Volume 14 | Issue 5 |

 Abstract

This research investigates the transition from traditional, school-based physical education (PE) to the modern "gym culture" popular among college students today. Historically, PE focused on collective values like teamwork, discipline, and general health. However, modern students now show a strong preference for commercial fitness centers, bodybuilding, and social-media-influenced workouts. This shift reflects deeper changes in youth identity and the influence of digital culture. Drawing on sociological theories from thinkers like Bourdieu, Foucault, and Goffman, the study argues that the gym has become a vital social space for "building a brand" and performing social status, rather than just a place for exercise. The paper explores how factors like gender, urbanization, and social media shape these preferences. While the rise of gym culture has increased overall health awareness, it has also introduced negative pressures, including body image anxiety, commercialization, and social exclusion. The study concludes that educational institutions should blend the structured benefits of traditional PE with modern fitness trends to create a more inclusive and healthy environment for students.

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 Keywords

Gym, Sports, Physical Education

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The emergence of Artificial Intelligence (AI) has catalyzed a paradigm shift across various sectors, most notably within the realms of education, healthcare, and the specialized domain of sports sciences. By leveraging sophisticated computational power, AI facilitates a move away from "one-size-fits-all" approaches toward highly individualized learning environments. These systems offer intelligent tutoring, instantaneous performance feedback, and forward-looking predictive analytics that empower both educators and practitioners to make data-driven decisions with unprecedented precision. In the context of health knowledge acquisition, AI serves as a critical bridge between complex medical data and the end-user. Through the deployment of sophisticated chatbots, AI-driven virtual assistants, and advanced diagnostic software, students and healthcare professionals can access and synthesize accurate medical information more efficiently than ever before. These adaptive learning systems ensure that health literacy is not just disseminated but is tailored to the specific cognitive needs and existing knowledge gaps of the individual. Furthermore, within the sphere of sports education, AI is revolutionizing traditional coaching methodologies. By integrating computer vision and machine learning, AI enables meticulous skill analysis, real-time biomechanical monitoring, and the development of proactive injury-prevention protocols. These technologies allow for a granular level of athlete training that was previously unattainable, ensuring that performance optimization is balanced with the physical well-being of the student-athlete. Health, Artificial Intelligence, Sports

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Health, Artificial Intelligence, Sports

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Quinoline-thiosemicarbazones(QTSCs),Chemosensors,Heavy-metal detection Fluorescence spectroscopy,Structure-activity relationships (SAR)

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The emergence of Artificial Intelligence and deep learning algorithms has revolutionized digital media in their entirety by generating incredibly real- istic images, videos, and audios that are artificial or fake. These are generated using advanced deep learning algorithms such as GANs and autoencoders. They are extremely difficult to distinguish between reality and fiction. However, they prove to be advantageous in entertainment, filmmaking, and virtual reality tech- nology applications but are equally harmful when misused, posing a great threat to people and spreading misinformation. In this paper, we discuss various Artificial Intelligence-based techniques utilized in detecting deepfakes in images and videos, as well as current developments in this domain. We offer an introductory insight into a generic deepfake detection technique and identify some crucial challenges in this domain.

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Deepfake Detection o Artificial Intelligence o GANs o Deep Learning o CNN

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Tax computation and filing are among the most critical yet cumbersome financial responsibilities for individuals and small businesses. The Indian tax system, governed by the Income Tax Act of 1961, encompasses a complex web of income categories, deduction provisions, exemptions, and frequently updated tax slabs that make the process highly prone to errors when performed manually. Millions of taxpayers across the country struggle annually to correctly compute their tax liability, identify eligible deductions, and complete their returns before the stipulated deadlines

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ClearTaxers-AI enables taxpayers to go from uploading their financial documents to receiving a comprehensive, filing-ready tax report in a fraction of the time it would take using manual or traditional software methods.

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The rapid digital transformation in Karnataka's modern business enterprises has significantly enhanced operational efficiency and market reach. However, this shift has also exposed organizations to escalating cyber security threats, including data breaches, ransom-ware attacks, phishing scams, and insider threats. As businesses in Karnataka increasingly adopt cloud computing, IOT, and AI-driven technologies, the complexity of cyber risks intensifies, necessitating robust security frameworks. This research paper examines the key cyber security challenges faced by enterprises in Karnataka, including inadequate security infrastructure, lack of employee awareness, regulatory compliance gaps, and emerging threats from advanced persistent threats (APTs). The study also explores mitigation strategies such as AI-based threat detection, cyber security training, and adherence to global standards like GDPR (General Data Protection Regulation) and India's DPDP (Digital Personal Data Protection) Act. By analysing real-world case studies and industry trends, this paper provides actionable insights for businesses to strengthen their cyber resilience and safeguard critical assets in an evolving threat landscape.

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 Keywords

Cyber security, Digital Transformation, Karnataka Enterprises, Data Breaches, AI in Security, Regulatory Compliance, Cyber Resilience.

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The integration of Artificial Intelligence (AI) in recruitment and talent acquisition has marked a significant transformation in how organizations identify, assess, and hire candidates. This paper explores the impact of AI technologies, such as chatbots, automated resume screening, predictive analytics, and AI-powered video interviews, on the recruitment process. It delves into the efficiency, cost-effectiveness, and bias reduction that AI offers while highlighting ethical concerns like algorithmic bias, lack of human touch, data privacy, and transparency. The research further examines case studies of companies like Unilever, Hire Vue, and IBM, showcasing how AI tools have streamlined their hiring practices, improved candidate experience, and enhanced decision-making.

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AI in recruitment, Talent acquisition technology, Artificial Intelligence in hiring, AI-powered recruitment tools, Automated resume screening, Candidate sourcing with AI, HR analytics with AI, Future of recruitment technology, End-to-end recruitment automation, AI and workforce planning, AI in job matching, Automated interview analysis. AI in diversity hiring, Recruitment process innovation, Talent pool management with AI, Machine learning hiring algorithms, Candidate profiling with AI, Recruitm

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Artificial Intelligence is enabling personalized learning, which is quickly changing the face of higher education, enhancing academic efficiency, and automating tasks. This study investigates students' perceptions of AI integration in higher education, with a specific focus on engagement, trust, and ethical concerns. Conducted in Shivamogga, India, the study adopts a quantitative and descriptive approach, collecting primary data from 50 college students using structured questionnaires. The findings reveal that students widely use AI tools like ChatGPT, Gemini, and Grammarly, appreciating their role in improving academic performance, understanding, and feedback. However, notable concerns include data privacy, reduced human interaction, and over-reliance on AI, which may hinder critical thinking and job security. An independent t-test confirmed no significant gender-based differences in perceptions. The study suggests the necessary for ethical AI integration, inclusive training, and transparent usage policies. These insights can guide educators, policymakers, and AI developers in implementing student-cantered AI strategies that promote equity, efficiency, and ethical use in academic environments.

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Artificial Intelligence in Education, Student Perception, AI-Based Learning Tools.

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The adoption of Artificial Intelligence (AI) in cybersecurity has transformed how organizations detect and respond to digital threats. AI systems process vast data in real-time, identify anomalies, and automate responses with great speed. However, this integration also introduces new risks--such as adversarial attacks, data poisoning, and the misuse of AI by malicious actors. The opaque nature of AI models complicates accountability, and reliance on high-quality data raises ethical and privacy concerns. This paper explores these challenges, presents real-world cases like Microsoft's Tay and IBM's DeepLocker, and suggests mitigation strategies such as adversarial training, secure data pipelines, and regulatory frameworks. While AI enhances cybersecurity, responsible deployment is crucial to prevent new vulnerabilities

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Cyber Security Challenges with AI Adoption

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The integration of Artificial Intelligence (AI) into performance management systems is transforming how organisations assess, monitor, and enhance employee performance. This study aims to explore the real-world applications of AI in performance management among organisations operating in Karnataka, India. Using a structured, questionnaire-based research design, primary data was collected from employees, HR professionals, and managers across various sectors including IT, finance, education, and manufacturing. The study investigates the extent of AI adoption, the perceived benefits and challenges, employee attitudes towards AI-driven evaluations, and concerns related to transparency, bias, and data privacy. Findings indicate that while AI tools have improved the objectivity and efficiency of performance reviews, concerns persist regarding ethical implications and the need for human oversight. The study contributes valuable insights into the practical implementation of AI in the Indian workplace and offers recommendations for more effective, ethical, and employee-friendly performance management systems.

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 Keywords

Artificial Intelligence, Performance Management, AI tools, HR Technology, Employee Appraisal, AI in HR, Organisations in Karnataka, Questionnaire-Based Research, Ethical Concerns, Feedback, HR Innovation

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