Degree of Involvement in Scientific Electronic Publishing by University Faculty Members

Author: K. Y. Al-Khalili, E. Wefky

Abstract— A series of eleven workshops were organized by the Scientific Publishing Center (SPC) to faculty members who are assigned to a specific college associated with the University of Bahrain (UoB). The total number of participants was 216. The participants were trained on how to create and manage a specialized scientific electronic journal that fulfill international standards among which having an impact factor within the minimum period of time which was also clarified at the workshops. At the end of each workshop a structured questionnaire was distributed requiring them to show their involvement in electronic journals as members in the editorial boards, readers, reviewers, and those publishing their own research in this kind of journals. Data analysis revealed that, irrespective of college affiliation, faculty members at the University of Bahrain are involved in scientific electronic journals especially as readers of published articles in this kind of journal. In total 79.2% of them indicated that they reviewed such kind of journals as sources of literature review. The study revealed low involvement among the majority of faculty members at the University of Bahrain, on membership of editorial boards, or being consulted for refereeing articles to be published in electronic journals especially those affiliated to humanity colleges with statistically significant differences due to college affiliation. Overall, only 11.1% of the respondents indicated that they were members on the editorial boards, 22.2% indicated that they were consulted to review articles to be published in electronic journals and 36.1% indicated that they had published articles in electronic journals.

Keywords— Electronic journals, college type, University of Bahrain, reviewing, publishing, reading, editorial board.

References-

[1] Abouserie, H. E.M R. (2006). Use of Electronic Journals by Library and Information Science Faculty Members in Performing Various Academic Tasks: A Field Study Performed at the School of Information Sciences at the University of Pittsburgh. (ERIC Document Reproduction Service Number ED494454).

[2] Al-Khalili, K. Y. (2012a). Electronic publishing at the Scientific Publishing Center at the University of Bahrain.Scientific Publishing (a monthly bulletin issued from the Scientific Publishing Center at the University of Bahrain), 1(1),4-5.

[3] Al-Khalili, K. Y. (2012b). Impact of training workshops on creation and adoption of new electronic scientific journals. The Online Journal of New Horizons in Education TOJNED,2(3), 16-24.

[4] Ahmad, E. W., & Al-Khalili, K. Y. (2013).The Impact of Using a Reflective Teaching Approach on Developing Teaching Skills of Primary Science Student Teachers.The Online Journal of New Horizons in Education TOJNED,3(2), 58-64.

[5] Carrington,V. (2005).The uncanny, digital texts and literacy.Language and Education,19(6),467-482. http://dx.doi.org/10.1080/09500780508668698. DOI: 10.1080/09500780508668698

[6] Arteimi, M. A. (2012). Electronic publishing: An analytical study. Retrieved January 2, 2012 from the World Wide Web:www.arteimi.info/site/publication/Electronic%20publishing. doc.

[7] Byrne, A. (2000). After the fireworks: Opportunities and directions for university libraries. Opinion paper (ERIC Document Reproduction Service No. ED 447825).

[8] Coonin, B., & Younce, L. M.(2010). Publishing in open access education journals: The authors' perspectives. Behavioral & Social Sciences Librarian, 29 (2), 118-132. (ERIC Document Reproduction Service Number EJ884359).

[9] Dilek-Kayaoglu, H. (2008). Use of electronic journals by faculty at Istanbul University, Turkey: The results of a survey. Journal of Academic Librarianship, 34(3), 239-247. (ERIC Document Reproduction Service Number EJ794713).

[10] Harley,D. (2008).The university as publisher: Summary of a Meeting Held at UC Berkeley on November 1, 2007. Center for Studies in Higher Education: University of California, Berkeley

[11] Heider, K., Laverick, D., & Bennett, B. (2009). Digital textbooks: The next paradigm shift in Higher Education? AACE Journal, 17 (2) 103-112.(ERIC Document Reproduction Service No. EJ853401).

[12] Krantz, M. (2003). The future of research publishing: The eReport and eJournal. Educational Technology Review, 11 (1), (ERIC document reproduction service number: EJ673504).

[13] Nelson.M. A. (2008). Is Higher education ready to switch to digital course materials? The cost of textbooks is driving electronic solutions. Cronicle of Higher Education, 55 (14), PA29.(ERIC Document Reproduction Service No. EJ822635).

[14] Shapiro, L. S. (2005). Establishing and publishing an online peerreviewed journal: Action plan, resourcing, and cost. From: Public Knowledge Project web site: http://pkp.sfu.ca.

[15] Steding, S. A. (2004). Increasing the use of electronic resources in the humanities. Journal of Computing in Higher Education, 15(2), 114-132. ( ERIC document Reproduction Service Number EJ836906).

An Improved Approach for Digital Image Edge Detection

Authors: Mahbubun Nahar, Md. Sujan Ali

Abstract— Before objects detection and image segmentation edge detection is the preliminary and major step. The problems of edge detection are: false edge detection, missing true edges, producing thin or thick lines, noise removal etc. There are many edge detection algorithms have been developed for detecting the true edges from an image. These algorithms use different types of masks such as Robert, Prewitt, Sobel, Laplacian masks etc. Though the algorithms have some advantages and disadvantages, some of these perform better than others for specific regions and specific type of images. This paper proposed a new algorithm which works with a new mask. By comparing with others the proposed algorithm performs better.

Keywords—Edge detection, false edges, true edges, image segmentation, object detection, edge detection algorithms, filters, masks, proposed algorithm.

References-

[1] N. Senthilkumaran and R. Rajesh, ―Edge Detection Techniques for Image Segmentation - A Survey‖, Proceedings of the International Conference on Managing Next Generation Software Applications (MNGSA-08), 2008, pp.749-760.

[2] R. C. Gonzalez, R. E. Woods, ―Digital Image Processing‖, 3 rd edition, Upper Saddle River, New Jersey, Prentice-Hall Inc. (2008).

[3] Djemel Ziou and Salvatore Tabbone, ―Edge detection Techniques – An overview‖, University of Sherbrooke, Canada.

[4] Md. Sujan Ali, ―A Survey of Image Edge Detection Techniques‖ Proceeding of the International Conference on Electrical, Computer and Telecommunication Engineering 28—28 December 2012 (ICECTE2012).

[5] Roberts, L. G., Tippet, J. T., Machine, ―Perception of ThreeDimensional Solids‖, Cambridge, Mass, MIT Press (1965).

[6] Raman Maini & Dr. Himanshu Aggarwal ―Study and Comparison of Various Image Edge Detection Techniques‖, International Journal of Image Processing (IJIP), Volume (3) : Issue (1) .

[7] L.G. Roberts,―Machine Perception of 3D Solids‖, Optical and Electro-optical Information Processing, MIT Press, 1986.

[8] Yuancheng ―Mike‖ Luo and Ramani Duraiswami, ―Canny Edge Detection on NVIDIA CUDA‖, University of Maryland, College Park.

[9] J. Canny, Finding Edges and Lines in Image, Master’s Thesis, MIT, 1983.

[10] Er. Snigdha Mohanty and Er. Mahesh Prasad Sahoo ―EDGE DETECTION: A COMPARISON‖, Bhubaneswar.

[11] S. Wenchang, S. Jianshe, Z. Lin, ―Wavelet Multi-scale Edge Detection Using Adaptive threshold,‖IEEE, 2009.

[12] Ireyuwa. E. Igbinosa ―Comparison of Edge Detection Technique in Image Processing Techniques‖, ITEE Journal, Volume 2, Issue 1, ISSN: - 2306-708X, February 2013.

[13] G. Seshikala, Dr.Umakanth Kulkarni, Dr.M.N. Giriprasad, ―Palm Print Feature Extraction Using Multi Scale Wavelet Edge Detection Method‖, IJAREEIE, Vol. 1, Issue 1, July 2012.

[14] JOHN CANNY, MEMBER, IEEE, ―A Computational Approach to Edge Detection‖, IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, VOL. PAMI-8, NO. 6, NOVEMBER 1986.

[15] P. Vidya, S. Veni and K.A. Narayanankutty,‖ Performance Analysis of Edge Detection Methods on Hexagonal Sampling Grid‖, International Journal of Electronic Engineering Research, ISSN 0975 - 6450 Volume 1 Number 4 (2009) pp. 313–328.

[16] G.T. Shrivakshan, Dr.C. Chandrasekar, ―A Comparison of various Edge Detection Techniques used in Image Processing‖, IJCSI, Vol. 9, Issue 5, No 1, September 2012.

Modules Embedded in a Flat Module and their Approximations

Authors: Asma Zaffar, Muhammad Rashid Kamal Ansari

Abstract--An F- module is a module which is embedded in a flat module F. Modules embedded in a flat module demonstrate special generalized features. In some aspects these modules resemble torsion free modules. This concept generalizes the concept of modules over IF rings and modules over rings whose injective hulls are flat. This study deals with F-modules in a non-commutative scenario. A characterization of F-modules in terms of torsion free modules is also given. Some results regarding the dual concept of homomorphic images of flat modules are also obtained. Some possible applications of the theory developed above to I (F)-flat module approximation are also discussed.

Keyswords-- 16E, 13Dxx

References-

[1] Ansari MRK (1997), D n -torsion and Dn -torsion free Modules, Journal of mathematics, Punjab university vol xxx, 79-91.

[2] Ansari MRK (1996), E. F. Modules, Riaz J.sci Res,vol 18, 19-26.

[3] Ansari MRK (1996), E. F. Ring, Journal of mathematics, Punjab University vol xxix, 39 - 42.

[4] Colby R R (1975), Rings which Have Flat Injective Modules, Journal of Algebra vol 35, 239-252

[5] Enochs E E, Hernandez M J and Valle D A (1998), Coherent Rings of Finite Weak Global Dimension, Proceeding of the American mathematical society vol.45. 1611-1620 [6] Enochs E, Belshoff R and Xu J (1994), The Existence of Flat Cover, Proceeding of the American Mathematical society, vol 122(4), 985- 991

[7] Enochs E E (1988) Remarker on Commutative Neotherian Rings Whose Flat Modules Have Flat Injective Envelopes, Portugaliae mathematica vol.45 fasc. 2, 151-156

[8] Enochs E & Ahsan J (1984) Torsion Free Injective Covers, communtcation In algebra,1139-1146.

[9] Gomez J (1991) Torsion Free Cover and covers by submodules of flat modules, communtcation In algebra, vol 19 (3), 803-827.

[10] Khashyarmanesh K and Salarain Sh. (2003), On the Rings whose Injective Hull are Flat, Porceedings of the American Mathematics Society, vol 131 (8), 2329-2335.

[11] Lam T.Y (1999), Lectures on Modules and Rings, springer. [12] Rotman J (2008), Homological Algebra 2nd Edition, Springer.

Minimization of Leakage Power using Process, Voltage and Temperature (PVT) Variations

Authors: M. R. Dhavale, . A. H. Ansari

Abstract— Leakage power has become a serious concern in nanometer CMOS technologies. In this paper to minimize the leakage power a supply voltage and body-bias voltage generating technique for nanoscale VLSI systems are used. The minimum level of VDD and the optimum body-bias voltage are generated for different temperature and process conditions adaptively using a lookup table method based on the PVT monitoring and controlling systems. The adaptive optimal body-bias voltage is generated from the proposed leakage monitoring circuit, which compares the sub threshold current (ISUB) and the band-to-band tunneling (BTBT) current (IBTBT) along with current comparator & charge pump circuit. . The result is simulated using HSPICE using 32-nm bulk CMOS technology.

Keywords— Leakage power, optimal VBody control, optimal VDD control, process, voltage, and temperature (PVT) variation.

References-

[1] Liang-Teck Pang, Borivoje Nikolic´, ―Measurements and Analysis of Process Variability in 90 nm CMOS.‖ IEEE JOURNAL OF SOLID-STATE CIRCUITS, VOL. 44, NO. 5, pp. 1655-1662 MAY 2009.

[2] Saibal Mukhopadhyay, Hamid Manhood- Meimand, Cassandra Neau, and Kaushikroy, ―Leakage in Nanometer Scale CMOS Circuits.‖ 0-7803-7765-6/03 IEEE December 2008.Pp.307-312.

[3] kaushik roy, saibal mukhopadhyay, and hamid manhoodmeimand,‖leakage current mechanisms and leakage reduction techniques in deep-sub micrometer cmos circuits.‖Proceedings of the ieee, vol. 91, no. 2 pp 305-327, february 2003.

[4] Oleg Semenov, Arman Vassighi, and Manoj Sachdev‖Impact of technology scaling on thermal behavior of leakage current in subquarter micron MOSFETs: perspective of low temperature current testing.‖ O. Semenov et al. / Microelectronics Journal 33 pp 985– 994, 2002.

[5] Yong-jun, Xu, Zi Ying Luo,Li-Jian-Li―Leakage current estimation of CMOS circuit with stack effect‖ JOURNAL COMP. SCIENCE & TECHNOLOGY,,VOL.19,NO.5,PP,708-717,SEPT2004.

[6] Haiqing Nan, Kyung Ki Kim, Wei Wang and Ken Choi ―Dynamic Voltage and Frequency Scaling for Power Constrained Design using Process Voltage and Temperature Sensor Circuits‖ JOURNAL OF INFORMATION PROCESSING SYSTEMS,VOL.7,NO.1PP.93- 100,MARCH2011.

[7] Kyung Ki Kim and Yong-Bin Kim Minsu Choi, NohpillPark,‖Leakage Minimization Technique for Nanoscale CMOS VLSI‖ IEEE Design & Test of Computers, PP.322-330 July– August 2007.

[8] PushpaSaini, Rajesh Mehra,‖Leakage Power Reduction in CMOS VLSI Circuits‖ International Journal of Computer Applications (0975 – 8887) Volume 55, No.8, PP.42-48, October 2012.

[9] SomayeAbdollahi Pour and Mohsen Saneei―Power Reduction by Automatic Monitoring and Control System in Active Mode.‖ World Academy of Science, Engineering and Technology 61, PP, 1282- 1187 2012.

[10] Heung Jun Jeon, Yong-Bin Kim, and Minsu Choi, Senior Member, IEEE‖ Standby Leakage Power Reduction Technique for Nanoscale CMOS VLSI Systems.‖ IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, VOL. 59, NO. 5, PP.1127-1133, MAY 2010

[11] Kyung Ki Kim and Yong-Bin Kim ―A novel adaptive design methodology for minimum leakage power considering PVT variations for nanoscale VLSI system‖ IEEE TRANSACTIONS ON VERY LARGE SCALE INTEGRATION (VLSI) SYSTEMS, VOL. 17, NO. 4, PP.517-528, APRIL2009.

[12] Jing Yang and Yong-Bin Kim‖ Self Adaptive Body Biasing Scheme for Leakage Power Reduction in Nanoscale CMOS Circuit‖ May 3– 4, 2012, Salt Lake City, Utah, USA.Copyright 2012 ACM 978-1- 4503-1244-8/12/05,pp.111-115.

[13] Hon-sum philipwong, David j. Frank, Paul m. Solomon, Clement h. J. Wann, and Jeffrey j. Welser,‖Nanoscale CMOS‖ PROCEEDINGS OF THE IEEE, VOL. 87, NO. 4, pp.530- 570APRIL 1999.

An Efficient Subcarrier and Power Allocation Scheme for Multiuser MIMO-OFDM System

Authors: Dushyant Kumar Tiwari, Manish Trivedi

Abstract - Multiuser multi-input multi-output orthogonal frequency division multiple (MU MIMO-OFDM) is a very promising technology for enhancing the flexibility and efficiency of cellular and future communication systems. A joint optimization problem for resource allocation is solved by a combine scheme of multiple-input multiple-output with orthogonal frequency division multiple (MIMO-OFDM) and used for broadband wireless applications. In this paper, we address the assignment of subcarriers and power to all users to optimize the sum of user average data rates subject to constraints on signal to noise ratio, total available transmitted power, and proportionality among users, subcarriers. We compare the proposed rate adaptive scheme that maximizes the average data rate of multiuser multi input multi output orthogonal frequency division multiplexing (MU MIMO-OFDM) systems with others conversional schemes. The total power allocation scheme for MU OFDM system is proposed on convex optimization environment. As the current optimization techniques either use uniform power allocation or process only subcarrier allocation and power allocation independently. In this paper, we propose an algorithm that process subcarrier and power allocation simultaneously under data rate constraint. In this paper, a rate adaptive resource-allocation scheme, which includes adaptive power distribution, subcarrier allocation according to instantaneous channel conditions, is proposed for multiuser MIMO-OFDM system. Simulation results show the large performance improvement of proposed rate adaptive scheme over other adaptive and fixed allocation schemes.

Keywords- Multiple input multiple output (MIMO), Orthogonal frequency division multiple (OFDM), Multiuser (MU), Convex optimization, Rate adaption, Resource allocation, Water-filling scheme

References-

[1 ] Helmut Bolcskei, “MIMO-OFDM wireless Systems: Basics, Perspectives, and Challanges”, IEEE Transactions on Wireless Communications, Volume: 13, Page(s): 31 – 37, Aug.2006.

[2 ] Harish Kumar, G. Venkat Babu, Upadhayay M D,”Dynamic SubChannel Allocation in Multiuser OFDM Systems to Achieve Variable Data Rate,” ACEEE Int. J. on Communication, Vol. 02, No. 01, Mar 2011.

[3 ] Long Gao, and Shuguang Cui, “Efficient Subcarrier, Power, and Rate Allocation with Fairness Consideration for OFDMA Uplink”, IEEE Transactions on Wireless Communications, Vol. 7, NO. 5, pp. 1507-11, May 2008.

[4 ] W. Rhee and J. M. Cioffi, “Increase in Capacity of Multiuser OFDM System Using Dynamic Subchannel Allocation”, Proc. IEEE Vehic. Tech. Conf., Tokyo, Japan, May 2000, pp 1085- 1089. [5 ] Z. K. Shen, J. G. Andrews, Evans B L, “Optimal Power Allocation in Multiuser OFDM Systems”, IEEE Global Communications Conference, San Francisco, pp.337-341, 2003

[6 ] I. C. Wong, Z. K. Shen, B. L. Evans, “A low complexity algorithm for proportional resource allocation in OFDMA systems”, IEEE Workshop on Signal Processing Systems, Austin, Texas, pp.1-6, 2004. [7 ] W. Yu, W. Rhee, and J. M. Cioffi, “Optimal power control in multiple access fading channels with multiple antennas,” in Proc. IEEE ICC, vol. 2, 2001, pp. 575–579.

[8 ] Li-Chun Wang and Chu-Jung Yeh,” Adaptive Joint Sub channel and Power Allocation for Multi-User MIMO-OFDM Systems”, Industrial Technology Research Institute (ITRI), and the National Science Council, Taiwan, 4244-2644-7, IEEE 2008.

[9 ] Yuehuai Ma, Yueming Cai, Youyun Xu,”Adaptive Subcarrier and Antenna Allocation for Multiuser MIMO-OFDM Systems,” , 1- 4244-0517-3/06/2006 IEEE.

[10 ] Bin Da and Chi Chung Ko, ”Resource Allocation in Downlink MIMO–OFDM with Proportional Fairness,” Journals of communications, Vol.4, No.1, February 2009.

[11 ] Ying Jun Zhang; Letaief, K.B., “An efficient resource-allocation scheme for spatial multiuser access in MIMO-OFDM systems”, IEEE Transactions on Communications, Volume: 53 , no.1,Page(s): 107 – 116, 2005

[12 ] Hassan, N.; Assaad, M., “Low complexity margin adaptive resource allocation in downlink MIMO-OFDMA system”, IEEE Transactions on Wireless Communications, Volume: 8 ,no.7, Page(s): 3365 – 3371, 2009.

An Error Correcting System For Marine Boundary Identification

Authors: Dharani.N, Geetha.R

Abstract— The navigation tools play a major role in finding the routes of the ships. The boundary detection technique does not allow the fishermen to cross their country border. When they reach the country limit an alarm will be raised and the message will be sent to the base station at the shore through the GSM module. The new system adapts the embedded architecture based on ARM and Linux real time operating system as the software. The ARM is used as the core processor because it has high definition, less power consumption. Positioning module may be affected by EMF and inorder to maintain the accuracy of the device extended kalman filter algorithm is implemented. Keywords— Extended Kalman Filter, ARM9, Linux.

References-

[1] K.Suresh Kumar “Design of low cost maritime boundary identification device using GPS system” International Journal of Engineering Science and Technology Vol. 2(9), 2010, 4665-4672.

[2] HARVERSINE FORMULA: http://en.wikipedia.org/wiki/ Harversine_formula.

[3] Shwu-Jing Chang “Vessel identification and monitoring systems for maritime security”. IEEE 37th Annual 2003 International Carnahan Conference, 14-16 Oct. 2003.

[4] James C. Reynolds , Robert P. Denaro & Rudolph M. Kalfus “ GPSbased vessel position monitoring and display system”. Aerospace and Electronic Systems Magazine, IEEE Publication Date: Jul 1990.

[5] Marco Morgado, Paulo Oliveira, Carlos Silvestre, and José Fernandes Vasconcelos “Embedded Vehicle Dynamics Aiding for USBL/INS Underwater Navigation System.” IEEE 2013.

[6] Zhao rui , Gu Qitai “ optimal nonlinear filter for INS alignment.”, ISSN vol 7, 2003.

[7] LIU Yujing , MENG Huadong , WANG Desheng “Steady-State Analysis of Target Tracker with Constant Input/Bias Constraint.” Vol 13,2008.

[8] Qiang Fang and Sheng Xin Huang “UKF for Integrated Vision and Inertial Sensors Based on Three-View Geometry.” IEEE vol 13, 2013.

[9] Karthikeyan R, Dhndapani A, Mahalingham U “Protecting the fishermen on Indian maritime boundaries" Journal of Computer Application, 2012.

Features Affecting the Classification of Images

Authors: Parag P. Gudadhe, Nikkoo N. Khalsa

Abstract— There are numbers of methods prevailing for Image classification. This Paper includes the effect of various features to classify the image into natural & synthetic. The database of 400 JPG images was created including the raw data. Single simple features such as color map, edge map, energy level(e1, e2, e3), & thresholding value are extracted from the raw images data in order to exploit the difference of color pattern and spatial correlation of pixels in natural and synthetic images. Every feature are extracted separately and evaluation was done to identify the class of an image. The class of the image is basically based on the Human Perception of the image. The Machine interpretation of the image is based on the number of colors & pixels, their edge location & mean and wavelet mean of image. Keywords--Synthetic image, Natural image, Color map, Edge map, Energy Level, Threshold value

References-

[1] M. Szummer and R.W. Picard. Indoor-Outdoor Image Classification.

[2] H.J. Zhang. Scheme for visual feature-based image indexing.

[3] A. Vailaya, A. Jain, and H.J. Zhang. On Image Classification: City vs. Landscape.

[4] Jon.R.Smith & Shih-Fu Chang Searching for image & videos on WWW

[5] Jon.R.Smith Detecting image purpose in World-Wide Web documents

[6] A. Vailaya. Semantic classification in image databases. PhD thesis

[7] A. Vailaya, M. Figueiredo, A. Jain, and H.J. Zhang. Bayesian framework for hierarchical semantic classification of vacation images.

[8] MM Gorkani and RW Picard. Texture orientation for sorting photos ’at a glance’. Pattern reorganization 1994, Vol.1- Conference A: Computer Vision & image processing Proceedings of the 12th IAPR International Conference on, 1, 1994.

[9] E.C. Yiu. Image classification using color cues and texture orientation.

[10] R. Schettini, C. Brambilla, G Ciocca, A, Valsasna & M. De Ponti. A hierarchical classification stratery for digital documents

[11] V. Athitsos, M.J Swain, and C. Frankel. Distinguishing photographs and graphics on the world wide web.

[12] R. Lienhart and A.hartmann.Classification of image on the web automatically. Journal of Electronic Imaging.

[13] T.T. Ng, S.F. Chang, J. Hsu, L. Xie, and M.P. Tsui. Physicsmotivated features for distinguishing photographic image and computer graphics.

[14] Pei-Yu Chao, Harr transform and its application.

[15] Piotr Porwik, Agnieszka Lisowska, The Harr –wavelet transform in digital image processing

[16] Xiaolu Yang, Xuanjing Shen,Jianwu Long Haipeng Chen, An improved median based OTSU image thresholding algorithm.

A Simulation Analysis of Optimal Power Flow using Differential Evolution Algorithm for IEEE-30 Bus System

Authors: Amit Shrivastava, Hasan Mustafa Siddiqui

Abstract—This paper presents application of Differential Evolution (DE) Algorithm for solution of optimal power flow. As conventionally we use gradient based methods for optimal power flow. But conventional methods sometimes give local optimum values. And if problem is non-linear mix-integer type then it is very difficult to get the optimum solution. Therefore evolutionary techniques are applied for such problems. In this paper a IEEE-30 bus system is used for testing of effectiveness of the algorithm.

Keywords—Optimal Power Flow, Differential Evolution.

References-

[1 ] Dommel H. W., Tinney W. F., "Optimal Power Flow Solutions," IEEE Transactions on Power Apparatus and Systems, Vol. PAS - 87, No. 10, pp. 1866 - 1876, October 1968.

[2 ] Lee K. Y.,. Park Y.M, and Ortiz J.L., "A United Approach to Optimal Real and Reactive Power Dispatch," IEEE Transactions on Power Systems, Vol. PAS-104, pp.1147-1153, May1985.

[3 ] Sasson M., "Non Linear Programming Solutions for Load Flow, Minimum Loss, and Economic Dispatching Problems." IEEE Trans. on Power Apparatus and Systems, Vol. PAS-88, No.4, pp. 399-409, April 1969

.[4 ] Bouktir T., Belkacemi M., Zehar K., "Optimal Power Flow using Modified Gradient Method," Proceeding ICEL'2000, U.S.T. Oran, Algeria, Vol. 2, pp. 436-442, 13-15 November 2000.

[5 ] Kothari D.P., Dhillon J.S., “Power System Optimization”, Second Edition, PHI Learning Pvt. Ltd., 2012.

[6 ] Gnanadas R., Venkatesh P., Narayana Prasad Padhy, "Evolutionary Programming Based Optimal Power Flow for Units with Non-Smooth Fuel Cost Functions," Electric Power Components and Systems, Vo1.33, pp. 1245-1250, 2005

[7 ] Jason Yuryevich, Kit Po Wong, "Evolutionary Programming Based Optimal Power Flow Algorithm", IEEE Transactions on Power Systems, Vol. 14, No.4, pp.1245-1250, November 1999

[8 ] Rau N.S and Yih Heui Wan, “Optimum Location of Resources in Distributed Planning”, Power systems. IEEE Trans. On, Volume: 9 Issue: 4, pp.2014-2020, Nov.1994.

[9 ] Price K., “An Introduction to Differential Evolution”, Chapter 6, in D. Corne, M Dorigo and F. Glover, edt. New Ideas in Optimization, McGraw Hill, pp.79−108 1999.

[10 ] Brayton H., Hachtel G. and Sangiovanni-Vincentelli A., “A Survey of Optimization Techniques for Integrated Circuit Design”, IEEE Proc. No. 69, pp. 1334−1362, 1981.

[11 ] Becerra R.L. and. Coello Coello C.A, “Culturizing Differential Evolution for Constrained Optimization”, Proc. The Fifth Mexican International Conference in Computer Science (ENC’04), pp. 304 – 311, 2004.

[12 ] Tarek Bouktir, Linda Slimani, "Iterative Non-deterministic Algorithms in Optimal Power Flow- A Comparative Study ", Journal of Electric Systems, Vol-6, Issue-4, pp.458-477, Dec2011.

[13 ] Wong K. P., Yuryevich J., "Optima Power Flow Method using Evolutionary Programming," Springer-Verlag Berli, pp. 405-412, 1999.

[14 ] Vaisakh K., Srinivas L.R. , "Differential Evolution Approach for Optimal Power Flow Solution" Journal of Theoretical and Applied Information Technology, pp.261-268, 2008.

[15 ] Rainer Storn, Kenneth Price, "Differential Evolution - A Simple and Efficient Heuristic Scheme for Global Optimization Over Continuous Spaces", Journal of Global Optimization, vol-11, pp.341-359, 1997.

[16 ] Dervis Karaboga, Selcuk Okdem, "A Simple and Global Optimization Algorithm for Engineering Problems: Differential Evolution Algorithm", Turk J Elec. Engin.,Vol. 12, No.1, pp. 53- 60, 2004.

[17 ] Balamurugan R. and Subramanian S., "Self Adaptive Differential Evolution Based Power Economic Dispatch of Generators with Valve Point Effects and Multiple Fuel Options", International Journal Of Computer Science And Engineering, Vol-1,No.l, ISSN 1307-3699, pp.10-17, 2007.

[18 ] Willis, H.L., and W.G.Scott, “Distributed Power Generation”, New York: Marcel Dekker, 2000.

[19 ] Celli G. and Pilo F., “Optimal Distributed Generation Allocation in MV Distribution Networks”, Proceedings of the IEEE International Conference on Power Engineering Society, pp. 81- 86, May 2001.

[20 ] Varadarajan M., Swarup K. S., " Solving Multi-Objective Optimal Power Flow using Differential Evolution, " lET Gener. Transm. Distrib., Vo1.2, No.5, pp.720-730, 2008.

[21 ] Abido M. A., AI-Ali N. A., "Multi-Objective Differential Evolution for Optimal Power Flow", Lisbon, Portugal International Conference on Power Engineering, Energy and Electric Drives, pp.101-106, March 18-20, 2009.

FEA Best Practices Approach

Authors: Dr. S. Rajadurai1, M. Guru Prasad, R.Kavin, M.Sundaravadivelu

Abstract— The growing computer capabilities, human skills, aggressive cost effective product development has made analyst to rethink a lot of parameters before proceeding into the simulations. The focus of this paper is to explain the principles of understanding the concepts, meshing guidelines, defining elements types and order for successful, time efficient solutions, reducing learning curve and avoid reinvention of cycle. By performing these check list, most of the queries are cleared in the initial phase by 30% rather than in latter stages which outlay time and rework if necessary.

Keywords— Element types, Finite element analysis, FEA best practice,

References-

[1] D. Baguley & D. R. Hose, How to Model with Finite Elements, NAFEMS, 1997

[2] K.A. Honkala, ―Adequate Mesh Refinement for Accurate Stresses‖, NAFEMS Benchmark, p. 4-9, January 2000

[3] D. Baguley & D. R. Hose, ―How to Model & Interpret Results Part 3: Validation & Interpretation Considerations‖, NAFEMS Benchmark, p. 4-8, January 2001

[4] G. Roth, ―Pitfalls in Determining Analysis Accuracy‖, ANSYS Solutions, Vol. 2, No. 3, p. 30-31, Summer 2000

[5] Nithin.S.Gokhale, Sanjay.S.Deshpande, Sanjeev.V.Bedekar &Anand.N.Tite, Practical Finite Element Analysis, p.27-29,p. 63.67 p. 161-168, 2008

Recent Developments in Ground Improvement Techniques- A Review

Authors: Dr. S. K. Tiwari, N. K. Kumawat

Abstract— In recent years rapid development of infrastructures in metro cities compounded with scarcity of useful land and compelled the engineers to improve the properties of soil to bear the load transferred by the infrastructure e.g Buildings, bridges, roadways railways etc. The engineering techniques of ground improvement are removal and replacement, pre-compression, vertical drains, in-situ densification, grouting, stabilization using admixtures and reinforcement. The purpose of these techniques to increase bearing capacity of soil and reduce the settlement to a considerable extent. The one of the method among ground improvement techniques is reinforcing the soil with materials like steel, stainless steel, aluminum, fibers, fiber glass, nylon, polyster, polyamides in the form of other strips or grids and Geotextiles. The Primary purpose of reinforcing a soil mass is to improve its stability, increasing its bearing capacity and reduce Settlements and Lateral deformations. Geotextiles and geomembranes, broadly speaking are synthetic fibres used to stabilize structures built on soil. The new widely accepted generic term for these non natural materials is Geosynthetics. Geosynthetics include permeable and impermeable materials that are either of knitted, woven, or non-woven nature, as well as polymer grids and meshes. The role of geosynthetic material varies in different application as it can serve as reinforcement, separation, filtration, protection, containment, fluid transmission and confinement of soil to improve bearing capacity. Geocell reinforcement is a recently developed technique in the area of soil reinforcement having a three dimensional, polymeric, honeycomb like structure of cells made out of geo-grids inter connected at joints. Selection processes for ground improvement methodologies, improved analysis, and knowledge of long term performance and understanding of effects of variability are required to develop more efficient designs. This paper presents a review on recent development in ground improvement techniques.

Keywords— Ground improvement, Geosynthetics, Vibrocompaction, Prefabricated vertical drains, Soil reinforcement.

Refereces-

[1] Hausmann,M(1990),―Engineering principles of Ground modification‖, Mc Graw-Hill Publications.

[2] Binquet,J.& Lee, K.L. (1975), ―Bearing capacity test on reinforced earth slabs‖, Journal of Geotechnical Engineering Division, ASCE, 101(12), 1241-1255.

[3] Guido, V.A., Chang, D.K. & Sweeney, M.A. (1986), ―Comparison of geogrid and geotextile reinforced earth slabs‖,Canadian Geotechnical Journal (23), 435-440.

[4] Varaksin, S.(1981), ―Recent development in soil improvement techniques and their practical applications‖, Solcompact Sols/Soils, Techniques Louis Menard, 15, rue des Sablons, Paris, 38/39-1981.

[5] Liu, J. (2003), ―Compensation grouting to reduce settlement of buildings during an adjacent deep excavation‖, Proc. 3rd Int. Conf. on Grouting and Ground Treatment, Geotechnical Special Publication120, ASCE, New Orleans, Louisiana, 2: 837-844.

[6] Welsh, J.P., & Burke, G.K. (2000), ―Advances in grouting technology‖, Proceedings of GeoEng 2000. Melbourne.

[7] Van Impe, W. F. (1989),‖ Soil improvement techniques and theirEvolution‖, Taylor & Francis.

[8] Charlie, W.A., Jacobs, P.J., & Doehring, D.O. (1992), ―Blastinginduced liquefaction of an alluvial sand deposit‖ Geotechnical Testing Journal, ASTM, 15(1): 14-23.

[9] Bo, M.W., Chu, J., Low, B.K. & Choa, V. (2003), ―Soil Improvement Prefabricated Vertical Drain Technique‖, Thomson Learning.

[10] Mitchell, J.K., & Katti R.K. (1981), ―Soil Improvement‖ - State of the Art Report. 10th ICSMFE, Stockholm, 4: 509-565. [11] Karol, R.H. (2003), ―Chemical Grouting and Soil Stabilization‖, 3rd: CRC Press.

An Enhanced Speech Recognition System

Authors: Suma Shankaranand, Manasa S, Mani Sharma, Nithya A.S, Roopa K.S., K.V. Ramakrishnan

Abstract— This paper describes the development of an efficient speech recognition system using various techniques such as Mel Frequency Cepstrum Coefficients (MFCC), Vector Quantization (VQ), Hidden Markov Model (HMM) and Autocorrelation. In this paper, a method to recognize the speech faster with more accuracy, speaker recognition is followed by speech recognition. MFCC/Autocorrelation is used to extract the characteristics from the input speech signal with respect to a particular word uttered by a particular speaker. Then HMM is used on Quantized feature vectors to identify the word by evaluating the maximum log likelihood values for the spoken word.

Keywords— MFCC, VQ, HMM, log likelihood, Autocorrelation.

Refereces-

[1] Ronald, M. Baecker, “Readings in human-computer interaction: toward the year 2000”, 1995.

[2] Melanie, Pinola, “Speech Recognition Through the Decades: How We Ended Up With Siri”, PCWorld.

[3] Ganesh Tiwari, “Text Prompted Remote Speaker Authentication: Joint Speech and Speaker Recognition/Verification System”.

[4] Dr.Ravi Sankar, Tanmoy Islam, Srikanth Mangayyagari, “Robust Speech/Speaker Recognition Systems”.

[5] Bassam A.Q.Al-Qatab and Raja.N.Aninon, “Arabic Speech Recognition using Hidden Markov Model ToolKit (HTK)”, IEEE Information Technology (ITSim), 2010, pp. 557-562.

[6] Ahsanul Kabir, Sheikh Mohammad Masudul Ahsan, ”Vector Quantization in Text Dependent Automatic Speaker Recognition using Mel-Frequency Cepstrum Coefficient”, 6th WSEAS International Conference on circuits, systems, electronics, control & signal processing, Cairo, Egypt, dec 29-31, 2007, pp. 352-355

[7] Lindasalwa Muda, Mumtaj Begam and Elamvazuthi.,”Voice Recognition Algorithms using Mel Frequency Cepstral Coefficient (MFCC) and DTW Techniques “,Journal of Computing, Volume 2, Issue 3, March 2010

[8] Mahdi Shaneh and Azizollah Taheri, ”Voice Command Recognition System based on MFCC and VQ Algorithms”, World Academy of Science, Engineering and Technology Journal, 2009.

[9] Remzi, Serdar Kurcan, “Isolated word recognition from in-ear microphone data using hidden Markov models (hmm)”, Master’s Thesis, 2006.

[10] Nikolai Shokhirev, ”Hidden Markov Models “, 2010.

[11] L.R. Rabiner, “A tutorial on Hidden Markov Models and selected applications in Speech Recognition”, Proceedings of the IEEE Journal, Feb 1989, vol. 77, Issue: 2. [12] Four phonetically balanced words list, Available from: http://www.meyersound.com/support/papers/speech/pblist.htm

Materials for Automotive Exhaust System

Authors: S. Rajadurai, M. Afnas, S. Ananth, S. Surendhar

Abstract— Durable exhaust system design, development and manufacturing is mandated for the vehicle to be competitive and comparative. Material selection for the exhaust system plays a vital role due to the increased warranty requirements and regulatory compliances. Physical, chemical and mechanical characteristics of the materials used for conventional and special applications are compared. Exhaust system materials should possess high temperature oxidation resistance, thermo mechanical vibration resistance, external salt corrosion resistance and internal acid/base corrosion resistances. Internal components such as inner cones, baffle plates, retainer rings, perforated pipes and external components such as hanger rod, outer shell, heat shield, end caps outer cones, flex tube, manifold etc. should be able to withstand high thermal impact and vibrations caused by road load, thermal load and engine load. The effect of additives such as Ti, Mo, Mn and Si to the base steel material is presented. Properties of mild steel, stainless steel and aluminized steel are compared. Applications of special materials such as Inconel, FeCrAlloy, 18CrCb and A286 are discussed in detail. Keywords— Conventional, Durability, Exhaust system, High temperature applications, Material selection, Properties.

References-

[1] WWW.AZOM.COM

[2] WWW.STAL.COM/CN.

[3] JIS HAND BOOK FERROUS MATERIALS & METALLURGY I, II(2001 EDITION)

[4] [JIS G (3141:2009, 3131:2010, 4303:2005, 3101:2010, 4051:2009 , 3314:2010, 3445:2010,4305:2005,4312:1991)].

[5] IS 3589:2001.

[6] WWW.JFE-STEEL.CO.JP/../GLE-001.PDF

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[8] WWW.EFUNDA.COM/.

[9] Metals.about.com/od/metallurgy/a/The-Effect-of-Alloying-Agentson-steel-properties.htm

[10] S. Rajadurai, L. Geer, C. Chung, H. Cheng, B. Snider, T. Carlson and J. Michels, H.Schwallbach, A. Montalbano, B.Chomicz, W. Ickes and R. Beason1999Shoebox Converter Design for Thin wall Ceramic Substrates

[11] Sivanandi Rajadurai, Shiju Jacob, Chad Serrell, Rob Morin and ZlatomirKircanski, 2006, Durable Catalytic Converter Mounting with Protective and Support Seals.

Observation and Calculation of Different Harmonics in Fly Back Converter

Authors: Pradosha Kumar Mohanty, R. P. Dalai

Abstracts-In order to avoid dangerous interactions between power and control part of the integrated circuit, it is necessary to control the rate of change of the power device voltage at turn-off. Accordingly, lossless passive Snubber was added to the conventional converter topology. The Snubber also limits the voltage spikes across the power device, due to the transformer leakage inductance, and reduces the electromagnetic noise generation. A basic review of the fly back switching topology will be presented with an emphasis on not-so-obvious design issues, such as effects of parasitic, fault protection, and EMI mitigation. Modeling and analysis will be demonstrated. The study involves analysis, circuit design, performance comparisons and implementation. The circuits are investigated by means of computer simulations. Operating principles and operating modes are studied along with design calculations. After applying prototypes in laboratory, the simulation results and theoretical analyses are confirmed.

Keywords----SMPS, MOSFET, Snubber Resistance, Snubber circuit, fly back converter

References-

[1] S. Y. Tseng, C. T. Hsieh and H. C. Lin, “Active clamp interleaved flyback converter with single-capacitor turn-off snubber for stunning poultry applications,” in Proc. IEEE PEDS Conf., 2007, pp. 1401- 1408

[2] A. Bakkali, P. Alou, J. A. Oliver and J. A. Cobos, “Average modeling and analysis of a flyback with active clamp topology based on a very simple transformer,” in Proc. IEEE APEC Conf., 2007, pp. 500-506.

[3] Y. Xi, P. K Jain, G. Joos and Yan Fei Liu, “An improved zero voltage switching flyback converter topology,” in Proc. IEEE PESC Conf., vol. 2, 1998, pp. 923-929.

[4] Keith Billings, Switchmode Power Supply Handbook, 1999. McGraw-Hill Professional.D.M. Mitchell, Switching Regulator Design & Analysis, distributed by E/J Bloom Associates, 2000.

[5] L. L. Fang, Y. Hong, “Power Electronics: Advanced Conversion Technologies”, CRC Press, 2010

[6] R. Redl, L. Balogh, and N. O. Sokal, “A new family of single stage isolated power factor correctors with fast regulations of the output voltage,” in Proc. IEEE-PESC’94 Annu. Meeting, 1994, pp. 1137– 1144.

[7] C. Qiao, K.M. Smedley, “A topology survey of single-stage power factor corrector with a boost type input-current-shaper” in Proc. IEEE Appl. Power Electron. Conf. (APEC), Feb. 2000, pp.460467.

[8] Q. Zhao, F.C. Lee, F. Tsai, “Voltage and current stress reduction in single-stage power factor correction ac/dc converters with bulk capacitor voltage feedback” IEEE Transactions on Power Electronics, Vol. 17, No. 4, July 2002.

[9] L. Huber and M.M. Jovanovic, “AC/DC flyback converter”, U. S. Patent No.6950319, Sept. 2005 [10] V. Vorperian, “Simplified analysis of PWM converters using model of PWM switch Part 2: discontinuous conduction mode” IEEE Transaction on Aerospace and Electronic Systems, Vol. 26, pg.497- 505, 1990.

Promoting Green Computing To Provision Backup Management of Disaster Recovery Cloud

Authors: Pavithra Mani, Rathi Gopalakrishnan

Abstract— Recent day situation show that frequently occurring natural disasters destroy large amount of data that are of prime importance. The use of Cloud Computing permits to have redundancy spread across the world and makes it possible for us to retrieve data that is lost or damaged from another centre using DRaaS as a sequence of Business Continuity Plan .The DR sites need to be powered throughout to ensure recovery. The power required to run these secondary sites can utilize the widely available renewable sources of energy and promote a green backup service to consumers.

Keywords— Cloud Computing, DRaaS, Business Continuity, Solar energy

References-

[1] Wood, Timothy, et al. "Disaster recovery as a cloud service: Economic benefits & deployment challenges." 2nd USENIX Workshop on Hot Topics in Cloud Computing. 2010.

[2] Li, Juan, et al. "Community-based cloud for emergency management." System of Systems Engineering (SoSE), 2011 6th International Conference on. IEEE, 2011.

[3] Wood, Timothy, Alexandre Gerber, K. K. Ramakrishnan, Prashant Shenoy, and Jacobus Van der Merwe. "The case for enterprise-ready virtual private clouds."Usenix HotCloud ,2009

[4] Alhazmi, Omar H., and Yashwant K. Malaiya. "Assessing Disaster Recovery Alternatives: On-site, Colocation or Cloud." Software Reliability Engineering Workshops (ISSREW), 2012 IEEE 23rd International Symposium on. IEEE, 2012.

[5] Velev, Dimiter, and Plamena Zlateva. "A Feasibility Analysis of Emergency Management with Cloud Computing Integration." International Journal of Innovation and Technology,Vol.3, No.2, 2012

[6] Hantula, Richard. How Do Solar Panels Work?. Infobase Publishing, 2010

[7] Smith, Eric. DIY Solar Projects: How to Put the Sun to Work in Your Home. Creative Publishing int'l, 2011

[8] Vine, Edward, and Jan Hamrin. "Energy savings certificates: A market-based tool for reducing greenhouse gas emissions." Energy Policy 36.1 (2008): 467-476.

[9] Manwell, J. F., J. G. McGowan, and A. L. Rogers. "Wind energy explained: theory, design and application. 2002." John Wiley&Sons Ltd, UK (2002): 577.

[10] Chiras, Daniel D. Wind Power Basics. New Society Publishers, 2010. [11] Dodge, Darrell M. Illustrated history of wind power development. Darell M. Dodge, 2001

A Survey of Estimation of Carrier Frequency Offset for OFDM Systems

Authors: Md Nasim Ansari, Garima Saini

Abstract-The paper proposed a detail survey of the estimation of carrier frequency offset (CFO) for orthogonal frequency division multiplexing (OFDM) systems in past ten years. The paper reviews a lot of estimation techniques as well as compares different types of blind estimation techniques based on carrier frequency offset estimation performance, cost constraint as well as on requirements. In CFO estimation using Blind Maximum likelihood estimation (MLE) scheme is always able to decode with probability close to one. In the maximum likelihood technique, numerical iteration for blind estimation of carrier frequency offset gives low complex. It has fast convergence and achieves high accurate estimation.

Keywords-Orthogonal frequency division multiplexing (OFDM); Carrier Frequency Offset (CFO); Mean square error (MSE); Signal to noise ratios (SNRs); Blind Maximum likelihood estimator (MLE).

References-

[1] U. S. Jha and R. Parsad, OFDM towards Fixed and Mobile Broadband Wireless Access, Artech House, 2000.

[2] S. Hara and R. Parsad, Multicarrier techniques for 4G Mobile Communication, Artech House, 2000.

[3] A.AL-Dweik, R. Hamila, and M. Renfors, “Blind Estimation of Large Carrier Frequency Offset in Wireless OFDM Systems”, IEEE Transactions on Vehicular Technology, Vol. 56, No.2, pp. 965-968, March 2007.

[4] Kun-Yi Lin, Hsin-Piao Lin, and Ming-Chien Tseng, “An Equivalent Channel Time Variation Mitigation Scheme for ICI Reduction in High Mobility OFDM Systems”, IEEE Transactions on Broadcasting, Vol.58, No. 3, pp. 472-479, September 2012.

[5] Jia-Chin Lin, “A Frequency Offset Estimation Technique Based on Frequency Error Characterization for OFDM Communications on Multipath Fading Channels”, IEEE transactions on vehicular technology, Vol. 56, No. 3, pp. 1209-1222, May 2007.

[6] Xiang Nian Zeng, and Ali Ghrayeb, “A Blind Carrier Frequency Offset Estimation Scheme for OFDM Systems with Constant Modulus Signaling”, IEEE Transactions on Communications, Vol. 56, No. 7, pp. 1032-1037, July 2008.

[7] Hyoung-Goo Jeon, Kyoung-Soo Kim, and Erchi Serpedin, “An Efficient Blind Deterministic Frequency Offset for OFDM Systems”, IEEE Transactions on Communications, Vol. 59, No. 4, pp. 1133- 1141, April 2011.

[8] A. Al- Dweik, A. Hazmi, S. Younis, B. Sharif and C. Tsimenidis, “Carrier Frequency Offset Estimation for OFDM Systems Over Mobile Radio Channels”, IEEE Transactions on Vehicular Technology, Vol. 59, No. 2, pp. 974-979, February 2010.

[9] A.J. Al-Dweik, B.S. Sharif and R.M. Shubair, “Blind frequencyoffset estimator for OFDM with general symbol constellation”, IEEE Electronics letters, Vol. 44, No. 16, pp. 980-981, July 2008.

[10] Feifei Gao and A Nallanathan, “Blind Maximum Likelihood CFO Estimation for OFDM Systems via Polynomial Rooting”, IEEE Signal Processing Letters,Vol.13, No.12, pp.73-76, February 2006.

[11] Jaechan Lim and Daehyoung Hong, “Gaussian Particle Filtering Approach for Carrier Frequency Offset Estimation in OFDM Systems”, IEEE Signal Processing Letters, Vol 20, No. 4, pp. 367- 370, April 2013.

[12] Michele Moreli, and Macro Moretti, “Carrier Frequency Offset Estimation for OFDM Direct- Conversion Receivers”, IEEE Transactions on Wireless Communications, Vol.11, No.7, pp. 2670- 2679, July 2012.

[13] Hyoung-Goo Jeon, Kyoung-Soo Kim, and Erchin Serpedin, “An Efficient Blind Deterministic Frequency Offset Estimator for OFDM Systems”, IEEE Transactions on Communications, Vol. 59, No. 4, pp. 1133-1141, April, 2011.

[14] Yingwei Yao, and Georgios B. Giannakis, “Blind Carrier Frequency Offset Estimation in SISO, MIMO, and Multiuser OFDM Systems”, IEEE Transactions on Communications, Vol. 53, No. 1, pp. 173-183, January, 2005.

[15] Seong wook Song, and Andrew C. Singer , “Pilot Aided OFDM Channel Estimation in the Presence of Guard Band”, IEEE Transactions on Communications ,Vol. 55, No.8, pp. 1459-1465, August 2007.

[16] Hung–Tao Hsieh and Wen Rong Wu, “Blind Maximum–Likelihood Carrier Frequency Offset Estimation for Interleaved OFDMA Uplink Systems”, IEEE Transactions on Vehicular technology, Vol. 60, No.1, pp. 160-173, January 2011.

[17] Wen-Long Chin, “Blind Symbol Synchronization for OFDM Systems Using Cyclic Prefix in Time-Variant and Long-Echo Fading Channels”, IEEE Transactions on Vehicular Technology, Vol.61, No.1, pp.185-195, January 2012.

Acoustic Echo Cancellation For Speech And Random Signal Using Estimated Impulse Responses

Authors: S. I. M. M. Raton Mondol, Y. Zhou

Abstract— In this paper, the Acoustic Echo Cancellation (AEC) are investigated by using Finite Impulse Responses Adaptive Filter with the analysis of Mean Square Error (MSE) and its convergence property. It is the result of a project in the course Fundamental of Signal Processing at Chongqing University of Posts and Telecommunications. It focuses on Normalized Least Mean Square (NLMS) algorithm of adaptive filtering, employing a discrete signal processing in MATLAB for simulation with speech and random signals.

Keywords— AEC, Adaptive Filter, MSE, LMS, NLMS

References-

[1] Rafid Ahmed Khalil, Adaptive Filter Application in Echo Cancellation System and Implementation using FPGA, Electrical Engineering Department, Engineering College, University of Mosul.

[2] Duong Quang K. Ngoc and Seung-Hyon Nam, IMPLEMENTATION OF A BASIC ACOUSTIC ECHO CANCELLER, Department of Electronic Engineering, Paichai University, Daejeon, Korea.

[3] J. B. ALLEN AND D. A. BERKLEY. Image Method for Efficiently Simulating Small-Room Acoustics. J. Acoust. Soc. Am. 65, 943–950 (1979).

[4] Christina Breining, Pia Dreiseitel, Eberhard Hänsler, Andreas Mader, Bernhard Nitsch, Henning Puder, Thomas Schertler, Gerhard Schmidt, and Jan Tilp, Acoustic Echo Control – An Application of Very High Order Adaptive Filters

[5] M. MBOUP AND M. BONNET. On the Adequateness of IIR Adaptive Filtering for Acoustic Echo Cancellation. In “Proc. EUSIPCO-92, Sixth European Conference on Signal Processing”, vol. 1, pp. 111–114, Brussels, Belgium (1992).

[6] A. P. LIAVAS AND P. A. REGALIA. Acoustic Echo Cancellation: Do IIR Models Offer Better Modeling Capabilities than Their FIR Counterparts? IEEE Trans. Signal Processing 46(9), 2499–2504 (1998).

[7] Ms. Kinjal Rasadia, Dr. Kiran Parmar, Adaptive Filter Analysis for System Identification Using Various Adaptive Algorithms. [8] Syed Zahurul Islam, Syed Zahidul Islam, Ra-zali Jidin, Mohd. Alauddin Mohd. Ali, “Performance Study of Adaptive Filtering Algorithms for Noise Cancellation of ECG Signal”, IEEE 2009.

Wireless Visual 3D Sensors For Monitoring Environments And Resource Allocation

Authors: Anto Rose.R, Vinod.S, Daya Florance.D

Abstract— The Sensors plays vital role in many fields like monitoring volcano, fire etc. This paper investigates the resource allocation for each and every sensed data. In this we considered a single hop network topology. Each and every sensors in single-hop network topology transmit the sensed data directly to a centralized control unit(CCU), Which manages the available network resources. The normal sensors does not sense the environmental condition properly, so for sensing the environmental condition properly instead of normal sensors we consider 3D sensors. The Sensed data like the data which are in video format requires more quality. For providing quality we use various quality driven criteria, which provides more quality for the varying motion characteristics of each recorded video. The CCU provides transmission power and source channel coding rates for each nodes. The swarm optimization algorithm is used for monitoring dynamic nature of the environment, the approximation algorithm is used for solving the coverage problem and the greedy algorithm is used for covering the most region. The simulation is used for demonstrate the process.

Keywords—Centralized Control Unit, Dynamic Nature, High Quality,Video Motions, Resource Allocation, 3D Senors .

References-

[1] I. F. Akyildiz, T. Melodia, and K. R. Chowdhury, ―A survey on wireless multimedia sensor networks,‖Comput. Netw. J., vol. 51, pp. 921–960,

[2] S. Soro and W. Heinzelman, ―A survey of visual sensor networks,‖ Adv.Multimedia, vol. 2009, pp. 640386-1–640386-21, May 2009.

[3] Y.-C. Lin and S.-C. Tai, ―Fast full-search block-matching algorithm for motion-compensated video compression,‖ IEEE Trans. Commun., vol. 45, no. 5, pp. 527–530, May 1997.

[4] E. S. Bentley, L. P. Kondi, J. D. Matyjas, M. J. Medley, and B. W. Suter,―Spread spectrum visual sensor networks resource management using an end-to-end cross layer design,‖IEEE Trans. Multimedia, vol. 13, no. 1,pp. 125–131, Feb. 2011.

[5] Y. S. Chan and J. W. Modestino, ―A joint source coding-power control approach for video transmission over CDMA networks,‖ IEEE J. Sel. Areas Commun., vol. 21, no. 10, pp. 1516–1525, Dec. 2003.

An Incentivized Approach for Fair Participation in Wireless Ad hoc Networks

Authors: Arka Rai Choudhuri, Kalyanasundaram S, Shriyak Sridhar, Annappa B

Abstract— In Wireless Ad hoc networks (WANETs), nodes separated by considerable distance communicate with each other by relaying their messages through other nodes. However, it might not be in the best interests of a node to forward the message of another node due to power constraints. In addition, all nodes being rational, some nodes may be selfish, i.e. they might not relay data from other nodes so as to increase their lifetime. In this paper, we present a fair and incentivized approach for participation in Ad hoc networks. Given the power required for each transmission, we are able to determine the power saving contributed by each intermediate hop. We propose the FAir Share incenTivizEd Ad hoc paRticipation protocol (FASTER) which calculates the worth of each node using the cooperative game theory concept of ‘Shapley Value’ applied on the power saved by each node. This value can be used for allocation of Virtual Currency to the nodes, which can be spent on subsequent message transmissions.

Keywords— Cooperative Game theory, Fair and Incentivized, Shapley Value, Virtual Currency

References-

[1] Zhong, Sheng, Jiang Chen, and Yang Richard Yang. "Sprite: A simple, cheat-proof, credit-based system for mobile ad-hoc networks." In INFOCOM 2003. Twenty-Second Annual Joint Conference of the IEEE Computer and Communications. IEEE Societies, vol. 3, pp. 1987-1997. IEEE, 2003.

[2] Zhu, Haojin, Xiaodong Lin, Rongxing Lu, Yanfei Fan, and Xuemin Shen. "Smart: A secure multilayer credit-based incentive scheme for delay-tolerant networks. "Vehicular Technology, IEEE Transactions on 58, no. 8 (2009): 4628-4639.

[3] Chen, Bin Bin, and Mun Choon Chan. "Mobicent: A credit-based incentive system for disruption tolerant network." In INFOCOM, 2010 Proceedings IEEE, pp. 1-9. IEEE, 2010.

[4] AuYoung, Alvin, Brent Chun, Alex Snoeren, and Amin Vahdat. "Resource allocation in federated distributed computing infrastructures." In Proceedings of the 1st Workshop on Operating System and Architectural Support for the On-demand IT InfraStructure, vol. 9. 2004.

[5] S. Das, C.E. Perkins and E. M. Royer. Ad hoc On Demand Distance Vector(AODV) Routing. Mobile Ad-hoc Network (MANET) Working Group, IETF, January 2002.

[6] Yang, Yaling, Jun Wang, and Robin Kravets. "Designing routing metrics for mesh networks." In IEEE Workshop on Wireless Mesh Networks (WiMesh). 2005.

[7] Cai, Jianfeng, and Udo Pooch. "Allocate fair payoff for cooperation in wireless ad hoc networks using shapley value." In Parallel and Distributed Processing Symposium, 2004. Proceedings. 18th International, p. 219. IEEE, 2004.

[8] Gomez, Javier, Andrew T. Campbell, Mahmoud Naghshineh, and Chatschik Bisdikian. "PARO: Supporting dynamic power controlled routing in wireless ad hoc networks." Wireless Networks 9, no. 5 (2003): 443-460.

[9] Buttyan, Levente, and Jean-Pierre Hubaux. "Nuglets: a Virtual Currency to stimulate cooperation in self-organized mobile ad hoc networks." (2001).

[10] David Kotz, Calvin Newport, Robert S. Gray, Jason Liu, Yougu Yuan, and Chip Elliott. “Experimental evaluation of wireless simulation assumptions”, Dartmouth Computer Science Technical Report TR2004-507 June 2004.

A 45-nm CMOS 16-bit Segmented Current-Steering Digital-to-Analog Converter

Author: Rahul J. Acharya

Abstract—This Paper presents a 16-bit Digital-to-Analog Converter (DAC) using 45 nanometer CMOS technology for mixed-signal applications. A segmented current steering architecture is used for this DAC in which 6-bits are used in thermometer coded architecture while 10-bits are used in binary weighted architecture. This architecture gives the most optimized results in terms of speed, resolution and power. The designed 16-bit DAC operates with two supply voltages, 1 V and 3.3 V. The designed 16-bit DAC provides acceptable accuracy with Differential Non-Linearity (DNL) and Integral Non-Linearity (INL) of + 0.8 Least Significant Bit (LSB) and + 0.7 Least Significant Bit (LSB), respectively. The measured Spurious Free Dynamic Range (SFDR) at 1 GHz sampling rate is 68 dB. The average power dissipation at 1 GHz sampling rate is 2.74 mW. The maximum sampling rate of DAC is 1.62 GHz. The tool used for simulation is Tanner SEdit and T-Spice.

Keywords— Binary Weighted, CMOS Analog Circuits, Current Steering, Digital to Analog Conversion, Mixed Analog -Digital Integrated Circuits.

References-

[1] R. Jacob Baker, CMOS Circuit Design, Layout and Simulation, Third Edition, Wiley Publication, 1964, pp. 1-31, 931-1022.

[2] J Jacob Wikner, Studies on CMOS Digital-To-Analog Converters, Department of Electrical Engineering Linköpings universitet, SE581 83 Linköping, Sweden Linköping, 2001, pp. 1-77.

[3] Chi-Hung Lin and Klaas Bult, "A 10-b, 500-MSample/s CMOS DAC in 0.6 mm2" IEEE Journal Of Solid-State Circuits, Vol. 33, No. 12, December 1998

[4] Samiran Halder, Swapna Banerjee, Arindrajit Ghosh, Ravi sankar Prasad, Anirban Chatterjee, Sanjoy Kumar Dey, ―A 10-bit 80-MSPS 2.5-V 27.65-mW 0.185-mm2 Segmented Current Steering CMOS DAC‖, Proceedings of the 18th International Conference on VLSI Design held jointly with 4th International Conference on Embedded Systems Design, 2005

[5] Xu Wu and Michiel Steyaert, ―A 90nm CMOS 5-bit 2GS/s DAC for UWB Transceivers‖, Proceedings of 2010 IEEE International Conference on Ultra-Wideband (ICUWB2010)

[6] Rahmi Hezar, Lars Risbo, Halil Kiper, Mounir Fares, Baher Haroun, Gangadhar Burra, Gabriel Gomez, ―A 110dB SNR and 0.5mW Current-Steering Audio DAC Implemented in 45nm CMOS‖, ISSCC 2010.

[7] Mahdi Khafaji, Hans Gustat, Behnam Sedighi, Frank Ellinger, and Johann Christoph Scheytt, ―A 6-bit Fully Binary Digital-to-Analog Converter in 0.25-μm SiGe BiCMOS for Optical Communications‖, IEEE Transactions on Microwave Theory and Techniques, 2011.

[8] Razavi Behzad, Principles of Data Conversion System Design, IEEE Press, 1995

[9] Aliparast Peiman, Koozehkanai Ziaddin Daie, Sobhi Jafar, ―Design of a 10-bit Low Power Current-Steering Digital-to-Analog Converter Based on a 4-D Thermometer Decoding Matrix‖, 17th International Conference "Mixed Design of Integrated Circuits and Systems", June 24-26, 2010, Wroc_aw, Poland

[10] Wikner J Jacob, Dissertation Thesis, ―Studies on CMOS Digital-ToAnalog Converters‖, Department of Electrical Engineering Linköpings Universitet, SE-581 83 Linköping, Sweden Linköping, 2001, pp. 1-77.

[11] Gustavsson Mikael, Wikner J. Jacob, Tan Nianxiong Nick, CMOS Data Converters for Communications, Kluwer Academic Publishers, 2002

[12] Zite Shalaka E., Beek P. C. W. van, Briaire Joost, Hegt J. A. and Roermund A. H. M. van, ―Scaling a Digital-to-Analog Converter from CMOS18 to CMOS090‖, In ProRisc 2005

[13] Raja Gaurav & Bhaumik Basabi, ―16-bit Segmented Type Current Steering DAC for Video Applications‖, Proceedings of the 19th International Conference on VLSI Design (VLSID’06), 2006

[14] Maruthi Chandrasekhar Bh, Dr. Sudeb Dasgupta, ―A 1.2 Volt, 90nm, 16-Bit Three Way Segmented Digital to Analog Converter (DAC) for Low Power Applications‖, 10th International Symposium on Quality Electronic Design, 2009

Emulating Interrupts Using Mobile Technology

Authors: R. Anusuya, M. Mahalakshmi, Dr.J. R. Arunkumar

Abstract— The analysis of sensor networks is a confirmed issue. In this paper, we disprove the emulation of compilers. Despite the fact that such a hypothesis at first glance seems unexpected, it is derived from known results. MIASM, our new heuristic for flexible methodologies, is the solution to all of these issues.

Keywords— WAN, SCSI Disks, MIASM, XML, DHCP, Mobile technology, Interrupts;

References-

[1] Agarwal, R., Karp, R., and arun. Web browsers considered harmful. Journal of Empathic, Atomic Algorithms (Jan. 2003), 79–91.

[2] Dongarra, J. Refinement of access points. In Proceedings of MOBICOM (Dec. 2001).

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[4] Garcia-Molina, H. Homogeneous, reliable symmetries for operating systems. In Proceedings of VLDB (Sept. 2002).

[5] Johnson, J., Harris, P., and Hopcroft, J.Log: Game-theoretic, peer-topeer methodologies. Journal of ―Fuzzy‖ Communication9 (Nov. 2002), 20–24.

[6] Kaashoek, M. F., Adelman, L., and Sato, M. Deconstructing DHTs. NTT Technical Review 366 (June 1999), 59–67

[7] Levy, H., Moore, Z., and Zhao, W. 64 bit architectures considered harmful.OSR 82 (Feb. 2003), 58–64.

[8] Nygaard, K. Simulation of forward-error correction. In Proceedings of the Workshop on Ambimorphic, Low-Energy, Introspective Models (Sept. 2000).

[9] Quinlan, J., and Garcia, B. D.A case for checksums. Journal of Pervasive, Modular, Electronic Archetypes (Sept. 2002), 49–55.

[10] Quinlan, J., Gupta, a., and Harris, L. Exploring expert systems and semaphores using Xyst. In Proceedings of the Symposium on Psychoacoustic Theory (Oct. 2005).

[11] Raman, O. S. The impact of large-scale modalities on software engineering. In Proceedings of the Work shop on Unstable, Knowledge-Based Methodologies (June 1997).

[12] Sasaki, T., Culler, D., Sutherland, I., and Maruyama, U. Exploring erasure coding using omniscient communication. In Proceedings of NSDI (Sept. 2003).

Design and Implementation of Different Generations of Current Conveyor using 100nm CMOS Technology

Authors: R V Yenkar, R S Pande, S S Limaye

Abstract— Current conveyors are unity gain analog building block having high linearity, wide dynamic range and provide higher gain-bandwidth product. The current conveyors operate at low voltage supplies and consume less power. It has high input impedance, low output impedance and unity current gain (Iz/Ix=±1) as well as unity voltage gain (Vx/Vy=1). The working principle of Current Conveyors is very simple. The current conveyors can easily be implemented using voltage follower and current mirrors. The proposed current conveyors are simulated using 100nm CMOS technology on Advanced Design System. The main features of these current conveyors are low voltage, less power, high slew rate and wide bandwidth for voltage transfer (Vy to Vx) and current transfer (Ix to Iz) which make them suitable for high frequency and low power applications.

Keywords— CCI, CCII, current conveyor, current mirrors, current mode circuit

References-

[1] R V Yenkar, R S Pande and S S Limaye. ‗The Survey of Historical - Technical Development In Current Conveyors And Their Applications‘. IJCA Proceedings on National Conference on Innovative Paradigms in Engineering and Technology (NCIPET 2012) ncipet(4):17-23, March 2012.

[2] B. Wilson, ‗Recent developments in current conveyors and currentmode circuits‘, IEE Proceedings, 1990, 137(2) pp. 63-77

[3] Liu, Tsao, J. Wu and Tsay, ‗Nonlinear circuit applications with current Conveyors‘, IEE PROC. 140(1), 1993, pp. 1-6.

[4] Smith K C and Sedra A: ‗The current conveyor – new building block‘, IEEE Proc., 1968, 56, pp. 1368-1369 [5] Sedra A and Smith K C: ‗A second generation current conveyor and its applications‘, IEEE trans, 1970, CT-17 pp. 132-134

[6] Sedra A, Robert G, Gohn F S: ‗The current conveyor: history and progress, IEEE International Symp. on Circuits and Systems, Portland, USA, 1989,3, pp. 1567-1570

[7] Grigorescu L, ‗Amplifier built with current conveyors‘, Rom. Journ. Phys., 2008, 53(1-2) pp. 109-113

[8] Senani R, ‗Novel application of generalized current conveyor‘, Electronics Letter, 1984, 20(4), pp. 169-170

[9] E. Bruun, ―Class AB CMOS first-generation current conveyor‘‘, Electronics letters, Vol. 31, No.6, pp. 442-443, 1995.

[10] Amruta Bhatt, ―Design and Analysis of CMOS Current Conveyor‖, Journal of Information, Knowledge and research in Electronics and communication Engineering, Nov2012. [11] O. Oliei and P. Loumeau, ―A low-input resistance class AB CMOS current-conveyor‘‘, IEEE MWSCAS, IWOA, pp. 11-14, 1996.

Yawning Detection of Driver Drowsiness

Authors: Ankita Shah, Sonaka Kukreja, Pooja Shinde, Ankita Kumari

Abstract-- Drowsiness in driver is primarily caused by lack of sleep. However, it can also be induced by extended time on task, obstructive sleep apnea and narcolepsy. “Drowsy drivers usually do not „drop off‟ instantaneously. As a substitute, there is a preceding period of quantifiable performance decrement with associated physiological signs.” In this paper, we discuss a method for detecting driver‟s drowsiness and subsequently alerting them. The aim is to reduce the number of accidents due to drivers fatigue and hence increase the transportation safety. Many special body and face gestures are used as sign of driver fatigue, including yawning, eye tiredness and eye movement, which indicate that the driver is no longer in a proper driving condition.

Keywords--Face Detection, Mouth Detection and Yawning Detection.

References-

[1] Shabnam, Adtahi, Behnoosh Hariri, ShervinShirmohammadi,"Drive Drowsiness Monitoring Based on Yawing Detection",In:Proc. International Conf. on Detecting Drowsiness of Driver,978-1-4244- 7935-1/11 IEEE 2011.

[2] X. Fan, B. Yin, Y. Fun. “Yawning Detection For Monitoring Driver Fatigue.” In: Proc. Sixth International Conf. on Machine Learning and Cybernetics, Hong Kong ,pp. 664-668, 2007.

[3] T.Azim, M..A Jaffar, A.M Mirza. “Automatic Fatigue Detection of Drivers through Pupil Detection and Yawning Analysis. “In :Proc.Fourth International Conf.on Innovative Computing, Information and Control, 2009, pp.441-445.

[4] L.Li,Y.Chen , Z.Li. “Yawning Detection for Monitoring Driver Fatigue Based on Two Cameras.” In:Proc. 12th International IEEE Conf. on Intelligent Transportation Systems, St. Louis, MO , USA, 2009, pp.12-17.

[5] Hsu Rein-Lien, M. Abdel-Mottalab, and A.K.jain.”face detection in color images.”

[6] http://www.vision.caltech.edu/html-files/archive.html

[7] S.G. Klauer, T.A. Dingus nele“the impact of driver inattention on near crash car risk: an analysis using the 100 car naturalistic driving study data”.

Real Time Communication

Authors: Simar Preet Singh, Anjali Passi

Abstract-The capabilities of real time communication are of its high speed, high bandwidth in real time application such as multimedia services and automation factory. It will help the user to exchange their information as multimedia, audio content in real time. Traditionally, real time communication is soft and hard real time communication. In this, VoIP is future of voice and video communication such as yahoo, Msn, Google talk and Skype. Several real time applications are used in corporation and business world. RTC is the new integrate communication medium based on W3C standards web RTC.

Keywords- Communications, Real-Time, Transmission, Multimedia, VoIP, Messaging

References-

[1] 3D Videocommunication: Algorithms, concepts and real-time systems in human centred communication edited by Oliver Schreer, Peter Kauff, Thomas Sikora

[2] Real-Time Systems: Theory and Practice Author name Rajib Mall Publisher: Pearson Education India

[3] Automatic Verification of Real-Time Communicating Systems by Constraint-Solving Wang Yi, Paul Pettersson, and Mats Daniels Department of Computer Systems, Uppsala University. Sweden.

[4] Real-Time Communication in Packet-Switched Networks Caglan M. Aras,1 James F. Kurose,2 Douglas S. Reeves3 and Henning Schulzrinne

[5] A Real-Time Communication Architecture for Large-Scale Wireless Sensor Networks Chenyang Lu Brian M. Blum Tarek F. Abdelzaher John A. Stankovic Tian He Department of Computer Science University of Virginia Charlottesville, VA 22903

[6] TU Wien Real time communication

[7] Introduction to Real time communication and embedded system University of Glassglow

[8] Ashok Agrawala Ardas Cilingiroglu,Sung Lee.Real Time Communication.University of Maryland Institute for Advanced Computer Studies

[9] Internet chat quick tour:real time conversation &communication online by Donald Rose

[10] An architecture for real-time multimedia communication systems by Cosmos Nicolaou University of Cambridge. Computer Laboratory

Seismic Gabor Deconvolution And The Color Correction To White-Reflectivity Assumption

Authors: M.S Saravanan, Dr Hesham Abu Haleemah, P. K Kumaresan

Abstract— Deconvolution is an essential part of seismic data processing. The deconvolution algorithm is derived from the corresponding convolution model. Conventional deconvolution methods are developed based on the stationary convolution model, such as Wiener spiking deconvolution. However, the seismic trace is nonstationary due to attenuation during the propagation for various reasons such as attenuation and geometric spreading. Deconvolution algorithms usually assume that the reflectivity is a random series, meaning that reflectivity has a white amplitude spectrum. In practice, the reflectivity is colored, i.e., the magnitude of its Fourier amplitude spectrum demonstrates obvious frequency dependency. The white reflectivity assumption can lead to distortion of reflectivity estimation. The nonstationary characteristic of both seismic trace and true reflectivity can be corrected in a nonstationary way. This chapter gives a basic introduction to Gabor deconvolution, and presents the color correction method to white-reflectivity assumption for Gabor deconvolution. The influence of the time-variant reflectivity color is analyzed in detail, and synthetic data and field data are used to evaluate the color correction method.

Keywords— Dconvolution, Gabor, seismic trace.

References-

[1 ] Aki, K., and Richard, P. G., 1980, Quantitative Seismology, W. H. Freeman and Co.,San Fransisco.

[2 ] Banik .N. C., Lerche, I., and Shuey, R. T., 1985, Stratigraphic filtering, Part 1: Derivation of the O’Doherty- Anstey formula: Geophysics, 50: 2768 – 2774.

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[5 ] Cheng, P., and Margrave, G. F., 2011c, Color correction for Gabor deconvolution: a test with field data: 2011 CSPG CSEG CWLS convention, abstract.

[6 ] Christensen, R. M., 1982, Theory of viscoelasticity – An introduction: Academic Press, Inc. Clark, G. K. C., 1968, Timevarying deconvolution filters: Geophysics, 33, 936-944.

[7 ] Dasgupta, R., and Clark, R. A., 1998, Estimation of from surface seismic reflection data: Geophysics, 63, 2120-2128.

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[9 ] Frazer, L. N., 1978, Synthesis of shear-coupled PL: Ph.D thesis, Princeton University.

[10 ] Frazer, L. N., and Gettrust, J. F., 1984, On a generalization of Filon’s method and the computation of oscillatory integrals of seismology: Geophys. J. Roy. Astr. Soc., 72, 193-211.

[11 ] Griffiths, L. J., F. R. Smolka, and L. D. Trembly, 1977, Adaptive deconvolution: A new technique for processing time-varying seismic data: Geophysics, 42, 742-759.

[12 ] Hackert, C. L., and Parra, J. O., 2004, Improving estimates from seismic reflection data using well-log-based localized spectral correction: Geophysics, 69, 1521-1529.

[13 ] Kennett, B. L. N., 1975, the effect of attenuation on seismograms: Bull. Seis. Soc. of Am., 43, 17-34.

[14 ] Margrave, G. F., M. P. Lamoureux, and D. C. Henley, 2011, Gabor deconvolution: Estimating reflectivity by nonstationary deconvolution of seismic data: Geophysics, 76, W15- W30.

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Ontology for Demining using Multi-Agent Programming-The Robotic Path Provider

Author: G.Sindhu

Abstract– Ontology is the process of automatic analysing by demining technique and looking for occurrences of a particular class of object or event and for relationship among software that perceives its environment through its sensors, and acts upon an environment with effectors. The Internet presents a huge amount of useful information which is usually formatted for its users, which makes it difficult to extract relevant data from various sources. Although many approaches for data extraction from Web pages have been developed, there has been limited effort to compare such tools. Unfortunately, in only a few cases can the results generated by distinct tools be directly compared since the addressed extraction tasks are different. Our project explains the robust, flexible Demining systems that automatically provides a way to reach particular destination from source through emitting U-V radiation and events. The Contribution of the project are : provide appropriate to way to reach particular destination in the building. In this paper we propose a non-humanoid robot for modelling agent organization and illustrate an operation for reaching desired destination.

Keywords–Ontology, Sensors, Demining, Non-Humaniod.

References-

[1] M. R. Adler, A. B. Davis, R. Weihmayer, and R. W. Worrest, “Conflict resolution strategies for non-hierarchical distributed agents,”In L. Gasser and M. Huhns, editors, Distributed Artificial Intelligence Volume II, pp 139–162,1989.

[2] J. R. Galliers, “A Theoretical Framework for Computer Models of Cooperative Dialogue,” Acknowledging Multi-Agent Conflict. PhD thesis, Open University, UK, 1988.

[3] Hsu, C.-N. and Dung, M, “Generating finite-state transducers for semi-structured data extraction from the web,” Journal of Information Systems 23(8): 521-538, 1998.

[4] C. Cheong and M.Winikoff. Hermes, “Designing goal-oriented agent interactions,”In Proceedings of the 6th International Workshop on Agent-Oriented Software Engineering (AOSE2005), July 2005.

[5] S. Kumar, M.J. Huber and P.R.Cohen, “Representing and Executing protocols as joint actions,” In Proceedings of the First International Joint Conference on Autonomous Agents and MultiAgent Systems, pages 543–550, Bologna, Italy, 15–19 July 2002.

[6] R.H.Bordini, M.Dastani, J.Dix and A.E.F.Seghrouchni, “MultiAgent Programming: Languages,Platforms and Applications,” Springer, 2005.

[7] S. Handschuh, S. Staab, and F. Ciravegna. 2002. “S-CREAM - Semi-automatic Creation of Metadata,”.In Proceedings of the 13th International Conferenceon Knowledge Engineering and Knowledge Management, EKAW02. Springer Verlag.

[8] Knoblock, A. et al., ed., 1998.Proc. 1998 Workshop on AI and Information Inte-gration, Menlo Park, California.: AAAI Press.Sim~oes, G., Galhardas, H., &Coheur, L. (2009). “Information extraction tasks: a survey,” (INESC ID technical report No. 37/2009). Lisbon, Portugal.

[9] B. Pollak and W. Gatterbauer. “Creating permanent test sets of web pages for information extraction research,” In Proceedings of 33rdSOFSEM: Theory and Practice of Computer Science, vol. II,pp. 103-115, Jan. 2007