Results 71 to 80 of about 4,458,250 (263)

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

open access: yesAdvanced 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   +14 more
wiley   +1 more source

ks: Kernel Density Estimation and Kernel Discriminant Analysis for Multivariate Data in R [PDF]

open access: yes
Kernel smoothing is one of the most widely used non-parametric data smoothing techniques. We introduce a new R package ks for multivariate kernel smoothing.
Tarn Duong
core  

Time-weighted kernel density for gearbox residual life prediction

open access: yesScientific Reports
With improvements in industrial automation, the reliability of the gearbox, a key transmission device, has become increasingly crucial for the stable operation of an entire operating system. However, predicting the remaining useful life of the gearbox is
Weizhen Zhang   +4 more
doaj   +1 more source

Enhancing Broiler Weight Prediction via Preprocessed Kernel Density Estimation

open access: yesAgriculture
Accurate broiler weight estimation in commercial farms is hindered by noisy scale data and multi-broiler occupancy. To address this challenge, we propose a KDE-based framework enhanced with systematic preprocessing, including coefficient of variation (CV)
Sangmin Yoo, Yumi Oh, Juwhan Song
doaj   +1 more source

Uncovering patterns of urban growth and infrastructure progress in Grand Casablanca: A descriptive multi-indicator approach [PDF]

open access: yesE3S Web of Conferences
Urbanization in Morocco has intensified, with 65% of the population living in cities by 2022 despite slowing growth rates. Road infrastructure plays a pivotal role in shaping urban form, land-use change, and socio-economic development.
El-Bouayady Rachida   +3 more
doaj   +1 more source

Detecting Anomalous Cell Behavior in Electrochemical Battery Testing Using Machine Learning

open access: yesAdvanced Engineering Materials, EarlyView.
Machine‐learning‐based screening enables automated identification of anomalous battery cells from complementary electrochemical tests. A curated battery database supports configuration‐aware comparison of rate‐capability and impedance data. Supervised classification of rate‐test data achieves 90% accuracy, while CNN‐VAE‐based impedance analysis reaches
Minu Rose   +7 more
wiley   +1 more source

Wearable Smart Patches on Sustainable Chitosan With Reversible Microbial Growth‐Inhibitory Properties

open access: yesAdvanced Functional Materials, EarlyView.
ABSTRACT Chitosan, a polysaccharide upcycled from biowaste, has long promised sustainable, biocompatible, and antimicrobial films and devices, an appeal reinforced by its recent regulatory recognition, with several chitosan‐based antibacterial dressings gaining clearance through the Food and Drug Administration's 510(k) pathway.
Jacopo Nicoletti   +16 more
wiley   +1 more source

Memristive‐Gated RC‐Delay Synaptic Transistors for Time‐Encoded Analog in‐Memory Computing

open access: yesAdvanced Functional Materials, EarlyView.
A Memristive‐Gated Transistor for Time‐Encoded Analog In‐Memory Computing — By exploiting the RC delay of a self‐rectifying interface‐type memristor, nonlinear I–V distortion is structurally bypassed, enabling 3‐bit nonvolatile memory, spike‐timing‐based analog encoding, and hardware‐calibrated reservoir‐computing validation within a unified device ...
Yun‐Seo Shin   +7 more
wiley   +1 more source

A Bayesian approach to parameter estimation for kernel density estimation via transformations [PDF]

open access: yes
In this paper, we present a Markov chain Monte Carlo (MCMC) simulation algorithm for estimating parameters in the kernel density estimation of bivariate insurance claim data via transformations.
David Pitt   +3 more
core  

Autonomous Multi‐Objective Nanoscale Characterization of Combinatorial (Al, Sc, B)N Films Reveals Composition‐Dependent Ferroelectric Regimes

open access: yesAdvanced Functional Materials, EarlyView.
Autonomous scanning probe microscopy and multi‐objective Bayesian optimization navigate a ternary (Al,Sc,B)N combinatorial library. Registered photoluminescence, electron‐probe compositional mapping, and X‐ray diffraction connect local electromechanical function to defect‐sensitive emission, composition, and crystal structure.
Yu Liu   +12 more
wiley   +1 more source

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