Maharaja Bir Bikram University

This chapter describes how fuzzy multi-criteria decision-making (MCDM) might enhance collaboration between government, business, and academic institutions. It demonstrates why cooperation in AI development entails ambiguity and conflicting viewpoints. Vague judgments are transformed into usable values with the use of fuzzy sets and triangular fuzzy numbers. Fuzzy numbers are used to assess various factors, including research strength, finance, policy flexibility, technology preparedness, and social impact. The shifting significance of each criterion for various partners is displayed by fuzzy weights. All viewpoints are combined into a single meaningful score using aggregation and defuzzification techniques. Fuzzy soft sets highlight areas of agreement and aid in identifying areas of disagreements between partners. Partners can select AI laboratories, internships, and ethical committees, as demonstrated by several cases. The chapter demonstrates how fuzzy models improve the clarity and fairness of collaborative judgments in AI development.

Agro-ecosystems support a vast diversity of insect fauna that play crucial roles in ecosystem functioning, including pollination, nutrient cycling, biological pest control, and soil health maintenance. Understanding insect diversity and its seasonal distribution is essential for sustainable agricultural management and biodiversity conservation. The present study aimed to assess the diversity, abundance, and seasonal variation of insect fauna in selected agro-ecosystems over a one-year period. Systematic sampling was conducted during four distinct seasons summer, monsoon, post-monsoon, and winter using sweep nets, pitfall traps, light traps, and hand collection methods. Insects were identified up to family and genus level using standard taxonomic keys. Diversity indices such as Shannon–Wiener, Simpson’s dominance, and species richness were calculated. Results revealed significant seasonal variation in insect diversity, with maximum abundance and species richness recorded during the monsoon season, followed by post-monsoon, summer, and winter. Orders Lepidoptera, Coleoptera, Hymenoptera, and Diptera dominated the agro-ecosystem. Beneficial insects such as pollinators and natural enemies showed strong seasonal dependence, highlighting the influence of climatic factors and crop phenology. The study emphasizes the importance of conserving insect biodiversity in agricultural landscapes through eco-friendly farming practices and reduced pesticide usage to ensure long-term sustainability and food security.

Grey wolves' leadership hierarchy scavenging habit served as the model for the bio-inspired optimization technique known as Grey Wolf Optimization (GWO). The primary basis for the search process in GWO is the behaviour of three distinct wolves: <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$a$</tex> (alpha), ℬ (beta), and δ (delta). The algorithm became more exploitative by searching with individuals who were upward in the hierarchy, which reduced the precision of the solution and increased the likelihood of becoming stuck in a local solution. This paper proposes a GWO with expanded exploration (GWOIE), which modifies the <tex xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">$a$</tex> wolf evaluation procedure and uses a newly developed weight vector to calculate the solution for the following generations. The algorithm's exploration potential was enhanced by the GWO alternations, which nearly balanced the algorithm. In this study, the KNN was applied as a classification approach to assess the quality of the selected subset of features. Eight medical datasets from the UCI repository are analyzed in order to test the methodology. To evaluate the effectiveness of GWOIE, the outcomes are contrasted with seven widely-used fundamental metaheuristics considering three matrices accuracy, minimum fitness and minimum feature. Numerical results from these experiments and comparisons with alternative techniques demonstrate GWOIE's improved performance.

The increasing pollution of river systems poses a significant challenge to water quality management and public health. This study was conducted to evaluate the water quality of the Gomati River in India, focusing on the impact of anthropogenic activities on pollution levels across different seasons. The primary objective was to develop a comprehensive assessment model using an effective weighted fuzzy soft expert system (WFSES) to derive a weighted water pollution score (WWP-score) for rating water pollution levels based on various water quality parameters. To achieve this, we employed a fuzzy soft set (FSS) methodology integrated with a weighted fuzzy soft set (WFSS) model to analyze water quality indices at six sampling stations along the Gomati River, the largest river in Tripura, India. Originating from the Raima and Sarma streams, the river flows westward through key regions, providing 249.39 million cubic meters of water annually, essential for drinking, agriculture, fishing, and transportation. The study utilized crisp data summaries of key water quality parameters, including pH, total dissolved solids, total suspended solids, electrical conductivity, biochemical oxygen demand, dissolved oxygen, total hardness, chloride, total alkalinity, and total coliform, across the pre-monsoon, monsoon, and post-monsoon seasons from May 2022 to April 2023, guided by the distribution of waste discharge points. Fuzzy membership functions were defined for these parameters, and the root mean square (RMSQR) operation was used to combine multiple FSSs. The results revealed that the WWP-scores, a measure of water quality, ranged from 0.744 to 0.872 across the sampling stations, with Srimantapur exhibiting the highest level of pollution and Udaipur showing comparatively better quality. These scores indicate that water quality at all sites falls into the poor category, with Srimantapur experiencing the most severe contamination due to high levels of coliform bacteria and organic pollutants. The analysis highlights the impact of domestic wastewater and agricultural runoff on the river's health. This research offers a novel application of FSS and WFSS theory in environmental management, providing a robust framework for evaluating and ranking water quality across multiple parameters. The findings are valuable to the scientific community as they offer detailed insights into the pollution dynamics of the Gomati River and propose a methodological approach for assessing water quality in other river systems facing similar challenges. The study's results underscore the need for targeted pollution control measures and continuous monitoring to safeguard water resources and public health.

Metal-based drugs have emerged as pivotal therapeutics in cancer therapy, enlightening a path toward innovative and effective treatment strategies. Platinum-based therapeutics, notably cisplatin, carboplatin, and oxaliplatin, have transformed the landscape of cancer treatment, setting the stage for the development of next-generation metal-based compounds. Delving into the principles governing the design of metal-based drugs, this article navigates through their intricate coordination chemistry, targeted delivery approaches, and mechanisms of action. Notably, metal-based compounds form covalent bonds with DNA, disrupting vital cellular processes and inducing apoptosis in cancerous tissues. Even though contemporary chemotherapy as well as radiotherapeutic methods have greatly increased patient survival rates, disease recurrence still represents a fatal danger. The probability of metastasis and the drug resistance are increased by the incomplete clearance of neoplastic tissues from the body. This review explores the compelling journey of metal-based compounds, from their historical significance in ancient remedies to their pivotal role in modern oncology, and also discusses the recent advancements and emerging trends that promise to shape the future of metallodrugs. The shining promise of metal-based drugs in cancer remedies holds the potential to revolutionize treatment paradigms, offering hope and resilience in the ongoing battle against one of humanity's most relentless adversaries.

The exclusiveness of Gharana has made Hindustani classical music different from Carnatic and other branches of North-Indian classical music. Ragas, the integral part of Indian classical music, have been a prevailing Cultural Tradition through the expression of various musical forms. The practice of Hindustani classical music is rightly executed by the Gharana representatives and those styles have enriched Indian art and culture. There had been many native lands or estates under certain kings or rulers before their inclusion into India. Most of the rulers possessed good sense and knowledge of art and culture. The formation of Court music was the consequence of their patronage to Indian classical music and dance. Princely Tripura was also blessed with Gharana maestros along with music personalities of other genres. This article inquires about those Gharana maestros who were somehow related to the Tripura Royal Court music and any sustainable development thereof.

The rise of artificial intelligence (AI) has led to significant changes in how businesses operate, particularly cybersecurity. The increasing reliance on technology for business processes and data storage has made companies vulnerable to cyberattacks, making it crucial for businesses to incorporate AI-powered cybersecurity systems to safeguard their operations. However, despite the numerous benefits of using AI in cybersecurity, there are still concerns surrounding the technology's safety and effectiveness. This study explores the role of AI in identifying threats in digital banking and highlights the benefits of using AI-powered cybersecurity to support business efficiency. The study also aims to raise awareness about the need to overcome the fear of experimenting with new technologies and to show how examples of Malta's risk management study drawing on the experiences of businesses that have implemented AI-powered cybersecurity systems in Malta, highlighting the success of such systems in safeguarding business operations. The study also examines the challenges of implementing AI-powered cybersecurity and offers recommendations for overcoming these challenges. The study concludes by emphasizing the need for businesses to embrace AI-powered cybersecurity systems to mitigate cyber risks and enhance their overall security posture. The findings of this study contribute to the body of knowledge on the role of AI in cybersecurity and provide insights for businesses looking to implement AI-powered cybersecurity systems.