International Journal of Engineering and Advanced Technology(TM)
Exploring Innovation| ISSN:2249-8958(Online)| Reg. No.:61902/BPL/CE/2011| Published By BEIESP| Impact Factor: 5.02
Publication Fee
Privacy Policy
Associated Journals
Frequently Asked Questions
Contact Us
Volume-1 Issue-4 Published on April 30, 2012
Volume-1 Issue-4 Published on April 30, 2012

 Download Abstract Book

S. No

Volume-1 Issue-4, April 2012, ISSN:  2249-8958 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.



S. R. Teleka, J.J. Green, S. Brink, J. Sheer, K. Hlophe

Paper Title:

The Automation of the ‘Making Safe’ Process in South African Hard-Rock Underground Mines

Abstract:   In South African hard-rock mines, best practice dictates that the hanging walls be inspected after blasting. This process is known as ‘making safe’ and, although intended to save lives, it is both laborious and subjective. Pressure is placed on the barrer (inspector) to conduct the test quickly and efficiently, as daily operations can only continue after the area has been declared safe. The process involves the barrer tapping the potentially loose rock mass with a sounding bar, listening to and assessing the generated acoustics, and deciding whether it is intact or loose. For a loose rock mass, the barrer would either bar it down or support it. For the purposes of this report, only the inspection task of the ‘making safe’ process is considered. It is highly dangerous and limits the critical decision making to the experienced barrer. Fatality rates due to falls of ground (FOG) can be reduced by using a simple tool that will produce consistent results in the ‘making safe’ exercise.

  Fall of ground (FOG), Hard-rock, Pre-entry examination, Sounding


1.        J. Jager and J. A. Ryder, “A Handbook on Rock Engineering Practice for Tabular Hard Rock Mine”s. Safety in Mines Research Advisory Committee (SIMRAC), Johannesburg, South Africa, 1999.
2.        S. Brink et al., “Electronic sounding device for testing structural stability in underground mines,” Council for Scientific and Industrial Research (CSIR), Johannesburg, South Africa, CSIR DMS Ref: JhbGen 19056, 2009. (Email:

3.        J. Dickens, “Mine fatalities,” Council for Scientific and Industrial Research (CSIR), Johannesburg, South Africa, CSIR DMS Ref: CotGen 6460, 2011. (

4.        A. V. Peake and S. G. E. Ashworth. (1996). “Factors influencing the detection of unsafe hanging wall conditions,” Safety in Mines Research Advisory Committee (SIMRAC), GAP 202 [Online]. Available:

5.        S. G. E. Ashworth and A. V. Peake. (1994). “Assess the dominant circumstances and factors giving rise to accidents in the gold and platinum mining industry,” Safety in
Mines Research Advisory Committee (SIMRAC), GAP055 [Online]. Available:

6.        H. Allison and R. D. Lama, “Low frequency sounding technique for predicting progressive rock failure,” Rock Mechanics, vol. 12, 1979. 

7.        R. W. Otterman et al., “Investigate a possible system for ‘making safe’,” Safety in Mines Research Advisory Committee (SIMRAC). GEN 801, 2002. 

8.        J. Simmonds, Safe operating procedures for making safe and barring down. Anglo Platinum, Bafokeng Rasimone Platinum Mine, 2008.

9.        R. W. Otterman et al., “Development of an effective pinchbar,” Safety in Mines Research Advisory Committee (SIMRAC), SIM 020201, 2003.

10.     J. J. Green et al., “Can a robot improve mine safety?” in 25th Int. Conf. CAD/CAM, Robotics & Factories of the Future Conference (CARs&FoF), Pretoria, South Africa, 2010.

11.     G. Ferreira, “An implementation of ultrasonic time-of-flight bases localization,” in 2nd Int. Conf. Wireless Communications in Underground and Confined Areas, 2008.

12.     D. Vogt et al., “Mining research for enhanced competitiveness,” presented at Science Real and Relevant: 2nd CSIR Biennial Conference, 2008. 

13.     V. Z. Brink and M. K. C. Roberts, “Early warning and/or continuous risk assessment of rockfalls in Deep South African mines,” in 4th Int. Seminar on Deep and High Stress Mining, Perth, Australia, 2007.

14.     R. Steward et al., “AziSA: An architecture for underground measurement and control networks,” in 2nd Int. Conf. Wireless Communications in Underground and
Confined Areas, Val-d’Or-Quebec-Canada, 2008. 

15.     Information on IP 65 enclosures, Available:, last visited on 03 May 2011.

16.     Degrees of Protection Provided by Enclosures (IP Code), SANS IEC 60526, Edition 2.1, South African Bureau of Standards, 2001.

17.     J. J. Green and D. Vogt. (2009). A Robot Miner for Low Grade Narrow Tabular Ore Bodies: The Potential and the Challenge. ROBMECH [Online]. Available:
18.     V. A. Kononov. (2000). “Pre-feasibility of infrared thermography of loose hanging wall,” Safety in Mines Research Advisory Committee (SIMRAC), GAP706. [Online]. Available: 
19.     V. A. Kononov, “Infrared thermography of loose hanging walls,” Safety in Mines Research Advisory Committee (SIMRAC), GAP820, 2002.

20.     D. Vogt. (2009). “New technology for real-time in-stope safety management,” The South African Institute of Mining and Metallurgy, Hard Rock Safe Safety Conf. [Online]. Available: 

21.     V. Brink, “Method and apparatus for testing installation quality in a grouted anchor system,” U.S. Patent 7 043 989 B2, United States Patent and Trademark Office, 2006.




J J Green, K Hlophe, J Dickens, R Teleka, M Price

Paper Title:

Mining Robotics Sensors

Abstract:   Underground mining robotics has not enjoyed the same technology advances as above-ground mining. This paper examines sensing technologies that could enable the development of underground autonomous vehicles. Specifically, we explore a combination of three-dimensional (3D) cameras (SR 4000 and XBOX Kinect) and a thermal imaging sensor (FLIR A300) in order to create 3D thermal models of narrow mining stopes. This information can be used in determining the risk of rock fall in an underground mine, which is a major cause of fatalities in underground narrow-reef mining. Data are gathered and processed from multiple underground mine sources, and techniques such as surfel modeling and synthetic view generation are explored towards creating visualizations of the data that could be used by miners to monitor areas of risk in the stope. Further work will determine this potential.

  underground mining robotics, perception sensors, sensor fusion, infrared camera, 3D laser scan.


1.        Sandvik. (2011, May 2). Automine [Online]. Available: 
2.        J. J. Green et al., “Can a robot improve mine safety?” presented at CAD/CAM, Robotics and Factories of the Future.  Pretoria, South Africa, July 2010

3.        J. Green and D. Vogt, “A robot miner for low grade narrow tabular ore bodies: The potential and the challenge,” presented at the 3rd Robotics and Mechatronics Symp. (ROBMECH 2009). Pretoria South Africa, November 2009

4.        L. Prinsloo. (2011, Jan 6). South African mine deaths down 24% in 2010. Last accessed 2011(May 3), p. 2. [Online]. Available: 

5.        K. Hlophe, “GPS-deprived localisation for underground mines,” presented at the Science Real and Relevant: 3rd CSIR Bienn. Conf. [Online]. Available: 

6.        K. Hlophe et al., “A posture estimation system for underground mine vehicles,” presented at CAD/CAM, Robotics and Factories of the Future, 2010. Pretoria, South Africa, July 2010

7.        FLIR, FLIR commercial vision systems, 'avoiding accidents with mining vehicles', Application Stories. 2008, vol. 2010, pp. 2, 2008. 

8.        V. A. Kononov. (2000 Sept.). “Pre-feasibility investigation of infrared thermography for the identification of loose hanging wall and impending falls of ground,” Safety in Mines Research Advisory Committee, South Africa [Online]. Available: 

9.        D. Vogt et al., “Mining research for enhanced competitiveness,” presented at Science Real and Relevant: 2nd CSIR Bienn. Conf.  Pretoria South Africa, 2008.

10.     D. Vogt et al., “New technology for real-time in-stope safety management,” presented at Hard Rock Safe Safety Conf., 2009 [Online]. Available: 

11.     D. Vogt et al., “New technology for improving entry examination, thereby managing the rock fall risk in South African gold and platinum mines,” presented at. Science Real and Relevant: 3rd CSIR Bienn Conf, 2010 [Online]. Available: 

12.     H. Bay et al., “SURF: Speeded-up robust features,” presented at 9th European Conf. Computer Vision [Online]. Available: 

13.     C. Baker et al., “A campaign in autonomous mine mapping,” presented at IEEE Int. Conf. Robotics and Automation. ICRA 2004, New Orleans, LA, USA.

14.     D. Huber and N. Vandapel. “Automatic 3D underground mine mapping,” presented at Field and Service Robotics, 2003. Lake Yamanaka, Japan

15.     A. Nüchter et al., “6D SLAM with an application in autonomous mine mapping,” presented at IEEE Int. Conf. Robotics and Automation. , ICRA 2004, New Orleans, LA, USA

16.     D. Droeschel et al., “Multi-frequency phase unwrapping for time-of-flight cameras,” presented at IEEE/RSJ Int. Conf. Intell. Robots and Systems (IROS),2010[Online].Available: 

17.     J. Bloomenthal, “An implicit surface polygonizer,” Graphics Gems, vol. IV, pp. 324–349, 1994. 
18.     G. Taubin, “Curve and surface smoothing without shrinkage,” presented at International Conference of Computer Vision. 1995 
19.     MIT, Visual Odometry for GPS-Denied Flight and Mapping using a Kinect, vol. 2011, Mar. 2011. 

20.     P. Henry et al., “RGB-D mapping: Using depth cameras for dense 3D modeling of indoor environments,” presented at the 12th Int. Symp. Experimental Robotics (ISER).




Manoj K Kowar and Sourabh Yadav

Paper Title:

Brain Tumor Detction and Segmentation Using Histogram Thresholding

Abstract:   The knowledge of volume of a tumor plays an important in the treatment of malignant tumors. Manual segmentation of brain tumors from Magnetic Resonance images is a challenging and time consuming task. This paper presents a novel technique for the detection of tumor in brain using segmentation and histogram thresholding. The proposed method can be successfully applied to detect the contour of the tumor and its geometrical dimension. This technique can be proved to be handy tool for the practitioners especially the physicians engaged in this field.

  Histogram, MRI, Thresholding, Brain Tumor.


1.       Mohammad Shajib Khadem, “MRI Brain image segmentation using  graph cuts”, Master of Science Thesis in Communication Engineering, Department of Signals and Systems, Chalmers University Of Technology, Goteborg, Sweden, 2010.
2.       Yan Zhu and Hong Yan, “Computerized Tumor Boundary Detection Using a Hopfield    Neural Network”, IEEE Trans. Medical Imaging, vol. 16, no. 1, pp.55-67 Feb.1997.

3.       Orlando J. Tobias and Rui Seara,”Image Segmentation by Histogram Thresholding Using Fuzzy Sets,” IEEE transactions on Image Processing,Vol. 11,NO. 12,PP-1457-1465,DEC 2002.

4.       Saif D. Salman and Ahmed A. Bahrani,  “Segmentation of tumor tissue in gray   medical images using watershed transformation method,” Intl. Journal of Advancements in Computing Technology,Vol. 2, No. 4,pp-123-127,OCT 2010.

5.       Wenbing Tao, Hai Jin, and Yimin Zhang, “Color Image Segmentation Based on Mean Shift and Normalized Cuts,” IEEE Trans. on Systems, Man, and Cybernetic-Part B: Cybernetics, vol. 37, no. 5, pp.1382-1389, Oct. 2007.

6.       F.kurugollu, “color image segmentation using histogram multithresholding and fusion,” Image and Vision Comuting,Vol. 19,pp-915-928,2001.

7.       Mrs.Mamata S.Kalas, “An Artificial Neural Network for Detection of Biological Early Brain Cancer,” Intl. Journal of Computer Applications, Vol. 1, No. 6,pp-17-23,2010.

8.       S.Shen,W. A. Sandham and M. H. Granat, “PREPROCESSING AND SEG-MENTATION OF BRAIN MAGNETIC RESONANCE IMAGES,” Proc of the 4th Annual IEEE Confon Information Technology Applications in Biomedicine, UK, pp. 149-152,2003.

9.       Heath LM, Hall LO, Goldgof DB and Murtagh FR (2001) Automatic segmentation of non-enhancing brain tumors in magnetic resonace images. Artificial Intelligence in Med. 21, 43-63.

10.     Yang Y, Yan X, Zheng C and Lin P (2004) A novel statistical method for segmentation of brain MRI. IEEE, 946 949.

11.     Salman YL, Assal MA, Badawi AM, Alian SM and MEI-EI Bayome (2005) Validation techniques for quantitative brain tumors measurements. IEEE Proc. Engg. Med. Biol. 7048- 7051.




Shalini Merine George

Paper Title:

Multicasting in Mobile ad Hoc Network Using Zone Based Structure

Abstract:   The challenge faced nowadays is to design a scalable and robust multicast routing protocol in a mobile ad hoc network (MANET). The use of mobile ad hoc networks (MANETs) is to be achieved with fast progress of computing techniques and wireless networking techniques. MANET is used because wireless devices could self-configure and form a network with an arbitrary topology. The difficulty is in achieving the group membership management, multicast packet forwarding, and the maintenance of multicast structure over the dynamic network topology for a large group size or network size. These areas in MANET are of large interest. Robust and Scalable Geographic multicast protocol is used for handling multicasting in mobile ad hoc networks. Virtual architectures are used in this protocol. MANETs have unstable wireless channels and node movements. Scalability and efficiency of group membership management is performed through a virtual-zone-based structure. The location service for group members is integrated with the membership management. The control messages as well as the data packets are forwarded along efficient tree-like paths. Here it avoids the need of explicitly creating and actively maintaining a tree structure. Geographic forwarding is used to achieve further scalability and robustness. Source tracking mechanism is designed for handling flooding of information. Other than that, empty-zone problem faced by most zone-based routing protocols is efficiently being handled. Overall advantages are higher delivery ratio in all circumstances, with different moving speeds, node densities, group sizes, number of groups, and network sizes. This has minimum control overhead and joining delay.

  MANET is used because wireless devices could self-configure and form a network with an arbitrary topology.


1.        W. Wu, J. Cao, J. Yang, and M. Raynal, “Design and Performance Evaluation of Efficient Consensus Protocols for Mobile Ad Hoc Networks,” IEEE Trans. Computers, vol. 56, no. 8, pp. 1055-1070, Aug. 2007.
2.        R. Beraldi and R. Baldoni, “A Caching Scheme for Routing in Mobile Ad Hoc Networks and Its Application to ZRP,” IEEE Trans. Computers, vol. 52, no. 8, pp. 1051
1062, Aug. 2003.

3.        R. Beraldi and R. Baldoni, “A Caching Scheme for Routing in Mobile Ad Hoc Networks and Its Application to ZRP,” IEEE Trans. Computers, vol. 52, no. 8, pp. 1051-1062, Aug. 2003.

4.        Y.C. Tseng, S.Y. Ni, and E.Y. Shih, “Adaptive Approaches to Relieving Broadcast Storms in a Wireless Multihop Mobile Ad Hoc Network,” IEEE Trans. Computers, vol. 52, no. 5, pp. 545-557,May 2003.

5.        S.M. Das, H. Pucha, and Y.C. Hu, “Distributed Hashing for Scalable Multicast in Wireless Ad Hoc Network,” IEEE Trans.Parallel and Distributed Systems, vol. 19, no. 3, pp. 347-362, Mar.2008.




Vishwas Massey, K. J. Satao

Paper Title:

Evolving a New Software Development Life Cycle Model (SDLC) incorporated with Release Management

Abstract:   Software Development Life Cycle or System development Life Cycle or simply SDLC (system and software is interchanged frequently in-accordance to application scenario) is a step by step highly structured technique employed for development of any software. SDLC allows project leaders to configure and supervise the whole development process of any software. Divide and conquer technique is widely used in SDLC models. Tasks that are complex in nature are broken down into smaller manageable components. Developers employ SDLC models for analyzing, coding, testing and deployment of software system. Efficient and effective software is developed because of SDLC model, thus making the software capable of addressing expectations of the customers, clients and the end-users. Software developed by employing the suitable SDLC models is better performers in the market when compared with their competitors. SDLC Models helps in regulating the software-system development time and helps in effective cost scheduling. In this paper we have tried to develop a model which guarantees that the development and delivery (release) teams engaged in some project have strong co-ordination and collaboration leading to enhanced productivity, efficiency, effectiveness and longer market life. This can be achieved by incorporating concept of release with basic SDLC phases (steps) with the concept of release management.

  Release Management, Spiral Model, Software Development Lifecycle Model (SDLC), Waterfall Model.


1.        Software Development Life Cycle (SDLC) – the five common principles.htm
2.        Software Methodologies Advantages & disadvantages of various SDLC models.mht

3.        Craig Larman, Victor R. Basili, "Iterative and Incremental Development: A Brief History," Computer, vol. 36, no. 6, pp. 47-56, June 2003, doi:10.1109/MC.2003.1204375. 

4.        Curtis, Krasner, Iscoe, 1988.

5.        Dr. Winston W. Royce (1929 - 1995) at Retrieved 27 Oct 2008.

6.        Conrad Weisert, Information Disciplines, Inc., Chicago, 8 February, 2003

7.        Craig Larman, Victor R. Basili (June 2003). "Iterative and Incremental Development: A Brief History.

8.        Using Both Incremental and Iterative Development.Dr. Alistair Cockburn, Humans and Technology, Crosstalk May 2008.

9.        International Journal of Computer Science and Network Security, VOL.10 No.1, January 2010, Evolving A New Model (SDLC Model-2010) For Software Development Life Cycle (SDLC)PK.Ragunath, S.Velmourougan, P. Davachelvan, S.Kayalvizhi, R.Ravimohan

10.     Hoek, A. van der, Wolf, A. L. (2003) Software release management for component-based software. Software—Practice & Experience. Vol. 33, Issue 1, pp. 77–98. John Wiley & Sons, Inc. New York, NY, USA.

11.     Software Release Management: Proceedings of the 6th European Software Engineering Conference, LNCS 1301, Springer,  Berlin, 1997(Andre van der Hoek, Richard S. Hall, Dennis Heimbigner, and Alexander L. Wolf Software Engineering Research Laboratory, Department of Computer Science, University of Colorado,
Boulder, CO 80309 USA)

12.     S. P. Overmyer: Revolutionary vs. Evolutionary Rapid Prototyping: Balancing Software Productivity and HCI Design Concerns. Center of Excellence in Command, Control, Communications and Intelligence (C3I), George Mason University, 4400 University Drive, Fairfax, Virginia..

13.     Systems Development Lifecycle: Objectives and Requirements Bender RBT

14.     Boehm B, "A Spiral Model of Software Development and Enhancement", ACM SIGSOFT Software Engineering Notes", "ACM", 11(4):14-24, August 1986 

15.     Roger Pressman, titled Software Engineering - a practitioner's approach.




Thummala Pavan Kumar, Malineni Madhuri, Vallabhaneni Surya, Jasti Nitheesha, Guru Jagadeesh

Paper Title:

Reducing Starvation in Multi-Channel Protocols Through Enhanced AMCP

Abstract:  The multi-channel protocols are determined to have more throughput when compared to single-channel protocols. Asynchronous Multi-Channel Co-Ordination protocol (AMCP) is devised to address the starvation in multi-channel protocols by having an approximate lower-bound on the throughput of any flow in arbitrary topology. We here determine that AMCP can be enhanced by modeling per-flow throughput. The determined methodology has been found to have higher per-flow throughput than IEEE802.11 and MMAC

  AMCP, MMAC, Multi-Channel.


1.        Adya, P. Bahl, J. Padhye, A. Wolman, and L. Zhou. A
2.        Multi-Radio Unification Protocol for IEEE 802.11 Wireless Networks. In Proc. IEEE International Conference on Broadband Networks (Broadnets) 2004, San Jose, CA, USA, October 2004.

3.        P. Bahl, R. Chandra, and J. Dunagan. SSCH: slotted seeded 0nodchannel hopping for capacity improvement in IEEE 802.11 ad-hoc wireless networks. In Proc. ACM MobiCom, NewYork, NY, USA, September 2004.

4.        G. Bianchi. Performance analysis of the IEEE 802.11 distributed coordination function. IEEE Journal on Selected Areas in Communications, 18(3):535–547, March 2000.

5.        T.A. ElBatt and A. Ephremides. Joint Scheduling and Power Control for Wireless Ad-hoc Networks. In Proc. IEEE INFOCOM, New York, NY, USA, June 2002.

6.        J.J. Garcia-Luna-Aceves and Y. Wang. Throughput and

7.        Fairness of Collision Avoidance Protocols in Ad Hoc Networks. Ad Hoc Networks: Technologies and Protocols, Kluwer Academic Publishers, 2004.

8.        M. Garetto, T. Salonidis, and E. Knightly. Modeling per-flow throughput and capturing starvation in CSMA multi-hop

9.        Wireless networks. In Proc. IEEE INFOCOM, Barcelona, Spain, 2006.

10.     M. Garetto, J. Shi, and E. Knightly. Modeling Media Access in Embedded Two-Flow Topologies of Multi-hop Wireless Networks. In Proc. ACM MobiCom, Cologne, Germany, August 2005.

11.     S. Lu H. Luo and V. Bharghavan. A new model for packet scheduling in multihop wireless neworks. In Proc. ACM MobiCom, Boston, MA, USA, August 2000.

12.     X. Huang and B. Bensaou. On max-min fairness and scheduling in wireless ad-hoc networks: Analytical framework and implementation. In Proceedings of ACM MobiHoc, Long Beach, CA, October 2001.

13.     N. Jain and S.R. Das. A Multichannel CSMA MAC Protocol with Receiver-Based Channel Selection for Multihop Wireless Networks. In Proc. IC3N, Scottsdale, AZ, USA, October 2001.

14.     M. Kodialam and T. Nandagopal. Characterizing the Achievable Rates in Multihop Wireless Networks. In Proc. ACM MobiCom, San Diego, CA, USA, September 2003.

15.     A. Kumar, E. Altman, D. Miorandi, and M. Goyal. New insights from a fixed point analysis of single cell IEEE 802.11 WLANs. In Proc. IEEE INFOCOM, Miami, FL, March 2005.




Yogendra kumar Jain, Geetika S. Pandey, Deshraj Ahirwar

Paper Title:

An Improved Routing Mechanism for Secure Ad-hoc Network

Abstract:    An ad-hoc network is a multi-hop wireless network where all nodes cooperatively maintain network connectivity without a centralized infrastructure. If these nodes change their positions dynamically, it is called a mobile ad-hoc network (MANET). The security of ad hoc networks is becoming an increasingly complex issue. Security requirements such as authentication, non-repudiation, data integrity and confidentiality, which would otherwise be provided by a central server, must be enabled and provided by all nodes. In this paper we proposed enhance based direction routing protocol. The zone direction is reduced until the node can select the strongest and most stable link and so increase availability in the network. Each node in the network has a counter for the stability of link (SL) to its neighboring nodes, which indicates which nodes are active in the network, improving the performance of the network and increasing the likelihood of selecting the optimal path. We also propose a novel secure routing protocol to improve the security level in ad hoc networks, based on key management and a secure node-to-node path, which protects data to satisfy our security requirements.  

  Ad-hoc Network, Routing Protocol, Security Mechanism.


1.        Matthew Tan Creti, Matthew Beaman, Saurabh Bagchi, Zhiyuan Li, and  Yung-Hsiang Lu, Multigrade Security Monitoring for Ad-Hoc Wireless Networks”, IEEE 2009.
2.        R.PushpaLakshmi and Dr.A.Vincent Antony Kumar, “Security aware Minimized Dominating Set based Routing in MANET”, IEEE 2010 Second International conference on Computing, Communication and Networking Technologies.

3.        YongQing Ni, DaeHun Nyang and Xu Wang, “A-Kad: an anonymous P2P protocol based on Kad network”, IEEE 2009, Issue Date:  12-15 Oct. 2009 On page(s): 747, Print ISBN: 978-1-4244-5113-5. 

4.        N.Bhalaji, Dr.A.Shanmugam, “ASSOCIATION BETWEEN NODES TO COMBAT BLACKHOLE ATTACK IN DSR BASED MANET”, IEEE 2009, Issue Date :  12-15 Oct. 2009 , On page(s): 747 , Print ISBN: 978-1-4244-5113-5. 

5.        Sohail Jabbar, Abid Ali Minhas, Raja Adeel Akhtar, Muhammad Zubair Aziz, “REAR: Real-time Energy Aware Routing for Wireless Adhoc Micro Sensors Network”, 2009 Eighth IEEE International Conference on Dependable, 

6.        D.Suganya Devi and Dr.G.Padmavathi, “Performance Efficient EOMCT Algorithm for Secure Multicast Key Distribution for Mobile Adhoc Networks”, IEEE 2009 International Conference on Advances in Recent Technologies in Communication and Computing, Issue Date:  27-28 Oct 2009,On,pages(s): 934 ,Print ISBN: 978-1-4244-5104-3. 

7.        Jian Ren and Yun Li and  Tongtong Li, “Providing Source Privacy in Mobile Ad Hoc Networks”, IEEE 2009, Issue Date :  12-15 Oct. 2009, On page(s): 332, Print ISBN: 978-1-4244-5113-5.

8.        Praphul Chandra, ―Bulletproof Wireless Security GSM, UMTS, 802.11 and Ad Hoc Security‖ Elsevier, 2005, ISBN: 0-7506-7746-5.

9.        Amitabh Mishra and Ketan M. NadKarni, ―Security in Wireless Ad Hoc Networks‖, The Hand Book of Ad hoc Networks, CRC Press, FL, USA, 2003, pp. 479-490.

10.     Xing Fei; Wang Wenye, ―Understanding Dynamic Denial of Service Attacks in Mobile Ad Hoc Networks‖, MILCOM 2006, Oct. 2006, pp. 1 – 7.




Subhransu Padhee, Nitesh Gupta, Gagandeep Kaur

Paper Title:

Data Driven Multivariate Technique for Fault Detection of Waste Water Treatment Plant

Abstract:   Collection of raw data from different sensors, processing the data and extracting information from it is a very challenging task. Because of the enhanced memory capacity of the present day computers, data logging has reached to a new level. The analyst has to classify the data according to their traits from the offline logged data. The whole task of collection of raw data, classification of data according to their traits involves different statistical as well as soft computational techniques. This research paper takes a case study of waste water treatment plant and using different data driven multivariate statistical techniques and soft computational techniques determine the faults in the system. This paper uses principal component analysis and backpropagation algorithm to classify the data and detect the faults in a waste water treatment plant.

  backpropagation, multivariate statistical technique, principal component analysis.


1.        R Dunia, S J Qin, T F Edgar and T J McAvoy, “Identification of faulty sensors using principal component analysis,” AICHE Journal, vol. 42, no. 10, 1996, pp. 2797- 2812
2.        T Amand, G Heyen and B Kalitventzeff, “Plant monitoring and fault detection: Synergy between data reconciliation and principal component analysis,” Computers and Chemical Engineering, vol. 25, no. 4-6, 2001, pp. 501-507

3.        Y M Sebzalli and X Z Wang, “Knowledge Discovery From Process Operational Data Using PCA and Fuzzy Clustering,” Engineering Applications of Artificial Intelligence, vol. 14, 2001, pp. 607-616

4.        N Bendwell, “Monitoring of a waste water treatment plant with a multi variate model- The benefits of PCA technology explained,” Pulp and Paper-Canada, vol. 103, no. 7, 2002, pp. 43-46 

5.        V Venkatasubramaniam, R Rengaswamy, K Yin and S N Kavuri, “A review of process fault detection and diagnosis Part-I: Qulitative model based methods,” Computers and Chemical Engineering, vol. 27, no. 3, 2003, pp. 293 – 311

6.        V Venkatasubramaniam, R Rengaswamy and S N Kavuri, “A review of process fault detection and diagnosis Part-II: Quantitative model and search strategies,” Computers and Chemical Engineering, vol. 27, no. 3, 2003, pp. 313 – 326  

7.        V Venkatasubramaniam, R Rengaswamy, S N Kavuri and K Yin, “A review of process fault detection and diagnosis Part-III: Process history based methods,” Computers and Chemical Engineering, vol. 27, no. 3, 2003, pp. 327 – 346

8.        R Ganesan, T K Das, V Venkataraman, “Wavelet based multiscale statistical process monitoring: A literature review,” Iie Transactions, vol. 36, no. 9, 2004, pp. 787 – 806

9.        H Albazzaz, X Z Wang and F Marhoon, “Multidimensional visualization for process historical data analysis: a comparative study with multivariate statistical process control,” Journal of Process Control, vol. 15, no. 3, 2005, pp. 285-294

10.     X Sun, H J Marquez, M Riaz and T W Chen, “An improved PCA method with application to boiler leak detection,” ISA Transactions, vol. 44, no. 3, 2005, pp. 379 - 397   

11.     D Wang and J A Romagnoli, “Robust multi scale principal components analysis with applications to process monitoring,” Journal of process control, vol. 15, no. 8, 2005, pp. 869 – 882

12.     H Albazzaz, X Z Wang, “Introduction of dynamics to an approach for batch process monitoring using independent component analysis,” Chemical Engineering Communications, vol. 194, no. 2, 2007, pp. 218 – 233 

13.     Z Q Ge and Z H Song,  “Process monitoring based on independent component analysis-principal component analysis and similarity factors”, Industrial & E14.     A. AlGhazzawi and B. Lennox, “Monitoring a complex refining process using multivariate statistics,” Control Engineering Practice, vol. 16, no. 3, 2008, pp. 294-307
15.     Vasil Simeonov, “Lake Water Monitoring Data Assessment By Multivariate Statistics,” Journal of Water Resource and Protection, vol. 2, 2010, pp. 353-361

16.     Ibrahim Massod and Adnan Hassan, “Issues in Development of ANN-Based Control Chart Pattern Recognition Schemes,” European Journal of Scientific Research, vol. 39, no. 3, 2010, pp. 336-355.




Sudeep Thepade, Rik Kamal Kumar Das

Paper Title:

A Study of Transport Protocols For Wireless Ad Hoc Networks

Abstract:  Ad hoc network is infrastructure less. Each individual node in an ad hoc network must be capable of acting as a host and as a router. The benefits of ad hoc architecture leads to self-reconfiguration and adaptability to highly variable mobile characteristics such as power and transmission conditions, traffic distributions, and load balancing. These benefits come at a cost. Randomness of network topology due to node mobility in ad hoc networks create new challenges, which, together with the local broadcast capability, causes a set of apprehensions relating  to medium access control protocol issues, routing and forwarding issues, transport protocol issues and security issues

  Transport Protocol, MAC, Routing, TCP, Security


1.        Misra, S., Woungang, I., & Misra, S. C. (2009). Guide to Wireless Ad Hoc Networks. (Sudip Misra, Isaac Woungang, & Subhas Chandra Misra, Eds.)Ad Hoc Networks (Vol. 3, p. 620). Springer London.
2.        Mobile Ad Hoc Networking. Edited by Basagni, Conti, Giordano, and Stojmenovic. ISBN 0-471-37313-3 © 2004 Institute of Electrical and Electronics Engineers, Inc.

3.        G., Latva-aho, K., & Qian Zhang , Y. (2009). eMAC—A Medium-Access Control Protocol for the Next-Generation Ad Hoc Networks. IEEE Transactions on Vehicular Technology, , 58(8), 4476. 

4.        Wang, P., Jiang, H., & Zhuang, W. (2008). A New MAC Scheme Supporting Voice/Data Traffic in Wireless Ad Hoc Networks. IEEE Transactions on Mobile Computing, 7(12), 1491-1503.

5.        Bandyopadhyay, S., Roy, S., & Ueda, T. (2006). Enhancing the performance of ad hoc wireless networks with smart antennas (p. 196). Auerbach Publications.

6.        Abdrabou, A., & Zhuang, W. (2009). Statistical QoS routing for IEEE 802.11 multihop ad hoc networks. IEEE Transactions on Wireless Communications, 8(3), 1542-1552. Retrieved from

7.        Chao, L., & Aiqun, H. (2007). Reducing the Message Overhead of AODV by Using Link Availability Prediction . (4864th ed.). SpringerLink.  

8.        Sarkar, S. KR., Basavaraju, T., & Puttamadappa, C. (2008). Ad hoc mobile wireless network Principles, Protocols and Application.. Auerbach Publication.

9.        Li, X., Kong, P.-Y., & Chua, K.-C. (2008). DTPA: A Reliable Datagram Transport Protocol over Ad Hoc Networks. IEEE Transactions on Mobile Computing, 7(10), 1285-1294.

10.     Li, Lujiao and Li, Yun and Chen, Qianbin and Nie, Neng, PTCP: Phase-Divided TCP Congestion Control Scheme in Wireless Sensor Networks, Mobile Ad-Hoc and Sensor Networks,Springer Berlin / Heidelberg ,2007, 4864, Lecture Notes in Computer Science,  pages 281-290

11.     R.R. Roy, Handbook of Mobile Ad Hoc Networks for Mobility Models, DOI 10.1007/978-1-4419-6050-4_1, C _ Springer Science+Business Media, LLC 2011

12.     Jeng, Jan, A., & R. (2011). Adaptive Topology Control for Mobile Ad Hoc Networks. IEEE Transactions on Parallel and Distributed Systems, PP(99), 1.

13.     Das, C. R. (2009). RandomCast: An Energy-Efficient Communication Scheme for Mobile Ad Hoc Networks. IEEE Transactions on Mobile Computing, 8(8), 1039-1051.

14.     Mishra, A. (2008). SECURITY AND QUALITY OF SERVICE IN AD HOC WIRELESS NETWORKS. (1st ed.). The Edinburgh Building, Cambridge CB2 8RU, UK: Published in the United States of America by Cambridge University Press, New York.

15.     Saxena, N., & Yi, J. H. (2009). Noninteractive self-certification for long-lived mobile ad hoc networks. IEEE Transactions on Information Forensics and, 4(4), 946955.

16.     Saxena, N., Tsudik, G., & Yi, J. H. (2009). Efficient Node Admission and Certificateless Secure Communication in Short-Lived MANETs. IEEE Transactions on Parallel
and Distributed Systems, 20(2), 158-170.

17.     Ilyas, M. (2003). The handbook of ad hoc wireless networks. (Mohammad Ilyas, Ed.)Digital Signal Processing. CRC Press.

18.     C., Malumbres, C., Oliver, M., Cano, J. , & Manzoni, J. (2009). QoS Support in MANETs: a Modular Architecture Based on the IEEE 802.11e Technology. IEEE Transactions on Circuits and Systems for Video Technology, 19(5), 678.

19.     Munaretto, A. (2007). Routing and quality of service support for mobile ad hoc networks. Computer Networks, 51(11), 3142-3156.  

20.     M., Khan, N., & KoK-Keong Loo , S. (2009). Limitation and challenges of TCP in Mobile ad hoc Networks. GCC Conference & Exhibition, 2009 5th IEEE.




I. V. Koteswara Rao, K. Sujesh, S. Radha Krishna Reddy¬, Y. Naresh Kumar, CH. Kamal

Paper Title:

A Novel Approach on Harmonic Elimination in Single Phase Systems by Means of a Hybrid Series Active Filter (HSAF)

Abstract:   In this paper, a fully-digital-controlled Hybrid Series Active Filter (HSAF) for harmonic elimination and reactive power compensation in single phase systems is presented. The HSAF is composed of two single tuned LC filters and a small-rated active filter. Discrete Fourier transformation is used as the control method. Simulation results using MATLAB program shows the effectiveness of the control method. A hybrid series active filter is implemented verifying the accuracy of the control method.

  Hybrid series active filter, single phase active filter, harmonic elimination, reactive power compensation, detection methods, power quality.


1.        B. Singh, A. Chandra and K. Al.haddad, “Hybrid Filters for Power Quality Improvement,” IEE Proc. Gener. Transm. Distrib., vol. 152, pp. 365 - 378, no. 3, May 2005.
2.        Fang Z. Peng, “harmonic sources and filtering approaches,” IEEE Industry Applications Magazine, vol. 7, pp. 18 – 25, Jul. /Aug. 2001.

3.        J. C. Wu and H. J. Jou, “Simplified control method for single-phase active power filter,” Proc. Inst. Elect. Eng., vol. 143, pp. 219 - 224, no. 3, May 1996.

4.        H. L. Jou, J. C.Wu, and H. Y. Chu, “New single-phase active power filter,” Proc. Inst. Elect. Eng.—Electr. Power Appl., vol. 141, pp. 129–134, no. 3, May 1994.

5.        C. Y. Hsu and H. Y. Wu, “A new single-phase active power filter with reduced energy-storage capacity,” Proc. Inst. Elect. Eng.Electr. Power Appl., vol. 143, pp. 25–30, no. 1, Jan. 1996.

6.        J. Barros, E. Perez ,“ An Adaptive Method for Determining the Reference Compensating Current in Single-Phase Shunt Active Power Filters,” IEEE Trans. Power Del., vol. 18, pp. 1578 – 1580, no. 4, Oct. 2003.

7.        M. Karimi-Ghartemani, H. Mokhtari, and M. R. Iravani, “A signal processing system for extraction of harmonics and reactive current of single phase systems,” IEEE Trans. Power Del., vol. 19, pp. 979–986, no. 3, Jul. 2004.

8.        M. K. Ghartemani and M. R. Iravani, “A nonlinear adaptive filter for online signal analysis in power system: application,” IEEE Trans. Power Del., vol. 17, pp. 617–622, no. 2, Apr. 2002.

9.        L. Zhou and Z. Li, “A novel active power filter based on the least compensation current control method,” IEEE Trans. Power Elec., vol. 15, pp. 655–659, No. 4, Jul. 2000.

10.     M. Welsh, P. Mehta, and M. K. Darwish, “Genetic algorithm and extended analysis optimization techniques for switched capacitor active filters - Comparative study,” Proc. Inst. Elect. Eng.—Electr. Power Appl., vol. 147, pp. 21–26, no. 1, Jan. 2000.

11.     M. El-Habrouk and M. K. Darwish, “A new control technique for active power filters using a combined genetic algorithm/conventional analysis,” IEEE Trans. Ind. Elec., vol. 49, pp. 58–66, no. 1, Feb. 2002.

12.     L. P. Kunjumuhammed, M. K. Mishra, “A Control Algorithm for Single Phase Active Power Filter under Non-Stiff Voltage Source,” IEEE Trans. Power Elec., vol. 21, 
p. 822 - 825 No. 3, May 2006.

13.     D. A. Torrey and A. M. A. M. Al-Zamel, “Single-phase active power filters for multiple nonlinear loads,” IEEE Trans. Power Elec., vol. 10, pp. 263–272, no. 3, May

14.     R. C. Castello, R. Grino, and E. Fossas, “Odd-harmonic digital repetitive control of a single-phase current active filter,” IEEE Trans. Power Elec., vol. 19, pp. 1060–1068, no. 4, Jul. 2004.

15.     K. Nishida, M. Rukonuzzman, and M. Nakaoka, “Advanced current control implementation with robust deadbeat algorithm for shunt single phase voltage-source type active power filter,” IEE Proc. Elect. Eng Electr. Power Appl., vol. 151, pp. 283–288, no. 3, May. 2004.

16.     A. M. Stankovic, G. Escobar, and P. Mattavelli, “Passivity-based controller for harmonic compensation in distribution lines with nonlinear loads,” in Proc. IEEE Power Elec. Specialists Conf. (PESC), vol. 3, pp. 1143–1148, Jun. 2000,

17.     H. Akagi, “Active Harmonic Filters,” in Proc. IEEE, vol. 93, pp. 2128 – 214, no. 12, Dec. 2005.

18.     S. Bhattacharya and D. M. Divan, “Synchronous frame based controller implementation for a hybrid series active filter system,” Ind. App. Conf., Thirtieth IAS
Annual Meeting, IAS '95., vol. 3, pp. 2531 - 2540, Oct. 1995.

19.     Wu Longhui, Zhuo Fang, Wang Zhaoan, “Soft Phase Locked Loop for Active Power Filter Applied in Small Rating Stand-alone Power System,” Power Elec. Specialists Conf. (PESC 2007). , pp. 2600 - 2606, Jun. 2007.

20.     F. D. Freijedo, J. Doval-Gandoy, O. Lopez and J. Cabaleiro, “Robust Phase Locked Loops Optimized for DSP Implementation in Power Quality Applications,” Ind. Elec. 34th Annual Conf. of IEEE (IECON 2008), pp. 3052-3057, Nov. 2008.

21.     IEEE Std. 519-1992, “IEEE Recommended Practice and Requirements for Harmonic Control in Electric Power Systems,” Published by IEEE, 1992.

22.     Electromagnetic Compatibility (EMC)—Part 3–4 Limits—Limitation of Emission of Harmonic Current in Low-Voltage Power Supply Systems for Equipment With Rated Current Greater Than 16 A, IEC Std. 61000- 3-4-1998.




A. Jameer Basha, V. Palanisamy, T. Purusothaman

Paper Title:

Multimodal Person Authentication using Qualitative SVM with Fingerprint, Face and Teeth Modalities

Abstract:   Multimodal biometrics systems are becoming increasingly efficient over the unimodal system, especially for the securing handheld devices. However, the challenge with this authentication system is the relative degradation of the biometric modalities involved in the development and test data respectively. To overcome this problem, in this paper we propose a novel Qualitative Support Vector Machine (SVM) classifier with Face, teeth, and fingerprint as biometric traits.  The test scores of individual modalities are adjusted according to their relative quality and then passed to binary SVM classifier. The experiments were conducted over a database collected from 20 individuals with three instances of all the three traits. The performance analysis of the fusion techniques revealed that the Equal Error Rates (EER) of 1.22%, 1.46%, and 1.88% for the qualitative SVM, raw score SVM and weighted summation rule classifiers respectively. On the other hand, the equal error rates for unimodal systems are 7.4%, 5.09% and 4.6% for teeth, face and fingerprint biometrics traits respectively.  Hence, we confirmed that the proposed qualitative SVM method outperformed other raw score fusion techniques and unimodal classifiers.               

  Multimodal biometrics, fingerprint verification, teeth recognition, face recognition, SVM classifier


1.        Jain, A.K., A. Ross and S. Pankanti, 2004. ” An introduction to biometric recognition” . IEEE Trans. Circuits Syst. ideo Technol., 14: 4-20. ISSN: 1051-8215
2.        Veeramachaneni, K., L.A. Osadciw and P.K. Varshney, 2005. “ An adaptive multimodal biometric management algorithm” . IEEE Trans. Syst. Man Cybern. C Appl. Rev., 35: 344-356. ISSN: 1094-6977

3.        Kumar, A., V. Kanhangad and D. Zhang, 2010. “A new framework for adaptive multimodal biometrics management”. IEEE Trans. Inform. Forensics Security, 5: 92-102. SSN: 1556-6013

4.        Tae-Woo KIM, Tae-Kyung CHO, "Teeth Image Recognition for Biometrics", IEICE TRANSACTIONS on Information and Systems Vol.E89-D No.3 pp.1309-1313, 2006.

5.        K. Prajuabklang, P. Kumhom, T. Maneewarn, K. Chamnongthai, "Realtime Personal Identification from Teeth-image using Modified PCA", Proceeding, the 4-th information and computer Engineering Postgraduate Workshop, Vol. 4, No. 1, pp.172-175, 2004.

6.        C. Nadee, P. Kumhom, K. Chamnongthai, "Improved PCA-Based Personal Identification Method Using Invariance Moment", The thirdInternational Conference on Intelligent Sensing and Information Processing, December 14-17, 2005.

7.        Yang, J., L. Liu and T. Jiang, 2002. “An improved method for extraction of fingerprint features.”  Proceeding of the 2nd International Conference Image and Graphics, Anhui, China, Aug.

8.        Chan, K.C., Y.S. Moon and Cheng, 2004. “Fast fingerprint verification using subregions of fingerprint images.”  IEEE Trans. Circuits Syst. Video Technol., 14.

9.        R. O. Duda and P. E. Hart, “Pattern Classification and Scene Analysis”. John Wiley & Sons, 1973.

10.     E. Erzin, Y. Yemez, A. Tekalp, "Multimodal speaker identification using an adaptive classifier cascade based on modality reliability", IEEE Transaction on Multimedia, vol. 7, no. 5, pp. 840-852, 2005.

11.     T. Wark, S. Sridharan, "Adaptive fusion of speech and lip information for robust speaker identification", Digital Signal Process, vol. 11, no. 3, pp. 169-186, 2001.

12.     P. Verlinde, G. Chollet and M. Acheroy, "Multi-Modal Identity Verification using Expert Fusion",  Information Fusion, no. 1, pp. 17-33, Elsevier, 2000.

13.     Dong-Ju Kim, Jeong-HoonShin and Kwang-SeokHong, “Teeth recognition based on multiple attempts in mobile device”, Journal of Network and Computer Applications 33 (2010) 283–292, Elsevier 2010.

14.     Dong-Ju Kim and Kwang-Seok Hong, “Multimodal Biometric Authentication using Teeth Image and Voice in Mobile Environment”, IEEE Transactions on Consumer Electronics, Vol. 54, No. 4, NOVEMBER 2008.

15.     C. Sanderson and K. K. Paliwal, "Adaptive Multi- Modal Person Verification System," Proceedings of the First IEEE Pacific-Rim Conference  on Multimedia, 2000.

16.     P. Verlinde, G. Chollet and M. Acheroy, "Multi-Modal Identity Verification using Expert Fusion", Information Fusion, no. 1, pp. 17-33, Elsevier, 2000.




N.Kirthika, Nisha Lali .R, Rejeesh.R S

Paper Title:

An Efficiednt Programmable Frequency Divider with Improved Division Ratio

Abstract:   The frequency divider is an important building block in today’s high speed integrated circuits. Frequency divider is the most power hungry block in the communication system. Considering the scope of the frequency divider An Efficient Programmable Frequency Divider (PD) is presented. In this paper a shared counter with a small control circuit is exploited using Reduced Module Control Signal generator (RMCS).This will reduce the output load capacitance and the redundant counter operations in the divider. A Dual Modules Prescaler (DMP), which gives initial division ratio for the input signal by N or N+1.Dividing factor of the Efficient PD can increased by modifying DMP circuit for 16 or 17.  A novel glitch less D flip-flop is also designed by considering the switching activities of the internal nodes of the flip-flop.

  Dual modulus prescaler (DMP), programmable divider (PD), Reduced module control signal generator (RMCS).


1.       Agnelli, F. Albasini, G. Bietti, I. (2006) ‘Wireless Multi-standard Terminals: System Analysis And Design Of A Reconfigurable RF Frontend’ IEEE Circuits Syst. Mag., 6, (36), 38–59.
2.       Chuang, Y. Lee, H .Yen, R H. Jang, J F. Lee, Juang, S L. (2006) ‘A     Wide Locking Range and Low Voltage CMOS Direct Injection Locked    Frequency Divider’, IEEE Microw. Wireless Compon. Lett., 16, (5), 299–301.

3.       Do, M A. Yu, X P. Ma, J G. Yeo, K S. Wu, p. Zhang, M. (2003)‘GHz Programmable Counter With Low Power Consumption’, Electronics Letters, 39, (22), 1572–1573.

4.       Guermandi, D. Franchi, E., et al (2002) ‘A CMOS Programmable   Divider for RF Multistandard Frequency Synthesizers’.Proc. Eur. Solid State Circuits Conf, pp. 843–846.

5.       Han, S. Youn, H. Kim Y S, Yu, C S. Park, H K.   (2003)  ‘Prescaler Using Complementary Clocking Dynamic Flip-Flop’,   Electronics      Letters, 39, (9), pp. 709–710.

6.       Kim, K. Lee Y, Kim W K, Kim, H (2008) ‘Low-power And Programmable Divider for Multi-Standard frequency Synthesizers Using Reset Modulus Signal Generator’, Proc. 2008 Asian Solid-State Circuits Conf., 77–80.

7.       Krishnapura, N. Kinget, P.R.  (2000) ‘A 5.3-GHz programmable Divider For HiPerLAN in 0.25-mm CMOS’, IEEE J. Solid-State Circuits, 35, (7), pp. 1019–1024.

8.       Navarro, J. Noije, W V. (2002) ‘Extended TSPC Structures with Double Input/output Data Throughput for Gigahertz CMOS Circuit Design’, IEEETrans.VLSI Syst., 10, (3), pp. 301–308.

9.       Pellerano, S. Levantino, S. Samori, C.   Lacaita, A L. (2004)   ‘A 13.5-mW 5-GHz Frequency Synthesizer with Dynamic-logic Frequency Divider’, IEEE J.Solid-State Circuits, 39, (2), pp. 378–383
10.     Rabaey, J. Chandrakasan, M.  Nikolic, B. (2005) ‘Digital Integrated Circuits’, (Prentice-Hall,  2nd edn.).

11.     Rana, R.S. (2005) ‘Dual-modulus 127/128 FOM Enhanced Prescaler Design In0.35mm CMOS Technology’, IEEE J. Solid-StateCircuits, 40, (8), pp.  1662 1670.

12.     Sivonen, P. Tervaluoto,  J.  Mikkola, Parssinen, N. (2006) ‘A 1.2-V RF Front- end with On-chip VCO For PCS1900 Direct Conversion Receiverin 0.13-mm CMOS’, IEEE J. Solid-State Circuits, 41, (2), pp. 384- 394.

13.     Song, E. Koo, Y.  Jung, Y. Lee, D. Chu, S., Chae, S. (2005)  ‘0.25-mm CMOS.

14.     Vaucher, C S. Ferencic, I. Locher,S. Sedvallson, S. Voegeli, U. Wang, Z. (2000) ‘A Family Of low-Power Truly Modular Programmable Dividers In Standard0.35-mm
CMOS Technology’, IEEE J. Solid-State Circuits, 35,  (7), pp. 1039–1045.

15.     Woo, K.  Liu, Y. Nam, E.  Ham, D. (2005) ‘Fast-lock Hybrid PLL Combining Fractional-N and Integer-N Modes of Differing Bandwidths’, IEEE J. Solid State Circuits, 43, (2), pp. 379–389.

16.     Yang, Y C. Yu, Y, Wang, T. Lu, S. (2005) ‘A Dual-mode Truly Modular Programmable Fractional Divider Based On 1/1.5 Divider Cell’,IEEE Microw. Wireless Compon. Lett., 15, (11), pp. 754–756.

17.     Yu, X.P. Do, M.A. Jia, L. Ma, J.G. Yeo, K.S. (2005) ‘Design of Low Power Wide-band High Resolution Programmable Frequency Divider’, IEEETrans. VLSI Systems, 13, (9), pp. 1098–1103




Manish Ranjan Pandey, Manoj Kapil, Sohan Garg

Paper Title:

Conversion of Citizens into E-Citizens: An Approach to Make E-Governance more Effective

Abstract:   Though E-Government initiatives in India have gained momentum in the past decade, the citizen participation is missing. Geographical, social, & economical disparities among citizens are the biggest barriers for e-governance. Illiteracy, lack of infrastructure, security and privacy of personal and financial data are other constraints that hamper e-governance efforts. Citizens’ participation should be increased against these constraints if we want good returns on investment from our e-governance efforts. The most benefits will be achieved if the e-governance is citizen-centric which itself will transform citizens to become active participators in establishing e-democracy.

  Illiteracy, e-democracy, security, privacy.


1.        Pacific Council On International Policy,  2002, Roadmap for E-government in the Developing World, The Working Group on E-Government in the Developing World, 
2.        (Marawar T et al., 2010) Marawar T., Kale S.,  Araspure K., E Governance, India, 2010 International Conference on Data Storage and Data Engineering, IEEE, 2010.
3.        Marita V., Westerhoudt E., 2008, "Trends in government communication in The Netherlands", Journal of Communication Management, Vol. 12(1), pp.18 – 29. 
4.        Yong. J.S.L, 2004, Promoting Citizen-Centered Approaches to e-Government Programmes - Strategies & Perspectives from Asian Economies, NCS, Singapore; Second APEC High-Level Symposium on e-Government, Acapulco, Mexico. 
5.        Balnaves M., Allen M., 2009, E-governance As Digital Ecosystem: A New Way to Think about Citizen Engagement and the Internet? International Conference on e-Government (ICEG), Boston. 
6.        Alshawi S., Alalwany H., 2009, E-government evaluation: Citizen's perspective in developing countries. Information Technology for Development, 15: 193–208. doi: 10.1002/itdj.20125. 
7.        Oates B. J., 2003, “The potential contribution of ICTs to the political process”, EJEG, Volume 1, Issue 1, pp. 33-42,
8.        VonHoffman C., 1999, ‘The Making of E-Government”, CIO Enterprise Magazine, 
9.        Kettani D., 2004, “Sustainable E-Government for the City of Fez”, Africa,
10.     Subramanian M., 2007, Theory and practice of e-governance in India: a gender perspective, ACM International Conference Proceeding Series; Vol. 232.
11.     DeBenedictis A., Howell W., Figueroa R., 2002, E-government defined: an overview of the next big information technology challenge, International Association for Computer Information Systems. 
12.     Hossan, G. et al., C., Chowdhury, M., Kushchu, I. (2005): Prospects of Using m-Technologies for Disster Information Management in Bangladesh and other LDCs, EURO mGOV 2005, Brighton, UK, pp. 243-253.
13.     Obeidat Rand A., Emad A. Abu-Shanab, (2010), Drivers of E-Government and E-Business in Jordan, Journal Of Emerging Technologies In Web Intelligence, Vol. 2, No. 3. 14.     Parston G., 2010, Beyond the e-government hype, Outlook,




T. Subramani

Paper Title:

Traffic Study On Road Links and  Estimate the Fund required for Identified  Road Improvement Projects in Major Urban Centre

Abstract:  Salem is the fifth largest city with a population of 7.54 lakhs (2011) in Tamil Nadu.   Local Authorities faced with great difficulties to identify required various road improvement projects. Repair or improvement works may have to be under taken on a basis which has to be decided based on socio-economic, administrative, technical, political factors etc., The identified road network selected for the study comprises 162 road links in Salem Corporation.   Existing    traffic condition, surface condition of carriageway, street lighting, footpath condition and drainage condition in the Salem Corporation area has been studied in detail. Traffic volume count survey was conducted on the idendified 162 road links in Salem Corporation. Identify the type of transport facilities required for the road links. In Salem Corporation area 44 road links required removal of onstreet parking and encroachment, 52 road links required widening of carriageway ,  23 road links required traffic management measures with extrawidening to carry the existing traffic flow efficiently. Total fund required for identified various road improvement projects have been calculated as Rs.100.16 Crores.

  Traffic, Road links, estimate, fund  


1.       DTCP (1986), ‘Short term improvement program ME – Traffic and Transportation study for Coimbatore, Madurai, Trichy and Salem’, DTCP, Tamil Nadu
2.       Hanspeter Georgi (1973),`Cost- Benefit Analysis and Public Investments in Transport: A Survey’, First Edition, Butter Worths (Publishers),London.

3.       Kadiyali.L.R.(2007),`Traffic Engineering and Transport  Planning’, 7th edition, Khanna publishers, Delhi.

4.       Khanna S.K – Justo C.E.G (2010),` Highway Engineering’,9th edition, Nem Chand and Bros. publishers, Roorkee(U.P) Lindsay R. Peat (1982),`Practical Guide to
DBMS selection’, Walter de Grawyter, New York.

5.       Meyer M.d.Miller E.J (1984),`Urban Transportation Planning’, Mcgraw – Hill series, New Delhi.

6.       Subramanian P. (1990) ,`Capacity restrained trip assignment model for Madras City’, ME Urban Engineering Thesis, Madras – 600025.

7.       V.N.Vazirani & S.P.Chandola, `Transportation Engineering  Vol.I ’, 5th edition,  Khanna Publishers, New Delhi

8.       Dr.L.R.Kadyali & Dr.N.B.Lal,` Principles and Practices of Highway  Engineering, 5th edition,  Khanna Publishers, New Delhi

9.       B.L.Gupta & Amit Gupta `Highway and bridge Engineering’3rd edition Standard Publishers Distributers, New Delhi

10.     C.Jotin Khisty & B.Kent Lall,` Transportation Engineering’ 3rd edition, PHI Learning Private Limited, New Delhi

11.     Gurcharan Singh, `Highway Engineering’5rd edition Standard Publishers Distributers, New Delhi

12.     R.K. Khitoliya, `Principles   of Highway Engineering’ 1st edition, Dhanpat Rai Publishing Company, New Delhi.

13.     DTCP (1999), ‘Comprehensive Traffic and Transportation Study for Salem`, Pallavan Transport Consultancy Services Ltd., Chennai, Tamil Nadu.




Avinash S. Kapse, Vishal S. Patil, Nikhil V. Patil

Paper Title:

E- Recruitment

Abstract:   Now a day the traditional method of recruitment has been revolutionized by the influence of the Internet. Hence In the last decade, the use of Internet has dramatically changed the face of HR recruitment and the ways organizations think about the Recruiting methods. In the next coming years, online recruitment and hiring new candidate is continued their explosion and Growth. Presently, e- recruitment has been adopted in many organizations like large organizations as well as in small Size companies, Even Most organizations are already using e-recruitment to post jobs and accept Resumes on the Internet, and correspond with the applicants by e-mail. It brings the benefits to the organizations. In this article, there will be an introduction on e-recruitment and its development process. There will also be a discussion on the various advantages and disadvantages of e-recruitment practice broadly taken from various literatures.

  Explosion, Growth, Internet.


1.        A research paper by Barber Linda on “Development of online recruitment” www.employment
2. full-report,synopsys.doc



5.     A research paper by vinky sharma on “Impact of E-recruitment on human resource supply chain management” %20Vinky%20Sharma.pdf

6. an047449.pdf

7.        A research paper by Carolien C. Handlogten on “ Implementation of e- recruitment”,






V. Priyanka, M. Nireesha, V. Venu Kumar, N. Venkat Ram, A. S. N. Chakravarthy

Paper Title:

CRT and ART Based Watermarking Scheme in DCT Domain

Abstract:   In this paper, we propose Chinese Remainder Theorem (CRT) and Aryabhata Remainder Theorem (ART) based watermarking scheme that work in the Discrete Cosine Transform (DCT) domain.CRT based scheme is more resistant to different types of attacks, particularly to JPEG compression; in addition, it improves the security feature of the watermarking scheme. Experimental results have shown that the proposed scheme makes the watermark perceptually invisible and has better robustness to common image manipulation techniques. ART-based algorithm can be applied to any kind of moduli and its computation cost is less than that of the CRT-based algorithm. Both techniques can be applied for protection of images and information.

  CRT, ART, DCT, Residue, Remainder, Inverse.


1.        C. Ding, D. Pei, and A. Solomaa, Chinese Remainder Theorem: Applications in Computing, Coding, Cryptography, World Scientific, Singapore, 1996. [2] N. Szabo and R. Tanaka, Residue Arithmetic and ItsApplications to Computer Technology, McGraw Hill, NewYork, 1967.
2.        N. Szabo and R. Tanaka, Residue Arithmetic and ItsApplications to Computer Technology, McGraw Hill, New York, 1967.

3.        C. C. Chang and Y. P. Lai, “A Fast Modular Square Computing Method Based on the Generalized Chinese Remainder Theorem for Prime Moduli”, Applied Mathematics and Computation, Vol. 161, No. 1, pp. 181-194,2005.

4.        A. S. Fraenkel, “New Proof of the Generalized Chinese Remainder Theorem”, Proceedings of American Mathematical Society, Vol. 14, pp. 790-791, 1963.

5.        Y. P. Lai and C. C. Chang, “Parallel Computational Algorithms for Generalized Chinese Remainder Theorem”,Computers and Electrical Engineering, Vol. 29, pp. 801-811,2003.

6.        H. Liao and X. G. Xia, “A Sharpened Dynamic Range of a Generalized Chinese Remainder Theorem for Multiple Integers”, IEEE Transactions on Information Theory, Vol. 53,No. 1, pp. 428-433, 2007. 

7.        Y. Wang, “Residue-to-Binary Converters Based on New Chinese Remainder Theorem”, IEEE Transactions on Circuits and Systems II: Analog and Digital Signal Processing, Vol.47, No. 3, pp. 197-205, 2000.

8.        X. G. Xia and K. Liu, “A Generalized Chinese Remainder Theorem for Residue Sets with Errors and Its Application in Frequency Determination from Multiple Sensors with Low Sampling Rates”, IEEE Signal Processing Letters, Vol.12, No.11, pp. 768-771, 2005.

9.        T. R. N. Rao and C. H. Yang, “Aryabhata Remainder Theorem: Relevance to Public-Key Crypto-Algorithms”,Circuits, Systems, and Signal Processing, Vol. 25, No. 1,pp.1-15, 2006.

10.     V.M. Potdar, S. Han and E. Chang, “A survey of digital image watermarking techniques”, IEEE Intl. Conf. Industrial Informatics, Perth, Australia, Aug. 2005, pp. 709 – 716.

11.     E. Kougianos, S. P. Mohanty and R. N. Mahapatra, “Hardware assisted watermarking for multimedia,” Computers and Electrical Engineering 35 (2009) 339–358.

12.     C. Shoemaker, “Hidden Bits: A Survey of Techniques for Digital Watermarking”, Available online:, Virtual Union, 2002.

13.     V.M. Potdar, S. Han and E. Chang, “A survey of digital image watermarking techniques”, IEEE Intl. Conf. Industrial Informatics, Perth, Australia, Aug. 2005, pp. 709 – 716. 

14.     C-T. Hsu and J-L. Wu, “Hidden digital watermarks in images”, IEEE Trans. on Image Processing, vol. 8, no. 1, pp. 58 – 68, Jan 1999.

15.     J. Cox, J. Killian, F.T. Leighton and T. Shamoon, “Secure spread spectrum watermarking for multimedia,” IEEE Transon Image Process., vol. 6, no. 12, pp. 1673–1687, Dec 1997.

16.     C-H. Wu, J-H. Hong and C-W. Wu, "RSA cryptosystem design based on the Chinese remainder theorem", in Proc. AsiaSouth Pacific Design Automation, Yokohama, Japan, 2001,pp. 391 – 395.

17.     J. S. Shyong and Y-R. Chen, "Threshold Secret Image Sharing by Chinese Remainder Theorem," IEEE Asia-Pacific Services Computing Conference, Yilin, Taiwan, Dec. 2008, pp.1332- 1337.

18.     P. Meerwald and A. Uhl, “Survey of wavelet-domain watermarking algorithms”, in Proc. of SPIE, Electronic Imaging, Security and Watermarking of Multimedia Contents III, vol.4314, pp. 505-516, 2001.




Nagendra Sah, Neelam Rup Prakash, Deepak Bagai

Paper Title:

Application of CSP in Optimizing The Path Loss of Wireless Indoor Propagation Model

Abstract:   Constraint satisfaction programming(CSP) is an emergent software technology for declarative description and effective solving of large particularly combinational problem especially in term of planning and scheduling. Constraint programming is the study of computational system based on constraints. The idea of constraint programming is to solve problem by stating constraints about the problem and consequently finding the solution satisfying all the constraints. In this paper the application of constraint satisfaction programming is used in predicting the path loss of various empirical propagation models using chronological backtrack algorithm, which is basic algorithm of CSP. After predicting the path loss at different set of parameter such as frequencies), floor attenuation factor (faf), path loss coefficient(n), penetration attenuation factor (paf), we find the optimum set of parameter (frequency (f), floor attenuation factor (faf), path loss coefficient(n), penetration attenuation factor (paf) at which path loss is minimum with the help of Branch and bound algorithm, which is used to optimized the constraint satisfaction problem.

  CSP;   Path Loss; Propagation Model; Wireless Communication.


1.       Tope r. Karem,H. Anthony chan, “A Low cost design of next generation Sonet/Sdh network with multiple constraint”, IEEE, National Research Foundation, 2007
2.       Stuart Bain, John Thorton, Abdul Sattar “Evolving Algorithm For Constraint Satisfaction”, IEEE, pp 265-272,  2004.

3.       Edward Tsang, “Foundation of constraints satisfaction”, Department of computer science University of Essex Colchester Essex, UK

4.       Tiong Sieh Kiong,  Zeti Akma, Loo Hooi KAR, poh Tzye Perng, “Propagation Loss models characterization for GSM 900MHz at Kaula Lumpur and putrajaya”, College of Engineering, Universiti Tenaga Malaysia

5.       Theodore S. Rappaport, “Wireless Communication System: Principles and Practice”, Second Edition, Prentice Hall of India Private Limited, 2005.

6.       V.S Abhayawardhana, I.J Wassell, D. Crosby,M.P. Sellars,M.G. Brown “Comparison of Empirical propagation path Loss Models for Fixed Wireless Access Systems”, BT Mobility Research Unit, U.K., University of Cambridge.

7.       Josip Milanovic, Snjezana Rimac-Drlje,Krunoslav Bejuk, “Comparison of propagation model Accuracy for Wi MAX on 3.5 GHz”, IEEE,1-4244-1378-8/07, 2007.

8.       Paolo Barsocchi, “Channel models for terrestrial wireless  communication”, ISTI Institute.




Shweta Dhawan

Paper Title:

Feature Extraction & Image Registration of the Palma Dorsa by Using Bifurcation Structures

Abstract:   In this paper, we perform feature extraction of venal pattern of hand dorsal images. Various minutiae points are discussed. Bifurcation points and endpoints are calculated and plotted for the hand images. The three branching angles are used for the characteristic vector of a bifurcation point. Further, Bifurcation structures are proposed for Palma Dorsa. The bifurcation structure is composed of a master bifurcation point and its three connected neighboring bifurcation points for Image Registration. Bifurcation structures make the method robust to image translation and scaling. Affine model has been used for the transformation. Mosaic hand and vein images are generated. In this work, we have used MATLAB R2009a, version 7.8.0 for coding.

  Bifurcation Structures, Characteristic Vector, Feature extraction, Image registration.  


1.       Sagar V.K., Alex K.J.B., "Hybrid Fuzzy Logic and Neural Network Model for Fingerprint Minutiae Extraction", Int. Joint Conf. on Neural Networks, Vol.5, 10-16 July 1999,pp .3255 - 3259.
2.       D.Maio and D.Maltoni, "Direct Gray Scale Minutiae Detection in Fingerprints", IEEE Trans. PAMI, vol. 19, No. 1. pp. 27-40, 1997

3.       Barbara Zitova, Jan Flusser, “Image registration methods: a survey”, Image and Vision Computing 21 (2003) 977–1000.

4.       L.G. Brown, “A survey of image registration techniques,” ACM Computing Surveys, vol. 24, no. 4, pp. 325-376, Dec.1992.

5.       Maleika Heenaye- Mamode Khan, “A New Method to Extract Dorsal Hand Vein Pattern using Quadratic Inference Function”, (IJCSIS) International Journal of Computer Science and Information Security, Vol. 6, No. 3, pp. 026-030, December 2009

6.       Yu Chengbo, Qing Huafeng, Zhang Lian, “A Research on Extracting Low Quality Human Finger Vein Pattern Characteristics”, International Conference on Bioinformatics and Biomedical Engineering, pp: 1876 – 1879, 2008.

7.       Ajay Kumar, K. Venkata  Prathyusha, “Personal Authentication using Hand Vein Triangulation and Knuckle Shape”, IEEE Transactions on Image Processing, vol. 38, pp. 2127-2136, September 2009.

8.       Dend Jinpeng, Zhang Yanzhi, “Hand Veins Feature Extraction Based on Morphology and Cellular Neural Network”, International Conference on Computer Application and System Modeling, Volume :  14, pp: V14-175 - V14-178, 2010.

9.       Kejun Wang, Hui Ma, Oluwatoyin P. Popoola, and Xuefeng Li, “A Novel Finger Vein Pattern Extraction Method Using Oriented Filtering Technology”, Proceedings of the 8th World Congress on Intelligent Control and Automation, July 6-9 2010, Jinan, China.

10.     S. Ranade and A. Rosenfeld, “Point pattern matching by relaxation,” Pattern Recognition, vol. 12, no. 4, pp. 269-275, Nov. 1980.

11.     B. Lucas and T. Kanade, “An iterative image registration technique with an application to stereo vision,” in Proc. DARPA Image Understanding Workshop, pp. 121-130, Apr. 1981.

12.     Xinyu Guo, Wynne Hsu, Mong Li Lee, Tien Yin Wong, “A Tree Matching Approach for the Temporal Registration of Retinal Images”.

13.     So Sasatani, Xian-Hua Han and Yen-Wei Chen, “Image registration using PCA and Gradient Method for Super-resolution Imaging”, International Conference on Software Engineering and Data Mining, pp: 631 – 634, June 2010.




Density Based Clustering Scheme Using Dynamic Dissimilarity Measures

Paper Title:

Density Based Clustering Scheme Using Dynamic Dissimilarity Measures

Abstract:   Clustering methods are used support estimates of a data distribution have newly attracted much attention because of their ability to generate cluster boundaries of arbitrary shape and to contract with outliers efficiently. This paper proposes, Density based clustering using dynamic dissimilarity measure based on a dynamical system associated with Density estimating functions. Hypothetical basics of the proposed measure are developed and applied to construct a clustering method that can efficiently partition the whole data space. Clustering based on the proposed dissimilarity measure is robust to handle large amount of data and able to estimate the number of clusters automatically by avoid overlap. The dissimilarity values are evaluated and clustering process is carried out with the density values.

  Clustering, kernel methods, dynamical systems, equilibrium vector, support, density.


1.        Daewon Lee and Jaewook Lee “Dynamic Dissimilarity Measure for Support-Based Clustering” IEEE Transactions on Knowledge and Data Engineering, vol. 22, no. 6, June 2010.
2.        F. Camastra and A. Verri, “A Novel Kernel Method for    Clustering,” IEEE Trans. Pattern Analysis and Machine  Intelligence, May 2005.

3.        T. Ban and S. Abe, “Spatially Chunking Support Vector  Clustering Algorithm,” Proc. Int’l Joint Conf. Neural Networks, 2004. 

4.        J. Lee and D. Lee, “An Improved Cluster Labeling Method for Support Vector Clustering,” IEEE Trans. Pattern Analysis and Machine Intelligence, 2005.

5.        H.-C. Kim and J. Lee, “Clustering Based on Gaussian Processes,” Neural Computation, vol. 19, no. 11, pp. 3088-3107, 2007.

6.        D. Lee  “Equilibrium-Based Support Vector Machine for Semi- Supervised Classification,” IEEE Trans. Neural Networks, 2007.

7.        D. Zhang, “A Novel Kernelised Fuzzy C-Means Algorithm with Application in Medical Image Segmentation,” Artificial Intelligence in Medicine, 2004.
8.        D. Lee, “Domain Described Support Vector Classifier for Multi- Classification Problems,” Pattern Recognition, 2007.
9.        J. Lee, “A Novel Three-Phase Trajectory Informed Search Methodology for Global Optimization,” J. Global  Optimization, 2007. 

10.     J. Lee, “An Optimization-Driven Framework for the Computation of the Controlling UEP in Transient Stablity Analysis,” IEEE Trans. Automatic Control, 2004.

11.     J. Park, “Support Vector Clustering Combined with Spectral Graph Partitioning,” Proc. 17th Int’l Conf. Pattern Recognition, 2004.

12.     W.J. Puma-Villanueva, “Improving Support Vector Clustering with Ensembles,” Proc. Int’l Joint Conf. Neural Networks, 2005.

13.     M.S. Hansen and R. Larsen, “Robust Pseudohierarchical Support Vector Clustering,” Proc. Scandinavian Conf. Image Analysis, 2007.

14.     J. Lee, “Dynamic Characterization of Cluster Structures for Robust and Inductive Support Vector Clustering,” IEEE Trans. Pattern Analysis and Machine Intelligence, 2006.




Neha Gosai, S. H. Patil

Paper Title:

Security Preservation Methods to Confidential Databases

Abstract:   Anonymization means to remove personal identifier or converted into non readable form by human to protect private or personal information. Data anonymization can be performed in different ways but in this paper k-anonymization approach is used. Suppose one person A having his own k-anonymous database and needs to determine whether database is still k-anonymous if tuple inserted by another person B. For some applications (for example, Student’s record), database needs to be confidential, So access to the database is strictly controlled. The confidentiality of the database managed by the owner is violated once others have access to the contents of the database. Thus, Problem is to check whether the database inserted with the tuple is still k-anonymous without letting the owner A and others (B) to know the content of the tuple and database respectively. In this paper, we propose a protocol solving this problem on suppression based k-anonymous and confidential database.

  Anonymization, Privacy, Confidentiality, Anonymous


1.       U.S. Department of Education. General Family Educational Rights and privacy Act (FERPA).
2.       B.C.M. Fung ,K. Wang, A.W.C. Fu and J. Pei, Anonymity for  Continuous Data Publishing Proc. Extending database Technology  Conference (EDBT),2008

3.       M.K.Reiter, A. Rubin. Crowds: anonymity with Web transctions.ACM Transactions on Information amd System Security (TISSEC),1(1),1998;66-92

4.       P. Samarati. Protecting respondent’s privacy in micro data release, IEEE Transactions on Knowledge and Data Engineering vol. 13,no. 6,pp.1010

5.       University of Miami Leonard M. Miller School of Medicine, Information Technology.

6.       Dr. Durgesh Kumar Mishra, Neha Koria, Nikhil Kapoor, Ravish Bahety ,A Secure Multi-Party Computation Protocol for  Malicious Computation Prevention for preserving privacy  during Data Mining, Vol. 3,No. 1,2009

7.       C. Blake and C. Merz, ―UCI Repository of Machine Learning Databases, E. Bertino and R. Sandhu, ―Database Security—  Concepts, Approaches and Challenges, IEEE Trans. Dependable and Secure Computing, vol. 2, no. 1, pp. 2-19, Jan.-Mar. 2005.





K. Anuradha, N. Tulasi Radha, T. Pavan Kumar

Paper Title:

A Decision Tree Algorithm for Uncertain Data

Abstract:   Classification is a classical problem in machine learning and data mining. Given a set of training data tuples, each having a class label and being represented by a feature vector, the task is to algorithmically build a model that predicts the class label of an unseen test tuple based on the tuple’s feature vector. One of the most popular classification models is the decision tree model. Decision trees are popular because they are practical and easy to understand. Rules can also be extracted from decision trees easily.   Tree learning algorithms can generate decision tree models from a training data set. When working on uncertain data or probabilistic data, the learning and prediction algorithms need handle the uncertainty cautiously, or else the decision tree could be unreliable and prediction results may be wrong. This paper presents a new decision tree algorithm for handling uncertain data.

  Classification, Decision tree, Prediction, Uncertain data.


1.        R. Agrawal, T. Imielinski, and A. N. Swami, “Database mining: A performance perspective,” IEEE Trans. Knowl. Data Eng., vol. 5, no. 6, pp. 914–925, 1993.
2.        C4.5: Programs for Machine Learning. Morgan Kaufmann, 1993, ISBN 1-55860-238-0.

3.        J. R. Quinlan, “Induction of decision trees,” Machine Learning, vol. 1, no. 1, pp. 81–106, 1986.

4. /public/ analytics/ decision tree. html




K.Naga Mallik, Ch. Radhika, D.Ujwala, H.M.Ramesh, A. Gowtham Kumar, P.Karthik

Paper Title:

A Compact Microstrip Patch Antenna with Triangular Snipped Slot for Wireless Applications

Abstract:   A compact microstrip patch antenna with a slot fed by coaxial probe is presented in this paper. The slot which is circular in shape with triangular truncations results three narrow bands. The patch is designed on FR4 substrate of thickness 1.6 mm and relative permittivity of 4.4. The size of the proposed antenna is 35mm x 45mm x 1.6mm. Return loss comparison is done for different feed locations. The proposed antenna is suitable for WiMax, Wi-Fi and WLAN applications. The simulations are carried out using Finite Element Method based Ansfot High Frequency Structure Simulator (HFSS).

  Microstrip patch, WLAN, Wi-Fi, WiMax.


1.        J Costantine, K Y. Kabalan, Ali El-Hajj, and Mohammad Rammal, “A New Multi-band Microstrip Antenna Design for Wireless Communications”, IEEE Transactions on Antennas and Propogation Magazine, Vol. 49, No. 6, Dec 2007.
2.        Cuthbert M. Allen, Atef Z. Elsherbeni, Charles E. Smith, Chun-Wen P. Huang and Kai-Fong Lee, “Tapered Meander Slot Antenna for Dual band personal wireless communication systems”, IEEE 2002.

3.        Vinod K. Singh, Zakir Ali and Dr. Shahanaz Ayub, “Design of Compact Rectangular Slot Microstrip Antenna for Mobile Communciation”, Global Journal of Researches 
n Engineering, vol. 10, pp. 52- 54.

4.        Y. C. Lee and J. S. Sun, “Compact printed Slot antennas for wireless Dual- and Multi- band operations”, Progress in Electromagnetics Research, PIER, 88, 289-305, 2008.

5.        Richard H. Chen and Yi- Cheng Lin, “Miniaturized Design of Microstrip-Fed Slot Antennas Loaded with C-Shaped Rings”, IEEE Antennas and Wireless Propagation Letters, vol. 10, 2011.

6.        Min-Chi Chang and Wei-Chung Weng, “A Dual-band printed dipole slot antenna for 2.4/5.2 GHz WLAN Applications”, IEEE, 2011.

7.        Boutheina Thili, “Design of Double C-slot Microstrip Patch Antenna for WiMax Application”, IEEE, 2010.

8.        Vedaprabhu. B and K. J. Vinoy, “A Double U-Slot patch antenna with Dual Wideband Characteristics”, IEEE, 2010.

9.        Yogesh Bhomia, Ashok Kajla and Dinesh Yadav, “V-Slotted Triangular Microstrip Patch Antenna”, International Journal of Electronics Engineering, 2(1), pp. 21-23, 2010.

10.     C. A. Balanis, Antenna Theory Analysis and Design, Second Edition, New York, Wiley, 1997.




R. Rahul, D. S. Ram Kiran, D.Ujwala, B. Harish, N. Anand Ratnesh

Paper Title:

Dimensional Variation Effects on the Performance of Slotted Millimeter Wave Antenna

Abstract:   A compact slotted micro strip patch antenna is proposed and designed in this paper for millimeter wave Radar applications. The antenna is designed on Quartz glass substrate of dielectric constant 3.78 with thickness of 0.8mm. The size of the proposed antenna is 4mm x 9mm x 0.8mm.  The proposed antenna resonates at three frequencies 24.42 GHz (24.17-24.69), 27.02 GHz (26.74 – 27.32) and 34.67 GHz (33.89 – 35.47). A comparative analysis is done by varying the dimensions of the slots in antenna. The proposed model is simulated using Finite Element Method based High Frequency Structure Simulator (HFSS).

  Dimensional variation, slot, millimeter wave antenna.


1.        C. L. Mak, R. Chair, K. F. Lee, K. M. Luk and A. A. Kishk, Half U-slot patch antenna with shorting wall", Electronics Letters, vol. 39, pp. 1779-1780, 2003.
2.        H. F. AbuTarbous et al., ‘Bandwidth Enhancement for Microstrip Patch Antenna Using Stacked Patch and Slot’, iWAT2009 IEEE International Workshop on Antenna Technology, 2-4 March 2009, Santa Monica, CA.

3.        Rafi, G. and L. Shafai, "Broadband microstrip patch antenna with V-slot," IEE Proc. Microw. Antenna Propag., Vol. 151, No. 5, 435-440, October 2004.

4.        Ayoub, A. F. A., "Analysis of rectangular microstrip antennas with air substrates," Journal of Electromagnetic Waves and Applications, Vol. 17, No. 12, 1755-1766, 2003.

5.        Aaron K.Shackelford, K.F.Lee, and K. M.Luk "Design of Small-Size Wide-Bandwidth Microstip patch antennas "Antennas and Propagation Magazine, IEEE Vol 45, issue 1,pp 75-83,Feb 2003.

6.        G. Gauthier, A. Courtay, and G. Rebeiz, “Microstrip antennas onsynthesized low dielectric-constant substrates,” IEEE Trans. Antennas Propag., vol. 45, pp. 1310–1314, Aug. 1997.

7.        T. Zwick, D. Liu, and B. Gaucher, “Broadband planar superstrat antenna for integrated millimeterwave transceivers,” IEEE Trans.Antennas Propag., vol. 54, pp.
2790–2796, Oct. 2006.

8.        J. Akkermans, M. van Beurden, and M. Herben, “Design of a millimeter- wave balanced-fed aperture-coupled patch antenna,” presented at the Eur. Conf. Antennas Propagation, Nice, France, Nov. 2006.




H. S. Behera, Sushree Sangita Panda, Jana Chakraborty

Paper Title:

Clustering-Based Deadline Monotonic Scheduling with Dynamic and Intelligent Time Slice for Real-time Systems

Abstract:   In this paper, clustering based deadline monotonic scheduling with dynamic and Intelligent Time Slice is proposed for real-time systems. The proposed algorithm determines the schedulability of a process, and groups the schedulable and unschedulable process into separate clusters. Then an improved Round Robin algorithm is used for all schedulable processes to calculate average turn-around time, average waiting time and context switch. Then the experimental analysis shows that the performance of the proposed algorithm is better in terms of average turnaround time, average waiting time and context switch.

  Real-time systems, Deadline monotonic scheduling(DM), Response Time Analysis Schedulability test, Clustering, Round Robin(RR) scheduling algorithm Turnaround time and Waiting time, Upper Quartile.


1.        H.S. Behera, Jana Chakraborty, Sushree Sangita Panda “Improved Deadline Monotonic Scheduling with dynamic and Intelligent Time Slice for real-time systems” department of computer science and engineering, V.S.S.U.T, Burla.
2.        N.C. Audsley , A. Burns , M.F. Richardson , A.J. Wellings “Hard Real-Time Scheduling: The Deadline-Monotonic Approach” Dept of Computer Science, University of York, York,YO1 5DD, England.

3.        Yaashuwanth .C & R. Ramesh “Intelligent Time Slice For Round Robin In Real Time Operating Systems” Dept of electrical and electronics engineering, Anna University Chennai, Chennai 600 025

4.        Audsley, N.C. (1990), Deadline Monotonic Scheduling, YCS 146, Dept. of Comp. Sci., Univ. of York.

5.        Barbara Korousic –Seljak (1994) “Task scheduling policies for real- time Systems” Journal on MICROPROCESSOR AND MICROSYSTEMS, VOL 18 NO. 9, pg501-512.

6.        Bur89a. A. Burns and A. J. Wellings, Real time Systems And Their Programming Languages, Addison Wesley(1989).

7.        Burns. A (1994) “Fixed priority scheduling with deadline prior to completion” Real time systems Research Group Department of computer science university of  york, UK.

8.        Sta88a. J. A. Stankovic, Misconceptions About Real Time Computing: A serious problem for next generation systems, IEEE Computer21(10), pp. 10-19(Oct 1988).

9.        Liu, C.L. and J. W. Layland (1973) scheduling algorithms for multiprogramming in a hard real time environmenJ. ACM, 20, pp.40-61

10.     Leung, J., and Whitehead, J. On the complexity of fixed priority scheduling of periodic, real time tasks.




S Arun Kumar, C Easwarlal, M Senthil Kumar

Paper Title:

Power System Stability Enhancement using Adaptive Neuro-Fuzzy Tuned Static Synchronous Series Compensator (SSSC)

Abstract:   This paper investigates the enhancement of voltage stability using Static Synchronous Series Compensator (SSSC). The continuous demand in electric power system network has caused the system to be heavily loaded leading to voltage instability. Under heavy loaded conditions there may be insufficient reactive power causing the voltages to drop. This drop may lead to drops in voltage at various buses. The result would be the occurrence of voltage collapse which leads to total blackout of the whole system. Flexible AC transmission systems (FACTS) controllers have been mainly used for solving various power system stability control problems. In this study, a static synchronous series compensator (SSSC) is used to investigate the effect of this device in controlling active and reactive powers as well as damping power system oscillations in transient mode. The Adaptive neuro fuzzy logic controller is used to tune the circuit and to provide the zero signal error. Results are compared with conventional PI controller. The dynamic performance of SSSC is presented by real time voltage and current waveforms using MATLAB software for IEEE 4 bus system.

  Static Synchronous Series Compensator (SSSC), Proportional-Integral Controller, Adaptive Neuro Fuzzy logic Controller, Real and Reactive Power Flow, Voltage Stability.


1.       M. Faridi, H. Maeiiat, M. Karimi, P. Farhadi and H. Mosleh (2011) “Power System Stability Enhancement Using Static Synchronous Series Compensator (SSSC)”  IEEE Transactions on Power System, pp. 387-391.
2.       Kalyan K. Sen, (1998) “SSSC - Static Synchronous Series Compensator: Theory, Modelling, and Applications”, IEEE Transactions on Power Delivery, Vol. 13, pp.241-246.

3.       Sandeep Gupta, R. K. Tripathi (2010) “Voltage Stability Improvement in Power Systems using Facts Controllers: State-of-the- Art Review”. IEEE Transactions on Power System, pp.1-8.

4.       H. Taheri, S. Shahabi, Sh. Taheri and A. Gholami (2009) “Application of Synchronous Static Series Compensator (SSSC) on Enhancement of Voltage Stability and Power Oscillation Damping”, IEEE Transactions on Power System, pp. 533-539. 

5.       Thieery Van Custem and Costas Vournas (1998), “Voltage stability of electrical power systems”, Kluwer academic publications.

6.       Abido M. A. (2009), “Power System Stability Enhancement Using Facts Controllers: A Review”, The Arabian Journal for Science and Engineering, Volume 34, pp. 153-172.

7.       B.N. Singh, A. Chandra, K.Al-Haddad and   B. Singh (1999) “Performance of sliding- mode and fuzzy controllers for a static synchronous series compensator”, IEEE proceedings, Volume 146, No.2, pp. 200-206.

8.       S.R.Khuntia, S. Panda (2010), Approach for TCSC-based control Design for power system stability Improvement” IEEE Transactions on Power System, pp. 149-154.




T R Shyama, R Satheesh Kumar, V Shanmugasundaram

Paper Title:

Design of FGSPI Controller Based Combined LFC and AVR of Two Area Interconnected Power Generating System

Abstract:   This work presents the Fuzzy Gain Scheduled proportional-integral controller (FGSPIC) parameters of Load Frequency Control (LFC) and Automatic Voltage Regulator (AVR) for two area interconnected power system. The proposed controller is used to tune the LFC and AVR .The LFC loop controls real power &frequency and AVR loop controls reactive power & voltage. To maintain the system parameters of the given system at nominal value, FGSPIC is proposed. This paper is proposed to show the interaction between the LFC and the AVR loops.  The system with its control method is going to implement in MATLAB software. Also, a conventional proportional and integral (PI) controller was used to control the same for the performance comparison. Two performance criteria were utilized for the comparison. The proposed method had superior features like, stable convergence characteristics, easy implementation and good computational efficiency.

  Automatic Voltage Regulator (AVR), Load Frequency Control (LFC), Fuzzy Gain Scheduled Proportional-Integral Controller (FGSPIC).


1.       A.Soundarrajan, Member ,IAENG, Dr.S.Sumathi, C.Sundar, “Particle Swarm Optimization Based LFC and AVR of Autonomous Power Generating System “, IAENG International journal of computer science , 2010.
2.       Elyas Rakhshani, Kumars Rouzbehi and Sedigheh Sadeh , “A New Combined Model for Simulation of Mutual Effects Between LFC and AVR Loops”, IEEE Transactions on power system, 2009.

3.       Ertugrul Cam and  Ilhan Kocaarslan, “ A Fuzzy Gain Scheduling PI Controller Application for an Interconnected Electrical Power System” , Electrical power systems research 73,264-274 2004.

4.       H.D. Mathur and S. Ghosh, “A Comprehensive Analysis of Intelligent Control for Load Frequency Control”, IEEE Power india conference, 2006.

5.       D.M. Vinod Kumar, “Intelligent Controllers for Automatic Generation Control”, IEEE Transactions on global connectivity in energy, computer, communication and control, 1988, pp557-574.

6.       P. Kundur, “Power System Stability and Control”, Tata Megraw Hill,Newyork, 1994
7.       M.S. Anower , “Fuzzy Frequency Controller for an AGC for the Improvement of Power System Dynamics”, 4th International conference on electrical & computer engineering, 2006.

8.       H.L. Zeynelgil, A. Demiroren, N.S. Sengor, “The Application of ANN Technique for Automatic Generation Control for Multi-Area Power System”, Electric power and energy systems, pp345-354, 2002.

9.       H.D. Mathur and H.V. Manjunnath, “Frequency Stabilization using Fuzzy Logic Based Controller for Multi-Area Power System”, The south pacific journal of natural science, pp22-30, 2007.

10.     A.R. Hasan, T.S. Martis , “Design and Implementation of a Fuzzy Based Automatic Voltage Regulator for a Synchronous Generator”,IEEE Transactions on energy conversion, 1994.

11.     Parveen Dabur, Naresh Kumar Yadav and Vijay Kumar, “Matlab Design and Simulation of AGC and AVR for Multi Area Power System and Demand Side Management”, International Journal of computer and electrical engineering, vol. 3, No.2, 2011.

12.     Hadi Saadat, eds 1999. “Power System            Analysis”, Mcgraw-Hill International edition , 2005.

13.     A. Khodabakhshian and N. Golbon, “Robust Load Frequency Controller   Design for Hydro Power Systems”,IEEE conference on control applications,pp28-31, 2005.

14.     J. Talaq, F. Al-Basri, “Adaptive Fuzzy Gain Scheduling for Load Frequency Control”, IEEE Transactions in power system,pp145-150, 1999.

15.     Parveen Dabur, Naresh Kumar Yadav and Vijay Kumar, “Matlab Design and Simulation of AGC and AVR for Multi Area Power System and Demand Side Management”, International Journal of computer and electrical engineering, vol. 3, No.2, 2011.

16.     A. Sreenath, Y.R. Atre, D.R. Patil, “Two Area Load Frequency Control with Fuzzy Gain Scheduling of PI Controller”, First International conference on emerging trends in engineering and technology, 2008.

17.     Sayed Mojtaba , “Load Frequency Control in Multi Area Electric Power System Using Genetic Scaled Fuzzy Logic”, International Journal of the physical science, pp377-385, 2011.

18.     N. Ndubisi Samuel, “An Intelligent Fuzzy Logic Controller Applied to Multi-Area Load Frequency Control”, American journal of scientific and industrial research, 2010.




M.Rupasri, P.Rajyalakshmi, V.Sangeeta

Paper Title:

A Study of Buffer Overflow Attacks

Abstract:   A computer buffer is an area of memory used for temporary storage of data when a program or hardware device needs an uninterrupted flow of information. A buffer overflow occurs when a program or process tries to store more data in a buffer than it was intended to hold. Since buffers are created to contain a finite amount of data, the extra information - which has to go somewhere - can overflow into adjacent buffers, corrupting or overwriting the valid data held in them.  In buffer overflow attacks, the extra data may contain codes designed to trigger specific actions, in effect sending new instructions to the attacked computer that could, for example, damage the user's files, change data, or disclose confidential information. This paper presents an overview of the buffer overflow attack and the countermeasures to defend that attack.

  Buffer overflow, Function pointers, Heap overflow, Stack overflow.


1.        Buffer Overflow Attacks by James C. Foster, Vitaly Osipov, Nish Bhalla, Niels Heinen and Dave Aitel , Syngress, 2005.

3.        Stack based overflows: detect and exploit by Morton Christiansen , SANS institute 2007.

4.        Buffer overflows for dummies, by Josef Neliben, SANS institute, 2002.

5.        A Buffer overflow study- attacks and defenses, by Pierre-Alain FAYOLLE, Vincent GLAUME, ENSEIRB, Networks and Distributed Systems, 2002.

6.        Format string attacks, by Tim Newsham, Guardent, Inc., September 2000.




Ketaki Chopde, Pratik Gosar, Paras Kapadia, Niharika Maheshwari, Pramila M. Chawan

Paper Title:

A Study of Classification Based Credit Risk Analysis Algorithm

Abstract:   Almost all business organizations these days generate large amounts of data regarding their work. Simply stated, data mining refers to extracting or “mining” knowledge from large amounts of data. The information thus extracted can be used by organizations in decision making process. In this paper, we study the data mining techniques used for credit risk analysis, in particular the decision tree technique.

  Data Mining, Credit risk analysis, Decision tree.


1.       Jiawei Han, MichelineKamber, “Data Mining Concepts and Technique”, 2nd edition.
2.       Abbas Keramati, NiloofarYousefi, “A Proposed Classification of Data Mining Techniques in Credit Scoring", International Conference on Industrial Engineering and Operations Management, 2011.

3.       Yap Bee Wah,  Irma Rohaiza Ibrahim, “Using Data Mining Predictive Models to Classify Credit Card Applicants”.

4.       QiweiGan, BinjieLuo, Zhangxi Lin, “Risk Management of Residential Mortgage in China Using Date Mining A Case Study”, 2009 International Conference on New Trends in Information and Service Science.

5.       Bernard ienko, LjupCoTodorovski, and Sago Dieroski, “A comparison of stacking with meta decision trees to bagging, boosting, and stacking with other methods”

6.       Jingping Chen, Haiwei Pan, Qilong Han, Linghu Chen, Jun Ni, “Credit Risk Assessment Model Based On Domain Knowledge Constraint”, 2008 International Multi-symposiums on Computer and Computational Sciences.

7.       Fei Li, JunXu, Zhi-Tong Mu, Ya-Lou Huang, “Data Mining-Based Credit Evaluation For Users Of CreditCard”

8.       Qiuju Yin, Ke Lu, “Data Mining Based Reduction on Credit Evaluation Index of Bank Personal Customer”, 2010 International Conference on Future Information Technology and Management Engineering.

9.       Hiroyuki Mori, Yasushi Umezawa, “Credit Risk Evaluation in Power Market with Random Forest”.

10.     Bastos, J. A., 2008, "Credit scoring with boosted decision trees". City: Munich Personal RePEc Archive, pp. 262-273.

11.     Defu Zhang,  Xiyue Zhou, Stephen C.H. Leung, JieminZheng, “Vertical bagging decision trees model for credit scoring”, Expert Systems with Applications 37 (2010) 7838–7843.

12.     Hong Yu, Xiaolei Huang, Xiaorong Hu, HengwenCai, “A Comparative Study on Data Mining Algorithms for Individual Credit Risk Evaluation”, 2010 International Conference on Management of e-Commerce and e-Government.




S.S. Sugania, K. John Peter

Paper Title:

Feature Extraction for Face Recognition by Using A Novel and Effective Color Boosting

Abstract:   This paper introduces the new color face recognition (FR) method that makes effective use of boosting learning as color-component feature selection framework. The proposed boosting color-component feature selection framework is designed for finding the best set of color-component features from various color spaces (or models), aiming to achieve the best FR performance for a given FR task. In addition, to facilitate the complementary effect of the selected color-component features for the purpose of color FR, they are combined using the proposed weighted feature fusion scheme. The effectiveness of my color FR method has been successfully evaluated on the following five public face databases (DBs): CMU-PIE, Color FERET, XM2VTSDB,SCface, and FRGC 2.0. Experimental results show that the results of the proposed method are impressively better than the results of other state-of-the-art color FR methods over different FR challenges including highly uncontrolled illumination, moderate pose variation, and small resolution face images.

 Boosting learning, color face recognition, color space, color component, feature selection.


1.        “Discrete Wavelet Transforms: Theory and Implementation” Tim Edwards ( University, September 1991.
2.        “Phase Congruency Detects Corners and Edges “ Peter Kovesi School of Computer Science & Software Engineering The University of Western Australia Crawley, W.A. 6009.

3.        ” Color Face Recognition for Degraded Face Images” Jae Young Choi, Yong Man Ro, Senior Member, IEEE, and Konstantinos N. (Kostas) Plataniotis, Senior Member, IEEE.

4.        ” Boosting Color Feature Selection for Color Face Recognition” Jae Young Choi, Student Member, IEEE, Yong Man Ro, Senior Member, IEEE, and Konstantinos N. Plataniotis, Senior Member, IEEE.

5.        “A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting” Yoav Freund and Robert E. Schapire-AT6T Labs, 180 Park Avenue, Florham Park, New Jersey.




G.R. Rameshkumar, B.V.A. Rao, K.P. Ramachandran

Paper Title:

Coast Down Time Analysis to Analyze the Effect of Misalignment in Rotating Machinery

Abstract:   Shaft misalignment in rotating machinery is one of the major industrial concerns. When the power supply to any rotating system is cut-off, the system begins to lose the momentum gained during sustained operation and finally comes to rest. The exact time period between the power cut-off time and the time at which the rotor stops is called Coast Down Time. In this paper an experimental study was conducted to investigate the effect of angular misalignment in forward curved centrifugal blower test setup. Tests were conducted for various level of angular misalignment at different shaft cut-off speeds. The results show that the coast down time decreases with increase in level of angular misalignment. At higher speed and at higher level of angular misalignment, the impact on percentage reduction in CDT is very high and there is a specific correlation between the percentage reduction, cut-off speeds and the level of introduced angular misalignment. The vibration signatures acquired at different cut-off speeds and at the various level of angular misalignment conditions. The 2X and 3X vibration amplitude components are predominant frequencies and increase as the angular misalignment and shaft rotational speed increases, thereby establishing the fact that the CDT analysis can be used as one of the diagnostic condition monitoring parameter for rotating machinery.

  Angular Misalignment, Coast Down Time, Condition Monitoring, Forward Curved Centrifugal Blower.


1.       J. Piotrowski, Shaft Alignment Handbook. 3rd ed. New York: CRC Press, Taylor & Francis Group LLC, 2007. 
2.       K.P. Ramachandran, “Vibration signature analysis for machine health monitoring and fault diagnosis,” Caledonian Journal of Engineering hen, vol.1, 2004, pp. 26–39.

3.       T. L. Daugherty and R. J. Craig, “Coast down time as a mechanical condition indicator for vertical axis motors with grease-lubricated ball bearings,” American Society of Lubrication Engineers Transactions, 1977, pp. 349–357.

4.       K.P. Ramachandran, M. Mahadevappa, M.K. Ravishankar and A. Ramakrishna, “An approach to machine misalignment studies using vibration, orbit and coast down phenomena,” Proceedings of the International Conference on Advances in Mechanical and Industrial Engineering, University of Roorkee, 1997, Roorkee. 

5.       G. Santhanakrishnan, B. S. Prabhu and B.V.A. Rao, “An experimental investigation of tribological effects on coast down phenomenon in horizontal machinery,” Journal of wear, 1983, pp. 25–31.

6.       Joseph S Shighley and Charies R Mischke. Hand book of Machine design, McGraw Hill, 1976. 

7.       A.S. Sekhar and B.S. Prabhu, “Effects of Coupling Misalignment on vibrations of rotating machinery,” Journal of Sound and Vibration, vol. 185, no. 4, 1995, pp. 655–671.

8.       P. Arumugam, S. Swarnamani and B.S. Prabhu, “Effects of journal misalignment on the performance characteristics of three-lobe bearings,” Wear, vol. 206, no. 1-2, 1997, pp. 122–129.

9.       K.M. Al-Hussain and I. Redmond, “Dynamic response of two rotors connected by rigid mechanical coupling with parallel misalignment,” Journal of Sound and Vibration, vol. 249, No. 3, 2002, pp. 483–498.

10.     P.N. Saavedra and D.E. Ramirez, “Vibration analysis of rotors for the identification of shaft misalignment, Part 1: theoretical analysis,” Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, vol. 218, no. 9, 2004,    pp. 971–985.

11.     P.N. Saavedra and D.E. Ramirez, “Vibration analysis of rotors for the identification of shaft misalignment. Part 2: experimental validation,” Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, vol. 218, no. 9, 2004,   pp. 987–999.

12.     M. Attia Hilli, T. Fakhfakh, L. Hammami and M. Haddar, “Shaft misalignment effect on bearings dynamical behavior,” The International Journal of Advanced Manufacturing Technology,       vol. 26, No. 5-6, 2005, pp. 615–622.

13.     E. Estupiflan D. Espinoza and A. Fuentes, “Energy losses caused by misalignment in rotating machinery: A theoretical, experimental and industrial approach,” International Journal of COMADEM, vol. 11, no. 2, 2008, pp. 12–18.

14.     M Xu and R.D. Marangoni, “Vibration analysis of a motor flexible coupling rotor system subject to misalignment and unbalance Part I: theoretical model and analysis,” Journal of Sound and Vibration,     vol. 176, no.5, 1994, pp. 663–679.

15.     M Xu and R.D. Marangoni, “Vibration analysis of a motor flexible coupling rotor system subject to misalignment and unbalance Part II: experimental validation,” Journal of Sound and Vibration, vol. 176, no.5, 1994a, pp. 681–691.

16.     G. R. Rameshkumar, B. V. A. Rao, and K. P. Ramachandran, “An experimental investigation to study the effect of misalignment using CDT as a condition monitoring parameter for rotating machinery,” 22nd International Congress, COMADEM 2009, San Sebastian, Spain, 2009, pp. 531–539.

17.     G. R. Rameshkumar, B. V. A. Rao, and K. P. Ramachandran, “Condition monitoring of forward curved centrifugal blower using coast down time analysis, International Journal of Rotating Machinery,” vol.2010, Article ID 962804, 12 pages, doi:10.1155/2010/962804
18.     R. Edwin Browne, K.P. Ramachandran, A.K.M. De Silva and D.K. Harrison, “An experimental investigation to analyze the effect of unbalance in a horizontal rotor system using coast-down factor,” International Journal of COMADEM, vol. 10, No. 3, 2007, pp. 11–18.




Sandeep Yadav, Kamal Kumar Verma, Swetamadhab Mahanta

Paper Title:

The Maze Problem Solved by Micro mouse

Abstract:   A Micromouse is a miniature Electro-mechanical robot, typical consisting of 3 main subsystems: The drive system, an array of sensors, and the control system. The purpose of Micromouse is to find its way through any type of Maze in shortest time. Aside from its being a fun, competitive challenge, the micromouse has proved to be an excellent teaching medium. It can be viewed as a small system involving interdisciplinary engineering aspects. Its successful designers often work in teams, and must consider electrical, electronic, mechanical and computer issues. Design decisions and tradeoffs involve weight, speed, and power, sensing techniques, turning methods, centre of gravity and programming. Autonomous robots have wide reaching applications. From Bomb sniffing to finding humans in wreckage to home automation. This paper covers one of the most important areas of robot, “Decision making Algorithm” or in lay-man’s language, “Intelligence”. The environment around the robot is not known, so it must have decision-making capabilities. For starting in the field of micro-mouse it is very difficult to begin with highly sophisticated algorithms. This paper covers very basic wall follower logic to solve the maze. And gradually improves the algorithm to accurately solve the maze in shortest time with some more intelligence. The Algorithm is developed up to some sophisticated level as Flood fill algorithm.

  Lorentz force, Differential Chassis, flood fill algorithm


1.        M.C. Fairhurst, “Computer Version for robotic systems: An Introduction,” Pentice Hall 1998.
2.        Laurie, P. Micromouse: Practical Computing, UK, Nov 1980, p50.

3.        Billingsley, J.: Micromouse at Expo '85 Tsukuba: Electronic System News, UK, Spring 1986, pp32-33

4.        Ernest L. Hall1 and Nathan Mundhenk, “Intelligent Robot Trends and Predictions for the New Millennium”.

5.        Dimitris C. Dracopoulos;”Robot Path Planning for Maze Navigation”, 1998.

6.        Babak Hosseini Kazerouni, Mona Behnam Moradi and Pooya Hosseini Kazerouni;”Variable Priorities in Maze- Sloving Algorithms for Robot’s Movement”, 2003.

7.        Horst-michael gross, Alexander Koenig; “Robust Omniview-basad Probilistic Self-loalization for Mobile Robots in Large Maze-like Environments”, proceedings of the 17th International Conference on Pattern Recognition, ICPR-2004.

8.        Shinichiro Yano, Manabu Noda, Hisahiro Itani, Masayuki Natsume, Haruhiko Itoh and Hajime Hattori, Tadashi Odashima, Kazuo Kaya, Shinya Kataoka and Hideo Yuasa, Xiangjun Li, Mitsuhiro Ando, Wateru Nogimori and Takahiro Yamada; “A Study of Maze Searching With Multiple Robots System”, 7th International Symposium on MicroMachine and Human Science, 1996.

9.        Frank Lingelbach; “Path Planning using Probabilistic Cell Decomposition”, International Conference on Robotics & Automation, 2004.

10.     Gorden Mc Comb, Myke Predko,“Robot Builder’s Bonanza”, Mc-Graw Hill, 2006.

11.     Provo, B: Robotic control and ultrasonic sensing, a MC68HC16 application. Proceedings of the National Electronics Convention. August 1992. NELCON '92. Wellington Centre for Continuing Education, University of Auckland, New Zealand

12.     Smith Martin: Rokeby's Racing Robot Rodents. IEEE Electronics Education Magazine. Autumn 2000. ISSN 02065-0096, p. 8-10.

13.     Auyeung, T: Popular Micromouse Algorithms Part III The Flood –Fill Algorithm. Robot Science and Technology Magazine, January 1999, pp. 42-46.

14.     Allen, S A: Simple maze traversal algorithms. Byte, 4- 6, June 1979, pp. 36-46.

15.     Smith, N: Micromouse sensors. Practical Computing, September 1981, p. 133.

16.     Witkowski, M: Robots: sense and sensibility. Practical computing, April 1980, pp.86-124.

17.     Hampshire, N: Micromouse -Amazing show. Practical Computing, October 1981, p. 157.

18.     Heiserman, D C: How to design and build your own custom robot. TAB Books, 1981.

19.    Goh, W L, Ng, H.K, Yap, P C: Design of amicromouse. Journal of the Institution of Engineers, Singapore, Vol. 27(1), May 19, pp. 27-36.
20.     Bidet, T:Micromouse competitions -an intellectual and technical challenge. NZ Engineering, August. 1991, pp. 27-28.




Aman Kumar Sharma, Arvind Kalia, Hardeep Singh

Paper Title:

Empirical Analysis of Object Oriented Quality Suites

Abstract:   As object oriented paradigm is becoming more pervasive, it becomes necessary that the software engineering methodologies have quantitative measurements for accessing the quality of software at both the architectural and component level. These measures allow the designer to access the software in early stages of the development process and making changes, that will reduce complexity and improving the quality of the product at the development phase. Object Oriented Design metrics is an essential part of software engineering. An empirical study of applying the design measures to asses the software quality is presented. The two metrics suites namely Chidamber and Kemerer (CK) Metrics and Metrics for Object-Oriented Design (MOOD) Metric Suite are used in this study. Using these metrics suite, various design metrics namely Depth of Inheritance Tree (DIT), Coupling Between Object Classes (CBO), Response for a Class (RFC), Number of Children (NOC), Method Inheritance Factor (MIF), Attribute Inheritance Factor (AIF), Method Hiding Factor (MHF), Attribute Hiding Factor (AHF), Polymorphism Factor (POF) for three latest versions of JfreeChart software have been analyzed to predict the software quality. The results of this empirical analysis will help the software developers and academicians in improving the software quality while developing software products using the Object-oriented (OO) approach.

  CK Suite, MOOD Suite, Object-Oriented Software Metrics, Software Quality


1.        Abreu F B and Carapuca R, “Object-Oriented Software Engineering: Measuring and Controlling the Development Process”, Proceedings of the 4th International Conference on Software Quality, ASQC, McLean, VA, USA, 1994.
2.        Abreu F B and Melo W, “Evaluating the Impact of Object- Oriented Design on Software Quality”, Proceeding of Third International Software Metrics Symposium, pp. 90-99, 1996.

3.        Abreu F B and Melo Walcelio, “Evaluating the Impact of Object-Oriented Design on Software Quality”, METRICS'96: Proceedings of the 3rd International Symposium on Software Metrics: From Measurement to Empirical Results, IEEE Computer Society Washington, DC, USA, 1996.

4.        Abreu F B, Coulao Miguel and Esteves Rita, “Toward the Design Quality Evaluation of Object-Oriented Software Systems”, Proceedings of the 5th International Conference on Software Quality, Austin, Texas, USA, 1995.

5.        Abreu F B, Esteves R and Goulao M, “The Design of Eiffel Programs:  Quantitative Evaluation Using the Mood Metrics”, Proceedings of TOOLS’96, Santa Barbara, CA. USA, 1996.

6.        Arisholm Erik, Briand Lionel C and Foyen Audun, “Dynamic Coupling Measurement for Object-Oriented Software”, IEEE Transaction Software Engineering, 30(8), pp. 491–506, 2004.

7.        Bansiya J and Davis C, “A Hierarchical Model for Object-Oriented Design Quality Assessment”, IEEE Transaction Software Engineering, 28(1), pp. 4-17, 2002.

8.        Basili V R, Briand L C and Melo W L, “A Validation of Object-Oriented Design Metrics as Quality Indicators”, IEEE Transactions on Software Engineering, 22, pp. 751–761, 1996.

9.        Boehm B W, "Improving Software Productivity", IEEE Computer, pp. 43-57, 1987.

10.     Briand L C, Wust J, Daly J W and Porter D V, “Exploring the Relationships between Design Measures and Software Quality in Object-Oriented Systems”, Journal of Systems and Software, 51, pp. 245–273, 2000.

11.     Chidamber S R and Kemerer C F, “A Metrics Suite for Object Oriented Design”, IEEE Transaction Software Engineering, 20(6), pp. 476–493, 1994.

12.     Daly J, Brooks A, Miller J, Roper M and Wood M, “Evaluating Inheritance Depth on the Maintainability of Object-Oriented Software”, Empirical Software
Engineering 1(2): 109– 132, 1996.

13.     El-Emam Khaled, Benlarbi S, Goel N and Rai S, “A Validation of Object-Oriented Metrics”, Technical Report, NRC/ERB 1063, National Research Council Canada,
14.     Harrison R, Counsell S and Nithi R, “Experimental Assessment of the Effect of Inheritance on the Maintainability of Object-Oriented Systems”, Journal of Systems and Software, 52(2-3), pp. 173–179, 2000.
15.     Harrison R, Counsell Steve J and Nithi Reuben V, “An Evaluation of the Mood Set of Object-Oriented Software Metrics”, IEEE Transaction Software Engineering, 24(6), pp. 491–496, 1998.

16.     Hitz M and Montazeri B, “Chidamber and  Kemerer's Metrics Suite: A Measurement  Theory Perspective”, IEEE Transactions On Software Engineering, 22(4),  pp. 267-271, 1996.

17.     Jacobson I, Christerson M, Jonsson P and Overgaard G, “Object-Oriented Software Engineering: A Use Case Driven Approach”, Wokingham, England, Addison-Wesley, 1992.

18.     Khan R A, Mustafa K and Ahson S I, "An Empirical Validation of Object Oriented Design quality Metrics, Journal of KSU, KSA, 19, 1427H, pp. 1-16.

19.     Korson T D and Vaishnavi V K, "An Empirical Study of Modularity on Program Modifiability", Empirical Studies of Programmers, pp. 168-86, 1986.

20.     Meyer B, “Software Engineering in the Academy", Computer IEEE, 34(5), pp. 28-35, 2001.

21.     Subramanyam R and Krishnan M S, “Empirical Analysis of CK Metrics for Object-Oriented Design Complexity: Implications for Software Defects”, IEEE Transactions on Software Engineering, 29(4), pp. 297-310, 2003.

22.     Gill Nasib Singh, “Software Engineering”, Khanna Book Publishing Co. Ltd., New Delhi, 2000, 1st ed.




Rathindra Nath Giri, M.K.Pandit

Paper Title:

Pipelined Floating-Point Arithmetic Unit (FPU) for Advanced Computing Systems using FPGA

Abstract:  Field Programmable Gate Arrays (FPGA) are increasingly being used to design high-end computationally intense microprocessors capable of handling both fixed and floating-point mathematical operations. Addition is the most complex operation in a floating-point unit and offers major delay while taking significant area. Over the years, the VLSI community has developed many floating-point adder algorithms mainly aimed to reduce the overall latency. An efficient design of floating-point adder onto an FPGA offers major area and performance overheads. With the recent advancement in FPGA architecture and area density, latency has been the main focus of attention in order to improve performance. Our research was oriented towards studying and implementing standard .Our work is an important design resource for development of floating-point adder hardware on FPGAs. This article reports the work done on the design of control path and data path of an optimized 64bit floating-point addition operation using field programmable gate array. At first we selected carry skip adder logic due to its best performance in terms of area, speed and power then we employ common a graph to determine the best mix of  cutsets, registors, MUXs for  pipelining.

  Data path, control path, VLSI, FPGA, adder logic, floating point addition, optimization, pipelining.


1.        Irvin Ortiz Flores,” Optimizing the Implementation of Floating Point Units for FPGA Synthesis” Electrical and Computer Engineering Department.
2.        ChiWai Yu, Alastair M. Smith, Wayne Luk, Fellow, IEEE, Philip H. W. Leong, Senior Member, IEEE “Optimizing Floating Point Units in Hybrid FPGAs”.

3.        Wayne Wolf, FPGA based system design.

4.        A. J. Al-Khalili,” A CAD tool for low power scalable floating-point”, Concordia University, Montreal

5.        Ted Williams, “Latency and Throughput Tradeoffs in Self-Timed Speed-Independent Pipelines and Rings”, Computer Systems Laboratory, Departments of Electrical Engineering and Computer Science, Stanford University

6.        Justin Davis and Robert Reese, “Finite State Machine Datapath Design, Optimization, and Implementation”

7.        A. J. Al-Khalili,  ” A CAD tool for low power scalable floating-point adder generator”, Concordia University, Montreal

8.        M.S. Hrishikesh, , Norman P. Jouppi_,  Keith I. Farkas, Doug Burger_ StephenW. Keckler_ Premkishore Shivakumar. “The Optimal Logic Depth Per Pipeline Stage is 6 to 8 FO4 Inverter Delays”.


9.        Ted Williams, “Latency and Throughput Tradeoffs in Self-Timed Speed-Independent Pipelines and Rings” Departments of Electrical Engineering and Computer Science Stanford University

10.     Subhash Kumar Shrama, Himanshu Pandey, Shailendra Sahni and Vishal Kumar Srivastava, “ Implementation of IEEE-754 Addition and Subtraction for Floating Point Arithmetic Logic Unit ”,  D.D.U. Gorakhpur University, Gorakhpur, U.P (India)




Navneet  Sharma , Vijay Singh Rathore

Paper Title:

Different Data Encryption Methods Used in Secure Auto Teller Machine Transactions

Abstract:   Data security is an important issue in current scenario of banking financial operation specially with transaction of secure and confidential data. It must be send with high security at the time of communication. In this paper we will discuss various types of encryption methods and standards which are used in secure banking data transmissions to make more data security. Specially here we discuss the communication security methods used between Auto teller machine and bank server banking financial operations, When we transmit data from an Auto Teller Machine to bank server it must send in encrypted form so that an unauthorized user cannot access the secure information directly at the time of data communication. using this paper I will try to explain different data security that how the data transactions can make more secure with different security techniques used in ATM transactions. Various security levels of data and encryption standard used in banking data transaction security. Encryption methods are built into the communication network to prevent unauthorized transactions that could protect the data from unauthorized access. This paper focuses on Data Encryption Standard and Advanced Encryption Standard, these are the encryption standards used by the banks to protect the data and for secure data transmission.

  Auto Teller Machine, Encryption,  DES, 3DES, AES, RC4, EPP.


1.       Oracle Advanced Security Administrator's Guide Release 8.1.5 A67766-01
2.       Enterprise Tape Encryption Requirements for the Banking Industry By: Jon Oltsik Enterprise Strategy Group August 2006


4.       Xie Baoxiu Shi Bing. Encryption in e-commerce application [J] Computer and Digital Engineering 12, 2005

5.       Zhao Lili. RSA algorithm and the speed improvements [D] Shenyang University of Technology 2007 

6.       Cai Jiren. Information Security Cryptography [J] Network Security 2003 

7.       W. Stallings, Cryptography and network security, Prentice Hall, 2006, New Jersey, United State

8.       R. Sililiano, ATM Security threats Aug. 2010

9.       Xie Baoxiu Shi Bing. Encryption in e-commerce application [J] Computer and Digital Engineering 12, 2005

10.     Zhao Lili. RSA algorithm and the speed improvements [D] Shenyang University of Technology 2007 





Prateek Verma, Maheedhar Dubey, Praveen Verma

Paper Title:

Correlation Based Method for Identification of Fingerprint- A Biometric Approach

Abstract:   With identity fraud in our society reaching unprecedented proportions and with an increasing emphasis on the emerging automatic personal identification applications, biometrics-based verification, especially fingerprint-based identification, is receiving a lot of attention Biometrics deals with identifying individuals with help of their biological data. Fingerprint scanning is the most common method of the biometric methods available today. The security of fingerprint scanners has however been questioned and previous studies have shown that fingerprint scanners can be fooled with artificial fingerprints, i.e. copies of real fingerprints. The fingerprint recognition systems are evolving and this paper will discuss the situation of today. We match the finger prints, one that is already in the database of the sensor and second the fingerprint that we enrolled in the sensor currently by using the Boolean function X-ORING. We get the matching score and decide the result on the matching score basis, whether the fingerprint is matched or not.

  Fingerprint, Biometrics, Artificial Intelligence, Sensors.


1.        B. Miller, “Vital Signs of Identity,” IEEE Spectrum 31, No. 2, 22–30 (1994).
2.        L. O’Gorman, “Practical Systems for Personal Fingerprint Authentication,” IEEE Computer 33, No. 2, 58–60 (2000).

3.        R. Germain, A. Califano, and S. Colville, “Fingerprint Matching Using Transformation Parameter Clustering,” IEEE Computational Science and Engineering 4, No. 4, 42–49 (1997).

4.        A. Jain, L. Hong, and S. Pankanti, “Biometrics Identification,” Communications of the ACM 43, No. 2, 91–98 (2000).

5.        B. Schneier, “The Uses and Abuses of Biometrics,” Communications of the ACM 42, No. 8, 136 (1999).

6.        B. Schneier, Applied Cryptography, John Wiley & Sons, Inc., New York (1996).

7.        N. Memon and P. W. Wong, “Protecting Digital Media Content,” Communications of the ACM 41, No. 7, 35–43 (1998).




K.V.V.Kumar, T.Ravi, B.M.S.Rani, Dr.Habibullah Khan

Paper Title:

Detection of Retinal Diseases by Tracing Vessel Trees and Accurately Segmenting Vessels

Abstract:  The extraction of retinal vessels plays an important role in the diagnosis and analysis of retinal diseases, such as Age-related Macular Degeneration (AMD), Diabetic Retinopathy, and Retinopathy of Prematurity (ROP). The blood vessels are the part of the circulatory system that transports blood throughout the body. There are three major types of blood vessels: the arteries, which carry the blood away from the heart; the capillaries, which enable the actual exchange of water and chemicals between the blood and the tissues; and the veins, which carry blood from the capillaries back toward the heart segmentation is the process of partitioning a digital image into multiple segments (sets of pixels also known as super pixels). The goal of segmentation is to simplify and/or change the representation of an image into something that is more meaningful and easier to analyze. The result of image segmentation is a set of segments that collectively cover the entire image, or a set of contours extracted from the image.The objective of fusion is to convolve foreground and background images to analyze the retinal vessels

  BRVO(Branch retinal vein oclusions),CNVM (Chroidal neo vascular membrane),VMT (Vitro  macular traction),ERM( Epiretinal membranes),DR(Diabetic Retinopathy).


1.        Segmentations Of The Intraretinal Surfaces, Optic Disc And Retinal Blood Vessels In 3d-Oct Scans Kyung Moo Lee, The University of Iowa. Biomedical Engineering
2.        Development of the Biomechanical Disc Culture System for Intervertebral Disc Mechanobiology Prem Subramanian Ramakrishnan. The University of Iowa

3.        S. Chaudhuri, S. Chatterjee, N. Katz, M. Nelson, and M. Goldbaum,.Detection of blood vessels in retinal images using twodimensional matchedfi lters,. IEEE Trans.
Medical imaging,vol.8,no.3,September1989.

4.        A. Hoover, V. Kouznetsova, and M. Goldbaum, .Locating blood vessels in retinal images by piecewise threshold probing of a matched _lter response,. IEEE

5.        Trans. Medical imaging, vol. 19, no. 3, March 2000,

6. ahoover

7.        N. R. Pal and S. K. Pal, .Entropic thresholding,. Signal processing, vol. 16, pp. 97.108, 1989

8.        An efficient blood vessel detection algorithm for retinal images using local entropy thresholding  Thitiporn Chanwimaluang and Guoliang Fan by 2002.

9.        C. Kirbas, and F. K. H. Quek, Vessel Extraction Techniques and Algorithms: a Survey, in Third IEEE Symposium on Bioinformatics by 2003


11.     J. Staal, M. D. Abramoff, M. Niemeijer, M. A. Viergever, B. van Ginnekea, Ridge Based Vessel Segmentation in Color Images of the Retina, IEEE Transactions on Medical Imaging, 2004, vol. 23, pp. 501-509.

12.     U. Ozertem, and D. Erdogmus, Local Conditions for Critical and Principal Manifolds, Proceedings of ICASSP’08, 2008, pp. 1893-1896.




Ishan B Shah, Kishore. R. Gawande

Paper Title:

Optimization of Cutting Tool Life on CNC Milling Machine Through Design Of Experimnets-A Suitable Approach – An overview

Abstract:   This paper discuss of the literature review of Optimization of tool life in milling using Design of experiment implemented to model the end milling process that are using solid carbide flat end mill as the cutting tool and stainless steels s.s-304 as material due to predict the resulting of  Tool life. Data is collected from CNC milling machines were run by 8 samples of experiments using DOE approach that generate  table design in MINITAB packages. The inputs of the model consist of feed, cutting speed and depth of cut while the output from the model is Tool life calculated by taylor’s life equation.  The model is validated through a comparison of the experimental values with their predicted counterparts. The optimization of the tool life is studied to compare the relationship of the parameters involve.

  Design of experiment(DOE), Two level Full and Fractional designs, ANOVA, Optimization of tool life, Minitab.


1.        I.A. Choudhury, M.A. El-Baradie ,’’ Tool-life prediction model by design of experiments for turning high strength steel (290 BHN).” Journal of Materials Processing Technology 77 (1998) 319–326
2.        Keun Park Jong-Ho Ahn, “Design of experiment considering two-way interactions and its application to injection molding processes with numerical analysis.” Journal of Materials Processing Technology 146 (2004) 221–227

3.        Christel Pierlot, Lech Pawlowski ,Muriel Bigan, Pierre Chagnon, “Design of experiments in thermal spraying: A review”. Surface & Coatings Technology 202 (2008)

4.        Dong-Woo Kim, Myeong-Woo Cho, Tae-Il Seo, Eung-Sug Lee,”Application of Design of Experiment Method for Thrust Force Minimization in Step-feed Micro Drilling.’’ Sensors 2008, 8, 211-221

5.        Ilhan Asiltürk , Harun Akkus,” Determining the effect of cutting parameters on surface roughness in hard turning using the Taguchi method.” Sciencedirect Measurement 44 (2011) 1697–1704

6.        Yung-Kuang Yang, Ming-Tsan Chuang, Show-Shyan Lin, ” Optimization of dry machining parameters for high-purity graphite in end milling process via design of experiments methods.”, Journal of Materials Processing Technology 209 (2009) 4395–4400.

7.        J.A. Ghani, I.A. Choudhury, H.H. Hassan, “Application of Taguchi method in the optimization of end milling parameters.”, Journal of Materials Processing Technology 145 (2004) 84–92.




Ch. Vijaya Sekhar Babu, K. Nalini, D.Ujwala, R.Rahul, K. Naga Mallik, A. Gowtham

Paper Title:

A Compact Triangular and Circular Serrated Rectangular Slot Patch Antenna for X-band Applications

Abstract:   A Rectangular slot patch antenna with triangular and circular serrations is presented in this paper. The proposed design is prototyped on Rogers RT/duroid of dieletric constant 2.2 which has a compact size of 24mm x 24mm x1.5mm. Two identical rectangular slots are on made on patch with double sided triangular and circular serrations. The proposed strucuture operates at dual band which can be used X-band applications. The dependence of impedance matching on feed location is analyzed by varying the feed location horizontally. The simulations are carried out using Finite Element method based Ansoft HFSS version 13.

  X-band, Ansoft HFSS version 13.


1.        Richard H. Chen and Yi-Cheng Lin, “Miniaturized Design of Microstrip-Fed Slot Antennas Loaded with C-Shaped Rings”, IEEE Antennas and Wireless Propagation Letters, Vol. 10, 2011.
2.        Kim, T.H., Park, D.C., “Compact dual-band antenna with double L-slits for WLAN operations”, IEEE, 2005.

3.        Vinod K. Singh, Zakir Ali, “Dual Band U-Shaped Microstrip Antenna for Wireless Communication”, Vol. 2(6), ISSN, 2010.

4.        Kin-Lu Wong, Compact and Broadband Microstrip Antennas, A Wiley-Interscience Publication, 2002.

5.        P. A. Ambresh, P. M. Hadalgl, “Experimental Results of Compact Dual Frequency Microstrip Slot Antenna”, IJECT Vol. 2, Issue 3, Sept. 2011.

6.        C. A. Balanis, Antenna Theory Analysis and Design, Second Edition, New York, Wiley, 1997.




P.K. Biswas, S. Banerjee

Paper Title:

Effect for Changing Different Parameters of Rail and Actuator Used in Electromagnetic Levitation System

Abstract:   In this paper the effect of different parameters like size of actuator and rail, current density, no of turns of coil, permeability of magnetic material, winding dimension etc. has been studied.An FEM analysis of U-I structure of rail (guide-way) and actuator for electromagnetic levitation system has been performed by the utilizing of the ANSYS software. The design of electromagnets is primarily controlled by the input power to lift power ratio and lift power magnet weight ratio. These factors are dependent on the magnet dimensions, required gap flux and hence the required current density in the winding. The magnet configurations chosen on the basis of required pole-face area and necessary window area to house the excitation coils. In this work a FEM based analysis has done to find out the flux pattern, working flux density, field intensity, force etc. for single actuator based levitation system. The changing of different parameters of rail and actuator the flux pattern, working flux density, field intensity and force will change.

  Electromagnetic Levitation, FEM analysis, eddy current effect, ANSYS software.


1.       B.V. Jayawant, 'Review lecture on electromagnetic suspension and levitation techniques', Proc. R. Soc. Lond. A416, 1988, pp.245-320. 
2.       P.K. Sinha, Electromagnetic Suspension, Dynamics and Control, Peter Peregrinus Ltd., London, 1987.

3.       N. A. Shirazee and A. Basak, 'Electro permanent suspension system for acquiring large air-gaps to suspend loads', IEEE Trans. on Magnetics, Vol.31, No.6, Nov.1995, pp.4193-4195.

4.       A. Bittar and R. M. Sales, 'H2 and H. control for maglev vehicles', IEEE Control Systems Magazine,Vol.18, No. 4, Aug.1998, pp.18-25.

5.       Reference Guide ANSYS CFX-Solver, Release 12.0

6.       S.Banerjee, P.Biswas, R.Bhaduri, “A Comparative study between different structures of Rail and Actuator used in Electromagnetic levitation systems’, proc in 5th IET Intentional Conference on Power Electronics, Machines and drives, PEMD 2010,UK,19-21 April 2010.

7.       Matthew N.O.Sadiku, ‘Elements of Electromagnetic’, OXFORD University press.

8.       Rothwell E.J., Cloud M.J., “Electromagnetics”, CRC Press 2001.

9.       Hammond P., Sykulski J.K., “Engineering Electromagnetism – Physical Processes and Computation”, Oxford University Press, New York 1994.

10.     Kwang-Ok An, Chang-Hwan Im, Chang-Hwan Lee, Hyun-Kyo Jung, “Optimal design of magnetic scale for linearizing magnetic flux density and force”, Proc. in
International Journal of Applied Electromagnetics and Mechanics", Volume 18, Number 4/2003, pp.251-258.

11.     Guirong Wang, Hong Xu, Jian Sun, Wei Wei , “Electromagnetic field analysis and dynamic modeling of force for motor in Maglev train”, Proc. of 7th World Congress on Intelligent Control and Automation, WCICA 2008., pp. 8198 – 8202.

12.     J. E. Paddison, R. M. Goodall. “EMS Maglev Suspension Control System Comparison and Trends”, MAGLEV’98, Mt. Fuji, Japan, 1998.

13.     R. D. Fruechte, R. H. Nelson, T. A. Radomski. “Power conditioning system for a magnetically levitated test vehicle”, IEEE transaction on vehicular technology, Vol VT-29, No 1, Feb 1980, pp 50-60.

14.     Y. Hikasa, Y. Takeuchi. “Detail and experimental results of ferromagnetic levitation system of Japan Air Lines HSST-01/-02 vehicles”, IEEE transaction on vehicular technology, Vol VT-29, No 1, Feb 1980, pp 35-41.




S. Sabna, D. Prasad, R. Shivakumar

Paper Title:

Power System Stability Enhancement by Neuro Fuzzy Logic Based SVC for Multi Machine System

Abstract:   This paper presents a hybrid technique to small signal stability enhancement using ANFIS thruster susceptance control of static vary compensator (SVC). Their main objective is to determine the synchronous generator’s ability to maintain stability after the occurrence of a fault or following a major change in the network such as the loss of an important generator or a large load. Static vary compensator is proven the fact that it improves the dynamic stability of power system apart from reactive power compensation; it has multiple role in the operation of power system. The main variable to be controlled in the power system for efficient operation is to mitigating the rotor electro-mechanical low frequency oscillations. Simulations are carried out for multi machine power system for without SVC and with ANFIS SVC. The proposed Neuro fuzzy logic based SVC for multi machine power system provides better damping to power system oscillation.  

  Damping of oscillation, Neuro fuzzy controller (ANFIS), static vary compensator (SVC), thruster susceptance control.


1.       M.CibaTherase M.MarsalineBeno, N.AlbertSingh, ,M.Mohamed Syed Ibrahim, “Design of pss for damping of low frequency oscillations using bacteria foraging tuned non linear neuro fuzzy controller”, IEEE GCC Conference 2011.
2.       D. Harikrishna and N.V. Srikanth, “Unified Philips-Heffron Model of Multi-Machine Power System equipped with PID damping controlled SVC for Power Oscillation Damping”, INDICON 2009, IEEE India Council Conference, pp 481 – 484, Dec – 2009.

3.       IEEE special stability controls working group, “Static VAR compensator models for power flow and Dynamic performance simulation”, IEEE Transaction on power systems, Vol. 19, No. 1,pp. 229 – 239, February – 1994
4.       E.Z. Zhou, ‘Application of static VAR compensators to increase power system damping’, IEEE Trans. on Power Systems, Vol.8, No.2, PP May 1993.

5.       Yousin. Tang & A.P Sakis Meliopoylos, ‘Power Systems small signal stability analysis with FACTS elements’, IEEE, on Power delivery, vol.12, no. 3, July-1997.

6.       Kitty Phorang & Prof.Dr.Yoshibumi Mizutani, ‘Damping improvement of oscillation in power system by fuzzy logic based SVC stabilizer’, IEEE–2002.

7.       Farsangi, M.M. Song, Y.H. Lee, K.Y. Kerman Univ., Iran,“Choice of FACTS device control inputs for damping inter-area oscillations”, IEEE Transactions on Power Systems, pp. 1135-1143, Vol. 19, May – 2004.

8.       Prabha kundur ‘power system stability and control” Tata McGraw hill education private limited.

9.       Robert fuller, “Neuro fuzzy methods for modeling and fault diagnosis”, Eotvos lorand university 2001.




Santanu Maity, Bishnu Prasad De, Aditya Kr. Singh

Paper Title:

Design and Implementation of Low-Power High-Performance Carry Skip Adder

Abstract:   The most timing critical part of logic design usually contains one or more arithmetic operations, in which addition is commonly involved. In VLSI applications, area, delay and power are the important factors which must be taken into account in the design of a fast adder. The carry-skip adder reduces the time needed to propagate the carry by skipping over groups of consecutive adder stages, is known to be comparable in speed to the carry look-ahead technique while it uses less logic area and less power. In this paper, a design of 8-bit Carry Skip Adder by various existing logic styles are to be compared quantitatively and qualitatively by performing detailed transistor-level simulation using T-Spice v13.0.

  Low power, High performance, Carry Skip adder, Logic design style, CMOS, CPL, DPL, Reversible Logic.


1.       Chandrakasan, A., and Brodersen, Low Power Digital Design, Kluwer Academic Publishers, 1995.
2.       Weste, N., and Eshragian, K., Principles of CMOS VLSI   Design: A Systems Perspective,   Pearson Addison-Wesley Publishers, 2008.

3.       R. Barnes Earl and G.Oklobdzija Vojin “New Multilevel Scheme for Fast Carry-Skip Addition,” in IBM Technical Disclosure Bulletin, vol.27, April, 2009, pp133-158 27,.

4.       R. Landauer, “Irreversibility and Heat Generation in the Computational Process,” IBM Journal of Research and development, vol. 5, 1961, pp.183-191.

5.       C.H. Bennett, “Logical Reversibility of Computation,” IBM J.Research and Development, November 1973, pp. 525-53.  

6.     L. Bisdounis, D.Gouvetas,., and O.Koufopavlou., “A Comparative study of CMOS circuit design styles for low power high-speed VLSI circuits,” Int. J. of Electronics, vol.84, no. 6, 1998, pp. 599-613.

7.       A.Gupta. “Design Explorations of VLSI Arithmetic Circuits,” Ph.D. Thesis, BITS, Pilani, India, 2003.

8.       Guyot Alain, Hochet Bertrand, and Muller Jean-Michel.  “A Way to Build Efficient Carry-Skip Adders,” IEEE Transactions on Computers C, vol.30, October, 2010, pp.1144-1151.

9.       R. Zlatanovici and B. Nikolic, “Power-Performance Optimization for Custom Digital Circuits”, Proc. of PATMOS, Sept 2007, pp. 404-414, Leuven, Belgium.

10.     E. Fredkin and T. Toffoli, “Conservative Logic,” Intl. J. Theoretical Physics, vol. 21, nos. 3-4,1982 ,pp. 219-253.

11.     M Perkowski and P Kerntopf, “Reversible Logic,” invited tutorial, Proc. of EURO-MICRO, Warsaw, Poland,Sept 2001.

12.     M. Perkowski, et al, “Regularity and Symmetry as a Base for Efficient Realization of Reversible Logic Circuits,” Proc. of Intl. Workshop on Logic Synthesis, June 2001, pp. 90-95.

13.     P.D. Picton, “Fredkin gates as the basis for comparison of different logic designs,” Synthesis and Optimisation of Logic Systems, in IEE, London, 1994.

14.     D.P.Vasudevan, P.K.Lala, J.Di and J.P. Parkerson, “Reversible-logic design with online testability,” IEEE Trans. on Instrumentation & Measurement, Vol.55, No.2,
April 2006, pp.406-414.

15.     J.W. Bruce, M.A. Thornton, L. Shivakumaraiah, P.S. Kokate, and X. Li, “Efficient Adder Circuits Based on a Conservative Reversible Logic Gate,” Proc.of IEEE Computer Society Annual Symp. On VLSI, Pittsburgh, Pennsylvania, April 2002, pp.83-88.

16.     Tanner EDA Inc. 1988, User’s Manual, 2005.

17.     F. Najm. “A survey of power estimation techniques in VLSI circuits,” IEEE Trans. on VLSI Systems, vol.2 (4), 1994, pages 446–455.

18.     Kang, S.,“Accurate simulation of power dissipation in VLSI circuits”, IEEE Journal of Solid-State Circuits, vol. 21,1986, pp.889-891.




S.H. Jagtap, M.M Patil, S.D. Ruikar

Paper Title:

Multiscale Geometric Representation for Single Image Super-Resolution

Abstract:   This paper presents comparative study of different single image SR algorithms and takes deep drive on a new approach to single-image super-resolution, based upon Multiscale Geometric Representations. Nowadays computational power of processors are increasing therefore, it has become feasible to use more robust and computationally complex algorithms that increase the resolution of images without distorting edges and contours. We present a novel image interpolation algorithm that uses the new contourlet transform to improve the regularity of object boundaries in the generated images.  By using a simple wavelet-based linear interpolation scheme as our initial estimate, we use an iterative projection process based on two constraints to drive our solution towards an improved high-resolution image. This algorithm generates high-resolution images that are competitive or even superior in quality to images produced by other similar SR methods.

  Image super-resolution (SR), contourlet transform, geometric regularity, directional multi-resolution image.


1.       Jianchao Yang, John Wright, Thomas S. Huang, Yi Ma “Image Super-Resolution Via Sparse Representation” in IEEE transactions on image processing, VOL. 19, NO. 11, NOVEMBER 2010.
2.       J. Yang, J. Wright, T. Huang, and Y. Ma “Image super-resolutions sparse representation of raw image patches” in Proc. IEEE Conf.Comput. Vis. Pattern Recognit., 2008, pp. 1–8.

3.       Qi Pan, Chengying Gao, Ning Liu,  Jiwu Zhu “Single Frame Image Super-resolution Based on Sparse Geometric Similarity” Journal of Information & Computational
Science 7: 3 (2010)  799–805

4.       Roman Zeyde, Michael Elad and Matan Protter “On Single Image Scale-Up using Sparse-Representations” The Computer Science Department Technion – Israel Institute of Technology – Haifa 32000.

5.       S. Farsiu, M. D. Robinson, M. Elad, and P. Milanfar, “Fast and robust multiframe super-resolution” IEEE Trans. Image Process., vol. 13, no.10,pp. Oct.2004.

6.       H. S. Hou and H. C. Andrews, “Cubic spline for image interpolation and digital filtering” IEEE Trans. Signal Process., vol. 26, no. 6, pp. 508–517, Dec. 1978.

7.       J. Sun, Z. Xu, and H. Shum, “Image super-resolution using gradient profile prior” in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2008, pp. 1–8.

8.       Lyndsey C. Pickup “Machine Learning in Multi-frame Image Super-resolution” Robotics Research Group Department of Engineering Science University of Oxford, Michaelmas Term, 2007

9.       M. E. Tipping and C. M. Bishop, “Bayesian image super-resolution” in Proc. Adv. Neural Inf. Process. Syst. 16, 2003, pp. 1303–1310.

10.     S. Baker and T. Kanade, “Limits on super-resolution and how to break them” IEEE Trans. Pattern Anal. Mach. Intell., vol. 24, no. 9, pp. 1167–1183, Sep. 2002.

11.     S. Dai, M. Han, W. Xu, Y. Wu, and Y. Gong, “Soft edge smoothness prior for alpha channel super resolution” in Proc. IEEE Conf. Comput. Vis. Pattern Class., 2007, pp. 1–8.

12.     W. T. Freeman, E. C. Pasztor, and O. T. Carmichael, “Learning low level vision” Int. J. Comput. Vis., vol. 40, no. 1, pp. 25–47, 2000.

13.     J. Sun, N. N. Zheng, H. Tao, and H. Shum, “Image hallucination with primal sketch priors” in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2003, vol. 2, pp. 729–736.

14.     S. T. Roweis and L. K. Saul, “Nonlinear dimensionality reduction by locally linear embedding” Science, vol. 290, no. 5500, pp. 2323–2326, 2000.

15.     D. L. Donoho, “Compressed sensing” IEEE Trans. Inf. Theory, vol. 52, no. 4, pp. 1289–1306, Apr. 2006.

16.     H. Rauhut, K. Schnass, and P. Vandergheynst, “Compressed sensing and redundant dictionaries” IEEE Trans. Inf. Theory, vol. 54, no. 5, May 2008.

17.     M. Elad and M. Aharon, “Image denoising via sparse and redundant representations over learned dictionaries” IEEE Trans. Image Process., vol. 15, no. 12, pp. 3736–3745, Dec. 2006.

18.     J. Mairal, G. Sapiro, and M. Elad, “Learning multiscale sparse representations for image and video restoration” Multiscale Model. Sim., vol. 7, pp. 214–241, 2008
19.     M. Aharon, M. Elad, and A. Bruckstein, “K-svd: An algorithm for designing overcomplete dictionaries for sparse representation” IEEE Trans. Signal Process., vol. 54, no. 11, pp. 4311–4322, Nov. 2006.

20.     H. Lee, A. Battle, R. Raina, and A. Y. Ng, “Efficient sparse coding algorithms” in Proc. Adv. Neural Inf. Process. Syst., 2007, pp. 801–808.

21.     Nickolaus Mueller, Yue Lu and Minh N. Do, “Image Interpolation Using Multiscale Geometric Representations” Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign.

22.     K. Jensen and D. Anastassiou, “Subpixel edge localization and the interpolation of still images,” IEEE Trans. Image Proc. 4, pp. 285–295, March 1995.

23.     J. Allebach and P. W. Wong, “Edge-Directed interpolation,” in Proc. IEEE Int. Conf. on Image Proc.,1996.

24.     D. Su and P. Willis, “Image interpolation by pixel level data-dependent triangulation,” Computer Graphics Forum 23, pp. 189–201, June 2004.

25.     X. Li and M. T. Orchard, “New edge-directed interpolation,” IEEE Trans. Image Proc. 10, pp. 1521–1527, October 2001.

26.     H. Jiang and C. Moloney, “A new direction adaptive scheme for image interpolation,” in Proc. IEEE Int. Conf. on Image Proc., pp. 369–372, 2002.

27.     W. K. Carey, D. B. Chang, and S. S. Hermami, “Regularity-preserving image interpolation,” IEEE Trans. Image Proc. 8, pp. 1293–1297, September 1999.

28.     D. D. Muresan and T. W. Parks, “Prediction of image detail,” in Proc. IEEE Int. Conf. on Image Proc., pp. 323–326, 2000.

29.     O. G. Guleryuz, “Nonlinear approximation based image recovery using adaptive sparse reconstructions and iterated denoising: Part I - theory,” IEEE Trans.
Image Proc. 15, pp. 539–554, March 2006.




Jeff Huang, Ken Nagasaka

Paper Title:

The Trends of Greenhouse Gas Emission for Japanese Electric Utility Post Kyoto Protocol

Abstract:   Japan was on track achieve the Greenhouse gas (GHG) emission reduction target defined under the Kyoto Protocol. But what will be happen after Post Kyoto Protocol, especially by including the impact of devastating March 11, 2011 Earthquake (311 Earthquake) in northeast coast of Japan remained unclear. This paper will firstly describe the current situation of GHG emission and reduction target for Japanese electric utility industry. Followed by introduced the technique of Artificial Neural Network (ANN) to forecast trend of the electricity consumption and GHG emission in Japan, with and without the impact of 311 Earthquake. In the conclusion, we analyze the challenges faced by Japanese electric utility industry regarding the issue of GHG emission reduction Post Kyoto Protocol. According to the simulation result, decrease in electricity consumption coupled with the large increase in nuclear energy to be introduce into Japanese electricity generation, the GHG emission level is expected to significantly decline from 2012-2020. The electricity consumption level in 2020 will be 1% higher than 2010 level but the GHG emission is 3% lower accordingly. If we included the impact of 311 Earthquake into the simulation, the GHG emission generated by Japanese electric utility industry will reach to 656 million metric tons CO2 in 2020. This is 311.4 million metric tons in excess of the forecast without the impact of the 311 Earthquake. This large increase amount will create a big pressure and challenge for Japanese electric utility in regard of emission reduction Post Kyoto Protocol.

  Greenhouse Gas (GHG) Emission, Post Kyoto Protocol, Emission Reduction, Forecasting, Artificial Neural Network (ANN).

1.       Environmental Action Plan by the Japanese Electric Utility Industry, The Federation of Electric Power Companies of Japan (FEPC), 2010,
2.       Electricity Review Japan, The Federation of Electric Power Companies of Japan (FEPC), 2011,

3.       The Strategic Energy Plan of Japan, Ministry of Economy Trade and Industry Japan (METI), 2010, 

4.       Doulai.P and W.Cahill,  “Short-Term Price Forecasting in Electric Energy Market”, International Power Engineering Conference (IPEC2001), Singapore.

5.       Yi, M.M., K.S. Linn and M. Kyaw, “ Implementation of Neural Network Based Electricity Load Forecasting”, World Academy of Science, Engineering and Technology, Singapore. Volume 32. pp: 381- 386. ISSN 2070-3740, 2008.

6.       Mamum . M.A., K. Nagasaka and S.M Salim Reza, “ Load Demand Prediction of a Power System by Applying an Intelligent Method”, 3rd International Conference Electrical & Computer Engineering ICECE, Dhaka, Banagladesh. pp: 198-201. ISBN 984-32-1804-4, 2004

7.       Jane Nakano, “Japan’s Energy Supply and Security since the March 11 Earthquake”, Center for Strategic and International Studies (CSIS), 2011.

8.       Electricity Generated and Purchased, The Federation of Electric Power Companies of Japan (FEPC), 2011




D.Devi Aruna, P.Subashini

Paper Title:

CCMP-AES Model with SNAuth-SPMAODV Routing Potocol to Secure Link and Network Layer for Mobile Adhoc Networks in Military Scenario

Abstract:   Mobile Adhoc network is a special kind of wireless networks. It is a collection of mobile nodes without having aid of established infrastructure. Mobile Adhoc network are vulnerable to attacks compared to wired networks due to limited physical security, volatile network topologies, power-constrained operations, intrinsic requirement of mutual trust among all nodes. During deployment, security emerges as a central requirement due to many attacks that affects the performance of the ad hoc networks. Particularly Denial of Service attack is one such severe attack against ad hoc routing protocols which   is a challenging one to defend against in military communication environments. The proposed model combines SNAuth-SPMAODV with CCMP-AES mode to defend against Denial of Service attack and  it also  provides confidentiality and authentication of packets in both routing and link layers of MANET. The primary focus of this work is to provide security mechanisms while transmitting data frames in a node to node manner. The security protocol CCMP-AES working in data link layer keeps data frame from eavesdropping, interception, alteration, or dropping from unauthorized party along the route from the source to the destination. The simulation is done for different number of mobile nodes using network simulator Qualnet 5.0. The proposed model has shown better results in terms of total bytes received, packet delivery ratio, throughput, End to End delay and Average jitter

Keywords:  MANET, Mobile adhoc network, Denial of Service attack, Strict priority algorithn, Secure neighbor authentication, Advanced encryption standard.


1.       Changhua He and John C Mitchell, “Security Analysis and Improvements for IEEE 802.11i”, in the Proceedings of the 12th Annual Network and Distributed System Security Symposium (NDSS'05), 2005. 
2        .Specification for the Advanced Encryption Standard (AES), FIPS 197, U.S. National Institute of Standards and Technology. November 26, 2001. [Online] Available at:

3.       D. Whiting, R. Housley, and N. Ferguson, “AES Encryption & Authentication Using CTR Mode & CBC-MAC”, IEEE Doc. 802.11-02/144r2, Mar 2002.

4.       M. Junaid , Dr Muid Mufti and  M.Umar Ilyas, “Vulnerabilities of IEEE 802.11i Wireless LAN CCMP Protocol”, In the Proceedings Of World Academy Of Science, Engineering And Technology Volume 11, February 2006,pp 228-233

5.       Asad Amir Pirzada Chris McDonald and  Amitava Datta: “Performance Comparison of Trust-Based Reactive Routing Protocols” IEEE Transactions on Mobile Computing, Vol. 5, Issue 6,June 2006, pp695 – 710.

6.       P. Chenna Reddy and Dr. P. ChandraSekhar Reddy, “Performance Analysis of Adhoc Network Routing Protocols”, International Symposium on Ad Hoc and Ubiquitous Computing, 2006. ISAUHC '06.  August 2007 ,pp.186 - 187

7.       Geetha Jayakumar and Gopinath Ganapathy ,“Performance Comparison of Mobile Ad-hoc Network Routing Protocol”, IJCSNS International Journal of Computer Science and Network Security, VOL.7 No.11, November 2007,pp 77-83.

8.       Hao Yang, Haiyun Loo, Fan Ye, Sogwu Lu and Lixia Zhog, Security in mobile ad hoc networks, challenges and solution, Wireless Communication, IEEE Volume I, issue 1, Feb 2004, pp .38 – 47.

9.       Dr.G.Padmavathi, Dr.P.Subashini, and Ms.D.Devi Aruna, Impact of Wormhole Attacks and Performance Study of  Protocols in Mobile Ad Hoc Networks, Journal of Information Assurance and Security , Pages 094-101,2010, pp. 094-101.

10.     Abhay Kumar Rai, Rajiv Rwandan Tewari & Saurabh Kant Upadhyay, Different Types of Attacks on Integrated MANET-Internet Communication, International Journal of Computer Science and Security (IJCSS) Volume 4, Issue 3, July 2010, Pages 265-274.

11.     C.E. Perkins, E.M. Royer & S. Das, Ad Hoc On Demand Distance Vector (AODV) Routing, IETFInternet draft, draft-ietf-manet-aodv-08.txt, March 2001

12.     A. Boukerche,” Performance Evaluation of Routing Protocols for Ad Hoc Wireless Networks”, Mobile Networks and Applications 9, Netherlands, 2004, pp. 333-342

13.     A.E. Mahmoud, R. Khalaf & A, Kayssi,” Performance Comparison of the AODV and DSDV Routing Protocols in Mobile Ad-Hoc Networks”, Lebanon, 2007

14.     Kamanshis Biswas and Md. Liakat Ali , “Security Threats in Mobile Ad Hoc Network” Department of Interaction and System Design School of Engineering, ,March2007, Page9-26.

15.     Wenjia Li and Anupam Joshi,”Security Issues in Mobile Ad Hoc Network” - A Survey, Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County ,2007, page 6-10,
16.     Jong mu Choi and Young bae Ko. A Performance Evaluation For Ad Hoc Routing Protocols In Realistic Military Scenarios. In Proceedings of The 9th CDMA International Conference, October 2004.

17.     Georgios Kioumourtzis, Christos Bouras, and Apostolos Gkamas, performance evaluation of ad hoc routing protocols for military communications, international journal of network management, Wiley InterScience 2011.

18.     Qualnet Documentation, “Qualnet 5.0 Model Library, Network Security”, Available:Http://Www.Scalablenetworks.Com/Products/Qualnet/Downlaod....




Sangeeta Jana, Malay K. Pandit, Asim K. Jana

Paper Title:

Statistical Optimal Controller for AGV’s to achieve High Index of Performance (IP)

Abstract:   This paper exhibits a new optimal control two simultaneous processes: velocity and speed control in an embedded controller for an AGV (autonomous guided vehicle) in uncertain situations. This technique has been used to fuse information from internal and external sensors to navigate the AGV in an unmapped environment or in case of uncertainty. Uncertainty, the lack of certainty, A state of having limited knowledge where it is impossible to exactly describe existing state or future outcome, more than one possible outcomes. We have optimized speed and position error that contribute to the motion control problems of an AGV. During the movement of an AGV, whether straight or arc create position and orientation errors. The main concern is to achieve the real time and robustness performance to precisely control the AGV movements. We report here for the first time a novel optimization method based on Markov chain.

  Uncertainty, Robust, system index performance, probability of system error.


1.        F.J.Cazorla, Peter M.W.Knijnenburg and E.Fernandez” QOS for high performance SMT processors in embedded systems”, IEEE Micro,July-Aug 2004,pp.24-31.
2.        J.M.Peha and F.A.Tobagi,”Cost based Scheduling and Dropping Algorithms to support Integrated Services”, IEEE transactions on Communications, Vol 44, No.2, Feb.1996, pp.192-202.

3.        J.Liu and E.A.Lee, “Timed multitasking for real-time embedded software”, IEEE Control system Magazine, pages 65-75, 2003.

4.        C.L.Liu and J.W.leyland, “Scheduling algorithms for multiprogramming in a hard real time environment”, Journal of the ACM, 20(1):46-61, 1973.

5.        A.Snaverly, D.M.Tullsen and G.Voelker , “systematic job scheduling with priorities for a simultaneous multithreaded processor” Proc of 9th International Conf on Architectural Support for programming languages and operating systems(ASPLOS-9),ACM Press,2000,pp,234-244.

6.        J.T.Buck,” static scheduling and code generation from dynamic dataflow graphs with integer valued control systems”. In IEEE Asilomar Conf. on signals, systems, and computers, Pacific Grove,CA, 1994.

7.        Matschulat ,C.A.M.Marcon ,F.Hessel,”A QOS scheduler for real time Embedded systems’’,9th Int symposium on Quality Electronic Design(Isqed-2008),March 17-19,2008

8.        S.Tomoyoshi, T.Kosuke,”Table based QOS control for embedded real time systems”, Proc of the ACM SIGPLAN 1999 workshop on languages, compilers, and tools for embedded systems,1999,pp-65-72.

9.        Atanas Georgive and Peter K.Allen(2004), “Localization Methods for a Mobile Robot in Urban environments” IEEE, Transactions on robotics,Vol,20.No.5,October2004,pp851-864.

10.     R.Jain,C.J.Hughes and S.V.Adve,’’Soft real time scheduling on simultaneous multithreaded processors”, Proc of 23rd real time systems symposium(RTSS-23),IEEE Press,2002,pp.134-135.




A.P.Shrotri, S.B.Khandagale

Paper Title:

Design of a Predictive Maintenance Program

Abstract:   The modern manufacturing plants are generally equipped with complex and continuous running machines and equipment. These are characterized with high speeds heavy working loads high temperatures and pressures etc. The shutdown costs are very large in case of such complex plants. Any breakdown or malfunctioning in such cases is not only a costly affair but it also raises the question of safety of plant itself and persons working there in. This initiates the need for prediction of failure of machines as well in advance so as to initiate the corrective action. The condition monitoring and subsequent condition based maintenance is an effective measure in this regard. However in a factory same maintenance practice is neither desirable nor required for all equipment and machines and a routine practice is to use mixed maintenance scheme. As the predictive maintenance efforts are very expensive hence the design of predictive maintenance scheme itself becomes a task of utmost care. This paper suggests a stepwise procedure for design of predictive maintenance program and also discusses the justification factors, choice of monitoring techniques and various related facts regarding predictive maintenance. The paper also includes a case study of condition monitoring and thereby arranging a predictive maintenance for sugar industry.

  condition monitoring, Predictive maintainance,VEIN analysis, vibration analysis.


1.        Higgnis L.R. and Morrow L.C. : Maintenance engineering Hand Book (McGraw-Hill).
2.        Corder A.A. : Maintenance Management Techniques (McGraw-Hill)  

3.        P. Gopalkrishnan & A.K. Banaerji : Maintenance and Spare parts management (Prentice-Hall of India).

4.        Dr. S.K.Basu : Reliability based condition monitoring (Proceedings of IPROM-97).

5.        R. Keith Mobley:  “An Introduction to Predictive Maintenance” 

6.        Sadettin Orhan , Nizami Aktu¨rk , Veli C¸ elik: “Vibration monitoring for defect diagnosis of rolling element bearings as a predictive maintenance tool: Comprehensive case studies”, NDT&E International 39 (2006) 293–298.

7.        MaCarmen Carnero :“An evaluation system of the setting up of predictive maintenance programmes”, Reliability Engineering and System Safety 91 (2006) 945–963.

8.        Dheeraj Bansal , David J. Evans , Barrie Jones :“A real-time predictive maintenance system for machine systems”, International Journal of Machine Tools & Manufacture 44 (2004) 759–766.




Devashree Rai, Kesari Verma, A. S. Thoke

Paper Title:

Comparative Analysis of Single and Multiple Minimum Support Based Association Rule Mining Algorithms

Abstract:   Association rule mining techniques discover associations between entities. Some techniques are single minimum support based while some are multiple minimum support based. Single minimum support based approach suffer from rare item problem dilemma while multiple support based approach considers rare items for mining association rules. In this paper we have evaluated performance of Apriori-T and MSApriori-T Algorithms that are single and multiple minimum based approaches respectively. These Algorithms uses an efficient data storage mechanism Total support tree for storing item sets.

  Apriori-T, Association rule mining, MSApriori-T, Total support tree.


1.       M.S. Chen, J. Han, P.S. Yu, “Data mining: an overview from a database perspective”, IEEE Transactions on Knowledge and Data Engineering, 1996, 8, pp. 866-883.
2.       J. Han, M. Kamber, Data Mining: Concepts and Techniques, Morgan Kaufmann Publisher, San Francisco, CA, USA, 2001.

3.       Agrawal, R., Imielinski, T., and Swami, A. “Mining association rules between sets of items in large databases.” SIGMOD, 1993, pp. 207-216.

4.       Agrawal, R., and Srikanth, R. “Fast algorithms for mining association rules.” VLDB, 1994.

5.       J.Han, Y. Fu, “Discovery of multiple-level association rules from large database”, in the twenty-first international conference on very large data bases, Zurich, Switzerland, 1995, pp. 420-431.W.-K. Chen, Linear Networks and Systems (Book style).            Belmont, CA: Wadsworth, 1993, pp. 123–135.

6.       J.Han, J.Pei and Y.Yin., “Mining frequent patterns without candidate Generation”, in: Proceeding of ACM SIGMOD International Conference Management of Data, 2000, pp. 1-12.

7.       Coenen and Leng (2004). Data Structures for Association Rule Mining: T-trees and P-trees to appear in IEEE Transaction in Knowledge and Data Engineering.

8.       Devashree Rai, Kesari Verma, A.S. Thoke “MSApriori using total support tree data structure” (accepted for publication) IJCA, to be published.

9.       Liu, B., Hsu, W., and Ma, Y. “Mining Association Rules with Multiple Minimum Supports.” SIGKDD Explorations, 1999.

10.     R. Rymon, “Search through Systematic Set Enumeration,” Proc. Third Int’l Conf. Principles of Knowledge and Reasoning, pp. 539-550, 1992.

11.     Weiss, G. M. “Mining With Rarity: A Unifying Framework.” SIGKDD Explorations, 2004, Vol. 6, Issue 1, pp. 7 - 19.

12.     Mannila, H. “Methods and Problems in Data Mining.” ICDT, 1997.

13.     Uci: Blake, c.l., & Merz, C.J (1998) UCI repository of machine leaning databases from




Venkata Raviteja. K, K.S.N Murthy, I.Govardhani, M.Venkata Narayana

Paper Title:

Read Range Performance of UHF RFID Reader Antenna

Abstract:   Now a days ultrahigh frequency (UHF) radio frequency identification has gaining popularity because of its rapid development in automated identification of objects wirelessly and having wide range of applications. Radio frequency identification (RFID) is a technology that uses radio waves to transfer data from an electronic tag called RFID tag or label attached to an object through a reader for the purpose of identifying and tracking the object. The tag's information is stored electronically. It includes a small RF transmitter and receiver. An RFID reader transmits an encoded radio signal to interrogate the tag. The tag receives the message and responds with its identification information. In this paper, the read range capabilities of proposed antenna at UHF range are determined. By using the proposed antenna we simulate return loss, gain, Vswr and radiation patterns using HFSS software.

  Radio frequency identification (RFID), Reader antenna, Ultrahigh frequency (UHF), Near-field, Far-field


1.        K. Finkenzeller, RFID Handbook: Radio-FrequencyIdentificationFundamentals and Applications, 2nd ed.: Wiley, 2004.
2.        D. M. Dobkin, The RF in RFID. Oxford, U.K.: Elsevier, 2008

3.        P. V. Nikitin, K. V. S. Rao, and S. Lazar, “An overview of near field UHF RFID,” in Proc. IEEE Int. Conf. RFID, Mar. 2007, pp. 167–174.

4.        X. Qing, C. K. Goh, and Z. N. Chen, “A broadband UHF near-field RFID antenna,” IEEE Trans. Antennas Propag., vol. 58, no. 12, pp.3829–3838, Dec. 2010.

5.        X. Qing and Z. N. Chen, “Antenna for near field and far field radio frequency identification,” U.S. Patent Appl. Pub. US 20100026439 A1, Feb. 4, 2010.

6.        D. M. Dobkin, S. M. Weigand, and N. Iye, “Segmented magnetic antennas for near-field UHF RFID,” Microw. J., vol. 50, no. 6, pp. 96–103, Jun. 2007.

7.        Dr. K.S.N Murthy, Venkata Raviteja.K, I.Govardhani, M.Venkata Narayana   Published a paper on “Multi-band Ladder-shape Microstrip Patch Antenna”, IJSER Volume 3, Issue 3, March 2012 Edition.

8.        Govardhani.Immadi, M.S.R.S Tejaswi  M.Venkata Narayana, N.Anil Babu, G.Anupama , K.Venkata Ravi teja“Design of Coaxial fed Microstrip Patch Antenna for 2.4GHz BLUETOOTH Applications” VOL. 2, NO. 12, December 2011 ISSN 2079-8407, Journal of Emerging Trends in Computing and Information Sciences.

9.        B.T.P.Madhav, K V L Bhavani, Prof. VGKM Pisipati, Venkata Ravi Teja.K, K.Rajkamal, K.V.V.Kumar “Dual Polarized 16X16 MSPA Antenna Using FR4 Epoxy” Int. J. Advanced Networking and Applications.Volume: 03; Issue: 03; Pages:1199-1202 (2011)

10.     I.Govardhani, K.Rajkamal, M.Venkata Narayana, S.Venkateswarlu published a paper on “Phased Array Antenna for Millimeter Wave Radar in W-band using Liquid Crystal Substrate” VOL. 2, NO. 12, December 2011 ISSN 2079-8407Journal of Emerging Trends in Computing and Information Sciences

11.     I.Govardhani , M.Venkata Narayana, Prof S.Venkateswarlu, K.Rajkamal Published paper in  International Journal of Engineering Research and Applications (IJERA) ISSN: 2248-9622 Vol. 2, Issue 1,Jan-Feb 2012, pp.764-767 on  “Microstrip patch antenna using holographic structure for WLAN and Ku Band application”.

12.     I.Govardhani , M.Venkata Narayana Published paper in International Journal of Computer   Science & Communication Networks,Vol 2(1), 375-380, ISSN:2249-5789  on  Rectangular Patch Array Antenna with Liquid Crystal Substrate for Ka and Q Band Applications.

13.     M. Venkata Narayana, I.Govadhani, K.P.Sai Kumar, K. Pushpa Rupavathipublished paper on “Comparative Analysis of Exponentially Shaped Microstrip-Fed Planar Monopole Antenna With and Without Notch “VOL. 2, NO. 11, October 2011 ISSN 2079-8407. Journal of Emerging Trends in Computing and Information Sciences.

14.     M. Venkata Narayana, A.Vikranth, I. Govardhani, Sd. Khaja Nizamuddin, Ch. Venkatesh  published paper on”A Novel Design of a Microstrip Patch Antenna with an End Fire Radiation for SAR Applications” Volume 2 No.1, January 2012 ISSN 2224-3577 International Journal of Science and Technology .

15.     A. L. Popov, O. G. Vendik, and N. A. Zubova, “Magnetic field intensity in near-field zone of loop antenna for RFID systems,” Tech. Phys. Lett., vol. 36, no. 10, pp. 882–884, 2010.




Anuradha Pathak, A.K. Wadhwani

Paper Title:

Data Compression of ECG Signals Using Error Back Propagation (EBP) Algorithm

Abstract:   Heart is one of the vital parts of our human body, which maintains life line. The paper deals with an efficient composite method which has been developed for data compression and signal reconstruct of ECG signals. ECG data compression algorithm is needed that will reduce the amount of data to be transmitted, stored and analyzed, but without losing the clinical information content. After carrying out detailed studies and by training different topologies of  error back propagation (EBP) artificial neural network (ANN) with respect to variation in number of hidden layers and number of elements, the topology with single hidden layer and four elements in each hidden layer has been finalized for ECG data compression using a data base. The compression ratio (CR) in ANN method increases with increase in number of ECG cycles. The entire programming in this paper is carried out on the version of MATLAB 7.8.

  Compression, Data compression, ECG, Compression ratio (CR), PRD and EBP.


1.        S.M.S. Jalaleddine., "ECG Data Compression Techniques - A Unified Approach", IEEE Trans. on Biomed. Eng., Vol. 37, No. 4.1990, pp. 329-343.
2.        Y. Zigel, A. Cohen, and A. Katz, “ECG Signal Compression Using Analysis by Synthesis Coding”, IEEE Trans. on Biomed.Eng, Vol. 47, No. 10, October, 2000, pp. 1308-1316;

3.        Y.Kocyigit, “ECG Data Compresion by Artifical Neural Networks,” Master Thesis, I.T.U., 1996.

4.        S.C. Saxena, Vinod Kumar and V.K.Giri, ‘ECG Data Compression using EBP-NN “Vol. 20,No.6, Nov-Dec 2003,pp 583-604.

5.        S C Saxena, A Sharma & S C Chaudhary, Data compression and feature extraction of ECG signals, International Journal of System Science, Vol. 28, No. 5, pp 483-498, 1997.

6.        J R Cox, F M  Nolle , H A Fozzard & G C Oliver, AZTEC  A  preprocessing program of real time ECG rhythm analysis, IEEE Trans on BME vol. 15, pp 128-129, 1968.




Hemlata Shakya, A.K.Wadhwani

Paper Title:

Transform Based ECG Data Compression

Abstract:  Electrocardiogram (ECG) is widely used in the diagnosis and treatment of cardiac disease. The data needs to be stored and transmitted, so it is necessary to compress the ECG signal data in efficient way. ECG compression methods can be classified into three categories: Direct method, Parameter extraction method & Transform method. In this paper a comparative study of transform. ECG compression allows real time transmission over telephone networks, economic off-line transmission to remote interpretation sites, improve Holter monitor system and enables efficient ECG rhythm analysis algorithms. Wavelet compression technique was found to be optimal in terms of compression

  ECG, Compression, DWT, DST, CR and PRD.


1.        MIT-BIH Arrhythmia Database,
2.        King-Chu Hung,Chin-Feng Tsai, “A linear quality control design for high efficient wavelet based ECG data compression”, Computer Method Programs in biomedicine 94(2009)

3.        B.R.S Reddy and I.S.N. Murty (1986) ECG data compression using Fourier description, IEEE Trans.Bio-med. Eng. BME-33

4.        R. S. Khndpur, “Biomedical Engineering and Instrumentation”.

5.        S.jalaleddine, C.Huthens, R.Strattun, W. Coberly, “ECG Data Compression Technique-A unified approach”,IEEE trans.On Biomedical Engineering, vol.37,pp. 329-343, 1990

6.        Wang,Ying Chen “ECG Signal Compression Based on MSPIHT Algorithm”,5th International Conference on Information technology and Application in Biomedicine,China,May30-31,2008.

7.        M. Clausen and U. Baum (1993): Fast Fourier Transforms. BI-Wiss.- Verl.

8.        Abedlaziz Ouamri “ECG compression method using Lorentzian Function model”, Science Direct, Digital Signal Processing 17(2007),8th August 2006.

9.        Xingyuan Wang,Juan Meng, “A 2-D ECG compression algorithm based on wavelet transform and vector quantization,Science Direct,Digital Signal Processing 18(2008)179-32,)28th March 2007.




R.Suresh, K.Saranya, S.Dhivya, K.Thilagapriya

Paper Title:

Proficient Search in Relational Database Based on Keyword

Abstract:   Information retrieval (IR) is the process of attaining documents relevant to an information need from a great document set. The integration of DB and IR provides flexible ways for users to query information in the same platform. Keyword search is the most popular information retrieval method as users need to know neither a query language nor the underlying structure of the data. In this paper we focus on the keyword query ranking and based on the user preference the top-k results will be retrieved from the relational database and returned to the user. This system will provide an efficient query processing and the ranking functions which is based on the scores calculated by different methods. These scores are the basis for the ranking of the documents.

  Candidate network, Information retrieval, Ranking method.


2.        Yi Luo ,Xuemin Lin, Wei Wang and Xiaofang Zhou “SPARK: Top-k Keyword Query in Relational Databases”, SIGMOD’07

3.        S. Agrawal, S Databases,” Proc. 18th Int’l Conf. Data Eng. (ICDE ’02), pp. 5-16, 2002

4.        Jeffrey Xu Yu, Lu Qin and  Lijun Chang “Keyword Search in Relational Databases: A Survey”,IEEE 2010.

5.        V. Hristidis and Y. Papakonstantinou, “DISCOVER: Keyword Search in Relational Databases,” Proc. Int’l Conf. Very Large DataBases (VLDB), pp. 670-681, 2002. 

6.        V. Hristidis, L. Gravano, and Y. Papakonstantinou, “Efficient IRStyle Keyword Search over Relational Databases,” Proc. 29th Int’l Conf. Very Large Data Bases (VLDB), 2003. 

7.        G. Bhalotia, A. Hulgeri, C. Nakhe, S. Chakrabarti, and S.Sudarshan, “Keyword Searching and Browsing in Databases Using BANKS,”Proc. 18th Int’l Conf. Data Eng. (ICDE ’02), pp. 431-440, 2002. 

8.        F. Liu, C.T. Yu, W. Meng, and A. Chowdhury, “Effective Keyword Search in Relational Databases,” Proc. ACM SIGMOD Int’l Conf. Management of Data, pp. 563-574, 2006.

9.        S. Wang, Z. Peng, J. Zhang, L. Qin, S. Wang, J.X. Yu, and B.Ding, “Nuits: A Novel User Interface for Efficient Keyword Search over Databases,” Proc. 32nd Int’l
Conf. Very Large Data Bases (VLDB), pp. 1143-1146, 2006.

10.     B. Ding, J.X. Yu, S. Wang, L. Qin, X. Zhang, and X. Lin, “Finding Top-k Min-Cost Connected Trees in Databases,” Proc. IEEE 23rd Int’l Conf. Data Eng. (ICDE), 2007. 

11.     K. Golenberg, B. Kimelfeld, and Y. Sagiv, “Keyword Proximity Search in Complex Data Graphs,” Proc. 28th ACM SIGMOD Int’l Conf. Management of Data, 2008.

12.     B.B. Dalvi, M. Kshirsagar, and S. Sudarshan, “Keyword Search on External Memory Data Graphs,” Proc. VLDB Endowment, vol. 1,no. 1, pp. 1189-1204, 2008.
13.     H. He, H. Wang, J. Yang, and P.S. Yu, “Blinks: Ranked Keyword Searches on Graphs,” Proc. ACM SIGMOD Int’l Conf. Management of Data, pp. 305-316, 2007.

14.     M. Sayyadan, H. LeKhac, A. Doan, and L. Gravano, “Efficient Keyword Search Across Heterogeneous Relational Databases,” Proc. 23rd IEEE Int’l Conf. Data Eng. (ICDE), 2007.

15.     S. Tata and G.M. Lohman, “SQAK: Doing More with Keywords,” Proc. ACM SIGMOD Int’l Conf. Management of Data, pp. 889-902, 2008.

16.     Q.H. Vu, B.C. Ooi, D. Papadias, and A.K.H. Tung, “A Graph Method for Keyword-Based Selection of the Top-k Databases,”Proc. ACM SIGMOD Int’l Conf. Management of Data, 2008.

17.     B. Yu, G. Li, K.R. Sollins, and A.K.H. Tung, “Effective Keyword- Based Selection of Relational Databases,” Proc. ACM SIGMOD Int’l Conf. Management of Data, pp. 139-150, 2007.

18.     S. Agrawal, S. Chaudhuri, and G. Das, “DBXplorer: A System for Keyword-Based Search over Relational Databases,” Proc. 18th Int’l Conf. Data Eng. (ICDE ’02), pp. 5-16, 2002. Chaudhuri, and G. Das, “DBXplorer: A System for Keyword-Based Search over Relational




K.Kantha Rao, K. Jayathirtha Rao, A.G.Sarwade, B.Madhava Varma

Paper Title:

Bending Behavior of Aluminum Honey Comb Sandwich Panels

Abstract:   Aluminum sandwich construction has been recognized as a promising concept for structural design of light weight systems such as wings of aircraft. A sandwich construction, which consists of two thin facing layers separated by a thick core, offers various advantages for design of weight critical structure. Depending on the specific mission requirements of the structures, aluminum alloys, high tensile steels, titanium or composites are used as the material of facings skins. Several core shapes and material may be utilized in the construction of sandwich among them, it has been known that the aluminum honeycomb core has excellent properties with regard to weight savings and fabrication costs. This paper is theoretically calculate bending behavior, of sandwich panels  and to compare the strength to weight ratios of Normal Aluminium rod(panel) and Aluminium Honey Comb Panel .

  Aluminium material, Sand witch Panel, Honey Comb core, Adhesive .


1.       Hexcel. Honeycomb sandwich design technology. Publication No. AGU 223, Hexcel Co., Ltd., Duxford (UK), 1995.
2.       Thomsen, O.T. and W. Rits, Analysis and design of sandwich plates with inserts - a high order sandwich plate theory approach. Composites Part B: Eng., 1998. 29B: p. 795-807.

3.       Gaetano G.Galletti, Christine UinQuist, OmarS.Es-Said. Theoretical Design and Analysis of a Honeycomb Panel Sandwich Structure Loaded in Pure Bending, Elser,  May 2007.

4.       D.H. Chen. Bending deformation of Honeycomb  consisting of regular hexagonal cells, Elsevier, August 2010.

5.       Annette Meidell. Minimum Weight Design of Sandwich beams with  honeycomb core of arbitrary density, Elsevier January 2009.

6.       Kesley S,Gellatly  RA,clark BW.The shear modulus of foil honeycomb cores.

7.       Metals data hand book by NAYAR

8.       Bitzer, T (1997). Honeycomb Technology: Materials, Design, Manufacturing, Applications and Testing, London: Chapman & Hall.




Gehad Mohammed Sharaf, Mahdi Alhaji Musa, Azizah Abdul Rahman

Paper Title:

An Examination of Social Networking Sites Usage Among Muslims Student in Islamic Perspectives

Abstract:   Social networking sites (SNS) have created a new social dimension where individuals can develop increased levels of their social awareness by keeping in touch with old friends, making new friends, dispense new data or product. And also getting information in many more aspects of everyday lives, making one to become more knowledgeable which is very beneficial especially for students. In spite of many preaches by Islamic scholars on the appropriate ways to use these social media, many students tend to use it against the ethics enshrines by Islamic laws. The purpose of this research is to examine student’s level of awareness of Islamic regulations while using social networking sites. A survey was conducted among 450 Muslims Undergraduate student of University Teknologi Malaysia. The finding of this research indicates that some students use the social media appropriately by creating ethical Islamic group that will promote the good image of Islam, while other students had become addicted to the social networks so much so that they delayed their prayer time.

  Factor Analysis, Islamic regulations, Malaysia, Social Networking Sites, Students,


1.        Bandura A. Social Foundation of Thought and Action. Engl. Cliffs, NJ: Prentice-Hall. International Journal of Cyber Society and Education, 2007, Pages 131-142, Vol. 1, No. 2.
2.        Ashitari, et al. Social Networks In Islamic perspectives, journal of information science, 2009, vol. 12, page3-5, 

3.        Adam G & Salem H. The impact of Facebook on our Muslims students. Teach. Lib., 2009, vol.36(5): page 36.

4.        Bobko P, Lee C, Earley CP, Locke EA. An empirical analysis of a goal setting questionnaire. J. Organ. Behav., 2006, vol.12: page 467- 482.

5.        Lane Jefferson, Social Networks Media in Academia, journal of Information Science, 2009, vol2, page34-56, 

6.        Hammad M. & Jaffar G "Online Social Networking Issues within Academia and Engineering Education." University of Malaysia Teranganu,available:

7.        Hernandez, Sharon. "Ball State Study Shows College Students' Smartphone Usage Rising." Ball State University, 2010, available:

8.        Coyle, C. and Vaughn, H. Social networking: Communication revolution or evolution?Bell Labs Journal, 2008, vol3, page13-17

9.        Boyd, d. m. & Ellison, N. B. Social network sites: Definition, history, and scholarship. Journal of Computer-Mediated Communication, 2007, vol.13(1), article 11.

10.     Lane, J. E. “Facebook and Freedom: Student Speech on the Internet.” ACPA Developments, Winter 2006. Retrieved Sept. 10, 2007,available:ttp://

11.     De Souza, Z. and Dick, G. Information dsclosure on myspace- the what, the why and the implications. Pastoral Care in Education, 2008, vol.page26, 143-157.

12.     Duven, C. and Timm, D. Privacy and social networking sites: New directions for student services. 2008, vol3.

13.     Geach, N. and Haralambous, N. Regulating harassment: Is the law fit for the social networking age? The Journal of Criminal Law, 2007, 73, 241-257.

14.     Greenfield, P. and Subrahmanyam, KOnline communication and adolescent relationships. The Future of Children, 2008, 18, 119-140. Available.


16.     Siibak, A. Constructing the self through the photo selection- Visual impression management on social networking websites. Journal of Psychological Research on Cyberspace, 2009, vol.3(1) 1-6. available:


18.     Anderson JC, Gerbing DW. Structural Equation Modeling in Practice: A review and recommended two-step approach. Psychol. Bull.,1998, vol2, page411 - 423.




AshwiniJajda Modi, N. P. Shinkar

Paper Title:

Environmental Impact Assessment of Road from Ujjain to Jaora

Abstract:   This paper is related to“Environmental Impact Assessment of Road from Ujjain to Jaora”. As the EIA report i.e. Environmental Impact Assessment contains the detail study about the  positive as well as negative effects on the plants, human, animals and Environment. Our capacity for destruction is illustrated through the deterioration of the ozone layer, through the extinction of species, and through mass deforestation and desertification. In many parts of the world, economic development projects directed at improving levels of material comfort have had unintended detrimental effects on people and natural resources. Water, land, and air have been degraded to the point where they can no longer sustain existing levels of development and quality of life.We know that as, India is an developing country and  economic development in developing countries has been focused on immediate economic gains environmental protection has not been a priority because the economic losses from environmental degradation often occur long after the economic benefits of development have been realized.

  EIA,EMP,EPA, MOEF,Desertification, Deforestation.


1.     Ebisemiju, F., “Environmental impact assessment: making it work in developing countries”, Journal of Environmental Management, ,38 : 247-273.
2.     Environmental Impact Assessment Report Of Central Secretariat – Badarpur Corrido
3.     Shri S.C. Padhee ,”Rapid Environmental Impact Assessment And Environmental Management Plan”,  Gurubeda Iron Ore Mines (Over 49.776 Ha, Vill. Gurubeda, Keonjhar)

4.     Muraleedharan, V., “Evaluation of EIA procedures in India. Impact Assessment” ,EIA vol. 12, pp. 75-88.

5.     Road Development Projects, Madhya Pradesh State. 28/01/2011.

6.     Ross, W.A., “Environmental impact assessment in the Philippines: progress, problems, and directions for the future.” Environmental Impact Assessment Review, 14: 217-232.

7.     Road Development Projects, Madhya Pradesh State. 03/02/2011.

8.     Biswas, A.K. and QuGeping (1987) , “Environmental Impact Assessment for Developing countries”, Tycooly International ,London.  pp. 232.

9.     Rau &Woofes, “ Environmental Impact Assessment”.

10.   W.F.Canter , “Environmental Impact Assessment”. McGraw Hill Publications, 1977

11.   Bindu N. Lohani,J. Warren Evans , Robert R. Everitt, Harvey Ludwig, Richard A. Carpenter, Shih-Liang Tu, “Environmental Impact Assessment for Developing Countries in Asia”, Volume 1 – Overview




N.N. Osadebe  and C.A. Chidolue

Paper Title:

Response of Double Cell Mono Symmetric Box Girder Structure to Torsional-Distortional Deformations

Abstract:   In this paper the effect of middle web member on torsional-distortional deformations of a double cell mono symmetric box girder structure is examined. First, the torsional and distortional deformations of a single cell mono symmetric box girder structure were examined using a single span, simply supported bridge structure on the bases of Vlasov’s theory. By introducing a middle (vertical) web member on the single cell mono symmetric box girder section a double cell mono symmetric box girder structure of the same overall cross sectional dimensions was obtained. The torsional and distortional deformations of the double cell cross sectional profile were also evaluated and compared with those of the mono symmetric cross sectional profile. Results show that the introduction of the middle web member to obtain the double cell mono symmetric box girder structure reduced the distortional deformation by 118% and increased the torsional deformation by 14%

  box girder, distortion, mono symmetric, thin-walled, torsion, Vlasov’s theory.


1.        C.P. Heins, Bending and torsion design in structural member (Lexinton Books,  Massachusetts, 1975).
2.        V.Z.Vlasov,  Thin-walled space structures (Gosstrojizdat, Moscow, 1958).

3.        R. Dabrowski, 1968, Curved thin-walled girder ( translation No. 144, Cement and Concrete Association, London, 1968).

4.        C.P. Varbanov, Theory of elasticity (Technika Press Sofia, 4th Edition, 1976).

5.        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. 

6.        Z. Fan, and T.A. Helwig, Distortional loads and brace forces in steel box girders, Journal of. Structural Engineering, 128(6), 2002, 710-718.

7.        K.M. Sennah, and J.B. Kennedy, Literature review in analysis of box girder bridges, Journal of Bridge Engineering, 7 (2), 2002, 134-140. 

8.        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.

9.        Z.P. Bazant and M. El-Nimeiru, Stiffness method for curved box girders at initial stress,  Journal of Structural Division, 100(10), 1974, 2071-2090.

10.     S.H. Zhang and L.P.R. Lyons, Thin-walled box beam finite element for curved bridge analysis, Comput. Struct. Journal, 18(6), 1984, 1035-1046. 

11.     L.F. Boswell and S.H. Zhang, The effect of distortion in thin-walled box-spine beams, International Journal of Solid Structures, 20(9/10), 1984, 845-852.

12.     T. Usuki, The Theory of Curved Multi-Cell Box Girder Bridges Under Consideration of Cross-Sectional Distortion, Struct. Eng./Earthquake Eng. Journal, 4(2), 1987, 277-287 

13.     P. Waldron, The Significance of warping torsion in the design of straight concrete box-girder Bridges, Canadian Journal of Civil Engineering, 15(5) 1988, 879-889 

14.     J. Paavola, Study of curved Thin-Walled Girders, doctoral diss., Helsinki University of Technology, Espoo, Finland, PhD, 1990.

15.     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  

16.     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. 

17.     A. Tesar, Shear Lag in the Behaviour of Thin-Walled Box Bridges, Comput. Struct. Journal, 59(4),  1996, 607-612.

18.     L. Elsgolt, Differential Equations and the Calculus of Variation,  (MIR publishers, Mosco,1980, translated from the Russian by George Yankovsky.)

19.     American Association of State Highway and Transportation Officials (AASHTO), Load and Resistance Factor Design, ( LRFD), Bridge Design Specifications Washington , D.C, 1998). 

20.     N.N. Osadebe and C.A. Chidolue, Torsional-distortional response of thin-walled mono symmetric box girder structures, International journal of engineering research and application, submitted for publication.

21.     V.G. Rekech, Static theory of thin-walled space structures, MIR publishers, Mosco, (1978) 

22.     C.A. Chidolue,  Torsional-distortional analysis of thin-walled box girder  bridges using Vlasov’s theory. PhD theses, (2012),  University of Nigeria, Nsukka, Nigeria




Sonal Jain, A. K Wadhwani

Paper Title:

Analysis of EEG Signals for Epilepsy and Seizure by decomposition with Wavelet Transform

Abstract:   The Electroencephalogram (EEG) is a complex signal that indicates the electrical activity of brain. EEG is a signal that represents that effect of the superimposition of diverse processes in the brain.  Epilepsy is a common brain disorder. Out of hundred one person is suffering from this problem. Here we study a novel scheme for detecting epileptic seizure from EEG data recorded for healthy subjects and Epileptic patients.  EEG is obtained by International 10-20 electrodes system. Wavelet transform is used for feature extraction. Wavelet Transform (WT) provides a flexible way of time-frequency representation of a signal.

  EEG (Electro Encephalo Graph), Epilepsy, Seizure, Wavelet Transform.


1.        N. Kannathal, Min Lim Choo, U. Rajendra Acharya and P.K. Sadasivan, “Entropies for detection of epilepsy in EEG,” Computer  Methods and Programs in Biomedicine, vol. 80, 2005, pp. 187-194.
2.        Michael Barnsley, “Fractals Everywhere,” 2nd  edition.,Academic press USA [1993]

3.        Kenneth Falconer, “Fractal Geometry: Mathematical Foundations and Applications,” 2nd ed., John Wiley & Sons Ltd, England, 2003.

4.        Hasan Ocak, “Optimal classification of epileptic seizures in EEG  using wavelet analysis and genetic algorithm,” Signal Processing, vol. 88, 2008, pp. 1858-1867.

5.        Hasan Ocak, “Automatic detection of epileptic seizures in EEG using discrete wavelet transform and approximate entropy,” Expert   Systems  with Applications, vol. 36, 2009, pp. 2027-2036.

6.        A. Subasi, “Application of adaptive neuro-fuzzy inference system For epileptic seizure detection using wavelet feature extraction,”Computers in Biology and Medicine, vol. 37, 2007, pp. 227-244.   

7.        R.G. Andrzejak, Klaus Lehnertz, Florian Mormann and et al., “Indications of nonlinear deterministic and finite-dimensional  structures in time series of brain electrical activity: Dependence on  recording region and brain state,” Physical Review E, vol. 64,  2001, pp. 061907-1 - 061907-8.

8.        H. Jing, M. Takigawa, "Topographic analysis of dimension estimatesof EEG and filtered rhythms in epileptic patients with complex partial seizures," Biological. Cybernetics. Vol. 83, pp. 391-397, 2000.

9.        K. Lehnertz, C.E. Elger, "Spatio-temporal dynamics of the primary epileptogenic area in temporal lobe epilepsy characterized by  neuronal complexity loss," Electroen. Clinical. Neurophysiology, 95 ppvol 108-117, 1995.

10.     M.C. Casdagli, L.D. Iasemidis, R.S. Savit, R.L. Gilmore, S.N. Roper, J.C. Sackellares, "Non-linearity in invasive EEG. recordings from patients with temporal lobe epilepsy," Electroencephalogr. Clin.

11.     Neurophysiol. 102 98-105, 1997.

12.     A. Subasia, and E. Ercelebi, "Classification of EEG signals using  neural network and logistic regression," Computer Methods and Programs in Biomedicine, vol. 78, pp. 87-99, 2005.




Mumtaz Ahmad Khan, Shadab Khan, Mohd Sadiq

Paper Title:

Systematic Review of Software Risk Assessment and Estimation Models

Abstract:   The process of Software risk evaluation and management embodies the identification, analysis, planning, tracking, controlling and communication of risk. Risk assessment methods are one of the most important elements in the process of risk management. The objective of this article is to present the systematic review of Software risk assessment and estimation models. The main emphasis is given to the risk assessment methods based on software metrics like Software Risk Assessment and Estimation Model (SRAEM) and Software Risk Assessment and Evaluation Process (SRAEP) using model based approach because these methods are the latest methods in the field of software risk assessment and estimation.

   Software Risk, Risk Exposure, Risk Assessment and Estimation.


1.       Roger L. Van Scoy, “Software Development Risk: Opportunity, not problem”, Technical report, September 1992.
2.       Barbara Kitchenham, Stephen Linkman, “ Estimates, Uncertainty, and Risk”, IEEE Software, pp.69-74, 1997

3.       Barry W. Boehm, “Software Risk Management: Principles and Practices”, IEEE Software, pp.32-41, 1991.

4.       Donald Reifer, “ Ten Deadly Risks in Internet and Intranet Software Development”, IEEE Software, 2002.

5.       A Risk Management Standard, ALARM, IRM:2002

6.       Ronald P.Higuera, David P. Gluch, Audrey J. Dorofee, Richard L. Murphy, Julie A. walker, and Ray C. William, “ An Introduction to Team Risk Management (Version 1.0), Software Engineering Institute, Technical Report, May 1994.

7.       Ray C. Williams, George J. Pandelios, and Sandra G. Behrens, “Software Risk Evaluation (SRE) Method description (Version-2.0), Technical report December-1999.

8.       Mohd. Sadiq, and Shabbir Ahmed, “Computation of Function Point of Software on the basis of Average Complexity”, Proceedings of 2nd International Conference on Advanced Computing and Communication Technologies, ICACCT2007, Panipat, Haryana. Pp.591-594.

9.       Mohd.Sadiq, Shabbir Ahmed,“Relationship between lines of code and Function Point and its application in the computation of Effort and Duration of a software using software equation”, Proceedings of International Conference on Emerging Technologies and Applications in Engineering, Technology and Sciences , ICATETS2008, Rajkot, Gujrat. 

10.     Susan A Sherer, “The Three dimensions of Software Risk: technical, Organizational, , and Environmental,”, IEEE-2005.

11.     Chris F. Kermerer, “Reliability of Function Points Measurements, A Field Experiment, Communication of the ACM, pp. 85- 97, Vol.36, February 1993.

12.     Tom Demarco, Tim Lister, “Risk Management during Requirements”, IEEE Computer society, IEEE Software, pp.99-100, 2003.

13.     K. Appukkutty, Hany H. Ammar, Katerina Goseva Popstajanova, “Software requirements Risk Assessment Using UML”, IEEE, pp.1-4, 2005.

14.     Poornima Ramachandra, Haeng-Kon Kim, Byeongdo Kang, Yan Ha, and Roger Lee, “Risk Management through Architecture Design”, Proceedings of the Fourth International Conference on Software Engineering Research Management and Applications (SERA-06), IEEE-2006.

15.     Joseph S. Sherif, “Metrics for Software Risk Management”, ISMN#0-7803-3274-1, pp.507-513.

16.     Say-Wei Foo , Armugam Muruganatham, “ Software Risk assessment Model”, ICMIT 2000, IEEE, pp-536-544.

17.     C.L. Chee et al, “ Using influence Diagram for Software Risk Analysis”, Proceedings of the 7th International Conference on Tools with Artificial Intelligence, IEEE Computer Society, Los Alamitos, 1995

18.     T. Deursen et al, “ Source based Software Risk Assessment”, Proceedings of the  International Conference on Software Maintenance, IEEE Computer Society, Los Alamitos, 2003.

19.     D.E. Neumann, “ An Enhanced Neural Network Technique for Software Risk Analysis”, IEEE transaction on Software Engineering, pp. 904-912, 2002

20.     J. Nogueira et al., “ A Risk Assessment Model for Software Prototyping Projects”, Proceedings of the 11th International Workshop on Rapid System Prototyping, IEEE Computer Society, Los Alamitos, 2000

21.     J.P. Vucovich et al., “ Risk Assessment in Early Software Design Based on the Software Function Failure Design Method”, Proceedings of the 31st Annual  International Conference on Computer Software and Applications, IEEE Computer Society, Los Alamitos, 1995

22.     S.M. Yacoub and H.H. Ammar, “ A Methodology for Architecture Level reliability Risk Analysis, IEEE Transaction Software”, pp. 529-547, 2002

23.     H. Yong et al., “ A neural Network Approach for Software Risk Analysis”, Proceedings of the 6th International Conference on Data Mining-Workshop, IEEE Computer Society, Los Alamitos, 2006.

24.     H. Young et al, “ Analysing Software System quality Risk using Bayesian Belief Network” Proceedings of the International Conference on Granular Computing, IEEE Computer Society, Los Alamitos, 2007

25.     R.C. Williams et al, “Software Risk Evaluation Method Description”, CMU/SEI-99-TR, ESC-TR-99-029, Software Institute, 1999.

26.     Daya Gupta and Mohd Sadiq, “ Software Risk Assessment and Estimation Model”, IEEE International Conference on Computer Science and Information Technology, 2008

27.     Mohd Sadiq et al., Software Risk Assessment and Evaluation Process ( SRAEP) using Model Based Approach”, Proceedings of the International Conference on Networking and Information Technology, pp. 171-177, 2010

28.     Georgieva K. Et al., “Analysis of Risk Analysis Methods- A Survey”, LNCS- Springer-Verlag Heidelberg, pp. 76-86, 2009.






Arshi Salamat

Paper Title:

Electrical Methods for Detection of Adulterants in Milk

Abstract:  Addition of substances in a product that results in unhealthy and harmful effects when consumed is called adulteration. This is done to increase the quantity of the product to gain profit. Adulteration is very common in almost all the countries and adulteration of milk is a very serious problem. India is the largest producer of milk but due to its growing population and therefore more requirements, milk adulteration is very common here also. Adulteration is not always to make greater profits but sometimes it is due to the lack of knowledge and skill in storing and transporting the milk. There are so many methods for milk analysis and very popular and common ones are chemical methods. Since, in developed countries advanced methods are used to adulterate milk and sophisticated methods are used to detect it therefore researchers proceed for electrical methods which are accurate, data can be stored and automated and the instrument can be made handy. In this paper different electrical techniques for detection of adulterants in milk are discussed.

Adulteration, Milk, Electrical Methods, population, sophisticated


1.    U.B.Trivedi, D.Lakshminarayan, I.L.Kothari, N.G. Patel, H.N Kapse, Makhija,P.B. Patel and C.J.Panchal., Sensors and Actuators : B  Chemical  140 260 (2009). Potentiometric Bio Sensors for urea determination in milk
2.    F.Conzuello, Journal of Agriculture and food Chemistry 58 7141 (2010) An Integrated Amperometric bio sensors for determination of Lactose in milk and dairy products.

3.    E.F.Renny, D.K.Daniel, A.I.Krastanov, C.A.Zachariah, R.Elizabeth, Biotechnol. Equip .19, 198 (2005) Enzyme based sensor for detection of urea in milk.

4.    A.Sadat, P.Mustajab, I.A.Khan, J.Food Engg. 77, 472 (2006) Determining the adulteration of natural milk with synthetic milk using ac conductance measurement.

5.    S.Mohanan, P.G.T.Panicker, L.Iype, M.Laila, I.Domini and R.G.Bindu, Pranama journal of Physics 59, 525 (2002).

6.    H.Yu, J.Wang, Y.Xu, Sensors and Materials, 19, 275 (2007) Identification of adulterated milk using electronic nose.

7.    M.F.Mabrook and M.c.Petty, sensors and actuators: B  96, 213 (2002) Applications of electrical admittance  measurements to quality control of milk.