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
Model Predictive Controlled Novel Supermaneuverable Tricopter Design
Afework Alemu Zeudu, Yemane Gebremichael Gebremedhin, Yohannes Kiros Amare, Nebyat Gebregziabhier Weldearegay
This paper presents the design, modeling, and control of a novel supermaneuverable tricopter (SMT) featuring dual-axis thrust vectoring on each of its three rotors. Unlike conventional tricopters, which face under-actuation and yaw-pitch coupling, the SMT offers over-actuation with nine independent control inputs for six degrees of freedom. This allows complete decoupling of motion and enables agi
Ensemble, Kernel-based, and Deep Learning approaches for flood susceptibility mapping: A case study at Lake-Watersheds
Sintayehu Adefires Abebe*, Mulu Sewinet Kerebih, Bewketu Assefa Mulu, Bekalu Weretaw Asres
Lake Tana and its surrounding regions experience frequent flooding, necessitating improved susceptibility mapping to mitigate risks and enhance resilience. This study applies data-driven machine learning techniques to assess flood susceptibility utilizing data sets commonly used in large-scale river basin studies. A comprehensive flood inventory of approximately 2,080 flooded locations was compile
Engineering and Analysis of Ai-Driven Systems Utilizing Deep Learning and Natural Language Processing Models for Biomedical Data Handling
Emmanuel, Victoria Nkemjika
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,
Advances In Transient Electromagnetic Methods for Mineral Exploration: A Review of The Recent Decade
Ogunkoya Charles Olubunmi*, Alasi Taiwo Kamorudeen
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
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