Researchers at Caltech and MIT have developed a theorem, dubbed IT-π, that identifies the most informative variables for predicting outcomes in AI and physics models while removing measurement units.

Soft measurement based on data-driven models is widely used to predict key variables in process industry due to low cost and real-time capability. However, these models struggle with noisy datasets ...

Understanding the costs associated with producing green hydrogen from renewable sources is essential to evaluate its large-scale viability in a global energy context. From this perspective, Enertis ...

Maybe this has happened to you: You walk into a conference room fully confident that you’ve prepared well and put together a crisp, persuasive presentation that will instantly wow your audience. The ...

Earnings compression does not necessarily translate into a down market. However, conviction portfolios are more favorable during macroeconomic turbulence. Regression analysis indicates that a general ...