The IMF develops a machine-learning nowcasting framework to estimate quarterly non-oil GDP in GCC countries in real time, ...

Learning how a physical system behaves usually means repeating measurements and using statistics to uncover patterns. That ...

They might train a machine-learning model to estimate the magnitude of this association, since machine-learning methods are especially good at learning complex relationships. Standard machine-learning ...

Abstract: This paper presents a systematic approach to enhancing ISO 26262, a widely adopted standard for automotive functional safety, by integrating Machine Learning (ML)-specific life cycle phases ...

Rep. Mary Miller, R-Ill., has introduced legislation that would require U.S. service academies and federally operated secondary schools to incorporate a new standardized test based on classical ...

College of Mechanical and Electronic Engineering, Shanghai Jianqiao University, Shanghai, China Introduction: To enhance energy management in electric vehicles (EVs), this study proposes an ...

No audio available for this content. High-precision GNSS applications, such as real-time displacement monitoring and vehicle navigation, rely heavily on resolving carrier-phase ambiguities. However, ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Machine learning (ML) tools have revolutionized protein structure prediction, ...

3 Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore 4 Yong Loo Lin School of Medicine, National University of Singapore, Singapore 5 ...

The emergence of using Machine Learning Techniques in software testing started in the 2000s with the rise of Model-Based Testing and early bug prediction models trained on historical defect data. It ...