Abstract: The high performance of conventional model predictive control (CMPC) for electric drives depends on the fidelity of the machine’s parametric model. However, the parameters of the interior ...
Researchers from the University of Chinese Academy of Sciences and collaborating institutions have developed a novel ...
A research team has developed a new way to measure and predict how plant leaves scatter and reflect light, revealing that ...
Beyond formal workplaces, Idiareh has taken her safety model into informal communities where accidents are common but hardly ...
Reverse Logistics, Artificial Intelligence, Circular Economy, Supply Chain Management, Sustainability, Machine Learning Share and Cite: Waditwar, P. (2026) De-Risking Returns: How AI Can Reinvent Big ...
Introduction Atrial fibrillation (AF) is the leading cause of cardioembolic stroke and is associated with increased stroke severity and fatality. Early identification of AF is essential for adequate ...
Objective Chronic kidney disease (CKD) arises due to uncontrolled hypertension (HTN). HTN significantly increases the risk of complications in vital organs, mainly the kidneys. If hypertensive ...
When experimental results don't match scientists' predictions, it's usually assumed that the predictions were wrong. But new ...
Abstract: Explicit model predictive direct speed control (EMP-DSC) for permanent magnet synchronous motors can achieve excellent control performance with high dynamics and high precision. However, the ...
With the wealth of data institutions have at their disposal, and with the emergence of more sophisticated analytics and decision-making capabilities, institutions have an opportunity to shift from ...
Joseph Alderman et al argue that predictive models in healthcare lack adequate oversight and regulation. They highlight the potential risks to patients and call for improved governance to ensure the ...
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