DATA MINING WITH BIG DATA REVOLUTION HYBRID

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International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering , Engineering, Electrical & Electronic

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VOLUME 10 , ISSUE 5 (December 2017) > List of articles

Special Issue

DATA MINING WITH BIG DATA REVOLUTION HYBRID

R. Elankavi / R. Kalaiprasath / R. Udayakumar

Keywords : HACE, demand-driven, data storage

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 10, Issue 5, Pages 560-573, DOI: https://doi.org/10.21307/ijssis-2017-270

License : (CC BY-NC-ND 4.0)

Received Date : 27-May-2017 / Accepted: 15-June-2017 / Published Online: 01-September-2017

ARTICLE

ABSTRACT

Big Data concern large-volume, complex, growing data sets with multiple, autonomous sources. With the fast development of networking, data storage, and the data collection capacity, Big Data are now rapidly expanding in all science and engineering domains, including physical, biological and biomedical sciences. This paper presents a HACE theorem that characterizes the features of the Big Data revolution, and proposes a Big Data processing model, from the data mining perspective. This data-driven model involves demand-driven aggregation of information sources, mining and analysis, user interest modeling, and security and privacy considerations. We analyze the challenging issues in the data-driven model and also in the Big Data revolution.

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[1] Aizat Azmi, Ahmad Amsyar Azman, Sallehuddin Ibrahim, and Mohd Amri Md Yunus, ―Techniques In Advancing The Capabilities Of Various Nitrate Detection Methods: A Review‖, International Journal on Smart Sensing and Intelligent Systems., VOL. 10, NO. 2, June 2017, pp. 223-261.

[2] Tsugunosuke Sakai, Haruya Tamaki, Yosuke Ota, Ryohei Egusa, Shigenori Inagaki, Fusako Kusunoki, Masanori Sugimoto, Hiroshi Mizoguchi, ―Eda-Based Estimation Of Visual Attention By Observation Of Eye Blink Frequency‖, International Journal on Smart Sensing and Intelligent Systems., VOL. 10, NO. 2, June 2017, pp. 296-307.

[3] Ismail Ben Abdallah, Yassine Bouteraa, and Chokri Rekik , ―Design And Development Of 3d Printed Myoelctric Robotic Exoskeleton For Hand Rehabilitation‖, International Journal on Smart Sensing and Intelligent Systems., VOL. 10, NO. 2, June 2017, pp. 341-366.

[4] S. H. Teay, C. Batunlu and A. Albarbar, ―Smart Sensing System For Enhanceing The Reliability Of Power Electronic Devices Used In Wind Turbines‖, International Journal on Smart Sensing and Intelligent Systems., VOL. 10, NO. 2, June 2017, pp. 407- 424

[5] SCihan Gercek, Djilali Kourtiche, Mustapha Nadi, Isabelle Magne, Pierre Schmitt, Martine Souques and Patrice Roth, ―An In Vitro Cost-Effective Test Bench For Active Cardiac Implants, Reproducing Human Exposure To Electric Fields 50/60 Hz‖, International Journal on Smart Sensing and Intelligent Systems., VOL. 10, NO. 1, March 2017, pp. 1- 17

[6] P. Visconti, P. Primiceri, R. de Fazio and A. Lay Ekuakille, ―A Solar-Powered White Led- Based Uv-Vis Spectrophotometric System Managed By Pc For Air Pollution Detection In Faraway And Unfriendly Locations‖, International Journal on Smart Sensing and Intelligent Systems., VOL. 10, NO. 1, March 2017, pp. 18- 49

[7] Samarendra Nath Sur, Rabindranath Bera and Bansibadan Maji, ―Feedback Equalizer For Vehicular Channel‖, International Journal on Smart Sensing and Intelligent Systems., VOL. 10, NO. 1, March 2017, pp. 50- 68

[8] Yen-Hong A. Chen, Kai-Jan Lin and Yu-Chu M. Li, ―Assessment To Effectiveness Of The  New Early Streamer Emission Lightning Protection System‖, International Journal on Smart Sensing and Intelligent Systems., VOL. 10, NO. 1, March 2017, pp. 108- 123

[9] Iman Heidarpour Shahrezaei, Morteza Kazerooni and Mohsen Fallah, ―A Total Quality Assessment Solution For Synthetic Aperture Radar Nlfm Waveform Generation And Evaluation In A Complex Random Media‖, International Journal on Smart Sensing and Intelligent Systems., VOL. 10, NO. 1, March 2017, pp. 174- 198

[10] P. Visconti ,R.Ferri, M.Pucciarelli and E.Venere, ―Development And Characterization Of A Solar-Based Energy Harvesting And Power Management System For A Wsn Node Applied To Optimized Goods Transport And Storage‖, International Journal on Smart Sensing and Intelligent Systems., VOL. 9, NO. 4, December 2016 , pp. 1637- 1667

[11] YoumeiSong,Jianbo Li, Chenglong Li, Fushu Wang, ―Social Popularity Based Routing In Delay Tolerant Networks‖, International Journal on Smart Sensing and Intelligent Systems., VOL. 9, NO. 4, December 2016 , pp. 1687- 1709

[12] Seifeddine Ben Warrad and OlfaBoubaker, ―Full Order Unknown Inputs Observer For Multiple Time-Delay Systems‖, International Journal on Smart Sensing and Intelligent Systems., VOL. 9, NO. 4, December 2016 , pp. 1750- 1775

[13] Rajesh, M., and J. M. Gnanasekar. "Path observation-based physical routing protocol for wireless ad hoc networks." International Journal of Wireless and Mobile Computing 11.3 (2016): 244-257.

[14]. Rajesh, M., and J. M. Gnanasekar. "Congestion control in heterogeneous wireless ad hoc network using FRCC." Australian Journal of Basic and Applied Sciences 9.7 (2015): 698-702.

[15]. Rajesh, M., and J. M. Gnanasekar. "GCCover Heterogeneous Wireless Ad hoc Networks." Journal of Chemical and Pharmaceutical Sciences (2015): 195-200.

[16]. Rajesh, M., and J. M. Gnanasekar. "CONGESTION CONTROL USING AODV PROTOCOL SCHEME FOR WIRELESS AD-HOC NETWORK." Advances in Computer Science and Engineering 16.1/2 (2016): 19.

[17]. Rajesh, M., and J. M. Gnanasekar. "An optimized congestion control and error management system for OCCEM." International Journal of Advanced Research in IT and Engineering 4.4 (2015): 1-10.

[18]. Rajesh, M., and J. M. Gnanasekar. "Constructing Well-Organized Wireless Sensor Networks with Low-Level Identification." World Engineering & Applied Sciences Journal 7.1 (2016).

[19] Aftab Ali Haider, AcmerNadeem, ShamailaAkram, ―Safe Regression Test Suite Optimization: A Review‖,In: Proc. of IEEE International Conference on Open Source Systems and Technologies, pp. 7-12, 2016.

[20] AvinashGupta,Namita Mishra,Dharmender Singh Kushwaha, ―Rule-Based test case Reduction Technique using Decision Table‖,In: Proc. of IEEE Conference on International Advance Computing Conference,pp.1398-1405,2014.

[21] Annibalepanichella,Rocco oliveto,Massimiliano Di Penta,Andrea De Lucia, ― Improving multi-objective test case Selection by Injecting Diversity in genetic Algorithms‖, IEEE Transactions on Software Engineering,pp.358-383,Vol.41,No.4,April 2015.

[22] Zhang Hui, ―Fault Localization Method Generated by Regression Test Cases on the Basis of Genetic Immune Algorithm‖, In: proc. Of IEEE conference on Annual International Computers, Software & Applications Conference, pp. 46-51, 2016.

[23] S. Yoo and M. Harman, ―Regression testing minimization, selectionand prioritization: A survey,‖ Softw. Test. Verif. Rel., vol. 22,no. 2, pp. 67–120, Mar. 2012.

[24] S. Yoo, ―A novel mask-coding representation for set cover problemswith applications in test suite minimisation,‖ In: Proc. of 2nd International Symposium. Search-Based Software. Eng., 2010, pp. 19–28.

[25] S. Yoo and M. Harman, ―Pareto efficient multi-objective test case selection,‖ In: Proc. of ACM /SIGSOFT Int. Symp. Softw. Testing Anal.,2007, pp. 140–150.

[26] S. Yoo and M. Harman, ―Using hybrid algorithm for Pareto efficientmulti-objective test suite minimisation,‖ J. Syst. Softw.,vol. 83, no. 4, pp. 689–701, 2010.

[27] S. Yoo, M. Harman, and S. Ur, ―Highly scalable multi objectivetest suite minimization using graphics cards,‖ In:Proc. of 3rd Int.Conf. Search Based Softw. Eng., 2011, pp. 219–236.

[28] Q. Zhang and Y.-W. Leung, ―An orthogonal genetic algorithm for multimedia multicast routing,‖ IEEE Trans. Evol. Comput., vol. 3,no. 1, pp. 53–62, Apr. 1999.

[29] J. Zhu, G. Dai, and L. Mo, ―A cluster-based orthogonal multi objective genetic algorithm‖, Comput. Intell. Intell. Syst., vol. 51,pp. 45–55, 2009.

[30] E. Zitzler, D. Brockhoff, and L. Thiele, ―The hypervolume indicatorrevisited: On the design of Pareto-compliant indicators via weighted integration‖,In: Proc. of 4th Int. Conf. Evol. Multi- CriterionOptim., 2007, pp. 862–876.

[31] Jones JA, Harrold MJ. ―Empirical Evaluation of the Tarantula Automatic Fault - Localization Technique‖. In: Proc. of 20th IEEE/ ACM International Conference on Automated Software Engineering, 2005: 273-282.

[32] Jones JA, Harrold MJ, Stasko J. ―Visualization of Test Information to Assist Fault Localization‖.In: Proc. ofthe 24th International Conference on Software Engineering, 2002:467-477.

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