Volume-4 , Issue-4 , Apr - 2016 Go Back

The state-of-art of the innovation focuses on data handling and, sharing to deal with enormous sum of data and, client’s needs. Wireless network is a promising technology, which empowers one to achieve the aforesaid goal, leading towards enhanced business performance. Wireless network comes into focus of consideration immediately when you think about what IT constantly needs: a implies to increment capacity or add abilities on the fly without investing in new infrastructure, training new human resources, or licensing new software. The network should give resources on demand, to its customers with high availability, scalable and, with decreased cost. Wireless network Framework has widely been adopted by the industry, though there are numerous existing issues which have not been so far wholly addressed. Load balancing is one of the primary challenges, which is required to distribute the dynamic workload over distinctive hubs to ensure that no single hub is overwhelmed. This Paper gives an effective dynamic load balancing calculation for network workload administration by which the load can be dispersed not only in a adjusted approach, but moreover it dispenses the load systematically and, uniformly by checking certain parameters like number of demands the server is handling currently. It parities the load on the over-stacked hub to under stacked hub so that reaction time from the server will diminish and, execution of the framework is increased.

Load Balancing, Network Framework, Wireless network.

[1] M. A. Kashem; V. Ganapathy; G. B. Jasmon, “A geometric approach for three-phase load balancing in distribution networks”, Power System Technology, 2000. Proceedings. PowerCon 2000. International Conference on, Year: 2000, Volume: 1, Pages: 293 – 298.
[2] Jasween Kaur, Kiranbir Kaur, "A Study of Fuzzy Based Dynamic Load Balancing for Cell Networks", International Journal of Computer Sciences and Engineering, Volume-04, Issue-01, Page No (70-75), Jan -2016
[3] Nico Kruber; Mikael Högqvist; Thorsten Schütt, “The Benefits of Estimated Global Information in DHT Load Balancing”, Cluster, Cloud and Grid Computing (CCGrid), 2011 11th IEEE/ACM International Symposium on, Year: 2011, Pages: 382 – 391.
[4] Zhihao Shang; Wenbo Chen; Qiang Ma; Bin Wu, “Design and implementation of server cluster dynamic load balancing based on OpenFlow”, Awareness Science and Technology and Ubi-Media Computing (iCAST-UMEDIA), 2013 International Joint Conference on, Year: 2013,Pages: 691 – 697.
[5] Quentin Bragard; Anthony Ventresque; Liam Murphy, “Global dynamic load-balancing for decentralised distributed simulation”, Proceedings of the Winter Simulation Conference 2014, Year: 2014, Pages: 3797 – 3808.
[6] Yingwu Zhu; Yiming Hu, “Efficient, proximity-aware load balancing for structured P2P systems”, Peer-to-Peer Computing, 2003. (P2P 2003). Proceedings. Third International Conference on, Year: 2003, Pages: 220 – 221.
[7] Hye-Seon Maeng; Hyoun-Su Lee; Tack-Don Han; Sung-Bong Yang; Shin-Dug Kim, “Dynamic load balancing of iterative data parallel problems on a workstation cluster” High Performance Computing on the Information Superhighway, 1997. HPC Asia '97, Year: 1997, Pages: 563 – 567.
[8] Vaishnavi Aher,Sayali Khairnar,Madhuri Shinde and Priyanka Shirole, "Load Balancing of node in Network using Ant Colony Optimization", International Journal of Computer Sciences and Engineering, Volume-03, Issue-01, Page No (105-108), Jan -2015
[9] Rajkumar Rajavel, “De-Centralized Load Balancing for the Computational Grid environment”, Communication and Computational Intelligence (INCOCCI), 2010 International Conference on, Year: 2010, Pages: 419 – 424.
[10] Gengbin Zheng; Esteban Meneses; Abhinav Bhatele; Laxmikant V. Kale, “Hierarchical Load Balancing for Charm++ Applications on Large Supercomputers”, 2010 39th International Conference on Parallel Processing Workshops, Year: 2010, Pages: 436 – 444.

J.Sagana, A.Ashlin Jeba, "Selective Load Balancing System of Video Traffic in Wireless Networks," International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.313-318, 2016.

The issue that Ontology learning bargains with is the learning obtaining bottleneck, that is to say the trouble to really show the learning significant to the area of interest. Ontologies are the vehicle by which we can show also, share the learning among diverse applications in a particular domain. So numerous relook created several Ontology learning approaches also, systems. In this paper, we introduce a review for the diverse approaches in Ontology learning from semi-organized also, unorganized date.

Ontology learning approaches, Ontology learning, Ontology learning evaluation, learning discovery

[1] N. Aloui; F. Gargouri, “An ontology-based approach for learning annotations reuse”, Education and e-Learning Innovations (ICEELI), 2012 International Conference on Year: 2012 Pages: 1 – 6.
[2] M. Suryani; Z. A. Hasibuan, “The study of dynamic delivery adaptive learning content in e-learning personalization using text mining and ontology approach”, Advanced Computer Science and Information Systems (ICACSIS), 2013 International Conference on Year: 2013 Pages: 21 – 26.
[3] D. Gašević; A. Zouaq; C. Torniai; J. Jovanović; M. Hatala, “An Approach to Folksonomy-Based Ontology Maintenance for Learning Environments”, IEEE Transactions on Learning Technologies Year: 2011, Volume: 4, Issue: 4 Pages: 301 – 314.
[4] F. Colace; M. De Santo, “Ontology for E-Learning: A Bayesian Approach”, IEEE Transactions on Education Year: 2010, Volume: 53, Issue: 2 Pages: 223 – 233.
[5] M. Farida Begam; G. Ganapathy, “Knowledge engineering approach for constructing ontology for e-Learning services”, Advanced Computer Science and Information System (ICACSIS), 2011 International Conference on Year: 2011 Pages: 125 - 132

Dr.N.Vetrivelan, C.Senthil Selvi, "A Review of Enhanced and Secure Ontology Learning Approaches," International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.319-326, 2016.

Gradually more furthermore, more associations are opting for outsourcing information to remote cloud administration providers (CSPs). clients can rent the CSPs capacity foundation to store furthermore, get back almost limitless sum of information by paying sum per month. On behalf of an improved level of scalability, availability, furthermore, durability, some clients may want their information to be virtual on distinctive servers over distinctive information centers. The more duplicates the CSP is asked to store, the more sum the clients are charged. As a result, clients need to have a solid assurance that the CSP is storing all information duplicates that are chosen upon in the administration contract, furthermore, all these duplicates are reliable with the most later changes issued by the clients. Map-based provable multi-copy dynamic information ownership (MB-PMDDP) technique is being proposed in this paper furthermore, comprises of the following features: 1) it affords an proof to the clients that the CSP is not degenerate by storing less copies; 2) it bolsters outsourcing of dynamic data, i.e., it bolsters block-level functions, such as square alteration, addition, deletion, furthermore, append; furthermore, 3) it licenses official clients to easily access the record duplicates stored by the CSP. In addition, we discuss the security against conspiring servers, furthermore, discuss how to perceive tainted duplicates by a little revising the projected scheme.

loud Computing, Dynamic Environment, Data Copy, Outsourcing Data Storage

[1] Zhou Peng; Jinhua Zheng; Juan Zou, “A population diversity maintaining strategy based on dynamic environment evolutionary model for dynamic multi objective optimization”, 2014 IEEE Congress on Evolutionary Computation (CEC),Year: 2014, Pages: 274 – 281.
[2] Shivlal Mewada, Umesh Kumar Singh, Pradeep Sharma, “Security Based Model for Cloud Computing”, International Journal of Computer Networks and Wireless Communications Vol. 1(1), pp (13-19), December 2011.
[3] Ling Zhang; Yan-bin Liu, “The influence of dynamic environment and resource allocation on enterprises financial performance”, Management Science and Engineering (ICMSE), 2012 International Conference on, Year: 2012, Pages: 1314 – 1320.
[4] Inderjeet Singh Dogra; Ziad Kobti, “Improving prediction accuracy in agent based modeling systems under dynamic environment”, 2013 IEEE Congress on Evolutionary Computation, Year: 2013, Pages: 2114 – 2121.
[5] C. E. Campbell; G. McCulley, “Terrain reasoning challenges in the CCTT dynamic environment”, AI Simulation, and Planning in High Autonomy Systems, 1994. Distributed Interactive Simulation Environments, Proceedings of the Fifth Annual Conference on, Year: 1994,Pages: 55 – 61.
[6] Aameek Singh; Ling Liu, “Sharoes: A Data Sharing Platform for Outsourced Enterprise StorageEnvironments”, 2008 IEEE 24th International Conference on Data Engineering, Year: 2008, Pages: 993 – 1002.
[7] Shaheen Ayyub and Devshree Roy, "Cloud Computing Characteristics and Security Issues", International Journal of Computer Sciences and Engineering, Volume-01, Issue-04, Page No (18-22), Dec -2013,
[8] Shivlal Mewada, Umesh Kumar Singh and Pradeep Sharma, "Security Enhancement in Cloud Computing (CC)", ISROSET-International Journal of Scientific Research in Computer Science and Engineering, Vol.-01, Issue-01, pp (31-37), Jan -Feb 2013
[9] Harsh Yadav; Mayank Dave, “Secure data storage operations with verifiable outsourced decryption for mobile cloud computing”, Recent Advances and Innovations in Engineering (ICRAIE), 2014, Year: 2014, Pages: 1 – 5.
[10] B.Subasri, P.Vijayalakshmi, P.Yurega and E.Revathi, "Improving Zero Knowledge in Cloud Storage Auditing System", International Journal of Computer Sciences and Engineering, Volume-02, Issue-03, Page No (204-207), Mar -2014
[11] Juan Camilo Corena; Anirban Basu; Shinsaku Kiyomoto; Yutaka Miyake; Tomoaki Ohtsuki, “Beyond proofs of data possession: Finding defective blocks in outsourced storage”, 2014 IEEE Global Communications Conference, Year: 2014,Pages: 2381 - 2386
[12] Ayad F. Barsoum; M. Anwar Hasan, “Provable Multicopy Dynamic Data Possession in Cloud Computing Systems”, IEEE Transactions on Information Forensics and Security, Year: 2015, Volume: 10, Issue: 3, Pages: 485 – 497.
[13] Qia Wang; Wenjun Zeng; Jun Tian, “A Compressive Sensing Based Secure Watermark Detection and Privacy Preserving Storage Framework”, IEEE Transactions on Image Processing, Year: 2014, Volume: 23, Issue: 3, Pages: 1317 – 1328.
[14] Xiuxia Tian; Ling Huang; Tony Wu; Xiaoling Wang; Aoying Zhou, “CloudKeyBank: Privacy and Owner Authorization Enforced Key Management Framework”, IEEE Transactions on Knowledge and Data Engineering, Year: 2015, Volume: 27, Issue: 12, Pages: 3217 – 3230.
[15] Ankita Lathey; Pradeep K. Atrey; Nishant Joshi, “Homomorphic Low Pass Filtering on Encrypted Multimedia over Cloud”, Semantic Computing (ICSC), 2013 IEEE Seventh International Conference on, Year: 2013, Pages: 310 – 313.

N.Sheeba Pershi, G.Sathish Kumar, "A Security of Cloud Data Storage Using AF Crawler Algorithm in Cloud Computing Systems," International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.327-332, 2016.

The use of Neuro-Fuzzy Network is extremely wide in data mining due to some trademark like parallel performance, Self-organizing adaptive, power Also, shortcoming tolerance. Data mining models depend on errand they accomplish: Affiliation Rules, Clustering, Prediction, Also, Classification. Neuro-Fuzzy Network is utilized to find outline in data. The gathering of Neuro-Fuzzy Network model Also, data mining strategy can significantly increment the proficiency of data mining Techniques Also, it has been comprehensively used. Diverse Calculations have been discussed or streamlining the Manufactured Neuro-Fuzzy Network (ANN). ANN consolidates with other Calculations to find out the high exact data as compare to Conventional algorithm. The part of ANN utilizing data mining strategies is playing an imperative part in gauging or conjecture about diversions Also, weather. This produces high exact expectations than that of Conventional algorithm. Data mining approaches utilizing ANN can moreover work well. ANN is a highly class calculation which can be accelerated utilizing neuron. The result of which will produce a high speed up ANN. ANN can moreover be utilized or the reason of Evacuating rules from prepared Neuro-Fuzzy networks.

ANN; Data mining; Application; Gathering

[1] Sheng Zhang; Hong-Xing Liu; Dun-Tang Gao; Wei Wang, “Surveying the methods of improving ANN generalization capability”, Machine Learning and Cybernetics, 2003 International Conference on Year: 2003, Volume: 2 Pages: 1259 – 1263.
[2] Y. X. Jin; B. Xu; X. C. Yang; Z. H. Qin; J. Y. Li; F. Zhao; S. Chen; H. L. Ma; Q. Wu, “Grassland aboveground biomass retrieval from remote sensing data by using artificial neural network in temperate grassland, northern China”, Agro-geoinformatics (Agro-geoinformatics 2014), Third International Conference on Year: 2014 Pages: 1 – 6.
[3] Guozheng Zhang; Faming Zhou; Junfeng Liu; Yong Lan, “Customer Satisfaction Data Analysis Based on BP ANN”, 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing Year: 2008 Pages: 1 – 3.
[4] Agustín Gajate; Rodolfo E. Haber; Pastora I. Vega; José. R. Alique, “A Transductive Neuro-Fuzzy Controller: Application to a Drilling Process”, IEEE Transactions on Neural Networks Year: 2010, Volume: 21, Issue: 7 Pages: 1158 – 1167.
[5] L. Arafeh; H. Singh; S. K. Putatunda, “A neuro fuzzy logic approach to material processing”, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) Year: 1999, Volume: 29, Issue: 3 Pages: 362 – 370.
[6] H. Ghezelayagh; K. Y. Lee, “Application of neuro-fuzzy identifier for a fossil fuel boiler system”, Power Engineering Society Winter Meeting, 2000. IEEE Year: 2000, Volume: 2 Pages: 1135 – 1139.
[7] P. C. Panchariya; A. K. Palit; D. Popovic; A. L. Sharrna, “Nonlinear system identification using Takagi-Sugeno type neuro-fuzzy model”, Intelligent Systems, 2004. Proceedings. 2004 2nd International IEEE Conference Year: 2004, Volume: 1 Pages: 76 – 81.
[8] Ginalber Serra; Celso Bottura, “An IV-QR Algorithm for Neuro-Fuzzy Multivariable Online Identification”, IEEE Transactions on Fuzzy Systems Year: 2007, Volume: 15, Issue: 2 Pages: 200 – 210.

J.Sheela Jasmine, "Application of Fuzzy Logic in Neural Network Using Data Mining Techniques: A Survey," International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.333-341, 2016.

The ageing populace worldwide is always rising, both in urban also, territorial areas. There is a need for IoT based remote wellbeing checking frameworks that take care of the wellbeing of elderly individuals without compromising their comfort also, preference of remaining at home. However, such frameworks may produce huge sums of data. The key research challenge addressed in this paper is to proficiently transmit healthcare data within the limit of the existing framework infrastructure, particularly in remote areas. In this paper, we distinguished the key framework necessities of a regular remote wellbeing checking framework in terms of constant occasion update, bandwidth necessities also, data generation. In this fast step of life, it is difficult for people to be constantly available for their near ones who might need them while they are suffering from a disease or physical disorder. So constant monitoring of the patient’s body parameters such as heartbeat level, temperature level, etc. becomes difficult. Hence to remove human error and to lessen the burden of monitoring patient’s health from doctor’s head, this project presents the methodology for monitoring patients remotely using Internet of Things. A patient monitoring system for the Internet of Things can be established through the integration of wireless body area network, communication infrastructure, and the hospital network. This project is useful in medical applications and offers less cost. The patient monitoring systems is one of the major improvements because of its advanced technology. This project describes the design of a simple, microcontroller based heart beat & temperature measuring device with IoT output. In case heart beat or pressure is abnormal condition then it will intimate us via IoT to server and mobile.

Remote Wellbeing Monitoring, Internet of Things, Sensor Communication, Ehealth, Shrewd City, Shrewd Region.

[1] Jacey-Lynn Minoi; Alvin W Yeo, “Remote health monitoring system in a rural population: Challenges and opportunities” Biomedical Engineering and Sciences (IECBES), 2014 IEEE Conference on, Year: 2014,Pages: 895 – 900.
[2] Hasmah Mansor; Muhammad Helmy Abdul Shukor; Siti Sarah Meskam; Nur Quraisyia Aqilah Mohd Rusli; Nasiha Sakinah Zamery, “Body temperature measurement for remote health monitoring system”, Smart Instrumentation, Measurement and Applications (ICSIMA), 2013 IEEE International Conference on, Year: 2013, Pages: 1 – 5.
[3] Ngo Manh Khoi; Saguna Saguna; Karan Mitra; Christer Ǻhlund, “IReHMo: An efficient IoT-based remote health monitoring system for smart regions”, 2015 17th International Conference on E-health Networking, Application & Services (HealthCom), Year: 2015, Pages: 563 – 568.
[4] Nabil Alshurafa; Jo-Ann Eastwood; Mohammad Pourhomayoun; Suneil Nyamathi;Lily Bao; Bobak Mortazavi; Majid Sarrafzadeh, “Anti-Cheating: Detecting Self-Inflicted and Impersonator Cheaters for Remote Health Monitoring Systems with Wearable Sensors”, 2014 11th International Conference on Wearable and Implantable Body Sensor Networks, Year: 2014, Pages: 92 – 97.
[5] Zhou Jianting; Huang Hanmin; Huang Shanglian; Chen Weiming; Jiang Zhen;Zhou Zhixiang; Liu Simeng, “Remote Real-time Health Monitoring and Evaluation System for Long Bridge Structure”, Computational Engineering in Systems Applications, IMACS Multi conference on, Year: 2006, Volume: 2,Pages: 1751 – 1755.
[6] Peng-fei Fan; Guang-zhao Zhou, “Analysis of the business model innovation of the technology of internet ofthings in postal logistics”, Industrial Engineering and Engineering Management (IE&EM), 2011 IEEE 18Th International Conference on, Year: 2011, Volume: Part 1, Pages: 532 – 536.
[7] Steven E. Collier, “The Emerging Enernet: Convergence of the Smart Grid with the Internet of Things”, Rural Electric Power Conference (REPC), 2015 IEEE Year: 2015, Pages: 65 – 68.
[8] Nima Bari; Ganapathy Mani; Simon Berkovich, “Internet of Things as a Methodological Concept”, Computing for Geospatial Research and Application (COM.Geo), 2013 Fourth International Conference on,Year: 2013,Pages: 48 – 55.
[9] Umesh Kumar Singh, Shivlal Mewada, Lokesh Laddhani and Kamal Bunkar, “An Overview & Study of Security Issues in Mobile Ado Networks”, International Journal of Computer Science and Information Security (IJCSIS) USA, Vol-9(4), pp (106-111), April 2011.
[10] Alfred Zimmermann; Rainer Schmidt; Kurt Sandkuhl; Matthias Wißotzki; Dierk, “Digital Enterprise Architecture - Transformation for the Internet of Things”, Jugel; Michael Möhring, 2015 IEEE 19th International Enterprise Distributed Object Computing Workshop, Year: 2015, Pages: 130 – 138.
[11] Xueying Wu; Peng Liu; Song Liu, “New structure of using image sensor communication in smart house with smart grid”, The First International Conference on Future Generation Communication Technologies, Year: 2012, Pages: 32 – 35.

U.Shyamli, A.Ashlin Jeba, "Efficient Revocable Certificateless Encryption Secure For Wireless Body Area Networks," International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.342-347, 2016.

The adoption of shrewd / versatile antenna Techniques in future remote frameworks is expected to have a huge impact on the productive use of the spectrum, the minimization of the cost of establishing new remote networks, the optimization of administration quality and realization of transparent operation across multi innovation remote systems. Mobile phones can be an essential means of communication when we are away from the office or home and it can be an important security asset in the event of an emergency. Cell phone technology has developed the telecommunication scenario in India. Due to its several advantages, cell phone technology has grown exponentially in the last period. Currently, there are more than 50 crore cell phone users and nearly 4.4 lakh cell phone towers to meet the communication demand. The numbers of cell phones and cell towers are increasing without giving due respect to its disadvantages. All over the world, people have been debating about associated health risk due to radiation from cell phone and cell tower. Majority of these towers are mounted near the residential and office buildings to provide good mobile phone coverage to the users. These cell towers transmit radiation 24x7, so people living within 10’s of meters from the tower will receive 10,000 to 10,000,000 times stronger signal than required for mobile communication. In India, crores of people reside within these high radiation zones. Children’s, adults, and birds are more vulnerable to cell phone radiation. So our project gives a solution to avoid more towers. We proposed multiple frequencies in single antenna for avoid the radiation.

Shrewd / Versatile Antenna; Wireless; Bar forming; DSP; Diversity

[1] S. K. Rao, “Design and analysis of multiple-beam reflector antenna,” IEEE Antennas Propag. Mag., vol. 41, no. 4, pp. 53–59, Aug. 1999.
[2] S. K. Rao, “Parametric design and analysis of multiple-beam reflector antennas for satellite communications,” IEEE Antennas Propag. Mag., vol. 45, no. 4, pp. 26–34, Aug. 1999.
[3] P. Bosshard et al., “Recent developments for Ka-band multibeam passive antennas,” presented at 32nd ESA Antenna Workshop Antennas Space Appl., The Netherlands, Oct. 2010.
[4] E. Amyotte, Y. Demers, L. Hildebrand, S. Richard, and S. Mousseau, “A review of multibeam antenna solutions and their applications,” presented at the 8th Eur. Conf. Antennas Propag. (EuCAP), The Hague, The Netherlands, Apr. 2014.
[5] R. Gehring et al., “Trade-off for overlapping feed array configurations,” presented at 29th ESA Antenna Workshop Multiple Beams Reconfigur. Antennas, The Netherlands, Apr. 2007.
[6] N. Ratkorn, M. Scheneider, R. Gehring, and H.Wolf, “MEDUSA–A multiple feeds per beam multi,” presented at 30th ESA Antenna Workshop, The Netherlands, May 2008.
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[13] M. Lisi, “Beamforming networks for future european communication satellites,” in Proc. 17th Eur. Microw. Conf. (EuMC), Rome, Italy, Sep. 1987, pp. 778–783.
[14] P. Angeletti and M. Lisi, “Multimode beamforming networks,” presented at 32nd ESA AntennaWorkshop Antennas Space Appl., The Netherlands, Oct. 2010.
[15] P. Magnusson and L. Jing, “Recent developments in L- and S- band reflector feed array elements at RUAG space,” presented at 32nd ESA Antenna Workshop Antennas Space Appl., The Netherlands, Oct. 2010.

C.Sivapriya, D.Karthika, "Adaptive Beam Forming Network with Multiple Beam Antennas," International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.348-353, 2016.

Research in Remote Sensor Systems has witnessed a tremendous increment in the last two decades. Apart from military surveillance, remote sensor framework (WSN) have been conveyed in the ranges of healthcare monitoring, oil-field explorations, nuclear power plant monitoring, underwater exercises surveillance, and geo-informatics. However, with the expanded sending of WSN utilizing the unauthorized range band (that is, the Industrial Scientific and Medical-ISM), there is an expanding demand for correspondence channels inside this band due to over-crowding of the band. Critical issues in sensor systems is the need to minimize vitality use without undermining the quality of administration (QoS) provisioning of the network. With the worldview shift in remote correspondences towards Intellectual Radio (CR) technology, it is believed that the issue of rare range in the unauthorized bands, and short framework lifetime rocking the WSN applications in the unauthorized band can be mitigated. In this paper, we present a Intellectual radio-based remote sensor framework (CRWSN), and propose a outline idea for this relatively new sensor framework paradigm. Also, we highlighted conceivable prospects and challenges related with the improvement and sending of this worldview in sensor networks. This, we accept will pave way for the next-era (NG) sensor framework applications.

CR-WSN, Energy, Sensing, Communication, Channels, Spectrum, Next-Generation

[1] Amna Jamal; Chen-Khong Tham; Wai-Choong Wong, “CR-WSN MAC: An energy efficient and spectrum aware MAC protocol for cognitive radio sensor network”, 2014 9th International Conference on Cognitive Radio Oriented Wireless Networks and, Communications (CROWNCOM), Year: 2014, Pages: 67 – 72.
[2] Ashwin Alur Sreesha; Shashank Somal; I-Tai Lu, “Cognitive Radio Based Wireless Sensor Network architecture for smart grid utility”, Systems, Applications and Technology Conference (LISAT), 2011 IEEE Long Island, Year: 2011, Pages: 1 – 7.
[3] Haythem Bany Salameh; Mohammed F. Dhainat; Ali Al-Hajji; Raed Aqeli;Mohammad Fathi, “A Two-Level Cluster-Based Cognitive Radio Sensor Network: System Architecture, Hardware Design, and Distributed Protocols”, Cloud Engineering (IC2E), 2015 IEEE International Conference on, Year: 2015, Pages: 287 – 292.
[4] Zhaowei Qu; Yang Xu; Sixing Yin, “A novel clustering-based spectrum sensing in cognitive radio wireless sensor networks”, 2014 IEEE 3rd International Conference on Cloud Computing and Intelligence Systems, Year: 2014, Pages: 695 – 699.
[5] Mustapha; Borhanuddin M. Ali; A. Sali; Mohd F. A. Rasid; H. Mohamad, “Energy-aware cluster based cooperative spectrum sensing for cognitive radio sensor networks”, Telecommunication Technologies (ISTT), 2014 IEEE 2nd International Symposium on, Year: 2014, Pages: 45 – 50.
[6] Kok-Lim Alvin Yau; Peter Komisarczuk; Paul D. Teal, “Cognitive Radio-based Wireless Sensor Networks: Conceptual design and open issues”, Cognitive Radio-based Wireless Sensor Networks: Conceptual design and open issues, 2009 IEEE 34th Conference on Local Computer Networks, Year: 2009, Pages: 955 – 962.
[7] Mostafa Hefnawi, “Large-Scale Multi-Cluster MIMO Approach for Cognitive Radio Sensor Networks”, IEEE Sensors Journal,Year: 2016, Volume: 16, Issue: 11, Pages: 4418 – 4424.
[8] Xiang Sheng; Jian Tang; Weiyi Zhang, “Energy-efficient collaborative sensing with mobile phones”, INFOCOM, 2012 Proceedings IEEE, Year: 2012, Pages: 1916 – 1924.
[9] Sagar Venkatesh Gubbi; Bharadwaj Amrutur”, All Digital Energy Sensing for Minimum Energy Tracking”, IEEE Transactions on Very Large Scale Integration (VLSI) Systems, Year: 2015, Volume: 23, Issue: 4,Pages: 796 – 800.
[10] Miguel Luís; António Furtado; Rodolfo Oliveira; Rui Dinis; Luis Bernardo, “Energy sensing parameterization criteria for cognitive radios”, 2012 International Symposium on Wireless Communication Systems (ISWCS), Year: 2012, Pages: 61 – 65.
[11] Yildiz Sinangil; Anantha P. Chandrakasan” An embedded energy monitoring circuit for a 128kbit SRAM with body-biased sense-amplifiers”, Solid State Circuits Conference (A-SSCC), 2012 IEEE Asian, Year: 2012, Pages: 69 – 72.
[12] Yildiz Sinangil; Anantha P. Chandrakasan, “A 128 Kbit SRAM With an Embedded Energy Monitoring Circuit and Sense-Amplifier Offset Compensation Using Body Biasing”, IEEE Journal of Solid-State Circuits, Year: 2014, Volume: 49, Issue: 11, Pages: 2730 – 2739.
[13] Ali O. Ercan; M. Oguz Suna, “Energy Sensing Strategy Optimization for Opportunistic Spectrum Access”, IEEE Communications Letters, Year: 2012, Volume: 16, Issue: 6, Pages: 828 – 830.
[14] Rafael Send; Qiliang Richard Xu; Igor Paprotny; Richard M. White; Paul K. Wright, “Granular Radio EnErgy-sensing Node (GREEN): A 0.56 cm3 wireless stick-on node for non-intrusive energy monitoring”, SENSORS, 2013 IEEE, Year: 2013, Pages: 1 – 4.
[15] Kameswari Chebrolu; Ashutosh Dhekne, “Esense: Energy Sensing-Based Cross-Technology Communication”, IEEE Transactions on Mobile Computing, Year: 2013, Volume: 12, Issue: 11, Pages: 2303 – 2316.

R.Venkatesh, S.Vijayakumar, "Performance Adaptive Frequency Switching and Reuse in Cognitive Radio for Enhancing Data Transmission," International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.354-360, 2016.

Globalization has made the Stock Market Expectation (SME) precision more testing also, compensating for the scientists also, other participants in the stock market. Nearby also, global monetary situations along with the company’s monetary quality also, prospects have to be taken into account to progress the expectation accuracy. Genetic Algorithm (GA) has been identified to be one of the overwhelming data mining methods in stock market expectation area. In this paper, we survey distinctive GA models that have been tested in SME with the unique improvement methods utilized with them to progress the accuracy. Also, we explore the conceivable research procedures in this precision driven GA models.

Genetic Algorithm, Multilayer Perceptron, Back Propagation, Stock market expectation & Expectation accuracy.

[1] Ortiz-Rodríguez José Manuel; Martínez-Blanco Ma. del Rosario; Gallego Eduardo; Vega-Carrillo Héctor Rene, “Artificial Neural Networks Modeling Evolved Genetically, a New Approach Applied in Neutron Spectrometry and Dosimetry Research Areas”, Electronics, Robotics and Automotive Mechanics Conference, 2008. CERMA '08, Year: 2008,Pages: 387 - 392
[2] Xue-Bin Li; Xiao-Ling Yu, “Influence of Sample Size on Prediction of Animal Phenotype Value Using Back-Propagation Artificial Neural Network with Variable Hidden Neurons”, Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on,Year: 2009,Pages: 1 - 4,
[3] Stephan H. Chagas; João B. Martins; Leonardo L. de Oliveira, “An approach to localization scheme of wireless sensor networks based onartificial neural networks and Genetic Algorithms”, New Circuits and Systems Conference (NEWCAS), 2012 IEEE 10th International, Year: 2012,Pages: 137 - 140
[4] Yuhong Li; Weihua Ma, “Applications of Artificial Neural Networks in Financial Economics: A Survey”, Computational Intelligence and Design (ISCID), 2010 International Symposium on, Year: 2010, Volume: 1,Pages: 211 - 214
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M.Vigneshwari, S.Dhanalakshmi, "A Morphological Based Prediction of News Stock Market and Money Using Genetic Algorithm," International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.361-366, 2016.

A remote sensor framework comprises of numerous sensor hubs which are deployed to monitor physical or environmental conditions Also, to pass the collected information to a base station. Though remote sensor framework is subjected to have major applications in all the areas, it too has numerous security dangers Also, attacks. Among all dangers such as sinkhole, wormhole, selective forwarding, denial of service also, hub replication, Sybil assault is a major assault where a single hub has different identities. When a Sybil hub act as a sender, it can send false information to its neighbors. When it acts as receiver, it can receive the information which is originally destined for a legitimate node. The existing arrangements consume more energy. So a vitality effective calculation named Sybil secure is proposed. Experimental results appear that Sybil secure devours less vitality than existing protection mechanisms.

Remote Sensor Network, Sybil, Group Head, Inquiry Packet

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K.Dhivya, S.Dhanalakshmi, "Efficient and Enhancement Prediction of Sybil Attacks in Online Social Networks Using Vote-Trust Method," International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.367-671, 2016.

Objective: The essential objective of this work is finding a false positioning conduct of mobile applications where mobile application designers may create false confirmations for giving a top positioning for them. The essential objective of this work is to find out the false confirmations present in the positioned mobile apps. This work endeavors to improve the precision of location of false positioning conduct of mobile applications by performing Idea vector based review Proof analysis. Method: Mobile application positioning false conduct is the biggest issue in the mobile application advancement environment due to the debasement of mobile app’s imperative level. In the existing work, Driving Session Approach based Proof total (LSMEA) is presented to leverage the false positioning activities. This LSM investigation the three types of confirmations such as positioning based, rating based furthermore, review based furthermore, aggregates their Yield finally for recognizing the false positioning conduct of mobile apps. Among the above said evidences, review based Proof is based on client conclusion about the corresponding mobile app. LSM investigation the clients review remarks by utilizing dormant semantic approach which will find the imperative semantic terms from the client review comments. However this method failed to recognize the ideas of semantic terms precisely which might lead to off-base assumption of false positioning behaviour. This problem is overcome in this work by introducing the Idea Vector based Review Proof Investigation (CVREA) which is done by utilizing WordNet tool. Word Net instrument will retrieve the most imperative ideas present in each sentence of client review remarks based on which extortion signature would be computed. Finally, result of these three confirmations would be consolidated together to distinguish the false positioning conduct of mobile apps. Application/ Improvements: This proposed research approach would be more helpful in the mobile application markets where the number of applications created for the specific reason has been expanded considerably. In this situation, it is required to give truthful furthermore, most popular mobile applications to the clients to increment the notoriety level. This proposed research approach gives a way for increasing the notoriety level of the mobile owners by recognizing furthermore, eliminating the false positioning conduct of mobile apps.

Mobile Apps, False Behaviour, Positioning Evidences, Sematic Relation

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V.Maniraj, S.Malarvizhi, "A Real Time fraud Rank Identification using Semantic Relation Analysis on Mobile Web Application," International Journal of Computer Sciences and Engineering, Vol.4, Issue.4, pp.372-378, 2016.