ASRIC Journal on Engineering Sciences 2025 v5-i2
ISSN: 2795-3548
EISSN: 2795-3556
ASRIC Journal on Engineering Sciences 2025 v5-i2
Published: 2025-12-31
Articles
Effective On-Site Supervision- A Yardstick to Minimizing Building Construction Failure In Southwest Nigeria
Adeyemi, F. O*, Olaniyi O. A, Esuruoso, O.T
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
Remote Sensing of Chlorophyll-A Concentrations in a Water Hyacinth-Infested Tropical Headwaters Lake: A Study of Lake Tana, Ethiopia
Bekalu W. Asres, Mebrahtom G. Kebedew, Meareg D. Neraec, Seneshaw Tsegaye*, Fasikaw A. Zimale
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
Production and Characterization of Aluminium Matrix Composite Containing Silicon Carbide, Fly and Orange Peel Ash
Olayide R. Adetunji*, Korede S. Rasheed, Olanrewaju M. Adesusi, Queeneth A. Kingsley-Omoyibo
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
A Smart Food Delivery Platform with Machine Learning-Driven Intelligent Matching
Emmanuel Victoria Nkemjika, Enyinnaya Victor Chibunna
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
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