Volume 12 | Issue 4 |

 Abstract

With the surge of online video platforms in the digital age, the risk of content piracy has significantly increased, posing serious challenges for content creators and distributors. This research aims to counteract unauthorized distribution by developing a system that matches video frames across various online platforms. Using advanced computer vision techniques, we propose a robust and scalable framework that combines image processing and machine learning to accurately identify and match frames from moving images, regardless of differences in format, resolution, and compression. Our framework includes essential components such as feature extraction, frame hashing, and deep learning-based similarity assessment to achieve high precision and recall in detecting pirated content. Extensive experiments on diverse datasets demonstrate our approach's superior accuracy and computational efficiency compared to existing methods. This study offers a comprehensive solution to video piracy, providing valuable insights into the development of cross-platform content identification systems. By enhancing the security and reliability of digital media distribution, our work contributes to protecting the rights of content creators and ensuring the integrity of online video content.

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 Keywords

Cyber Security, Digital Piracy, Machine Learning, Computer Vision

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Artificial Intelligence (AI) has emerged as a cornerstone within the domain of cybersecurity, presenting advanced solutions to combat the ever-growing complexity of cyber threats. This abstract delves into the foundational principles of AI within the context of cybersecurity, emphasising its pivotal role, diverse applications, and potential implications.In recent years, AI has revolutionised cybersecurity practices by enabling automated threat detection, rapid response mechanisms, and enhanced predictive analytics. This chapter is a comprehensive introduction to the combination of AI in modern cybersecurity strategies. It elucidates the importance of AI-driven technologies in fortifying cyber defences and lays the groundwork for a deeper understanding of their application across various security domains.The introduction outlines the elemental concepts of AI, providing insights into machine learning, linguistic communication processing, and other core AI techniques relevant to cybersecurity. It explores how AI algorithms can analyse vast amounts of knowledge, identify patterns, and detect anomalies, thereby bolstering threat detection capabilities and proactive defence mechanisms.

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ARTIFICIAL INTELLIGENCE: A MODERN TOOL TO REINFORCE CYBERSECURITY

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Introduction: Pseudomonas aeruginosa is a Gram-negative bacterium with resistance to many antibiotics, causing severe infections in immunocompromised individuals. Resistance patterns vary geographically and over time, with beta-lactams showing high resistance to penicillins and cephalosporins, carbapenems increasing resistance, aminoglycosides having variable susceptibility, fluoroquinolones being common, and polymyxins reserved for multidrug- resistant cases. Management involves prevention, culture, prompt antimicrobial therapy, and combination therapy. In our present study, we will study the antibiotic sensitivity pattern in P. aeruginosa. Aim & Objectives: The aim and objectives of present study is to isolate Pseudomonas aeruginosa among various samples and estimate its antibiotic sensitivity pattern. Material & Methods: The study analysed antibiotic sensitivity patterns in Pseudomonas aeruginosa from clinical samples, using 50 non-repetitive isolates from outpatient and inpatient departments. The modified Kirby-Bauer disc diffusion method was used for antimicrobial susceptibility testing in the Department of Microbiology, National Medical College, Birgunj, Nepal, between 1 st July 2022 and 30 th June 2023. Results: Pseudomonas aeruginosa was found to be most abundant in pus samples, followed by ear swabs, urine, sputum, E.T. secretion, and blood. Out of 50 isolates, the most sensitive were Polymyxin-B (98%), Colistin (98), Imipenem (89%), Cefeparazone/Salbactum (86%), Meropenem (84%), Pipercillin/Tazobactum (82%), ciprofloxacin (72%), and cefepime (38%). Conclusion: The study identifies a drug for Pseudomonas aeruginosa infection, focusing on species-level identification and resistance mechanisms, promoting judicious use of chemotherapeutic agents

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 Keywords

Pseudomonas aeruginosa, Polymyxin-B, Colistin, Infection

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This article brief focuses on the energy dimension of India-Central Asia Relations and fulfillment of India's energy needs. Central Asia's vast energy resources and India's growing energy demand combine to form India's aspirations of expanding energy relations with the region. Article argues that the Indian government and scholars are focused quite narrowly on the energy reserves, i.e., stocks of different resources like natural gas and uranium. Due to their narrow focus, they do not account sufficiently for the energy infrastructure within Central Asia, namely pipelines that would allow energy sources to be efficiently extracted and transported to India.

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Energy Relation between India and Central Asia: A Review

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Mukt Evam Durasth Shiksha me Namankit Shiksharthiyo ki pristhabhumi evam Pathyakarma lokpriyata-Ek Vishleshan

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Mukt Evam Durasth Shiksha,Siksharthiyo ki prushtbhumi,namakan,pathyakram lokpriyata

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Ethnographic approaches have recently emerged as promising methodologies in educational research, offering rich insights into the social and cultural dynamics of learning environments. However, their application within pharmacy education remains relatively unexplored. This systematic review aims to fill this gap by synthesizing the existing literature on the practical applications of ethnographic methods in pharmacy education. The review highlights implications for pharmacy educators and institutions, emphasizing opportunities to enhance teaching practices, foster inclusive learning environments, and inform curriculum development and policy-making. Recommendations for future research and practice are provided, advocating for longitudinal studies, examination of inter professional collaborations, and sharing of best practices. Ultimately, this systematic review underscores the significance of ethnographic approaches in advancing pharmacy education and calls for further exploration and application within the field.

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Ethnography, Pharmacy education, teaching methods, Institutional development

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Contract farming has been prevalent in agriculture, especially in countries like India. The outbreak of COVID-19 in 2020 significantly disrupted the functioning of contract farmers, posing various challenges to their livelihoods. At the same time, the pandemic crisis was seen as an opportunity for corporate penetration into agriculture by the three farm laws. This article analyzes the impact of COVID-19 on contract farming, how contract farmers coped with the pandemic, and the challenges faced by small farmers during the pandemic.

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Contract farming, COVID-19, Farm laws, Small farmers.

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This study explores the impact of green marketing practices on consumer spending patterns within shopping malls in the city of Haryana, India. Utilizing a quantitative research approach, data was collected from a diverse sample of 100 consumers across different demographics, and ANOVA analysis was employed to examine the impact of Green marketing practices on consumer decision-making. The findings revealed significant differences in consumer spending patterns across malls with varying levels of Green marketing practices. The study underscores the substantial influence of environmentally conscious initiatives on shaping consumer behavior. Based on these results, practical recommendations are offered, emphasizing the enhancement of Green marketing initiatives, tailored marketing strategies, educational campaigns, continuous monitoring, and collaboration among shopping malls. The insights derived from this research contribute to a nuanced understanding of the relationship between sustainable marketing practices and consumer behavior, providing valuable guidance for the strategic development of environmentally responsible initiatives within the retail sector.

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Green Marketing, Consumer Behaviour, Consumer Spending Patterns, Retail products

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Creative Commons Attribution 4.0 and The Open Definition

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The treadmill bicycle represents an innovative device that merges traditional exercise equipment with a transportation mechanism. It works on the idea of transforming forward momentum from motion of humans without the use of electricity. This combines a bicycle frame with a treadmill platform such that when a person walks on the treadmill, the action goes backward and the bicycle moves forward via a chain system. By harnessing kinetic energy from the user's physical effort, it eliminates the need for external power sources or electrical assistance. This unique combination promotes health and lessens dependency on fossil fuels while providing an environmentally friendly, independent, and effective means to commute or work out. It even gives off an innovative perspective on transportation. The treadmill bicycle is an innovative and sustainable way to move and keep active without relying on electricity or other external power sources. It represents the merging of exercise and mobility.

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Treadmill, bicycle, rollers

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This research tries to explore the link between Equal Employment Opportunity (EEO) policies and the diversity in recent work surroundings. It purposes to acknowledge the importance of EEO framework in enhance the diversity, evaluate their effect on operational culture, employee contribution, and entire performance. Employing a combination of actual evidence and conceptual frameworks, this paper tries to define the native connection between EEO compulsory and the facilitation of workplace diversity.

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Equal Employment Opportunity, Workplace Diversity, Organizational Culture, Employee Engagement, Performance, Inclusion, EEO Policies

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Creative Commons Attribution 4.0 and The Open Definition