Daily Archives: November 14, 2025

Authors: Umudi Ese Queen, Erienu Obruche Kennedy, Apuyor Kingsley Efe, Apuyor Stanley Ejohwomu, Onwugbuta Godpower Chukwuemeka, Eresanya Olanrewaju Isola, Ikechukwu Sampson Chikwe

Abstract: The research looked into how dumpsites affect the areas around them. They collected and tested the dust and heavy metals found in chickens raised near these waste sites during both dry and wet seasons. For three months, young chickens were fed solid waste and leachates from these sites, and then they were sacrificed for analysis. A standard method for testing dust and heavy metals was followed, as recommended by the World Health Organization (WHO). They used Atomic Adsorption Spectroscopy to find out how much heavy metal was present. The levels of Zn, Cd, Cu, Pb, and Hg in the dust varied by season, ranging from 1.40 (JK) to 210.60 (SA), BDL (CTR) to 3.74 (RA), 0.241 (KU) to 390.0 (JK), 2.26 (CTR) to 78.260 (SH), and BDL (CTR) to 25.69 (AJ). For the chicken samples, the heavy metal levels ranged from BDL (CTR) to 8.844 (JK), BDL (CTR) to 2.850 (BG), BDL (CTR) to 0.099 (BG), BDL (CTR) to 128.017 (NTC), and BDL (CTR) to 83.122 mg/kg (DD) for Zn, Pb, Cd, Cu, and Hg across different sites and seasons. Most of the metal levels in the chicken samples were below safe limits, but a few were not, indicating that people living near these dumpsites are affected. The Kaduna State Environmental Agency (KEPA) needs to work on reducing hazardous waste and provide better waste disposal options.

DOI: http://doi.org/10.5281/zenodo.17637261

Published by: vikaspatanker

Authors: P. Shiva Sanakara Pandian, K. Sai varsha

Abstract: College Event Management System represents a comprehensive software solution designed to optimize and streamline the planning, organization, and management of events within college. This research project addresses the challenges encountered by academic institutions in coordinating and executing a diverse range of events, including conferences, seminars, cultural festivals, and sports tournaments, with a primary focus on enhancing efficiency, communication, and collaboration. The objective of this study is to explore the development and implementation of the College Event Management System, underscoring its potential to transform event management within educational institutions. By combining user insights, case studies, and in- depth analysis. The findings underscore the importance of modernized event management tools in promoting student engagement, fostering effective communication, and facilitating the successful execution of events within the college environment. Ultimately, this research project aims to provide valuable insights for academic institutions seeking to optimize their event management processes, thereby enhancing the overall campus experience.

Published by: vikaspatanker

Authors: Professor Shivani Karhale, Mr. Rohit Pawar, Ms. Sanskruti Marawade, Ms. Nandini Jadhav, Ms. Vaishnavi Pawaskar

Abstract: The rapid advancement of artificial intelligence, image editing tools, and generative models has made visual manipulation easier than ever. Altered images can influence legal investigations, journalism, social media, and political narratives, creating a critical need for automated authenticity verification systems. This research introduces an AI-Powered Forensic Image Suite integrating shadow analysis, image consistency detection, and metadata verification to identify tampered digital images. The system preprocesses images through resizing, normalization, and noise reduction, followed by shadow recognition using gradient-based and geometric estimation techniques. Image consistency is evaluated using structural similarity, lighting coherence, and texture uniformity checks. Metadata analysis extracts EXIF information to verify timestamps, camera signatures, and editing traces. Experiments conducted on a dataset of 500 real and manipulated images demonstrate high accuracy, with shadow detection (94%), consistency check (92%), and metadata validation (98%). The suite serves as a reliable tool for investigators, journalists, and forensic professionals, and provides a scalable foundation for advanced features such as deepfake detection, reverse image search, and error-level analysis.

Published by: vikaspatanker

Authors: B.Parthiban, R.Sripadma

Abstract: Libraries have come a long way from the traditional manual processes to the modern digital solutions that we now have, changing forever how information is handled and accessed. This paper presents the design, construction and application of a Library Management System (LMS) integrated with various advanced capabilities like Chat Bot, Voice Recognition and GUI. This LMS is intended to automate library operations, help improve user experience as well as optimize resource management. The paper describes the problem definition, project aims, approach taken, and system level architecture along with future work directions.

DOI: https://doi.org/10.5281/zenodo.17607767

Published by: vikaspatanker

Authors: Prajwal Sunil Saste, Om Santhosh Dhage, Aditya Arun Tathe, Prof. Rahane.D.A

Abstract: The swift advancement of AI in education has paved the way for more customized and flexible educational settings. This study introduces a student feedback analysis system powered by AI, which offers immediate, smart feedback to boost learning results. The system uses sentiment analysis to determine the emotional aspectof student communications and uses machine learning methods like decision trees, support vector machines (SVM), and deep learning models to assess participation, success, and emotional conditions. By merging cognitive and emotional understandings,the suggested system offers tailored, relevant feedback to help students conquer learning obstacles. Testing outcomes reveal enhanced student involvement, contentment, and general academic success, emphasizing the ability of AI to revolutionize contemporary education

Published by: vikaspatanker

Authors: Prajwal Sunil Saste, Om Santhosh Dhage, Aditya Arun Tathe, Prof. Rahane.D.A

Abstract: The swift advancement of AI in education has paved the way for more customized and flexible educational settings. This study introduces a student feedback analysis system powered by AI, which offers immediate, smart feedback to boost learning results. The system uses sentiment analysis to determine the emotional aspectof student communications and uses machine learning methods like decision trees, support vector machines (SVM), and deep learning models to assess participation, success, and emotional conditions. By merging cognitive and emotional understandings,the suggested system offers tailored, relevant feedback to help students conquer learning obstacles. Testing outcomes reveal enhanced student involvement, contentment, and general academic success, emphasizing the ability of AI to revolutionize contemporary education

Published by: vikaspatanker