iosr-JCE   Volume-8 ~ Issue-2

Abstract:Multilevel inverters have been widely applied industries. A family of optimal puisewidth modulation (PWM) methods for multilevel inverters, such as step modulation, can generate output voltage with less harmonic distortion than popular modulation strategies, such as the carrier-based sinusoidal PWM or the space vector PWM. However, some drawbacks limit the application of optimal PWM. One of such crucial drawback is that the optimal switching angles could not be calculated in real-time and one has to rely on lookup tables with precalculated angles. We propose a novel real-time algorithm for calculating switching angles that minimizes total harmonic distortion (THD) for step modulation. We give a mathematical proof that the output voltage has the minimum THD. We implemented the algorithm on a digital signal processor and provide experimental results that verify the performance of the proposed algorithm.
Keywords: Multilevel inverter, optimal puisewidth modulation (PWM), power conversion, Total Harmonic Distortion (THD), Digital Signal Processing (DSP).

[1] J. Rodriguez, J.-S. Lai, and F. Z. Peng, ―Multilevel inverters: A survey of topologies, controls, and applications.‖ IEEE Trans. Ind. Electron., vol. 49, no. 4, pp. 724-738, Aug. 2002.
[2] J. M. Carrasco, L. G. Franquelo, J. T. Bialasiewicz, E. Galvan, R. C. PortilloGuisado, M. A. M. Prats, J. i. Leon, and N. Moreno-
Alfonso, ―Power-electronic systems for the grid integration of renewable energy sources: A survey," IEEE Trans. Ind. Electron., vol.
53, no. 4, pp. 1002-1016, Jun. 2006.
[3] X. Xu, Y. Zou, K. Ding, and F. Liu, ―Cascade multilevel inverter with phase-shift SPWM and its application in STATCOM,‖ in Proc. IEEE 1ECON, 2004, vol. 2, pp. 1139-1143.
[4] Y. Liang and C. O. Nwankpa, "A new type of STATCOM based on cascading voltage-source inverters with phase-shifted unipolar
SPWM,‖ IEEE Trans. Ind. Appl., vol. 35, no. 5, pp. 1118-1123, Sep/Oct. 1999.
[5] J. Rodriguez, J. Pontt, P. Correa, P. Cortes, and C. Silva, "A new modu-vJ‟lation method to reduce common-mode voltages in multilevel inverters,‖ IEEE Trans. Ind. Electron., vol. 51, no. 4, pp. 834-839, Aug. 2004.
[6] S. Lakshminarayanan, G. Mondal, P. N. Tekwani, K. K. Mohapatra, Sn*^ and K. Gopakumar, ―Twelve-sided polygonal voltage space vector based multilevel inverter for an induction motor drive with common-mode voltage elimination,‖ IEEE Trans. Ind. Electron., vol. 54, no. 5, pp. 276i-2768, Oct. 2007.
[7] S. Sirisukprasert, J.-S. Lai, and T.-H. Liu, "Optimum harmonic reduction with a wide range of modulation indexes for multilevel
converters,‖ IEEE Trans. Ind. Electron., vol. 49, no. 4, pp. 875-881, Aug. 2002.
[8] L. M. Tolbert, F. Z. Peng, and T. G. Habetler, ―Multilevel converters for large electric drives,‖ IEEE Trans. Ind. Appl., vol. 35, no. 1, pp. 36-44, ,Jan./Feb. 1999.
[9] C. Rech and J. R. Pinheiro, ―Hybrid multilevel converters: Unified analysis and design considerations,‖ IEEE Trans. Ind. Electron., vol. 54, no. 2, pp. 1092-1104, Apr. 2007.
[10] Y. Liu and F. Luo, "Trinary hybrid multilevel inverter used in STATCOM with unbalanced voltages," Proc. Inst. Electr. Eng.—Elect. Power Appl., vol. 152, no. 5, pp. 1203-1222, Sep. 2005.

Abstract:The Usage of internet in now a day is more and it became necessity for the people to do some applications such as searching web data bases in domains like Animation, vehicles, Movie, Real estates, etc. One of the problems in this context is ranking the results of a user query information. Earlier approaches problem have toused frequencies of database value regions, handling query logs, and user profiles information. A common thread in most of these approaches is that ranking is done in a usage page ranking manner. This paper simulates the usage of ranking query results based on user and query Dependent ranks by taking user and query similarities as input including the workload. K- Means algorithm used for cluster and re ranking process, multiple database system used for clustering the data. Among rank learning methods, ranking SVM has been favorably applied to various applications, e.g., optimizing search engine for web information, improving data retrieval quality. We define these similarities formally in discuss their effectiveness analytically and experimentally over four distinct web databases.
Keywords: Automated Ranking, Animation Database, Vehicle and Movie Databases, User similarity, Query similarity, workload.

[1] AdityaTelang, Chengkai Li, and Sharma Chakravarthy. ―One Size Does Not Fit All: Toward User- and Query-Dependent Ranking
for Web Databases; IEEE Transactions On Knowledge And Data Engineering, Vol. 24, No. 9, September 2012.
[2] Alex Penev, Raymond K. Wong; Finding Similar Pages in a Social Tagging Repository;WWW 2008,April 21–25, 2008, Beijing,
China. ACM 978-1-60558-085-2/08/04.
[3] Cynthia Dwork, Ravi Kumar, MoniNaor, D. Sivakumar; Rank Aggregation Methods for the Web;WWW10,May 1-5, 2001, Hong
Kong. ACM 1-58113-348-0/01/0005.
[4] Hwanjo Yu, Youngdae Kim, and SeungwonHwang.RV-SVM: An Efficient Method for Learning Ranking SVM;Korea Research
Foundation Grant funded by the Korean Government(KRF-2008-314-D00483)2009.
[5] KaushikChakrabarti, SurajitChaudhuri, Seung-won Hwang; Automatic Categorization of Query Results;SIGMOD 2004, June 13–
18, 2004, Paris, France.
[6] Marko balabanovic, yoavshoham. Content based, collaborative Recommendation; March 1997/Vol. 40, No. 3 Communication Of
The ACM.

[7] SurajitChadhuri, Gautam Das, VagelisHristidis; Probabilistic Information Retrieval Approach for Ranking of Database Query
Results; ACM Transactions on Database Systems, Vol. 31, No. 3, September 2006, Pages 1134–1168.
[8] SubbaraoKambhampati, Garrett Wolf, Yi Chen, HemalKhatriBhaumikChokshi, Jianchun Fan, UllasNambiar; QUIC: Handling
Query Imprecision & Data Incompleteness; in Autonomous Databases;(http://creativecommons.org/licenses/by/2.5/) CIDR 2007.
[9] Tapas Kanungo, Senior Member, IEEE, David M. Mount, Member, IEEE, Nathan S. Netanyahu, Member, IEEE, Christine D.
Piatko, Ruth Silverman, and Angela; An Efficient C-Means Clustering Algorithm: Analysis and Implementation; IEEE
Transactions On Pattern Analysis And Machine Intelligence, Vol. 24, No. 7, July 2002.
[10] Weifeng Su, Jiying Wang, Qiong Huang, Fred Lochovsky; Query Result Ranking over E-commerce Web Databases; CIKM'06,
November 6–11, 2006, Arlington, VA Virginia, USA.

Abstract:A new approach for implementing number of expressions, emotions and, actions to operate objects through the thoughts of brain using a Non-Invasive Brain Computing Interface (BCI) technique has been proposed. In this paper a survey on brain and its operations are presented. The steps involved in the brain signal processing are discussed. The current systems are able to present few expressions and emotions on a single device. The proposed system provides the extended number of expressions on multiple numbers of objects.
Keywords: Brain Computer Interaction (BCI), Electroencephalogram (EEG), Expressions, Emotions.

[1] "Brain Facts, A Primer on the brain and nervous systems", http://www.sfn.org/skins/main/pdf/brainfacts/2008/brain_facts.pdf,
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[3] Lia Stannard, "Parts of the brain and their functions", Available: http://www.livestrong.com/article/77671-parts-brain-functions/, 2011.
[4] Jerry J.Shih;Dean. J. Krusienski: and Jonathan R, Wolpaw "Brain Computing Interfaces in Medicine", Mayo Clinical Proceedings,
Volume 87, pp 268-279, 2012.
[5] Erica Westly, "Fixing the Brain Computer Interface", IEEE Spectrum, July 2010.
[6] Theodore W. Berger, John K. Chapin, Greg Patrick A. Tresco, "Brain-Computer Interfaces-An International Assessment of
Research & Development Trends", Springer, 2008.
[7] Reza Fazel Rezai, "Recent advances in Brain Computer-Interface systems", InTech Publication, 2011.
[8] Niels Birbaumer, "Breaking the silence: Brain Computer Interfaces (BCI) for communication and motor control",
Psychophysiology, 43, 517–532, 2006.
[9] Leigh R. Hochberg, John P. Donoghue, "Sensors for Brain Computer-Interfaces", IEEE Engineering and Medicine, 2006.
[10] Jorge Baztarrica Ochoa, Gary Garcia Molina, Touradj Ebrahimi, "EEG signal classification for Brain Computer Interface
Applications", 2002.

Abstract:The task of classification in recovery systems is to differentiate between normal and abnormal brain. In this paper feature extraction from MR Images is carried out by DAUB-4 Wavelet method. DAUB-4 is an efficient tool for feature extraction because it gives better contrast to an image. Due to better contrast it improves easily hanging signals of an image and reduces the overhead. PCA is used to select the best features for classification. These PCA selected features are given as an input to SVM for classification. In this work we are using two SVM kernel functions which are Linear Kernel and Radial Basis Kernel. Experimental results show that the proposed system have high classification accuracy of 98.7% with Radial Basis Kernel.
Keywords: Wavelets transform, Principle component analysis, Support vector machine, MRI, Brain tumor

[1] M. G. Mostafa and M. F. Tolba, Medical Image Segmentation Using Wavelet Based Multi resolution EM Algorithm, IEEE trans on
Industrial Electronics, Technology and automation, IETA, 2001.
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modeling to vessel segmentation, Medical Image Analysis, pp. 259-274, 2010.
[3] J. H. Kazmi, K. Qureshi, H. Rasheed, An Implementation of SAN Filter and Edge Sharpening Method for MRA images, Malaysian
Journal of Computer Science, 2007.
[4] R. Mishra, MRI based Brain Tumor Detection using Wavelet Packet Feature and Artificial Neural Networks, Department of
computer science India Ghandi Institute of Technology Indraprastha University, Delhi, India, 2010.
[5] E. A. El-Dihshan, T, Hosney, A. B. M. Salem, Hybrid intelligence techniques for MRI Brain images classification, ELSEVIER,
Digital Signal Processing, , Volume 20, pp.433-441, 2010
[6] S. Chaplot, L. M. Patnaik, Classification of magnetic resonance brain images using wavelets as input to support vector machines
and neural networks, Biomedical Signal Processing and Control, pp. 86-92, 2006.
[7] S. Chaplot, L. M. Patnaik, Brain Tumor Diagnosis with wavelets and Support Vector Machine, proceeding of 3rd international
Conference on intelligent Systems and Knowledge Engineering, 2008.
[8] Q. Ain, I. Mehmood, S. M. Naqvi, M. A. Jaffar, Bayesian classification using DCT features for Brain tumor detection, National
University of Computer & Emerging Sciences, FAST Islamabad, 2010.
[9] A. E. Lashkari, A Neural Network based Method for Brain Abnormality Detection in MR Images Using Gabor Wavelets,
International Journal of Computer Applications, vol. 4.no.7, 2010.
[10] A. E. Lashkari, A Neural Network based Method for Brain Abnormality Detection in MR Images Using Zernike Moments and
Geometric moments, International Journal of Computer Applications, vol. 4.no.7, 2010.

Abstract:In this project an approach is being made to use Fuzzy Logic(a computational intelligence paradigm) in the Probabilistic routing protocol for Intermittently connected network: Delay Tolerant Network. Communication between two mobile nodes in an infrastructure less network is possible if they are within the wireless communication range. Delay Tolerant Network (or DTN) is not only an infrastructure less network but it also suffers from intermittent connection i.e. there is not always a connected path from the source to the destination. As a result traditional routing protocols cannot serve the purpose of this type of network. A passive routing protocol for DTN's named PROPHET routing works on the principle of history of encounters and transitivity [3]. It is called Probabilistic routing protocol since it uses a parameter 'Delivery of Predictability'. Using Fuzzy Logic some rules will be defined and another parameter 'Energy value' will be considered to calculate the probability of delivery. With the aim of consuming fewer resources by the network and minimizing the delay in message delivery this new Fuzzy based probabilistic routing protocol has been introduced.
Keywords: Delay tolerant network, Fuzzy logic, Delivery Predictability, Prophet routing protocol, Epidemic routing protocol.

[ 1 ] EL MASTAPHA SAMMOU "Efficient Probabilistic Routing in Delay Tolerant Networks"2012 IEEE.
[ 2 ] A. Vahdat and B. Becker, "Epidemic Routing for Partially-Connecte Ad- hoc Networks," Technical Report CS-2000-06, Duke
University,July 2000.
[ 3 ] A. Lindgren, A. Doria, and O. Scheln, "Probabilistic Routing in Intermittently Connected Networks," in Proc. Workshop on
Service Assurance with Partial and Intermittent Resources, August 2004.
[ 4 ] T. Spyropoulos, K. Psounis, and C. S. Raghavendra, "Spray and wait: Efficient routing in intermittently connected mobile networks," in Proceedings of ACMSIGCOMM workshop on Delay Tolerant Networking (WDTN), 2005.
[ 5 ] Morteza Karimzadeh "Efficient routing protocol in DTNs",2011
[ 6 ] Arash Dana, Golnoosh Ghalavand, Azadeh Ghalavand and Fardad Farokhi "A Reliable routing algorithm for Mobile Adhoc
Networks based on fuzzy logic". IJCSI International Journal of Computer Science Issues, Vol. 8, Issue 3, No. 1, May 2011.
[ 7 ] CMU Monarch Project. The CMU Monarch Project's wireless and mobility extensions to ns
ftp.monarch.cs.cmu.edu/pub/monarch/wireless-sim/ns-cmu.ps, August 1999.
[ 8 ] Olaf Wolkenhauer"Fuzzy Inference Engines Composition and Individual-Rule Based Composition, Non-Linear Mappings".
[ 9 ] V.Rishiwal,A.Kush and S.Verma, "Backbone nodes based Stable routing for mobile ad hoc network",UBICC Journal,
Vol2,No.3,2007,pp34-39.
[10] Etienne C. R. de Oliveira and C´ elio V. N. de Albuquerque "NECTAR: A DTN Routing Protocol Based on Neighborhood Contact
History". SAC'09 March 2009.

Abstract:TCP (Transmission Control Protocol) has been performing well over the traditional wired networks. However it cannot react efficiently in wireless network where packet losses occur mostly because of congestion and wired cum wireless networks where the significant packet losses are due to bit errors or handoffs. In order to evaluate the Quality of Service it is essential to measure the performance of network in terms of throughput, efficiency, delay, packet dropping probability etc. These parameters are usually influenced by variations in the network parameters such as packet size and packet interval. Consequently it could not differentiate whether the increased round trip time is due to route change or network congestion. As a solution to this problem a mechanism (Snoop protocol) is proposed for efficient rerouting. The rerouting of packets using Snoop helps avoid congestion and to improve the performance of TCPs with rerouting.
Keywords: rerouting, round trip time, Snoop, wired cum wireless networks.

[1] J.H.Saltzer ,D.P.Reed, and D.D.Clark, "End-to-end arguments in system design," ACM Trans. Comp. Sys., Vol. 2, no. 4, Nov. 1984, pp. 277-88. An earlier version appeared in 2nd int‟l. Conf. Dist. Comp. Sys., Apr., 1981, pp. 509-12.
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Laboratory, University of California, Berkeley, Jan. 1999.
[5] K. N. Srijith, L. Jacob, and A. L. Ananda, "TCP Vegas-A: improving the performance of TCP Vegas," Computer Commun., vol. 28,
no. 4,pp. 429-440, Mar. 2005.
[6] Y.-C. Chan, C.-T. Chan, and Y.-C. Chen, "RoVegas: a router-based congestion avoidance mechanism for TCP Vegas," Computer
Commun., vol. 27, no. 16, pp. 1624-1636, Oct. 2004.
[7] Srikanth Tiyyagura , Rajesh Nutangi , and Dr. P. Chenna Reddy ,"An Improved Snoop For TCP Reno And TCP Sack In Wired-
Cum-Wireless Networks", Computer Commun.,IJCSE.,Vol. 2 No. 3 Jun-Jul 2011.
[8] C. Perkins, "IP mobility support for IPv4," IETF RFC 3344, Aug. 2002.
[9] Jeonghoon Mo, Richard J. Lo., Venkat Anantharam and Jean Walrand"Analysis And Comparison of TCP Reno and Vegas",
Computer commun., University of California, Berkeley, July 13, 1998.
[10] Sarma Vangala and Miguel A. Labradorb ."Performance of TCP over Wireless Networks with the Snoop Protocol." Department of
Computer Science and Engineering University of South Florida, Tampa, FL 33620.

Abstract:The microcontroller based portable image acquisition and wireless data transmission is a security surveillance device. This can be used in monitoring of an area for effective image capturing and image data transmission. It combines the effectual hardware and software components and brings an output through blinking bulb and there is also a buzzer alarm if the system detects any image. Finally, it bridges the gap between visitors, intruders and the host using surveillance device.
Keywords: Security, Surveillance, image, data, camera, transmitter, gates

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Abstract:This paper contributes modeling links and route stabilities in three diverse wireless routing protocols. For this purpose, we select three extensively utilized proactive protocols; Destination-Sequenced Distance Vector (DSDV), Optimized Link State Routing (OLSR) and Fish-eye State Routing (FSR). We also enhance the performance of these protocols by modifying their default parameters. All experiments for evaluating and comparing the performance of protocols are performed in NS-2. Optimization of these routing protocols is done via performance metrics; average Throughput, End to End Delay (E2ED) and Normalized Routing Load (NRL) achieved by them. Default routing protocols DSDV, OLSR and FSR and compared and evaluated with modified versions named as M-DSDV, M-OLSR and M-FSR. Numerical Computations for Route Stabilities of these routing protocols through a mathematical modeled equation is determined and then compared with the results obtained through Simulations in NS-2. Moreover, all-inclusive evaluation and scrutiny of these proactive routing protocols are done under the Mac layer standards 802.11 DCF and 802.11e EDCF. In this way both Network and Mac layer exploration has been done under the performance metrics which gives overall performance and tradeoff with respect to full utilization of the available resources of Ad-hoc network high scalability scenario. Routing latency effects with respect to route stabilities and Mac layer standards 802.11 and 802.11e are compared and scrutinized with the tradeoff observed in throughput and in overhead (NRL) generated.
Keywords: Diverse wireless, routing protocol, proactive protocols, enhance performance, route statbilities, NS-2, DSDV, OLSR, FSR

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International Symposium, 2005.
[4] J. Hu, et al., ''A comprehensive analytical model for IEEE 802.11e QoS differentiation schemes under unsaturated traffic load s, in:
Proceedings of the ICC08'', 2008.
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SIGCOMM Comput. Commun. Rev.,vol. 24, pp. 234-244, 1994.
[6] G. Pei, et al., "Fisheye State Routing in Mobile Ad Hoc Networks," in ICDCS Work-shop on Wireless Networks and Mobile
Computing, 2000, pp. D71-D78.
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[8] T. Clausen and P. Jacquet, "Optimized Link State Routing Protocol (OLSR)'', 2003.
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[10] Samir R. Das, et al.,"Simulation-based performance evaluation of routing protocols for mobile ad hoc networks".