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Abstract: Heart disease is a major cause of morbidity and mortality in present society. Medicinal identification is extremely important but complicated task that should be performed precisely and proficiently. Although substantial advancement has been made in the diagnosis and treatment of heart disease, additional investigation is still needed. The obtainability of massive expanses of medical data leads to the need for powerful data analysis tools to extract useful information. There is a massive data available within the healthcare organisations. However, there is a task of effective analysis tools to discover trends in data , hidden relationships , Knowledge discovery and data mining have found numerous application in business and scientific domain. Investigators have long been apprehensive with applying statistical and data mining tools to improve data analysis on very big data sets. Any of the disease diagnosis is one of the applications where data mining tools are proving successful results. This paper projected to find out the heart attack type through data mining.
Keywords: Data Mining, Heart Disease.
[1] Sellappan P., Rafiah A., Intelligent Heart Disease Prediction System Using Data Mining Techniques, IJCSNS, VOL.8, Aug 2008.
[2] M. A. Jabbar , B.L Deekshatulu, Priti Chandra, Classification of Heart Disease Using Artificial Neural Network and Feature Subset Selection, GJCST, Volume13, Issue 3.
[3] Nang Y. Hand book of Data Mining, Lawrence Erlbaum associates (2003).
[4] M. A. Jabbar et.al., Predictions Of Risk Score For Heart Disease Using Associative Classification & Hybrid Feature Subset Selection. In Proceedings of 12th International Conference on Intelligent Systems Design and Applications (ISDA), pages 628-634.
[5] M. Ambarasi et.al, Enhanced Prediction of Heart Disease With Feature Subset Selection Using Genetic Algorithm, JEST Vol2, pp 5370-5376.
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Paper Type | : | Research Paper |
Title | : | Fake Reviewer Groups' Detection System |
Country | : | India |
Authors | : | Kolhe N. M. || Joshi M. M. || Jadhav A. B. || Abhang P. D. |
: | 10.9790/0661-16150609 |
Abstract: We have the cyber space occupied with most of the opinions, comments and reviews. We also see the use of opinions in decision making process of many organizations. Not only organizations use these reviews but also users use them to a great extent. So using this opportunity, many groups try to game this system by providing fake reviews. These reviews enhance or demote the emotions of the products they are acting upon. Many of the organizations pay such groups to promote their product and acquire most of the market share. For a genuine user experience these fake reviews should be detected and deleted. Work had been performed on detecting individual fake reviews and individual fake reviewers; but a fake reviewer group is much more damaging as they take the total control of the product sentiments. This project presents a way to detect these fake reviewer groups. This uses indicators and models to calculate the spamicity of the group. This system deals with detecting fake reviewers' group rather than individual fake reviewers.
Keywords: Fake review detection, Group opinion spam, Opinion spam.
[1] Amir A. Sheibani IST' 2012.Opinion mining and opinion spam. Shiraz University.
[2] Nitin Jindal and bing liu 7th IEEE ICDM. Analyzing and detecting review spam. University of illinios, Chicago.
[3] Yingying ma and fengjun li. 8th ICCC. Detecting review spam: challenges and opportunities. The University of Kansas, Lawrence.
[4] C.L. lai, K.Q. Xu, Raymond Y.K. lau, City University of Hong Kong, Y. Li Queensland University ofTechnology, L. Jing Beijing Jiaotong University, China. IEEE ICEBE. Towards a language modeling approach for consumer review spam detection.
[5] Siddu P. Algur, Amit P. Patil, P.S. Hiremath, S. Shivashankar. Conceptual level similarity measure based review spam detection. B.V. Bhoomaraddi College of engineering and technology, hubli, Karnataka, India.
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Abstract: Diseases in plants cause major production and economic losses as well as reduction in both quality and quantity of agricultural products. Now a day's plant diseases detection has received increasing attention in monitoring large field of crops. Farmers experience great difficulties in switching from one disease control policy to another. The naked eye observation of experts is the traditional approach adopted in practice for detection and identification of plant diseases. In this paper we review the need of simple plant leaves disease detection system that would facilitate advancements in agriculture. Early information on crop health and disease detection can facilitate the control of diseases through proper management strategies. This technique will improves productivity of crops. This paper also compares the benefits and limitations of these potential methods. It includes several steps viz. image acquisition, image pre-processing, features extraction and neural network based classification.
Keywords: Disease detection, Image acquisition, pre-processing, features extraction, classification, symptoms and neural network.
[1] Anand H. Kulkarni, Ashwin Patil R. K., Applying image processing technique to detect plant diseases, International Journal of Modern Engineering Research, vol.2, Issue.5, pp: 3661-3664, 2012.
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[3] P. Revathi, M. Hemalatha, Classification of Cotton Leaf Spot Diseases Using Image Processing Edge Detection Techniques, IEEE International Conference on Emerging Trends in Science, Engineering and Technology, pp-169-173, Tiruchirappalli, Tamilnadu, India, 2012.
[4] Tushar H. Jaware, Ravindra D. Badgujar and Prashant G. Patil, Crop disease detection using image segmentation, National Conference on Advances in Communication and Computing, World Journal of Science and Technology, pp:190-194, Dhule, Maharashtra, India, 2012.
[5] Prof.Sanjay B. Dhaygude, Mr.Nitin P. Kumbhar, Agricultural plant Leaf Disease Detection Using Image Processing, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering , S & S Publication vol. 2, Issue 1, pp: 599-602, 2013. Nov-1999.
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Abstract:The network performance in WSNs is mainly affected by the congestion due to bursty traffic. Congestion can cause large packet drops, increased energy consumption and latency. Different traffic rate control mechanisms have proposed to mitigate congestion and most of these mechanisms are greatly affecting the fidelity requirement of the applications. In this paper, we proposed an algorithm named, Mitigating Congestion using Distance based Routing (MCDR) technique to mitigate congestion. This technique has successfully reduced congestion by scattering the traffic through the nodes which are placed at comparatively minimum distance from the sink and whose Queue Length is below the threshold value. The Residual Energy and Depth are two added parameters to strengthen the scattering decision. Simulation results shows that the network throughput has significantly improved with minimized latency due to the reduction of loops when compared to previous works.
Keywords: Congestion, Distance based routing, Wireless Sensor Networks (WSNs), Residual Energy.
[1] Y. Yi and S. Shakkottai, "Hop-by-Hop Congestion Control over a Wireless Multi-Hop Network," In IEEE/ACM Transactions on Networking, vol. 15, no. 1, pp. 133-144, Feb. 2007.
[2] J. B. Helonde, V.Wadhai, V. Deshpande, and S. Sutar, "EDCAM: Early Detection Congestion Avoidance Mechanism for Wireless Sensor Network," In International Journal of Computer Applications, vol. 7, no. 2, pp. 11-14, Sep. 2010.
[3] K. K. Sharma, H. Singh, and R. B. Patel "A Hop by Hop Congestion Control Protocol to Mitigate Traffic Contention in Wireless Sensor Networks," In International Journal of Computer Theory and Engineering, vol. 2, no. 6, pp. 986-991, Dec. 2010.
[4] S. Chen and N. Yang, "Congestion Avoidance Based on Lightweight Buffer Management in Sensor Networks," In IEEE Transactions Parallel and Distributed Systems, vol. 17, no. 9, pp. 934-946, Sep. 2006.
[5] J. Kang, Y. Zhang, and B. Nath, "TARA: Topology-Aware Resource Adaptation to Alleviate Congestion in Sensor Networks," In IEEE Transactions Parallel and Distributed Systems, vol. 18, no. 7, pp. 919-931, July 2007.
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Abstract: Cloud Computing is the long dreamed vision of computing as a utility, where users can remotely store their data into the cloud so as to enjoy the on-demand high quality applications and services from a shared pool of configurable computing resources. By data outsourcing, users can be relieved from the burden of local data storage and maintenance. However, the fact that users no longer have physical possession of the possibly large size of outsourced data makes the data integrity protection in Cloud Computing a very challenging and potentially formidable task, especially for users with constrained computing resources and capabilities. Thus, enabling public auditability for cloud data storage security is of critical importance so that users can resort to an external audit party to check the integrity of outsourced data when needed. To securely introduce an effective third party auditor (TPA), the following two fundamental requirements have to be met: 1) TPA should be able to efficiently audit the cloud data storage without demanding the local copy of data, and introduce no additional on-line burden to the cloud user; 2) he third party auditing process should bring in no new vulnerabilities towards user data privacy. In this paper, we utilize and uniquely combine the public key based homomorphic authenticator with random masking to achieve the privacy-preserving public cloud data auditing system, which meets all above requirements. To support efficient handling of multiple auditing tasks, we further explore the technique of bilinear aggregate signature to extend our main result into a multi-user setting, where TPA can perform multiple auditing tasks simultaneously. Extensive security and performance analysis shows the proposed schemes are provably secure and highly efficient.
Keywords: Cloud computing, Dynamic Encryption, Third Party Auditor (TPA), Threats.
[1] C. Wang, Q. Wang, K. Ren, and W. Lou, "Privacy-preserving public auditing for storage security in cloud computing," in Proc. of IEEE INFOCOM'10, March 2010.
[2] P. Mell and T. Grance, "Draft NIST working definition of cloud computing," Referenced on June. 3rd, 2009. http://csrc.nist.gov/groups/SNS/cloudcomputing/index.html.
[3] M. Armbrust, A. Fox, R. Griffith, A. D. Joseph, R. H. Katz, A. Konwinski, G. Lee, D. A. Patterson, A. Rabkin, I. Stoica, and M. Zaharia, "Above the clouds: A Berkeley view of cloud computing," University of California, Berkeley, Tech. Rep. UCBEECS-2009-28, Feb 2009.
[4] Cloud Security Alliance, "Top threats to cloud computing,"2010, http://www.cloudsecurityalliance.org
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Abstract: Text classification is the task of assigning predefined categories to free-text documents based on their content. Traditional approaches used unigram based models for text classification. Unigram based models such as Bag Of Words(BOW) models are not considering co-occurrence of set of words in a document level. This paper proposes a way to find co-occurrence feature from anchor text of wikipedia pages, proposes a way to incorporate co-occurrence feature to BOW model. Finally the method is analyzed to know how it performs in task of text classification.
Keywords: Text Classification, Natural Language Processing, Machine Learning, Bag Of Words, Naive Bayes classifier.
[1] Fabrizio Sebastiani, Machine learning in automated text categorization, ACM computing surveys (CSUR) 34 (2002), no. 1, 1–47.
[2] Kjersti Aas and Line Eikvil, Text categorisation: A survey, Raport NR 941 (1999).
[3] Martin F Porter, An algorithm for suffix stripping, Program: electronic library and information systems 14 (1980), no. 3, 130–137.
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Abstract: Wireless spoofing attacks are easy to launch and can significantly impact the performance of networks. Although the identity of a node can be verified through cryptographic authentication, conventional security approaches are not always desirable because of their overhead requirements. The project is proposed to use spatial information, a physical property associated with each node, hard to falsify, and not reliant on cryptography, as the basis for 1) detecting spoofing attacks; 2) determining the number of attackers when multiple adversaries masquerading as the same node identity; and 3) localizing multiple adversaries. It is proposed to use the spatial correlation of received signal strength (RSS) inherited from wireless nodes to detect the spoofing attacks. It formulates the problem of determining the number of attackers as a multi-class detection problem. Cluster-based mechanisms are developed to determine the number of attackers. When the training data are available, the project explores using the Support Vector Machines (SVM) method to further improve the accuracy of determining the number of attackers. The localization results use a representative set of algorithms that provide strong evidence of high accuracy of localizing multiple adversaries. In addition, a fast and effective mobile replica node detection scheme is proposed using the Sequential Probability Ratio Test. evaluated our techniques through two testbeds using both an 802.11 (WiFi) network and an 802.15.4 (ZigBee) network in two real office buildings.
Keywords: Wireless network security, spoofing attack, attack detection, localization.
[1] Bellardo J. and Savage S. (2003) "802.11 Denial-of-Service Attacks:Real Vulnerabilities and Practical Solutions", Proc. USENIX Security Symp, pp. 15-28.
[2] Bohge M. and Trappe W. (2003) "An Authentication Framework for Hierarchical Ad Hoc Sensor Networks", Proc. ACM Workshop Wireless Security (WiSe), pp. 79-87.
[3] Brik V., Banerjee S., Gruteser M. and Oh s. (2008) "Wireless Device Identification with Radiometric Signatures" ,Proc. 14th ACM Int'l Conf. Mobile Computing and Networking, pp. 116-127.
[4] Chen Y., Trappe W., and Martin R.P. (May 2007) "Detecting and Localizing Wireless Spoofing Attacks", Proc. Ann. IEEE Comm. Soc. Conf. Sensor, Mesh and Ad Hoc Comm. and Networks, pp.5-10.
[5] Chen Y., Kleisouris K., Li X., Trappe W. and Martin R.P. (2006 ) "The Robustness of Localization Algorithms to Signal Strength Attacks: A Comparative Study", Proc. Int'l Conf. Distributed Computing in Sensor Systems (DCOSS),pp. 546-563.
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Abstract: Energy efficiency is a central challenge in sensor networks, and the radio is a major contributor to overall energy node consumption. These Wireless Sensor Networks have severe resource constrains and energy conservation is very essential. The aim of this project is to reduce the energy consumption in wireless sensor networks. This paper proposes adaptive radio low-power sleep modes based on current traffic conditions in the network. It provides an analytical model to conduct a comparative study of different MAC protocols (BMAC, TMAC, SMAC, DMAC) suitable for reduction of energy consumption in wireless environment. This technique exposes the energy trade-offs of different MAC protocols. It first introduces a comprehensive node energy model, which includes energy components for radio switching, transmission, reception, listening, and sleeping for determining the optimal sleep mode and MAC protocol to use for given traffic scenarios. The model is then used for evaluating the energy-related performance of our recently proposed RFID Impulse protocol enhanced with adaptive low-power modes, and comparing it against BMAC under varying data rates. The comparative analysis confirms that RFID Impulse with adaptive low power modes provides lower energy consumption than the BMAC and DMAC in low traffic scenario. The evaluation also yields the optimal settings of low-power modes on the basis of data rates for node platform, and provides guidelines and a simple algorithm for the selection of appropriate MAC protocol, low-power mode, traffic requirements of a sensor network application.
Index Terms: RFID, wake-up radio, sleep mode, adaptive, energy efficiency, MAC protocols, routing protocols, energy model, sensor networks.
[1] Radio Sleep Mode Optimization in Wireless Sensor Networks Raja Jurdak, Member, IEEE, Antonio G. Ruzzelli, and Gregory M.P. O‟Hare
[2] R. Jurdak, A.G. Ruzzelli, and G.M.P. O‟Hare, "Adaptive Radio Modes in Sensor Networks: How Deep to Sleep?" Proc. IEEE Comm. Soc. Conf. Ad Hoc and Sensor Networks (SECON '08), June 2008.
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Paper Type | : | Research Paper |
Title | : | A Study on Quality of Service for Computer Networks |
Country | : | India |
Authors | : | D. Rama Krishna Reddy || D. Hemalatha || Azmath Mubeen |
: | 10.9790/0661-16155155 |
Abstract: This paper presents some of the basic concepts of Quality of Service. The major research areas of Quality of Service for Computer Networks are represented. The paper also correlates and compares few of the current and evolving and popular Quality of Service Routing techniques.
Keywords: GoS, QoS, QoS Routing.
[1] X. Yuan and W. Zheng, "A Comparative Study of Quality of Service Routing Schemes That Tolerate Imprecise State Information," Florida State University Computer Science Department, Technical Report. [Online].Available:http://websrv.cs.fsu.edu/research/reports/TR-010704.pdf.
[2] "Quality of Service Based Routing: A Performance Perspective", ACM SIGCOMM, 1998.
[3] Chao Peng, Hong Shen, ''New Algorithms For Fault-Tolerant QoS Routing",submitted to the International Conference Dependable Systems and Networks(DSN-2006)
[4] S. Chen and K. Nahrstedt, "An Overview of Quality of Service Routing for Next-Generation High-Speed Networks: Problems and Solutions,".
[5] "Predictive routing to enhance QoS for stream-based flows sharing excess bandwidth" Xun Su, Gustavo de Veciana.
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Abstract: In the mobile ad hoc networks, the major role is played by the routing protocols in order to route the data from one mobile node to another mobile node with security. But in such mobile networks, routing protocols are vulnerable to various kinds of security attacks such as blackhole node attacks. The routing protocols of MANET are unprotected and hence resulted into the network with the malicious mobile nodes in the network. These malicious nodes in the network are basically acts as attacks in the network. In this paper, we are considering the one such attack on mobile ad hoc network called blackhole attack. We proposed methods to detect and prevent cooperative blackhole attack in the MANET. We modify the existing DSR protocol to adopt the proposed cooperative algorithm of blackhole attack detection as well as prevention without the affecting overall performance of the network. Mobile nodes in the mobile ad hoc networks are acts host node and router node means nodes in the MANET are responsible for both data forwarding and routing mechanisms. But because of few malicious nodes which acts as misbehaving & selfish nodes, data packets not delivered to the destination and dropped by such nodes. We investigating the performance of existing DSR protocol with this new modified security enabled DSR protocol using the performance metrics like throughput, delay and jitter. Simulations for this work are carried out over the NS2 simulator.
Keywords: Ad Hoc Networks, Black Hole Attack, DSR, Routing Protocols, Security.
[1] Sun B, Guan Y, Chen J, "Detecting Black Hole Attack in Mobile Ad Hoc Networks", 5th European Personal Mobile
Communications Conference Glasgow, United Kingdom, 22-25 April 2003.
[2] Al –Shurman M, Yoo S-M, Parks S, "Black Hole Attack in Mobile Ad Hoc Networks", 42nd Annual ACM Southest Regional
Conference (ACM-SE' 42), Huntsville, Alabama, 2-3 April 2004.
[3] Tamilselvan, L. and Sankaranarayanan, V., "Prevention of Blackhole attack in MANET", The 2nd International Conference on
Wireless Broadband and Ultra Wideband Communications. Aus Wireless, 21-21, 2007.
[4] Djenouri D, Badache N, " Struggling Against Selfishness and Black Hole Attacks in MANETs", Wireless Communication and
Mobile Computing Vol. 8 Issue 6, pp 689-704, August 2008.
[5] H.Weerasinghe H. Fu., "Preventing Cooperative Blackhole Attack in Mobile Ad Hoc Networks, Simulation, Implementation and
Evaluation". International Journal of Software Engineering and Its Application vol.2, No.3, 2008.
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Keywords: Mobile Computing, UMKM, Information Technology, IT Performance, Business e-Commerce.
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Paper Type | : | Research Paper |
Title | : | Reversible Encrypted Data Hiding In Encrypted Video |
Country | : | India |
Authors | : | Biby Bino Varghese || Rosna P. Haroon |
: | 10.9790/0661-16157182 |
Keywords: Video Encryption, Data Embedding, Frames.
[1] W.Bender, D.Gruhl, N.Morimoto and A.Lu (1996). Techniques for Data Hiding, IBM Systems Journal. 35(3,4).
[2] Arup Kumar Bhaumik, Minkyu Choi, Roslin J. Robles and Maricel O. Balitanas (2009, June). Data Hiding in Video, International Journal of Database Theory and Applications. 2(2).
[3] A.K.Al-Frajat, H.A.Jalab, Z.M.Kasirun, A.A.Zaidan and B.B.Zaidan "Hiding Data in Video File: An Overview, Journal of Applied Sciences", 2010. pp.1644-1649.
[4] Min Wu, Heather Yu, Bede Liu (2003, June). Data Hiding in Image and Video: Part II – Designs and Applications. IEEE Trans. Image Processing. 12(6).
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Keywords: Data Mining, Association Rule, Fuzzy Association Rule Mining.
[1] Han, J., Kamber, M. (2001). "Data Mining: Concepts and Techniques", Harcourt India Pvt. Ltd. [2] K.SuriyaPrabha, R.Lawrance," Mining Fuzzy Frequent itemset using Compact Frequent Pattern(CFP) tree Algorithm" International Conference on Computing and Control Engineering (ICCCE 2012), 12 & 13 April, 2012.
[3] SunitaSoni, O.P.Vyas,"Fuzzy Weighted Associative Classifier: A Predictive Technique For Health Care Data Mining", International Journal of Computer Science, Engineering and Information Technology (IJCSEIT), Vol.2, No.1, February 2012. [4] Praveen Arora, R. K. Chauhan and AshwaniKush ," Frequent Itemsets from Multiple Datasets with Fuzzy data", International Journal of Computer Theory and Engineering, Vol. 3, No. 2, April 2011. [5] Farah Hanna AL-Zawaidah, YosefHasanJbara and Marwan AL-Abed Abu-Zanona, "An Improved Algorithm for Mining Association Rules in Large Databases", World of Computer Science and Information Technology Journal (WCSIT) ISSN: 2221-0741 Vol. 1, No. 7, 2011, pp. 311-316.
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Paper Type | : | Research Paper |
Title | : | Use of Gait Energy Image in Implementation of Real Time Video Surveillance System |
Country | : | India |
Authors | : | Sonali Vaidya || Dr. Kamal Shah |
: | 10.9790/0661-16158893 |
Keywords: Feature extraction, Gait analysis, GEI (Gait Energy Image), GEI Template Matching, MDA (Multiple Discriminant Analysis), PCA (Principle Component Analysis).
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Keywords: Ad hoc Networks, Energy Management, , DSR Protocol, EE MAC Protocol,, PMAC Protocol.
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