Archive for: Volume 4

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Abstract: This paper introduces the concept of fuzzy dominance matrix (FDM) for solving multiple attribute decision making (MADM) problems. During decision making process, dominance of one expert over others plays an important role to find out the optimal alternative(s). In uncertain decision making problems, often dominances are expressed using linguistic variables which can be represented by fuzzy dominance degree. We have proposed an algorithmic approach to solve multiple attribute decision making problems using FDM. Finally the proposed algorithm is illustrated using a numerical example.

Keywords: Fuzzy Set, Fuzzy Dominance Matrix, Fuzzy Decision Matrix, Multiple Attribute Decision Making.

References:

1. R. Harris, “Introduction to Decision Making,” VirtualSal, http:// www.virtualsalt.com/crebook5.htm, accessed December 30, 2013.
2. F. Herrera, S. Alonso, F. Chiclana, and E. Herrera-Viedma, “Computing with words in decision making: foundations, trends and prospects,” Fuzzy Optimization and Decision Making, vol. 8, no. 4, pp. 337–364, 2009.
3. W. Pedrycz, P. Ekel, and R. Parreiras, “Fuzzy Multicriteria Decision-Making: Models, Methods and Applications,” John Wiley and Sons, Chicester, 2011.
4. J. Liu, L. Martinez, H. Wang, R.M. Rodriquez, and V. Novozhilov, “Computing with words in risk assessment,” International Journal of Computational Intelligence Systems, vol. 3, no. 4, pp. 396–419, 2010.
5. R. R. Yager, “Aggregation of ordinal information,” Fuzzy Optimization and Decision Making, vol. 6, no. 3, pp. 199–219, 2007.
6. Y. H. Chen, T. C. Wang, and C.Y. Wu, “Multi-criteria decision making with fuzzy linguistic preference relations,” Applied Mathematical Modelling, vol. 35, no. 3, pp. 1322–1330, 2011.
7. M. Roubens, “Fuzzy sets and decision analysis,” Fuzzy Sets and Systems, vol. 90, no. 2, pp. 199–206, 1997.
8. F. Herrera and E. Herrera-Viedma, “Linguistic decision analysis: steps for solving decision problems under linguistic information,” Fuzzy Sets and Systems, vol. 115, no. 1, pp. 67–82, 2000.
9. F. Herrera, E. Herrera-Viedma, and F. Chiclana, “Multiperson decision-making based on multiplicative preference relations,” European Journal of Operational Research, vol. 129, no. 2, pp. 372–385, 2001.
10. S. Das, M. B. Kar, and S. Kar, “Group Multi Criteria Decision Making using Intuitionistic Multi Fuzzy Sets,” Journal of Uncertainty Analysis and Applications, 1:10, Springer, 2013, doi:10.1186/2195-5468-1-10.
11. S. Das, S. Karmakar, T. Pal, and S. Kar, “Decision Making with Geometric Aggregation Operators based on Intuitionistic Fuzzy Sets,” in Proc. of 2nd International Conference of Business and Information Management (ICBIM 2014), Durgapur, January 9-11, 2014, (in press).
12. S. Das and S. Kar, “The Hesitant Fuzzy Soft Set and its Application in Decision Making,” in Proc. of International Conference on Facets of Uncertainties and Applications (ICFUA 2013), Kolkata, December 7-9, 2013, (in press).
13. S. Das and S. Kar, “Intuitionistic Multi Fuzzy Soft Set and its Application in Decision Making,” Fifth International Conference on Pattern Recognition and Machine Intelligence (PReMI), Kolkata, December 10-14, 2013, P. Maji et al. (Eds.): Lecture Notes in Computer Science (LNCS), 8251, Springer, pp. 587–592.
14. Z. Xu, “Group decision making based on multiple types of linguistic preference relations,” Information Sciences, vol. 178, no. 2, pp. 452–467, 2008.
15. R. R. Yager, “On ordered weighted averaging aggregation operators in multicriteria decision making,” IEEE Transactions on Systems, Man and Cybernetics, vol. 18, no. 1, pp. 183–190, 1988.
16. L. A. Zadeh, “Fuzzy sets,” Information and Control, vol. 8, pp. 338-353, 1965.
17. K. Atanassov, “Intuitionistic Fuzzy Sets,” Springer Physica-Verlag, Heidelberg, 1999.
18. K. Atanassov, “Intuitionistic fuzzy sets,” Fuzzy Sets and Systems, vol. 20, pp. 87- 96, 1986

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Abstract: Image segmentation is one of the most important categories of image processing. The purpose of image segmentation is to divide an original image into homogeneous regions. It can be applied as a pre-processing stage for other image processing methods. There exist several approaches for image segmentation methods for image processing. The watersheds transformation is studied in this report as a particular method of a region-based approach to the segmentation of an image. First, the basic tool, the watershed transform is defined. It has been shown that it can be implemented by applying flooding process on grey tone image. This flooding process can be performed by using basic morphological operations. The complete transformation incorporates a pre-processing and post-processing stage that deals with embedded problems such as edge ambiguity and the output of a large number of regions. Watershed Transform can be applied to gray scale images, textural images and binary images. The watershed transform has been widely used in many fields of image processing, including medical image segmentation.

Keywords: Flooding, Gradiant, Segmentation, Watershed Transform,.

References:
1. Rafael C. Gonzalez and Richard E. Woods, Digital Image Processing, Prentice-Hall, 2002, pp. 617-620.
2. Jackway PT. “Gradient watersheds in morphological scale space”,1999, IEEE Trans Image Proc 5:913-21
3. Jia Wang, Hanqing Lu, Gerard Eude, Qingshan Liu, “A Fast Region Merging Algorithm For Watershed Segmentation”,2004,pp.781-784.
4. Qing Chen, Xiaoli Yang, Emil M. Petri. “Watershed Segmentation for Binary Images with Different Distance Transforms”,2006, pp.111-116
5. Nagaraja Rao, Dr. V. Vijay Kumar, C. Nagaraju. “A New Segmentation Method Using Watersheds on grey level images”,2006, pp.275-278.
6. Marco A.G. de Carvalho a, Roberto de A. Lotufo a, Michel Couprie b. “Morphological segmentation of yeast by image analysis” ,Image and Vision Computing ,vol.25,2007,pp. 34–39.
7. N. Lu, X. Z. Ke “A Segmentation Method Based on Gray-Scale Morphological Filter and Watershed Algorithm for Touching Objects Image”, Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007).
8. H.P. Ng, S. Huang, S.H. Ong, K.W.C. Foong, P.S. Goh, W.L. Nowinski, “Medical Image Segmentation Using Watershed Segmentation with Texture-Based Region Merging”, 2008,pp. 4039-4042
9. Yurong Ge,Wen jhang,Guangrog ji.2009 “ Adaptive Algae Image Segmentation Based on Morphological Watersheds”, IEEE ,2009.
10. Chen Wei-bin, Zhang Xin, “A New Watershed Algorithm for Cellular Image Segmentation based on Mathematical Morphology”, IEEE:International Conference on Machine Vision and Human-machine Interface,2010.
11. Ms. S.Malathi , Ms. S.Uma

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Abstract: The steps of process of generated PWM are implemented by using a microcontroller 89c51 and using personal computer (PC). In this project the unipolar modulation technique is presented to overcome many problems. The generated pulses are fed to six pulses at bridge inverter consist of six (MOSFET) transistors. The fundamental operation of PWM is depending upon mathematical relationships between the voltage and the frequency (V/ F) constant value, this relationship gives low harmonics that takes place the modulation process. The control signal of PWM inverters is generated by comparing a reference sinusoidal waveform and triangular waveform of modulating signal. The dc link is constant value, and modulation index is variable according to the varying output voltage of the inverter.

Keywords: PC, MOSFET, V/F.PWM

References:

[1] C.W. Lander “Power Electronic”, ten editions. London: McGraw Hillbook Company, 20012.
[2] G.K. Dubey, “Power Semiconductor Controlled Drives”, nine editions USA. Prentice Hall, International Inc.2011.
[3] A. Zucckerbeger and A. Alexandrovitz, “Dertermination of Commutation Sequence With a View to Eliminating Harmonics in Microprocessor Controlled PWM Voltage Inverter”, IEEE.Trans. Ind. Electron .Vol. IECI 28, No.4, NOV. 20011.
[4] Bowes, S.R., and Midoum, A., “Suboptimal Switching Strategies For Microprocessor Controlled PWM Inverter Drives”, IEEE Proc., Electric power application, Vol. 132, pt. B, No. 3, May 2011, P.P. 133-148.2011.
[5] J.E. Gilliam, J.A. Hould Worth, L. Hadley, “Variable Speed Induction Motor With Integral PWM Inverter”. IEEE Conference APEC, 2011, P.P 92-100.
[6] J.A. Houlds worth, W.B. Rosink, “Introduction to PWM speed control system for three phase ac motor”, Electronic components and applications, Vol. 2, No. 2, 2010.
[7] Intel corporation, “Microcontroller Handbook”, 2010.
[8] You Lee and Y. Yith Sun, “Adaptive Harmonic Control in PWM Inverter With Fluctuating Input Voltage”, IEEE. Trans. Ind Electron, Vol. IE-33 No. 1, FEB, 2010.

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Abstract: Oceanographers need to study, analyse and interpret the biological and physical characteristics of marine organisms in the waterbed and sea floor. Images and Videos are important source of information and aids for their study. However, there are unique set of constraints in underwater environment that have limited our ability to process underwater images. Some of the important constraints in underwater images are associated with the physics of the light and attenuation of the electromagnetic spectrum. Processing issues also need to be dealt for the required application. Some of the research issues underwater have been the tasks associated with reconstructing three-dimensional information about the world from its two-dimensional Projections. In this paper the techniques of underwater video processing for detecting and tracking moving objects are discussed, analysed and compared.

Keywords: Video Processing, Detection, Tracking, Affine Transformation, Feature Extracion

References:

[1] SamanPoursoltan, Russell Brinkworth, Matthew Sorell “Biologically-inspired Video Enhancement Method For Robust Shape Recognition,” University of Adelaide, Australia, IEEE, 2013.
[2] Prabhakar C J & Praveen Kumar P U. “Feature Tracking of Objects in Underwater VideoSequences.”, Kuvempu University, India, ACEEE 2012.
[3] SaeedVahabiMashak, BehnamHosseini, S.A.R. Abu-Bakar.“Background Subtraction for Object Detection under Varying Environments.”UniversitiTeknologi Malaysia, IJCISIMA, 2012
[4] M. Weber, M. Welling, and P. Perona. “Detecting ,Tracking And Counting Fish In Low Quality Unconstrained Underwater Videos” University of Edinburgh, Edinburgh, UK.
[5] “Underwater ColorConstancy :Enhancement of Automatic Live Fish Recognition” M. Chambah, D. Semani, A. Renouf, P. Courtellemont, A. Rizzi, Université de La Rochelle, France, Dept. of Information Technology – University of Milano/Italy
[6] CodrutaOrnianaAncuti, CosminAncuti, Tom Haber and Philippe Bekaert “FUSION-BASED RESTORATION OF THE UNDERWATER IMAGES,” Belgium, IEEE, 2011.
[7] MohamedAmer, Emil Bilgazyev “Fine-grained Categorization of Fish Motion Patterns in Underwater Videos”, Oregon State University, ICCV, 2011
[8] PiotrJasiobedzki, Stephen Se, Michel Bondy, and Roy Jakola,“Underwater 3D mapping and pose estimation for ROVoperations”, OCEANS 2008, pp. 1-6, September 2008.
[7] Li Ma, KaihuaWu,L. Zhu, “Fire smoke detection in videoimages Using Kalman filter and Gaussian Mixture Colormodel”, International Conference on Artificial Intelligence andComputational Intelligence, 2010
[8] Li Xu, Feihu Qi, Renjie Jiang, YunfengHao, Guorong Wu,“Shadow Detection and Removal in Real Images: A Survey”Shanghai JiaoTong University, P.R. China, June 2006.
[9] J Shin, S Kim, et all, “Optical flow-based real-time object tracking using non-prior training active feature model”Computer Vision and Image Understanding, June 2005,Volume 98, Issue 3, Pages 462-490.
[10] B.Hosseini, SaeedVahabiMashak and A.S.R Abu Bakar,”Human Movement Based on Rule based classifier” Asia Modelling Symposium, May 2010.
[11] [14] S.S. Beauchemin and J.L. Barron, “The Computation of Optical Flow”, ACM Computing Surveys, 1995 Vol. 27,No.3, PP 43-467.
[12] S.Y. Chien, S.Y. Ma and L.G. Chen ,” Efficient moving objectsegmentation algorithm using background registrationtechnique” IEEE Trans Circuits Syst. Video Technol, JULY2002
[13] Hu Fuyuan, Zhang Yanning, et all, “A New Method of MovingObject Detection and Shadow Removal” JOURNAL OFELECTRONICS (CHINA), July 2007
[14] Dongxiang Zhou, Hong Zhang and NilanjanRay,“TextureBased Background Subtraction”, Proceedings of theInternational Conference on Information and Automation,Zhangjiajie China, IEEE Conference, June 20 -23, 2008.
[15] YunlongGuo, Bo Yang, Yangyang Ming, Aidong Men, “AnEffective Background Subtraction Under the Mixture ofMultiple Varying Illuminations”,Second InternationalConference on Computer Modeling and Simulation, IEEEConference, 2010.
[16] V. Brandou, A. G. Allais, M. Perrier, E. Malis, P. Rives, J.Sarrazin, and P. M. Sarradin, “3D Reconstruction of NaturalUnderwater Scenes Using the Stereovision System IRIS”, OCEANS 2007 – Europe , pp. 1-6, 2007.
[17] David G Lowe, “Distinctive image features from scale-invariantkeypoints”, International Journal of Computer Vision, vol. 60(2),pp. 91-110, 2004.
[18] David G Lowe, “Object recognition from local scale-invariantfeatures”, Proceedings of the International Conference on ComputerVision, vol. 2, pp. 1150-1157

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Abstract: The advent and wide adoption of cloud computing has brought a new revolution in the field of IT. As consumers using cloud for data storage either in the SaaS, PaaS or IaaS deployment model are increasing-they realize the necessity of file compression. It becomes imperative to understand the scenarios where transition to the Cloud is beneficial. In our research, we have demonstrated that for small businesses – making a move to the cloud is not a good approach as less demanding applications can run well even on stand-alone machines, however as the data size grows – making a move towards cloud can yield higher availability. In this paper we evaluate and compare the performances of virtual machines running in cloud with stand-alone (unvirtualized) machine.

Keywords: Cloud computing, Amazon EC2, File Compression, Performance Analysis

References:

[1] Amazon Web Services (2011). Eucalyptus open-source cloud computing infrastructure -an overview. technical report, eucalyptus, inc.
[2] Chee, B. and Franklin Jr, C. (2009). Cloud computing: technologies and strategies of the ubiquitous data center. CRC.
[3] Chorafas, D. and Francis, T. . (2011). Cloud computing strategies. CRC Press. D, J. and Murari, K. and Raju, M. and RB, S. and Girikumar, Y. (2010). Eucalyptus Beginner’s Guide – UEC Edition.
[4] Ghoshal, D., Canon, R., and Ramakrishnan, L. Understanding i/o performance of virtualized cloud environments. Godard, S. (2004). Sysstat:System performance tools for the Linux OS.
[5] He, Q., Li, Z., and Zhang, X. (2010). Study on cloud storage system based on distributed storage systems. In Computational and Information Sciences (ICCIS), 2010 International Conference on, pages 1332–1335. IEEE.
[6] Hovestadt, M., Kao, O., Kliem, A., and Warneke, D. (2011). Evaluating adaptive compression to mitigate the effects of shared i/o in clouds. In Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW), 2011 IEEE International Symposium on, pages 1042–1051. IEEE.
[7] Hugos, M. and Hulitzky, D. (2010). Business in the Cloud: What Every Business Needs to Know About Cloud Computing. Wiley.
[8] Iosup, A., Ostermann, S., Yigitbasi, N., Prodan, R., Fahringer, T., and Epema, D. (2010).
[9] Performance Analysis of Cloud Computing Services for Many-Tasks Scientific Computing. IEEE Transactions on Parallel and Distributed Systems, pages 1–16.
[10] Krintz, C. and Calder, B. (2001). Reducing delay with dynamic selection of compression formats. In High Performance Distributed Computing, 2001. Proceedings. 10th IEEE International Symposium on, pages 266–277. IEEE.
[11] Lilja, D.J. (2005). Measuring computer performance: a practitioner’s guide. CambridgeUniv Pr.
[12] Miyamoto, T., Hayashi, M., and Tanaka, H. (2009). Customizing network functions for high performance cloud computing. In Network Computing and Applications, 2009. NCA 2009. Eighth IEEE International Symposium on, pages 130–133. IEEE.
[13] Nurmi, D., Wolski, R., Grzegorczyk, C., Obertelli, G., Soman, S., Youseff, L., and Zagorodnov, D. (2009). The eucalyptus open-source cloud-computing system. In Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid, pages 124–131. IEEE Computer Society.
[14] Ostermann, S., Iosup, A., Yigitbasi, N., Prodan, R., Fahringer, T., and Epema, D. (2010).A Performance Analysis of EC2 Cloud Computing Services for Scientific Computing, pages 115–131.
[15] Ozsoy, A. and Swany, M. (2011). Culzss: Lzss lossless data compression on cuda. In Cluster Computing (CLUSTER), 2011 IEEE International Conference on, pages 403–411. IEEE.

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Abstract: In today’s world most of the communication is done using electronic media. Data Security is widely used to ensure security in communication, data storage and transmission. Security of multimedia data is an imperative issue because of fast evolution of digital data uses the permutation step, taking from Data Encryption Standard (DES) algorithm. Theoretical analysis and experimental results prove that this technique provides high speed as well as fewer exchanges or transfer over unsecured network. Multimedia data security is achieved by methods of cryptography, which deals with encryption of data. Standard symmetric encryption algorithms provide better security for the multimedia data. But applying symmetric key encryption algorithm on more complex multimedia data (mostly images); we might face the problem of computational overhead. To overcome that problem, we analyze the Advanced Encryption Standard (AES) and modify it, to reduce the calculation of algorithm and for improving the encryption performance. In modified AES algorithm instead of using Mixcolumne overheads on data. Modified-AES algorithm is a fast lightweight encryption algorithm for security of multimedia data. All above advantages make algorithm highly suitable for the images and plaintext transfer as well , than the AES algorithm.

Keywords: Advanced Encryption Standard (AES), Cryptography, DES, and Symmetric Key Algorithms.

References:

[1] Shtewi, A.M.”An Efficient Modified Advanced Encryption Standard (MAES) adapted for image cryptosystems” IJCSNS International Journal of Computer Science and Network Security, VOL.10 No.2,
[2] ShashiMehrotra Seth, 2Rajan Mishra,” Comparative Analysis Of Encryption Algorithms For Data Communication”, IJCST Vol. 2, Issue 2, June 2011 pp.192-192.
[3] Gurjeevan Singh, Ashwani Kumar Singla,K.S. Sandha, ”Through Put Analysis Of Various Encryption Algorithms”, IJCST Vol. 2, Issue 3.
[4] Behrouzan A. Forouzan (2010), Cryptography & Network Security, TMH Publisher, ISBN: 9780070660465.
[5] Bruce Schneier (2009), Applied Cryptography, John Wiley & Sons Publisher, ISBN:9780471117094

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Abstract: Depletion of nonrenewable source of energy (fossil fuels like petroleum, coal and natural gas) many researchers are looking forward to find an alternative source of renewable energy. One such alternative to diesel fuel is biodiesel. Biodiesel can be defined as fuel comprising of mono alkyl ester of long chain of fatty acid derived from vegetable oil or animal fat. So, there is an increasing interest in India to search for suitable alternative fuels that are environmental friendly. Environmental concerns and limited amount of petroleum resources have caused interests in the development of alternative fuels for internal combustion (I.C.) engines. As an alternative, biodegradable, renewable and sulphur free biodiesel is receiving increasing attention. The use of biodiesel is rapidly expanding around the world, making it imperative to fully understand the impacts of biodiesel on the diesel engine combustion process and pollutant formation. Therefore, in this study, the performance test of a variable compression diesel engine with neat diesel fuel and biodiesel mixtures was carried out. Experiments are carried out by using dual biodiesel blends and compared it with diesel fuel characteristics. The literatures were focused on single biodiesel and its blends. So far a very few dual biodiesel blends of oils have been tried on diesel engine leaving a lot of scope in this area. This paper investigated the performance and emission characteristics of various dual biodiesel blends (mixture of biodiesel and diesel fuel) of Thumba biodiesel on a single cylinder variable compression ratio diesel engine having bore diameter 87.50mm, developed power 3.5kw at 1500rpm, compression ratios 12 to 18, stroke length 110mm, water cooled engine. The biodiesel blends of B10% (combination of Diesel 90% by volume, biodiesel 10% by volume ) and B20% (combination of Diesel 80% by volume, biodiesel 20% by volume) gave better brake thermal efficiency and lower brake specific fuel consumption than other biodiesel blends. The blends of B10% and B20% have superior emission characteristics than other blends and closer to diesel values. From the experimental results obtained, Thumba oil blends are found to be a promising alternative fuel for compression ignition engines. At CR 18 BTE and BSFC of Thumba B10, B20 and BP of Thumba B40 showed better performance.CO, HC, CO2 of B100 of Thumba biodiesel showed less emission percentage/ppm, for NOx emission B10 and B20 of Thumba, biodiesel showed less emission ppm.

Keywords: Biodiesel, Blends, Thumba Biodiesel, Engine performance, Emission Characteristics

References:

1. K. Pramanik. “Properties and use of Jatropha curcas oil and diesel fuel blends in C.I engines”, Journal of Renewable Energy, 239-248, (2003).
2. F.K.Forson, E.K Oduro, E.Hammond-Donkoh, “Performance of jatropha oil blends in a diesel engine”, Journal of Renewable Energy, 1135-1145, (2004).
3. J.Narayana Reddy, A. Ramesh “Parametric studies for improving the performance of Jatropha oil-fuelled compression ignition engine”, Journal of Renewable Energy, 1994-2016, (2006).
4. H.Reheman, S.V.Ghadge “Performance of diesel engine with biodiesel at varying compression ratio and ignition timing”, Fuel, Volume 87, Issue 12, 2659-2666, (2008).
5. Jehad A. A. Yamin, Nina Sakhnin, Ahmed Sakhrieh, M Hamdan “Performance of C.I. engines using biodiesel as fuel”, GCREEDER 2009, Amman‐Jordan, (2009)
6. GVNSR Ratnakara Rao, V. Ramachandra Raju and M. Muralidhara Rao “Optimising the compression ratio of diesel fuelled CI engine”, ARPN Journal of Engineering and Applied Sciences, APRIL 2008
7. Indraj Singh and Vikas Rastogi “Performance Analysis of a Modified 4- Stroke Engine Using Biodiesel Fuel for Irrigation Purpose”, International Journal of Applied Environmental Sciences (2009), 229–242.
8. Amit Pal, S S Kacggwaha, S. Maji and M K G Bahu, “Thumba (Citrullus Colocyntis) seed oil: A sustainable source of renewable energy for biodiesel production “Journal of scientific and industrial research” , Vol 69, May 2010.
9. T. Elango1, T. Senthil kumar “Performance and emission characteristics of CI engine fuelled with non edible vegetable oil and diesel blends”, Journal of Engineering Science and Technology, Vol. 6, No. 2 , 240 – 250, (2011) .
10. A.M. Liaquat, M.A. Kalam, H.H. Masjuki, M.H. Jayed “Engine Performance and Emissions Analysis using “Envo Diesel” and Coconut Biodiesel Blended Fuel as Alternative Fuels”, 2nd International Conference on Environmental Science and Technology, Vol.6, 2011.
11. Shiv Lal, V. K. Gorana1, N. L. Panwar “A Comparative Study of Thumba Seed Bio Diesel”, Journal of Environmental Protection, Vol 2, 454-459, 2011.
12. K. Kalyani Radha, S. Naga Sarada, K. Rajagopal and E.L. Nagesh“Performance and emission characteristics of CI engine operated on vegetable oils as alternate fuels”, International Journal of Automotive and Mechanical Engineering (IJAME), Vol 4, 414-427, July-December 2011.
13. H. M. Dharmadhikari1, Puli Ravi kumar ,S. Srinivasa Rao “Performance and emissions of CI engine using blends of biodiesel and diesel at different injection pressures”,International Journal of Applied Research in Mechanical Engineering (IJARME), Vol 2, Issue 2, 2012.
14. Suvendu Mohanty, Dr. Om prakash “Analysis Of Exhaust Emission Of Internal Combustion Engine Using Biodiesel Blend”,International Journal of Emerging Technology and Advanced Engineering, Volume 3, Issue 5, May 2013.
15. Sivaramakrishnan Kaliamoorthy, and Ravikumar Paramasivam“ Investigation on performance and emissions of a biodiesel engine through optimization techniques”, Vol 17, No 1, 179-193, 2013.
16. Mekalilie Benjamin Bol, T. K. Bhattacharya and H. I. Mohammed “Studies on compatible fuel properties of soybean ethyl ester and its blends with diesel for fuel use in compression ignition engines”.

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Paper Title:

Abstract: India is one of the leading countries in the word for technical education and management education. A study shows that in India e-education is growing with a massive growth. The students find relevant information from various e-education web sites. Numbers of pages are indexed on www and finding the desired information is not an easy task. For solving this problem we need an approach which helps in finding precise solution as per students need. In this paper we also use Web log analysis via neural network structure. We are using a neural approach with fuzzy clustering that shows the analysis of web logs, depends on the performance of the clustering the number of requests. Clustered data is used to analyze with neural approach for effective web site modification and behavior analysis. The proposed model use neural network approach with a firing rule to discover and analyze useful knowledge from the available Web log data.

Keywords: A study shows that in India e-education is growing with a massive growth.

References:

[1] Ajith Abraham, “Business Intelligence from Web Usage Mining” Journal of Information & Knowledge Management, Vol. 2, No. 4 (2003) 375-390.
[2] Jos´e Borges, Mark Levene “An Average Linear Time Algorithm for Web Usage Mining” Sept 2003.
[3] Kumar Harish, Solanki A.K “Adaptive Markov Chain For Next Page Access Prediction” Vol. 9 No. 7 JUL 2011 Aug 25, 2011 by IJCSIS .
[4] Renáta Iváncsy, and Sándor Juhász, “Analysis of Web User Identification Methods” International Journal of Electrical and Computer Engineering 2:3 2007.
[5] . Suresh ,Madana ,A.RamaMohan Reddy, “Improved FCM algorithm for Clustering on Web Usage Mining” K IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 1, January 2011 ISSN (Online): 1694-0814
[6] Soumi Ghosh ,Sanjay Kumar Dubey “Comparative Analysis of K-Means and Fuzzy C-Means Algorithms” , International Journal of Advanced Computer Science and Applications, Vol. 4, No.4, 2013
[7] V Chitra, Dr. Antony “An Enhanced Clustering Technique for Web Usage Mining” ,International Journal of Engineering Research & Technology (IJERT) Vol. 1 Issue 4, June – 2012
[8] Michal Munka, Martin `Drlíka Procedia “Impact of Different Pre-Processing Tasks on Effective Identification of Users’ Behavioral Patterns in Web-based Educational System” Computer Science 4 (2011) 1640–1649 International Conference on Computational Science, ICCS 2011.
[9] Marquardt, Becker and D. Ruiz “A Pre-Processing Tool forWeb Usage Mining in the Distance Education Domain” . In Proceedings of the International Database Engineering and Applications, IDEAS 2004, pp. 78-87.
[10] Wang X., Abraham A. and Smith K.A.,, “Web Traffic Mining Using a Concurrent Neuro-Fuzzy Approach” In Proceedings Second International Conference on Hybrid Intelligent Systems, Chile, IOS Press Amsterdam, The Netherlands, 2002.
[11] Olfa Nasraoui and Christopher Petene. “Combining Web Usage Mining and Fuzzy Inference for Website Personalization”
[12] ”Harish Kumar, Dr. Anil Kumar Solanki “Effective Cleaning of Educational website usage patterns and predicting their next visit,International journal of computer applications Volume 53 Nov 12.
[13] Archana N Boob “ Fuzzy Clustering: An Approach for Mining Usage Profiles from Web” International Journal of Computer Technology & Applications, Vol 3 (1),329-331.
[14] Jaykumar, Kamlesh Patel, “A survey on web usage mining with neural network and proposed solutions on several issues” journal of information, knowledge and research in computer engineering, ISSN: 0975 – 6760 nov 12 to oct 13 volume – 02, issue – 02 page 330.
[15] Valishali A. Zilpe, Dr. Mohammad Atique “Neural network apprach for web usage mining”, ,ETCSIT, published in IJCA [2011]

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Paper Title:

Abstract: Quadrature amplitude modulation (QAM) has been widely used in adaptive modulation because of its efficiency in power and bandwidth while Pulse Amplitude Modulation (PAM) used for high rate data link where transmitting more bits is a symbol time, QAM and PAM systems are both tested under AWGN, Rayleigh fading, Rician Fading channels as comparison performance in term of BER between the two systems, to improve the performance of both systems convolutional code, diversity order and K-factor are used, where these techniques decrease the BER on both systems.

Keywords: QAM and PAM, fading channel, Convolutional AWGN channel, QAM in rician channel.

References:

[1] M.S. Richer et al,” The ATSC digital television system”, proc. IEEE, vol.94, pp.37-43, Jan, 2006.
[2] Cho, K., and Yoon, D., “On the general BER expression of one- and two-dimensional amplitude modulations”, IEEE Trans. Commun., vol. 50, no. 7, July 2002, pp. 1074-1080.
[3] Proakis, J. G., Digital Communications, 4th Ed., McGraw-Hill, 2001.
[4] Simon, M. K , Hinedi, S. M., and Lindsey, W. C., Digital Communication Techniques – Signal Design and Detection, Prentice-Hall, 1995.
[5] Simon, M. K., and Alouini, M. S., Digital Communication over Fading Channels – A Unified Approach to Performance Analysis, 1st Ed., Wiley, 2000
[6] Vo Nguyen Quoc Bao, Hyung Yun Kong, Seong Wook Hong, ‘Performance Analysis of M -PAM and M -QAM with Selection Combining in Independent but Non-Identically Distributed Rayleigh Fading Paths’, IEEE, 2008 .
[7] Daniel J. Ryan, ‘Blind Detection of PAM and QAM in Fading Channels’ , IEEE TRANSACTIONS ON INFORMATION THEORY, VOL. 52, NO. 3, MARCH 2006.

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Authors:

Paper Title:

Abstract: Scattering phenomenon due to foliage plays an important role in millimeter band as the wavelength approaches to the order of the size of the obstacles. It is important to estimate the propagation attenuation due to scattering when the arid zone foliage leaves and twigs size affect adversely in millimeter band signal propagation. A 35 GHz trans-receiver link system was used to measure the attenuation through trees due to scattering pattern of tree foliage of western rajasthan region. Measurements were made to study the angular variations of the positioning of receiver unit around the target foliage. The measurements, which were made for HH polarization configurations over a wide range of the azimuth angle, provide a quantitative reference for the design of high speed data communication links and use of millimeter-wave bistatic radar, point to point communication systems.

Keywords: A35 GHz, millimeter wave, 35 GHz, scattering, Foliage, Western Rajasthan

References:

[1]D.R.Godara,Dr.J.S.Purohit,SandeepRankawat,S.K.Modi “Effect of Foliage Length on Signal Attenuation in Millimeter Band at 35Ghz Frequency” IJCA ISSN: 0975-8887, Volume-84, DEC2013.
[2]D.R.Godara,Dr.J.S.Purohit,SandeepRankawat,S.K.Modi “Propagation Attenuation Due to Foliage at 35Ghz” IJECT ISSN: 2230-9543, Volume-4, Issue-4, OCT-DEC2013.
[3] D.R.Godara, S.K.Modi, Rupesh Kumar Rawat “Experimental studies on millimeter wave scattering from ground and vegetation at 35 GHz” IJSCE ISSN: 2231-2307, Volume-1, Issue-6, January2012.
[4] Akira Ishimaru, “Wave Propagation and Scattering in Random Media and Rough Surfaces”, Proceedings of the IEEE, Vol 79, No. 10, October 1991
[5] Hao Xu,Theodore S. Rappaport, Robert J. Boyle,James H. Schaffner, “Measurements and Models for 38-GHz Point-to-Multipoint Radiowave Propagation”,IEEE journal on selected areas in communications, Vol. 18, No. 3, March 2000
[6] Rogers, N. C., A. Seville, J. Richter, D. Ndzi, N. Savage,R. Caldeirinha, A. Shukla, M. O. AlNuaimi, K. H. Craig, E. Vi-lar, and J. Austin, “A generic model of 1-60 GHz radio propa-gation through vegetation” , Tech. Report, Radiocommunications Agency, May 2002.
[7] Wang, F. and K. Sarabandi, “An enhanced millimeter-wave foliage propagation model”, IEEE Trans. Antennas Propag., Vol. 53, No. 7, 2138-2145, 2005.
[8] “An Improved Propagation Model for Wireless Communications.”, Majeed, M. and, Tjuata, S. (1996). IEEE International Conference on Communications, Converging Technologies for Tomorrow’s Applications, Vol. 1, pp. 292-296, ICC 96.

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Paper Title:

Abstract: Mobile Adhoc Networks (MANETs) is a collection of mobile nodes. Due to globalization and revolution in communication technology, growth in the deployment of wireless and mobile communication networks have been noticed. Several challenges and issues are raised by researchers working in the field of Dynamic topology and infrastructure less MANETs. Such facility generates easy installation of Ad hoc networks and provides node stability without loss of connection. In such facility packet dropping is a serious challenge for quality performance of MANETs. Exhaustive literature survey reveals that MANETs generally suffer from security attacks such as black hole attack, wormhole attack and malicious attack due to the packet dropping problems. For the minimization attack and packet dropping researchers have provided the solutions like authentication, reputation based scheme, certification based scheme, passive feedback scheme, ack-based scheme etc. In certification based scheme, a problem of huge overhead due to extra authentication of packet is noticed. Also, the problem of issuing certificate and authentication of certificate at each node are the great challenge to be resolved. To resolve these challenges, Entropy based reference-broadcast synchronization (RBS) scheme is used in which nodes send reference beacons to their neighbors using physical-layer broadcasts. The characteristic entropy changes are used to construct a threshold based detector for fast worms. Proposed scheme is implemented in NS2 simulator and its result shows the effect of normal behavior and improvement of performance after application of this scheme. In this, 50 nodes are used for simulation process and performance is evaluated by packet delivery ratio and normalized load using ad-hoc on-demand multipath distance vector (AOMDV) as routing protocol. This entropy based scheme, successfully minimizes the communication cost by reducing the number of overhead packets, removes the node ambiguity in broadcast synchronization process and minimizes packet dropping also.

Keywords: AOMDV Protocol, Dynamic Topology, Mobile Ad-hoc Networks, Reference-broadcast Synchronization

References:

[1] Shuyao Yu, Youkun Zhang , Chuck Song and Kai Chen” A security architecture for Mobile Ad Hoc Networks” Proceedings of the II ACM Mobi HOC, 2001
[2] T. Fahad, D. Djenouri and R. Askwith. “On detecting Packets Droppers in MANET: a Novel Low Cost Approach”, Proceeding. III International Symposium on Information Assurance and Security, Manchester, UK August 2007.
[3] Tony Larsson, Nicolas Headman; A report on “Routing Protocols in Wireless Ad Hoc Networks: A Simulation Study”1998.
[4] M. Amitabh, “Security and quality of service in ad hoc wireless networks”, Cambridge University Press I edition, March 2008.
[5] T R Andel and A Yasinsac, “Surveying Security Analysis Techniques in MANET Routing Protocols”, IEEE Communication Surveys & Tutorials, 9,4 pp 70-84, Fourth Quarter 2007
[6] Mahesh K. Marina and Sameer . Das “Ad hoc on-demand multipath distance vector routing” wireless communications and mobile computing, 2006; 6:969–988
[7] E.A.Mary Anita, V.Thulasi Bai, E.L.Kiran Raj, B.Prabhu, “Defending against Worm Hole Attacks in Multicast Routing Protocols for Mobile Ad hoc Networks”, in proceeding of IEEE communication 2011
[8] Jeremy Elson, NLewis Girod and Deborah Estrin,” Fine-Grained Network Time Synchronization using Reference Broadcasts” in proceeding of IEEE communication 2011.
[9] Adel Saeed Alshamrani” PTT: Packet Travel Time Algorithm in Mobile Ad Hoc Networks”, in proceeding of IEEE 2011
[10] Satoshi Kurosawa, Hidehisa Nakayama, Nei Kato, Abbas Jamalipour, and Yoshiaki Nemoto, “Detecting Wormhole Attack on MAODV-based Mobile Ad Hoc Networks by Dynamic Learning Method.” in proceeding of IEEE 2011.
[11] Y. Zhang, W. Lou, W. Liu and Y. Fang, “A secure incentive protocol for mobile ad hoc networks”, Wireless Networks journal, 13(5): pp569-582, October 2007.
[12] Ning Song and Lijun Qian, Xiangfang L WINLAB “Wormhole Attacks Detection in Wireless Ad Hoc Networks: A Statistical Analysis Approach” Parallel and Distributed Processing Symposium, Proceedings, 19th IEEE International ,April 2005.
[13] Jaiswal R and Sharma S, “ Relative cluster entropy based wormhole detection using AOMDV in adhoc networks” Computational intelligence and communication networks (CICN) 2012 Proceeding of Fourth International conference, held at Mathura, Nov.2012, pp 747-752

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Authors:

Paper Title:

Abstract: This paper the authors mainly concern with the best order of the FIR filter using Boxcar windowing method. Simulation results give encouraging results regarding best order of the FIR Filters among the orders. A new method of implementation of best order of FIR Filter is proposed using MATLAB SIMULINK. Interesting results are obtained by comparing the different order filter’s cut-off frequency to the assumption fixed 1000 Hz using Boxcar window. This novel concept of finding of the best order of the FIR filter using different order in Boxcar windows method that has been verified through MATLAB simulation results.

Keywords: FIR, MATLAB SIMULINK, DSK5416 Kit, TMSC32054 hardware.

References:

1. J G Proakis and D M Malonakis, ‘Digital Signal Processing: Principles, Algorithms and Applications, Prentice Hall, Englewood Cliffs, NJ, 1996.
2. B Porat, ‘A Course in Digital Signal Processing’, John Wiley & Sons, 1997.
3. S K Mitra, ‘Digital Signal Processing: A Computer Science based Approach’, McGraw Hill Publications.
4. Oppenheim, Schfar and Buck, ‘Discrete Time Signal Processing’, Pearson Publication.
5. L. B. Jackson, J. F. Kaiser and H. S. McDonald, “An approach to the implementation of digital filters”, IEEE Trans. Audio Electroacoust., vol. AU-16, pp.413 -421 1968.
6. 6) C. M. Rader and B. Gold, “Digital filter design techniques in the frequency domain”, Proc. IEEE, vol. 55, pp.149 -171 1967.

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Authors:

Paper Title:

Abstract: In this paper we develop and analyze an inventory model assumption that deterioration rate follows Weibull two parameter distributions with selling price dependent demand. Here it is assumed that demand rate is a function of selling price. With shortage and without shortage both cases have been taken care of in developing the inventory models. Shortages are fully backlogged whenever they are allowed. Through numerical examples the results are illustrated. The sensitivity analysis for the model has been performed to study the effect changes of the values of the parameters associated with the model.

Keywords: EOQ model; deteriorating items; shortage; selling price dependent demand; Weibull distribution.

References:

[1] Aggarwal, S.P., “A note on an order-level inventory model for a system with constant rate of deterioration”, Opsearch, 15(1978), pp: 84-187.
[2] Burwell T.H., Dave D.S., Fitzpatrick K.E., Roy M.R., “ Economic lot size model for price-dependent demand under quantity and freight discounts”, International Journal of Production Economics, 48(2)(1997), pp: 141-155.
[3] Chakrabarti, et al, “An EOQ model for items Weibull distribution deterioration shortages and trended demand an extension of Philip’s model. Computers and Operations Research, 25(1997), pp: 649-657.
[4] Chakraborti, T., and Chaudhuri, K.S., “An EOQ model for deteriorating items with a linear trend in demand and shortages in all cycles”, International Journal of Production Economics, 49(1997), pp: 205-213.
[5] Chung, K., and Ting, P., “A heuristic for replenishment of deteriorating items with a linear trend in demand”, Journal of the Operational Research Society, 44(1993), pp: 1235-1241.
[6] Covert, R.P., and Philip, G.C., “An EOQ model for items with Weibull distribution deterioration.AIIE Transactions”, 5(1973), pp: 323-326.
[7] Dave, U., and Patel. L.K., “(T, S) policy inventory model for deteriorating items with time proportional demand”, Journal of the Operational Research Society. 32(1981),pp: 137-142.
[8] Deb, M., and Chaudhuri. K.S., “An EOQ model for items with finite rate of production and variable rate ofdeterioration”, Opsearch, 23(1986), pp:175-181.
[9] Fujiwara, O., “EOQ models for continuously deteriorating products using linear and exponential penalty costs”, European Journal of Operational Research, 70(1993), pp:104-14.
[10] Ghare, P.M., and Schrader, G.F., “An inventory model for exponentially deteriorating items”, Journal of Industrial Engineering, 14(1963), pp:238-243.
[11] Giri, B.C., and Chaudhuri, K.S., “Heuristic models for deteriorating items with shortages and time-varying demand and costs”, International Journal of Systems Science, 28(1997), pp:53-159.
[12] Goh, M., EOQ models with general demand and holding cost functions”, European Journal of Operational Research, 73(1994), pp:50-54.
[13] Hariga, M., “Optimal EOQ models for deteriorating items with time varying demand”, Journal of Operational Research Society, 47(1996),pp: 1228-1246.
[14] Hariga, M.A., and Benkherouf, L., “Optimal and heuristic inventory replenishment models for deteriorating items with exponential time-varying demand”, European Journal of Operational Research. 79(1994), pp: 123-137.
[15] Jalan, A.K., and Chaudhuri, K.S., “Structural properties of an inventory system with deterioration and trended demand”, International Journal of systems Science, 30(1999), pp: 627-633.
[16] Jalan, A.K., Giri, R.R., and Chaudhuri, K.S., “EOQ model for items with Weibull distribution deterioration shortages and trended demand”, International Journal of Systems Science. 27(1996),pp: 851-855.
[17] Mishra, R.B., “Optimum production lot-size model for a system with deteriorating inventory”, International Journal of Production Research, 3(1975), pp: 495-505.
[18] Mondal, B., Bhunia, A.K., Maiti, M., “An inventory system of ameliorating items for price dependent demand rate”, Computers and Industrial Engineering, 45(3)(2003), pp: 443-456.
[19] Muhlemann, A.P. and Valtis-Spanopoulos, N.P., “A variable holding cost rate EOQ model”, European Journal of Operational Research,4(1980), pp: 132-135.
[20] Shah, Y.K., and Jaiswal, M.C., “An order-level inventory model for a system with constant rate of deterioration”, Opsearch, 14(1977), pp:174-184.
[21] Su, C.T., et al, “An inventory model under inflation for stock-dependent consumption rate and exponential decay”, Opsearch, 33(1996), pp: 72-82.
[22] Van Der Veen, B., “Introduction to the Theory of Operational Research”, Philip Technical Library, Springer-Verlag, New York, 1967.
[23] Wee, H.M., “A deterministic lot-size inventory model for deteriorating items with shortages and a declining market”, Computers and Operations, 22(1995), pp: 345-356.
[24] Weiss, H.J., “Economic Order Quantity models with nonlinear holding cost”, European Journal of Operational Research, 9(1982), pp: 56-60.
[25] You, S.P., “Inventory policy for products with price and time-dependent demands”, Journal of the Operational Research Society, 56(2005), pp: 870-873.
[26] C. K. Tripathy., et al, ”An Inventory Model for Weibull Deteriorating Items with Price Dependent Demand and Time-Varying Holding Cost”, Applied Mathematical Sciences, 4(2010), pp: 2171 – 2179.
[27] Sushil Kumar., et al, “An EOQ Model for Weibull Deteriorating Items With Price Dependent Demand”, IOSR Journal of Mathematics, 6(2013), pp: 63-68.

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Paper Title:

Abstract: Clients play a crucial role in construction projects: they provide the sites, arrange for financing, invest their funds and define the scope. While projects are being executed; they coordinate with consultants and contractors, dictate the level of scope change management and ensure regular flow of construction funds either individually, as corporate and or through commitment to financiers. The relationship of the client with other team members and or the level of coordination can affect the performance of construction projects. If clients are going to appreciate and promote the practice of project management then they are going to get value for their money; considering the fact that project management was introduced to ensure efficiency in performance of construction projects. This paper examines the role of clients in ensuring the efficiency of construction projects performance in Kenya

Keywords: Project Management, Efficiency, Teamwork, Project Planning And Project Execution.

References:

1. Burke, R. (2007). Introduction to Project Management. Burke Publishing, USA.
CII, 1997. Alignment during pre-project planning: A key to project success. Implementation resource 113-3.
2. CIT 1996. Benchmarking best practice report: Briefing and design, Construct IT Centre of excellence, Salford, UK (ISBN: 1-900491-33-8).
3. Kerzner, H. (2013). Project management: A systems approach to planning, scheduling and controlling. Wily & Blackwell.
4. Muchungu, P. K.(2012). The contribution of human factors in the performance of construction projects in Kenya. Unpublished Phd. Thesis. University of Nairobi.
5. Murray, J.P., Hudson, J., Ganeson, R.N. and Toft, B., 1990. An expert system approach to Client briefing. Building Economics and Construction Management: subject D: Expert system (2), pp. 538-548.
6. Newman, R.,Bacon, V. and Dawson, S. 1990. Brief formulation and design of building. Report at Oxford Polytechnic.
7. Rowing, J., Nelson, M. and Perry, K., 1987. Project objective setting by owners and contractors, University of Texas at Austin, source document 31, the University of Texas at Austin, the construction Industry Institute.

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15.

Authors:

Paper Title:

Abstract: The success of a project would normally be measured by the extent to which the predetermined targets set by the Client have been met, whether it performs the function it was intended to meet satisfactorily and if it solves an identified problem within the stipulated time, cost and quality standards. To meet the objectives, the project will require effective planning control through the application of project management systems (Muchungu,2012). Developed economies have made use of project management in meeting the stated objectives. For an effective project management to apply; developed economies have made use of project management modelling to enable track and monitor project performance. There is need for developing economies to emulate the approaches of developed economies. Problems identified with the existing models prompted a discussion on the need to reconfigure the measurement process and the measures used. For this to be achieved, it is imperative that causes of project management failures be identified, analyzed, and or solutions or the way forward suggested. This paper therefore critically analyses the causes of project management failures in Kenya. A survey approach was used on a sample size of 500 members of which 312 members were responsive. The response rate was 62.4%.

Keywords: Project Management, Project failures, Construction Problems, Performance Measurement Systems

References:

1. Beatham, S., Anumba, C., and Thorpe, T., Hedges, I. (2004), “KPIs: a critical appraisal of their use in construction, Benchmarking”, An International Journal. Vol. 11 No. 1, 2004. pp. 93-117. Benchmarking the Government Client stage 2 study (1999), as quoted in “improving performance: project evaluation and benchmarking”, OGC (2007).
2. Chimwaso, D.K. (2000), “An Evaluation of Cost Performance of Public Project Case of Botwana”, Conference Proceedings, Construction Industry Development in The New Millennium. 2nd International Conference on Construction Industry Development and 1st Conference of CIB TG 29 on Construction in Developing Countries, Singapore.
3. Du Plessis, C. D. (2002), Agenda 21 for Sustainable Construction in Developing Countries –A discussion document.
4. Egan, J (1998) Rethinking Construction, Department of the Environment, Transport and the Regions, http://www.construction.detr.gov.uk. Accessed on 12th March 2013.
5. Gichunge, H. (2000). Risk Management in The Building Industry in Kenya. Unpublished PhD. Thesis. University of Nairobi.
6. Hamza, R. A., 1995. Some observations on the management of quality among construction professionals in the UK. Construction Management and Economics, 14, pp. 485-495.
7. Hillebrandt, P. (2000), Economic Theory and the Construction Industry, Third Edition, Macmillan, London.
8. Koskela, L. and Howell, G., (2002a), “The Underlying Theory of Project Management is Obsolete”, Proceedings of the PMI \Research Conference, 293-302.
9. Latham, M. (1994), Constructing the team, Joint Review of Procurement and Contractual Arrangement in the United Kingdom. Design, Drawing and Print Services.
10. Le-Hoai, L, Lee,Y.D., Lee, J.Y. (2008), “Delay and Cost Overruns in Vietnam Large Construction Projects: A Comparison with other selected Countries”, KSCE Journal of Civil Engineering, 12(6):367-377
11. Lock, D.(2007). Project Manament, 9th ed. Gower Publishing Company. 101 Cherry Street. Burlington. United States of America.
12. Kerzner, H. (2013). Project management: A systems approach to planning, scheduling and controlling. Wily & Blackwell.
13. Makulwasaatudom, A., Emsley, M., Sinthawanarong, K. (2003), “Critical Factors Influencing Construction Productivity in Thailand”, Second International Conference on Construction in the 21st Century (CITC-II) “Sustainability and Innovation in Management and Technology”, 10-12 December, Hong Kong.
14. Masu, S.M. (2006).An Investigation Into The Causes and Impact of Resource Mix Practices in The Performance of Construction Firms in Kenya. Unpublished Phd. Thesis. University of Nairobi.
15. Mbatha, C.M. (1986). Building contract performance “A Case Study of Government Projects in Kenya”. Unpublished M.A. Thesis. University of Nairobi.
16. Muchungu, P. K.(2012). The contribution of human factors in the performance of construction projects in Kenya. Unpublished Phd. Thesis. University of Nairobi.
17. Mutijwaa, P., and Rwelamila, D (2007), “Project Management Competence in Public Sector Infrastructure Organisation”, Construction Management and Economics, Vol. 25, pp55-66
18. Talukhaba, A.A. (1988). Time and Cost Performance of Construction Projects. Unpublished M.A. Thesis. University of Nairobi.
19. World Bank (1994), World Development Report 1994: Infrastructure for Development, World Bank, Washinton, D.C
20. Yisa, S., Edwards, D.J. (2002), Evaluation of Business Strategies in the UK Construction Engineering Consultancy, Measuring Business Excellence, Vol. 6, No.1.
21. Zhang, Y., Zhang, Y, Zhang, L. (2003), “Study on Reasons for Delays in Civil Engineering Project in China”, Conference Proceeding, “Sustainability and Innovation in Management and Technology”, 10¬12 November 2003, Hong Kong.

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Authors:

Paper Title:

Abstract: The construction industry is a crucial sector for the growth of any economy. It is the sector involved with erection, repair and demolition of buildings and Civil Engineering structures in an economy (Hillebrandt, 2000). According to the Kenya National Bureau of statistics (KNBS; 2012) the construction industry contributed 3.8%, 4.1 %, 4.3% and 4.1 % towards Gross Domestic Product (GDP) for the years 2008, 2009, 2010 and 2011 respectively. This is an average of 4.1 % as compared to 10% for the developed economies (Hillebrandt, 2000). Project management was introduced as a solution to the perennial problems of cost, time and quality in execution of construction projects. But the much touted benefits are not always achieved leaving clients with a lot of disappointments. It can be argued that the traditional project management variables have been inadequate in the assessment and control of construction projects. This paper set out to develop the most appropriate project management variables for Kenya to enable achieve an efficient and effective construction industry. A survey approach covering a sample of 500 members; randomly selected from the population was utilized.

Keywords: Project Management Variables, Lagging Measures, Leading Measures, Project Success, Project Management Models.

References:

1. Atkinson, R. (1999), “Project Management: Cost, Time and Quality, Two Best Guesses and A Phenomenon, Its Time to Accept Other Success Criteria”, International Journal of Project Management, 17 (6)337-42
2. Beatham, S., Anumba, C., and Thorpe, T., Hedges, I. (2004), “KPIs: a critical appraisal of their use in construction, Benchmarking”, An International Journal. Vol. 11 No. 1, 2004. pp. 93-117.
3. Chan, A.P.C and Chan, A.P.L., (2004), “Key Performance Indicators for Measuring Construction Success Benchmarking”, An International Journal Vol.11 No. 2, 2004 Pp. 2003-221.
4. De wit, A. (1988), “Measurement of project Success”, International of Project Management, 6 (3),164-170, Butterworth & co (Publishers) Ltd.
5. Bitici, U.S., 1994. Measuring your way to profit. Management Accounting, 14(3), PP. 141-151.
6. Chinyio, P., Olomolaiye, P. and Kometa, S., 1998. Needs based methodology for classifying construction Clients and selecting contractors. Construction Management and Economics, 16, PP 91-98.
7. Davenport, D.M. and Smith, P., 1995. Assessing the effectiveness of Client participation in construction Projects. 1ST RICS conference, 8-9 September, Edinburgh, UK, PP. 17-28.
8. Gichunge, H. (2000). Risk Management in The Building Industry in Kenya. Unpublished PhD. Thesis. University of Nairobi.
9. Harvey, R.C., and Ashworth, A., 1997. The construction industry of Great Britain, London: Laxtons.
10. Hillebrandt, P. (2000), Economic Theory and the Construction Industry, Third Edition, Macmillan, London.
11. Latham, M. (1994), Constructing the team, Joint Review of Procurement and Contractual Arrangement in the United Kingdom. Design, Drawing and Print Services.
12. Lim, K.C., Mohammed, A.Z., (1999). “Criteria of Project Success: An Exploration Re-Examination”. International journal of project management, Vol. 17 No.4, pp.243-8,
13. Love, P.I., 1996. Fast building: An Australian prospective. Proceedings of CIB-W92, procurement system symposium, north meets south, developing ideas, Durban, South Africa, 14-17 January, pp. 329-343.
14. Klagegg, O. J., Samset, K., and Magnussen, O.M.(2005), “Improving Success in Public Investment Projects: Lessons from Givernemen Initiative in Norway to Improve Quality at Entry”, a paper presented at the 19th IPMA World Congress, 2005.
15. Kometa, S.T., Olomolariya, P. O., and Harris, F.S. 1994. Attributes of UK construction Clients influencing project consultant’s performance. Construction Management and Economics, 12, 433-443.
16. Masu, S.M. (2006).An Investigation Into The Causes and Impact of Resource Mix Practices in The Performance of Construction Firms in Kenya. Unpublished Phd. Thesis. University of Nairobi.
17. Mbatha, C.M. (1993). An analysis of Building Procurement Systems, Features and Conception of An Appropriate Project Management Systems for Kenya. PhD Thesis. University of Wuppertal, Germany.
18. Morris, P. W. and Hough, G, H (1987), “The Anatomy of Projects”, John Wiley and Sons, New York (1987),
19. Muchungu, P. K.(2012). The contribution of human factors in the performance of construction projects in Kenya. Unpublished Phd. Thesis. University of Nairobi
20. Murray, M.D., Tookey, J.E., Langford, D.A, Hardcastle, C. (2002), “Construction Procurement Systems: Don’t Forget Murphy’s Law”, Paper submitted at the International Sympossium of the Working Committee, CIB W92 (Procurement Systems).
21. Patanakul , P. and Milosevic, D. (2009), “The Effectiveness in Managing a group of Multiple Projects: Factors of influence and Measurement Criteria”, International Journal of Project Management Vol.27, pp 216-233. Robbins, S.P. (2005), Organisational Behaviour, 11th ed., Prentice Hall, New Jersey.
22. Sadeh, A., Dvir, D., Shenhar, A. (2000), “The Role of Contract Type in Success of R & D Defence Projects under Increasing Uncertainty”, Project Management Journal, Vol. 31, No. 3, pp14-21
23. Shenhar, A.J., Levy, O., Dvir, D. (1996), “Towards a typological theory of Project Management”, Research Policy 25(4), 607-632.
24. Shenhar, A.J., Levy, O., Dvir, D. (1997), “Mapping the dimensions of project Success”, Project Management Journal 8 (2) 5-13.
25. Shenhar, A.J., Tishler, A, Dvir, D., Lipovetsky, S., Lechler, T. (2002), “Refining the Search for Project Success Factors: A Multivariate, Typological Approach”, R & D Management 32, 2. Blackwell Publishers.
26. Suh, N. P. (2001), Axiomatic Design: Advances and Applications, Oxford University Press.
27. Talukhaba, A.A. (1999). An investigation into The Factors Causing Construction Project Delays in Kenya. Case Study of High-rise Building Projects in Nairobi. Unpublished PhD. Thesis. University of Nairobi.
28. Vandevelde, A., Dierdonck, R.V., Debackere, K. (2002), “Practitioners View on Project Performance: A Three-Polar Construct”, Vlerick Leuven Gent Management School Fellows, R., Liu, A (2005), Research Methods for Construction. Blackwell Publishing, pp. 3-34
29. Walker D.H.T. (1994). An investigation into Factors that Determine Building Construction Time Performance. PhD Thesis: Royal Melbourne Institute of Technology Australia.
30. Wanyona G. (2005). Risk management in the cost planning and control of building projects. The case of Quantity Surveying profession in Kenya. Unpublished PhD Thesis. University of Cape Town.
31. Willard, B.K (2005) Project Success: Looking Beyond Traditional Metrics, Max’s Project Management Wisdom.

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Authors:

Paper Title:

Abstract: The geometry of surfaces with system of flat coordinate lines is investigated. The general vector equation of surfaces obtained. On the basis of which formulas of the main quadratic forms are obtained. The condition at which performance the system of flat coordinate lines will be system of the main lines of curvature is obtained. The subclass of normal surfaces – surfaces with system of flat coordinate lines in the normal planes of directrix is studied. As an example on the basis of the general formulas the equation of Monge’s ruled surfaces is obtained. Drawings of surfaces of Monge with various flat and spatial directrices and various flat generatrices are given.

Keywords: Surfaces with system of flat coordinate lines, the vector equation, coefficients of quadratic forms, lines of main curvatures, normal surfaces, Monge’s ruled surfaces

References:

1. Vygodsky M. I. Differential geometry. – M, L. : GITTL, 1949. -512 pages
2. Kagan V. F. Bases of the theory of surfaces. M, L. : OGIZ, 1947, t. 1 . – 512 pages; 1948, t. 2 . – 408 pages.
3. Milinsky V.I. Differential geometry.  L.: Publishing house of “Kubuch”, 1934.  332 pages.
4. Rashevsky P.K. Course of differential geometry. M, L. : GITTL, 2004. –428 pages.
5. Krivoshapko S. N., Ivanov V. N., Encyclopedia of analytical surfaces. – M: Book house “Librokom”, 2010. – 556 pages.
6. Krivoshapko S. N. Torsion surfaces and shells//Directory. M: UDN publishing house, 1991. 288 pages.
7. Ivanov V. N. Architectural compositions on the basis of Koons’s surfaces. Structural mechanics of engineering designs and constructions. – 2007 . – No. 4. – Page 5-10.
8. Krivoshapko S. N., Shambina S. L. Investigation of surfaces of velaroidal type with two sets of sinusoids on the ring plan. Structural mechanics of engineering designs and constructions. – 2009 . – No. 4. – Page 9-12.
9. Ivanov V. N. Geometry of cyclic surfaces//Collection scientific works of graduate students of engineering faculty.  Edition VIII.  М: UDN, 1971.  Pages 137-142.
10. Ivanov V. N. The theory of calculation of shells in the form of cyclic surfaces//Reports of scientific and technical conference of engineering faculty. M. : UDN, 1971.  Pages 27-29.
11. Ivanov V. N. Some questions of the theory of surfaces with set of flat coordinate lines//Calculation of shells of construction designs.  M: UDN, 1977.  Page 37-48.
12. Ivanov V. N., Rizvan Muhammad. Geometry of Monge’s carved surfaces and designing of shells//Structural mechanics of engineering designs and constructions: Interuniversity collection of scientific works, 11 Edition .  M: ASV publishing house, 2002.  Pages 27-36.
13. Ivanov V. N., Nasr Yunes Abbusha. Architecture and designing of shells in the form of wavy, umbrella and Ioakhimstal’s channel surfaces //Installation and special works in construction. – M: 2002 . – Pages 21-24.
14. Ivanov V. N. Geometry and designing of hells on the basis of surfaces with system of coordinate lines in the bunch planes//Spatial structures of buildings and constructions / Collection of scientific works of MOO “Spatial Structures”. – Edition 9 . – M: “Nine PRINT”, 2004. – Pages 26-35.
15. Ivanov V. N. Spherical curves and geometry of surfaces on the basic sphere//Modern problems of geometrical modeling / Materials of the Ukrainian-Russian scientific and practical conference, Kharkov, April 19-22, 2005 – Kharkov: 2005. – Pages 114-120
16. Ivanov V. N. Designing of shells using parabolo-sinusoidal surfaces//Structural mechanics of engineering designs and constructions, No. 2, 2005. – Pages 15-25.
17. G. Monge. Appendix of the analysis to geometry. – M: ONTI, 1936.

77-82

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Paper Title:

Abstract: The multi-carrier code division multiple access (MCCDMA) is a attractive choice for the future wireless systems where multiplexing and diversity in space, time and frequency are joined together through multiple input multiple output (MIMO) and space time block coding (STBC) in order to increase user capacity. In this study, the orthogonal complete complementary (OCC) spreading codes are employed along with unique spreading modulation for synchronous downlink transmission of MCCDMA systems. However, MC-CDMA suffers from multiple access interference (MAI) due to frequency-selective fading and multipath effects. To mitigate this MAI effect and achieve diversity gain, adaptive switched interleaving technique is proposed based on the concept of Minimum Distance Conditional Bit Error Rate (MDCBER) criterion. Furthermore, simple correlation reconstruction based maximal ratio combing (CRMRC) scheme is introduced at the receiver to compensate the diversity fading and suppress the effect of MAI at the receiver. The proposed technique modifies interleaving pattern adaptively for STBC encoded sequence of the users to reconstruct the orthogonality among the users to counteract the fading and multipath effects. For this purpose only a quantized detail of the Squared Minimum Distance Estimation (SMDE) is enough at the users such that the associated overhead is nominal compared to perfect channel state information (CSI) at the users. The simulation result shows that the MCCDMA system using switched interleaving technique along with CRMRC scheme achieves significant performance improvement in terms of BER. It also shows that the proposed technique reduces the MAI and increases user capacity.

Keywords: Multicarrier code division multiple access (MCCDMA), multiple access interference (MAI), switched interleaving, combining schemes, orthogonal complete complementary (OCC) Codes

References:

1. S. Hara and R. Prasad, “Design and performance of multicarrier CDMA system in frequency selective Rayleigh fading channels,” IEEE Transactions on Vehicular Technology, vol. 48, no. 5, pp. 1584-1595, Sep. 1999.
2. K. Fazel and S. Kaiser, “Multi-Carrier and Spread Spectrum System,” Second Edition, John Wiley and Sons, 2008.
3. S. M. Alamouti, “A simple transmit diversity technique for wireless communications,” IEEE Journal on Selected Areas in Communication, vol. 16, no. 8, pp. 1451-1458, Oct. 1998.
4. M. El-Hajjar and Lajos Hanzo, “Multifunctional MIMO systems: A combined diversity and multiplexing design perspective,” IEEE Communication Magazine, pp. 73- 79, Apr. 2010
5. H. Chenggao, N. Suehiro, T. Hashimoto, “A systematic framework for the construction of optimal complete complementary codes,” IEEE Trans. Inf. Theory, vol. 57, no. 9, pp. 6033–6042, Sept. 2011.
6. Mario E. Magaña , Thunyawat Rajatasereekul , Daniel Hank, and Hsiao-Hwa Chen, “Design of an MC-CDMA system that uses complete complementary orthogonal spreading codes,” IEEE Trans. on Vehicular Technology, vol. 56, no. 5, pp. 2976-2989, Sept. 2007
7. S.Verd´u, “Multiuser Detection, “Cambridge University Press, 1998.
8. Lu, H.-Y, “A family of minimum mean square error multiuser detectors for three-domain spread multi-carrier direct sequence-code division multiple access,” Communications, IET, vol. 6, no. 6, pp. 587 – 598, 2012.
9. Yan Z, “QoS-based space-frequency prefiltering for TDD MC-CDMA systems in slowly time-varying channels,” Wireless Communication Mobile Computing, vol. 9, pp. 1113-1124, 2009
10. B. M. Masini and, A. Conti, “Adaptive TORC detection for MCCDMA wireless systems,” IEEE Transactions on Communications, vol. 57, no. 11, pp. 3460–3471, 2009
11. S. Chen, A. Livingstone, and L. Hanzo, “Minimum bit-error rate design for space-time equalization-based multiuser detection,” IEEE Trans. Commun., vol. 54, no. 5, pp. 824_832, May 2006.
12. Katsutoshi Kusume, Gerhard Bauch, and Wolfgang Utschick, “IDMA vs. CDMA: Analysis and Comparison of Two Multiple Access Schemes,” IEEE Transactions on Wireless Communications, vol. 11, no. 1, pp.78-87, January 2012.
13. M.S. Alouini, M.K. Simon, “Performance of generalized selection combining over Weibull fading channels,” Wireless Communication Mobile Computing, vol. 6, pp. 1077-1084, 2006.
14. Wei-Xiao Meng, Si-Yue Sun, Hsiao-Hwa Chen, and Jin-Qiang Li, “Multi-User Interference Cancellation in Complementary Coded CDMA with Diversity Gain,” IEEE Wireless Commn. letters, vol. 2, no. 3, pp. 303-306, June 2013.
15. J. Harshan and B. Sundar Rajan, “On two-user Gaussian multiple access channels with finite input constellations,” IEEE Trans. Inf. Theory, vol. 57, no. 3, pp. 1299–1327, Mar. 2011.
16. G.Senthilkumar and G.Nagarajan, “Performance Enhancement of MCCDMA Using Orthogonal Complete Complementary Codes,” Proceedings of the International Conference on Communications, Networking and Signal Processing (ICCNASP-2013), India, Sep. 2013
17. Tain-Sao Chang, Cherng-Chang Yen, Ya-Yin Yang and Jyh-Horng Wen, “Pre-filtering technique for MAI cancellation in MC-CDMA systems,” Wirel. Commun. Mob. Comput, vol. 3, pp. 63–71, 2013.

83-87

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Paper Title:

Abstract: Influence of different materials on graded index optical fiber systems was studied, these materials(channel 1 has a core made from PMMA+ and cladding of carbon fluorine polymer,channel 2has a core made from Polystyrene PS++ and cladding of Polymer PMMA+,the third channel has the core made from Silica with cladding of Silicon resin), were examined for their effect on quality factor ,total output power (dBm) and intermodal dispersion at the receiver.All the channels operated at the same optical transmitted with non return-to-zero (NRZ).Performance study was done for variable lengths of fiber 1, 2, 3, 4 km for these different material channelsby simulating a model of communication system. Optisystem software has been used for this simulation.Results reveal the ability of improving the graded index fiber characteristics by using these materials and theoptimum effect concluded at(20dBm) input powerby using the third channel material i.e.the quality factor and total output power were increased to reach(374.2 ) and (-9.073 dBm) respectively and intermodal dispersion decreased to reach(11.822 ns/km).

Keywords: Graded index fiber, Polymer Optical Fiber, Intermodal dispersion.

References:

[1]. R. Dangel, C. Berger, R. Beyeler, L. Dellmann, M. Gmür, R. Hamelin, F. Horst, T. Lamprecht, T. Morf, S. Oggioni, M. Spreafico, and B. J. Offrein, “Polymer waveguide based board level optical interconnect technology for datacom applications,” IEEE Trans. Adv. Packag. 31(4), 759–767 (2008).
[2]. X. Wang, W. Jiang, L. Wang, H. Bi, and R. T. Chen, “Fully embedded board-level optical interconnects fromwaveguide fabrication to device integration,” J. Lightwave Technol. 26(2), 243–250 (2008).
[3]. R. N. HAWARD, B. M. MURPHY and E. F. T. WHITE. In Proceedings of Conference on Fracture, Brighton. 1969.Paper 45.
[4] Y. Koike, “High-bandwidth graded-index polymer optical fiber,” Polymer,vol. 32, no. 10, pp. 1737–1745, 1991.
[5] Y. Koike, T. Ishigure, and E. Nihei, “High-bandwidth graded-index polymer optical fiber,” J. Lightwave Technol., vol. 13, pp. 1475–1489,July 1995.
[6] J. Senior,“ Optical Fiber Communications,” Principles and Practice, 1st, Prentice Hall International,Inc. 1985
[7]. M Rajesh,“Fabrication and characterisation of polymer optical fibers for smart sensing and optical amplification,”International School of Photonics, Cochin University of Science & Technology Cochin, INDIA www.photonics.cusat.edu July 2006.
[8]. J. Brandrup, E.H. Immergut, D.R. Bloch and E.A. Grulke,“ Polymer Handbook,”2 Volume ,Wiley, 2003
[9]. A Ravve ,“ Principles of Polymer Chemistry,” Springer, 2000
[10] W.Daum.J.Krause,P.Zamzow,O.Ziemann,“POF fordatacommunication,”,2000.
[11] J. Senior, Optical Fiber Communications: Principles and Practice, 1st, Prentice Hall International,Inc. 1985
[12]. A. Tagaya, Y. Koike, T. Kinoshita, E. Nihei, T. Yamamoto, and K. Sasaki,”Polymer optical fiber amplifier”, App Phy Left. 63,883-884,1993
[13] T. Barake, “A Generalized Analysis of Multiple-Clad Optical Fibers with Arbitrary Step-Index Profiles and Applications” M.Sc thesis, Virginia Polytechnic Institute and State University, 1997.
[14] G. P. Agrawal, Fiber-Optic Communications Systems, 3rd ed. John Wiley & Sons, Inc., 2002.
[15] R. M. Gayliard and S. Karp, Optical Communication system, John wiely and sonce ING.1979.
[16] MohamadHasrulAriffin Bin MohdBadri, “A Cost Effective Broadband ASE Light Source Based FTTH”, thesis, page 20-26.
[17] Chong Wing Keong, K R Subramanian, V K Dubey, “Optical Fiber System for Video and Telemetry Signal.” Singapore Polytechnic, Electronics and CommEngineering, School of Electrical and Electronic Engineering, Nanyang Technology University, Singapore.

88-94

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Authors:

Paper Title:

Abstract: The issue of mobility is considered among the foremost of concerns for visually impaired individuals. This work develops a Navigation Assistant that aids the visually impaired with mobility in a known environment such as a household, by combining the principles behind Scale-Invariant Feature Transform (SIFT) and Content-Based Image Retrieval (CBIR). Furthermore, this work proposes and tests several techniques such as Color Segmentation, Difference of Images, and Contrast Manipulation to improve the Navigation Assistant. Using a video stream that was obtained from a small camera that the user carries, key objects in the household were identified using the software developed. The Navigation Assistant created using the enhancements was markedly improved in both accuracy and speed from the control Assistant, and is therefore applicable to real-life usage by visually impaired individuals.

Keywords: CBIR, SIFT, Color Segmentation, Difference of Images.

References:

[1] “Statistical Facts about Blindness in the United States (2011)”,

Internet: https://nfb.org/factsaboutblindnessintheus, 2011 [Sept. 09, 2013].
[2] Frick, KD., Gower, EW., Kempen, JH., et al.: “Economic Impact of Visual Impairment and Blindness in the United States,”

Archives of Ophthalmology, Vol. , no. 125.4, pp. 544-50, 2007.
[3] “Facts and Figures about Issues around Sight Loss”, Internet:

https://www.actionforblindpeople.org.uk/about-us/media-centre/facts-and-figures-about-issues-around-sight-loss, 2008 [Sept. 09, 2013].
[4] “Free White Cane Program”, Internet: https://nfb.org/free-cane-program [Sept. 09, 2013].
[5] Lowe, DG.: “Distinctive Image Features from Scale-Invariant Keypoints” Int. J. Comput. Vision, vol. 60.2, pp. 91–110, 2004.
[6] Young, S.: “MIT Technology Review: What it’s like to see again with an artificial retina”, Internet: http://www.technologyreview.com/news/514081/can-artificial-retinas-restore-natural-sight/, 2013 [Sept. 09, 2013].
[7] Browne, D.: “Towards a Mobility Aid for the Blind” Image Vision Comput. Nz, pp. 275–79, 2003.
[8] “Location Awareness Programming Guide”, Internet: https://developer.apple.com/library/ios/documentation/userexperience/conceptual/

LocationAwarenessPG/CoreLocation/CoreLocation.html, 2012 [Sept. 09, 2013].
[9] McDaniel, T., Kahol, K., Villanueva, D., et al.: “Integration of RFID and computer vision for remote object perception for individuals who are blind” in Proceedings of the 2008 Ambi-Sys workshop on Haptic user interfaces in ambient media systems (HAS ’08). ICST (Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering), ICST, Brussels, Belgium, Belgium, Article 7.
[10] Kain, A., Macon, MW.: “Spectral voice conversion for text to-speech synthesis” In Proceedings of the International Conference on Acoustics, Speech, and Signal Processing, Vol.1, pp. 285-288, May 1998.
[11] Van Kleek, M.: “Evaluating the Stability of SIFT Keypoints across Cameras”, tech. rep., Agent-based Intelligent Reactive Environments MIT CSAIL.
[12] Ran, L., Helal, S., Moore, S.: “Drishti: An Integrated Indoor/Outdoor Blind Navigation System and Service”, In Proceedings of the Second IEEE Annual Conference on Pervasive Computing and Communications (PerCom.04), pp. 23-30, 2004.
[13] Adrien Auclair, LC., Vincent, N.: “How to use sift vectors to analyze an image with database templates” tech. rep., University Paris-Descartes, vol. 4918, pp. 224-236, 2008
[14] Bakken, T.: “An Evaluation of the SIFT Algorithm for CBIR”, tech. rep., Telenor R&I Research Note, 16 Aug. 2007.
[15] [Gabsi, N., Clerot, F., Hebrail, G.: “Efficient Trade-Off between Speed Processing and Accuracy in Summarizing Data Streams”, In Proceedings of the 14th Pacific-Asia conference on Advances in Knowledge Discovery and Data Mining – Volume Part I, pp. 342-53, 2010.

95-100

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Authors:

Paper Title:

Abstract: This paper presents the design to control the speed of permanent magnet brushless DC motor using sensorless method. In conventional operation Hall sensors are used to detect the position of the rotor windings and according to which the six switches of the voltage source inverter are gated. In sensorless method, zero crossing point of back EMF of line voltage differences are measured, which will give the information about the phase which is to be energized. The zero crossing instant of back EMF waveforms is estimated indirectly from the measurement of three terminal voltages of the motor, from which correct commutation instants of the six switches are estimated. A direct phase current control method is used to control the phase currents in four switches. Cost reduction is achieved by elimination of three Hall Effect position sensors and the numbers of power switches are reduced to four instead of six. An algorithm for four switch topology is developed with the third winding connected to the neutral of the supply line and performance of the developed sensorless technique is demonstrated by simulation. The hardware implementation is done by using PIC16F877 and the voltage and virtual hall signals are verified.

Keywords: brushless DC motor, four switch inverter, sensorless control.

References:

[1] P.Pillay and R.Krishnan, “Modelling of permanent magnet motor drives”, Industrial Electronics, IEEE Transactions on, vol. 35, pp. 537-541,1988.
[2] Mingyao Lin, Weigang Gu, Wei Zhang,Qiang Li, “Design of Position Detection Circuit for Sensorless Brushless DC Motor”.
[3] B.k.Lee,T.H.Kim and M.Ehsani “On the feasibility of four switch three-phase BLDC motor drives for low cost commercial applications:Topology and control”IEEE Trans.Power Electron vol. 18, no. 1, pp.164–172, Jan. 2003.
[4] Halvaei Niasar, H. Moghbelli and A. Vahedi, “A Low-Cost Sensorless Control for Reduced-Parts, Brushless DC Motor Drives,” IEEE Transactions on Industry Applications, 2008.
[5] T.J.E. Miller, “Brushless permanent magnet and reluctance motor drive”, Oxford, 1989.
[6] Halvaei Niasar, H. Moghbelli and A. Vahedi, “A Novel Sensorless Control Method for Four-Switch, Brushless DC Motor Drive without Phase Shifter”, IEEE Transactions on Power Electronics, Vol. 23, No. 6, November 2008.
[7] J.P. Johnson, M. Ehsani, Y. Guzelgunler; “Review of Sensorless Methods for Brushless DC Motor”, IEEE Industry Applications Conference, 1999, Vol. 1, pp. 143 –150.
[8] Halvaei Niasar, H. Moghbelli and A. Vahedi, “Implementation of four-switch brushless dc motor drive based on TMS320LF2407 DSP”, 2007 IEEE International Conference on Signal Processing and Communications (ICSPC 2007), 24-27 November 2007, Dubai, United Arab Emirates, PP 332-335.
[9] Halvaei Niasar, H. Moghbelli and A. Vahedi, “Modeling, simulation and implementation of four-switch brushless dc motor drive based on switching functions”, IEEE Transactions on Industry Applications, 2009, pp 682-687.

101-106

22.

Authors:

Paper Title:

Abstract: The objective of this paper is to simulate, design and implementation of a proposed system of multilevel bandpass QAM modems (modulation/demodulation) schemes with selectable technique between them based on Software Defined Radio (SDR) using FPGA for WIMAX system. These modems are 8QAM, 16QAM, 32QAM and 64QAM. MATLAB-Simulink tool and M-files are used to design these modems.“Simulink HDL Coder” is used to convert all files to VHDL Codes for hardware implementation using FPGA Altera-Cyclone II Family DE2 board. Simulink HDL Coder proves the capabilities to generate Hardware Description Language (HDL) code to MATLAB model (Simulink and M-file) for complex units of proposed system. The complex units are converted to simple units compatible with Simulink HDL Coder. The experimental results show that there is coincidence between transmitted and received data with average time delay of (0.35-0.40µsec) for different data rate (1.5-3Mbps).

Keywords: FPGA, SDR, Simulink HDL Coder, VHDL and WIMAX.

References:

[1] F. Kasperski, O. Pierrelee, F. Dotto and M. Sarlotte, ″High Data Rate Fully Flexible SDR Modem Advanced Configurable Architecture & Development Methodology″, IEEE Design, Automation & Test in Europe Conference & Exhibition, pp. 1040 – 1044, September 2009.
[2] R. Muzammil, M.S. Beg and M.M. Jamali ″ Design and Implementation of BPSK Transmitter and Receiver for Software Defined Radio on a Model Based Development Platform″, IEEE Symposium on Industrial Electronics and applications, pp.89_94, September 2011.
[3] Z. Zhao, Y. Shen and Y. Bai, ″Design and Implementation of the BPSK Modem Based on Software Defined Radio″, IEEE First International Conference on Instrumentation, Measurement, Computer, Communication and Control, pp. 780_784, 2011.
[4] A. Karmakar and A. Sinha, ″A Novel Architecture of a Reconfigurable Radio Processor for Implementing Different Modulation Schemes″, IEEE Computer Research and Development (ICCRD) 3rd International Conference, pp. 115_119, 2011.
[5] Y. H. Chye, M. F. Ain and N. M. Zawawi, ″Design of BPSK Transmitter Using FPGA with DAC″, IEEE 9th Malaysia International Conference on Communications, pp. 451_456, December 2009.
[6] S. W. Shaker, S. H. Elramy and K. A. Shehata, ″FPGA Implementation of a Reconfigurable Viterbi Decoder for WIMAX Reciver″, IEEE International Conference on Microelectronics, pp. 264_267, 2009.
[7] Y. Yang, J. Liu, Q. Zhang and C. Xiu ″Performance Analysis for Rectangular QAM Modulation with Arbitrary Bits-to-Symbols Mapping over Rician Channel″, IEEE International Conference, pp. 1007_1010, 2010.
[8 A. Goldsmith, ″ Wireless Communications″, Cambridge University Press, 2005.
[9] S. O. Leary, ″Understanding Digital Terrestrial Broadcasting″, Artech House Boston London, INC., 2000.
[10] J. G. Andrews, A. Ghosh and R. Muhamed, ″Fundamentals of WiMAX Understanding Broadband Wireless Networking″, Pearson Education, Inc., 2007.
[11] ″Simulink HDL Coder″, the Mathwork Inc., 2011.

107-116

23.

Authors:

Paper Title:

Abstract: This paper presents modeling and simulation for the PV cells, modules, and array, and building of blocks based on MATLAB / Simulink software package. The main aim of this work is the improvement of the PV solar cell simulator based on a two-diode model. This model is more accurate than the single diode model especially at low insolation levels; therefore this will gives more accurate prediction of the performance of the solar cell system. Most of the inputs to the simulator are given in the PV module datasheet, and the other (i.e. Rp and Rs) are estimated by an iteration method. The simulation model makes use of the two-diode model basic circuit equations of PV solar cell, taking the effect of sunlight irradiance and cell temperature into consideration on the output current V-I and output power V-P characteristics. The output current and power characteristics of PV module and PV array are simulated using the proposed model. The simulator is verified by applying the model to Kyocera Solar KC200GT and Solarex MSX-64 PV Modules.

Keywords: Modeling, PV module/ Array, Simulation, MATLAB/Simulink

References:

[1] S.Chowdhury, S.P.Chowdhury, G.A. Taylor, and Y.H.Song ,“Mathematical Modeling and Performance Evaluation of a Stand-Alone Polycrystalline PV Plant with MPPT Facility”, IEEE, 2008.
[2] Huan-Liang Tsai, Ci-Siang Tu, and Yi-Iie Su, “Development of Generalized Photovoltaic Model Using MATLAB/SIMULINK”, Proceedings of the World Congress on Engineering and Computer Science WCECS, San Francisco, USA, 2008.
[3] Zainal Salam, Kashif Ishaque, and Hamed Taheri, “An Improved Two-Diode Photovoltaic (PV) Model for PV System”, 978-1-4244-7781-4/10/2010, IEEE.
[4] Zainal Salam, Kashif Ishaque, and Hamed Taheri,”Accurate MATLAB Simulink PV System Simulator Based on a Two-Diode Model”, Journal of Power Electronics, Vol. 11, No. 2, March 2011.
[5] Atul Gupta and Venu Uppuluri Srinivasa, “Design, Simulation and Verification of Generalized Photovoltaic Cells Model Using First Principles Modeling”, ACEEE Int. J. on Control System and Instrumentation, Vol. 03, No. 01, Feb 2012.
[6] S. Sheik Mohammed, “Modeling and Simulation of Photovoltaic module using MATLAB/ Simulink”, International Journal of Chemical and Environmental Engineering, volume 2, No.5, October 2011.
[7] Haitham S.Dawood, “Analytical Equivalent Circuit of High-Irradiated Conventional Silicon Solar Cell Performance”, Iraqi Journal of Applied Physics, Vol. (5), No. (4), October 2009.
[8] H. Bourdoucen and A. Gastli, “Analytical Modeling and Simulation of Photovoltaic Panels and Array”, The Journal of Engineering Research, Vol. 4, No. 1, 2007.

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Authors:

Paper Title:

Abstract: Computational fluid dynamics applications become crucial for scientist to understand various Natural phenomenon. These applications require high performance computing resources that most small academic institutions cannot afford. Elastic cloud clusters are best suited environment for those small academic institutions to gain high performance computing power and enable researchers to explore new trends in scientific computing with reasonable cost. This work aims to study the parallelism efficiency; in term of communication time and execution time for a highly optimized parallel lattice Boltzmann solver on elastic cloud clusters. On these elastic clusters we have found that the lattice Boltzmann implementation is fully adaptive, highly flexible and cost effective to use for solving complex large fluid mechanical systems.

Keywords: Computational Fluid Dynamics, Elastic Cloud Computing, Multi-core Programming, Lattice Boltzmann.

References:

[1] S. Ostermann, A. Iosup, N. Yigitbasi, R. Prodan, T. Fahringer and D. Epema, “A Performance Analysis of EC2 Cloud Computing Services for Scientific Computing,” in Cloud Compting , Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, 2010.
[2] “AWS Amazon Elastic Compute Cloud (EC2) – Scalable Cloud Servers:,” 2013. [Online]. Available: http://aws.amazon.com/ec2/.
[3] “Cloud Services – Windows Azure,” Microsoft Co. Ltd., 2013. [Online]. Available: http://www.windowsazure.com/en-us/services/cloud-services/.
[4] M. J. H. Ferziger, “Computational Methods for Fluid Dynamics,” 1996.
[5] P. Wesseling, “Principles of Computational Fluid Dynamics,” 2001.
[6] Y. Yan, Flow and particle transport by the Lattice Boltzmann Method, New York: ProQuest, 2008.
[7] X. He and L.-S. Luo, “Lattice Boltzmann model for the incompressible Navier-Stokes equation,” vol. Journal of Statistical Physics, no. 88, 1997.
[8] A. M. Artoli, “Mesoscopic Computational Haemodynamics,” PHD Thesis, 2003.
[9] A. M. Artoli, D. Kandhai, H. J. Hoefsloots, A. G. Hoekstra and P. M. Sloot, “Lattice BGK simulations of flow in a symmetric bifurcation,” Future Generation Computer Systems, vol. 20, no. 6, pp. 909-916, 2004.
[10] M. Geveler, D. Ribbrock, D. Goddeke and S. Turek, “Lattice-Boltzmann Simulation of the Shallow-Water Equations with Fluid-Structure Interaction on Multi- and Manycore Processors,” Facing the Multicore-Challenge, vol. 6310, 2010.
[11] H. Chen, S. Chen and W. H. Matthaeus, “Recovery of the Navier-Stokes equations using a lattice-gas Boltzmann method,” The American Physical Society, vol. 45, no. 8, 1992.
[12] P. Barham, B. Dragovic, K. Fraser, S. Hand, T. Harris, A. Ho, R. Neugebauer, I. Pratt and A. Warfield, “Xen and the art of virtualization,” in Proceedings of the Nineteenth ACM Symposium on Operating systems principles, New York, USA, 2003.
[13] S. Succi, The Lattice Boltzmann Equation for Fluid Dynamics and Beyond, USA : Oxford University Press, 2002.
[14] A. M. Artoli, D. Kandhai, H. C. Hoefsloot and A. G. Hoekstra, “Lattice Boltzmann, a Robust and Accurate Solver for Interactive Computational Hemodynamics,” Computational Science, vol. 2657, pp. 1034-1043, 2003.

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25.

Authors:

Paper Title:

Abstract: Social networking sites facilitate and develops a virtual community for people to share their thoughts, interest activities or to increase their horizon of camaraderie. With the advancement in Social networking sites or we can refer it as with online social networks the user can connect to each other. With all these options available on Social Networking sites it creates a virtual world for the users. Social Networking sites go upwards because of all these reasons. In recent years indicates that for many people they are now the mainstream communication technology. Social networking sites come under few of the most frequently browsed categories websites in the world. Nevertheless Social Networking sites are also vulnerable to various problems threats and attacks such as disclosure of information, identity thefts etc. Privacy practices in social networking sites often appear convoluted as information sharing stands in discord with the need to reduce disclosure-related abuses. Facebook is one such most popular and widely used Social Networking sites which has its own robust set of Privacy policies. Yet they are also prone to various privacy issues and attacks. In this work we examine the currently existing privacy policies of Facebook since 2013 and then provide with certain new policies that enhance and strengthen the existing ones. We conclude with a discussion of how these educts may be integrated into the design of Facebook like Social Networking sites systems to facilitate interaction while enhancing the individual privacy.

Keywords: Social networking sites (SNS’s), Cyber Stalking, Cyber Bullying.

References:

[1] MARK Hachman (Aoril 23,2012). “Facebook Now Totals 1.20 billion Users, Profits Slip”. PCMag.com. Retrieved September 24, 2013.
[2] A. Ho, A4. Maiga, and E. Aimeur, “Privacy protection issues in social networking sites,”IEEE/Acs International Conference on Computer Systems and Applications 2009 (AICCSA 2009),PP.271-278,Country,2009
[3] Aimeur, E.; gambus,S.; Ai Ho; , “UPP: User Privacy Policy for Social Networking Sites,”Internet and Web Applications and Services,2009. ICIW ’09.Fourth International Conference on vol., no., pp.267-272,24-28 May 2009.
[4] C.Zhang, J.Sun,X.Zhu and Y.Fang,” Privacy and security for online social networks: challenges and opportunities,” IEEE Network, vol.24,no.4,pp.13-18,2010
[5] Stutzman, F.and Kramer-Duffield, J. Friends only: Examining a Privacy Enhancing behaviour in Facebook. In Proc. CHI’10.ACM Press, 2010.1553—1562.
[6] Thomas,K., Grier, C., and Nicol,D.M.unFriendly: Multi party privacy risks in social networks.In proceedings of the 10th international conference on Privacy enhancing technologies(2010),Soringer-Verlag,pp.236
[7] http://www.facebook.com\privacy
[8] Ai Ho; Maiga, A.; Aimeur, E.; , “Privacy protection issues in social networking sites,” Computer Systems and Applications, 2009. AICCSA 2009.IEEE/ACS International Conference on vol.,no., pp.271-278, 10-13 May 2009
[9] Xi Chen; Shuo Shi; ,”A Literature review of Privacy Research on Social Network Sites,” Multimedia Information Networking and Security,2009.MINES’09.International Conference on, vol.1,no.,pp.93-97,18-20 Nov.2009
[10] http://www.privacyawarenessweek.org
[11] DotRights Social Networking Page, www.dotrights.org/social-networking
[12] SeyedHossein Mohtasebi and Ali Dehghantanha,” A Mitigation Approach to the Malwares Threats of Social Network Services,” Muktimedia Information Networking and Security,2009. MINES’09. International Conference on, vol.1,no.,pp.448-459,2011
[13] Mohammad Mannan, Paul C. Van Oorschot,” privacy-Enhanced Sharing of Personal Cpntent on the Web,” Security And Privacy- Misc” , pp.487-496,April 21-25,2008 Beijing, China
[14] Privacy Policy Facebook (2011), www.facebook.com/policy.php
[15] Chi Zhang; Jinyuan Sun;, ”Privacy and Security for Online Social networks:Challenges and Opportunities,” IEEE Network,Aug.2010
[16] Vorakulpipat, Marks, Rezgui, “ Security and Privacy Issues in Social Networking Sites from User’s Viewpoint,”IEEE Network,Jun.2011
[17] P.Kodeswaran, and E.Viegas, “Towards A privacy preserving Policy Based Infrastructure for Social Data Access To enable Scientific Research,”2010 Eighth Annual International Conference on Privacy,Security and Trust,Jun 2010
[18] I. Polakis and G. Kontaxis,” Using Social Networks to harvest Email Addresses,” In Proc.CHI”10. ACM Press,2010
[19] C.Squicciarini and M.Shehab,” Privacy policies for shared content in social network sites,” In Proc.Chi’10.Acm Press,30 June 2010
[20] Yabing Liu and P. Gummadi, “Analyzing Facebook Privacy Settings:User Expectations vs. Reality,” In Proceedings of the 10th international conference on Privacy enhancing technologies(2011)
[21] P.Joshi anf C Kuo,” Security and Privacy in Online Social Networks: A Survey”,IEEE Network,2011
[22] D Michslopoulos and I Mavridis,” Surveying Privacy Leaks Through Online Social Networks”, 2010 14th panhellenic Conference on Information,2010.

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26.

Authors:

Paper Title:

Abstract: Image Segmentation has been an area for a long time which is providing opportunities for the intellectual communities to do research work. Image segmentation is a process of partitioning an image into meaningful regions. There exist many digital image segmentation techniques which are currently applied on different fields. These image segmentation techniques need comparative analysis for further development and modifications for continuous and consistent improvement. Hence, in this paper an overview of image segmentation and its present techniques is presented which demands a lot of research work.

Keywords: Image, Image Segmentation, Segmentation Techniques.

References:

[1] P. Rafael C. Gonzalez and Richard E. Woods, “Digital Image Processing”, Third Edition, Pearson Education, Asia.
[2] Jay Acharya, Sohil Gadhiya and Kapil Raviya, “Segmentation Techniques for Image Analysis: A Review”, International Journal of Computer Science and Management Research, Vol 2 Issue 1, January 2013, Pg. 1218-1221.
[3] Dzung L. Pham, Chenyang Xu and Jerry L. Prince, “A Survey Of Current Methods In Medical Image Segmentation”, Annual Review of Biomedical Engineering, January 19, 1998.
[4] Rajvi Parikh and Dr Hitesh shah, ”A Survey on Computer Vision Based Diagnosis for Skin Lesion Detection”, International Journal of Engineering Science and Innovative Technology (IJESIT) Volume 2, Issue 2, March 2013, Pg. 431-437.
[5] Nadia Smaoui and Souhir Bessassi, “A developed system for melanoma diagnosis”, International Journal of Computer Vision and Signal Processing, 3(1), 10-17(2013), Pg. 10-17.
[6] Aswin.R.B, J. Abdul Jaleel and Sibi Salim, “Implementation of ANN Classifier using MATLAB for Skin Cancer Detection”, International Journal of Computer Science and Mobile Computing, ICMIC13, December- 2013, Pg. 87-94.
[7] Ayesha Khalid Khan, Gulistan Raja and Ahmad Khalil Khan, ”Implementation of Marker based Watershed Image Segmentation on Magnetic Resonance Imaging”, Life Science Journal 2013; 10(2): 115-118. (ISSN: 1097-8135), Pg. 115-118.
[8] E. Nadernejad, S. Sharifzadeh and H. Hassanpour, “Edge Detection Techniques: Evaluations and Comparisons”, Applied Mathematical Sciences, Vol. 2, 2008, no. 31, Pg. 1507 – 1520.
[9] Rajesh Dass, Priyanka, Swapna Devi, “Image Segmentation Techniques”, IJECT Vol. 3, Issue 1, Jan. – March 2012.
[10] Arpit Maheshwari, Sachin Sonawane and Shashikant Patil, “Performance Overview, Comprehensive Assessment and Review of Image Segmentation Techniques for Natural Images”, Current Trends in Technology and Science, ISSN : 2279-053. Volume : II, Issue : VI, Pg. 367-373.
[11] Ramadevi, Y., B. Kalyani, and T. Sridevi, “Synergy between Object Recognition and Image Segmentation”, International Journal on Computer Science & Engineering (2010).
[12] Vishal B. Langote and Dr. D. S. Chaudhari, “Segmentation Techniques for Image Analysis”, International Journal of Advanced Engineering Research and Studies (IJAERS)/Vol. I/ Issue II/January-March, 2012.
[13] Pedro F. Felzenszwalb and Daniel P. Huttenlocher, ” Efficient Graph-Based Image Segmentation”, International Journal of Computer Vision 59(2), 167–181, 2004.
[14] Bo Peng and Olga Veksler, “Parameter Selection for Graph Cut Based Image Segmentation”, In: British Machine Vision conference (2008).
[15] S. Vicente, V. Kolmogorov, and C. Rother, “Graph cut based image segmentation with connectivity priors”. In CVPR, 2008.
[16] Mehmet Sezgin and Bulent Sankur, “Survey over image thresholding techniques and quantitative performance evaluation”, Journal of Electronic Imaging 13(1), 146–165 (January 2004).
[17] Dmitrij Csetverikov, “Basic algorithms for digital image analysis: a course“, http://ssip2003.info.uvt.ro/lectures/chetverikov/shape_analysis.pdf.
[18] Prerna Pachunde, Prof.Vikal.R.Ingle and Prof. Dr Mahindra. A. Gailwad, “Segmentation of Color Images Using Genetic Algorithms: A Survey”, IOSR Journal of Electrical and Electronics Engineering (IOSRJEEE) ISSN: 2278-1676 Volume 1, Issue 6 (July-Aug. 2012), PP 09-12.
[19] M.E. Farmer and D. Shugars. “Application of genetic algorithms for wrapper-based image segmentation and classification”. In IEEE Congress on Evolutionary Computation, pages 1300–1307, July 2006.
[20] Catalin Amza, ”A Review on Neural Network –Based Image Segmentation Techniques”, De Montfort University, Mechanical and Manufacturing Engg., The Gateway Leicester, LE1 9BH, United Kingdom, 1-23.
[21] A. Gavlasova, A. Prochazka, M. Mudrova, “Wavelet based image segmentation”, in Proceedings of the 14th Annual Conference Techincal Computing, Prague, 2006, pp.1-7.
[22] Dongwook Cho, and Tien D. Bui, “Image Inpainting Using Wavelet-based Inter- and Intra- scale Dependency”, IEEE Transactions Image Processing, 978-1-4244-2175-6, 2008.
[23] Vaibhav V Nalawade and Sachin D Ruikar, “Image Inpainting Using Wavelet Transform“, IJAET/Vol.II/ Issue IV/October-December, 2011/302-307.
[24] M.Ceylan, O.N.Ucan, Y.Özbay, R.Jennane, G.Aufort, C.L.Benhamou, “Comparison of discrete wavelet transform and complex wavelet transform in hybrid skeletonization based on cvann”, İstanbul Aydın Üniversitesi, Fen Bilimleri Dergisi, 1, 27-51, ( Üniversite Dersgisi ).
[25] Divya.D, Sushma P.S, “FPGA Implementation of a Distributed Canny Edge Detector”, International Journal of Advanced Computational Engineering and Networking, ISSN: 2320-2106, Volume- 1, Issue- 5, July-2013.
[26] Heimann, Tobias, and Hervé Delingette, “Model-based Segmentation”, Biomedical Image Processing, Springer Berlin Heidelberg, 2011. 279-303.

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Authors:

Paper Title:

Abstract: Remote Sensing Images (RSI) employs various Feature Extraction Techniques (FET) that implement different algorithms to extract features from a query image. In this paper, we provide a critical and comprehensive survey on algorithms implemented by different FET, their parameter selection strategies and performance. The survey is divided into three parts where initially three FET are selected and the algorithms they implement are analysed. Secondly, their parameter selection strategies are surveyed and finally a critical analysis on performance based on literature results obtained is provided with some concluding remarks.

Keywords: Remote Sensing, Feature Extraction, Convolution Mask, Mahalanobis Distance, Gaussian Envelope, Frequency Harmonic.

References:

[1] Henrique Momm and Greg Easson, Feature Extraction from High-Resolution Remotely Sensed Imagery using Evolutionary Computation. Mississippi, USA: Prof. Eisuke Kita, 2011.
[2] J.G Daugman, “Uncertainty relations for resolution in space, spatial frequency, and orientation optimized by two-dimensional visual cortical filters,” Optical Society of America, vol. 2, pp. 1160-1169, 1985.
[3] P Moreno, A Benardino, and J Santos-Victor, “Gabor Parameter Selection for Local Feature Detection,” in IBPRIA 2nd Iberian Conference on Pattern Recogniton and Image Image Analysis, Portugal, 2005.
[4] J Yang, L Liu, T Jiang, and Y Fan, “A modified Gabor Filter Design Method for Fingerprint Image Enhancement,” Pattern Recognition Letters, no. 24, pp. 1805 – 1817, January 2003.
[5] S Fejes and F Vaida, “Simplified Adaptive Approach To Efficient Morphological Image Analysis,” 2004.
[6] E Saffor and A Salama, “Objective Evaluation of Mathematical Mophology Edge Detection on Computed Tomography (CT) Images,” International Journal of Medical Science and Engineering, vol. 7, no. 9, pp. 631 – 635, 2013.
[7] D Ze-Feng, Y Zhou-Ping, and X You-Lun, “High Probability Impulse Noise-Removing Algorithm Based on Mathematical Morphology,” IEEE Signal Processing Letters, vol. 14, no. 1, pp. 31-34, January 2007.
[8] G Joseph, Fundamentals of Remote Sensing, 2nd edition. India: Universities press private Ltd., 2005.
[9] M.S Moran, Y Inoue, and Barnes E.M, “Opportunities and Limitations for image-based Remote Sensing in Precision Crop Management.,” Remote Sensing environment, vol. 61, pp. 319 – 346, January 1997.
[10] Pesaresi, Kolbeinn A Benediktsson J.A, “Classification and Feature Extraction for Remote Sensing Images from Urban Based on Morphological Transformations,” IEEE Transactions on Geo-Science and Remote Sensing, vol. 41, no. 9, September 2003.
[11] Lee C., “Feature Extraction Based on Decision Bounderies,” IEEE Trans. Pattern Anal. Machine Intell, vol. 15, pp. 388-400, April 1993.
[12] Suruliandi A. Jeyabharathi D., “Perfomance Analysis of Feature Extraction and Classification Techniques in CBIR,” International Conference on Circuits, Power and Computing Technologies, pp. 1211 – 1214, 2013.
[13] Mehta K., Arora S. Basal A., “Face Recognition using PCA and LDA Algorithms ,” Advancded Computing and Communication Technologies (ACCT), Jan 2012.

140-144

28.

Authors:

Paper Title:

Abstract: The microwave as well as the small signal noise properties on a one dimensional n+npp+ DDR structure 4H-SiC IMPATT Diode have been studied using advanced computer simulation program developed by us and compared at different frequency of Ka band by taking the area of the diode as . Also the theory for the diode current noise associated with the electron hole pair generation and recombination in the space charge region of the diode is presented. This paper can help to know about the small signal behavior as well as noise behavior of IMPATT diode along with power density at the Ka band and will be helpful for designing the 4H-SiC based IMPATT diode depending upon the microwave applications.

Keywords: Impact ionization, efficiency, mean square noise voltage, quality factor, noise spectral density, power density, noise measure.

References:

[1] J.B. Casady and R.W. Johnson, Status of silicon carbide as a wide-bandgap semiconductor for high-temperature applications: a review Solid-State Electron., 39(10), p. 1409-1422 (1996).
[2] P.G. Neudeck, Progress in silicon carbide semiconductor electronics technology, J. Electron. Mater., 24 (4), p. 283-288 (1995).
[3] Joydeep Sengupta, Dr. Monojit Mitra “Comparison of Performance of Impatt Diode for Various Materials” IJSER Vol 4,Issue 6, June 2013 Edition (2229-5518).
[4] H. Eisele and G. I. Haddad, “Active Microwave Devices in Modern Semiconductor Devices Physics”, S. M. Sze , Ed. New York: Wiley, 1998, pp. 343–407.
[5] D.N.Datta,S.P.Pati,J.P.Banerjee,B.B.Pal and S.K.Roy,”Computer Analysis of DC Field and Current density profiles of DAR Impatt Diode”,IEEE Trans. on Electron Devices ,Vol.ED-29,No.11,Nov.1982.
[6] S. K. Roy, M. Sridharan, R. Ghosh, and B. B. Pal, “Computer method for the dc field and carrier current profiles in the IMPATT device starting from the field extremum in the depletion layer” Proceedings of the 1st Conference on Numerical Analysis of Semiconductor Devices (NASECODE I), J. H. Miller, Ed., Dublin, Ireland, 266-274 (1979).
[7] S.M Sze and R.M Ryder, “Microwave Avalanche Diodes”,Proceedings of the IEEE, Volume: 59, PP: 1140,1971.
[8] Hermann K. Gummel and J.L Blue, “A small-signal theory of avalanche noise in IMPATT diodes”,IEEE Transaction. Electron Devices, Volume: 14, PP: 569, 1967.
[9] Mukherjee M, Roy S K “Wide band gap III-IV nitride based avalanche transit time diode in terahertz regime: studies on the effects on punch through on high frequency characteristics and series resistance of the device”Current Applied Physics 10(2010) 646-651.
[10] Eisele H and Haddad G I,” Active microwave Devices Microwave Semiconductor Device Physics” S M Sze (New York) p 343, ed:1997.
[11] S.M.Sze,”Physics of Semiconductor Devices”,1969,John Wiley and sons.
[12] J.K.Mishra, G.N.Dash, S.R.Pattanaik, I.P.Mishra,”Computer Simulation Study on the noise and millimeter wave properties of InP/GaInAs hetero junction double avalanche region IMPATT didoe”, Solid-state electronics,vol-48.pp:401-408,2004.
[13] G.N.Dash,J.K.Mishra and A.K.Panda,”Noise in mixed tunneling Avalanche transit time (MITATT) diodes”,Solid-state electronics,vol-39(10),pp:1473-1479,Jan-1996.
[14] A.K. Panda, D. Pavlidis, and E. Alekseev, Noise characteristics of GaN-based IMPATTs,IEEE Trans. Electron Devices, 48, p. 1473-1475,2001.
[15] A. Reklaitis and L. Reggiani, Monte Carlo investigation of current voltage and avalanche noise in GaN double-drift impact diodes , J. Appl. Phys., 97, 043709 (2005).
[16] J.K.Mishra, A.K.Panda, and G.N.Dash,”An Extremely low noise hetero junction IMPATT”, IEEE Trans. on Electron Devices ,Vol.ED-44,No.12,Dec.1997.
[17] T.Misawa,”IMPATT diodes”, in semiconductor and semimetals, vol.7,Newyork,Academic Press.1971,partB.

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29.

Authors:

Paper Title:

Abstract: Automatic Speech recognition and conversion of speech to text is a work which has proved its importance for decades. A lot of work has already been done in this contrast. This paper focuses on the Punjabi speech and the conversion of speech to text using advanced system voice recognition pattern. This paper also focuses on the optimization of the EEMD process by combining EEMD process with the Neural Network. Neural Network has been found to be friendly in the contrast of compounding different algorithms to it and it produces significant results. This paper also focuses on the future works to be considered in the same field.

Keywords: ASR, EEMD, Neural Network, Acoustical Models, Neural Identifier, Data Acquisition.

References:

[1] Preeti Saini, “Automatic Speech Recognition”, A Review International Journal of Engineering Trends and Technology- Volume4Issue2- 2013.
[2] WiqasGhai, “Literature Review on Automatic Speech Recognition”, International Journal of Computer Applications (0975 – 8887)Volume 41– No.8, March 2012.
[3] Yuqiang Qin,“EEMD-Based Speaker Automatic Emotional Recognition,” Chinese Mandarin Appl. Math.Inf. Sci. 8, No. 2, 617-624 (2013).
[4] Akshay S. Utane, “Emotion Recognition through Speech Using Gaussian Mixture Model and Support Vector Machine “, International Journal of Scientific & Engineering Research, Volume 4, Issue 5, May-2013.
[5] Shing-Tai Pan, “Robust Speech Recognition by DEEMD with A Codebook Trained by Genetic Algorithm”, Journal of Information Hiding and Multimedia Signal Processing, October 2012.
[6] Wu, S., Falk, “Automatic recognition of speech emotion using long-term spectro-temporal features,” Proc. Internat. Conf. on Digital Signal Processing, 1-6 (2009).
[7] Geoffrey Hinton, Li Deng, “Neural Networks for Acoustic Modeling in Speech Recognition”.
[8] H. Hermansky, D. P. W. Ellis, “Tandem connectionist feature extraction for conventional EEMD systems,” Proceedings of ICASSP, Los Alamitos, CA, USA, 2000, vol. 3, pp. 1635–1638, IEEE Computer Society.
[9] H. Bourlard, N. Morgan, “Connectionist Speech Recognition: A Hybrid Approach”, Kluwer Academic Publishers, Norwell, MA, USA, 1993.
[10] L. Deng, “Computational models for speech production,” in Computational Models of Speech Pattern Processing, pp. 199–213. Springer- Verlag, New York, 1999.
[11] L. Deng, “Switching dynamic system models for speech articulation and acoustics,” in Mathematical Foundations of Speech and Language Processing, pp. 115–134. Springer-Verlag, New York, 2003.
[12] A. Mohamed, G. Dahl, and G. Hinton, “Deep belief networks for phone recognition,” in NIPS Workshop on Deep Learning for Speech Recognition and Related Applications, 2009.
[13] A. Mohamed, G. Dahl, “Acoustic modeling using deep belief networks,” IEEE Transactions on Audio, Speech, and Language Processing,, vol. 20, no. 1, pp. 14–22, jan. 2012.
[14] D. E. Rumelhart, G. E. Hinton, “Learning representations by back-propagating errors,” Nature, vol. 323, no. 6088, pp. 533–536, 1986.
[15] X. Glorot and Y. Bengio, “Understanding the difficulty of training deep feedforward neural networks,” in Proceedings of AISTATS, 2010, pp. 249–256.
[16] D. C. Ciresan, U. Meier, “Deep, Big, Simple Neural Nets for Handwritten Digit Recognition,” Neural Computation, vol. 22, pp. 3207–3220, 2010.
[17] G. E. Hinton , R. Salakhutdinov, “Reducing the dimensionality of data with neural networks,” Science, vol. 313, no. 5786, pp. 504–507, 2006.
[18] H. Larochelle, D. Erhan, “An empirical evaluation of deep architectures on problems with many factors of variation,” in Proceedings of the 24th international conference on Machine learning, 2007, pp. 473–480.
[19] J. Pearl, “Probabilistic Inference in Intelligent Systems: Networks of Plausible Inference”, Morgan Kaufmann, 1988.
[20] G. E. Hinton, “Training products of experts by minimizing contrastive divergence,” Neural Computation, vol. 14, pp. 1771–1800, 2002.
[21] G. E. Hinton, “A practical guide to training restricted boltzmann machines,” Tech. Rep. UTML TR 2010-003, Department of Computer Science, University of Toronto, 2010.

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Authors:

Paper Title:

Abstract: Orthogonal Frequency Division Multiplexing (OFDM) has been currently under intense research for broadband wireless transmission due to its robustness against multipath fading. However OFDM signals have a problem with high Peak-to-Average power ratio (PAPR) and thus, a power amplifier must be carefully manufactured to have a linear input-output characteristic or to have a large input power back-off. The drawbacks of high peak to average power ratio (PAPR) can outweigh all the potential benefits of Orthogonal Frequency Division Multiplexing (OFDM) signals. In this Paper, a sophisticated PAPR reduction technique, named Iterative Clipping and filtering (ICF) is proposed for OFDM system. By considering the example of OFDM, with Quadrature Phase-Shift Keying (QPSK) mapping, simulation results under Matlab environment show that the proposed method performs well in reducing PAPR..

Keywords: OFDM, High Peak to Average Power Ratio, Iterative Clipping and Filtering.

References:

1. Z. Cheng, D. Dahlhaus: Time versus Frequecy Domain Channel Estimation for OFDM Systems with Antenna Arrays, Proc. of the 6th International Conference on Signal Processing, ICSP’02, vol. 2, pp 1340-1343, Aug. 2002
2. Jeffrey G. Andrews, Ph.D., Arunabha Ghosh, Ph.D,Rias Muhamed., ed, Fundamentals of WiMAX Understanding Broadband Wireless Networking. Theodore S. Rappaport, Series Editor, ed. P.H.C.E.a.E.T. Series. 2007
3. Y.-J. Wang, W. Chen. A PAPR Reduction Method Based on Artificial Bee Colony Algorithm for OFDM Signals. IEEE Trans. Wireless Commun.; vol. 9, no. 10, pp. 2994-2999, Oct. 2010.
4. L. J. Cimini Jr. and N. R. Sollenberger. Peak-to-average power ratio reduction of an OFDM signal using partial transmit sequences. IEEE Comm. Lett.; vol. 4, no. 3, pp. 86-88, Mar. 2000.
5. Physical Channels and Modulation (Release 9); 3GPP TS 36.211 v9.1.0, 3rd Generation Partnership Project; Technical Specification Group Radio Access Network; Evolved Universal Terrestrial Radio Access (E-UTRA); 2010.
6. T.Jiang, W.Xiang, P.C.Richardson, J.Guo, and G. Zhu, “PAPR Reduction of OFD Signals Using Partial Transmit Sequences with Low Computational Complexity,” IEE Transactions on Broadcasting, Vol.53, No.3, September 2007, pp.719-724.
7. C.-P. Li, S.-H. Wang, and C.-L. Wang. Novel Low-Complexity SLM Schemes for PAPR Reduction in OFDM Systems. IEEE Trans. Signal Processing; vol. 58, no. 5, pp. 2916-0921, May. 2010.
8. Y.-C. Wang and Z.-Q. Luo. Optimized Iterative Clipping and Filtering for PAPR Reduction of OFDM Signals. IEEE Trans. Commun.; vol. 59, no. 1, pp. 33-37, Jan. 2011.
9. X. Zhu, G. Zhu, and T. Jiang. Reducing the peak-to-average powerra- dio using unitary matrix. IET Commun.; vol. 2, no. 2, pp. 161-171, 2009.
10. D.Guel and J.Palicot, “FFT/IFFT Pair based Digital Filtering for the Transformation of Adding Signal PAPR Reduction Techniques in Tone Reservation Techniques,” Fifth International Conference on Wireless and Mobile communications, (ICWMC 2009), August 2009.
11. Y.Wu and W. Y. Zou, “Orthogonal frequency division multiplexing: A multi-carrier modulation scheme,” IEEE Trans. Consumer Electronics, vol. 41, no. 3, pp. 392–399, Aug. 1995.
12. J. Tellado, “Peak to Average Power Ratio Reduction for Multicarrier Modulation,” PhD thesis, University of Stanford, Stanford, 1999.

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Authors:

Paper Title:

Abstract: Mostly, testing techniques are designed for data which are having low dimensional space and less intention is paid to the testing of high dimensional data. In this paper, data undergoes a process of dimensionality reduction by principal component analysis (PCA) which leads to the automate subspace clustering of data. The combination of distributed based approach and coverage based approach is used to test the test cases sampled from each cluster formed. The contribution of this paper is related to the dimensionality reduction as well as test case suite reduction by discovering patterns in software testing in a rigorous manner.

Keywords: Dimensionality reduction using PCA, clustering, the test suite minimization.

References:

[1] Mark Shtern and Vassilios Tzerpos,” Clustering Methodologies for Software Engineering ”in Hindawi Publishing Corporation Advances in Software Engineering ,Volume 2012, Article ID 792024, 18 pages, doi:10.1155/2012/792024.
[2] Rakesh Agrawal, Johannes Gehrke, Dimitrios Gunopulos, Prabhakar Raghavan,” Automatic Subspace Clustering Of High Dimensional Data, ”in Data Mining and Knowledge Discovery, 11, 5–33, 2005, Springer Science ,Inc. Manufactured in The Netherlands.
[3] Lilly Raamesh, Lilly Raamesh,” An Efficient Reduction Method for Test Cases,”in International Journal of Engineering Science and Technology”,Vol. 2(11), 2010, 6611-6616.
[4] Mamta Santosh,Rajvir Singh,”Test Case Minimization By Generating Requirement Based Mathematical Equations,”in International Journal of Engineering Research & Technology (IJERT), Vol. 2 Issue 6, June – 2013
[5] Rajvir Singh and Mamta Santosh,” Test Case Minimization Techniques : A Review,” in International Journal of Engineering Research & Technology (IJERT), Vol. 2 Issue 12, December – 2013.
[6] Saeed Parsa and Alireza Khalilian,” A Bi-objective Model Inspired Greedy Algorithm for Test Suite Minimization,” FGIT ’09 Proceedings of the 1st International Conference on Future Generation Information Technology,2009.
[7] Saeed Parsa and Alireza Khalilian,” On the Optimization Approach towards Test Suite Minimization,” in International Journal of Software Engineering and Its Applications,Vol. 4, No. 1, January 2010.
[8] Shin Yoo & Mark Harman,” TR-09-09: Regression Testing Minimisation, Selection and Prioritisation – A Survey,” in Technical report TR-09-09, Department of Computer Science, King’s College London, 2009.
[9] Mary Jean Harrold ,Rajiv Gupta And Mary Lou Soffa,” A Methodology for Controlling the Size of aTest Suite,” 1993 ACM 1049 -331X/93 /’O7OO-O27O $01.50 Julv 1993, Pages 270–285.
[10] Alireza Khalilian and Saeed Parsa,” Bi-criteria Test Suite Reduction by Cluster Analysis of Execution Profiles,” in International Federation for Information Processing, 2012, CEE-SET 2009, LNCS 7054, pp. 243–256, 2012.
[11] Tajunisha1 and Saravanan “An efficient method to improve the clustering performance for high dimensional data by Principal Component Analysis and modified K-means,”in International Journal of Database Management Systems ( IJDMS ), Vol.3, No.1, February 2011.
[12] Imola K. Fodor “A survey of dimension reduction techniques” UCRL-ID-148494, May 9, 2002.
[13] Siripong Roongruangsuwan, jirapun Daengdej,” Test Case Prioritization Techniques” in Journal of Theoretical and Applied Information Technology,© 2005 – 2010 JATIT & LLS.
[14] Book: An Introduction to Neural Networks, Simon Haykin, Prentice Hall, 1999.

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Authors:

Paper Title:

Abstract: Graphical authentication is more efficient and more securable. An important usability goal for knowledge based authentication systems is to support user in selecting passwords for higher security in the sense of being from an expanded effective security space. Here we are using x and y coordinates to choose a picture password. Additionally the pictures in x and y coordinates are changing randomly and hence it is difficult to find the original picture. In our base paper the approaches used are “Persuasive cued click points”,” Cued click points” and “Pass points”. Main tools used here are pccp, viewport and that is used for password creation. Viewport approaches are used to memorable user chosen password and secure system generated random password that are difficult to remember. The pccp creating a less guessable password is the easiest course of action. In order to avoid “Shoulder surfing” algorithm we are going for AES (Advanced encryption standard).

Keywords: Authentication, Security, Graphical Passwords, Knowledge-based.

References:

[1] S. Chiasson, P. van Oorschot, and R. iddle, “Graphical Password Authentication Using Cued Click Points,” Proc. European Symp. Research in Computer Security (ESORICS), pp. 359-374, Sept. 2007
[2] L. O’Gorman, “Comparing Passwords, Tokens, and Biometrics for User Authentication,” Proc. IEEE, vol. 91, no. 12, pp. 2019-2020, Dec. 2003.
[3] S. Wiedenbeck, J. Waters, J. Birget, A.Brodskiy, and N. Memon, “Pass Points: Design and Longitudinal Evaluation of a Graphical Password System,” Int’l J. Human-Computer Studies, vol. 63, nos. 1/2, pp. 102-127, 2005.
[4] S. Wiedenbeck, J. Waters, J. Birget, A. Brodskiy, and N. Memon, “Authentication Using Graphical Passwords: Effects of Tolerance and Image Choice,” Proc. First Symp. Usable Privacy and Security (SOUPS), July 2005.
[5] P.C. van Oorschot, A. Salehi-Abari, and J. Thorpe, “Purely Automated Attacks on PassPoints-Style Graphical Passwords,” IEEE Trans. Information Forensics and Security, vol. 5, no. 3, pp. 393- 405, Sept. 2010.
[6] S. Chiasson, E. Stobert, A. Forget, R. Biddle, and P. van Oorschot, “Persuasive Cued Click-Points: Design, Implementation, and Evaluation of a Knowledge-Based Authentication Mechanism,” Technical Report TR-11-03, School of Computer Science, Carleton Univ., Feb. 2011.
[7] A. Forget, S. Chiasson, and R. Biddle, “Shoulder-Surfing Resistance with Eye-Gaze Entry in Click-Based Graphical Passwords,” Proc. ACM SIGCHI Conf. Human Factors in Computing Systems (CHI), 2010.
[8] B. Pinkas and T. Sander, “Securing Passwords against Dictionary Attacks,” Proc. Ninth ACM Conf. Computer and Comm. Security (CCS), Nov. 2002.
[9] Alireza Pirayesh Sabzevar and Angelos Stavrou, “Universal Multi-Factor Authentication Using Graphical Passwords,” in IEEE International Conference on Signal Image Technology and Internet Based Systems, 2008.
[10] Ahmad Almulhem, “A Graphical Password Authentication System,” in 978-0-9564263-7/6/$25.00 IEEE, 2011
[11] S. Man, D. Hong, and M. Mathews, “A shoulder-surfing resistant graphical password scheme,” in Proceedings of International conference on security and management. Las Vegas, NV, 2003
[12] Birget, J.C., D. Hong, And N. Memon, “Graphical Passwords Based On Robust Discretization” IEEE Trans. Info. Forensics And Security, 1(3), September 2006.
[13] Thorpe, J. and P.C. van Oorschot. Human-Seeded Attacks and Exploiting HotSpots in Graphical Passwords. 16th USENIX Security Symposium, 2007.
[14] Zhi Li, Qibin Sun, Yong Lian, and D. D. Giusto, 2005, „An Association-Based Graphical Password Design Resistant to Shoulder Surfing Attack‟, IEEE International Conference on Multimedia and Expo (ICME).

163-165

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Paper Title:

Abstract: The alpha-ketoglutarate dehydrogenase complex (KGDHC) is elemental in mitochondria, and its deficiency is associated with a number of neurological disorders like Alzheimer’s disease, Parkinson’s disease and Dihydrolipoamide dehydrogenase deficiency (DLDD). The molecular mechanisms underlying the age dependent loss of brain KGDHC activity remain incomprehensible. In order to disentangle this phenomenon, a kinetic model is developed representing correlations between three aspects namely the reduced AKGDHC activity; mitochondrial ATP generation and increased pyruvate concentration. The kinetic model centralizes on the mitochondrial-derived ATP production and is distributed into cytosol and mitochondria. The model revealed a decline in ATP production with lowered enzyme concentration. With the effect, the concentration of pyruvate was increased resulting in its excretion which is a characteristic feature of DLDD. In agreement with the previous literature the model simulations confirmed the decline in reaction fluxes and NADH level. The finding suggests that reduction of pyruvate is the rate limiting step of the TCAC which is supported by past bibliographic findings. Since ATP production is also affected by NADH production rate hence it can be safely assumed that decrease in NADH also causes Change in ATP production rate. Change in pyruvate concentration on changing the concentration of AKGDH also underpins the importance of the studied enzyme in DLDD. It is clearly indicated by simulations that AKGDH deficiency can cause increase in pyruvate concentration.

Keywords: Alpha-Ketoglutarate Dehydrogenase Complex, Dihydrolipoamide Dehydrogenase Deficiency, Kinetic Model

References:

[1] Reddy PH (2007) Mitochondrial dysfunction in aging and Alzheimer’s disease: strategies to protect neurons. Antioxid Redox Signal, 9: 1647–58.
[2] Blass JP, Brown AM. Lower activity of Krebs cycle enzymes than of electron transport in human brain: disease implications. Neurobiol. Aging. 2000;21 Suppl:81.
[3] Chinopoulos C, Adam-Vizi V. (2006) Calcium, mitochondria and oxidative stress in neuronal pathology. Novel aspects of an enduring theme. FEBS J, 273: 433–450
[4] Cooney GJ, Taegtmeyer H, Newsholme EA. (1981) Tricarboxylic acid cycle flux and enzyme activities in the isolated working rat heart. Biochem J, 200: 701–703.
[5] Felipe A. Beltrán, Aníbal I. Acuña, María Paz Miró and Maite A. Castro (2012). Brain Energy Metabolism in Health and Disease, Neuroscience – Dealing With Frontiers, Dr. Carlos M. Contreras (Ed.), ISBN: 978-953-51-0207-6, InTech.
[6] Gancedo C and Serrano R. (1989) Energy-yielding metabolism, pp. 205–209 in The Yeasts, Vol. 3, Ed. 2, edited by A. H. Rose and J. S. Harrison. Academic Press, San Diego.
[7] Gibson GE, Starkov A, Blass JP, Ratan RR, and Beal MF. (2010) Cause and Consequence: Mitochondrial Dysfunction Initiates and Propagates Neuronal Dysfunction, Neuronal Death and Behavioral Abnormalities in Age Associated Neurodegenerative Diseases. Biochim Biophys Acta, 1802(1): 122–134.
[8] Sengupta A and Saxena S. (2014) A Computational Model of Mitochondrial Beta-Oxidation Highlighting the Implications on Uremia Disease in Human. IJSCE, Vol. 3, No.6: 188-192.
[9] Kim Y, Kim Y, Hwang O and Kim DJ. (2012) Pathology of Neurodegenerative Diseases, Brain Damage – Bridging Between Basic Research and Clinics, Dr. Alina Gonzalez-Quevedo (Ed.), ISBN: 978-953-51-0375-2
[10] Lai JC, Walsh JM, Dennis SC & Clark JB. (1977) Synaptic and non-synaptic mitochondria from rat brain: isolation and characterization. J. Neurochem, 28: 625–631.
[11] Lyubarev AE, Kurganov BI. Supramolecular organization of tricarboxylic acid cycle enzymes.Biosystems. 1989;22:91–102. [PubMed]
[12] Mazziotta JC, Phelps ME, Pahl JJ, Huang SC, Baxter LR, Riege WH, Hoffman JM, Kuhl DE, Lanto AB, Wapenski JA. (1987) Reduced cerebral glucose metabolism in asymptomatic subjects at risk for Huntington’s disease. N Engl J Med, 12; 316(7): 357-62
[13] Mclain AL, Szweda PA, and Szweda LI. (2011) α-Ketoglutarate dehydrogenase: AN mitochondrial redox sensor. Free Radic Res, 45(1): 29–36.
[14] Moreno-Sanchez R, Hogue BA, Hansford RG. (1990) Influence of NAD-linked dehydrogenase activity on flux through oxidative phosphorylation. Biochem J, 268: 421–428.
[15] Navarro A and Boveris A. (2009) Brain mitochondrial dysfunction and oxidative damage in
[16] Nunomura A, Perry G, Aliev G, Hirai K, Takeda A, Balraj EK, et al., (2001) Oxidative damage is the earliest event in Alzheimer disease. J Neuropathol Exp Neurol, 60(8): 759–767.
[17] Parkinson’s disease. J Bioenerg Biomemb, 41(6): 517-21.
[18] Sandstrom PA, Tebbey PW, Van Cleave S, Buttke TM. (1994) Lipid hydroperoxides induce apoptosis in T cells displaying a HIV-associated glutathione peroxidase deficiency. J Biol Chem, 269(2): 798–801.
[19] Santa-Cruz LD, Ramírez-Jarquín UN and Tapia R. (2012) Role of Mitochondrial Dysfunction in Motor Neuron Degeneration in ALS, Amyotrophic Lateral Sclerosis, Prof. Martin Maurer (Ed.), ISBN: 978-953-307-806-9
[20] Schapira, A. H. (2008). Mitochondrial dysfunction in neurodegenerative diseases. Neurochem Res, 33(12): 2502-2509
[21] Shi Q, Xu H, Yu H, Zhang N, Ye Y, et al., (2011) Inactivation and reactivation of the mitochondrial α-ketoglutarate dehydrogenase complex. J Biol Chem, 286: 17640–17648.
[22] Shimohama S. (2000) Apoptosis in Alzheimer’s disease–an update. Apoptosis, 5(1):9-16.
[23] Sundaram S, Tripathi A and Gupta DK. (2010) Metabolic modeling of Rosmarinic acid biosynthetic pathway. Bioinformation, 5: 168-172.
[24] Tretter L, Adam-Vizi V. (2000) Inhibition of Krebs cycle enzymes by hydrogen peroxide: a key role of [alpha]-ketoglutarate dehydrogenase in limiting NADH production under oxidative stress. J Neurosci, 20: 8972–8979.
[25] Tretter L, Adam-Vizi V. (2005) Alpha-ketoglutarate dehydrogenase: a target and generator of oxidative stress. Phil. Trans. R. Soc. B, 360: 2335–2345
[26] Turrens JF, Alexandre A and Lehninger AL. (1985) Ubisemiquinone is the electron donor for superoxide formation by complex III of heart mitochondria. Archives of biochemistry and biophysics, Vol.237, No.2: 408-414.

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Authors:

Paper Title:

Abstract: The problem of underutilization of spectrum may be solved by allowing the Secondary Users (SU) to use the spectrum allocated to the Primary Users(PU) (license holder of a spectrum band) when they are not using it, without causing any harmful interference to the PUs. Cognitive Radio (CR) technology promises to solve the problem of spectrum underutilization and spectrum crowding. The cognitive users employ their cognitive abilities, to adaptively change the radio parameters as per the radio environment, to communicate, without harming the primary users. In this paper Cyclostationary Feature Detection method has been taken as the detection method as it not only can detect the signal under low SNR but can also detect different features of the signal such as modulation type, carrier frequencies etc.. Energy Detection or radio meter can only detect presence or absence of the primary signal whereas a Matched Filter system requires extensive knowledge about the channel and the signals that are to be identified. The signals exhibiting cyclostationarity includes Spectral Correlation Function which is a data analysis algorithm that measures how the properties of a spectra varies, position to position, in a two dimensional spectral line map . We have proposed an adaptive sensing mechanism for an effective and efficient detection of spectrum hole. The signal SNR is determined in the first phase and appropriate sensing technique is adopted by the system based on the SNR level in the second phase confirming the radio parameters for CR.

Keywords: Cycle Frequency, Cyclic Autocorrelation Function, Cyclostationarity, Spectral Correlation Function, Spectrum Sensing.

References:

[1] FCC, B Spectrum Policy Task Force, ET Docket 02-135, Nov. 2002.
[2] M. McHenry, E. Livsics, T. Nguyen, and N. Majumdar, BXG dynamic spectrum access field test results, IEEE Commun. Mag.,vol. 45, pp. 51–57, Jun. 2007.
[3] J. Mitola and G. Q. Maguire, “Cognitive radio: Making software radios more personal,” IEEE Pers. Commun. , vol. 6, Aug. 1999, pp. 13–18.
[4] S. Haykin, “Cognitive radio: brain-empowered wireless communications,” IEEE J. Select. Areas Commun., vol. 23, Feb. 2005, pp. 201-220.
[5] Paul D. Sutton. “Cyclostationary signature inpractical cognitive radio application”. IEEE journalon Selected Areas In Communications, VOL. 26, NO.1, January 2008.
[6] J. Mitola III, “Cognitive radio an integrated agent architecture for software defined radio”, KTH Royal Institute of Technology, Stockholm, Sweden, 2000.
[7] Qiwei Zhang, Andre B.J. Kokkeler and Gerard J.M.Smit, “A reconfigurable radio architecture for cognitive radio in emergency network”, Proceedings of 9th European Conference on Wireless Technology.
[8] K. Kim, I.A. Akbar, K. K. Bae, J. S. Um, C. M. Spooner, and J. H. Reed, “Cyclostationary approaches to signal detection and classification in cognitive radio,” in Proc. IEEE DySpan, 2007, pp. 212–215.
[9] W. A. Gardner, Statistical Spectral Analysis: A Non probabilistic Theory. Englewood Cliffs, NJ: Prentice-Hall, 1988.
[10] G. K. Yeung and W. A. Gardner, “Search efficient methods of detection of cyclostationary signals,” IEEE Trans. Signal Processing , vol. 44, no. 5, pp. 1214–1223, May 1996.
[11] Paul D. Sutton. “Cyclostationary signature inpractical cognitive radio application”. IEEE journalon Selected Areas In Communications, VOL. 26, NO.1, January 2008
[12] William A. Gardner, “Spectral Correlation of Modulated Signals-Part-I-Digital Modulation”, IEEETrans. on Commun. ,Vol.35,no.6, pp-595-601.
[13] ArtemT kachenko, DanijelaCabric, and Robert W.Brodersen, “Cyclostationary Feature Detector Experiments using Reconfigurable BEE2”, in 2ndIEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks ,2007
[14] Dong-Chan Oh and Yong-Hwan Lee, “Energy detection based spectrum sensing for sensing error minimization in Cognitive Radio networks” International journal of Communication Networks and Information Security, vol. 1, no. 1, April 2009.
[15] W. M. Gardner, “Measurement of Spectral Correlation,” IEEE Trans. Acoustics, Speech, and Signal Processing, vol. ASSP-34, No. 5, Oct. 1986.

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Authors:

Paper Title:

Abstract: The web application security has currently become a very significant area of scholarship, the best way to deal with it is to use web application security scanner to discover the architectural weaknesses and vulnerabilities in the web application. The goal of this paper is to use The Web Application Security Scanner Evaluation Criteria (WASSEC) to compare and contrast the Commercial Web Application Security Scanners, and show the differences between them. We used six factors to do this compression (Protocol Support, Authentication, Session Management, Crawling, Parsing and Testing). The study shows that Acunetix WVS, Ammonite and Burp Suite Professional are the most suitable ones because they have 0.831325, 0.771084 and 0.73494 averages respectively. As the result of this study and depend on the information about the Commercial Web Application Security Scanner we collected; the Acunetix WVS, Burp Suite Professional and Ammonite are the best respectively. So the web developer or administrator can use them together or choose one.

Keywords: Web Application Security Scanner, WASSEC, Evaluation.

References:

[1] Jan-Min Chen and Chia-Lun Wu, “An Automated Vulnerability Scanner for Injection Attack Based on Injection Point”, Proceedings of the 2010 IEEE Symposium on Security and Privacy, 2010, pp.
[2] J. Bau, E. Bursztein, D. Gupta, and J. Mitchell, “State of the Art: Automated Black-Box Web Application Vulnerability Testing”, Proceedings of the 2010 IEEE Symposium on Security and Privacy, 2010, pp.332-345.
[3] WASSEC project, Web Application Security Consortium (http://www.webappsec.org).
[4] http://en.wikipedia.org/wiki/Information_security
[5] http://en.wikipedia.org/wiki/Web_application_security.
[6] Y.-W Huang, F. Yu, C. Huang, C.-H.Tsai, D.-T.Lee, and S.-Y Kuo, “Securing Web Application code by static analysis and runtime protection”, Proc. 13th Int. Conf. on World Wide Web (WWW’04), NY, USA. ACM, pp. 40-52.
[7] V.B. Livshits and M. S. Lam, “Finding security errors in Java program with static analysis”, Proc. 14th Usenix Security Symposium, Baltimore, MD, USA, 2005.
[8] N. Jovanovic, C. Kruegel, and E. Kirda, “Static analysis for detecting taint-style vulnerabilities in web applications”, Journal of Computer Security, 18 (2010), pp. 861-907.
[9] Y. Xie, A. Aiken, “Static detection of vulnerabilities in scripting languages”, Proc. 15th USENIX Security Symposium, 2006, pp. 179-192
[10] G. Wassermann and Z. Su, “Sound and precise analysis of web applications for injection vulnerabilities”, SIGPLAN Notices, vol 42, n06, 2007, pp.32-41.
[11] M. S. Lam, M. Martin, B. Livshits, and J. Whaley, “Securing Web Applications with static and dynamic information flow tracking”, Proc . of the 2008 ACM SIGPLAN Symposium on Partial evaluation and semantics based program manipulation (PEPM’08), New York, NY, USA : ACM, 2008, pp. 3-12.
[12] T. Pietraszek, C.V. Berghe, “Defending against injection attacks through context sensitive string evaluation”, Recent Advances in Intrusion Detection (RAID-2005), Seattle, WA, USA, 2005.
[13] C. Kruegel, G. Vigna, “Anomaly Detection of Web-based Attacks”, Proc. of the 10th ACM Conference on Computer and Communication Security (CCS’03, October 2003), pp. 251-261.
[14] E. Kirda, C. Kruegel, G. Vigna, and N. Jovanovic, “Noxes: A client-side solution for mitigating cross-side scripting attacks”, 21st ACM Symposium on Applied Computing (SAC2006), Dijon, France, 2006.
[15] K.Stefan, E. Kirda, C. Kruegel and N. Jovanovic,“SecuBat: a web vulnerability scanner”, Proc. of the 15th int. conf. on World Wide Web (WWW ’06), Edinburgh, Scotland, 2006.
[16] Zoran Djuric, ”A Black-box Testing Tool for Detecting SQL Injection Vulnerabilities”, Proceedings of the 2010 IEEE Symposium on Security and Privacy, 2010, pp.216-221.
[17] A. Doup´e, M. Cova, and G. Vigna, “Why Johnny Can’t Pentest: An Analysis of Black-box Web Vulnerability Scanners”, July 2010
[18] J. Fonseca, M. Vieira, and H. Madeira, “Testing and Comparing Web Vulnerability Scanning Tools for SQL Injection and XSS Attacks”, prdc, 13th Pacific Rim International Symposium on Dependable Computing (PRDC 2007), 2007, pp.365-372
[19] Fakhreldeen Abbas Saeed, “Comparing and Evaluating Open Source E-learning Platforms”, International Journal of Soft Computing and Engineering (IJSCE), ISSN: 2231-2307, Volume-3, Issue-3, July 2013,pp.244-249.¬¬¬¬¬¬
[20] Price and Feature Comparison of Web Application Scanners (http://www.sectoolmarket.com/) Last updated: 27/08/2012.

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Authors:

Paper Title:

Abstract: Walsh sequences of the order 2k, k positive integer, form an additive group generated by Rademacher sequences set of k-order. Except the zero sequences, Walsh formed an orthogonal set of The present work allows generating orthogonal sequences with length 2k , 22k, l.2k respectively, by using Walsh sequences and theirs complements.

Keywords: Walsh sequences, Rademacher sequences, Orthogonal sequences.

References:

[1] BEAUCHAMP, K. Applications of Walsh And Related Functions. Academic
[2] WALSH, J.L. A Closed Set of Normal Orthogonal Functions. Amer. J. Math.
[3] BYRNES, J.S.; SWICK. Instant Walsh Functions. SIAM Rever., VOL. 12 1970, 131.
[4] LEE, D.S.; MILLER, L.E. CDMA Engineering Hand Book. Artech House, Boston,London, 1998. 48 – 70
[5] MAC WILLIAMS, F.J.; SLOANE N.G.A. The Theory of Error-Correcting Codes. North-Holland, Amsterdam, 1978
[6] YANG, S.C. CDMA RF System Engineering. Artech House, Boston and London, 1998. 80 – 110
[7] AL-CHEIKHA, A. Generation of Sets of Sequences Isomorphic to Walsh Sequences. Qatar Uni. Sci. J. VOL 25, 2005. 16-30
[8] YANG K, S. C.; KIM, Y.; KUMAR, P.V. Quasi-orthogonal Sequences for Codes-Division Multiple Access Systems. IEEE Trans. On Information Theory, VOL 46, 2000. 982-993

182-184

37.

Authors:

Paper Title:

Abstract: Mobility management (MM) is one of the main functions in mobile networks. It aims to track the user equipment (UEs) and to allow calls, other mobile phone services to be delivered to UEs. For any mobility protocol there are two separate problems to be solved. One is location management (or sometimes called reachability), which keeps track of the positions of a UE in the mobile network. The other one is handover management (or sometimes called session continuity), which makes it possible for a UE to continue its sessions while moving to another cell and changing its access point. This document focuses on the location management problems. Tracing UEs in a mobile network is the key task in location management. Tracking Area (TA) in LTE is a logical grouping of cells in a network. TA is almost the same concept as the Location Area (LA). In configuring TAs, a key consideration is to minimize the total amount of signaling overhead.

Keywords: LTE, Tracking Area, Paging Capacity TA list.

References:

[1] Lte – The Umts Long Term Evolution from Theory To Practice 2nd Edition by Stefania Sesia , Issam Toufik, Matthew Baker
[2] 3GPP TS 36.213 “Evolved Universal Terrestrial Radio Access (E-UTRA) Physical layer procedures”.
[3] 3GPP TS 36.221 “Evolved Universal Terrestrial Radio Access (E-UTRA); Medium Access Control (MAC) protocol specification”
[4] 3GPP TS 36.300 “Evolved Universal Terrestrial Radio Access (E-UTRA), Evolved Universal Terrestrial Radio Access Network (E-UTRAN).
[5] 3GPP TS 24.301: “Non-Access-Stratum (NAS) protocol for Evolved Packet System”.
[6] 3GPP TS 24.302: “Access to the 3GPP Evolved Packet Core (EPC) via Non-3GPP Access Networks”.
[7] 3GPP TS 36.331: “Evolved Universal Terrestrial Radio Access (E-UTRAN); Radio Resource Control (RRC) Protocol Specification”
[8] 3GPP TS 36.401: “Evolved Universal Terrestrial Radio Access Network (E-UTRAN); Architecture Description”
[9] 3GPP TS 36.413: “Evolved Universal Terrestrial Radio Access Network (E-UTRAN); S1 Application Protocol (S1AP).

185-190

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Authors:

Paper Title:

Abstract: An image and sound based authentication of a user,it means we will authenticate the users of a system by a password that they entered through a sequence of images. And also having some special sound effects associated with a password. In the previous days, Pass Point was the technique,used to give image based password.But it requires five clicks on one image.This will take more memory to store the clicks and become easy for attacker to guess. To overcome that drawback CCP technique was developed which takes a sequence of five images and one click on each image. In addition, a user has to select sound signature with respective each click on image to easily recall the password. After addition a persuasive feature to CCP, we will get PCCP,which was used to address an issue of hotspots.While creating an image based password a complete image is dimmed except viewport area.A user has to click within this viewport. This viewport area can be repositioned randomly by using shuffle button. In the proposed work, we aimed to build more interactive, user-friendly and secure email system by creating strong and difficult password to guess by attacker.

Keywords: CCP and PCCP technique, system architecture, working of proposed system.

References:

[1] S.Singh, G.Agrawal ”Integration of sound signature in graphical password authentication system” Invertis University Bareilly,India, January 2011.
[2] S. Chiasson, E. Stobert, A. Forget, R. Biddle, and P. van Oorschot, “Persuasive cued click-points: Design, implementation and evaluation of a knowledge-based authentication mechanism,” School of Computer Science, Carleton University ,Tech. Rep. TR-11-03, February 2011.
[3] Chippy.T, R.Nagendran “Defence Against Large Scale Online Password Guessing Attacks By Using Persuasive Click Points” International Journal of Communications and Engineering Volume-3, 01 March 2012.
[4] S.Chiasson,JaykumarSrinivasan, Robert Bibble, P.C. van Oorschot “Centered Discretization with Application to Graphical Passwords” Ottawa,Canada Carleton University.

191-192

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Authors:

Paper Title:

Abstract: Cloud computing, is fast growing Technology having its originations from Distributed computing technology. Cloud computing is a collaboration of different computing technologies and it has many advantages in the field of data storage, high expansibility, high reliability, virtualization, and low price service. Cloud computing has massive effects how we store and access our personal and business data. It is a matter of great concern to secure personal information and data from attacks like DDos, MIMA and data theft. And therefore it is extremely important to understand the existing security issues and risks in cloud computing. This paper analyses the above mentioned existing security issues and protection against threats in cloud computing. This paper is to quantify the need of security between networks in cloud computing, therefore minimizes the vulnerabilities.

Keywords: DDos, man in the middle attack, packet sniffing.

References:

[1] Survey of network-based defence mechanisms countering the DoS and DDoS problems.
[2] Trusted cloud computing with secure resources and data coloring 1080-7801/10/$26 2010 by IEEE.
[3] http://www.dummies.com/how-to/content/common-network-attack-strategies-packet-sniffing.html
[4] http://www.symantec.com/threatreport/topic.jsp?id=threat_activity_trends&aid=data_breaches_that_could_lead [9]. Above the Clouds: A Berkeley View of Cloud Computing”
[5] Denz and Taylor Journal of Cloud Computing: Advances, Systems and Applications 2013, 2:17http://www.journalofcloudcomputing.com/content/2/1/17
[6] CLOUD COMPUTING AND SECURITY ISSUES IN THE CLOUD International Journal of Network Security & Its Applications (IJNSA), Vol.6, No.1, January 2014

193-194

40.

Authors:

Paper Title:

Abstract: To satisfy the increasing demand for multimedia services in broadband Internet networks, the WiMAX (Worldwide Interoperability for Microwave Acces) technology has emerged as an alternative to the wired broadband access solutions. It provides an Internet connection to broadband coverage area of several kilometers in radius by ensuring a satisfactory quality of service (QoS), it’s an adequate response to some rural or inaccessible areas. Unlike DSL (Digital Subscriber Line) or other wired technology, WiMAX uses radio waves and can provide point-to-multipoint (PMP) and point-to-point (P2P) modes. In parallel, it’s observed that in the opposite of the traditional quality evaluation approaches, nowadays, current researches focus on the user perceived quality, the existing scheduling algorithms take into account the QoS and many other parameters, but not the Quality of Experience (QoE). In this paper, we present a QoE-based scheduling solution in WiMAX network in order to make the scheduling of the UGS connections based on the use of QoE metrics. Indeed, the proposed solution allows controlling the packet transmission rate so as to match with the minimum subjective rate requirements of each user. Simulation results show that by applying various levels of mean opinion score (MOS) the QoE provided to the users is improved in term of throughput, jitter, packet loss rate and delay.

Keywords: WiMAX, QoE, QoS, UGS, NS-2.

References:

[1] Z. Abichar, Y. Peng and J. Morris Chang, “WiMax: The Emergence of Wireless Broadband”, IT Professional, Vol. 8, Issue. 4, pp. 44-48, Doi:10.1109/MITP.2006.99, July-Aug. 2006.
[2] M. Alreshoodi, J. Woods, “Survey on QoE\QoS Correlation Models for Multimedia Services”, International Journal of Distributed and Parallel Systems (IJDPS) Vol.4, No.3, May 2013.
[3] T. Anouari and A. Haqiq, “Analysis of VoIP and Video Traffic over WiMAX Using Different Service Classes”, Journal of Mobile Multimedia, Vol. 9, No.3&4, pp. 230-241, 2014.
[4] A. Belghith, L. Nuaymi “Design and Implementation of a QoS-included WiMAX Module for NS-2 Simulator”, SIMUTools 2008, Marseille, France, March 3-7, 2008.
[5] P. Brooks, B. Hestnes,”User measures of quality of experience: Why being objective and quantitative is important”. IEEE Network 24(2): pp. 8–13, 2010.
[6] P. Calyam, P. Chandrasekaran, G. Trueb, N. Howes, R. Ramnath, D. Yu, Y. Liu, L. Xiong, &D. Yang, “Multi-Resolution Multimedia QoE Models for IPTV Applications”, Volume 2012, Article ID 904072, 13 pages doi:10.1155//904072, 2012.
[7] H. Du, C. Guo, Y. Liu& Y. Liu,(2009)“Research on Relationships between QoE and QoS based on BP Neural Network”, In: Proceedings of IC-NIDC, pp. 312-315, 2009.
[8] P. Frank & J. Incera, “A neural network based test bed for evaluating the quality of video streams in IP networks”, 0-7695-2569-5/06 © IEEE, Proceedings of the Electronics, Robotics and Automotive Mechanics Conference (CERMA’06), 2006.
[9] S. R. Gulliver and G. Ghinea. “The Perceptual and Attentive Impact of Delay and Jitter in Multimedia Delivery”. IEEE Transactions on Broadcasting, 53(2): pp. 449–458, June 2007.
[10] IEEE 802.16-2004, “IEEE Standard for Local and Metropolitan Area Networks Part 16: Air Interface for Fixed Broadband Wireless Access Systems”, October, 2004.
[11] IEEE standard 802. 16-2005, “IEEE standard for Local and Metropolitan Area Networks-Part16: Air Interface for Fixed and Mobile Broadband wireless Access systems Amendment 2”, February 28, 2006.
[12] ITU-T Rec. P.10/G.100, Amendment 2, “New definitions for inclusion in Recommendation ITU–T P.10/G.100,” July 2008.
[13] ITU-T Recommendation P.800,” Methods for subjective determination of transmission quality”. http://www.itu.int/, Geneva, 08/1996
[14] V. Machado, C. Oliveira , A. Marcelino, S. Carlos, N. Vijaykumar, C. Hirata, “A New Proposal to Provide Estimation of QoS and QoE over WiMAX Networks, An approach based on computational intelligence and discrete-event simulation”, 978-1-4673-0279-1©IEEE, 2011.
[15] Marc Greis, “Tutorial for Network Simulator NS”, http://www.scribd.com/doc/13072517/tutorial-NS-full-byMARC-GREIS.
[16] C. H. Muntean, “Improving learner quality of experience by content adaptation based on network conditions”, Computers in Human Behavior, 24(4), pp. 1452-1472, 2007.
[17] D. Norman and S. Draper, “User centered system design: New perspectives on human-computer interaction”. L. Erlbaum Associates, 1986.
[18] P. Rengaraju, C.H. Lung, A. Srinivasan, R.H.M. Hafez, “Qos Improvements in Mobile WiMAX Networks”, AHU J. of Engineering & Applied Sciences, Vol. 3, Issue 1, pp. 107-118, 2010.
[19] Seamless and secure mobility.
http://www.nist.gov/itl/antd/emntg/ssm_tools.cfm

195-199

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Authors:

Paper Title:

Abstract: Wireless Sensor Networks are networks of large number of tiny, battery powered sensor nodes having limited on-board storage, processing, and radio capabilities. Nodes sense and send their reports toward a processing center which is called sink or base station. Since this transmission and reception process consumes lots of energy as compare to data processing, Designing protocols and applications for such networks has to be energy aware in order to prolong the lifetime of the network. Generally, real life applications deal with Heterogeneity rather than Homogeneity. In this paper, a protocol is proposed, which is heterogeneous in energy. We first completely analyze the basic distributed clustering routing protocol LEACH (Low Energy Adaptive Clustering Hierarchy), and SPIN focused on energy consumption.

Keywords: Security Protocols, Network Security, Energy efficient, Authentication, Wireless Sensor Networks

References:

[1]. J.P. Walters, Z. Liang, W. Shi, and V. Chaudhary,“Wireless Sensor Network Security: A Survey,” TechnicalReport MIST-TR-2005-007, July, 2005.
[2]. J.P. Walters, Zh. Liang, W. Shi, V. Chaudhary, Security in Distributed, Grid, and Pervasive Computing, Chapter 17, CRC Press, 2006.
[3]. A. Perrig, R. Szewczk, J.D. Tygar, V. Wen, D.E. Culler, SPINS: Security Protocols for Sensor Networks, Wireless Networking, Vol. 8, No. 5, pp. 521-534, Sept 2002.
[4]. A. Perrig, R. Canneti, J. D. Tygar, D. Song, The TESLA Broadcast Authentication Protocol, Crypto Bytes, Vol. 5, No. 2, pp. 2-13, 2002.
[5]. D. Boyle, T. Newe, Security Protocols for use with Wireless Sensor Networks: A Survey of Security Architectures, Proceedings of the 3rd International Conference on Wireless and Mobile Communications, Guadeloupe, French Caribbean, pp. 54, 04-09 March 2007.
[6]. Sun Limin, Li Jianzhong, Chen Yu, ―Wireless Sensor Networks, Tsinghua publishing company Beijing, 2005.
[7]. Wendi Rabiner, Heinzelman, Anantha Chandrakasan, and Hari Balakrishnan, Energy-efficient Communication Protocol for Wireless MicrosensorNetworks, In: Proc. of 33rd Annual Hawaii Inter Cord on System Sciences, Hawaii, USA: IEEE Computer Society, 2000.
[8]. Li Han, LEACH-HPR: An Energy Efficient Routing Algorithm for heterogeneous WSN IEEE 2010.
[9]. Vivek Mhatre and Catherine Rosenberg, Homogeneous Vs Heterogeneous Clustered Sensor Networks:A Comparative Study In Proceeding of IEEE International Conference on Communications(ICC), 2004, PP. 3646-3651.
[10]. Georgious Smaragdakis, Ibrahim Matta and Azer Bestavors, ―SEP: A Stable Election Protocol for Clustered Heterogeneous Wireless Sensor Networks. In Proceding of the International Workshop on SANPA, 2004.
[11]. Wendi Rabiner Heinzelman, Amit Sinha. Alice Wang and Anatha P. Chandrakasan, ―Energy Scalabel Algorithms and Protocols for Wireless Micro sensor Networks, 2000.
[12]. J. Al-Karaki, and A. Kamal, Routing Techniques in Wireless Sensor Networks: A Survey., IEEE Commun-ications Magazine, vol 11, no. 6, Dec. 2004, pp. 6-28.
[13]. W.R. Heinzelman, A. Chandrakasan, and H. Balakrishnan, An Application-Specific Protocol Architecture for Wireless Microsensor Networks. In IEEE Transactions on Wireless Communications vol. 1(4), 2002, pp. 660-670.
[14]. Yan Li, Yan Zhong Li, Energy-Efficient clustering Routing algorithm based on LEACH, Journal of Computer Applications, 2007.
[15]. Ben Alla Said, Ezzati Abdellah, Abderrahim Beni Hssane, Moulay Lahcen Hasnaoui, ―Improved and Balanced LEACH for heterogeneous wireless sensor networks (IJCSE) International Journal on Computer Science and Engineering Vol. 02, No. 08, 2010, 2633-2640
[16]. Zeenat Rehena, Sarbani Roy, Nandini Mukherjee ,”A Modified SPIN for Wireless Sensor Networks”, 978-1-4244 8953-4/11 2011 IEEE.

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Paper Title:

Abstract: With the appearance of the web, it’s fascinating to interpret and extract helpful data from the net. One major challenge in internet interface interpretation is to get the semantic structure underlying an internet interface. Several heuristic approaches have been developed to get and cluster semantically related interface objects. However, those approaches cannot solve the problem of non similarity satisfactorily and don’t seem to be ready to tag the participant role of every object. Distinct from existing approaches, this paper develops a sturdy and formal approach to ill interface semantics mistreatment graph grammars induction. Due to the distinct capability of spatial specifications within the abstract syntax, the spatial graph grammar induction algorithm (SGGI) is chosen to perform the semantic grouping and interpretation of divided screen objects. Instead of analyzing HTML supply codes, we tend to apply an economical image processing technology to acknowledge atomic interface objects from the screenshot of an interface and manufacture a spatial graph, which records vital spatial relations among recognized objects. A spatial graph is a lot of taciturn than its corresponding document object model structure and, thus, facilitates interface analysis and interpretation. Supported the spatial graph, the SGGI parser recovers the graded relations among interface objects.

Keywords: Content extraction, Image Segmentation, Graph Grammar Induction Algorithm, Spatial Parsing.

References:

[1] H. Ahmadi and J. Kong, “Efficient web browsing on small screens,”in Proc. ACM Int. Working Conf. Adv. Visual Interfaces, 2008, pp. 23–30.
[2] F. Ashraf, T. Ozyer, and R. Alhajj, “Employing clustering techniques for automatic information extraction from HTML documents,” IEEE Trans. Syst., Man, Cybern.—Part C: Appl. Rev., vol. 38, no. 5, pp. 660–673, Sep.2008.
[3] F. Ashraf and R. Alhajjt, “ClusTex: Information extraction from HTML pages,” in Proc. 21st Int. Conf. Adv. Inf. Netw. Appl. Workshops, May 2007, pp. 355–360.
[4] K. Ates, J. Kukluk, L. Holder, D. Cook, and K. Zhang, “Graph grammar induction on structural data for visual programming,” in Proc. IEEE 18th Int. Conf. Tools Artif. Intell., Nov. 2006, pp. 232–242.
[5] K. Ates and K. Zhang, “Constructing VEGGIE: Machine learning for context-sensitive graph grammars,” in Proc. IEEE 19th Int. Conf. Tools Artif. Intell., Oct. 2007, pp. 456–463.
[6] S. Baluja, “Browsing on small screens: Recasting web-page segmentation into an efficient machine learning framework,” in Proc. World Wide Web, 2006, pp. 33–42.
[7] O. Boiman, E. Shechtman, and M. Irani, “In defense of nearest-neighbor based image classification,” in Proc. IEEE Conf. Comput. Vision Pattern Recogn., Jun. 2008, pp. 1–9.
[8] Y. Borodin, J. Mahmud, and I. V. Ramakrishnan, “Context browsing with mobiles—When less is more,” in Proc. 5th Int. Conf. Mobile Syst., Appl. Services, 2007, pp. 3–15.
[9] R. Burget, “Visual HTML document modeling for information extraction,”in Proc. Reconfigurable Architectures Workshop, 2005, pp. 17–24.
[10] J. Kong, K. Zhang, and X. Q. Zeng, “Spatial graph grammar for graphic user interfaces,” ACM Trans. Human-Comput. Interaction, vol. 13, no. 2, pp. 268–307, 2006.
[11] N. Milic-Frayling and R. Sommerer, “SmartView: Flexible viewing ofweb page contents,” presented at the Proc. of the 11th World Wide Web Conf. (poster paper), New York, 2002.
[12] S. Zheng, R. Song, and J. Wen, “Template-independent news extraction based on visual consistency,” in Proc. 22nd Nat. Conf. Artif. Intell., 2007, vol. 2, pp. 1507–1512.
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[15] Y. Chen, W. Y. Ma, and H. J. Zhang, “Detecting web page structure foradaptive viewing on small form factor devices,” in Proc. WorldWide Web,2003, pp. 225–233.
[16] F. Paterno and G. Zichittella, “Desktop-to-mobile web adaptation through customizable two-dimensional semantic redesign,” in Proc. 3rd Int. Conf.Human-Centered Softw. Eng., 2010, pp. 79–94.
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Abstract: In this paper we have presented a BPSK modulator using low power CMOS technology. The key design issues in VLSI circuit design are power and delay. Thus in this paper we have focused on LP CMOS with different technologies(16nm, 22nm ,32nm,and 45nm) with the help of TANNER EDA Tool. The value of model parameters are used from Predictive Technology Model(PTM). The T-SPICE simulation results indicate that there is a 59% deduction in Dynamic power For 16nm technology compare to 45nm technology keeping supply voltage constant whereas there is 74.64% reduction in power delay product in 16nm technology compare to 45nm technology.

Keywords: BPSK, LP CMOS, Power dissipation, PTM

References:

[1]. Bong-Young Chung, Charles Chien, Henry Samueli,”Performance Analysis of an All-Digital BPSK Direct-Sequence Spread-Spectrum IF Receiver Architecture”, IEEE JOURNAL ON SELECTED AREAS IN COMMUNICATIONS, VOL. 11, NO. 7, SEPTEMBER 1993.
[2]. S.-M. Moon, J.-W. Yu and M.-Q. Lee,” Performance Analysis of an All-Digital BPSK Direct-Sequence Spread-Spectrum IF Receiver Architecture”, ELECTRONICS LETTERS 19th November 2009 Vol. 45 No. 24.
[3]. Han Yan, Jose Gabriel Macias-Montero, Ate Akhnoukh, Leo C. N. de Vreede John R. Long, Joachim N. Burghartz, “An Ultra-Low-Power BPSK Receiver and Demodulator Based on Injection-Locked Oscillators”, IEEE TRANSACTIONS ON MICROWAVE THEORY AND TECHNIQUES, VOL. 59, NO. 5, MAY 2011.
[4]. ASU, Berkeley Predictive Technology Model (BPTM) Dept. of EE, Arizona State Univ., Tempe, AZ, 2006 [Online].
[5]. Sanjay Sharma, “Digital Communication”,S.K Katariya and sons,2009.
[6]. R.Saleh,”Design and Technology Trends”, Dept. of ECEUniversity of British Columbia,[Online].
[7]. S.M Kang,Y.Leblebici,”CMOS Digital Integrated Circuit”,The McGraw-hill Companies,3rd Edition,1999.
[8]. Issam S. Abu-Khater, Student Member, IEEE, Abdellatif Bellaouar, and M. I. Elmasry,” Circuit Techniques for CMOS Low-PowerHigh-Performance Multipliers”, IEEE JOURNAL OF SOLID-STATE CIRCUITS, VOL 31, NO 10, OCTOBER 1996.
[9]. Eitan N. Shauly,” CMOS Leakage and Power Reduction in Transistors and Circuits: Process and Layout Considerations”, J. Low Power Electron. Appl. 2012.
[10]. Hung-Chi Wang#\ Jyh-Ching Juang#2, Chun-Lin LU,” A CMOS BPSK Transmitter with a Monitoring Demodulator Embedded”, Proceedings of Asia-Pacific Microwave Conference 2010.

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Abstract: The Smart Grid is formed by many sub-networks such as the Home Area Network (HAN), service providers, transmission, distribution, and bulk generation, operations and market which are at risk and can be attacked remotely. Smart grids that is supports data aggregation and access control. Data can be aggregated by home area network (HAN), building area network (BAN), and neighboring area network (NAN) in such a way that the privacy of customers is protected. Smart grid designing a mutual authentication scheme and a key management protocol. This paper proposes an efficient scheme that mutually authenticates a smart grid and an authentication server in SG by decreasing the number of steps in the secure remote password protocol. In this paper we propose an efficient key management protocol based on our enhanced identity-based cryptography for secure SG communications using the public key infrastructure. The improved efficiency for key management is realized by periodically refreshing all public/ private key pairs as well as any multicast keys in all the nodes using only one newly generated function broadcasted by the key generator entity. We show that the proposed mechanisms are resilient against insider attackers performing serious attacks such as man-in-the-middle or impersonation during device authentication. Further, the proposed authentication mechanisms are intuitive and require no (or minimum) user effort.

Keywords: Enhanced identity-based, key management, cryptography (EIBC), smart grid (SG) mutual authentication, and secure remote password (SRP).

References:

1. Z. Fan, P. Kulkarni, S. Gormus, C. Efthymiou, G. Kalogridis, M. Sooriyabandara, Z. Zhu, S. Lambotharan, and W. H. Chin, “Smart grid communications: Overview of research challenges,solutions, and standardization activities,” IEEE Commun. Surveys Tuts., vol. 15, no. 1, pp. 21–38,2013.
2. J.Wang and V. Leung, “A survey of technical requirements and Consumer application standards for IP-based smart grid AMI network,” in Proc. ICOIN, 2011, pp. 114–119.
3. H. Nicanfar, P. Jokar, and V. Leung,“Smart grid authentication and key management for unicast and multicast communications, ” in Proc. IEEE PES ISGT, 2011, pp. 1–8.
4. D. Cooper, S. Santesson, S. Farrell, S. Boeyen, R. Housley, and W. Polk, “Internet X. 509 Public Key Infrastructure Certificate and Certificate Revocation List (CRL) Profile,” Internet Engineering Task Force, Fremont, CA, USA, 2008.
5. M. Amin, “Challenges in reliability, security, efficiency, and resilience of energy infrastructure: Toward smart self-healing electric power grid,” in Power and Energy Society General Meeting – Conversion and Delivery of Electrical Energy in the 21st Century, 2008 IEEE, Jul. 2008, pp. 1–5.
6. Metke and R. Ekl, “Security technology for smart grid networks,” Smart Grid, IEEE Transactions on, vol. 1, no. 1, pp. 99 –107, Jun. 2010.
7. Z. Fadlullah, N. Kato, R. Lu, X. Shen, and Y. Nozaki, “Towards secure targeted broadcast in smart grid,” IEEE Commun. Mag., vol. 50, no. 5, pp. 150–156, May 2012 [Online]. Available: http://bbcr.uwaterloo.ca/h8liang/sg/Papesg commx.pdf
8. J. Xia and Y. Wang, “Secure key distribution for the smart grid,” IEEE Trans. Smart Grid, vol. 3, no. 3, pp. 1437–1443, Sep. 2012.
9. M. Fouda, Z. M. Fadlullah, N. Kato, R. Lu, and X. S. Shen, “A light-weight message authentication scheme for smart grid communications,” IEEE Trans. Smart Grid, vol. 2, no. 4, pp. 675–685, 2011.
10. S. R. Rajagopalan, L. Sankar, S.Mohajer, and H. V. Poor, “Smartmeter privacy: A utility-privacy framework,” Proc. IEEE Smart Grid Comm, 2011.

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