iosr-JCE   International Conference on RECENT TRENDS IN ENGINEERING AND MANAGEMENT

Abstract: The multi-hop routing in wireless sensor network (WSNs) offers little protection against identity deception through replaying routing information. An adversary can exploit this defect to launch various harmful attacks like wormhole attack, sinkhole and Sybil attack. Traditional cryptographic techniques used in trust aware routing framework (TARF) but it do not effectively address this severe problem. To secure the WSNs against adversaries misdirecting the multi-hop routing, we have designed and implemented TARF .Without tight time synchronization or known geographic information. TARF provides trustworthy and energy efficient route. TARF proves effective against those harmful attacks developed out of identity deception.

[1]. G.Zhan, W.Shi, and J.Deng, "Tarf: A trust aware routing framework for wireless sensor network," in proceeding of the 7th European conference on Wireless sensor networks (EWSN'10), 2010.
[2]. C.Karlof and D.Wagner, "Secure routing in wireless sensor networks: attacks and countermeasures," in proceedings of th 1st IEEE International Workshop on Sensor Network Protocols and Applications, 2003.
[3]. A.Perrig, R.Szewczyk, W.Wen, D.Culler and J.Tygar, "SPINS: Security protocols for sensor networks," Wireless Networks Journal (WINET), vol.8, no.5, pp.521-534, sep. 2002
[4]. Z.Cao, J.Hu, Z.Chen, M.Xus, and X.Zhou, "Fbsr: feedback-based secure routing protocol for wireless sensor networks," International journal of Pervasive Computing and Communictions, 2008.I.FAkyildiz, W.Su, Y.Sankarasubramaniam, and E.Cayirci, "A Surveyon sensor networks," IEEE Communications Magazine, vol.40, no.8, pp.102-114, Aug.2002.
[5]. S.Chang, S.Shieh, W.Lin, and C.Hsieh, "An efficient broadcast authentication scheme in wireless sensor networks, " in proceedings of the 2006 ACM Symposium on Information, computer and communications security (ASIACCS'06). New York, NY, USA: ACM, 2006, PP.311-320.
[6]. J.Al-Karaki and A.Kamal, "Routing techniques in wireless sensor networks: a survey," wireless Communication, vol.11,no. 6, pp.6-28, Dec.2004.
[7]. J.Newsome, E.Shi, D.Song, and A.Perrig, "The sybil attack in sensor networks: Analysis and defenses," in Proc of the 3rd International Conference on Information Processing in Sensor Networks (IPSN'04), Apr. 2004.
[8]. R.Watro, D.Kong, S.Cuti, C.Gardiner, C.Lynn, and P.Kruus, "Tinypk: securing sensor networks with public key technology," in proceedings of the 2nd ACM workshop on Security of ad hoc and sensor networks (SASN'04). New York, NY, USA: ACM, 2004, PP.59-64.
[9]. T.Ghosh, N.Pissinou, and K.Makki, "Collaborative trust-based secure routing against colluding malicious nodes in multi-hop ad hoc networks," in Local Computer Networks, 2004.29th Annual IEEE International Conference on, Nov.2004, pp.224-231.

Abstract:Epidemic routing and two-hop forwarding routing are two routing schemes used in delay tolerant networks. That allows multiple message replicas to be received in order to increase message delivery ratio and to reduce message delivery delay. But this suffers from buffer space limitation. Thus, to achieve efficient utilization of network resources, it is important to come up with an new message scheduling strategy to determine which messages should be forwarded and which should be dropped in case of buffer is full. A novel message scheduling framework for epidemic and two-hop forwarding routing maintains the forwarding or dropping decision. It checks for the nodes priority for message delivery. This can be made at a node during each contact to achieve optimal message delivery ratio or message delivery delay and also buffer space is maintained.
Keywords:- Routing, Buffer Management, message scheduling, DTN.

[1]. Spyropoulos, K. Psounis, and C.S. Raghavendra, "Efficient
[2]. Routing in Intermittently Connected Mobile Networks: The Multiple-Copy Case," IEEE Trans. Networking, vol. 16, no. 1, pp. 63-76, Feb. 2008.
[3]. R.Groenevelt,p.Nain,A.Krifa,C.Barakat and T.Optimal Buffer Management Policies for DelayTolerant Networks,"proc.IEEE CS Fifth Ann.Conf.Sensor,Aug-2008.
[4]. T.Turletti and k.Obraczka,"A Routing Protocol for Socially Selfish Delay Tolerant Networks,"Aug-2009 and G.Koole,"The Message Delay in Mobile Ad Hoc Networks",July-2005.
[5]. Y.-K. Ip, W.-C. Lau, and O.-C. Yue, "Performance Modeling of Epidemic Routing with Heterogeneous Node Types," Proc. IEEE Int'l Conf. Comm. (ICC), 2008.
[6]. Zhang, G. Neglia, J. Kurose, and D. Towsley,"Performance Modeling of Epidemic Routing," Proc. IFIP Networking, 2006.
[7]. Lindgren and K. Phanse, "Evaluation of Queueing Policies and Forwarding Strategies for Routing in Intermittently Connected
[8]. Networks," Proc. First Int'l Conf. Comm. System Software and Middleware, 2006.
[9]. Krifa, C. Barakat, and T. Spyropoulos, "Optimal Buffer Management Policies for Delay Tolerant Networks," Proc. IEEE
[10]. CS Fifth Ann. Conf. Sensor, Mesh, Ad Hoc Comm. and Networks (SECON), 2008. S.C. Nelson, M. Bakht, R. Kravets, and A.F. Harris,

Abstract: This paper deal swithdepthmapsextractionfrommulti-viewvi-deo.Contraryto standard stereo matching-basedapproaches, de-pthmapsarecomputedhereusingopticalflowestimationsbe tweenconsecutiveviews. We compare our approach with the one proposed in the Depth Estimation Reference Software(DERS)for normalization purposes in the ISO-MPEG3DVgroup.Ex-perimentsconductedonsequencesprovidedtothenormalizationcommunityshowthatthepresentedmethodprovideshighqualitydepth maps in terms of depth fidelity and virtual views synthesis. Moreover, being implementedontheGPU,itisfarfasterthantheDERS.
Keywords - Depthmaps, disparitymaps, Multi-view videos, 3DVideos, 3DTV, Normalization, GPGPU, and Opticalflow

[1]. DanielScharsteinandRichardSzeliski,―Ataxonomyandevaluationofdensetwo-framestereocorrespondencealgo rithms,‖InternationalJournalofComputerVision,vol.47,no.1-3,pp.7–42,April2002.
[2]. ManuelWerlberger,WernerTrobin,ThomasPock,AndreasWedel,DanielCremers,andHorstBischof,―Anisotropichuber-L1opticalflow,‖inProceedingsoftheBritishMachineVisionConference(BMVC'09),London,UK,2009.
[3]. WernerTrobin,Local,semi-globalandglobaloptimizationformotionestimation,Ph.D.thesis,GrazUniversityofTech-nology,December2009.
[4]. BertholdK.P.HornandBrianG.Schunk,―Determingopticalflow,‖ArtificialIntelligence,vol.17,pp.185–203,1981.
[5]. NilsPapenberg,Andre´sBruhn,ThomasBrox,StephanDidas,andJoachimWeickert,―Highlyaccurateopticflowcomputa-tionwiththeoreticallyjustifiedwarping,‖InternationalJour-nalofComputerVision(IJCV),vol.67,no.2,pp.141–158,April2006.
[6]. ChristopherZach,ThomasPock,andHorstBischof,―Adual-itybasedapproachforrealtimeTV-L1opticalflow,‖inPro-ceedingsoftheDAGM-Symposium,2007,pp.214–223.PeterJ.Huber,RobustStatistics,JohnWileyandsons,1981.
[7]. Eun-KyungLee,Yun-SukKang,Jae-IlJung,andYo-ShunHo,―3-dvideogenerationusingmulti-depthcamerasystem,‖ISO-MPEGInputdocumentm17225,GwangjuInstituteofScienceandTechnology(GIST),Kyoto,Japan,2010.
[8]. E.Gershikov,E.LaviBurlak,andM.Porat,―Correlation-basedapproachtocolorimagecompression,‖SP:IC,vol.22,no.9,pp.719–733,Oct.2007.

Abstract: Medical imaging equipment is taking on an increasingly critical role in healthcare as the industry strives to lower patient costs and achieve earlier disease prediction. Due to complexity of their mathematical calculation, many QRS detectors are implemented in software and cannot operate in real time. This project presents a real-time hardware based solution for this task. Several techniques have been proposed in literature survey to achieve high speed implementation and detection of QRS complex. The mathematical morphological technology extracts the effective information with low SNR by removal of baseline wandering and background noise from original ECG image. The multi pixel modulus accumulation employs to act as a low-pass filter to determine the maximum value of QRS. Finally threshold decided the accurate range of QRS. The proposed new hardware architecture is designed in an alter a embedded system image processing framework with NIOS II RISC processor. The ECG image waveform stored in flash memory and algorithms, manipulations are done in NIOS II processor. The proposed hardware architecture utilizes the area and it dissipates power at least few milliwatts. It achieves excellent sensitivity, detection rate.
Key terms: Electrocardiogram (ECG), Field programmable gate array (FPGA), Mathematical morphology, QRS detection, Very large scale integration (VLSI) architecture.

[1]. B.U.Kohler, C.Hennig, and R.Orglmeister, (Jan. 2002) "The principles of software QRSdetection," IEEE Eng. Med. Biol. Mag., vol. 21, no. 1, pp. 42–57.
[2]. Chris F.Zhang and Tae-Wuk Bae, (Mar. 2012) "VLSI Friendly ECG QRS Complex Detector for Body Sensor Networks," in Proc. Int. Conf. IEEE Biomed. Eng.
[3]. Vijaya.V, Vaishali Baradwaj, Jyothirani Guggilla "Low power FPGA implementation of real-time QRS detection algorithm" International Journal of Science, Engineering and Technology Research (IJSETR), November 2012.
[4]. Luc Vincent,(August 1991) "Recent Developments In Morphological Algorithms", in Proc.8 th International Congress for Stereology.Irvine CA.1/Suppl 1.pp. 521-532.
[5]. F. Zhang, J. Tan, and Y. Lian, (Nov. 2007) "An effective QRS detection algorithm for wearable ECG in body area network," in Proc. Int. Conf. IEEE Biomed. Circuits Syst., Montreal, ON, Canada, pp.195–198.
[6]. Chio In Ieong, Mang I Vai and Peng Un Mak,(August.2008) "ECG QRS Complex Detection with Programmable Hardware "in Proc. 30th Annual International IEEE EMBS Conference Canada.
[7]. F. Zhang and Y. Lian, "Effective ECG QRS detection based on multiscale mathematical morphologyfiltering," IEEE Trans. Biomed. Circuits Syst., vol. 3, no. 4, pp. 220–228, Aug. 2009.
[8]. J. Hu and S. Bao, "An approach to QRS complex detection based on multiscale mathematical morphology," in Proc. 3rd IEEE Int. Conf. Biomed. Eng. Inform. (IEEE BMEI 2010), 2010, p. 725.
[9]. C.-H. N. Chu and E. J. Delp, "Impulsive noise suppression and background normalization of electrocardiogram using morphological operators," IEEE Trans. Biomed. Eng., vol. 36, no. 2, pp. 262–273, Feb. 1989.
[10]. P. E. Trahanias, "An approach to QRS complex detection using mathematical morphology," IEEE Trans. Biomed. Eng., vol. 40, no. 2, pp. 201–205, Feb. 1993.

Abstract: To perform tracking in an illumination insensitive feature space, called the gradient logarithm field (GLF) feature space. The GLF feature mainly depends on the intrinsic characteristics of a face and is only marginally affected by the lighting source. The GLF feature is a global feature and does not depend on a specific face model, and thus is effective in tracking low-resolution faces. By using the GLF face tracking system, the modified image like editing image did not recognition. To overcome this problem, we propose, to find the original image of the editable image by using the outline dimension of the image. To recognition original face from the modified face, we track the inclusive (complete) region of the face. The SFS (Shape from Shading) is used to recover the shape of the face and then find the face after comparing the faces. This project propose a low resolution image to modified recognition original image with SFS techniques and which now are considering illumination variation to perform image-based tracking, which relies on the selective integration of a small subset of pixels that contain a lot of information about the state variables to be estimated. The resulting dramatic decrease in the number of pixels to process results in a substantial speedup of the basic tracking algorithm. We have used this new method within company, a surveillance application, where it will enable new capabilities of the system, i.e. real-time, dynamic background subtraction from a panning and tilting camer
Keywords - Face tracking, Shape from Shading, Illumination variations, low-resolution face

[1]. B. Bambino, M. Yang, and S. Belonged, "Visual tracking with online multiple instance learning," in 2011.
[2]. S. Staler, H. Grabber, and L. Van Goal, "Beyond semi-supervised tracking: Tracking should be as simple as detection, but not simpler than recognition," in 2009.
[3]. S. Zhou, R. Chellappa, and B. Moghaddam, "Visual tracking and recognition using appearance-adaptive models in particle filters", in 2008.
[4]. T. Ahonen, A. Hadid, and M. Pietikainen, "Face description with local binary patterns: Application to face recognition," in Dec.2006.
[5]. H. Grabner, M. Grabner, and H. Bischof, "Real-time tracking via on-line boosting," on 2006.
[6]. G.Prakash, Smart Stego card Based on two factor Authentication by using Image Processing," on 20012

Abstract: The escalation of network security, day-by-day there are many encryption schemes has been come. Belongs to one of them is Attribute-Based Encryption (ABE) system, it is used for more sensitive data is stored by third party websites on the internet,(such as e-mail stored on website in yahoo,google,etc.,)there will be need to encrypt data and gave private key to the individual users for decrypt the data.Secondly,there is another policy has been came it is Cipher text-Attribute-Based Encryption(CP-ABE)technique, encrypted data can be kept confidential even if the storage server is untrusted.It is act against the collusion attacks. But in this (ABE) and (CP-ABE) there will be a drawback of giving private key to other users with the same set of attributes other than the original users persuade to seep out the data and decrypt the data. So the secret was not maintained efficiently, it may not be always possible to mark out the original key users. So this problem rigorously limits the applications of (CP-ABE).[1] I proposed a policy of Traceable Cipher text- Policy Attribute-Based Encryption (T-CP-ABE) systems have been proposed to tackle this problem, but the articulateness of policies in those systems, where only AND gate with wildcard is now supported, and accessed in any monotone access structures. Before that non-monotonic access structure was handled. So the number of intrusion, worms attacks has being caught, so the security was now maintained efficiently. But currently available, that is, this work adds traceability to an existing expressive, efficient, and secure CP-ABE scheme, without declining its security
Keywords:- Cipher text, Traceability, Monotone access, Attribute-Based Encryption.

[1]. V.Goyal,O.Pandey,A.Sahai,and B.Waters,"Attribute-based encryption for fine-grained access control of encrypted data "in Proc.ACM conf. Computer and Communication Security, A.Juels, R.N.Wright, and S.D.C. di Vimercati,Eds., 2006,pp,89-98,ACM
[2]. R.Ostrovsky,A.Sahai,andB.Waters,"Attribute-based encryption with non-monotonic access structures "in Proc.ACM conf. Computer and Communication Security, P.Ning, S.D.C. di Vimercati,Eds.,and P.F.Syverson,Eds.,2007,pp.195-203,ACM.
[3]. A.Sahai and B.Waters,"Fuzzy identity-based encryption," in proc.EUROCRYPT, R.Cramers, Ed., 2005, vol.3494, pp.457-473, ser.Lecture Notes in Computer Science, Springer.
[4]. D.Boneh and M.K.Franklin,"Identity-based encryption from the weil pairing "in Proc.CRYPTO, J.Kilian, Ed., 2001, vol.2139, pp.213-229, ser.Lecture Notes in Computer Science, Springer.
[5]. A.Shamir,"Identity-based cryptosystems and signature schemes, "in Proc.CRYPTO, 1984, pp.47-53.
[6]. J.Bethencourt, A.Sahai, and B.Waters,"Cipher text-policy attribute –based encryption ", in Proc.IEEE Symp.Security and Privacy, 2007, pp.321-334.

Abstract: Mobile Ad-hoc Networks (MANETs) are multihop wireless networks with mobile nodes that can move freely. One fundamental primitive in a MANET is searching a path from a source node to a destination. In MANETs, the network topology changes frequently and unpredictably due to the arbitrary mobility of nodes. This feature leads to frequent path failures and route reconstructions, which causes an increase in the routing control overhead. The main objective of the work is to reduce the overhead of route discovery in the design of routing protocols of MANETs. Neighbour knowledge based routing protocol is used to reduce the overhead in route discovery by selectively broadcasting RREQ packets to the uncovered neighbour set instead of all neighbours. Thereby the congestion in the network is reduced considerably which leads to increased lifetime of the network.
Keywords:- Mobile adhoc networks, neighbor coverage, network connectivity, probabilistic rebroadcast, routing overhead.

[1]. X.M. Zhang A Neighbor Coverage-Based Probabilistic Rebroadcast for Reducing Routing Overhead in Mobile Ad Hoc Networks
[2]. C. Perkins, E. Belding-Royer, and S. Das, Ad Hoc On-Demand Distance Vector (AODV) Routing, IETF RFC 3561, 2003.
[3]. D. Johnson, Y. Hu, and D. Maltz, The Dynamic Source Routing Protocol for Mobile Ad Hoc Networks (DSR) for IPv4, IETF RFC
[4]. 4728, vol. 15, pp. 153-181, 2007.
[5]. H. AlAamri, M. Abolhasan, and T. Wysocki, "On Optimising Route Discovery in Absence of Previous Route Information in MANETs,
[6]. " Proc. IEEE Vehicular Technology Conf. (VTC), pp. 1-5, 2009.
[7]. X. Wu, H.R. Sadjadpour, and J.J. Garcia-Luna-Aceves, "Routing Overhead as a Function of Node Mobility: Modeling Framework
[8]. and Implications on Proactive Routing," Proc. IEEE Int‟l Conf. Mobile Ad Hoc and Sensor Systems (MASS ‟07), pp. 19,2007.
[9]. [S.Y. Ni, Y.C. Tseng, Y.S. Chen, and J.P. Sheu, "The Broadcast Storm Problem in a Mobile Ad Hoc Network," Proc. ACM/IEEE
[10]. MobiCom, pp. 151-162, 1999.

Abstract: Video surveillance is widely used to monitor the place which needs constant security such as Banks, Shopping Malls, Highways, crowded public places, country borders etc. The major disputes include the complex motion behaviours of different human objects, complex scenes with numerous targets, detection of change in human motion. The objective of this paper is to develop a visual detection and tracking system of observing moving objects. We propose the GMM-Likelihood matching Method of tracking algorithm which integrates the adaptive best background detection, data association, adding new hypothesis update kalman measurement, and linear assignment problem to minimise the cost of observation of tracking. The experimental result shows that the active background can be extracted accurately and expeditiously, the algorithm is more robust, and can be utilized in the real time tracking applications.
Index terms - Real-time visual tracking, Active background estimation, Activity modelling, Data association, Video surveillance and monitoring, Gaussian mixture model, negative log likelihood matching, Kalman filter, Linear Assignment problem.

[1]. A. Lipton, H. Fujiyoshi and R. Patil, "Moving target classification and tracking from real-time video," in Proc. of IEEE Workshop Application of Computer Vision, Los Alamitos, CA, Oct. 1998.
[2]. A. Shafie, F. Hafiz, and M. Ali, "Motion detection techniques using optical flow," World Academy of Science. Engineering and Technology, 2009, vol.56, pp.559-561
[3]. L. Wang, W. Hu, and T. Tan. Recent developments in human motion analysis. Pattern Recognition, 36(3):585-601, March 2003.
[4]. N. Friedman and S. Russell, "Image Segmentation in Video Sequences: The 13th Conference on Uncertainty in Artificial Intelligence, Brown University, Rhode Island, Morgan Kaufmann Publishers, Inc., San Francisco, 1997, pp. 175-181.
[5]. C. Stauffer and W. Grimson "Adaptive Background Mixture Models for Real-Time Tracking," Proceedings of IEEE Computer Vision and Pattern Recognition, Vol. 2, 1999, pp. 246-252.
[6]. C. Stauffer and W. Grimson, "Learning Patterns of Activity Using Real-Time Tracking" IEEE Transactions on Pattern Analysis & Machine Intelligence, Vol. 22, No. 8, 2000, pp. 747-757.
[7]. W. Grimson, C. Stauffer, R. Romano and L. Lee, "Using Adaptive Tracking to Classify and Monitor Activity in a Site," Proceedings of IEEE Computer Society Conference on Computer Vision and Pattern Recognition, 1998, pp. 22-29.
[8]. Wren, R. Christopher, A. Azarbayejani, T. Darrell and A, Pentland, "Pfinder: real-time tracking of the human body", IEEE Transactions on Pattern Analysis and Machine Intelligence, 1997, 19(7), pp.780-785.
[9]. O. Javed, K. Shafique and M. Shah. "A hierarchical approach to robust background subtraction using color and gradient information". in Proc. Of IEEE Workshop Motion Video Computing, Dec. 2002, pp.22-27.
[10]. S. Zhang et al, "Dynamic background modeling and subtraction using spatio-temporal local binary patterns," in Proc. of IEEE Int. Conf. On Image Processing, 2008, pp.1556-1559.

Abstract: Database systems for uncertain and probabilistic data promise to have many applications. Query processing on uncertain data occurs in the contexts of data warehousing, data integration, and of processing data extracted from the Web. Data cleaning can be fruitfully approached as a problem of reducing uncertainty in data and requires the management and processing of large amounts of uncertain data. Decision support and diagnosis systems employ hypothetical queries. Scientific databases, which store outcomes of scientific experiments, frequently contain uncertain data such as incomplete observations or imprecise measurements. Sensor and RFID data is inherently uncertain. Applications in the contexts of fighting crime or terrorism, tracking moving objects, surveillance, and plagiarism detection essentially rely on techniques for processing and managing large uncertain datasets. Beyond that, many further potential applications of probabilistic databases exist and will manifest themselves once such systems become available. Frequent items in a large data set are commonly referred to as heavy hitters. More precisely, the heavy hitters in a data set are those items whose relative frequency exceeds a specified threshold. We can easily adapt our algorithms to answer top-k queries, returning the k items with the largest confidence of being heavy hitters.
Index terms - Uncertain data, knowledge representation Expected rank, topk values

[1]. P. Agrawal, O. Benjelloun, A. Das Sarma, C. Hayworth, S. Nabar,T. Sugihara, and J. Widom, "Trio: A System for Data,Uncertainty, and Lineage," Proc. Int‟l Conf. Very Large Data Bases (VLDB), 2006.
[2]. L. Antova, C. Koch, and D. Olteanu, "10106 Worlds and Beyond:
[3]. Efficient Representation and Processing of Incomplete Information,"Proc. IEEE Int‟l Conf. Data Eng. (ICDE), 2007.
[4]. L. Antova, T. Jansen, C. Koch, and D. Olteanu, "Fast and Simple Relational Processing of Uncertain Data," Proc. IEEE Int‟l Conf.
[5]. Data Eng. (ICDE), 2008. O. Benjelloun, A.D. Sarma, A. Halevy, and J. Widom, "ULDBs:
[6]. Databases with Uncertainty and Lineage," Proc. Int‟l Conf. Very Large Data Bases (VLDB), 2006.
[7]. T. Bernecker, H.-P. Kriegel, M. Renz, F. Verhein, and A. Zuefle, "Probabilistic Frequent Itemset Mining in Uncertain Databases,"
[8]. Proc. ACM SIGKDD Int‟l Conf. Knowledge Discovery and Data Mining (KDD), 2009.
[9]. G. Beskales, M.A. Soliman, and I.F. Ilyas, "Efficient Search for the Top-k Probable Nearest Neighbors in Uncertain Databases," Proc.
[10]. VLDB Endowment, vol. 1, pp. 326-339, 2008.

Abstract: Mobile ad hoc network (MANET) is a self-configuring infrastructureless network of mobile devices connected by wireless. This paper focuses a new power aware routing and grouping multicast algorithm to increase the lifetime of node and network within the mobile ad hoc network. Here multicasting from the source to a group of destination nodes is done by considering two metrics, namely residual battery capacity of the node and relay capacity of the node. This algorithm is used to reduce the energy consumption of all nodes in mobile ad hoc network. In proposed model the lifetime of the node and network is increased and the packet loss is identified.
Index terms - MANET, residual battery capacity, relay capacity.

[1] M. Cagalj, J. P. Hubaux, C. Enz, "Minimum-energy broadcast in wireless networks: NP-completeness and distribution issues," in Proc. ACM 8th Annu. Int. Conf. Mobile Comput. Netw., 2002, pp. 172–182.
[2] I. Kang and R. Poovendran, "Maximizing static network lifetime of wireless broadcast ad hoc networks," in Proc. IEEE Int. Conf. Commun., May 2003, pp. 2256– 2261.
[3] J. E. Wieselthier, G. D. Nguyen, and A. Ephremides, "Algorithms for energy-efficient multicasting in static ad hoc wireless networks," J. Mobile Netw., vol.6, no.3, pp. 251–263, 2001.
[4] W. H. Cheng, C.-Y. Wen, and K.T. Feng, "Power controlled hybrid multicast routing protocol for mobile ad hoc networks," in Proc. IEEE Veh. Technol. Conf., May 2006, pp. 1087–1089.
[5] S. Singh, M. Woo, and C. S. Raghavendra, "Power-aware with routing in mobile ad hoc networks," in Proc. ACM MOBICOM, 1998, pp. 368–369.
[6] B. Floréen, P. Kaski, J. Kohonew, and P. Orponen, "Multicast time maximization in energy constrained wireless networks," in Proc. Workshop Found. Mobile Computing, 2003, pp. 50–58.
[7] W. Liang, "Approximate minimum-energy multicasting in wireless ad hoc networks," IEEE Trans., Mobile Comput., vol. 5, no. 4, pp. 377–387, Apr. 2006.
[8] J. A. Sanchez and P. M. Ruiz, "Improving delivery ratio and power efficiency in unicast geographic routing with a realistic physical layer for wireless sensor networks," in Proc. 9th EUROMICRO Conf. Digital Syst. Design, Archit., Methods Tools, 2006, pp. 591–597.
[9] J. E. Wieselthier, G. D. Nguyen, and A. Ephremides, "On the construction of energy-efficient broadcast and multicast trees in wireless networks," in Proc. IEEE 9th Annu. Joint Conf. IEEE Comput. Commun. Soc., Mar. 2000, pp. 585–594.
[10] B. Wang, and S. K. S. Gupta, "S-REMiT, an algorithm for enhancing energy efficiency of multicast trees in wireless ad hoc networks," in Proc. IEEE GLOBECOM, May 2003, pp. 3519–3524.

Abstract: Video surveillance is widely used to monitor the place which needs constant security such as Banks, Shopping Malls, Highways, crowded public places, country borders etc. The major disputes include the complex motion behaviours of different human objects, complex scenes with numerous targets, detection of change in human motion. The objective of this paper is to develop a visual detection and tracking system of observing moving objects. We propose the GMM-Likelihood matching Method of tracking algorithm which integrates the adaptive best background detection, data association, adding new hypothesis update kalman measurement, and linear assignment problem to minimise the cost of observation of tracking. The experimental result shows that the active background can be extracted accurately and expeditiously, the algorithm is more robust, and can be utilized in the real time tracking applications.
Index terms - Adverse drug reactions, data mining methods.

[1]. Christopher C. Yang, Ling Jiang, Haodong Yang, Xuning Tang." Detecting Signals of Adverse Drug Reactions from HealthConsumer Contributed Content in Social Media".2012
[2]. G. Niklas Norén · Johan Hopstadius · Andrew Bate · Kristina Star · I. Ralph Edwards." Temporal pattern discovery in longitudinal electronic patient records".2009
[3]. A. Mansour, Y. Ji, H. Ying, R.M. Massanari, P. Dews, J. Tran, R.E. Miller, and "A Potential Causal Association Mining Algorithm for Screening Adverse Drug Reactions in Postmarketing Surveillance," IEEE Trans. Information Technology in Biomedicine, 2011.
[4]. L. Szathmary, P. Valtchev and, A. Napoli, "Towards Rare Itemset Mining," Proc IEEE 19th Int'l Conf. Tools with Artificial Intelligence, 2007.
[5]. P.M. Doraiswamy, and A. Szarfman, ,"Pharmacovigilance in the 21st Century: New Systematic Tools for an Old Problem," Pharmacotherapy, , 2004.
[6]. H. He, G. Williams, H. Jin, J. Chen and C. Kelman, ,"Mining Unexpected Temporal Associations: Applications in the Detecting Adverse Drug Reactions," IEEE Trans. Information Technology in Biomedicine, vol. 12, no. 4, pp. 488-500, July 2008.
[7]. Ji, H.Ying,M.S.Farber, J.Yen,"ADistributed, Collabrative Intelligent Agent Approach for Proactive Pastmarketing Drug Safety Surveillance,"IEEE Trans.Information Technology in Biomedicine.vol.14.no.3. Dec 2010.
[8]. B. Scho¨ lkopf and I. Guyon, D. Janzing, "Causality: Objectives and Assessment," JMLR Machine Learning Research Workshop and Conf. Proc., vol. 6, pp. 1-42, 2010..
[9]. J. Pearl, Causality: Models, Reasoning and Inference, second ed. Cambridge Univ. Press, 2009.
[10]. [Scho¨ lkopf, and I. Guyon, D. Janzing "Causality: Objectives and Assessment," JMLR Machine Learning Research Workshop and Conf. Proc., vol. 6, pp. 1-42, 2010.

Abstract: This paper deals with depth maps extraction from multi-view vi- deo. Contrary to standard stereo matching-based approaches, de- PTH maps are computed here using optical flow estimations be- tween consecutive views. We compare our approach with the one proposed in the Depth Estimation Reference Software (DERS) for normalization purposes in the ISO-MPEG 3DV group. Ex- periments conducted on sequences provided to the normalization community show that the presented method provides high quality depth maps in terms of depth fidelity and virtual views synthesis. Moreover, being implemented on the GPU, it is far faster than the DERS.
Index terms - Depth maps, disparity maps, Multi-view videos, 3D Videos, 3DTV, Normalization, GPGPU, Optical flow

[1]. Daniel Scharstein and Richard Szeliski, ―A taxonomy and evaluation of dense two-frame stereo correspondence algo- rithms,‖ International Journal of Computer Vision, vol. 47, no. 1-3, pp. 7–42, April 2002.
[2]. Manuel Werlberger, Werner Trobin, Thomas Pock, Andreas Wedel, Daniel Cremers, and Horst Bischof, ―Anisotropic huber-L1 optical flow,‖ in Proceedings of the British Machine Vision Conference (BMVC'09), London, UK, 2009.
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Abstract: Multimodal biometric can overcome the limitation possessed by single biometric trait and give better classification accuracy. The present work proposes an authentication system with the fingerprint, face and iris multimodal biometric system based on fusion at the feature level. The performances of fingerprint, face and iris recognition can be enhanced using a proposed feature selection method to take an optimal subset of features. Fingerprints are the most popular and studied biometric features. Their stability and uniqueness makes the fingerprint identification system extremely reliable and useful for security applications. An optimized fingering print algorithm is used to extract the ridge count, ridge length, and ridge curvature direction features from a fingerprint. Iris is also a unique biometric feature, advanced iris and sclera algorithm is used to extract the iris and sclera features of the eye and Eigen face feature extraction algorithm is used to extract the face feature extraction. The results indicate that the proposed feature selection method is able to improve the classification accuracy in terms of total error rate.
Index terms - Biometrics, Multimodal, Face, Fingerprint, Iris and Fusion.

[1] Vincenzo Conti, Carmelo Militello, Filippo Sorbello," A Frequency-based Approach for Features Fusion in Fingerprint and Iris Multimodal Biometric Identification Systems", JULY 2010.
[2] Abhishek Nagar, Karthik Nandakumar, and AnilK. Jain "Multibiometric Cryptosystems Based on Feature-Level Fusion", FEBRUARY 2012.
[3] Krishneswari, K. and S. Arumugam," Multimodal Biometrics using Feature Fusion", Journal of Computer Science, 2012.
[4] Sumit Shekhar, Vishal M. Patel, Nasser M. Nasrabadi and Rama Chellappa" Joint Sparse Representation for Robust Multimodal Biometrics Recognition", 2013.
[5] Dhiman Karmakar • C. A. Murthy, "Generation of new points for training set and feature-level fusion in multimodal biometric identification".Springer, 2013.
[6] Maryam Eskandari and Onsen Toygar" Fusion of face and iris biometrics using local and global feature extraction methods", Springer, Nov 2012.