Friday, May 2 2025

MBA Dept. signs an MoU with GFGC, Punjalkatte

Department of Business Administration signed a Memorandum of Understanding (MoU) with GFGC, Punjalkatte to offer training services to undergraduate students. The MoU outlines collaboration in the following key areas:
• Expert sessions by Sahyadri faculty on subject-related topics, general knowledge, and personality development.
• Training in computer skills for both students and faculty at the Sahyadri campus.
• Placement-oriented training, including guidance on interviews, group discussions, and other job-related skills.
• Opportunities for industry visits to enterprises located within the Sahyadri campus.
• Participation in seminars, workshops, and other academic activities hosted by Sahyadri College.
As part of this collaboration, Prof. Padmanabha B and Prof. Ramesh K G conducted sessions for students of GFGC Punjalkatte.
Prof. Padmanabha B delivered a session titled "Collaborate to Conquer: Unleashing Collective Power" for first- and second-year students, emphasizing the significance of self-awareness in effective team building.
Prof. Ramesh K G presented a session on "Navigating PGCET: A Strategic Roadmap" for final-year students, focusing on the importance of pursuing postgraduate education from a career standpoint, strategies for preparing for the PGCET examination, and an in-depth overview of the PGCET exam process.

CSE Faculty Publish Research Paper in Elsevier’s Q1-Ranked Journal

The research paper titled “Developing an Explainable Human Action Recognition System for Academic Environments: Enhancing Educational Interaction” authored by Dr. Mustafa Basthikodi, Professor and Head of the Department of Computer Science & Engineering, and Dr. Poornima B V, Assistant Professor, Department of Computer Science & Engineering, has been published in Results in Engineering, a Q1-ranked, Scopus-indexed journal by Elsevier, with an impressive impact factor of 6.0. The journal is renowned for disseminating high-quality and impactful research. Its open-access model ensures global visibility and accessibility, fostering widespread dissemination and meaningful contributions to the scientific and academic community.

This study introduces an Explainable Human Action Recognition System designed to improve educational interactions in academic settings. Utilizing a Temporal Segment Network, the system analyses video sequences in segments to capture dynamic patterns and accurately classify actions. Its explainable architecture ensures transparency in decision-making, aiding both educators and learners. The system achieved higher accuracy, demonstrating its potential to enhance understanding of classroom behaviour and support more engaging learning environments.

The article is accessible via the following link, to download, read and cite:

https://doi.org/10.1016/j.rineng.2025.105014

News Details

MBA Dept. signs an MoU GFGC, Punjalkatte

Fri May 02 2025