Category Archives: Uncategorized

Authors: Ms.Usha Dhankar, Ms. Preeti Kalra, Ms.Agrima Samanotra, Mr.Aaditya Shriv Astava

Abstract: This research explores the application of Retrieval-Augmented Generation (RAG) for enhancing information extraction and question-answering tasks from scanned PDF documents using Optical Character Recognition (OCR). By integrating a retrieval mechanism with a generative language model, we present a novel framework that intelligently interprets noisy, unstructured OCR outputs and enables contextual interaction via natural language queries[1][2]. The approach bridges the gap between image-based document archives and intelligent systems, facilitating improved document accessibility in fields like legal, academic, and archival research.

DOI: https://doi.org/10.5281/zenodo.16445198

 

Published by: vikaspatanker

Authors: Arsh Ahmed , Abhishek , Shivam Bhardwaj , Piyush Tiwari , Ms. Jyoti

Abstract: This comprehensive study examines the multifaceted impact of Artificial Intelligence (AI) on global education systems. Through an analysis of current implementations, case studies, and empirical data, we explore how AI-driven technologies are reshaping pedagogical approaches, institutional administration, and learning outcomes. The paper investigates adaptive learning platforms like Squirrel AI, ALEKS, and ALO7 through the lens of Bloom's 2 Sigma Problem, while critically analyzing both the transformative potential and ethical challenges of educational AI. Our findings suggest that while AI offers unprecedented opportunities for personalization and accessibility, its successful integration requires careful consideration of pedagogical, ethical, and socioeconomic factors. The study concludes with policy recommendations for balanced adoption in educational contexts.

DOI: https://doi.org/10.5281/zenodo.16444680

 

Published by: vikaspatanker

Authors: Usha Dhankar, Aditya Prakash Rai, Harsh Maheshwari, Deepanjal Uppal, Ankit Singhal

Abstract: Vision Play" is an advanced AI-driven video analysis system based on artificial intelligence, machine learning, and computer vision that is aimed at redefining traditional visual data processing. Initially designed to support football analysis, the platform has grown to be a flexible and scalable architecture used in sports, surveillance, and real-time monitoring applications. The system supports current models like YOLOv5 for real-time object recognition, optical flow for movement tracking, and KMeans clustering for team or object identification. Perspective transformation is applied to translate pixel-level information to real-world coordinates, making possible precise speed, distance, and positioning measurement.The system handles video streams to identify, categorize, and track objects such as players, referees, or pedestrians with accuracy, even for very dynamic or crowded scenes. It produces relevant visualizations such as movement traces, heatmaps, and performance dashboards to enable users to gain profound insights into behavior trends and spatial dynamics. Built in modularity and real-time capacity, "Vision Play" can handle varied camera feeds and is extensible to cloud or edge infrastructures.Through automated processing of advanced video analysis operations, the system lowers human labor by a large margin and increases accuracy, uniformity, and decision-making efficiency. Its multi-industry suitability makes it a desirable asset for analysts, strategists, security organizations, and researchers seeking to leverage smart video insights for performance optimization, security enhancement, and data-driven operation.

DOI: https://doi.org/10.5281/zenodo.16444484

 

Published by: vikaspatanker

Authors: Gautam Yadav, Sakshi Singh, Dharna, Ankit Kumar, Deepanshu Bhola, Aryan

Abstract: Food waste is growing daily, and hunger is a major problem in the globe today. An online food management system called Surplus Food for Orphanage (SFO) oversees excess food for malnourished individuals who don't have enough to sustain themselves. The goal of the study is to create a web-based platform called "Surplus Food for Orphanage" that facilitates communication between food seekers and donors. This paper is an example of a new online platform that will be useful for giving away used items and surplus food to anyone in need. The donor can create an account on this website. Donors can access this website by logging into their accounts after completing the registration process. The donor will publish their post by providing the name of the food item, the amount of food they wish to donate, their location, and their phone number. Food waste will be lessened thanks to this technique, which will also encourage more people to give food to orphanages.

DOI: https://doi.org/10.5281/zenodo.16440477

 

Published by: vikaspatanker

Authors: Senthil Kumar T, Mardeni Roslee, Jayapradha, Shubhanshu Tiwari, Pranjal Mishra

Abstract: Classroom attendance tracking was a fundamental task in educational institutions, traditionally managed through manual roll calls or sign-in sheets. These methods were time-consuming, error-prone, and susceptible to manipulation. With advancements in computer vision and embedded systems, there was an opportunity to automate this process. In this research paper, a novel approach to classroom attendance management was presented, utilizing OpenCV and face recognition technologies, implemented on the ESP32-CAM microcontroller. The proposed system was designed to automatically identify and record student attendance, offering enhanced accuracy and efficiency. Comparative results demonstrated that the face recognition-based approach significantly outperformed traditional manual methods and other automated systems in terms of accuracy and processing speed. The system's architecture, implementation, and evaluation were outlined, showcasing its potential to transform attendance tracking in educational settings.

DOI: https://doi.org/10.5281/zenodo.16440464

 

Published by: vikaspatanker

 

Mohammed Mohsin
Affiliation	Editor in Datawarehousing/BI solutions, Charless Schwab
Email-Id:	mdmo0580@gmail.com, mohammed.mohsin1@tcs.com
Education: Bachelors of Computer Science Engineering
Publication/Conference Papers:

 

Published by: vikaspatanker

Authors: Praveen, Bhaskarm

Abstract: Healthcare is the foundation of a well-functioning society, yet billions especially in rural, remote, or economically disadvantaged regions continue to face limited or delayed access to qualified medical support. In such contexts, Artificial Intelligence (AI) is not just a technological advancement but a transformative tool for democratizing healthcare services. The AI-Powered MediKit is designed as a comprehensive, intelligent, and accessible digital healthcare assistant that empowers users with preliminary diagnostics, wellness support, and actionable medical guidance from the comfort of their homes. Rather than being a single-purpose tool, MediKit is a modular, multi-functional platform that integrates advanced AI technologies such as image processing, speech and audio analysis, natural language understanding, and knowledge-based recommendation systems. Each module is carefully developed for scalability, usability, and inclusivity ensuring that the system is effective across diverse user groups. MediKit bridges the healthcare gap by making intelligent, early-stage diagnostics available on everyday devices, thus contributing to more equitable and proactive health management

DOI:

 

Published by: vikaspatanker

Authors: Udith A, Harsha H S, Jayanth B R, Prathibhavani P M

Abstract: – In today’s fast-changing digital environment, phishing attacks are a major cybersecurity concern. These attacks use deceptive messages to trick users into revealing sensitive information or installing harmful software. Historically, such attacks have involved widespread spam campaigns that target many users with malicious URLs or files designed to bypass standard security measures. To address the increasing so- phistication of these threats, this research introduces an intelligent, real-time framework for detecting phish- ing URLs using machine learning. A gradient boosting classifier was specifically chosen to systematically examine and distinguish phishing URLs from legitimate ones. The approach relies on a broad suite of lexical, structural, and host-based feature extraction. The classifier outperforms traditional methods—including support vector machines, decision trees, random forests, and neural networks—demonstrating both higher accuracy and lower false positive rates. These results validate the system’s capacity for timely and effective phishing detection. The work underscores the promise of sophisticated machine learning methods for enhancing digital trust and reinforcing cyber defense architectures.

DOI: http://doi.org/10.5281/zenodo.16408435

 

 

Published by: vikaspatanker

Authors: Professor Fiza Pathan, Professor Hirkanya Bhole, Professor Nageshwari Sarade, Professor Sushma Borewar, Professor Bhavesh Thakre

Abstract: Polymeric materials have become increasingly significant due to their wide-ranging applications and adaptability to modern societal needs. These materials exhibit remarkable properties, including thermal stability, chemical resistance, conductivity, and ion-exchange capacity. The development of polymeric ligands and coordination polymers, particularly those containing donor atoms such as N, S, and O, has expanded their utility in various fields, including catalysis, electronics, surface coatings, and biomedical applications. Chelate polymers, formed by coordinating metal ions with organic ligands, exhibit both organic and inorganic characteristics, offering desirable magnetic, thermal, and electrical properties. Despite challenges such as poor solubility and plasticity, chelate polymers are utilized in the aerospace, automotive industries, and semiconductor sectors due to their thermal resilience and functional diversity. Recent research has focused on designing low-band-gap conducting polymers and synthesizing various metal complexes with Schiff bases, hydroxamic acids, and thiosemicarbazones, leading to advances in coordination chemistry and material science. These developments underline the transformative role of polymers in science, industry, and everyday life.

DOI: https://doi.org/10.5281/zenodo.16420178

Published by: vikaspatanker

Authors: Ms. Suman, Mr. Kartik Gossain

Abstract: Healthcare appointment scheduling is crucial for improving patient access and optimizing medical resources. Traditional booking methods often lead to inefficiencies, delays, and poor user experience. This research presents the design and implementation of MediConnect, a Full-Stack Healthcare Appointment Scheduling System, developed using the MERN (MongoDB, Express.js, React, Node.js) stack. The system enables seamless appointment booking, user authentication, real-time availability updates, secure payments, and role-based access for patients, doctors, and admins. The MERN stack was chosen for its scalability, flexibility, and performance, offering advantages over traditional web technologies. Implementation results demonstrate improved efficiency and accessibility in healthcare booking. Future work may include AI-driven doctor recommendations, telemedicine integration, and enhanced security measures.

DOI: https://doi.org/10.5281/zenodo.16419927

Published by: vikaspatanker