Volume-1 Issue-7

  • Version
  • Download 20
  • File Size 4.00 KB
  • File Count 1
  • Create Date August 27, 2017
  • Last Updated March 9, 2020

Volume-1 Issue-7

 Download Abstract Book

S. No

Volume-1 Issue-7, May 2013, ISSN:  2319–6378 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.



Mitrabasu, Neelam Chhillar

Paper Title:

Integrating Kano Model and Herzberg Two Factor Theory to Unveil the Third Quality Factor of Patient Satisfaction in a Multispecialty Outdoor Medical Centre

Abstract: Perception of quality by customers remains most important determinant of success of a healthcare unit, influencing consumption of service by improved compliance, better satisfaction levels and stronger bondage between healthcare team and patients. Whereas Herzberg two factor theory was designed originally to discover hygiene and motivating factors for employees, it could be used similarly to identify such factors in a customer population of an industry. Kano model to study service quality attributes considers both functional and non functional data analysis to classify attributes in four categories viz. must- be, reverse, indifferent and attractive. Present study was conducted on 243 employees of Institute of Nuclear Medicine and Allied sciences (INMAS), Delhi. Data was collected in structured questionnaire (Both functional and non functional) developed based on Kano model. Frequency analysis was done to identify Kano category of service attribute and customer satisfaction coefficient was calculated to identify hygiene or motivating factors. We concluded that it is possible to identify key determinants of quality perception using Kano model in a healthcare service unit. Also, it was concluded that service quality attributes could be categorises not only in hygiene and motivating factors but some of them are both hygiene and motivating

Healthcare, Kano model, Patient satisfaction, Service quality.


1.        Institute of Medicine. Medicare: A Strategy for Quality Assurance. Washington, D.C.: National Academy Press, 1990
2.        Parul Gupta, Dr. R.K. Srivastava. Customer Satisfaction for DesigningAttractive Qualities of Healthcare Service in India using Kano Model and Quality Function Deployment MIT International Journal of Mechanical Engineering Vol. 1 No. 2 Aug 2011,  pp 101-107

3.        Paul D. Cleary and Barbara J. McNeil. Patient Satisfaction as an Indicator of Quality Care. Vol. 25, No. 1, The Challenge of Quality (Spring 1988), pp. 25-36

4.        A Donabedian. Explorations in Quality Assessment and Monitoring, Vol. 1: The Definition of Quality and Approaches to Its Assessment ( Ann Arbor MI: Health Administration Press, 1980)

5.        Kano, N., Seraku, N., Takahashi, F. and Tsuji, S. (1984), “Attractive quality and must be quality”, Quality,Vol. 14 No. 2, pp. 39-48

6.        JoséM.M. Bloemer, Hans D.P. Kasper, The complex relationship between consumer satisfaction and brand loyalty, Journal of Economic Psychology, Volume 16, Issue 2, July 1995, Pages 311-329, ISSN 0167-4870, 10.1016/0167-4870(95)00007-B.(http://www.sciencedirect.com/science/article/pii/016748709500007B)

7.        Shahin, A. (2004). Integration of FMEA and the Kano model: An exploratory examination, International Journal of Quality & Reliability Management Vol. 21 No.7.731-746

8.        James E Bartlet, Joe W Kotrlik, Chadwick C. Higgins. Organizational Research: DeterminingAppropriate Sample Size in Survey Research. Information Technology, Learning, and Performance Journal, Vol. 19, No. 1, Spring 2001

9.        Berger, Charles; Blauth, Robert; Boger, David; Bolster, Christopher; Burchill, Gary; DuMouchel,William; Pouliot, Fred; Richter, Reinhard; Rubinoff, Allan; Shen, Diane; Timko, Mike; Walden,David. "Kano’s Methods for Understanding Customer-defined Quality", In: Center for QualityManagement Journal, Vol. 4 (Fall 1993), pp. 3 - 36.

10.     Dr. DwiSulisworo. Integrating Kano’s Model and SERVQUAL to Improve Healthcare Service Quality. Available at http:/mc.manuscriptcentral.com/rgph accessed on 11th Jan 2013

11.     Yoshio Kondo, Customer satisfaction: How can I measure it?.Total Quality Management Vol. 12, Iss. 7-8, 2001

12.     Oscar W. DeShields Jr, Ali Kara, Erdener Kaynak, (2005) "Determinants of business student satisfaction and retention in higher education: applying Herzberg's two-factor theory", International Journal of Educational Management, Vol. 19 Iss: 2, pp.128 – 139

13.     Edwin N. Torres, Sheryl Kline, (2006) "From satisfaction to delight: a model for the hotel industry", International Journal of Contemporary Hospitality Management, Vol. 18 Iss: 4, pp.290 – 301

14.     Fan, Xiaomeng, Sandra Liu, and Michael Zhu. "An Innovative Approach Examining the Asymmetrical and Nonlinear Relationship between Attribute-Level Performance and Service Outcomes." Advances in Consumer Research 36 (2009)






Y. Madhavi Reddy, P. Venkata Ramana

Paper Title:

A Survey Report of Initial Value Problem with Boundary Value Problems

Abstract: In mathematics, an initial value problem is an ordinary differential equation together with a specified value, called the initial condition, of the unknown function at a given point in the domain of the solution. In physics or other sciences, modeling a system frequently amounts to solving an initial value problem; in this context, the differential equation is an evolution equation specifying how, given initial conditions, the system will evolve with time. But In this paper specifies that various boundary conditions and boundary value problem with initial value problem.

 Boundary Condition.


1.        A. D. Polyanin and V. F. Zaitsev, Handbook of Exact Solutions for Ordinary Differential Equations (2nd edition), Chapman & Hall/CRC Press, Boca Raton, 2003. ISBN 1-58488-297-2.
2.        A. D. Polyanin, Handbook of Linear Partial Differential Equations for Engineers and Scientists, Chapman & Hall/CRC Press, Boca Raton, 2002.

3.        Coddington, Earl A. and Levinson, Norman (1955). Theory of ordinary differential equations. New York-Toronto-London: McGraw-Hill Book Company, Inc.

4.        Hirsch,MorrisW. and SmaleStephen (1974). Differential equations, dynamical systems, and linear algebra. New York-London: Academic Press.

5.        Okamura, Hirosi (1942). "Condition nécessaire et suffisante remplie par les équations différentielles ordinaires sans points de Peano". Mem. Coll. Sci. Univ. Kyoto Ser. A. (in French) 24: 21–28.

6.        Polyanin, Andrei D. and Zaitsev, Valentin F. (2003). Handbook of exact solutions for ordinary differential equations (2nd ed.). Boca Raton, FL: Chapman & Hall/CRC. ISBN 1-58488-297-2.

7.        Robinson, James C. (2001). Infinite-dimensional dynamical systems: An introduction to dissipative parabolic PDEs and the theory of global attractors. Cambridge: Cambridge University Press.ISBN 0-521-63204-8






L. Devi Priya, S. Karthik

Paper Title:

Secure Captcha Input Based Spam Prevention

Abstract: Spam is one of the principal stumbling blocks of Internet, which consistently emerge as redundant or unsolicited messages in various communication areas. For example in VoIP, spam appears as unnecessary calls generated by the computers and other auto call generating BOTs. In WEB servers like Gmail, FTP servers like Rapid Share spam appears as fake accounts creation and it sometimes lead to jam of server process due to the BOTs. We have anticipated a resolution to thwart the spam using SECURE CAPTCHA INPUT (SCI) system. CAPTCHA (Completely Automated Public Turing Test to Tell Computers and Human Apart) method aims to determine whether the call is coming from a human or a machine. A CAPTCHA is a type of challenge-response test used in computing to ensure that the response is not generated by a computer. The process usually involves one computer (a server) asking a user to complete a simple test which the computer is able to generate and grade. Because other computers are unable to solve the CAPTCHA, any user entering a correct solution is presumed to be human. Thus, it is sometimes described as a reverse Turing test, because it is administered by a machine and targeted to a human, in contrast to the standard Turing test that is typically administered by a human and targeted to a machine. CAPTCHA that is deployed here is a 3D model developed with action script that can overcome RT-MITM attack which is another milestone in the CAPTCHA security.



1.        Ahmad El Ahmad, Jeff Yan and Wai-Yin Ng “CAPTCHA Design-Color, Usability, and Security”.
2.        CAPTCHA Official Site
3.        Elie Bursztein, Matthieu Martin, John C. Mitchell, “Text-based CAPTCHA Strengths and Weaknesses”, ACM Computer and Communication security 2011.
4.        Elie Bursztein, Steven Bethard, John C. Mitchell, Dan Jurafsky, and Celine Fabry. How good are humans at solving captchas? A large scale evaluation. In Security and Privacy, 2010.

5.        Ismail Ahmedy, Marius Portmann, “Using Captchas To Mitigate The VoIP Spam Problem”, Second International Conference on Computer Research and Development 2010.

6.        Jeff Yan and Ahmad Salah El Ahmad,” Captcha Robustness: A Security Engineering Perspective”, Research feature, New Castle University.

7.        L. von Ahn, M. Blum, N. J. Hopper, and J. Langford, (2003) “Captcha: Using hard AI problems for security,” in EUROCRYPT, pp. 294–311.

8.        L. von Ahn, M. Blum, and J. Langford, “Telling Humans and Computer Apart automatically”, ACM, vol. 47, no. 2, 2004, pp. 57-60

9.        MacIntosh, R.; Vinokurov, D., (18-19 April 2005) "Detection and mitigation of spam in IP telephony networks using signaling protocol analysis," Advances in Wired and Wireless Communication”, 2005 IEEE/Sarnoff Symposium on , vol., no., pp.49-52.

10.     Robert MacIntosh and Dmitri Vinokurov, “Detection and Mitigation of Spam in IP Telephony Networks using Signaling Protocol Analysis”.

11.     Sajad Shirali-Shahreza, Ali Movaghar,” A New Anti-Spam Protocol Using CAPTCHA”, Proceedings of the 2007 IEEE International Conference on Networking, Sensing and Control, London, UK, 15-17 April 2007.

12.     S.Y. Huang, Y.K. Lee, G. Bell, and Z. Ou. A projection-based segmentation algorithm for breaking MSN and YAHOO CAPTCHAs. In Proceedings of the World Congress on Engineering, volume 1.  Citeseer, 2008.

13.     T. Converse, “CAPTCHA Generation as a Web Service,” Proc. 2nd Int’l Workshop Human Interactive Proofs”, Springer, 2005, pp. 82-96.

14.     3D Captcha






Muhammad Nawaz Tunio, Nazia Rasheed Arain, Shazia Parveen Tunio

Paper Title:

Assessment of Computer Literacy at Secondary Education Level in Rural Areas of Sindh (Pakistan)

Abstract: Efforts have been taken to some extent in public sector schools but no constant attention and continuous interest is paid to fill the digital gape. Education and ICT can be sound and significant if these kept beyond the political priorities in Pakistan. Urban areas of t Pakistan are well equipped with sound facilities and education of recognized quality but rural areas suffer from this experience. Expansion of private sector in education system has elevated the use of ICT accordingly and middle and upper class families prefer to get services from private schools for quality education of the children. This research recommends that ICT practice should be uniform in all units of Pakistan. ICT application should not be left on the sympathy of conditions as this system needs strong leadership.

ICT, Secondary Education, learning, Training.


1.        Crede, A., & Mansell, R., Knowledge societies… in a nutshell: Information technologies for sustainable development. Ottawa, Canada: IDRC, 1998.
2.        Akpore, A. S., Free expression in age of the Internet: Social and legal boundaries. Boulder: Westview Press, 1999.  

3.        Federal Republic of Nigeria (2001). Nigeria national policy for information technology (IT).  October 03, 2011 Retrieved from: http://www.uneca.org/aisi/nici/documents/it%20policy%20for%20nigeria.pdf

4.        Balanskat, A., Blamire, R., Kefala, S., A review of studies of ICT impact on schools in Europe: The ICT Impact Report: 11 December 2006, 2006.

5.        Mioduser, Nachmias, Web-Based Learning Environments (WBLE): Current State and Emerging trends., & quote, 1999.

6.        ICT capacities and capabilities in Secondary Schools in Kenya. NCST NO. 046, Ministry of Higher Education, Science and Technology and National Council for Science and Technology, 200/2010.

7.        Yelland, N., Teaching and learning with information and communication technologies (ICT) for numeracy in the early childhood and primary years of schooling. Australia: Department of Education, Training and Youth Affairs, 2001.






Reshma Banu M, Sowghandhi, Pulidindi Venugopal

Paper Title:

A Study on Charanka Solar Park and Kudankulam Nuclear Power Plant in India

Abstract: Electricity generation is the process of generating electric power from different sources of energy. Nowadays electricity is very important to run each and every appliance. So, it is a big task how to generate electricity with cheaper cost to fulfill the electricity demand of the consumers. The dependence on fossil fuels, the need for reducing the carbon emissions associated with energy use and the prospects of developing a new and innovative technology sector, make solar energy increasingly attractive, However higher cost per unit of electricity is the major drawback that have held back this energy source. In India, Nuclear power holds the fourth position among the different resources of electricity, presently there are 19 nuclear power plants in India which generates 4,560 MW (2.9% of total installed base) and 4 such power plants are in the pipeline and would be generating around 2,720 MW. India's contribution in fusion development is done through its involvement in the ITER project. This paper examines the comparative study on solar and nuclear power plant in India.

   Electricity generation is the process of generating electric power.


1.        [Online].Available:http://thehindu/news/national/article2627059.ece]
2. Power Consumption in India to Double Up by 2020 
3.        Kudankulam a victim of misinformation’ Published: Sunday, Nov 13, 2011, 9:13 IST ,Updated: Sunday, Nov 13, 2011, 9:13 IST,

4.        By M Raghuram, Place: Manipal | Agency: DNA[Online].Available:www.dnaindia.com/bangalore/interview_kudankulam-a-victim- 
5.        [Online].Available:www.indianuclearenergy.net/summit/
6.        [Online].Available:. http://en.wikipedia.org/wiki/Nuclear_fuel

7.        [Online].Available: http://www.barc.gov.in/egreport.pdf

8.        Nuclear_fuel_cycle[Online].Available:http://en.wikipedia.org/

9.        Nuclear-Power-Plant-Advantages-Disadvantages    [Online].Available: http://kiran111.hubpages.com/hub/

10.     [Online].Available:Gujarat%20Solar%20Park,%20Charank20 Costs%20%20%20Natural%20Group.htm

11.     [Online].Available:www.narendramodi.in/cm-to-dedicate-600-mw-solar-power-generation-capacity-to-the-nation/comment-page-15/

12.     Online].Available:.www.gpclindia.com/showpage.aspx? contentid=15

13. [Online].Available:http://epaper.timesofindia.com/Default/Scripting/ArticleWin.asp?From=Archive&Source=Page&Skin=TOINEW 
& Base Href=TOIA/2013/03/11&PageLabel=4&EntityId=Ar00401&ViewMode=HTML
14.     Electricity_generation[Online].Available:http://en.wikipedia.org/wiki/indian_electricity_scenario[Online].Available:http://www.powermin.
15.     Cost Economics of Solar kWh, AVIJIT NAYAK, National Productivity Council, Kolkata, [Online].Available:www.energetica-india.net/

16.     Green Energy, Vol.5. No.3. ½ May-June 2001.World Institute of Sustainable Energy, P-10.

17.     “India’s GHG Emission Profile Results of Five Climate Modelling Studies”, September 2009, MOEF, GOI.

18.     [Online].Available:http://www.npcil.nic.in/main/ allprojectoperationdisplay.aspx






Rutuja K. Pensionwar, Anil Kumar Mishra, Latika Singh

Paper Title:

Quality Metrics in Ubiquitous Computing

Abstract: Ubiquitous computing is the latest technology that not just make computer as a tool, but helpful and calm device which is one of the main part of human being in his day to day life. The purpose behind this paper is that to share some valuable quality metrics that help us in our near future that help us to improve the quality of our project. In Software engineering Software quality metrics is one of the research areas. In this paper we will see some quality metrics that one can use in ubiquitous projects. As we know that ubicomp is one of the different techniques with some different methods, design guidelines so we can say that there may be different quality metrics for the same. As well as we will see what is meant by ubiquitous, ubiquitous computing and also some new devices in them.

Quality, Software Metrics, Quality Metrics, ubiquitous computing, ubiquitous.


1.        M. Weiser, "The computer for the 21st century," Scientific American, vol. 272, pp. 78-89, 1995.
2.        S.Dritsas, D.Gritzalis, and C.Lambrinoudakis, "Protecting privacy and anonymity in pervasive computing: trends and perspectives", Telematics and Informatics, vol. 23, pp. 196-210, 2006.

3.        International Journal of Multimedia and Ubiquitous Engineering  Vol. 2, No. 1, January, 2007

4.        Ubiquitous Computing Environment Threats and Defensive  Measures  Dr. Byeong-Ho KANG  International Journal of Multimedia and Ubiquitous Engineering   Vol. 2, No. 1, January, 2007

5.        Towards a Discipline for Evaluating Ubiquitous Computing Applications J. Scholtz, S. Consolvo IRS-TR-04-004 January 2004

6.        Keefe, D., & Zucker, A. (2003). Ubiquitous Computing Projects: A Brief History (Technical Report No. P12269): SRI International.






Narendra Kumar Agarwal, Vishal Shrivastava

Paper Title:

Simulation Results and Performance Evaluation of Routing Protocols in Mobile Ad-Hoc Networks

Abstract: One  of  the  majority  vital  issues in mobile ad hoc network(MANET) is collecting and processing  data  apparent  from the atmosphere and sending that  data to be processed and evaluated. Routing in MANETs is a challenging task due to the unpredictable changes in the network topology. MANETs  are  a  heterogeneous  mix of  different  wireless and mobile devices ,  ranging  from  little hand- held  devices to laptops  that  are dynamically  and arbitrarily located  in  such  a  manner  that  the  interconnections  between  nodes  are capable of  changing  on  a  continual  basis. The major  goal  of   the proposed  paper  is  to  analyze the  behavior  of  the both  reactive  Ad hoc On- demand  Distance Vector protocol (AODV)  and  proactive  Destination Sequenced Distance Vector (DSDV)  in high mobility scenario under  dense and  sparse  medium. Unlike military applications, most of the other applications of MANETs require moderate to high mobility. That’s why it becomes important to analyze the behavior of high mobility. Simulation is done using ns2 in different scenarios in MANET.

MANET, Routing protocol, AODV, DSDV, NS2.


1.        Elizabeth M. Royer, University of California, Santa Barbara Chai-Keong Toh, Georgia Institute of Technology, “A Review of Current Routing Protocols for Ad Hoc Mobile       Wireless Networks”.
2.        Charles E. Perkins;Pravin Bhagwat. Highly dynamic destination-sequenced distance-vecto routing (dsdv) for mobile computers. 1994.

3.        Charles E. P.; Elizabeth M. R., Ad hoc on-demand distance vector routing. In Proceedings of the 2nd IEEE Workshop.on Mobile Computing Systems and Applications, pages 80–100.IEEE, February 1999.

4.        AODV, internet-draft. World Wide Web, http://www.ietf.org/internet-drafts/draft-ietf-manet-aodv-08.txt.

5.        David A.; David B. Johnson; Josh Broch; Maltz,; Jorjeta Jetcheva.;Yih-Chun Hu;  A performance comparison of multihop wireless adhoc network routing protocols. In Mobicom 1998, pages 85–97.ACM, 1998.

6.        Das B.; Bhargavan V.; Sivakumar E., Routing in ad-hoc networks using a spine, 1997.

7.        Haas. ZRP, internet-draft. World Wide Web,  

8.        Ford Jr. L.R. ; Fulkerson D. R., Flows in Networks. Princeton Univ. Press, 1962.

9.        David B. J.;David A. M;,“ Dynamic Source Routing in Ad Hoc Wireless Networks“, chapter  5, pages 153–181. Kluwer Academic Publishers, 1996.

10.     http://www.isi.edu/nsnam/ns/ns-tutorial/index.html






Ashwini Singh, Ajeet Kumar, Pankaj Kumar, M. A. Mujeeb

Paper Title:

Body Sensor Network: Monitoring and Analysing Real Time Body Parameters in Medical Perspect

Abstract: As because of modern emerging technologies, low power integrated circuits and wireless communication has enabled a new generation of sensors network. The incorporation of these sensors networks in Health care is very popular and plays a vital role in breath breaking situations. The deployment of monitoring and analysing hardware incorporated with various wireless standards plays a key role in regard to monitors body parameters and collects the data for analysing related issues. The goal of our paper is to develop a wireless system that provides the heartbeat rate, body temperature and body acceleration with real time data which helps to control situation of emergency and all these information will send to the caregivers by various wireless techniques.

Wireless Body area Sensors network, Zigbee, Activity Monitors, WSN.


1.        C. Otto, A. Milenkovic, C. Sanders, and E. Jovanov, "System  Architecture of a Wireless Body Area Sensor Networkfor  Ubiquitous  Health Monitoring," Journal of Mobile Multimedia,
2.        E. Jovanov, A. Milenkovic, C. Otto, and P. C. d. Groen, "A  Wireless Body    Area Network of Intelligent Motion Sensors for  Computer Assisted Physical Rehabilitation,"  Journal of  NeuroEngineering and Rehabilitation.

3.        www.MaxStream.net

4.        A. Milenkovic, C. Otto, and E. Jovanov, "Wireless Sensor  Networks for Personal Health Monitoring: Issues andan  Implementation,"  Computer Communications .

5.        C. V. C. Bouten, K. T. M. Koekkoek, M. Verduin,R. Kodde,  and J. D. Janssen, "A Triaxial Accelerometer and Portable Data  Processing Unit for the Assessment of Daily Physical Activity,"  IEEE Transactions on Biomedical Engineering.

6.        S. Warren, “Beyond Telemedicine: Infrastructures for Intelligent  Home Care Technology,” Pre-ICADI Workshop on Technology for  Aging, Disability, and Independence, The Royal Academy of  Engineering, Westminster, London, England, June 2003.

7.        E. Bielli, F. Carminati, S. La Capra, M. Lina, C. Brunelli, M.  Tamburini, “A Wireless Health Outcomes Monitoring System  (WHOMS): development and field testing with cancer patients using  mobile phones,” BMC Medical Informatics and Decision Making,  2004, 4:7,






Kashyap Patel, R. K. Prasad

Paper Title:

Speech Recognition and Verification Using MFCC & VQ

Abstract: Speech recognition is very important branch in digital signal processing. Speaker Recognition software using MFCC (Mel Frequency Cepstral Co-efficient) and vector quantization has been designed, developed and tested satisfactorily for male and female voice. In this paper the ability of HPS (Harmonic Product Spectrum) algorithm and MFCC for gender and speaker recognition is explored. HPS algorithm can be used to find the pitch of the speaker which can be used to determine gender of the speaker. In this algorithm the speech signals for male and female ware recorded in .wav(dot wav) file at 8 KHz sampling rate and then modified. This modified wav file for speech signal was processed using MATLAB software for computing and plotting the autocorrelation of speech signal. The software reliably computes the pitch of male and female voice. The MFCC algorithm is used to simulate feature extraction module. Using this algorithm the cepstral co-efficient are calculated of Mel frequency scale. VQ (Vector Quantization) method will be used for reduction of amount of data to decrease computation time. In the feature matching stage Euclidean distance is applied as similarity criterion. Because of high accuracy of used algorithm the accuracy of voice command system is high. In this paper the quality and testing of speaker recognition and gender recognition system is completed and analysed.

Autocorrelation, Signal, Voice command, Pitch, MFCC, Vector quantization, Euclidean distance.


1.        Mahdi Shaneh and Azizollah Taheri, "Voice Command Recognition System Based on MFCC and VQ algorithms" World Academy of Science, Engineering and Technology 33 2009.
2.        Ms. Arundhati S. Mehendale and Mrs. M.R. Dixit "Speaker Identification" Signals and Image processing: An International Journal (SIPIJ) Vol. 2, No. 2, June 2011.

3.        Jamel Price, Sophomore student, Dr. Ali Eydgahi "Design of an Automatic Speech Recognition System Using MATLAB" Chesapeake Information Based Aeronautics Consortium August 2005.

4.        E. Darren. Ellis "Design of a Speaker Recognition Code using MATLAB "Department of Computer and Electrical Engineering- University of Tennessee, Knoxville Tennessee 37996. 9th May  2001.

5.        J.S Chitode, Anuradha S. Nigade " Throat Microphone Signals for Isolated Word Recognition Using LPC "   International Journal of Advanced Research in  Computer Science and Software Engineering, Volume 2, Issue 8, August 2012. ISSN: 2277 128X.






Kashyap Patel, R. K. Prasad

Paper Title:

Speech Recognition and Verification Using MFCC & VQ

Abstract: Speech recognition is very important branch in digital signal processing. Speaker Recognition software using MFCC (Mel Frequency Cepstral Co-efficient) and vector quantization has been designed, developed and tested satisfactorily for male and female voice. In this paper the ability of HPS (Harmonic Product Spectrum) algorithm and MFCC for gender and speaker recognition is explored. HPS algorithm can be used to find the pitch of the speaker which can be used to determine gender of the speaker. In this algorithm the speech signals for male and female ware recorded in .wav(dot wav) file at 8 KHz sampling rate and then modified. This modified wav file for speech signal was processed using MATLAB software for computing and plotting the autocorrelation of speech signal. The software reliably computes the pitch of male and female voice. The MFCC algorithm is used to simulate feature extraction module. Using this algorithm the cepstral co-efficient are calculated of Mel frequency scale. VQ (Vector Quantization) method will be used for reduction of amount of data to decrease computation time. In the feature matching stage Euclidean distance is applied as similarity criterion. Because of high accuracy of used algorithm the accuracy of voice command system is high. In this paper the quality and testing of speaker recognition and gender recognition system is completed and analysed.

Autocorrelation, Signal, Voice command, Pitch, MFCC, Vector quantization, Euclidean distance.


1.        Mahdi Shaneh and Azizollah Taheri, "Voice Command Recognition System Based on MFCC and VQ algorithms" World Academy of Science, Engineering and Technology 33 2009.
2.        Ms. Arundhati S. Mehendale and Mrs. M.R. Dixit "Speaker Identification" Signals and Image processing: An International Journal (SIPIJ) Vol. 2, No. 2, June 2011.

3.        Jamel Price, Sophomore student, Dr. Ali Eydgahi "Design of an Automatic Speech Recognition System Using MATLAB" Chesapeake Information Based Aeronautics Consortium August 2005.

4.        E. Darren. Ellis "Design of a Speaker Recognition Code using MATLAB "Department of Computer and Electrical Engineering- University of Tennessee, Knoxville Tennessee 37996. 9th May  2001.

5.        J.S Chitode, Anuradha S. Nigade " Throat Microphone Signals for Isolated Word Recognition Using LPC " International Journal of Advanced Research in  Computer Science and Software Engineering, Volume 2, Issue 8, August 2012. ISSN: 2277 128X.






Selvaradjou, K. Bharathi Manjula

Paper Title:

Redundant Transmission of Sensed data in Wireless Sensors and Actor Networks for Improved Reliability

Abstract: In Wireless Sensor and Actor Network (WSAN), sensors and actors are linked through wireless channel. Sensor nodes are those which sense data and forward them to actors, which in turn process the data and perform a suitable action on the environment. An actor is a node that also acts as a data sink in the WSANs. The actor node, which can be a mobile, or a static node, may take actions on the environment either individually or collaboratively with other such nodes that may be present in the network. It is important that the sensed events are reported to the sink nodes with high reliability and in a timely manner in order to effect a real-time response behavior of the network. We consider a network in which sensors deliver the sensed events in the form of messages and data in a multi-hop manner. While forwarding data there is a possibility of data loss due to various reasons such as collision, noise interference, and congestion in the network. In such cases, the messages need to be re-transmitted to ensure reliability. Such re-transmissions would waste bandwidth and scarce energy of the sensor nodes and will lead to a shorter lifetime of the network. We propose redundant data transmission schemes in which, the messages are retransmitted by embedding the neighbor node’s message as backup data along with the original message. So data even when lost, reaches the destination via neighbour nodes’ messages. We evaluated the performance of the protocol using TOSSIM simulator and the embedding of data packets helps improving the lifetime of the network.

Medium Access, Reliability, Sensor Networks, Wireless.


1.        Akyildiz I. F. and Kasimoglu I. H., “Wireless Sensor and Actor Networks:   Research Challenges”, Ad Hoc Network, vol 2 (4), pp 351-367, 2004.
2.        Rezgui A. and Eltoweissy M., “Service-Oriented Sensor-Actuator Networks: Promises, Challenges and the road ahead”, Computer Communications , vol 30, pp 2627-2648, 2007.

3.        Melodia T., Pompili D., Gungor V.C. and Akyildiz I.F., “Communication and Coordination in Wireless Sensor and Actor Networks”, IEEE Transactions on Mobile Computing, vol 6(10), pp 1116-1129, 2007.

4.        M. Demirbas, S. Balachandran, “ROBCAST: A Single hop Reliable Broadcast Protocol for Wireless Sensor Networks”, in Proceedings of The Sixth International Workshop on Assurance in Distributed Systems and Networks (ADSN2007).

5.        Kiyohiro Morita, Kenichi Watanabe, Naohiro Hayashibara, and Makoto Takizawa, “An Efficient Data Transmission Protocol in a Wireless Sensor-Actuator Network”,  in Proceedings of the First International Conference on Complex, Intelligent and Software Intensive Systems (CISIS'07), 2007.

6.        Wireless sensor networks Getting Started Guide, Crossbow Technology, Inc., 2004. Available at:    https://www.eol.ucar.edu/rtf/facilities/isa/internal/CrossBow/Doc/Getting_Started_Guide_7430-0022-04_A.pdf

7.        P. Levis, N. Lee, W. Welsh, and D. Culler, “TOSSIM: Accurate and Scalable Simulation of Entire TinyOS Applications”, in Proceedings of the 1st International Conference on Embedded Networked Sensor Systems, pp 126-137, 2003.






Gaurav Raghav, B. S. Kadam, Manjeet Kumar

Paper Title:

Optimization of Material Removal Rate in Electric Discharge Machining Using Mild Steel

Abstract: This paper aims at achieving the integrated approach to solve the optimization problem of EDM process. At any stage, the dominance factor of the input variables and output variables contained in the constraints and objective functions can be computed. This technique helps in getting the reliable multi-objective decisions under constrained penalties for the constrained optimization of such processes. In the present work, relationships have been developed between the input decision variables and the desired goals by applying the statistical regression analysis of investigations obtained by Electro Discharge machining process for a considerable variation in the crisp sets of variables. The objectives functions were maximized or minimized by using the generalized Genetic Algorithms and the data are stored for a given set of objectives. The results are interpreted with respect to those obtained by using the bi-criterion approach. It is concluded that the results obtained by bi-criterion approach are approximately of the same order of accuracy as calculated experimentally but the computational simplicity of this method makes this methodology favorable to use to solve such mechanical engineering complex problems.

EDM, Material removal Rate, Mild Steel, Optimization.


1.        Book title:- “Engineering optimization: methods and applications.”By: A. Ravindran, K. M. Ragsdell, G.V. Reklaitis
2.        A charnes and W. W. Cooper, “Goal programming and multiple objective programming.” Pp. 39-54, 1977.

3.        Joopelli, V., "Multi-Objective Optimization of Parameter Combinations in Electrical Discharge Machining with Orbital Motion of Tool Electrode," Journal of Processing of Advanced Materials, Vol. 4, pp. 1-12, 1994.

4.        Jain, V. K., "Multi-Objective Optimization of Electro discharge Machining Process," Microtechnic journal issue, Vol. 2, pp. 33-37, 1990.

5.        Kahng, C. H., "Surface Characteristic Behavior Due to Rough and Fine Cutting by EDM," Annuals of the CIRP, Vol. 26/1, pp. 77 -82, 1977.

6.        Kee, P., “Development of Constrained Optimization Analyses and Strategies for Multi-Pass Rough Turning Operations,” Int. J. Mach. Tools Manuf., pp. 115–127, 1996.

7.        L.C. Lim, H.H. Lu,"  Better Understanding of the Surface Features of Electro-discharge”, Journal of Materials Processing Technology, Vol. 24, pp.513-523, 1990.

8.        Madhu, P., Jain, V. K., "Finite Element Analysis of EDM Process," Journal of processing of Advanced Materials, Vol. 2, pp. 161-173, 1991.

9.        Masatoshi, S., and Ryo, Kubota, “Fuzzy Programming for Multi-objective Job Shop Scheduling with Fuzzy Processing Time and Fuzzy Due date through Genetic Algorithms,” Europian Journal of Operation research, Volume  120, pp. 393–407, 2005.

10.     Pandit, S. M., "Analysis of Electro-Discharge Machining of Cemented Carbides," Annuals of the CIRP, Vol. 30/1, pp. 111-116, 1981.

11.     Spedding, T.A. and Wang, Z.Q. "Study on Modelling of Wire EDM Process" International Journal of Materials Processing Technology Vol 69, No 1-3,18-28, 1997.

12.     Spedding, T.A., "Parametric Optimization and Surface Characterization of the Wire EDM Process" Journal of Precision Engineering, American Society of Precision Engineering, , Vol 20, No 1, 5-15, 1997.

13.     Smyers, S., Guha, A., "Electrodischarge Machining of Beryllium Copper Alloys Safely and Efficiently," Proceedings of the International Symposium on Electro -Machining, ISEM-11, pp. 217-224, 1995.

14.     Wang, W.M., "Advances in EDM Monitoring and Control Systems Using Modern Control Concepts," International Journal of Electro machining, No.2, pp. 1-7, January 1997.

15.     Zhang, B., "Effect of Dielectric Fluid Characteristics on EDM Performance," a report from GE Research and Development, December 1997.

16.     Steve Krar,” Electric Discharge Machining: cutting metal to precise Shapes using electricity.” 1994.






Neenu Prasad

Paper Title:

A Comparative Dimensionality Reduction Approach For Face Recognitionunder Uncontrolled Illumination Variations

Abstract: Most of the method developed for face recognition with face images collected under relatively well controlled conditions have difficulty in dealing with the range of appearance variations that commonly occur in unconstrained natural images due to different factors. A simple, efficient image processing chain is used whose practical recognition performance is comparable to or better than current methods, a rich descriptor for local texture called Local Binary Pattern(LBP), is used for feature extraction, dimensionality reduction is performed using Principal Component Analysis(PCA) and Linear Discriminant Analysis (LDA). To demonstrate the effectiveness of the proposed method, we give results on the Extended Yale-B dataset which contains images of 38 subjects under 64 illumination and 9 poses.

Face recognition, Feature extraction, illumination normalization, linear discriminant analysis, local binary patterns, principal component analysis.


1.        X. Tan and B. Triggs, “Enhanced local texture feature sets for face recognition under   difficult   lighting   conditions,”   in Proc. AMFG, 2007, pp. 168–182.W.-K. Chen, Linear Networks and Systems (Book style).  Belmont, CA: Wadsworth, 1993, pp. 123–135.
2.        J.  Yang,  A.  F.  Frangi,  J.-Y.  Yang,  D.Zhang, and Z. Jin, “KPCA plus LDA: A complete kernel fisher discriminant framework for feature extraction and recognition,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 27, no. 2, pp. 230– 244, Feb. 2005.

3.        R. Javier, V. Rodrigo, and C. Mauricio, “Recognition of faces in unconstrained Environments: A comparative study,” in EURASIP J. Adv.Signal Process., 2009, vol. 2009, pp. 1–19..

4.        X.  Tan  and  B.  Triggs,  “Fusing  Gabor and LBP feature sets for kernel based face recognition,” in Proc. AMFG, 2007, pp. 235–249.

5.        N. Dalal and B. Triggs, “Histograms of oriented gradients for human detection,” in Proc. CVPR, Washington, DC, 2005, pp. 886–893.

6.        Y. Pang, Y. Yuan, and X. Li, “Gabor-based region covariance matrices for face recognition,” IEEE Trans. Circuits Syst. Video Technol., vol.18, no. 7, pp. 989–993, Jul. 2008.

7.        H. Chen, P. Belhumeur, and D. Jacobs, “In search of illumination invariants,”in Proc. CVPR, 2000, pp. 254–261.

8.        K.   Lee,   J.   Ho and D.   Kriegman,“Acquiring   linear   subspaces   for   face recognition under    variable                lighting,”.

9.        M. Turk and A. Pentland, “Eigenfaces for recognition,” J. Cognitive Neursci., vol. 3, no. 1, pp. 71–86, 1991.

10.     L.Sirovich and M. Kirby, “Low dimensional procedure for the characterization of human faces,” J. Opt. Soc. Amer., vol. 4, no. 3, pp.519– 524, 1987.






Hansaraj S. Wankhede, S. A. Chhabria, R. V. Dharaskar

Paper Title:

Human Computer Interaction Using Eye and Speech: The Hybrid Approach

Abstract: The physically impaired users cannot handle the traditional input devices such as keyboard, mouse etc. the alternate for this category of users must be available. Speech is another promising technology to achieve this goal. The first approach researches estimation of eye gaze point as pointing device. The second approach researches speech recognition as an input and the third approach deals with the hybrid approach for the combination of both. The aim of ongoing research is to develop an application to replace a computer mouse for a people with physical impairment. The application is based on an eye gaze estimation algorithm and assumes that the camera and the head position are fixed. The system after successful development will able to interact user with specific application.

 Eye Gaze Point, Disable users, Speech Recognition, Hybrid approach etc.


1.        Jason S.Babcock and Jeff B. Pelz. "Building a lightweight eyetracking headgear." Eye Tracking Research & Application, Texas, 2004.
2.        J. Babcock, J. Pelz and J. Peak. "The Wearable Eyetracker: A Tool for the Study of High-level Visual Tasks". February 2003

3.        Li, D., Babcock, J., Parkhurst, D. J. openEyes: "A low-cost head-mounted eye-tracking solution". Proceedings of the ACM Eye Tracking Research and Applications Symposium 2006.

4.        Javier San Agustin, Henrik Skovsgaard, John Paulin Hansen, Dan Witzner Hansen. "Low-Cost Gaze Interaction: Ready to Deliver the Promises". CHI 2009, Boston, Massachusetts, USA.

5.        Michał Kowalik, "How to build low cost eye tracking glasses for head mounted system ",  September 2010.

6.        Masrullizam Mat Ibrahim, John J Soraghan, Lykourgos  Petropoulakis, “Non Rigid Eye Movement Tracking and Eye State Quantification”, IEEE,2012.

7.        Mehrube Mehrubeoglu, Linh Manh Pham, Hung Thieu Le, Ramchander Muddu, and Dongseok Ryu, “Real-Time Eye Tracking Using a Smart Camera”, IEEE,2012.

8.        Peter M. Corcoran, Florin Nanu, Stefan Petrescu,and Petronel Bigioi, “Real-Time Eye Gaze Tracking for Gaming Design and Consumer Electronics Systems”, IEEE,2012.

9.        Chiao-Wen Kao, Bor-Jiunn Hwang, Che-Wei Yang, Kuo-Chin Fan, Chin-Pan Huang, “A Novel with Low Complexity Gaze Point Estimation Algorithm”, IMECS, March 14 – 16, 2012, Hong Kong.

10.     Minoru Nakayam , Yuko Hayashi , “Prediction of Recall Accuracy in a Contextual Understanding Task Using Eye Movement Features”, IEEE, 2011.

11.     Corey Holland, Oleg Komogortsev Department of Computer Science Texas State University – San Marcos, “Eye Tracking on Unmodified Common Tablets: Challenges and Solutions”, ACM Symposium on Eye Tracking Research & Applications (ETRA 2012)

12.     Vazquez L. J. G, Minor M. A., Sossa A. J. H. ,  "Low Cast Human Computer Interface voluntary Eye Movement as communication system for disable people with limited movement.”, IEEE, 2011.

13.     Dan Hartescu, Andreas Oikonomou, “Gaze Tracking As a Game Input Interface”, The 16 th International Conference on Computer Games ,CGAMES 2011.

14.     Jae Won Bang, Eui Chul Lee, Kang Ryoung Park, “New Computer Inteface Combining Gaze Tracking and Brainwave Measurements”, IEEE, 2011.

15.     Giancarlo Lannizzotto, Francesco La Rosa, “Competitive Combination of Multiple Eye Detection and Tracking Technique”, IEEE,2010.

16.     Pradeep K. Atrey, M. Anwar Hossain, Abdulmotaleb El Saddik, Mohan S. Kankanhalli, " Multimodal fusion for multimedia analysis: a survey" , Multimedia Systems,  Springer-Verlag 2010.






A. D. Pathak, S. J. Karale

Paper Title:

Partially Improved Subsequence Discovery Algorithm for Sequence Matching

Abstract: This article describes an Improved technique for the sub sequence discovery algorithm used for natural language processing in question answering system for matching user text input in natural language processing against an existing knowledge base, consisting of semantically described words or phrases. Most common methods & techniques of natural language processing are overviewed and their main problems are outlined. A sequence matching with subsequence analysis algorithm is analyzed and improvements are done which deals with the problems of exact matching,change in custom spelling errors as well as the improvement in the performance metric of the similarity matching.Popular approaches that solve this problem include stemming, lemmatization and various distance functions,sequence matching techniques are analysed to get the better possible technique for solving the problems with higher accuracy. Then the major components of the similarity measure are defined and the computation of concurrence and dispersion measure is presented. Results of the algorithms performance on a test set are then analysed.

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


1.        Marko Ferme, Milan  Ojsteršeko “Sequence matching with  subsequence analysis”, ISBN: 978-960-474-250-9. Advances in Communications, Computers, Systems, Circuits and Devices.
2.        INES ČEH, MILAN OJSTERŠEK “Developing a Question Answering System for the Slovene Language”, WSEAS TRANSACTIONS on INFORMATION SCIENCE and APPLICATIONS, Issue 9, Volume 6, September 2009,ISSN: 1790-0832.

3.        Deepa gupta, Rahul kumar yadav, Nidhi sajan, “ Improving Unsupervised Stemming by using Partial Lemmatization Coupled with Data-based Heuristics for Hindi” International Journal of Computer Applications (0975 – 8887) Volume 38– No.8, January 2012 .

4.        Maria Vargas-Vera, Enrico Motta and John Domingue “AQUA: An Ontology-Driven Question Answering System”, AAAI Technical Report SS-03-07.

5.        Information Retrieval: Data Structures & Algorithms, edited by William B. Frakes and Ricardo Baeza-Yates.

6.        M. Popovic, P. Willett, "The effectiveness of stemming for natural language access to Slovene textual data", Journal of the American Society for Information Science, 43(5), 384–390, 1992.

7.        Anjali Ganesh Jivani,” A Comparative Study of Stemming Algorithms” Int. J. Comp. Tech. Appl., Vol 2 (6), 1930-1938.

8.        “A survey sequence matching & alignment algorithm” by By Jennifer  Johnstone.

9.        “A Guided Tour to Approximate String Matching by GONZALO NAVARRO, ACM Computing Surveys, Vol. 33, No. 1, March 2001,  pp.31–88.

10.     A Fast Generic Sequence Matching Algorithm, David R. Musser Gor  V. Nishanov Computer Science Department Rensselaer Polytechnic Institute, Troy,   NY 12180 fmusser,gorikg@cs.rpi.edu February 2,   2001.

11.     Borut Gorenjak, Marko Ferme, Milan Ojsteršek, “A Question Answering System on Domain Specific Knowledge with Semantic Web Support” INTERNATIONAL JOURNAL OF COMPUTERS Issue 2, Volume 5, 2011.

12.     Yajing Zhao,Jing Dong ,senior Member ,IEEE ,and  Tu Peng “Ontology classification for Semantic-Web based software Engineering” IEEE Transactions on services computing ,vol 2 no 4 October-December 2009.

13.     “Text searching algorithm,volume-1,forward string matching” Borivoj Melichar ,Jan houlab, Tomas Polchar,November 2005.

14.     ”Udi Manber, Sun Wu. "Fast text searching with errors." Technical Report TR-91-11. Department of Computer Science, University of Arizona, Tucson, June 1991.

15.     Udi Manber, Sun Wu. "Fast text search allowing errors." Communications of the ACM, 35(10): pp. 83–91, October 1992, doi:10.1145/135239.135244.

16.     A comparison of four pair-wise sequence alignment methods” Nadia Essoussi1 and Sondes Fayech1, published online December 28, 2007.

17.     ”Solving Sequence Alignment Problem Using Pipeline Approach” by Pankaj Agarwal1 and S. A. M. Rizvi2, BVICAM’s International Journal of Information Technology. BIJIT – 2009 Vol. 1 No. 2 ISSN 0973 – 5658.

18.     “Method of Fuzzy Matching Feature Extraction and Clustering Genome    Data”by Nagamma Patil 1+, Durga Toshniwal 1 and Kumkum Garg 2,     IPCSIT vol. 30 (2012) © (2012) IACSIT Press, Singapore.

19.     S. Pohorec, M. Verlič, M. Zorman, Domain specific information retrieval system, Proceedings of the 13th WSEAS international conference on computers (part of the 13th WSEAS CSCC multiconference), July 2009, pp. 502-508.






Vaibhav V. Deshpande, A. R. Bhagat Patil

Paper Title:

Energy Distributed Clustering for Improving Lifetime of Wireless Sensor Network

Abstract: Clustering is an efficient way to improve lifetime of wireless sensor network.  To enhance lifetime of sensor network this paper proposes to have multiple cluster heads within the cluster of sensor nodes. At a given time one cluster head (CH) from the cluster acts as a leader of the cluster and the leadership is rotated among the cluster heads based on the energy levels. The experimental results show the efficiency of proposed algorithm in terms of residual energy, total alive nodes and the execution time as compared to the cluster with single cluster head and LEACH protocol.

Clustering, Cluster heads, Lifetime, Wireless Sensor Network.


1.        B. Meenakshi, P. Anandhakumar, “Lifetime extension of wireless sensor network by selecting two cluster heads and hierarchical routing”, IEEE International Conference on Advances in Computing, Communications and Informatics, 2012. 
2.        Babar Nazir, Halabi Hasbullah, “Energy Balanced Clustering in Wireless Sensor Network”, IEEE International Conference on Information Technology, 2010.

3.        Ying Liang, Haibin Yu , “Energy Adaptive Cluster-Head Selection for Wireless Sensor Networks”, IEEE International Conference on Parallel and Distributed Computing, Applications and Technologies, 2005.

4.        Jinchul Choi, Chaewoo Lee, “Energy consumption and lifetime analysis in clustered multi-hop wireless sensor networks using the probabilistic cluster-head selection method”, IEEE International conference on Wireless and Mobile Networking, 2011.

5.        Gaurav Gupta, Mohamed Younis, “Fault-Tolerant Clustering of Wireless Sensor Network”, IEEE International Conference on Wireless Communications and Networking, 2003.

6.        Mao YE, Cengafa LI, Guihai Chen, Jie WU, “Energy Efficient Clustering Scheme in Wireless Sensor Networks”,  IEEE International Conference on Performance, Computing and Communications, 2005.

7.        Wendi Rabiner Heinzelman, Anantha Chandrakasan, Hari Balakrishnan, “Energy-Efficient Communication Protocol for Wireless Microsensor Networks”,  IEEE Hawaii International conference on System Sciences, 2000.

8.        Seema Bandyopadhyay, Edward J. Coyle, “An Energy Efficient Hierarchical Clustering Algorithm for Wireless Sensor Networks”, Twenty-Second Annual Joint Conference of the IEEE Computer and Communications, 2003.

9.        Gaurav Gupta, Mohamed Younis, “Performance Evaluation of Load-Balanced Clustering of Wireless Sensor Networks”, IEEE International Conference on Telecommunications, 2003.

10.     Jalil Jabari Lotf, Mehdi Nozad Bonab, Siavash Khorsandi, “A Novel Cluster-based Routing Protocol with Extending Lifetime for Wireless Sensor Networks”, IEEE International Conference on Wireless and Optical Communications Networks, 2008.

11.     Younis, O., “HEED: a hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks”, IEEE Transactions on Mobile Computing,  2004.

12.     Nazia Majadi, "U-LEACH: A Routing Protocol for Prolonging Lifetime of Wireless Sensor Networks", International Journal of Engineering Research and Applications, Volume 2, Issue 4, 2012.

13.     Yunxia Chen, Qing Zhao, “On life time of sensor network”, IEEE Communications Letters, Vol 9,  No. 11, 2005.

14.     Mao YE, Chengfa LI, Guihai CHEN, and Jie WU, “An Energy Efficient Clustering Scheme in Wireless Sensor Networks”, Ad Hoc & Sensor Wireless Networks, Vol. 3, 2006.

15.     Harneet Kaur, Ajay K. Sharma, “Hybrid Energy Efficient, Distributed Protocol for Heterogeneus Wireless Sensor Network”, International Journal of Computer Applications, Vol 4, 2010.

16.     D. J. Dechene, A. El Jardali, M. Luccini, A. Sauer, “A Survey of Clustering Algorithms for Wireless Sensor Networks”, Information and Automation for Sustainability, 2008. ICIAFS 2008. 4th International Conference , Publication Year: 2008 , Page(s): 295 – 300.

17.     Network Simulator-2 (NS-2) - http://www.isi.edu/nsnam/ns

18.     Vivek Katiyar, Narottam Chand, Surender Soni, “Clustering Algorithms for Heterogeneous Wireless Sensor Network:A Survey”, IJAER, volume1, No 2, ISSN-0976-4259, 2010.






Radhika P. Fuke, M. V. Sarode

Paper Title:

Foreground Extraction in the Compressed Imaging Domain Using Saliency Detection Technique

Abstract: Salient region detection in images is very useful for image processing applications like image segmentation, object detection and recognition. In this paper, an improved approach to detect salient region is presented Using saliency detection technique. Existing saliency detection models are built in the uncompressed domain. Since most images over Internet are typically stored in the compressed domain such as joint photographic experts group,a novel saliency detection model in the compressed domain in this paper. The intensity, color, and texture features of the image are extracted. Detection of irregular visual patterns in images and in video sequences is useful for a variety of tasks. Detecting suspicious behaviors or unusual objects is important for surveillance and monitoring. Identifying spatial saliency in images is useful for quality control and automatic inspection.

Compressed domain, image retargeting, joint photographic experts group, saliency detection, denoising.

1.        L. Itti, C. Koch, and E. Niebur, “A model of saliency-based visual attention for rapid scene analysis”.
2.        Fan, X., Xie, X., Ma, W.-Y., Zhang, H.-J., and Zhou, H.-Q., Visual attention based image browsing on mobile devices”.

3.        Liu, H., Xie, X., Ma, W.-Y., and Zhang, H.-J., Automatic browsing of large pictures on   mobile devices“.

4.        Z. Lu, W. Lin, X. Yang, E. Ong, and S. Yao, “Modeling visual attention’s modulatory aftereffects on visual sensitivity and quality evaluation”.

5.        S. Goferman, L. Zelnik-Manor, and A. Tal, “Context-aware saliency detection”.

6.        X. Hou and L. Zhang, “Saliency detection: A spectral residual approach”.

7.        O. Le Meur, P. Le Callet, D. Barba, and D. Thoreau, “A coherent computational approach to model the bottom-up visual attention”.

8.        S. Avidan and A. Shamir, “Seam carving for content-aware image resizing”.

9.        M. Rubinstein, A. Shamir, and S. Avidan, “Improved seam carving for video retargeting”.

10.     L. Wolf, M. Guttmann, and D. Cohen-Or, “Non-homogeneous content-driven video retargeting”.

11.     Y. Jin, L. Liu, and Q. Wu, “Nonhomogeneous    scaling optimization for realtime image resizing,” Visual Comput., 2010.

12.     Liu, Z., Yan, H., Shen, L., Ngan, K. N., and Zhang, Z., Adaptive image retargeting using saliency-based continuous seam carving," Optical Engineering 49(1) (2010).

13.     J. Wei, “Color object indexing and retrieval in digital libraries,” IEEE Trans. Image Process., Aug. 2002.






Nishand K, Ramasami S, T. Rajendran

Paper Title:

An Efficient way of Record Linkage System and Deduplication using Indexing Techniques, Classification and FEBRL Framework

Abstract: Record linkage is an important process in data integration, which is used in merging, matching and duplicate removal from several databases that refer to the same entities. Deduplication is the process of removing duplicate records in a single database. In recent years, data cleaning and standardization becomes an important process in data mining task. Due to complexity of today’s database, finding matching records in single database is a crucial one. Indexing techniques are used to efficiently implement record linkage and deduplication. In this paper, three indexing techniques namely blocking index, sorting indexing and bigram indexing are used with a modification of existing techniques that reduces the variance in the quality of the blocking results. In addition to the indexing techniques, six comparison techniques and two classifiers are used. There is a potential for large performance speed-ups and better accuracy to be achieved by using indexing techniques along with comparison and classifier techniques.

Record linkage, Indexing techniques, data matching, blocking, Febrl framework.


1.        T. Churches, P. Christen, K. Lim, and J.X. Zhu, “Preparation ofName and Address Data for Record Linkage Using HiddenMarkov Models,” BioMed Central Medical Informatics and DecisionMaking, vol. 2, no. 9, 2002.
2.        P. Christen, “Febrl: An Open Source Data Cleaning, Deduplicationand Record Linkage System With aGraphical User Interface,”Proc. 14th ACM SIGKDD Int’lConf. Knowledge Discovery and DataMining (KDD ’08),pp. 1065-1068, 2008.

3.        L. Gu and R. Baxter, “Decision Models for Record Linkage,”Selected Papers from AusDM, LNCS 3755, Springer, 2006.

4.        S. Yan, D. Lee, M.Y. Kan, and L.C. Giles, “Adaptive SortedNeighborhood Methods for Efficient RecordLinkage,” Proc.Seventh ACM/IEEE-CS Joint Conf.Digital Libraries (JCDL ’07), 2007.

5.        L. Gravano, P.G. Ipeirotis, H.V. Jagadish, N. Koudas, S.Muthukrishnan, and D. Srivastava, “Approximate StringJoins ina Database (Almost) for Free,” Proc. 27th Int’lConf. Very Large DataBases (VLDB ’01), pp. 491-500, 2001.

6.        J.I. Maletic and A. Marcus, “Data Cleansing: Beyond IntegrityAnalysis,” Proc. Fifth Conf. Information Quality(IQ ’00), pp. 200-209, 2000.

7.        L. Jin, C. Li, and S. Mehrotra, “Efficient Record Linkage in LargeData Sets,” Proc. Eighth Int’l Conf.Database Systems for AdvancedApplications (DASFAA ’03), pp. 137-146, 2003.

8.        C. Faloutsos and K.-I. Lin, “Fastmap: A Fast Algorithm forIndexing, Data-Mining and Visualization of Traditional andMultimedia Datasets,” Proc. ACMSIGMOD Int’l Conf. Managementof Data (SIGMOD ’95), pp. 163-174, 1995.






Saket Vihari, Arun Prakash Agrawal

Paper Title:

A System of Humanizing Test Automation Outlay Efficiency

Abstract: Software can be tested either manually or automatically. The two approaches are complementary: automated testing can perform a large number of test in little time, whereas manual testing uses the knowledge of the testing engineer to target testing to the part of the system that are assumed to be more error-prone. Auto test is a testing tool that provide a “best of both worlds” strategy :it integrates developers test cases into an automated process of systematic contract –driven testing. Test automation has become more and more popular as the market demand for more complex software, involving higher risks and using the same or fewer resources in development, has increased. A number of research paper discuss the problem faced in the test automation process ,such as the complexity of automation ,poor choice of tools,and the effort spent to automate. This paper proposes a test automation viability analysis method of a test case based on mathematical procedures which intend to increase the chance of finding outlay efficiency test automation process.

Test automation, outlay efficiency, Viability, Method.


1.        M. Fewster, “Jumping Into Automation Adventure with Your Eyes Open”, Journal of Software Testing Professionals,  March, 2002.
2.        J. Bach, “Test Automation Snake Oil”, presented at 14th International Conference on Testing Computer Software,  Washington-USA, 1999.

3.        J. Kent, “Advanced approaches to Software Test Automation  Part 1”, Journal of Software Testing Professionals, June, 2001.

4.       J. G. Soderborg, “Five Factors for Finding Test Automation  Success”, WEB Seminars, available in http://www.segue.com/aboutsegue/ webinars/public/sdtimes_en/index.html, April, 2005.

5.        B. Pettichord, “Success with Test Automation”, presented at  Quality Week, San Francisco, May, 1996.

6.        B. Marick, “When Should a Test Be Automated”, presented  at Quality Week’ 98, San Francisco, 1998.

7.        L. Hayes, “Establishing a Test Automation Function”, Journal of Software Testing Professionals, March, 2000.

8.        S. Russel and P. Norvig, Artificial Intelligence, Prentice  Hall; 2nd edition (December 20, 2002), USA, December 20,  2002.






P. Subbaraj, A. Ramu, N. Raman, J. Dharmaraja

Paper Title:

Mixed Ligand Complexes Containing (2-Hydroxy- 4 -Methoxyphenyl) (Phenyl) Methanone and 2-Aminophenol: Synthesis and DNA Cleavage

Abstract: A bidentate NO type Schiff base ligand (HA) has been obtained by the condensation reaction of 2-hydroxy-4-metoxy benzophenone with aniline. Using this Schiff base as main ligand(HA) and 2-aminophenol as co-ligand (B), few novel mixed ligand complexes of composition MAB [M = Mn(II), Co(II), Ni(II), Cu(II) and Zn(II)] have been synthesized. The resulting Schiff base (HA) and the mixed ligand complexes have been structurally characterized by UV-Vis., IR, 1H-NMR, FAB-Mass, EPR, XRD, SEM and magnetic studies. XRD and SEM reveal that all the complexes are microcrystalline nature with uniform morphology. In-vitro biological activities of free Schiff base  (HA) and the mixed ligand complexes (1-5) were screened against few pathogenic bacterial and fungal strains by well diffusion technique. All the complexes show moderate potent activities than Schiff base ligand. Furthermore, the oxidative DNA cleavage activities of free Schiff base and the mixed ligand complexes have been done by agarose gel electrophoresis method in peroxide medium.

Keywords: Mixed ligand complexes, Powder XRD, SEM, Biological, DNA activity.


1.        M. J. Genin, C. Biles, B. J. Keiser, S. M. Poppe, S. M. Swaney, W. G. Tarapley, and D. L. Romero, “Novel 1,5-diphenylpyrazole nonnucleoside HIV-1 reverse transcriptase inhibitors with enhanced activity versus the delavirdine-resistant P236L mutant: lead identification and SAR of 3- and 4-substituted derivatives”, J. Med. Chem., vol. 43(5), March 2000, pp. 1034–1040.
2.        P. Vicini, A. Geronikaki, M. Incerti, B. Busonera, G. Poni, C. A. Cabras, and P.L. Colla, “Synthesis and biological evaluation of benzo[d]isothiazole, benzothiazole and thiazole Schiff bases”, Bioorg Med Chem., vol. 11(22), 2003, pp. 4785–4789.

3.        S. A. Ali, A. A. Soliman, M. M. Aboaly, and R. M. Ramadan, “Chromium, Molybdenum and Ruthenium Complexes of 2-Hydroxyacetophenone Schiff Bases”, J. Coord. Chem., 55(10), 2002, pp. 1161–1170.

4.        Z. H. Chohan, and S. Kausar, “Synthesis, characterization and biological properties of tridentate NNO, NNS and NNN donor thiazole-derived furanyl, thiophenyl and pyrrolyl Schiff bases and their Co(II), Cu(II), Ni(II) and Zn(II) metal chelates”, Metal-Based Drugs, vol. 7(1), 2000, pp. 17–22. 

5.        Z. H. Chohan, A. Rauf, and C. T. Supuran, “Antibacterial Co(II) and Ni(II) complexes of N-(2-Furylmethyene)-2-aminothiazole and role of SO42−, NO3−, C2O42− and CH3CO2 anions on biological properties,” Metal-Based Drugs, vol. 8(5), 2002, pp. 287–291.

6.        A. P. Mishra, M. Khare, and S. K. Gautam, “Synthesis, physico-chemical characterization, and antibacterial studies of some bioactive Schiff bases and their metal chelates,” Synthesis and Reactivity in Inorganic and Metal-Organic Chemistry, vol. 32(8), 2002, pp. 1485–1500. 

7.        E. Wagner, K. Al-Kadasi, M. Zimecki, and W. Sawka-Dobrowolska, “Synthesis and pharmacological screening of derivatives of isoxazolo[4,5-d]pyrimidine”, Eur. J. Med. Chem., 43(11), 2008, pp. 2498–2504.

8.        A. Bacchi, M. Carcelli, L. Gabbam, S. Lanelli, P. Pelagatti, G. Pelizzi, and D. Rogolino, “Nickel(II) complexes of  some Schiff base ligands”, Inorg. Chim. Acta, 342, 2003, pp.229–235.

9.        R. K. Parashar, R. C. Sharma, A. Kumar, and G. Mohan G, “Stability studies in relation to IR data of some schiff base complexes of transition metals and their biological and pharmacological studies”, Inorg. Chim. Acta, 151(3), 1988, pp. 201–208.

10.     A. J. M. Xavier, M. A. Raj, and J. M. Marie, “Synthesis and spectral characterization of an aminoacetophenone-based schiff base and its interaction studies with ascorbic acid”, J. Chem. Pharm. Res.,4(1), 2012, pp. 669–672.

11.     D.S. Sigman, A. Mazumder, and D. M. Perrin, “Chemical nucleases”, Chem. Rev., 93(6), 1993, pp. 2295–2316.

12.     N. Zhang, S. Ayral–Kaloustian, T. Nguyen, R. Hernandez, and C. Beyer, “2-cyanoaminopyrimidines as a class of antitumor agents that promote tubulin polymerization”, Bioorg. Med. Chem. Lett., 17(11), June 2007, pp. 3003–3005.

13.     N. Raman, S. Sobha, and A. Thamaraichelvan, A, “A novel bioactive tyramine derived Schiff base and its transition metal complexes as selective DNA binding agents”, Spectrochimi. Acta, 78A (2), 2011, pp. 888–898.

14.     N. Raman, R. Jeyamurugan, R, Senthilkumar, B, Rajkapoor, and S. G. Franzblau, “In vivo and in vitro evaluation of highly specific thiolate carrier group copper(II) and zinc(II) complexes on Ehrlich ascites carcinoma tumor model”, Eur. J. Med. Chem., 45(11), November 2010, pp. 5438–51.

15.     N. Raman, R. Jeyamurugan, A. Sakthivel, and L. Mitu, “Novel metal-based pharmacologically dynamic agents of transition metal(II) complexes: Designing, synthesis, structural elucidation, DNA binding and photo-induced DNA cleavage activity”, Spectrochimi. Acta, 75A (1), 2010, pp. 88–97.

16.     M. J. Pelczar, E. C. S. Chan, and N. R. Krieg, “Microbiology”, 5th Ed., New Delhi, Tata Mc-Graw Hill Publishing Co., Ltd. 1998.

17.     W. J. Geary, "Use of Conductivity Measurements in Organic Solvents For The Characterization of Coordination Compounds", Coord. Chem. Rev., Vol.7, 1971, pp. 81–122.

18.     M. Hamming, and N. Foster, “Interpretation of Mass Spectra of Organic Compounds”, New York, USA, Academic Press, 1972.

19.     K. Nakamoto, “Infrared and Raman Spectra of Inorganic and Coordination Compound” 5th Ed., Part B, John Wiley and Sons, Inc., 1997.

20.     T. M. Dunn, “The Visible and Ultraviolet spectra of Complex Compounds in Modern Coordination Chemistry”, New York, Wiley Interscience, 1960.

21.     A.B.P. Lever, “Electronic spectra of dn ions in Inorganic Electronic Spectroscopy”, 2nd Ed., Elsevier, Amsterdam, The Netherlands, 1984.

22.     R.L. Dutta, and A. Syamal, “Electron Spin Resonance Responses, In Elements of Magnetochemistry”, 2nd Ed., New Delhi, East–West Press, 1992, pp. 206–250.

23.     D. Kivelson, and R. Neiman, “ESR studies on the bonding in copper complexes”, J. Chem. Phys., Vol.35, 1961, pp. 149–155.

24.     A. M. Khedr, and H. M. Marwani, “Synthesis, Spectral, Thermal Analyses and Molecular Modeling of Bioactive Cu(II)-complexes with 1,3,4-thiadiazole Schiff Base Derivatives. Their Catalytic Effect on the Cathodic Reduction of Oxygen”, Int. J. Electrochem. Sci., vol. 7, 2012, pp. 10074–10093.

25.     O. Turkoglu, M. Soylak, and I. Belenli, "Electrical Conductivity of Chloro(phenyl)glyoxime and Its Co(II), Ni(II) and Cu(II) Complexes", Collect. Czech. Chem. Commun..vol. 68(7), 2003, pp.1233–1242.
26.     B. G. Tweedy, “Possible mechanism for reduction of elemental sulfur by monilinia fructicola’, Phytopathology., vol. 55, 1964, pp.  910–914.
27.     Mithun Roy, Ashis K Patra, Arindam Mukherjee, Munirathinam Nethaji, Akhil R Chakravarty, “Ternary iron(II) complexes of phenanthroline bases showing DNA binding and cleavage activity”, Indian J. Chem., vol.46A, 2007, pp.  227–237.






Jayalakshmi N, Sagar B. M

Paper Title:

Virtual Machine Scheduling for Architectural Shared Resources in Open Stack Based Cloud

Abstract: In IAAS cloud virtual machine (VM) migration between socket and nodes has been used to avoid conflicts among VM on system resources such as CPU and memory. Micro-architectural resources such as caches, memory controllers and non-uniform memory access (NUMA) affinity, have relied on intra socket scheduling to reduce cache contention. This paper proposes algorithm for cluster-level virtual machine scheduling based on cache sharing on same socket and these are considered in dynamic environment which do not require any prior knowledge on nature of VMs.The paper would present algorithm for the scheduler into a real cloud system (Open Stack), and the performance of the scheduler will then be investigated on various scientific and commercial workloads.

IAAS architecture, NUMA, OpenStack, CPU bound, memory bound.


1.        VMware ESX Server 2 NUMA Support. White paper.
2.        BLAGODUROV, S., ZHURAVLEV, S., MOHAMMAD, D., AND FEDOROVA,A. A case for numa-aware contention management on multicore processors. In Proceedings of the USENIX Annual Technical Conference (2011).

3.        CLARK, C., FRASER, K., HAND, S., HANSEN, J. G., JUL, E., LIMPACH, C., PRATT, I., AND WARFIELD, A. Live migration of virtual machines. In Proceedings of the 2nd conference on Symposium on Networked Systems Design & Implementation (2005).

4.        GULATI, A., SHANMUGANATHAN, G., HOLLER, A., AND AHMAD,I. Cloud-scale resource management: challenges and techniques.In Proceedings of the 3rd USENIX conference on Hot topics in cloud computing (2011).

5.        MERKEL, A., STOESS, J., AND BELLOSA, F. Resource conscious scheduling for energy efficiency on multicore processors. In Proceedings of the 5th European conference on Computer systems (2010).

6.        QURESHI, M. K., AND PATT, Y. N. Utility-based cache partitioning: A low-overhead, high-performance, runtime mechanism to partition shared caches. In Proceedings of the 39th Annual IEEE/ACMInternational Symposium onMicroarchitecture (2006).

7.        SUH, G. E., DEVADAS, S., AND RUDOLPH, L. A new memory monitoring scheme for memory-aware scheduling and partitioning. In Proceedings of the 8th International Symposium on High-Performance Computer Architecture (2002).

8.        WOOD, T., SHENOY, P., VENKATARAMANI, A., AND YOUSIF,M. Black-box and gray-box strategies for virtual machine migration. In Proceedings of the 4th USENIX conference on Networked systems design and implementation (2007).

9.        ZHURAVLEV, S., BLAGODUROV, S., AND FEDOROVA, A. Addressing shared resource contention in multicore processors via scheduling. In Proceedings of the 15th International Conference on Architectural support for programming languages and operating systems (2010).






Sunil Kumar C. A

Paper Title:

Local Maximum Lifetime Algorithms for Strong Barrier Using Coordinated Sensors

Abstract: Barrier coverage is known to be an appropriate model of coverage for movement detection and boundary guard, which is achieved by barriers of coordinated sensors. A Border Security System watches intruders by using sensor nodes with communication function. The detection of some intruders and the use of a long-term operation system are required in this system. This paper proposes network construction methods of sensor nodes for Border Security Systems that uses a Divide-and-Conquer scheme. The design is based on new local maximal lifetime algorithm and following protocol for strong k- barrier with coordinated sensors. The proposed barrier coverage network construction methods are suitable for Border Security Systems and reduce the power consumption of the whole network system by effective control of sensor nodes.

Wireless sensor network, barrier coverage, local algorithm, data fusion.


1.        T. H. Lai, and A. Arora,“Barrier coverage with wireless sensors,” Proc. ACM International Conference on Mobile Computing and Networking(Mobicom05), ACM,Aug.2005,pp.284
2.        A.Chen,S. Kumar,and T. H. Lai, “Local barrier coverage in wireless sensor networks”.IEEE Transactions on Mobile Computing. vol.9, pp.491-504, April 2010

3.        B. Liu, O. Dousse, J. Wang, and A. Saipulla, “Strong barrier coverageof wireless sensor networks,” Proc. ACM International Symposium on Mobile AdHoc Networking and Computing   (MobiHoc 08),ACM,May.2008, pp.411-420

4.        A.Saipulla,.B.Liu,.G.Xing,X.Fu,andJ.Wang,“Barrier coverage withsensors of limited mobility” Proc. ACM International Symposium onMobile Ad HocNetworkingandComputing(MobiHoc10),ACM,Sep.2010, pp.201-210

5.        N.Ahmed, S.S.Kanhere, and S.Jha, "Probabilistic coverage in wireless sensor networks". Proc.IEEE Conference on Local ComputerNetworks (LCN 05), IEEE Press, Nov.2005,pp. 672–681

6.        M.Hefeeda, H.Ahmadi," A probabilistic coverage protocol forwireless sensor networks". Proc. IEEE International Conference onNetwork Protocols (ICNP 07), IEEE Press, Oct. 2007, pp. 1–10

7.        B.Wang, K.C.Chua, V.Srinivasan, and W.Wang,"Information coverage in randomly deployed wireless sensor networks". IEEE Transactions on Wireless Communications, vol.6,pp .2994–3004, August 2007

8.        G.Yang, G.Qiao, "Barrier information coverage with wirelesssensors" Proc.IEEE Conference on Computer Communications (Infocom 09), IEEE Press,Apr.2009, pp. 918-926

9.        J.He, H.Shi, “Finding barriers with minimum number of sensors inwireless sensor networks” Proc. IEEE International Conference on Communications (ICC 10), IEEE Press,May.2010,pp. 1-5

10.     W.Choi, S.K.Das. “Coverage-adaptive random sensor scheduling forapplication-aware data gathering in wireless sensor networks” Computer Communications. Vol. 29, pp.3476–3482,November 2006

11.     G.Xing, X.Wang, and Y.Zhang,“Integrated coverage and connectivityconfiguration for energy conservation in sensor networks”.ACMTransactions on Sensor Networks,vol.1,pp. 36 – 72, August 2005






Arvind Jaiswal, Gaurav Dubey

Paper Title:

Identifying Best Association Rules and their Optimization Using Genetic Algorithm

Abstract: Data mining is the analysis step of the "Knowledge Discovery in Databases", It is the process that results in the detection of new patterns in large data sets. The main aim of data mining is to pull out knowledge from an existing dataset and transform it into a flexible structure.  In data mining association rule is a popular and easy method to find frequent itemsets from large datasets. In general frequent itemsets are generated from large data sets by applying association rule mining take too much computer time to compute all the frequent itemsets. By using Genetic Algorithm (GA) we can improve the results of association rule mining. Our main purpose is by Genetic Algorithm to generate high quality Association Rules, by which we can get four data qualities like accuracy, comprehensibility, interestingness and completeness. Genetic Algorithms are powerful and widely applicable stochastic search and optimization methods based on the concepts of natural selection and natural evaluation. The advantage of using genetic algorithm is to discover high level prediction rules is that they perform a global search and cope better with attribute interaction than the greedy rule induction algorithm often used in data mining. The main aim of this paper is to find all the frequent itemsets from given data sets using genetic algorithm. In this paper we are using the large dataset and our Experimental results on this dataset show the effectiveness of our approach. This paper provides the major improvement in the approaches for association rule mining using genetic algorithms.

Genetic Algorithm (GA), Association Rule, Frequent itemset,  Support,  Confidence,  Data Mining.


1.        Rupali Haldulakar and Prof. Jitendra Agrawal, “Optimization of Association Rule Mining through Genetic Algorithm”, International Journal on Computer Science and Engineering (IJCSE), Vol. 3 No. 3 Mar 2011, pp. 1252-1259.
2.        Manish Saggar, Ashish Kumar Agarwal and Abhimunya Lad, “Optimization of Association Rule Mining using Improved Genetic Algorithms”IEEE 2004.

3.        Anandhavalli M, Suraj Kumar Sudhanshu, Ayush Kumar and Ghose M.K., “Optimized association rule mining using genetic algorithm”, Advances in Information Mining, ISSN: 0975–3265, Volume 1, Issue 2, 2009, pp-01-04.

4.        Farah Hanna AL-Zawaidah, Yosef Hasan Jbara and Marwan AL-Abed Abu-Zanona, “An Improved Algorithm for Mining Association Rules in Large Databases”, World of Computer Science and Information Technology Journal (WCSIT) ISSN: 2221-0741 Vol. 1, No. 7, 2011, pp. 311-316.

5.        L.Jain, A.Abraham, R.Goldberg, “Evolutionary Multiobjective Optimization”, Second Edition, Springer 2005).International Journal of Data Mining & Knowledge Management Process (IJDKP) Vol.2, No.1, January 2012.

6.        Pei M., Goodman E.D., Punch F. (2000) Feature Extraction using genetic algorithm, Case Center for Computer-Aided Engineering and Manufacturing W. Department of Computer Science.

7.        Stuart J. Russell, Peter Norvig (2008) Artificial Intelligence: A Modern Approach.

8.        Han J., Kamber M. Data Mining: Concepts & Techniques, Morgan & Kaufmann, 2000.

9.        Goldberg, David E. (1989). Genetic Algorithms in Search Optimization and Machine Learning. Addison Wesley. pp. 41.

10.     1S. Dehuri,A. K. Jagadev, A. Ghosh and R. Mall, “Multi-objective Genetic Algorithm for Association Rule Mining Using a Homogeneous Dedicated Cluster of Workstations”, American Journal of Applied Sciences 3 (11), 2006, pp. 2086-2095.

11.     S. Ghosh., S. Biswas., D. Sarkar., and P. Sarkar, “Mining Frequent Itemsets Using Genetic Algorithm,” international Journalof Artificial Intelligence & Applications (IJAIA), Vol.1, No.4, October 2010

12.     A. Ghosh and B. Nath, “Multi−objective rule mining using genetic algorithms,” Information Sciences 163, pp 123-133, 2004.

13.     S. Kotsiantis and D. Kanellopoulos, “Association Rules Mining: A Recent Overview,” GETS International Transactions on Computer Science and Engineering, Vol.32(1), 2006, pp.71-82.

14.     M. Fonesca and J. Fleming, “Multi-objective Optimization and Multiple Constraint Handling with Evolutionary Algorithms,” Part I: A Unified Formulation. IEEE Transactions on Systems, Man and Cybernetics - Part A: Systems and Humans, 28(1), pp. 26-37, 1998.

15.     A. Freitas, “Survey of Evolutionary Algorithms for Data Mining and Knowledge Discovery,” Advances in evolutionary computing: theory and applications, pp 819 – 845, 2003.

16.     LIU, B., HSU, W., CHEN, S., AND MA, Y. 2000. Analyzing the Subjective Interestingness of Association Rules. IEEE Intelligent Systems.

17.     David Beasley et al., “An overview of genetic algorithms”, Part 1 & 2, University Computing, Vol. 15, No. 2 & 4, pp.58-69 & 170-181, 1993.

18.     GHOSH, A., NATH, B. 2004. Multi-objective rule mining using genetic algorithms. Information Sciences 163 pp 123-133.






Divakar Singh, Bal Krishan

Paper Title:

Optimization of Organic Light Emitting Devices

Abstract: A program in MATLAB has been developed  for calculating various parameters e.g., Efficient use of excitation energy by proper use of dopants (by studying exciton density profile as a function of time), locating correct position of emission zone ( location of charge accumulation layer) and thus enabling maximum recombination in single layer and multilayer devices. The extracted features of organic material are used as input vectors for the standard equations, results in increasing the efficiency of OLED. The test results helps in the analysis of identify the fault and help us to use the device more accurately and has a better emission rate compared to the previous time analysis.

OLED, Exciton, Optimization, Organic Material, MATLAB, Device Simulation, Electronic and Optical Model.


1.        Simulating Electronic and Optical Processess in multilayer oled, Beat Rushstaller, Tilman beierlein, heike Riel, J. Campbell Scott, and Walter Riess-IEEE Journal of selected topics in Quantum Electronics, Vol. 9, No .3, may/June 2003.
2.        Christopher M Snowden Solid State Materials, Devices and Applications Group, Department of Electrical and Electronic Engineering, University of Leeds, Leeds LS2 9JT, UK

3.        Wolfgang Brutting, Stefan Berleb, Anton G.Muckl , ‘Devicephysics of organic light-emitting diodes based on molecular materials’, Organic Electronics 2 (2001) 1- 36

4.        H.Bassler, ‘Charge Transport in Disordered Organic Photoconductors - a Monte-Carlo Simulation Study’,Phys.State Sol .(b), 175 (1993),15

5.        I.D. Parker, ‘Carrier tunneling and device characteristics in polymer light emitting diodes’ Journal of Applied Physics. 75 1994, 1656. 

6.        P. W. M. Blom, M. J. M. De Jong, and S. Breedijk, ‘Field dependent electron-hole recombination in polymer light-emitting diodes’, Appl. Phys. Lett., vol. 71, pp. 930-932, 1997.

7.        Y.Kawabe,M.M.Morrell,G.E.Jabbour,S.E.Shaheen,B.Kippelen and N.Peyghambarian, ‘A numerical study of operational characteristics of organic light emitting diodes’ Journal of Applied Physics 84(9) 1998, 5306-14






Minu Rani, Rekha Yadav, Suman Sehrawat

Paper Title:

Study of Clustering and Neighbor Detection Protocol in MANET for Energy Efficiency

Abstract: Now a days for quick communication various of the communication protocol is being used. Out of them MANET mobile ad-hoc network is widely attracting all the research. Various protocol is being used for the detection methods and reducing the battery life. In this paper we are introducing a complete study and comparison of the modern MANET technology and clustering in case of mobile ad-hoc network. The analyzed result for the algorithm is given for the detection of neighbor detection algorithm. The studied result to insuring reduced energy consumption is by using color Petri net (CPN) tool. To calculate the weight node is also done to ensure research fruitful.

MANET, NDP, Clustering in MANET, CWP.


1.        C Siva Ram Murthy and B S Manoj. Ad Hoc Wireless Networks. Pearson Education, 2005.
2.        http://trends-in-telecoms.blogspot.com/2011/05/4g-wirelessarchitecture-and.html.
3.        Kurt Jensen. Coloured Petri Nets. Springer Verlag, 1992.
4.        L. M. Feeney. An energy consumption model for performance analysis of routing protocols for mobile ad hoc networks. Journal of Mobile Networks and Applications, 6(3):239–249, 2001.
5.        S.Basagni. Distributed and mobility adaptive clustering for multimedia support in multi-hop wireless networks. In Proceedings of vehicular technology conference VTC, volume 2, pages 889–893, 1999.
6.        C Siva Ram Murthy and B S Manoj. Ad Hoc Wireless Networks. Pearson Education, 2005.
7.        C K Toh. Ad Hoc Mobile Wireless Networks: Protocols and Systems. Prentice Hall PTR, 2002.
8.        C. C. Chiang, H.K. Wu, W.Liu, and M. Gerla. Routing in clustered multihop, mobile wireless networks with fading channel. In Proceedings of IEEE Singapore International Conference on Networks SICON’ 97, pages 197–212, 1997.
9.        I. Chlamtac, M.Conti, and J.-N. Liu. Ad hoc networking: imperatives and challanges. Ad Hoc Networks, 1:13–64, 2003.
10.     I. Chlamtac and A. Farago. A new approach to the design and analysis of peer-to-peer mobile networks. Wireless Networks, 5:149–156, 1999.
11.     T. Ohta aand S. Inoue and Y. Kakuda. An adaptive multi-hop clustering scheme for highly mobile ad hoc networks. In proceedings of sixth international symposium on autonomous decentralized systems(ISADS’03), Pisa, Italy, April 2003.
12.     C. R. Lin and M. Gerla. A distributed control scheme in multi-hop packet radio networks for voice/data traffic support. In Proceedings of IEEE GLOBECOM, pages 1238–1242, 1995.
13.     S Bandyopadhyay and E J Coyle. An energy efficient hierarchical clustering algorithm for wireless sensor networks. In Proceedings of INFOCOM 03. IEEE, April 2003.
14.     S. Basagni, I. Chlamtac, and A. Farago. A generalized clustering algorithm for peer-to-peer networks. In Proceedings of Workshop on Algorithmic aspect of communication (satellite workshop of ICALP), July 1997.
15.     A Ephremides. Energy concerns in wireless networks. IEEE Wireless Communications, pages 48–59, 2002.
16.     suchismita chnara , “analysis and design of protocol for clustering in mobile adhoc netwok” submitted dissertation for doctorate at NIT Rourkela 2011 .






P.  M. Chavan, Manan C. Jadhav, Jinal B. Mashruwala, Aditi K. Nehete, Pooja A. Panjari

Paper Title:

Real Time Emotion Recognition through Facial Expressions for Desktop Devices

Abstract: Thepaper states the technique of recognizing emotion using facial expressions is a central element in human interactions. By creating machines that can detect and understand emotion, we can enhance the human computer interaction. In this paper, we discuss a framework for the classification of emotional states, based on still images of the face and the implementation details of a real-time facial feature extraction and emotion recognition application are discussed. The application automatically detects frontal faces from the captured image and codes them with respect to 7 dimensions in real time: neutral, anger, disgust, fear, joy, sadness, surprise. Most interestingly the outputs of the classifier change smoothly as a function of time, providing a possibly worth representation of code facial expression dynamics in a fully automatic and unnoticeable manner. The main objective of the paper is the real-time implementation of a facial emotion recognition system. The system has been deployed on a Microsoft’s Windows desktop.

Real time, facial expression, emotion recognition.


1.        MarianStewart Bartlett, Gwen Littlewort, Ian Fasel, Javier R. Movellan, Real Time Face Detection and Facial Expression Recognition:         Development andApplications to Human Computer Interaction,Machine perception laboratory Institute for Neural Computation, University of California, San Diego, CA.
2.        Liyanage C De Silva, Suen Chun Hui, Real Time Facial Feature Extraction and Emotion Recognition 2003.

3.        Abdesselam Bouzerdoum, Son Lam Phung, Fok Hing Chi Tivive, Peiyao LiFeature, Selection For Facial Expression Recognition.

4.        Irfan A. Essa,Coding, Analysis, Interpretation, and Recognition of Facial Expressions.






K. P. Shaji, I.Alsheba, Y. A. Syed Khadar, S. Kannan

Paper Title:

Multiparameter Monitoring and Fault Indication Using Inductive Power Transfer System

Abstract: The paper aims at demonstrating communication capabilities of IPT. For this data communication is performed between two modules using the concept of IPT. IPT was deemed to be the best solution to the system houses a multi parameter acquisition module such as temperature, speed, voltage, current and data transfer from the motor. The receiver side is another microcontroller coupled to an inductive coil that gets the data and displays in the LCD.  A brief background to IPT (Inductive Power Transfer) technology and its applications is given and the design criteria for the paper are defined in detail. To be accurate, IPT data communication helps to reduce unnecessary wire connections and data is transmitted without any touch.  Further the paper can be enhanced by looking for fault analysis inside the motor. This can be done by analyzing various parameters of the motor. A novel two-way IPT communication system was designed, which worked on the concept of pulsing the system on and off to send data serially. The paper involves transmission of data through inductive flux without any contact between the two modules. Further as no frequency tunings or any calibration is required between different modules a single system can be used with multiple clients. This reduces a lot of hazards such as interference with other modules and RF transmitters in the vicinity.

Switching, LCD, LED, Port.


1.        Sunil S.Rao (2005)”Protection and Switch gear”, Khanna
2.        K.R. Botker(2005),” Integrated circuits”, Tata McGraw Hill

3.        Rodger Richey,” PIC Microcontroller” AMSH Application 2nd Edition

4.        www.atmel.com
5.        www.microchip.com

6.        www.datasheet4u.com

7.        www.IR.com

8.        www.ieee.org