Results 51 to 60 of about 49,315 (263)

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

A new family of kernels from the beta polynomial kernels with applications in density estimation

IJAIN (International Journal of Advances in Intelligent Informatics), 2020
One of the fundamental data analytics tools in statistical estimation is the non-parametric kernel method that involves probability estimates production.
Israel Uzuazor Siloko, Wilson Nwankwo, Edith Akpevwe Siloko   +2 more
doaj   +1 more source

Multivariate mixed kernel density estimators and their application in machine learning for classification of biological objects based on spectral measurements [PDF]

Компьютерная оптика, 2019
A problem of non-parametric multivariate density estimation for machine learning and data augmentation is considered. A new mixed density estimation method based on calculating the convolution of independently obtained kernel density estimates for ...
Alexander Sirota, Artem Donskikh, Alexey Akimov, Dmitry Minakov   +3 more
doaj   +1 more source

Improved Coresets for Kernel Density Estimates [PDF]

, 2018
We study the construction of coresets for kernel density estimates. That is we show how to approximate the kernel density estimate described by a large point set with another kernel density estimate with a much smaller point set. For characteristic kernels (including Gaussian and Laplace kernels), our approximation preserves the $L_\infty$ error ...
Jeff M. Phillips, Wai Ming Tai
openaire   +3 more sources

Influence of TiC and TiN Ceramic Reinforcements on the Microstructure, Thermal Expansion Behavior, and Tensile Properties of Invar 36 Manufactured by Laser Powder Bed Fusion

Advanced Engineering Materials, EarlyView.
This study examines Invar composites reinforced with titanium carbide (TiC) and titanium nitride (TiN) using laser powder bed fusion (LPBF). It presents the influence of reinforcements on microstructure, tensile properties, and thermal expansion. Results show that TiC effectively strengthens Invar while maintaining low thermal expansion, whereas TiN ...
Ayodeji Nathaniel Oyedeji, Natasha Sacks, Johannes Pötschke, Björn Matthey   +3 more
wiley   +1 more source

Improving Radio Source Count Estimation Using Kernel Density Estimation

The Astrophysical Journal
Radio source counts provide a fundamental census of cosmic radio emission, yet their estimation is usually based on coarse histograms that suffer from bin-choice bias, boundary effects, and survey incompleteness.
Luozhenhan Liu, Zunli Yuan, Wenjie Wang, Chuanqi Li   +3 more
doaj   +1 more source

Leveraging Symbolic Artificial Intelligence and Fuzzy Logic for Materials Science: A Review of Methods, Challenges, and Applications to Scarce and Imperfect Experimental Data

Advanced Engineering Materials, EarlyView.
This article explores the transformative potential of symbolic artificial intelligence (AI) in the field of materials science, particularly in leveraging experimental data. The article presents several symbolic AI models and discusses their applications in materials science.
Ahmed Amrani, Mohamed‐Ali Belloum, Laurence Boudet, Valentin Fouillard, Edwin Friedmann, Guillaume Lacharme, Ali Mahmoud, Jean‐Philippe Poli   +7 more
wiley   +1 more source

Optimal Bandwidth Selection for Kernel Density Functionals Estimation

Journal of Probability and Statistics, 2015
The choice of bandwidth is crucial to the kernel density estimation (KDE) and kernel based regression. Various bandwidth selection methods for KDE and local least square regression have been developed in the past decade.
Su Chen
doaj   +1 more source

Bayesian Bandwidth Selection for a Nonparametric Regression Model with Mixed Types of Regressors

Econometrics, 2016
This paper develops a sampling algorithm for bandwidth estimation in a nonparametric regression model with continuous and discrete regressors under an unknown error density.
Xibin Zhang, Maxwell L. King, Han Lin Shang   +2 more
doaj   +1 more source

A Multi‐Scale Machine Learning Framework for the Inverse Design of High Entropy Alloys

Advanced Engineering Materials, EarlyView.
High‐entropy alloys offer vast potential for various applications, including electrocatalysis; however, their compositional complexity challenges conventional screening. We introduce an inverse‐design framework combining two neural networks to determine optimal compositions and reconstruct nanoparticle geometry from targeted properties and conventional
Mikael Takoutsin, Marta Campolucci, Nicolas de Andrade Ishiki, Nathan Mirgot, Nadir Zhamantay, Frédéric Kanoufi, Jennifer Peron, Jean Charlety, Emiliano Fonda, Valérie Briois, Marco Faustini, Maria‐Letizia De Marco, Christine Goyhenex, Ovidiu Ersen, Hervé Bulou   +14 more
wiley   +1 more source