iosr-JCE   Volume-16 ~ Issue-6 ~ Nov-Dec 2014

Abstract:Disruption tolerant networks (DTNs) are characterized by low node density, unpredictable node mobility, and lack of global network information. Most of current research efforts in DTNs focus on data forwarding, but only limited work have been done on providing efficient data access to vehicle users. The proposed Fuzzy Probabilistic Routing Protocol using History of Encounters and Transitivity (FPRoPHET) protocol uses an algorithm that attempts to exploit the non-randomness of real-world encounters by maintaining a set of probabilities for successful delivery to known destinations in the VDTN (delivery predictabilities) and replicating messages during opportunistic encounters only if the Mule that does not have the message appears to have a better chance of delivering it.

1] N. Sadagopan, f. Bai, b. Krishnamachari, and a. Helmy, "paths: analysis Of path duration statistics and their impact on reactive manet routing Protocols," in proceedings of the 4th acm international symposium on Mobile ad hoc networking & computing. Acm, 2003, pp. 245-256.
[2] V.Cerf et al. "rfc 4838, delay-tolerant networking architecture," irtf Dtn research group, 2007.
[3] W.Zhao, m. Ammar, and e. Zegura, "a message ferrying Approach for data delivery in sparse mobile ad hoc networks," In the fifth acm international symposium on mobile ad hoc Networking and computing (mobihoc 2004), roppongi hills, Tokyo, japan, may 24-26, 2004, pp. 187–198.
[4] H.Ammar, "message ferrying: proactive routing in highly-Partitioned wireless ad hoc networks," in the ninth ieee Workshop on future trends of distributed computing systems, San juan, puerto rico, may 28-30, 2003, pp. 308-314.
[5] A.Vahdat and d. Becker, "epidemic routing for partially connected ad hoc networks", tech. Rep. Cs-2000-06, cs dept., duke university, april 2000.

Abstract:Load balancing in cloud is different from the typical architecture of load balancing techniques. This opens up new opportunities and challenges. Resource management is the use of available processors in the most efficient way possible. A CPU scheduling algorithm is said to efficient when it keeps the CPU and disks busy. The Scheduling algorithm is of greater interest if the technique is dynamic.The dynamic technique is of larger interest because of its dynamic adaptability to the current state of the system. In dynamic technique, weights are designated to servers and by searching a lightest server in the whole network, the load is balanced. Key words: Cloud, Cloud environment, Load Balancing, Qualitative, distributed computing, efficiency

[1]. Bestavros (1997): WWW traffic reduction and load balancing through server-based caching. Concurrency, IEEE, 5(1):56-57.
[2]. Ajith Singh N and M. Hemalatha, An Approach on Semi-Distributed Load Balancing Algorithm for Cloud Computing System, International Journal of Computer Applications (0975 – 8887), Volume 56– No.12, 2012.
[3]. Ali M. Alakeel, A guide to dynamic load balancing in distributed computer system, IJCSNS International Journal of Computer Science and Network Security, Vol 10 No.6 2010.
[4]. Bin Fan, Hyeontaek Lim, David G. Andersen, Michael Kaminsky: "Small cache, Big effect: provable Load Balancing for randomly partitioned cluster services
[5]. Charles Border, CloudComputing in the curriculum: Fundamental and Enabling Technologies,
[6]. David Excalante and Andrew J. Korty, Cloud services: policy – Assessment, EDUCAUSE Review. Vol 46, no. 4, 2011.

Abstract: Data mining can be used to model crime detection problems, detect unusual patterns, terrorist activities and fraudulent behaviour. We will look at k-means clustering with some enhancements to aid in the process of identification of crime patterns. The k-means algorithm is one of the frequently used clustering method in data mining, due to its performance in clustering massive data sets. The final clustering result of the k-means clustering algorithm greatly depends upon the correctness of the initial centroids, which are selected randomly. The original k-means algorithm converges to local minimum, not the global optimum. Many improvements were already proposed to improve the performance of the k-means, but most of these require additional inputs like threshold values for the number of data points in a set. In this paper a new method is proposed for finding the better initial centroids and to provide an efficient way of assigning the data points to suitable clusters with reduced time complexity.

Keywords: Clustering, data mining, k-means, counter-terrorism, predictive analytics

[1]. K. A. Abdul Nazeer and M. P. Seba stian, "Improving the accuracy and efficiency of the k-means clustering algorithm," in International Conference on Data Mining and Knowledge Engineering (ICDMKE), Proceedings of the World Congress on Engineering (WCE-2009), Vol 1, July 2009, London, UK.
[2]. Corcoran J.J., Wilson I.D. AND Ware J.A. (2003) Predicting the geo-temporal variations of crime and disorder, International Journal of Forecasting, Vol. 19, Pp.623–634.
[3]. Hsinchun Chen, Wingyan Chung, Yi Qin, et al. Crime Data Mining: An Overview and Case Studies. Proceeding of the 2003 annual national conference on Digital government research, Boston, M.A, 2003, pp 1-5.
[4]. T. Abraham and O. de Vel. Investigating profiling with computer forensic log data and association rules. Proc. Of the IEEE International Conference on Data Mining (ICDM'06), 2006, pp 11-18.
[5]. Gary LaFree and Laura Dugan.( 2007). "Introducing the Global Terrorism Database," Political Violence and Terrorism 19:181-204G. P. Zarri. Semantic web and Knowledge Representation, Proc. Of the 13th International Workshop on Database and Expert System Applications (DEXA'02), 2002, pp. 1529-4188.

Abstract:The job shop scheduling is a very important scheduling problem, which is NP-complete in the strong sense and with well-known benchmark instances of relatively small size, which attest the practical difficulty in solving. Artificial neural network models have been successfully applied to solve such a job-shop scheduling problem (JSSP) known as a Nonpolynomial (NP-complete) constraint satisfaction problem. Our main contribution is an improvement of the algorithm proposed in the literature, which consists optimization of initial value of starting time. The main objective is to minimize the total weighted completion time of the jobs in the system that is the minimization of the makespan time by using the heuristic method. In this study, the heuristic method is used which gives a high quality approximate solution in reasonable time. The main advantage of using Hopfield Neural Network (HNN) is to improve the searching speed for getting an optimal or near optimal solution of a deterministic JSSP for reducing the makespan time. The simulation of the proposed method has been performed on various benchmarks. For two jobs and three machines (2/3/J/Cmax) dataset problem and any dataset problems, the simulation results shows the efficient with respect to the resolution speed, quality of the solution, and the reduction of the computation time which was not solved by Fanaiech et al. So, the simulation results have revealed that proposed heuristic algorithm can find high quality solutions to large sized instances very quickly.

Keywords: Artificial Neural Network, Constraints, Job shop scheduling, Heuristic, Hopfield network, Optimization methods.

[1] T.M Willems and J.E Rod, " Neural nets for job shop scheduling will they do the job?" Proc. IFAC 12th World Conf., 1993, vol. 3, pp. 53–56.
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[3] ] J. Käschel, T. Teich, G. Köbernik, and B. Meier, "Algorithms for the jobshop scheduling problem: A comparison of different methods," in Proc. Eur. Symp. Intell. Techn., Chania, Greece, Jun. 1999.
[4] A. Ferrolho and M. Crisostomo, "Intelligent control and integration software for flexible manufacturing cells," IEEE Trans. Ind. Electron., vol. 3, no. 1, pp. 3–11, Feb. 2007.
[5] S. Yang and D. Wang, "Constraint satisfaction adaptive neural network and heuristics combined approaches for generalized job-shop scheduling," IEEE Trans. Neural Netw., vol. 11, no. 2, pp. 474–485, Mar. 2000.
[6] D. E. Akyol and G. M. Bayhan, "A review on evolution of production scheduling with neural networks," Comput. Ind. Eng., vol. 53, no. 1, pp. 95–122, Aug. 2007.
[7] Amel Yahyaoui, Nader Fnaiech, and Farhat Fnaiech, "A Suitable Initialization Procedure for Speeding a Neural Network Job-Shop Scheduling", IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 58, NO. 3, MARCH 2011

Abstract:In order to solve the cooperation of autonomous agent systems，an artificial immune network cooperation algorithm is proposed，which is based on Jerne's idiotypic immune network hypothesis. A sheep- dog herding problem is taken as an example. The relative position information of dogs with the sheep and sheep pen is taken as an antigen. Dogs' action is taken as an antibody. We calculate antibody concentration according to Farmer's kinetic model. By selecting the appropriate antibody according to the antibody concentration the cooperation for autonomous agent systems can be realized. Simulation of sheep-dog herding in different environment shows that a herding strategies based on immune network can not only realize sheep-dog herding but also be more robust and flexible， which shows the effectiveness of the artificial immune network algorithm in autonomous agents systems.

Keywords: Immune network, Autonomous agents, Planning and cooperation, Sheep-dog herding

[1] Y.P. Yang, X.M. Li and X.M. Xu, A survey of technology of multi-agent cooperation, Information and Control, 4, 2001, 337-342.
[2] Y.Q. Chu, X.A. Li and Y. Pu, Cooperative control of multi-agent soccer robot system, Journal of Harbin Institute of Technology, 7,
2004, 911-913.
[3] Y. Gao, W. Zhou and X.Q. Zeng, Multi-agent learning negotiation research in virtual enterprise based on contract net, Computer
Integrated Manufacturing Systems, 4, 2004, 471-475.
[4] H.T. Xue, L.C. Shen and Y.Y. Ye, Multi-agent collaboration system architecture and simulation framework based on co-evolution
method, Journal of System Simulation, 3, 2002, 297-299.
[5] J. Zhuang, S.A. Wang, Further study of robot path planning algorithm based on artificial immune net theory, Journal of System
Simulation, 5, 2004,1017-1019.

Abstract:In this paper, we examine steps to system reconfiguration in a Distributed Database using some fault tolerance scheme for a distributed database system that is compatible with respect to system failure i.e. Normal transaction processing is carried out assuming that no failure will occur, but if failure is suspected at some stage or site then a system reconfiguration is undertaken. The reconfiguration and system transaction are guaranteed as long as there exist a majority of working sites belonging to the same database Keywords: Distributed Database, Reconfiguration, Homogeneous database, Database Replication, Failures

[1]. A. Kashem, Concurrency Control in Distributed Databases, Lecture Note in Computer Science, Gazipur, India, 2005.
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[4]. A. Silberschatz, H.F. Korth, S. Sudarshan, Database System concept, 6th Edition, 2010.
[5]. B. k. Vidyasankar and T. Monoura, An optimistic Resiliency control Scheme for Distributed Database System, LNCS, Vol. 312, pp 297-307, 2005.
[6]. D. Agrawal and E. El Abbadi., On the power of Reconfiguration in Fault-tolerant Distributed Databases, Proceedings of the twenty-seventh Hawaii International conference on System science, vol.5, pp 341-350, 1994.

Abstract:E- Learning is the most feasible way to hold distance learning by providing learning materials over the internet; thus trend is becoming popular in developed and developing countries. This learning style becomes difficult to use by learners, usually by vague interface design. Due to which learner/user becomes reluctant towards E- Learning system. Usability testing of E- Learning systems targets its interface design, usability and human computer interaction. This study is an attempt to uncover the problems that occur in the use of such systems at user end. A survey from learners of an E- Learning system is carried out and result are compared by another usability evaluation technique named Heuristic Evaluation commonly employed by experts. Both end users and usability expert participated in this research by which two different evaluation methods are used to evaluate the usability of Virtual University Learning Management System. At the end some suggestions are given in order to improve the usability of target system after validating the results.

Keywords: E- Learning, HCI (Human Computer Interaction), Usability Evaluation, Usability Evaluation Criteria.

[1]. U. Yousf , L. Khaw , H. Ch'ng and B.J. Neow, Balancing between usability and aesthetics of Web design, Information Technology (ITSim) 2010 International Symposium in U.K., 1(1), 2010, 1-6.
[2]. D. Sharma, Toward a new foundation of human-computer interaction, Electronics Computer Technology (ICECT), 2011 3rd International Conference, 6(1), 2011, 395-397.
[3]. J, Nielsen, and R.L. Mack, Usability Inspection Methods (John Wiley and Sons, Inc., 1994).
[4]. A. Hope, and P. Guiton, Strategies for Sustainable Open and Distance E- Learning, Routledge Taylor and Francis Group, Madison Ave., New York. 2006.
[5]. D. Dhar, and P. Yammiyavar, Design Approach for E- Learning Systems: Should it be User Centered or Learner Centered. Technology for Education (T4E), IEEE Fourth International Conference, 5(1), 2012, 239-240. [6]. R. Schunk, Rapid prototyping of patterned functional nanostructures, Nature international weekly Journal of Science. 2010, 56-60.
[7]. M.D. Myers, Qualitative Research in Information Systems ( London, 1997).

Abstract:With the advancement in wireless technologies, wireless networks are developing at a fast rate and so are the MANET's. Several routing attacks are introduced in the wireless networks due to their dynamically changing network topologies. A severe type of attack known as wormhole attack is the main theme of this paper and the work has been done to detect and prevent this attack. The work has been done with the help of DSR protocol. The existing functionality of DSR is extended so that the wormhole nodes are easily detected in the routing path and then that path is not used in the future because it is blacklisted by the network. A brief overview of the algorithm is also mentioned in the paper by which the detection and elimination of wormhole node is actually done.

Keywords: MANET; DSR; wormhole; detection

[1]. Yudhvir Singh, Avni Khatkar, Prabha Rani, Deepika, Dheer Dhwaj Barak, "Wormhole Attack Avoidance Technique In Mobile Adhoc networks" Third International Conference on Advance Computing & Communication Technologies, IEEE 2013.
[2]. Rajpal Singh Khainwar, Mr. Anurag Jain, Mr. Jagdish Prasad Tyagi, "Elimination of Wormhole Attacker node in MANETs using performance evaluation multipath algorithm", International Journal of Emerging Technology and Advanced Engineering, Volume 1, Issue 2,PP 40-47, December, 2011.
[3]. Weichao Wang, Bharat Bhargava, Yi Lu, Xiaoxin Wu, "Defending against Wormhole Attacks in Mobile Ad Hoc Networks", Conference of Wiley Journal Wireless Communications and Mobile Computing (WCMC), 2010 .
[4]. Shalini Jain, Dr.Satbir Jain, " Detection and prevention of wormhole attack in mobile adhoc networks", International Journal of Computer Theory and Engineering, Vol. 2, No. 1, pp 123-127, February, 2010.
[5]. Dr. Karim Konate, Abdourahime Gaye, "A Proposal Mechanism Against the Attacks: Cooperative Blackhole, Blackmail, Overflow and Selfish in Routing Protocol of Mobile Ad Hoc Network", International Journal of Future Generation Communication and Networking Vol. 4, No. 2, pp 156-158, June, 2011.

Abstract:Patent Search has attracted considerable attention recently for finding existing relevant patents and validating new patent application. Earlier try-and-see approach was used to find any relevant underlying patents. Recent development has involved partition methods to find relevant patents. However, that method mainly focuses on Effectiveness of the search but not the Efficiency. To address this problem, we propose a new user-friendly patent search method which focuses on both Effectiveness and Efficiency of the patent search method. Error correction, query expansion and query suggestion techniques are used to get the patent search effectively and to improve the efficiency of the patent search, The proposed system uses two tools called WordNet and POS Tagger. We have used PoS tagger and SynSets from WordNet for identifying the intention of the user for the given search keyword and to create relevant partitions based on the Synsets. Finally top-k answers are generated from those highly relevant partitions are grouped together and displayed to the user.

Keywords: Patent search, error correction, query suggestion, query expansion, PoS tagger, WordNet .

1]. L.Azzopardi, W. Vanderbauwhede, and H. Joho, "Search System Requirements of Patent Analysts," Proc. 33rd Int'l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR), pp.775-776, 2010.
[2]. S. Bashir and A. Rauber, "Improving Retrievability of Patents in Prior-Art Search," Proc. European Conf. Information Retrieval (ECIR), pp. 457-470, 2010.
[3]. D.M Blei, A.Y Ng, and M.I Jordan, "Latent Dirichlet Allocation," J. Machine Learning Research, vol. 3, pp. 993-1022, 2003.
[4]. J. Fan, H. Wu, G. Li, and L. Zhou, "Suggesting Topic-Based Query Terms as You Type," Proc. Int'l Asia Pacific Web Conf. (APWEB), pp. 61-67, 2010.
[5]. G. Li, J. Feng, and C. Li, "Supporting Search-As-You-Type Using SQL in Databases," IEEE Trans. Knowledge and Data Eng., vol. 25, no. 2, pp. 461-475, Feb. 2013.
[6]. Y. Guo and C.P. Gomes, "Ranking Structured Documents: A Large Margin Based Approach for Patent Prior Art Search," Proc. Int'l Joint Conf. Artificial Intelligence (IJCAI), pp. 1058-1064, 2009.

Abstract:This paper presents a technique to use ID3 decision rules to produce fuzzy rules to get the optimize prediction of the students academic performance. In this paper, a the student administrative data for a class is used in order to classify the students final year marks in fuzzy logic prediction . This paper is using the machine learning approach to generate the rules so as to overcome the difficulties in a conventional approach like deriving fuzzy rules base from expert experience. This research provides us with: a way to produce meaningful and simple fuzzy rules; a method to fuzzify ID3-derived rules to deal with many inputs variables; and a de-fuzzification system to get the output in human understandable form. The Id3 tree is generated by the WEKA software and is utilized by the Fuzzy Inference System . A Fuzzy inference system was constructed to give the final crisp output. The ID3 was generated on 300 training data to get the better output. The output of our Fuzzy Student Performance Predictor was then tested on 50 test data to check for the accuracy.

Keywords: Student administrative data, Students performance, ID3 Decision tree, Fuzzy rules , Fuzzification, linguistic variables, Membership function , Defuzzification

[1]. B.K. Bhardwaj and S. Pal, Data Mining: A prediction for performance improvement using classification, International Journaof Computer Science and Information Security, Vol. 9(4), 2011.
[2]. V. Juana-Maria and F. Manuel, How does one assess the accuracy of academic success predictors? ROC analysis applied to university entrance factors, International Journal of Mathematical Education in Science and Technology, Vol. 39 (3), 2008, pp 325–340.
[3]. Emerson, T and Taylor, B.,"Comparing Student Achievement Across Experimental and Lecture-Oriented Sections of a Principles of Microeconomics Course," Southern Economic Journal 703:672-693 (2004).
[4]. Cindy P. Veenstra ,‖A Strategy for Improving Freshman College Retention‖ , Journal for Quality and Participation, ASQ, January 2009.
[5]. P.H. Zhu, "Learning factors for technical school students," Taipei college of business journal, 12, pp.81-94, 2007.
[6]. Waikato ML Group. User Manual Weka: The Waikato Environment for Knowledge Analysis. Department of Computer Science,
[7]. University of Waikato (New Zealand), June 1997

Abstract:Opinion mining/Sentiment analysis is a field of research which focuses on tracking human opinions written in natural language. Many companies, Now-a-days, extract opinions from various internet sources (such as review sites, blogs, twitter) and try to predict customer's reviews on their upcoming products. Parts-Of-Speech Tagging or POS Tagging, being a crucial step in the process of opinion mining, is the assigning of each word with its POS tag, according to its definition and context in the corpus. In this paper, we will first have detailed study of a POS tagging algorithm i.e. Memory Based Learning Algorithm, along with other POS tagging techniques and then, dealing with its limitations, we will propose an enhanced model in order to significantly improve the efficiency of Memory-Based Learning Algorithm.

[1] Parmar Mitixa R, Prof.Arpit Rana, A Survey on Opinion and Sentiment Analysis With Applications and Issues, International Journal of Computational Linguistics and Natural Language Processing, ISSN 2279 – 0756, Vol. 2, Issue 1, January 2013
[2] G.Vinodhini, RM.Chandrasekaran, Sentiment Analysis and Opinion Mining: A Survey, International Journal of Advanced Research in Computer Science and Software Engineering, ISSN: 2277 128X , Volume 2, Issue 6, June 2012.
[3] Antony P J and Dr. Soman K P, Parts Of Speech Tagging for Indian Languages: A Literature Survey, International Journal of Computer Applications, ISSN 0975 – 8887, Vol.3, No.8, November 2011
[4] Jakub Zavrel & walter Daelemans, Recent Advances in Memory Based Part of Speech Tagging, VI Simposio Internacional de Comunicacion Social, Santiago de Cuba pp., 1999, 590-597
[5] Ari Rappoport, Roi Reichart and Shulamit Umansky-Pesin, A Multi DomainWeb-Based Algorithm for POS Tagging of Unknown Words, Coling 2010, Beijing, Poster Volume, 1274–1282, August 2010
[6] Adwait Ratnaparkhi, A Maximum Entropy Model For Part-Of-Speech Tagging, Conference on Empirical Methods in Natural Language Processing, Philadelphia, Pa. USA, 1996, W96-0213, 133-142