Results 51 to 60 of about 260,346 (290)
Multimodal Data‐Driven Microstructure Characterization
Advanced Engineering Materials, EarlyView.A self‐consistent autonomous workflow for EBSP‐based microstructure segmentation by integrating PCA, GMM clustering, and cNMF with information‐theoretic parameter selection, requiring no user input. An optimal ROI size related to characteristic grain size is identified.
Qi Zhang +4 more
wiley +1 more source
Kernel density estimation for stationary random fields [PDF]
, 2014 In this paper, under natural and easily verifiable conditions, we prove the $\mathbb{L}^1$-convergence and the asymptotic normality of the Parzen-Rosenblatt density estimator for stationary random fields of the form $X_k = g\left(\varepsilon_{k-s}, s \in
Machkouri, Mohamed El
core +1 more source
Kernel density estimation for multiclass quantification
Machine Learningfixed broken references to ...
Alejandro Moreo +2 more
openaire +4 more sources
An Experimental High‐Throughput Approach for the Screening of Hard Magnet Materials
Advanced Engineering Materials, EarlyView.An entire workflow for the high‐throughput characterization and analysis of compositionally graded magnetic films is presented. Characterization protocols, data management tools and data analysis approaches are illustrated with test case Sm(Fe, V)12 based films.
William Rigaut +16 more
wiley +1 more source
Advanced Functional Materials, EarlyView.The study presents biodegradable and recyclable mixed‐matrix membranes (MMMs), hydrogels, and cryogels using luminescent nanoscale metal‐organic frameworks (nMOFs) and biopolymers. These bio‐nMOF‐MMMs combine europium‐based nMOFs as probes for the status of the materials with the biopolymers agar and gelatine and present alternatives to conventional ...
Moritz Maxeiner +4 more
wiley +1 more source
Asymptotic Properties of Error Density Estimators in the Two-Phase Linear Regression Model
StatsThis paper investigates kernel estimation of the error density function for the two-phase linear regression model. We derive the asymptotic distributions of residual-based kernel density estimators.
Fuxia Cheng, Lixia Wang
doaj +1 more source
Fault Diagnosis of Rolling Bearings Based on EWT and KDEC
Entropy, 2017 This study proposes a novel fault diagnosis method that is based on empirical wavelet transform (EWT) and kernel density estimation classifier (KDEC), which can well diagnose fault type of the rolling element bearings.
Mingtao Ge, Jie Wang, Xiangyang Ren
doaj +1 more source
Parallel Space-Time Kernel Density Estimation
, 2017 The exponential growth of available data has increased the need for interactive exploratory analysis. Dataset can no longer be understood through manual crawling and simple statistics.
Delmelle, Eric +4 more
core +1 more source
Advanced Functional Materials, EarlyView.Automat optical inspection (AOI) techniques in semiconductor fabrication can be leveraged in battery manufacturing, enabling scalable detection and analysis of electrode‐ and cell‐level imperfections through AI‐driven analytics and a digital‐twin framework.
Jianyu Li, Ertao Hu, Wei Wei, Feifei Shi
wiley +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 +3 more
doaj +1 more source