Mesh Networks,” Acm Journal Of Computers & Mathematics With Applications, Vol. 60, Issue 2, July 2010.

3.       Patrick P.C. Lee A, Tian Bu B, Thomas Woob, “On The Detection of Signaling DoS Attacks on 3G/WiMax Wireless Networks,” Elsevier Journal on Computer Networks 53 2601–2616, 2009.

4.       Xiaowei Yang, Wetherall, D. Anderson, T. IEEE/ACM Transactions on Networking, Vol. 16 , Issue 6, December 2008.  

5.       Haidar Safa, Mohamad Chouman, Hassan Artail, Marcel Karam, “A collaborative defense mechanism against SYN flooding attacks in IP networks,” Elsevier Journal of Network and Computer Applications, Volume 31 Issue 4, November 2008.

6.       Dimitris Geneiatakis, Nikos Vrakas, Costas Lambrinoudakis, “Utilizing bloom filters for detecting flooding attacks against SIP based services,” Elsevier Journal of Computers & Security, Volume 28, Issue 7, October 2009, Pages 578-591.

7.       Bin Xiaoa, Wei Chenb, Yanxiang Hec, “An autonomous defense against SYN flooding attacks: Detect and throttle attacks at the victim side independently,” Elsevier Journal of Parallel and Distributed Computing, Volume 68 (2008), Pages 456 – 470.

8.       P.Ferguson and D.Senie, “Network ingress filtering: Defeating denial of service attacks that employ IP source address spoofing,” Internet RFC 2827, 2000.

9.       Suman Jana And Sneha K. Kasera, “On Fast And Accurate Detection Of Unauthorized Wireless Access Points Using Clock Skews,” Ieee Transactions On Mobile Computing, Vol. 9, No. 3, March 2010.

10.     J.Ioannidis and S. Bellovin, “Implementing pushback: Router-based defense against DoS attacks,” in Proc. NDSS, 2002.

11.     I.B. Mopari, S.G. Pukale, M.L. Dhore, Detection of DDoS attack and defense against IP spoofing, in: Proceedings of the International Conference on Advances in Computing, Communication and Control, ICAC3'09, January 23_24, 2009, Mumbai, Maharashtra, India, pp. 489_493.

12.     Amey Shevtekar, Karunakar Anantharam, And Nirwan Ansari, “Low Rate Tcp Denial-of-service Attack Detection At Edge Routers,” Ieee Communications Letters, Vol. 9, No. 4, April 2005.

13.     Supranamaya Ranjan, Member, Ieee, Ram Swaminathan, Mustafa Uysal, Antonio Nucci, Senior Member, Ieee, And Edward Knightly, Senior Member, Ieee, “Ddos-shield: Ddos-resilient Scheduling To Counter Application Layer Attacks,” IEEE/ACM Transactions on Networking, Vol. 17, No. 1, February 2009.  

14.     CERT Advisory CA-1996-21 TCP SYN Flooding and IP Spoofing Attacks, CERT CC, http://www.cert.org/advisories/CA-1996-21.html, 1996.

15.     Nikhil Saxena, Mieso Denko, Dilip Banerji, “A hierarchical architecture for detecting selfish behaviour in community wireless mesh networks,” Elsevier Journal of Computer Communications, 2010.





V.Shanmugasundaram, A.R Rajkumar, T.Jayabarathi

Paper Title:

Load Frequency Control Using Optimal PID Controller for Non-Reheat Thermal Power System with Tcps Unit

Abstract:    The main objective of Load Frequency Control (LFC) is to regulate the power output of electric generator within an area, in response to the changes in system frequency and tie-line loading. Thus, LFC helps in maintaining the scheduled system frequency and tie-line power interchange with other areas within the prescribed limits. Most LFCs are primarily composed of an integral and PID controller. The integrator gain is set to a level that compromises between fast transient recovery and low overshoot in the dynamic response of the overall system. This type of controller is slow and does not allow the controller designer to consider the possible changes in operating condition and non-linearity in the generator unit. Moreover, it lacks in robustness. FACTS are designed to overcome the limitations of present non-reheat thermal-thermal power systems and enhance the power system stability. One of the promising FACTS devices is the Thyristor controlled phase shifter (TCPS) to alleviate this difficulty.  TCPS is connected in the tie-line to self-tune the parameters of integral and PID controller. Two area system, have been considered for simulation of the proposed TCPS connected integral and PID controller .The performance of the Conventional controller, TCPS connected Integral and PID controller have beenCompared through MATLAB Simulation. The qualitative and quantitative comparisons have been carried out for Integral, PID controllers. The dynamic of performanceresponses of Integral and PID controller with TCPS shows that in terms of settling Time, peak overshoot and steady state error are greatly improved than that of without TCPS. 

   Load Frequency Control, Power system, PID controller, Thyristor controlled Phase Shifter.


1.        N.Jaleeli, d.N.Ewart, and L.H.Fink, Aug 2008’understanding Automatic Generation Control’ IEEE Trans.Power System Volume 7, no. 3, PP 1106-1122
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3.        O.I.Elgered, McGraw-Hill, NewYork1982’Electric Energy System theory’, An Introduction

4.        T.Hiyama, 2009, 17-22 ‘design Of Decentralized Load Frequency Regulators for Interconnected Power System IEEE Proceedings on Generation, transmission distribution’ 129

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6.        K.Xing&G.Kusic,’Application of Thyristor controlled Phase Shifters to minimize real power losses and argument stability of power Systems,IEEE trans on Energy Conversion,3,2009,792-798

7.        R.J.Abraham, D.Das & A.Patra, IET Generation Transmission and distribution, 1(4), 2007, 632-639,’effect of TCPS on oscillations in tie-power and area frequencies in an interconnected thermal power system’

8.        M.H.Ali, Wubin & R.A.Dougal,’an overview of SMES application in power and energy Systems’, IEEE transactions on sustainable energy1 (1), 2010, 38-47

9.        H.Hayashi, Y.Hatabe, T.Nagfuchi, at al test results of power system control byExperimental SMES, IEEE transaction on applied superconductivity 16(2), 2006, 598-601





Shobha Sharma

Paper Title:

Ring Oscillator Comparative Analysis at 22nm with bulk And High-K Metal Gate CMOS Technology and frequency impact

Abstract:    As we progress toward higher technology nodes there are improvement in density, frequency of operation and low power dissipation along with increase in leakage current and power. This paper examines a CMOS 11 stage ring oscillator implemented at 22nm node with bulk technology and High K metal Gate technology. Supply voltage increase results in increase in oscillation frequency in both the technology as expected. The simulation result shows the average power dissipated is more in High K Metal Gate technology compared to Bulk technology but the output frequency is more in High K metal gate technology. This results in lower energy/cycle in High K metal gate technology Ring Oscillator comparatively and hence shows that for advanced technology nodes this technology is a better option with reduced leakage due to High K material used. The experimental set up uses Predictive Technology models of Arizona State University at the two technology node and HSPICE   simulator is used to carry out simulations

   bulk CMOS,, high K, Ring Oscillator, PTM.


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Charlie Eapen, A.K Jaiswal, Mukesh Kumar, Ravi Jon, A.Ashok  

Paper Title:

Improving the Efficiency of Wireless Sensor Networks through Signal Processing Techniques

Abstract:    The minimization of energy consumption in modern technology has become a crucial element of research in engineering it is not only advantageous to realizing versatile, robust designs, but also the demand of an environmentally-awakened society. In the case of wireless networking, discovering energy-efficient solutions is just as important to the practicality and success of the technology as it is to commercialization and public reception. In this paper we show that a large portion of the beamforming gains can be realized even with imperfect synchronization corresponding to phase errors with reasonably large variance. We present a master-slave architecture where a designated master transmitter coordinates the synchronization of other (slave) transmitters for beamforming. We observe that the transmitters can achieve distributed beamforming with minimal coordination with the Base Station using channel reciprocity. Thus, inexpensive local coordination with a master transmitter makes the expensive communication with a distant Base Station receiver more efficient.

   Wireless Sensor Network (WSN), Master-Slave Architecture, Signal Processing.


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11.     R. Mudumbai, J. Hespanha, U. Madhow, and G. Barriac, “Scalable feedback control for distributed beamforming in sensor networks,” in Proc. IEEE Intl. Symp. on Inform. Theory (ISIT) 2005.





Deepthi chamkur .V , Vijayakumar.T

Paper Title:

Reliable Routing & Deadlock free massive NoC Design with Fault Tolerance based on combinatorial application.

Abstract:    Technological evolution enables the integration of billions of transistors on a chip. As VLSI technology scales, and processing power continues to improve, inter-processor communication becomes a performance bottleneck. On-chip networks have been widely proposed as the interconnect fabric for high performance SoCs. Recently, NoC architectures are emerging as the candidate for highly scalable, reliable, and modular on-chip communication infrastructure platform. This paper proposes the generalized binary de Bruijn (GBDB) graph based on combinatorial application as a reliable and efficient network topology for a large NoC. We propose a deadlock free & reliable routing algorithm to detour a faulty channel between two adjacent switches. In this implementation, using just two-layer VLSI layout, we can implement a NoC with any desired number of nodes. Note that current VLSI technology allows more than two wiring layers and the number is expected to rise in the future. Our experimental results show that the latency and energy consumption of the generalized de Bruijn graph are much less than those of Mesh and Torus. The low energy consumption of a de Bruijn graph-based NoC makes it suitable for portable devices which have to operate on limited batteries. Also, the gate level implementation of the proposed reliable routing shows small area, power, and timing overheads due to the proposed reliable routing algorithm.

   Network on chip (NoC), combinatorial application, energy consumption.


1.       S. R. Vangal et al., “An 80-tile sub-100-W TeraFLOPS processor in 65-nm CMOS,” IEEE J. Solid-State Circuits, vol. 43, no. 1, pp. 29–41, Jan. 2008.
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3.       M. Yang, T. Li, Y. Jiang, and Y. Yang, “Fault-tolerant routing schemes in RDT(2,2,1)/based interconnection network for networks-on-chip designs,” in Proc. 8th Int. Symp. Parallel Arch., Algorithms Netw. (ISPAN), 2005, pp. 52–57.

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8.       D. K. Pradhan and S. M. Reddy, “A fault-tolerant communication architecture for distributed systems,” IEEE Trans. Comput., vol. C-31, no. 9, pp. 863–870, Sep. 1982.





Shashiraj Teotia, Sohan Garg

Paper Title:

A Characteristic Study of Mobility Models Prediction Methods for MANETs

Abstract:    A Mobile Ad hoc Network (MANET)  is a collection of wireless mobile  nodes forming  a  network  without  using  any  existing  infrastructure.  All  mobile  nodes function as mobile routers that discover and maintain routes to other mobile nodes of the network and therefore, can be connected dynamically in an arbitrary manner. The mobility attribute of MANETs is a very significant one. The mobile nodes may follow different  mobility  patterns  that  may  affect  connectivity,  and   in  turn  protocol mechanisms and performance. Mobility prediction may positively affect the service- oriented aspects as well as the application-oriented aspects of ad hoc networking. At the network level, accurate node mobility prediction may be critical to tasks such as call admission control, reservation of network resources, pre-configuration of services and  QoS  provisioning.  At   the   application  level,  user  mobility prediction  in combination with user’s profile may provide the  user with enhanced location-based wireless  services,  such  as  route  guidance,  local  traffic  information  and  on-line advertising. In this chapter we present the most important mobility prediction schemes for  MANETs  in  the  literature,  focusing  on  their  main  design  principles  and characteristics.

   MANETs, Cluster, Clustering, Global Positioning System (GPS), Mobility Prediction, Network Scalability, Signal attenuationIntroduction


1.       Basu, P., Khan, N. & Little, T. (2001). A Mobility Based Metric for Clustering in Mobile  Ad  Hoc   Networks.  Proc.  of  the  21st  International  Conference  on Distributed Computing Systems Workshops (ICDCSW ’01), 413–418.
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4.       Camp T., Boleng, J. & Davies, V. (2002). A Survey of Mobility Models for Ad Hoc Network  Research.  Wireless  Communication  &  Mobile  Computing  (WCMC): Special issue on Mobile Ad Hoc Networking: Research, Trends, Applications. Vol.2(5), 483-502.

5.       Chellapa-Doss, R., Jennings, A. & Shenoy, N. (2003a). User Mobility Prediction in Hybrid         and          Ad           Hoc          Wireless Networks.  Proc.        of      the           Australian Telecommunications Networks and Applications Conference (ATNAC’03).

6.       Chellapa-Doss, R., Jennings, A. & Shenoy, N., (2003b). A Comparative Study of Mobility Prediction in Cellular and Ad Hoc Wireless Networks. Proc. of the IEEE Int’l Conf. on (ICC 2003). Alaska, 2003.

7.       Chellapa-Doss, R., Jennings, A. & Shenoy, N., (2004). A Review of Current Mobility Prediction   Techniques   for   Ad   Hoc   Networks.   Proc.   of   the   4th    IASTED International   Multi-Conference   on   Wireless   and   Optical   Communications, Canada, 536-542.

8.       Da Fontoura Costa L., Oliveira Jr O.N., Travieso, G., Rodrigues F.A.,, A.,, Villas Boas, P.R., Antiqueira, L., Viana, M.P. & da Rocha, C. (2007). Analyzing and Modeling   Real-World  Phenomena  with  Complex  Networks:  A  Survey  of Applications”, arXiv:0711.3199v1

9.       Dekar, L., & Kheddouci, H., (2008). A Cluster Based Mobility Prediction Scheme For Ad Hoc Networks”, Ad Hoc Networks Journal. Vol. 6(2), April 2008, Elsevier.

10.     Dempster, A.P. (1968).  A Generalization of Bayseian Inference. Journal of Royal Statistical Society, Vol. 30, 205-247.

11.     Eagle, N. & Pentland, A. (2006) Reality mining: sensing complex social systems.Personal and Ubiquitous Computing, 10(4).

12.     Er, I. & Seah, W., (2004). Mobility-based d-Hop Clustering Algorithm for Mobile Ad Hoc Networks. Proc. of the IEEE Wireless Communications and  Networking Conference (WCNC 2004), Vol. 4, 2359–2364.

13.     Er, I. & Seah, W. (2006). Performance analysis of mobility-based d-hop (MobDHop) clustering algorithm for mobile ad hoc networks. Computer Networks, Vol. 50, 3375-3399

14.     Erbas, F., Steuer J., Kyamakya, K., Eggesieker, D. & Jobmann K. (2001). A Regular Path  Recognition  Method  and  Prediction  of  User  Movements  in  Wireless Networks.  Proceedings of the Vehicular Technology Conference (VTC’ 2001), IEEE, 2672-2676.

15.     Gerla, M. & Tsai, J., (1995). Multicluster, Mobile, Multimedia Radio Network. ACM, Baltzer Journal of Wireless Network. Vol. 1(3), 255–265.

16.     Haas, Z.J. & Pearlman, M., (1999). The Zone Routing Protocol (ZRP) for Ad Hoc Networks. Internet Draft. June 1999.

17.     Jiang, S., He, D. & Rao, J., (2001). A Prediction-based Link Availability Estimation for Mobile Ad Hoc Networks. Proc. of IEEE INFOCOM 2001, 1745- 1752.

18.     Konstantopoulos,  C.,   Gavalas,  D.  &  Pantziou,  G.,  (2006).  A   Mobility Aware Technique  for  Clustering  on  Mobile  Ad-Hoc  Networks. Proc. International Conference on Distributed Computing and Networking ICDCN 2006), Springer Verlag, LNCS Vol. 4308, 397–408.

19.     Konstantopoulos, C., Gavalas, D. & Pantziou, G., (2008). Clustering in Mobile Ad- Hoc Networks through Neighbourhood  Stability-Based  Mobility Prediction. Computer Networks, Elsevier. In Press

20.     Lee, S-J., Su, W. & M. Gerla, (2001) “Wireless Ad Hoc Multicast Routing With Mobility Prediction”, Mobile Networks and Applications, Vol. 6, 351-360.

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23.     McDonald A.B. & Znabi, T.F., (1999b). A mobility-based framework for Adaptive clustering  in  wireless  ad  hoc  networks.  IEEE  Journal  of  Selected Areas  in Communications, 17(8), 1466-1487.

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25.     Palit, R., Hossain, E. & Thulasiraman, P. (2006). MAPLE: a Framework for  Mobility- Aware Pro-active Low Energy Clustering in Ad-hoc Mobile Wireless Networks.Wireless Communications and Mobile Computing, 6(6), 773–789.

26.     Saman, N. & Karmouch, A. (2005). A Mobility Prediction Architecture Based on Contextual  Knowledge  and  Spatial  Conceptual  Maps.  IEEE  Tansactions  on Mobile Computing. 4(6), 537-551.

27.     Schwartz, M. (2005).  Mobile  Wireless  Communications.  Cambridge   Univeristy Press. 28. Shafer, G., (1975). A Mathematical Theory of Evidence. Princeton University   Press.

29.     Sivavakeesar, S., Pavlou G. & Liotta, A. (2004). Stable Clustering Through Mobility Prediction  for  Large-Scale  Multihop  Ad  Hoc  Networks.  Proc.  of  the  IEEE Wireless Communications and Networking Conference (WCNC’2004).

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Sohrab Mirsaeidi, Mohammad Reza Miveh, Majid Gandomkar

Paper Title:

Evaluation of Dynamic Stability During a Symmetrical Three-Phase Short Circuit at Machine Terminals of Siah Bishe Pumped Storage Power Plant

Abstract:  This paper presents a survey on the research and applications of the pumped storage plants based on the published papers in trying to provide a suitable picture of the development of this electric load regulation approach. Moreover, the paper summaries two separate pumped storage power plants projects, one in America (Seneca) and another in Iran (Siah Bishe) from the following point of view:
•              The operation of power plant generator/motor during day and night             

•              Introduction of starting system in motors state

•              Technical, economic and environmental aspects of such power plant

•              Determination of system efficiency 

Since there are some experiences with Siah Bishe power plant project, the performances of the plant in dynamic stability improvement of the network following a symmetrical short circuit is analyzed. Based on the obtained results, it becomes clear that the plant can have great effect on the recovery of the network dynamic and transmitted energy between the synchronous machines installed in the plant and the network. High speed response is the most important factor which enhances the small signal stability of the system. This function of the plant can be critical in the fault events.

   Pumped Storage, Dynamic Stability, load regulation, Siah Bishe power plant.


1.        Hailun Huang, Zheng Yan, "Present Situation and Future Prospect of Hydropower in China", Journal ElSEVIER, 2009.
2.        J.P.fitzqerald, E.A.Cooper, F.P.Solomon, "Operation Of Seneca Pumped Storage Plant", IEEE Power Engineering, New York,1973.

3.        Specifications of Siah Bishe dams and pumped storage power plant project, Moshanir Company, Iran.

4.        Lay out plan of 400 kV Siah Bishe GIS substation, Moshanir Company, Iran.

5.        Plan of pumped storage power plant position in Iran power network, Tehran Electric Company, Iran.

6.        U.Karaagac, J.Mahseredjian, S.Dennetiere, "Modeling and Simulation of Startup of a Pumped Storage Power Plant Unit", Journal IEEE, 2009.

7.        Components plan of SFC excitation system, Moshanir Company, Iran   

8.        EIIisL.Armstrong, Ted W.Mermel, "Converting Existing Hydro-EIectric Dams and Reservoirs into PUMPED STORAGE", Franklin Pierce CoIIege Rindge.N.H, August 1974.

9.        M.T. Ameli, H Mehrouz, "The roal of  Siah Bishe pumped storage power plant in frequency control of Iran network", Abaspour university, Tehran, Iran.

10.     Reports of studies about Tehran 400 kV network, Tehran Dispatching Center, Iran, July-Aug. 2010.

11.     Sohrab Mirsaeidi, Mohammad Reza Miveh, Majid Gandomkar, Hosein Refahi, Arup Sinha, "Power System Load Regulation by Pumped Storage Power Plants", ICECT 2012, Kanyakumari, India, 2012.

12.     Siah Bishe Technical Data Sheets for the Four Generator-Motors, Section M-Lot4- Chapter1, (2007-11-30), Moshanir Company, Iran.

13.     Ong,Chee-Mun," Dynamic Simulation of Electric Machinery: Using MATLAB  /SIMULINK", 1998.

14.     M. Movahed, "Economic evalution  of  Siah Bishe pumped storage power plant",  Tavanir  Company, Iran.

15.     J.P.fitzqerald, E.A.Cooper, G.W.Groscup, " Synchronous Starting Of Seneca Pumped Storage Plant", IEEE, VOL. PAS-88, NO .4, April 1969.

16.     Supervisory inspection report of Siah Bishe dams and pumped storage power plant project, Budget supervision bureau, Iran, June-July 2008.   





Mohammad Reza Miveh , Sohrab Mirsaeidi

Paper Title:

Introduction and Evaluation of Teleprotection Systems in Micro-Grids

Abstract:    A micro-grid is an aggregation of electrical and heat loads and small capacity micro-sources operating as a single controllable unit at the low or medium voltage level. Nowadays, digital telecommunications have been used in many industrial applications which micro-grid protection has also been benefited. Occurred challenges in distribution network caused by micro-grids presence, telecommunication and distribution engineers failure in recognizing the protection schema requirements and telecommunication networks restrictions always have made problems in implementation and utilization of the protection schema. In this paper, in addition to introducing types of telecommunication technology and protection system, problems existed in applying the digital telecommunication network is also evaluated for protection purpose in micro-grids and some points which a schema should consider for teleprotection system to make improvement and dependability is also explained.

   Micro-grid, Protection, Teleprotection, Telecommunication.


1.       Nikkhajoei H, Lasseter R. H, “Micro-grid Fault Protection Based on Symmetrical and Differential Current Componsents”, Power System Engineering Research Center, 2006.
2.       European Smart Grid Technology Platform, Vision and Strategy for Europe’s Electricity Networks of the Future, EU Commission, Directorate-General for Research, Information and Communication Unit. Brussels, Belgium, 2006.

3.       C. Green and J. D. McDonald, “Modeling and analysis of fault behavior of inverter micro-grids to aid future fault detection,” in Proc. IEEE Int. Conf. Syst. Eng, pp. 1–6, 2007.

4.       Ming Sun, Juan Y, DENG B, “Analysis of Impact of DGs on Line Protection of Distribution Networks”, Power System Technology, vol, 33(8), pp, 104-107, 2009.

5.       Chao Y, Gang W, Xiang-Jun Z, “Protection technology for distributed generation systems”, Power System Protection and Control, Vol, 37(2), Jan, pp: 99-105, 2009.

6.       Shen L, “Reaserch of the protection of the distribution network with distributed generator”, Tianjin, Tianjin University, 2007.

7.       Zhong W, “Study on Relay Protection in Power Distribution Network with Distributed Generation”, Urumchi, Urumichi University, 2009.

8.       Lasseter R. H, “CERTS Micro-grid”, IEEE International Conference on System of Systems Engineering, April 16-18, 2007.

9.       Mohammad Reza Miveh, Mojtaba Nouri, Sohrab Mirsaeidi, Hossein Refahi and Arup Sinha, "Distributed Generation Placement to Maximize the Loadability of Distribution System Using Genetic Algorithm", ICECT, Kanyakumari, India, 2012.

10.     Conti S, Raiti S, “Integrated Protection Scheme to Coordinate MV Distribution Network Devices,DG Interface Protections and Micro-grid Operaion”, IEEE Clean Electrical Power, International Conference on, 2009, pp. 640-646, 2009.

11.     Anish Prasai, Yi Du, Andrew Paquette, Edward Buck, Ronald Harley, and Deepak Divan “Protection of Meshed Micro-grids with Communication Overlay”, IEEE International Conference on System of Systems Engineering, April 64-71, 2010.

12.     "IEEE Guide for Power-Line Carrier Applications," IEEE Std 643- 2004 (Revision of IEEE Std 643-1980), vol., no., pp.0_1-134, 2005.

13.     Atheros Communications. "White Paper - Powerline Communications Performance Testing," Accessed June 20, 2010, http://www.atheros.com/pt/plc/downloads/whitepaper_PLCPerformanceTesti ng.pdf.

14.     PRIME Alliance. “MAC Spec White Paper,” Accessed June 27, 2010, <http://www.prime-alliance.org/portals/0/specs/

15.     Ed Hare, "Power Lines as Antennas from 100 kHz to 50 MHz", July 2003, www.arrl.org.

16.     E. Sortomme, S. S. Venkata, and J. Mitra, "Micro-grid Protection Using Communication-Assisted Digital Relays," IEEE Transactions on Power Delivery, 2010.

17.     R. Moxley and K. Fodero, “High-Speed Distribution Protection Made Easy: Communications-Assisted Protection Schemes for Distribution Applications,” Proceedings of the 31st Annual Western Protective Relay Conference, Spokane, WA, October 2004.

18.     Yongli Li, Zhiqian Bo, Klimek, A.  “Design of protection and control scheme for micro-grid systems”, IEEE International Conference on System of Systems Engineering, Universities Power Engineering Conference (UPEC) 1-4 Sept. 2009, 2009.

19.     M.R. Miveh, M. Gandomkar, S. Mirsaeidi, H. Nasiban, “Micro- Grid Protection by Designing a Communication-Assisted Digital

20.     Relay”, American Journal of Scientific Research, Isuue 51, Feb.

21.     2012, pp. 62-68.

22.     Cigre, WG D2.26, “Telecommunication Service Provisioning and Delivery in the Electrical Power Utility”, TB-461, April 2011.

23.     Chao Y, “Novel Protecion Methods of Distributed Generation System”, Changsha, Changsha University of Science & Technology, 2009.

24.     Xia L, Yu-ping L, Lian-he W, “New Fault Region Location Scheme in Distribution System With DGs”, Transactions of China Electro Technical Society, vol. 23(11), Nov, pp. 139-145, 2008.

25.     Xia L, Yu-ping L, Lian-he W, “New Current Protection Scheme Considering Distributed Generation Impact”, Automation of Electric Power Systems, vol. 32(20), Oct, pp.50-56, 2008.





N.P. Zinjad, S. S. More

Paper Title:

Energy Efficiency in Data Centers: How to Reduce Power Consumption in Data Centers by Optimum UPS Loading

Abstract:    Computation and data center has a huge value to modern enterprise. This has resulted in the installation of millions of data centers in business around the globe. Historically, the cost to power and cool these facilities was small relative to the investment in servers, storage units and other equipments. Today, however, the annual power and cooling costs of typical data centers are almost equal to the cost of hardware. In the past decade, India has witnessed an exponential increase in the demand for digital storage, from 1 petabyte in 2001 to more than 34 petabytes by 2007. They also continue to grow at a compounded rate of 25-30%. Datacenter growth is basically driven by increasing requirements from the sectors such as financial institutions, telecom operators, manufacturing and services. While large financial institutions and telecom companies are likely to build captive Datacenters for hosting their growing data storage needs. Datacenter service providers are expected to invest significantly to multiply their capacities, so as to fulfill the demand arising from small and midsize users. Datacenter is highly energy intensive. With the increasing energy cost, the increase in operational cost is inevitable. Therefore it becomes necessary to reduce the energy consumption to offset the increasing operational cost and to maintain competitiveness. Existing Datacenters need to adopt the best practices in design, operation and maintenance to achieve operational excellence. The increasing IT business process outsource from foreign countries has resulted in phenomenal growth of Datacenters in India. The total datacenter capacity in India is growing at a rapid pace and is expected to exceed 5.1 million square feet by 2012. The primary scope of this paper is to provide a framework in which data centers, large and small, could analyze and reduce their power consumption. This paper provides a quantitative approach to understanding energy efficiency within a server and within a data center. A panorama for power minimization and energy efficiency beginning with the basics of dual in line memory modules (DIMM) selection, configuring processors with reduced power states, options for constantly spinning disks, power management features in operating systems and other internal equipments.

   Loading optimization, Harmonics, Flywheel plus converter, Loading, Efficiency, Five “nines”, MTTF, MTBR, MTBF.


1. Datacenter book; Publisher: BEE India
2. Energy Efficiency in Data Centers; Publisher: Intel

3. www.leonardo energy.com

4. APC journals

5. www.schneider electricals.com

6. www.cockvalley.com

7. Configuring your UPS; Publisher: EAMS





M.Siva Sathyanarayana, J.Amarnath

Paper Title:

Modelling and Analysis of Trajectories of A Wire Like Particle in A Three Phase Common Enclosure Gas Insulated Busduct (GIB) With Image Charges

Abstract:   Metallic particle contamination in a compressed Gas Insulated Busduct (GIB) system may substantially lower the corona onset and breakdown voltages of the system. The random movement of metallic particles in a GIB system plays a crucial role in determining the insulation performance of the system. In this study a statistical approach has been used to evaluate the probability of SF6 insulation breakdown due to the presence of contaminating metallic particles. Under 50-Hz AC voltage, the particle motion is complex, and under appropriate conditions, the particle may cross the gaseous gap from the low-field region near the outer enclosure to the high-field region near the central conductor. For the commonly encountered size of metallic particles in practical Gas Insulated systems, such a crossing of the gaseous gap takes several cycles of the 50-Hz voltage. In order to determine the particle trajectories in a three-phase common enclosure Gas Insulated Bus duct (GIB) an outer enclosure of diameter 500 mm and inner conductors of diameters 64 mm spaced equilaterally are considered. Wire like particles of aluminum and copper has been considered to be present on enclosure surface of a three-phase bus duct. A method based on particle movement is proposed to determine the particle trajectory in Gas Insulated Substation (GIS) or Gas Insulated Busduct (GIB) for a three phase common enclosure while the image charge effects of the conductors are considered. The motion of the wire particle was simulated using the charge acquired by the particles, the macroscopic field at the particle site, the drag coefficient, Reynold’s number and coefficient of restitution. The computation of particle movement has been carried out on bare electrode system for different voltages. The results have been presented and analyzed.



1.        CIG& Working Group 15.03, “Effects of Particles on GIS Insulation and the Evaluation of Relevant Diagnostic Tools,” CIGRE 1994 Session, August 28-September 3, 1994.
2.        N-J. Ftlici, “Forces et charges de petits objets en contact avec une tlectrode affectke d’un champ Clectrique,”Revue GCnCrale de L‘tlectricitt, pp. 1145-1160, Octobre 1966.

3.        A.H. Cookson, R.E. Wotton, “Movement of Filamentary Conducting Particles Under AC Voltages in High Pressure Gases,” International

4.        Symposium Hochspannungstechnik Zurich, 1975.

5.        M.E. Holmberg, M.L-A. Sjoberg, A.E. Vlasths, “Identification of Metallic Particles in GIS by Statistical Analysis of Acoustical Measurements and Computer Simulations,” 9th International Symposium on High Voltage Engineering, Graz, Austria, August 1995.

6.        Westinghouse Research and Development Center, “Investigation of High Voltage Particle-Initiated Breakdown in Gas Insulated Systems,” EPFU Project 7835 Report, Pittsburgh, Pennsylvania, March 1979.

7.        F.A.M. Rizk, C. Masetti, R.E Comsa, “Particle-Initiated Breakdown in SF6 Insulated Systems under High Direct Voltage,” IEEE Transactions on Power Apparatus and Systems, Vol. PAS-98, No. 3, May/June 1979.

8.        M. Wohlmuth, “Measurement and Calculation of Lift-off Fields and Charges for Free Moving Particles,” 10 Int. Conf. on GD, Swansea, pp. 414, 1992.

9.        H.D. Schlemper, K. Feser, “Estimation of Mass and Length of Moving Particles in GIS by Combined Acoustical and Electrical PD Detection,” Conference on Electrical Insulation and Dielectric Phenomena (CEIDP), San Francisco, CA, USA, October 1996.





C.A. Chidolue, C.H. Aginam

Paper Title:

Effect of Shape Factor on the Flexural-Torsional-Distortional Behaviour of Thin- Walled Box Girder Structures

Abstract:    The governing differential equations of equilibrium for flexural-torsional-distortional analysis of thin-walled box girder structures with various shapes were derived in this work using V. Z. Vlasov’s theory. The obtained equations were used to evaluate the cross sectional deformations of some box girder structures having rectangular (doubly symmetric) and trapezoidal (mono symmetric) shapes. Evaluation of Vlasov’s coefficients for the obtained differential equations of equilibrium formed a major part of this work. This was accomplished by examining the strain modes interaction diagrams for the various cross sections and by using Morh’s integral chart for displacement computations. Cross sectional deformations of the box girder structures were obtained by integration of the differential equations of equilibrium using method of trigonometric series with accelerated convergence.   For irregular (asymmetric) box girder shapes, complex differential equations of equilibrium were obtained as a result of the interaction between all the strain modes of flexure, torsion and distortion. Application of these set of equations for the analysis of irregular shaped box girder structures is presented in another work.

   Box structure, distortion, flexure, shape factor, thin-walled, torsion


1.        V.Z.Vlasov,  Thin-walled space structures (Gosstrojizdat, Moscow, 1958).
2.        C.A. Chidolue, Torsional-distortional analysis of thin-walled box girder bridges using Vlasov’s theory, Ph.D. thesis, University of Nigeria, Nsukka, 2012.

3.        Y.T. Hsu, C.C. Fu and D.R. Shelling,  EBEF method for distortional analysis of steel box girder bridges, Journal of Structural Engineering, 121(3) 1995, 557-566

4.        Z. Fan, and T.A. Helwig, Distortional loads and brace forces in steel box girders, Journal of. Structural Engineering, 128(6), 2002, 710-718.

5.        K.M. Sennah, and J.B. Kennedy, Literature review in analysis of box girder bridges, Journal of Bridge Engineering, 7 (2), 2002, 134-140.

6.        A.M. Okeil, and S. El-Tawil, Warping stresses in curved box girder bridges: case study, Journal of Bridge Engineering, 9(5) , 2004, 487- 496.

7.        J. Paavola,  Study of curved Thin-Walled Girders, doctoral diss., Helsinki University of Technology, Espoo, Finland, PhD, 1990.

8.        A.G. Razaqpur, and H.G. Li, Analysis of multi-branch multi-cell box girder bridges, Proc.3rd Int. Conf. on Short and Medium Span Bridges, Toronto, 1990, 153-164 

9.        C.C. Fu, and Y.T. Hsu, The Development of an Improved Curvilinear Thin-Walled Vlasov Element, Computational Structures Journal, 54(1),  1995, 147-159.

10.     A. Tesar,  Shear Lag in the Behaviour of Thin-Walled Box Bridges, Comput. Struct. Journal, 59(4),  1996, 607-612.

11.     N.N. Osadebe and C.A. Chidolue, Torsional-distorsional response of thin-walled mono symmetric box girder structures, International journal of engineering research and applications, 2 (3),  2012, 814-821

12.     N.N. Osadebe and C.A. Chidolue, Response of double cell mono symmetric box girder structure to torsional-distortional deformations, Intrnational journal of engineering and advanced technology, 1 (4),  2012, 285-292.

13.     Ezeh J.C., Buckling behaviour of axially compressed multi cell doubly symmetric thin-walled column using Vlasov’s theory, International journal of engineering, 4 (2), 2010, 179-194  

14.     C.P. Varbanov, Theory of elasticity (Technika Press Sofia, 4th Edition, 1976).

15.     L. Elsgolt, Differential Equations and the Calculus of Variation,  (MIR publishers, Mosco,1980, translated from the Russian by George Yankovsky.)

16.     American Association of State Highway and Transportation Officials (AASHTO),      Load and Resistance Factor Design,  LRFD, Bridge Design Specifications Washington , D.C, 1998.

17.     C.A. Chidolue and N.N. Osadebe, Flexural-torsional behaviour  of thin-walled mono symmetric box girder structures, International Journal of Engineering Sciences and Emerging Technologies, 2 (2), 2012, 11-19

18.     N.N.Osadebe and C.A. Chidolue, Flexural-distortional behaviour of thin-walled mono symmetric box girder structure, International Journal of Engineering Research and Technology, to be published.





Sudhanshu Shekhar

Paper Title:

Online Non Destructive Evaluation of Large Pipe Lines and Cylindrical Structures Using Guided Ultrasonic Wave Diffraction Tomography

Abstract:    This Research work evaluates the ability of ultrasonic guided waves to detect several types of defects in cylindrical structures with different pre-selected wave modes. It will also demonstrate ultrasonic guided wave method [1& 2]  as an alternative to standard ultrasonic techniques and how to address their deficiencies. This approach is based on the use of ultrasonic guided waves. In this work the use of ultrasonic guided waves for thickness mapping of large, partially accessible areas was investigated.  The problem of interest is to evaluate the minimum remaining plate thickness over a large area. Guided waves [3 & 4] have multiple properties that can be used for thickness mapping over large areas. Firstly, the dispersive nature and variation of the phase velocity as a function of the frequency thickness product of guided waves [5 &6] make them potentially suitable for thickness mapping by time-of-flight tomography and diffraction tomography based on the variation of the velocity in the in homogeneities [7] . The experimental result was validated with FE (Finite Element) profile to arrive at the conclusion. Diffraction tomography can reconstruct a map of the velocity from the scattered field produced by the interaction of an incoming wave field and a velocity in homogeneity. It has been shown that Diffraction tomography with low frequency guided waves can be used for thickness reconstruction of plates or large diameter pipes. Low frequency guided waves can be used for thickness reconstruction of plates or large diameter pipes. It has been shown that the scattering from the array of transducers needs to be minimized in order to reconstruct thickness accurately.  However when the scattering from the array of transducers is large it is possible to use guided wave diffraction tomography in a structural health monitoring approach and obtain accurate thickness reconstruction.

   Cylindrical Structures, Frequency


1.        J L Rose, Ultrasonic waves in solid media, Cambridge University Press, 1999.
2.        J Krautkramer , Ultrasonic testing of materials, 1969 edition, Springer.

3.        F Cegla, Ultrasonic crack monitoring using guided waves in extreme inaccessible environments, Proceedings of 17 th World conference on Nondestructive Testing, 2008, p 245 – 249.

4.        J L Rose, Recent advances in Guided waves Non Destructive Evaluation, Ultrasonic symposium, 2009, p 761 – 770. 

5.        R P Dalton, P Cawly and MJS Lowe, Potential of guided waves for monitoring large areas of metallic aircraft fuselage structure, Journal of NDE, 2009, 20(1), p 29 – 46.

6.        L.M. Brekhovskikh.  Waves in layered media. Academic Press, 1980.

7.        W. Zhu, J.L. Rose, J.N. Barshinger, and V.S. Agarwala.  Ultrasonic  guided wave ndt for hidden corrosion detection.  Research in Nondestructive  Evaluation, 10:205–225, 1998.

8.        Geir Instanes, Lakshminarayan  Balachander,  Mads Toppe, and P. B. Nagy. The use of non-intrusive ultrasonic intelligent  sensors for corrosion and erosion monitoring.  In Offshore Europe  2005, Aberdeen, 2005. Society  of Petroleum Engineers.

9.        P. Wilcox, M. J. S. Lowe, and P. Cawley. Mode and transducer selection for long range lamb wave inspection. Journal of Intelligent Material  Systems and Structures, 12(8):553–65, 2001.

10.     F. E. Ernst and G. C. Herman. Tomography of dispersive media. Journal of the Acoustical Society of America, 108(1):105–16, 2000.

11.     J. Spetzler and R. Snieder. The effect of small-scale heterogeneity on the arrival time of waves. Geophysical Journal International, 145(3):786–96, 2001.

12.     D.W. Vasco,  J.E. Peterson,  and E.L. Majer.  Beyond ray tomography: Wavepaths and fresnel volumes. Geophysics, 60(6):1790–1804, 1995.

13.     W. Menke and D. Abbott. Geophysical Theory.  Columbia University Press, 1990.

14.     A. Kak and M. Slaney. Principles of Computerized Tomography Imaging. IEEE Press, 1988.

15.     A.H. Rohde, M. Veidt, L.R.F. Rose, and J. Homer.  A computer simulation study of imaging flexural inhomogeneities using plate-wave diffraction tomog- raphy. Ultrasonics, 48:6–15, 2008.

16.     V. C  Erveny. Seismic Ray Theory. Cambridge Univeristy  Press, 2001.

17.     P. P. Ewald. Introduction to the dynamical theory of X-ray diffraction. Acta Crystallographica  Section A, 25(1):103–108, 1969.

18.     M. Drozdz, L. Moreau, M. Castaings, M.J.S. Lowe, and P. Cawley. Efficient nu- merical modelling of absorbing regions for boundaries of guided waves problems. In D. Chimenti and D. Thompson, editors, Review of Progress in Quantitative Nondestructive Evaluation,  volume 25, pages 126–133, Brunswick,  ME, USA, 2006. AIP.

19.     M. Drozdz, E. Skelton, R.V. Craster, and M.J.S. Lowe.  Modeling bulk and guided waves in unbounded elastic media using absorbing layers in commercial finite element packages. In D. Chimenti and D. Thompson, editors, Review of Progress in Quantitative Nondestructive Evaluation,  volume 26, pages 87–94, Portland, OR, USA,  2007. AIP.

20.     H. Gao, S. M. Ali, and B. Lopez, “ Efficient detection of delamination in multilayered structures using ultrasonic guided wave EMATs” in NDT&E International Vol. 43 June 2010, pp: 316-322.

21.     Gao, H., and B. Lopez, "Development of Single-Channel and Phased Array EMATs for Austenitic Weld Inspection", Materials Evaluation (ME), Vol. 68(7), 821-827,(2010).





Pragati Priyadarshinee, Pragya Jain

Paper Title:

Load Balancing and Parallelism in Cloud Computing

Abstract:    Large-scale heterogeneous distributed computing environments (such as Computational Grids and Clouds) offer the promise of access to a vast amount of computing resources at a relatively low cost. In order to ease the application development and deployment on such complex environments, high-level parallel programming languages exist that need to be supported by sophisticated runtime systems. The anticipated uptake of Cloud computing, built on well-established research in Web Services, networks, utility computing, distributed computing and virtualization, will bring many advantages in cost, flexibility and availability for service users. These benefits are expected to further drive the demand for Cloud services, increasing both the Cloud’s customer base and the scale of Cloud installations. This has implications for many technical issues in Service Oriented Architectures and Internet of Services (IoS)-type applications; including fault tolerance, high availability and scalability. Central to these issues is the establishment of effective load balancing techniques. It is clear the scale and complexity of these systems makes centralized assignment of jobs to specific servers infeasible; requiring an effective distributed solution.

   Load Balancing,Parallelism,SOA, Virtualization.


1.        Anthony T.Velte, Toby J.Velte, Robert Elsenpeter, Cloud Computing A Practical Approach TATA McGRAW-HILL Edition 2010.
2.        Martin Randles, David Lamb, A. Taleb-Bendiab, A Comparative Study into Distributed Load Balancing Algorithms for Cloud Computing, 2010 IEEE 24th International Conference on Advanced Information Networking and Applications Workshops.

3.        Mladen A. Vouk, Cloud Computing Issues, Research and Implementations, Proceedings of the ITI 2008 30th Int. Conf. on Information Technology Interfaces, 2008, June 23-26.

4.        Ali M. Alakeel, A Guide to Dynamic Load Balancing in Distributed Computer Systems, IJCSNS International Journal of Computer Science and Network Security, VOL.10 No.6, June 2010.

5.        http://www-03.ibm.com/press/us/en/pressrelease/22613.wss

6.        http://www.amazon.com/gp/browse.html?node=201590011

7.        Martin Randles, Enas Odat, David Lamb, Osama Abu- Rahmeh and A. Taleb-Bendiab, ”A Comparative Experiment in Distributed Load Balancing”, 2009 Second International Conference on Developments in eSystems Engineering.

8.        Peter S. Pacheco,”Parallel Programming with MPI”, Morgan Kaufmann Publishers Edition 2008

9.        Mequanint Moges, Thomas G.Robertazzi, ”Wireless Sensor Networks: Scheduling for Measurement and Data Reporting”, August 31, 2005





Jamuna.M,  A.M.Vijaya Prakash, J.Pushpanjali

Paper Title:

Low Power VLSI Architecture for Image Compression System Using Discrete Wavelet Transform

Abstract:    Image compression has got applications in many fields like digital video, video conferencing and video over wireless networks and internet etc. This paper deals with the implementation of VLSI Architecture of image compression system using low power DWT (Discrete Wavelet Transform). DWT is the most widely used image compression technique and it is the most efficient algorithm used in JPEG image compression. This paper presents implementation of 2 methods of DWT, one is conventional method and the other one is lifting scheme. Since conventional method requires more memory, area and power, lifting scheme is used as an enhanced method.  Architecture of the DWT which is a powerful image compression algorithm is implemented using lifting based approach. This architecture enjoys reduced memory referencing¸ related low power consumption¸ low latency and high throughput. The Inverse Discrete Wavelet Transform (IDWT) is also obtained in a similar way to get back the image matrix. The design is implemented in verilog HDL. ISIM is used for the simulation of the design. MATLAB is used as a support for the design for obtaining the input pixels and comparison of the results. CADENCE RTL compiler is used to synthesize and obtain the detailed power and area of the design.

   Discrete Wavelet Transform (DWT), Inverse Discrete Wavelet Transform (IDWT), Digital filters.


1.        “VLSI Implementation of Discrete Wavelet Transform (DWT) for Image Compression” by Abdullah AlMuhit, Md. Shabiul Islam and Masuri Othman.
2.        Chin Fa Hsieh, Tsung Han Tsai, Neng Jye Hsu,Chin Hung Lai, “A Novel, Efficient Architecture for the 1D, Lifting Based DWT with Folded and Pipelined Schemes” .

3.        Chung- Hsien Yang, Jia-Ching Wang,”A Block Based Architecture for Lifting Scheme Discrete Wavelet Transform,”IEICE Transactions on fundamentals Electronics and Communication and Computer Sciences, 2007, vol. E90-A(5), p.p.1062-1071.

4.        A. Bruce, D. Donoho, and H.-Y. Gao, “Wavelet analysis,” IEEE Spectr.,vol. 33, pp. 26-35, Oct. 1996.

5.        Feng Hui, Guo Lanying, Xiao Jinsheng,”The Lifting Scheme Based on the Second Generation Wavelets,” Wuhan University Journal of Natural Sciences, vol.11, no.3, May2006, p.p.503-506.

6.        Ping-Sing Tsai, Tinku Acharya, “Image Upsampling Using Discrete Wavelet Transform”, Proceedings of the Joint Conference on Information Sciences 2006, October2006 on VLSI Systems, vol. l(2). pp. 181-202, June 1883.

7.        T.J.Heaton, B.W. Silverman,”A wavelet or Lifting Scheme based imputation method, journal of the Royal Statistical Society: Series B(Statistical Methodology), vol.70, 2008, p.p.567-587.

8.        M. Vishwanath, R.M. Owens, and M.J. Irwin, “Discrete wavelet transforms in VLSI,” in Proc. Int. Conf. Application Specific Array Processors, Berkeley, CA, 1-2 Aug. 1992, pp. 218-229.

9.        J. Limqueco and M. Bayoumi, “A VLSI architecture for separable 2-D discrete wavelet transform,” J. VLSI Signal Processing, vol. 18, pp. 125-140, 1998.





Vijaykumar, R K Karunavathi, Vijay Prakash

Paper Title:

Design of Low Power Double Data Rate 3 Memory Controller with AXI compliant

Abstract:    As system bandwidths continue to increase, memory technologies have been optimized for higher speeds and performance. The next generation family of Double Data Rate (DDR)RAMs are DDR3 RAM. DDR3 RAMs offer numerous advantages compared to DDR2. These devices are lower power, they operate at higher speeds, offer higher performance (2x the bandwidth), and come in larger densities. DDR3 memory devices provide a 30% reduction in power consumption compared to DDR2, primarily due to smaller die sizes and the lower supply voltage (1.5V for DDR3 vs. 1.8V for DDR2). This paper represents the overall design and architecture of Low power Double Data rate 3(DDR3) memory controller. In this paper clock gating is used as a low power technique .

   DDR3 memory devices provide a 30% reduction in power consumption compared to DDR2, primarily due to smaller die sizes and the lower supply voltage (1.5V for DDR3 vs. 1.8V for DDR2).


1.        A High Performance DDR3 SDRAM Controller.  International Journal of Electrical and Electronics Engineering (IJEEE),Volume-1,Issue-1,2011.
2.        H. Song et al, “A 1.2 Gbs/pin double data rate SDRAM with on die-termination”, in IEEE Int. Solid-State Circuits Conf. (ISSCC) Dig. Tech. Papers, 2003, pp. 31

3.        “High-Performance DDR3 SDRAM Interface in Virtex-5Devices”, Xilinx, XAPP867 (v1.0), Sept 24, 2007.
4.        DDR3 SDRAM Specification (JESD79-3A), JEDEC Standard, JEDEC Solid State Technology Association, Sept. 2007.
5.        http://micron.com/parts/dram/ddr3-sdram/~/media/Documents/Products/Data%20Sheet/DRAM/4242Gb_DDR3_SDRAM.ashx

6.        Implementation of AXI Design Core with DDR3 Memory Controller for SoC. IJCST Vol. 2, Iss ue 4, Oct . - Dec. 2011.

7.        www.altera.com/literature/ug/ug_altmemphy.pdf, External DDR Memory PHY Interface Megafunction User Guide (ALTMEMPHY), accessed on 23 Feb. 2009

8.        Implementing High-Speed DDR3 Memory Controllers in a Mid-Range FPGA  A Lattice Semiconductor White Paper  March 2010 http://www.latticesemi.com/documents/WP-ImplementingDDR3.pdf





Pankaj Kumar Srivastava, T. R. Sontakke

Paper Title:

Performance of Cooperative Spectrum Sharing and Dynamic Sensing Strategies for Efficient Spectrum Utilization in Cognitive Radio

Abstract:    Due to crowd in the spectrum, interference protection is guaranteed through policy spectrum licensing. Cognitive radio and mesh network can facilitate spectrum sharing that improves spectral efficiency, provided spectrum policies are in place that supports these forms of sharing. This paper discusses the enhancement of Cognitive Radio which enable all the parameter. Cognitive Radios have been receiving increasing attention in academia, industry, and government. This has come after several studies indicating that up to 90% of the allocated radio spectrum less than 3GHz is idle most of the time. As a result, spectrum regulation around the world is in progress to allow unlicensed access on a non-interfering. Current researches are investigating different techniques of using cognitive radio to reuse more locally unused spectrums to increase the total system capacity. In this paper we address more spectrums sensing, protocol, hardware, measurement methodology, security and algorithmic challenges that could limit their performance or even make them infeasible. We also give some insight into the evolution of cognitive radios and characteristics. We conclude highlighting open research challenges in this exciting area.

   component: Cognitive radio, Spectrum sensing, Dynamic spectrum access, Multi-dimensional spectrum sensing, Cooperative sensing, Radio identification.


1.        Akyildiz IF, Lee WY, Vuran MC, Mohanty S. A survey on spectrum management in cognitive radio networks. IEEE Communications Magazine 2008; 46(4):4048.
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3.        Federal Communications Commission, “Notice of proposed rule making and order: Facilitating opportunities for flexible, efficient, and reliable spectrum use
employing cognitive radio technologies,” ET Docket No. 03-108, Feb. 2005.

4.        J. O. Neel, “Analysis and design of cognitive radio networks and distributed radio resource management algorithms,” Ph.D. dissertation,Virginia Polytechnic Institute and State University, Sept. 2006.

5.        J. Andrews, “Interference cancellation for cellular systems: a contemporary overview,” IEEE Wireless Commun. Mag., vol. 12, no. 2, pp.19–29, 2005.

6.        Matheson RJ. Strategies for spectrum usage measurements. Proceedings of the IEEE International Symposium on electromagnetic Compatibility(EMC 1988), 1988; 235–241.

7.        Ellingson SW. Spectral occupancy at VHF: implications for frequency-agile cognitive radios. Proceedings of the IEEE 62nd VehicularTechnology Conference (VTC 2005 Fall), Vol. 2, 2005; 1379–1382.

8.        Sanders FH. Broadband spectrum surveys in Denver, CO, San Diego,CA, and Los Angeles, CA: methodology, analysis, and comparative results. Proceedings of IEEE International Symposium on Electromagnetic Compatibility (EMC 1998), Vol. 2, 1998; 988–993.

9.        Petrin A, Steffes PG. Analysis and comparison of spectrum measurements performed in urban and rural areas to determine the total amount of spectrum usage. Proceedings of the International Symposium on Advanced Radio Technologies (ISART 2005), 2005; 9–12.

10.     L´opez-Ben´ıtez M, Umbert A, Casadevall F. Evaluation of spectrum occupancy in Spain for cognitive radio applications. Proceedings of the IEEE 69th Vehicular Technology Conference (VTC 2009 Spring),2009; 1–5.

11.     L´opez-Ben´ıtez M, Casadevall F, Umbert A, et al. Spectral occupation measurements and blind standard recognition sensor for cognitive radio networks. Proceedings of the 4th International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2009), 2009; 1–9.

12.     McHenry MA, Tenhula PA, McCloskey D, Roberson DA, Hood CS.Chicago spectrum occupancy measurements & analysis and a long term studies proposal. Proceedings of the 1st International Workshop on Technology and Policy for Accessing Spectrum (TAPAS 2006), 2006; 1–12.

13.     Bacchus RB, Fertner AJ, Hood CS, Roberson DA. Long-term, wideband spectral monitoring in support of dynamic spectrum access networks at the IIT spectrum observatory. Proceedings of the 3rd IEEE Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN 2008), 2008; 1–10.

14.     Y¨ucekT, Arslan H.Asurvey of spectrum sensing algorithms for cognitive radio applications. IEEE Communications Surveys and Tutorials 2009; 11(1):116–130.

15.     Ariananda DD, Lakshmanan MK, Nikookar H. A survey on spectrum sensing techniques for cognitive radio. Proceedings of the Second International Workshop on Cognitive Radio and Advanced Spectrum Management (CogART 2009), 2009; 74–79.

16.     Jones SD, Jung E, Liu X, Merheb N, Wang IJ. Characterization of spectrum activities in the U.S. public safety band for opportunistic spectrum access. Proceedings of the 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks (DySPAN2007), 2007; 137–146.

17.     Islam MH, Koh CL, Oh SW, et al.. Spectrum survey in Singapore:Occupancy measurements and analyses. Proceedings of the 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2008), 2008; 1–7.

18.     Radiocommunications Bureau. Handbook on spectrum monitoring.International Telecommunication Union (ITU), 2002.

19.     Otsu N. A threshold selection method from gray-level histograms IEEE Transactions on Systems, Man, and Cybernetics 1979; 9(1):62–66.

20.     Datla D, Wyglinski AM, Minden GJ. A spectrum surveying framework for dynamic spectrum access networks. IEEE Transactions onVehicular Technology 2009; 58(8):4158–4168.

21.     G.Dimitrakopoulos, P.Demestichas, D.Grandblaise, K. J.Hoffmeyer, J.Luo, “Cognitive Radio, Spectrum and Radio Resource Management”, Wireless World Research Forum, 2004.

22.     R.W. Brodersen, A. Wolisz, D. Cabric, S.M. Mishra, D. Willkomm, “Corvus: a cognitive radio approach for usage of virtual unlicensed spectrum”, Berkeley Wireless Research Center (BWRC) White paper, 2004

23.     Nie Nie, Cristina Comaniciu,”Adaptive Channel Allocation Spectrum Etiquette for Cognitive Radio Networks” Springer Science Business Media, 2006

24.     Raul Etkin, Abhay K. Parekh, David Tse, “Spectrum Sharing for Unlicensed Bands,” IEEE Journal on Selected Areas in Communications, vol. 25, pp. 517–528, April 2007.

25.     A.Shukla, P.Hall, J.Bradford, D.Chandler, M.Kennett, P.Levine, A.Alptekin,” Cognitive Radio”, NETIQ/06/00420 Issue 1.1, November 2006.

26.     Kwang-Cheng Chen, Irving T. Ho,” Cognitive Radio Networks”, CTiF Workshop 2007.

27.     William Krenik, Anuj Batra, “Cognitive Radio Techniques for Wide Area Networks”, ACM, Anaheim, California, USA, June 2005

28.     Joe Evans, U. Kansas, Gary Minden, U. Kansas Ed Knightly, Rice,”Technical Document on Cognitive Radio Networks “, September 15, 2006.

29.     Dipankar Raychaudhuri , Narayan B. Mandayam, Joseph B. Evans, Benjamin J. Ewy, Srinivasan Seshan, Peter Steenkiste ,”CogNet - An

30.     Architectural Foundation for Experimental Cognitive Radio Networks within the Future Internet”, MobiArch’06, San Francisco, CA, USA. December 1, 2006

31.     IMEC research group,” Cross-layer performance-energy modeling and optimization for wireless multimedia systems”, scientific report 2006.

32.     Mark Scoville, Stephen Berger, Richard C. Reinhart, Jeffrey E. Smith,” The Software -Defined Radio and Cognitive Radio Inter-Consortia Affiliation”, Military Communications Conference (MILCOM), Washington, USA, 2006.253.

33.     N. Devroye, P. Mitran, and V. Tarokh, “ Achievable Rates in Cognitive Channels”, IEEE Trans. IT, vol. 52, no. 5, pp. 1813-1827, May 2006

34.     A. Jovicic and P. Viswanath, “Cognitive Radio: An Information-Theoretic Perspective”, submitted to IEEE Transactions on information Theory,Apr. 2006.

35.     Majed. Haddad, Aawatif. Menouni Hayar and Merouane Debbah, “On Achievable Performance of Cognitive Radio Systems,” submitted to IEEE Journal on Selected Areas in Communications Cognitive Radio: Theory and Applications.

36.     T. M. Cover and J. A. Thomas, Elements of Information Thoery, Wiley,1991.





Archana Paranjpe, Abhay Kumar Sharma, R.K.Ranjan, V.K.Bajpai, Vishal Paranjape V

Paper Title:

MSW A Potential Energy Resources: A Two Stage Anaerobic Digestion

Abstract:    Present investigation reveals the biodegradability of municipal solid wastes (MSW) in context of Jabalpur city (1) (at 23˚10ˈNorth latitude and 79˚57ˈ East longitude, at an altitude of 393 meters above mean sea level) and harnessing energy through two stage anaerobic digestion. A critical study of various process parameters affecting the anaerobic digestion has been analyzed. During the anaerobic digestion of MSW it has been seen that the retention time of the process increases as compared to other waste such as fruits and vegetable waste, cow dung, agricultural residues etc. With the use of suitable bio-methanization technology the twin objectives (a) waste reduction and (b) the environmental problems can be achieved. The present work will help all academicians, rural and urban energy industry people in generating eco-friendly energy and maintaining environment too. In this study the biodegradability of the MSW organic fraction has been tested and in particular a comparison between the production of biogas from landfills and organic wastes in anaerobic conditions has been performed. Two stage digestion of this kind of wastes were proved a better efficiency than single stage digestion.

   bio-methanization, MSW, biogas, two stage anaerobic digestion.


1.        Jabalpur population census 2011 ,Jabalpur (M.P.).
2.        Chalmin P. and Gaillochet C. (2009). From waste to resource, an abstract of world waste survey,  Cyclopes, Veolia Environmental Services, Edition Economical, France.

3.        A report from Pike Research March 23, 2012.

4.        A report from Aug 29, 2011 sustainable solid waste management in India, Earth Engineering centre  (EEC)  Waste     to  Energy Research and Technology Council (WTERT) Columbia University Aug 29, 2011.

5.        Alvarez, J., Mace, S. and Llabres, P. 2000.” Anaerobic digestion of organic solid wastes”. An  overview of research       achievements and perspectives. Bioresource Technology (74): 3-16.

6.        Channakya, H. N., Jagadish.K.S, and Rajabapaiah, P., 2002. “Biogas plants: Towards a green and  organic future”.  Rural Technology- A 25 year Perspective, Silver jubilee Proc. Volume 2. Technical  Report:  “ Environmental Audit of Municipal Solid Waste Management”.

7.        Srinivas, S. V., 2003. “Energy from Municipal and Industrial Wastes.”  Department of Chemical  engineering, Indian   Institute of Madras, Chennai. Waste Management and Research ,IS ,PP-255-266.

8.        Poland, F.G.and Ghosh, S. 1971. Development in anaerobic stabilization of organic wastes-The two  phase concept. Evn. Letter 1:255-266.

9.        Ghosh, S., Conrad, J.R. and Klass, D.L. 1975. Anaerobic acidogenesis of waster watersludge. J.  Water Pollut. Control Fed. 47:30-45.

10.     Cohen, A.1983. Two-phase digestion of liquid and solid wastes. In: Proceedings 3rd International Symposium on Anaerobic Digestion, Boston (USA). 1983, 3rd A.D. Secretariat (Eds):123-38.

11.     Brummeler, E.T., Aarnink, M.J. and Koster, I.W. 1992. Dry anaerobic digestion of solid organic waste in a biocell reactor at a pilot-plant scale. Water Sci. Tech. 25(7):301-10.

12.     Braber, K. (1995) “ Anaerobic digestion of municipal solid waste: A modern waste disposal option on the verge of breakthrough”. Biomass and Bioenergy 9(1-5), 365–376.

13.     Held, C., Wellacher, M., Robra, K.-H., and Gubitz, G. M. (2002) . Two-stage anaerobic fermentation of organic waste in CSTR and UFAF-reactors. Bioresource Technology 81(1), 19–24

14.     Isa Z (1991). “Fundamental Of Anaerobic Waste Treatment Technology.” In: Yeoh BG (Ed.) Anaerobic     Digestion Technology In Pollution Control: Proceeding of the Workshop On Anaerobic Digestion Technology In pollution control held at SIRIM, Shah Alam, Selangor  Darul Ehsan, 5-7 August 1991.

15.     Sperling VM, Cherincharo CAL (2005). “Principles of anaerobic digestion. In: Biological Wastewater Treatment in Warm Climate “Region, 1st edition. IWA publishing, London, UK.





Jaspreet Singh, Harvinder Lal, Gautam Kocher

Paper Title:

Musculoskeletal Disorder Risk Assessment in small scale forging Industry by using RULA METHOD

Abstract:    Musculoskeletal disorders (MSDs) are common health problem throughout the world. Work related musculoskeletal disorders are group of painful disorders of muscles, tendons and nerves. The low back, or lumber area, serves a number of important functions for the men in working area many occupational tasks in industrial are still associated with strenuous working postures and movement. Combined with a heavy physical workload, they result in a high frequency of work-related musculoskeletal disorders. The present study was aimed to evaluate the musculoskeletal disorder (MSD) of workers engaged in Small scale forging industries. Study was conducted on 102 workers of a forging industry using the posture analysis tool RULA Method. A video showing the different activities of the workers was shot and then images were cropped from it for the analysis. The results of RULA showed that about 20.33% of the workers were under high risk levels and required immediate change. About 45.32% of the workers were at lower risk levels and 34.33% of the workers were at medium risk levels. The present Study recommended the awareness and proper ergonomics training to the workers.

   Musculoskeletal disorders, men, forging industry, RULA.


1.        Buckle P, Devereux J. Work Related Neck and Upper Limb Musculoskeletal Disorders. Bilbao, Spain: European Agency for Safety and Health at Work (1999)
2.        McAtamney, L. and Corlett. E. N., RULA: a survey method for the investigation of work related upper limb disorders. Applied Ergonomics, 24, 91-99(1993)

3.        J.N.Saraji, M.A.hassanzadeh, M.Pourmahabadian & S.J.Shahtaheri. Evaluation of Musculoskeletal Disorders Risk Factors among the Crew of the Iranian Ports and Shipping Organication’s Vessels. Acta Medica Iranica, 42(5): 350-354 (2004)

4.        Aarås, A, G. Horgen, M. Helland. Can visual discomfort influence on muscle pain for visual display unit (VDU) workers. (2007)

5.        Christine Brulin, Karl-Axel Angquist, Margareta Barnekow-Bergkvist and Ulrika Aasa. Relationships between work-related factors and disorders in the neck-shoulder and low-back region among female and male Ambulance Personnel. (2003)

6.        Dan Anton, John C Rosecrance, Linda A Merlino and Thomas M Cook. Method for quantitatively assessing physical risk factors during variable non cyclic work. (2003)

7.        Markku Mattila, Waldemar Karwowski & Mika Vilkki.  Analysis of working postures in hammering tasks on building construction sites using the computerized OWAS method. Applied Ergonomic, 24(6): 405-412 (1993)

8.        Sakineh varmazyar, Ali safari varyani, Isa Mohammadi Zeidi,  Hasan Jahani Hashemi Evaluation Working Posture and Musculoskeletal Disorders Prevalence in Pharmacy Packaging Workers European Journal of Scientific Research ISSN 1450-216X Vol.29 No.1 (2009)

9.        L P Singh. Work posture assessment in forging industry: an exploratory study in India International Journal of Advanced Engineering Technology Oct.-Dec.,(2010)

10.     A. R. Ismail, M. L Yeo, M.H.M. Haniff, R. Zulkifli, B.M. Deros. Assessment of Postural Loading among the Assembly Operators: A Case Study at Malaysian Automotive Industry Euro Journals Publishing, Inc. (2009)

11.     M. Massaccesi, A. Pagnotta, A. Soccetti, M. Masali, C. Masiero,      F. Greco Investigation of work-related disorders in truck drivers using RULA method Applied Ergonomics Received 1 January 2002; accepted 21 March 2003
12.     S Sahu, M Sett, Ergonomic evaluation of tasks performed by female workers in the unorganized sectors of the manual brick manufacturing units in India Ergonomics. (2010)
13.     www.dcmsme.gov

14.     www.vassarstat.com

15.     www.indianforging.com





Abdussamad U. Jibia

Paper Title:

Measurement of Fluorescence Lifetimes Using Minimum Norm and Multiparameter Deconvolution

Abstract:   A new method of fluorescence decay analysis is presented. The method relies on the classical Gardner transform to convert the fluorescence decay data into a convolution model which is deconvolved using multiparameter deconvolution technique. Minimum norm eigenvector method is then used to further model the resulting complex exponentials to obtain better estimates of fluorescence decay rates and number of components. Simulation results indicate that the SNR detection threshold is very low compared with several other methods. Fluorescence decay data is finally postprocessed using the proposed approach. The results are motivating.

   fluorescence, Gardner transform, multiexponential, multiparameter deconvolution, minimum norm. 


1.       J. R. Lakowicz, Principles of Fluorescence Spectroscopy,3rd Edition.
2.       Springer Science and Business Media, LLC, Singapore, 2006.

3.       A.A. Istratov and O.F. Vyvenko, “Exponential Analysis in Physical Phenomena,” Rev. Sci. Instruments., vol. 70 no. 2, pp. 1233-1257, 1999.

4.       A.U. Jibia and M.J.E. Salami. An Appraisal of Gardner Transform-Based Methods of Transient Multiexponential Signal Analysis. International Journal of  Computer Theory and Engineering,  2012, 4 (1): 16-25.

5.       Isernberg, I., & Dyson, R. D. (1969).  The analysis of fluorescence decay by a method of moments.  The Biophysical Journal, 9 (11), 1337-1350.

6.       Isernberg, I. (1983).  Robust estimation in pulse fluorometry: A study of the method of moments and least squares. The Biophysical Journal, 43 (2), 141-148

7.       A. U. Jibia, M. J. E. Salami and O. O. Khalifa, ”Effect of Multiple Deconvolution Parameters on the Resolvability of Decay Rates of Multiexponential Signals,” Proceedings of 15th International Conference on Systems, Signals and Image Processing (IWSSIP 2008) Bratislava, pp. 347 - 350, 2008. ISBN 978-80-227-2856-0.

8.       A. U. Jibia, and M. J. E., Salami, “Performance Evaluation of MUSIC and Minimum Norm Eigenvector Algorithms in Resolving Noisy Multiexponential Signals,” International Journal of Computer Science, Vol. 2 no 4, pp. 235- 239, 2007.

9.       A.U. Jibia, M.J.E. Salami, O.O. Khalifa. Effect of Sampling on the Parameter Estimates of Multicomponent Transients, 2nd International Conference on Computer and Automation Engineering,  Singapore. Vol. 5, 2010, PP: 704-708.

10.     A.U. Jibia and M.J.E. Salami. Transient Multiexponential Data Selection Using Cramer-Rao Lower Bound. Proc. International Conference on Computer and Automation Engineering, Mumbai, January 2012, pp.  227-232.

11.     A.U. Jibia and M.J.E. Salami. Analysis of transient multiexponential signals using exponential compensation deconvolution. Measurement 45(2012) 19–29.

12.     D.G.Manolakis, V.K. Ingle, S.M. Kogon, “Statistical and adaptive signal processing,” Artech House, Inc., Norwood, 2005.





J.Suganthi, N.Kumaresan, K.Anbarasi

Paper Title:

Design of Low Power Zigzag 8T SRAM array with Differential Write Back Scheme

Abstract:    Static random access memory (SRAM) has been widely used as the representative memory for logic LSIs. This is because SRAM array operates fast as logic circuits operate, and consumes a little power at standby mode. array. Therefore, the good design of SRAM cell and SRAM cell array is inevitable to obtain high performance, low power, low cost, and reliable logic LSI. Various kinds of SRAM memory cell has been historically proposed, developed and used. Nanometer SRAM cannot achieve lower VDDmin due to read-disturb, half-select disturb and write failure. This paper demonstrates quantitative performance advantages of a zigzag 8T-SRAM (Z8T) cell over the decoupled single-ended sensing 8T-SRAM (DS8T) with write-back schemes, which was previously recognized as the most area-efficient cell under large supply voltage variations. In this paper, we propose a new compact z-shape cell layout to prioritize symmetric device placement while providing high area efficiency.

   Low supply voltage, SRAM, read disturb, static voltage, SRAM, read disturb, static noise margin, write margin.


1.       Akamatsu.H, Satomi.K, Suzuki.T, Yamagami.Y and Yamauchi.H ( 2008) “A stable 2-port SRAM cell design against simultaneously read/write disturbed accesses”  IEEE J. Solid-State Circuits, vol. 43, no. 9, pp.2109–2119.
2.       Bhattacharya.U ,Bohr.M, Chen.Z, Hamzaoglu.F, Murray.D, Vallepalli.N, Wang.Y Zhang.K  and  Zheng.B ( 2006)  “A 3-GHz 70-Mb SRAM in 65-nm CMOS Technology  with integrated column-based dynamic power supply” IEEE J. Solid- State Circuits, vol. 41, no. 1, pp. 146–151.
3.       Barwin.J,  Braceras.G,  Browning.C, Burns.S, Gabric.J, Lamphier.S,  Miller. Pilo.H, Roberts.A and  Towler.F  (2006) “An SRAM design in 65 nm and 45 nm Technology  nodes featuring read and write-assist circuits to expand operating  voltage” in Symp. VLSI Circuits Dig. Tech. Papers, pp. 15–16. 
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