Abstract:VANET (Vehicular Ad-hoc Network) is an emerging new technology with some unique characteristics that makes it different from other ad hoc network. Due to rapid topology changing and frequent disconnection it is also difficult to design an efficient routing protocol for routing data among vehicles, called V2V or vehicle to vehicle communication and vehicle to road side infrastructure, called V2I. Because of road accident daily occurrence VANET is one of the influencing areas for the improvement of Intelligent Transportation System (ITS) which can increase road safety and provide traffic information etc. The existing routing protocols for VANET are not efficient to meet every traffic scenarios. Suitable routing protocols are required to establish communication between vehicles in future for road safety. In this paper, we focus on the merits and demerits of routing protocols which will help to develop new routing protocols or improvement of existing routing protocol in near future..
Keywords: Proactive, Reactive, Routing Protocol, VANET, MANET.

Websites
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[2] Online, http://www.ist-drive.org/index2.html.

Thesis Papers
[3] W. Franz, H. Hartenstein, and M. Mauve, Eds., Inter-Vehicle-Communications Based on Ad Hoc Networking Principles-The Fleet
Net Project. Karlshue, Germany: Universitatverlag Karlsuhe, November 2005.
[4] Forderer, D (2005). "Street-Topology Based Routing." Master's thesis, University of Mannheim, May 2005.
[5] Rainer Baumann, "Vehicular Ad hoc Networks", Master's Thesis in Computer Science, ETH Zurich (2004).
Workshop Papers
[6] Festag, et. al., "NoW-Network on Wheels: Project Objectives, Technology and Achievements", Proceedings of 6th International
Workshop on Intelligent Transportations (WIT), Hamburg, Germany, March 2008.
[7] Lochert, C., Hartenstein, H., Tian, J., Fussler, H., Hermann, D., Mauve, M. (2003), "A routing strategy for vehicular ad hoc
networks in city environments," Intelligent Vehicles Symposium, 2003. Proceedings. IEEE, vol., no., pp. 156-161, 9-11 June 2003.
[8] O. K. Tonguz, N. Wisitpongphan, F. Bai, P. Mudalige and V. Sadekar, "Broadcasting in VANET", Proc. IEEE INFOCOM MOVE
Workshop 2007, Anchorage, USA, (2007).
Journal Papers
[9] Perkins, C.; Belding-Royer, E.; Das, S. (July 2003)"Adhoc On-Demand Distance Vector (AODV) Routing".
[10] Johnson, D. B. and Maltz, D. A. (1996), "Dynamic Source Routing in Ad Hoc Wireless Networks," Mobile Computing, T.
Imielinski and H. Korth, Eds., Ch. 5, Kluwer, 1996, pp. 153–81.

Abstract:Natural disasters are an unexpected fact of life that may occur during unpredictable times and in unpredictable ways. Ability to mitigate and adapt to natural disasters after many devastating events is becoming a greater challenge to the emergency response operators. Inefficiencies in the technology during rescue operations makes the communication between the rescuers problematic. The emerging role of GPR and GSM remote cameras makes it possible to capture and process the mission-critical data for the use of first responders. Due to its portability and affordable cost, it is feasible to integrate them into environment monitoring tasks in critical care regions. A problem is that there is a need to switch between different access networks for providing effective mission critical communication. IEEE 802.21 standard provides a media independent framework that enables seamless handover between heterogeneous access technologies. We proposed a life detection framework that assists the rescue operators in detecting alive humans and thereby provides a smooth communication between them. This framework together with media independent handover scheme and real time data distribution service operates in a reliable and timely manner against unpredictable environments.
Keywords: Media Independent Handover (MIH), unmanned aerial vehicles(UAVs),disaster detection, handover.

[1] Rong Jyh Kang, Hsung-Pin Chang, Ruei-Chuan Chang: A seamless Vertical Handoff Scheme. Proceedings on First International
Conference on Wireless Internet. 0-7695-2382-X (2005).
[2] Witayangkurn, M. Nagai,K. Honda,M. Dailey and R. Shibasaki Real-time monitoring system using unmanned aerialvehicle
integrated with sensor observation service",Remote Sensing and Spatial Information Sciences, Vol. XXXVIII -1/C22 UAV-g 2011.
[3] Felipe A. Cruz-Perez, Arturo Seguin-Jimenez, Lauro Ortigoza-Guerrero: Effects of Handoff Margins and Shadowing on the
Residence Time in Cellular Systems with Link Adaptation. 0-7803-521-7/04.IEEE (2004).
[4] Tein-Yaw Chung, Yung-Mu Chen, Pu-Chen Mao, Chen-Kuan Tsai, Sheng-Wen Lai, Chun-Po Chen: The Design and
Implementation of IEEE 802.21and Its Application on Wireless IEEE (2010).
[5] White (2004) Paper on Emergency Communications prepared by the Space & Advanced Communications Research Institute
(SACRI) George Washington University 2006.
[6] IEEE P802.21/D14.0 Media Independent Handover Services, Sept 2008.
[7] Aiswaria Ramachandran, Baliji Haiharan,"Collaborative Mobile Device based Data Collection and Dissemination using MIH for
Effective Emergency Management".
[8] Woochul Kang, Krasimira Kapitanova, "RDDS: A Real-Time Data Distribution Service for Cyber Physical Systems".

Abstract:Sustaining a given level of data redundancy is a basic requirement of peer-to-peer (P2P) storage systems to make certain desired data availability, additional replicas must be created when peers fail. Because the majority of failures in P2P networks are short-lived (i.e., peers return with data intact), reliably distinctive permanent and transient failures, however, is a demanding task, because peers are apathetic to probes in both cases. This paper proposes MASS (Maximum Available Server Selection), an algorithm that detects the failure and redirect the user services by the available server.
Keywords: Failure detector, P2P storage, availability, Failure Recovery.

[1] CleversafeInc.,http://www.cleversafe.org/dispersed-storage,2011.
[2] Wuala, Peer-to-peer storage system, http://wua.la/en/home.html, 2010.
[3] R. Bhagwan, K. Tati, Y.-C. Cheng, S. Savage, and G.M. Voelker,"Total Recall: System Support for Automated Availability
Management," Proc. Symp. Networked Systems Design and Implementation (NSDI '04), 2004.
[4] C. Blake and R. Rodrigues, "High Availability,Scalable Storage,Dynamic Peer Networks: Pick Two," Proc. Ninth Workshop Hot
Topicsin Operating Systems (HotOS '03), 2003.
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pp 23-31, Jan. 1987.
[6] D. Manivannan and M. Singhal, "A Low-Overhead Recovery Technique Using Quasi Synchronous Check pointing," Proc. IEEE
Int'l Conf. Distributed Computing Systems, pp. 100-107, 1996.
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Secaucus, NJ, USA, 1992.
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Network Systems (SocialNets '08), 2008.
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Quantitative Approach," Computer, 2005.
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and Yafei Dai, Member, IEEE Transaction on parallel and distributed systems, VOL. 22, NO. 9, Sep 2011

Abstract:The medicine that is practiced today is an Evidence-Based Medicine (EBM) in which medical expertise is not only based on years of practice but on the latest discoveries as well. All research discoveries come and enter the repository at high rate, making the process of identifying and disseminating reliable information a very difficult task. The work that we present in this paper is focused on two tasks: automatically identifying sentences published in medical abstracts as containing or not information about diseases and treatments, and automatically identifying semantic relations that exist between diseases and treatments. The second task is focused on three semantic relations: Cure, Prevent, and Side Effect. The objective for this work is to show what Natural Language Processing (NLP) and Machine Learning (ML) techniques—what representation of information and what classification algorithms—can be used for identifying and classifying relevant medical information in short texts.
Keywords: Natural Language Processing; Machine Learning, Medical abstracts, semantic relations

[1] Rindflesch,T. EDGAR: extraction of drugs, genes and relations from the biomedical literature.
[2] Asma Ben Abacha, Pierre Zweigenbaum Automatic extraction of semantic relations between medical entities: a rule based approach
[3] Anna Divoli and Teresa K. Attwood BioIE: extracting informative sentences from the biomedical literature
[4] Alan R. Aronson Effective Mapping of Biomedical Text to the UMLS Metathesaurus: The MetaMap
[5] Rindflesch TC and Aronson AR. Ambiguity Resolution while Mapping Free Text to the UMLS Metathesaurus
[6] McCray AT, Srinivasan S and Browne AC. Lexical methods for managing variation in biomedical terminologies.
[7] Lee CH, Khoo C, Na JC: Automatic identification of treatment relations for medical ontology learning: An exploratory study.
[8] Ben Abacha A, Zweigenbaum P: Medical Entity Recognition: A Comparison of Semantic and Statistical Methods.

Abstract:Intrusion detection is one of the major research problems in network security. It is the process of monitoring and analyzing the events occurring in a computer system in order to detect different security violations. The aim of this paper is to classify activities of a system into two major categories: normal and abnormal activities. In this paper we present the comparison of different classification techniques to detect and classify intrusions into normal and abnormal behaviours using WEKA tool. WEKA is open source software which consists of a collection of machine learning algorithms for Data mining tasks. The algorithms or methods tested are Naive Bayes , j48, OneR, PART and RBF Network Algorithm. The experiments and assessments of the proposed method were performed with NSL-KDD intrusion detection dataset. With a total data of 2747 rows and 42 columns will be used to test and compare performance and accuracy among the classification methods that are used.
Keywords: Intrusion detection, Classification, Machine Learning, WEKA , j48,PART.

[1] http://nsl.cs.unb.ca/NSL-KDD/KDDTrain+_20Percent.arff
[2] Richard Power. 1999 CSI/FBI computer crime and security survey. Computer Security Journal Volume XV (2), 1999
[3] Jian Pei Shambhu J. Upadhyaya Faisal Farooq Venugopal Govindaraju. Proceedings of the 20th International Conference on Data
Engineering (ICDE‟04) 1063-6382/04 $ 20.00 © 2004 IEEE
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55, No. 7–8, 361–378, 2000.
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[7] WEKA at http://www.cs.waikato.ac.nz/~ml/weka
[8] Http://en.wikipedia.org/wiki/C4.5_algorithm
[9] Http://www.saedsayad.com/oner.html
[10] S.Vijayarani, M.Divya " An efficient algorithm for Generating classification rules".International Journal of Computer Science &
Technology issue4 october- December 2011.

Abstract:This paper presents a framework for token based mutual exclusion algorithms in distributed systems. Their exists some traditional token based mutual exclusion algorithm. Some new algorithms are proposed in order to increase fault tolerance, minimize message complexity and decrease synchronization delay. In this paper, some new approaches are used, like Token ring algorithm with centralized approach, which is a betterment of the already existing token ring algorithm and overcome all the problems in the existing algorithm. A new token passing approach , which incurs 3 messages at high load, irrespective of no of node N and N message at low loads. Fairness algorithm for priority process, which has low message complexity and fairness in token algorithm. Several Token approach which allow simultaneous existence of several tokens. Hope the proposed framework provides a suitable context for technical and clear evaluation of existing and future methods.
Keywords: Critical Section, Inverted Tree Structure, Logical Ring, Mutual Exclusion, Token

[1] W. Stallings, "Operating Systems Internals and Design Principles", Prentice Hall, pp.205-261(2009).
[2] M.G.Velaquez, "A Survey Of Distributed Mutual Exclusion Algorithms", Technical Report CS. Colarido State University,
September 1993.
[3] Ichiro Suzuki and Tadao Kasami, "A Distributed Mutual Exclusion Algorithm", ACM Transactions on Computer Systems, Vol. 3,
No. 4, pp. 344-349, November 1985.
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No. 1, pp. 61-77, February 1989.
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Reversal", Journal Of Parallel And Distributed Computing, 34(1), pp. 1-13, April 1996.
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Tree", 2005
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International Journal of Computer Science Issues, Vol. 8, Issue 1, January 2011.
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international Conference on Machine Learning and Computing IPCSIT vol. 3, 2011.

Abstract:Recognition of the most facial variations, such as identity, expression and gender, has been extensively studied. Automatic age estimation has rarely been explored. With age progression of a human the face angle changes. This paper concerns with providing a methodology to estimate age groups using face features. The proposed method is based on the face triangle which has three coordinate points between left eye ball, right eyeball and mouth point. The face angle between left eyeball, mouth point and right eyeball estimates the age of a human. However, very few studies have been done on age classification or age estimation. This paper proves that face angle can estimate and classify human age according to face features extracted from human facial images. Age ranges are classified into five categories. Those are child (up to 17 years), young (18 to 25 years), adult (26 to 35 years), middle aged (36 to 45 years) and old (more than 45 years). The obtained results were significant. This paper can be used for predicting future faces, classifying gender, and expressions from facial images.
Keywords: Age estimation, Eyeball detection, Face angle, Face triangle, Mouth point detection

[1] Y.H.Kwno and N.daVitoria Lobo, "Age Classification from Facial Images," Computer Vision and Image Understanding, vol.74,
no.1, pp.1-21, 1999.
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Recognition, San Diego, CA, 2005, vol.2, pp.462-469.
[3] P. N. Belhumeur, J. P. Hespanha, and D. J. Kriegman. Eigenfaces vs. Fisherfaces: Recognition using class specific linear projection.
IEEE Transactions on Pattern Analysis and Machine Intelligence, 19(7):711–720, July 1997.
[4] M. A. Turk and A. P. Pentland. Eigenfaces for recognition. Journal of Cognitive Neuroscience, 3(1): 71–86, 1991.
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Machine Intelligence, 25(9):1063 –1074, September 2003.
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August 2005.
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Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems, pages 58-63, Corfu, Greece, Sept. 1999.
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Intelligence, 24(5):696-706, May 2002.
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Abstract:Computer networks need security in place to protect IT systems. As computer networks are everywhere, it is essential to have a mechanism for selective data stream blocking. This paper presents a tailor made mechanism that is responsible to monitor, detect and block as per the definitions associated with the customized mechanism. The proposed mechanism blocks data packets after verifying the protocols that govern the proposed mechanism. The empirical results revealed that the mechanism is robust and can be used in the real world networks.
Keywords: data packets, packet sniffers, intrusion detection, firewall, data stream

[1] The New Lexicon Webster's Encyclopedic Dictionary of the English Language. New York: Lexicon.
[2] Associating Network Flows with User and Application Information, Ralf Ackerman, UtzRoedig, Michael Zink, Carsten Griwodz , Ralf Steinmetz, ACM Multimedia Workshop, 2000, Marina Del Rey CA USA
[3] Detecting Intruders on a Campus Network: Might the Threat Be Coming From Within? Rich Henders, Bill Opdyke, SIGUCCS'05, November 6–9, 2005, Monterey, California, USA
[4] A Taxonomy of free network sniffers for teaching and Research, Victor A Clincy and Nael Abu- Halaweh, JCSC 21, 1(October 2005), Midwestern Conference, Consortium for Computing Sciences in Colleges
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Abstract:Supervised text classification algorithms rely on the availability of large quantities of quality training data to achieve their optimal performance. However, not all training data is created equal and the quality of class-labels assigned by human experts may vary greatly with their levels of experience, domain knowledge, and the time available to label each document. In our experiments, focused label validation and correction by expert journalists improved the Micro and Macro-F1 scores achieved by Linear SVMs by as much as 14.5% and 30% respectively, on a corpus of professionally labeled news stories. Manual label correction is an expensive and time consuming process and the classification quality may not linearly improve with the amount of time spent, making it increasingly more expensive to achieve higher classification quality targets. We propose ATDC, a novel evidence-based training data cleaning method that uses training examples with high-quality class- labels to automatically validate and correct labels of noisy training data. A subset of these instances are then selected to augment the original training set. On a large noisy dataset with about two million news stories, our method improved the baseline Micro-F1 and Macro-F1 scores by 9% and 13% respectively, without requiring any further human intervention.
Keywords: Classification, Clustering, Naïve Bayes, Support, Training Data Cleaning

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Abstract:Mobile devices are growing day by day, so the mobile database. Transactions from ATM machines are a good example of wireless Transactions. Since these transaction flows using medium as air hence security is a issue till the transaction reaches the Base station from where the transaction is much more secure as compared to wireless network. In this paper a new scheme of securing database transaction is proposed till it reaches the Base station. This is also required to provide security against frequent disconnections [2][5].
Keywords: transactions, Shared key Cryptography, Wireless Network, Security.

[1] Ziyad Tariq Abdul-Mehdi FIST-MMU Ali Bin Mamat& Hamidah Ibrahim
FSKTM-UPM Mustafa. M.Dirs FITM," MULTI-CHECK-OUT TIMESTAMP ORDER TECHNIQUE (MCTO) FOR PLANNED
DISCONNECTIONS IN MOBILE DATABASE",2006.
[2] Margaret H. Dunham a,_, Abdelsalam Helal b,__ and Santosh Balakrishnan c a Department of Computer Science and Engineering
Southern Methodist University, Dallas, "A mobile transaction model that captures both the data and movement behaviour",1997
[3] Ziyad.T.Abdul-Mehdi , Ramlan Mahmod, "Security Management Model for Mobile Databases Transaction Management",2008
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[5] Lubinski. A. 1999. "Adaptation Concepts for Mobile Database Security" University of Rostock,
Rostock, Germany.
[6] Abdul-Mehdi, Z.T. Mamat, A.B. Ibrahim, H. Dirs, Mustafa.M. 2006."Multi-Check-Out Timestamp Order Technique (MCTO) for
Planned Disconnections in Mobile Database", The 2nd IEEE International Conference on Information & Communication
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in Computer Science, Faculty of Computer Science and Information Technology, University Putra Malaysia, P.P.3.

Abstract:WSN has the potentiality to join the physical world with the virtual world by creating a network of sensor nodes. Here, sensor nodes are usually battery-operated devices, and hence energy reduction of sensor nodes is a major design issue. To extend the network's lifetime, minimization of energy consumption should be used. In cluster-based routing, cluster heads shape a wireless stamina to the sink. Each cluster heads collects data starting the sensors belonging to its cluster and ahead it to the sink. Here, the cluster head position rotates, i.e., each node works as a cluster head for a restricted period of time. Energy saving in BFA approaches can be done by cluster formation, cluster-head election, data collection at the cluster-head nodes to reduce data redundancy and thus save energy and also it improve energy efficiency of homogeneous WSN. It also defined Bacterial Foraging Algorithm (BFA) as an algorithm for selecting best cluster head selection for WSN. The simulation results enhanced performance of BFA based on total energy dissipation and no .of .alive nodes of the network when compared with LEACH
Keywords:WSN, BFA, LEACH, routing protocol, cluster head election.

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