Aviation enthusiast and reporter Zach Griff used flight schedule data to map out the busiest times at border control in ...

This valuable study tests whether prediction error or prediction uncertainty controls how the brain segments continuous experience into events. The paper uses validated models that predict human ...

China is building a very different kind of AI story than the one most people see in the West. Instead of focusing mainly on ...

The next "butks" stop. Eating a "banns bc a". It's "mi longer shiny sync". The above gobbledegook is what my phone dished up the other day when I was texting the ...

Researchers from the Johns Hopkins Applied Physics Laboratory (APL) in Laurel, Maryland, and Johns Hopkins University in Baltimore have developed a practical, comprehensive noise-modeling framework ...

Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Early detection of individuals at high risk of disease onset is crucial for health-care systems to cope ...

MPC, a well-known control methodology that exploits a prediction model to predict the future behaviour of the environment and compute the optimal action and RL, a Machine Learning paradigm that showed ...

What is a Gaussian Graphical Model ? A Gaussian graphical model captures conditional (in)dependencies among a set of variables. These are pairwise relations (partial correlations) controlling for the ...

Abstract: The goal of this article is to provide a simple model-free solution to the loss problem of accuracy in system model inherent in the existing finite control-set (FCS) model predictive control ...

This paper presents a novel visual-admittance-based model predictive control scheme to cope with the problem of vision/force control and several constraints of a nuclear collaborative robotic visual ...

Short-term forecasts of infectious disease burden can contribute to situational awareness and aid capacity planning. Based on best practice in other fields and recent insights in infectious disease ...