In one instance, to further enhance output voltage swing and linearity, the authors propose a novel “breakdown-voltage (BV) ...

Background Early graft failure within 90 postoperative days is the leading cause of mortality after heart transplantation. Existing risk scores, based on linear regression, often struggle to capture ...

This paper presents a novel framework for optimizing Carbon Release (CR) through an AI-driven approach to Fossil Fuel Intake (FFI) management. We propose a new training methodology for AI models to ...

Background Asthma is an umbrella diagnosis encompassing distinct pathophysiological mechanisms. While a global problem, our ...

AI systems now operate on a very large scale. Modern deep learning models contain billions of parameters and are trained on large datasets. Therefore, they produce strong accuracy. However, their ...

Abstract: Multi-output symbolic regression involves predicting two or more target variables simultaneously, adding complexity compared to single-output symbolic regression due to the interdependence ...

1 College of Computer Engineering, Jimei University, Xiamen, Fujian, China 2 China-Belarus “Belt and Road” Electromagnetic Environmental Effects Laboratory, China Electronics Technology Group ...

Although [Vitor Fróis] is explaining linear regression because it relates to machine learning, the post and, indeed, the topic have wide applications in many things that we do with electronics and ...