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Distributed Sensing plays a keyrole in the realm of modern sensing technology and fiber optic sensors are the ultimate choice for that. Fiber optic distributed sensors are extremely popular because it can able to measure strain and temperature difference with very high resolution of about 2 cm. In this paper we have tried to simulate the process of measuring the strains using Stimulated Brillouin and Rayleigh scattering by FDTD method and tried to investigate how well it will match with the strains obtained from the experimental process.These distributed sensors are used to monitor mainly the structural health of the civil or mechanical engineering systems and are facilitate to develop advanced sensing devices like Distributed Acoustic Sensors.

Stimulated Brillouin Scattering, Rayleigh scattering, FDTD, Optical Fiber Sensor, Cross-correlation, Tunable Wavelength Coherence Time Domain Reflectometer (TW-COTDR)

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Mitsuharu Shiwa, Kisalaya Chakrabarti, "Simulation Study of Strains Obtained by Two Different Scattering Processes in Optical Fiber Sensors," International Journal of Computer Sciences and Engineering, Vol.4, Issue.10, pp.1-9, 2016.

By increasing the advantages of network based systems and dependency of daily life with them, the efficient operation of network based systems is an essential issue. Since the number of attacks has significantly increased, intrusion detection systems of anomaly network behavior have increasingly attracted attention among research community. Intrusion detection systems have some capabilities such as adaptation, fault tolerance, high computational speed, and error resilience in the face of noisy information. So, construction of efficient intrusion detection model is highly required for increasing the detection rate as well as decreasing the false detection. . This paper investigates applying the following methods to detect the attacks intrusion detection system and understand the effective of GA on the ANN result: artificial Neural Network (ANN) for recognition and used Genetic Algorithm (GA) for optimization of ANN result. We use KDD CPU 99 dataset to obtain the results; witch shows the ANN result before the efficiency of GA and compare the result of ANN with GA optimization.

Artificial Neural Network (ANN); Intrusion detection; Genetic algorithm (GA); Machine learning; Network Security

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Author Profile

A. Dastanpour, S. Ibrahim, R. Mashinchi, "Effect of Genetic Algorithm on Artificial Neural Network for Intrusion Detection System," International Journal of Computer Sciences and Engineering, Vol.4, Issue.10, pp.10-18, 2016.

Re-contextualization is basically a transformative process of reframing a system structure to assume that of another system. It extracts texts, symbols, signs, artefacts, or meanings from its original structure to assume another structure in context. The concept is applied in abstract and quantitative fuzziness to resolve and re-interpret discrete fuzzy function by assuming fuzzy polynomial structure. This study is premised upon the fuzziness in relationships exhibited by cyber-security vulnerabilities and threat constructs as fuzzy functions. The evaluation of discrete fuzzy functions based on arbitrary equidistant computations render the solution indeterminate. However, re-contextualizing the cyber-risk function into a fuzzy polynomial simplifies the solution and depicts its functional nature for real world applications. Numerical examples are used to illustrate the concept by the Ranking method.

Cyber-Risk; Re-contextualization; Fuzzy Polynomial; Discrete Fuzzy Functions; Ranking Method

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E.O. Yeboah-Boateng, "Re-contextualization of Discretized Fuzzy Cyber-Risk Functional Arguments with Fuzzy Polynomials," International Journal of Computer Sciences and Engineering, Vol.4, Issue.10, pp.19-26, 2016.

In this paper, we report about the design and implementation of a web-based prototype system for allowing consumers to access general services using their computers or handheld devices. The aim of the work is to use technology to assist people having a daily routine of work in getting needed services that may hinder their regular work. These services include housekeeping, vehicle maintenance, child tutoring, and many others. We proposed and developed a web-based general service provider system where business entities can offer their services and consumers can book and use those services. Such a system can greatly save consumers` time and lower their stress level as they will be relieved to focus on their daily routine work.

Keywords� E-commerce; General service provider; Web-based systems; Bootstrap framework

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J. Ali, "A Web-Based General Service Provider," International Journal of Computer Sciences and Engineering, Vol.4, Issue.10, pp.27-32, 2016.

Synthetic Aperture Radar(SAR) image filtering has been of interest since its inception. A variety of denoising filters for SAR images have been proposed in the recent years, which are targeted at removing the speckle noise to increase the contrast of the image, and make it useful for further image interpretation and applications. Of late, Wavelet based SAR data denoising techniques have been gaining popularity due to its space-frequency localization capability and the capacity to analyse the data at different scales. In this paper, we have attempted to derive an optimal approach for wavelet based SAR image filtering based on the quality criteria which takes into account not only the radiometric quality but also the geometric quality using point target data of actual Corner Reflector. Different orders of Daubechies wavelet coefficients have been used in the DWT(Discrete Wavelet Transform) based approach. In this study all aspects of an image quality have been taken into consideration such as the geometric fidelity and the radiometric quality, and using a simple heuristic soft thresholding criteria, optimal basis has been arrived at.

SAR, speckle, denoising, Wavelet based denoising, thresholding, decomposition, mother wavelets, radiometric resolution, geometric resolution, corner reflector.

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[33] V S Rathore & V S Kharsan, �Simulation of Hybrid Filter Model to Enhance the Quality of Noisy Images�, International Journal of Computer Sciences and Engineering, Vol-04, Issue-07, pp (18-23), July, 2016.

A. Ray, B. Kartikeyan, S. Garg, "Towards Deriving an Optimal Approach for Denoising of RISAT-1 SAR Data Using Wavelet Transform," International Journal of Computer Sciences and Engineering, Vol.4, Issue.10, pp.33-46, 2016.

Visual information transmitted in the form of digital images is becoming a major method of communication in the modern age, but the image obtained after transmission is often corrupted with noise. The received image needs processing before it can be used in applications. Image denoising involves the manipulation of the image data to produce a visually high quality image. This thesis reviews the existing denoising algorithms, such as filtering approach, wavelet based approach, and multifractal approach, and performs their comparative study. Different noise models including additive and multiplicative types are used. They include Gaussian noise, salt and pepper noise, speckle noise and Brownian noise. Selection of the denoising algorithm is application dependent. Hence, it is necessary to have knowledge about the noise present in the image so as to select the appropriate denoising algorithm. The filtering approach has been proved to be the best when the image is corrupted with salt and pepper noise. The wavelet based approach finds applications in denoising images corrupted with Gaussian noise.

Image Processing, Denoising, Pattern Recognition and Image Enhancement

[1] D. L. Donoho and I. M. Johnstone, �Adapting to unknown smoothness via wavelet shrinkage,� J. Amer. Statist. Assoc., vol. 90, pp. 1200-1224, 1995.
[2] M. K. Mihcak, I. Kozintsev, K. Ramchandran, and P. Moulin, �Low-complexity image denoising based on statistical modeling of wavelet coefficients,� IEEE Signal Process. Lett., vol. 6, pp. 300-303, 1999.
[3] S. G. Chang, B. Yu, and M. Vetterli, �Spatially adaptive wavelet thresholding with context modeling for image denoising,� IEEE Trans. Image Process., vol. 9, pp. 1522-1531, 2000.
[4] I. Prudyus, S. Voloshynovskiy, and A. Synyavskyy, �Wavelet-based MAP image denoising using probably better class of stochastic i.i.d. image models,� Proc. Int. Conf. Telecommun., Modern Satellite, Cable and Broadcasting Service, pp. 583-586, 2001.
[5] L. Kaur, S. Gupta, and R. C. Chauhan, �Image denoising using wavelet thresholding,� Proc. Int. Conf. Computer Vision, Graphics and Image Process., pp. 1-4, 2002.
[6] L. Sendur and I. W. Selesnick, �Bivariate shrinkage with local variance estimation,� IEEE Signal Process. Lett., vol. 9, pp. 438-441, 2002.
[7] A. Achim and E. E. Kuruoglu, �Image denoising using bivariate α-stable distributions in the complex wavelet domain,� IEEE Signal Process. Lett., vol. 12, pp. 17-20, 2005.
[8] A. Pizurica and W. Philips, �Estimating the probability of the presence of a signal of interest in multiresolution single- and multiband image denoising,� IEEE Trans. Image Process., vol. 15, pp. 654-665, 2006.
[9] F. Luisier, T. Blu, and M. Unser, �A new SURE approach to image denoising: Interscale orthonormal wavelet thresholding,� IEEE Trans. Image Process., vol. 16, pp. 593-606, 2007.
[10] H. Rabbani, �Image denoising in steerable pyramid domain based on a local Laplace prior,� Pattern Recognition, vol. 42, pp. 2181-2193, 2009.
[11] Q. Guo and S. Yu, �Image denoising using a multivariate shrinkage function in the curvelet domain,� IEICE Electron. Express, vol. 7, pp. 126-131, 2010

D. Tripathi, V.K. Shukla, "Review on Recent Applications of High Accuracy Approach for High Level Image Denoising Techniques," International Journal of Computer Sciences and Engineering, Vol.4, Issue.10, pp.47-51, 2016.

Recommender Systems are eminently in demand to manage the problem of highly overloading data and to avoid the retrieval of irrelevant information from Web, which is a major part of Information Filtering. Recommender Systems helps user to make precise and explicit decisions and study the user�s knowledge to enhance the Business growth. Different Recommendation methods are implemented for achieving varied recommendations in numerous vital applications based on the expected behavior of the system and relevant data mining strategies are used to perform efficient information retrieval. This paper analyses the various Recommendation methods available for building effective Recommender Systems and exploits the participation and usage of Recommendation methods in different domains. This paper also focuses to discuss Data Mining techniques and their scope towards implementing such effective Recommender Systems.

Recommendation Algorithm; Content Based Filtering; Collaborative Filtering; Hybrid Recommendation; Knowledge Based Recommendation; Group Recommendation; Data Mining Methods

[1] R.Akil Sindhu and Dr.R.Manicka Chezian, �The Movement of Web from Web 0.0 to Web 5.0: A Comparative Study�, International journal of Multidisciplinary Research and Development, Vol-03, Issue-01, Pp. (176-179), Mar 2016.
[2] Jie Lu, Dianshuang Wu, Mingsong Mao, Wei Wang, Guangquan Zhang, �Recommender System Application Developments: A Survey�, Decision Support Systems, Vol-74, Issue -C, Pp. (12-32), June 2015.
[3] R.Akil Sindhu and Dr.R.Manicka Chezian, �Semantic Web and Ontology: Effective Approaches to Build Intelligent Web�, International Journal of Innovative Research in Computer and Communication Engineering, Vol-04, Issue-03, Pp. (4241-4248), Mar 2016.
[4] RVVSV Prasad and V Valli Kumari, �A CATEGORICAL REVIEW OF RECOMMENDER SYSTEMS�, International Journal of Distributed and Parallel Systems (IJDPS) Vol-03, No-05, Pp. (73-83), Sep 2012.
[5] Daniar Asanov, �Algorithms and Methods in Recommender Systems�, Berlin Institute of Technology Berlin, Germany, 2011.
[6] Zuping Liu, �Collaborative Filtering Recommendation Algorithm Based on User Interests�, International Journal of
u- and e- Service, Science and Technology, Vol-08, No-04, Pp. (311-320), 2015.
[7] Sihem AmerYahia, Senjuti Basu Roy, Ashish Chawla, Gautam Das, Cong Yu, �Group Recommendation: Semantics and Efficiency �, Proceedings of the VLDB Endowment, Vol-02, Issue-01, Pp. (754-765), Aug 2009.
[8] Francesco Ricci, Lior Rokach, Bracha Shapira, Paul B. Kantor �Recommender Systems Handbook�, Springer Science + Business Media, LLC-2011, Second (2nd) Edition, ISBN: 978-0-387-85819-7.
[9] Poonam B.Thorat, R.M Goudar, Sunita Barve, �Survey on Collaborative Filtering, Content-based Filtering and Hybrid Recommendation System�, International Journal of Computer Applications (0975 � 8887) Vol-110, No-04, Pp. (31-36), Jan 2015.
[10] Neethu Raj, Suja Rani M S, �An Overview of Content Recommendation Methods�, International Journal of Innovative Research in Compute and Communication Engineering Vol-03, Issue-01, Pp. (334-339), Jan 2015.
[11] Lalita Sharma, Anju Gera, �A Survey of Recommendation System: Research Challenges�, International Journal of Engineering Trends and Technology (IJETT) � Vol-04, Issue-05, Pp. (1989-1992), May 2013.
[12] Ruchita V. Tatiya , Prof. Archana S. Vaidya, �A Survey of Recommendation Algorithms�, IOSR Journal of Computer Engineering Vol-16, Issue-06, Pp.(16-19), Nov � Dec. 2014.
[13] Majid Hatami and Saeid Pashazadeh, �Enhanciing Prediction in Collaborative Filtering-Based Recommender Systems�, International Journal of Computer Sciences and Engineering, Vol-02, Issue-01, Pp. (48-51), Jan 2014.

R.A. Sindhu, R.M. Chezian, "A Concise Analysis of Various Recommendation Methods and Techniques for Efficient Recommender Systems," International Journal of Computer Sciences and Engineering, Vol.4, Issue.10, pp.52-58, 2016.

Vehicular Adhoc Networks (VANETs) are gaining growing interest and research efforts over recent years for it offers enhanced safety and enriched travel comfort. However, security concerns that are either general seen in adhoc networks or unique to VANET present great challenges. This review paper presents the basics of VANET which includes architecture of VANET, its applications and its characteristics. The major consideration of this paper is on security, so security requirements and issues related to security are also presented in this paper. This paper also provides information about types of attackers and types of attacks in VANET.

MANET, VANET, Key management

[1] Diyar Khairi M S, Amine Berqia, �Survey on QoS and Security in Vehicular Ad hoc Networks�, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 5, Issue 5, 2015, pp. 42-52.
[2] Praveen G Salagar, Shrikant S Tangade,� A SURVEY ON SECURITY IN VANET‟, International Journal For Technological Research In Engineering, Volume 2, Issue 7,2015, pp. 1397- 1402
[3] Jaydeep P. Kateshiya, Anup Prakash Singh, �Review To Detect and Isolate Malicious Vehicle in VANET�, International Journal of Innovative Research in Science, Engineering and Technology Vol. 4, Issue 2, 2015, pp.127-132
[4] Arif Sari, Onder Onursal, Murat Akkaya, �Review of the Security Issues in Vehicular Ad Hoc Networks (VANET)�, Int. J. Communications, Network and System Sciences, Vol. 8, 2015,pp.552-566
[5] Komal B. Sahare, DR. L.G.Malik, � Review - Technique for Detection of Attack in VANET�, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 4, Issue 2, 2014, pp.580-584.
[6] Rashmi Raiya, Shubham Gandhi, � Survey of Various Security Techniques in VANET�, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 4, Issue 6, 2014, pp. 431-433.
[7] Divya Chadha, Reena, �Vehicular Ad hoc Network (VANETs): A Review�, International Journal of Innovative Research in Computer and Communication Engineering, 2015.

V. Singh, K. Mahajan, "VANET and its Security Issues- A Review," International Journal of Computer Sciences and Engineering, Vol.4, Issue.10, pp.59-64, 2016.

Cloud computing is a kinds of computing that depend on distribution computing resources before having local servers or own devices to knob applications. Cloud computing is equivalent to grid computing, In the cloud is a kind of computing where vacant handing out rounds of the entire computers in a network are harnesses to solved the concerns also focused for some stand-alone mechanism. Cloud computing security mentions to the group of processes, procedures and standards designed to deliver information security guarantee in a cloud environment. Cloud computing security comprises both logical and physical security concerns across all the diverse various models of software platform, infrastructure and software. It also defines how these services are delivered (public, private or hybrid delivery model).

Encryption, Decryption, ECC, RSA, SLA cloud storage

[1] Ranjit Kaur and Raminder Pal Singh �Enhanced Cloud Computing Security and Integrity Verification via Novel Encryption Techniques� International Conference on Advances in Computing, Communications and Informatics (ICACCI), IEEE-2014
[2] Dr. L. Arockiam and S. Monikandan �Efficient Cloud Storage Confidentiality to Ensure Data Security� International Conference on Computer Communication and Informatics (ICCCI), IEEE-2014, DOI-Jan. 03 � 05, 2014, Coimbatore, INDIA
[3] R.K. Banyan, V.K. Jain and Pragya Jain �Data Management System to Improve Security and Availability in Cloud Storage� International Conference on Computational Intelligence & Networks, IEEE-2015, DOI 10.1109/CINE.2015.32.
[4] Mohammed faez AL-Jaberi, AnazidaZainal �data integrity and privacy model in cloud computing� International Symposium on Biometrics and Security Technologies (ISBAST), IEEE, 2014.
[5] Cindhamani.J, Naguboynia Punya, Rasha Ealaruvi and L.D. Dhinesh babu �An enhanced data security and trust management enabled framework for cloud computing systems� 5th ICCCNT, IEEE-2014, DOI- July 11-13, 2014.
[6] Mr.Chandrashekhar S. Pawar ,Mr.Pankaj R. Patil �Providing Security and Integrity for Data Stored in Cloud Storage� ICICES2014 - S.A. Engineering College, Chennai, Tamil Nadu, India , IEEE 2014
[7] Rukaiya Sheikh, Disha Deotale Security and Authentication Process using ECC in VANET�. International Journal of Advance Research in Computer Science and Management Studies
[8] F. Yahya, V. Chang, R.J. Walters and G.B. Wills �Security Challenges in Cloud Storage� 6th International Conference on Cloud Computing Technology and Science, IEEE-2014, DOI 10.1109/CloudCom.2014.171.
[9] Y Govinda Ramaiah and G Vijaya Kumari �Complete Privacy Preserving Auditing for Data Integrity in Cloud Computing� 12th International Conference on Trust, Security and Privacy in Computing and Communications, IEEE-20 13,DOI 10.1109/TrustCom.2013.191.
[10] Sravan kumar R and Ashutosh Saxena �Data Integrity Proofs in Cloud Storage� IEEE-2011.
[11] V.Nirmala, R.K.Sivanandhan and Dr..R. Shanmuga Lakshmi �Data Confidentiality and Integrity Verification using User Authenticator� International Conference on Green High Performance Computing ,IEEE-2013, March 14-15, 2013.
[12] S.Mahdi Shariati, Abouzarjomehri and M Hossein Ahmadzadegan �Changes and Security issues in cloud computing from two perspectives: Data Security and Privacy Protection�2nd International Conference on Knowledge-Based Engineering and Innovation (KBEI), IEEE-2015.
[13] Siddharth Dutt Choubey and Mohit Kumar Namdeo �Study of Data Security and Privacy Preserving Solutions in Cloud Computing� International Conference on Green Computing and Internet of Things (ICGCloT), IEEE-2015.

A. Bansal, A. Agrawal, "Providing Confidentiality, Integrity and Atomicity for data stored in the cloud storage," International Journal of Computer Sciences and Engineering, Vol.4, Issue.10, pp.65-70, 2016.

Wireless sensor network consists various sensor nodes that are used to monitor any target area like forest fire detection by our army person and monitoring any industrial activity by industry manager. Wireless sensor networks have been deployed in several cities to monitor the concentration of dangerous gases for citizens. In wireless sensor network when sensor nodes communicate from each other then routing protocol are used for communication between protocol layers. Wireless sensor network protocol stack consist five layers such as Application layer, Transport layer, Network layer, MAC Layer, Physical layer. In this paper we study and analysis Bellman-Ford routing algorithm and check the flow of data between these protocol layers. For simulation purpose we are using Qualnet 5.0.2 simulator tool.

Sensor nodes, Wireless Sensor Network, Bellman-Ford routing algorithm, Qualnet 5.0.2.

[1]. I.F. Akyildiz et al., �Wireless sensor networks: a survey�, Computer Networks 38, 393�422, 2002.
[2]. Jagdeep Singh, Manju Bala and Varsha , "REAC-IN Regional Energy Aware Clustering Protocol in Wireless Sensor Network", International Journal of Computer Sciences and Engineering, Volume-04, Issue-05, Page No (90-94), May -2016
[3]. A. Hemalatha and D. Sasirekha, "A Survey on Energy Efficient Routing Protocols in WSN", International Journal of Computer Sciences and Engineering, Vol. 4(3), pp.77-81, Mar -2016
[4]. W. R. Heinemann, A. Chandrakasan, and H. Balkrishnan, �Energy-Efficient Communication Protocol for Wireless Micro sensor Networks�, in Proceedings of 33rd Hawaii International Conference on System Science, Vol. 2, pp.1-10, Jan. 2000.
[5]. Nathiya, R., and S. G. Santhi. "Energy Efficient Routing with Mobile Collector in Wireless Sensor Networks (WSNs)." International Journal of Computer Sciences and Engineering, Vol. 2 (2), pp36-43, 2014
[6]. S.G. Santhi and R.Nathiya, "Power Consumption Based Efficient Routing With Mobile Collector in Wireless Sensor Networks", International Journal of Computer Sciences and Engineering, Vol.2, Issue-4, pp.64-70, Apr -2014
[7]. C-Y. Chong, S.P. Kumar, �Sensor networks: evolution, opportunities, and challenges�, Proceedings of the IEEE 91 (8) ,1247�1256, July 2007.
[8]. Aditya Singh Mandloi and Vinita Choudhary, "An Efficient Clustering Technique for Deterministically Deployed Wireless Sensor Networks", International Journal of Scientific Research in Network Security and Communication, Vol.1, Issue-1, pp.6-10, 2013
[9]. Al-Karaki, Jamal N., and Ahmed E. Kamal. "Routing techniques in wireless sensor networks:a survey." Wireless communications, IEEE 11.6: 6-28, 2004.
[10]. Mardani, Morteza, Seung-Jun Kim, and Georgios B. Giannakis. "Cross-layer design of wireless multihop random access networks." Signal Processing, IEEE Transactions on 60.5 (2012): 2562-2574.
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[13]. Yong Ding, Zhou Xu, Lingyun Tao,�An Cross Layer Algorithm Based on Power Control for Wireless Sensor Networks�, Springer-Verlag Berlin Heidelberg, pp.209-216, 2010.
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R.K. Saini, Ritika, S. Vijay, "Data flow in Wireless Sensor Network Protocol Stack by using Bellman-Ford Routing Algorithm," International Journal of Computer Sciences and Engineering, Vol.4, Issue.10, pp.71-75, 2016.