Daily Archives: June 24, 2025

Authors: Ramlah Ampatuan Duge,, Taya Panigel Adam, Salahudin D. Solaiman

Abstract: – This research determined the level of cooperative learning strategies in group activities, group games, peer mentoring, and problem-solving activities; the students' level of learning outcomes on the 2nd and 3rd quarter of the S.Y. 2023-2024; and the relationship of demographic profile to cooperative learning strategies on students' learning outcomes. Additionally, this study determined the relationship between cooperative learning strategies and learning outcomes; and the significant influence of cooperative learning strategies on students' learning outcomes. Descriptive-correlation research design was utilized to analyze the gathered data from the respondents who were identified using stratified sampling with proportional allocation and complete enumeration. Mean and the spearman's rho with correlation coefficient were used to describe the results and to test the hypotheses of the study correspondingly.Results of the statistical analyses revealed that the majority of the respondents strongly agreed on their cooperative learning strategies in peer mentoring and problem-solving activities. Subsequently, most of the respondents strongly agreed that there are learning outcomes in their subjects such as English, Mathematics, and Science. Findings revealed that cooperative learning strategies have a significant relationship with the learning outcomes in English, Mathematics and Science subjects. Moreover, cooperative learning strategies have a significant influence on learning outcomes in the same subjects.

DOI: https://doi.org/10.5281/zenodo.15738047

 

Published by: vikaspatanker

Authors: Ms. Tanvi Parab, Ms.Saloni Pawar, Dr. Jasbir Kaur, Assistant Professor Ms. Sandhya Thakkar

Abstract: The field of drug discovery has undergone a remarkable transformation with the integration of artificial intelligence (AI) techniques. AI-driven approaches have the potential to significantly accelerate and enhance the drug discovery pipeline by streamlining key stages such as target identification, compound screening, lead optimization, and preclinical prediction. This paper provides a comprehensive overview of the various AI methodologies employed in drug discovery, including machine learning, deep learning, reinforcement learning, and natural language processing. We explore how these technologies are being utilized to analyze complex biological data, predict molecular interactions, and identify promising drug candidates with greater efficiency and accuracy. Furthermore, the paper examines the challenges and limitations associated with data quality, model interpretability, and regulatory acceptance. We also highlight recent advancements and successful case studies demonstrating real-world applications of AI in pharmaceutical research. Ethical implications, data privacy concerns, and the evolving role of human expertise in AI- assisted workflows are critically discussed. Finally, the paper outlines future prospects, emphasizing the potential of AI to revolutionize personalized medicine and accelerate the development of novel therapeutics in a cost-effective and time- efficient manner.

Published by: vikaspatanker

 

Dr. Soumalya Kundu
Affilation:	Assistant Professor (Physics) Department of Basic Science NSHM Knowledge Campus, Durgapur, India
Email-Id:	physics.soumalya@gmail.com
Publication: R. Majumder, S. Kundu, R. Ghosh, M. Pradhan, D. Ghosh, S. Roy, S. Roy, M. P. Chowdhury, “Expeditious UV detection of tungstite (WO3·H2O) and tungsten oxide (WO3) decorated multiwall carbon nanotubes (MWCNT) based photodetector: ultrafast response and recovery time”, SN Applied Sciences 2020, 2, article no. 81. R. Ghosh, R. Majumder, S. Kundu, M. Pradhan, S. Roy, R. Gayen, M. P. Chowdhury, “Effect of grain–grain boundary on ZnOnanorod-based UV photosensor: a complex impedance spectroscopic study”, J. Mater. Sci. 2021, 56, 19128–19143. R. Majumder, S. Kundu, M. P. Chowdhury, “Investigation of ambient regulated enhanced photo-responsive properties of GO-ZnO and transition metal doped GO-ZnO nanocomposite: Improved photocurrent and swift response”, Optical Materials, 2023, 142, 113981. S. Kundu, R. Majumder, R. Ghosh, MP Chowdhury, “Enhanced relative humidity sensing property of porous Al:ZnO thin films”, Materials Today: Proceedings 2020, 26, 138-141. S. Kundu, R. Majumder, S. Roy and MP Chowdhury, “Electro-polymerization of Polyaniline on CVD grown transferrable vertically aligned CNT forest and its application in resistive detection of relative humidity”, Materials Today: Proceedings 2021, 43, 3591-94. R. Ghosh, S. Kundu, R. Majumder, M. P. Chowdhury, “Hydrothermal synthesis and characterisation of multifunctional ZnO nanomaterials”, Materials Today: Proceedings 2020, 26, 77-81.

 

Published by: vikaspatanker

Authors: Assistant Professor K.M.Jadhav, Ms.Shreya Deshmukh, Ms.Anushka Kshirsagar, Ms.Sanika Patil, Ms.Gauri Mharanur, Ms.Priya Kolar, Ms.Tanuja Patil, Ms.Ashish Katkar, Ms.Shlok Katu, Ms.Umer Ibuse

Abstract: Augmented Reality (AR) and Virtual Reality (VR) are rapidly transforming how users interact with digital environments by enhancing real-world experiences and simulating fully immersive virtual scenarios. This paper explores the current landscape, practical applications, and future directions of AR and VR technologies, with a focus on their role in education, healthcare, engineering, and retail. A qualitative research approach was adopted, incorporating academic literature, platform documentation, and real-world use cases. The study also highlights sector-specific challenges including usability, cost, and cultural limitations, while discussing technological trends such as gesture recognition, virtual simulations, and cross-platform development. Through this analysis, the paper underscores the importance of context-aware, user-centred design in maximizing the impact of immersive technologies.

Published by: vikaspatanker

Authors: Assistant Professor S.N.Sudhal, Mr.Vishal Patil, Mr.Aniruddha Jagadale, Mr.Harshvardhan Jadhav

Abstract: The growing global demand for sustainable energy solutions has accelerated the development and integration of biofuels in modern engine technologies. Biofuels—renewable fuels derived from biological sources such as crops, algae, and waste—offer a cleaner and more environmentally friendly alternative to fossil fuels. This paper explores the types of biofuels, including first, second, and third-generation fuels, and examines their physical and chemical properties relevant to combustion performance. Emphasis is placed on the compatibility of various biofuels with current internal combustion engine (ICE) systems, including spark-ignition and compression-ignition engines. Advances in engine modifications, fuel injection systems, and emission control technologies are discussed in the context of optimizing engine performance while minimizing environmental impact. The paper also addresses the technical and economic challenges in large-scale biofuel adoption and outlines future directions for research and development. Ultimately, the synergy between biofuels and evolving engine technology presents a promising pathway toward a more sustainable and energy-secure future.

Published by: vikaspatanker

Authors: Madhura.M.Raste, Aniruddha. R. Sawant,, Prathmesh.S.Patil,, Sourabh. S. Kurne, Sandip.S.Sawant,

Abstract: – In today’s digital age, farmers and livestock owners still face challenges when it comes to buying and selling animals or cattle feed. Traditional methods are often time-consuming, limited by geography, and involve middlemen who may increase costs. This project aims to develop a user-friendly website that serves as an online marketplace where farmers, feed suppliers, and livestock traders can connect directly. The platform allows users to list livestock for sale, browse available cattle feed, compare prices, and make purchases or inquiries all from their mobile or computer. It includes features like secure user accounts, search filters (by location, type of animal or feed, price range), and contact options for buyers and sellers. By bringing these transactions online, the platform helps reduce market inefficiencies, increase transparency, and give rural communities better access to trade opportunities. This website is designed to be simple, multilingual, and accessible even in low-connectivity areas. Overall, the goal is to modernize livestock and cattle feed trading, empowering farmers with the tools they need to grow their businesses more efficiently.

 

 

Published by: vikaspatanker

Authors: Assistant Professor H.S.Bhore, Mr.Shreyas Shivankar, Ms.Payal Kamble, Ms.Aishwarya Bansode

Abstract: This paper explores the applications of Artificial Intelligence (AI) in smart city management, focusing on traffic, waste, and resource management. We discuss the benefits and challenges of implementing AI-powered solutions in urban settings and propose a framework for integrating AI into smart city infrastructure.

Published by: vikaspatanker

Authors: Associate Professor Mrs. Archana Dongardive, Aakash Gophane, Vishwajit Godbole, Vivek Khairnar

Abstract: CivicCompass is a centralized, web-based platform developed to streamline public access to state and district- level welfare schemes in India. Government portals often contain fragmented and unstructured information, which makes it difficult for citizens—particularly from rural and underprivileged areas—to discover and understand available benefits. This project addresses that gap by implementing automated web scraping to collect data from various official sources. The extracted content is cleaned, categorized, and stored using structured CSV files via pandas, then dynamically displayed using Django's Model-View-Template (MVT) architecture. The portal allows users to filter schemes by state, district, and department. It also incorporates a feedback mechanism where users can submit comments or inquiries, which are reviewed through an admin panel before publication. The system was designed for scalability and maintainability, with future improvements possible through API integrations and multilingual support. Overall, the portal bridges the gap between digital governance and grassroots-level access, enabling inclusive participation in government programs.

DOI: https://doi.org/10.5281/zenodo.15727253

Published by: vikaspatanker

Authors: Abirama SundariAbstract: ETHICAL CONSIDERATION IN AI DRIVEN TRADING SYSTEM Artificial Intelligence (AI) has revolutionized financial markets, introducing unprecedented efficiency and capabilities in trading systems. However, this technological advancement brings with it a host of ethical challenges that demand careful consideration. This white paper explores the ethical dimensions of AI-driven trading systems, analyzing key issues such as fairness, transparency, accountability, market integrity, privacy, and human oversight. As a global leader in both artificial intelligence and financial technology, China stands at the forefront of AI-driven trading systems. With its rapidly growing economy, innovative tech sector, and forward-thinking regulatory approach, China offers unique insights into the ethical considerations surrounding AI in finance. This white paper examines the global landscape of AI-driven trading systems with a particular focus on China's contributions, challenges, and regulatory framework. The paper concludes with actionable recommendations for various stakeholders and a forward- looking perspective on the future of AI in financial markets.

 

 

Published by: vikaspatanker