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Daily Archives: November 27, 2025

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AI in Everyday Life: How Artificial Intelligence Shapes Modern Applications

Authors: Ishaan Iyer, Abhijeet Anand Aiwale

Abstract: From voice assistants and recommendation systems to navigation tools and personalized learning, AI shapes how people live, work, and interact with technology. This rapidly growing area of research has transformed AI from a concept of the future to a technology that permeates almost every aspect of human life. This paper will discuss the integration of AI into everyday applications, identify common areas where students interact with AI unknowingly, and examine its positive impacts and potential ethical concerns. This study is based on a survey among first-year engineering students and a review of secondary literature. The results show that while AI enhances convenience and efficiency, the awareness of its mechanisms and ethical issues remains limited.

DOI: https://doi.org/10.5281/zenodo.17733691

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Smart Gaming Supervision System

Authors: Goutami Bankapure, Rakshita Giri, Nandini Khadakhade, Sneha Teli, Aishwarya shengar, pallavi pandhare

Abstract: The rapid growth of digital gaming has led to increasingly complex behavioral challenges, particularly among adolescents and young adults. Excessive gameplay, exposure to toxic communication, and unhealthy engagement patterns continue to raise concerns regarding digital well-being. Existing monitoring tools typically offer only partial solutions, such as parental controls or time-restriction features, and lack the ability to analyze user behavior holistically. To address these gaps, this research presents the Smart Gaming Supervision System, an integrated AI-driven framework designed to promote healthier gaming habits while reducing abusive interactions. The system combines real-time gameplay duration monitoring, multilingual text toxicity detection, voice-based abusive speech recognition, motivational prompt generation, and behavior-based reward mechanisms. Leveraging state-of-the-art technologies such as XLM-R transformer models for text analysis, Whisper-based speech-to-text pipelines, and a rule-based behavioral engine supported by SQLite storage, the system continuously evaluates player behavior across multiple channels. Real-time alerts, warnings, and positive reinforcement are generated to encourage self-regulation and promote responsible gaming. Experimental evaluation demonstrates that the system achieves high accuracy in toxicity detection, effective time-limit enforcement, and improved user engagement through positive reinforcement techniques. The proposed solution highlights the potential of combining machine learning, psychology-driven reward systems, and digital wellness principles to create a comprehensive, scalable, and user-centric gaming supervision platform. This work contributes a novel and practical approach toward fostering safe, balanced, and respectful digital gaming environments.

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Invest Wise – Ai Driven Investment Portfolio Recommendation System Based On Risk Profiling And Market Analytics

Authors: Ayush Sadanand Bhuyar, Bhakti Kiran Kumar Yete, Jayendrasin Rathod, Jayendrasin Rathod, Mr. Yatin Shukla

Abstract: The growth of retail participation in financial markets has created a strong need for intelligent, transparent and easy-to-use investment advisory tools. Beginner investors in particular often struggle to understand their own risk-bearing capacity and to select a suitable mix of equity, bonds and cash instruments. This paper presents INVESTWISE, an AI‑driven investment portfolio recommendation system that models user risk profiles using questionnaire responses and combines them with live market fundamentals such as P/E ratio, beta, dividend yield and sector information. The backend is designed using a hybrid MongoDB and relational database approach, while the frontend delivers a modern web dashboard that visualises allocations, recommended stocks and market movers. Experimental evaluation on simulated user profiles and live NSE data demonstrates that the system can generate consistent, risk-aligned portfolios with low response time, making it suitable for real‑time decision support.

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Advanced Cooling Systems for Nuclear-Powered Data Centers

Authors: Girish Kishor Ingavale

Abstract: The demand for computational power in nuclear-powered data centers requires effective thermal management. Traditional cooling methods are inadequate for the heat generated in these environments. This article examines advanced cooling systems for nuclear-powered data centers, focusing on energy efficiency, safety, and performance. Analyzed technologies include liquid cooling, immersion cooling, free cooling, and hybrid systems. Findings show these systems reduce energy consumption by up to 50%, improve PUE by 20-35%, and enhance computational performance by 15-20%. They also reduce server failure rates and improve reliability. Initial investment is offset by long-term energy cost savings and reduced maintenance. This article highlights the importance of advanced cooling systems for sustainable and efficient operation of nuclear-powered data centers.

DOI: https://doi.org/10.5281/zenodo.17731414

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