Manuscripts

Recent Papers

Research Paper

Access to Microcredit and Its Impact on Women Entrepreneurs in Rural India

This research paper investigates how microcredit access has transformed women’s entrepreneurial landscapes in rural India. Microcredit programs, often implemented through Self-Help Groups (SHGs) and microfinance institutions, have been instrumental in enhancing financial inclusion, promoting entrepreneurship, and empowering women socially and economically. The study assesses how access to small loans helps women develop enterprises, increase income, and gain greater control over family decisions. Using a mixed-method research design, the paper combines quantitative data from 100 rural entrepreneurs with qualitative interviews highlighting personal success stories and challenges. The results demonstrate a positive correlation between access to microcredit and women’s entrepreneurial growth, with implications for policy design and rural development strategies.

Published by: Keya Yash Panchmatia

Author: Keya Yash Panchmatia

Paper ID: V11I5-1250

Paper Status: published

Published: October 31, 2025

Full Details
Review Paper

Hybrid Logistic Regression and Random Forest Model for Diabetes Prediction Using Feature Elimination

The most common chronic diseases, diabetes mellitus, affect millions of people annually throughout the world. In order to lower the long-term health risk of diabetes, such as heart disease, kidney failure, and nerve damage, early detection and management are essential. The order to predict the risk of diabetes uses actual clinical data; this study presents a hybrid model that combines the Random Forest (RF) and Logistic Regression (LR) algorithms. Increase accuracy and interpretability, model also use Recursive Feature Elimination (RFE) to identify the most significant predictive features.PIMA Indian Diabetes dataset, along with World Health Organization (WHO) global health data, was used to train and validate the suggested model. The hybrid LR–RF approach obtained an accuracy of 89.2%, based on the findings and outperformed the individual model with a ROC-AUC score of 0.91. This model method shows how data-driven and interpretable artificial intelligence can help with clinical decision-making and provide patients and healthcare providers with trustworthy diagnostic tools.

Published by: Ritik Chauhan, Priyanka

Author: Ritik Chauhan

Paper ID: V11I5-1242

Paper Status: published

Published: October 31, 2025

Full Details
Research Paper

Forecasting Stock Market Prices Using Long Short-Term Memory (LSTM)

This study applies a Long Short-Term Memory (LSTM) neural network to forecast stock closing prices for selected technology companies (Apple, Google, Microsoft, and Amazon). The paper documents data collection, preprocessing, exploratory analysis (returns, volume, correlations), model architecture, and results. The aim is to evaluate LSTM’s ability to capture temporal patterns in stock prices and to provide practical insights for short-term forecasting. Key findings show that the LSTM model captures overall price trends and produces reasonable short-horizon forecasts; however, prediction accuracy is affected by market volatility, data noise, and model complexity.

Published by: Siddhi Rajput

Author: Siddhi Rajput

Paper ID: V11I5-1227

Paper Status: published

Published: October 31, 2025

Full Details
Research Paper

Factors Considered while Choosing a Life Insurance Company

This paper evaluates the factors considered for the selection of a Life Insurance Company by individuals. Life Insurance is an important part of one’s life, which gives security to the family of that individual future security in the absence of that individual. Many people take a policy on the recommendation of friends or family members, which can prove wrong as that individual doesn’t consider the important factors related to the policy, its terms and conditions, etc. So, it is important to consider the factors related to a life insurance company, like the Claim Settlement Ratio of the company, Solvency Margins, Reputation, etc. Therefore, this paper evaluates the behaviour of consumers while selecting a company by way of a survey with a structured questionnaire where people are asked about their choices about a company. The research focuses more on the salaried people, who were the samples for this survey, as they are primarily responsible for protection themselves and their families. The main objective of this research is to check the knowledge of people about different terms associated with life insurance, as well as the importance of these terms, while selecting a life Insurance Company.

Published by: Chaitrali Gaidhani, Arya Mohite, Ayush Deshmukh, Adit Bhoite, Kanchan Kawale, Kashish Khandelwal

Author: Chaitrali Gaidhani

Paper ID: V11I5-1235

Paper Status: published

Published: October 29, 2025

Full Details
Research Paper

Intellectual Property Rights and Competition Law: A Critical Analysis

This research paper examines the complex interface between Intellectual Property Rights (IPR) and Competition Law, analyzing the delicate balance between promoting innovation through temporary monopolies and preventing anti-competitive practices that harm consumer welfare. The study critically evaluates the legal framework governing this interface in India, primarily through Section 3(5) of the Competition Act, 2002, and examines landmark judicial precedents that have shaped the jurisprudence in this domain. Through comparative analysis of international approaches and examination of contemporary challenges, this paper argues that while IPR and competition law serve complementary objectives of promoting innovation and consumer welfare, their intersection requires careful judicial and regulatory navigation to prevent abuse of monopoly power while preserving incentives for innovation. Through a comprehensive examination of case law, statutory frameworks, and emerging trends in digital markets, this paper argues that a balanced approach is essential to foster innovation while maintaining competitive markets. The analysis includes recent developments in the technology sector antitrust enforcement, particularly focusing on major cases involving Google, Apple, Microsoft, and other tech giants that illustrate the contemporary challenges at this legal intersection.

Published by: Vanshika Nakra, Estuti kumari

Author: Vanshika Nakra

Paper ID: V11I5-1210

Paper Status: published

Published: October 28, 2025

Full Details
Review Paper

An AI-Based Framework for Early Cancer Detection Using Machine Learning Technique

Cancer detection using machine learning has emerged as a promising approach for improving early diagnosis and patient outcomes. This research focuses on applying advanced algorithms such as Convolutional Neural Networks (CNN), Support Vector Machines (SVM), and ensemble models to analyze medical imaging and histopathological data. The system automates feature extraction and classification, enhancing diagnostic accuracy and reducing human error. Data from breast, lung, and oral cancer datasets were used for model training and validation. Preprocessing techniques were applied to ensure image clarity and consistency. The proposed model achieved high precision and recall in identifying cancerous patterns. Limitations include data imbalance and interpretability challenges. Future work aims to integrate real-time diagnostics and multi-modal data for broader clinical use.

Published by: Ms. Rashida Bano, Ms. Noorishta Hashmi, Ms. Umaima fatima

Author: Ms. Rashida Bano

Paper ID: V11I5-1214

Paper Status: published

Published: October 25, 2025

Full Details