Abstract: A two-layer soft voting ensemble machine learning based algorithm for the diagnosis of turn-to-turn faults in the stator winding of three-phase induction motors is presented. The suggested ...

1 Department of Information Technology and Computer Science, School of Computing and Mathematics, The Cooperative University of Kenya, Nairobi, Kenya. 2 Department of Computing and Informatics, School ...

Machine learning, a key enabler of artificial intelligence, is increasingly used for applications like self-driving cars, medical devices, and advanced robots that work near humans — all contexts ...

aDepartment of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital, Peking University, Beijing, China bState Key Laboratory of Vascular Homeostasis and Remodeling, Peking ...

ABSTRACT: This research developed an all-rounded cyber risk assessment framework for supply chains, which focused on third-party vulnerabilities and security gaps that arise due to increasing ...

Machine learning model improves transplant risk assessment for patients with myelofibrosis, helping clinicians make informed decisions, as per an expert. A new machine learning model has significantly ...

The water inrush is one of the most catastrophic emergencies in metro tunnels. To avoid the potential water inrush, this paper proposes a risk assessment model for the metro tunnel based on Delphi ...

Background: In reperfusion treatment, advanced neuroimaging can be used to indicate treatment or forecasting outcomes, however immediate access is not widely available. This study aims to explore the ...

Abstract: The objective of this work is to propose a machine learning-based methodology system architecture and algorithms to find patterns of learning, interaction, and relationship and effective ...