Polymers are a versatile class of materials with widespread industrial applications. Advanced computational tools could revolutionize their design, but their complex, multi-scale nature poses ...

Machine learning is the practice of teaching a computer to learn. The concept uses pattern recognition, as well as other forms of predictive algorithms, to make judgments on incoming data. This field ...

Abstract: Urban traffic simulation is useful in many ways to understand, manage, and predict the growing complexities of traffic dynamics within a city. Traditional simulation models often struggle to ...

CGSchNet, a fast machine-learned model, simulates proteins with high accuracy, enabling drug discovery and protein engineering for cancer treatment. Operating significantly faster than traditional all ...

ABSTRACT: Machine learning (ML) has revolutionized risk management by enabling organizations to make data-driven decisions with higher accuracy and speed. However, as machine learning models grow more ...

In this webinar from Dassault Systemes, learn how engineers can leverage machine learning (ML) and surrogate modeling to enhance simulation workflows. As engineering challenges become increasingly ...

Granular materials are widely encountered in food processing, but understanding their behavior and movement mechanisms remains in the early stages of research. In this paper, we present our recent ...

Cooperative Institute for Research in Environmental Sciences (CIRES), University of Colorado, Boulder, Colorado 80309, United States National Oceanic and Atmospheric Administration (NOAA), Chemical ...

The AI and Machine Learning major is one of two specialized majors in Purdue University’s 100% online Master of Science in Artificial Intelligence program. This major equips you with advanced ...

Abstract: This study focuses on simulating and modeling the behavior of a frequency-controlled asynchronous electric drive using MATLAB/Simulink. The control system is designed using the root locus ...