Results 201 to 210 of about 9,085,112 (391)
A Case‐Based Reasoning Approach to Model Manufacturing Constraints for Impact Extrusion
Advanced Engineering Materials, EarlyView.A hybrid modeling approach is presented that combines constraint‐based process modeling and case‐based reasoning. The model formalizes manufacturing constraints and integrates simulation data to model complex manufacturing processes. The approach supports manufacturability analysis during product design through an adaptive modeling environment.
Kevin Herrmann +5 more
wiley +1 more source
Auditory oddball responses in the human subthalamic nucleus and substantia nigra pars reticulata
Neurobiology of DiseaseThe auditory oddball is a mainstay in research on attention, novelty, and sensory prediction. How this task engages subcortical structures like the subthalamic nucleus and substantia nigra pars reticulata is unclear.
Dallas Leavitt +8 more
doaj
Holographic implementation of a fully connected neural network [PDF]
, 1990 Ken Y. Hsu, H.-Y. Li, Demetri Psaltis
openalex +1 more source
Advanced Engineering Materials, EarlyView.An electronic system is presented consisting of a silver thin‐film electrode on a polyimide substrate working both as a heating element and a resistive temperature sensor, generating millisecond heat pulses with very fast heating and cooling rates and a flat peak temperature with a tunable duration.
Bahman K. Boroujeni +5 more
wiley +1 more source
Advanced Engineering Materials, EarlyView.In this study, the mechanical response of Y‐shaped core sandwich beams under compressive loading is investigated, using deep feed‐forward neural networks (DFNNs) for predictive modeling. The DFNN model accurately captures stress–strain behavior, influenced by design parameters and loading rates.
Ali Khalvandi +4 more
wiley +1 more source
Pulsed neural networks and perceptive grouping [PDF]
, 1994 Dominique Derou, Laurent Hérault
openalex +1 more source
Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials
Advanced Engineering Materials, EarlyView.This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani +4 more
wiley +1 more source