ISSN: 2795-3556
EISSN: 2795-3548
Published: 2025-12-31
This paper explores the role of AI-driven systems utilizing deep learning and natural language processing (NLP) models in biomedical data handling. The aim is to enhance the efficiency, accuracy, and scope of data analysis in biomedical research and healthcare delivery. Despite their transformative potential, the deployment of these AI systems faces several challenges, including data integration,
Transient Electromagnetic (TEM) methods have undergone significant advancements over the past decade, revolutionizing their application in mineral exploration. This review synthesizes recent developments in TEM technology, data acquisition, processing, and interpretation, highlighting their enhanced capability to detect conductive ore bodies at greater depths and with higher resolution. Innovation
The building construction industry plays an essential role in the development of any developing nation. Despite various regulations and professional guidelines in the building construction sector, Nigeria continues to experience frequent building failure. This research therefore aims at assessing the effectiveness of on-site supervision as a yardstick to minimizing building construction failure in
Intensified agriculture practices contribute to nutrient enrichment in freshwater lakes, causing eutrophication, algal blooms, and water hyacinth infestations. Eutrophication in Lake Tana, the source of the Blue Nile in Ethiopia, necessitates effective monitoring due to rapid infestation of water hyacinths. While traditional monitoring is costly and limited in spatial and temporal coverage, remote
Metal matrix composites are sophisticated materials having reinforcement components to create materials with specific qualities such as stiffness, impact resistance that can be used in high-temperature situations.This research produced and characterized Aluminium matrix composite from Silicon Carbide, Fly and Orange peel ash (OPA).Casting was done from scrapped aluminium pot, Silicon carbide
This study presents the design and implementation of a smart food delivery platform powered by machine learning-driven intelligent matching. The platform is developed in response to the growing need for efficient and personalized food ordering experiences, reducing the time, effort, and costs associated with visiting physical food outlets. Common issues such as long wait times, lack of real-time e