Results 131 to 140 of about 258,672 (295)
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
Global identification from the equilibrium manifold under incomplete markets [PDF]
We show that even under incomplete markets, the equilibrium manifold identifies individual demands everywhere in their domains. For this, we assume conditions of smoothness, interiority and regularity, but avoid implausible observational requirements. It
Andres Carvajal, Alvaro Riascos
core
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
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
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
Manifold learning in statistical tasks
Many tasks of data analysis deal with high-dimensional data, and curse of dimensionality is an obstacle to the use of many methods for their solving.
A.V. Bernstein
core
Calculation of Hydrodynamic Coefficients in the Process of Manifold Deploying
The manifold is an important part of the subsea production system. Accurately understanding the hydrodynamic coefficient of the manifold is of great significance for the safe deploying of the manifold.
Qi Yu +5 more
doaj
Radial–axial runner blade design using the coordinate slice technique
There is a lack of information about the geometric description of radial–axial runner blades. The article aims to fill this gap using a method that exploits modern differential geometry for the description and shape modification of the runner blade ...
Koudelka Libor
doaj +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

