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The present scenario describes that there are some untouched areas in the world, which are electrified but from pollution-generating energy sources. Since pollution generating energy sources provide the advantage of continuity of power supply so they are used especially in different islands of the world as compared to individual renewable energy sources. Most of these islands have huge possibilities for renewable power generation. Thus renewable energy based hybrid system is the only option that can replace these pollution generating energy sources. A hybrid system uses multiple energy sources for generating electricity due to which it helps in maintaining the continuity of power supply. However, the most significant thing is that the system should be cost-effectively attractive. In this paper, the optimization study of the hybrid system is done using the HOMER Pro software. This work investigates an optimum combination of grid-connected solar, wind and bio-generator based hybrid system, which can supply electricity in Portugal Island at an affordable price with an acceptable level of reliability. The main objective of the present study is to utilize the available solar, wind and biomass resources at the selected location to meet the demands of residential load, telecom tower load and water pump load in Portugal Island. The result of the study indicates that the system is a cost-effective system as well as it successfully satisfies the load demand by generating a large amount of energy every year.

Hybrid System, Renewable Energy, Global Warming, Solar Energy, Wind Energy, Converter, Grid, Bio-generator

[1] Maya Nayak, “A Review on Hybrid Renewable Energy- Solar, Wind and Hydrogen Energy”, International Journal of Computer Sciences and Engineering, vol.6, Issue.6, pp.594-599, 2018
[2] C. Nandi, S. Bhattacharjee, and S. Reang, “An optimization case study of hybrid energy system based charging station for electric vehicle on Mettur, Tamil Nadu”, International Journal of Advanced Scientific Research and Management, Vol.3, Issue11, pp.225-231, 2018.
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[4] S. Bhattacharjee, S. Chakraborty, B. B. Jena, S. Deb, and R. Das, “An Optimization Study of both On-Grid and Off-Grid Solar-Wind-Biomass Hybrid Power Plant in Nakalawaka, Fiji”. International Journal for Research in Applied Science and Engineering Technology, Vol.6, Issue4, pp.3822-3834, 2018.
[5] Zeinab Abdallah M Elhassan, Muhammad Fauzi Mohd Zain, K. Sopian, and A Abass. “Design and Performance of Photovoltaic Power System as Renewable Energy Source for Residential in Khartoum”, International Journal of Physical Sciences Vol.7, Issue25, pp.4036-4042, 2012.
[6] MA Elhadidy, SM Shaahid. “Decentralized/Standalone Hybrid Wind–Diesel Power Systems to Meet Residential Loads of Hot Coastal Regions”. Energy Conversion and Management, vol.46, Issue.15-16, pp.2501–2513, 2005.
[7] G. Bekele, B. Palm. “Feasibility Study for a Standalone Solar-Wind-Based Hybrid Energy System for Application in Ethiopia”. Applied energy, Vol.87, Issue.2, pp.487–495, 2010.
[8] S. Bhattacharjee, S. Reang, and C. Nandi, “Intelligent Energy Management controller for Hybrid System”. 2018 3rd International Conference for Convergence in Technology (I2CT), The Gateway Hotel, XION Complex, Wakad Road, Pune, India, pp.1-7, Apr 06-08, 2018.
[9] homerenergy.com website. [Online]. Available: https://www.homerenergy.com/company/index.html
[10] homerenergy.com website. [Online]. Available: https://www.homerenergy.com/products/pro/version-history.html
[11] H. Rezzouk, and A. Mellit, “Feasibility study and sensitivity analysis of a stand-alone photovoltaic-diesel-battery hybrid energy system in the north of Algeria,” Renewable and Sustainable Energy Reviews, vol.43, Issue.C, pp.1134-1150, 2015.
[12] L. Olatomiwa, S. Mekhilef, a. S. N. Huda, and O. S. Ohunakin, “Economic evaluation of hybrid energy systems for rural electrification in six geo-political zones of Nigeria,” Renew. Energy, vol.83, pp.435–446, 2015.
[13] M. Nurunnabi and N. K. Roy, “Grid connected hybrid power system design using HOMER,” 3rd International Conference on Advances in Electrical Engineering 17-19 December, 2015, Dhaka, Bangladesh, pp.18-21, IEEE, 2015.

Somudeep Bhattacharjee, Rupan Das, Gagari Deb, Brahma Nand Thakur, "Techno-Economic Analysis of a Grid-Connected Hybrid System in Portugal Island," International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.1-14, 2019.

With a rapid growth of the world of Internet, the social media is eventually growing and is playing a very major role in most of our lives. There are various social networking sites such as Twitter, Google+, Face book which provide a platform for the people to present themselves. Twitter is an efficient micro-blogging tool which has become very popular throughout the world. Nowadays, there is an ongoing trend of posting every thought and emotion of one’s life on these social networking sites. Due to this, emotion analysis has gained popularity in analyzing the thoughts, opinions, feelings, sentiments, etc., of various people. But handling such a huge amount of unstructured data is a tedious task to take up. Feature selection is the process of reducing the number of collected features to a relevant subset of features and is often used to combat the curse of dimensionality. This paper proposes a Relevance Feature Selection for efficient analytics on twitter data. After selecting the features from the tweets, Support Vector Machine (SVM) based classification is applied to analyze the data using Hidden Morkov Model(HMM). The performance of the proposed method has been evaluated through experiments. The entire research was evaluated through publicly available twitter data set with various metrics such as precision, recall, F-measure and Accuracy. By comparing the obtained results with the existing research results, the performance of the proposed work provides better result.

Twitter, Bigdata,Feature Selection ,HMM

[1] Tsapatsoulis, Nicolas, and Constantinos Djouvas (2017), "Feature extraction for tweet classification: Do the humans perform better?.", Semantic and Social Media Adaptation and Personalization (SMAP), 2017 12th International Workshop on. IEEE, 2017.
[2] Packiam, R. Merlin, and V. Sinthu Janita Prakash. "An empirical study on text analytics in big data." Computational Intelligence and Computing Research (ICCIC), 2015 IEEE International Conference on. IEEE, 2015.
[3] Anna Stavrianou, Caroline Brun, Tomi Silander, and Claude Roux, "NLP-based feature extraction for automated tweet classification". In Proceedings of DMNLP, Workshop at ECML/PKDD .7,2014.
[4] Prusa JD, Khoshgoftaar TM, Dittman DJ , "Impact of feature selection techniques for tweet sentiment classification", In: Proceedings of the 28th International FLAIRS Conference; 2015. p. 299–304,2015.
[5] harmendra Sharma, Suresh Jain, “Evaluation of Stemming and Stop Word Techniques on Text Classification Problem”, International Journal of Scientific Research in Computer Science and Engineering Science and Engineering, Vol: 3, No. :2, 2015.
[6] Jundong Li, Kewei Cheng, Suhang Wang, Fred Morstatter, Robert Trevino, Jiliang Tang, and Huan Liu. “Feature selection: A data perspective”. arXiv preprint arXiv:1601.07996, 2016
[7] Riham Mansour, Mohamed Farouk Abdel Hady,Eman Hosam, HaniAmr, and Ahmed Ashour , "Feature selection for twitter sentiment analysis: An experimental study", In International Conference on Intelligent Text Processing and Computational Linguistics, pages 92–103. Springer,2015.
[8] O. Soufan, D. Kleftogiannis, P.Kalnis, V. B. Bajic, and D.Gupta , "DWFS: a wrapper feature selection tool based on a parallel genetic algorithm", PLoSONE, vol. 10, no. 2, Article ID e0117988, 2015.
[9] S. Wang, W. Pedrycz, Q. Zhu, and W. Zhu, "Subspace learning for unsupervised feature selection via matrix factorization," Pattern Recognit. , vol. 48, no. 1, pp. 10–19, 2015.
[10] H.B.Nguyen, B.Xue, I.Liu, P. Andreae, and M. Zhang , "Gaussian transformation based representation in particle swarm optimisation for feature selection" in Applications of Evolutionary Computation (LNCS 9028). Cham, Switzerland: Springer, pp. 541–553,2015.
[11] E. Hancer, B. Xue, D. Karaboga, and M. Zhang , "A binary ABC algorithm based on advanced similarity scheme for feature selection" Appl. Soft Comput., vol. 36, pp. 334–348, Nov. 2015
[12] Manek,A.S., Shenoy,P.D., Mohan,M.C., and Venugopal,K. , "Aspect term extraction for sentiment analysis in large movie reviews using Gini index feature selection method and SVM classifier", World Wide Web, 20 (2), 135–154,2017 .
[13] Agarwal B., Mittal N., "Machine Learning Approach for Sentiment Analysis", In: Prominent Feature Extraction for Sentiment Analysis. Socio-Affective Computing. Springer, Cham, 2016.
[14] Akshi Kumar, Shikhar Garg, Shobhit Verma and Siddhant Kumar(2019), "Sentiment Analysis Using Cuckoo Search for Optimized Feature Selection on Kaggle Tweets", International Journal of Information Retrieval Research (IJIRR) ,vol. 9, no. 1, 2019.
[15] A. Tommasel, D. Godoy “A Social-aware online short-text feature selection technique for social media “ Inf. Fusion, 40 ( pp. 1-17. 2018.
[16] Sinthu, R. Merlin Packiam, Dr V., and Janita Prakash. "Multilevel Sparse Dimension Selection Approach For Improved Big Data Processing Using Taxonomy." International Journal Of Innovation In Engineering Research And Management, ISSN 2348-4918, ISO 2000-9001 certified, E 4, no. 4 ,2017.
[17] Packiam, R. Merlin, and V. Sinthu Janita Prakash. "A Novel Integrated Framework Based on Modular Optimization for Efficient Analytics on Twitter Big Data." In Information and Communication Technology for Intelligent Systems, pp. 213-224. Springer, Singapore, 2019.
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R. Merlin Packiam, V. Sinthu Janita Prakash, "Relevance Based Feature Selection Algorithm For Efficient Preprocessing of Textual Data Using HMM," International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.15-21, 2019.

Gender identification of an individual is a fundamental task, as many social interactions are gender-based. The fingerprint is the most precise and reliable biometric trait for gender identification. It plays a vital role to link the suspect in a crime scene or to find an unknown person. The gender identification can significantly enhance the performance of authentication systems and reduces the search space and speed up the matching rate. Several previous studies have investigated the gender identification from fingerprints but lack’s in conventional results. In this work, the authors propose gender identification based on fingerprints by using the fusion of two well-known local descriptors, such as LBP and LPQ. The proposed algorithm is evaluated on state of two datasets i.e. publically available SDUMLA-HMT fingerprint dataset and other is self-created fingerprint dataset, which embraces fingerprints of 348 individuals (10 samples from each individual) of which 183 are males and 165 are female volunteers and obtained the best classification rate of 97% accuracy using SVM classifier. The results are competitive and appreciable as compared to earlier methods.

Gender Identification, Biometrics, Fingerprint, LBP, LPQ, KNN, and SVM

[1] Anil K. Jain, Karthik Nandakumar, Xiaoguang Lu, and Unsang park, “Integrating Faces, Fingerprints, and Soft Biometric Traits for user Recognition.” Proceedings of Biometric Authentication Workshop, LNCS 3087, pp.259-269, PRAGUE,-May 2004.
[2] Suchita T, Akhile Anjikar and Hemant Thakur, ”Fingerprint-Based Gender Identification using DWT Transformation”, International Conference on Computing Communication Control and Automation,(ICCCA-2015), Pune , India,2015.
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[6] A. S. Falohun, O.D.Fenwa, F. A. Alala,” A Fingerprint-based Age and Gender Detector System using Fingerprint Pattern Analysis ”, International Journal of Computer Applications (0975 – 8887) Vol.4, pp.136 –140, February 2016.
[7] M vadivel , T Arulkumaran “Gender Identification from FingerPrint Images Based on a Supervised Learning Approach”, PASJ International Journal of Computer Science (IIJCS), Volume 2, Issue 7, July 2014.
[8] Pragya Bharti, Dr. C. S. Lamba,” DWT-Neural Network based Gender Classification”, International Journal of Digital Application & Contemporary research, Volume 2, Issue 8, March 2014.
[9] Vikas Humbe, S S Gornale , K V Kale, R. R. Manza’, “Mathematical Morphology Approach for Genuine Fingerprint Feature Extraction”, International Journal of Computer Science and Security, ISSN: 1985-1533 Vol. 1 Issue 2, pp 53-59-2007.
[10] Manish Verma and Suneeta Agarwal.’’ Fingerprint Based Male - Female Classification. ’’ in Proceedings of the international workshop on computational intelligence in security for information systems (CISIS’08), Genoa, Italy, pp.251 – 255, 2008.
[11] A. Badawi, M. Mahfouz, R. Tadross, and R. Jantz “Fingerprint-based gender classification” The International Conference on Image Processing, Computer Vision, and Pattern Recognition,(CVPR-2006) in June 2006.
[12] Naveen Kumar Jain, Sunil Sharma, Anurag Paliwal., A Real-Time Approach To Determine The Gender Using Fingerprints”, IJAIR ISSN: 2278-7844, pp:229-233, 2012.
[13] Rijo Jackson Tom, T. Arulkumaran, “Fingerprint-Based Gender Classification Using 2D Discrete Wavelet Transforms and Principal Component Analysis”, International Journal of Engineering Trends and Technology, Vo. 4, Issue 2,2013
[14] Pallavi Chand, Shubhendu Kumar Sarangi, “A Novel Method for Gender Classification Using DWT and SVD Techniques”, International Journal of Computer Technology & Applications, Vol 4 (3),pp.445-449, May-June 2013.
[15] Ritu Kaur and Susmita Ghosh Mazumdar, Mr. Devanand Bhonsle, “A Study On Various Methods of Gender Identification Based on Fingerprints”, International Journal of Emerging Technology and Advanced Engineering, ISSN 2250-2459, Vol.2, Issue 4, April 2012.
[16] S. S. Gornale, Mallikarjun Hangarge, Rajmohan Pardeshi, Kruthi R“ Haralick Feature Descriptors for Gender Classification Using Fingerprints: A Machine Learning Approach “,IJARCSSE Vol. 5,Issue 9,September-2015.
[17] S. S. Gornale, Geetha D, Kruthi R “Analysis of a fingerprint image for gender classification using spatial and frequency-domain analysis”, American International Journal of Research in Science, Technology, Engineering and Mathematics”,ISSN 2328-3491, ISSN:2328-3580, ISSN (CD-ROM): 2328-3629, pp.46-50, 2013.
[18] S. S. Gornale, “Fingerprint-Based Gender Classification for Biometric Security: A State-Of-The-Art Technique”,International Journal of Research in Science, Technology, Engineering & Mathematics ISSN 2328-3491, pp. 39-49 Dec-2014.
[19] V. Ojansivu and J. Heikkilä, “Blur insensitive texture classification using local phase quantization,” in Image and Signal Processing. Heidelberg: Springer, 2008, pp. 236-243.
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[21] Shivanand Gornale, Basavana M, and Kruti R, “Fingerprint-Based Gender Classification Using Local Binary Pattern”, International Journal of Computational Intelligence and Research Vol.13 Issue 2, pp. 261-272,2017.
[22] Prabha,S Jitendra, and P Rajmohan,”Fingerprint-based Automatic Human Gender Identification”, International Journal of Computer Applications ISSN 0975 – 8887, Vol-170 Issue-7, July 2017 .
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Kruthi R, Abhijit Patil, Shivanand Gornale, "Fusion of Local Binary Pattern and Local Phase Quantization features set for Gender Classification using Fingerprints," International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.22-29, 2019.

Cloud platforms are increasingly being used for hosting a broad diversity of services from traditional ecommerce applications to interactive web-based IDEs. However, we have noticed that the proliferation of offers by service providers promotes several challenges. Developers have to consider migrating services from one cloud to another and manage distributed applications spanning multiple clouds while specific service is not available in single cloud. In this paper, we have introduced a new methodology of web services scheduling in multi-cloud environment based on the request of preferred user services in different time slots of the day. A comparison has been made on the performance and cost of single and multi-cloud environments to show how multi-cloud is more efficient than single cloud and also to conclude that web service scheduling in multi-cloud environment is more efficient than single cloud during service migration.

Scheduling, Multi Cloud System, Web Services, Service Scheduling, Service Composition, Web Service Scheduling

[1] FeiTeng, “Resource allocation and scheduling models for cloud computing”,EcoleCentrale Paris, 2011.
[2] Han Zhao, Xiaolin Li, “AuctionNet: Market oriented task scheduling in heterogeneous distributedenvironments”, Research Gate,IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd forum, IEEE, pp.1-5, 2010.
[3] Lee, Young Choon, Wang, Chen, Zomaya, Albert Y. and Zhou, Bing Bing, “Profit-Driven Service Request Scheduling in Clouds”, 10th IEEE/ACM International Conference on Cluster,Cloud and Grid Computing, IEEE, pp. 1-13, 2010.
[4] Emeakaroha, V.C., Brandic, I., Maurer, M.andBreskovic, I., “SLA-Aware Application Deployment and Resource Allocation in Clouds”,IEEE 31st Annual Computer Software and Applications Conference Workshops, IEEE, pp.1-7, 2011.
[5] Ahuja, R., De, A., Gabrani, G., “SLA Based Scheduler for Cloud for Storage & Computational Services”, International Conference on Computational Science and its Applications.IEEE , 2011.
[6] Daniel, D., Lovesum, S.P.J. “A novel approach for scheduling service request in cloud with trust monitor”, International Conference on Signal Processing, IEEE , 2011.
[7] Boloor, K., Chirkova, R., Salo, T., Viniotis, Y., "Heuristic-Based Request Scheduling Subject to a Percentile Response Time SLA in a Distributed Cloud",GLOBECOM , IEEE, 2010.
[8] Luqun Li, "An Optimistic Differentiated Service Job Scheduling System for Cloud Computing Service Users and Providers",2009 Third International Conference on Multimedia and Ubiquitous Engineering, IEEE, pp.1-5, 2009.
[9] Qi Zhang, Quanyan Zhu, Boutaba, R., “Dynamic Resource Allocation for Spot Markets in Cloud Computing Environments”, 2011 Fourth IEEE International Conference on Utility and Cloud Computing, IEEE, pp.1-6, 2012.
[10] Thomas A. Henzinger, Anmol V. Singh, Vasu Singh, Thomas Wies, Damien Zufferey, “Static Schedling in Clouds”, Austria,IST Austria, pp.1-6.
[11] Zhongyuan Lee, Ying Wang, Wen Zhou, “A dynamic priority scheduling algorithm on service request scheduling in cloud computing”,Proceedings of 2011 International Conference on Electronic and Mechanical Engineering and Information Technology, IEEE, 2011.
[12] L. Zeng, B. Benatallah, M. Dumas, J. Kalagnanam, and Q.Sheng, “Quality driven web services composition,” In Proc. of the 12th WWW Conference, pp.411 –421, 2003.
[13] Lifeng Ai, Maolin Tang, Colin Fidge., “Resource allocation and scheduling of multiple composite web services in cloud computing using cooperative coevolution genetic algorithm”, Neurak Information Processing, Lectures Notes in Computer Science, Volume 7063, pp.258 –267, 2011.
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P. Sen, D.Sarddar, S.K. Sinha, R. Pandit, "Web Service Scheduling in Multi-Cloud Environment," International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.30-38, 2019.

For transmitting real time information (over the standalone network), video wireless sensor networks are becoming more popular. As the video data is inherently very large in size, it requires more memory, greater processing speed and larger bandwidth for its transmission. In this paper, zigbee is used for video transmission, as it economical and consumes less power. The video is initially compressed using discrete cosine transform (DCT) based compression technique and then transmitted over zigbee using two different baud rates. The same video is transmitted number of times at two different baud rates, which helps in comparing and getting more accurate values of various parameters for video transmission at two different baud rates. Comparison is carried out by calculating average values of image parameters, transmission time, reception time, frame loss and frame delay independently. Finally reliable and efficient baud rate is found out for video data transmission over zigbee network.

Wireless Sensor Network (WSN); Video Wireless Sensor network (VWSN); Zigbee; baud rate, Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE), Structural Similarity Index (SSI), Compression Ratio (CR)

[1] Maung, S., Shiraje, S., Islam, A., Hossain, M.M., Nahar, S. and Arif, Md.F.H. (2018) “Optimization of ZigBee Network Parameters for the Improvement of Quality of Service”. Journal of Computer and Communications, vol.6, pp1-14. https://doi.org/10.4236/jcc.2018.66001
[2] Ievgeniia Kuzminykh et.al; “Testing of Communication Range in ZigBee Technology”, CADSM 2017, 21-25 February, 2017, Polyana-Svalyava (Zakarpattya), UKRAINE; 2017 IEEE; pp:133-136
[3] Dan Tao et.al;, “Data acquisition and transmission reliability for wireless image sensor networks”, Tenth International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IEEE 2014, pp: 819 – 822.
[4] Chia-Hsin Cheng et.al;, “Implementation of multi-channel technology in ZigBee wireless sensor networks”, Computers and Electrical Engineering Journal, Elsevier. 2015; pp: 1-11.
[5] M. Masurkar et.al, “LIFETIME MAXIMIZATION IN WIRELESS SENSOR NETWORK USING CROSS LAYER DESIGN: A DESIGN REVIEW” First International Conference on Emerging Trends in Engineering and Technology, (ICETET) 2008 IEEE pp: 234-237.
[6] P D Joshi, G M Asutkar, “Lifetime Enhancement of WSN by Heterogeneous Power Distributions to Nodes: A Design Approach”, International Journal of Applied Information Systems (IJAIS) – ISSN : 2249-0868
[7] Xiaoxia Ren; Zhigang Yang, “Research on the key issue in video sensor network” Computer Science and Information Technology (ICCSIT), 2010 3rd IEEE International Conference, 2010, Volume: 7 pp 423 – 426
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[9] Congduc Pham et.al, “Performances of Multi-Hops Image Transmissions on IEEE 802.15.4 Wireless Sensor Networks for Surveillance Applications” 9th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) 2013 IEEE pp: 477-484
[10] Dhote K., Asutkar G.M. (2016), “Enhancement in the Performance of Routing Protocols for Wireless Communication Using Clustering, Encryption, and Cryptography”. In: Dash S., Bhaskar M., Panigrahi B., Das S. (eds) Artificial Intelligence and Evolutionary Computations in Engineering Systems. Advances in Intelligent Systems and Computing, vol 394. Springer, New Delhi
[11] D. P. Mishra et.al, “An Application of Wireless Sensor Network in Intelligent Transportation System”,6th International Conference on Emerging Trends in Engineering and Technology, 2013, IEEE Computer Society pp:90-91.
[12] Chahat Aggarwal and B. B. Gupta, “A Survey of Civilian Applications of WSN and Security Protocols” International Journal of Scientific Research in Computer Science and Engineering Vol.6, Issue.3, pp.56-66 , June (2018)
[13] Sharma, Shamneesh, Dinesh Kumar, and Keshav Kishore. "Wireless Sensor Networks-A review on topologies and node Architecture." International Journal of Computer Sciences and Engineering 1, no. 2 (2013): 19-25.

Mrunal Khedkar, G.M. Asutkar, "Comparison between Baud Rates for Serial Video Data Transmission over Zigbee in Wireless Sensor Network," International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.39-45, 2019.

Transportation Problem plays an important role in our economy and managerial decision- making. The main objective of transportation problem solving method is to obtain an optimal solution. An initial basic feasible solution is the first step to obtain an optimal solution for the transportation problems. Among the existing methods, Vogel’s Approximation Method gives an initial basic feasible solution near to the optimal solution, but it is very expansive in term of the execution of time. This paper introduces a new method, Reduction Method using minimum supply & demand method, to find an initial basic feasible solution of Transportation Problem. This method is easy to apply and fast compared to Vogel’s Approximation Method. It gives better initial basic feasible solution compared to all existing prominent methods. The method is also illustrated with numerical examples.

Linear Programming, Assignment, Transportation problem, initial basic feasible solution, Reduction method using Supply & Demand method

[1] KAPOOR V. K., “Operations Research ( Quantitative Techniques for management )”, Sultan Chand & Sons Publisher, India ,pp. 5.3-5.97, 2008.
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[3] N. M. Morade, “New Method to find initial basic feasible solution of Transportation Problem using MSDM” , International Journal of Computer Sciences and Engineering, Vol.5, issue.12, pp.223-226, 2017.
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N.M. Morade , "Reduction Method Using Minimum Supply And Demand Method to Find an Initial Basic Feasible Solution of Transportation Problem," International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.46-50, 2019.

Text categorization is an active research area in information retrieval and machine learning. The major issue regarding preprocessing the document for this categorization is redundancy. The redundant documents slow down the learning steps of classification and also affect its efficiency and scalability. To resolve this issue it is preferred, first identify the duplicates and then perform the classification. This paper proposes to apply the Similarity Measure for duplicate detection and Random forest for classification. The results are evaluated using ‘20 newsgroups’ data sets with generated duplicate documents. Accuracy and time parameters show better results in the proposed method than that in the existing text categorization model.

Duplicate-detection, text categorization, information retrieval, similarity measure

[1] D. Xue, F. Li, “Research of Text Categorization Model based on Random Forests,” IEEE International Conference on Computational Intelligence & Communication Technology, pp. 173-176, 2015.
[2] G. Gao, S. Guan, “Text Categorization Based on Improved Rocchio Algorithm,” International Conference on Systems and Informatics, pp. 2247-2250, 2012.
[3] Thamarai, S.S., Kartikeyan, P., Vincent, A., Abinaya, V., Neeraja, G. and Deepika, R. 2016.Text Categorization using Rocchio Algorithm and Random Forest Algorithm. In the IEEE 2016 Eighth International Conference on Advanced Computing (ICoAC) held at Chennai, India, pp. 7-12, 2017.
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[5] M.L. Zhang, Z.H. Zhou, “A lazy learning approach to mullti-label learning,” National Laboratory for Novel Software Technology, Vol. 40, Issue. 7, pp. 2038-2048, 2007.
[6] S. Seshasai,” Efficient near duplicate document detection for specialized corpora“, Massachusetts Institute of Technology, 2008.
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[10] E.P. Sim,” Classification & Detection of Near Duplicate Web Pages using Five Stage Algorithm”,Online International Conference on Green Engineering and Technologies (IC-GET), 2015.

S. Singh, K. Jain, "Document Categorization for Probabilistic Redundant Documents," International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.51-55, 2019.

This paper aim at analyzing use of electronic resources by the Faculty members of Social Science departments, Annamalai University. From this study the investigator is able to find out that most the Faculty members prepare Wikipedia as the first source of information for guiding the students. This study reveals that the majority of the Faculty members are using e-resources more than one hour.

E-resources, Social Sciences, Annamalai University

[1]. Latha, J K and Nagarajan, M (2010), “Information Communication Technology Infrastructure Development in Special Libraries in Tamilnadu: A Study” Indian Journal of Information Science and Services, Vol.4 (1) pp 61.65.
[2]. Rani, T and Nagarajan, M (2013), “Use of ICT based Resources among Faculty members and PG students of Arts and Science Colleges in Cuddalore District, Tamilnadu: A Study”, Indian Journals of Information Sources and Services, Vol.3 (1) pp40-43.
[3]. Tamar Sadeh E, Mark Ellingsen(2005); Electronic Resource Management Systems: The Need and the Realization; New Library World; Vol.106(5/6)
[4]. Preeti Mahajan(2006), ”Internet use by researchers at Punjab University, Chandigarh”, Library Philosophy and Practice,Vol: 8( 2) Pp:15-19.

M. Nagarajan , "Use of Electronic Information Sources by the Faculty Members of Social Science Departments in Annamalai University: A Study," International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.56-58, 2019.

Success of any company or product depends on customer’s satisfaction. If customers do not satisfied with the services or product provided by company, then certainly company needs to improve it. Opinion mining (OM) can help in doing this. OM is the process of computationally identifying and categorizing opinions from piece of text and determines whether the writer’s attitude towards a particular topic or the product is positive, negative or neutral. This paper proposed a training model using sentdex data set to train the OM algorithm. This algorithm is based on supervised machine learning model to calculate OM of given text. Entire system is developed to calculate opinion from tweeters feeds. This system is working on real time data. Proposed system is designed for open field. One can take opinion of many field like political issue, product, company, person etc. this paper also presented the comparison of proposed results with well known python textblob API. textblob is used to perform many texts based operations. Sentiment analysis (OM) is one of them. In many OM systems this API is used.

Opinion Mining, Machine Learning, NLP, textblob, sentdex, NLTK

[1] Farhan Hassan Khan, Saba Bashir and Usman Qamar, “TOM: Twitter opinion mining framework using hybrid classification scheme”, Decision Support Systems, Vol. 57, pp. 245–257 , 2014.
[2] Marıa del Pilar Salas, Rafael Valencia, Antonio Ruiz and Ricardo Colomo, “Feature-based opinion mining in financial news: An ontology-driven approach”, Journal of Information Science, Vol. 34, Issue 4, pp. 458-479, 2016.
[3] Nuno Oliveira, Paulo Cortez and Nelson Areal, “The impact of microblogging data for stock market prediction: Using Twitter to predict returns, volatility, trading volume and survey sentiment indices”, Expert Systems With Applications, Vol. 73, pp. 125–144, 2017.
[4] Shiliang Sun, Chen Luo, Junyu Chen, “A Review of Natural Language Processing Techniques for Opinion Mining Systems”, Information Fusion, Vol. 36, pp. 10-25, 2017.
[5] R. Piryani, D. Madhavi and V.K. Singh, “Analytical mapping of opinion mining and sentiment analysis research during 2000–2015”, Information Processing and Management, Vol. 53, pp. 122-150, 2017.
[6] Mangi Kang, Jaelim Ahn and Kichun Lee, “Opinion mining using ensemble text hidden Markov models for text classiÞcation”, Expert Systems With Applications ,Vol. 94, pp. 218-227, 2018.
[7] M. Rathan, Vishwanath R. Hulipalled, K.R. Venugopal and L.M. Patnaik, “Consumer Insight Mining: Aspect Based Twitter Opinion Mining of Mobile Phone Reviews”, Applied Soft Computing Journal, Vol. 68, pp. 765-773, 2018.
[8] Betoul Duondar,Diyar Akay, Fatih Emre Boran and Suat Ozdemir, “Fuzzy Quantification and Opinion Mining on Qualitative Data using Feature Reduction”, International Journal of Intelligent System, Vol. 33, Issue 9, pp. 1840–1857, 2017.
[9] Soujanya Poria, Erik Cambria and Alexander Gelbukh, “Aspect Extraction for Opinion Mining with a Deep Convolutional Neural Network”, Knowledge-Based Systems, Vol. 108, pp. 42-49, 2016.
[10] Bird, Steven, Edward Loper and Ewan Klein, “Natural Language Processing with Python”, O’Reilly Media Inc., 2009.
[11] Shrija Madhu, “An approach to analyze suicidal tendency in blogs and tweets using Sentiment Analysis”, International Journal of Scientific Research in Computer Science and Engineering, Vol.6, Issue.4, pp.34-36, 2018.
[12] Ketan Sarvakar, Urvashi K Kuchara, “Sentiment Analysis of movie reviews: A new feature-based sentiment classification”, Vol.6, Issue.3, pp. 8-12 , 2018

Urmita Sharma, Dhanraj Verma, "Implementation of a Generalized, Real Time and Natural Language Processing Based Opinion Mining System for Twitter," International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.59-66, 2019.

NLP is a vast field and thesaurus is its integral part. Thesaurus is a software tool which is inbuilt in few word processors that provides synonyms for selected words. A thesaurus is used on a computer while writing an e-mail, letter, or paper to find an alternative meaning for words. A thesaurus is a reference work that lists the synonyms and sometimes antonyms of words. Synonyms are words with similar meanings, and antonyms are words with opposite meanings. The research work in the paper elaborates the development of thesaurus in relevance with the Hindi language. The paper focuses on the development of framework which may assist the people finding it difficult to write and dealing with Hindi.

Thesaurus, Hindi language, Synonyms, Antonyms

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Mandeep Kaur, "Development of Thesaurus for Hindi," International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.67-72, 2019.