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Spectral Evidence for the One-Step Three-Electron Oxidation of Phenylsufinylacetic Acid and Oxalic Acid by Cr(VI)

American Journal of Analytical Chemistry 2013年第10期4卷 20-29页

作者： Perumal Subramaniam natesan thamil selvi Department of Chemistry Govindammal Aditanar College for Women Tiruchendur India Research Department of Chemistry Aditanar College of Arts and Science Tiruchendur India

The co-oxidation of a mixture of phenylsulfinylacetic acid (PSAA) and oxalic acid (OxH2) by Cr(VI) in 20% acetonitrile-80% water (v/v) medium follows third order kinetics, first order, each with respect to PSAA, OxH2 and Cr(VI). The reaction involves nucleophilic attack of sulfur atom of PSAA on chromium of the oxidizing species, Cr(VI)-OxH2 to form a ternary complex, Cr(VI)-OxH2-PSAA followed by a one-step three-electron reduction of Cr(VI) to Cr(III) and simultaneous oxidation of both the substrates. The reaction is catalysed by Mn2+ ion while retarded by Al3+ ion. Electron releasing substituents in the meta- and para-positions of the phenyl ring of PSAA enhance the rate of co-oxidation while electron withdrawing substituents retards the reaction. The Hammett plots at different temperatures exhibit excellent correlation with negative ρ values. The reaction series obey isokinetic relationship and the observed isokinetic temperature is lying below the experimental range of temperature.

关键词： Phenylsulfinylacetic Acid Oxalic Acid Co-Oxidation Nucleophilic Attack of Sulfur Three-Electron Transfer Substituent Effect

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SA-MSVM:Hybrid Heuristic Algorithm-based Feature Selection for Sentiment Analysis in Twitter

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Computer Systems Science & Engineering 2023年第3期44卷 2439-2456页

作者： C.P.thamil selvi R.PushpaLaksmi Department of Computer science and Engineering Sri Ranganathar Institute of Engineering and TechnologyCoimbatoreTamilnadu641009India Department of Information and Technology PSNA College of Engineering and TechnologyDindigulTamilnadu624622India

One of the drastically growing and emerging research areas used in most information technology industries is Bigdata *** is created from social websites like Facebook,WhatsApp,Twitter,*** about products,persons,initiatives,political issues,research achievements,and entertainment are discussed on social *** unique data analytics method cannot be applied to various social websites since the data formats are *** approaches,techniques,and tools have been used for big data analytics,opinion mining,or sentiment analysis,but the accuracy is yet to be *** proposed work is motivated to do sentiment analysis on Twitter data for cloth products using Simulated Annealing incorporated with the Multiclass Support Vector Machine(SA-MSVM)***-MSVM is a hybrid heuristic approach for selecting and classifying text-based sentimental words following the Natural Language Processing(NLP)process applied on tweets extracted from the Twitter dataset.A simulated annealing algorithm searches for relevant features and selects and identifies sentimental terms that customers ***-MSVM is implemented,experimented with MATLAB,and the results are *** results concluded that SA-MSVM has more potential in sentiment analysis and classification than the existing Support Vector Machine(SVM)***-MSVM has obtained 96.34%accuracy in classifying the product review compared with the existing systems.

关键词： Bigdata analytics Twitter dataset for cloth product heuristic approaches sentiment analysis feature selection classification

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Twitter Media Sentiment Analysis to Convert Non-Informative to Informative Using QER

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Intelligent Automation & Soft Computing 2023年第3期35卷 3545-3555页

作者： C.P.thamil selvi P.Muneeshwari K.Selvasheela D.Prasanna Department of Computer Science and Engineering Sri Ranganathar Institute of Engineering and TechnologyCoimbatore641009TamilnaduIndia Department of Artificial Intelligence and Machine Learning Saveetha School of Engineering Chennai602105Tamil NaduIndia Department of Computer Science and Engineering Sreesakthi Engineering CollegeKaramadai641104Tamil NaduIndia Department of Computer Science and Engineering Mahendra Engineering CollegeNamakkal637503Tamil NaduIndia

The term sentiment analysis deals with sentiment classiﬁcation based on the review made by the user in a social *** sentiment classiﬁcation accuracy is evaluated using various selection methods,especially those that deal with algorithm *** this work,every sentiment received through user expressions is ranked in order to categorise sentiments as informative and *** order to do so,the work focus on Query Expansion Ranking(QER)algorithm that takes user text as input and process for sentiment analysis andﬁnally produces the results as informative or *** challenge is to convert non-informative into informative using the concepts of classiﬁers like Bayes multinomial,entropy modelling along with the traditional sentimental analysis algorithm like Support Vector Machine(SVM)and decision *** work also addresses simulated annealing along with QER to classify data based on sentiment *** the input volume is very fast,the work also addresses the concept of big data for information retrieval and *** result com-parison shows that the QER algorithm proved to be versatile when compared with the result of *** work uses Twitter user comments for evaluating senti-ment analysis.

关键词： Sentiments QER SVM bayes multinomial big data analysis simulated annealing

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