Since 2021, Korean researchers have been providing a simple software development framework to users with relatively limited ...

The U.S. Army has established a new career pathway for officers to specialize in artificial intelligence and machine learning (AI/ML), ...

The Temporal Fusion Transformer model provides near-real-time insights into sintering temperatures, addressing critical challenges in steelmaking processes.

Abstract: Traditional machine-learning approaches face limitations when confronted with insufficient data. Transfer learning addresses this by leveraging knowledge from closely related domains. The ...

In large public multi-site fMRI datasets, the sample characteristics, data acquisition methods, and MRI scanner models vary across sites and datasets. This non-neural variability obscures neural ...

Traffic prediction is the core of intelligent transportation system, and accurate traffic speed prediction is the key to optimize traffic management. Currently, the traffic speed prediction model ...

Electric Vehicle (EV) cost prediction involves analyzing complex, high-dimensional data that often contains noise, multicollinearity, and irrelevant features. Traditional regression models struggle to ...

1 Faculty of Electrical and Computer Engineering, University of Tabriz, Tabriz, Iran 2 College of Engineering, Design and Physical Sciences, Brunel University London, Uxbridge, United Kingdom ...

ABSTRACT: Introduction: the left atrial appendage, a dormant embryonic vestige, would play a major role in cardiac hemodynamic changes, volume homeostasis and thrombi formation. It, therefore ...

Abstract: Fault detection in electric drives is crucial for ensuring operational reliability and minimizing downtime. This paper provides a brief overview of the methods based on machine learning used ...