Manuscripts

Recent Papers

Research Paper

Divided by Wealth: A Deep Dive into Women’s Access to Credit

Women’s access to credit has historically been restricted by systemic discrimination and by outdated financial structures, limiting female economic independence and business opportunities. While landmark pieces of legislation such as the 1974 Equal Credit Opportunity Act (ECOA) in the United States have attempted to address these issues, research continues to indicate that gender biases in credit persist. While previous academic studies have examined econometrics, Fletschner (2008), and legal reforms, Garikipati (2008), this paper argues that deeply ingrained societal biases continue to shape credit lending systems, disproportionately disadvantaging women. By analyzing case studies from the United States, India, and South Korea, this research evaluates how gender-based disparities in credit access manifest across different economic and cultural contexts. The study incorporates data from financial institutions, government reports, and scholarly articles to highlight ongoing barriers. Ultimately, this paper argues that while progress has been made, financial institutions remain skewed in favor of men, necessitating policy changes that prioritize inclusivity and fairness. Without reform, women will continue to face unnecessary hurdles in obtaining credit, reinforcing long-standing economic inequalities.

Published by: Krish Gupta

Author: Krish Gupta

Paper ID: V11I3-1282

Paper Status: published

Published: June 3, 2025

Full Details
Research Paper

AI-Driven Medical Fundraising Verification System to Detect and Prevent Fraudulent Treatment Requests

Medical fund fraud, where individuals fake treatment documents to solicit donations, is a growing concern in crowdfunding. Traditional verification methods are often manual, slow, and prone to error. This project introduces an AI-based system using YOLOv8 to detect text in medical bills and Paddle OCR to extract key information. Extracted data—like hospital names and treatment costs—is verified using fuzzy matching against a trusted hospital database. This automated approach enhances accuracy, blocks fraudulent requests, and helps restore donor trust.

Published by: D V Vidhya Sri, N Aravindhan

Author: D V Vidhya Sri

Paper ID: V11I3-1280

Paper Status: published

Published: June 1, 2025

Full Details
Research Paper

An In-Depth Analysis of Dollar Liquidity in the Global Economy

As the US dollar is the basis of international finance and trade, dollar liquidity is vital to the health of the economy. Developing countries such as India feel the brunt of less dollar access through higher import costs, volatile currencies, and reduced corporate competitiveness. Cross-border banks, upon which the availability of dollar financing depends, are also at risk and may produce credit shortages. United States policy making can rock global markets, as was done with the 2008 Financial Crisis and the 2013 Taper Tantrum. The paper puts emphasis on stable dollar liquidity by emphasising the complexity of the global economy and how dislocation of dollar flow impacts banks, companies, and individuals everywhere.

Published by: Jaanya Rathi

Author: Jaanya Rathi

Paper ID: V11I3-1279

Paper Status: published

Published: June 1, 2025

Full Details
Research Paper

Thyroid Gland Abnormality Detection Using Pre-Trained Neural Networks

Medical image analysis plays a crucial role in the early detection and diagnosis of thyroid nodules, which are indicative of various thyroid illnesses. Thyroid nodules are classified using machine learning methods like Random Forest and Support Vector Machine in the current framework. In this work, we propose a unique use of transfer learning algorithms to thyroid nodule categorization. Neural network models that have already been trained on large datasets are modified for specific tasks that require less data through the use of transfer learning. Our approach involves using a state-of-the-art convolutional neural network (CNN) that has been pre-trained on a range of medical pictures to extract significant information from thyroid ultrasound scans. To optimize its performance for accurate classification, the model is trained on a particular dataset of thyroid nodule images. We examine the effectiveness of many transfer learning architectures, such as VGG16 and Xception CNN, and assess their overall accuracy, sensitivity, and specificity. The proposed methodology aims to provide physicians with a reliable thyroid problem diagnosis tool by increasing the categorization efficiency of thyroid nodules. The results pave the way for more precise thyroid image analysis, diagnosis by demonstrating how transfer learning can be utilized to maximize model performance even in the presence of sparsely labelled medical data.

Published by: B. Madhu Varshini, S. Sridevi, G. Kokila

Author: B. Madhu Varshini

Paper ID: V11I3-1256

Paper Status: published

Published: May 30, 2025

Full Details
Research Paper

Invisible Economies: The Gendered Burden and Cultural Dimensions of Unpaid Labour

This paper critically examines the pervasive issue of unpaid labour through a gendered lens, focusing on its systemic normalization and deeply entrenched roots in patriarchal traditions. Primarily undertaken by women, unpaid labour includes caregiving, household maintenance, and community service—tasks essential to the functioning of society yet systematically excluded from economic valuations and policy recognition. Drawing on feminist economic theory, particularly the work of Marilyn Waring, the paper explores how unpaid work perpetuates gender inequality by limiting women's access to education, employment, and leadership roles. Cultural contexts, especially in South Asia, further entrench these roles, framing domestic work as a woman's natural duty. The discussion incorporates cross-cultural comparisons, highlighting how traditions, economic transformations, and evolving gender norms affect perceptions of labour equity. Additionally, the mental health ramifications of this invisible burden are analysed, revealing a gendered gap rooted in structural inequities and societal expectations. By exposing the fiction of the "head of household," the paper advocates for an equitable redistribution of unpaid work, challenging outdated norms and emphasizing the shared responsibility of dismantling patriarchal labour divisions. Recognising and valuing unpaid labour is crucial not only for women's empowerment but for redefining partnerships and societal well-being at large.

Published by: Samara Khanduja

Author: Samara Khanduja

Paper ID: V11I3-1254

Paper Status: published

Published: May 30, 2025

Full Details
Research Paper

Smart Wheel Bot: An IoT-Driven Obstacle Avoidance System for Wheelchairs

Like many other sectors, the medical field in India is not widely known for its automation. Even in contemporary society, people with physical disabilities often rely on a caregiver for movement assistance. However, caregivers may be busy attending to other responsibilities and obligations, which can leave patients feeling stuck and dependent. To solve this problem, we designed an autonomous wheelchair which further enhances safety and facilitates greater independence in mobility. The Smart Mobility Bot is an economical autonomous wheelchair with decently priced features. It is controlled by DC motors and employs ultrasonic sensors for detecting obstacles.

Published by: Surya J, Swetha S, Vinayaga Moorthi M A

Author: Surya J

Paper ID: V11I3-1246

Paper Status: published

Published: May 29, 2025

Full Details
Request a Call
If someone in your research area is available then we will connect you both or our counsellor will get in touch with you.

    [honeypot honeypot-378]

    X
    Journal's Support Form
    For any query, please fill up the short form below. Try to explain your query in detail so that our counsellor can guide you. All fields are mandatory.

      X
       Enquiry Form
      Contact Board Member

        Member Name

        [honeypot honeypot-527]

        X
        Contact Editorial Board

          X

            [honeypot honeypot-310]

            X