Clarkson University researchers have developed an artificial intelligence tool that can uncover the mathematical equations ...

Genomic surveillance—the process of monitoring and sequencing pathogens—is one of the most important tools for detecting ...

Combinatorial optimization problems are often encountered in real-world applications, including logistics, scheduling and ...

Abstract: Cell-free massive multiple-input multiple-output (mMIMO) systems are an alternative topology for mMIMO deployment, wherein a large number of access points are distributed over the coverage ...

Abstract: In this letter we present Hybrid iterative Linear Quadratic Estimation (HiLQE), an optimization based offline state estimation algorithm for hybrid dynamical systems. We utilize the ...

Large sparse linear systems arise in diverse fields such as structural engineering, fluid dynamics, network analysis and machine learning. Direct factorisation techniques often become impractical for ...

While iterative calibration of computational models is a fundamental aspect of digital twins, it has been largely overlooked. Instead of focusing on parameter identification for static models, the ...

Iteration has always been at the heart of human engagement and learning. From the probing questions of Socratic dialogues to the collaborative discussions in hospital rounds, and even the storytelling ...

Physics-Informed Neural Networks (PINN) are neural networks encoding the problem governing equations, such as Partial Differential Equations (PDE), as a part of the neural network. PINNs have emerged ...

Phase measuring deflectometry (PMD) is an effective technique for three-dimensional measurement of specular surfaces. However, the ambiguity of monoscopic PMD and the time-consuming searching process ...