Results 101 to 110 of about 191,170 (252)
Event-Triggered Control for the Stabilization of Probabilistic Boolean Control Networks
This paper realizes global stabilization for probabilistic Boolean control networks (PBCNs) with event-triggered state feedback control (ETSFC). Via the semitensor product (STP) of matrices, PBCNs with ETSFC are converted into discrete-time algebraic ...
Shiyong Zhu +4 more
doaj +1 more source
Application of High-Performance Techniques for Solving Linear Systems of Algebraic Equations
Solving many problems in mechanics, engineering, medicine and other (e.g., diffusion tensor magnetic resonance imaging or finite element modeling) requires the efficient solving of algebraic equations. In many cases, such systems are very complex with a
Daniel Grzonka
doaj +1 more source
Performance of algebraic multigrid methods for non-symmetric matrices arising in particle methods
Large linear systems with sparse, non-symmetric matrices arise in the modeling of Markov chains or in the discretization of convection-diffusion problems.
Seibold, Benjamin
core
Revealing Protein–Protein Interactions Using a Graph Theory‐Augmented Deep Learning Approach
This study presents a fast, cost‐efficient approach for classifying protein–protein interactions by integrating graph‐theory parametrization with deep learning (DL). Multiscale features extracted from graph‐encoded polarized‐light microscopy (PLM) images enable accurate prediction of binding strengths.
Bahar Dadfar +5 more
wiley +1 more source
A linear two - point boundary value problem for a system of loaded differential equations with impulse effect is investigated. The parameterization method is used to solve the problem.
E.A. Bakirova +2 more
doaj +1 more source
Overcoming the Nyquist Limit in Molecular Hyperspectral Imaging by Reinforcement Learning
Explorative spectral acquisition guide automatically selects informative spectral bands to optimize downstream tasks, outperforming full‐spectrum acquisition. The selected hyperspectral data are used for tasks such as unmixing and segmentation. BandOptiNet encodes selection states and outputs optimal bands to guide spectral acquisition. Recent advances
Xiaobin Tang +4 more
wiley +1 more source
This study proposes a deep learning approach to evaluate the fatigue crack behavior in metals under overload conditions. Using digital image correlation to capture the strain near crack tips, convolutional neural networks classify crack states as normal, overload, or recovery, and accurately predict fatigue parameters.
Seon Du Choi +5 more
wiley +1 more source
Robotic Arm‐Assisted Conformal 3D Printing of Displays for Structural Electronics
This study presents a robotics‐enabled platform combining 3D scanning and a 6‐DOF robotic arm for conformal printing on complex non‐planar structures. By maintaining nozzle perpendicularity, the system enables high‐fidelity direct ink writing on steep sidewalls, spherical surfaces, successfully demonstrating a fully printed 7‐segment dynamic display ...
Chanbin Yoo +5 more
wiley +1 more source
Introduction: An interesting type of fractional derivatives that has received widespread attention in recent years is the tempered fractional derivatives. These fractional derivatives are a generalization of the well-known fractional derivatives, such as
Mohammad Hossein Heydari +1 more
doaj +1 more source
In nuclear engineering, the λ -modes associated with the neutron diffusion equation are applied to study the criticality of reactors and to develop modal methods for the transient analysis. The differential eigenvalue problem that needs to be
Amanda Carreño +5 more
doaj +1 more source

