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Volume-1 Issue-3: Published on August 10, 2012
56
Volume-1 Issue-3: Published on August 10, 2012

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Volume-1 Issue-3, August 2012, ISSN:  2278-3075 (Online)
Published By: Blue Eyes Intelligence Engineering & Sciences Publication Pvt. Ltd. 

Page No.

1.

Authors:

Probal Banerjee, Pallab Banerjee, Shweta Sonali Dhal

Paper Title:

Comparative Performance Analysis of ANN Implemented LMS with ANN for Channel Estimation in AWGN Channel Scenario

Abstract:  In this paper we have done channel estimation using the concepts of LMS algorithm, after that we have implemented the logic of LMS algorithm using the concepts of Supervised Artificial Neural Network and then we have performed channel estimation directly applying the concepts of Supervised Artificial Neural Network. Finally we have compared the performances (BER v/s SNR and Throughput v/s SNR) of these three methods for channel estimation under AWGN channel scenario. Matlab (version 7.9) is used here as the simulation platform.

Keywords:
  Channel estimation, LMS, Artificial Neural Network, BER, Throughput


References:

1.        T.Paul, P.Karmakar, S.Dhar, ”Comparative Study of Channel Estimation Algorithms under Different Channel Scenario,” International Journal of Computer Applications,Volume:34,Number:7,doi:10.5120/4113-5927, November’2011.
2.        Ye Li, Nambirajan Seshadri, Sirikiat Ariyavisitakul, “Channel Estimation for OFDM Systems with Transmitter Diversity in Mobile Wireless Channels”, IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 17, NO. 3, MARCH 1999

3.        A. Soysal and S. Ulukus. Optimizing the rate of a correlated MIMO link jointly over channel estimation and data transmission parameters. In Conference on Information Sciences and Systems, March 2008.

4.        T. Yoo and A. Goldsmith. Capacity and power allocation for fading MIMO channels with channel estimation error. IEEE Transactions on Information Theory, 52(5):2203–2214, May 2006.

5.        Ye Li, Andreas F. Molisch and Jinyun Zhang, “Channel Estimation and Signal Detection for UWB”, MITSUBISHI ELECTRIC RESEARCH LABORATORY, TR-2003-74 November 2003

6.        P.Karmakar, B.Roy, T.Paul, “Target Classification: An application of Artificial Neural Network in Intelligent Transport System”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 2, Issue 6, June 2012, ISSN: 2277 128X. 

7.        Guangmin Sun , Jing Wang, Shengfeng Qin , Jingfang Na, “Radar target recognition based on the multi-resolution analysis theory and neural network”, Pattern Recognition Letters 29 (2008) 2109–2115,ELSEVIER

8.        R. Vicen-Bueno et al, ” Artificial Neural Network-Based Clutter Reduction Systems for Ship Size Estimation in Maritime Radars”, EURASIP Journal on Advances in Signal Processing, Vol.2010, doi:10.1155/2010/380473.

9.        T. Yoo and A. Goldsmith. Capacity and power allocation for fading MIMO channels with channel estimation error. IEEE Transactions on Information Theory, 52(5):2203–2214, May 2006.

10.     Ye Li, Andreas F. Molisch and Jinyun Zhang, “Channel Estimation and Signal Detection for UWB”, MITSUBISHI ELECTRIC RESEARCH LABORATORY, TR-2003-74 November 2003

11.     P.Karmakar, B.Roy, T.Paul, “Target Classification: An application of Artificial Neural Network in Intelligent Transport System”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 2, Issue 6, June 2012, ISSN: 2277 128X. 

12.     Guangmin Sun , Jing Wang, Shengfeng Qin , Jingfang Na, “Radar target recognition based on the multi-resolution analysis theory and neural network”, Pattern Recognition Letters 29 (2008) 2109–2115,ELSEVIER

13.     R. Vicen-Bueno et al, ” Artificial Neural Network-Based Clutter Reduction Systems for Ship Size Estimation in Maritime Radars”, EURASIP Journal on Advances in Signal Processing, Vol.2010, doi:10.1155/2010/380473


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2.

Authors:

Rajat Chaudhary, Prem Singh, Ambika Agarwal

Paper Title:

A Security Solution for the Transmission of Confidential Data and Efficient File Authentication Based on DES, AES, DSS and RSA

Abstract:   Data security is an integral part of web based business applications like insurance, banking etc. These applications require a secure infrastructure to meet the security requirements of confidentiality, endpoint authentication, message integrity and no repudiation. Document encryption/decryption and signatures/validation are the data security standards that define XML vocabularies and processing rules to meet these security requirements. In this paper, we present a how a file securely passes from sender (server) to the receiver (client) through a central gateway with web services applications which mean a secure architecture for the exchange of confidential documents. Designing a secured electronic system architecture i.e. connected to the central gateway through which the whole work is established and takes place accordingly to pass only the files over the internet and have security features like digital signatures. Various algorithms, implementations and coding have been developed for encryption/decryption, signatures/validations and web services.

Keywords:
  Confidentiality, Authentication, Algorithms and Methods.


References:

1.        Haas, H., Seminar, “XML Security: Signature, Encryption, and Key Management”,    December 2005.http://www.w3.org/2004/Talks/0520-hhxmlsec/
2.        Organization for the Advancement of Structured Information Standards (OASIS), Web Services Security: SOAP Message Security 1.0. (2004).

3.        Chi Chester: Wiley, “E-commerce: fundamentals and applications”, [Henry Chanetal.], pp 203-217, (2001).

4.        “Cryptography and Network Security” by- William Stallings.

5.        Wikipedia, the Free Encyclopedia, “WS-Security”, no. Wikimedia Foundation, Inc. (2006).
http://en.wikipedia.org/wiki/Web_Services_Security
6.        W3C, “Decryption Transform for XML Signature”, W3C Candidate Recommendation: March 04, 2002. 
http://www.w3.org/TR/2002/CR-    xmlenc-decrypt-20020304
7.        ZipPay MasterCard® Gift Card is issued by MetaBank pursuant to license by MasterCard International Incorporated, Columbus Data services, (2007). http://www.zippaycard.com/terms.htm

8.        The Apache XML Project, “Welcome to XML Security”, Apache XML Security, published on September, 2007.  http://santuario.apache.org/

9.        University of West Indies at Cave Hill, “Decryption/Encryption”, published on 2003. http://scitec.uwichill.edu.bb/cmp/online/ CS22K/security/decrypt_encrypt.htm

10.     Santa Barbara, Calif., “Advances in cryptology - CRYPTO '89: proceedings”, CRYPTO (Conference-1989), published by Springer, XII, 634 p. (1990).

11.     “Private key (Symmetric) Encryption”, MyCrypto.net, (2008). http://www.mycrypto.net/encryption/private_key_encryption.html

12.     Garrett, Paul B., “Making, breaking codes: an introduction to cryptography”, published by Prentice Hall, XIX, 524 p., (2001).

13.     “Encryption Algorithms”, CES Setting the Standard, (2003).
http://www.cescomm.co.nz/about/algorithms.html
14.     FIPS PUB 197, Federal Information Processing Standards Publication, “Advance Encryption Standard (AES)”, U.S. Department of Commerce/National Institute of Standards and Technology, dated on November 2001.
http://csrc.nist.gov/publications/fips/fips197/fips-197.pdf
15.     Wikipedia, the Free Encyclopedia, “Advanced Encryption Standard (AES)”, no. Wikimedia Foundation, Inc. (2008). http://en.wikipedia.org/wiki/Advanced_Encryption_Standard

16.     FIPS PUB 46-3, Federal Information Processing Standards Publication, “Data Encryption Standard (DES)”, U.S. Department of  Commerce/National Institute of Standards and Technology, dated on October 1999.
http://csrc.nist.gov/publications/fips/fips46-3/fips46-3.pdf
17.     FIPS PUB 186, Federal Information Processing Standards Publication 186, announcing the Standard for, “Digital Signature Standard (DSS)”, dated on May 1994.  
http://www.itl.nist.gov/fipspubs/fip186.htm
18.     Wikipedia, the Free Encyclopedia, “RSA”, no. Wikimedia Foundation, Inc. (2008).
http://en.wikipedia.org/wiki/RSA
19.     Bilal Siddiqui, CEO, WAP Monster, “Exploring XML Encryption Part-1”, IBM, Demonstrating the secure exchange of structured data, published on March 2002.
http://www.ibm.com/developerworks/xml/library/x-encrypt/#code1
20.     W3C, “XML Signature Features”, W3C Recommendation, (2002).
http://www.w3.org/2004/Talks/0520-hh-xmlsec/  slide6-0.html
21.     Robert Richards, “XML Security”, published on September 2006.                               http://66.102.9.104/search?q=cache:KqMFAXAetVcJ:cdatazone.org/talks/php_works_2006/xml_security.ppt+XML+Security&hl=en&ct=clnk&cd=5&client=firefoxa

22.     Sean Mullan, “Programming with the Java XML Digital Signature API”, Sun Microsystems, Sun Developer Network (SDN), March 2007.http://java.sun.com/developer/technicalArticles/xml/dig_signature_api/


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3.

Authors:

Zhenxing Luo

Paper Title:

Robust Energy-based Target Localization in Wireless Sensor Networks in the Presence of Byzantine Attacks

Abstract:   This paper presents a robust energy-based target localization method in wireless sensor networks (WSNs) in the presence of Byzantine attacked sensors. Byzantine attacks will cause sensors to send false information to the fusion centre and disturb the target localization method. Therefore, a robust energy-based target localization method is needed to counter the Byzantine attacks and a method is presented in this paper. The method presented in this paper assumes that the fusion centre knows the exact information about the percentage of Byzantine sensors and the attack probability. If the fusion centre does not know the Byzantine attack information, a Byzantine sensor identification scheme can be used to identify Byzantine sensors. Results showed the robust energy-based target localization method could provide better performance results than the energy-based target localizatin method, which did not consider Byzantine attacked sensors. Moreover, simulation results showed that the Byzantine sensor identificaiton scheme could identify most Byzantine attacked sensors.

Keywords:
  Byzantine sensors, Cramer-Rao lower bound, maximum likelihood estimation, reputation value.


References:

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

3.       Z. X. Luo, “A censoring and quantization scheme for energy-based target localization in wireless sensor networks”, To appear in Journal of Engineering and Technology.

4.       K. Agrawal, A. Vempaty, C. Hao, and P. K. Varshney, "Target localization in Wireless Sensor Networks with quantized data in the presence of Byzantine attacks," 2011 Conference Record of the Forty Fifth Asilomar Conference on Signals, Systems and Computers (ASILOMAR), vol., no., pp.1669-1673, 6-9 Nov. 2011

5.       Z. X. Luo and T. C. Jannett, “Performance Comparison between Maximum Likelihood and Heuristic Weighted Average Estimation Methods for Energy-Based Target Localization in Wireless Sensor Networks”, in Proceedings of the 2012 IEEE Southeastcon, Orlando, FL, Mar. 2012, in press. 

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

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

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

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

10.     M. P. Michaelides and C. G. Panayiotou, "Fault tolerant maximum likelihood event localization in sensor networks using binary data," IEEE Trans. Signal Process.,  vol. 16, no. 5, pp. 406-409, May 2009.

11.     M. P. Michaelides and C. G. Panayiotou, "SNAP: Fault tolerant event location estimation in sensor networks using binary data," IEEE Trans. Comput., vol. 58, no. 9, pp. 1185-1197, Sept. 2009.

12.     S. Marano, V. Matta, and Lang Tong, "Distributed Detection in the Presence of Byzantine Attacks", IEEE Transactions on Signal Processing, vol.57, no.1, pp.16-29, Jan. 2009

13.     A.S. Rawat, P. Anand, H. Chen, and P.K. Varshney , "Collaborative Spectrum Sensing in the Presence of Byzantine Attacks in Cognitive Radio Networks", IEEE Transactions on Signal Processing, vol.59, no.2, pp.774-786, Feb. 2011.

14.     K. Guan, L. Gharai, S. Dehnie, R. Ghanadan, and S. Kumar, “Trust management for distributed decision fusion in sensor networks,” in Proc. of the 12th International Conference on Information Fusion Fusion, 2009.

15.     R. Chen, J. M. Park, and K. G. Bian, “Robust distributed spectrum sensing in cognitive radio networks”, in Proc. IEEE INFOCOM, 2008, pp. 1876–1884.

16.     P. Kaligineedi, M. Khabbazian, and V. K. Bhargava, "Malicious User Detection in a Cognitive Radio Cooperative Sensing System", IEEE Transactions on Wireless Communications, vol. 9, pp. 2488-2497, 2010.


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4.

Authors:

Srikanth V, Leelavathi G

Paper Title:

Video Monitoring System Based on ARM9

Abstract:   The preceding and existing video surveillance system which entails high end cameras, video servers, network switch and monitoring PC all these resources leads to complexity, expensive, high power consumption and also requires more area to establish. In order to overcome the hitch in the preceding and existing system, this paper presents a proficient where it uses few hardware resources for the implementation of the video monitoring system. S3C2440 is a very good ARM9 family processor providing a camera interface which is very conducive to the application and development. Embedded Linux is chosen as operating system which provides open-source, multi-task, multi-process, highly modular, multi-platform support, performance and stability to the system. The design system achieves maximum frame rate of 30fps with a resolution of 1280x1024 if individual camera is initialized and 10fps with a maximum video resolution of 340x480 if two cameras are initialized. The application of this paper can be implemented at security surveillance, patient monitoring in hospitals and polling booths.

Keywords:
  ARM9, MINI 2440, MJPG-streamer, JPG, IP address,


References:

1.        Min Zhang, Jin-guang Sun and Shi Wang,”Research and Implementation of the CMOS Camera Device Driver Based on S3C2440”, Intelligent Computation Technology and Automation (ICICTA), 2010 IEEE International Conference, Vol-2, 1039 – 1042, 11-12, May 2010.
2.        Denan Li, Zhiyun Xiao,” Design of embedded video capture system based on ARM9”, Electric Information and Control Engineering (ICEICE), 2011 IEEE International Conference, 2092 – 2095, 15-17, April 2011.

3.        Yi-Shin Tung , Ja-Ling Wu and Ho Chia-Chiang ” Architecture Design of an MPEG-4 System”, Consumer Electronics, 2000. ICCE. 2000 Digest of Technical Papers. IEEE International Conference, 122 – 123, 2000.

4.        Guerri, J.C.,Pajares, A.,Esteve, M,Palau, C and Leon, A,” A feedback packet-level error control for real-time applications in wireless networks” , Vehicular Technology Conference, 1999. VTC 1999 - Fall. IEEE VTS 50th , Vol 2,879 – 883, 1999.

5.        Jianyu Dong; Chao He; Zheng, Y.F,” AVP: a highly efficient real-time protocol for multimedia communications on Internet “,Information Technology: Coding and Computing, 2001. Proceedings. IEEE International Conference, 280 – 284, 2001.

6.        Parthasarathy, V.; Bharathi, A.V.; Rhymend Uthariaraj, V,” Performance analysis of embedded media applications in newer ARM architectures “,Parallel Processing, 2005. ICPP 2005 Workshops.IEEE  International Conference Workshops, 210 – 214, 2005.

7.        Hyung Su Lee; Hee Young Youn; Hye Dong Jung,” Packet control mechanism for seamless multimedia streaming service in wireless network “,Advanced Communication Technology, 2006. ICACT 2006. The 8th International Conference , Vol 3, 6 pp. – 1838, 20-22 Feb. 2006.

8.        Lihong Xu, Shuhua Ai,” A New Feedback Control Strategy of Video Transmission Based on RTP”, Industrial Electronics and Applications, 2006 1ST IEEE Conference, pp. 1 – 4, 24-26 May 2006.


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5.

Authors:

Roopashree S S, Manjunath Lakkannavar

Paper Title:

The Controlling of Mobile Robot Based on ARM9

Abstract:   In this proposed work the robot is built using two dc motors for the movement which is administered by AT89C51 Microcontroller, the obstacle is detected by ultrasonic sensor, the controlling of the robot is done by using the resources of MINI 2440 development board. The application of this system can be implemented at archeological survey, place of natural disaster and industrial applications. The previous system of Mobile robot which relies on PC System to coordinate the whole resources, in order to achieve advanced arithmetic among different module, and to realize intelligent behavior just as human beings by plan and decision. In order to overcome the hitch in the previous system, this work is proficient where it is stable and reliable, with low-power, tiny-volume and high integration.

Keywords:
  ARM9, L293D, LCD, MINI 2440, ultrasonic sensor, Linux.


References:

1.        Shuangyou Wang, Zhi’an Wang and Xuhui Wang “The Design of PC System for Mobile Robot Based on ARM9”. International Conference of Information Science & Engineering, PP 292-295, 2010.
2.        Luca Bascetta and Paolo Rocco. “Revising the Robust-Control Design for Rigid Robot Manipulators” IEEE TRANSACTIONS ON ROBOTICS, VOL. 26,PP.180-187, NO. 1, 2009.

3.        Yong Zhang, Brandon K. Chen, Xinyu Liu, and Yu Sun.” Autonomous Robotic Pick and Place of Micro-objects”. IEEE Transactions On Robotics, VOL. 26, PP. 200-207,NO. 1, FEBRUARY 2010.

4.        MINI 2440 user’s manual, 2004.

5.        Andreas Kolling, and Stefano Carpin. “Pursuit-Evasion on Trees by Robot Teams”. IEEE TRANSACTIONS ON ROBOTICS, VOL. 26, PP. 32-47, NO. 1, FEBRUARY 2010.

6.        Andreas M¨uller ” Consequences of Geometric Imperfections for the Control of Redundantly Actuated Parallel Manipulators”. IEEE TRANSACTIONS ON ROBOTICS, VOL. 26,  PP. 21-31, NO. 1, FEBRUARY 2010.

7.        Samsung S3C2440A, User’s manual, 2004. 

8.        Torsten Kroger and Friedrich M. Wahl” Online Trajectory Generation: Basic Concepts for Instantaneous Reactions to Unforeseen Events”. IEEE TRANSACTIONS ON ROBOTICS, VOL. 26, PP. 94-111, NO. 1,  FEBRUARY 2010.

9.        Matthew Baumann, Simon L´eonard, Elizabeth A. Croft, and James J. Little.” Path Planning for Improved Visibility Using a Probabilistic Road Map”. IEEE TRANSACTIONS ON ROBOTICS, VOL. 26, PP. 195-200, NO. 1, FEBRUARY 2010.

10.     Data sheet of lv-maxsonar-ez1 and Data sheet of LCD 16x2.

11.     Ravinder S. Dahiya, Giorgio Metta, Maurizio Valle and Giulio Sandini.” Tactile Sensing-From Humans to Humanoids”. IEEE TRANSACTIONS ON ROBOTICS, VOL. 26, PP. 1-20, NO. 1, FEBRUARY 2010

12.     Dekneuvel E and H.Medromi.” AN ULTRASONIC SOUND INTELLIGENT SENSOR FOR A MOBILE ROBOT PERCEPTION SYSTEM”. Principles, design and experimentations. VOL.2, PP. 513-520, NO.1 , 1999.

13.     Zou Yi, Ho Yeong Khing, Chua Chin Seng, and Zhou Xiao Wei.” Multi-ultrasonic Sensor Fusion for Mobile Robots”. IEEE Intelligent Vehicles Symposium. VOL.6 , PP. 387-391, NO.2 , October 2000.

14.     K. Ohtani  ” Shape Recognition by Network Configuration of Ultrasonic Sensor Array and CCD Image Sensors”. The 47th IEEE International Midwest Symposium on Circuits and Systems. VOL.77 , PP.509-512 , NO.5 , December 2008.

15.     Fuquan Pan , Lixia Zhang, Gang Sun and Jiyou Li.” Design of Vehicle Reversing Collision Avoidance Device Based on Single Chip Computer”. International Conference on Power Electronics and Intelligent Transportation System. VOL.19, PP. 223-226, NO.4, 2009.

16.     Ying-Wen Bai, Li-Sih Shen and Zong-Han Li. “Design and Implementation o f an Embedded Surveillance System by Use of Multiple Ultrasonic Sensors”. IEEE Paper. Vol. 2, PP. 1-3, NO. 1, 2010.

17.     Ying-Wen Bai, Li-Sih Shen and Zong-Han Li.” Design and Implementation of an Embedded Home Surveillance System by Use of Multiple Ultrasonic Sensors”. Design and Implementation of an Embedded Home Surveillance System by Use of Multiple Ultrasonic Sensors. VOL. 56,  PP. 119-124, NO. 1, FEBRUARY 2010.

18.     Zhen Wang” The Design of a Speed Regulator of DC motor Based on TMS320LF2407A and AT89C51”.  VOL. 2, PP. 121-126, NO. 1, December 2010.

19.     Luo Genghe, Guo YanLing and Yan Jie. “The Communication Interface Design of  AT89C51 Preparation Robot Based on Serial”. IEEE Intenational paper. VOL. 2, PP. 19-25, NO. 1, November 2011.

20.     Endrowednes Kuantama, Leonardy Setyawan and Jessie Darma. “Robogotchi. on Emoticon Robot”. Measurement, Instrumentation, and Sensor Handbook CRCnet. VOL. 2, PP. 90-94. NO. 2, December 2011.


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6.

Authors:

Hemanth Kumar G, Manjunath Lakkannavar

Paper Title:

The Design of Granary Environmental Monitoring and Control System Based On ARM9 and ZIGBEE

Abstract:   Grain storage is a vital component in the economy and the society. The quality and safety of grain storage are related to the hundreds of millions of people. In the process of grain storage, temperature and humidity are two major ecological factors that can affect the grain quality. Therefore, the parameters of temperature, humidity must be in accurate and real-time monitoring by supervisory systems in large granaries. The automatic monitoring of the grain storage will help us to improve the operation levels of grain storage, reduce the grain losses during stored procedure and reduce labor intensity. This project designs an environment monitoring system of the granary combining Embedded and ZigBee wireless sensor network technology. Using ZigBee wireless sensor network to complete acquisition and transmission of environment parameters and using ARM9 to achieve precise control of the barn environment as system data controller and using GSM to achieve the system's remote control, it greatly improves the flexibility and scalability of the warehouse management which sends available data to grain depot manager (Database management) in time and filters invalid data on the spot. It makes many important aspects not need manager to complete on the scene, which saves a lot of manpower and material resources and improves labor productivity.

Keywords:
 ARM9, MINI 2440, ZIGBEE,GSM,Visual studios


References:

1.        Sun Fang and Li Qiang, “A Study And Design Of A Wireless Serial Port Hub Based On ZigBee,” Control and Automation Publication Group,vol.24, 2008.
2.        Lv Jie, GPRS technology, Beijing University of posts and telecommunications press, pp.117-139, 2001.

3.        He Caijun and Fang Houhui, “Application of ZigBee Technology in Industrial Monitoring Network,” Computer system,” vol.19,2010.

4.        Wei Dongshan, Complete Guide to Embedded Linux Application Development, Post & telecom press, pp.170-180, 2008.

5.        Zhang Jianwu, LiJie, and Yao Yingbiao, Design and Development of Embedded System, XiDian university press, 2009.

6.        Jiang Ting and Zhao Chenglin, ZigBee purple crazy Technology and Its Application IEEE 802.15.4, Beijing university of posts and telecommunications press,

7.        Ni Jili, QT and window design of the Linux operating system, Beijing industry press, pp. 156-187, 2006.

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7.

Authors:

Meshram Vaibhav Bhimrao, Ramesh T

Paper Title:

ASIC Implementation of HDB3 Codec

Abstract:   This paper demonstrates the working of HDB3 encoder & decoder and also its implementation at chip level. The HDB3 code consist of 3 modules namely violation module, balance module and polarity correction module. The decoder consists of violation detection module, balance detection module and polarity detection module. The encoder design accepts serial data from the information source in binary format. HDB3 encoder encodes the binary data into two bit symbol data. The encoder data is transmitted over a physical channel. At receiver’s end when the data is present, the decoder detects the violation symbol and balance symbol using the violation and balance detection module. The polarity is restored by the polarity detection module. The HDB3 codec is a modified AMI generator, the design is targeted on 180nm technology provided by JAZZ foundry. The HDB3 codec’s front-end design development and verification is carried out using QuestaSim simulator. ASIC implementation of HDB3 codec is done using SYNOPSYS tools.

Keywords:
 HDB3 codec.


References:

1.        Xiaohua Wang, Ning Tang, Songqing Zhou, Yanggang Yin, “ASIC design of the HDB3 encoder chip”, 2011 Fourth International Conference on  Intelligent Computation Technology and Automation.
2.        Yang Zhang, Xiumin Wang, Yuduo Wang, “A New  Design of HDB3 Encoder and Decoder based on FPGA”, 2009 Ninth International Conference on Hybrid Intelligent Systems

3.        Zhang Chan-sen, Xu Qi, “A Design of HDB3 CODEC based on FPGA”, 2010, IEEE.

4.        Daniel R. Hicks, “Tale of an IC Design Engineer-HDB3 encoder/decoder circuit”.

5.        H.Kobayashi, “A Survey of Coding Schemes for Transmission or Recording of Digital  Data,”IEEE Trans. on Communications, Vol.  COM-19, p. 1087 (Dec. 1971).

6.        A. Brosio, U. DeJulio, V. Lazzari, R. Ravaglia, and A. Tofanelli, “A Comparison of Digital Subscriber Line Transmission Systems Employing Different Line Codes,” IEEE
Trans. on Communications, Vol. COM-29 (11), p. 1581 (Nov. 1981).

7.        R.F. Lyon, “Two-Level Block Encoding for Digital Transmission,” IEEE Trans. on Communications, Vol. COM-21 (12), p. 1438 (Dec. 1973).

8.        E. Kretzmer, “Generalization of a Technique for Binary Data Communication,” IEEE Trans. on Communication Tech., Vol. COM-14, (Feb. 1966).

9.        Rung-Bin Lin and Meng-ChiouWu. A new statistical approach to timing analysis of VLSI circuits. In VLSI ’98: Proceedings of the Eleventh International Conference on VLSI Design: VLSI for Signal Processing, page 507, Washington, DC, USA, 1998. IEEE Computer Society.

10.     Anirudh Devgan and Chandramouli Kashyap. Block-based static timing analysis with uncertainty. In ICCAD ’03: Proceedings of the 2003 IEEE/ACM international conference on Computer-aided design, page 607, Washington, DC, USA, 2003. IEEE Computer Society.

11.     Aseem Agarwal, Kaviraj Chopra, and David Blaauw. Statistical timing based optimization using gate sizing. In DATE ’05: Proceedings of the conference on Design, Automation and Test in Europe, pages 400–405, Washington, DC, USA, 2005. IEEE Computer Society.

12.     J. L. Neves and E. G. Friedman. Design  methodology for synthesizing clock distribution  networks exploiting nonzero localized clock skew. IEEE Transactions on Very Large Scale Integration  (VLSI) Systems, 4(2):286–291, June 1996.

13.     J. N. Franklin and J. R. Pierce, “Spectra and Efficiency of Binary Codes without DC,” IEEE Trans. on Communications, Vol. COM-20 (6), p. 1182 (Dec. 1972).

14.     Assuncao P,"Post-processing of MPEG - 2 coded video for transmission at lower bit rates," IEEE IntConfAcoust, Speech, Signal Processing, 1996 (4):1998 - 2001.

15.     R. H. J. M. Otten, Automatic Floorplan Design, Proc. 19th ACM/IEEE Design Automation Conf. (1982), pp. 261-267.

16.     Lou Scheffer. Explicit computation of performance as a function of process variation. In TAU ’02: Proceedings of the 8th ACM/IEEE international workshop on Timing issues in the specification and synthesis of digital systems, pages 1–8, New York, NY, USA, 2002. ACM Press.

17.     S. R. Nassif. Modeling and analysis of manufacturing variations. In Custom Integrated Circuits, 2001, IEEE Conference on., pages 223–228, San Diego, CA, May 2001.

18.     Ngspice Circuit Simulator. http://ngspice.sourceforge.net.http://www.cpe.ku.ac.th/~nguan.


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8.

Authors:

Paras Chawla, Ruchi Mittal, Kavita Grewal

Paper Title:

Hybrid Filtering Technique for Image Denoising Using Artificial Neural Network

Abstract:  Image enhancement and restoration in a noisy environment are fundamental problems in image processing. Various filtering techniques have been developed to suppress noise in order to improve the quality of images. Many filters for image processing are designed assuming a specific noise distribution. In the medical field image processing play an important role because most of the diseases are diagnosed by means of medical images. In order to use these images for the diagnosing process, it must be noiseless. However, most of the images are affected by noises and artifacts. Hence an effective technique for denoising medical images particularly in Computed Tomography (CT) is necessary, which is a significant and most general modality in medical imaging. In order to achieve this denoising of CT images, an effective CT image denoising technique is proposed. The proposed technique remove the Additive white Gaussian Noise from the CT images and improves the quality of images. The proposed work is comprised of three phases; they are preprocessing, training and testing. In the preprocessing phase, the CT image which is affected by the AWGN noise is transformed using multi wavelet transformation. In the training phase the obtained multi-wavelet coefficients are given as input to the Adaptive Neuro-Fuzzy Inference System (ANFIS). In the testing phase, the input CT image is examined using this trained ANFIS and then to enhance the quality of the CT image thresholding is applied and then the image is reconstructed. Hence, the quality enhanced and the denoising CT images are obtained in an effective manner.

Keywords:
 CT image; denoising; Additive White Gaussian Noise (AWGN); multi-wavelet transformation; Adaptive Neuro- Fuzzy Inference System (ANFIS); thresholding.


References:

1.        YangWang and Haomin Zhou, "Total Variation Wavelet-Based Medical Image Denoising", International Journal of Biomedical Imaging, Vol. 2006, pp.1-6, January 2006
2.        Ahmed Badawi, "Scatterer Density in Nonlinear Diffusion for Speckle Reduction in Ultrasound Imaging: The Isotropic Case", International Journal of Biological and Life Sciences, Vol. 2, No. 3, pp.   149-167, 2006

3.        Fernanda Palhano Xavier de Fontes, Guillermo Andrade Barroso and Pierre Hellier, "Real time ultrasound image denoising", Journal of Real-Time Image Processing, Vol. 1, pp.1-14, April 2010

4.        Shujun Fu, Qiuqi Ruan, Wenqia Wang and Yu Li, "Feature Preserving Nonlinear Diffusion for Ultrasonic Image Denoising and Edge Enhancement", World Academy of Science, Engineering and Technology, Vol. 2, pp. 148-151, February 2005

5.        Tanaphol Thaipanich and Jay Kuo, "An Adaptive Nonlocal Means Scheme for Medical Image Denoising", In Proceedings of SPIE Medical Imaging, Vol. 7623, San Diego, CA, USA, February 2010

6.        Su Cheol Kang and Seung Hong Hong, "A Speckle Reduction Filter using Wavelet- Based Methods for Medical Imaging Application", In Proceedings of 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, Vol. 3, pp. 2480-2483, Istanbul, Turkey, October 2001

7.        Jose V. Manjón, Neil A. Thacker, Juan J. Lull , Gracian Garcia-Marti , Luis Marti-Bonmati and Montserrat Robles, "Multicomponent MR Image Denoising", Journal of Biomedical Imaging, Vol. 2009, No. 18, pp. 1-27, 2009
8.        Perona and Malik, “Scale-space and edge detection using anisotropic diffusion”, IEEE Transaction on Pattern Analysis and Machine Intelligence, Vol. 12, No. 7, pp. 629-639, 1990
9.        Manjon, Robles and Thacker, “Multispectral MRI de-noising using non-local means”, In Proceedings of MIUA, pp. 41-46, Aberystwyth, 2007

10.     Gerig, Kubler, Kikinis and Jolesz, “Nonlinear Anisotropic Filtering of MRI Data”, IEEE Transaction on Medical Imaging, Vol. 11, No. 1, pp. 221-232, 1992

11.     Wood and Johnson, “Wavelet Packet Denoising of Magnetic Resonance Images: Importance of Rician Noise at Low SNR", Magnetic Resonance in Medicine, Vol. 41, No. 1, pp. 631-635, 1999

12.     Sudha, Suresh and Sukanesh, "Comparative Study on Speckle Noise    Suppression Techniques for Ultrasound Images", International Journal of Engineering and Technology, Vol. 1, No. 1, pp. 57-62, April 2009

13.     Hyder Ali, Sukanesh and Fellow, "An Edge Preserving Denoising Technique for MR Images using Curvelet Transform" ,Interdisciplinarty Journal, Vol. 91, pp. 3-8, May 2010

14.     Dar-Ren Chen, Ruey-Feng Chang, Wen-Jie Wu, Woo Kyung Moon and Wen-Lin Wu, "3-D Breast Ultrasound Segmentation Using Active Contour Model", Ultrasound in Medicine and Biology, Vol. 29, No. 7,  pp. 1017–1026, 2003

15.     Shujun Fu, Qiuqi Ruan, Wenqia Wang and Yu Li, "Adaptive Anisotropic Diffusion for Ultrasonic Image Denoising and Edge Enhancement", International Journal of Information Technology, Vol. 2, No. 4, pp. 284-287, 2006

16.     Buades, Coll and Morel, "A Review of Image Denoising Algorithms, With a New One", SIAM Journal on Multiscale Modeling and Simulation, Vol. 4, No. 2, pp. 490-530, 2005

17.     Jung and Scharcanski, "Adaptive Image Denoising In Scale-Space Using the Wavelet Transform", In Proceedings of XIV Brazilian Symposium on Computer Graphics and Image Processing, pp. 172- 178, Florianopolis, Brazi, October 2001

18.     Yansun Xu, John B. Weaver, Dennis M. Healy, Jr and Jian Lu, "Wavelet Transform Domain Filters: A Spatially Selective Noise Filtration Technique", IEEE Transactions on Image Processing, Vol. 3, No. 6, pp. 747-758, November 1994

19.     Ahmed Badawi, Michael Johnson and Mohamed Mahfouz, "Scatterer Density in Edge and Coherence Enhancing Nonlinear Anisotropic Diffusion for Medical Ultrasound Speckle Reduction", International Journal of Biological and Life Sciences, Vol. 3, No. 1, pp. 1-24, 2007

20.     Sudha, Suresh and Sukanesh, "Speckle Noise Reduction in Ultrasound Images by Wavelet Thresholding based on Weighted Variance", International Journal of Computer Theory and Engineering, Vol. 1, No. 1, pp. 7-12, April 2009

21.     Thangavel, Manavalan and Laurence Aroquiaraj, "Removal of Speckle Noise from Ultrasound Medical Image based on Special Filters: Comparative Study", International journal on Graphics, Vision and Image Processing, Vol. 9, No. 3, pp. 25-32, June 2009

22.     Pierrick Coupe, Pierre Hellier, Charles Kervrann and Christian Barillot, "Nonlocal Means-Based Speckle Filtering for Ultrasound Images", IEEE Transactions on Image Processing, Vol. 18, No. 10, pp. 2221-2229, October 2009.


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9.

Authors:

Anil Kamboj, Kavita Grewal, Ruchi Mittal

Paper Title:

Color Edge Detection in RGB Color Space Using Automatic Threshold Detection

Abstract:   Edge detection is one of the most commonly used operations in image processing and pattern recognition, the reason for this is that edges form the outline of an object. An edge is the boundary between an object and the background, and indicates the boundary between overlapping objects. Edge detection reduces the amount of data needed to process by removing unnecessary features. Edge detection in color images is more challenging than edge detection in gray-level images.  Compared with gray image, color image provides more edge information of objects. However, the current color edge detection algorithms acquired so much time to compute and they are hardly used in real-time system. In order to improve the efficiency and the performance of the color edge detection. This paper  proposes a method for edge detection of color images with automatic threshold detection. The proposed algorithm extracts the edge information of color images in RGB color space with fixed threshold value. The algorithm works on three channels individually and the output is fused to produce one edge map. The algorithm uses the improved Kuwahara filter to smoothen the image, sobel operator is used for detecting the edge. A new automatic threshold detection method based on histogram data is used for estimating the threshold value. The method is applied for large number of images and the result shows that the algorithm produces effective results when compared to some of the existing edge detection methods.

Keywords:
 RGB color space Kuwahara filter, Sobel Operator, Histogram, Edge Thinning, Threshold.


References:

1.        Chen, X., Chen, H., Chen, H.: A Novel Approach for Color Edge Detection in RGB Color Space. In: 10th IEEE International Conference on Signal Processing, pp. 793–797. IEEE Press, Germany (2010)
2.        Niu, L., Li, W.: Color Edge Detection Based on Direction Information Measure. In: 6th World Congress on Intelligent Control and Automation, pp. 9533–9536. IEEE Press,China (2006)

3.        Zou, J., Li, H., Liu, B., Zhang, R.: Color Edge Detection Based on Morphology. In: 1st International Conference on Communication and Electronics, p. 291. IEEE Press, China(2006)

4.        Dikbas, S., Arici, T., Altunbasak, Y.: Chrominance Edge Preserving Grayscale Transformation with Approximate First Principal Componenet for Color Edge Detection.In: IEEE International Conference on Image Processing, p. 261. IEEE Press, USA (2007)

5.        Liu, K.-C., Chou, C.-H.: Perceptual Contrast Estimation for Color Edge Detection. In:IEEE International Conference on Systems, Signals and Image Processing and 6th EURASIP Conference Focused on Speech and Image Processing, Multimedia Communications and Services, pp. 86–89. IEEE Press, Poland (2007)

6.        Perumal, E., Rajesh, R.S., Shanugam, P.: Fuzzy-PL Transformation based Color Edge Detection. In: 16th International Conference on Advanced Computing and Communications, p. 297. IEEE Press, India (2008)

7.        Wang, J., Liu, L.: Specific Color-pair Edge Detection using Quaternion Convolution. In: 3rd International Congress on Image and Signal Processing, pp. 1138–1140. IEEE Press, China (2010)

8.        Datta, S., Chaudhuri, B.B.: A COLOR Edge Detection in RGB Color Space. In: IEEE International Conference on Advances in Recent Technologies in Communications and Computing, India, p. 337 (2009)

9.        Harish Kumar, J.R., Chaturvedi, A.: Edge Detection of Femur bone – A Comparative Study. In: IEEE International Conference on Signal and Image Processing, India, p. 337 (2009)

10.     Navatia, R.: A Color Edge Detector and Its Use in Scene Segmentation. J. SMC-7, 820(1977)


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Authors:

Siddalinga Aland, V. Venkateswarlu, Rohith B.R

Paper Title:

Block Level Physical Design of Interfacing Module in RISC Core

Abstract:   The physical design plays a major role in implementing the circuit and logic cells physically, because physical devices and interconnecting materials will have its own parasitic resistances and capacitances. Placement and Routing (PNR) flow involves proper placement and routing the interfacing module including majorly PCI and SDRAM. In this project work digital cells called standard cells and macro are placed with minimum congestion of 3% in a block. And routing is done by keeping in mind the manufacturability by utilizing non default rule (NDR) design rules. The clock tree network is built by using the H-Tree network topology. The power network is synthesized with higher metal layers available in technology node. This project is implemented in TSMC 120nm technology, which has 7 metal layers but as this project is block level so 6 metal layers are used for routing.  The clock frequency of block system is 250MHz is used as the main clock, peripheral clocks and generated clock of 133MHz. The GDSII format of layout is generated with no violations. 

Keywords:
 Placement and Routing (PNR) flow involves proper placement and routing the interfacing module including majorly PCI and SDRAM.


References:

1.       Stephan Rusu, “Trends and challenges in VLSI Technology scaling towards  100nm”, Intel Corporation, Sept 2011.
2.       Subrat Kumar panda, “Advanced VLSI Design Lab”, Dept. of Computer science,   IIT   Kharagpur.

3.       Ioannis Fudos, Xrysovalantis Kavousianos , Dimitrios Markouzis and Yiorgos Tsiatouhas, “Placement and Routing in Computer Aided Design of Standard Cell Arrays by Exploiting the Structure of the Interconnection Graph”, Computer-Aided Design & Applications, 5(1-4), 2008, 325-337.

4.       Eisenmann H, “Generic global placement and floor-planning”, Design Automation  Conference IEEE, 1998, page 269-274.

5.       Naveed Sherwani, “Algorithm for physical design Automation”, third edition,  kluwer academic publication, page 16.

6.       Impact of small process geometries on microarchitectures in systems on a chip,  Sylvester, D. Keutzer, K. Michigan Univ., Ann Arbor, MI Proceedings of the IEEE  Apr 2001, pages 467 – 489.

7.       Yao-Wen Chang, “Physical Design for Nanometer ICs”, Department of Electrical  Engineering National Taiwan University Spring 2012

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Authors:

Bashar Alsarayreh, Hassan Khudair

Paper Title:

Structural Equation Modeling Analysis between Enabler and Results in EFQM Model; a Case Study in Vocational Training Corporation in Jordan

Abstract:   In order to achieve excellence, organizations need to be aware of the impact of the individual criteria on each other and also the analysis of relationships between Enabler criteria and Results criteria. The aim of this paper is to evaluate the relationships between Enablers and Results in the EFQM Excellence Model applied in a Vocational Training Corporation (VTC) in Jordan. To this end, all the EFQM model data of the Vocational Training Corporation (VTC) was collected. Research method used for this article is descriptive, where Structural Equation Modeling (SEM) was used to assess the relations between the criteria. The results confirm the previous findings and shows that Enablers are strongly related to the Results. All the Enabler criteria contribute to Results improvements, so a balanced approach in the development of Enabler criteria allows organizations to obtain an optimal gain from the implementation of the EFQM Excellence Model.

Keywords:
 EFQM Excellence Model, Structural equation modeling Analysis, Vocational Training Corporation.


References:

1.        Najmi M. and Hosseini S. (2003), "The EFQM Excellence Model: from idea to application", Book published by IPHRD, Reprinted 8 times.
2.        Westlund, A.H., (2001), "Measuring environmental impact on society in the EFQM system".

3.        Tutuncu, O. and Kucukusta, D., (2009),"Canonical correlation between job satisfaction and EFQM business excellence model". Springer Science and Business Media B.V; DOI: 135-009-9269-0.

4.        EFQM business excellence model". Springer Science and Business Media B.V; DOI:

5.        Eskildsen, J.K., and Dahlgaard, J.J. (2000), "A causal model for employee satisfaction", Total

6.        Quality Management. Vol.11 No 8, pp.1081-1094.Total Quality Management, 12 (1), PP: 125–135.

7.        www.efqm.org/en/tabid/132/default.aspx.

8.        Bou-Llusar, J. C; Escrig-Tena, A. B.; Roca-Puig, V. n-Martin, I. (2009)."An empirical assessment of the EFQM Excellence Model: Evaluation as a TQM framework

9.        relative to the MBNQA Model". Journal of Operations Management, Volume 27, Issue 1, pp:1-22.

10.     Calvo-Mora, A; Leal A. and Roldan, J. L. (2006)."Using enablers of the EFQM model to manage institutions of higher education". Quality Assurance in Education, Volume: 14; Issue:2; pp 99-122.

11.     Martinez-Lorente, A.; G omez-Go mez, J. and Martinez-Costa, M. (2009)."An evaluation of the EFQM excellence model", proceeding of 16th International annual EUROMA conference.

12.     www4.gu.edu.au:8080/adt-root/uploads/approved/.../02Whole.pdf

13.     B. Smith, “An approach to graphs of linear forms (Unpublished work style),” unpublished.

14.     E. H. Miller, “A note on reflector arrays (Periodical style—Accepted for publication),” IEEE Trans. Antennas Propagat., to be published.

15.     J. Wang, “Fundamentals of erbium-doped fiber amplifiers arrays (Periodical style—Submitted for publication),” IEEE J. Quantum Electron., submitted for publication.

16.     Hair, J.R.; Anderson, R.E.; Tatham, R.L. and Black, W.C. (1998), "Multivariate Data Analysis", 5th ed.), Prentice Hall International Inc., NJ, USA.

17.     M. Young, The Techincal Writers Handbook.  Mill Valley, CA: University Science, 1989.

18.     CAUSAL RELATIONSHIPS BETWEEN ENABLERS OF CONSTRUCTION SAFETY CULTURE Thanwadee Chinda .(2010)

19.     (PhD Candidate, Griffith University, Gold Coast, Queensland, Australia) J. Jones. (1991, May 10). Networks (2nd ed.) [Online]. Available: http://www.atm.com

20.     (Journal Online Sources style) K. Author. (year, month). Title. Journal [Type of medium]. Volume(issue), paging if given.          Available: http://www.(URL)

21.     R. J. Vidmar. (1992, August). On the use of atmospheric plasmas as electromagnetic reflectors. IEEE Trans. Plasma Sci. [Online]. 21(3). pp. 876—880.  
Available:

22.     http://www.halcyon.com/pub/journals/21ps03-vidmar

23.     Wongrassamee, S., Gardiner, P., D. & Simmons, J., E., L. (2003), Performance measurement tools: The Balanced Scorecard and the EFQM Excellence Model, Measuring Business Excellence, Vol. 7, No. 1, pp. 14-29.

24.     Principles and Practice of Structural Equation Modeling  Third Edition Rex B. Kline  


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Authors:

Pallab Banerjee, Probal Banerjee, Shweta Sonali Dhal

Paper Title:

Comparative Performance Analysis of Average Max Round Robin Scheduling Algorithm (AMRR) using Dynamic Time Quantum with Round Robin Scheduling Algorithm using static Time Quantum

Abstract:   Round Robin Scheduling algorithm is designed especially for time sharing Operating system (OS).It is a preemptive CPU scheduling algorithm which switches between the processes when static time Quantum expires. The Round Robin Scheduling algorithm has its disadvantages that is its longer average waiting time, higher context switches, higher turnaround time .In this paper a new algorithm is presented called Average Max Round Robin (AMRR) scheduling algorithm .In this scheduling algorithm the main idea is to adjust the time Quantum dynamically so that (AMRR) perform better performance than simple Round Robin scheduling algorithm.

Keywords:
 Operating System, Round Robin, Average Max Round Robin, Turnaround time, Waiting time, Context Switch.


References:

1.        “Silberschatz, A., P.B. Galvin and G. Gagne, 2008” Operating Systems Concepts. 7th Edn., John Wiley and Sons, USA., ISBN: 13: 978-0471694663, pp: 944.
2.        “Tanebaun, A.S., 2008” Modern Operating Systems. 3rd Edn., Prentice Hall, ISBN: 13:9780136006633, pp: 1104.

3.        Sanjay Kumar Panda and  Saurav Kumar Bhoi, “An Effective Round Robin Algorithm using Min-Max Dispersion Measure” ISSN : 0975-3397 ,Vol. 4 No. 01, January 2012.

4.        Sarojhiranwal and D.r. K.C.Roy“Adaptive Round Robin Scheduling using Shortest Burst Approach Based on Smart Time Slice”.volume 2,issue 3.

5.        H. S. Behera, Rakesh Mohanty, Sabyasachi Sahu and  Sourav Kumar Bhoi.” Comparative performance analysis of multi-dynamic time quantum round robin (mdtqrr) algorithm with arrival time”, ISSN : 0976-5166, Vol. 2, No. 2, Apr-May 2011.

6.        10“Tarek Helmy, Abdelkader Dekdouk” Burst Round Robin: As a Proportional-Share Scheduling Algorithm, IEEE Proceedings of the fourth IEEE-GCC Conference on towards Techno-Industrial Innovations, pp. 424-428, 11-14 November,2007

7.        “Yaashuwanth .C & R. Ramesh” Inteligent time slice for round robin in real time operating system, IJRRAS 2 (2), February 2010

8.        R. J. Matarneh, “Seif-Adjustment Time Quantum in Round Robin Algorithm Depending on Burst Time of the Now Running Proceses”, American Journal of Applied Sciences 6 (10), pp. 1831-1837, 2009.

9.        J. Nieh, C. Vaill and H. Zhong, “Virtual-Time Round-Robin: An O(1) Proportional Share Scheduler”, Proceedings of the USENIX Annual Technical Conference, Boston, Massachusetts, USA, pp. 25-30, June 2001.

10.     S. M. Mostafa, S. Z. Rida and S. H. Hamad, “Finding Time Quantum of Round Robin CPU Scheduling Algorithm in General Computing Systems using Integer Programming”, IJRRAS 5 (1), pp.64-71, October 2010.

11.     H. S. Behera, R. Mohanty, and D. Nayak, “A New Proposed Dynamic Quantum with Re-Adjusted Round Robin Scheduling Algorithm and Its Performance Analysis,” vol. 5, no. 5, pp. 10-15, August 2010.

12.     A. Bhunia, “Enhancing the Performance of Feedback Scheduling”, IJCA, vol. 18, no. 4, pp. 11-16, March 2011.

13.     “Prof. Rakesh Mohanty, Prof. H. S. Behera, Khusbu Patwari, Manas Ranjan Das, Monisha Dash, Sudhashree” Design and Performance Evaluation of a New Proposed Shortest Remaining Burst Round Robin (SRBRR) Scheduling Algorithm, Am. J. Applied Sci., 6 (10): 1831-1837, 2009.


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13

Authors:

Shrutika Suri, Vandna Batra

Paper Title:

Comparative Study of Network Monitoring Tools

Abstract:   There are billions of packets flying around the web sky today. A significant number of them are of malicious intent. These packets help us to understand when there are notable security or performance events occurring on the network and also to find out common network problems such as loss of connectivity, slow network etc.This paper focus on the comparative study of different packet analyzers available in current market and how we can choose amongst them according to our requirements.

Keywords:
 Packetcapturing, Packetanalysis, Wireshark, Eherape, capsa, libpcap.


References:

1.        Network Traffic Monitoring ieee paper www.ijarcsse.com/docs/papers/january2012/V2I1059.pdf by Prof. Radha S. Shirbhate
2.        iresharkIntroduction: http://en.wikipedia.org/wiki/Ettercap_%28computi ng%29wireshark

3.        A Survey of Network Traffic Monitoring and Analysis Toolswww.cse.wustl.edu/~jain/cse567-06/ftp/net...monitors3/index.html

4.        Evaluation of the Capabilities of WireShark as a tool for Intrusion Detection by Usha Banerjee

5.        Wireshark machanisms:http://en.wikipedia.org/wiki/Wireshark

6.        Tcpdump introduction: .http://en.wikipedia.org/wiki/Tcpdump

7.        Netsniff-ng –the packet sniffing beast:-.http://netsniff-ng.org/

8.        Etherape introduction and key features:-http://en.wikipedia.org/wiki/Etherape

9.        Capsa:-.http://en.wikipedia.org/wiki/Capsa

10.     WiresharkFeatures:-.http://www.wireshark.com/wireshark-reviews downloads.html

11.     http://www.wireshark.org/about.html


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Authors:

Preetam Bhosle, Hari Krishna Moorthy

Paper Title:

Fpga Implementation Of Low Power Pipelined 32-Bit Risc Processor

Abstract:   This paper presents the design and implementation of a low power pipelined 32-bit High performance RISC Core. The various blocks include the Fetch, Decode, Execute and Memory Read / Write Back to implement 4 stage pipelining. In this paper we are proposing low power design technique in front end process. Harvard architecture is used which has distinct program memory space and data memory space. Low power consumption helps to reduce the heat dissipation, lengthen battery life and increase device reliability. To minimize the power of RISC Core, clock gating technique is used in the architectural level which is an efficient low power technique. 7-SEG LEDs are connected to the RISC IO interface for testing purpose, Verilog code is simulated using Modelsim and then implementation is done using Altera Quartus II and Altera FPGA board.

Keywords:
 Architectural level power reduction, Auto branch prediction, Clock Gating, High performance architecture.


References:

1.        M.E. Hopkins, "A Perspective on the 801/Reduced Instruction Set Computer", IBM Systems Journal, Vol. 26, No. 1, pp. 107-121, 1987.
2.        John L. Hennessy, David A. Patterson, Computer Architecture A Quantitative Approach, Morgan Kaufmann Publishers, San Mateo, 1990.

3.        R.R. Oehler and R.D. Groves, "IBM RISC System/6000 processor architecture", IBM Journal of Research and Development, Vol. 34, No. 1, pp. 23-36, 1990.

4.        Michael J. Flynn, Chad L. Mitchell and Johannes M. Mulder, "And Now a Case for More Complex Instruction Sets", IEEE Journal on Computer, pp. 71-83, 1987.

5.        Norman P. Jouppi, David W. Wall, "Available Instruction-Level Parallelism for Superscalar and Superpipelined Machines", IEEE Proceedings of the Third International Conference on Architectural Support for Programming Languages and Operating Systems, Boston, Mass, pp. 272-282, 1989.

6.        Michael Butler, Tse-Yu Yeh, Yale Patt, Mitch Alsup, Hunter Scales, Michael Shebanow, "Single Instruction Stream Parallelism is Greater than Two", ACM Proceedings of the 18th Annual International Symposium on Computer Architecture,  pp. 276-286, 1991.

7.        Michael D. Smith, Mike Johnson and Mark A. Horowitz, "Limits on Multiple Instruction Issue", IEEE Proceedings of the Third International Conference on Architectural Support for Programming Languages and Operating Systems, Boston, Mass., pp. 290-302, 1989.

8.        Kui Yi, Yue-Hua Ding, “32-bit RISC CPU based on MIPS” , Proceedings of Second Pacific-Asia Conference on web mining and web-based application, pp.  124 - 128, 2009.

9.        Bassoy, C.S.,Manteuffel, H., Mayer-Lindenberg, F.,“SHARF: An FPGA-Based customizable processor architecture”, Proceedings of International Conference on Field Programmable Logic and applications, pp.516-520, 2009.

10.     Gautham,P., Parthasarathy, R., Balasubramanian, K., “Low-Power Pipelined MIPS Processor Design”, Proceedings of the 12th International Symposium on Integrated Circuits, ISIC,  pp.  462 – 465, 2010.

11.     Adamec, F.,Fryza, T., “Design and Optimization of  ColdFire CPU Arithmetic and Logic Unit”, Proceedings of 16th International Conference on mixed design of integrated circuits & Systems, pp. 699 – 702, 2009.

12.     Shofiqul Islam, Debanjan Chattopadhyay, Manoja Kumar Das, V Neelima; Rahul Sarkar,     “Design of High Speed Pipelined Execution Unit of 32-bit RISC Processor” India Conference,  Annual IEEE , pp. 1 - 5, 2006.

13.     Geun-young Jeong; Ju-sung Park; Science and Technology, “ Design of 32-bit RISC Processor and efficient verification” 2003, Proceeding of the 7th Korea-Russia International Symposium, vol.2, pp. 222 - 227 , 2003.

14.     J. Hennessy and D. Patterson, Computer Architecture: A Quantitative Approach, Morgan & Kaufman Publishers, San Mateo, California.

15.     G.M.Amdahl,  G.A.  Blaauw,  F.P.  Brooks,  "Architecture  of  the  IBM  System/360,  IBM  Journal  of Research and Development, vol.8,  pp.87-101, April 1964.


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Authors:

Shaik Ghouse Basha, P B Chennaiah, Kandalam Giridhar

Paper Title:

Economic Generation of Electrical Power by using SFL Algorithm

Abstract:   An important criterion in power system operation is to meet the power demand at minimum fuel cost using an optimal mix of different power plants. Moreover, in order to supply electric power to customers in a secured and economic manner, unit commitment (UC) is considered to be one of the best available options. The problem of unit commitment (UC) is to decide which units to inter connect over the next T hours, where T is commonly daily or weekly duration of time. The problem is complicated by the presence of constraints and also it is complicated because it involves integer decision variables, i.e., a unit is either committed or not. In this paper SFLA algorithm is used for the solution of UC by meeting all its constraints. Minimum up and minimum down constrains are directly coded. This SFLA algorithm has been applied to 10 generating units considered for one day scheduling period.

Keywords:
 Economic dispatch, generation scheduling, optimization techniques, unit commitment.


References:

1.        N. P. Padhy, “Unit commitment—A bibliographical survey,” IEEE   Trans. Power Syst., vol. 19, no. 2, pp. 1196–1205, May 2004.
2.        H. H. Happ, R. C. Johnson, and W. J. Wright, “Large scale hydro-thermal unit commitment-method and results,” IEEE Trans.

3.        C. K. Pang, G. B. Sheble, and F. Albuyeh, “Evaluation of dynamic programming based methods and multiple area representation for thermal unit commitment,” IEEE Trans. Power App. Syst., vol. PAS-100, pp. 1212–1218, Mar. 1981

4.        S. A. Kazarlis, A. G. Bakirtzis, and V. Petridis, “A genetic algorithm solution to the unit commitment problem,” IEEE Trans. Power Syst, vol. 11, no. 1, pp. 83–92, Feb. 1996.

5.        A. Rudolf and R. Bayrleithner, “A genetic algorithm for solving the unit commitment problem of a hydro-thermal power systems,” IEEE Trans. Power Syst., vol. 14, no. 4, pp. 1460–1468, Nov. 1999.

6.        W. Xiong, M. J. Li, and Y. Cheng, “An improved particle swarm optimization algorithm for unit commitment,” in Proc. ICICTA 2008.

7.        V. S. Pappala and I. Erlich, “A new approach for solving the unit commitment problem by adaptive particle swarm optimization,” in Proc. IEEE Power and Energy Soc. General Meeting, Jul. 2008, pp. 1–6.

8.        S. Virmani, E. C. Adrian, K. Imhof, and S. Muhherjee, “Implementation of a Lagrangian based unit commitment problem,” IEEE Trans. Power Syst., vol. 4, no. 4, pp. 1373–1380, Nov. 1989.

9.        A. Y. Saber, T. Senjyu, N. Urasaki, and T. Funabashi, “Unit  commitment computation—A novel fuzzy adaptive particle swarm optimization approach,” in Proc. IEEE PSCE, Nov. 2006, pp. 1820–1828.

10.     Z. L. Gaing, “Discrete particle swarm optimization algorithm for unit commitment

11.     M. Shahidehpour, H. Yamin, and Z. Li, Market Operations in Electric Power Systems. New York: Wiley, 2002.

12.     M. M. Eusuff, K. E. Lansey, and F. Pasha, “Shuffled frog-leaping algorithm: A memetic meta-heuristic for discrete optimization,” Eng. Optimiz., vol. 38, no. 2, pp. 129–154, 2006.

13.     J. Kennedy and R. C. Eberhart, “Particle swarm optimization,” in Proc. IEEE Conf. Neural Networks, 1995, vol. 4, pp. 1942–194

14.     M. M. Eusuff and K. E. Lansey, “Optimization of water distribution network design using the shuffled frog leaping algorithm,” J. Water Resour. Plan. Manage., vol. 129, no. 3, pp. 210–225, 2003.


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Authors:

Nandeesh.B.B, Ganesh Kumar R, Jitendranath Mungara

Paper Title:

Secure and Dependable Cloud Services for TPA in Cloud Computing

Abstract:   The cloud storage provides users to easily store their data and enjoy the good quality cloud applications need not install in local hardware and software system. So benefits are clear, such a service is also gives users’ physical control of their outsourced data, which provides control over security problems towards the correctness of the storage data in the cloud. In order to do this new problem and further achieve a secure and dependable cloud storage services, we propose in this paper a flexible distributed storage integrity auditing mechanism, using the homomorphism token and distributed erasure-coded data. We are also proposing allows users to audit the cloud storage with very lightweight communication and computation cost. The auditing result not only ensures strong cloud storage correctness guarantee, but also simultaneously achieves fast data error localization, i.e., the identification of hacker information. And securely introduce an effective TPA, the auditing process should bring in no new vulnerabilities towards user data privacy, and introduce no additional online burden to user. In this paper, we propose a secure cloud storage system supporting privacy-preserving public auditing. We further extend our result to enable the TPA to perform audits for multiple users simultaneously and efficiently. This shows the proposed scheme is highly efficient and data modification attack, and even server colluding attacks.

Keywords:
 Data integrity, dependable distributed storage, error localization, data dynamics, Cloud Computing.

References:

1.        Wang, C. “Privacy-Preserving Public Auditing for Secure Cloud Storage” computers IEEE transaction.
2.        Cong Wang ;  Kui Ren ;  Wenjing Lou ;  Jin Li  “Enabling Public Auditability and  Data Dynamics for Storage Security in Cloud Computing” International conference on may 2011.

3.        Shuai Zhang; Shufen Zhang; Xuebin Chen; Xiuzhen Huo “cloud computing research and development” international conference on digital networks in 2010.

4.        Ji Hu; Klein, A. “ A Benchmark of transparent data encryption migration of web applications International conference on digital identifier.

5.        Tang, Y.; Lee, P.; Lui, J.; Perlman, R. “Secure Overlay Cloud Storage with Access Control and Assured Deletion” transaction paper.

6.        Min Chao Wang; Xing Wu; Wu Zhang; FuQiang Ding; Jun Zhou; GuoCai Pei “A conceptual platform of SLA in cloud computing IEEE 9th international conference.

7.        Singh, Y.; Kandah, F.; Weiyi Zhang “A  ecure cost effective multi cloud storage in cloud computing” on computer communication conference.

8.        Syam Kumar, P.; Subramanian, R.; Thamizh Selvam, D. “Ensuring data storage security in cloud computing” International conference.

9.        Ramachnadran, N. “The immenant convergence of the tech and cloud computing” in IEEE conference 2010.

10.     Wenjun Luo; Guojing Bai “Efficient Sharing of Secure Cloud Storage Services” in international conference 2011.

11.     Cong Wang; Qian Wang; Kui Ren; Wenjing Lou “Privacy-Preserving Public Auditing for Secure Cloud Storage” International conference in 2012.

12.     Singh, Y.; Kandah, F.; Weiyi Zhang “A secured cost-effective multi-cloud storage in cloud computing“.

13.     Erotokritou, S.; Nair, S.K.; Dimitrakos, T. “An Efficient Secure Shared Storage Service with Fault and Investigative Disruption Tolerance” published in 2010.

14.     Qian Wang; Cong Wang; Kui Ren; Wenjing Lou; Jin Li “Enabling Public Audit ability and Data Dynamics for Storage Security in Cloud Computing” in conference.

15.     Takayama, K.; Yokota, H. “Performance and Reliability of a Revocation Method Utilizing Encrypted Backup Data” in 2011 conference.

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Authors:

A.Arockia Aswini, V.R.Manisankar, J.Jagadeesan

Paper Title:

An Efficient Approach For Avoiding Down Time of Production Data Base Server In Active/Passive Windows Failover Clustering Environment

Abstract:   Modern IT department facing immense challenge is to ensure the production Server availability at all times. To avoid downtime of Production Server, High availability Solution should be implemented like Microsoft Windows Failover Clustering.  Microsoft Failover Windows Cluster provides the automatic failover to the standby node if a hardware (RAM, SMPS, CPU and etc...) failure or software failure (OS, SQL Server and etc...) occurs. Failover automatically occurs if the primary server fails. In this case, Active/passive two node windows Cluster is implemented along with SQL Server cluster. Windows Failover cluster will not failover for the customized application services which are node specific. In three tier architecture (Web, App and DB), SQL Server Database instance  installed in Cluster Environment as it has capable of failover  to the passive node if primary node SQL instance or with Server level  Software/Hardware failure occurs. Suppose, if any Application dependent Services which is installed in Primary Node which is required for providing interface between Web and Database Servers will not failover to the secondary node even though SQL Server and Cluster resources can does.  Again, there will be a showstopper of entire business due to this application dependent services non-working. Intention of this paper is to provide the solution for how to failover such dependent application services to the passive node along with Cluster Services in order to avoid downtime.

Keywords:
 SQL Server Database instance  installed in Cluster Environment as it has capable of failover  to the passive node if primary node


References:

1.        Smith, S.M. ProSapien LLC, Eagle Mountain Krolik, J. ;  Bilik, I. “Theoretical Passive Sonar Performance of a Cluster of UUV Towed Line Arrays Employing Orientation Diversity” 9th international conference on Advance Communication Technology
2.        Mamun-or-Rashid, Md. Dept. of Comput. Eng., Kyung Hee Univ., Kyunggi Mahbub Alam, M. Choong Seon Hong ,” Energy Conserving Passive Clustering for Efficient Routing in Wireless Sensor Network”, Advance communication technology, 9th international conference

3.        Gerla, M. Dept. of Comput. Sci., California Univ., Los Angeles, CA Taek Jin Kwon ;  Pei, G. ,” On-demand routing in large ad hoc wireless networks with passive clustering”, Wireless Communications and Networking Confernce, 2000. WCNC. 2000 IEEE

4.        Sheng-Shih Wang Dept. of Inf. Manage., Minghsin Univ. of Sci. & Technol., Hsinchu, Taiwan,” Performance evaluation of passive clustering based techniques for inter-vehicle communications”, Wireless and Optical Communications Conference (WOCC), 2010 19th Annual

5.        Hafid, A.S. Network Res. Lab., Montreal Univ., Montreal, QC Chender, F. ;  Taek Jin Kwon,” Energy Aware Passive Clustering in Wireless Mobile Networks “,Wireless Communications and Mobile Computing Conference, 2008. IWCMC '08. International

6.        El Ghanami, D. Ecole Mohammadia d'Ing., Rabat Kwon, T.J. ;  Hafid, A.,” GRIDS: Geographically Repulsive Insomnious Distributed Sensors – An Efficient Node Selection Mechanism Using Passive Clustering “,Networking and Communications, 2008. WIMOB '08. IEEE International Conference on Wireless and Mobile Computing,

7.        Gerla, M. Dept. of Comput. Sci., California Univ., Los Angeles, CA Taek Jin Kwon ;  Pei, G. ,” On-demand routing in large ad hoc wireless networks with passive clustering “,Wireless Communications and Networking Confernce, 2000. WCNC. 2000 IEEE

8.        Alonso-Zarate, J. Centre Teratologic de Telecomunicacions de Catalunya (CTTC), Castelldefels,” Saturation Throughput Analysis of a Passive Cluster-Based Medium Access Control Protocol for Ad Hoc Wireless Networks “,Communications, 2008. ICC '08. IEEE


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Authors:

Mrs. Preet Kaur, Geetu lalit

Paper Title:

Comparative Analysis of DCT, DWT &LWT for Image Compression

Abstract:   Image compression is a method through which we can reduce the storage space of images, videos which will helpful to increase storage and transmission process’s performance. In image compression, we do not only concentrate on reducing size but also concentrate on doing it without losing quality and information of image. In this paper, we present the comparison of the performance of Discrete cosine transform, Discrete wavelet transform & Lifting wavelet transform for implementation in a still image compression system and to highlight the benefit of these transforms relating to today’s methods. The performance of these transforms are compared in terms of Peak-signal-to-noise ratio (PSNR), Signal to noise ratio SNR, Mean squared error (MSE), Energy Retained (ER) & Execution time etc.

Keywords:
 DWT, DCT, LWT, image compression.


References:

1.       Sonal, Dinesh Kumar, A STUDY OF VARIOUS IMAGE COMPRESSION TECHNIQUES, GJU Hissar.
2.       Edmund Y. Lam, Member, IEEE, and Joseph W. Goodman, Fellow, IEEE,”A Mathematical Analysis of the DCT Coefficient Distributions for Images”, IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 9, NO. 10, OCTOBER 2000

3.       NunoRoma ,LeonelSousa , “ A tutorial overview on the properties of the discrete cosine transform for encoded image and video processing”, IST/TULisbon/INESC-ID,RuaAlves Redol,9-1000-029 Lisboa-Portugal.

4.       Andrew B. Watson, NASA Ames Research Center, Image Compression Using the Discrete Cosine Transform, Mathematica Journal, 4(1), 1994, p. 81-88.

5.       DCT-BASED IMAGE COMPRESSION by Vision Research and Image Sciences Laboratory.
6.       Amara Graps , “An Introduction to Wavelets “,1995 Institute of Electrical and Electronics Engineers, Inc.
7.       Christian Gargour, Marcel Gabrea, VenkatanarayanaRamachandran, and Jean-Marc Lina , “A Short introduction to Wavelet & Its Applications” ©2009 IEEE, IEEE CIRCUITS AND SYSTEMS MAGAZINE.

8.       Priyanka Singh, Priti Singh, Rakesh Kumar Sharma,“JPEG Image Compression based on Biorthogonal, Coiflets and Daubechies Wavelet Families”, International Journal of Computer Applications (0975 – 8887)Volume 13– No.1, January 2011.

9.       Chesta Jain, Vijay Chaudhary,KapilJain,SaurabhKarsoliya, “Performance Analysis of Integer Wavelet Transform for Image Compression”©2011 IEEE.

10.     Wade Spires, University of Central Florida,wspires@cs.ucf.edu, “Lossless Image Compression Via the Lifting Scheme”, November 2005

11.     SwanirbharMajumder, N.Loyalakpa Meitei, A.Dinamani Singh, Madhusudhan Mishra on “Image Compression on lifting Wavelet Transform” in 2010 international Conference On Advances in Communication, Network & Computing
12.     Syed Ali Khayam, “The Discrete Cosine Transform (DCT):Theory and Application”, Michigan State University March 10th 2003

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Authors:

B. Rajesh kumar, CH. Sai Murali

Paper Title:

Multimedia Content protection Based on Commutative Watermarking and Cryptographic Technique

Abstract:   Watermarking embeds information into a digital signal like images. Watermarking Technologies are being regarded as a vital mean to proffer copyright protection of digital signals. The effectiveness of watermarking and Encryption technique is indicated by the robustness of embedded watermarks against various attacks such as, Rotation, Resizing, etc. In this paper, a novel Commutative Watermarking and Partial Encryption technique using single level 2-Dimension Discrete Wavelet Transform and Multi-Map Orbit Hopping Chaotic System is proposed. In  proposed system, the low-low sub-band decomposition is only encrypted. So, it is able to reduce the encryption to one quarter of the image information and the watermark image is embedded into the selected high sub-1bands. The results of the security analysis shows that the proposed algorithm provides a high security level for real time application.

Keywords:
 Chaos; Partial Encryption; Watermarking; DWT


References:

1.       Shiguo Lian, Multimedia content Encryption, CRC Press, Taylor & Francis Group, 2009.
2.       S. Lian, Z. Liu, Z. Ren, and H. Wang, “Commutative watermarking and encryption for media data,” International Journal of Optical Engineering 45(8): pp. 5101–5103, 2006.

3.       S. Lian, Z. Liu, Z. Ren, and H. Wang, “Commutative encryption and watermarking in compressed video data,” IEEE Circuits and Systems for Video Technology 17(6): pp. 774–778, 2007.

4.       Said E. El-Khamy, M. A. El-Nasr, and Amina H. El-Zein, “A Partial image encryption scheme based on ELKINZ chaotic stream cipher,” MASAUM Journal of basic and applied sciences, Vol. 1, No. 3, pp. 389-394,October 2009.

5.       Ke Lue, Xiaolin Tian, “A New Robust Watermarking Scheme based on Wavelet Transform,” Congress on Image Processing vol 2 .pp. 312-316, 2008.

6.       P.Ramman, Munage.V.N.K.Prasad, D.Sreenivasa Rao, 2'Robust Digital Watermarking of Images using Wavelets,” International Journal of Computer and Electrical Engineering, Vol.1, No.2, pp. 111-116, June 2009.

7.       TianKai Sun, XiaoGen Shao, XingYuan Wang, “A Novel Binary Image Digital Watermarking Algorithm Based on DWT and Chaotic Encryption,” The 9th International Conference for Young Computer Scientists, pp 2797-2802, 2008.

8.       Khalil Zebbiche, Lahouari Ghouti, Fouad Khelifi and Ahmed Bouridane, “'Protecting Fingerprint Data using Watermarking,”' Proceedings of the First NASA/ESA Conference on Adaptive Hardware and Systems (AHS'06) 4/06, 2006.

9.       W. Stallings, Cryptography and network security, Prentice Hall, New Jersey, 2006.

10.     Howard Chi Ho Cheng, Partial encryption for image and video communication, Master’s thesis, Department of Computing Science, University of Alberta, Edmonton, Alberta, Canada, 1998.  


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Authors:

Adarsh. R, Ganesh Kumar. R, Jitendranath Mungara

Paper Title:

Secure Data Transition over Multicast Routing In Wireless Mesh network

Abstract:   Multicast routing for wireless mesh networks has focused on metrics that estimate link quality to maximize throughput. Nodes must collaborate in order to compute the path metric and forward data. The assumption that all nodes are honest and behave correctly during metric computation, propagation, and aggregation, as well as during data forwarding, leads to unexpected consequences in adversarial networks where compromised nodes act maliciously. In high-throughput multicast protocol in wireless mesh networks we identify novel attacks in wireless mesh networks. The attacks exploit the local estimation and global estimation of metric to allow attackers to attract a large amount of traffic. We show that these attacks are very effective against multicast protocols based on high-throughput metrics. We can say that aggressive path increases attack effectiveness in the absence of defense mechanism. Our approach to defend against the identified attacks combines measurement-based detection and accusation-based reaction techniques. The solution also accommodates transient network variations and is resilient against attempts to exploit the defense mechanism itself. A detailed security analysis of our defense scheme establishes bounds on the impact of attacks. We demonstrate both the attacks and our defense using ODMRP, a representative multicast protocol for wireless mesh networks, and SPP, an adaptation of the well-known ETX unicast metric to the multicast setting.

Keywords:
 DSA Key Generation, High-Throughput metrics , Wireless mesh Network, Secure Data transition

References:

1.        J. Dong, R. Curtmola, and C. Nita-Rotaru, “On the pitfalls of using highthroughput multicast metrics in adversarial wireless mesh networks,” in Proc. of IEEE SECON ’08, 2008.
2.        Y. B. Ko and N. H. Vaidya, “Flooding-based geocasting protocols for mobile ad hoc networks,” Mob. Netw. Appl., vol. 7, no. 6, 2002.

3.        R. Chandra, V. Ramasubramanian, and K. Birman, “Anonymous gossip: Improving multicast reliability in mobile ad-hoc networks,” in Proc. Of ICDCS, 2001.

4.        D. S. J. D. Couto, D. Aguayo, J. C. Bicket, and R. Morris, “A highthroughput path metric for multi-hop wireless routing,” in Proc. Of MOBICOM ’03. ACM, 2003, pp. 134–146.

5.        S. Roy, D. Koutsonikolas, S. Das, and C. Hu, “High-throughput multicast routing metrics in wireless mesh networks,” in Proc. of ICDCS ’06, 2006.

6.        A. Chen, D. Lee, G. Chandrasekaran, and P. Sinha, “HIMAC: High throughput MAC layer multicasting in wireless networks,” in Proc. Of Mobile Adhoc and Sensor Systems (MASS ’06), October 2006.

7.        Adya, P. Bahl, J. Padhye, A. Wolman, and L. Zhou, “A multi-radio unification protocol for ieee 802.11 wireless networks,” in Proc. Of BroadNets ’04, 2004.

8.        S. Keshav, “A control-theoretic approach to flow control,” Proc. of the Conference on Communications Architecture and Protocols, 1993.

9.        P. Papadimitratos and Z. Haas, “Secure routing for mobile ad hocnetworks,” in Proc. of CNDS, January 2002, pp. 27–31.

10.     Y.-C. Hu, D. B. Johnson, and A. Perrig, “SEAD: Secure efficient distance vector routing for mobile wireless ad hoc networks,” in Proc. of WMCSA, June 2002.

11.     Y.-C. Hu, A. Perrig, and D. B. Johnson, “Ariadne: A secure on-demand routing protocol for ad hoc networks,” in Proc. of MOBICOM, 2002.

12.     S. Marti, T. Giuli, K. Lai, and M. Baker, “Mitigating routing misbehavior in mobile ad hoc networks,” in Proc. of MOBICOM, August 2000.

13.     S. Roy, V. G. Addada, S. Setia, and S. Jajodia, “Securing MAODV: Attacks and countermeasures,” in Proc. of SECON ’05. IEEE, 2005.

14.     R. Curtmola and C. Nita-Rotaru, “BSMR: Byzantine-resilient secure multicast routing in multi-hop wireless networks,” in Proc. of IEEE SECON ’07, June 2007.

15.     R. Draves, J. Padhye, and B. Zill, “Comparison of routing metrics for static multi-hop wireless networks,” in Proc. of SIGCOMM ’04, 2004.

16.     S. Roy, D. Koutsonikolas, S. Das, and C. Hu, “High-throughput multicast routing metrics in wireless mesh networks,” Elsevier Ad Hoc Networks, 2007.


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Authors:

Ankur Kumar Shrivastava, Ishan Ranjan, Abhinav Kumar, Anant Kumar Rai, Ramander Singh, Archit Rastogi, Nitisha Payal, Amod Tiwari

Paper Title:

A Tailored Approach to Enhance Wireless LAN Security

Abstract:   In the current business scenario world most organizations are moving from wire-connected networks to wireless networks. Thus there is a large growing market for Wireless LANS globally but there are various black holes, which is associated with such types of networks. This paper will provide an overview of the major risk threats and vulnerabilities in WLAN systems and finally we will present a holistic approach of securing Wireless Network.

Keywords:
 IEEE 802.11, SSID (Service Set Identifier), WEP (Wired Equivalent Privacy), Wi-Fi (Wireless Fidelity), WPA (Wi-Fi Protected Access).


References:

1.       http://cybersecurity.my/data/content_files/11/649.pdf  (Wierless LAN Security Guied Line By Noor Aida Idris and Mohamad Nizam Kasim).
2.       http://www.freewimaxinfo.com/wired-network-connections.html (31st May, 2012. 12:50 PM).

3.       http://en.wikipedia.org/wiki/Wireless_network (31st May, 2012. 12:50 PM).

4.       http://compnetworking.about.com/cs/wireless80211/g/bldef_wifi.htm (31st May, 2012. 12:57 PM).

5.       http://www.windowsnetworking.com/articles_tutorials/overview-wireless-network-security.html.

6.       http://www.lanarchitect.net/Articles/Wireless/SecurityRating/.

7.       http://www.zdnet.com/blog/ou/the-six-dumbest-ways-to-secure-a-wireless-lan/43.

8.       http://www.computerworld.com/s/article/97178/Five_Steps_To_WLAN_Security_A_Layered_Approach.

9.       http://www.iss.net/documents/whitepapers/wireless_LAN_security.pdf.

10.     http://www.sans.org/reading_room/whitepapers/wireless/wireless-lan-security-issues-solutions_1009.      
      

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Authors:

Shiv Pratap Singh Kushwah, Keshav Rawat, Pradeep Gupta

Paper Title:

Analysis and Comparison of Efficient Techniques of Clustering Algorithms in Data Mining

Abstract:   This paper presents the comparison of data mining algorithms for clustering. These algorithms are among the most influential data mining algorithms in the research community. With each algorithm, we provide a description of the algorithm, discuss the impact of the algorithm, and review current and further research on the algorithm. These algorithms cover classification, clustering, statistical learning, association analysis, and link mining, which are all among the most important topics in data mining research and development.

Keywords:
 cluster, data mining, clustering method, k-mean


References:

1.        Agrawal R, Srikant R (1994) Fast algorithms for mining association rules. In: Proceedings of the 20th   VLDB conference, pp 487–499
2.        Banerjee A, Merugu S, Dhillon I, Ghosh J (2005) Clustering with Bregman divergences. J Mach Learn   Res 6:1705–1749

3.        Cover T, Hart P (1967) Nearest neighbor pattern classification. IEEE Trans Inform Theory 13(1):21–27

4.        Fix E, Hodges JL, Jr (1951) Discriminatory analysis, nonparametric discrimination. USAF School of  Aviation Medicine, Randolph Field, Tex., Project 21-49-004, Rept. 4, Contract AF41(128)-31, February     1951

5.        Han E (1999) Text categorization using weight adjusted k-nearest neighbor classification. PhD thesis, University of Minnesota, October 1999
6.        Gray RM, Neuhoff DL (1998) Quantization. IEEE Trans Inform Theory 44(6):2325–2384
7.        Hart P (1968) The condensed nearest neighbor rule. IEEE Trans Inform Theory 14:515–516

8.        Han J, Pei J, Yin Y (2000) Mining frequent patterns without candidate generation. In: Proceedings of ACM SIGMOD international conference on management of data, pp 1–12

9.        Kuramochi M, Karypis G (2005) Gene Classification using Expression Profiles: A Feasibility Study. Int J Artif Intell Tools 14(4):641–660

10.     Tan P-N, Steinbach M, Kumar V (2006) Introduction to data mining. Pearson Addison-Wesley11. Toussaint GT (2002) Proximity graphs for nearest neighbor decision rules: recent progress. In: Interface- 2002, 34th symposium on computing and statistics (theme: Geoscience and Remote Sensing). Ritz-Carlton Hotel, Montreal, Canada, 17–20 April, 2002

11.     12.Toussaint GT (2002) Open problems in geometric methods for instance-based learning. JCDCG 273–283

12.     Wilson DL (1972) Asymptotic properties of nearest neighbor rules using edited data. IEEE Trans Syst Man Cyberne 2:408–420


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Authors:

Idigo V.E., Azubogu A.C.O., Ohaneme C.O., Isizoh A.N.

Paper Title:

Comparative Performance Analysis of Empirical and Radio Propagation Model for Bluetooth Indoor Localization

Abstract:   This work presents the possibility of using channel simulated results as alternative to site measurement for RSS based indoor localization. Three reference radio maps were generated for on-site measurement, Wall Attenuation factor (WAF) and Ray Tracer (RT) channel models. The Bayesian localization algorithm was applied to the three radio maps. An important performance metric called localization error was used which depends on the resolution of the reference radio map. Results obtained show that the performance of an RT model is comparable to a system based on on-site measurement for grid resolutions greater than 10 meters, on the other hand, the WAF model produced results that are very close to the on-site results for grid resolutions less than 8 meters.

Keywords:
 Grid resolution, Localization error, propagation model, Radio Channel, reference point


References:

1.        Kamol k and prastiant K. (2004), “ Modelling of indoor positioning system based on location fingerprint” school of information science, university of Pittsburgh publications pp 15-23
2.        Kiran Thapa and steven case (2006), “ An indoor positioning service for Bluetooth Adhoc Networks” Department of computer and information Science, Minnesota state university, Mankato

3.        Bluetooth special interest group (2001). SIG, 16th feb. 2006, available at www.bluetooth.com

4.        Bahl P and Padmanabhan.V. (2000), “RADAR” “An in-building RF based user location and tracking system” proceeding of the IEEE infocom 2000, Tel-Aviv Israel, vol 2 pp 775-784

5.        Li S., Zhao G and Liao L.(2005) “ User location service over an 802.15 Adhoc Network”, IEEE wireless communication and Networking Conference pp 56-64

6.        Hellebrandt M. and Mathar R. (2005) “Location Tracking of mobile in cellular Radio Networks”, IEEE transactions and vehicular Technology vol 48 no 5 pp 1558-1562
7.        Jaakko L., Raffaele M. and seppo P. (2001) “Cellular network optimization based on mobile location”, IEEE international conference pp 10-15
8.        Niculescu D. and Nath B.(2002), “ Adhoc positioning system” IEEE globecom 2nd edition, pp 3-12

9.        Bager Zarei, Mohammed Z. and Vahid Majid(2010) , IJCSI vol 7, issue 4, www.ijcsi

10.     Seidel S.V et al, (1999), “ The Impact of surrounding Building on propagation for wireless indoor personal communication system design” IEEE Transaction on Wireless communications, pp 50-58

11.     Seidel S. Y, Rappaport T.S (1992), “ 914MHZ Path Loss Prediction Model for Indoor Wireless Communication in Multi- Floor Building” IEEE transactions on antennas and propagation pp14-20

12.     Prasithsangaree, P. Krishnamurthy P.K and Chrysanthus P.K, (2002), “ On Indoor position location with wireless LAN. IEEE publications,pp 15 -20

13.     Jeffery H. and Ginetamo B., (2001), “Location systems for ubiquitos computing” IEEE computer, pp 57-66

14.     Idigo Victor, Azubogu A.C.O, Oguejiofor Obinna, Nnebe scholar,(2011), “ Modelling an Enhanced Routing protocol for Wireless Sensor Networks using Implicit Clustering Techniques” IJCSI, Vol 8, issue 5

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Authors:

Jyoti Shankar Prasad

Paper Title:

Cost Optimized Trends in Contouring Using Hand-Held GPS

Abstract:   This paper reveals the use of hand – held Global Positioning System for the purpose of contouring. In this research, major stress is laid on the use of cheaper and accurate GPS along with the conventional instruments. A hand – held GPS is used to determine the position of the particular station and the corresponding reduced level of the occupied station is determined with respect to a Temporary Bench Mark. The data collected is interpolated using Surfer 8.0 software. The profile of the surface generated was found to be in accordance with the actual topography of the site. The accuracy of the hand – held GPS is also taken into account from the data collected from some of the researches undertaken by various organizations. Thus, the use of hand – held GPS along with the cheaper conventional leveling instruments for the purpose of contouring prove to be very cost effective and considerably accurate.

Keywords:
 A hand – held GPS is used to determine the position of the particular station and the corresponding reduced level of the occupied station is determined with respect to a Temporary Bench Mark.


References:

1.       Cook, A.E., & Pinder, J.E., 1996, Relative Accuracy of Rectifications Using Coordinates Determined From Maps And The Global Positioning System. Programmetric Engineering And Remote Sensing.
2.       Chalermchon Satirapod, Chris Rizos and Jinling Wang, GPS Single Point Positioning With SA off: How accurate can we get?. Survey Review.

3.       Using GPS: Conrad Dixon (3rd edition), Adlard Coles Nautical, London.

4.       GPS made easy: Using Global Positioning Systems In The Outdoors(4th  edition); Lawrence Letham, Cordee, Great Britain.

5.       Simple GPS Navigation: Air, Sea and Land; Mik Chinery; Fernhurst, U.K.

6.       GPS For Geometric Correction Of Remotely Sensed Imagery: Possibilities After Termination Of SA; Ph.D. Thesis Of Dr. S.K.Katiyar, IIT Kanpur. 
 

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