As organizations consider the synergy of digital twins and RTLS for factory optimization, having a clear understanding of ...
Discover how early CMC, process optimization, and formulation strategy drive scalable, commercially viable drugs.
Abstract: Impedance control is one of the fundamental control approaches for contact-rich robotic tasks. However, to apply the impedance control, the robot dynamics needs to be completely known, which ...
Abstract: This article proposes a constrained Gaussian process regression (GPR)-based multiobjective distribution optimal power flow (GPR-DOPF) framework to coordinate the voltage-regulating devices ...
ABSTRACT: This paper introduces a method to develop a common model based on machine learning (ML) that predicts the mechanical behavior of a family with three composite materials. The latter are ...
Neural networks revolutionized machine learning for classical computers: self-driving cars, language translation and even artificial intelligence software were all made possible. It is no wonder, then ...
ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...
The many stages of a bioprocess offer endless opportunities for optimization. Improving a process starts with process design (PD) and never really ends. In late 2024, Jun Luo, PhD, Genentech’s head of ...
Insect trap networks targeting agricultural pests are commonplace but seldom optimized to improve precision or efficiency. Trap site selection is often driven by user convenience or predetermined trap ...
You might have heard the term “splat” or “Gaussian splat” used recently in the XR space. Gaussian splatting is a rendering technique that has been around for a long time but has found a new ...
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