A Consistent Routing Protocol Based On Graph Theory For Efficient Vehicle To Vehicle Communication
Survey Paper | Journal Paper
Vol.6 , Issue.12 , pp.899-907, Dec-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i12.899907
Abstract
Vehicular Ad-hoc Networks (VANETs) are made exclusive for vehicular communications in which each node makes a bidirectional connectivity with other nodes. VANET has attracted more researchers and has unlocked a track to cultivate few applications like propagation of travel alerts, traffic status, and user defined applications. Each node in VANET has some unique features like dynamic network structure, high mobility, low processing speed and low memory. These features make VANET unique and different from other wireless networks. These features need a special attention, while designing a routing protocol to VANETs. This paper proposes a novel consistent routing protocol called CRP for inter vehicular communications to achieve a consistent and reliable route between the source and destination. Based on link reliability value and graph traversals, a source node predicts a reliable path among the neighboring nodes. The proposed algorithm is designed to work in a stressful urban environment and significantly outperforms than the other existing algorithms.
Key-Words / Index Term
Consistent, graph theory, protocol, reliable, vehicle ad hoc networks (VANETs), wireless, urban
References
[1] Neelesh Gupta and Roopam Gupta, “Routing protocols in Mobile Ad-hoc Networks: An overview”, IEEE International Conference on Emerging Trends in Robotics and Technologies, 2010, pp. 173-177
[2] J. Monteiro, A. Goldman and A. Ferreira, “Performance evaluation of dynamic networks using an evolving graph combinatorial model”, IEEE International Conference on Wireless and Mobile Computing, Networking and Communications, 2006, pp. 173-180.
[3] G. Mao and B. D. O. Anderson, “Graph theoretic models and tools for the analysis of dynamic wireless multi-hop networks”, IEEE Wireless Communications and Networks Conference, 2009, pp. 1-6.
[4] T. Taleb, M. Ochi, A. Jamalipour, N. Kato and Y. Nemoto, “An efficient vehicle-heading based routing protocol for VANET networks”, IEEE Wireless Communications and Networks Conference, 2006, pp. 2199-2204.
[5] K. T. Feng, C. H. Hsu and T. E. Lu, “Velocity-assisted predictive mobility and location-aware routing protocols for mobile ad hoc networks”, IEEE Transactions on Vehicular Technology 57(1) (2008), 448-464
[6] V. Namboodiri and L. Gao, “Prediction-based routing for vehicular ad hoc networks”, IEEE Transactions on Vehicular Technology 56(4) (2007), 2332-2345
[7] Hao Jiang Hao Guo and Lijia Chen, “Reliable and efficient alarm message routing in VANET”, IEEE International Conference on Distributed Computing Systems, 2008, pp. 186-191.
[8] Peiyuan Lai, Xinhong Wang, Ning Lu and Fuqiang Liu, “A Reliable broadcast routing scheme based on mobility prediction for VANET”, IEEE Intelligent Vehicles Symposium, 2009, pp. 1083-1087.
[9] Hassan Aboubakr Omar, Weihua Zhuang and Li Li, VeMAC: “A TDMA based MAC protocol for reliable broadcast in VANETs”, IEEE Transactions on Mobile Computing 12(9), 1724-1736
[10] G. Pallis, D. Katsaros, M. D. Dikaiakos, N. Loulloudes, and L. Tassiulas, “On the structure and evolution of vehicular networks”, IEEE/ACM Annual Symposium on Modeling, Analysis and Simulation of Computer and Telecommunication Systems, 2009, pp. 1-10.
[11] M. Rudack, M. Meincke, K. Jobmann and M. Lott, “On the dynamics of ad hoc networks for inter vehicle communication (IVC)”, International Conference on Wireless Networks, 2002.
[12] I. D. Chakeres and E. M. Belding-Royer, “AODV routing protocol implementation design”, IEEE International Workshop on Distributed Computing Systems, 2004, pp. 698-703.
[13] Kavin Tantipongsakul and Akharin Khunkitti, “Dynamic policy-based routing using firewall rules”, IEEE European Symposium on Computer Modeling and Simulation, 2009, pp. 540-545.
Citation
A.Navis Vigilia, J.Suresh Suseela, "A Consistent Routing Protocol Based On Graph Theory For Efficient Vehicle To Vehicle Communication," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.899-907, 2018.
Controlling Congestion by using Cluster Routing as a Gateway in WSN
Research Paper | Journal Paper
Vol.6 , Issue.12 , pp.908-918, Dec-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i12.908918
Abstract
For extending the lifespan of a wireless sensor network we apply a well-known technique known as cluster. In this technique we select cluster chiefs (CC) which are responsible for routing and regulate liabilities and this technique continuously interchanges the role of dispersed energy ingestion between nodules. As the main objective is saving energy so that throughput, packet delivery ratio strengthens and end-to-end delay may decrease. For this purposes sensory nodules are organised in such a way so that it may sense, calculate, and interconnect warnings in a WSN for prevention of gateway overcrowding. Cluster founded procedure is favoured because usual transportation methods consumes extra energy in sensing and calculating. For the purpose of preserving energy and to escape overcrowding throughout in multiclass traffic flow a novel approach for governing overcrowding on gateway is used. In which nodules are structured dynamically into clusters to offer whole exposure and connectivity. It calculates overcrowding. There is a suitable queue model in each mobile nodule inside the cluster for scheduling prioritized packet for the period of overcrowding without drop or delay. Simulation results shows that throughput, packet delivery ratio strengthens and end-to-end delay are decreases in comparison with other existing phenomenon.
Key-Words / Index Term
Cluster, Routing, gateway, packet delivery, throughput and end-to-end delay
References
[1] J. Rezazadeh, “Mobile wireless sensor networks overview,” International Journal of Computer Communications and Networks, vol. 2, no. 1, pp. 17–22, 2012.
[2] R.Velmani and B. Kaarthick, “An efficient cluster-tree based data collection scheme for large mobile wireless sensor networks,” IEEE Sensors Journal, vol. 15, no. 4, pp. 2377–2390, 2015.
[3] J.Zhao, L.Wang, S. Li, X. Liu, Z. Yuan, and Z. Gao, “A survey of congestion control mechanisms in wireless sensor networks,” in Proceedings of the 6th International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIHMSP ’10), Darmstadt, Germany, pp. 719–722, October 2010.
[4] M. A. Kafi, D. Djenouri, J. Ben-Othman, and N. Badache, “Congestion control protocols in wireless sensor networks: a survey,” IEEE Communications Surveys and Tutorials, vol. 16, no. 3, pp. 1369–1390, 2014.
[5] C.Sergiou, P. Antoniou, and V.Vassiliou, “A comprehensive survey of congestion control protocols in wireless sensor networks,” IEEE Communications Surveys and Tutorials, vol. 16, no. 4, pp. 1839–1859, 2014.
[6] J. Kaur, R. Grewal, and K. S. Saini, “A survey on recent congestion control schemes in wireless sensor network,” in Proceedings of the IEEE International Advance Computing Conference (IACC ’15), IEEE, Banglore, India, pp. 387–392, June 2015.
[7] Al-Fuqaha, A.; Guizani, M.; Mohammadi, M.; Aledhari, M.; Ayyash, M. Internet of Things: A survey on enabling technologies, protocols, and applications. IEEE Commun. SurveyTutor. 2347–2376, 2015, 17,.
[8] Wu, J. “Dominating-set-based routing in ad hoc wireless networks, Handbook of wireless networks and mobile computing”, 425-450, 2002.
[9] Haas, Z. J. and Pearlman, M. R., “The zone routing protocol”, Internet Draft, 1998.
[10] Krishna, P., Vaidya, N. H., Chatterjee, M., and Pradhan, D. K., “A cluster-based approach for routing in dynamic networks”. SIGCOMM. Comput. Commun., Rev. 27, 2, 49-64, 1997.
[11] Amis, A. D. and Prakash, R., “Load-balancing clusters in wireless ad hoc networks”, In Proceedings of the 3rd IEEE Symposium on Application-Specific Systems and Software Engineering Technology (ASSET), IEEE Computer Society, Washington DC, 25 , 2000.
[12] Bechler, M., Hof, H.-J., Kraft, D., Pahlke, F., and Wolf, L., “A cluster based security architecture for ad hoc networks”, In Proc. of 23rd IEEE INFOCOM. Hong Kong, 2393-2403, 2004.
[13]Heinzelman, W. R., Chandrakasan, A., and Balakrishnan, H., “Energy-e_cient communication protocol for wireless microsensor networks”, In Proc. of the 33rd Hawaii Int`l Conf. on System Sciences-Vol.e 8. Hawaii, HI, , Pp. 8020, 2000.
[14]Mhatre, V. and Rosenberg, C., “Design guidelines for wireless sensor networks: Communication, clustering and aggregation”. Ad Hoc Networks Journal 2, 45-63 , 2004.
[15] Qin, Y.; Sheng, Q.Z.; Falkner, N.J.G.; Dustdar, S.; Wang, H.; Vasilakos, A.V., “When things matter: A survey on data-centric internet of things”. J. Netw. Comput. Appl, 64, 137–153, 2016.
[16] Sarkar, A.; Murugan, T.S. “Routing protocols for wireless sensor networks: What the literature says?” Alex. Eng. J., 55, 3173–3183, 2016.
[17] Pantazis, N.A.; Nikolidakis, S.A.; Vergados, D.D. “Energy-efficient routing protocols in wireless sensor networks: A survey”. IEEE Commun. Surv. Tutor., 551–5912013, 15,.
[18] Heinzelman,W.R.; Chandrakasan, A.; Balakrishnan, H. “Energy-efficient communication protocol for wireless micro sensor networks”, In Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, Maui, HI, USA, 7 January; pp. 1–10, 2000.
[19] Malathi, L.; Gnanamurthy, R.K.; Chandrasekaran, K. “Energy efficient data collection through hybrid unequal clustering for wireless sensor networks”. Comput. Electr. Eng., 48, 358–370, 2015.
[20] Gupta, V.; Pandey, R. “An improved energy aware distributed unequal clustering protocol for heterogeneous wireless sensor networks”. Int. J. Eng. Sci. Technol., 19, 1050–1058, 2016.
[21] Mahdieh Sasan,Farhad Faghani, “Using imperialist competitive algorithm in clustering of wireless mesh network,”7th Iranian Conference on Electrical and Electronics Engineering(ICEEE2015),August 2015.
[22] Gerla and J.T.C. Tsai, “Multicluster, mobile, multimedia radio network”, Wireless Networks 1(3), pp.255–265, 1995.
[23] S.Muthuramalingam, R.RajaRam, Kothai Pethaperumal and V.Karthiga Devi, “A Dynamic Clustering Algorithm for MANETs by modifying Weighted Clustering Algorithm with Mobility Prediction” International Journal of Computer and Electrical Engineering, Vol. 2, No. 4, August 2010
[24] S. Basagni, “Distributed Clustering for Ad Hoc Networks”, International Symposium on Parallel Architectures, Algorithms and Networks’, Perth, pp. 310-315, June 1999.
[25] Prerna Malhotra, Ajay Dureja, “A Survey of Weight-Based Clustering Algorithms in MANET”, IOSR Journal of Computer Engineering (IOSR-JCE), Volume 9, Issue 6, PP 34-40, March- April 2013.
[26] Chatterjee M., Das S. K. and Turgut D.:“WCA: A Weighted Clustering Algorithm for Mobile Ad Hoc Networks”. Cluster Computing 5 (2), Kluwer Academic Publishers, Pp. 193–204, 2002.
[27] M. Chatterjee, S.K. Das and D. Turgut, “An on-demand weighted clustering algorithm (WCA) for ad hoc networks,” in: Proceedings of IEEE GLOBECOM 2000, November, San Francisco, pp. 1697–1701, 2000.
[28] S. Balaji and V. Priyadharsini, “A Robust Cluster Head Selection Based On Neighbourhood Contribution and Average Minimum Power for MANETS” ICTACT Journal on Communication Technology, Volume: 06, Issue: 02, June 2015.
[29] A. Garg Et.Al., “ Cluster Formation based Comparison of Genetic Algorithm and Particle swarm Optimization Algorithm in Wireless Sensor Network”, International Journal of Scientific Research in Computer Science and Engineering, Vol.5, Issue.2, pp.14-20, April 2017.
[30] Annlin Jeba S.V.,Gnana King D.R, “Combining Trust with Authentication Information for Routing in Wireless Sensor Networks”, IJSRNSC, Volume-6, Issue-5, October 2018.
Citation
Anamol Chand Jain, Ashendra Kumar Saxena, "Controlling Congestion by using Cluster Routing as a Gateway in WSN," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.908-918, 2018.
Cyber Security through Password Management Strategies
Research Paper | Journal Paper
Vol.6 , Issue.12 , pp.919-923, Dec-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i12.919923
Abstract
Out of various cyber security measures password is one the most crucial measure especially due to exponential growth of Internet and multi-media users after the advent of these services over mobile gadget. This work focusses on password management strategies in context of cyber safety. Different password cracking techniques have been used by hackers in past which had been varying with the changing paradigms related to population growth and its literacy level. Recent password cracking techniques used in 2017 are analyzed. Permutation and combinations used for password strength are discussed with a mathematical model which gives how long will it take to crack a password over different machines. Two case studies for password operations have been discussed by taking Windows and Unix operating systems. For making a password a strong unbreakable password hashing & salting techniques are analyzed.
Key-Words / Index Term
Cyber security, password management, password cracking, hashing, salting
References
1. http://manuals.ucdavis.edu/ppm/310/310-22.htm)
2. http://security.ucdavis.edu/cybersafety.cfm
3. http://security.ucdavis.edu
4. http://security.ucdavis.edu/cybersafetybasics.cfm
Citation
Monika Varshney, Azad Kumar Shrivastava, Alok Aggarwal, Adarsh Kumar, "Cyber Security through Password Management Strategies," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.919-923, 2018.
A Novel Machine Learning Methodology to Increase Sales in Business Services
Research Paper | Journal Paper
Vol.6 , Issue.12 , pp.924-926, Dec-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i12.924926
Abstract
Ticket purchasing in advance is a well- known traditional approach but it entirely depends on the Airline industry to change the fare according to factors whether the travel is during the holidays, the number of free seats in the plane etc. Some of the features are seen, but some of them remained hidden. We are using Indian Domestic Airline Dataset which contains multiple columns so over a period as the data increases (approx. 1 year) we will be able to extract few more hidden features to increase the efficiency and accuracy of the system. The goal is to use machine learning techniques to model the behaviour of flight ticket prices over the time. In other words system will be able to provide a general idea to the clients when to increase or decrease the fares i.e. prediction of Airfare. For that after collecting the dataset the proposed system will extract important features from dataset, cleaning of data and using Regression Machine Learning Algorithms multiple models will be trained and the accuracy of those models will be compared and prediction report will be given to client.
Key-Words / Index Term
Airfare, Feature Extraction, Cleaning data, Regression, Machine Learning, Data Analytics
References
[1] A regression model for predicting optimal purchase timing for airline tickets.
[2] “A Model of Optimal Consumer Search and Price Discrimination in the Airline Industry”. David Li Sunday 15th November, 2015
[3] International Journal of Computer Science and Mobile Computing “big data analysis of airline data set using hive” by p. swathi1, j. kumari2.
[4] International journal of engineering science invention “airfare analysis and prediction using data mining and machine learning” by bhavuk chawla1,ms.chandandeep kaur2.
[5] “Dynamic Pricing in the Airline Industry” By R. Preston McAfee and Vera Te Velde: California Institute of Technology.
[6] Airline Data Set,United States Department of Transportation, Office of the Assistant Secretary for Research and Technology,BureauofTransportationStatistics,http://www.tr anstats.bts.gov/DL_SelectFields.asp?Table_ID=236
[7] William Groves and Maria Gini, ”On Optimizing Airline Ticket Purchase Timing”, University of Minnesota, 2011
[8] ManolisPapadakis, “Predicting Airfare Prices” in Stanford,2013
[9] Yuwen Chen, Jian Cao, Shanshan Feng and Yudong Tan,“An ensemble learning based approach for building airfare forecast service” Big Data (Big Data), 2015 IEEE International Conference, 29 Oct.-1 Nov. 2015.
[10] WEKA Manual for Version 3-6-8, The University of Waikato, 2012
Citation
Tadvi Shabana, Shaikh Afifa, Sayyed Naziya, Khan Mariya, "A Novel Machine Learning Methodology to Increase Sales in Business Services," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.924-926, 2018.
A Comparative Study On Folk Songs and Western Songs in the Contemporary Tamil Cinema
Review Paper | Journal Paper
Vol.6 , Issue.12 , pp.927-929, Dec-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i12.927929
Abstract
The aim of the research work is to compare the folk songs and western songs in the recent Tamil cinema. Also, this research examines memory and lyrical content of songs in recent Tamil films. In this experimental research, an experiment was carried out to find out the stress factors, memory level of words, and content relevance. A comparative study between the folk songs and western songs was conducted among the viewers of the film audience. The members divided into three groups. Those group members were shown different film songs for thirty minutes. The standardized NSAD stress questionnaire used to study the stress level among the members. The folk songs which are being used in this experimental study are, Naatupurapaatu, Kilakku Seemaiyele, and Enthiran. These film songs are categorized into traditional folk songs, (traditional instruments), modernized folk songs, (fusion of classical and modern instruments), and western songs (computerized instruments). These film’s songs show the differences in lyrics, instruments, fusion and modernized music. This experimental research clearly shows the differences in memory of the lyrics and musical beats. This research shows that there is a development exists in the short-term memory among the viewers. The traditional folk songs play a vital role in the communication process and memory. It helps to convey the story during the film and improve the memory in remembering the story and contents of the film. This research shows that the reduced stress level among the film watchers. The presence of folk media enhances the communication process. This research can be extended to other medium of communication.
Key-Words / Index Term
Folk Songs, Western Songs, Tamil Films, Stress, Short-Term Memory, Computerised Instrumental Music
References
[1] Yves Thoraval, “Cinemas of India -18990-2000”, Mac Milan publishers, India, 2000.
[2.] Keval J. Kumar, “Mass communication in India”, Jaico publishers, New Delhi, India 2009.
[3] Fr. Gaston Roberge, “Films for an ecology of mind”, Firma KLM Publishers, 1978
[4] Arora, “Encyclopaedia of Indian Cinema”, Anmol Publications, 2004.
[5]Halliwell, “Film goer’s companion”, Paladin Granada Publications, 1979.
[6] Shanmuga sundaram, “Folklore and Folk songs”, Kavya publication, India, 2006.
[7] Vaanamamali, “Tamilar naatu padalgal”, Amazon kindle, 2018 2017.
[8] Kalai Ilakiya, "Oppari Paadalgal”, Amazon kindle edition 2018.
[9] Kasbekar and Asha, “Pop culture India, media art and lifestyle”, ABC OCLC, 2006
[10] Selvaraj velayutham, “Tamil cinema”, Routledge publication, 2008.
Citation
M. Iyyanar, C. Jebakumar, "A Comparative Study On Folk Songs and Western Songs in the Contemporary Tamil Cinema," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.927-929, 2018.
Ultrasound Medical Image Representation For Systematic Learning
Research Paper | Journal Paper
Vol.6 , Issue.12 , pp.930-933, Dec-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i12.930933
Abstract
Ultrasound screened image is the output screen of ultrasound device. The nature of ultrasound screened image is noisy. These images are produced by sound waves by scanning inside the body. High - Frequency sound waves in the range 1 MHZ to 15 MHZ transmitted from the probe passed through gel to the body and output is produced. Though the technology is improved by detecting the kind of input image format, Ultrasound medical images have a high impact over natural color images since the pixel values range similar. The objective of the article is differentiating computer generated medical images among the collection of images in a dataset. Most of the research approaches have modeled images by its features and detecting it with several images. However, with advance growth in technology, the image quality is better in dimensional effects and thus visually differentiating the images is a significant task. A systematic filtering group of images is the ultimate aim of the work. A number of computer generated medical image in excess of the dataset and the approach starts compares the given digital image to store medical images in the form of key metrics. The values are used to identify medical images. The proposed method has achieved up to 95% of accuracy in identifying ultrasound medical images.
Key-Words / Index Term
Systematic approach, natural image, medical image, classifier, matrix
References
[1] Eric Tokuda, Helio Pedrini , Anderson Rocha, “Computer generated images vs. digital photographs: A synergetic feature and classifier combination approach”, J. Vis. Commun. Image R. 24 (2013) 1276–1292
[2] T.-T. Ng, S.-F. Chang, J. Hsu, L. Xie, M.-P. Tsui, Physics-motivated features for distinguishing photographic images and computer graphics, in: ACM Multimedia (ACMMM), Singapore, 2005, pp. 239–248.
[3] A. da Silva Pinto, H. Pedrini, W.R. Schwartz, A. Rocha, Video-based face spoofing detection through visual rhythm analysis, in: 25th Conference on Graphics, Patterns and Images (SIBGRAPI), Ouro Preto, Brazil, 2012, pp. 221– 228.
[4] T. Pouli, E. Reinhard, Image statistics and their applications in computer graphics, Tech. rep., Eurographics State of the Art Report (STAR), 2010.
[5] E. Dirik, H. Sencar, N. Memon, Source camera identification based on sensor dust characteristics, in: IEEE Signal Processing Applications for Public Security and Forensics (SAFE), USA, 2007, pp. 1–6.
[6] F. Peng, J. Liu, M. Long, Identification of natural images and computer generated graphics based on hybrid features, International Journal of Digital Crime and Forensics (IJDCF) 4 (2013) 1–16.
[7] W. Li, T. Zhang, E. Zheng, X. Ping, Identifying photorealistic computer graphics using second-order difference statistics, in: International Conference on Fuzzy Systems and Knowledge Discovery (FSKD), China, vol. 5, 2010, pp. 2316–2319.
[8] H. Farid, M.J. Bravo, Image forensic analyses that elude the human visual system, in PIE Symposium on Electronic Imaging (SEI), CA, 2010, pp. 754106– 754106–10.
Citation
V. Mary Kiruba Rani, S.S. Dhenakaran, "Ultrasound Medical Image Representation For Systematic Learning," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.930-933, 2018.
Architecture for Integrating Learning Platforms Using Adapter
Research Paper | Journal Paper
Vol.6 , Issue.12 , pp.934-938, Dec-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i12.934938
Abstract
The advantage of the electronic and mobile learning platforms is the dissemination of learning contents with ease. But these platforms operate differently to exchange the learning contents from the server (educator’s site) to the clients (learner’s site). Integrating these learning platforms to operate as a single platform and exchange the contents based on learners’ request could improve the learning efficiency and reduce the operational cost. This work introduces a Web services approach based on client-server model to develop an integrated architecture that join the two learning platforms. In this paper, the architecture of the learning platforms is presented and explained. Furthermore, an adapter in a form of web service is develop as a fuse between the server and the client. Finally, the process of using the web services to unify the two learning architectures using the adapter is demonstrated and explained.
Key-Words / Index Term
Adapter, e-learning, m-learning, Client-server, Web services, XML
References
[1] A. Chaudhary, G. Agrawal, M. Jharia, “A Review on applications of smart class and E-Learning”, Future, Vol.2 Issue.3, pp 234-242, 2014.
[2] J. Joo-Nagata, F.M. Abad, J.G.B. Giner, F.J. García-Peñalvo, “Augmented reality and pedestrian navigation through its implementation in m-learning and e-learning: Evaluation of an educational program in Chile”, Computers & Education, Vol.1, Issue.11, pp.1-17, 2017.
[3] A.Trifonova, M. Ronchetti, “Where is mobile learning going?” Conference on E-Learning in Corporate, Government, Healthcare, and Higher Education, pp. 1794-1801, 2003.
[4] D. Dagger, A. O`Connor, S. Lawless, E. Walsh, V. P. Wade, “Service-oriented e-learning platforms: From monolithic systems to flexible services”. IEEE Internet Computing, pp. Vol.11, Issue.4, 2007.
[5] A. Parkavi, “An e-proctorial system using service-oriented architecture for institutions”, Conference on Emerging Trends in Science, Engineering and Technology, IEEE, pp. 369-372, 2012.
[6] P. Nedungadi, R. Raman, “A new approach to personalization: integrating e-learning and m-learning”, Educational Technology Research and Development, Vol. 60, Issue. 4, pp. 659-678, 2012.
[7] Sharmila, Nisha Jebaseeli, "Enhancing M-Learning System Using Cloud Computing", International Journal of Computer Sciences and Engineering, Vol.4, Issue.1, pp.51-55, 2016.
[8] V. G. Abhaya, Z. Tari, P. Bertok, “Building Web services middleware with predictable execution times”, World Wide Web-Internet and Web Information Systems, Vol.15, Issue.5, pp.685-744, 2012.
[9] M. K. Senagi, O. George, C. Wilson, S. Arthur, K. Jades, “A review of SOAP performance optimization techniques to improve communication in web services in loosely coupled systems”, International Journal of Computer Science Issues, Vol.11, Issue.2, pp.142-153, 2014.
[10] G. Raj, M. Mahajan, D. Singh, "V&V Analysis of Composite Web Service using WS Simulator for Trust Management in WS Lifespan", International Journal of Computer Sciences and Engineering, Vol.6, Issue.6, pp.616-624, 2018.
[11] H. Kreger, “Web services conceptual architecture (WSCA 1.0)”. IBM software group, Vol.5, Issue.1, pp.6-7, 2001.
[12] S.K. Sharma, F.L. Kitchens, “Web services architecture for m-learning”. Electronic Journal of e-Learning, Vol.2, Issue.1, pp.203-216, 2004.
[13] S. S. Al-Gahtani, “Empirical investigation of e-learning acceptance and assimilation: A structural equation model”, Applied Computing and Informatics, Vol.12, Issue.1, pp.27-50, 2016.
[14] M. J. Casany, M. Alier, E. Mayol, J. Piguillem, N. Galanis, F. J. García-Peñalvo, M. A. Conde, “Moodbile: A framework to integrate m-learning applications with the LMS”, Journal of Research and Practice in Information Technology, Vol.44, Isssue.2, pp.123-129, 2012.
[15] Kamaran HamaAli.A.Faraj, "Web-based Teaching in Particular Developing Counties, Experience at “Sulamani University”", International Journal of Computer Sciences and Engineering, Vol.4, Issue.3, pp.1-4, 2016.
[16] Faiz Akram, Rajeev Kumar, "Accuracy of Retrieval Files in Learning Objects using Cloud E-Learning", International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.241-244, 2018.
[17] A.B. Dauda, Zerdoumi Saber, Alotaibi Faiz, M. A. Mustapha, M. T. Abdullah, “Effect of serialized messaging on Web services performance”. IEEE Conference on Computing Networking and Informatics, pp. 1-5, 2017.
[18] Faiz Akram, Rajeev Kumar, "Accuracy of Retrieval Files in Learning Objects using Cloud E-Learning", International Journal of Computer Sciences and Engineering, Vol.6, Issue.8, pp.241-244, 2018.
[19] Tusha garwal, Neeta Sharma, "Efficient Load Balancing Using Restful Web Services in Cloud Computing: A Review", International Journal of Scientific Research in Computer Science and Engineering, Vol.6, Issue.3, pp.67-70, 2018
[20] K. Gottschalk, S. Graham, H. Kreger, J. Snell, “Introduction to web services architecture”, IBM systems Journal, Vol.41, Issue.2, pp.170-177, 2002.
[21] W. Huang, D. Webster, D. Wood, T. Ishaya, “An intelligent semantic e‐learning framework using context‐aware Semantic Web technologies”, British Journal of Educational Technology, Vol.37, Issue.3, pp.351-373, 2006.
[22] A. T. Korucu, A. Alkan, “Differences between m-learning (mobile learning) and e-learning, basic terminology and usage of m-learning in education”. Procedia-Social and Behavioral Sciences, Vol.15, Issue.1 pp.1925-1930, 2001.
[23] L. F. Motiwalla, “Mobile learning: A framework and evaluation”, Computers & education, Vol.49, Issue.3, pp.581-596, 2007.
[24] E. Newcomer, G. Lomow, Understanding SOA with Web services. Addison-Wesley, 2012.
[25] M. Urh, G. Vukovic, E. Jereb, “The model for introduction of gamification into e-learning in higher education”, Procedia-Social and Behavioural Sciences, Vol.197, pp.388-397, 2007.
Citation
Ali B. Dauda, Abubakar A. Idris, Peter Yohanna Mshelia, Abdulaziz.I. Ibrahim, Suleman Umar, "Architecture for Integrating Learning Platforms Using Adapter," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.934-938, 2018.
Overview on Single Image Shadow Removal Using Different Techniques
Review Paper | Journal Paper
Vol.6 , Issue.12 , pp.939-942, Dec-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i12.939942
Abstract
Shadow in the image degrades the quality of the image. So it is necessary to remove the shadow from the image. The detection of shadow and removal of the shadow from the images can be done through many different methods like reintegration method, cubic spline etc. The shadow in the image can be detected through user-assisted method that uses Support Vector Machine (SVM) and Markov Random Field (MRF) methods. Shadow from single image is removed using 3D intensity surface modelling to preserve texture without any loss in image. Using 3D intensity surface modelling method the accuracy can be increased i.e., the exact texture can be recovered in the shadow region after the shadow removal as compared to previous methods.
Key-Words / Index Term
Cartoon Image, Shadow Detection, 3D intensity surface modelling, Shadow Removal
References
[1] G.D Finlayson and S.D. Hordley, “On the removal of shadows from images”, IEEE Trans. Pattern Anal. Mach. Intell., vol. 28, Jan 2006.
[2] E. Arbel and H. Hel-Or, “Shadow removal using intensity surfaces and texture anchor points”, IEEE Trans. Pattern Anal. Mach. Intell., vol. 33, no. 6, pp. 1202–1216, Jun. 2011.
[3] R. Guo, Q. Dai, and D. Hoiem, “Paired regions for shadow detection and removal”, IEEE Trans. Pattern Anal. Mach. Intell., vol. 35, no. 12, pp. 2956–2967, Dec. 2013.
[4] L. Zhang, Q. Zhang, and C. Xiao, “Shadow remover: Image shadow removal based on illumination recovering optimization”, IEEE Trans. Image Process., vol. 24, no. 11, pp. 4623–4636, Nov. 2015.
[5] Salman H. Khan, Mohammed Bennamoun, “Automatic Shadow Detection and Removal from a Single Image”, IEEE Trans. Pattern Anal. Mach. Intell., vol. 38, no. 3, march 2016.
[6] Kai He, Rui Zhen, Jiaxing Yan and YunfengGe “Single-Image Shadow Removal Using 3D Intensity Surface Modeling”, IEEE Transaction on Image Processing, Vol. 26, No. 12, DEC 2017, pp. 6046-6060.
[7] C. Cortes and V. Vapnik, “Support-vector networks”. Machine. Learning., vol. 20, no. 3, pp. 273–297, 1995.
[8] S. Z. Li, “Markov Random Field Modeling in Image Analysis”. New York, NY, USA: Springer-Verlag, 2001.
Citation
Namde Veena, Suhas B. Bhagate, Smita S. Darbastwar, "Overview on Single Image Shadow Removal Using Different Techniques," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.939-942, 2018.
A Study on Optical Parameters of Ge-Se-Te Thin Film for Optical Storage Devices
Research Paper | Journal Paper
Vol.6 , Issue.12 , pp.943-947, Dec-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i12.943947
Abstract
The chalcogenide glasses have recently been investigated intensively because of their promising technological applications in reversible phase change optical recording. Recently, there is a trend of using amorphous materials, rather than carefully prepared crystalline semiconductors, in much needed investigation of such chalcogenide based materials. The present study examines the impact of germanium (Ge) content variation on the optical properties of GexSe50Te50-x (x = 10, 20, 30, 40 at %) based thin films. The optical absorption estimations were performed at room temperature with the change in wavelength. Numerous optical constants were also studied for the concentrated thin films using the optical absorption information in transmission spectra. It was observed that the optical absorption mechanism follow the rule of the allowed direct transition. The theoretical band gap was found to decrease as the Ge content (%) increases from 10 to 40 at %. This outcome was clarified regarding the compound bond approach and hence shows usefulness for optical recording devices.
Key-Words / Index Term
Absorption coefficient, extinction coefficient, theoretical energy band gap, refractive index
References
[1]. T. Phatak, S.D. Sawarkar, “Detection of Faulty Sensor Node within Wireless Sensor Network for improving Network Performance”, Int. J. Sc. Res. in Network Security and Communication, Vol. 5, Issue 3, pp. 117 – 122, 2017.
[2]. R. V. Dharmadhikari, S. S. Turambekar, S. C. Dolli, P K Akulwar, “Cloud Computing: Data Storage Protocols and Security Techniques”, International Journal of Scientific Research in Computer Science and Engineering Vol.6, Issue.2, pp.113-118, 2018.
[3]. M. Ilyas, M. Zulfequar, M. Husain, “Optical properties of a-(Se70Te30)100-x(Se98 Bi2)x Thin Films”, Optical Materials, Vol. 13, Issue 4, pp. 397-404, 2000.
[4]. J. C. Phillips, M. F. Thorpe, “Constraint Theory, Vector Percolation and Glass Formation”, Solid State Comm., Vol. 53, Issue 8, pp. 699-702, 1985.
[5]. M. Saxena and S. Gupta, “Effect of Compositional Dependence on Physical Properties of Ge16Se84-xBix Glass System for Phase Change Optical Recording”, MIT Int. J. Electronics & Communication Engg., Vol. 2, Issue 2, pp. 63, 2012.
[6]. K. M. Al Mokhtar and B.O. Alsobhi, “Structural, Morphology and Some Optical Properties of Chalcogenide Ga80−xSexTe20 (Where x = 10%, 15% and 20%) Glassy Material,” New Journal of Glass and Ceramics, Vol. 7, pp. 91-99, 2017.
[7]. M. Saxena, and S. Gupta, “A Comparison on Physical Properties of Ge–Se–Bi Based Chalcogenide Glasses,” Material Focus, Vol. 6, Issue 4, pp. 474–479, 2017.
[8]. S. Tiwari, A.K. Saxena, D. Saxena, “Optical characterization of Ge0.15Se0.85-xAgx (0
[9]. P. Nermec, M. Frumar ,J. Jedelsky , M. Jelinek, J. Lancok, I. Gregora, “Optical Properties of As36Te42Ge10Si12 Thin Films”, J. Non-Cryst.Solids, Vol.1013, pp. 299–302, 2002.
[10].M. S. Kamboj, G. Kaur, R. Thangaraj “Dark and photoconductivity of amorphous Se–Te–Pb thin films”, Thin Solid Films, Vol. 420, pp. 350 – 353,2002.
[11].J.A. Savage, “Infrared Optical Materials and their Antireflection Coatings”, Adam Hilger, Bristol, 1985.
[12].K. A. Aly, “Optical properties of Ge–Se–Te wedge-shaped films by using only transmission spectra”, J.Non-Cryst.Solids, Vol. 355, pp. 1489-1495, 2009.
[13].A. El-korashy, Bakry A, M.A. Abdel-Rahim and M. Abdel-Sattar, “Annealing effects on some physical properties of Ge5Se25Te70 chalcogenide glasses”, Physica B, Vol. 391, pp. 266-273, 2007.
[14].M. K. Agarwal, M. Saxena and N. Rastogi, “Study Of Influence Of Ge Content On Physical Parameter Of Ge-Se-Te System”, Vol. 8, Issue, 10, pp. 20914-20917,2017,
[15].M. Kubliha, P. Kostka, V. Trnovcová, J. Zavadil, J. Bednarcik, V. Labaš , J. Pedlíková, A. Ch-Dippel, H.-P. Liermann and J. Psota, “Lanthanides in Non-oxide Glasses”, J. Alloys Compd. Vol. 586, pp. 308-313, 2014.
[16].J. Collway, Book on “The theory of energy bands Structure,” Moscow Mir, 1969.
[17].M. Naser Ahmed , Zaliman Sauli, Uda Hashim and Yarub Al-Douri, “Investigation of the absorption coefficient, refractive index, energy band gap, and film thickness for Al0.11Ga0.89N, Al0.03Ga0.97N, and GaN by optical transmission method”, Int. J. Nanoelectronics and Materials, Vol. 2, pp. 189-195, 2009.
[18].A. Shamshad Khan, M. Zulfquar and M. Husain, “Effects of annealing on crystallization process in amorphous Ge5Se95− xTex thin films”, Physica B, Vol. 324, Issue 1-4, pp. 336-343, 2002.
[19].K. Morigaki, “Physics of Amorphous emiconductors”,World Scientific, Singapore, 1999.
[20].S. R. Elliott, “The Physics and Chemistry of Solids”, Wiley, Chichester, 2000.
[21].M. Kastner, “Bonding Bands, Lone-Pair Bands, and Impurity States in Chalcogenide Semiconductors,” Physics Review Lett., Vol. 28, Issue 6, pp. 355-357, 1972.
[22].M. Kastner, “Compositional Trends in the Optical Properties of Amorphous Lone-Pair Semiconductors”, Physics: Review B, Vol. 7, Issue 12, pp. 5237-5252, 1973.
Citation
Manuj Kumar Agarwal, Manish Saxena, Shilpa Gupta, "A Study on Optical Parameters of Ge-Se-Te Thin Film for Optical Storage Devices," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.943-947, 2018.
A Critical Analysis of Predominant Colours in the Movie Pudhupettai
Review Paper | Journal Paper
Vol.6 , Issue.12 , pp.948-951, Dec-2018
CrossRef-DOI: https://doi.org/10.26438/ijcse/v6i12.948951
Abstract
This research papera aimed to anylse the predominant colors like red, blue, and green used in the newly released movie named ‘Pudhupettai’. Also, this research examines the use of red and green colour lightings in the movie Pudhupettai to expose the scene mood and the character’ state of mind with reference to colour psychology in movies. Colour has always been one of the nonverbal languages in communication. Story telling has been followed around the world for ages in various forms including the traditional and new media. Films have paved a massive way among the audience to attain exposure in various platforms. The aim of the directors in general would be making the scene clearer and more realistic to watch and to attract numerous viewers on the stand. Hence, this explores the possibilities of such used emotions using the colours and the pattern of character discourse according to the state of mind. Green again is used in both negative and positive terms to depict the character’s start of mind. Green is unique in the sense that it is the quintessential colour of nature, yet green light can also make a place look eerie or portray illness. Human mood is set upon several ranges and on several platforms. In here, movie serves as a platform to depict a mood or emotion through Red and Green Light. The behavioural understanding of characters is understood through the colour revolving around them. The study about the application for colour psychology is new a very area to explore in the Indian context. This research results can be extended to other films and other forms of communication.
Key-Words / Index Term
Colour Psychology, Story telling, Colour and Communication, Light and Mood, Non-verbal language
References
[1] Kingsway “A Study of Colour Emotion and Colour Preference”, United Kingdom, 2003
[2] Mahnke, “Colour, Environmental and Human Response” Ch.3, 4, Van Nostrand Reinhold, NY, 1996
[3] Discourse Analysis as Ideology Analysis by TEUN A. VAN DIJK
The psychology behind colour by JORY MACKAY
[4] Learning and Applying Colour Styles From Feature Films S. Xue1,2 A. Agarwala2 , J. Dorsey1 , H. Rushmeier1 1Yale University
[5] Foucault, Michel. (1980). Power/knowledge: Selected interviews and other writings 1972-77. Brighton: Harvester Press
[6] Keval J Kumar, “Mass communication in India”, Jaico publications, 2010.
[7] Cheng-Yu wei, “Colour mood analysis of films based on syntactic and psychological models”, ICME, 2004.
[8] N. Dimitrova, et al. “Colour superhistorgrams for video representation”, IEEE ICIP, 1999.
[9]Salway, “Extracting information about emotions in films”, ACM Multimedia, 2003.
[10] Truong, B.T., “Application of computational media aesthetics methodology to extracting Colour semantics in films” ACM multimedia, France, 2002.
Citation
Chandra Mouly V, Nandhini C, "A Critical Analysis of Predominant Colours in the Movie Pudhupettai," International Journal of Computer Sciences and Engineering, Vol.6, Issue.12, pp.948-951, 2018.