Volume-6 , Issue-10 , Oct - 2018 Go Back

Cloud services are increasing day by day over the Internet. Using the cloud services both time and money will be saved for user. However, there are some security problems to be solved for users and enterprises for data storing in secure way in the cloud. The real fact is that when users will have not any kind of physical control on outsourced data. Cloud user is concerned about the security and integrity of data stored in the cloud environment as it can be attacked by attacker. The purpose of this research paper using Third Party Auditor an efficient public data auditing technique works for verify the security and integrity of data. Which data is stored in the cloud. The proposed auditing technique makes use of Secure Hash Algorithm (SHA-2) for generating verification meta data and message digest for data integrity authentication and AES algorithm for encryption. Analysis of proposed technique shows provably more secure and TPA takes a constant time to audit files of different sizes.

Cloud Computing, Public Auditing, Data Integrity, Data Privacy, Third Party Auditor (TPA).Cloud Service Provider (CSP).

[1] W. A. Sultan Aldossary, “Data Security, Privacy, Integrity and Availability in Cloud Computing”, International Journal of Advanced Computer Science and Applications,Volume 7, Issue 4, pp. 485- 498, 2016.
[2] Amazon.com, “Amazon Web Services (AWS).
[3] X. Jia and N. K. Yang, “Data Storage Auditing Service in Cloud Computing: Challenges, Methods and Opportunities”, World Wide Web, Volume 15, Issue 4, pp. 409–428, 2012.
[4]. Cong Wang , Sherman S M Chow, Qian Wang, Kui Ren, and Wen jing Lou. “Privacy Preserving Public Auditing for Secure Cloud Storage.” IEEE Transactions on Computers, Volume 62, Issue 2, February 2013.
[5] . Sangita Chaudhari, Swapnali More, , “Third Party Public Auditing Scheme for Cloud Storage”, International Journal of Procedia Computer Science, Volume 79, pp. 69-76, 2016.
[6] Tejaswini, K. Sunitha, and S. K. Prashanth. “Privacy Preserving Public Auditing Service for Data Storage in Cloud Computing”. Indian Journal of Research PARIPEX, Volume 2, Issue 2, pp. 131- 133, February 2013.
[7] S Ezhil Arasu, B Gowri, and S Ananthi. “Privacy Preserving Public Auditing in cloud using HMAC Algorithm”. International Journal of Recent Technology and Engineering (IJRTE) ISSN: 2277, 3878, Volume 2, Issue 1, pp. 149-152, March 2013.
[8]. Cong Wang, Qian Wang, Kui Ren, Ning Cao, and Wenjing Lou. “Towards Secure and Dependable Storage Services in Cloud Computing”. IEEE Transactions on Services Computing, Volume 5, Issue 2, pp. 220–232, May 2011.
[9] Wang, C., Wang, Q., Ren, K., Lou, W., 2010. “Privacy-Preserving Public Auditing for Data Security in Cloud Computing”. In: INFOCOM, 2010 Proceedings IEEE, pp. 1–9, 2010.
[10]. Solomon GuadieWorku, Jining Zhao, Chunxiang Xu, and Xiaohu.“Secure and Efficient Privacy-Preserving Public Auditing Scheme for Cloud Storage”. Computers & Electrical Engineering, Volume 40, Issue 5, pp. 1703-1713, July 2014.

Shraddha Saxena, Manish Sharma, "Secure Technique to Achieve Data Privacy and Data Integrity in Cloud Computing," International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.545-548, 2018.

Impulsive differential equations deals with the study of the dynamic processes which undergo sudden changes. Since 1990’s many mathematicians have derived lots of results on differential equations undergoing impulsive effects. Problems including local initial condition and the problems including nonlocal conditions were considered in their work. But the deterministic impulsive differential equations fail to demonstrate many real life situations. And to handle such situations the concept of random impulsive differential equations were introduced. In this paper, we introduce random impulsive differential equations with nonlocal condition . The main aim of this paper to study the existence and uniqueness of solutions of random impulsive differential equations with nonlocal condition. For, we prove a result using fixed point theory technique.

Existence, Uniqueness, Fixed point theorem, Random impulses, Nonlocal conditions

[1] A. Anokhin, L. Berezansky, E. Braverman," Exponential stability of linear delay impulsive differential equations", J. Math. Anal. Appl. vol.193, pp.923-941,1995.
[2] J. Bana, B. Rzepka, "An application of a measure of noncompactness in the study of asymptotic stability", Appl. Math. Lett. vol.16, pp.1-6, 2003.
[3] L. Berezansky, E. Braverman, "Explicit conditions of exponential stability of linear delay impulsive differential equation", J. Math. Anal. Appl. vol.214, pp. 439-458, 1997.
[4] Bheeman, Radhakrishnan, Aruchamy Mohanraj, Velu Vinoba, “Existence of solutions for nonlinear Impulsive Neutral Integro differential Equations of Sobolev type with nonlocal conditions in banach space”, Electron. J. Differential Equations, Vol.2013 , No.18, pp.1-13, 2013.
[5] K. Deng, “Exponential decay of solutions of sem -ilinear parabolic equations with non-local initial conditions”, J. Math. Anal. Appl., Vol.179, Issue 2 pp.630-637, 1993.
[6] Eduardo Hernandez, “On abstract differential equ- ations with state dependent non-local conditions” 2018.
[7] Eduardo Herndez, M. Rabello, and H.R. Henriquez, "Existence of solutions for impulsive partial neutral functional differential equations", J. Math. Anal. Appl. vol.331, pp. 1135-1158, 2007.

[8] E. Freedman, X. Liu, J. Wu, “Comparison principles for impulsive parabolic equations with applications to models of single species growth”, J. Australian Math. Soc., Series B, Vol.32, pp.382-400, 1991.
[9] M. Gowrisankar, P. Mohankumar, A. Vinodkumar, " Stability results of random impulsive semilinear differential equations", Acta Mathematica Scientia, Vol. 34, pp.1055-1071, 2014.
[10] Hernan R. Henriquez, Veronica Poblete, Juan C. Pozo, “Mild solutions of non-autonomous second order problems with nonlocal initial conditions ”, J. Math. Anal. Appl., Vol.412, pp.1064-1083, 2014.
[11] He Yang, Ravi P Agarwal, Yue Liung, “ Controllabi-lity for a class of Integro-differential equation envo-lving nonlocal Initial conditions”, Int. J. Control, Vol.99, Issue 12, 2017.
[12] R. Iwankievicz, and S. R. K. Nielsen, "Dynamic response of non-linear systems to Poisson distributed random impulses”, J. Sound Vibration, vol.156, pp.407-423,1992.
[13] M. Jahanshahi, M.Darabadi, “ An Analytic Solution for a nonlocal Initial boundary value problem including a partial Initial a partial differential equation with variable coefficients”, Bull. Iranian World Scientific Math. Soc., Vol.42, No.2, pp.315-326, 2016.
[14] V. Lakshmikantham, D.D. Bainov, P.S. Simeonov, "Theory of Impulsive Differential Equations", World Scientific, Singapore, 1989.
[15] Li, “Nonlinear impulsive evolution equations”, Dynam. Conti. Discr. Impul. Sys., Vol.6, 77-85, 1999.
[16] A.M. Samoilenko, and N.A Perestyuk, "Impulsive Differential Equations", Singapore, 1995.
[17] Sayooj Aby Jose, Venkitesh Usha, “Existence and uniqueness of solutions for special random impulsive differential equation”, Journal of Appl. Science and Computations, Vol.5, Issue.10, pp.14 − 23, 2018.
[18] J.M. Sanz-Serna, A.M. Stuart, "Ergodicity of dissipative differential equations subject to random impulses," J. Differential Equations, Vol.155, pp.262-284,1999.
[19] K. Tatsuyuki, K. Takashi, and S. Satoshi,"Drift motion of granules in chara cells induced by random impulses due to the myosinactin interaction," Physica A., Vol.248, Issues. 1-2, pp. 21-27,1998.
[20] A. Vinodkumar, "Existence results on random impulsive semilinear functional differential inclusions with delays", Ann. Funct. Anal., vol.3 , pp. 89-106, 2012.
[21] S. J. Wu, X. Z. Meng, "Boundedness of nonlinear differential systems with impulsive effect on random moments", Acta Math. Appl. Sin., Vol.20, Issue.1, pp.147-154, 2004.
[22] S. J. Wu, Y. R. Duan, “Oscillation, stability, and boundedness of second-order differential systems with random impulses", Comput. Math. Appl., Vol.49, Issue.9-10, pp.1375-1386, 2005.
[23] S. J. Wu, X. L. Guo, S. Q. Lin, "Existence and uniqueness of solutions to random impulsive differential systems", Acta Math. Appl. Sin., Vol.22(4), pp.595-600, 2006.
[24] S. J. Wu, X. L. Guo and Y. Zhou, "p-moment stability of functional differential equations with random impulses", Comput. Math. Appl., Vol.52, pp.1683-1694, 2006.
[25] S. J. Wu, X. L. Guo and R. H. Zhai, "Almost sure stability of functional differential equations with random impulses", Dyn. Cont. Discre. Impulsive Syst.: Series A, Vol.15, pp.403-415, 2008.
[26] A. Zavalishchin, “Impulse dynamic systems and applications to mathematical economics”, Dynam. Systems Appl., Vol.3, pp.443-449, 1994.

Sayooj Aby Jose, Venkatesh Usha, "Existence of Solutions for Random Impulsive Differential Equation with Nonlocal Conditions," International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.549-554, 2018.

Computation of topological indices is a recent research problem in mathematical and computational chemistry. Based on the number of non-neighbors of a vertex u in a graph G, non-neighbor harmonic index is defined. In this paper we compute the non-neighbor harmonic polynomial of some graphs. We develop a MATLAB program for computing the roots of the non-neighbor harmonic polynomial and hence define the perfect non-neighbor harmonic graphs.

Graphs, non-neighbors, non-neighbor harmonic polynomial, perfect non-neighbor harmonic graphs

[1] Narsing Deo, “Graph Theory with Applications to Engineering and Computer Science”, Prentice–Hall of India, Indian Reprint, New Delhi,
[2] Ivan Gutman, “Degree-based topological indices”, Croat. Chem. Acta, 86 (4) (2013) 251-361.
[3] Huiqing Liu, Mei Lu, Feng Tian, “On the Randic index”, Journal of Mathematical Chemistry Vol. 38, No. 3, October (2005).
[4] T.Doslic, “Vertex-Weighted Wiener Polynomials for Composite Graphs”, ARS MATHEMATICA CONTEMPORANEA 1 (2008) 66–80.
[5] A.R. Ashrafi, T. Doslic, A. Hamzeh, “The Zagreb coindices of graph operations”, Discrete Applied Mathematics 158 (2010) 1571-1578.
[6] A.R. Ashrafi, T. Doslic, A. Hamzeh, “Extremal Graphs with Respect to the Zagreb Coindices”, MATCH Commun. Math. Comput. Chem. 65 (2011) 85-92.
[7] Hongbo Hua, Shenggui Zhang, “Relations between Zagreb Coindices and Some Distance Based Topological Indices”, MATCH Commun. Math. Comput. Chem. 68 (2012) 199-208.
[8] Maolin Wang and Hongbo Hua, “More on Zagreb Coindices of Composite Graphs”, International Mathematical Forum, Vol. 7, 2012, No. 14, 669 – 673.
[9] P.S Ranjini, V. Lokesha, M. Bindusree and M. Phani Raju, “New Bounds on Zagreb indices and the Zagreb Co-indices”, Bol. Soc. Paran. Mat. (3s.) v. 31 1 (2013): 51–55.
[10] Douglas B.West, “Introduction to Graph Theory”, Second Edition, PHI Learning Private Limited, New Delhi.
[11] Lingping Zhong, “The harmonic index for Graphs”, Applied Mathematics Letters, 25(2012)561-566.
[12] A.Rizwana G,Jeyakumar, S.Somusundaram, “On Non-Neighbor Zagreb Indices and Non-Neighbor Harmonic Index”, International Journal of Mathematics And its Applications, Volume 4, Issue 2-D (2016), 89-101.
[13] Mohammad A. Iranmanesh and Mahboubeh Saheli, “On the harmonic index and harmonic polynomial of caterpillars with diameter four”, Iranian Journal of Mathematical Chemistry, Vol.6, No.1, March 2015; pp.41-49.

A.Rizwana, G. Jeyakumar, M.Mohamed Ismail, "Perfect Non-Neighbor Harmonic Graphs," International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.555-560, 2018.

In this fast changing era, information or data sharing is one of the key requirement of human and machines. Networks are designed so as to provide this facility of data sharing to the humans or machines. The networks which work under the adverse circumstances (i.e. intermittent connectivity) are termed as Delay Tolerant Networks. In the Delay Tolerant Networks, Congestion is the key area which needs to be addressed by the researcher and the community. In this paper we have proposed a novel technique for buffer management to avoid / remove the congestion in Delay Tolerant Networks. This approach for buffer management contemplates the size of message and the rest of the TTL of message for buffer management and for convenience of new approaching message at every node. Through the simulative results obtained in this study we found that the approach proposed and evaluated in this work is providing better delivery probability of the messages.

Delay Tolerant Network; Time to Live; Delivery Probability; Overhead Ratio; Congestion Avoidance

[1]. B A, Forouzan, “Data Communication and Networking”, McGraw Hill, India, pp.33 2012.
[2]. T. Dheepak, S. Neduncheliyan, "Low Power Distributed MAC Protocol Against Various Kinds Of Attacks By Using Traffic Analysis Methodology", International Journal of Scientific Research in Computer Science and Engineering, Vol.6, Issue.3, pp.1-7, 2018
[3]. Andrew S, Tananbaum, “Computer Networks”, Pearson Education, India, pp. 343-44, 2010.
[4]. K. Fall, S. Fareell, "DTN: An Architectural Retrospective”, IEEE Journal on Selected Areas in Communications, Vol. 26. Issue.5, June 2008.
[5]. M. Loubser, ”Delay Tolerant Networking for Sensor Networks”, SICS Technical Report, ISSN 1100-3154, January 2006.
[6]. Anurag Singh, Rajnesh Singh, Sunil Gupta, "Evaluating the Performance of TCP over Routing Protocols in MANETs Using NS2", International Journal of Scientific Research in Network Security and Communication, Vol.6, Issue.4, pp.1-4, 2018
[7]. Z. Zhang, "Routing in Intermittently Connected Mobile Ad Hoc Networks and Delay Tolerant Networks: Overview and Challenges", IEEE Communications Surveys and Tutorials, Vol. 8, Issue No. 1, pp. 24-37, January 2006.
[8]. K. Fall, “A Delay-Tolerant Network Architecture for Challenged Internets” In the proceedings of Intel Research Conference Berkley, 2003.
[9]. Daowen Hua, X. Du, L. Cao, G. Xu, Y. Qian, “A DTN Congestion Avoidance Strategy based on Path Avoidance”, In the Proceedings of 2nd Intl. Conf. Future Computer and Communication, Wuhan, China, 2010.
[10]. Qicai Yang et al: “Adaptive Parameter estimation based Congestion Avoidance Strategy for DTN”, In the Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering, Atlantic Press, Paris, 2013.
[11]. Deng-yin Zhang, Min Yang and Lei Cui. “Congestion Control Strategy for Opportunistic Network based on Message values”, Journal of Networks, Vol. 9, No. 5, May 2014.
[12]. Peeyush Patil, “Congestion Control in DTN”, In the Proceedings of Fourth Postgraduate Conference, SPPU, Pune, March 2015.
[13]. H S Bindra, “Performance Improvement of Epidemic Routing Protocol of Delay Tolerant Networks Using Improved Buffer Management”. In the proceedings of Afzalpulkar N., Srivastava V., Singh G., Bhatnagar D. (eds) Proceedings of the International Conference on Recent Cognizance in Wireless Communication & Image Processin,. Springer, New Delhi, 2016.
[14]. Anita Rani, Sangeeta Rani, Harminder Singh Bindra, “Performance Evaluation of MaxProp Routing Protocol with DL, FIFO, DLA and MOFO Buffer Management Techniques in DTN under Variable Message Buffer Size” IJERT, ISSN: 2278-0181 Vol. 3 Issue 2, February – 2014.
[15]. H S Bindra, A.L.Sangal, “Analyzing Buffer Occupancy of the Nodes under Acknowledged Delay Tolerant Network’s Routing Protocols. In the Proceedings of: Das V.V., Chaba Y. (eds) Mobile Communication and Power Engineering. AIM 2012. Communications in Computer and Information Science”, Vol. 296. Springer, Berlin, Heidelberg, 2013.
[16]. Harminder Singh Bindra, A L Sangal, "Need of Removing Delivered Message Replica from Delay Tolerant Network - A Problem Definition", IJCNIS, Vol.4, Issue.12, pp.59-64, 2012.
[17]. Amardeep et. al., “Message Size and TTL Based Congestion Control in Delay Tolerant Network”, International Journal of Advance Research in Science and Engineering, Vol. 06, Issue No. 10, pp. 1935-44, October 2017.
[18]. Lindgren, A., Doria, A., Schelén, O., “Probabilistic routing in intermittently connected networks” In the proceedings of SIGMOBILE Mob. Comput. Communication, Vol. 7, pp.19–20, 2003.

Amardeep, Devendar Gahlot, H S Bindra, "Buffer based Analysis of Congestion Control in Delay Tolerant Network," International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.561-567, 2018.

Currently, the detection of moving objects is being mandatory in most of the security systems. Moving objects are crucial in the areas of image searching, automatic annotation and for the understanding of scenes. Although the detection is a challenging task therefore, the detection of moving objects is essential to describe the accurate position and unique features of an object. The tracking of moving objects used in most of the computer vision applications. The detection and identification of objects form a moving scene or a video is called tracking. Some of the major challenges are occurred because of the position of moving cameras are not stable hence. The visibility of pictures is affected and the shadow area also considered as a challenge for the detection. In the previous research, Decision tree (J48), MLPNN (Multi-Layer Perceptron Neural Network) and KNN (K- Nearest Neighbor) used for the detection of moving objects but all these approaches are supervised that are not applicable to easily classify the data. The accuracy decreased and the false error rates increased. To sort out the previous work challenges, the current approaches are considered as namely as Optimized-MLPNN that easily stables the position and fix the location of objects.. For the classification, filters are trained that performed well and used the basic three operators as selection, crossover and mutation for the classification of moving objects. In proposed work, improve the accuracy rate, specificity, precision and reduce the FAR, FPR and FRR rate using simulation Tool MATLAB 2016a.

Moving Object Detection (MOD), Tracking and Classifciation, OMLPNN (Optimized Multi Perceptron Neuron Network), Artifical Intellgience (AI) and GMM (Gassuian Mixture Model)

[1] Neff, Michael G., Shirley N. Cheng, and Ted L. Johnson. "Moving object detection." U.S. Patent 7,999,849, issued August 16, 2011.
[2] Dhar, P. K., Khan, M. I., Gupta, A. K. S., Hasan, D. M. H., & Kim, J. M. (2012). An efficient real time moving object detection method for video surveillance system. International journal of Signal processing, Image processing and Pattern Recognition, 5(3), 93-110.
[3] Brouard, O., Delannay, F., Ricordel, V., &Barba, D. (2008, October). Spatio-temporal segmentation and regions tracking of high definition video sequences based on a Markov Random Field model. In Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on (pp. 1552-1555). IEEE.
[4] Kalirajan, K., &Sudha, M. (2015). Moving object detection for video surveillance. The Scientific World Journal, 2015.
[5] Kulchandani, J. S., &Dangarwala, K. J. (2015, January). Moving object detection: Review of recent research trends. In Pervasive Computing (ICPC), 2015 International Conference on (pp. 1-5). IEEE.
[6] Mahamuni, P. D., Patil, R. P., &Thakar, H. S. (2014). Moving object detection using background subtraction algorithm using Simulink. International Journal of Research in Engineering and Technology (IJRET), 3(6), 594-598.
[7] Sangale, K., and Kadu, N. B. Real-time foreground segmentation and boundary matting for live videos using SVM technique. International journal of advanced research in computer engineering and technology (IJARCET), volume 4 issue 11.
[8] Gong, M. (2011, June). Foreground segmentation of live videos using locally competing 1SVMs. In Computer Vision and Pattern Recognition (CVPR), 2011 IEEE Conference on (pp. 2105-2112). IEEE.
[9] Cheng, J., Yang, J., Zhou, Y., and Cui, Y. (2006). Flexible background mixture models for foreground segmentation. Image and Vision Computing, 24(5), 473-482.
[10] Mohan, Anaswara S., and R. Resmi. "Video image processing for moving object detection and segmentation using background subtraction." In Computational Systems and Communtions (ICCSC), 2014 First International Conference on, pp. 288-292. IEEE, 2014.
[11] Jadhav, Ms Jyoti J., and J. Jyoti. "Moving Object Detection and Tracking for Video Survelliance." International Journal of Engineering Research and General Science 2, no. 4 (2014): 372-378.
[12] Fablet, Ronan, P. Bouyhemy, and Marc Gelgon. "Moving object detection in color image sequences using region-level graph labeling." In Image Processing, 1999. ICIP 99. Proceedings. 1999 International Conference on, vol. 2, pp. 939-943. IEEE, 1999.
[13] Jadav, K., M. Lokhandwala, and A. Gharge. "Vision based moving object detection and tracking." In National Conference on Recent Trends in Engineering & Technology, pp. 13-14. 2011.
[14] Cohen, Isaac, and Gerard Medioni. "Detecting and tracking moving objects for video surveillance." In Computer Vision and Pattern Recognition, 1999. IEEE Computer Society Conference on., vol. 2, pp. 319-325. IEEE, 1999.
[15] Ergezer, Hamza, and Kemal Leblebicioglu. "Visual detection and tracking of moving objects." In Signal Processing and Communications Applications, 2007. SIU 2007. IEEE 15th, pp. 1-4. IEEE, 2007.

A. Kumar, M. kaur, "Moving Object Detection, Tracking and Classification Using Optimized Multiple Perceptron Neural Network," International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.568-574, 2018.

The accident is an unplanned incident which leads to injury to people, damage to a plant, machinery or some other loss. The goal of this paper is an analysis of road accidents at country level and statewide of India. The analysis shows that accidental fatalities and injuries changes according to age, gender, month and time. Analysis of road accidents plays an important role in a transportation system. Road traffic injuries and fatalities are common in nature, it would be impractical to predict one-to-one relationship among the safety measures in road accidents, injuries, and fatalities. Road safety is an important concern for both national and international level. Data mining tools and techniques are used to predict accident-prone locations. For every four minutes, one death is occurred due to road mishap in India. The crucial thing is an analysis of road accident data is its heterogeneousness. The relationship between road surface conditions, road type, severity, light conditions, etc... are investigated.

Road accidents, fatality, classification, clustering

[1] Lilting Li, Shared Shrestha, Gongzhu Hu “Analysis of Road Traffic Fatal Accidents Using Data Mining Techniques” 2016 5th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO).pp 363-3707-9 Sept. 2016.
[2] Prajakta S.Kabse, Apeksha Prajakta S. kasbe, Apeksha V. Sakhare “A review on road accident data analysis using data mining techniques” International Conference on Innovations in Information, Embedded and Communication Systems (ICIIECS).March 2017.
[3] ANGAPREET KAUR, GEETIKA GANDHI, GOBINDGARH, INDIA”A FRAMEWORK FOR ANALYZING THE ROAD ACCIDENTS IN DATA MINING USING RULE MINING” INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH IN COMPUTER AND COMMUNICATION ENGINEERING, PP 6931-6939, APRIL 2017.
[4] Ayushi Jain1, Garima Ahuja2, Anuranjana3, Deepti Mehrotra” Data Mining Approach to Analyse the Road Accidents in India”,pp.175-179.
[5] K Jayasudha and C Chandrasekar. “An overview of data mining in road traffic and accident analysis”. Journal of Computer Applications, pp.32–37, 2009.
[6] Carlo Giacomo Prato, Victoria Gitelman and Shlomo Bekhor, “Mapping patterns ofpedestrian fatal accidents in Israel”,Accident Analysis and Prevention, pp. 54–62,Jan. 2012
[7] Svetlana Bačkalić, Boško Matović and Dragan Jovanović, “Identification of hotspots road locations of traffic accidents with pedestrian in urban areas”, International Co-operation on Theories and Concept in Traffic Safety, Dec. 2014
[8] Data available online 2017: https://datamillnorth.org/dataset/road-traffic-accidents
[9] Vikas Verma, Shaweta Bhardwaj and Harjit Singh,"A Hybrid K-Mean Clustering Algorithm for Prediction Analysis,”Indian Journal of Science and Technology,(july 2016),DOI:10.17485/ijst/2016/v9i28/98392,pp.0974-6846.
[10] Frantisek Babi, Karin Zuskaova, Liangzheng Xia, “Descriptive and Predictive Mining on Road Accidents Data,” IEEE 14th International Symposium on Applied Machine Intelligence and Informatics (SAMI),2016,DOI: 10.1109/SAMI.2016.7422987, pp. 87-92.

N. Usha Rani, T. Vanaja, "Data Mining Approach to Analyze the Road Accidents in India," International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.575-579, 2018.

E-commerce business has surmounted rapidly in the past few years. Flipkart, Amazon, Snapdeal and Shopclues are excellent citation of same. Flipcart was founded in 2007 by two IITn`s only, and today it is among the top 3 e-commerce companies over a span of just seven years. Consistent growth of an organization is depend on the robust strategy predestined by the upper management, especially when you have swingeing competitors in front of you. Most of the giant e-commerce companies has adopted emerging IT technologies to align their business for sustainable growth, but still they are struggling in some of the segments, such as Personalization, where customer expectations, likes and dislikes are changing expeditiously day by day [1][2]. Personalization is a technique, where the front page of a website, which also called persona, is portrayed disparately for each customer in pursuance to the products they are interested only. This is one of the best strategy ever, to attract new customers, retain existing one, and to increase e-transactions on a website.

E-commerce, E-business, Personalization, Persona, Business Intelligence, and Analytics

[1] Shuwen Zhou, Guanghong Lei, “Application of data mining technology in membership supermarket’s customer segmentation, Proceedings of IEEE international conference on business computing and global informatization, 2011, pp 181-183, DOI 10.1109/ BCGIn. 2011.53.
[2] Malhotra, D. and Rishi, O.P., (2016), “IMSS-E: An Intelligent Approach to Design of Adaptive Meta Search System for E-Commerce Website Ranking”, in Proceedings of the International Conference on Advances in Information Communication Technology & Computing, ACM.
[3] Verma, N. and Singh, J., (2015), “Improved web mining for e-commerce website restructuring”, In Computational Intelligence & Communication Technology, 2015 IEEE International Conference, IEEE, pp. 155-160
[4] YanguangShen, Lili Xing, YitingPeng, “Study and application of web based data mining in E business”, Proceedings of IEEE Eighth ACIS international conference on software Engineering, Artificial Intelligence, Networking, and Parallel/ Distributed Computing, 2007, pp 812-816, DOI 10.1109/SND.2007.117.
[5] Conversational commerce is a term coined by ubersChrisMessina[1] in 2105 piece published on medium.
[6] Z. Ruvalcaba, A. Boehm, "Introduction To The Web Development" in murach`s HTML5 and CSS 3 1sted., Fresno, CA:Mike Murach and Associates, Inc., pp. 4-7, 201
[7] A. T. Stephen and O. Toubia, "Deriving Value from Social Commerce Networks," in Journal of Marketing Research, Forthcoming. 2010, pp. 215-228.
[8] A. M. Kaplan and M. Haenlein, "Users of the world, unite! The challenges and opportunities of Social Media" in Business Horizons. 2010, 53, pp. 59-68.
[9] X. Sun; Y. Zhao; Q. Zhu, "Understanding the niche strategies adopted by social commerce websites," in International Conference onInformation Management, Innovation Management and Industrial Engineering (ICIII`12). 2012, pp. 418-421.
[10] Y. A. Kim and J. Srivastava, "Impact of Social Influence in E-Commerce Decision Making" in Proceedings of the 9th International Conference on Electronic Commerce (ICEC `07). Minnesota, USA, 2007, pp. 293-301.
[11] D. L. Hoffman and M. Fodor, "Can you measure the ROI of your social media marketing?," MIT Slogan Management Review, vol. 52, no. 1, pp. 41-49.
[12] Eze U. C., 2008, E-Business Deployment in Nigerian Financial Firms: An Empirical Analysis of Key Factors, International Journal of E-Business Research, Volume: 4, Issue: 2, 2008 pp. 29-47
[13] Mahmood M. A., Gemoets L., Hall L. L., López F. J., and Mariadas R., 2008, Measuring e-Commerce Technology Enabled Business Value: An Exploratory Research, International Journal of E-Business Research, Volume: 4 Issue: 2, 2008 pp. 48-68
[14] koh B. 2001, E-business in the developing world, Africa and Ethopia (Ethopia in the KnowledgeAge). ICTAfrica Plc., Ethopia 2001
[15] Eze U. C., 2008, E-Business Deployment in Nigerian Financial Firms: An Empirical Analysis of Key Factors, International Journal of E-Business Research, Volume: 4, Issue: 2, 2008 pp. 29-47

Mukesh Negi, "Personalization - An Efficient Technique to Sustain Growth of an E-Commerce and Promotional Websites, Using Emerging Technologies," International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.580-584, 2018.

Fast advancement in the technology offering much smarter functionalities giving tremendous increase in Smartphone users. The battery powered Smartphone is being used to keep people engaged, communicate and remain online throughout the day, no matter where they are located so the scarcity of power is also increased. The technology advancement speed of offering functionalities in the Smartphone is much faster than that of the technology for development in batteries. Most of the applications waste energy in rest condition. The power consumption for a Distributed database system “SmartSource” using Smartphone in cellular network has been analyzed in this paper. The performance evaluation of the consumption of energy for the system is tested and presented.

Distributed Database, Smart phone, SMS

[1] Li, D., Hao, S., Gui, J., & Halfond, W. G., “An Empirical Study of the Energy Consumption of Android Applications.”, IEEE International Conference on Software Maintenance and Evolution, 2014, doi:10.1109/icsme.2014.34.
[2] Perrucci, G. P., Fitzek, F. H., & Widmer, J., “Survey on Energy Consumption Entities on the Smartphone Platform.”, IEEE 73rd Vehicular Technology Conference (VTC Spring), 2011, doi:10.1109/vetecs.2011.5956528.
[3] Li, S., & Mishra, S., “Optimizing power consumption in multicore smartphones.”, Journal of Parallel and Distributed Computing, Issue. 95,pp 124-137, 2016, doi:10.1016/j.jpdc.2016.02.004Chen, A. C., “The Evolution of Wireless Mobile Data Communication Technologies and Their Market Opportunities.”, 28Th Annual Conference of The Industrial Electronics Society. IECON 02, IEEE 2002, doi:10.1109/Iecon.2002.1182952
[4] Narayanan, L. S., & Venugopal, M. B., “An Application-Specific Windows Management Instrumentation Architecture for Improving Performance on Wireless Network.”, Journal of Computer Science, Volume 10, Issue 3, pp. 443-452, 2014, doi:10.3844/Jcssp.2014.443.452.
[5] Papadimitratos, P., & Haas, Z. J., “Secure Communication In Adverse Mobile Ad Hoc Networks.”, Network Theory and Applications, pp. 447-485, 2004, doi:10.1007/978-1-4613-0223-0_12.
[6] Sen, R., & Ramamritham, K., “Efficient Data Management on Lightweight Computing Devices.”, 21st International Conference on Data Engineering, ICDE 2005, doi:10.1109/Icde.2005.58.
[7] Mohammed Ahmed A. S., Dr. Bilal K. H. and Dr. Mustafa A. B., "Comparison between Cellular Generations", International Journal of Engineering, Applied and Management Sciences Paradigms, Vol. 22, Issue 01, 2015, ISSN (Online): 2320-6608.
[8] Ficek, M., Pop, T., Vláčil, P., Dufková, K., Kencl, L., & Tomek, M., “Performance study of active tracking in a cellular network using a modular signaling platform.”, Proceedings of the 8th international conference on Mobile systems, applications, and services (MobiSys), 2010, doi:10.1145/1814433.1814458.
[9] Zerfos, P., Meng, X., Wong, S. H., Samanta, V., & Lu, S., "A study of the short message service of a nationwide cellular network.", Proceedings of the 6th ACM SIGCOMM on Internet measurement (IMC), 2006, doi:10.1145/1177080.1177114
[10] Bhargava, B., “Building Distributed Database Systems.”, IEEE Transactions on Reliability, Volume 32, Issue 5, pp. 437-443, 1983, doi:10.1109/Tr.1983.5221722.
[11] Idwan, S. A., “Developing A Mobile Application Via Bluetooth Wireless Technology for Enhancing Communication.”, International Journal of Interactive Mobile Technologies (IJIM), Volume 3, Issue 3, 2009, doi:10.3991/Ijim.V3I3.830.
[12] Shanmugapriya M., Dr Tamilarasi A., "Designing An M-Learning Application For A Ubiquitous Learning Environment In The Android Based Mobile Devices Using Web Services", Indian Journal Of Computer Science And Engineering (IJCSE), Volume 2 Issue 1, pp. 22-30, 2011, ISSN : 0976-5166
[13] Bhargave, A., Jadhav, N., Joshi, A., Oke, P., Prof. Lahane, S.R., "Digital Ordering System for Restaurant using Android", International Journal of Scientific and Research Publications (IJSRP), Volume 3, Issue 4, April 2013, ISSN 2250-3153.
[14] Tanpure, S.S., Shidankar, P.R., Joshi, M.M.,"Automated Food Ordering System with Real-Time Customer Feedback", International Journal of Advanced Research in Computer Science and Software Engineering (IJARCSSE), Volume 3, Issue 2, February 2013, ISSN: 2277 128X
[15] Samsudin, N. A., Ahmad Khalid, S. K., Mohd Kohar, M. F., Senin, Z., & Ihkasan, M. N., “A Customizable Wireless Food Ordering System With Real-time Customer Feedback.”, IEEE Symposium on Wireless Technology and Applications (ISWTA), IEE Publication, 2011, doi:10.1109/Iswta.2011.6089405.
[16] Cristina, F., Dapoto, S., Thomas, P., & Pesado, P., “A Simplified Multiplatform Communication Framework for Mobile Applications.”, 9th International Conference on Computer Engineering & Systems (ICCES), 2014, doi:10.1109/Icces.2014.7030917.
[17] El-Masri, S., & Saddik, B., “An Emergency System To Improve Ambulance Dispatching, Ambulance Diversion and Clinical Handover Communication—A Proposed Model.”, Journal of Medical Systems, Volume 36, Issue 6, pp. 3917-3923, 2012, doi:10.1007/S10916-012-9863-X.
[18] Lombera, I. M., Moser, L. E., Melliar-Smith, P. M., & Chuang, Y., “Decentralized Mobile Search and Retrieval Using SMS and HTTP to Support Social Change.”, 8th International Conference on Wireless and Mobile Computing, Networking, and Communications (WIMOB), IEEE Publication, 2012, doi:10.1109/Wimob.2012.6379066.
[19] Isong, B., Dladlu, N., & Magogodi, T., “Mobile-Based Medical Emergency Ambulance Scheduling System.”, International Journal of Computer Network and Information Security, Volume 8, Issue 11, pp. 14-22, 2016, doi:10.5815/Ijcnis.2016.11.02.
[20] Muhammad, S., Kyung-Goo, D., "Generic Information System Using SMS Gateway", Fourth International Conference on Computer Sciences and Convergence Information Technology, 2009, IEEE Publication, DOI 10.1109/ICCIT.2009.99
[21] Tsafack, P. H., “Wireless Communications and Application To School Attendance: A Case Study.”, International Journal of Wireless Communications and Mobile Computing, Volume 5, Issue 4, pp. 18, 2017, doi:10.11648/J.Wcmc.20170504.11.
[22] Khanna, S. O., “The concept of Web-Based SMS Messaging Server With Mobile., International Journal of Advanced Research In Computer Science and Software Engineering (IJARCSSE), Volume 1, Issue 1, pp. 1-4, 2011, ISSN 2277-128X.
[23] Mishra, A., & Singh, S. P., “A Survey on Mobile Databases and Query Processing In Mobile Databases.”, International Journal of Scientific & Engineering Research (IJSER), Volume 4, Issue 3, pp. 1-4, 2013, ISSN 2229-5518.
[24] Wankhade, N.V., & Deshpande, S.P., “Data Communication In Ad-Hoc Network: The Challenges and Issues.”, International Journal of Advanced Research In Computer and Communication Engineering, Volume 2, Issue 1, January 2013, ISSN (Online): 2278-1021.
[25] Ficek, M., Pop, T., Vláčil, P., Dufková, K., Kencl, L., & Tomek, M., “Performance study of active tracking in a cellular network using a modular signaling platform.”, Proceedings of the 8th international conference on Mobile systems, applications, and services (MobiSys), 2010, doi:10.1145/1814433.1814458.
[26] Li, X., Zhang, X., Chen, K., & Feng, S., "Measurement and analysis of energy consumption on Android smartphones.", 4th IEEE International Conference on Information Science and Technology, 2014, doi:10.1109/icist.2014.6920375
[27] Pu, J., Song, Z., & Tilevich, E., “Understanding the Energy, Performance, and Programming Effort Trade-Offs of Android Persistence Frameworks.”, IEEE 24th International Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS), 2016, doi:10.1109/mascots.2016.42

Nitin V. Wankhade, S.P. Deshpande, "Analysis of Energy Consumption for a Distributed Database System Using Smartphone in Cellular Network," International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.585-589, 2018.

During today’s period about current information technology, great amount about information be produced each next toward allow succeeding information aggregation moreover psychiatry. but, the IT infrastructures to contain element set awake more than previous little decades also ought near currently be used designed for it principle be awfully heterogeneous also complex. Because result, tasks used for scrutinizing information, such because gathering, searching, kinds also giving out information grow to be extremely time-consuming. It creates difficult near recognized revelation, such like Internet about making, which follow the objective about declaration the ease of use about concurrent information on several time also set in an business location. Near decrease the time just before analytics in such location, we near a information eating, combination also giving out proceed consisting about a flexible also configurable information eating pipeline as well as a dynamic semantic information period name ESKAPE. The major objective be, consequently, the convenient right of entry to information also Meta information enclosed inside machines moreover additional systems lying on the superstore. Moreover, it provides the opportunity near onward the together information near a configurable endpoint, such information mere. ESKAPE acts like individual about person`s endpoints enable dynamic semantic information incorporation also processing. Near explain information sets by dynamic semantic models initiated as of the Semantic Web, information analyst be clever near realized procedure also find out these information sets additional competently. ESKAPE skin a three or more - layered information storage structural design consisting about an information layer intended for accumulated included untreated information sets, a layer included user-defined semantic models near illustrated the relative acquaintance required near understand the accumulated information also a top layer bent by a incessantly developing acquaintance graph, unite semantic information since every individual near semantic models. Based lying on it storage system, ESKAPE facilitate the elastic annotation as well as well-organized investigate also giving out about information basis lacking behind the skill about study also query the original raw information by logical gear. The text suggests to a lot of obstacle have to still be alive deal by near gets improved repeated translations. Individual about these obstacles be lexical also syntactic ambiguity. A promising method about conquered it difficulty be by Semantic Web technologies. It article presents the consequences about a systematic evaluation about machine translation come near to rely lying on Semantic Web technologies used for translating texts. Generally, our inspection propose to as Semantic Web technologies be able to improve the excellence about machine translation production used for a variety about problems, the grouping about equally be still inside its infancy. We there discuss our come near also its profit with limits based lying on a real-world industrial, engineering also scientific utilized case.

semantic web information stage, time to analytics; semantic modeling; knowledge graph; applied semantics

[1] M. Popovi´c, Class error rates for evaluation of machine translation output, in: Proceedings of the Seventh Workshop on Statistical Ma-chine Translation, Association for Computational Linguistics, 2012, pp. 71–75.
[2] M. R. Costa-Jussa, M. Farrús, J. B. Mariño, J. A. Fonollosa, Study and comparison of rule-based and statistical Catalan-Spanish machine translation systems, Computing and Informatics 31 (2) (2012) 245– 270.
[3] G. Thurmair, Comparing rule-based and statistical MT output, in: The Workshop Programme, 2004, p. 5.
[4] P. F. Brown, J. Cocke, S. A. D. Pietra, V. J. D. Pietra, F. Jelinek, J. D. Lafferty, R. L. Mercer, P. S. Roossin, A statistical approach to machine transla-tion, Computational linguistics 16 (2) (1990) 79–85.
[5] M. R. Costa-Jussa, J. A. Fonollosa, Latest trends in hybrid machine translation and its applications, Computer Speech & Language 32 (1) (2015) 3–10.
[6] M. R. Costa-jussà, How much hybridization does machine translation Need?, Journal of the Association for Information Science and Tech-nology 66 (10) (2015) 2160–2165.
[7] G. Thurmair, Comparing different architectures of hybrid Machine Translation systems, MT Summit XII: proceedings of the twelfth Ma-chine Translation Summit (2009) 340–347.
[8] P. Koehn, R. Knowles, Six Challenges for Neural Machine Translation, arXiv preprint arXiv:1706.03872.
[9] T. Berners-Lee, J. Hendler, O. Lassila, The Semantic Web, Scientific american 284 (5) (2001) 34–43.
[10] T. Heuss, Lessons learned (and questions raised) from an interdisci-plinary Machine Translation approach, in: Position paper for the W3C Workshop on the Open Data on the Web, 2013, pp. 23–24.
[11] A. Ettinger, S. Gella, M. Labeau, C. O. Alm, M. Carpuat, M. Dredze (Eds.), Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, ACL, Vancouver, Canada, 2017.
[12] K. Erk, N. A. Smith (Eds.), Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, ACL, Berlin, Germany, 2016.
[13] C. Zong, M. Strube (Eds.), Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th Interna-tional Joint Conference on Natural Language Processing, ACL, Beijing, China, 2015.
[14] K. Toutanova, H. Wu (Eds.), Proceedings of the 52nd Annual Meet-ing of the Association for Computational Linguistics, ACL, Baltimore, Maryland, 2014.
[15] T. H. K. U. o. S. Pascale Fung, Technology, U. o. E. Massimo Poesio (Eds.), Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL, Sofia, Bul-garia, 2013.
[16] H. Li, C.-Y. Lin, M. Osborne, G. G. Lee, J. C. Park (Eds.), Proceedings of the 50th Annual Meeting of the Association for Computational Lin-guistics (Volume 1: Long Papers), ACL, Jeju Island, Korea, 2012.
[17] Y. Matsumoto, R. Mihalcea (Eds.), Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL, Portland, Oregon, USA, 2011.
[18] J. Hajiˇc, S. Carberry, S. Clark, J. Nivre (Eds.), Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics, ACL, Uppsala, Sweden, 2010.
[19] K. Knight, A. Nenkova, O. Rambow (Eds.), Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, ACL, San Diego, California, 2016.
[20] R. Mihalcea, J. Y. Chai, A. Sarkar (Eds.), Proceedings of the 2015 Con-ference of the North American Chapter of the Association for Com-putational Linguistics: Human Language Technologies, ACL, Denver, Colorado, USA, 2015.
[21] L. Vanderwende, H. D. III, K. Kirchhoff (Eds.), Proceedings of the 2013 Conference of the North American Chapter of the Association of Com-putational Linguistics: Human Language Technologies, ACL, Atlanta, Georgia, USA, 2013.
[22] E. Fosler-Lussier, E. Riloff, S. Bangalore (Eds.), Proceedings of the 2012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, ACL, Montréal, Canada, 2012.
[23] R. Kaplan, J. Burstein, M. Harper, G. Penn (Eds.), Proceedings of the 2010 Annual Conference of the North American Chapter of the Associ-ation for Computational Linguistics: Human Language Technologies, ACL, Los Angeles, California, 2010.
[24] M. Palmer, R. Hwa, S. Riedel (Eds.), Proceedings of the 2017 Con-ference on Empirical Methods in Natural Language Processing, ACL, Copenhagen, Denmark, 2017.
[25] J. Su, X. Carreras, K. Duh (Eds.), Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing, ACL, Texas, USA, 2016.
[26] L. M. rquez, C. Callison-Burch, J. Su (Eds.), Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing, ACL, Lisbon, Portugal, 2015.
[27] Q. C. R. I. Alessandro Moschitti, G. Bo Pang, U. o. A. Walter Daelemans (Eds.), Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing, ACL, Doha, Qatar, 2014.
[28] D. Yarowsky, T. Baldwin, A. Korhonen, K. Livescu, S. Bethard (Eds.), Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing, ACL, Seattle, Washington, USA, 2013.
[29] J. Tsujii, J. Henderson, M. PaÃEÅÿcaˇ (Eds.), Proceedings of the 2012 Joint Conference on Empirical Methods in Natural Language Process-ing and Computational Natural Language Learning, ACL, Jeju Island, Korea, 2012.
[30] R. Barzilay, M. Johnson (Eds.), Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing, ACL, Edinburgh, Scotland, UK., 2011.
[31] H. Li, L. M‘arquez (Eds.), Proceedings of the 2010 Conference on Em-pirical Methods in Natural Language Processing, ACL, Cambridge, MA, 2010.
[32] N. Calzolari, Y. Matsumoto, R. Prasad (Eds.), Proceedings of COLING, the 26th International Conference on Computational Linguistics, ACL, Osaka, Japan, 2014.
[33] J. Tsujii, J. Hajic (Eds.), Proceedings of COLING, the 25th International Conference on Computational Linguistics, ACL, Dublin, Ireland, 2014.
[34] M. Kay, C. Boitet (Eds.), Proceedings of COLING, the 24th Interna-tional Conference on Computational Linguistics, ACL, Mumbai, India, 2012.
[35] C.-R. Huang, D. Jurafsky (Eds.), Proceedings of COLING, the 23th In-ternational Conference on Computational Linguistics, ACL, Beijing, China, 2010.
[36] R. Barrett, R. Cummings, E. Agichtein, E. Gabrilovich (Eds.), WWW ’17 Proceedings of the 26th International Conference on World Wide Web, ACM, Perth, Australia, 2017.
[37]J. Bourdeau, J. Hendler, R. Nkambou, I. Horrocks, B. Y. Zhao (Eds.),’16 Proceedings of the 25th International Conference on World Wide Web, ACM, Montreal, Canada, 2016
[38]S. Srinivasan, K. Ramamritham, A. Kumar, M. P. Ravindra, E. Bertino, r Kumar (Eds.), WWW ’11: Proceedings of the 20th International Con-ference on World Wide Web, ACM, New York, NY, USA, 2011.
[39]A. Mille, F. L. Gandon, J. Misselis, M. Rabinovich, S. Staab (Eds.), WWW ’12: Proceedings of the 21st International Conference on World Wide Web, ACM, New York, NY, USA, 2012.
[40]D. Schwabe, V. A. F. Almeida, H. Glaser, R. A. Baeza-Yates, S. B. Moon (Eds.), WWW ’13 Companion: Proceedings of the 22Nd International Conference on World Wide Web Companion, International World Wide Web Conferences Steering Committee, Rio de Janeiro, Brazil, 2013.
[41]C. Chung, A. Z. Broder, K. Shim, T. Suel (Eds.), WWW ’14: Proceedings of the 23rd International Conference on World Wide Web, ACM, New York, NY, USA, 2014.
[42]A. Gangemi, S. Leonardi, A. Panconesi (Eds.), WWW ’15 Companion: Proceedings of the 24th International Conference on World Wide Web Companion, ACM, Republic and Canton of Geneva, Switzerland, 2015.
[43]P. Buitelaar, P. Cimiano, E. Montiel-Ponsoda (Eds.), Proceedings of the 1st International Workshop on the Multilingual Semantic Web, CEUR-WS.org, Raleigh, North Carolina, USA, 2010.
[44]L. Aroyo, H. Welty, Chris Alani, J. Taylor, A. Bernstein, L. Kagal, N. Noy, E. Blomqvist (Eds.), The Semantic Web–ISWC 2011, Springer-Verlag, Berlin Heidelberg, Germany, 2011.
[45]P. Cudré-Mauroux, J. Heflin, E. Sirin, T. Tudorache, J. Euzenat, M. Hauswirth, J. X. Parreira, J. Hendler, G. Schreiber, A. Bernstein, E. Blomqvist (Eds.), The Semantic Web–ISWC 2012, Springer-Verlag, Berlin Heidelberg, Germany, 2012.
[46]H. Alani, L. Kagal, A. Fokoue, P. Groth, C. Biemann, J. X. Parreira, L. Aroyo, N. Noy, C. Welty, K. Janowicz (Eds.), The Semantic Web–ISWC 2013, Springer-Verlag, Berlin Heidelberg, Germany, 2013.
[47]P. Mika, T. Tudorache, A. Bernstein, C. Welty, C. A. Knoblock, D. Vran-decic, P. T. Groth, N. F. Noy, K. Janowicz, C. A. Goble (Eds.), The Se-mantic Web - ISWC 2014, Riva del Garda, Italy, October 19-23, 2014. Proceedings, Vol. 8796, Springer, 2014.
[48]M. Arenas, Ó. Corcho, E. Simperl, M. Strohmaier, M. d’Aquin, K. Srini-vas, P. T. Groth, M. Dumontier, J. Heflin, K. Thirunarayan, S. Staab (Eds.), The Semantic Web – ISWC 2015, Springer, Bethlehem, PA, USA, 2015.
[48]P. T. Groth, E. Simperl, A. J. G. Gray, M. Sabou, M. Krötzsch, F. Lécué, F. Flöck, Y. Gil (Eds.), The Semantic Web - ISWC 2016 - 15th Interna-tional Semantic Web Conference, Springer, Kobe, Japan, 2016.
[49]C. d’Amato, M. Fernández, V. A. M. Tamma, F. Lécué, P. Cudré-Mauroux, J. F. Sequeda, C. Lange, J. Heflin (Eds.), The Semantic Web - ISWC 2017 - 16th International Semantic Web Conference, Lecture Notes in Computer Science, Springer, Vienna, Austria, 2017.
[50]E. Blomqvist, D. Maynard, A. Gangemi, R. Hoekstra, P. Hitzler, O. Har-tig (Eds.), The Semantic Web - 14th International Conference, ESWC, Lecture Notes in Computer Science, Portorož, Slovenia, 2017.
[51]H. Sack, E. Blomqvist, M. d’Aquin, C. Ghidini, S. P. Ponzetto, C. Lange (Eds.), The Semantic Web. Latest Advances and New Domains, Vol. 9678 of Lecture Notes in Computer Science, Springer, Berlin Heidel-berg, Germany, 2016.
[52]G. Antoniou, M. Grobelnik, E. Simperl, B. Parsia, D. Plexousakis, P. de Leenheer, J. Z. Pan (Eds.), The Semantic Web: Research and ap-plications, Vol. 6643 of Lecture Notes in Computer Science, Semantic Technology Institute International (STI2), Springer-Verlag, Berlin Hei-delberg, Germany, 2011.
[53]E. Simperl, P. Cimiano, A. Polleres, O. Corcho, V. Presutti (Eds.), The Semantic Web: Research and applications, Vol. 7295 of Lecture Notes in Computer Science, Semantic Technology Institute International (STI2), Springer-Verlag, Berlin Heidelberg, Germany, 2012.
[54]V. Presutti, C. d’Amato, F. Gandon, M. d’Aquin, S. Staab, A. Tordai (Eds.), The Semantic Web: Trends and Challenges, Vol. 8465 of Lecture Notes in Computer Science, Semantic Technology Institute Interna-tional (STI2), Springer International Publishing, Cham, Switzerland, 2014.
[55]F. Gandon, M. Sabou, H. Sack, P., A. Zimmermann (Eds.), The Se-mantic Web. Latest Advances and New Domains, Vol. 9088 of Lecture Notes in Computer Science, Semantic Technology Institute Interna-tional (STI2), Springer International Publishing, Cham, Switzerland, 2015.
[56]L. Aroyo, G. Antoniou, E. Hyvönen, A. ten Teije, H. Stuckenschmidt, A Cabral, T. Tudorache (Eds.), The Semantic Web: Research and Applications, 7th Extended Semantic Web Conference, ESWC 2010, Springer, Heraklion, Crete, Greece, 2010.
[57]A. M. Almasoud, H. S. Al-Khalifa, A proposed semantic machine trans-lation system for translating Arabic text to Arabic sign language, in: Proceedings of the Second Kuwait Conference on e-Services and e-Systems, ACM, 2011, p. 23.
[58]J. P. McCrae, P. Cimiano, Mining translations from the web of open linked data, in: Joint Workshop on NLP&LOD and SWAIE: Semantic Web, Linked Open Data and Information Extraction, 2013, p. 8.
[59]O. Lozynska, M. Davydov, Information technology for Ukrainian Sign Language translation based on ontologies, ECONTECHMOD: an in-ternational quarterly journal on economics of technology and mod-elling processes 4 (2) (2015) 13–18.
[60]K. Simov, P. Osenova, A. Popov, Towards Semantic-based Hybrid Ma-chine Translation between Bulgarian and English, Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies.
[61]T. Santosh Kumar, Word Sense Disambiguation Using Semantic Web for Tamil to English Statistical Machine Translation, IRA-International Journal of Technology & Engineering 5 (2) (2016) 22–31.
[62]I. A. A.-B. G. H. G. Neama Abdulaziz Bin-Dahan, Fadl Mutaher Ba-Alwi, Towards an Arabic-English Machine-Translation Based on Semantic Web, in: SCITN, Vol. 1, 2016, p. 6.
[63]J. Du, A. Way, A. Zydron, Using babelnet to improve OOV coverage in SMT, in: Proceedings of the Tenth International Conference on Lan-guage Resources and Evaluation LREC 2016, Portorož, Slovenia, May 23-28, 2016., 2016, pp. 9–15.
[64]A. Srivastava, F. Sasaki, P. Bourgonje, J. M. Schneider, J. Nehring, G. Rehm, How to Configure Statistical Machine Translation with Linked Open Data Resources, in: Translating and the Computer 38 - Proceedings, AsLing, 2016, pp. 138–148.
[65]C. Shi, S. Liu, S. Ren, S. Feng, M. Li, M. Zhou, X. Sun, H. Wang, Knowledge-Based Semantic Embedding for Machine Translation, in: Proceedings of the 54th Annual Meeting of the Association for Com-putational Linguistics (Volume 1: Long Papers), Vol. 1, 2016, pp. 2245– 2254.
[66]A. Srivastava, G. Rehm, F. Sasaki., Improving Machine Translation through Linked Data, in: Improving Machine Translation through Linked Data., The Prague Bulletin of Mathematical Linguistics - EAMT, 2017, pp. 355–366.
[67]R. Sennrich, B. Haddow, A. Birch, Neural machine translation of rare words with subword units, in: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Pa-pers), Association for Computational Linguistics, 2016, pp. 1715–1725.
[68]M.-T. Luong, C. D. Manning, Achieving open vocabulary neural ma-chine translation with hybrid word-character models, in: Proceedings of the 54th Annual Meeting of the Association for Computational Lin-guistics (Volume 1: Long Papers), Association for Computational Lin-guistics, 2016, pp. 1054–1063.
[69]J. Chung, K. Cho, Y. Bengio, A character-level decoder without explicit segmentation for neural machine translation, in: Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Association for Computational Linguistics, 2016, pp. 1693–1703.
[70]A. Lopez, M. Post, Beyond bitext: Five open problems in machine translation, in: Proceedings of the EMNLP Workshop on Twenty Years of Bitext, 2013, pp. 1–3.
[71]C.-k. Lo, P. Dowling, D. Wu, Improving evaluation and optimization of MT systems against MEANT., in: WMT@ EMNLP, 2015, pp. 434–441.
[72]M. Popovi´c, chrF: character n-gram F-score for automatic MT evalu-ation, in: Proceedings of the Tenth Workshop on Statistical Machine Translation, 2015, pp. 392–395.
[73]M. Popovi´c, chrF deconstructed: beta parameters and n-gram weights, in: Proceedings of the First Conference on Machine Trans-lation: Volume 2, Shared Task Papers, Vol. 2, 2016, pp. 499–504.
[74]A. Zaveri, A. Rula, A. Maurino, R. Pietrobon, J. Lehmann, S. Auer, Qual-ity assessment for linked data: A survey, Semantic Web 7 (1) (2015) 63–93.
[75]J. Bosque-Gil, J. Gracia, G. Aguado-de Cea, E. Montiel-Ponsoda, Ap-plying the OntoLex Model to a Multilingual Terminological Resource, in: The Semantic Web: ESWC 2015 Satellite Events, Springer, 2015, pp. 283–294.
[76]R. Navigli, S. P. Ponzetto, BabelNet: The automatic construction, eval-uation and application of a wide-coverage multilingual semantic net-work, Artificial Intelligence 193 (2012) 217–250.
[77]O. Bojar, R. Chatterjee, C. Federmann, Y. Graham, B. Haddow,Huang, M. Huck, P. Koehn, Q. Liu, V. Logacheva, et al., Findings of the 2017 conference on machine translation (WMT17), in: Proceed-ings of the Second Conference on Machine Translation, 2017, pp. 169– 214.C. Hokamp, Q. Liu, Lexically constrained decoding for sequence gen-eration using grid beam search, in: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Association for Computational Linguistics, 2017, pp. 1535–1546.
[78]RWTH Aachen University. Digital Connected Production. 2017. Available online: https://www.rwth-campus.com/wp-content/uploads/2015/01/Broschuere-Cluster-Productionstechnik-20170508-web.pdf (accessed on 6 September 2018).
[79]Hai, R.; Geisler, S.; Quix, C. Constance: An Intelligent Data Lake System. In Proceedings of the 2016 International Conference on Management of Data, SIGMOD’16, San Francisco, CA, USA, 26 June–1 July 2016; ACM: New York, NY, USA, 2016; pp. 2097–2100.
[80]Pomp, A.; Paulus, A.; Jeschke, S.; Meisen, T. ESKAPE: Platform for Enabling Semantics in the Continuously Evolving Internet of Things. In Proceedings of the 2017 IEEE 11th International Conference on Semantic Computing, ICSC, San Diego, CA, USA, 30 January–1 February 2017; IEEE: Piscataway, NJ, USA, 2017; pp. 262–263.
[81]Pomp, A.; Paulus, A.; Jeschke, S.; Meisen, T. ESKAPE: Information Platform for Enabling Semantic Data Processing. In Proceedings of the 19th International Conference on Enterprise Information. SCITEPRESS— Science and Technology Publications, Porto, Portugal, 26–29 April 2017.
[82]Moghe, P. Time to Analytics: The New Metric for Data Management. In Bloomberg Professional Services2016. Available online: https://www.bloomberg.com/professional/blog/time-to-analytics-the-new-metric-for-data-management/ (accessed on 6 September 2018).
[83]Khan, M.; Wu, X.; Xu, X.; Dou, W. Big data challenges and opportunities in the hype of Industry 4.0. In Proceedings of the 2017 IEEE International Conference on Communications (ICC), Paris, France, 21–25 May 2017; pp. 1–6.
[84]Kirmse, A.; Kraus, V.; Hoffmann, M.; Meisen, T. An Architecture for Efficient Integration and Harmonization of Heterogeneous, Distributed Data Sources Enabling Big Data Analytics. In Proceedings of the 20th International Conference on Enterprise Information Systems, Funchal, Madeira, Portugal, 21–24 March 2018; SCITEPRESS—Science and Technology Publications: Setúbal, Portugal, 2018; Volume 1, pp. 175–182.
[85]Vinoski, S. Advanced Message Queuing Protocol. IEEE Internet Comput. 2006, 10, 87–89. [Cross Ref]
[86]Spring. Available online: https://spring.io (accessed on 6 September 2018).
[87]Technology, I. ISO/IEC 9075 Database languages—SQL; Technical Report; International Organization for Standardization/International Electrotechnical Commission: Geneva, Switzerland, 2008.
[88]Gruber, T. What is an Ontology. WWW Site. 1993. Available online: http://www-ksl.stanford.edu/kst/ whatis-an-ontology.html (accessed on 24 January 2018).
[89]Ehrlinger, L.; Wöß, W. Towards a Definition of Knowledge Graphs. In proceedings of the SEMANTICS 2016, Leipzig, Germany, September 13–14 2016.
[90]The Neo4j Graph Platform. Available online: https://neo4j.com (accessed on 6 September 2018)DB-Engines Ranking. Available online: https://db-engines.com/de/ranking/graph+dbms (accessed on 6 September 2018).
[91]Apache TinkerPop. Available online: https://tinkerpop.apache.org (accessed on 6 September 2018
[92]Paulus, A.; Pomp, A.; Poth, L.; Lipp, J.; Meisen, T. Gathering and Combining Semantic Concepts from Multiple Knowledge Bases. In Proceedings of the 20th International Conference on Enterprise Information, Madeira, Portugal, 21–24 March 2018; SCITEPRESS—Science and Technology Publications: Setúbal, Portugal, 2018.
[93]Measurement, V.S.; GMA. Reference Architecture Model Industrie 4.0 (RAMI4.0). 2016. Available online: https://ec.europa.eu/futurium/en/system/files/ged/a2-schweichhart-reference_architectural_model_industrie_4.0_rami_4.0.pdf (accessed on 6 September 2018).
[94]Group, C.C.E.S.G.C. Smart Grid Reference Architecture. 2011. Available online: http://www.pointview. com/data/files/1/636/2181.pdf (accessed on 6 September 2018).
[95]Society, F. Reference Architecture Model For The Industrial Data Space. 2017. Available online: https://www.fraunhofer.de/content/dam/zv/de/Forschungsfelder/industrial-data-space/Industrial-Data-Space_Reference-Architecture-Model-2017.pdf (accessed on 6 September 2018).
[96]Quix, C.; Hai, R.; Vatov, I. GEMMS: A Generic and Extensible Metadata Management System for Data Lakes. In Proceedings of the CAiSE’16 Forum at the 28th International Conference on Advanced Information Systems Engineering, Ljubljana, Slovenia, 13–17 June 2016.
[97]Microsoft Corporation. Microsoft Data Catalog; Microsoft Corporation: Redmond, WA, USA, 2018.
[98]Informatica Corporation. Enterprise Data Catalog; Informatica Corporation: Redwood City, CA, USA, 2018.
[99]Enterprise Data Lake| Big Data | Data Lake | Informatica US. Available online: https://www.informatica. com/products/big-data/enterprise-data-lake.html (accessed on 6 September 2018).
[100]Knoblock, C.A.; Szekely, P.; Ambite, J.L.; Goel, A.; Gupta, S.; Lerman, K.; Muslea, M.; Taheriyan, M.; Mallick, P. Semi-Automatically Mapping Structured Sources into the Semantic Web. In Proceedings of the Extended Semantic Web Conference, Heraklion, Crete, Greece, 27–31 May 2012.
[101]Cambridge Semantics. Anzo Smart Data Discovery. 2016. Available online: https://www. cambridgesemantics.com (accessed on 6 September 2018).
[102]MAANA. Knowledge Platform. 2018. Available online: https://www.maana.io (accessed on 6 September 2018).
[103]Mantra. Smart Data Platform. 2018. Available online: http://www.altiliagroup.com/platform/mantra-platform (accessed on 6 September 2018).

Sachin Kumar Pandey, Prabhat Pandey, "ROLE OF SEMANTICS WEB TECHNOLOGIES IN REDUCE TIME COMPLEX HETEROGENEOUS INFRASTRUCTURES," International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.590-609, 2018.

This paper deals with two systems have a single unit with two dissimilar components. The system remains operative even if a single component is in operative mode. The failure of one component creates change in life time parameter of other component. Both components can be replaced with a similar component. After replacement of each component, the system is as good as new. In second system Preventive maintenance (i.e. inspection, minor repair etc) is provide to system when system is in the state S0 where both components are normal mode.

Reliability, Availability, Busy Period Analysis, Mean Sojourn Time, Transition Probabilities and Preventive Maintenance

[1]. Goel, L.R., Srivastava P. and Gupta R, “Two unit cold standby system with correlated failures and repairs”. International journal of system science,Vol 23,Issue3, 379-391,1992.
[2]. Goel, L.R. and Gupta Praveen, "Stocastic behaviour of a two unit (dissimilar) hot standby system with three modes", Microelectron relib. vol. 23 No 6 pp 1035-1040, 1983.
[3]. Goel, L.R. and P. Gupta, ”Stochastic analysis of a two-unit parallel system with partial and catastrophic failures and preventive maintenance", Microelectron relib. vol. 24, pp. 881-883, 1984.
[4]. Gupta, R. and G. Varshney, “A two-identical unit parallel system with geometric failure and repair time distributions”,Journal of Cobinatories, Information and System Science, Vol. 32, issue. 2, pp.127-136,1984.
[5]. Goel, L.R., Srivastava P. and Gupta R. “Comparison of reliability characteristics of two system with bivariate exponential lifetime”, International journal of system science, Vol 23, issue 3, pp.135-144,1992.

Praveen Gupta, Pooja Vinodiya, "AVAILABILITY ANALYSIS OF TWO SYSTEM WITH AND WITHOUT PREVENTIVE MAINTENANCE," International Journal of Computer Sciences and Engineering, Vol.6, Issue.10, pp.610-616, 2018.