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The Central Bank is calling it| Call for Paper|

Ale Journal of Sustainable Intelligent System Applications

Editor: S. Silvia Priscila


pISSN: XXXX-XXXXeISSN: XXXX-XXXX


2026 Vol.1 No.1

Title and author(s) Pages
CampusConnect: A Data-Driven Web Framework for Smart Campus Operations Management K. Adivigneshwaran, J. Arun, M.S. Om Akash, R. Regin, R.L. Shyja, Robert Balku This paper presents the design and implementation of CampusConnect, a centralized campus platform developed to address the inefficiencies of traditional, manually driven, paper-based service systems. This system integrates three critical student-based service systems: the hostel management system, the canteen ordering…
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1-15
AI-Driven Student Performance Prediction Using Behavioral, Academic and Lifestyle Analytics B. Rithuja Sai Sri, R. S. Jessie Bernice David, B. Sowmya, R. Regin, K. Senthamilselvan, Prasanna Ranjith Christodoss Modern education relies on student success prediction due to personalised learning and early academic support. Most traditional evaluation methods rely on exam scores, which don't necessarily reflect student learning or its effects. This research uses AI to link academic data…
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16-34
Multilingual NLP and Voice-Based System for Predicting Scheme Eligibility and Providing Guidance J. Angelin Jeba, S. Rubin Bose, O. Jeba Singh, R. Regin, R. Jesfer, Jouma Ali Al-Mohamad Citizens have a problem accessing government programs because of the dispersion of information, lack of clarity on the application eligibility, and inadequate assistance when applying. Such issues often deny beneficiaries the support and opportunities to which they are entitled. To…
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35-47
Autonomous Cloud Engineering Mechanism for Elastic Service Optimization in AI Integrated Enterprise Platforms Jeyakumar Ramachandran This research focuses on the design and deployment of an Autonomous Cloud Engineering Mechanism (ACEM) to manage the dynamic computational load of enterprise systems integrated with AI. While manual scaling approaches have typically proven inadequate in today’s corporate landscape, which…
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48-58
Machine Learning and Mathematical Modeling for Pattern Recognition in Large-Scale Numerical and Time-Series Datasets Khin Myo Myo Minn, Hlaing Htake Khaung Tin, M. Sakthivanitha, J. Anciline Jenifer, I. Meireles Chrisostomo The fast advancements in the field of digital technologies have resulted in the generation of tremendous volumes of numerical and time-series data in different application fields, ranging from financial markets, medicine, climate research, to manufacturing processes and social networks. This…
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59-67