Volume 13 | Issue 6 |

 Abstract

Art & Culture is India's strongest contribution to its rich heritage and history and is intrinsically woven into its identity. It contributes to India's GDP by generating both direct and indirect employment through handmade crafts and arts, unique only to our Country. There is another facet of art and culture which is getting recognized all over the world and that is performing arts 1-2. Be it drama or stage or acts and plays, it is getting wide attention from the customers The customers being the hall listeners , or students or the scholars of the widely recognized universities. The potential in this sector is immense .With the help of multiple fascinating techniques such as use of crafts , colours,acts ,actions and acting, teachers are devising various ways to make it easy and interesting for the students to grasp the difficult and wieldy and even called scary concepts in education confidently and interestingly .Present paper explored the various challenges faced by performing arts particularly with education field or sector in India . Thereafter it also proposed the interrelationship amongst them using ISM methodology.

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 Keywords

Teachers, drama, fine arts, stage shows, performing arts, ISM Methodology, MIC -Mac Analysis , Budding talents

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The Podcast Application is an AI-integrated, user-friendly platform designed to empower students and educators in creating and consuming high-quality, AI-generated educational podcasts. Leveraging modern web technologies such as Next.js, Tailwind CSS, and Fire- base Authentication, the application offers a seamless frontend interface and robust se- curity. At its core, the system utilizes advanced AI services, including Gemini for script generation, Aiguru for voice synthesis and image generation, Deepgram for captioning, and Remotion for dynamic video rendering. These tools collaborate to automate the entire content generation pipeline--from entering a topic to delivering a fully packaged podcast with synchronized audio, images, and captions. Users can easily log in, input a topic, and receive script suggestions. Once finalized, the script is converted into mul- timedia podcast episodes, which can be played, downloaded, or shared. The app also includes a credit-based payment model powered by PayPal, ensuring scalability and mon- etization. The backend infrastructure is supported by Convex, a reactive database that maintains real-time data updates. This ensures smooth podcast storage, retrieval, and credit management. AI orchestration within the application ensures modular execution of tasks, offering efficiency and high-quality outputs. Designed for accessibility and practical learning, the Podcast Application stands as an innovative solution to enhance learning outcomes by merging automation and creativity. Its minimalistic UI, rich AI integration, and modular workflow make it a cutting-edge tool in modern digital education.

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 Keywords

AI-Generated Content, Audio Streaming, Voice-Based Media, Educational Podcast, Text-to-Speech Integration, On-Demand Audio, Human-Computer Interaction , Deep Learning for Audio, Multimedia Content Delivery, AI-Powered Podcasting, Natural Language Processing (NLP), Audio Content Curation, Smart Recommendations ,User-Centric Design

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Tamrakalpa is one of the Herbo-mineral Kharaliya Rasayana with Tamra Bhasma as its chief ingredient, mainly stated under Yakrit-Pleeha & Udara vikaras, also indicated in other Vyadhis like Amlapitta, Sangrahani, Shotha, Jwara, Agramamsa, & acts as Sarvarogahara. It is mentioned in various Rasagranthas under same rogadhikara, wherein ingredients are same but the variation is seen in its matra and proportion of the drugs used in the preparation. So here an attempt is made to compile all the available literature regarding Tamrakalpa- its ingredients, method of preparation, therapeutic applications, dosage and further scope of studies has also been highlighted.

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 Keywords

Tamrakalpa, Kharaliya Rasayana, Yakrit- Pleeha vikaras, Udara vikaras

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The economic reforms initiated by the Government of India about two decades ago have changed the landscape of several sectors of the Indian economy. The Indian banking sector is no exception. This sector is going through major changes as a consequence of economic reforms. The role of banking industry is very important as one of the leading and mostly essential service sector. India is the largest economy in the world having more than 120 core population. Today in India the service sector is contributing half of the Indian GDP and the banking is most popular service sector in India. The significant role of banking industry is essential to speed up the social economic development. Banks plays an important role in the economic development of developing countries. Economic development involves investment in various sectors of the economy. The economic reforms have also generated new and powerful customers (huge Indian middle class) and new mix of players (public sector units, private banks, and foreign banks).they are also nationalization to privatization of banks and now increasing numbers of foreign banks in India. In this paper an attempt has been made to identify the general sentiments, challenges and opportunities for the Indian Banking Industry. This article is divided in three parts. First part includes the introduction and structure of Indian banking industry. The second part discusses the various challenges and opportunities faced by Indian banking.

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 Keywords

Liberalization, Privatization, Globalization, Governance, Risk Management, Associate, Grievances,

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Abstract Performance management is a critical function in human resource management that influences employee development, organizational productivity, and overall success. This paper explores the relationship between performance management and employee development by analyzing key performance management practices, their effectiveness, and the role of feedback mechanisms in employee growth. The study further examines how organizations can implement robust performance management systems to enhance employee skills, motivation, and career advancement. The research is based on a comprehensive review of literature, industry case studies, and theoretical frameworks that connect performance management to employee development.

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Performance Management, Employee Development, Feedback Mechanisms, Career Growth, Human Resource Management

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Abstract The integration of Artificial Intelligence (AI) and generative algorithms into fashion illustration is reshaping creative workflows, expanding accessibility to design tools, and challenging traditional aesthetic boundaries. This paper explores the diverse opportunities presented by AI-generated fashion illustrations across design education, product development, personalization, and sustainable innovation. Simultaneously, it critically examines ethical challenges, including authorship, originality, labor displacement, cultural appropriation, and algorithmic bias. Employing a qualitative mixed-method approach and a review of advanced AI models such as GANs, diffusion models, and transformers, the study proposes the F.A.S.H.I.O.N. AI Ethics Framework to guide responsible integration. The research contributes a globally contextualized and original taxonomy of AI in fashion illustration--an area previously under-examined in academic literature.

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 Keywords

Artificial Intelligence (AI), Generative Fashion Illustration, Fashion Design Technology, AI Ethics, Sustainable Innovation, Cultural Appropriation, Digital Creativity

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The terms "environment" is used in different senses. In broad sense, environment means everything external to an organism that affects it. Environmental pollution has direct as well as indirect effects on human health. The World Health organization in its report has emphasized that diseases can be prevented through healthy environment. WHO report that more than 33% of diseases in children below 5yrs.are due to Environmental exposures? Environmental pollutants can cause health problems like respiratory diseases, heart disease, and some types of cancer. People with low incomes are more likely to live in polluted areas and have unsafe drinking water. Anthropogenic air pollution is one of biggest public health hazards worldwide, given that it accounts for about 9 million deaths per year. So in this paper, researcher attempts to study how Environmental Air pollution impacts the human health problems basically of North East India.

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Environmental, Pollution, Human health, Diseases and Income.

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Urban flooding was considered a concern of municipal and local governance only till the 1990s,but currently it draws the attention of disaster and environmental scientists. Urban floods have attained the status of disaster due to high vulnerability and risks. It leads to extreme fatalities and enormous economical losses in every country. Especially in developing countries like India, where population density is high and has enormous population growth during the last few decades due to high migration in urban areas and have a lot of issues about uncontrolled and inappropriate development .Flood is a phenomenon occurring from time to time in all rivers. An attempt has been made in this project to study the rainfall in urban areas & the effects area and solution of flash floods.

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Frequency, Extreme rainfall depth, Depth area duration, Probable maximum temperature, Rate of infiltration, Infiltration Capacity, initial infiltration capacity, limiting constant value of infiltration

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Deep learning is one of the most prominent areas of machine learning that relies entirely on artificial neural networks. Since neural networks are designed to replicate the functioning of the human brain, deep learning may also be thought of as a form of brain mimicking. Owing to its capacity for data-driven learning, deep learning (DL) technology--which has its roots in artificial neural networks (ANNs)--has gained significant traction in the computer community and finds extensive use across a wide range of industries, including the field of cybersecurity, health care, visual identification, and text analytics. However, it is not easy to develop a suitable deep learning model because of its dynamic nature of data. In many different fields, deep learning approaches have become successful tools for resolving challenging issues.This paper offers a systematic and thorough analysis of deep learning approaches, which includes a nomenclature that takes into account different kinds of real-world challenges, such as supervised and unsupervised ones. Moreover, this article also includes a deep study of the core deep learning approaches, with particular emphasis on generative adversarial networks (GANs), long short-term memory networks (LSTMs), recurrent neural networks (RNNs), and convolutional neural networks (CNNs). Deep learning methods still have difficulties with interpretability, resilience to adversarial attacks, and scalability to big datasets, despite their amazing success. More explainable models, adversarial training for increased robustness, and effective training methods on large-scale datasets are some of the areas of future research. To gain a competitive edge in the future, organisations aiming to utilise artificial intelligence must comprehend and effectively utilise deep learning methodologies.

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 Keywords

Machine Learning, Deep learning, SVM, KNN

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The exponential growth of Online Social Media (OSM) platforms has provided users with dynamic means of communication, content sharing, and interaction. However, this growth has also attracted malicious entities that exploit these platforms for spamming, spreading misinformation, and executing fraudulent activities. Traditional content-based and user-behavioral spam detection techniques often fall short in detecting sophisticated spam patterns. In response, network-based approaches have gained significant traction by leveraging the structural and relational properties of social networks. This comprehensive review explores the spectrum of network-centric methodologies used in spam detection, including graph-based models, community detection algorithms, propagation patterns, and trust networks. The paper categorizes and analyzes the state-of-the-art techniques, evaluates their strengths and limitations, and highlights emerging trends in network science applied to OSM spam detection. Furthermore, it discusses real-world datasets, performance metrics, and the integration of hybrid frameworks combining machine learning with network-based insights. This review serves as a valuable resource for researchers and practitioners aiming to develop robust and scalable spam detection systems in the dynamic landscape of online social platforms.

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 Keywords

Online Social Media (OSM), Spam Detection, Network-Based Approaches, Graph Theory, Community Detection, Propagation Modeling, Trust Networks, Hybrid Frameworks, Machine Learning, Social Network Analysis

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Creative Commons Attribution 4.0 and The Open Definition