Department of Information Technology

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Author: search.filters.author.Harini SStart date: 2020

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    IMPACT OF ACINETOBACTER BAUMANNII ON DYE DEGRADATION AND A MOLECULAR ANALYSIS STUDY
    (Springer Link, 2023-06-05) Nivetha V; Harini S; Maria Shyla J; Sophia Reena G
    Acinetobacter baumanni was isolated from polluted soil. An attempt to study the A. baumannii to degrade dye was explored. It was found effective against azo dye and was able to completely degrade the dye under 48 h in a shake flask. Molecular analysis on the isolate A. baumanni was performed together with Hedychium flavum, and the sequence was submitted to the NCBI database to procure accession number MT192652.1. Response surface Methodology-Box-Behnken design (RSM-BBD) was used to optimize the condition and achieve 98–99% dye decolorization.
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    DATA MINING IN FRAUD DETECTION
    (Sri Krishna Arts and Science College, 2020-02-12) Hashni T; Harini S; Janani Shree G; Divya K
    Fraud is an increasing crime in day-to-day modern world. Fraud possibilities co-evolve withtechnology especially with InformationTechnology. Fraud detection is amethod/technique of identifying illegal actswhich are offensive, that are occurring all aroundthe world. It defines a skilled impostorformulizes the key forms and sub forms ofrecognized frauds and reveals the gathered datanature. To detect the fraud patterns from datacollected/stored, the paper explains somepreferred data mining techniques. Data mining ismost commonly used for fraud detection andprevention among various tools available. Thispaper gives an idea in a well-defined way by which any number of frauds can be detected and analyzed. This paper also describes clearly aboutdifferent types of fraud detection techniques.Theme of this paper is to firstly identify the typeof fraud using data mining techniques and toresolve the criminal aspect in simplified way.