Category Archives: Uncategorized

Authors: Professor Swati Bagade, Pallavi Patil, Vaishnvi Patil, Riya Sankpa, Harshwardhan Thorat

Abstract: Artificial Intelligence (AI) models, also known as foundation models, are advanced computer systems that can process huge amounts of data and have billions of settings to fine-tune their performance. Once trained, these models can handle a wide range of tasks with impressive accuracy. A well-known example is GPT, which has amazed people with its abilities and potential to impact different areas of life. In healthcare, AI models are changing the way medical research and diagnosis work. With the rise of deep learning, the amount of medical and biological data has grown significantly, providing new opportunities to develop AI systems that can improve healthcare.This paper explores the role of large AI models in medicine, discussing their background and how they are used. We focus on four key areas where AI can make a big difference:1)Bioinformatics 2)Medical Diagnosis 3)Medical informatics 4)Public Health.

 

 

Published by: vikaspatanker

Authors: Anjali R

Abstract: This study aims to explore and analyze the Gen Z’s reaction towards Shrinkflation and their affect on purchasing behavior of Gen Z consumers, a phenomenon where product sizes decrease while the price remains the same. This has become increasingly prevalent in today’s economy. A sample of 100 respondents from diverse age groups, ranging from 18 years to26 and above, was surveyed using a structured questionnaire. . The data were analyzed using statistical and graphical tools to identify key trends and insights. The results indicated that about 61% of respondents belonged to the age group of 18-20 years, where half of the respondents (50%) were not even aware of the term Shrinkflation. About majority (68%) of respondents felt that brands or companies are not being transparent about Shrinkflation due to which consumers have started shifted to buying the product less often and also looking for various discounts to tackle this long term trend. Based on the data received it implies that Gen Z consumers have started exploring alternative brands and they want more transparency regarding the product to improve their experience on Shrinkflation.

Published by: vikaspatanker

Authors: Anjali R

Abstract: This study aims to explore and analyze the Gen Z’s reaction towards Shrinkflation and their affect on purchasing behavior of Gen Z consumers, a phenomenon where product sizes decrease while the price remains the same. This has become increasingly prevalent in today’s economy. A sample of 100 respondents from diverse age groups, ranging from 18 years to26 and above, was surveyed using a structured questionnaire. . The data were analyzed using statistical and graphical tools to identify key trends and insights. The results indicated that about 61% of respondents belonged to the age group of 18-20 years, where half of the respondents (50%) were not even aware of the term Shrinkflation. About majority (68%) of respondents felt that brands or companies are not being transparent about Shrinkflation due to which consumers have started shifted to buying the product less often and also looking for various discounts to tackle this long term trend. Based on the data received it implies that Gen Z consumers have started exploring alternative brands and they want more transparency regarding the product to improve their experience on Shrinkflation.

Published by: vikaspatanker

Authors: Professor Swati Bagade, Dr. Anamika Jain, Saad Shaikh, Om Salunkhe, Sourish Chatterjee, Aditya Salunkhe

Abstract: As the need for secure and effective data storage continues to grow, Network-Attached Storage (NAS) has emerged as an essential element for personal and business applications. This project aims to deploy a NAS system based on a virtual machine (VM) with OpenMediaVault (OMV) as the central storage management software. For added security, a Virtual Private Network (VPN) is incorporated, providing secure remote access. Moreover, data encryption is used to protect sensitive information from unauthorized access. This paper examines the design, implementation and security provisions of the proposed NAS system, showing its gains in terms of accessibility, scalability, and data integrity.

 

 

Published by: vikaspatanker

Authors: Deepti Varshney, Prajakta Mane, Raisa Shaikh, Kais Peerzade, Sumit Dharmadhikari

Abstract: The traditional hostel management system relies on manual operations such as physical registers, handwritten records, and labor-intensive procedures. These methods pose several inefficiencies, necessitating the development of a digital Hostel Management System (HMS) to streamline and automate hostel administration. The HMS is designed as an Android application integrating real-time authentication, notifications, and secure data management. This paper explores the design, implementation, and future enhancements of the system, incorporating insights from contemporary research on hostel automation.

 

 

Published by: vikaspatanker

Authors: Manisha Wasnik, Varad Landge, Sameer Mail, Shriya Watkar, Siddhesh Kamire

Abstract: — CryptoNavigator is a cryptocurrency tracking application built with Flutter, Dart, and Supabase. It fetches live market data through the CoinGecko API, providing real-time price tracking, search, favorites, and deep insights per cryptocurrency. Secure user login through email verification and profile management are some of its security features. One of the main features is price prediction to assist investors in making knowledge-based decisions. With a user-friendly UI and cross-platform support, CryptoNavigator aims to assist both new and experienced investors in tracking and predicting cryptocurrency trends.

 

 

Published by: vikaspatanker

Authors: Asstsitant Professor Sangeeta Mohapatra, Sourav Kale, Tejaswini Katole, Vrushali Kase, Aniket Kasturi, Pratiksha Ingle

Abstract: The continuous rise of urbanization has led to an overwhelming increase in waste generation with serious consequences for the environment and humans. Most waste disposal methods are inefficient, with little accountability or participation from the community, hence we propose a Smart Waste Management System (SWMS) built on AI technologies that employs computer vision and cloud computing to track on a real-time basis, facilitating improved waste sorting and the complaint making towards upcycling. The system allows the community to upload pictures of items to be reused and are identified as categories using an artificial intelligence model through which there is a trgging of the item for appropriate action. The platform also enables conversations on tracking complaints and donations of reusable items, thereby enabling data emergence for urban waste management authorities in making decisions. This paper explains the system design and implementation and is sustainability implications.

 

 

Published by: vikaspatanker

Authors: Professor Swati Bagade, Aarohi Wagh, Veerashwar Kshirsagar, Shivam Ubarhande

Abstract: In today's digital era, students face significant challenges in finding authentic and structured reviews about colleges. The existing online platforms often provide scattered, biased, or unverified information, making it difficult for prospective students to make informed decisions. This paper presents an AI-powered College Review Chatbot designed to provide instant, structured, and reliable information about various colleges based on student feedback and key institutional parameters. The chatbot leverages Natural Language Processing (NLP) to interpret user queries and retrieve relevant insights from a curated database. Additionally, sentiment analysis is employed to filter biased or misleading reviews, ensuring a balanced perspective. The chatbot serves as an interactive guide, simplifying the decision-making process for students and enhancing user engagement. Experimental results demonstrate the chatbot's effectiveness in improving accessibility and reducing the time required to gather accurate college-related information.

 

 

Published by: vikaspatanker

Authors: Assistant Professor Swati Bagade, Ajay Ugale, Umer Tukdi, Sudhanshu Tripathi, Sundaram Tiwari

Abstract: The agricultural sector plays a critical role in ensuring food security and economic stability worldwide. However, farmers often encounter significant challenges, including limited access to markets, inefficient supply chains, price exploitation by intermediaries, and a lack of real-time market data. The Agriculture Management System (AMS) is a digital solution designed to bridge the gap between farmers and buyers by offering an online platform that ensures direct sales, fair pricing, and increased efficiency. AMS integrates three core modules: Farmer, Buyer, and Administrator, each with distinct functionalities aimed at optimizing market interactions. The system provides real time market price updates, a secure transaction mechanism, and a knowledge base for product quality assurance. By leveraging technology, AMS enhances transparency, reduces operational costs, and empowers farmers, ultimately leading to a more sustainable and profitable agricultural ecosystem. This paper examines the system's architecture, functionalities, expected impact, and future enhancements, emphasizing its potential to revolutionize agricultural trade.

 

 

Published by: vikaspatanker

Authors: Assistant Professor Manisha Wasnik, Prajwal Sharma, Karan Ranpise, Purvi Garvir, Aryan Poddar

Abstract: This paper explores the conceptualization, development, and anticipated impact of an innovative integrated ride-hailing application designed to seamlessly connect with Ola, Uber and Rapido through their respective APIs. The core objective of this research is to address the inefficiencies and user dissatisfaction caused by the need to switch between multiple ride-hailing platforms to compare real-time fares and estimated arrival times. By aggregating data from Ola, Uber and Rapido within a single, unified interface, the proposed solution eliminates the hassle of time-consuming searches, thereby streamlining the ride selection process and enhancing user convenience.The study employs a comprehensive mixed-methods approach, incorporating a detailed technical analysis of API integration, system architecture design, and user experience assessments conducted through simulations and surveys. The findings demonstrate that this integrated platform significantly improves search efficiency, enhances user satisfaction, and offers broader implications for urban mobility by optimizing resource allocation within the ride-sharing industry. The significance of this research lies in its potential to revolutionize the ride-hailing ecosystem, paving the way for a more efficient, user-centric, and technology-driven transportation landscape.

 

 

Published by: vikaspatanker