Notice Board :

Call for Paper
Vol. 6 Issue 9

Submission Start Date:
Sep 01, 2025

Acceptence Notification Start:
Sep 10, 2025

Submission End:
Sep 25, 2025

Final MenuScript Due:
Sep 30, 2025

Publication Date:
Sep 30, 2025
                         Notice Board: Call for PaperVol. 6 Issue 9      Submission Start Date: Sep 01, 2025      Acceptence Notification Start: Sep 10, 2025      Submission End: Sep 25, 2025      Final MenuScript Due: Sep 30, 2025      Publication Date: Sep 30, 2025




Volume V Issue X

Author Name
Amey Rajiv Naik, Trilok Singh
Year Of Publication
2024
Volume and Issue
Volume 5 Issue 10
Abstract
The safeguarding of India's financial infrastructure is critical to maintaining economic stability and public trust in the nation's financial systems. This research paper explores various strategies and techniques for mitigating cybersecurity risks within India's financial sector. Through an in-depth analysis of case studies and a comprehensive review of current literature, the study identifies key vulnerabilities, effective mitigation approaches, and the broader implications of cyber threats on financial institutions. The findings underscore the importance of robust cybersecurity frameworks, the integration of advanced technologies, and the implementation of best practices to enhance resilience against cyberattacks. The study concludes with recommendations for policymakers, financial institutions, and cybersecurity professionals to ensure the security and integrity of India's financial infrastructure, ultimately safeguarding the nation's economic well-being
PaperID
2024/IJEASM/5/2024/3001

Author Name
Rohit Chaudhary, Harsh Lohiya
Year Of Publication
2024
Volume and Issue
Volume 5 Issue 10
Abstract
This paper presents a comprehensive review of the application of machine learning techniques to analyze customer satisfaction derived from airline-related tweets. As social media has become a critical platform for customer feedback, understanding sentiments expressed in tweets offers valuable insights for airline companies striving to enhance their service quality. We explore various machine learning methodologies, including sentiment analysis, topic modeling, and predictive analytics, that have been employed to decipher customer sentiments and identify recurring themes in user feedback. By systematically examining existing literature and case studies, this review highlights the effectiveness of different algorithms—ranging from traditional classifiers to advanced deep learning approaches—in extracting meaningful patterns from large volumes of unstructured tweet data. We discuss the implications of these findings for airline management, emphasizing the importance of real-time monitorin
PaperID
2024/IJEASM/5/2024/3002

Author Name
Priyanka Asthana, Manish Maheshwari, Babita Agrawal
Year Of Publication
2024
Volume and Issue
Volume 5 Issue 10
Abstract
Proactive planning, resource optimization, and improving the general quality and relevance of education all depend on forecasting in the educational field. It makes it possible for institutions to foresee and react to opportunities and difficulties in the future, ensuring that they can continue to effectively educate future generations. Students who are expected to struggle or fail early in the academic term can be identified with the use of forecasting. This increases the likelihood of success for these students by enabling educators and administrators to offer prompt support and interventions. In complex student data scenarios, both non-linear and linear mapping must be accomplished. Consequently, the goal of our research is to present a novel, effective ANN-based CFFBPNN model for forecasting student performance. Result shows that CFFBPNN outperform in terms of MSE and NRMSE in all the three cases and demonstrates potential for the method to be utilized for student performance predi
PaperID
2024/IJEASM/5/2024/3003

Author Name
Khushboo Dadhakar
Year Of Publication
2024
Volume and Issue
Volume 5 Issue 10
Abstract
In the context of India’s burgeoning digital economy and the paradigm shift towards skill-oriented education, the imperative for technologically proficient and industry-adaptive graduates has become increasingly pronounced. This empirical investigation critically examines the transformative potential of vocational training frameworks with a 70% hands-on instructional component within the domain of computer education, specifically tailored for students enrolled at Government Industrial Training Institutes (ITIs) in Bhopal. The study employs a methodologically triangulated approach, integrating inferential statistical analysis with qualitative stakeholder insights, to assess the multidimensional impact of practice-intensive curricula on employability metrics, cognitive-operational dexterity, and recruitment efficacy. Anchored in the tenets of experiential learning theory and cognitive constructivism, the research delineates the correlation between pragmatic skill acquisition and enhanced
PaperID
2024/IJEASM/5/2024/3003a