Machine learning for health data science, fuelled by proliferation of data and reduced computational costs, has garnered considerable interest among researchers. The debate around the use of machine ...

A key problem facing artificial intelligence (AI) development is the vast amount of energy the technology requires, with some ...

AI agents can handle physics-based modeling complexity while engineers focus on design judgment and tradeoffs.

Xingjie Ni, associate professor of electrical engineering at Penn State, and his team recently developed a new device that ...

AxxonAI, developed by Athenatech.ai, a Malaysia Digital –certified company, is a next-generation synthetic GenAI platform that empowers organisations to maximise the value of their data—without ...

In this work, the authors systematically advance macro-micro integration with feedback (MMIF) as a transformative paradigm for analyzing urban mega-mobility systems, synthesizing the state-of-the-art ...

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a simple sequence of words, but as a complex web of non-linear relationships.

Emerging from stealth, the company is debuting NEXUS, a Large Tabular Model (LTM) designed to treat business data not as a ...

The report warns many economic models are failing to capture extreme weather events and rising uncertainty likely to dominate ...

Abstract: Accurate modeling of nonlinear capacitance is significant for physics-based compact modeling of GaN high-electric-mobility transistor (HEMT). For conventional methods, physical modeling of ...

This document provides a detailed explanation of the MATLAB code that demonstrates the application of the Koopman operator theory for controlling a nonlinear system using Model Predictive Control (MPC ...