Volume 13 | Issue 5 |

 Abstract

Cloud operating systems face challenges in managing dynamic workloads for applications like e-commerce and streaming, processing over 2.5 quintillion bytes daily. Traditional static and heuristic-based resource allocation methods often lead to 40% resource wastage or 20-30% latency spikes, failing to adapt to fluctuating demands. This paper proposes a hybrid framework integrating reinforcement learning and large language models to dynamically allocate CPU, memory, and network resources. A lightweight large language model, similar to DistilBERT, analyzes system logs and user requests to predict resource demands with 92% accuracy, updated every 10 seconds. A reinforcement learning component, using a Deep Q- Network with a three-layer neural network, optimizes allocations based on these predictions and real-time metrics. Simulations on a 10-server testbed with 100 virtual machines demonstrate a 32% improvement in resource utilization, 18% reduction in latency to 75 ms, and 12% decrease in energy consumption to 0.70 kWh compared to heuristic methods. Throughput increased by 31%, handling 12,500 requests per second. The framework outperforms static, heuristic, and reinforcement learning-only approaches, particularly under high loads of 15,000 requests per second. Challenges include computational overhead of large language models, consuming 10% CPU, and model interpretability, critical for 80% of administrators. Future work focuses on lightweight algorithms and multi-cloud scalability to enhance efficiency and practicality in dynamic cloud environments.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Cloud Computing, Resource Management, Reinforcement Learning, Large Language Models, Dynamic Allocation, Artificial Intelligence

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Hate crimes are bias-motivated offenses targeting individuals or groups based on caste, religion, ethnicity, gender, or other protected identities. These acts inflict not only direct harm on victims but also create a climate of fear and exclusion within communities. While countries like the United States and members of the European Union have enacted comprehensive hate crime legislation and developed specialized enforcement mechanisms, India continues to rely on fragmented provisions under general criminal law and selective statutes such as the Scheduled Castes and Scheduled Tribes (Prevention of Atrocities) Act, 1989. This paper critically examines the limitations of India's existing legal framework and compares it with international best practices to highlight systemic gaps in definition, enforcement, and victim protection. It further explores the role of civil society organizations, the tension between hate speech regulation and free expression, and the need for institutional reforms. The study calls for the enactment of a dedicated hate crime law in India, supported by specialized training, reliable data systems, and victim-centric mechanisms. Addressing hate crimes requires not only legal reform but also a holistic, rights-based approach that affirms constitutional values and social justice.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Hate crimes, Indian Penal Code, SC/ST Act, bias-motivated violence, legal reform, enforcement challenges, human rights, freedom of expression

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Government's microfinance initiatives, increases financial inclusion, business performance and socio-economic empowerment of entrepreneurs among small scale enterprises in average income regions and thereby provides boost to economy. This research studies the effectiveness of microfinance initiatives in empowering entrepreneurs in Amravati District, Maharashtra. Using a mixed-methods approach with survey data and strategic analysis, the findings indicate significant impacts on financial inclusion (R2 = 0.298), business performance (R2 = 0.040), and socio-economic empowerment (R2 = 0.223). On other hand high and variable interest rates, documentation delays, and poor skill development programs pose challenges that obstruct microfinance initiatives from reaching their full potential. The scope of study includes 120 women entrepreneurs who have undertaken loan under Pradhan Mantri Mudra Yogna. The study suggests enhanced outreach, simple loan processes, and effective training programs to optimize benefits for women entrepreneurs.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Key Words: Microfinance Initiatives, Financial inclusion, Business Performance, Socio-Economic Empowerment.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

In recent years, artificial intelligence and analytics have dominated all new inventions and technology. With the advent of Internet and mobile banking platforms, digital transactions gained considerable acceptance, resulting in a progressive decrease in "footfall in branches." Customers of today need a flawless experience across all platforms, and highly customized services are urgently needed. However, communicating with and comprehending the distinct needs of these clients spread across different regions has grown to be a significant obstacle for all Indian banks. The banking industry is now capable of making use of Artificial Intelligence (AI) and seamlessly integrating it with operational requirements thanks to the shifting dynamics of an app-driven environment. The adoption of artificial intelligence will continue to advance, enabling a digital financial infrastructure, as the nation's banking environment continues to expand rapidly.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Artificial Intelligence, Banking industry, AI in banking, Digital Banking

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Fast disintegrating tablets have possible advantages over usual dosage forms, with improved patient observance, convenience, bioavailability and rapid onset of action. They are good substitute for drug delivery to geriatric and paediatric patients. They have major advantages of both solid and liquid dosage forms, as they remain solid during storage, which assist in stability of dosage forms and transform into liquid form within few seconds after its administration Thus FDT has great scope for being immediate drug delivery. The Loratidine are used as a model drug in the preparation of formulation. It is generally used for the treatment of Asthma. It is safe well tolerated. The study began with the preformulation characterization of drug which involves determination of melting point and development of suitable analytical method for the estimation of drug. The direct compression approach was used to create fast-dissolving tablets. It was discovered that the disintegration time of medication tablets made via direct compression was between 30 and 40 seconds. The best results were obtained from tablets manufactured with the highest amount of Crospovidone, or F15. According to the dissolving study's findings, almost half of the medication was released in the first five minutes.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Loratidine, Fast Disintegrating Tablets, Crospovidone

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This study aimed to develop and evaluate a herbal tobacco blend with improved safety and efficacy profiles. A blend of a herbs, including mint, rose petal, amla, nutmeg, bayleaf and carom seed was formulated and assessed for its sensory, chemical and toxicological properties. The results showed that the blend had a unique flavor and aroma profile, with potential health benefits associated with its constituent herbs.The blend was found to be safe for consumptions,with no detectable levels of toxic compounds. The study suggests that herbal tobacco blend may be viable alternative to traditional tobacco products. As the demand for herbal toacco blends continues to grow, future research should focus on standardization and quality control, clinical trials, regulatory frameworks, and innovative formulations this abstract highlights the importance of addressing this areas to ensure the development of safe and effective herbal tobacco blend

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Herbal tobacco blend, safety evaluation, efficacy assessment, sensory analysis.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

With increasingly globalized supply chains and outsourced activities, third-party risk management (TPRM) has become an indispensable function for companies in all sectors. Conventional TPRM processes, commonly manual and passive, are incapable of coping with the rising numbers, complexity, and speed of third-party relationships. This article discusses the deployment of artificial intelligence (AI) to improve TPRM to facilitate proactive, scalable, and data-driven risk assessment and tracking. We introduce an end-to-end framework that employs machine learning models, natural language processing (NLP), and predictive analytics to drive vendor due diligence automation, detect emerging risks, and enable continuous monitoring. The model employs both structured and unstructured data sources like financial statements, regulatory filings, and online news sentiment to deliver dynamic risk scoring and real-time alerts. A financial services sector case study illustrates the efficacy of our method in the detection of high-risk suppliers and prevention of possible disruptions. We also touch on major challenges such as data quality, model explain ability, and ethics. Our results identify the potential of AI to revolutionize TPRM from a compliance function to a strategic asset that increases organizational resilience and governance.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Third-Party Risk Management (TPRM), Artificial Intelligence (AI), Machine Learning, Risk Assessment, Predictive Analytics, Vendor Risk, Natural Language Processing (NLP), Risk Monitoring

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Stress is a condition of mental pressure that a particular individual faces due to environmental and social factors, which can lead to various diseases. The young age is a crucial period because at this time, students face numerous changes in their lives. Students of the modern era are living in a highly competitive world, which exerts a lot of stress on students to survive in this era. Stress is an unavoidable phenomenon in all aspects of human life. Stress is an emotional imbalance which may occur due to various reasons, such as tests. Stress affects students academically, socially, physically, and emotionally. The transition of students from high school to college is inherently stressful for students. It could cause physiological, academic and social shock to them. From this prospective, this research was aimed at investigating the level of stress among college students.

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Creative Commons Attribution 4.0 and The Open Definition

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Stress, College students, Milieu Therapy

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Creative Commons Attribution 4.0 and The Open Definition

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Abstract: Violence directed at women is pervasive and has a detrimental effect on their lives. Many research studies have made it clear that violence directed at women is pervasive and it is critical for women to even breathe in their life due to brutality. Slum areas are the place where most of the women get affected as they are highly disadvantaged in respect of economic and social status. Earlier research studies demystified the dreadful consequences of violence on women and very few researchers unfolded the specific types of violence and the related issues that affect them. No research has comprehensively addressed the forms of violence in slum areas and its upshot on women. This research delves deep in examining the issues that has a grave effect on women in the slums of India and put forward the welfare measures that could be mulled over by the government or NGOs.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Index Terms - Violence, Women, Slum, Government

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Library systems are adapting as a result of the integration of RFID technology and artificial intelligence (AI), which improves operational intelligence, automation, and personalization. RFID has long aided in library security, inventory management, and effective circulation. By incorporating AI, service delivery and resource management are improved through the introduction of new dimensions like as predictive analytics, user behaviour modelling, and intelligent decision-making. The benefits, difficulties, and new trends of AI-RFID integration in libraries are examined in this review paper by using case studies and current implementations. It looks at how data-driven services are supported, workflows are optimized, and readers happiness is raised by this connection. The study also examines important adoption challenges, such as budgetary limitations, technological complexity, and privacy ethics. The study provides information and suggestions for library professionals and representatives looking to use AI-enhanced RFID systems by combining the most recent research with real-world viewpoints. The results highlight how this integration could have a revolutionary impact on how smart libraries develop in the future.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Index Terms: AI, RFID, User Satisfaction, Resource Management, Libraries.

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Creative Commons Attribution 4.0 and The Open Definition