Volume 13 | Issue 2 |

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AI has revolutionized various industries, improving efficiency, accuracy, and decision-making. It has enabled personalized learning in education, entertainment, healthcare, agriculture, finance, manufacturing, and customer service. AI has also improved outcomes and reduced costs, leading to improved outcomes. The integration of Artificial Intelligence (AI) has revolutionized various industries, leading to significant enhancements in efficiency, accuracy, and decision-making. In education, AI has enabled personalized learning and automated grading. Entertainment has seen AI-generated content and personalized recommendations. Healthcare has experienced improved diagnosis accuracy and personalized medicine. Agriculture has benefited from precision farming and crop prediction. Finance has seen automated trading and fraud detection. Manufacturing has optimized supply chains and predictive maintenance. Customer service has become more efficient with chatbots and virtual assistants. Overall, AI has transformed these industries, leading to improved outcomes and reduced costs.

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 Keywords

AI Uses in smart cities, Advance technology, Uses in various industries

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Coolant Tank, FEM, PP Material, PP GF 10 Material, Stress and Displacement.

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Madraspattinam and Chennapattinam combined in the seventeenth century that was during the period when the British picked up ownership of the territory. The British then knew the unified town as Madarasapattinam though the people in the vicinity liked to call it as 'Chennapattinam'. From the sixteenth to the eighteenth century, Portuguese and Frenchmen led Madras. The entry of railroad in India amid the nineteenth century helped the city to interface with other urgent urban communities such as Mumbai and Kolkata, which supported the correspondence and exchanging the encompassing region.

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History, Madras Residency, Integrated Madras, Historical Significance

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Convolutional Neural Network (CNN), Road Sign Recognition, Autonomous Vehicles, Multi-language Translation, Image Classification, Deep Learning, Computer Vision , Audio Description System

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The increasing sophistication of cyber threats necessitates advanced solutions for securing website traffic. This paper explores the integration of Artificial Intelligence (AI) in predictive analytics to enhance cybersecurity through real-time website traffic analysis. The proposed framework leverages AI-driven honeypots to attract and analyze malicious bots and cybercriminals, enabling the preemptive identification and mitigation of attack vectors. Implementing a ZeroTrust Architecture (ZTA) that verifies the identity of the users and devices involved continuously, based on their behavior and contextual factors, reduces the security gap even when the users may have successfully authenticated initially. The proposed study also develops an AI-powered system for the classification of URL safety, threat prediction, and efficient management of block/unblock actions, thus streamlining website security operations. Text message authentication further enhances the security framework by verifying user access and preventing unauthorized activities. This paper highlights the transformative potential of AI in predictive analytics, offering a comprehensive approach to cybersecurity in website traffic analysis

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Artificial Intelligence (AI). Predictive analytics. Cybersecurity. Website traffic analysis. AI-driven honeypots. Malicious bots. Cybercriminals. Threat mitigation. Zero-Trust Architecture (ZTA). Continuous verification. Identity-based security. Behavioral analysis. Contextual authentication. URL safety classification. Threat prediction. Block/unblock management. Text message authentication. Unauthorized access prevention. Real-time security monitoring. AIpowered cybersecurity solutions.

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Abstract This research paper investigates the role of cyber law in promoting digital financial inclusion in rural India, focusing on legal frameworks, cybersecurity challenges, and policy gaps. As India increasingly adopts digital banking solutions, particularly in its rural sectors, the risks associated with cyber fraud and data breaches have also escalated. The paper critically analyzes the Information Technology Act, 2000, the Digital Personal Data Protection Act, 2023, and the RBI cybersecurity guidelines, evaluating their effectiveness in safeguarding digital financial transactions. Through a mixed-method approach, including surveys and interviews with rural banking users, fintech companies, and policymakers, the study explores the cybersecurity challenges faced by rural populations in India, such as lack of awareness, digital literacy, and vulnerability to online fraud. The findings indicate that while existing legal frameworks provide a foundation for securing digital transactions, their implementation in rural areas remains inconsistent. The research also identifies significant policy gaps, such as the need for stronger enforcement mechanisms and increased collaboration between banks, fintech firms, and regulators. Based on the findings, the paper proposes several policy recommendations, including strengthening cyber laws, expanding digital literacy initiatives, and leveraging AI and blockchain technologies for enhanced security. The paper concludes by highlighting the importance of cybersecurity education and technology integration for promoting inclusive digital financial services and building trust among rural users. This study contributes to the ongoing discourse on cybersecurity in financial inclusion and offers valuable insights for policymakers, financial institutions, and tech innovators in addressing the unique challenges of rural India.

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Key Words o Cyber Law o Digital Financial Inclusion o Rural India o Cybersecurity o IT Act, 2000 o Digital Personal Data Protection Act, 2023 o RBI Cybersecurity Guidelines o Fintech o Data Protection o Digital Literacy o Cyber Fraud o Blockchain o AI-based Fraud Detection o Policy Recommendations o Financial Regulations

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The integration of Natural Language Processing (NLP) in English pedagogy has significantly transformed traditional teaching methodologies. This study examines the impact of NLP-based tools on the learning outcomes of graduating students in Chandigarh. By employing qualitative and quantitative methods, this research evaluates how NLP applications enhance language acquisition, comprehension, and fluency. The findings highlight the effectiveness of NLP in personalized learning, error detection, and interactive engagement, underscoring its potential in modern education.

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Natural Language Processing, English Pedagogy, Educational Technology, Language Acquisition.

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Fibro-osseous lesions (FOLs) are a group of benign conditions involving the replacement of normal bone with fibrous tissue and mineralized components like bone or cementum-like material. These lesions primarily affect the jaws and craniofacial bones, with common types including fibrous dysplasia (FD), cemento-osseous dysplasia (COD), and fibro-osseous neoplasms. FOLs can be classified based on clinical behaviour, histology, and radiographic features. Fibrous dysplasia, which presents as monostotic or polyostotic, is characterized by a "ground-glass" appearance on radiographs. Cemento-osseous dysplasia is often asymptomatic and involves the gradual replacement of bone with fibrous and cementum-like material. Fibro-osseous neoplasms such as cementifying and ossifying fibromas are benign tumours that may cause bone expansion and deformities. Diagnosis of FOLs requires correlation of clinical, radiographic, and histopathological findings due to overlapping features. Treatment depends on symptoms and severity, ranging from observation to surgical intervention. Accurate diagnosis ensures appropriate management and optimal patient outcomes.

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Fibro-osseous lesions, Fibrous dysplasia, Cemento-osseous dysplasia.

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Abstract Background: Drug dependence occurs when need one or more drugs to function. The American Psychiatric Association (APA) used to distinguish between dependence and abuse. Abuse was considered the mild or early phase of inappropriate drug use that led to dependence. People viewed dependence as a more severe problem than abuse. It's possible to be dependent on drugs without being addicted. Dependence can be a bodily response to a substance. This often occurs if rely on medications to control a chronic medical condition. Objectives: 1) To assess the pre test knowledge of adolescent students regarding Problems of drug dependence. 2) To assess the post test knowledge of adolescent students regarding Problems of drug dependence. 3) To evaluate the effectiveness of Planned teaching programme on knowledge of adolescent students regarding Problems of drug dependence. 4) To determine the association between pre test knowledge of adolescent students regarding Problems of drug dependence and selected demographic variables. Hypothesis: H1 - There will be significant difference between pre test and post test knowledge scores of adolescent students regarding Problems of drug dependence. H2- There will be significant association between the pre test knowledge of adolescent students regarding Problems of drug dependence and selected demographic variables. Methodology: The research design consisted of pre experimental research design of one group pretest and post-test design. The population selected for the study was adolescent students of selected PU colleges at Bangalore. The study samples were 60 adolescent students and were selected by using purposive sampling technique. The development of the tool involved steps of test construction i.e. preparing the blue print, selection of items, content validation and establishment of reliability. The content validity of the questionnaire was done and modifications were done according to the suggestions given by the experts. Pre testing and reliability of the tools were done. The reliability co efficient of the knowledge questionnaire was found to be 0.893. The tool was found to be reliable. Results: In the pretest, level of knowledge of adolescent students studying in PU colleges of Bangalore before using Planned Teaching Programme. Where as in posttest level of knowledge of adolescent students studying in PU colleges of Bangalore after using Planned Teaching Programme majority 50(83.4%) of them had adequate knowledge and remaining 10(16.6%) had moderately adequate knowledge regarding Problems of drug dependence. Hence Planned Teaching Programme had increased level of knowledge. The mean difference in knowledge level of the adolescent students regarding Problems of drug dependence was -18.7 with standard deviation of 3.11 and its t-value was equal -46.61 which was highly significant as its p-values was less than 0.0001. Hence Planned Teaching Programme was effective in increasing the knowledge. Area wise comparison of mean pre-test and post-test score of the adolescent students regarding problems of drug dependence mean post-test score was higher as compared to mean pre-test score and was highly significant with p-value less than 0.0001. The study was concluded that there was a significant improvement obtained following Planned Teaching Programme on Knowledge regarding problems of drug dependence. This study was recommended that there is an immense need for educational programme to improve the knowledge regarding problems of drug dependence among adolescent students.

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 Keywords

Key words: Evaluate, effectiveness, Planned Teaching Programme, Problems of drug dependence, adolescent students

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This study investigates the influence of brand activism on consumer purchase intention, focusing on Vicks' Touch of Care campaign. By examining consumer perceptions, demographics, and the alignment between brand values and social issues, the study aims to understand how brand activism can shape consumer behavior.

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brand activism, consumer perception, purchase intention, Vicks Touch of Care, social responsibility, corporate social responsibility, cause-related marketing, authenticity, empathy, alignment, engagement, trust, reputation

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