Results 101 to 110 of about 2,833,548 (240)
Building machine‐readable vocabularies for materials science is slow, expert‐driven work. This study benchmarks 13 large language models on two of its first steps: finding candidate terms in engineering articles and deciding where they belong in a class hierarchy.
Thomas Bjarsch +3 more
wiley +1 more source
We develop a data‐driven method to derive the mathematical expressions of the Flory–Huggins interaction parameter χ for the swelling behavior of temperature–responsive hydrogels. Starting from initial assumptions of χ, our workflow combines Bayesian optimization, Flory–Rehner theory, and symbolic regression to generate candidate χ expressions.
Yawen Wang +2 more
wiley +1 more source
Information Geometry of Asymmetric Interaction Matrices
Asymmetric interaction matrices encode the linear coupling structure and directed interaction patterns that arise in mathematical models of complex networks across ecology, finance, and machine learning, yet their geometric structure as points on a ...
TzeHoung Lee, Xue-Ming Yuan
doaj +1 more source
Optimization of the Production of Rubber Compounds Using Mathematical Models
Rubber compounds were mixed in a batch internal mixer, and symbolic regression was used to derive mathematical models linking recipe and process parameters to ram path, torque, and mixing quality (incorporation, dispersion, distribution). Subsequent optimization with evolutionary algorithms identified operating conditions that reduce specific energy ...
Anke Bardehle +7 more
wiley +1 more source
Roughness-informed machine learning – A call for fractal and fractional calculi
This paper presents a unified framework for roughness-informed machine learning, dividing roughness into four categories: statistical, geometric, manifold, and topological.
Mohammad Partohaghighi +3 more
doaj +1 more source
A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy
A lightweight and reproducible denoising pipeline for high‐throughput Raman spectroscopy is introduced, based on a 1D convolutional autoencoder trained with a Noise2Noise strategy. Using only repeated short‐exposure acquisitions, the method suppresses stochastic noise without reference spectra, enabling reliable spectral reconstruction while preserving
David Martin‐Calle +5 more
wiley +1 more source
This perspective reframes additive manufacturing for electrical machines as a qualification‐limited materials and architecture design problem. It links process–structure–property–performance relationships to magnetic, conducting, dielectric, and thermal property windows, highlighting where AM can enable segmented magnetic circuits, permanent magnet ...
Dénes Fodor, Loránd Szabó
wiley +1 more source
Bifurcation from a normally degenerate manifold
Local bifurcation theory typically deals with the response of a degenerate but isolated equilibrium state or periodic orbit of a dynamical system to perturbations controlled by one or more independent parameters, and characteristically uses tools from ...
Chillingworth, D. R. J. +2 more
core +1 more source
An all‐in‐one analog AI accelerator is presented, enabling on‐chip training, weight retention, and long‐term inference acceleration. It leverages a BEOL‐integrated CMO/HfOx ReRAM array with low‐voltage operation (<1.5 V), multi‐bit capability over 32 states, low programming noise (10 nS), and near‐ideal weight transfer.
Donato Francesco Falcone +11 more
wiley +1 more source
Journal of the Statistical Society.
Mode of access: Internet.Vols. 36-50, 1873-87. 1 v.
Statistical Society (Great Britain)
core

