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Review Paper

Credit card fraud detection

In today's world, due to the rapid increase of technology many countries in the world encouraging cashless transactions. Credit cards are the easiest and fastest mode of payment both in offline as well as online transactions. So, credit cards are becoming a more popular mode of transaction in modern-day life. This also increases fraud cases in credit card transactions. Peoples and companies face a huge amount of loss of money due to these increasing cases of fraud transactions. This also affects the liability of the bank systems and service providers. This is why it becomes very important to detect fraud transactions and avoid financial loss. The good thing is fraud tends to occur in patterns so machine learning algorithms can help us to predict them. Our objective is to reduce the tedious work of the fraud detection process with the help of machine learning and data science.

Published by: Pratik Prashant Borkar, Ankita Vijay Munj, Prathmesh Prakash Risbud, Sahil Ganpat Sarang

Author: Pratik Prashant Borkar

Paper ID: V7I3-1459

Paper Status: published

Published: May 25, 2021

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Review Paper

HPLC method development and validation – A review

High-Performance liquid chromatography analytical tool used to qualitative and quantitative the drug product and drug stability, impurities. The separation is done by column, detection wavelength and other composition (organic & PH) for analysis of the drug. The analytical method development and validation play an important role in drug discovery and development. The validations are done by [Accuracy, Precision, Repeatability, Specific limit, etc.] the review articles are discussed by the High-Performance Liquid Chromatography Method Development and Validation of the drug.

Published by: D. Satheeshkumar, M. Gokul, S. Shalini, M. Ukeshraj, M. Mullaivendan

Author: D. Satheeshkumar

Paper ID: V7I3-1429

Paper Status: published

Published: May 25, 2021

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Research Paper

Cloud technologies in healthcare industry

The term “Cloud Computing” is a buzzword in the IT world and has been a major topic of conversation as of late and is emerging as one of the most important technologies of this decade. A distributed computing administration utilized by medical care suppliers for putting away, keeping up, and backing up close to home wellbeing data (PHI). Cloud services are capable of storing significantly more data than an on-site physical server, particularly when it involves the massive image files common in radiology departments. Also, medical care distributed storage costs are a small portion of these for on-location workers; in any case, the progress requires an undeniable worker virtualization execution. Numerous doctors and medical care associations are hesitant to utilize medical services cloud administrations because of a paranoid fear of enduring an information break infringing upon the protection Portability and Accountability Act (HIPAA). Because of the delicate idea of the data being put away and gotten too, numerous medical care associations are picking to keep away from public cloud benefits and carrying out an individual cloud administration in-house all things being equal.

Published by: Omkar Chavan

Author: Omkar Chavan

Paper ID: V7I3-1462

Paper Status: published

Published: May 24, 2021

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Research Paper

E-Commerce Website

Building a single page web application for ecommerce, to create a platform over online portals that facilitates online transactions of goods and services through transfer of information and trade over the Internet. In this project we are going to build a dynamic webpage which is different from the usual website, where in we are introducing to a website which dynamically loads the content and details of the products and services to the user in which he is interested in. Users will have a great experience while surfing on the web site because in a dynamic web page user need not load the entire page. Single page applications are fast and responsive because it does not load the entire page which significantly increases the website’s speed and efficiency

Published by: Harshadi Hansora, Sneha Bendale, Natraj Varanmala, Vinay Solanki

Author: Harshadi Hansora

Paper ID: V7I3-1424

Paper Status: published

Published: May 24, 2021

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Research Paper

The effect of air pollution on APTI values of some plant species and their comparative study

Air pollution is one of the serious problems faced by people globally due to its transboundary dispersion of pollutants over the entire world. But, whatever mode, whether natural or artificial, is a major concern in to-days developing countries like India. The present research is aimed at assessing the air pollution tolerance index of plants at two different locations. The locations selected were Maheshwari Udayaan, Mumbai, India (located at the center of four signals routes (location 1), and Khalsa College garden, Mumbai, India (location 2). Plants available commonly in both locations were selected for the present research. Four physiological and biochemical parameters which are relative water content, leaf pH, Ascorbic acid, and total chlorophyll were used to compute the APTI. Plants' responses towards air pollution are assessed by the air pollution tolerance index (APTI) value. The plant species having higher APTI value can be given priority for plantation programs in urbanize and industrial areas; so as to reduce the effects of air pollution and to make the ambient atmosphere clean and healthy. The present study was conducted for evaluating the Air Pollution Tolerance Index (APTI) value of six plant species i.e., 1. Mangifera Indica 2.Polyathia longifolia 3. Ixora 4. Codiaeum variegatum 5.Canna Indica 6.Phyllanthus amarus.

Published by: Dr. Ranjeet Kaur

Author: Dr. Ranjeet Kaur

Paper ID: V7I3-1453

Paper Status: published

Published: May 24, 2021

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Research Paper

Prediction of plant leaf disease using image pre-processing and filter based optimal feature selection for KNN classifier

In plants, disease detection is a significant task related to the agricultural production of a country. The major economy of a country is linked with agricultural production which is very important for the development of a nation. Any kind of infection on the leaves of the plants leads to a loss in crop production and puts down the effort of farmers which in turn hits the economy and livelihood of the country. In this paper, we propose an image processing and filter-based feature selection method which distinguishes the disease of the plant leaf and classifies them using a KNN classifier. Using the feature selection process the unwanted redundancy and irrelevant data is filtered which helps the classifier to learn and classify the data more precisely.

Published by: Komala T., Ashwini S. S., Dr. M. Z. Kurian

Author: Komala T.

Paper ID: V7I3-1452

Paper Status: published

Published: May 24, 2021

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