Daily Archives: March 6, 2026

Authors: Ms. Dipti Rathod

Abstract: Artificial Intelligence (AI) has significantly transformed the field of computer vision by enabling machines to interpret and analyze visual data with high accuracy and efficiency. Computer vision, a major branch of AI, focuses on developing systems that can acquire, process, and understand images and videos in a manner similar to human vision. With the advancement of machine learning and deep learning techniques—particularly Convolutional Neural Networks (CNNs)—computer vision systems have achieved remarkable improvements in tasks such as image classification, object detection, facial recognition, and image segmentation. The integration of AI into computer vision has led to widespread applications across various industries, including healthcare, autonomous transportation, security and surveillance, retail, agriculture, and manufacturing. In healthcare, AI assists in medical image analysis and disease detection; in transportation, it powers self-driving vehicles; and in industrial sectors, it enhances quality inspection and automation. Despite these advancements, challenges such as the need for large labeled datasets, high computational costs, security risks, bias in algorithms, and ethical concerns remain significant issues in the computer industry. This research examines the role of artificial intelligence in the development of computer vision technology, explores its major applications, and highlights the key problems that need to be addressed. The study concludes that while AI-driven computer vision has revolutionized modern computing, continued research, ethical governance, and technological innovation are essential to fully realize its potential and ensure responsible implementation.

 

 

Published by: vikaspatanker

Authors: Nagaraju Goshikonda

Abstract: The digitalization of critical infrastructure sectors of the U.S. economy such as energy, transportation, healthcare, and defense has expanded the cyber-attack surface at a rapid pace. The old models of perimeter-based security are no longer effective against complex attacks, like advanced persistent attacks (APTs), insider attacks and AI-assisted cyber-attacks. This paper will suggest AI-based Zero Trust Security Architecture (ZTSA) adapted to secure the critical infrastructure in the United States. The framework incorporates behavioral analytics, federated learning, and adaptive risk scoring, that allow one to continue verification and intelligent response to threats. The predictive and generative AI models are utilized to simulate the attack scenario, improve anomaly detection, and automate policy enforcement. Experimental assessment based on simulated critical infrastructure datasets is shown to have a higher detection rate of 95.8 and a 30% lower rate of false positives than traditional zero-trust systems. The outcomes show that AI-enhanced zero-trust models will be capable of mitigating critical infrastructure in the US to a considerably greater extent in terms of resilience, scalability, and mitigation of threats in real-time.

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Published by: vikaspatanker

Authors: Dipak Kadve, Vaishali Suryawanshi, Aditi Choure, Pratibha Ghodake

Abstract: In recent years, digital streaming platforms have become an integral part of students’ daily routines. Among various forms of online entertainment, anime has gained significant popularity among college students in urban Indian cities, including Pune. While entertainment media can provide relaxation and emotional engagement, concerns are often raised regarding excessive viewing habits and their potential academic implications. The present study explores the relationship between anime consumption patterns and academic productivity among college students in Pune. A structured online questionnaire was administered to 150 respondents across different academic disciplines. The study examined variables such as daily viewing duration, binge-watching behavior, late-night streaming habits, sleep duration, study hours, and self-reported academic performance. The findings suggest that moderate anime consumption does not significantly affect academic productivity. However, extended late-night viewing and frequent binge-watching were associated with reduced study hours and irregular sleep patterns. The study highlights the importance of balanced digital engagement and responsible time management among students.

 

 

Published by: vikaspatanker

Authors: Dr. Snehal Godse, Mr. Prathameshsingh U. Rajput, Prof. Apurva Shende

Abstract: Artificial Intelligence (AI) has evolved from task specific systems to increasingly adaptive and socially responsive agents. As research advances toward Artificial General Intelligence (AGI), a transformative shift is anticipated not only in computational capability but also in human–machine relationships. This study explores the dual nature of AGI—conceptualized as “Syrup and Sword”—wherein emotionally intelligent systems may deepen human closeness while simultaneously introducing existential and psychological risks. Drawing upon attachment theory, alignment research, and human–computer interaction (HCI) scholarship, this paper develops an integrative conceptual framework linking AI capability progression with attachment intensity and societal outcomes. A mixed-method research design is proposed, combining qualitative thematic analysis and quantitative experimental surveys to examine emotional scaling from Narrow AI to AGI-level systems. The study identifies key drivers of attachment such as empathy simulation, memory continuity, adaptive responsiveness, and perceived moral agency. It further analyzes risks including emotional dependency, anthropomorphic projection, manipulation, and value misalignment. The proposed “Syrup vs. Sword Framework” offers a structured lens to evaluate how increasing cognitive and affective sophistication in AGI could produce both enhanced well-being and destabilizing consequences. The findings contribute to interdisciplinary discourse by bridging psychological, ethical, and technical perspectives, emphasizing the necessity of emotionally aware governance in future AGI development. Index Terms—Artificial General Intelligence (AGI), Human–AI Attachment, AI Ethics, Alignment Problem, Emotional AI, Existential Risk, Human–Computer Interaction.

 

 

Published by: vikaspatanker