Results 61 to 70 of about 194,949 (275)

Creep‐Induced Microstructural Evolution in an A2‐B2 Superalloy

Advanced Engineering Materials, EarlyView.
A 27.3Ta‐27.3Mo‐27.3Ti‐8Cr‐10Al (at.%) refractory high‐entropy alloy with precipitation‐strengthened A2‐B2 microstructure was studied by creep tests at 1030°C, which demonstrate a transition in deformation mechanisms in the range of 100–150 MPa applied stress. This is associated with changes in dislocation–precipitate interactions. Relevant deformation
Liu Yang, Aparajita Pramanik, Sandipan Sen, Shubhashis Dixit, Marcel Muench, R. J. Vikram, Daniel Schliephake, Yolita M. Eggeler, Ankur Chauhan, Martin Heilmaier, Alexander Kauffmann   +10 more
wiley   +1 more source

Face Recognition System Based on Kernel Principle Component Analysis and Fuzzy-Support Vector Machine

Tikrit Journal of Pure Science, 2018
In recent year, Face recognition system has taken much attention and used for different types of purposes for instance web application authentication, online investment and banking, mobile authentication, smart home security, virtual reality, database ...
Harith A. Hussein
doaj   +1 more source

Nonlinear Fault Detection of Batch Processes Using Functional Local Kernel Principal Component Analysis

IEEE Access, 2020
In order to guarantee and improve the product quality, the data-driven fault detection technique has been widely used in industry. For three-way datasets of batch process in industry process (i.e., batch × variable × time), a novel method ...
Fei He, Zhiyan Zhang
doaj   +1 more source

Influence of Test Temperature and Test Frequency on Fatigue Life of Aluminum Alloy EN AW‐2618A

Advanced Engineering Materials, EarlyView.
The influence of test temperature and test frequency on the fatigue life of EN AW‐2618A is investigated. High‐cycle fatigue tests are performed at different test temperatures and frequencies on the 1000 h/230°C overaged state. Both test parameters reduce fatigue life due to time‐dependent damage mechanisms.
Ying Han, Julian M. Rosalie, Jan Radners, Mauro Madia, Philipp von Hartrott, Birgit Skrotzki   +5 more
wiley   +1 more source

Face Recognition Algorithm Fused Kernel Principal Component Analysis and Minimum Distance Discriminant Projection [PDF]

Jisuanji gongcheng, 2016
By fusing Kernel Principal Component Analysis(KPCA) and Minimum Distance Projection(MDP),a new method based on the original minimum distance differential projection is developed to address the face recognition problem.Different from the classical minimum-
LIU Jun,HUANG Yanqi,XIONG Bangshu
doaj   +1 more source

Quantum machine learning for quantum anomaly detection

, 2017
Anomaly detection is used for identifying data that deviate from `normal' data patterns. Its usage on classical data finds diverse applications in many important areas like fraud detection, medical diagnoses, data cleaning and surveillance.
Liu, Nana, Rebentrost, Patrick
core   +1 more source

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, Pierre Le Berre, Hamdi Jaballah, Lukas Fink, Victor Poline, Richard Haettel, Stéphane Grenier, Gilbert Chahine, Ewen Bellec, Guillaume Buatier, Wilfried Hortschitz, Santa Pile, Thomas Schrefl, Nils Blanc, Yuan Hong, Thibaut Devillers, Nora M. Dempsey   +16 more
wiley   +1 more source

A comparative study to examine principal component analysis and kernel principal component analysis-based weighting layer for convolutional neural networks

Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization
In the recent decay, the focus on processing signal data processing such as time series, images, and videos increased. The purpose of this processing is mainly forecasting, classification, and regression.
Amir Mehrabinezhad, Mohammad Teshnehlab, Arash Sharifi   +2 more
doaj   +1 more source

Nonlinear Multimode Industrial Process Fault Detection Using Modified Kernel Principal Component Analysis

IEEE Access, 2017
Kernel principal component analysis (KPCA) has been a state-of-the-art nonlinear process monitoring method. However, KPCA assumes the single operation mode while the real industrial processes often run under multiple operation conditions.
Xiaogang Deng, Na Zhong, Lei Wang
doaj   +1 more source

An iterative algorithm for robust kernel principal component analysis [PDF]

Neurocomputing, 2011
We introduce a technique to improve iterative kernel principal component analysis (KPCA) robust to outliers due to undesirable artifacts such as noises, alignment errors, or occlusion. The proposed iterative robust KPCA (rKPCA) links the iterative updating and robust estimation of principal directions.
Hsin-Hsiung Huang, Yi-Ren Yeh
openaire   +1 more source