Results 71 to 80 of about 26,356,550 (281)

Rapidly Solidified High‐Strength Invar 36 Prepared by Planar‐Flow Melt Spinning

open access: yesAdvanced Engineering Materials, EarlyView.
The Invar 36 alloy was rapidly solidified using the planar‐flow melt‐spinning technique. Ribbon samples with thicknesses ranging from 20 to 160 mm were produced. As the grain size of the ribbon decreased to sub‐micron levels, the hardness increased by more than 2 times.
Bekir Akgül, Mehmet Kul
wiley   +1 more source

Research on indoor localization algorithm based on kernel principal component analysis

open access: yesTongxin xuebao, 2017
An indoor localization algorithm based on kernel principal component analysis (KPCA) was proposed.It applied KPCA to train the original location fingerprint (OLF) and extract the nonlinear feature of the OLF data at the offline stage,such that the ...
Hua-liang LI   +2 more
doaj   +2 more sources

High‐Entropy Alloy Interlayers Toward Advanced Joining for High‐Performance Structural Applications: Current Progress and Emerging Challenges

open access: yesAdvanced Engineering Materials, EarlyView.
HEA interlayers offer a versatile route for joining high‐performance structural materials. Their compositional and structural design regulates interfacial reactions, suppresses brittle IMCs, and improves metallurgical bonding. Sandwich interlayers further integrate defect healing with precipitation strengthening, enabling improved strength–ductility ...
Lin Yuan   +4 more
wiley   +1 more source

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

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

On Software Defect Prediction Using Machine Learning

open access: yesJournal of Applied Mathematics, 2014
This paper mainly deals with how kernel method can be used for software defect prediction, since the class imbalance can greatly reduce the performance of defect prediction.
Jinsheng Ren   +3 more
doaj   +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

Inference on point processes with unobserved one-dimensional reference structure [PDF]

open access: yes, 2008
We present a novel approach to examining local anisotropy in planar point processes. Our method is based on a kernel Principal Component Analysis and produces a tensor field that describes local orientation.
Thönnes, Elke   +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

Detecting All Possible Ionospheric Precursors by Kernel-Based Two-Dimensional Principal Component Analysis

open access: yesIEEE Access, 2019
Kernel-based two-dimensional principal component analysis (K2DPCA), a nonlinear method, was performed to examine ionospheric 2-D total electron content (TEC) variations obtained from the NASA Global Differential GPS (GDGPS) network, which consisted of ...
Jyh-Woei Lin   +2 more
doaj   +1 more source

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