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Research Paper

Bridging the Gap: Education Inequality and Economic Impact in India

This paper examines the disparities in school enrollment and dropout rates across various Indian states and their correlation with economic conditions. The paper uncovers states with higher government and private enrollments and dives deeper into steps taken by government and its impact. Despite government initiatives like Sarva Shiksha Abhiyan, significant inequalities persist, particularly affecting marginalized communities and girls. The study utilizes secondary data from ASER and MOSPI, analyzing trends from 2009 to 2018. Findings reveal that states like Tripura and West Bengal have high government school enrollments, while Manipur leads in private school enrollments. Dropout rates are notably high in states like Uttar Pradesh, possibly due to less government initiatives, whereas Kerala and Tamil Nadu show low rates due to robust educational policies. The regression analysis indicates that higher per capita NSDP correlates with lower dropout rates and increased private school enrollments, suggesting economic factors significantly influence educational trends. Conversely, government school enrollments decrease with better economic conditions, highlighting the need for improved public education quality. The paper underscores the importance of targeted policies and social awareness in specific states to address these disparities and promote inclusive education.

Published by: Taksheel Agrawal, Priyonkon Chatterjee

Author: Taksheel Agrawal

Paper ID: V10I5-1278

Paper Status: published

Published: October 9, 2024

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Research Paper

Face Recognition-Based Attendance System

This research paper is about the creation of a program for attendance marking using face recognition, which takes the concepts of the Haar Cascade algorithm created by Viola and Jones and the LBPH classifier developed by Timo Ahonen et al. Each student’s data was collected by a program interface that also took photos of each student for face detection and recognition to take place. The success of the program was it was able to detect each student correctly with an accuracy of 91%. This program has been successfully implemented in the last 12 months.

Published by: Shubh Agarwal

Author: Shubh Agarwal

Paper ID: V10I5-1282

Paper Status: published

Published: October 9, 2024

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Research Paper

Consumer Behaviour of UPI Applications / Companies

Abstract: Due to factors such as demonetization and COVID-19, UPI has quickly become India’s first choice when it comes to digital payment and is now being incorporated in other countries such as Bhutan and, more recently, France. This research paper explores the various reasons behind the rapid growth of UPI since its introduction in 2016 and why it has become so easy to adopt and integrate into our daily transactions. The paper compares UPI to other forms of digital transactions, and cash transactions, and goes into depth on the advantages, as well as barriers, faced when using UPI.

Published by: Kabir Bhattacharya

Author: Kabir Bhattacharya

Paper ID: V10I5-1283

Paper Status: published

Published: October 8, 2024

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Research Paper

Corporate Social Responsibility: Ethical and Economic Considerations

This research paper focuses on the constant conflict of businesses working towards corporate social responsibility with ethical or economic considerations. Hence, it reviews the government, markets and social norms as the pressure behind corporate social responsibility. This brings us to the basic rationale behind CSR and to whom these firms bring those CSR schemes. The paper also analyses various companies' perspectives on CSR and their expenditures on these schemes. Further, it talks about CSR as a byproduct of the ethical practices of the firms, which follows up to consider the kinds of CSR that are important to be taken care of. This leads to the origin of CSR, as the result of labour conflicts in the 19th century, which elaborates on the current situation in the three pressures which discipline companies into a certain social behaviour.

Published by: Tia Agrawal

Author: Tia Agrawal

Paper ID: V10I5-1258

Paper Status: published

Published: October 7, 2024

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Research Paper

Understanding the Potential Risks and Uses of SLS in Daily Life

A popular chemical in personal care goods like shampoos and cleaning solutions is sodium lauryl sulfate, or SLS. Its emulsifying and foaming qualities make it valuable. Many Concerns have been voiced about its possible negative effects on health, especially skin irritation, as well as its environmental impact. This paper discusses the history of SLS, its uses, and the safety issues that surround it. Further covered is the topic of substitute ingredients for SLS, especially in the cosmetics sector. Despite SLS's effectiveness, these results imply that safer and more environmentally friendly options exist.

Published by: Tunisha Chaudhary

Author: Tunisha Chaudhary

Paper ID: V10I5-1271

Paper Status: published

Published: October 4, 2024

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Research Paper

Categorization and Forecasting of Hepatitis C Diagnosis via an Unconventional Consensus Classifier

Liver diseases are increasingly becoming one of the most fatal health conditions in several countries, especially after Covid-19 (i.e., after 2019) and the prevalence of liver disease has been rising since then due to factors such as excessive alcohol consumption, inhalation of harmful gases, and the intake of contaminated food, pickles, drugs and medications and not to miss, also due to the Covid-19 virus. To address this issue, several multimodal data are collected and given as input to build categorization and forecasting models aimed at predicting liver diseases, especially Hepatitis C and, by utilizing machine learning approaches, we comprehensively assess the patients' liver conditions and the stage of Hepatitis C. We first categorize the results into positive and negative outcomes using rudimentary machine learning algorithms. As we process the liver parameters and their percentages, we present the results as votes derived using the Unconventional Consensus Classifier Algorithm to classify the stages of Hepatitis C. This project aims to develop a robust machine-learning model for the categorization and forecasting of liver disease diagnosis. Leveraging various machine learning algorithms, including decision trees, support vector machines, and so on, the project focuses on accurately predicting liver disease based on a set of medical and demographic features. By analyzing the available existing data and utilizing advanced data preprocessing and feature engineering methods, the proposed system seeks to assist healthcare professionals in early diagnosis and treatment planning, ultimately improving patient outcomes.

Published by: S. Sri Krishna, N T Sunil Kumar, K S Saran, Dr. B. Aarthi

Author: S. Sri Krishna

Paper ID: V10I5-1273

Paper Status: published

Published: October 4, 2024

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