This proposal outlines a machine learning-based approach aimed at improving productivity in haulage operations within open-pit mining. Since hauling accounts for up to 60% of total operational costs, ...

Large language models (LLMs) can generate credible but inaccurate responses, so researchers have developed uncertainty quantification methods to check the reliability of predictions. One popular ...

With exploitation of vulnerabilities taking just days, preemptive security must be the new model for defenders.

Drug developers will be able to use alternatives to animal testing and possibly get new products to market faster under draft guidance issued Wednesday by the FDA. In a press release, officials said ...

New paired studies from the University of Minnesota Twin Cities show that machine learning can improve the prediction of floods. The studies, published in Water Resources Research and the Proceedings ...

The transformer-based model is being developed to help organizations—most notably in the finance industry—dig deeper into their data.

In most boardrooms, the final decision still comes down to a small circle of leaders weighing a narrow set of choices. Yet the problems they face now contain thousands, sometimes millions, of possible ...

BackgroundWater scarcity, declining water quality, and increasing climate variability are imposing unprecedented constraints on global food production, ...

Utilities worldwide are turning to artificial intelligence (AI) and machine learning to stabilize networks, forecast ...

Abstract: In this paper, a model predictive based minimum DC-link voltage control (MP-mDVC) method is proposed to enhance both the reliability and dynamic performance of grid-connected converters ...

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 ...