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Santhi, P.
- Classification System for Identifying the Chemical Structure Using Support Vector Machine
Abstract Views :284 |
PDF Views:2
Authors
Affiliations
1 Department of CSE, M. Kumarasamy College of Engineering, Karur, Tamil Nadu, IN
1 Department of CSE, M. Kumarasamy College of Engineering, Karur, Tamil Nadu, IN
Source
International Journal of Emerging Trends in Science & Technology, Vol 3, No 1 (2017), Pagination: 10-14Abstract
In laboratory, each effort is taken only for identifying the unknown chemicals. All the chemicals are having its own characteristics and structure of molecules such as lines, hexagons and pentagons. The chemical database is used to find the detailed information of that molecule. Even though, the current database does not provide the up to date chemical information. To overcome the above identified problem, this paper introduces the kernel based support vector machine for identifying the chemicals using its structure. The SVM's are becoming more popular algorithm for identification of variety of chemicals in chemical applications. Final result shows the chemical identification and performance analysis of this proposed system.Keywords
Chemistry, Classification, Molecules, Support Vector Machine.
References
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- A Safe Mechanism for Handling Data in Free Cloud
Abstract Views :276 |
PDF Views:7
Authors
S. Saravanan
1,
P. Santhi
1
Affiliations
1 Department of Computer Science and Engineering, M. Kumarasamy College of Engineering, Karur, Tamil Nadu, IN
1 Department of Computer Science and Engineering, M. Kumarasamy College of Engineering, Karur, Tamil Nadu, IN
Source
International Journal of Emerging Trends in Science & Technology, Vol 3, No 2 (2017), Pagination: 34-38Abstract
In this genuine those distributed computing, require make a cloud sensibly be normal enter for offering enrolling resources. On the off chance that it require disseminating enrolling organization insignificantly over Hosting neighbourhood servers or individual units ought to control applications, there would extreme protection nerves to administration data. The present structure requires help developed with cruel security arranges yet it require precisely issues. Those considerations are equivalent discrete duty, certifiable data possession, outcast Inspecting are secure regardless it require precisely issues. With give enough security straight forwardly cloud A little examine need been settled on around past flawless we suggest another structure recognized Likewise uniqueness constructed data dealing with and data checking transparently cloud which accomplishments those welfares for quantum instruments ought to asylum open database. We took a part reference in which cruel open cloud server, director Furthermore client would given with secure relationship with our expected piece of information which use optional Prophet display. Our honest to goodness taking in need both achievement what is more dissatisfaction rates with isolated also typical Clouds separately. Various customers might need to accumulate their larger part of the information on typical cloud servers along the side with those quick improvement about cloud enrolling. New wellbeing issue must make decided so as on sponsorship All the more customers change their data secured close by consistent cloud.Keywords
Distributed Computing, Open Cloud Server, Server.References
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- Smart India Agricultural Information Retrieval System
Abstract Views :117 |
PDF Views:0
Authors
Affiliations
1 Department of CSE, M. Kumarasamy College of Engineering, Karur, Tamil Nadu, IN
1 Department of CSE, M. Kumarasamy College of Engineering, Karur, Tamil Nadu, IN
Source
International Journal of Emerging Trends in Science & Technology, Vol 6, No 2 (2020), Pagination: 13-23Abstract
In the contribution of Information Retrieval System in Agricultural field provide innovative idea and improve cognitive level of farmer while farming. It evaluates the necessary requirements of farmer, Transporting farmer query to Exports, distributing data through web service without complication. The main aim of Information Retrieval system is to supply right information at the hand of right user at a right time. Hence, we implement multiple regression techniques with Search Based Analysis. To improve the Quality of data parsing between server to client and decrease the response time with high precision of Data respectively.Keywords
Dataset Retrieval, Multiple Regression, Query ComputationReferences
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- Sentiment Analysis on Verbatim Responses for Understanding Students' Living and Learning Experience
Abstract Views :94 |
PDF Views:0
Authors
Affiliations
1 Associate Professor, Department of CSE, M. Kumarasamy College of Engineering, Karur, Tamil Nadu, IN
2 UG Student, Department of CSE, M.Kumarasamy College of Engineering, Karur, Tamil Nadu, IN
1 Associate Professor, Department of CSE, M. Kumarasamy College of Engineering, Karur, Tamil Nadu, IN
2 UG Student, Department of CSE, M.Kumarasamy College of Engineering, Karur, Tamil Nadu, IN
Source
International Journal of Emerging Trends in Science & Technology, Vol 7, No 1 (2021), Pagination: 04-06Abstract
Sentimental Analysis the computational study of sentiments, people’s opinions and emotions expressed in written language. It is very popular because of the wide range of applications it possesses. Opinions are the key influences of our behaviours and decision-making. Opinion mining helps in taking the right decisions as the analyzed data reports give the right emotion on products, companies, services, public personalities, governments, etc. Students’ opinions on their institutions, teachers, and trainers are collected nowadays. But the collected opinions are not useful unless it is analyzed and the measures according to it are taken. The conventional method is followed by analyzing it manually. Yet it could not be the consistent method for time and resource saving. Hence, we go for the computational method for opinion mining using Machine Learning techniques for extracting the emotions of the students. Machine Learning algorithms have come a long way, with Naive Bayes, Support Vector Machine and Maximum Entropy is the feature used in research. Sentiment classification by different categories involving the sentiments is the topic of research. This paper presents the survey on Sentimental Analysis on students’ feedback to extract the emotions of the students with the text feedback.Keywords
Sentimental Analysis (SA), Opinion Mining, Machine Learning (ML), Natural Language Processing (NLP), Student Feedback AnalysisReferences
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