The current MA risk adjustment model has shortcomings, both in predictive accuracy and payment equity across the Medicare ...

Brian Ferdinand, a portfolio manager at EverForward and Strategic Advisor to Helix Alpha Systems, argues that while predictive models are useful, they are inherently limited in today’s volatile, ...

Dynamic AI systems applied in biopharmaceutical manufacturing must be governed within established regulatory frameworks.

Production plans at oil refineries do not always survive contact with the plant floor. Changes in feedstock quality, ...

Researchers developed a continuous-time AI framework for adaptive energy control across multi-zone building profiles using ...

While wildfires mostly start as a result of human action, such as a discarded cigarette or arson, their impact has been ...

Abstract: In past robotics applications, Model Predictive Control (MPC) has often been limited to linear models and relatively short time horizons. In recent years however, research in optimization, ...

Anshul Karnik discusses how semiconductor technologies are successfully transitioned from early technology development (TD) through new product introduction (NPI) and into high-volume manufacturing ...

Abstract: In this article, we establish a collection of new theoretical properties for nonlinear stochastic model predictive control (SMPC). Based on the concept of stochastic input-to-state stability ...

Integrating plant biosensors, IoT, and AI transforms precision agriculture, enhancing crop monitoring and resource efficiency ...

SK hynix (SKHY) and the global memory sector face extreme volatility, with recent price action driven by shifting investor ...