Abstract: This paper presents a kernel-based framework for physics-informed nonlinear system identification that extends kernel-based techniques, accounting for unmodeled dynamics, to seamlessly embed ...
The current closure of the Strait of Hormuz is not fully priced into Brent crude, which trades at $84 despite severe ...
More engineers are turning to reinforcement learning to incorporate adaptive and self-tuning control into industrial systems. It aims to strike a balance between traditional ...
A new study published in the journal Minerals sheds light on this sweeping shift. Titled Big Data and AI in Geoscience: From ...
Abstract: Nonlinear dynamics are inherent in a wide range of industrial processes and mechatronic systems, where impulsive noise—arising from sensor faults, switching transients, or electromagnetic ...
Support vector machines improve classification by mapping inseparable signals into higher-dimensional spaces. Random forest models, through ensemble decision trees, increase robustness against ...
High-throughput sequencing, single-cell technologies, and large-scale population studies have transformed genetics and genomics into data-intensive ...
Introduction The clinical management of Obstructive Hypertrophic Cardiomyopathy remains challenging, and the phase III EXPLORER-HCM trial has demonstrated that the novel cardiac myosin inhibitor ...
Background Patients with heart failure (HF) frequently suffer from undetected declines in cardiorespiratory fitness (CRF), which significantly increases their risk of poor outcomes. However, current ...
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