Mathematicians Just Figured Out How to Better Predict the Future

A team of mathematicians has recently taken steps to improve our ability to predict future data. It’s not exactly ...

New AI framework can uncover space physics equations in raw data

Artificial intelligence (AI) systems, particularly artificial neural networks, have proved to be highly promising tools for uncovering patterns in large amounts of data that would otherwise be ...
Investopedia

Understanding Exponential Growth: Definition, Formula, and Real-Life Examples

Timothy Li is a consultant, accountant, and finance manager with an MBA from USC and over 15 years of corporate finance experience. Timothy has helped provide CEOs and CFOs with deep-dive analytics, ...
IEEE

Using Control Barrier Function in Distributed Explicit Reference Governor

Abstract: This article presents an explicit reference governor (ERG) design method, which incorporates a control barrier function (CBF) and considers both nonconvex and convex constraints in different ...
Scientific Research Publishing

Covariant-Scale: Riemannian Manifold Learning for Scale-Invariant Video Anomaly Detection ()

Video-Based Anomaly Detection, Urban Surveillance, Scale-Projective Ambiguity, Riemannian Manifold, Scale-Covariant Tracking, ...
Scientific Research Publishing

Artificial Intelligence in Science Learning within the Framework of Situated Learning Theory: A Qualitative Investigation of Teachers’ Perspectives ()

Artificial Intelligence in Science Learning within the Framework of Situated Learning Theory: A Qualitative Investigation of Teachers’ Perspectives This study explores how artificial intelligence (AI) ...
IEEE

Linear State Signal Shaping Explicit Model Predictive Control Using Tensor Decompositions

Abstract: Due to the increasing use of nonlinear loads in modern power systems, harmonic currents have become a more prominent problem for power quality. Typically, harmonic currents are compensated ...