Manuscripts

Recent Papers

Case Study

Applications of Lean Manufacturing Techniques to Enhance the Productivity of the Base Coating Process

Lean manufacturing techniques have increasingly been adopted in the automotive lighting sector to enhance efficiency, reduce waste, and improve product quality. This project explores the application of Lean methodologies in automotive lighting production, focusing on key practices such as value stream mapping, and continuous improvement (Kaizen). By analysing case studies from leading automotive lighting manufacturer (Varroc Engineering), the study highlights how these practices evaluate waste, streamline operations, minimize process costs, and enhance productivity. The integration of Lean principles not only optimizes the manufacturing process but also fosters a culture of innovation and responsiveness to organizational demands. Furthermore, the Project discusses the challenges faced in implementing Lean practices within this specialized field and offers strategies for overcoming these obstacles. Ultimately, the findings underscore the significance of Lean manufacturing in enhancing competitiveness and sustainability in the automotive lighting industry.

Published by: MajaharAli Shikalgar, Dr. Javed G. Khan

Author: MajaharAli Shikalgar

Paper ID: V12I3-1223

Paper Status: published

Published: June 30, 2026

Full Details
Research Paper

Comparative Assessment of Deep Learning Architectures for Urban Feature Extraction in ArcGIS Pro: U-Net vs. DeepLabV3+

The rapid development of deep learning has fundamentally transformed the way urban features are extracted from remotely sensed imagery. Among the most widely adopted architectures for semantic segmentation tasks in geospatial analysis are U-Net and DeepLabV3+, each offering distinct approaches to pixel-level classification. This paper presents a comparative theoretical and methodological assessment of both architectures in the context of urban land cover feature extraction, with specific reference to their implementation within ArcGIS Pro — a leading commercial GIS platform that natively supports deep learning workflows. The analysis focuses on architectural design principles, segmentation performance metrics reported in the literature, and the practical feasibility of deploying each model in an urban GIS environment such as the city of Plovdiv, Bulgaria. Results from existing studies indicate that both architectures achieve competitive accuracy on urban datasets, with U-Net demonstrating strengths in boundary-sensitive tasks and DeepLabV3+ excelling in multi-scale contextual feature capture. The study discusses the implications for GIS practitioners seeking to integrate deep learning into operational workflows using ArcGIS Pro tools.

Published by: Kaloyan Ivanov

Author: Kaloyan Ivanov

Paper ID: V12I3-1230

Paper Status: published

Published: June 28, 2026

Full Details
Research Paper

Serial Position Effect: The Causes of Forgetting

This study investigated the effect of loud rock music on memory recall using the Serial Position Effect. Participants were divided into two groups: one completed a word recall task in silence, while the other completed the same task while exposed to loud rock music. The study examined the primacy and recency effects by analyzing the number of words recalled from the beginning and end of a word list. Results showed that participants in the silent condition demonstrated stronger recall and a clearer serial position curve compared to those exposed to loud music. The findings suggest that loud background music interferes with attention, encoding, and retrieval processes, thereby reducing memory performance. These results highlight the influence of environmental distractions on cognitive functioning and learning.

Published by: Saisha Mehta

Author: Saisha Mehta

Paper ID: V12I3-1229

Paper Status: published

Published: June 28, 2026

Full Details
Research Paper

Solar-Powered Touchless Doorbell for Home and Industrial Applications

This project presents a Solar-Powered Touchless Doorbell for home and industrial applications using renewable energy and contactless sensing technology. An IR sensor detects the presence of a hand and activates the doorbell without physical contact, improving hygiene and convenience. The system is energy-efficient, cost-effective, and suitable for modern smart environments.

Published by: Vasanth, Dheena Prasanth K, Ravi Vinod, Vishal K, Dr. G. Sundar

Author: Vasanth

Paper ID: V12I3-1217

Paper Status: published

Published: June 23, 2026

Full Details
Thesis

Sadhu Om Swami – His Life and Poetic Compositions

Sadhu Om was a poet from Punnai Nallur, a famous kshetra, 2 miles from Thanjavur in Tamil Nadu. Even from his childhood Natarajan was naturally blessed with ‘asu kavitvam’ as it called. He could spontaneously compose poetry. He had great love for Lord Muruga and many songs in His praise flowed from him. As he was a good singer as well, he would joyously sing these songs. At the age of 24, (i.e., in 1946) he happened to come across and read the book ‘Sri Ramana Vijayam’, a Tamil biography of Ramana. This attracted his heart and he yearned to have Darshan of Bhagavan Ramana. He had the darshan of Ramana and was lost in his presence. Natarajan arrives with a song “Kuyil Vidu Thoodhu” and starts singing it before Bhagavan Ramana. Soon he started finding his job at the Thanjavur Collector’s Office a hindrance to his spiritual pursuit and resigned from it. Sri Sadhu Om’s association with Ramana Maharshi lasted four years from July 1946 until Ramana’s Mahasamadhi in April 1950. Sri Muruganar, often regarded as one of Ramana’s foremost disciples, designated Sri Sadhu Om as his literary executor. Sadhu Om had exclusive devotion to Bhagavan and regularly went for the giri-pradakshina, the circumambulation of the sacred Arunachala, Annamalai. He talked about the boundless merits of the Giri valam and created an awareness of its auspiciousness in Western seekers and other Bhagavan devotees. Dedicating his life to the twin purposes of composing hymns on Bhagavan and performing giri - pradakshina, Sadhu Om merged in Bhagavan’s grace on 17-3-1985.

Published by: Revathi Sankar, Dr. Ambika Kameshwar

Author: Revathi Sankar

Paper ID: V12I3-1226

Paper Status: published

Published: June 23, 2026

Full Details
Research Paper

Artificial Intelligence and Risk Management in Digital Banking Services: Opportunities, Challenges, and Future Perspectives

The rapid growth of digital banking has transformed the financial services sector by enhancing accessibility, efficiency, and customer experience. Simultaneously, the increasing dependence on digital platforms has exposed banks to various risks, including cyber threats, operational failures, fraud, data breaches, and regulatory compliance issues. Artificial Intelligence (AI) has emerged as a significant technological solution for identifying, assessing, and mitigating these risks. This paper examines the role of AI in risk management within digital banking services. The study explores AI-based applications such as fraud detection, predictive analytics, credit risk assessment, anti-money laundering systems, and cybersecurity monitoring. The paper also highlights challenges associated with AI adoption, including algorithmic bias, privacy concerns, regulatory issues, and technological dependence. Based on a review of contemporary literature and industry practices, the study concludes that AI significantly enhances the effectiveness of risk management while requiring appropriate governance frameworks to ensure ethical and secure implementation.

Published by: Mohd Sarim Syed

Author: Mohd Sarim Syed

Paper ID: V12I3-1219

Paper Status: published

Published: June 17, 2026

Full Details