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Research Paper

Rural India’s FMCG Consumer: A Review

This review paper synthesizes existing research to provide a comprehensive understanding of the Indian rural FMCG consumer. It examines the unique demographic, psychographic, and behavioral characteristics that influence purchasing decisions in this significant market segment. By analyzing various marketing insights, the paper identifies key challenges and opportunities for FMCG companies seeking to penetrate rural India. Specifically, it explores the impact of socio-cultural factors, economic conditions, and evolving digital literacy on consumer behavior, emphasizing the importance of localized marketing strategies, innovative distribution models, and community engagement. This review contributes to the existing literature by providing a consolidated perspective on the multifaceted nature of the Indian rural FMCG consumer, offering actionable insights for effective market penetration and sustainable growth.

Published by: Thilakk MB, S. Swetha Shree, Dr. A.S. Princy

Author: Thilakk MB

Paper ID: V11I1-1509

Paper Status: published

Published: April 2, 2025

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Research Paper

History of Music: How History Shaped Music, and Music Shaped History

Music is not merely a reflection of history—it is a force that has shaped it. This paper explores the symbiotic relationship between music and historical events, illustrating how melodies, rhythms, and lyrics have influenced societies, driven political movements, and preserved cultural identities. Music has acted as a catalyst for social change, fueling revolutions, advocating for justice, and even altering the course of global diplomacy. Genre hybridization and technological advancements have further expanded music’s impact, allowing for cross-cultural fusion and worldwide accessibility. By analyzing key moments in history where music played a pivotal role—whether through protest anthems, nationalistic compositions, or groundbreaking innovations—this study highlights music's enduring power as both a historical artifact and an agent of transformation.

Published by: Jiya Doshi

Author: Jiya Doshi

Paper ID: V11I1-1515

Paper Status: published

Published: April 2, 2025

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Research Paper

Dairy Farming

The Dairy Farming App enhances traditional livestock trading by offering a secure, transparent, and user-friendly digital platform. Built with Android Studio for the frontend and Java for backend integration, the app facilitates direct interaction between farmers, veterinarians, and buyers, reducing reliance on intermediaries. Its core functionalities include real-time messaging, location-based listings, livestock health record management, and IoT-driven herd monitoring. Comprehensive testing ensured the app meets functional, UI/UX, and security standards, achieving a 95% success rate in transaction completion. This paper explores the app’s development, implementation, and its transformative impact on modernizing livestock management through innovative technology.

Published by: Purvank Chauhan, Shubham Upadhyay

Author: Purvank Chauhan

Paper ID: V11I1-1475

Paper Status: published

Published: April 2, 2025

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Review Paper

Data Privacy and Artificial Intelligence Governance for Marginalized Communities in the United States: How Important is Inclusivity?

The study, “Data Privacy and AI Governance for Marginalized Communities in the United States,” examines the digital divide affecting marginalized groups and its exacerbation by biased AI governance. With the objectives of assessing data privacy risks, analyzing biases in AI systems, and proposing inclusive policies to improve AI governance, the research highlights key findings, including that marginalized communities, particularly racial minorities and low-income populations, face disproportionate risks from surveillance capitalism, biased facial recognition, and AI-driven hiring processes. Healthcare is also affected by the technological bias as AI models less accurately serve marginalized groups owing to unrepresentative data sets. In response, the study recommends stringent data protection laws akin to the European Union’s GDPR, ethical AI standards focused on transparency, as well as mandatory diversity in AI development teams to ensure demographic representation. To address biases in surveillance, the enactment of the George Floyd Justice in Policing Act and the Facial Recognition and Biometric Technology Moratorium Act are recommended. The work concludes with an emphasis on the need for digital inclusion and equitable AI governance to prevent further marginalization and foster fair participation in a digital society.

Published by: Idara Bassey

Author: Idara Bassey

Paper ID: V11I1-1469

Paper Status: published

Published: March 27, 2025

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Research Paper

Cab Fare Prediction Machine Learning Model

Predicting cab fares accurately is crucial for urban transportation, benefiting both passengers and service providers. This research explores machine learning techniques to enhance fare prediction using real-world trip data. Various models, including Linear Regression, Decision Trees, Random Forest, Gradient Boosting, and XGBoost, were evaluated. The Gradient Boosting Regressor emerged as the best-performing model after hyperparameter tuning, achieving high prediction accuracy. The study highlights the significance of trip distance and pickup time in fare estimation. Future enhancements include integrating weather data and deploying the model as a real-time API service to improve usability and precision.

Published by: Purvank Chauhan, Shubham Upadhyay

Author: Purvank Chauhan

Paper ID: V11I1-1480

Paper Status: published

Published: March 27, 2025

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Research Paper

Reinforced War Bunker Construction

Propagation of shock waves in partially- or fully-confined environments is a complex phenomenon due to the possibility of multiple reflections, diffraction and superposition of waves. In a military context, the study of such phenomena is of extreme relevance to the evaluation of protection systems, such as survival containers, for personnel and equipment. True scale testing of such structures is costly and time consuming but small-scale models in combination with the Hopkinson- Cran scaling laws are a viable alternative. This paper combines the use of a small-scale model of a compound survival container with finite element analysis (with LS- DYNA) to develop and validate a numerical model of the blast wave propagation. The first part of the study details the experimental set-up, consisting of a small-scale model of a survival container, which is loaded by the detonation of a scaled explosive charge. The pressure-time histories are recorded in several locations of the model. The second part of the study presents the numerical results and a comparison with the experimental data.

Published by: Aryan Sable, Priyanshu Arde, Siddharth Patil, Lakshmi Hanchate, Sagar Mungase

Author: Aryan Sable

Paper ID: V11I1-1472

Paper Status: published

Published: March 27, 2025

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