Results 61 to 70 of about 3,282,070 (234)

Characterization of Defect Distribution in an Additively Manufactured AlSi10Mg as a Function of Processing Parameters and Correlations with Extreme Value Statistics

Advanced Engineering Materials, EarlyView.
Predicting extreme defects in additive manufacturing remains a key challenge limiting its structural reliability. This study proposes a statistical framework that integrates Extreme Value Theory with advanced process indicators to explore defect–process relationships and improve the estimation of critical defect sizes. The approach provides a basis for
Muhammad Muteeb Butt, Varma Kvvssn, Hossein Laieghi, Zia Uddin, Peyman Ansari, E. Kıvanç Sadak, Can Barış Toprak, Hüseyin Kızıl, Enrico Salvati   +8 more
wiley   +1 more source

Matrices related to some Fock space operators [PDF]

Opuscula Mathematica, 2011
Matrices of operators with respect to frames are sometimes more natural and easier to compute than the ones related to bases. The present work investigates such operators on the Segal-Bargmann space, known also as the Fock space.
Krzysztof Rudol
doaj   +1 more source

Symbolic Regression and Multi‐Objective Optimization of the Flory–Huggins Interaction Parameter for Hydrogels

Advanced Engineering Materials, EarlyView.
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, Adrian Ehrenhofer, Thomas Wallmersperger   +2 more
wiley   +1 more source

The Kernel Function of Reproducing Kernel Hilbert Space and Its Application on Support Vector Machine

Science and Technology Indonesia
Reproducing Kernel Hilbert Space (RKHS) is a Hilbert space consisting of functions that can be represented or reproduced by a kernel function. The development of data science has made RKHS a method that refers to an approach or technique using the ...
Bernadhita Herindri Samodera Utami, Warsono, Mustofa Usman, Fitriani   +3 more
doaj   +1 more source

Reproducing Kernel Hilbert Space and Coalescence Hidden-variable Fractal Interpolation Functions

Demonstratio Mathematica, 2019
Reproducing Kernel Hilbert Spaces (RKHS) and their kernel are important tools which have been found to be incredibly useful in many areas like machine learning, complex analysis, probability theory, group representation theory and the theory of integral ...
Prasad Srijanani Anurag
doaj   +1 more source

INFORMATIVE ENERGY METRIC FOR SIMILARITY MEASURE IN REPRODUCING KERNEL HILBERT SPACES [PDF]

International Journal of Computational Intelligence Systems, 2012
In this paper, information energy metric (IEM) is obtained by similarity computing for high-dimensional samples in a reproducing kernel Hilbert space (RKHS).
Songhua Liu, Junying Zhang, Caiying Ding
doaj   +1 more source

Microstructure Reconstruction in Battery Electrodes Using Machine Learning Based on Low‐Voltage Focused Ion Beam–Scanning Electron Microscopy Tomography Images

Advanced Engineering Materials, EarlyView.
Low‐voltage FIB‐SEM tomography combined with a image preprocessing pipeline improves phase contrast and enables reliable machine‐learning segmentation of conductive networks in lithium‐ion battery electrodes. Structural descriptors are extracted from segmented images, done semimanually and automated, and compared.
Lisa Beran, Vincent Nebel, Dominik Perius, Kshitij Kumar, Yannis Heim, Laura Bies, Tobias Kraus   +6 more
wiley   +1 more source

A Practical Noise2Noise Denoising Pipeline for High‐Throughput Raman Spectroscopy

Advanced Engineering Materials, EarlyView.
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, Cesar Alvarez‐Llamas, Vincent Motto‐Ros, Christophe Dujardin, Jérémie Margueritat, David Rodney   +5 more
wiley   +1 more source

On $n$-widths of classes of holomorphic functions with reproducing kernels

Illinois Journal of Mathematics, 1994
For a subset \(A\) of a Banach space \(X\), the Kolmogorov and Gel'fand \(n\)-widths are defined by \(d_ n (A,X) = \inf_{X_ n} \sup_{x \in A} \inf_{y \in X_ n}\) \(\| x - y \|\) and \(d^ n(A,X) = \inf_{Y_ n} \sup_{x \in A \cap Y_ n} \| x \|\), respectively, where \(X_ n\) runs over all \(n\)-dimensional subspaces and \(Y_ n\) over all closed subspaces ...
Fisher, Stephen D., Stessin, Michael
openaire   +3 more sources

Controlling Grain Growth in Powder Bed Fusion of Yttria‐Stabilized Zirconia Using Femtosecond Lasers: Challenges and Methodological Insights

Advanced Engineering Materials, EarlyView.
Binder‐free laser powder bed fusion of 8YSZ with a femtosecond laser is used to map process windows linking scan strategy, heat accumulation, and grain growth. Time‐resolved thermography and simulations reveal thermal regimes that enable continuous, vitrified, and fine‐grained 8YSZ surface layers without absorptive additives and demonstrate ...
Markus Kühn, Sarah Kaden, Andrea Barz, Daniel Störzner, Jens Bliedtner, Andrés Fabián Lasagni   +5 more
wiley   +1 more source