iosr-JCE   Volume-16 ~ Issue-3 ~ May-June 2014

Abstract: This paper aims at development of a prevention mechanism for avoiding major fire accidents in garbage dumps with the help of Internet of Things Middleware. Internet of Thing Middleware enables communication between objects; which are completely heterogeneous with the nodes in network. This proposed methodology will divide the garbage area into sectors according to the coverage of thermal cameras and each sector will be divided into four parts; so that it will be easier for the authorities to locate the fire and solve the problem with less effort. This architecture incorporates an infrared thermal camera, a micro controller which will act as a gateway device & an adaptable user interface to intimate the fire stations at the initial stage of the problem.

[1] Albreto.M.C.Souza,"A Novel Smart Home Application using an Internet of things Middleware" Smart SysTech,Erlangen/Nuremberg, Germany 2013.
[2] Soma Bandyopadhyay, Munmun Senguptha,souvik Maiti and subhajit Dutta Inovation Lab,TATA Consultancy Services Ltd. Kolkata,India, "Role of Middleware for internet of things: A study" International Journel of Computer Science and Engineering Survey(IJCSES)Vol.2,No.3,August 2011.
[3] The COTS Enterprise Architecture Workgroup, Middleware Domain Team "A middleware framework for Delivering Business Solutions" Version 1.0,May 2001.
[4] Robert Orfali, Dan Harkey and jeri Edwards, "The Essential Client/Server Survival Guide", Galgotia Publications Pvt. Ltd.,2002.
[5] Jeffrey.C.Jacson,"Web Technology-A Computer Science Perspective", Pearson Education,2007.
[6] James Keogh," The Complete Reference J2ME" Tata McGraw – Hill Education (2003).

Abstract: Prediction of Indian stock market data with data mining technique is one of the fascinating issues for researchers over the past decade. Statistical and traditional methods are no longer feasible for proper analysis of huge amount of data. With the help of Data mining technique information technology tool , it is able to uncover hidden patterns and predict future trends and behavior in stock market. In this paper there are combination of four supervised machine learning algorithms, classification and regression tree (CART), linear discriminant analysis (LDA) and quadratic discriminant analysis (QDA) are proposed for classification of Indian stock market data. These resulted forms help market analyst to make decision on selling, purchasing or holding stock for a particular company in Indian stock market. In section IV and V, experimental results and performance comparison section show that classification and regression tree misclassification rate is only 56.11% whereas LDA and QDA show 74.26% and 76.57% respectively. Smaller misclassification reveals that CART algorithm performs better classification of Indian stock market data as compared to LDA and QDA algorithms.
Keyword: Machine learning algorithm; classification; patterns.

[1]. U. Fayyad, G. Piatetsky-Shapiro, P. Smyth, and R. Uthurusamy. Advances in Knowledge Discovery and Data Mining. AAAI Press/MIT Press, Menlo Park, California/Cambridge, Massachusetts/ London, England, 1996.
[2]. Subhendu Kumar Pani and Amit Kumar and Maya Nayak,‖ Performance Analysis of Data Classification Using Feature Selection‖ (October 24, 2013). The IUP Journal of Information Technology, Vol. IX, No. 2, June 2013, pp. 36-50
[3]. Matthew N. Anyanwu and Sajjan G. Shiva,‖ Comparative Analysis of Serial Decision Tree Classification Algorithms,‖ International Journal of Computer Science and Security, (IJCSS) Volume (3) : Issue (3) ,.pp: 230-240.
[4]. XindongWu ,Vipin Kumar , J. Ross Quinlan ,Joydeep Ghosh , Qiang Yang ,Hiroshi Motoda , et al ―Top 10 algorithm in data mining according to the survey paper of Xindong wu et al know (inf syst (2008) @ springer verlog London limited 2007,pp:1-37, Dec. 2007.
[5]. Yoav Freund and Robert E. Schapire. A decision-theoretic generalization of on-line learning and an application to boosting. Journal of Computer and System Sciences, 55(1):119–139, August 1997

Abstract: The safe and satisfactory provision of water related services in urban areas of developing countries remain a major challenge mainly attributed to limited resources and inability to promptly detect operational failures (blockage, leakage, organic infiltration etc..) in water infrastructure. In this paper we investigated the feasibility of real time monitoring for contexts similar to developing countries and developed a decision support tool to prioritize/optimize water management practice. Wireless sensors were use to generate data and identification of opportunities /challenges/strategies for setting up a viable real time monitoring mechanism. The application of wireless sensor networks is composed of a number of sensor nodes that have the capability of carrying out network activities and can work continuously for the sake of monitoring. This paper proposes how urban water monitoring systems for developing countries and emerging economies can be developed with emphasis on cost effectiveness, easy ad hoc installation such that the mechanism will be easy to handle and maintained. The use of wireless network for this purpose reduced the manpower required, set up cost and provided flexibility in terms of distance. The paper will made use of Zigbee technology because of its low power consumption and it can be used to realize water quality parameters, remote probing and real time monitoring function. Several results are presented and the feasibility of using wireless sensor network is presented.
Keywords: Real-Time, Monitoring, Water Systems, Developing Countries.

[1]Chris Scholin, (2009). "Real-time water quality monitoring" http://www.mbari.org/education/internship/09interns/papers/Frazier.pdf. Retrieved 23 April, 2014.
[2]. Darshana N. Tambe and Ms. Nikita Chavan (2013) "Detection of Air Pollutant Using Zigbee" International Journal of Ad hoc, Sensor & Ubiquitous Computing (IJASUC) Vol.4, No.4, August 2013
[3]. Diersing, Nancy (2009). "Water Quality: Frequently Asked Questions." Florida Brooks National Marine Sanctuary, Key West Florida.
[4]. JMP, Water for Life: making it happen,2005http://www.wssinfo.org/pdf/JMP_05_text.pdf
[5]. Totti Konnola (2006). "Future Outlook on Water Quality Monitoring Technologies" VTT Technical Research Centre of Finland

Abstract: A level of trust can be developed by online relationships in social network which are based on real world relationships. To form a dynamic Social Cloud and to enable users to share heterogeneous resources within the context of a social network we have proposed leveraging of the social relationships. We believe that combining trust relationships with suitable incentive mechanisms could provide much more sustainable resource sharing mechanisms. We have introduced a business application as a means of regulating sharing, due to the unique nature of the Social Cloud. The business application is innovative as it uses both social and economic protocols. In today's world, social community credentials are being used for authentication purpose on various other websites (e.g. Facebook). Here we outline our vision of creating a Social Storage Cloud, looking especially at possible market mechanisms that could be used to create a dynamic Cloud infrastructure in a Social network environment.
Keyword :Business Application, Cloud computing, Services computing, Social Cloud, Social networks, Web services..

[1] Rajkumar Buyya, Srikumar Venugopal. Grid Computing and Distributed Systems Laboratory, Department of Computer Science and Software Engineering. The University of Melbourne, Australia , \The Gridbus Toolkit for Service Oriented Grid and Utility Computing: An Overview and Status Report"
[2] Miranda Mowbray, Francisco Brasileiroz, Nazareno Andradez, Jaindson Santanaz, Walfredo Cirne . \A Reciprocation-Based Economy for Multiple Services in Peer-to-Peer Grids" Hewlett-Packard Laboratories Bristol zUniversidade Federal de Campina Grande Filton Rd, Stoke Gi_ord Av. Aprgio Veloso, s/n - 58.109-970 Bristol BS34 8QZ, UK Campina Grande.
[3] Je_ Pasternack,Waldspurger, Hogg, Huberman, Kephart, and Stornetta .\Spawn: A Distributed Computation Economy". .
[4] David P. Anderson. \BOINC: A System for Public-Resource Computing and Storage". Published in Grid Computing, 2004. Proceedings: Fifth IEEE/ACM International Workshop on 8 Nov 2004.
[5] Kyle Chard, Simon Caton, Omer Rana, and Kris Bubendorfer. \Social Cloud: Cloud Computing in Social Networks". Published in Cloud Computing (CLOUD), 2010 IEEE 3rd International Conference on 5-10 July 2010

Abstract: Significant advancements have been made in the field of data mining and knowledge discovery. But there is no universal algorithm that can be dynamic enough to extract information from a continuous data stream or from a large stored dataset. A combination of algorithms has to work cohesively in order for the system to yield accurate and timely results according to user specifications. Algorithms are expected to be fast, accurate and visually informative to the user. We have tried to analyse the most effective and recent algorithms and techniques which have been developed to mine information from different data sources. We project our insight on the working of these algorithms and elicit possible loopholes and limitations.
Keywords : Data mining, Knowledge discovery, data stream mining, high speed data streams

[1]. Semi-supervised learning. Vol. 2. Cambridge: MIT press, 2006.
[2]. Domingos, Pedro, and Geoff Hulten. "Mining high-speed data streams." Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 2000.
[3]. Guyon, Isabelle, ed. Feature extraction: foundations and applications. Vol. 207. Springer, 2006.
[4]. Panigrahi, Debmalya, et al. "Online selection of diverse results." Proceedings of the fifth ACM international conference on Web search and data mining. ACM, 2012.
[5]. Matysiak, Martin. "Data Stream Mining." (2012).

Abstract: To make sure that the vehicles on road follow traffic rules, lane disciplines and traffic signals, it takes a lot of human effort and precious time. An automated system which is coupled with traffic cameras can help in this monitoring process. Haar-like features is one of the best techniques that can be used for detecting the objects within images/video feed from the traffic cameras. This process includes the subtasks of data collection, negative positive separation, creating training samples, creating description files, haar training and a strong action program which can detect vehicles and the traffic events. Hence alerting the monitoring authority to take care of the situation and make sure that the traffic events handled carefully. For experimental purpose one can train their database for few vehicles but a more robust database and a robust detection program can produce a great performance results.
Keywords: Road Traffic, haar training, Event detection, Surveillance, Monitoring.

[1] Hongliang Bai; Jianping Wu; Changpin Liu, "Motion and haar-like features based vehicle detection," Multi-Media Modelling Conference Proceedings, 2006 12th International , vol., no., pp.4 pp. Dec 2006
[2] Soojin Kim; Sangkyun Park; Seonyoung Lee; Seungsang Park; Kyeongsoon Cho, "Design of high-performance pedestrian and vehicle detection circuit using Haar-like features," TENCON 2012 - 2012 IEEE Region 10 Conference , vol., no., pp.1,5, 19-22 Nov. 2012
[3] Xi Yong; Liwei Zhang; Zhangjun Song; Ying Hu; Lan Zheng; Jianwei Zhang, "Real-time vehicle detection based on Haar features and Pairwise Geometrical Histograms," Information and Automation (ICIA), 2011 IEEE International Conference on , vol., no., pp.390,395, 6-8 June 2011
[4] Heechul Jung; Junggon Min; Junmo Kim, "An efficient lane detection algorithm for lane departure detection," Intelligent Vehicles Symposium (IV), 2013 IEEE , vol., no., pp.976,981, 23-26 June 2013
[5] Xiaokun Li and Fatih M. Porikli, "A Hidden Markov Model Framework for Traffic Event Detection Using Video Features", IEEE TR2004-130, October 2004

Abstract: In this paper we implement a moving Object classification system with cloud environment which is used for tracking any objects in non-ideal environment using android mobile. The tracked image is send to the cloud for storage and classification. The image is then retrieved by the system from the cloud storage (image sent by the android mobile) and it is classified based on the HAAR classifier algorithm. The HAAR classifier algorithm classifies the objects by comparing it with the objects in the cloud database and tracked objects and stores the result objects in the cloud for providing the details to be accessed anytime, anywhere from the remote system. A software approach for real time implementation of moving object classification is done through java.

[1] D. Comaniciu and V. Ramesh, Real Time Tracking of Non-Rigid Objects using Mean Shift, Computer vision and Pattern
Recognition, 2000 proceedings IEEE conference.
[2] OpenCV Library, Intel Corporation.
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[4] E.Pauwles and G.Frederix. Non-Parametric Clustering for Image Segmentation and Grouping. Computer Vision and Image
Understanding, 75 nos. 1/2, pp. 73-85, 1999.
[5] Y.Fang and T.Tan, A Novel Adaptive Colour Segmentation Algorithm and its Application to Skin Detection. In Proc.BMVC 2000,
pp.23-31. BMVA, 2000

Abstract: In this article, a number of posterior probabilistic based equations were introduced to detect the effect of controlling the correlation between variables on the behavior of feed forward neural network weights. In this paper it was proofed that, under certain assumptions, in a feed forward neural network with backprobagation learning algorithm, the correlation between the input variables on one side and the target variable on the other, is directly proportional to the values of the connection weights from the input layer to the output layer through the hidden layer.
Keywords: Correlation Coefficients, Features Selection, Data Mining, Logistic Regression, Machine Learning, Neural Networks, Posterior Probability.

[1] Arribas, I., J., Cid-Sueiro, J., & Alberola-Lopez, C., Handbook of Neural Engineering. The Institute of Electrical and Electronic Engineers, Inc. 41. 2007.
[2] Bourland, H., & Morgan, N., Connectionist Speech Recognition . Kluwer Academic, Boston. 1998.
[3] Duin, R., B. W., & Tax, M. J., D., Classi_er Conditional Posterior Priority .SSPR 98/SPR 98 Proceedings of the Joint IAPR International Workshop on Advances in Pattern Recognition.Volume 1451. pp. 611-619. ISBN: 3-540-64858-5, 1998.
[4] Richard, M. D., & Lippmann, R. P., Neural Network Classi_ers Estimate a Posteriori Probabilities. Neural Comp. 3 (4), 461-483, 1991.
[5] Rojas, R., A Short Proof of the Posterior Probability Property of Classi_er Neural Networks .Neural Computation.Vol. 8. 41-43, 1996.

Abstract: The amount of information available on the internet is increasing day by day which is leading to information overload. For more information than can realistically be digested is available on the World-Wide Web and in other electronic forms. News information, biographical information, minutes of meetings missed, it isn't possible to read everything one would want to read and so some form of information condensation is needed. Summarization is the process of reducing a text document with a computer program in order to create a summary that retains the most important points of the original document. Somplification os done to append meanings of the nouns so as to facilitate the easy reading and understanding of the text by the user.
In this summarization. the input text document is divided into two parts informative & non informative and summarizing and simplifying them individually. It uses the NLTK tagger to tag the words and get their parts of speech. The nouns in the informative sentences were simplified using WorldNet. In order to summarize and simplify non-informative sentences keyword selection approach was used. Finally, the two files obtained after summarizing and simplifying were merged together to obtain the output file.
Keywords: keyword selection,, Weighted approach, NLTK Tagger, Text Features, keyword selection, informative & non informative sentence.

[1] Hovy, E. H. Automated Text Summarization. In R. Mitkov (ed), The Ox-ford Handbook of Computational Lin-guistics, chapter 32, pages 583-598.Oxford University Press, 2005.
[2] Dehkordi, P.K., Khosravi, H., Kumarci, F., 2009. Text Summarization Based on Genetic programming. International Journal of Computing and ICT Research, 3(1), 57-64.
[3] Te-Min Chang Wen-Feng Hsiao "A hybrid approach to automatic text summarization" IEEE 2008

[4] Vishal Gupta & Gurpreet Singh Lehal (2012): Paper Review on Text Summarization Extractive Techniquesjournal of emerging technologies in web intelligence, vol. 2, no. 3, august 2010
[5] Atif Khan, Naomie Salim (2014): Paper Review on Abstractive Summarization Methods journal of Theoretical andApplied Information Technology,10,th,January 2014. Vol. 59 No.1 ,© 2005 - 2014 JATIT & LLS. All rights reserve

Abstract: Optimization problem consists of maximizing or minimizing a real function by systematically
Choosing input values from within an allowed set and the value of the function can be solved.Whenever the user enter a query in a search engine and hit 'enter' the program searches documents for specified keywords and returns a list of the documents where the keywords are found. The program uses a proprietary algorithm to create its indices such that only meaningful results are returned for each query.Users normally tend to visit websites that are at the top of this list as they perceive those to be morerelevant to the query. Search Engine Optimisation is a technique which helps search engines to find and rank your site higher than the millions of othersites in response to a search query.SEO helps to get traffic from search engines. Choosing the
Rightkeywords to optimize are the first and most crucial step to a successful SEO campaign. In the context of searchengine optimization keyword density can be used as a factor in determining whether a web page is relevant to a specifiedkeyword or keyword phrase. This paper presents the factors which affects the searching of the keyword on the World Wide Web.
Keywords: Crawling, Key Density, Links, SEO, Web Crawler

[1]. IESG, "IPv6 Address Allocation Management", 12/26/1995," "RequestFor Comments No. 1881" International Journal of Advanced Engineering Technology E-ISSN 0976-3945 IJAET/Vol.II/ Issue IV/October-December, 2011

[2]. Aaron Wall's SEO Book [3]. Google SEO Guide
[4]. Google search
[5]. SEO-FINAL-White-Paper-web

Abstract: Cloud computing has revolutionized the information technology industry by enabling elastic on demand provisioning of computing resources. The increase of Cloud computing has resulted in the organization of large-scale data centers around the world contain thousands of total nodes. This paper presents overview of cloud computing, issues in cloud computing, novel techniques, and software for distributed dynamic consolidation of Virtual Machines (VMs) in Cloud data centers. The goal is to improve the utilization of computing resources and reduce energy consumption under workload independent quality of service constraints. Dynamic VM consolidation leverages fine-grained fluctuations in the application workloads and continuously reallocates VMs using live migration to minimize the number of active physical nodes. Energy consumption is reduced by dynamically deactivating and reactivating physical nodes to meet the current resource demand. The proposed approach is distributed, scalable, and efficient in managing the energy-performance trade-off. In this paper, we introduce DVFS concept with live migration technique to improve efficiency of energy management and adaption scheme on real-time services.
Keyword: Cloud Computing, Data Center, Energy Management, Virtualization, Real-time Service, DVFS, Live Migration

[1]. V.Krishna Ready, B.Thirumala Rao, Dr.L.S.S.Ready, P.Sai Kiran" Research Issues in Cloud Computing"Global Journal of Computer Science and Technology, Volume 11 Issue 11 Version 1.0 July 2011.
[2]. M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. Katz, A. Konwinski, G. Lee, D. Patterson, A. Rabkin, I. Stoica, and M. Zaharia. "Above the Clouds: A Berkeley View of Cloud Computing," Technical Report EECS-2009-28, EECS Department, Univ.of California, Berkeley, 2009.
[3]. Mohiuddin Ahmed, Abu Sina Md. Raju Chowdhury,"An Adavanced Survey On Cloud Computing and State-of-art Research Issues" IJCSI International Journal of Computer Science Issues, Vol.9,Issue 1,January 2012 ISSN(Online): 1694-0814
[4]. Hamilton J "Cooperative expendable micro-slice servers (CEMS): low cost, low power servers for Internet-scale services In: Proc of CIDR",(2009)
[5]. A. Beloglazov, R. Buyya, Y. C. Lee, "A taxonomy and survey of energy-efficient data centers and Cloud computing systems" Advances in Computers, M. Zelkowitz (ed.), vol. 82, pp. 47–111, 2011.

Abstract: Hadoop is a Java software framework that supports data - intensive distributed applications and is developed under open source license. It enables applications to work with thousands of nodes and petabytes of data. The two major pieces of Hadoop are HDFS and MapReduce. HDFS works with two types of hardware machines, the DataNode (Slave machine) which is the machine on which application's data is stored and the NameNode (Master machine) which store the metadata of file system. Where NameNode is the only single machine for storing metadata of file system and is the Single Point of Failure (SPOF) for the HDFS. SPOF of NameNode machine affects the overall availability of Hadoop. When NameNode goes down the entire system become offine and cannot do any operation until NameNode gets restart. If the NameNode machine fails, the system needs to be re-started manually, making the system less available. This paper proposes a highly available architecture and its working principle for the HDFS NameNode against its SPOF utilizing well-known 2-Phase Commit (2PC) Protocol and election by bully with Time synchronization mechanism.
Keywords : Hadoop, HDFS, Two Phase Commit Protocol, Berkeley algorithm for time synchronization, Name node.

[1] Mohammad Asif Khan, Zulfiqar A. Memon,Sajid Khan, "Highly Available Hadoop NameNode Architecture", Department of CSE and ECE, 978-0-7695-4959-0/13 2013 IEEE
[2] Konstantin Shvachko, Hairong Kuang, Sanjay Radia, Robert Chansler, "The Hadoop Distributed File System", Yahoo! Sunnyvale, California USA,978-1-4244-7153- 9/10/2010 IEEE
[3] Dhruba Borthakur, "The Hadoop Distributed File System: Architecture and Design", The Apache Software Foundation,2007
[4] Aaron Myers, "http://blog.cloudera.com/blog/2012/03/highavailability for-the- hadoop-distributed-file-system-hdfs/", cloudera,March 07, 2012.
[5] Tom White,"Hadoop: The Definitive Guide", 1005 Gravenstein Highway North, Sebastopol, CA 95472, 2009.

Abstract: Mining classification rules from data is a key mission of data mining and is getting great attention inrecent years. Rule induction is a method used in data mining where the desired output is a set of Rules or Statements that characterize the data. Within Rule Induction model, Swarm Intelligence (SI) is a technique where rules may be discovered through the study of joint behavior in decentralized, self-organized systems, such as ants. Ant-Miner is a rule induction algorithm that uses SI techniques to form rules. The main idea of this study is to discover the suitability of ant colony optimization for constructing accurate classifiers which can be learned in practical time even for big datasets. The cAntMinerPB algorithm is an extension of the cAntMineralgorithm. The main task is to modify the existing algorithm cAntMinerPB to allow each rule to dynamically select rule quality evaluation function and to improve the accuracy and preserving rule list simplicity. In this study, we examine the use of different rule quality evaluation functions for rule quality assessment prior to pheromone update and check how the use of different evaluation function affects the output model in terms of predictive accuracy and model size. In experimental results, we use 10 different rule quality evaluation functions on 12 benchmark datasets and found that predictive accuracy obtained by new proposed method is statistically significantly higher than the predictive accuracy of existing algorithm.
Keywords: ACO, SI, Rule Classifier, AntMiner

[1] DorigoM.,&Caro,G.D,"Ant Algorithm for Optimatisation" , Artificial Life,5(3),137 ,1999.
[2] Bonabeau, E., Dorigo,M., & Theraulaz, G."Swarm Intelligence: From Natural to Artifical System", New York: Oxford University Press, 1999.
[3] Dorigo,M.,&Maniezzo,V."The ant System: Optimization by a colony of cooperating Agents", IEEE Transactions on Systems, Man, and Cybernectics,26(1),1-13,1996.
[4] M. Dorigo and T. Stuetzle.,"Ant Colony Optimization", MIT Press, 2004.
[5] J.Kennedy and R.Mendes,"Population structure and Particle Swarm Performance", Procedeing of IEEE Conference on Evolutinary Computation, Honolulu, Hawalii USA, 2002.

Abstract: The world wide web is filled with billions of images and redundant copies of images can frequently be found on many websites. These duplicates can be exact copies or differ slightly in their visual content. To assure privacy it is mandatory to preserve copyright verification, image-content identification, copy detection and authentication. This paper provides a comparative study on how content-based image copy detection methods are used to detect the copy of original image. The methods based on content based copy detection which includes signs of discrete cosine transform (DCT) and discrete wavelet transform (DWT), color histograms, by using concept of dual signature are presented.
Keywords: Copyright, Content Based Image Copy Detection, Redundancy, Discrete Wavelet Transform

[1] Y.H. Wan, Q.L. Yuan, S.M. Ji, L.M. He,Y.L. Wang "A survey of the image copy detection" Zhejiang Province NSF Grant #
Y106332 IEEE Zhejiang University of Technology Hangzhou, China 2008
[2] M. Diephuis, S. Voloshynovskiy_, O. Koval and F. Beekhof IEEE "DCT Sign Based Robust Privacy Preserving Image Copy
Detection for Cloud-based Systems" Stochastic Information Processing Group, Universit´e de Gen`eve 1227 Carouge, Switzerland
{Maurits.Diephuis, svolos, Oleksiy.Koval, 978-1-4673-2369-7/12 2012.
[3] Bart Thomee Mark J. Huiskes Erwin Bakker Michael S. Lew, "Large Scale Image Copy Detection Evaluation" LIACS Media Lab,
Leiden University Niels Bohrweg 1, 2333 CA Leiden, The Netherlands. MIR'08, October 30–31, 2008, Vancouver, British
Columbia, Canada. Copyright 2008 ACM 978-1-60558-312-9/08/10
[4] J. Haitsma and T. Kalker, "A highly robust audio fingerprinting system with an efficient search strategy," Journal of New Mus ic
Research, vol. 32, no. 2, pp. 211–221, 2003.
[5] D. Engel, T. St¨utz, and A. Uhl, "Analysis of jpeg 2000 encryption with key-dependent wavelet packet subband structures," 2010.

Abstract: The objective of this paper is to provide a uniform means of transmitting data (audio, video) to real time constraints over multicast or unicast network services and providing much enhanced experience of the Real-time communication over the existing systems. In this paper we will explore usage of the dominating technologies in the real time systems and shows how to design and develop communications within such systems. In particular, it proposes reliable protocol over UDP transport layer that gains less than one millisecond average round trip time (RTT) and processes dozens of thousands of messages every second at each and every port in network. This paper presents the current internet protocols: Real-time Transport Protocol (RTP), RTP Control Protocol (RTCP) and Real-time Streaming Protocol (RTSP). Together these protocols may provide controlled delivery of multimedia traffic over the Internet. The feedback mechanisms for the quality of service (QoS) monitoring, such as delay, jitter and packet loss calculations, are described in detail.
Keywords : header compression; jitter; multimedia traffic; real-time;RTP;RTCP;

[1] Audio/Video Transport (AVT) Working Group, IETF. http://www.ietf.org/html.charters/avtcharter.html
[2] ITU-T Recommendation H.323: Packet-Based Multimedia Communications Systems. February 1998.
[3] ITU-T Recommendation H.225.0: Media Stream packetization and Synchronization on Non- Guaranteed Quality of Service LANs. November 1996.
[4] RTP: A Transport Protocol for Real-Time Applications. IETF RFC 1889. January 1996.
[5] RTP Profile for Audio and Video Conferences with Minimal Control. IETF RFC 1890. January 1996

Abstract: Vehicular Ad-hoc Network (VANET) is an extraordinary manifestation of MANET which is a vehicle to vehicle & vehicle roadside remote correspondence system, where nodes in VANET include themselves as servers or clients for trading & offering data. VANET (Vehicular Ad-hoc Network) could be another innovation that has taken gigantic consideration in the late years. Because of the quick topology the element cohort degreed incessant separation and it troublesome to style an efficient directing convention for steering data around vehicles, Vehicular Ad-hoc Network (VANET) could be a system of self sorted out vehicles and way side framework human movement with each one in turn over remote, with a read to support activity well being and intensity. Data exchanged over Vanets ordinarily assumes a significant part in movement well being. Such data ought to be right and truthful, as it rely on the requisition and verification is important administrations for activity security in Vanets. This paper is for the most part proposed to enhance the Quality of services (QOS ) in vehicular Ad-hoc Network by breaking down parameters like throughput, End-to-End Delay, Average jitter, and so forth in conventions like ZRP, STAR and DSR by utilizing the Qualnet 5.0.1 test system.
Keywords : DSR, Qualnet, STAR, VANET, ZRP.

[1] Bijan Paul, Md. Ibrahim, Md. Abu Naser Bikas " VANET Routing Protocols: Pros and Cons" International Journal of Computer Applications (0975 – 8887) Volume 20– No.3, April 2011
[2] Z. J. Haas, "The Zone Routing Protocol", Sixth WINLAB Workshop on Third Generation Wireless information Networks, New Brunswick, NJ, Nov. 1997.
[3] D. Johnson, B.D.A. Maltz, Y.C.Hu, "DSR", by International Journal of Advance in Science and Technology, 2004, pp.64-69
[4] Seet, B.-C., "A-STAR: A Mobile Ad Hoc Routing Strategy for Metropolis Vehicular Communications." 1980.
[5] www.google.co.in

Abstract: In text mining, text categorization is an important technique for classifying the documents. Most of the times statistical approaches that are based on analysis of the term in the form of frequency of the term, that is the number of occurrences of one or more words in the document are used for classification. Even statistical analysis indicates the importance of the term, but it is hard to analyze when multiple terms have the same frequency value, but one term is more important in terms of meaning than the other. Also, there are a wide variety of documents being generated that belongs to different domains which differ in formats, writing styles, etc. These domains can be news articles, e-mails, online chats, blogs, wiki articles, twitter posts, message forums, speech transcripts, etc. Often a classification method that works well in one domain does not work as well in another. The proposed system tries to implement a concept based text classification model that classifies the cross-domain text data based on the semantics or theme of the text data. Also the proposed approach makes the training system stronger and stronger at all possible positive tests of the categorizer. This system is called as a Self Appreciating Concept Based Classifier (SACBC).
Keywords: Document Classification, Concept Mining, Cross Domain Document classification

[1] Arul Deepa K & Deisy C,"A Self Appreciating Approach of Text Classifier Based on Concept Mining", 2012 International Conference on Computer Communication and Informatics (ICCCI -2012), Jan. 10 – 12, 2012, Coimbatore, INDIA
[2] M. Ramakrishna Murty, J.V.R Murthy, Prasad Reddy PVGD, S. C. Satapathy "A Survey of Cross-Domain Text Categorization Techniques", Ist Int'I Conf'. on Recent Advances in Information Technology , RAIT -2012.
[3] K. Nithya, P C D. Kalaivaani, R. Thangarajan, "An Enhanced Data Mining Model for Text Classification"
[4] Anjum Gupta,"New Framework for Cross-domain Document Classification", Ph.D. thesis, NPS, Montery, California, March 2011.
[5] Shehata, F. Karray, and M. Kamel, "An Efficient Concept Based Mining Model for Enhancing Text Clustering" IEEE Transactions on Knowledge and Data Engineering, Vol. 22, No. 10, October 2010.

Abstract: Right from the Stone Age one law is governing the market for every generation and that well acknowledged law is "Law of Demand & Supply". ICT is not far away from this law. It is a well-known fact that when cyber world is marching rapidly towards higher form of technological evolution, Cloud Computing has entered as backbone support to ICT as a tool for better cost performance. It is a platform, which is highly governed by the law of "Demand &Supply", whether it is Banking, Healthcare or Agriculture, all are in need of this technology to make their performance as cost effective as possible and ubiquitous in functionality. As by the law, Demand and Supply both go hand-to-hand. This paper presents some of the demand facets and corresponding supply services for banking, agriculture and healthcare. It enables software architect to make the framework of any sector to build up fully fledged working domain in due consideration of cloud computing.
Keyword: Banking and Financial System (BFS), Cloud Computing, Hospital Management Information System (HMIS), Information Communication Technology (ICT), SaaS Application, Total Cost of Ownership (TCO)

[1] Yanxin Zhu, Di Wu and Sujian Li, Cloud Computing and Agricultural Development of China: Theory and Practice, IJCSI
International Journal of Computer Science Issues, Vol. 10, Issue 1, No 1, January 2013
[2] Rajan Kumar Yadav, Avinash Thakur, Manoranjan Kumar, Cloud Computing: Environment of Next Generation Technology, IOSR
Journal of Computer Engineering (IOSR-JCE), e-ISSN: 2278-0661, p-ISSN: 2278-8727Volume 16, Issue 2, Ver. IX (Mar-Apr.
2014), PP144-148
[3] Sudhir Sriram, Cloud Computing in Banking, Capgemini Financial services, Copyright © 2011 Capgemini
[4] www.capgemini.com/financialservices
[5] Abhinav Garg,CLOUD COMPUTING FOR THE FINANCIAL SERVICES INDUSTRY, © 2011 Sapient Corporation

Abstract: Our present fuel resources are not going to be around forever and with the ever increasing consumption their extinction is nearly unavoidable. Also our fuel resources which are mostly made up of fossil fuels are not renewable in nature. Currently around the world the consumption of fossil fuels is 100,000 times faster than their natural production. According to an estimate the demand for these fuels will suddenly outstrip their availability in a matter of centuries-or less. Also the combustion of fossil fuels emits carbon dioxide. This harmful gas when released into the atmosphere makes a huge contribution to the greenhouse effect. This effect prompts the atmosphere to capture and reflect back the energy that radiate from the surface of the earth, instead of letting them to escape back into space. This causes global warming that melts the polar ice caps and affects weather all around the world. This project is discusses about the variability of using H2 as a fuel along with petroleum. There are many reasons to choose H2 as a motive power.H2 has one of the highest gravimetric energy densities of all available fuels, which means it has very high energy content per unit mass (143MJ/kg) 40% more than other. Also we have to preheat the inlet air to get the more efficient for the performance of engine.
Index Terms: four stroke petrol engine, hydrogen gas, air preheater, fuel consumption, emission control

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Abstract: Cloud computing is a model for enabling convenient, on-demand network access to a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) that can be rapidly provisioned and released with minimal management effort or service provider interaction. With a promising technology like this, it certainly abdicates users' privacy, putting new security threats towards the certitude of data in cloud. The security threats such as maintenance of data integrity, data hiding and data safety dominate our concerns when the issue of cloud security come up. In this research paper, we have contemplated a design for cloud architecture which ensures secured movement of data at client and server end. We have used the non breakability of Elliptic curve cryptography (ECC) with ones compliment for data encryption, proposed algorithm is based on 1's complement subtraction to represent scalar in scalar multiplication which offer less Hamming weight and will remarkably improve the computational efficiency. It has three security checkpoints: authentication, key generation and encryption of data.
Keywords: Cloud Computing, ECC, Scalar Multiplication, , One's Compliment, Diffie Hellman

[1] "Data Security in Cloud Architecture Based on Diffie Hellman and Elliptical Curve Cryptography" Neha Tirthani Ganesan R School of computing Sciences and Engineering,School of computing Science and Engineering,M. tech. Computer Science,Associate Professor (CSE),VIT, Chennai campus,neha.tirthani2013@vit.ac.in VIT, Chennai campus,ganesan.r@vit.ac.in
[2] "Algorithm based on one‟s complement for fast scalar multiplication in ECC for Wireless Sensor Network" Pritam Gajkumar Shah, Xu Huang, Dharmendra Sharma, University of Canberra, Australia
[3] "Enhancing Security of Cloud computing using Elliptic Curve Cryptography" Abhuday Tripathi MTech Amity University Lucknow , Volume 57– No.1, November 2012.
[4] "Enhanced public auditability & secure data storage in cloud computing", Chakraborty, T.K, Dept. of Comput. Sci. & Eng., Motilal Nehru Nat. Inst. of Technol. Allahabad.
[5] "Data Security in Cloud computing with Elliptic Curve Cryptography" Veerraju Gampala, Srilakshmi Inuganti, Satish Muppidi, ISSN: 2231-2307, Volume-2, Issue-3, July 2012

Abstract: In this paper, we propose a minimum, power efficient and max throughput routing protocol for Wireless Body Area Networks (WBANs). We use multi-hop topology to achieve minimum energy consumption and longer network lifetime. We propose a cost function to select forwarder node. Proposed cost function selects a forwarder node which has high residual energy and minimum distance to sink. Residual energy parameter balances the energy consumption among the sensor nodes while distance parameter ensures successful packet delivery to sink. Simulation results show that our proposed protocols maximize the network stability period and nodes stay alive for longer period. Longer stability period contributes high packet delivery to sink which is major interest for continuous patient monitoring.
Keywords: Wireless body Area Network, Cost Function, and Residual Energy

[1] M. F. F. B. Ismail and L. W. Yie, "Acoustic monitoring system using wireless sensor networks," Procedia Engineering, vol. 41, pp. 68–74, 2012.
[2] S.-D. Bao, Y.-T.Zhang, and L.-F. Shen, "Physiological signal based entity authentication for body area sensor networks and mobile healthcare systems," in Engineering in Medicine and Biology Society, 2005. IEEE-EMBS 2005.27th Annual International Conference of the, pp. 2455–2458, IEEE, 2005.
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[5] "A survey on indoor localization techniques in wireless body area sensor networks,"