Notice Board :

Call for Paper
Vol. 7 Issue 2

Submission Start Date:
Feb 01, 2026

Acceptence Notification Start:
Feb 10, 2026

Submission End:
Feb 25, 2026

Final MenuScript Due:
Feb 28, 2026

Publication Date:
Feb 28, 2026
                         Notice Board: Call for PaperVol. 7 Issue 2      Submission Start Date: Feb 01, 2026      Acceptence Notification Start: Feb 10, 2026      Submission End: Feb 25, 2026      Final MenuScript Due: Feb 28, 2026      Publication Date: Feb 28, 2026




Volume VI Issue XII

Author Name
Varun Bachle, Devendra Sharma
Year Of Publication
2025
Volume and Issue
Volume 6 Issue 12
Abstract
This review paper presents an analysis of solar photovoltaic (PV) based multifunctional electric vehicle (EV) charging systems, focusing on converter topologies, control strategies, and energy-management techniques. Recent studies highlight the use of bidirectional DC–DC converters, such as SEPIC, to enable efficient G2V, V2G, and V2H operations while supporting residential loads under variable solar conditions The reviewed implementation demonstrates a unified charger capable of MPPT without a separate DC–DC converter, seamless grid/islanded switching, active filtering, and robust dc-link control using SOGI-FLL and sliding-mode techniques .An Implementation of Solar PV Overall, the review identifies key advancements and existing gaps in designing cost-effective, reliable, and multifunctional PV-integrated EV charging infrastructures.
PaperID
2025/IJEASM/12/2025/3282

Author Name
Anil Tiwari, Trilok Singh
Year Of Publication
2025
Volume and Issue
Volume 6 Issue 12
Abstract
The accelerating digital transformation of organizations has expanded the scale, complexity, and sophistication of cyber threats, challenging the effectiveness of traditional rule-based and reactive security frameworks. This research explores the strategic integration of Artificial Intelligence (AI) into information security architectures as a means to enhance predictive defense capabilities and strengthen digital trust. The study examines how AI-driven technologies—including machine learning, behavioral analytics, threat intelligence automation, and anomaly detection—can enable continuous monitoring, early threat forecasting, and adaptive security responses across distributed digital environments. Through a conceptual framework supported by industry case insights and existing security models, the paper evaluates the role of AI in improving threat detection accuracy, minimizing response times, and reducing human dependency in security operations. It further analyzes implementation chal
PaperID
2025/IJEASM/12/2025/3285

Author Name
Shivani Chouhan, Nitin Chauhan, Yashraj Thakur, Harsh Yadav, Mohit Kadwal
Year Of Publication
2025
Volume and Issue
Volume 6 Issue 12
Abstract
The rapid evolution of artificial intelligence has significantly transformed the landscape of career guidance and employability enhancement. Traditional career counseling methods often suffer from limited accessibility, lack of personalization, and dependency on human experts. This research paper presents an AI-based career guidance system that integrates three core modules: an intelligent chatbot, an AI-driven mock interview platform, and an automated resume analysis engine. The proposed system aims to provide personalized, scalable, and cost-effective career support to students and job seekers. The chatbot module leverages Natural Language Processing (NLP) to deliver real-time career guidance and query resolution. The mock interview module simulates real interview environments, evaluates candidate responses, and provides structured feedback. The resume analysis module uses machine learning and NLP techniques to assess resume quality, skill relevance, and job-role alignment. This pape
PaperID
2025/IJEASM/12/2025/3286

Author Name
Priyanshi Dwivedi, Shreya Kumari, Rishika Baheti, Ashif Raza, Mohit Kadwal
Year Of Publication
2025
Volume and Issue
Volume 6 Issue 12
Abstract
Traveling has become an essential part of daily life for education, work, tourism, and personal reasons. However, many travelers still face problems such as lack of proper travel information, confusion about routes, safety concerns, and communication difficulties due to language barriers. Most existing travel platforms focus mainly on ticket booking and hotel reservations and do not provide complete assistance during the actual journey. To address these issues, TRIPधारा is developed as a Web-Based Intelligent Travel Analytics and Assistance System. This system helps users plan, organize, and manage their trips in a simple and effective way. It provides features such as route information, trip planning, expense tracking, chatbot-based guidance, and language translation support. The chatbot assists users by answering common travel-related questions and guiding them while using the platform. The translator feature helps users understand information in their preferred language, making the
PaperID
2025/IJEASM/12/2025/3287