Journal of the Oriental Institute, ISSN:0030-5324 UGC CARE Group 1

AI-DRIVEN INNOVATIONS IN SUSTAINABLE SUPPLY CHAIN MANAGEMENT FOR LIBRARY SERVICES: A SCIENTOMETRICS OVERVIEW

2025-04-18T05:35:41+00:00

The study focused on analysing contributions to Artificial Intelligence (AI) research from 2014 to 2023. Data from the Scopus database was utilized to extract information on AI-related publications. The objectives included analysing the growth of AI research, identifying authorship patterns, and understanding the level of research conducted by global authors. The study revealed a significant increase in AI publications over the years, with 2023 expected to account for 38.61% of the total publications. Conference papers comprised the highest percentage of publications, while the United States, China, and India emerged as leading contributors to AI research. The data also provided insights into the distribution of publications and citations across different document types and countries. The findings shed light on the scientific development and collaborative efforts within the global scientific community in the field of AI.

Assessing the Role of Financial Literacy in Enhancing Personal Financial Decision-Making among Students

2025-04-21T11:46:55+00:00

Financial literacy is increasingly recognized on a global scale. The prosperity of an economically thriving society is significantly reliant on financial literacy, as it fosters informed decision-making and promotes economic empowerment. In the context of India's swiftly changing financial markets, it is essential to evaluate the level of financial awareness among its student mass. As students cultivate long-term financial habits, the significance of financial literacy has become increasingly acknowledged as a crucial competency for effective personal financial management. This research aims to evaluate the influence of financial literacy on enhancing students' personal financial decision-making. A fundamental grasp of financial principles, including budgeting, saving, investing, and debt management, facilitates efficient money management. Students who possess financial literacy are more likely to make informed choices regarding the allocation of their resources, enabling them to achieve both short-term and long-term objectives. The study highlights the necessity of integrating comprehensive financial literacy programs into university curricula to equip students with essential skills for responsible financial management. Personal financial management is vital for students, as it establishes a foundation for their financial health during their academic pursuits and in the future. The demand for financial literacy education among students is further emphasized by its broader economic advantages, such as enhanced savings rates, reduced debt levels, and improved economic stability. This research also investigates barriers to acquiring financial literacy, including socio-economic challenges, a lack of practical financial experience, and restricted access to financial education resources. Data for this analysis was gathered through a questionnaire administered to 100 respondents using a convenience sampling method to assess how financial literacy contributes to better financial decision-making among students.

Leveraging Botanical Gardens for the Conservation and Sustainable Utilization of Wild Food Plant Resources

2025-05-04T06:13:40+00:00

Wild food plants (WFPs) are consumed by the indigenous communities in various parts of the
world for food, nutrition, and medicinal purposes. They are usually collected from the wild and
sometimes grown in the vicinity of the forests and the dwellings of the indigenous people in a
way such that they are not far from their natural habitats. WFPs are important for the food and
nutritional requirements of the indigenous communities. The WFPs are seasonal and collected
from the wild whenever they are available. Therefore, the food menu of the tribal communities
changes with the seasons. A number of studies have demonstrated various WFPs consumed by
indigenous communities including India. The results show that an enormous diversity of WFPs
is consumed by the indigenous people of India. However, a few studies also suggest that the
consumption of WFPs among the indigenous communities is declining along with the
dwindling of traditional ethno botanical knowledge linked to the collection, processing,
cooking, storage, and limited cultivation of WFPs. India can leverage the network of its botanic
gardens for the conservation of its wild food plant resources, the traditional and indigenous
knowledge linked to it, and its popularization among the citizens within the framework of
Global Strategy for Plant Conservation (GSPC). This article provided an overview of the need
to focus on WFPs, limitations of current studies, and role of botanic gardens in the conservation
of wild food plants through the implementation of GSPC. This article further provided a
framework for the role of botanic gardens in the popularization of WFPs, increasing the
awareness about their importance, documentation, and preservation of the traditional
knowledge linked to various aspects of WFPs within the GPSC framework.

A STATE OF THE ART COMPOUND MODEL FOR CONSUMER TYPICAL LOAD PROFILE FORECASTING

2025-05-04T06:38:27+00:00

The rollout of advanced residential meters and sensors has been progressive over the years. This initiative is turning into better planning, forecasting, regulation and optimization of power systems. With the advent of Smart meters, consumer data analytics is becoming a prominent research area in which supervised clustering is one of the most common. Furthermore, predicting the typical load profile (TLP) of consumers is important for short, medium and long term load forecasting. With the increasing complexity, varying load and renewable energy interventions, forecasting demands for deep computational algorithms. This paper presents a State of the Art Compound model (SACM) to forecast TLP of electricity consumers. The model combines the fringe benefits of smart meters installed at the consumer’s premises and modern machine learning tools such as K-means Clustering, Principal Component Analysis (PCA) and Recurrent Neural Network (RNN). The effectiveness of the model is substantiated through data collected from smart meters in Mathura, Uttar Pradesh, India.