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Volume-1 Issue-2: Published on June 05, 2012
Volume-1 Issue-2: Published on June 05, 2012
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S. No

Volume-1 Issue-2, June 2012, ISSN:  2277-3878 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.



M.S. Pavithraa, C.Balakrishnan

Paper Title:

Fake Data Termination in Wireless Sensor Networks

Abstract: Wireless sensor networks are specified ad-hoc networks. They are characterized by their limited computing power and energy constraints because they are generally limited in memory, power and computational ability. Thus they can only transmit data to a limited distance. The major challenges of wireless sensor networks are security. This paper proposes a study of security in this kind of network. Here a list of attacks with their specificities and vulnerabilities are presented. Based on the location information presence of fake data can be identified. Here a solution to terminate this fake information is discussed.

 Ad-hoc networks, sensor networks, attacks, security.


1.        J.-Y.L. Boudec and M. Vojnovi_c, “Perfect Simulation and Stationary of a Class of Mobility Models,” Proc. IEEE INFOCOM, pp. 2743-2754, Mar. 2005
2.        S. _Capkun and J.P. Hubaux, “Secure Positioning in Wireless Networks,” IEEE J. Selected Areas in Comm., vol. 24, no. 2, pp. 221- 232, Feb. 2006.

3.        M. Conti, R.D. Pietro, L.V. Mancini, and A. Mei, “A Randomized,Efficient, and Distributed Protocol for  the Detection of NodeReplication Attacks in  Wireless Sensor Networks,” Proc. ACM MobiHoc, pp. 80-89, Sept. 2007.

4.        K. Dantu,      M. Rahimi,    H. Shah, S. Babel, A.Dhariwal, and G.S.Sukhatme, “Robomote: nabling Mobility in Sensor Networks,”Proc. Fourth IEEE Int’l Symp. Information Processing in Sensor Networks (IPSN), pp. 404-409, Apr. 2005.

5.        J. Ho, M. Wright, and S.K. Das, “Fast Detection of Replica Node Attacks in Mobile Sensor Networks Using Sequential Analysis,” Proc. IEEE INFOCOM, pp. 1773-1781, Apr. 2009.

6.        J. Ho, D. Liu, M. Wright, and S.K. Das, “Distributed Detection of Replicas with Deployment Knowledge in Wireless Sensor Networks,” Ad Hoc Networks, vol. 7, no. 8, pp. 1476-1488, Nov. 2009.

7.        L. Hu and D. Evans, “Localization for Mobile Sensor Networks,” Proc. ACM MobiCom, pp. 45-57, Sept. 2004.

8.        J. Jung, V. Paxon, A.W. Berger, and H. Balakrishnan, “Fast Portscan Detection Using Sequential Hypothesis Testing,” Proc. IEEE Symp. Security and Privacy, pp. 211-225, May 2004.

9.        A. Liu and P. Ning, “TinyECC: A Configurable Library for Elliptic Curve Cryptography in Wireless Sensor Networks,” Proc. Seventh IEEE Int’l Symp. Information Processing in Sensor Networks (IPSN),

10.     pp. 245-256, Apr. 2008.

11.     S. PalChaudhuri, J.-Y.L. Boudec, and M. Vojnovi_c, “Perfect Simulations for Random Trip Mobility Models,” Proc. 38th Ann.Simulation Symp., Apr. 2005.

12.     B. Parno, A. Perrig, and V.D. Gligor,Distributed Detection of Node Replication Attacks  in  Sensor Networks,” Proc. IEEE Symp. Security and Privacy, pp. 49-63, May 2005.

13.     H. Song, S. Zhu, and G. Cao, “Attack-Resilient Time Synchronization for Wireless Sensor etworks,” Ad Hoc Networks, vol. 5, no. 1, pp. 112-125, Jan. 2007.

14.     K. Sun, P. Ning, C. Wang, A. Liu, and Y. Zhou, “TinySeRSync: Secure and Resilient Time Synchronization in Wireless Sensor Networks,” Proc. 13th ACM Conf. Computer and Comm. Security (CCS), pp. 264-271, Oct. 2006.




G. Umarani Srikanth, M. Akilandeshwari

Paper Title:

Computational Intelligence Routing For Lifetime Maximization in Heterogeneous Wireless Sensor Networks

Abstract:  In wireless sensor networks, sensor nodes are typically power-constrained with limited lifetime, and thus it is necessary to know how long the network sustains its networking operations. Heterogeneous WSNs consists of different sensor devices with different capabilities.  One of major issue in WSNs is finding the coverage distance and connectivity between sensors and sink. To increase the network lifetime, this paper proposed Swarm Intelligence, routing technique called Ant Colony Optimization (ACO). Ant colony optimization algorithm provides a natural and intrinsic way of exploration of search space of coverage area. Ants communicate with their nest-mates using chemical scents known as pheromones, Based on Pheromone trail between sensor devices the shortest path is found. By finding the coverage distance and sensing range, the network lifetime maximized and reduces the energy usage. Extensive Java Agent Framework (JADE) multi agent simulator result clearly provides more approximate, effective and efficient way for maximizing the lifetime of heterogeneous WSNs.

   wireless sensor networks (WSNs), Ant colony optimization (ACO), connectivity, coverage, network lifetime, JADE.


1.        ] C.Y. Chong and S.P. Kumar, “Sensor Networks: Evolution, Opportunities, and Challenges,” Proc. IEEE, vol. 91, no. 8, pp. 1247-1256, Aug. 2003.
2.        M. Cardei, M.T. Thai, Y. Li, and W. Wu, “Energy-Efficient Target Coverage in Wireless Sensor Networks,” Proc. IEEE INFOCOM, vol. 3, pp. 1976-1984, 2005.

3.        Carle, J. and Simplot, D. (2004) “Energy Efficient Area Monitoring by Sensor Networks”, IEEE Computer, Vol. 37, No. 2, pp. 40-46.

4.        Tian, D. and Georganas, N. D. (2002) “A Coverage Preserving Node Scheduling Scheme for Large Wireless Sensor Networks”, ACM Workshop on Wireless Sensor Networks and Applications.
5.        I. F. Akyildiz, T. Melodia, and K. R. Chowdury, “Wireless multimediasensor network: A survey,” IEEE Wireless Commun., vol. 14, no. 6,   pp. 32–39, Dec. 2007.
6.        I. Dietrich and F. Dressler, “On the lifetime of wireless sensor networks,”ACM Trans. Sensor Networks, vol. 5, no. 1, Feb. 2009.

7.        C.-Y. Chang, J.-P. Sheu, Y.-C. Chen, and S.-W. Chang, “An obstacle-free and power-efficient deployment algorithm for wireless sensor networks,”  IEEE Trans. Syst., Man, Cybern., Part A, vol. 39, no. 4, pp. 795–806, Jul   2009.

8.        Al-Karaki, J.N.; Kamal, A.E. Routing Techniques in Wireless Sensor Networks: a Survey. IEEEWirel. Commun. 2004, 11, 6-28.

9.        Bonabeau, E.; Dorigo, M.; G.T. Swarm Intelligence. In Natural to Artificial Systems; Oxford Univ. Press: London, U.K., 1999; pp. 1-278.

10.    Q. Zhao and M. Gurusamy, “Lifetime maximization for connected target coverage in wireless sensor networks,” IEEE/ACM Trans. Networking, vol. 16, no. 6, pp. 1378–1391, Dec. 2008.

11.     Liu, Z.; Kwiatkowska, M.Z; Constantinou, C. A Biologically Inspired QOS Routing Algorithm for Mobile Ad Hoc Networks. In 19th International Conference on Advanced Information Networking and Applications, 2005; pp. 426–431.

12.     Schoonderwoerd, R.; Holland, O.; Bruten, J.; Rothkrantz, L. Ant-based Load Balancing in Telecommunications Networks. Adapt. Behavior 1996, 5, 169–207.




G.V Krishna Reddy, N.Chikkanna, B.Uma Maheswar Gowd

Paper Title:

A Novel Method to Reduce the Thermal Contact Resistance

Abstract: In this research work, a novel method is designed to reduce the thermal contact resistance at the interface between the heat sink and the computer processor. One of the major problems in using high conducting materials or greases as the thermal interfacial materials is, the circuitry inside the processor which is lying near the interfacial wall will get shorted and the some of the transistor may not function as intended thus leading to the failure of the processors. Hence low electrically conducting interfacial materials are preferred. Usually for most of the materials, the electrical and thermal conductivities are proportional to each other. However, the drawback in using the low electrically or thermally conducting materials is, it cannot remove the heat generated from the high speed processors fast enough thus increasing the temperature of the processor. With the raise in temperature, the performance of the processor drops down. To avoid this, low conducting grease is applied to the processor first in the order of 5 microns and highly conducting grease is applied between the processor (over the low conducting grease) and the heat sink. The performance of the two layers of the grease is measured in this work and compared with a single layer of the grease.

Thermal interfacial materials, grease, aluminum foils, thermal contact resistance, thermal conductivity, electronics cooling.


1.        R. Hopkins, A. Faghri, D. Krustalev, Flat miniature heat pipes with micro capillary grooves, J. Heat Transfer 121 (1999) 102-109.
2.        L.S., Fletcher, A review of thermal enhancement techniques for electronic systems, Intersociety Conference on Thermal Phenomena (1990) 136-148.

3.        J.P. Bardon, Introduction aÁ l'eÂtude des reÂsistances thermiques de contact, Rev. GeÂn. Therm. 125 (1972) 429-446.
4.        L.S. Fletcher, Recent developments in contact conductance heat transfer, J. Heat Transfer 110 (1988) 1059-1070.
5.        M.J. Edmonds, A.M. Jones, S.D. Probert, Thermal contact resistances for hard machined surfaces pressed against relatively soft-optical ¯ats, Applied Energy 6 (1980) 405-427.

6.        R.R. Somers, J.W. Miller, L.S. Fletcher, An experimental investigation of the thermal conductance of dissimilar metal contacts, in: 4th Intersociety Conference on
Thermal Phenomena in Electronic Systems, Washington, May, 1994, pp. 280-299.

7.        D.V. Lewis, H.C. Perkins, Heat transfer at the interface of stainless steel and aluminum. The influence of surface conditions on the directional e€ect, Int. J. Heat Mass Transfer 11 (1968) 1371-1383.

8.        M.M. Yovanovich, Overall constriction resistance between contacting rough, wavy surfaces, Int. J. Heat Mass Transfer 12 (1969) 1517-1520.

9.        M.R. Sridhar, M.M. Yovanovich, Thermal contact conductance of tool steel and comparison with model, Int. J. Heat Mass Transfer 39 (4) (1996) 831-839.

10.     M.R. Sridhar, M.M. Yovanovich, Elastoplastic contact conductance model for isotropic conforming rough surfaces and comparison with experiments, J. Heat Transfer 118 (1996) 3-9.

11.     B.B. Mikic, Thermal contact conductance; theoretical considerations, Int. J. Heat Mass Transfer 17 (1974) 205-214.

12.     M. Mittelbach, C. Vogd, L.S. Fletcher, G.P. Peterson, The interfacial pressure distribution and thermal conductance of bolted joints, J. Heat Transfer 116 (1994) 823-829.

13.     L.S. Fletcher, G.P. Peterson, C.V. Madhusudana, E. Groll, Constriction resistance through bolted and riveted joints, J. Heat Transfer 112 (1990) 857-863.

14.     L.R. Jeevanashankara, C.V. Madhusudhana, M.V. Kulkarni, Thermal contact conductances of metallic contacts at low loads, Applied Energy 35 (1990) 151-164.

15.     L.G. Hays, Thermal conductance of alumina±nickel interfaces at elevated temperatures, Int. J. Heat Mass Transfer 13 (1970) 1293-1297.

16.     B. Snaith, P.W. O'Callaghan, S.D. Probert, Interstitial materials for controlling thermal conductances across pressed metallic contacts, Applied Energy 16 (1984) 175-191.

17.     L.J. Salerno, P. Kittel, A.L. Spivak, Thermal conductance of pressed metallic contacts augmented with indium foil or Apiezon grease at liquid helium temperatures, Cryogenics 34 (8) (1994) 649-654.

18.     A.L. Peterson, Silicones with improved thermal conductivity for thermal management in electronic packaging, in: 40th Electronic Components and Technology Conf., Las Vegas, May, 1990, pp. 613-618.

19.     W. Jamison, G. Sears, G. Larsen, R. Hunadi, Thermally conductive, water cleanable greases, in: Proc. Technical Conference, Int. Electronic Packaging Conf., 1991, pp. 190-203.

20.     T. McWaid, T.E. Marschall, Thermal contact resistance across pressed metal contacts in a vacuum environment, Int. J. Heat Mass Transfer 35 (11) (1992) 2911-2920.

21.     B.B. Mikic, G. Carnasciali, The e€ect of thermal conductivity of plating material on thermal contact resistance, J. Heat Transfer (1970) 475-482.

22.     T.K. Kang, G.P. Peterson, L.S. Fletcher, Effect of metallic coatings on the thermal contact conductance of turned surfaces, J. Heat Transfer 112 (1990) 864-871.

23.     A.H. Howard, J.M. Ochterbeck, G.P. Peterson, Effects of metallic vapor deposition process and the overall coating thickness on thermal contact conductance, J. Heat Transfer 117 (1995) 828-834.

24.     C.R. Hicks, K.V. Turner, in: Fundamental Concepts in the Design of Experiments, 5th Ed., Oxford University Press, Oxford, 1999, p. 576.

25.     C.V. Madhusudana, Thermal contact conductance and recti®cation at low joint pressures, Int. Comm. Heat Mass Transfer 20 (1993) 123-132.




G.V.Krishna Reddy, Chikkanna, B.Uma Maheswar Gowd

Paper Title:

Experimental Evaluation of Thermal Resistance of Composites

Abstract: In this paper thermal contact resistance is measured for different kinds of composite materials. The gaps at contact surface between two highly conducting materials are filled with the interstitial material. The interfacial gap is maintained by applying pressure on the surface by using shim, until certain thickness has been obtained. Shims of multiple sizes are used obtain different sizes of the gaps. Samples of the interface materials like Silicone grease, Eupec grease, Unial grease, graphite foil, silicone foil, aluminum foils, etc were tested.  Also these samples with different material compositions were experimented. The measured thermal resistance values are compared with the theoretical values of thermal resistance for all the materials tested. In other words, the thermal conductivities published by their respective manufacturers are validated. It is found that thermal resistance is least for foils compared to grease or grease filled with powder. Also of all the foils tested, aluminum yielded the best results as far as the thermal resistance is concerned.

Thermal interfacial materials, grease, aluminum foils, thermal contact resistance, thermal conductivity, electronics cooling..


1.           R. Hopkins, A. Faghri, D. Krustalev, Flat miniature heat pipes with micro capillary grooves, J. Heat Transfer 121 (1999) 102-109.
2.           L.S., Fletcher, A review of thermal enhancement techniques for electronic systems, Intersociety Conference on Thermal Phenomena (1990) 136-148.

3.           J.P. Bardon, Introduction aÁ l'eÂtude des reÂsistances thermiques de contact, Rev. GeÂn. Therm. 125 (1972) 429-446.

4.           L.S. Fletcher, Recent developments in contact conductance heat transfer, J. Heat Transfer 110 (1988) 1059-1070.

5.           M.J. Edmonds, A.M. Jones, S.D. Probert, Thermal contact resistances for hard machined surfaces pressed against relatively soft-optical ¯ats, Applied Energy 6 (1980) 405-427.

6.           R.R. Somers, J.W. Miller, L.S. Fletcher, An experimental investigation of the thermal conductance of dissimilar metal contacts, in: 4th Intersociety Conference on Thermal Phenomena in Electronic Systems, Washington, May, 1994, pp. 280-299.

7.           D.V. Lewis, H.C. Perkins, Heat transfer at the interface of stainless steel and aluminum. The influence of surface conditions on the directional e€ect, Int. J. Heat Mass Transfer 11 (1968) 1371-1383.

8.           M.M. Yovanovich, Overall constriction resistance between contacting rough, wavy surfaces, Int. J. Heat Mass Transfer 12 (1969) 1517-1520.

9.           M.R. Sridhar, M.M. Yovanovich, Thermal contact conductance of tool steel and comparison with model, Int. J. Heat Mass Transfer 39 (4) (1996) 831-839.

10.        M.R. Sridhar, M.M. Yovanovich, Elastoplastic contact conductance model for isotropic conforming rough surfaces and comparison with experiments, J. Heat Transfer 118 (1996) 3-9.

11.        B.B. Mikic, Thermal contact conductance; theoretical considerations, Int. J. Heat Mass Transfer 17 (1974) 205-214.

12.         M. Mittelbach, C. Vogd, L.S. Fletcher, G.P. Peterson, The interfacial pressure distribution and thermal conductance of bolted joints, J. Heat Transfer 116 (1994) 823-829.

13.        L.S. Fletcher, G.P. Peterson, C.V. Madhusudana, E. Groll, Constriction resistance through bolted and riveted joints, J. Heat Transfer 112 (1990) 857-863.

14.        L.R. Jeevanashankara, C.V. Madhusudhana, M.V. Kulkarni, Thermal contact conductances of metallic contacts at low loads, Applied Energy 35 (1990) 151-164.

15.        L.G. Hays, Thermal conductance of alumina±nickel interfaces at elevated temperatures, Int. J. Heat Mass Transfer 13 (1970) 1293-1297.

16.        B. Snaith, P.W. O'Callaghan, S.D. Probert, Interstitial materials for controlling thermal conductances across pressed metallic contacts, Applied Energy 16 (1984) 175-191.

17.        L.J. Salerno, P. Kittel, A.L. Spivak, Thermal conductance of pressed metallic contacts augmented with indium foil or Apiezon grease at liquid helium temperatures, Cryogenics 34 (8) (1994) 649-654.

18.        A.L. Peterson, Silicones with improved thermal conductivity for thermal management in electronic packaging, in: 40th Electronic Components and Technology Conf., Las Vegas, May, 1990, pp. 613-618.

19.        W. Jamison, G. Sears, G. Larsen, R. Hunadi, Thermally conductive, water cleanable greases, in: Proc. Technical Conference, Int. Electronic Packaging Conf., 1991, pp. 190-203.

20.        T. McWaid, T.E. Marschall, Thermal contact resistance across pressed metal contacts in a vacuum environment, Int. J. Heat Mass Transfer 35 (11) (1992) 2911-2920.

21.        B.B. Mikic, G. Carnasciali, The e€ect of thermal conductivity of plating material on thermal contact resistance, J. Heat Transfer (1970) 475-482.

22.        T.K. Kang, G.P. Peterson, L.S. Fletcher, Effect of metallic coatings on the thermal contact conductance of turned surfaces, J. Heat Transfer 112 (1990) 864-871.

23.        A.H. Howard, J.M. Ochterbeck, G.P. Peterson, Effects of metallic vapor deposition process and the overall coating thickness on thermal contact conductance, J. Heat Transfer 117 (1995) 828-834.

24.        C.R. Hicks, K.V. Turner, in: Fundamental Concepts in the Design of Experiments, 5th Ed., Oxford University Press, Oxford, 1999, p. 576.

25.        C.V. Madhusudana, Thermal contact conductance and recti®cation at low joint pressures, Int. Comm. Heat Mass Transfer 20 (1993) 123-132.




K. Karthika, C. Arunachal Aperumal

Paper Title:

Mining in Navigation-Pattern using Content-Based Image Retrieval

Abstract: Research has been devoted in the past few years to relevance Feedback as an effective solution to improve performance of Content-based image retrieval (CBIR). In this paper, we propose a color image pattern for further use, which reduce the iteration og image. To achieve the high efficiency and effectiveness of CBIR we are using two type of methods for feature extraction like SVM (support vector machine) and NPRF (navigation-pattern based relevance feedback).By using svm classifier as a category predictor of query and database images, they are exploited at first to filter out irrelevant images by its different low-level, concept and key point-based features. Thus we may reduce the size of query search in the db and enhanced by using texture based in which we combine GLCM and CCM.

  GLCM, CCM, SVM, content based image retrieval.


1.        A. Pentalnd, R.W. Picard, and S. Sclaroff, “Photobook: Content- Based Manipulation of Image Databases,” Int’l J. Computer Vision (IJCV), vol. 18, no. 3, pp. 233-254, June 1996.
2.        T. Qin, X.D. Zhang, T.Y. Liu, D.S. Wang, W.Y. Ma, and H.J. Zhang, “An Active Feedback Framework for Image Retrieval,” Pattern Recognition Letters, vol. 29, pp. 637-646, Apr. 2008.

3.        J.J. Rocchio, “Relevance Feedback in Information Retrieval,” The SMART Retrieval System—Experiments in Automatic Document Processing, pp. 313-323, Prentice Hall, 1971.

4.        Y. Rui, T. Huang, and S. Mehrotra, “Content-Based Image Retrieval with Relevance Feedback in MARS,” Proc. IEEE Int’l

5.        Conf. Image Processing, pp. 815-818, Oct. 1997.

6.        Y. Rui, T. Huang, M. Ortega, and S. Mehrotra, “Relevance Feedback: A Power Tool for Interactive Content-Based Image Retrieval,” IEEE Trans. Circuits and Systems for Video Technology, vol. 8, no. 5, pp. 644-655, Sept. 1998.

7.        J.R. Smith and S.F. Chang, “VisualSEEK: A Fully Automated Content-Based Image Query System,” Proc. ACM Multimedia Conf., Nov. 1996.

8.        G. Salton and C. Buckley, “Improving Retrieval Performance by Relevance Feedback,” J. Am. Soc. Information Science, vol. 41, no. 4, pp. 288-297, 1990.

9.        H.T. Shen, S. Jiang, K.L. Tan, Z. Huang, and X. Zhou, “Speed up Interactive Image Retrieval,” VLDB J., vol. 18, no. 1, pp. 329-343, Jan. 2009.




Maruthi B H, K M Narayanappa, M Krishna,Venkatarama Reddy

Paper Title:

Modified Disc Model for Over-Speed Burst Margin with Thermal Load and Disc Speed Corrections and Compared with FE Model 

Abstract: The present work was focused on modification of the disc model for over speed burst margin with thermal load and disc speed correction and verify the same with FE model. Hoop stress, radial stress and burst margin were carried out at different speed and thermal loading conditions using both finite element and mathematical model. Investigations are performed based on non-linear problem employing linear analysis tool ANSYS 12.0. A non-linear finite element method was utilized to determine the stress state of the disc / blade segment under operating conditions.  In both cases (FE and mathematical model)  the numerical burst rotation rate, associated with the loss of stability of the structure, is found to be in good agreement with the  each other.

 Modified Model, Gas Turbine, Over-speed, thermal load.


1.        R A Claudio, C M Branco, E C Gomes and J Byrne, Life prediction of a gas turbine disc using the finite element method, 8AS Journadas De Fractura-2002, pp. 131-144
2.        G C Fraccone, M Ruzzene, V Volvoi, P Cento and C Vining, Assessment of uncertainity in response estimation  for turbine engine bladed disks, Journal of Sound and vibration, vol. 317 (2008), pp. 625-645.

3.        Walls DP, Delaneuville RE, Cunningham SE. Damage tolerance based life prediction in gas turbine engine blades under vibratory high cycle fatigue. Journal of Engineering for Gas Turbines and Power 1997;119:143–6

4.        Burns J. Gas turbine engine blade life prediction for high cycle fatigue. The Technical Cooperation Program (TTCP), P-TP1, 1998.

5.        Benallal A, Berstad T, Clausen A, and Hopperstad O. Dynamic strain aging and related instabilities: experimental, theoretical and numerical aspects, Eur, J Mech., vol. 25, (2006), pp.357-424

6.        Ahmet N Eraslan, Elastic-plastic deformations of rotating variable thickness annular disks with free, pressurized and radially constrined boundary conditions, International Journal of Mechanical Sciences, vol. 45, (2003), pp.643-667.

7.        Mohammad Shanobghzani, Vahid Heidarpour and Iraj Mirzee, Computer Aidied Analyis of flow in a rotating single disc, World Academy of Science, Engineering and Technology, vol. 58, (2009), pp.161-163.

8.        G J Nie, R C  Batra, Stress analysis and material tailoring in isotropic linear thermoelastic incompressible functionally graded rotating disk of variable thickness, Composite Structure, vol. 92, (2010), pp.720-729.

9.        Franceso Vivio, Vincenzo Vullo, Elastic stress analysis of rotating converging conical disks subjected to thermal load and having variable density along the radius, International Journal of Solids and Structures, vol. 44, (2007), pp.7767-7784.

10.     Walz, G., Riesch-Oppermann, H., Probabilistic fracture mechanics assessment of flaws in turbine disks including quality assurance procedures. Structural Safety, vol.28, (2006), pp. 273–288.

11.     Bayat M, Saleem M, Sahari BB, et al. Mechanical and thermal stresses in a functionally graded rotating disk with variable thickness due to radially symmetry loads. Int J Press Vessels Pip 2009;86:357–72.

12.     Eraslan, A.N., Akis, T., 2006. On the plane strain and plane stress solutions of functionally graded rotating solid shaft and solid disk problems. Acta Mechanica 181 (1-2), 43–63.

13.     Eraslan, A.N., Arges_o, H., 2002. Limit angular velocities of variable thickness rotating disks. International Journal of Solids and Structures 39 (12), 3109–3130.

14.     Orcan, Y., Eraslan, A.N., 2002. Elastic–plastic stresses in linearly hardening rotating solid disks of variable thickness. Mechanics Research Communications 29 (4), 269–281.

15.     Eraslan, A.N., 2005. A class of nonisothermal variable thickness rotating disk problems solved by hypergeometric functions. Turkish Journal of Engineering and Environmental Sciences 29 (4), 241–269.

16.     Eraslan, A.N., Orc¸an, Y., 2004. A parametric analysis of rotating variable thickness elastoplastic annular disks subjected to pressurized and radially constrained boundary conditions. Turkish Journal of Engineering and Environmental Sciences 28 (6), 381–395.

17.     Eraslan, A.N., Apatay, T., 2004. On annular disks of variable thickness subjected to external pressure. Forschungim Ingenieurwesen/ Engineering Research 68 (3), 133–138.

18.     Eraslan, A.N., 2003. Elastic–plastic deformations of rotating variable thickness annular disks with free, pressurized and radially constrained boundary conditions. International Journal of Mechanical Sciences 45 (4) , 643–667.




Minal Saxena, Kavita Khare

Paper Title:

A Novel Approach of Frequency offset Estimation for OFDM System

Abstract:  Orthogonal frequency division multiplexing(OFDM)has recently attracted vast research attention from both academia and industry and has become a part of new emerging standards for broadband wireless access. Synchronization at receiver end represents one of the most challenging issues and plays a major role in physical layer design.This paper presents design and implementation of a Channel estimation algorithm which successfully achieves minimization of Timing and Frequency offsets at receiver end. Also it has been synthesized and simulated on Virtex 6 device.

 Cyclic prefix, timing offset, Intersymbol Interference(ISI),Channel estimator.


1.           Channel Estimation for OFDM Systems -Anza Rani James, Revathy S Benjamin, Shilpa John, Treesa Mary Joseph, Vineetha Mathai, and Dr. Sakuntala S. Pillai ,Proceedings -ICSCCN 2011
2.           Superimposed training aided Carrier Frequency Offset Estimation in OFDM systems by Malihe Ahmadi Aryan Saadat Mehr -IEEE EIT 2007 Proceedings

3.           OFDM Baseband Modulation Technology based on VHDL Lin Lin ,Yan-feng Qiao, Wan-xin Su 2010- Proceedings of the IEEE.

4.           Moose P., "A Technique for Orthogonal Frequency Division Multiplexing Frequency Offset Correction", IEEE Transactions on Communications, Vol. 42, No. 10, pages 2908-2914, October 1994

5.           Jan-Jaap van de Beek, Magnus Sandell, Per Ola Börjesson, "ML Estimation of Time and Fr[3]

6.           and Frequency Offset in OFDM Systems", IEEE Transactions on Signal Processing, July 1997.

7.           T. M. Schmidl and D. C. Cox, "Robust frequency and timing synchronization for OFDM," IEEE Trans. Commun., vol. 45, pp. 1613--1621, Dec. 1997.

8.           H. Nogami and T. Nagashima “A frequency and timing period acquisition technique for OFDM system”PIRMC pp1010-1015,Sept 27-29,1995

9.           J J van de beek ,M Sandell,M.Isaksson and P. Borjesson,”Low complex frame synchronization in OFDM systems” ICUPC Nov6-10,1997

10.         “OFDM Transceiver Reference Design”, Lattice Semiconductor OFDM Transceiver design package, 2005.

11.         “Implementation of an OFDM Wireless Transceiver using IP Cores on an FPGA”, Lattice Semiconductor white paper, 2005. Frequency Offset in OFDM Systems",




P. M. Chawan, Aniruddha P. Tekade, Pankaj R. Ingle

Paper Title:

Intergroup Conflict Handling Modes in Communication Management

Abstract: The paper aims to analyses the types of conflicts that generally occur during the lifecycle of a project. Particularly if the project belongs to the field of Information Technology where computation plays the indistinguishable part throughout the lifecycle, conflicts are unavoidable; rather they can be resolved with a good mindset and good managerial skills. All people can benefit, both personally and professionally, from learning conflict management skills. Typically we respond to conflict by using one of five modes: Compromising, Collaborating, Competing, Avoiding, Accommodating. The study examined the intergroup conflict between R&D managers and non - managers in four corporate companies, as well as the relationship between each of the five conflict-handling modes: competition, accommodation, sharing, collaboration, and avoidance, with the following variables:
1) Conflict frequency,

2) Job satisfaction, and

3) Job performance

Assertiveness, cooperation, TKI, Nonthreatening confrontation, conflict frequencies.


1.     IEEE transactions engineering management on , vol. 36, NO. 2, May 1989 95 Intergroup Conflicts and Conflict Management in the R&D Divisions of Four Aerospace Companies Marjorie Chan, Associate Member
2.     The Impact of Group Support Systems on Group Conflict and &conflict Management: An Empirical Investigation Sheila M. Miranda Florida Atlantic University

3.     Proceedings of the 33rd Hawaii International Conference on System Sciences – 2000 Group Conflict and Conflict Management in a Decision Conferencing Environment in Singapore

4.     Quaddus, M. A. Tung, Lai Lai, Foo, Wai Mei, Poh, Li-jean and Soon, Chia Minh, Graduate School of Business School of Accountancy and Business Curtin University of Technology Nanyang Technological University GPO Box U 1987, Nanyang Avenue

5.     Conflict Management in an Aerospace IEEE Distributed Human-in-the-loop results by Nathan A. Doble, Titan Corporation, Hampton, VA Richard Barhydt, NASA Langley Research Center, Hampton, VA James M. Hitt II, Booz Allen Hamilton, McLean, VA

6.     IEEE transaction on engineering management, vol. 55, NO. 2, May 2008 Task Conflict, Integrative Potential, and Conflict Management Strategies in Joint Ventures Mark E. Parry, Michael Song, and Robert E. Spekman.




V. Nehru Kumar, S. Syed Enayathali

Paper Title:

Performance of Rotating Biological Contactor for Treating Segregated Grey Water for Reuse

Abstract:  The laboratory model of two-stage Rotating Biological Contactor (RBC) which was used in the present study is a modified one, with a provision to vary the speed of rotating blades. Grey wastewater was used to study the performance of the modified rotating biological contactor. The reactor had four rotating blades in each stage, having the size of 300 mm x100 mm x 10 mm, attached perpendicular to the shaft.  The experiment was conducted for different influent COD loads and different speeds of rotating blades. Among the different speeds of rotational blades in treating grey water, the rotational speed of 3 rpm was found to yield better percent removal of COD at 95.07% as maximum, where as against the rotational speeds of 4.5 and 6 rpm, the treatment efficiency is 95.04% and 94.96% respectively.

 RBC, Rotating blades, Grey water, COD, OLR,


1.        Metcalf & Eddy (2007). Wastewater Engineering treatment and reuse, Tata McGraw-Hill, 23th Edition.
2.        APHA, 1995. Standard Methods for the Examination of Water and Wastewater, 17th Edition. American Public Health Association,  

3.        Washington,DC,USA.

4.        Friedler, E.,R.Kovalio and N.I.Galil (2005), On site Grey water Treatment and Reuse in Multi-Storey Buildings, Water science & Technology

5.        vol51 no 10 pp187-194.

6.        Eriksson,E., Auffarth,K., Henze,M., and Lendin ,A.,(2002), Characteristics of Grey water , Urban water , 4, pp85-104.

7.        Jeppersen, B.and Solley, D,(1994) Domestic grey water reuse :overseas practice and its applicability to Australia, Urban water research

8.        association of Australia, Melbourne.

9.        Nehru Kumar, V.,(2005) Effect of speed of rotating discs in the modified RBC for treating sago wastewater , Poll.Res.24(4):823-825(2005).

10.     Trivedy, R.K. and Goel.P.K (1986) Chemical and Biological methods for water pollution studies, environmental publications, Karad..




R.Vijayarajan, S.Muttan

Paper Title:

Cross Neighbourhood Kernel Filtering for Speckle Noise Removal in Ultrasound Images

Abstract:   Ultrasound imaging is the most popular, non-invasive and inexpensive diagnostic tool in clinical imaging for treatment planning and therapy. Due to noise and artefacts present, pre-processing of these images is difficult which leads to poor image processing and analysis. In this paper, an improved frost filter with kernel of cross neighbourhood is proposed for denoising and performance analysis for different neighbourhood kernels is carried out using peak signal to noise ratio and mean square error.

   Despeckling, frost filter, speckle noise, Ultrasound.


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11.  Keh-Shih Chuang., et al., 2006. “Fuzzy c-means clustering with spatial information for image segmentation”, Journal on Computerized medical imaging and graphics, no.30, 9-15.

12.  Sadoghi Yazdi and Faranak Homayouni, “Modified Adaptive Center Eighted Median Filter For suppressing impulsive Noise in Images”, International Journal of Research and Reviews in Applied Sciences Volume 1, Issue 3(December 2009). 




Ruchi Gupta, Pramod Kumar Sethi

Paper Title:

A Reliable And Scalable Multicast Model (RSM2)

Abstract:    Multicasting is the ability of a communication network to accept a single message from an application and to deliver copies of the message to multiple recipients at different location[1]. With the emergence of mobile users, many existing Internet -protocols, including those with multicast support, need to be adapted in order to offer support to this increasingly growing class of users. Our research in multicasting, as to design a Multicast Model, which provides reliability & scalability with best path for data delivery. Reliability means guaranteed Delivery of packets.  Scalability means capability to serve growing needs .In this context , A few concepts of  Proactive routing technique are  used  to make available this model in Infrastructured wireless also. Minimum Spanning path is used to deliver the packets, to reduce the cost & delay.

    Combo-Casting, Minimum Spanning Path, Multicasting, Reliable , Scalable.


1.     Sanjoy Paul, Member, IEEE, Krishan K. Sabnani, Fellow, IEEE, John C.-H. Lin, and Supratik Bhattacharyya “ Reliable Multicast Transport Protocol (RMTP) “.IEEE journal on  Selected  Areas  in  Communications  , Vol. 15, No. 3, April 1997.
2.     Ali Alsaih and Tariq Alahdal. ,”Non-Real Time Reliable Multicast Protocol Using Sub-Sub Casting ,” The International Arab Journal of Information Technology , Vol. 4 , No. 1 , January 2007.

3.     Jim Gemmell, Jorg Liebeherr, Dave Bassett ,“An API for Scalable Reliable Multicast”.

4.     Tie Liao , “Light-weight Reliable Multicast Protocol” ,INRIA , Rocquencourt , BP 105 ,78153 Le Chesnay Cedex, France .

5.     Danyang Zhang , Sibabrata Ray , Rajgopal Kannan , S. Sitharama  Iyengar  “A Recovery Algorithm for Reliable Multicasting in reliable networks.” Proceedings of the 2003 International Conference on Parallel Processing (ICPP’03).  




Jose Vicente Berna-Martinez, Francisco Macia-Perez

Paper Title:

Multi-agent System for Control of Robots inspired on the Distributed Activity and Hormonal Regulation of Humans

Abstract: Robotics is an emerging field with great activity. Robotics is a field that presents several problems because it depends on a large number of disciplines, technologies, devices and tasks. Its expansion from perfectly controlled industrial environments toward open and dynamic environment presents a many new challenges. New uses are, for example, household robots or professional robots. To facilitate the low cost, rapid development of robotic systems, reusability of code, its medium and long term maintainability and robustness are required novel approaches to provide generic models and software systems who develop paradigms capable of solving these problems. For this purpose, in this paper we propose a model based on multi-agent systems inspired by the human nervous system able to transfer the control characteristics of the biological system and able to take advantage of the best properties of distributed software systems. Specifically, we model the decentralized activity and hormonal variation.

  Multi-agent systems, Bio-inspired system, Human nervous system; Service oriented architectures, Web Services. .


1.        Berná-Martínez, J.V. and Maciá-Pérez, F. " Model of Integration and Management for Robotic Functional Components Inspired by the Human Neuroregulatory System". IEEE International Conference on Emerging Technologies and Factory Automation 2010. ISBN 978-1-4244-6849-2.
2.        Pina-Garcia, C.A. and Garcia-Vega, V.A. “A Hybrid Methodology for Robotic Architectures with a Cellular Approach”. E-Learning in Industrial Electronics, 2006 1ST IEEE International Conference. ISBN 1-4244-0324-3, pp.156 – 160.

3.        Tu, X. and Terzopoulos, D. “Artificial fishes: physics, locomotion, perception, behavior”, Computer Graphics Proceedings (SIGGRAPH’94).

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5.        Pina, A., Seron, F.J., Cerezo, E. and Gutierrez, D. “ALVW: an alife behaviour modelling systems”. Kybernetes, Vol 35, no. 9. 2006. Pp 1431-1451.

6.        Mataric, M.J. “Behavior-based control: examples from navigation, learning, and group behavior”, Journal of Experimental and Theoretical Artificial Intelligence, special issue on Software Architectures for Physical Agents, H. Hexmoor, I. Horswill, and D. Kortenkamp, (Eds), Vol. 9, Nos 2/3, pp. 323-36.

7.        Charles R. Noback, Norman L. Strominger, Robert J. Demarest, David A. Ruggiero. The Human Nervous System. Structure and Function. 2005. ISBN 1-58829-039-5

8.        John Barton Furness. The Enteric Nervous System. Blackwell Publishing. 2006. ISBN 978-1-4051-3376-0

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13.     Arnold, A. P., Etgen, A.M., Fahrbach, S.E., Rubin, R.T., Pfaff, D.W. "Hormones, Brain and Behavior". Academic Press; 2 edition (July 6, 2009). ISBN-13: 978-0123743824

14.     Ferber, J. Multi-Agent Systems. An Introduction to Distributed Artificial Intelligence. Addison-Wesley.1999. ISBN-13: 978-0201360486.

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16.     Posadas, J.L., Pozaa, J.L., Simóa, J.E., Beneta, G., Blanesa, F. “Agent-based distributed architecture for mobile robot control” Engineering Applications of Artificial Intelligence archive, vol. 21 -6, 2008, pp. 805-823. ISSN:0952-1976.

17.     Maciá-Perez, F., García-Chamizo, J.M. "Mobile Agent System Framework Suitable for Scalable Networks". Kybernetes. The International Journal of Systems and Cybernetics. ISSN 0368-492X. Emerald. 2006. Vol.: 35. no 5. pp 688-699

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19.     Remy, S.L.  Blake, M.B. " Distributed Service-Oriented Robotics". IEEE Internet Computing, vol. 15, issue 2, pp 70-74. ISSN: 1089-7801.




Kiruthiga M, Prakasam P and L.M.I Leo Joseph

Paper Title:

Proposed Low-Power FPGA Architecture Using an Autonomous Fine-Grain Power Gating

Abstract: FIELD-PROGRAMMABLE gate arrays (FPGAs) are widely used to implement special-purpose processors. FPGAs are economically cheaper for low quantity production because its function can be directly reprogrammed by end users. FPGAs consume high dynamic and standby power compared to custom silicon devices. This paper presents a low power field-programmable gate array (FPGA) based on lookup table (LUT) level fine-grain power gating with small overheads. The activity of each LUT can be easily detected using the proposed power gating technique by exploiting features of asynchronous architectures. In this paper, the novel Logic Block utilizing the LUT with autonomous power gating has been proposed and the developed model has been simulated and synthesized in a selected target device. Also the power analysis has been carried out and it has been found that using the proposed fine-grain power gating method, the FPGA consumes only 34 uW.

   FPGA, Power Gating, Logic Block, Lookup Table


1.        H. Z. V. George and J. Rabaey, “The design of a low energy FPGA,” in Proc. Int. Symp. Low Power Electron. Des., CA, Aug. 1999, pp. 188–193.
2.        Synplicity Inc., Sunnyvale, CA, “Gated clock conversion with Synplicity’s synthesis products,” Jul. 2003.

3.        Xilinx Inc., San Jose, CA, “Synthesis and simulation design guide,” 2008. [Online]. Available: docs/sim/sim.pdf

4.        Y. Zhang, J. Roivainen, and A. Mammela, “Clock-gating in FPGAs: A novel and comparative evaluation,” in Proc. EUROMICRO Conf. Digit. Syst. Des., 2006, pp. 584–590.

5.        T. Tuan, S. Kao, A. Rahman, S. Das, and S. Trimberger, “A 90 nm low-power FPGA for battery-powered applications,” in Proc. FPGA, Feb. 2006, pp. 22–24.

6.        Xilinx Inc., San Jose, CA, “Spartan-3 FPGA family datasheet,” 2009. [Online]. Available:

7.        Xilinx Inc., San Jose, CA, “Virtex-4 FPGA family datasheet,” 2009. [Online]. Available:

8.        M. Keating, D. Flynn, R. Aitken, A. Gibbons, and K. Shi, Low Power Methodology Manual: For System-on-Chip Design. New York: Springer, 2007.

9.        Rahman, S. Das, T. Tuan, and S. Trimberger, “Determination of power gating granularity for FPGA fabric,” in Proc. IEEE Custom Intergr. Circuits Conf. (CICC), 2006, pp. 9–12.

10.     M. Hariyama, S. Ishihara, and M. Kameyama, “A low-power field- programmable VLSI based on a fine-grained power-gating scheme,” in Proc. IEEE Int. Midw. Symp. Circuits Syst. (MWSCAS), Knoxville, Aug. 2008, pp. 430–433.

11.     S. Ishihara, M. Hariyama, and M. Kameyama, “A low-power FPGA based on autonomous fine-grain power-gating,” in Proc. Asia South Pacific Des. Autom. Conf. (ASP-DAC), Yokohama, Japan, Jan. 2009, pp. 119–120.




O.Homa Kesav   , B. Abdul Rahim

Paper Title:

Automated Wireless Meter Reading System for Monitoring and Controlling Power Consumption

Abstract:  The use of wireless automation in almost all the fields of power, gas and water generation, distribution and billing has come of age. Here with the inclusion of wireless communication with the automation may lead to paradigm change in the current trend. The design presents a new methodology for avoiding the high construction and maintenance costs in the existing meter reading technology. Apart the use of wireless meter reading with network technologies has become need of the day. The designed system avoids the human intervention in Power Management. The Consumer has to pay the bill in time, if couldn’t, the power connection may be disconnected automatically from the remote server. It displays the corresponding billing information on LCD and data is sent to the server through the GSM Module. The ARM7 based hardware system consists of a processor core board and the peripheral board. The entire programming for microcontroller operation is based on Embedded C Language. This system provides efficient meter reading, avoiding the billing error and reduces the maintenance cost. This paper also addresses advantages of implementing the GSM communication module and design detail and discusses the advanced security of the data communications.

    Wireless meter reading, GSM, ARM7 (LPC 2148) Microcontroller.


1.           Li Xiaoguang Hu, “Design of an ARM-Based Power Meter Having WIFI Wireless Communication Module” IEEE 2009.
2.           B. S. Koay, etc, "Design and implementation of Bluetooth energy meter", Proceedings of the Joint Conference of the Fourth International Conference on Information, vol. 3, pp.1474-1477, Dec. 2003.

3.           Petri Oksa, Mikael Soini, “Considerations of Using Power Line Communication in the AMR System”, 2006 IEEE International Symposium on 26-29, pp.208-211, Mar. 2006

4.           S. Battermann and H. Garbe, “Influence of PLC transmission on the sensitivity of a short-wave receiving station,” IEEE Power Line Communications and Its Applications, pp.224-227, Apr. 2005.

5.           Chih-Hung Wu, etc, “Design of a Wireless ARM Based Automatic Meter Reading and Control System”, Power Engineering Society General Meeting, 2004. IEEE 6-10, Vol.1, pp.957-962, June 2004

6.           Yu Qin, “The Research and Application of ARM and GPRS Technology in Remote Meter Reading Terminal Equipment”, A Thesis Submitted in Partial Fulfilment of the Requirements for the Degree of Master of Engineering, 2007

7.           Honestar Electronics Co., Ltd, “Single-phase bidirectional Power/Energy IC-CS5460A”, Jan.2003.

8.           L. Shiwei, etc, "Design of an automatic meter reading system," Proceedings of the 1996 IEEE IECON 22nd International Conference on Industrial Electronics, pp.631-636, Aug. 1996

9.           Liting Cao, Jingwen Tian and Dahang Zhang, “Networked Remote Meter-Reading System Based on Wireless Communication Technology” in International Conference on Information Acquisition, 2006 IEEE.

10.        Liting Cao, Wei Jiang, Zhaoli Zhang “Automatic Meter Reading System Based on Wireless Mesh Networks and SOPC Technology” in International Conference on Intelligent Networks and Intelligent Systems, 2009 IEEE.

11.        P. Zerfos, X. Meng, S. Wong, V. Samanta, and S. Lu, “A study of the short message service of a nationwide cellular network,” in ACM SIGCOMM Internet Measurement Conf., Oct. 2006.




Indu Hariyale, Vina Gulhane

Paper Title:

Development of an Embedded Web Server System for Controlling and Monitoring of Remote Devices Based on ARM and Win CE

Abstract: The paper presents the design of an embedded Web server system, which is based on ARM920T processor. The server is implemented in VB with ASP. After the successful development of server it is transplanted on ARM processor. WIN CE is installed on ARM processor. This is because Win CE can be reduced and transplanted. The method used to transplant the web server on the embedded WIN CE platform, After the successful development of the embedded web server system it will be used for controlling and monitoring of remote devices. The remote device can be any electrical device. RF module is used for wireless communication between server and remote devices.AVR ATmega324 is used to control the wireless communication. AT each remote device RF module communicates with server via AVR ATmega8.

   Embedded web server; ARM, AVR, VB, ASP.


1.        Srinivas Raja, G. Srinivas Babu, “Design of Web based  Remote Embedded Monitoring system” International Journal  of  Technology and Engineering system(IJTES),Jan-March 2011-Vol.2,No.2.
2.        Fang Hongping, Fang KangLing, “The Design of       Remote Embedded Monitoring System based on   Internet” Internationa Conference on Measuring         Technology and Mechatronics Automation,,2010.

3.        Young-tao ZHOU, Xiao-hu CHEN,XU-ping WANG ,Chun-      jiang YAO, “Design of equipment Remote Monitoring System Based on Embedded Web”, International conference on Embedded software and Symposium(ICESS2008), 2008.

4.        Zhan mei-qiong , Ji chang-peng “Research and   Implementation of Embedded Web Server”,International Conference on MultiMedia and Information Technology,        2008.

5.        Liu Yang, Linying Jiang , Kun Yue ,Heming Pang, “Design  and Implementation of the Lab Remote Monitoring System        Based on Embedded Web Technology” International Forum  on Information Technology and Applications, 2010

6.        Guoling Liu, Xiaozhu Wang, He Jiang, Runian Geng ,“Research on Embedded Remote Communication Mode”,      978-1-4244-6349-7/10, IEEE 2010 .

7.        Wang XinxinChen Yun and Yan Ruzhong,     “Implementation of the Web-based Mechanical and Electrical      Equipment Remote   Monitoring System”, Computer      Engineering, (31):231-233 ,2005 .

8.        Xu Wei, “The Research of Embedded Database of Mass  Storage Technology”, microcomputer Information, (in Chinese). (24):119-120 2008.

9.        Zhang Quan-gui, “Embedded Internet and the application in  the monitoring and control system, Information Technology”, vol. 28 no. 4, pp52-54,2004.




Reddy Bharath Kumar D, CH.Nagaraju

Paper Title:

A Novel Data Collection Scheme in Wireless Sensor Networks Using MASP

Abstract:  In wireless sensor networks the energy efficiency can be improved with path constrained sink mobility. But collecting data from the nodes deployed randomly by the mobile sink as limited communication time due to constant speed of the mobile sink in the path constrained approach. This affects the amount of data collected and the energy consumption of the network. To overcome this issue, a novel data collection scheme called MASP is proposed. MASP is implemented as a two phase communication protocol base on zone partition. Our results are validated and simulated using OMNET++.  .

    mobile sink, path constrained, STP, wireless sensor network (WSNs).


1.        A.chakrabati, A.Sabharwal. and B.Aazhang”communication power optimization in a sensor Network with a Path-Constrained Mobile Observer” ACM Trans. Sensor Networks, vol.2, no.3, pp.297-324, Aug.2006.
2.        S.Jain, R.C.Shah, W.Brunette,  G.Borriello, and S. Roy, “Exploiting  Mobility  for  Energy Efficient Data Collection in  Sensor networks” mobile networks and applications, vol 11,no.3,pp.327-339,2006.

3.        R.C.Shah, S.Roy, S.Jain, and W.Bruneete, “Data MULESs: Modeling a Three- Tier Architecture for sparse Sensor Networks” Proc.First IEEE int,l Workshop on sensor Network Protocols and Applications ,pp.30-41,2003.

4.        A.Somasundra,A.Kansal, D.Jea,D.ESTIN, and M.Srivastava, ”controllably Mobile Infrastructure for Low energy  embedded networks” IEE Trans. Mobile computing, vol.5, no.8,pp.958-973,aug.2006

5.        J.Luo,J. Panchard, M.Piorkowski,M .Grosglauser, and J.Hubaux, “MobiRoue:Routing towards a Mobile Sink for improving Lifetime in Sensor Networks” Proc. Second IEEE/ACM int’l Conf.Distributed computing in sensor systems (DCOSS).

6.         Al-Karai and A.amal, “Routing Techniques in Wireless Sensor Networks’ Survey,” IEEE Wireless comm. Magazine vol.11, no.6, pp.6-28, Dec.2004. OMNET++3.3,,Oct.2006.

7.         M. Marta and M. Cardei, “Using Sink Mobility to Increase Wireless Sensor Networks Lifetime,” Proc. Ninth IEEE Int’l Symp.World of Wireless, Mobile and Multimedia Networks (Wow Mom), pp. 1-10, 2008

8.        S.Gao, H.Zhang, and S.K. Das, “efficient data collection in wireless sensor networks with path-constrained Mobile sinks,”Proc,10thIEEE ,int’l symp, world of wireless, mobile and multimedia(Wow Mom), 2009.

9.        G. Xing, T. Wang, Z. Xie, and W. Jia, “Rendezvous Design Algorithms for Wireless Sensor Networks with a Mobile Base Station,” Proc. ACM Mobi Hoc, pp. 231-240, 2008

10.     A. Kansal, A. Somasundara, D. Jean, M. Srivastava and D. Estrin, “Intelligent Fluid Infrastructure for Embedded Networks”, proc. ACM Mobisys, pp. 111-124, 2004.

11.     M. Marta and M. Cardei, “Using Sink Mobility to Increase Wireless Sensor Networks Lifetime,” Proc. Ninth IEEE Int’l Symp.World of Wireless, Mobile and Multimedia Networks (WoWMoM), pp. 1-10,




S.Surekha, C.Rajendra

Paper Title:

Applications of Wireless Sensor Network By Avoiding Congestion

Abstract:   Wireless Sensor Networks (WSNs) have emerged as an important new area in wireless technology. In many real-life environment applications of WSN’s, data is generated continuously and it should reach the sink node without delay and loss. Congestion is the one of the main problem in Wireless sensor networks. Congestion detection and Avoidance in WSN’s is a critical issue, it will not only affect transmission reliability, but also causes transmission delay and will waste valuable energy resources. The data flowing through the WSN have great impact on the link load. The way of handling the data against the congestion is tough task. Queue occupancy is an accurate indicator of congestion. In this paper we propose the scheme that detects efficiently congestion by using queue occupancy parameter of a node. If queue length of any node has reached maximum threshold level then data should not be transmitted through that node for certain time period to avoid congestion. It overcomes the congestion by selecting alternative neighboring node which does not cause congestion and transmit the data reliably and fastly to the destination (sink node) without delay and loss.

Wireless network, Sensor, Congestion detection, Congestion avoidance, Low level, High level, Congestion notification (CN) bit, Alternative node selection and Queue occupancy.


1.        Chieh-Yih  Wan,  Shane  B.  Eisenman  and  Andrew  T. Cambell, “CODA-Congestion Detection and Avoidance in Sensor”, in Proc. Of ACM SenSys “03.
2.        Vivek             Deshpande,              Prachi      Sarode,    Sambhaji  Sarode,”International   journal   of   Computer   Application”,Numbe 18, Article 6, Feb 2010.

3.        Y.Sankarsubramaniam,     Ozgur     B     Akan,     I.F. Akyildiz,”ESRT:Event to sink reliable transport in Wireless Sensor Network”,Proc. of ACM MobiHoc‟03

4.        C.Y. Wan, S. B. Eisenman, A. T. Campbell, "CODA: Congestion detection and avoidance in sensor networks," In Proc. of the First International Conference on Embedded Networked Sensor Systems (Sensys) 2003 Los Angeles 266-279.

5.        DR.Helonde J B, GNIET ,Nagpur, India , “Early Detection Congestion Avoidance Mechanism for Wireless Sensor Network”,International  journal of computer applications, Sep 2010.

6.        Energy Efficient Congestion Control in Duty-Cycled Wireless Sensor Networks ongho Lee, Nonmember and Kwangsue Chung, Senior Member, IEEE School of Electronics Engineering, University of Kwangwoon, Seoul, Korea 2010.




Parul Ahuja, Vivek Sharma

Paper Title:

A Review on Mobile Agent Security

Abstract: Mobile agents are enjoying a lot of popularity and are destined to influence research in distributed systems for the years to come. Thus far, technology has been instrumental in disseminating new design paradigms where application components are not permanently bound to the hosts where they execute. Mobile agents are gaining in complexity as they evolve and are now widely used in e-commerce. All phases of a business transaction, such as negotiating and signing contracts can be done using mobile agents. In this paper, we provided a brief introduction to the recent researches & developments associated with the field of mobile agents, highlighting various security threats, also touching the weakest hot-spots of the field which need to be nurtured.

  Intelligent agent, Mobility, Security, Security Threats.


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6.     G.P. Picco, “Mobile agents: an introduction”, Microprocessors and Microsystems 25(2001) pp. 65-74, Dipartimento di Elettronica e Informazione, Politecnico di Milano, Milan, Italy.

7.     H.S. Nwana, “Software Agents: An Overview”, Knowledge Engineering Review, 11(3):1- 40, 1996.

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12.  A. Singh, D. Juneja, and A.K. Sharma, “Elliptical Curve Cryptography Based Security Engine for Multiagent Systems Operating in Semantic Cyberspace”, In International Journal of Research and Review in Computer Science (IJRRCS), Vol. 2, No. 2,     April 2011.

13.  C. Xiaorong, L. Su, L. Mingxuan, “Research of Network Security Situational Assessment Quantization Based on Mobile Agent”, Volume 25, 2012, Pages 1701–1707, International Conference on Solid State Devices and Materials Science, April 1-2, 2012, Macao.

14.  S. M.. Moussa, G.A.  Agha, “Integrating Encrypted Mobile Agents with Smart Spaces in a Multi-agent Simulator for Resource Management”,  Journal of Software, Vol 5, No 6 (2010), 630-636, Jun 2010.

15.  S. Karnouskos, “Security implications of implementing active network infrastructures using agent technology”, Special Issue on Active Networks and Services, In Computer Networks Journal, Elsevier, Vol. 36, Issue 1, pp. 87-100, June 2001.

16.  W. Jansen and T. Karygiannis, “Mobile Agent Security”, Nist Special Publication 800-19-, 2000. National Institute of Standards and Technology.

17.  [N. Borselius, “Mobile agent security”, Electronics & Communication Engineering Journal, IEEE London 14(5), 211-218(October 2002).

18.  W.A. Jansen, “Countermeasures for Mobile Agent Security”, National Institute of Standards and Technology, Gaithersburg, MD 20899, USA,

19.  S.M.S.I. Rizvi, Z. Sultana, B. Sun, and  Md. W. Islam, “Security of Mobile Agent in Ad hoc Network using Threshold Cryptography”, World Academy of Science, Engineering and Technology 70- 2010.

20.  P. Dadhich, Dr. K. Dutta, and Prof.(Dr.) M.C. Govil, “Security Issues in Mobile Agents”, International Journal of Computer Applications(0975-8887), Volume 11-No.4, December 2010.

21.  D.M. Chess, “ Security issues in mobile code systems. In : mobile agents and security”,  Editor Vigna, vol. LNCS1419. Springer-Verlag 1998.

22.  K. Lauter, “The Advantages of Elliptic Curve Cryptography for Wireless Security”, In IEEE Wireless Communications, pp. 62-67. February 2004.

23.  R. Shanmugalakshmi and M. Prabu, “Research Issues on Elliptic Curve Cryptography and its applications”, In International Journal of Computer Science and Network Security, Vol. 9, No.6, pp 19- 22, June 2009.               

24.  A. Singh, D. Juneja, A.K. Sharma, “Introducing Trust Establishment Protocol in Contract Net Protocol”. In Proceedings of IEEE International Conference on Advances in Computer Engineering (ACE’2010), pp. 59-63, June, 2010.

25.  N. Koblitz, “Elliptic Curve Cryptosystems”, Mathematics of Computation, Vol. 48, pp. 203-209, 1987.

26.  V.S. Miller, “Use of Elliptic Curves in Cryptography”, Advances in Cryptology- CRYPTO’85, LNCS, vol. 218, Springer-Verlag, pp. 417-426,1986.

27.  V. Roth & M. Jalali-Sohi, “ Access Control and Key Management for Mobile Agents”, Fraunhofer Institute for Computer Graphics, Rundeturmstr. 6, 64283 Darmstadt, Germany, 8 November, 2001.

28.  G. Knoll, N. Suri, and J.M. Bradshaw, “Path-based Security for Mobile Agents”, Electronic Notes in Theoretical Computer Science, Vol. 58, No. 2 , pp. 16, (2002).




Rinku Rajankar, R.W. Jasutkar

Paper Title:

Fuzzy Approach to Mobile Cloud Computing

Abstract:  In a world that sees new technological trends bloom and fade on almost a daily basis, one new trend promises more longevity. This trend is called mobile cloud computing, and it will change the way we use computer and the Internet. The increased degree of connectivity and the increasing amount of data has led many providers and in particular data centers to employ larger This raises a bottleneck to efficiently access the data. In this paper we introduce idea of improving accessibility of Cloud using if then concept of Fuzzy. In the developing process of various servers proposed work make use of Microsoft’s latest windows Azure cloud computing platform. 

Mobile Cloud Computing, Azure framework, fuzzy IF-THEN rule.


1.          Pipieter Simoens, Filip De Turck et al, “Remote Display Solutions for Mobile Cloud Computing,” IEEE Computer.
2.          Vijay Sarathy, Purnendu Narayan et al, “Next generation Cloud Computing Architecture,” 2010 Workshops on Enabling Technologies: Infrastructure for  Collaborative Enterprises.

3.          Li Ye-bai and Zhang Bin, Wang Hai-bin, “Study and Design on Data Management Model of SQL Server CE For Mobile Application,” 2010 International Conference on   e-Education, e-Business, e-Management and e-Learning.

4.          Wei Lu, Jared Jackson, Jaliya Ekanayake,et al “Performing Large Science Experiments on Azure: Pitfalls and Solutions” 2nd IEEE International Conference on Cloud Computing Technology and Science

5.          Amel Grissa Touzi and Mohamed Ali Ben Hassine, “New Architecture of Fuzzy  Database Management Systems,” The International Arab Journal of Information  Technology, Vol. 6, No. 3, July 2009

6.          Gwan-Hwan Hwang. “Supporting Cloud Computing in Thin-client/server Computing model ” 2010 IEEE International Symposium on Parallel and Distributed Processing with Applications.




Ashwini Motghare, Swapnili P. Karmore

Paper Title:

Hardware -in-the-Loop Search –Based Testing Approach to Embedded Systems

Abstract: The complexity of embedded systems is ever increasing while high system quality is being demanded at the same time. With the continuously growing software and system complexity in electronic control units and shortening release cycles, the need for efficient testing grows. In order to perform testing of electronic control units in practice search-based hardware-in-the-loop test environments are used to run the system under test in a simulation environment under real-time conditions.  The potential of applying search-based testing approach to the functional testing has been demonstrated in various test cases. The focus was mainly on simulating the system under test in order to evaluate test cases. However, in many cases only the final hardware unit is available for testing. This paper present an approach in which evolutionary functional testing is performed using an actual electronic control unit for test case evaluation. An extensive case study has been carried out to access its capabilities. We demonstrate the use of evolutionary testing for functional testing in an industrial setting by applying the developed solution to test functioning of serial production of an automation-system electronic control unit.

Evolutionary Algorithm (EA), Functional Testing, Hardware-in-the-loop-Testing (HiL), Automation-System (AS)


1.          Byeongdo Kang, Young-Jik Kwon, Roger Y. Lee, “A Design and Test Technique for Embedded Software”, IEEE, 2005.
2.          Pei Tian, Kai Wang, Kai Qiang, " Construction of Distributed Embedded Software Testing Environment", IEEE, 2009.               

3.          Dae-Hyun Kum, Joonwoo Son, Seon-bang Lee, “Automated Testing  for Automotive Embedded Systems”, SICE-ICASE, 2006.

4.          Yongfeng YIN, Bin LIU, Guoliang ZHANG, “On Framework Oriented Embedded Software Testing Development Environment”, IEEE,2009.

5.          Kandl, S.Kirner, R. Puschner, "Development of Framework Automated  Systematic Testing of Safty-Critical Embedded Systems”, IEEE,  Intelligent Solutions in Embedded Systems, 2006.

6.          D. L. kaleita and N. Hartmann, "Test Development Challenges for  Evolving Automotive Electronic Technologies", SAE, 2004-21-0015,2004.         

7.          Bringmann, E.Kramer, “Model-Based Testing Automotive Systems”, IEEE, Software Testing, Verification, and Validation, 2008.

8.          Lindlar, F. Windisch, “A Search-Based Approach to Functional Hardware-in-the-Loop Testing”, IEEE, 2010.

9.          Siegl, S.Caliebe, “Improving Model-Based Verification of Embedded System by Analyzing Component Dependences”, IEEE, Industrial Embedded Systems (SIES), 2011.

10.       N. H. Lee and S. D. Cha, "Generation Test Sequences from a Set of  MSCs", The International Journal of Computer and                     Telecommunications Networking, Volume 42, Issue 3, Page 405 - 417, 2003. 

11.       Y. G. Kim, H. S. Hong, D. H. Bae and S.D.Cha,"Test Cases Generation from UML State Diagrams", IEE proceedings, online no. 199990602, 1999.

12.       R. L. Probert, H. Ural and A.W.Williams, "Rapid Generation of  Functional Tests using MSCs, SDL and TTCN", Computer Communications, Volume 24, Issues 3-4, Page 374-393, 2001.

13.       Wegener, J.; Baresel, A.; Sthamer, H.; “Evolutionary test environment for automatic structural testing”, Information and Software Technology, 2001.




Vivekanand P. Thakare, N. A. Chavan

Paper Title:

Performance Evaluation of Parking Guidance and Management  System using Wireless Sensor Network

Abstract: To deal with the parking guidance system issue related to the parking lots, this   paper   proposes   a   vision of improvements in parking   guidance   and information system based on wireless sensor network.  This system consists of parking space monitoring nodes (senor nodes), parking status display unit (PSDU), Micro Control Unit (MCU) and Central Co-ordinator. The guiding nodes transmit the information of vehicle entrance through   wireless   sensor   network. Micro Control Unit sends information to sensor nodes as well as PSDU which shows the parking status and also display the nearest parking lot. All the process can be monitored by the central co-ordinator. The preliminary test results show that the performance of this WSN based system can effectively satisfy the needs and requirements of the existing parking systems. Also it minimizes the time consumed for finding the free parking lot as well as nearest parking lot.

Wireless Sensor Network (WSN), Parking Status Display Unit (PSDU), Micro Control unit (MCU), Advanced Virtual RISC (AVR).


1.        Mingkai Chen, Tainhai Chang, “A Parking guidance & Information system based on Wireless Sensor Networks”, IEEE International Conference on information & Automation Shenzhen, China, June 2011.
2.        Mingkai Chen, Chao Hu and Tianhai Chang. “The Research on Optimal Parking Space Choice Model in Parking Lots”. 2011 3rd International Conference on Computer Research and Development, March 11 - 13, 2011,Shanghai, China,Vol. 2, pp:93-97.

3.        Abhijit Sharma, Rituparna Chaki, Uma Bhattacharya, “Applications of Wireless Sensor Network in intelligent traffic system: A Review”, 978-1-4244-8679-3/11,IEEE 2011.

4.        S. V. Srikanth, Pramod P. J., Dileep K. P., Tapas S., Mahesh U. Patil, Sarat Chandra Babu N, “Design & Implementation of a Prototype Smart PARKing (SPARK) System using Wireless Sensor Networks” International Conference on  Advanced Information Networking & Applications workshops, 978-0-7695-3639-2/09, 2009 IEEE.

5.        Seong-eun Yoo, Poh Kit Chong, Taehong Kim, Jonggu Kang, Daeyoung Kim, Cahngsyb Shin, Kyungbok Sung, Byungtae Jang,“PGS: Parking Guidance System based on Wireless Sensor Networks”, 978-1-42441653-0/08, 2008 IEEE.

6.        Vipin Kumar Verma, Rahul Chaudhari, Siddharth Kumar Singh, Tapas Mishra, Pankaj Srivastava , “Intelligent Transport Management System using Wireless Sensor Networks”, IEEE Intelligent Vehicle Symposium Elndhoven University of technology Elndhoven, Netherlands, June 4-6, 2008.

7.        Fanyu Kong and Jindong Tan, “A Collaboration-based Hybrid Vehicular Sensor Network Architecture” Proc. International Conference on Information and  Automation, June 20 -23, 2008, pp.584-589.

8.        Jatuporn Chinrungrueng, Udomporn Sunantachaikul, Satien Triamlumlerd, “ Smart Parking: An Application of Wireless Sensor Network”, International Symposium on Applications and Internet  Workshops(SAINTW07), 978-0-7695-2757-4/07, 2007 IEEE.

9.        Rakesh Kumar, Naveen K Chilamkurti, Ben Soh, “A Comparative Study of Different Sensors for Smart Car Park Management”, International Conference on Intelligent Pervasive Computing, 2007”, 978-0-7695-3006-0/07, 2007 IEEE.

10.     S. Shaheen, C. Rodier, and A. Eaken, “Smart parking management field test: A bay area rapid transit (bart) district parking demonstration”, Jan 2005. Final Report.

11.     Yaser E. Hawas and Marc Joseph B. Napenas, “Infrastructureless Inter-Vehicular Real-Time Route Guidance”, Proc. 11th International IEEE Conference on Intelligent Transportation Systems, 12-15 Oct 2008, pp. 1213-1219.

12.     IrisNet: Internet -scale Resource-Intensive Sensor Network Service,

13.     Seong-eun Yoo, Poh Kit Chong, Taisoo Park, Youngsoo Kim, Daeyoung Kim, Cahngsyb Shin, Kyungbok Sung, Hyunhak Kim,“DGS: Driving Guidance System based on Wireless Sensor Networks”, 978-0-7695-3096-3/08, 2008 IEEE.

14.     Xu Li, Wei Shu, Minglu Li, Hongyu Huang and Min-You Wu, “DTN Routing in Vehicular Sensor Networks”, Proc. Global Telecommunications Conference, GLOBECOM" 2008, pp. 752-756.

15.     Vanessa W.S. Tang, Yuan Zheng, Jiannong Cao,” An Intelligent Car Park Management System based on Wireless Sensor Networks”, 1st International Symposium on Pervasive       Computing and Applications, 2006, pp. No. 65 – 70. IEEE 2006.




Sweeta A.Kahurke, Bhushion N. Mahajan

Paper Title:

Implementation of Priority Based Scheduling and Congestion Control Protocol in Multipath Multi-Hop WSN

Abstract: :- Congestion Control and data fidelity is the most important goal in wireless sensor network. Wireless sensor network is the event based system. When the event occurred, multiple sensor nodes sense the same event and are active for transmitting the information. Transfer rate could  be varied due to multiple events occurred simultaneously. This increases too much data traffic in the network, load becomes heavy this lead to network congestion.  Congestion causes packet drop, low throughput, increasing queuing delay, retransmission of packets this causes consumption of additional energy and wastage of communication resources . In this paper, we implemented  a priority based scheduling and congestion control protocol (PBSCCP) using multipath multihop routing in wireless sensor network . This new scheme is alleviated congestion in network , increases the throughput and packet delivery ratio and also minimize delay . This scheme is also increased network efficiency based on delivery of packets .

Congestion Control, Packet delivery ratio, priority of packets, network efficiency, priority based scheduling and congestion control protocol , data fidelity


1.           D.F.Jenolin Flora , Dr.V.Kavita , M.Muthuselvi  “A Survey on Congestion Control Techniques in  Wireless Sensor Network” Proceeding of ICETECT    2011. PP . 1146-1149.
2.           Dongho Lee, and Kwangsue Chung, “Adaptive duty-cycle    based congestion control for home automation networks”, IEEE Trans.Consumer Electronics, vol. 56, No. 1, pp. 42-47, Feb. 2010.

3.           C.-Y. Wan, A. T. Campbell, and L. Krishnamurthy, "PSFQ: A reliable transport protocol for wireless sensor networks," Proc. First ACM Intl. Workshop on Wireless Sensor Networks and Applications (WSNA '02), Atlanta, GA, 2002.

4.           C. Wang, B. Li, K. Sohraby, M.Daneshmand, and Y. Hu, “Upstream congestion control in wireless sensor networks through cross-layer optimization”, IEEE Journal on Selected Areas in Communications, vol. 25, No. 4, pp. 786-795, May 2007.

5.           R. Anantharangachar , C. Reddy and D.Ranganathan , “A Case study of Survice Oriented Application Integration Framwork”.

6.           Shigang Chen, and Na Yang, “Congestion avoidance based on lightweight buffer management in sensor networks”, IEEE Trans. Parallel and Distributed Systems, vol. 17, No. 9, pp. 934-946, Sep. 2006.

7.           Ozgur B. Akan, and Ian F. Akyildiz, “Event to sink reliable transport in wireless sensor networks”, IEEE Trans. Networking, vol. 13, No. 5, pp.1003-1016, Oct. 2005.

8.           Jenn-Yue Teo, Yajun Ha, and Chen-Khong Than, “Interferenceminimized multipath routing with congestion control in wireless sensor network for high-rate streaming”, IEEE Trans. Mobile Computing, vol.7, No. 9, pp. 1124-1137, Sep. 2008.

9.           C.Y.Wan , S.B. Esenman and A.T. Combell , “CODA : Congestion detection and avoidance in sensor network”, proc . ACM SENSYS 2003, Los Angeles , CA , USA ,
Nov 2003 pp. 266-279.

10.        Guangxue Wang and Kai Liu , “Upstream Hop-by-Hop Congestion Control in wireless sensor networks”. IEEE 2009.

11.        Chonggang Wang , Kazem Sohraby , Victor Lawrence , Bo Li , Yueming Hu , “Priority based congestion control in wireless sensor networks” , proceeding of IEEE International Conference on sensor networks, Ubiquitous and Trustworthy computing (SUTC’06) IEEE 2006.

12.        Zhibin Li , Peter X. Liu , “ Priority based congestion control in multipath and multihop wireless sensor network” , proceeding of 2007 IEEE international conference on robotics and biomimetics.

13.        Joa-Hyoung Lee and In-Bung Jung , “Adaptive- Compression based congestion control Technique for wireless sensor network” , Sensors 2010 , ISSN 1424 – 8220 ,

14.        Atif Sharif , Vidyasagar Pothdar , A.J.D.Rathanayaka , “ Priority enabled Transport layer protocol for wireless sensor network” , 2010 IEEE 24th international conference on advanced information networking and application workshop.

15.        Xiaoyan Yin , Xingsche Zhou , Rongscheng Huang , “A Fairness – Aware congestion control scheme in wireless sensor networks” , IEEE Transactions on vehicular technology vol-58 , No-9 , November 2009.

16.        Srikanth Jagabathula , Devavrat Shah, “A Fair Scheduling in Networks through packet election”,IEEE Transactions on information theory vol-57,No. – 3, march 2011.




Sweeta A.Kahurke, Bhushion N. Mahajan

Paper Title:

Novel Image Compression Technique WithImproved Wavelet Method

Abstract: :-  Image compression is minimizing the size in bytes of a graphics file without degrading the quality of the image to an unacceptable level. The reduction in file size allows more images to be stored in a given amount of disk or memory space. It also reduces the time required for images to be sent over the Internet or downloaded from Web pages. . This would imply the need for a compression scheme that would give a very high compression ratio very high compression ratio usually comes with a price. This refers to the quality of the image. Wavelet method for compression gives better vision and quality. In our case we are taking the Modified Haar wavelet transformation (MFHWT) method with SVD. This research work will not only compress the images but also take care for the loss of information.

Wavelet , Haar, MFHWT, SVD


1.        Kazuhiko HAMAMOTO “Study on Medical Ultrasonic Echo Image  Compression by JPEG2000” - Optimization and the subjective assessment of the quality – Proceedings of the 25 Annual International Conference of the IEEE EMBS Cancun, Mexico September 17-21, pp 833 – 836, 2003.
2.        Y.-G. Wu “GA-based DCT quantisation table design procedure for  medical images” IEEE Proc.-Vis. Image Signal Process, Vol. 151,    No. 5, pp 353 – 359, October 2004.

3.        Guofang Tu, Derong Liu  and  Can Zhang “A New Compression     Algorithm for Medical Images Using Wavelet Transform”  0-7803-88 12-7/05/20.00 pp 84 – 89 ,2005 IEEE.

4.        Gerald Schaefer, Roman Starosolski and Shao Ying Zhu “An evaluation of lossless compression algorithms for medical infrared images” Proceedings of the 2005 IEEE Engineering in Medicine and Biology 27th Annual Conference. Shanghai, China, September 1-4,pp                                  

5.        1673 – 1676, 2005

6.        P. Tsai “Histogram-based reversible data hiding for vector  quantisation-compressed images” IET Image Process., 2009, Vol. 3,      Iss. 2, pp. 100–114 doi: 10.1049/iet-ipr.2007.0220

7.        Piyamas Suapang, Kobchai Dejhan and Surapun Yimmun “A Web-based DICOM-Format Image Archive, Medical Image Compression and DICOM Viewer System for Teleradiology Application” SICE Annual Conference 2010 August 18-21, PR0001/10/0000-3005, pp 3005 – 3011,  2010.

8.        Piyamas Suapang, Kobchai Dejhan and Surapun Yimmun “Medical Image Archiving, Processing, Analysis and  Communication System for Teleradiology” IEEE  TENCON, 978-1-4244-6890-4/10, pp 339 – 345, 2010.

9.        Puja Bharti, Dr. Savita Gupta and Ms. Rajkumari Bhatia “Comparative Analysis of Image Compression Techniques: A Case Study on Medical Images” 2009 International Conference on Advances in Recent Technologies in Communication and Computing, IEEE 978-0-7695-3845-7/09, pp 820 – 822, 2009.

10.     K.V.Sridhar and Prof. K.S.R.Krishna Prasad “MEDICAL IMAGE COMPRESSION USING ADVANCED CODING TECHNIQUE” ICSP2008 Proceedings, IEEE 978-1-4244-2179-4/08, 2008.

11.     Yen-Yu Chen and Shen-Chuan Tai “Embedded Medical Image Compression Using DCT Based Subband Decomposition and Modified SPIHT Data Organization” Proceedings of the Fourth IEEE Symposium on Bioinformatics and Bioengineering (BIBE’04) 0-7695-2173-8/04,2004.

12.     D Campbell, A Maeder and F Tapia-Vergara “Mammogram JPEG Quantisation Matrix Optimisation for PACS” Seventh Australian and New Zealand Intelligent Information Systems Conference, 18-21 November 2001, Perth, Western Australia

13.     Yong-Jie Ni, Chan-Hyun Youn, Hyewon Song, Byoung-Jin   Kim and Youngjoo Han “A PACS-Grid for Advanced Medical Services based on PQRM” ISSNIP IEEE , 1-4244-1502-0/07,2007.

14.     Yung-Gi Wu “Medical Image Compression by Sampling DCT Coefficients” IEEE TRANSACTIONS ON INFORMATION TECHNOLOGY IN BIOMEDICINE, VOL. 6, NO. 1, MARCH 2002.

15.     Seoncheol Hwang, Jeongwhan Lee, Junyoung Lee, Jeonghoon Kim, Inkwee Choi,Gunsoo Shin, Heejoung Kim, M youngho Lee “DEVELOPMENT OF WWW-BASED TELEPACS USING SATELLITE DATA COMMUNICATION SYSTEM” Proceedings of the 20th Annual International Conference of the ZEEE Engineering in Medicine and Biology Society, Vol. 20, No 3,pp 1281 – 1283, 1998.




A. P. Zurani, B. N. Mahajan

Paper Title:

Clustered Time Synchronization Algorithm for Wireless Sensor Networks

Abstract: A Time Synchronization algorithm based on Cluster for WSN was Proposed for WSN ( Wireless Sensor Network)  -(CTS) Clustered Time Synchronization algorithm for WSN. This algorithm consist of two phases: In the Cluster-Inter Synchronization phase- It adopt pair-wise  packet exchange mechanism to achieve time synchronization  between the Base station and cluster heads through establishing a hierarchical topology structure. In the Cluster-Intra Synchronization phase  - It used reference broadcast mechanism to achieve time synchronization between the cluster heads and cluster members. The purpose of this algorithm is to set the logical clock of the cluster heads and cluster nodes with global time. The simulation result shows that this algorithm has better synchronization accuracy and lower power consumption and better synchronization precision as compared to Reference Broadcast Synchronization (RBS), Timing-Sync Protocol for Sensor Networks (TPSN) algorithms

 Sensor Networks, Time Synchronization, Malicious   nodes, Battery, clustered synchronization, delay , energy, cluster, reference broadcast.




Sonia Sharma, Shikha Rai

Paper Title:

Genetic K-Means Algorithm – Implementation and Analysis

Abstract: K-means algorithm is most widely used algorithm for unsupervised clustering problem. Though it is accepted but it has some problems which make it unreliable. Initialization of the random cluster centres, number of clusters and terminating condition play a major role in quality of clustering achieved. This paper empirically analyses a derived form [Krishna &Narasimha, 1999] of K-means using Genetic algorithm approach. The new algorithm prevents algorithm to converge towards local minima by considering a rich population of potential solutions. A tool that implements this algorithm is presented in the paper. The time complexity and execution expectation is also tested over an exhaustive set of data of different dimensions.

   K-Means clustering, Genetic Algorithm, Local Minima, Optimization.


1.     Krishna K, Murty M “ Genetic K-means algorithm” ,IEEE Transactions on Systems, Man and Cybernetics ,Part B: Cybernetics 1999 , 29:433-439.
2.     William A. Greene “Genetic Algorithms For Partitioning Sets” University of New Orleans New Orleans, LA 70148,2000

3.     Monica Chi,” Evolutionary  Hierarchical Clustering Technique”,2001

4.     N. Sujatha,” Refinement Of Web Usage Data Using Clustering From K Means Using GenticAlgorithm”,Research Scholar, Department of Computer Science Madurai Kamaraj University, Madurai,European Journal of Scientific Research , 2010

5.     Hall, L.O. Ozyurt, I.B.  Bezdek, J.C,” Clustering With Genetically Optimized Approach”,1999

6.     R. J. W. Hodgson,”Genetic Algorithm Approach to Particle Identification by Light Scattering”,2000




Jeff Huang, Ken Nagasaka

Paper Title:

Allocation of Greenhouse Gas (GHG) Emission for Japanese Electric Utility Post Kyoto Protocol

Abstract: In May 2011, the Japanese Government decided not to participate in the new reduction agreement which will take place after the end of Kyoto Protocol. The Japanese Government believes the new reduction agreement is not capable of tackling the global Greenhouse Gas (GHG) emission problem unless all large GHG emitting countries, such U.S and China, participate. Although the Japanese Government has decided not to participate in this new reduction agreement, it still undertook initiatives to set up its new emission reduction targets. From the latest revision of the Strategic Energy Plan in 2010, Japan has committed to reduce its GHG emission level by 25% compared to its 1990 level, conditional on other industrialized countries making similar reduction effort. Although the target has been established, it did not specify the allocation of the GHG emission reduction target to each General Electric Utility (GEUs) in Japan. In this research we began with an analysis of electricity demand forecasting and relate GHG emission of Japanese Electric Utility Post Kyoto Protocol by Artificial Neural Networks (ANN) methodology. Then based on these forecasting results, we allocated the target emission allowance to each Japanese General Electric Utility (GEUs) in 2013-2016 based on two most common allocation approaches, namely the Grandfathering Approach and the Output-based Benchmarking Approach. In the conclusion, we analyzed the trends and necessary actions that the Japanese electric utility need to undertake to achieve its emission target under different allocation approach.

    Allocation, Benchmarking; Forecasting; Greenhouse Gas (GHG) Emission


1.           The Strategic Energy Plan of Japan, Ministry of Economy Trade and Industry Japan (METI), 2010,
2.           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

3.           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

4.           R. Betz, W. Eichhammer, J. Schleich. “ Designing National Allocation Plans for EU emissions trading – A Fiest Analysis of the Outocme” Energy & Environment, vol.15,  number3, pp.375-425, 2004

5.           General Guidance to the allocation methodology, European   Commission,, 2011.

6.           Position paper on Benchmarking and allocation rules in phase three of the EU Emissions Trading System, CAN Europe, 2010.

7.           Environmental Action Plan by the Japanese Electric Utility Industry, The Federation of Electric Power Companies of Japan (FEPC) , 2010.




Yogita L, Pankaj H. Rangaree

Paper Title:

A Biometric ECG Identification using LNF in Wireless Body Area Sensor Network

Abstract:  Wireless body area sensor networks low-power integrated circuits, and wireless communications have enabled the design of low-cost, miniature, lightweight, and intelligent physiological sensor nodes. These nodes, capable of sensing, processing, and communicating one or more vital signs, can be seamlessly integrated into wireless personal or body networks (WPANs or WBANs) for health monitoring. These networks promise to revolutionize health care by allowing inexpensive, non-invasive, continuous, ambulatory health monitoring with almost realtime updates of medical records via the Internet. This paper proposes a power and area efficient electrocardiogram (ECG) acquisition and signal processing application sensor node for wireless body area networks (WBAN). This sensor node can accurately record and detect the QRS peaks of ECG waveform with high-frequency noise suppression. analog front end integrated circuit (IC) and digital application. This ECG sensor node is convenient for long-term monitoring of cardiovascular condition of patients, and is very suitable for on-body WBAN applications.we minimize the other signal such as the ECG signal along with a bunch of noise is in analog form. In we use the Low Noise Filter (LNF) to filter the noise from the ECG Signals.

     Wireless body area sensor network, GSM model, ECG Sensor Node


1.           Honggang Wang, Hua Fang, Liudong Xing, Min Chen,( 2011) ” An Integrated Biometric-based Security Framework Using Wavelet-Domain HMM in Wireless Body Area Networks (WBAN)” IEEE Communications Society subject matter experts for publication in the IEEE ICC proceedings.
2.           Raju Singh(March 2011) “Confidentiality & Authentication Mechanism for Biometric Information Transmitted over Low Bandwidth & Unreliable channel” School of Computer Engineering and IT, Shobhit University, Meerut, India Vol.3, No.2,

3.           Mikael Soini, Jussi Nummela, Petri Oksa, Leena Ukkonen and Lauri Sydänheimo (2009).” Wireless Body Area Network for Hip rehabilitation” Tampere University of Technology, Department of Electronics, Rauma Research Unit pp. 202-206 .

4.           Cory Cornelius(August 2010) “On Usable Authentication for Wireless Body Area Networks” Department of Computer Science Dartmouth College, Presented at HealthSec, .

5.           Jamil Y. Khan, Mehmet R. Yuce, and Farbood Karami “Performance Evaluation of a Wireless Body Area Sensor Network for Remote Patient Monitoring”

6.           A. Soomro, D. Cavalcanti, IEEE (Feb 2007)“Opportunities & Challenges using WPAN  and WLAN Technologies in Medical Environments”, Communications Magazine, vol:45, no:2, page 114-122.

7.           Adnan Saeed, Miad Faezipour IEEE 2009,

8.           ”Plug and Play Sensor Node for Body Area Network”,. Jamil Y. Khan,school of computer science,Australia,IEEE (09,07, 2009,)

9.           ”Wireless Body Area Network for Medical Applications”. Emil Jovanov, Dejan Raskovic, John Price,John Chapman, Anthony Moore, Abhishek Krishnamurthy,IEEE (2008) ,.” Patient Monitoring Using Personal Area Networks of Wireless Intelligent Sensors”.

10.        CHRIS OTTO, ALEKSANDAR MILENKOVIĆ, COREY SANDERS, EMIL JOVANOV, Journal of Mobile Multimedia, Vol. 1, No.4 (2006) 307-326


12.        Chao Chen and Carlos Pomalaza-Ráez , International Journal of Computer Science and Information Technology, Volume 2, Number 3, 16June 2010.,

13.        ”Implimenting and EvaluatingA wireless body Sensor System for Automated Physiological Data Acquisition At Home”, Frank Agyei-Ntim, Member IEEE, Kimberly Newman, Senior Member IEEE, September 2-6, 2009,

14.        “Lifetime Estimation of Wireless Body Area Sensor Network for Patient Health Monitoring” 31st Annual International Conference of the IEEE EMBS Minneapolis, Minnesota, USA, Adnan Saeed, Mehrdad Nourani, Gil Lee, Gopal Gupta and Lakshman Tamil ,IEEE 2007,

15.        ” A Scalable Wireless Body Area Sensor Network for Health-Care Monitoring “, The University of Texas at Dallas, Richardson, Texas. Adnan Saeed*, Miad Faezipour*, Mehrdad Nourani*, Subhash Banerjee, June 2009 , ” A Scalable Wireless Body Area Network for Bio-Telemetry”, Journal of Information Processing Systems, Vol.5, No.2.

16.        Aleksandar Milenković, Chris Otto, Emil Jovanov, Accessed: July 2005, “Wireless Sensor Networks for Personal Health Monitoring:Issues and an Implementation” .

17.        Mehmet R. Yuce & Steven W. P. Ng & Naung L. Myo &Jamil Y. Khan &Wentai Liu , “Wireless Body Sensor Network Using Medical Implant Band”, Received: 10 July 2007 / Accepted: 25 July 2007.




Nupur Singh, Pinky Tanwar

Paper Title:

Image Fusion Using Improved Contourlet Transform Technique

Abstract:   Image fusion is the process by which two or more images are combined into a single image retaining the important features from each of the original images. The fusion of images is often required for images acquired from different instrument modalities or capture techniques of the same scene or objects .Several approaches to image fusion can be distinguished, depending on whether the images are fused. The purpose of image fusion is to combine information from several different source images to one image, which becomes reliable and much easier to be comprehended by people (Youcef and Amrane,2003). Image fusion can be broadly defined as the process of combing multiple input images or some of their features into a single image without the introduction of distortion or loss of information. The objective of image fusion is to combine complementary as well as redundant information from multiple images to create a fused image output. Therefore, the new image generated should contain a more accurate description of the scene than any of the individual source image and is more suitable for human visual and machine perception or further image processing and analysis tasks.



1.     Ali , F.E . Dokany , I. M. El.Saad , A. A.  and  Abd El-Samie , F.E. (2008) , “   Fusion   of MR and CT Images Using The Curvelet Transform”, 25th National  Radio  Science Conference (NRSC 2008).
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Signal Processing, China , pp.976-981

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7.     Choi , M . Kim, R.Y . Nam, M. Rand  Kim , O.H ,(2005) “Fusion Of Multispectral And Panchromatic Satellite Images Using The Curvelet Transform,” IEEE Geosci. Remote Sens., vol. 2, no. 2, pp. 136–140

8.     Dawei , Z. and Fang ,Z .(2007) ,“A New Improved Hierarchical Model of Image Fusion ,”The Eighth International Conference on Electronic MeasurementandInstruments,pp.25-35.

9.     Gonzalez, R.C.andWoods, R.E. (1994) “Digital Imag Processing, Addison Wesley, Reading”

10.  Hui ,T. and Binbin,W.(2009) , “Discussion and Analyze on Image Fusion Technology”, Second International Conference on Machine Vision , pp.246-250.

11.  He , D.C . Wang , L. and  Amani , M. (2004) ,“A new technique for multiresolution  image fusion ,pp.4901-4904.

12.  Hu , X . Lu , H and  Zhang ,L (2010) , “A New Type of Multi-focus Image Fusion Method Based on Curvelet Transforms”, International Conference on Electrical and Control Engineering,pp  172 -175.

13.  Jun,Y  .Zhong . ming , (2007) ,“Multi-focus image fusion method based on curvelet transform”, Opto-Electronic Engineering, vol.34, no.6, pp.67-71.

14.  Krishnamoorthy , S. and  Soman , K .P. (2010) “Implementation and Comparative Study of Image Fusion Algorithms,” International Journal of Computer Applications , Volume 9–No.2,pp.25-35.

15.  Lajevardi , S.M .and  Hussain , Z.M ,(2009), “Facial Expression Recognition Using Log-Gabor Filters and Local Binary Pattern Operators”, International  Conference  On Communication and  Power (ICCCP ) MUSCAT,pp 349-353.

16.  Li H., Maniunath B. S.. and Mitra ,S. K,(1995),“Multisensor image fusion using the wavelet Transform,”Graphical Models and Image Processing, 57(3),235-245.

17.  Li , Y . Xu,  X , Bai  , B .D. and   Zhang , Y .N .(2008), “Remote Sensing Image Fusion Based On Fast Discrete Curvelet Transform,” IEEE Trans. Geosci. Remote Sens.vol.1,pp.106-109.

18.  Mara , N.S.S . and Fookesb , C  .(2010), “Automatic Solder Joint Defect Classification using the Log-Gabor Filter” Advanced Materials Research, vol. 97-101. pp. 2940-2943.

19.  Mehrotra , H . Majhi , B and  Gupta , P.(2009), “Multi-algorithmic Iris Authentication System”, International Journal of Electrical and Computer Engineering,pp 78—82.

20.  Mallat,S.G .(1989),"A theory of multiresolution signal decomposition: the wavelet representation," IEEE Trans on Pattern Analysis and Machine Intelligence,vol.11,pp,674-693

21.  Olkkonen ,H .and Pesola ,P. (1996) ,“Gaussian Pyramid Wavelet Transform for Multiresolution Analysis of Images,” Graphical Models and Image Processing,vol.58,pp.394-398

22.  Shu Xia ,Z .and  Xun Zheng ,C .(2009) , “Medical Image Fusion Based on An Improved Wavelet Coefficient Contrast”, School of Computer Science, Shaanxi Normal University ,China,pp.1-4.

23.  Shen ,Y. Ma , J .and Ma , L .(2006) , “An Adaptive Pixel-weighted Image Fusion Algorithm Based on Local Priority for CT and MRI Images” , Instrumentation and Measurement Technology Conference Sorrento, Italy,pp.420-422.

24.  SABARI .BANU,R. (2011) ,“Medical Image Fusion by the analysis of Pixel Level Multi-sensorUsing Discrete Wavelet Transform ,” Proceedings of the National Conference on Emerging Trends in Computing Science, pp.291-297.

25.  Sun , F . Li , S .and  Yang , B. (2008), “A New Color Image Fusion Method for Visible Infrared Images”, Proceedings of  IEEE International Conference on Robotics and Biomimetics  Sanya, China , pp 2043 -2048.




Vishal Garg, Nisha Raheja

Paper Title:

Image Denoising Using Curvelet Transformation Using Log Gabour Filter 

Abstract In this we propose a new method to reduce noise in digital image. Image corrupted by Gaussian Noise is still a classical problem. In images to reduce the noise or to improve the quality of image peak signal to noise ratio (PSNR) is compared. Higher the PSNR better the quality of the image.In this paper we explain the method curvelet Transformation using log gabor filter Experimental results show that our method gives comparatively higher peak signal to noise ratio (PSNR), are much more efficient and have less visual artifacts compared to other methods.

   Image Denoising, Discrete Wavelets Curvelet, Log Gabor filter.


1.           Buades, B. Coll, and J Morel.  A non-Local Algorithm for image denoising.  IEEE International Conference on Computer Vision  and Pattern Recognition, 2005.
2.           Buades, B. Coll, and J Morel. On image denoising methods.  Technical Report 2004-15, CMLA, 2004.

3.           Mallat,  S.,  A  wavelet  tour  of  signal processing, Second addition,  Academic Press, 1998.

4.           G.Y.Chen, T.D.Bui A.Krzyzak,”image denoising using neighboring wavelet coefficient ,”Proc.of IEEE International conference on acoustics, speech and signal Processing ICASSP,  Montreal, que.,Canada,2004

5.           Unser, P.-G., Thévenaz P. And Aldroubi A., Shift-Orthogonal wavelet bases using splines, IEEE Signal Processing Letters, Vol. 3, No. 3, pp. 85-88,1996     .

6.           Donoho, D.L., Johnstone, I.M., Adapting to Wavelet shrinkage, 1995

7.           Vidakovic, B., Non-linear wavelet shrinkag with Bayes rules and  Bayes factors, J.American Statistical Association, 93, pp. 173-179, 1998 known  smoothness  via
wavelet Shrinkage, 1995.

8.           Ogden, R.T.  “Essential Wavelets for Statistical Applications and Data Analysis”, Birkhauser, Boston, 1997.

9.           Vidakovic, B., Ruggeri, F., BAMS method: theory and simulations, Sankhy, pp. 234–249, 2001

10.        “Feature Adaptive Wavelet Shrinkage for Image Denoising” Karunesh K.Gupta'and Rajiv Gupta2 IEEE - ICSCN 2007, MIT Campus, Anna University, Chennai, India. Feb. 22-24, 2007. pp.81-85.

11.        Fast non local means (NML) computation with probabilistic early termination, Ramanath vignesh, byung Tae Oh, and C.-C jay kuo, IEEE Signal Processing letters, vol. 17, NO. 3, March 2010.

12.        Image denoising based on wavelet shrinkage   using neighbor and level dependency, International Journal of Wavelet, multiresolution and Information processing , Vol. 7, No. 3,(2009) 299- 311,World scientific Publishing company.

13.        Ming Zhang and Bahadir. A new image denoising method based on the bilateral filter.This work was supported in part by the National Science foundation under grant no 05287875.1-4244-1484-9/08/$25.00©2008, ICASSP 2008

14.        Qing Xu, Hailin jiang, Reccardo scopigno, and Mateu Sbert.A new apporch for very dark video denoising and enhancement.Proceeding of 2010 IEEE 17th
international conference on image processing,September 26-29 2010,Hong kong.

15.        R.K.Kulkarni, S.Meher, Mrs.J.M.Nair. An algorithm for image denoising by Robust estimator. European journal of scientific research, ISSN 1450-216X vol.39 No3 (2010) pp.372-380




Sonia Sharma, Anjali Dua

Paper Title:

Design and Implementation of an Stegnography Algorithm Using Color Transformation

Abstract: In a computer, images are represented as arrays of values. These values represent the intensities of the three colors R(ed) G (reen) and B (lue), where a value for each of the three colors describes a pixel. Through varying the intensity of the RGB values, a finite set of colors spanning the full visible spectrum can be created. In an 8-bit gif image, therecan be 28 = 256 colors and in a 24-bit bitmap, there can be 224 = 16777216 colors. Large images are most desirable for steganography because they have the most space to hide data in. The best quality hidden image is normally produced using a 24-bit bitmap as a cover image. Each byte corresponding to one of the three colors and each three-byte value fully describes the color and luminance values of one pixel. The cons to large images are that they are cumbersome to both transfer and upload, while running a larger chance of drawing an “attacker’s” attention due to their uncommon size.  Our main focus to introduce the stegnography using color transformation.

Stegnography, Color Transformation, RGB, Data Hiding, Imperceptability.


1.        Lisa M. Marvel, Member, IEEE, Charles G. Boncelet, Jr., Member, IEEE, and Charles T. Retter, Member, IEEE, “Spread Spectrum Image Steganography”, IEEE

2.        Jessica Fridrich, Miroslav Goljan,Binghamton, Department of Electrical Engineering, Binghamton, NY,” Practical Steganalysis of Digital Images – State of the Art”, Conference , San Jose CA , ETATS-UNIS (21/01/2002).

3.        Kevin Curran, Internet Technologies Research Group, University of  Ulster ,Karen Bailey, Institute of Technology, Letter Kenny , Ireland,” An Evaluation of Image Based Steganography Methods, International Journal of Digital Evidence Fall 2003, Volume 2, Issue 2.

4.        Sabu M Thampi,Assistant Professor,Department of Computer Science & Engineering,LBS College of Engineering, Kasaragod,Kerala- 671542, S.India  ,” Information Hiding Techniques: A Tutorial Review”, ISTE-STTP on Network Security & Cryptography, LBSCE 2004.

5.        Kefa Rabah, Department of Physics, Eastern Mediterranean University, Gazimagusa, North Cyprus, Turkey,” Steganography-The Art of Hiding Data”, Information Technology Journal 3 (3): 245-269, 2004,ISSN 1682-6027.

6.        Mantiuk,R.Myszkowski,Seidel,H.-P.MPI Informatik, Saarbrucken, Germany,“Visible difference predicator for high dynamic range images “, IEEE International Conference on Systems, Man and Cybernetics , Oct. 2004, ISSN: 1062-922X.

7.        C. A. Bouman,” The Visual Perception of Images” Digital Color Imaging    magazine,April, 2005.

8.        H.-C. Wu, N.-I. Wu, C.-S. Tsai and M.-S. Hwang,” Image steganographic scheme based on pixel-value differencing and LSB replacement methods”, IEEE Proc.-Vis. Image Signal Process., Vol. 152, No. 5, October 2005.

9.        Ching-Yu Yang, Department of Computer Science and Information Engineering,National Penghu University Penghu, Taiwan,” Color Image Steganography based on Module Substitutions”, Third International Conference on International Information Hiding and Multimedia Signal Processing Year of Publication: 2007 ISBN:0-7695-2994-1.

10.     S .K. Moon , R.S. Kawitkar,PICT, Pune and SCOE, Pune,INDIA,” Data Security using Data Hiding”, International Conference on Computational Intelligence and Multimedia Applications 2007.

11.     Jae-Gil Yu1, Eun-Joon Yoon2, Sang-Ho Shin1 andKee-Young Yoo, Dept. of Computer Engineering, Kyungpook National University Daegu, Korea,” A New Image Steganography Based on 2k Correction and Edge-Detection”, Fifth International Conference on Information Technology: New Generations 978-0-7695-3099-4/08 © April 2008 IEEE.

12.     Junhui He, Shaohua Tang and TingtingWu,School of Computer Science and Engineering,South China University of Technology,University Town, Guangzhou 510006, China2008,” An Adaptive Image Steganography Based on Depth-varying Embedding”, Congress on Image and Signal Processing, Steganographic technique is a means of covert communication.Volume 5, Issue , 27-30 May 2008 Page(s):660 – 663.




Shruti Bangre, Alka Jaiswal

Paper Title:

SQL Injection Detection and Prevention Using Input Filter Technique

Abstract:  SQL injection attacks, a class of injection flaw in which specially crafted input strings leads to illegal queries to databases, are one of the topmost threats to web applications. A number of research prototypes and commercial products that maintain the queries structure in web applications have been developed. But these techniques either fail to address the full scope of the problem or have limitations. Based on our observation that the injected string in a SQL injection attack is interpreted differently on different databases, in this paper, we propose a novel and effective solution to solve this problem. It has been proposed to detect various types of SQLIA. This method checks the attribute value for single quote, double dash and space provided by the user through the input fields. When attacker is making SQL injection he should probably use a space, single quotes or double dashes in his input. Depending on the no of space, double dash and single quote the count value of the input field (having default count as1) will get increased by 1 respectively. The fixed count value and the dynamically generated count value of the input parameters are then compared. If both the count values are same, there is no SQLIA and if they vary that means some SQL code has been injected through the input fields. Finally such attempt will be recorded separately and will be blocked to access the database.

  SQLIA, attribute, etc


1.           The Open Web Application Security Project, "OWASP TOP 10 Project" .
2.           PHP, magic quotes,

3.           Apache Struts project, Struts.

4.           C. Gould, Z. Su, P. Devanbu, “  JDBC Checker: A Static       Analysis Tool for SQL/JDBC Applications”  , In Proceedings of the 26th International Conference on Software Engineering (ICSE), pp. 697-698, 2004.

5.           G Wassermann, Z. Su, “  An Analysis Framework for Security in Web Applications”  , In Proceedings of the FSE Workshop on Specification and Verification of Component-Based Systems(SAVCBS), pp. 70-78, 2004.

6.           Thomas. S, Williams. L, "Using Automated Fix Generation ot Secure SQL Statements", In Proceeding of the 29th international Conference on Software Engineering Workshops (ICSEW. IEEE Computer Society), pp. 54, 2007

7.           Paros.,

8.           Kosuga. Y, Kernel. K, Hanaoka. M, Hishiyama. M, Takahama. Yu, “  Sania: Syntactic and Semantic Analysis for Automated Testing against SQL Injection”  , In Proceedings of the Computer Security Applications Conference 2007, pp. 107-117, 2007.

9.           Yonghee Shin, "Improving the Identification of Actual Input Manipulation Vulnerabilities", 14th ACM SIGSOFT Symposium on Foundations of Software Engineering ACM, 2006.

10.        Z. Su, G. Wassermann, “  The Essence of  Command Injection Attacks in Web Applications”  , In Conference Record of the 33rd ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages, pp. 372-382, 2006.

11.        Halfond W. G, Orso. A, "AMNESIA: Analysis and Monitoring for NEutralizing SQL-Injection Attacks", In Proceedings of the 20th IEEE/ACM international Conference on Automated Software Engineering, pp. 174-183, 2005.

12.        Buehrer. G, Weide. B. W, Sivilotti. P A, "Using Parse     Tree Validation to Prevent SQL Injection Attacks", In Proceedings of the 5th international Workshop on Software Engineering and Middleware, pp. 105-113, 2005.

13.        Wei. K, Muthuprasanna. M, Kothari. S, "Preventing SQL injection attacks in stored procedures", Software Engineering Conference 2006. Australian, pp. 18-21,

14.        S. Boyd, A. Keromytis, "SQLrand: Preventing SQL injection attacks", Applied Cryptography and Network Security LNCS, Volume 3089, pp. 292-302, 2004.

15.        Jae-Chul Park, Bong-Nam Noh, "SQL Injection Attack Detection: Profiling of Web Application Parameter Using the Sequence Pairwise Alignment", Information Security Applications LNCS, Volume 4298, pp. 74-82, 2007.

16.        F. Valeur, D. Mutz, G. Vigna, "A Learning-Based Approach to the Detection of SQL Attacks", In Proceedings of the Conference on Detection of Intrusions and Malware and Vulnerability Assessment, pp 123-140, 2005.

17.        Huang. Y, Huang. S, Lin. T, Tasi. C, "Web application security assessment by fault injection and behavior monitoring", In Proceedings of the 12th international Conference on World Wide Web, pp 148-159, 2003.

18.        GotoCode, .

19.        W. G. Halfond, J. Viegas, A. Orso, "A Classification of SQL-Injection Attacks and Countermeasures", In proceeding on International Symposium on Secure Software Engineering Raleigh, NC, USA, pp. 65-81, 2006.




Pankita A Mehta, Vivek Pandya

Paper Title:

Impacts of DG on Distribution Losses

Abstract:   This paper shows the results obtained in the analysis of the impact of distributed generation (DG) on distribution losses. The main objective has been to determine if DG whether increments or decrements distribution losses, based on the penetration level and dispersion of DG and on the different DG technologies. Different scenarios with several penetration levels and dispersion of DG have been studied. The special characteristics of different DG technologies have been taken into account. The considered technologies are: combined heat and power (CHP), wind turbines, photovoltaics and some theoretical ones. Real radial distribution feeders have been used.

   Distributed generation (DG), Distribution, Losses.


1.        Power System Operation. Preliminary Report 2001." Red Eléctrica de España, 2001.
2.        P. P. Barker and R. W. de Mello, "Determining the Impact of Distributed Generation on Power Systems: Part 1 – Radial Distribution Systems", 2000 IEEE Power Engineering Society Summer Meeting, Seattle, Washington, 2000, pp. 1645 1656.

3.        Embedded Generation. London, UK, The Institution of Electrical Engineers, 2000.

4.        V. H. Méndez, J. Rivier and T. Gómez, "Tratamiento Regulatorio de las Pérdidas en el Mercado Eléctrico Español", 7as Jornadas Hispano-Lusas de Ingeniería Eléctrica, Madrid, 2001, pp. 91-96.

5.        "Allocation of losses in distribution systems with embedded generation", J. Mutale, G. Strbac, S. Curcic and N. Jenkins, IEE Proceedings. Generation, Transmission and Distribution, Vol. 147, Nr. 1, January 2000, pp. 7-14.

6.        "Royal Decree 1164/2001, dated October 26th, setting access tariff to transmission and distribution networks", Ministry of Economy, Oficial State Journal, 2001, pp. 40618-40629.

7.        G. Jóos, B. T. Ooi, D. McGillis, F. D. Galiana and R. Marceau, "The Potential of Distributed Generation to Provide Ancillary Services", 2000 IEEE Power Engineering Society Summer Meeting, Seattle, Washington, 2000, pp. 1762-1767.




Nikhil Dalshania, Anand Bora, Aditya Bhongle

Paper Title:

Reversible Watermarking: A comparative Study

Abstract: Considering the age of reversible watermarking which is just a decade to count, it has fetched enormous attention of researchers to boast of. Due to many researches in this field, it has become very difficult to judge an algorithm for a specific application. So a definite need arises to compare these algorithms on some criteria. In this paper, we present a comprehensive and competitive study of three basic algorithms which are reversible watermarking using data compression, Tian’s difference expansion and histogram bin shifting. We have compared these algorithms based on criteria like PSNR, embedding capacity and processing time.

ReversibleWatermarking,Compression, difference expansion, histogram bin shifting, PSNR, embedding capacity, processing time


1.        J. Tian, “Reversible data embedding using a difference expansion,” IEEE Transactions on Circuits Systems and Video Technology, vol. 13, no. 8, pp. 890–896, Aug. 2003.
2.        J. Tian, “Wavelet-based reversible watermarking for authentication,” in Proceedings of SPIE Sec. and Watermarking of Multimedia Cont. IV, vol. 4675, Jan. 2002.

3.        Ni, Z., Y.Q. Shi, N. Ansari and W. Su, “Reversible data hiding”, IEEE Trans. Circ. Syst. Video Technology, 16:354-362, 2006.

4.        Guorong Xuan   Jiang Zhu   Jidong Chen   Shi, Y.Q.   Zhicheng Ni   Wei Su, “Distortionless data hiding based on integer wavelet transform”, Department of Computer Science, Tongji University, Shanghai, Dec 2002.

5.        C. D. Vleeschouwer, J. E. Delaigle, and B. Macq, “Circular interpretation of histogram for reversible watermarking”, in Proceedings of the IEEE 4th Workshop on Multimedia Signal Processing, pp. 345–350, France, Oct. 2001.




P.Kannan, K.Balamurugan, K.Thirunaavukkarasu

Paper Title:

Reducing the Particle Fracture in Dissimilar Friction Welds by Introducing Silver Interlayer 

Abstract:  The present work discusses about the introduction of silver interlayer in dissimilar friction welding process. The characteristics of silver interlayer influenced friction weld are compared with the silver free dissimilar friction welding process. Particle fracture occurs commonly in welding process. It leads to poor quality of welds and decreases the strength of the weld. The introduction of silver interlayer reduces the particle fracture. Hence, the friction welding process with silver interlayer produces more efficient welds.

  Dissimilar Friction Welding, Particle fracture, Silver interlayer


1.        Alpas, A.T., and Zhang, J., 1992, “Effect of sic particulate  reinforcement on the dry sliding wear of aluminium-silicon alloys (A356)”, wear 155: 83-104.
2.        Zhao, D., Tuler, F.R., and Lloyd, D.J., 1994, “Fracture at elevated temperatures of a particle reinforced composite”, Acta Metallurgica Materialia 42 (7): 2525-2533.

3.        Dunkerton, S.B., 1982, report 201/1982, “The effect of interlayers on dissimilar friction weld properties”, TWI, Abington Hall, Cambridge.

4.        Dunkerton, S.B., 1982, report 229/1982, “The effect of interlayers on dissimilar friction welds properties” TWI, Abington Hall, Cambridge.

5.        Lewis, C.A., and Withers, P.J., 1995, “Weibull modelling of particle cracking in metal matrix composites”, Acta Metallurgica Materialia 43 (10): 3685 – 3699.




Ravi Prakash Shukla, Mukesh Kumar, A.K. Jaiswal, Rohini Saxena

Paper Title:

Performance Analysis of Dispersion in Optical Communication link Using Different Dispersion Compensation Fiber (DCF) Models

Abstract:   Fiber-optic dispersion   and   its effect   on   optical transmission system are analyzed. The most commonly used dispersion compensation fiber (DCF) technology is studied in this    article. Three schemes (pre-compensation, post­ compensation, mix-compensation of dispersion compensation) of dispersion   compensation   with   DCF   are   proposed.  In  this  study,  we  propose  three  DCF  compensation scheme,  pre-compensation,  under-compensation  and mix compensation  scheme.  Simulation studies show that mix compensation scheme is the best. It can greatly reduce the influences   of   the   fiber   nonlinearity   and   increase   the transmission distance greatly. The simulation model of the WDM based on the Optisystem is presented according to the above principle.  The simulation  results  such  as  Q  factor  and  BER  are  given  and  deeply  analyzed. It is found that mix- compensation performance is the best. And the input fiber power is taken about 16 dB, the corresponding BER performance is better.

   dispersion compensation, optical communication dispersion compensation fiber (DCF) Model,    BER, Q-factor


1.     Mochida Y, Yamaguchi N, Ishikawa G, "Technology-oriented review and vision of 40Gb/s-based optical transport Networks", Journal of light-wave technology.PP. 2272-228,12002,20(12)
2.     Zhang Hongb in, Q iu Kun, "Emulation of characteristics of optical fiber transmission for a 10Gb/s single channel situation," acta photonica sinica 2001 vol.30 No.6 715-720

3.     Omae T, "Universal conditions for estimating the nonlinear refractive index n2 of dispersion com- pensating fibers by the CW- 43 SPM method", IEEE Photon. Technol. Lett., Vol 13. No.6, pp. 571-573, Nov, 2001.

4.     Mohammad. Amin. Dallaali, "Malin Premaratne Power and dispersion constrained optimization of optical links with unequally spaced repeater modules", Optical Fiber Technology, Vol 13, No 4, pp.309-317, October. 2007.

5.     Zou X Y, Hayee M I, H wang S M, et al. Limitations in 10 GB/s WDM optical-fiber transmission when using a variety of fiber types to manage dispersion and nonlinearities [J]. Light wave Technol., PP: 1144-1152, June, 1996

6.     WuQiang, Yu Chong Xiu, "Analysis on dispersion compensation with DCF", semiconductor optoelectronics,Vol.24 No.3 pp.186- 196.June 2003

7.     Zhaohuaigang, "study on dispersion compensation in optical transmission system", study p n optical communications, Vol.3, No.141, 2007

8.     Wangchen, Raomin, "the performance of the DCF Transmission system", Journal of applied sciences, Vol.21, No.2,pp.177-181,June 2003

9.     BU CHAL IF, LANNES. Fast eye monitor for 10G/bs and its application for optical PMD compensation [Z]. Optical Society of America, 2000.

10.  Killy R I, Thiele H J, Mikhailov v, ea al. Reduction of intrachannel nonlinear distortion in 40-Gb/s based WDM transmission over standard fiber [J]. IEEE Photonics Technology Letters, 2000, 12(12): 1642-1626

11.  Eggleton B 1. Dynamic dispersion, compensation devices for high speed transmission systems. Optical Fiber communication conference and exhibit, 2001(3): WHlII-WH1I3

12.  Djafar K. Mynbaev Lowell L. Scheiner, Fiber-optic communications technology. Beijing: Science publishing company, 2002

13.  Jianjun Yu, Bojun Yang,"Dispersion-allacated soliton technology with long amplifier spacing and long distance," IEEEphoton technol lett, vol 9, pp. 952-954,No.7, 1997:

14.  ZhouZhiQiang, TangYuLiang, "Optimum schemes of dispersion compensation transmission systems using dispersion compensation fibers”, laser technology, VoI.24, No.5, pp.265-269 Oct.200




Vishal B. Langote, D. S. Chaudhari     

Paper Title:

Segmentation Using Outlier Based Adaptive Thresholding

Abstract:    Image segmentation plays an important role in image analysis as a frequent pre-processing step, which divides the image into set of different segments. Thresholding is an easy yet efficient method for image segmentation, while dividing different objects with distinct gray levels. Finding an effective threshold is especially complicated task in the segmentation. In this paper, for efficient threshold selection fuzzy methodology used which produces better segmentation results than other methodologies. It was observed that at different background intensity levels favourable results were obtained.

    Image segmentation, thresholding, fuzzy methodology


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2.        Verma D. and Meila M., ‘A Comparison of Spectral Clustering Algorithms’, Ph. D. Thesis, University of  Washington Technical Report, 2001.

3.        Shi J. and Malik J., ‘Normalized Cuts and Image Segmentation’, IEEE Transactions on Pattern Analysis and Machine Learning, 888-905, 2000.

4.        Ng Y., Jordan M. I. and Weiss Y., ‘On Spectral Clustering: Analysis and An Algorithm’, NIPS, 849-856, 2002.

5.        Kannan R., Vempala S. and Vetta A., ‘On Clustering - Good, Bad and Spectral’, FOCS, 367-37, 2007.

6.        Meila M. and Shi J., ‘Learning Segmentation By Random Walks’, NIPS, 873-879,2000




Rashmi Mishra, Baibaswata Mohapatra, Nitin Naiyar

Paper Title:

Effect of Cyclic Prefix on OFDM System

Abstract:  Orthogonal Frequency Division Multiplexing (OFDM), because of its resistance to multipath fading, has attracted increasing interest in recent years as a suitable modulation scheme for commercial high-speed broadband wireless communication systems. OFDM can provide large data rates. Orthogonal frequency division multiplexing (OFDM) is one of the Multi-Carrier Modulation (MCM) techniques that transmit signals through multiple carriers. These carriers (subcarriers) have different frequencies and they are orthogonal to each other. There are different parameters which alters the performance of OFDM system. This thesis analyzes OFDM system and the effect of cyclic prefix and length of cyclic prefix on OFDM system. Besides, compare the performance of the system with and without cyclic prefix and with different RSF(Repeated Symbol Fraction).BER performance of the OFDM system is carried out with emphasis on the cyclic prefix and RSF. The simulation results show how a tradeoff is needed between reduction in multi-path effects and Transmission efficiency.

     BER, RSF, ISI


1.        Jianwei  Huang, Vijay  G. Subramanian, Rajeev  Agrawal, and  Randall  Berry,    “Joint  Scheduling  and  Resource  Allocation  in Uplink  OFDM  Systems   for Broadband  Wireless  Access  Networks “ , IEEE  Journal  2009.
2.        Ian C. Wong and Brian L. Evans “Optimal Resource Allocation in the OFDMA  Downlink with Imperfect Channel Knowledge “

3.         “Time-Varying Carrier Offsets in Mobile OFDM “ ,Scott L. Talbot, and Behrouz Farhang-Boroujeny, S.M. Alamouti, "A simple transmit diversity technique for wireless communications," IEEE Journal on Selected Areas in Communications, Vol. 16, No. 8, Oct. 1998, pp. 1451-1458.

4.        Michele Morelli, Luca Sanguinettiand H. Vincent Poor, “A Robust Ranging Scheme for OFDMA-Based Networks”

5.        Jianghua Wei, Yuan Liu, “Carrier Frequency Offset Estimation Using PN Sequence Iteration in OFDM Systems”

6.        H. Yin and H. Liu, “An efficient multiuser loading algorithm for OFDM based broadband wireless systems,” in Proc. IEEE Globecom, vol. 1, pp.  103–107, Dec. 2000.

7.        Poonam Singh, Saswat Chakrabarti, “A Bandwidth Efficient Multiple Access  Scheme  using MSE-OFDM” , “2010 5th International Symposium on Wireless Pervasive Computing (ISWPC)”

8.        Y.Emre and C. Chakrabarti School of Electrical, “Energy-Aware Adaptive OFDM Systems”, “Acoustics Speech and Signal Processing(ICASSP)” 2010,IEEE Conference on 14-19 march 2010”

9.         F Prianka, M A Matin, A Z Saleh, M A Mohd Ali , “BER Analysis of OFDM with Improved ICI Self- Cancellation Scheme”, “ICMMT 2010 Proceedings”

10.     Jianghua Wei Yuan Liu, “Carrier Frequency Offset Estimation Using PN Sequence  Iteration   in OFDM Systems”, “2010 Second International




Bhumika, Vivek Sharma

Paper Title:

Use of Honeypots to Increase Awareness regarding Network Security

Abstract: Honeypots are closely monitored decoys that are employed in a network to study the trail of hackers and to alert network administrators of a possible intrusion. Honeypots are a relatively new technique for achieving network security. While other techniques for securing networks e.g. IDS, Firewall etc are made to keep the attackers out, for the first time in the history of network security there is a technique which intends to keep the attackers ‘in’ thus allowing the researchers to gain more insight into the workings of an attacker. With the rapid development of Internet and the advent of the network socialization, network security has been more concerned in the technologies. Among the main network security technologies are firewall, intrusion detection techniques, access control, etc., which are based on the known facts and attack mode and adopt passive defensive approach. The current commonly-used intrusion detection technology of passive defense, based on model matching, needs to update the intrusion detection rule library, otherwise omission of the latest attack will occur in the process. To eliminate the shortcomings of detection system being unable to update feature library, the users should adopt a proactive defense honeypot technology to automatically update its att ack signature to reduce the miss probability of int rusion detection system. Honeypot is a newly-developing area of network security. It lures the intruder to attack it by constructing a system with security vulnerability and then record the intrusion methods, motives, and tools of the intruder in the intruding process. By analyzing the intrusion information, we can get the content of the newest techniques of the intruder and find the system vulnerability. And the virtual honeypot can prevent the host computer from attacking.

   Honeypots, Honeyd, Honeynets, IDS, Network Security


1.        Lance Spitzner, Honeypots: Tracking Hackers. Addison Wesley, September 13,2002
2.        Eric Peter et al., A Practical Guide to Honeypots.˜jain/cse571-09/ftp/honey/index.html, Fetched 20/06/2011.

3.        RyanTalabis,Honeypots101:RisksandDisadvantages. 2007, Fetched 21/06/2011

4.        HoneynetProject.KnowYourEnemy:Honeynets.

5.        Neils Provos, A Virtual Honeypot Framework. SSYM’04 Proceedings of the 13th conference on USENIX Security Symposium, Volume 13, 2004

6.        Neils Provos,Thorsten Holz, Virtual Honeypots: From Botnet Tracking to Intrusion Detection. Addison Wesley Professional, July 16, 2007

7.        RyanTalabis,Honeypots101:What’sinitforme?., 2007, Fetched 21/06/2011




Pushpa .R. Suri, Mahak

Paper Title:

Image Segmentation With Modified K-Means Clustering Method

Abstract:  Image segmentation is used to recognizing some objects or something that is more meaningful and easier to analyze In this paper we are focus on the the K means clustering  for segmentation of the image. K-means clustering is the most widely used clustering algorithm to position the radial basis function (RBF)  centres. Its simplicity and ability to perform on-line clustering may inspire this choice. However, k-means clustering algorithm can be sensitive to the initial centres and the search for the optimum centre locations may result in poor local minima. Many attempts have been made to minimise these problems In this paper two updating rules were suggested as alternatives or improvements to the standard adaptive k-means clustering algorithm. The updating methods are proposed to give better overall RBF network performance rather than good clustering performance. However, there is a strong correlation between good clustering and the performance of the RBF network. The sensitivity of the RBF network to the centre locations will also be studied.Thus we will test the modified K means different set of images. 

    Image segmentation, anisotropic diffusion, smoothing filters, contrast enchancement.


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Bavanish. B, Thyagarajan. K

Paper Title:

Aerodynamic Performance Analysis of A Flat plate Hawt

Abstract:   Composite material design has almost become routine due to the palpable advantages like considerable weight saving and opportunity to adapt the structure to the given set of design requirements. Pollution free  electricity generation, low operation and maintenance costs, quick installation, commissioning capability, free renewable energy are the added advantages of wind electric generators. This paper also addresses the design parameters of composite wind turbine blades. The key factors for proper utilization of wind power and designing wind energy conversion systems are the performance characteristics of available wind energy conversion system and the availability of wind resources. The performance characteristics depend on the aerodynamic, mechanical and electrical subsystems whereas the wind resources depend on the weather conditions of the region. The goal in designing a wind turbine is to attain highest possible output under specified atmospheric conditions and profit from better structural model using suitable composite material and optimization techniques in manufacturing. Determining optimal shape of the blade and optimal composite material is complex one, as the mathematical description of aerodynamic load is complex and it should satisfy both the constraints and objectives of the problem. This paper incorporates the performance and design aspects, siting requirements, classification of wind electric conversion systems, choice of rotors and generators, environmental aspects and optimization concepts of wind turbine rotors.

     Aerodynamic, Composite material, Wind-Electric Conversion Systems, Optimization


1.        Ozgener. A small wind turbine system (SWTS) application and its performance analysis. Energy Conservation and Management, 2006; 47: 1326 – 1337
2.        R.C. Bansal, T.S. Bhatti, D.P. Kothari. On some of the design aspects of wind energy conversion systems. Energy Conversion and Management, 2002; 43: 2175 – 2187

3.        F. Wang, L. Bai, J. Fletcher, J. Whiteford, D. Cullen. The methodology for aerodynamic study on a small domestic wind turbine with scoop. Journal of Wind Energy and Industrial Aerodynamics, 2007; 1 – 24

4.        H. D. Ammari, A. Al-Maaitah. Assessment of wind – generation potentially in Jordan using the site effectiveness approach. Energy, 2003; 28: 1579 – 1592

5.        Onder Ozgener. A review of blade structures of SWTSs in the Aegean region and performance analysis. Renewable & Sustainable Energy Reviews 2005; 9: 85 – 99

6.        V.H. Morcos. Aerodynamic performance analysis of horizontal axis wind turbines. Renewable Energy,1994: Vol. 4., No. 5, PP 505 – 518

7.        Roger Scherer. Blade design aspects. Renewable Energy, 1999; 16: 1272 – 1277

8.        G. K. Nathan. A simplified design method and wind – tunnel study of horizontal – axis windmills. Journal of Wind Energy and Industrial Aerodynamics, 1980; 6: 189 – 205

9.        M. Jureczko, M. Pawlak, A. Mezyk. Optimisation of wind turbine blades. Journal of Materials Processing Technology, 2005; 167: 463 – 471

10.     P. Fuglsang, H.A. Madsen. Optimization method for wind turbine rotors. Journal of Wind Engineering and Industrial Aerodynamics 1999; 80: 191 – 206

11.     K.L. Edwards, C. Davenport. Materials for rotationally dynamic components: rationale for higher performance rotor – blade design. Materials and Design, 2006; 27: 31 – 35




Mumtaz Ahmad Khan, Preeti Bhatia, Mohd. Sadiq

Paper Title:

BBTool: A Tool to Generate the Test Cases

Abstract:    Software testing (ST) is an important phase of a software development life cycle (SDLC). During ST, software are verified and validated by the software testers to check whether it meets the stakeholder’s expectations or not. It is time consuming process to check each and every condition of the software during ST, if we check it manually. Therefore, to reduce the time of software testing, an effort has been made to reduce the time of testing. In this paper, we have proposed BBTool, i.e. Black Box Tool, to generate the test cases. Straight line problem is employed to show the validity of BBTool.

   Software, Software Testing, Black Box Testing, Boundary Value Analysis, and Robustness Technique


1.       Pressman, Roger S. software Engineering .New Delhi: Prentice Hall of India.
2.       Ghezzi, Carlo. Fundamentals of Software Engineering. New Delhi Prentice Hall of India 

3.       Mali, Rajib, Fundamental of Software Engineering. New Delhi Prentice Hall of India

4.       Summerville, Ian Software Engineering New Delhi: addision Wesley

5.       B. Beizer, Black Box Testing. New York: John Wiley & Sons, Inc., 1995.

6.       M. Dowson. The Ariane 5 software failure. SIGSOFT Software Engg. Notes, 22(2):84, 1997

7.       IEEE. Standard glossary of software engineering terminology. IEEE Std 610.12-1990, 10 Dec 1990

8.       Boehm, Barry & Basili, Victor R. “Software Defect Reduction Top 10 List.” IEEE Computer 34, 1 (January 1991): 135-137.

9.       IEEE, "IEEE Standard 610.12-1990, IEEE Standard Glossary of Software Engineering Terminology," 1990.

10.    Mohd. Sadiq, Mohd. Shahid, “Elicitation and Prioritization of Software Requirements”, International Journal of Recent Trends in Engineering, Finland                                                                      

11.    Mohd. Sadiq, Mohd. Shahid, Shabbir Ahmed, “Adding Threat during Software Requirements Elicitation and Prioritization”, International Journal of Computer Application.                                          

12.    Mohd. Sadiq, Javed Ahmad, Abdul Rahman, R. Suman and Shweta Khandelwal, “More on Adding Threat during Software Requirements Elicitation and Prioritization”, IACSIT International Journal of Engineering and Technology, pp.286-290, Vol.2, No.3, June 2010, ISSN: 1793-8236. 

13.    Eero Uusitalo, Marko Komssi, Marko Kauppinen, Alan M. Davis, “ Linking Requirements and Testing in Practice”, 16th IEEE International Requirements Engineering Conference, 2008, pp.265-270

14.    Ian Sommervilla, “Integrated Requirements Engineering: A Tutorial”, IEEE Software, 2005.

15.    Mumtaz Ahmed Khan, Mohd. Sadiq, “Analysis of Black Box Software Testing Techniques: A Case Study”, IEEE International Conference and Workshop on Current Trends in Information Technology, pp.1-5, December, 2011, Dubai, UAE.




Anand Bora, Nikhil Dalshania, Aditya Bhongle

Paper Title:

Competitive Analysis of Digital Image Watermarking Techniques

Abstract: - :- Digital Image Watermarking, in recent times has seen a huge surge of professional work due to the skyrocketing usage of digital media. In this paper we present a competitive survey of existing watermarking techniques. This paper surveys the features and concepts pertaining to the two popular watermarking algorithm types and analyzes them to evaluate with metrics such as Time complexity, PSNR values and similarity measure of watermarks based on implementation i.e.  A) Spatial based techniques (under which we analyzes LSB modification, correlation based and CDMA based techniques) and b) Transform based techniques (DCT and DWT based techniques). We have also studied the effects of different types of noises on each method.

Image Watermarking,  lsb, correlation, cdma, dct, dwt


1.       Cox IJ, Miller ML & Bloom, JA 2002, “Digital Watermarking andSteganography”, Morgan Kaufmann Publisher, San Francisco, CA, USA. Gonzalez and Woods, “Digital Image Processing”, PHI ,Second Edition, 2005.
2.       Arthur Weeks Jr., “Fundamentals of Digital Image Processing”, Eastern Economy Edittion, 2005.

3.       T. Ramashri and S. Narayana Reddy, “Robust Image Watermarking Algorithm Using Decimal Sequences”, International Journal of WirelessNetworks and Communications Volume 1, Number 1, pp. 1–8, 2009.

4.       Suhad Hajjara, Moussa Abdallah & Amjad Hudaib,  “Digital Image Watermarking Using Localized Biorthogonal Wavelets”, European Journal of Scientific Research ISSN 1450-216X Vol.26 No.4 , pp.594-608, 2009.

5.       T. Furon_ and P. Duhamel, “An Asymmetric Watermarking Method”, IEEE Transaction On Signal Processing, Vol. 51, No. 4, April 2003

6.       Vidyasagar M. Potdar, Song Han, Elizabeth Chang, “A Survey of Digital Image Watermarking Techniques”, Proc. IEEE Int. Conf. On IndustrialInformatics (INDIN), 2005.

7.       MahaSharkas, Dahlia ElShafie, and NadderHamdy,” A Dual Digital-Image Watermarking Technique”, World Academy of Science, Engineering and Technology , 2005

8.       Mei Jiansheng, Li Sukang1 and Tan Xiaomei, “A Digital Watermarking Algorithm Based On DCT and DWT”, Proceedings of the InternationalSymposium on Web Information Systems and Applications, 2009

9.       Peining Tao and Ahmet M. Eskicioglu, “A robust multiple watermarking scheme in the Discrete Wavelet Transform domain”, Internet multimedia management systems V  (Philadelphia PA, 26-28 October 2004)

10.    Nitesh Dixit and AnkushAgarwal, “Wavelets based Digital Watermarking”, March 2004.

11.    Ingemar J. Cox and Matt L. Miller, “Electronic Watermarking: The First 50 Years”, Published in the Proceedings of the IEEE 2001 Int. Workshop on MultiMedia Signal Processing, 2001.

12.    Van Schyndel, R.J., Tirkel, A.Z., Osborne, A.F., “A digital watermark,” Proc.IEEE Int. Conf. Image Processing, vol. 2, 86-90, 1994

13.    PeiningTaoa and Ahmet M. Eskicioglub, “A robust multiple watermarking scheme in the Discrete Wavelet Transform domain”, The Graduate Center, The City University of New York, 365 Fifth Avenue, New York, NY 10016 Department of Computer and Information Science, Brooklyn College, The City University of New York, 2900 Bedford Avenue, Brooklyn, NY 11210.

14.    Kamran Hameed, AdeelMumtaz, and S.AM. Gilani, “Digital Image Watermarking in the Wavelet Transform Domain”, World Academy of Science,EngineeringandTechnology,13,2006

15.    M. S. Sutaone , M.V. Khandare “Image Based Steganography Using LSB Insertion Technique”, IEEE WMMN pp. 146-151, January 2008.

16.    Gerhard C. Langelaar, IwanSetyawan, and Reginald L. Lagendijk      “Watermarking Digital Image and Video data”, in Proc. IEEE Int. Conf. A State-of-the-Art Overview, September 2000.

17.    DeepaKundur and DimitriosHatzinakos,”Digital Watermarking Using Multiresolution Wavelet Decomposition”, In Proc. IEEE Int. Conf., 1998






R. Mohan, N. Partheeban

Paper Title:

Power Generation Using Bio-Mass Power Plant

Abstract: Technologies to produce electricity from biomass through combustion are state of the art. There are many applications with different power generation principle (steam turbine, steam screw type engines, ORC turbines) in operation. Caused by the logistic frame conditions of biomass production, storage and transportation as well as the possibility to use the thermal energy for community heating, decentralized power plants are the most economically solutions. Similar statuses have the bio-chemical conversion technologies (e.g. biogas technologies) or the physical-chemical conversion technologies like the production of plant oils and the power generation of the liquid/gaseous fuels in internal combustion engines. All these technologies are highly developed and reached readiness for marketing in Europe as well as in Asian countries.

  Renewable Energy, Biomass, Conversion Technologies, Combined Heat & Power Generation


1.        Ang, A (1997), Present Status of Biomass Energy Technologies in Malaysia, Presented in Regional Consultation on Modern Biomass Energy Technologies, Regional Wood Energy Development Programme, FAO, Kuala Lumpur, Malaysia.
2.        Baofen, L and Xiangjun, Y (1997), Development and Utilization of Biomass in China, Presented in Regional Consultation on Modern Biomass Energy Technologies, Regional Wood Energy Development Programme, FAO, Kuala Lumpur, Malaysia.

3.        Bawagan, P.V and Semana, J.A (1980), Dendrothermal Power Plants: Prospects andProblems, Paper presented at seminar-workshop on Forestry and the Energy Crisis, 26-28November, Forest Research Institute Central Office, Los Banos, Philippines

4.        Chaturvedi P. (1993). Bioenergy Production and Utilization in India- Expert Consultation on Biofuels for Sustainable Development; Their Potential as Suitable to Fossil Fuels and CO2. Emission Reduction, Food and Agriculture Organization, Rome.

5.        CMIE (1996), India's Energy Sector. Centre for Monitoring Indian Economy, Bombay

6.        Dixon R K, Brown S, Houghton, R A, Solomon A M, Trexler M C and Wisniewski J (1994), Carbon Pools and Flix of Global Ecosystems. Science. 263. 185-190..

7.        Durst, P.B (1986), Dendrothermal Dream Threatened in the Philippines, Journal of Forestry, Vol 84, No. 8.

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10.     FAO (1986), FAO Yearbook of Forest Products 1984, Food and Agricultural Organisation of the Untied Nations, Rome.

11.     FAO (1996), FAO Yearbook of Forest Products 1994, Food and Agricultural Organisation of the Untied Nations, Rome.

12.     FAO (1997), Review of Wood Energy Data in RWEDP Member Countries, Field Document No. 47, Bangkok.

13.     Frisch, L.E (1993), Reliable cogeneration utilizing wood as a primary fuel, Paper Presented at the ASME Power Conference.

14.     Hillring, B (1997), Price Trends in the Swedish Wood-Fuel Market,  Biomass and Bioenergy,Vol. 12, No. 1.    




R.Mohan1, N.Partheeban2

Paper Title:

Safety Preventive Maintenance In Nuclearpower Plant

Abstract: Safety analysis of a nuclear power plant for postulated initiating events (PIEs) is an essential part of the design process, both as a regulatory requirement and also to generate performance requirement of safety system. A wide variety of computer codes have been developed in-house at Nuclear Power Corporation of India Limited (NPCIL) for safety analysis of Indian Pressurized Heavy Water Reactors (PHWRs). The applications and validation of these codes are discussed in this article. In addition to the conventional ‘deterministic’ safety analysis approaches, probabilistic safety assessment (PSA) techniques are also being applied in Indian PHWRs to gain additional insights Passing of steam trap becomes a major concern for all power plants due to high-enthalpy energy loss as well as wastage of costly DM water. On the other hand, if steam trap does not do its intended function, then it may lead to the damage of turbine and pipelines. Unfortunately, most power plants do not have a proper condition monitoring or preventive maintenance programmed for steam trap to know its healthiness.

   Nuclear Energy, Thermal Hydraulic, Stream Trap. Thermo dynamic, Radioactive Waste


1.       Bajaj S. S., “Probabilistic Safety Assessment for KAPS: An overview”, 1st National Conference on Nuclear Reactor Technology, November 25-27, 2002, Mumbai, India.
2.       Guptan Rajee, Nalini Mohan, Ghadge S. G., Bajaj S. S., “Plant Specific Risk Informed Decision Making - A Vision for Indian PHWR”, International conference on Reliability, Safety and Hazard, 2005, Mumbai, India..

3.       Rammohan H. P., Bajaj S. S.,“ATMIKA – A System Thermal hydraulic Computer Code – Model Description”, NPCIL, August1996.

4.       Rammohan H. P., Bajaj S. S., “Assessment of Station Transient Analysis Code, ATMIKA.T’”, December 1997.

5.       Pramod P., Dubey A., Rammohan H. P, Bajaj S. S., “Primary Coolant Circuit Coast down and Thermo syphon Mode Under Failure of Forced Circulation in Indian PHWR”, IAEA- TECDOC- 1149,pp 391- 400.

6.       Pramod P., Rammohan H. P., Bajaj S. S., “ Assessment of Station Transient Analysis Code ATMIKA-T against plant data for Net Load Rejection Test, 1st National Conference on Nuclear Reactor Technology, November 25-27, 2002, Mumbai, India.

7.       Pramod P., Rammohan H. P., Bajaj S. S., “Validation of Plant Transient Analysis Computer Code ATMIKA-T, 16th National Heat & Mass Transfer Conference, Kolkata, January, 2002.

8.       Pramod P., Rammohan H. P., Pahari Santanu, “Deletion of Stepback Auto Logic”, NPCIL/01500/06/M, April 2006. Singhal Mukesh, Khan T. A., Yadav S. K., Pramod P., Rammohan H. P., Bajaj S. S., “LBLOCA Analysis for at MAPS using ModifiedComputer Code ATMIKA”, 1st National Conference on Nuclear Reactor Technology,November 25-27, 2002, Mumbai,India .\

9.       Ravi M., Rammohan H. P., Bajaj S. S., “Assessment of Fuel Failure during LOCA”, 1st National Conference on Nuclear Reactor Technology, November 25-27, 2002, Mumbai, India.

10.    Sharma S. L., Banerjee S.,Rammohan H. P., Bajaj S. S.,“Postulated Initiating Events andtheir Effect on Fuel Behaviour for Water Reactors”, Metals Materials & Processes, 2006, Vol. 18, No-1, pp. 73-84.

11.    AERB Safety Guide SG/D-6,“Fuel Design for PHWR”, March2003.

12.    Kalra H., Rammohan H. P.,Malhotra P. K., “Reactor ChannelHeatup effect during postulatedaccident conditions of LOCA and unavailability of ECCS in 540 Mwe Indian PHWRs”, Paper 430, 11th International Topical Meeting on Nuclear Reactor Thermal Hydraulics (NURETH-11), October 2-6, 2005, France.

13.    Bajaj S. S., “Containment Systems for Indian PHWRs”, Invited talk at 1st National Conference on Nuclear Reactor Technology, November 25-27, 2002, Mumbai, India.