Review Paper on Leaf Disease Detection using Digital Image Processing with SVM Classifier
Review Paper | Journal Paper
Vol.7 , Issue.6 , pp.1110-1113, Jun-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i6.11101113
Abstract
Recognizable proof of the mango leaf malady is the primary objective to avert the misfortunes and nature of horticultural item. In India mango natural product harvest is broadly developed. So infection discovery and grouping of mango leaf is basic for maintainable farming. It`s impractical to rancher, to screen consistently the mango illness physically. It requires the over the top handling time, colossal measure of work, and some aptitude in the mango leaf ailments. To recognize and characterize the mango ailment we need quick programmed procedure so we use SVM classifier strategy. This paper shows predominantly five phases, viz picture securing, pre-handling, division, include extraction and SVM order. This paper is proposed to profit in the location and order of mango leaf infection utilizing bolster vector machine (SVM) classifier.
Key-Words / Index Term
Image obtaining, pre-handling, Image division, SVM classifier
References
[1]Sachin D. Khirade, A.B Patil, “Plant Disease Detection Using Image Processing”, International Conference on Computing Communication Control and Automation”, 2015.
[2] Prof. Sanjay B. Dhaygude, Mr.Nitin P.Kumbhar, “Agricultural plant Leaf Disease Detection Using Image Processing”, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering Vol. 2, Issue 1, January 2013.
[3] Amandeep Singh ,Maninder Lal Singh, “Automated Color Prediction of Paddy Crop Leaf using Image Processing”, International Conference on Technological Innovations in ICT for Agriculture and Rural Development (TIAR 2015), 2015.
[4] M.Malathi, K.Aruli , S.Mohamed Nizar, A.Sagaya Selvaraj, “A Survey on Plant Leaf Disease Detection Using Image Processing Techniques”,International Research Journal of Engineering and Technology (IRJET),Volume: 02 Issue: 09, Dec 2015.
[5] Malvika Ranjan, Manasi Rajiv Weginwar, NehaJoshi, Prof.A.B. Ingole, “detection and classification of leaf disease using artificial neural network”, International Journal of Technical Research and Applications, 2015.
[6] Y.Sanjana, AshwathSivasamy, SriJayanth, “Plant Disease Detection Using Image Processing Techniques”,International Journal of Innovative Research in Science, Engineering and Technology, Vol. 4, Special Issue 6, May 2015.
[7] Bhumika S.Prajapati, Vipul K.Dabhi Harshadkumar, B.Prajapati, “A Survey on Detection and Classification of Cotton Leaf Diseases”, International Conference on Electrical, Electronics, and Optimization Techniques (ICEEOT) – 2016.
[8] P.Revathi, M.Hemalatha, “Advance Computing Enrichment Evaluation of Cotton Leaf Spot Disease Detection U sing Image Edge detection”, ICCCNT`12.
[9] Mr. Pramod S. landge, Sushil A. Patil, Dhanashree S. Khot, “Automatic Detection and Classification of Plant Disease through Image Processing”, International Journal of Advanced Research in Computer Science and Software Engineering, Volume 3, Issue 7, 2013.
[10] Heeb Al Bashish, Malik Braik, and Sulieman Bani-Ahmad, “A Framework for Detection and Classification of Plant Leaf and Stem Diseases”, IEEE 2010.
Citation
Sagar Gaikwad, Sagar Shinde, "Review Paper on Leaf Disease Detection using Digital Image Processing with SVM Classifier," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.1110-1113, 2019.
Review on Health Care Monitoring System
Review Paper | Journal Paper
Vol.7 , Issue.6 , pp.1114-1117, Jun-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i6.11141117
Abstract
The healthcare monitoring systems have drawn considerable attentions of the researchers. The prime goal was to develop a reliable patient monitoring system so that the healthcare professionals can monitor their patients, who are either hospitalized or executing their normal daily life activities. In this work we present a mobile device based wireless healthcare monitoring system that can provide real time online information about physiological conditions of a patient. Our proposed system is designed to measure and monitor important physiological data of a patient in order to accurately describe the status of her/his health and fitness. By using the information contained in the text or e-mail message the healthcare professional can provide necessary medical advising. The system mainly consists of sensors (i.e. temperature sensor, gyroscope, accelerometer), location locker (i.e. GPS), microcontroller (i.e. Node MCU), and software (i.e. Embedded C). The patients temperature, no. of steps he/she walks, location, displayed, and stored by our system. Along with above mention parameters, android app will display timing and amount for drinking water and alert about same.
Key-Words / Index Term
Healthcare, Io, Temprature,heart rate
References
[1] International Journal of Computer Networks Communications (IJCNC) Vol.7, No.3, May 2015 DOI : 10.5121/ijcnc.2015.7302 13 REAL TIME WIRELESS HEALTH MONITORING APPLICATION USING MOBILE DEVICES Amna Abdullah, Asma Ismael, Aisha Rashid, Ali Abou-ElNour, and Mohammed Tarique
[2] International Journal of Computer Applications (0975 8887) Volume 62 No.6, January 2013 1 Wireless Patient Health Monitoring System Manisha Shelar R.G.P.V. University Department of E T C S.S.S.I.S.T. Sehore Jaykaran Singh R.G.P.V. University Department of E T C S.S.S.I.S.T. Sehore Mukesh Tiwari
[3] A Real-Time Health Monitoring System for Remote Cardiac Patients Using Smartphone and Wearable Sensors Priyanka Kakria,1 N. K. Tripathi,1 and Peerapong Kitipawang, Hindawi Publishing Corporation International Journal of Telemedicine and Applications Volume 2015, Article ID 373474, 11 pages
[4] Real-Time Cloud-Based Health Tracking and Monitoring System in Designed Boundary for Cardiology Patients Aamir Shahzad , 1 Yang Sun Lee,2 Malrey Lee,3 Young-Gab Kim , 1 and Naixue Xiong Hindawi Journal of Sensors Volume 2018, Article ID 3202787, 15 pages
[5] IOT BASED HEALTH CARE MONITORING AND TRACKING SYSTEM USING GPS AND GSM TECHNOLOGIES SARA FATIMA1 , AMENA SAYEED INTERNATIONAL JOURNAL OF PROFESSIONAL ENGINEERING STUDIES Volume VIII /Issue 5 / JUN 2017
[6] Wearable Sensors for Remote Health Monitoring Sumit Majumder 1 , Tapas Mondal 2 and M. Jamal Deen Sensors 2017, 17, 130; doi:10.3390/s17010130 www.mdpi.com/journal/sensors [7] IoT Based Wearable Health Monitoring System B.Srirama Chowdary1 , K.Durgaganga Rao 2
[8] Development of a Heartbeat and Temperature Measuring System for Remote Health Nursing for the Aged in Developing Country Blessed Olalekan Oyebola1 , Ogunlewe Adeyinka Oluremi2 , Toluwani Victor Odueso Science Journal of Circuits, Systems and Signal Processing 2018; 7(1): 34-42
[9] Aashay Gondaliaa , Dhruv Dixitb , Shubham Parasharc , Vijayanand Raghavad , Animesh Senguptae Communicating Author: Vergin Raja Sarobin IoT-based Healthcare Monitoring System for War Soldiers using Machine Learning International Conference on Robotics and Smart Manufacturing (RoSMa2018)
[10] Mr. Ajinkya A. Bandegiri Dr. Pradip C. Bhaskar Real-Time Health Monitoring System: A Review International Journal of Trend in Scientific Research and Development (IJTSRD) ISSN: 2456-6470 Volume 2 — Issue 1 — Nov-Dec 2017
Citation
Rahul Pawar, M.M. Sardeshmukh, Sagar Shinde, "Review on Health Care Monitoring System," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.1114-1117, 2019.
Low Energy Adaptive Clustering Hierarchy (LEACH) Protocol for Extending the Lifetime of the Wireless Sensor Network
Research Paper | Journal Paper
Vol.7 , Issue.6 , pp.1118-1124, Jun-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i6.11181124
Abstract
Wireless Sensor Network (WSN) is demanding and very appealing technology useful for different applications. WSNs consist of wirelessly interconnected sensor nodes (SNs) which can assemble, distribute and process information in a range of application regions. Power utilization in WSN is a key difficulty. Some of the usages comprise landslide detection, glacial monitoring, wildlife tracking, health care, military applications, environmental monitoring and a large number of applications to robotics and projects on “internet of things”. Our paper will illustrate the primary characteristics of WSN followed by power consumption protocol LEACH. Here we have carried out the comparative performance analysis of power consumption protocol LEACH at different energy levels and multi-path factors.
Key-Words / Index Term
WSN, LEACH, Cluster Head, Hierarchical routing protocols, Network Life time
References
[1]. Y-h Zhu, W W-d, J Pan, T Y-p, “An energy-efficient data gathering algorithm to prolong lifetime of wireless sensor networks”, Comput. Commun. , Vol. 3, Issue.3, pp.639–647, 2010.
[2]. S Gao, H Zhang, SK Das, “Efficient data collection in wireless sensor networks with path-constrained mobile sinks”, IEEE Trans. Mob. Comput., Vol. 10, pp. 592–608 , 2011.
[3]. MH Anisi, AH Abdullah, SA Razak, “Energy-efficient data collection in wireless sensor networks”, Wirel. Sens. Netw., Vol. 3, pp.329-333 ,2011
[4]. C.S Raghavendra, K.M. Sivalingam, T.Z Eds, “Wireless Sensor Networks”, Kluwen Academic, NewYork, 2004.
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[6]. R. Kaur, D.sharma, N.Kaur, “Comparative analysis of LEACH and its descendant protocols in wireless sensor network”, Int. j. P2P Netw.TrendsTechnolol., Vol.3, Issue. 1,2013.
[7]. Yi Liu, Shan zhong, Licai you, Bu LV, Lin Du,” A Low Energy Uneven Cluster protocol Design for wireless sensor network”, Int. j. Communications, Network and System Sciences, Vol. 5, pp. 86-89, 2012.
[8]. M. Malik, Y.Singh, A. Arora, “ Analysis of Leach Protocol in Wireless Sensor Networks”,Internatrional Journal of advanced Research in Computer Science and Software Engineering, Vol. 3, Issue. 2, 2013.
[9]. L.Y. Ming, V.W.S.Wong, “An energy efficient multi-path routing protocol for wireless micro sensor networks”,research articles. Int. J. Commun. Syst., Vol. 20, Issue. 7, pp.747-767, 2007.
[10]. W. Heinzelman, A. Chandrakasan, H. Balakrishnan, “An Application- specific protocol architecture for wireless microsensor networks”, IEEE Transactions on Wireless Communication, Vol. 1, Issue. 4, pp. 660-670, 2002.
[11]. J. Peng,W. Chengdong, C. Fei, “ A Low-Energy Adaptive Clustering Routing Protocol of Wireless Sensor Networks”, in Proceeding of 7th IEEE on Wireless Networking and Mobile Computing 2011.
[12]. G. Smaragdakis, I.Matta, A. Bestavros,” SEP: A Stable Election Protocol for clustered heterogeneous wireless sensor networks”,in: Second International Workshop on Sensor and Actor Network Protocols and Applications(SANPA 2004),2004.
[13]. L. Qing, Q. Zhu, M. Wang,” Design of a distributed energy efficient clustering algorithm for heterogeneous wireless sensor networks”, Computer Communications, Volume 29, Issue .12, pp. 2230-2237, 2006.
[14]. A. Manjeshwar , D. P. Agarwal,” TEEN: A Routing Protocol for Enhanced Efficiency in Wireless Sensor Networks”, IEEE Computer Society Washington, DC,USA, 2001.
[15]. C. Siva Ram Murthy and B.S Manoj ,” Adhoc Wireless Networks Architectures and Protocols”, Prentice Hall Communication Engineering and Emerging Technologies Series, 2004.
[16]. S. Bandyopadhyay , E.J Coyle,”An energy efficient hierarchical clustering algorithm for wireless sensor networks”, in Proceedings of INFOCOM 2003, April 2003.
[17]. J. Xu,N. Jin, X. Lou,T. Peng,Q.Zhou,Y.Chen“Improvement of LEACH protocol for WSN” 2012 IEEE.
[18]. R.A.Roseline, .P.Sumathi, Energy Efficient Routing Protocol and Algorithms for Wireless Sensor Networks-A Survey. Global Journal of Computer Science and Technology, Vol.11, December 2011.
[19]. W.C.Luan, B.S. Zhu,,C. P.ei. ,”An Improved Routing Algorithm on LEACH by Combining Node Degree and Residual Energy of WSNs. – Internet of Things”, Communications in Computer and Information Science, Vol. 312, pp. 104-109, 2012.
[20]. H.Taneja,P. Bhalla. An Improved Version of LEACH: Three Levels Hierarchical Clustering LEACH Protocol (TLHCLP) for Homogeneous WSN. – International Journal of Advanced Research in Computer and Communication Engineering, Vol. 2, Issue. 9, pp. 3610-3615, 2013.
[21]. J. Wang, X. Yang, T. Ma, M. Wu, and J.-U. Kim, “An energy efficient competitive clustering algorithm for wireless sensor networks using mobile sink,” International Journal of Grid and Distributed Computing, Vol. 5, Issue. 4, pp. 79–92, 2012.
[22]. C. FU, Z. JIANG, W. WEI, A.WEI, “An Energy Balanced Algorithm of LEACH Protocol in WSN” IJCSI International Journal of Computer Science Issues, Vol. 10, Issue. 1, No 1, January 2013.
[23]. S. Choudhary, S. Sharma, “A Survey of LEACH Protocol and its Modified Versions in Wireless Sensor Network” International Journal of Advanced Research in Computer Science and Software Engineering, Vol. 4, Issue. 1, January 2014.
[24]. P.Sivakumar, M.Radhika, “Performance Analysis of LEACH-GA over LEACH and LEACH-C in WSN”, 6th International Conference on Smart Computing and Communications, ICSCC 2017, 7-8 December 2017, Kurukshetra, India, Procedia Computer Science Vol.125, pp.248–256, 2018.
[25]. M.B.Yassein, S.Aljawarneh, R.K. Al-huthaifi, , Enhancements of LEACH protocol: Security and open issues, 2017 International Conference on Engineering and Technology(ICET),IEEE,10.1109/ICEngTechnol.2017.8308164,2018.
Citation
R.Ghosh, S. Mohanty, S. Pramanik, "Low Energy Adaptive Clustering Hierarchy (LEACH) Protocol for Extending the Lifetime of the Wireless Sensor Network," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.1118-1124, 2019.
Search Engine Optimization for a Website (3PDigital.Co)
Survey Paper | Journal Paper
Vol.7 , Issue.6 , pp.1125-1128, Jun-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i6.11251128
Abstract
In today’s world internet is growing fast day by day. data is very huge and complex. To sort this amount of data over large database search engine plays a very important role. Google is the basic search engine through which we can optimize the website. With the help of search engine, we can actively gather the visitors to our site. Search engine is the most common part of our today’s life. Because of this reason, search engines play “a prominent position in the online world”; because of this people can find any information that they want from the internet very easily. Search Engine is the most valuable asset for the company to grow their market in the current business. It increases the market value This research paper provides to improve the ranking of a website(3pdigital.co)
Key-Words / Index Term
Search engine optimization(SEO), On page and Off page optimization. Page Rank, Metadata, Organic Search
References
[1] http://www.brightworkweb.com/images/s earch_engine_marketin g.jpg
[2] http://searchengineland.com/21- essential-SEO-tips-techniques11580
[3] https://neilpatel.com/
[4] http://www.webconfs.com/importance-of- sitemaps-article17.php
[5] Khalil ur Rehman and Muhammad Naeem Ahmed Khan: The Foremost Guidelines for Achieving Higher Ranking in Search Results through Search Engine Optimization
[6] K.Chiranjeevi , K.Archana and J.Pradeep Kumar, "Design and Implementation of a Cost Effective Ranking Adaptation Algorithm", ISROSET-International Journal of Scientific Research in Computer Science and Engineering, Najam Nazar: Exploring SEO Techniques for Web 2.0Websites, Department of Computer Science and Engineering Chalmers University of Technology Göteborg, Sweden, June 2009, Publikationen registrerades 2009-08-25. Den ändrades senast 2013-04-04, Examiner: C. Carlsson.
[7] Vinit Kumar Gunjan, Pooja, Monika and Amit: Search engine optimization with Google, IJCSI International Journal of Computer Science Issues, Vol. 9, Issue 1, No 3, January 2012, ISSN (Online): 1694-0814.
[8] P. T. Chung, S. H. Chung and C. K. Hui, “A web server design using search engine optimization techniques for web intelligence for small organizations”, LISAT IEEE Long Island University Brooklyn NY USA, (2012)
[9] https://moz.com/blog/best-seo-blogs-top- 10-sources-to-stay-uptodate
[10] https://www.wordstream.com/blog/ws/2015/04/30/seo-basics
[11] https://searchengineland.com/library/search- engine-optimization/seo-blogs-feeds
Citation
Abhijeet Joshi, Suhasini Vijaykumar, "Search Engine Optimization for a Website (3PDigital.Co)," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.1125-1128, 2019.
Improving the Security of Secret Questions using Smartphone Sensor and App Data
Research Paper | Journal Paper
Vol.7 , Issue.6 , pp.1129-1134, Jun-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i6.11291134
Abstract
Security and privacy is an important topic in the field of sensitive data communication. Secondary authentication methods like secret questions are widely used as a form of authentication which can be easily guessed. Moreover, users may forget his/her answers, and even if a user remembers the answer, they can forget how it was written. The recent prevalence of smartphone has provided a rich source of personal data concerning the user’s knowledge of its short-term history. Such a feature has made it possible for people to spend more and more time on these devices. Furthermore, the popularity of social media applications and single sign-on increases day after day, users with their information do not always take as many precautions as they need. We present a “Secret-Question based Authentication System” having a set of secret questions based on user’s short-term smartphone usage. We have developed prototype of android application, and have evaluated the security of the secret questions. We also present a multifactor authentication that creates more and more walls to prevent people from seeing your information. It allows the verification of user’s identity for a login or other transaction-based on more than one method of authentication from independent categories of credentials.
Key-Words / Index Term
Android, Secret Questions, Security, Authentication
References
[1] P. Zhao et al., "Understanding Smartphone Sensor and App Data for Enhancing the Security of Secret Questions," in IEEE Transactions on Mobile Computing, vol. 16, no. 2, pp. 552-565, 1 Feb. 2017.
[2] A. Bissada and A. Olmsted, "Mobile multi-factor authentication," 2017 12th International Conference for Internet Technology and Secured Transactions (ICITST), Cambridge, 2017, pp. 210-211. [3] Karthick S, Dr. SumitraBinu "Android Security Issues and Solutions," IEEE 2017
[4] S. Yadav, A. Apurva, P. Ranakoti, S. Tomer and N. R. Roy, "Android vulnerabilities and security," 2017 International Conference on Computing and Communication Technologies for Smart Nation (IC3TSN), Gurgaon, 2017, pp. 204-208.
[5] F. Aloul, S. Zahidi and W. El-Hajj, "Two factor authentication using mobile phones," 2009 IEEE/ACS International Conference on Computer Systems and Applications, Rabat, 2009, pp. 641-644.
[6] S. Schechter, A. B. Brush, and S. Egelman, “It’s no secret measuring the security and reliability of authentication via secret questions,” in S & P., IEEE, 2009, pp. 375–390.
[7] A. Babic, H. Xiong, D. Yao, and L. Iftode, “Building robust authentication systems with activity-based personal questions,” in SafeConfig. New York, NY, USA: ACM, 2009, pp. 19–24.
[8] M. Zviran and W. J. Haga, "User authentication by cognitive passwords: an empirical assessment," Proceedings of the 5th Jerusalem Conference on Information Technology, 1990. `Next Decade in Information Technology`, Jerusalem, Israel, 1990, pp. 137-144.
[9] J. Podd, J. Bunnell, and R. Henderson, “Cost-effective computer security: Cognitive and associative passwords,” in Computer-Human Interaction, 1996. Proceedings, Sixth Australian Conference on. IEEE, 1996, pp. 304–305.
[10] X. Jiang and J. Ling, "Simple and effective one-time password authentication scheme," 2013 2nd International Symposium on Instrumentation and Measurement, Sensor Network and Automation (IMSNA), Toronto, ON, 2013, pp. 529-531.
[11] P. B. Tiwari and S. R. Joshi, "Single sign-on with one time password," 2009 First Asian Himalayas International Conference on Internet, Kathmandu, 2009, pp. 1-4.
[12] K. Renaud, D. Kennes, J. van Niekerk and J. Maguire, "SNIPPET: Genuine knowledge-based authentication," 2013 Information Security for South Africa, Johannesburg, 2013, pp. 1-8.
[13] J. Bonneau, "The Science of Guessing: Analyzing an Anonymized Corpus of 70 Million Passwords," 2012 IEEE Symposium on Security and Privacy, San Francisco, CA, 2012, pp. 538-552.
[14] Joseph Bonneau, Elie Bursztein, Ilan Caron, Rob Jackson, and Mike Williamson. 2015. Secrets, Lies, and Account Recovery: Lessons from the Use of Personal Knowledge Questions at Google, pp. 141-150.
Citation
Prabin Joshi, Naidila Sadashiv, Bivek Gyawali, Sudeep Simkhada, "Improving the Security of Secret Questions using Smartphone Sensor and App Data," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.1129-1134, 2019.
Review paper on Privacy Preserving Data Analysis
Review Paper | Journal Paper
Vol.7 , Issue.6 , pp.1135-1138, Jun-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i6.11351138
Abstract
Privacy-Preserving Data Mining (PPDM), as an important branch of data mining and an interesting topic in privacy preservation, has gained special attention in recent years. In addition to extracting useful information and revealing patterns from large amounts of data, PPDM also protects private and sensitive data from disclosure without the permission of data owners or providers. In recent years, privacy preserving data mining has been studied extensively, because of the wide proliferation of sensitive information on the internet. The major area of concern is that non-sensitive data even may deliver sensitive information, including personal information, facts or patterns. K-anonymity is a property that models the protection of released data against possible re-identification of the respondents to which the data refers. Anonymization approach makes the data owners anonymous but vulnerable to attacks like linking attacks. The paper presents various techniques which are used to perform PPDM technique and also tabulates their advantages and disadvantages.
Key-Words / Index Term
Anonymization, Privacy Preserving Data Mining, k-anonymity, Randomization
References
[1] Agrawal R., Srikant R. Privacy-Preserving Data Mining. ACM SIGMOD Conference, 2000.
[2] K David Raju, L Vijay Kumar, K Anthony Rahul Showry, B LhoitKrishn ,(2018) ." techniques of providing data integrity in cloud computing".
[3] Aggarwal C. C., Yu P. S. On Variable Constraints in Privacy Preserving Data Mining. ACM SIAM Data Mining Conference, 2005.
[4] Alexandre Evfimievski, Tyrone Grandison, “Privacy Preserving Data Mining”.
[5] Evfimievski, A., R. Srikant, R. Agrawal and J. Gehrke. “Privacy preserving mining of association rules”. Proceedings of the 8th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, July 23-25, ACM Press, Edmonton, AB., Canada, pp. 1-12,2002.
[6] Surbhi Sharma and Deepak Shukla, “Efficient multi-party privacy preserving data mining for vertically partitioned data”,Inventive Computation Technologies (ICICT), 10.1109/INVENTIVE.2016.7824852, © 2017 IEEE.
[7] Y. Lindell and B. Pinkas, “Privacy preserving data mining”, J. Cryptology, 15(3):177–206, 2002.
[8] L. Sweeney, "k-ANONYMITY: A MODEL FOR PROTECTING PRIVACY," Int. J.Uncertain., vol. 10, no. 5, pp. 557- 570, 2002.
[9] G. T. Duncan and S. Mukherjee. Optimal disclosure limitation strategy in statistical databases: Deterring tracker attacks through additive noise. Journal of the American Statistical Association, 95(451):720–729, 2000.
[10] T. Evans, L. Zayatz, and J. Slanta. Using noise for disclosure limitation of establishment tabular data. Journal of Official Statistics, 14(4):537–551, 1998.
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[12] S. E. Fienberg, U. E. Makov, and R. J. Steele. Disclosure limitation using perturbation and related methods for categorical data. Journal of Official Statistics, 14(4):485–502, 1998.
[13] Mahima Joshi, Yudhveer Singh Moudgil,"secure Cloud Storage."
[14] Yogendra Kumar Jain, Vinod Kumar Yadav& Geetika S. Panday, An Efficient Association Rule Hiding Algorithm for Privacy Preserving Data Mining, International Journal on Computer Science and Engineering (IJCSE), Vol. 3 No. 7 July 2011.
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[16] J. Jesu Vedha Nayahi and V. Kavitha,” Privacy and utility preserving data clustering for data anonymization and distribution on Hadoop”,Future Generation Computer Systems, 0167-739X/© 2016 Elsevier.
[17] R. Rajeswari and Mrs R. Kavitha ,”Privacy Preserving Mechanism for anonymizing data streams in data mining”, International conference on current research in Engineering Science and Technology(ICCREST-2016).
Citation
Yuvraj Singh, Pankaj Pratap Singh, Anirudh Tripathi, Amit kishor, "Review paper on Privacy Preserving Data Analysis," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.1135-1138, 2019.
Intelligent Opinion Polarity and Analysis in Discovering Product Related Customer Reviews: A Survey
Survey Paper | Journal Paper
Vol.7 , Issue.6 , pp.1139-1143, Jun-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i6.11391143
Abstract
Due to rapid advancements in Social media consumer interactions are increasing at faster rate. Twitter has now a days become a social media platform for industries, individuals, educational institutes and organizations who have a strong educational, political, industrial, social, banking or economic concern in maintaining and enhancing their social status and reputation. Posts are generally composed of poorly structured, incomplete, and noisy sentences, irregular expressions, non-dictionary terms, and ill-formed words. The problem is some customers given rating contrast with their comments. The other reviewers must read many comments and comprehend the comments that are different from the rating. Opinion Mining is the computational detailed investigation of people’s attitudes, opinions, and emotions concerning of issues, events, topics or individuals. This paper represents the survey of customer feelings related to online product with their opinion polarity and analysis.
Key-Words / Index Term
Sentiment analysis, Opinion mining, Machine learning, Social Media, Support Vector Machine, Sentiment Polarity
References
[1] Wararat Songpan, The Analysis and Prediction of Customer Review Rating Using Opinion Mining, IEEE SERA 2017, pp. 71-77
[2] Arno Scharl, David Herring, Walter Rafelsberger, Alexander Hubmann-Haidvogel, Ruslan Kamolov, Daniel Fischl, Michael Föls, and Albert Weichselbraun, “Semantic Systems and Visual Tools to Support Environmental Communication”, IEEE SYSTEMS JOURNAL, VOL. 11, NO. 2, JUNE 2017, pp. 762-772
[3] ANH-DUNG VO , QUANG-PHUOC NGUYEN , AND CHEOL-YOUNG OCK, Opinion-Aspect Relations in Cognizing Customer Feelings via Reviews, IEEE 2018, Vol-6, pp.5414-5426
[4] Kamps, J., Marx, M., Mokken, R. J.Using WordNet to Measure Semantic Orientation of Adjectives. LREC 2004. Volume IV, pp. 1115-1118.
[5] Andreevskaia, A., Bergler, S., Urseanu, M.All Blogs Are Not Made Equal: Exploring Genre Di_erences in Sentiment Tagging of Blogs. International Conference on Weblogs and Social Media (ICWSM-2007), Boulder, CO. 2007.
[6] Vandana V. Chaudhari*, Chitra A. Dhawale** and Sanjay Misra,“ Sentiment Analysis Classification: A Brief Review”, I J C T A, 9(23) 2016, pp. 447-454
[7]ANH-DUNG VO , QUANG-PHUOC NGUYEN , AND CHEOL-YOUNG OCK, “Opinion_Aspect Relations in Cognizing Customer Feelings via Reviews”, IEEE 2017, pp. 5415-5427
[8]ATHIRA U, AND SABU M. THAMPI, “Linguistic Feature Based Filtering Mechanism for Recommending Posts in a Social Networking Group”, IEEE 2018, pp. 4469-4484
[9] S. 1. Wu, R.D. Chiang and Z.H. Ji, Development of a Chinese opinion mining system for application to Internet online forum, The Journal of Supercomputing, Springer US[Online], 2016.
[10] Z. Li, L.Liu and C.Li, Analysis of customer satisfaction from Chinese reviews using opinion mining, Proceeding of the 6th IEEE International Conference on Software Engineering and Service Science(ICSESS). 2015, pp.95-99.
[11] Q.Su, X.Xu, H.Guo, Z.Guo, X. Wu, X. Zhang and B.Swen. Hidden Sentiment association in Chinese web opinion mining. Proceeding of the 17th International Conference on World Wide Web, 2008, pp.959-968.
[12] R.M. Duwairi and I. Qarqaz, Arabic Sentiment Analysis using Supervised Classification. Proceeding of 2014 International Conference on Future Internet of Things and Cloud. 2014, pp. 579-583.
[13] H.S. Le, T.V. Le and T.V. Pham, Aspect Analysis for Opinion Mining of Vietnamese Text. Proceeding of International Conference on Advance Computing and Application, 2015, pp.118-123.
[14] V.B. Raut and D.D. Londhe, "Survey on opinion mining and summarization of user review on web", International Journal of Computer Science and Information Technology, Vol. 5(2), 2014, pp. 1026-1030.
[15] Fiaidhi, O. Mohammed, S. Mohammed, S. Fong, and T.H, Kim, Opinion Mining over twiiterspace: Classifying tweets programmatically using the R approach. Proceeding of the 7th International Conference on Digital Information Management, 2012, pp. 313-319.
[16] L. Lin, 1. Li, R. Zhang, W. Yu and C. Sun, Opinion mInIng and sentiment analysis in social networks: A retweeting structure-aware approach. Proceeding of the 7th International Confernece on Utility and Cloud Computing, 2014, pp.890-895.
Citation
Karuna Sahay, Kaptaan Singh, Amit Saxena, "Intelligent Opinion Polarity and Analysis in Discovering Product Related Customer Reviews: A Survey," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.1139-1143, 2019.
Analysing vegetation cover of an area using established Green Index from Satellite Image
Research Paper | Journal Paper
Vol.7 , Issue.6 , pp.1144-1148, Jun-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i6.11441148
Abstract
In present day scenario decrease in tree count or vegetative area is one of the major challenges to humanity. Identification of vegetative area and analysing the density of forest cover is one of the fields in remote sensing. Manually detecting the vegetation change effectively and accurately is quite time consuming. Hence comes the need of automated system which identifies area of forest cover, analyses its density and makes a comparison of its vegetative cover of an area over a certain time period. This paper establishes a parameter ‘Green Index’ to identify forest cover of an area. Satellite images are used to monitor any change. The spectral index NDVI (Normalized Difference Vegetation Index) is used to calculate green index of an area from satellite image. Histogram is plotted for different wavelengths (Red, Green, and Blue) versus different area (Forest, Desert, Sea and Snow area) to compare its green index.
Key-Words / Index Term
Green Index, Vegetative cover, NDVI, Satellite images
References
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[14] J. Tian, P. Reinartz, P. d’Angelo, and M. Ehlers, “Region-based automatic building and forest change detection on Cartosat-1 stereo imagery,” ISPRS J. Photogramm. Remote Sens., vol. 79, pp. 226–239, May 2013.
[15] He Yin, Thomas Udelhoven , Rasmus Fensholt , Dirk Pflugmacher and Patrick Hostert, “How Normalized Difference Vegetation Index (NDVI) Trends from Advanced Very High Resolution Radiometer (AVHRR) and Système Probatoire d’Observation de la Terre VEGETATION (SPOT VGT) Time Series Differ in Agricultural Areas: An Inner Mongolian Case Study”, Remote Sens., 4, 3364-3389; doi:10.3390/rs4113364, 2012 .
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Citation
S. Manna, S. Mitra, "Analysing vegetation cover of an area using established Green Index from Satellite Image," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.1144-1148, 2019.
Simulation Based Exploration of SKC Block Cipher Algorithm
Research Paper | Journal Paper
Vol.7 , Issue.6 , pp.1149-1152, Jun-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i6.11491152
Abstract
Social media provides an environment of information exchange. They principally rely on their users to create content, to annotate others’ content and to make on-line relationships. The user activities reflect his opinions, interests, etc. in this environment. We focus on analyzing this social environment to detect user interests which are the key elements for improving adaptation. This choice is motivated by the lack of information in the user profile and the inefficiency of the information issued from methods that analyze the classic user behavior (e.g. navigation, time spent on web page, etc.). So, having to cope with an incomplete user profile, the user social network can be an important data source to detect user interests. The originality of our approach is based on the proposal of a new technique of interests` detection by analyzing the accuracy of the tagging behavior of a user in order to figure out the tags which really reflect the content of the resources. So, these tags are somehow comprehensible and can avoid tags “ambiguity” usually associated to these social annotations. The approach combines the tag, user and resource in a way that guarantees a relevant interests detection. The proposed approach has been tested and evaluated in the Delicious social database. For the evaluation, we compare the result issued from our approach using the tagging behavior of the neighbors (the egocentric network and the communities) with the information yet known for the user (his profile). A comparative evaluation with the classical tag-based method of interests detection shows that the proposed approach is better
Key-Words / Index Term
MCP, Feedback, Relavance
References
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Citation
T. Sai Iswarya, K. Rangaswamy, "Simulation Based Exploration of SKC Block Cipher Algorithm," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.1149-1152, 2019.
Real Time River Bridge Monitoring and Alert System using GSM
Research Paper | Journal Paper
Vol.7 , Issue.6 , pp.1153-1157, Jun-2019
CrossRef-DOI: https://doi.org/10.26438/ijcse/v7i6.11531157
Abstract
In India, many bridges built by the British east India company 100 years ago. Due to long time span, it is required to monitor them. The main objective of the proposed system is to read the water level and vibration of the bridge continuously. Upon crossing the threshold level, a short message get send to the observation section periodically by using GSM (Global System for mobile communication).This system may help in flood situation and may be a communication tool between the traveler and government. This proposed system also avoids the traffic jam due to availability of time with users for finding an alternative solution before they are going to be stuck at flood.
Key-Words / Index Term
PIC32MM0256GPM064, LiDAR sensor, vibration sensor, GPS Module GSM Module
References
[1] Amrit Kumar Panigrahi, Chandan Kumar Singh, Diwesh Kumar, Nemisha Hota,“Tank Water Level Indicator & Controller Using Arduino”, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, ISSN (Print) : 2320 – 3765 ISSN (Online): 2278 – 8875, Vol. 6, Issue 3, March 2017
[2] Kodathala Sai Varun, Kandagadla Ashok Kumar , Vunnam Rakesh Chowdary, C. S. K. Raju “Water Level Management Using Ultrasonic Sensor(Automation)”, International Journal of Computer Sciences and Engineering, E-ISSN: 2347-2693 E, : Vol.-6, Issue-6, June 2018 2347-2693
[3] Prof. Savita Lade, Prathamesh Vyas, Vikrant Walavalkar, Bhaiyasab Wankar, Pranjal Yadav,“Water Management System Using IoT with WSN”, International Research Journal of Engineering and Technology (IRJET), e-ISSN: 2395-0056 p-ISSN: 2395-0072, Volume: 05 Issue: 03 | Mar-2018
[4] Rachana Parashuram Khatwate, Ashvini Appasaheb Kashid,“Wireless Sensor Network Based Real Time Water Level Management System”, International Journal of Innovations & Advancement in Computer Science, ISSN 2347 – 8616, Volume 7, Issue 3 March 2018
[5] Pranoti Bhatele, Sheeja Suresh,“Zigbee based prototype implementation of water level monitoring and control in canal and sub canals”, IOSR Journal of VLSI and Signal Processing (IOSR-JVSP), e-ISSN: 2319 – 4200, p-ISSN No. : 2319 – 4197, Volume 6, Issue 3, Ver. III (May. - Jun. 2016), PP 74-78
[6] Sourin Acharjee, Arunabho Kanti Som, Arpita Ghosh,“Liquid Level Controller using ARDUINO Board and Zigbee Module”, International Journal of Electronics, Electrical and Computational System, ISSN 2348-117X, Volume 6, Issue 5, May 2017
[7] Mr. Muthamil Selvan.S , Aratrika Roy, Kurnal Pratap Singh, Ashutosh Kumar,“Automatic Water Level Indicator Using Ultrasonic Sensor and GSM Module”, IJARIIE-ISSN(O)-2395-4396, Vol-4 Issue-5 2018
[8] Ayob Johari, Mohd Helmy Abd Wahab, Nur Suryani Abdul Latif, “Tank Water Level Monitoring System using GSM Network”, International Journal of Computer Science and Information Technologies, ISSN-0975-9646, Vol. 2 (3) , 2011, 1114-1120
[9] Mr. M. C. Pawaskar, Mr. Pranjal Gadikar, Ms. Pournima Kambli, Ms. Snehal Pawar, Ms. Shweta Savardekar,“GSM Based Water Control and Management”, International Research Journal of Engineering and Technology, e-ISSN: 2395 -0056 p-ISSN: 2395-0072, Volume: 04 Issue: 04 Apr -2017
[10] Priya J., Sailusha Chekuri, “Water level monitoring system using IOT”, International Research Journal of Engineering and Technology (IRJET), e-ISSN: 2395-0056 p-ISSN: 2395-0072, Volume: 04 Issue: 12 | Dec-2017
[11] V. Jeevagan, S. Prem Kumar,“Water level monitoring system using IoT & atmega328p microcontroller”, International Journal of Pure and Applied Mathematics, ISSN: 1314-3395 (on-line version), Volume 119 No. 18 2018, 1497-1501
[12]Datasheet LiDAR, available at: https://www.generationrobots.com/media/pj2-de-lidar-tf02-datasheet-v2-2-1576.pdf
[13] Datasheet PIC32MM0256GPM064, available at: http://ww1.microchip.com/downloads/en/DeviceDoc/60001387c.pdf
Citation
Sameep S. Sawardekar, Sanjay Nalbalwar, S. B. Deosarkar, Sachin Singh, "Real Time River Bridge Monitoring and Alert System using GSM," International Journal of Computer Sciences and Engineering, Vol.7, Issue.6, pp.1153-1157, 2019.