Authors: Nishikant Kshirsagar, Manas Lonkar, Pratik Ingle, Suraj Kushwaha, Prof. Madhavi Patil

Abstract: The Unified Health System (UHS) integrates multi- ple healthcare stakeholders into a single digital platform to im- prove patient care, records management, and treatment decision- making. This paper examines the design and implementation of a web-based UHS using Spring Boot for backend microservices, MongoDB as a NoSQL cloud database, and React JS as a dy- namic frontend framework. The system enables real-time access to patient medical history, digital prescriptions, lab reports, and appointment scheduling with hospitals. The project demonstrates reduced administrative delays, secure role-based data access, and a modern patient-centric healthcare experience. Existing research confirms that fragmented healthcare data and the absence of interoperable systems remain critical barriers to efficient clinical outcomes [1], [3]. By adopting a microservice-based approach and leveraging NoSQL document storage, this system overcomes the scalability limitations of monolithic architectures. The find- ings align with recent studies demonstrating that cloud-based digital platforms can significantly enhance healthcare workflow efficiency and reduce manual intervention [5], [7].

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Published by: vikaspatanker

Authors: Saurav Patankar, Abhijeet Waghmare, Swaraj khadhe, Durvesh Kavire, Prof. Pradnya Satpute

Abstract: Communication across different languages has become a major challenge in today’s globalized world. The need for a system that enables seamless interaction between users speaking different languages has led to the development of multilingual communication platforms. This paper presents Chat Verse, a multilingual chat application that allows users to communicate in real time without language barriers. The application provides automatic language detection and real-time message translation, enabling users to send messages in their native language while the system translates them into the receiver’s preferred language. The system is developed using Android Studio, with Java for application logic and XML for user interface design, ensuring a responsive and user-friendly experience. Chat Verse includes essential features such as user authentication, private and group chat functionality, language preference settings, notification system, and feedback module. The application focuses on delivering a smooth communication experience by integrating translation capabilities within the chat interface. The motivation behind developing Chat Verse is to create an efficient, accessible, and intelligent communication platform that removes language barriers and enhances global connectivity. Traditional messaging applications often lack seamless multilingual support, making communication difficult for users from different linguistic backgrounds. This system aims to address that limitation by providing an intuitive and automated translation-based chat environment. The proposed system emphasizes usability, efficiency, and scalability, and demonstrates how multilingual chat applications can play a significant role in improving communication in fields such as business, education, and social networking. The study also highlights the future potential of integrating advanced AI-based translation techniques for even more accurate and context-aware communication.”

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Published by: vikaspatanker

Authors: Jag Pratap Singh Yadav

Abstract: Classical diffusion models based on Fick’s law assume Brownian motion and local transport, leading to a mean squared displacement that grows linearly with time. However, many physical, biological, and engineering systems exhibit anomalous diffusion, where the mean squared displacement follows a power law in time rather than a linear relationship. Such behavior commonly arises in heterogeneous porous materials, crowded biological environments, polymeric systems, and disordered media, where long trapping times and memory effects invalidate standard integer-order diffusion equations. Despite significant progress in fractional modeling, there remains a need for mathematically consistent and computationally efficient formulations that clearly link the physical origin of anomalous transport to robust numerical implementation. In this paper, we develop a time-fractional diffusion model using the Caputo fractional derivative to represent memory-dependent transport induced by heavy-tailed waiting times. Starting from the conservation of mass and a constitutive relation with temporal memory, we derive a physically meaningful fractional diffusion equation. An analytical solution for a benchmark initial-boundary value problem is presented using Laplace and Fourier transforms, and a numerical approximation based on the L1 finite difference scheme is constructed. The stability and convergence properties of the numerical method are discussed. Numerical experiments demonstrate that the fractional order controls the transition from normal to subdiffusive transport and accurately reproduces power-law mean squared displacement behavior. The model captures anomalous transport with significantly fewer parameters than multi-scale classical alternatives. These results show that fractional differential equations provide an effective and parsimonious framework for describing memory-driven diffusion processes, with direct relevance to transport in porous media, biological tissues, and complex soft matter systems.

DOI: http://doi.org/10.5281/zenodo.70

 

 

Published by: vikaspatanker

Authors: Dr. Harsha R. Vyawahare, Sukhada Shripad Tare, Ashwini Nitin Shingane, Shreya Sunil Shinde, Bhavika Suraj Jain

Abstract: This paper presents a practical and lightweight bidirectional communication system that translates between speech/text and Indian Sign Language (ISL) using machine learning and computer vision techniques. The system supports two modes: Speech-to-ISL and ISL-to-Text/Speech. In Speech Mode, spoken input is converted into text using speech recognition, then mapped to corresponding ISL alphabet images. In Camera Mode, hand gestures are captured using a webcam and classified using a Convolutional Neural Network (CNN) model to generate text and voice output. The system is implemented using Streamlit for the user interface, OpenCV for image processing, TensorFlow/Keras for gesture recognition, and pyttsx3 for speech synthesis. The proposed system provides a simple, real-time, and cost-effective solution to improve communication accessibility for the Deaf and Hard-of-Hearing (DHH) community

DOI: https://doi.org/10.5281/zenodo.19484295

Published by: vikaspatanker

Authors: Assistant Professor Anshul Khandelwal, Abhishek Pakhariya, Associate Professor Brajesh Tripathi

Abstract: A comprehensive comparative computational fluid dynamics (CFD) investigation is presented, analyzing three representative wing configurations: the transonic ONERA M6 benchmark wing, a finite wing based on the symmetric NACA 0012 airfoil section, and a tapered finite wing evaluated at low subsonic speeds. The primary objective is to examine benchmark-oriented transonic flow prediction capabilities and evaluate low-speed finite-wing performance parameters within a unified aerodynamic framework. For the ONERA M6 configuration, the flow field is simulated under the standard validation conditions of a Mach number of 0.8395, an angle of attack of 3.06°, and a Reynolds number of $11.72 \times 10^6$ based on the mean aerodynamic chord. For the low-speed wings, integrated aerodynamic loads at a free-stream velocity of 50 m/s are utilized to determine the aerodynamic coefficients and efficiency trends across various angles of attack. The CFD solver successfully reproduces the expected transonic pressure redistribution, including the characteristic shock-dominated flow structure over the ONERA M6 wing. In the low-speed analysis, the rectangular NACA 0012 wing achieves its maximum aerodynamic efficiency near an 8° angle of attack, whereas the tapered wing exhibits superior aerodynamic efficiency at low angles but suffers a more rapid degradation at higher incidences due to accelerated drag growth. This study effectively consolidates benchmark computational validation, finite-wing aerodynamic theory, and comparative performance analysis.

Published by: vikaspatanker

Authors: Muthulakshmi M, Saravanan P, Srihari M, Shunmugapandian P

Abstract: This paper presents Q-Track, a Smart QR Code and Geo-Fenced Attendance System designed to provide a secure, efficient, and automated solution for attendance management in educational institutions. Traditional attendance systems, including manual registers and biometric methods, suffer from limitations such as time consumption, proxy attendance, and lack of real-time monitoring. To overcome these challenges, the proposed system integrates dynamic QR code generation with geo-location verification.In this system, a unique and time-bound QR code is generated for each class session by the faculty. Students scan the QR code using their mobile devices to mark attendance. To ensure authenticity, the system incorporates geo-fencing technology, which validates the real-time location of the student. Attendance is recorded only when both QR authentication and location verification are successful, thereby eliminating proxy attendance and ensuring reliability.The system is implemented as a web-based application with a user-friendly interface accessible on both mobile and desktop devices. It includes modules for user authentication, QR code generation, attendance tracking, and report generation. Real-time data processing enables faculty to monitor attendance instantly and generate detailed reports for analysis.The proposed solution enhances accuracy, reduces manual workload, and improves transparency in attendance management. By combining QR technology with geo-location services, the system provides a scalable and cost- effective approach suitable for modern academic environments.

Published by: vikaspatanker

Authors: Mr. R.Rajesh, Bura Keerthi, K.Keerthan Reddy, A.Siddartha

Abstract: Smart Loan is an intelligent system designed to predict loan eligibility and assess risk using machine learning techniques. Traditional loan approval processes are time-consuming and prone to human bias. This system automates the evaluation process by analyzing applicant data such as income, credit history, employment status, and financial behavior. The model predicts whether a loan should be approved and categorizes applicants based on risk level (low, medium, high). The system ensures faster decision-making, reduces default risks, and improves efficiency for financial institutions.

Published by: vikaspatanker

Authors: Dr. CH. Kishore Kumar, Joruka Vigneshwar, SK Khaja Mohinuddin Pasha, Karingula Dileep Goud

Abstract: The “Intelligent Web-Based System for Automated Code Assessment and Learning”, designed to enhance programming education using Artificial Intelligence and Machine Learning techniques. The system allows users to submit programming code through a web interface, where it is automatically evaluated for syntax, correctness, logic, and efficiency. Unlike traditional manual evaluation methods, this system provides instant and meaningful feedback by analyzing errors, identifying logical mistakes, and suggesting improvements and optimized solutions. This enables learners to better understand their mistakes and improve their coding skills effectively. The web-based platform supports real-time code execution and evaluation, making it scalable and accessible to a large number of users. It also includes features such as performance analysis, scoring mechanisms, and personalized learning recommendations based on user performance. The system can be extended to support multiple programming languages and adaptive learning paths. Overall, this project focuses on developing a smart and efficient solution that bridges the gap between theoretical learning and practical coding skills, offering benefits such as reduced instructor workload, faster evaluation, improved learning outcomes, and enhanced user engagement through intelligent feedback.

Published by: vikaspatanker

Authors: Dr Vinit Kumar Sharma, Insaf Ali

Abstract: Group Theory is one of the fundamental branches of modern algebra and provides the mathematical framework for studying symmetry, transformations, and algebraic structures. This paper presents a comprehensive study of groups and their fundamental properties, including closure, associativity, identity, inverses, commutativity, cyclicity, normality, solvability, and nilpotency. The paper examines finite and infinite groups, discusses important classification theorems, and highlights applications in cryptography, coding theory, physics, and computer science. A graphical analysis is presented to compare major classes of groups according to their structural complexity. Recent developments in finite group classification and graph-theoretic approaches to group theory are also reviewed.

DOI: http://doi.org/10.5281/zenodo.20759238

Published by: vikaspatanker

Authors: Saurabh.D. Kamble, Dr. V. P. Varghese, Prof. M.N. Umare

Abstract: The high consumption rate of raw materials by the construction sector, results in chronic shortage of building material and the associated environmental damage. In the last decade, many research on the utilization of waste products in concrete in order to reduce the utilization of natural available resource have been undertaken. Thus, in this paper we have tried to review the use of waste products which are replaced as cement partially by ground granulated blast furnace slag (GGBFS) and coarse aggregate by rubber pallets. The aim is to study literature review & determine how GGBFS & Rubber pallets would affect the compressive strength of concrete when used in different proportions of GGBFS 20%, 30% & 50%, & Rubber pallets 5%, 10%, 15%. This literature review investigation supports the potential use of GGBFS and rubber pallets as partial replacement in concrete production, contributing to eco-friendly and resource efficient construction practice.

Published by: vikaspatanker