Results 91 to 100 of about 115,342 (279)
Nonlinear Process Monitoring Based on Global Preserving Unsupervised Kernel Extreme Learning Machine
IEEE Access, 2019 Recently, the unsupervised extreme learning machine (UELM) technique as a nonlinear data mining approach has been employed to diagnose nonlinear process faults.
Hanyuan Zhang +5 more
doaj +1 more source
Spline Embedding for Nonlinear Dimensionality Reduction [PDF]
, 2006 This paper presents a new algorithm for nonlinear dimensionality reduction (NLDR). Smoothing splines are used to map the locally-coordinatized data points into a single global coordinate system of lower dimensionality. In this work setting, we can achieve two goals.
Shiming Xiang +3 more
openaire +1 more source
A Topology Optimization Framework for the Inverse Design of Nonlinear Mechanical Metamaterials
Advanced Engineering Materials, EarlyView.This work uses topology optimization to design unit cells for mechanical metamaterials with a prescribed nonlinear stress–strain response. The framework adds contact and postbuckling modeling to synthesize microstructures for three highly nonlinear responses, including pseudoductile behavior, monostable with snap‐through buckling, and bistable ...
Charlie Aveline +2 more
wiley +1 more source
IEEE Access, 2017 To improve smoke detection accuracy, we combine local binary pattern (LBP) like features, kernel principal component analysis (KPCA), and Gaussian process regression (GPR) to propose a novel data processing pipeline for smoke detection.
Feiniu Yuan +4 more
doaj +1 more source
Advanced Engineering Materials, EarlyView.Do not let thermal drift and instrument artifacts deceive high‐temperature nanoindentation results. We compare classical Oliver–Pharr and automatic image recognition analyses across steels and a Ni alloy to quantify these effects. Accounting for artifacts reveals systematic softening with temperature, while Cr and Ni additions boost resistance ...
Velislava Yonkova +2 more
wiley +1 more source
Kernel Based Nonlinear Dimensionality Reduction and Classification for Genomic Microarray
Sensors, 2008 Genomic microarrays are powerful research tools in bioinformatics and modern medicinal research because they enable massively-parallel assays and simultaneous monitoring of thousands of gene expression of biological samples.
Lan Shu, Xuehua Li
doaj
International Journal of Mathematics and Mathematical Sciences, 1988 This paper suggests a method of formulating any nonlinear integer programming problem, with any number of constraints, as an equivalent single constraint problem, thus reducing the dimensionality of the associated dynamic programming problem.
Balasubramanian Ram, A. J. G. Babu
doaj +1 more source
Maximum Discriminant Difference Criterion for Dimensionality Reduction of Tensor Data
IEEE Access, 2020 Discriminant analysis is an important tool in machine learning. One of the motivations of this paper is to judge whether a dataset is suitable for discriminant analysis.
Xinya Peng, Zhengming Ma, Haowei Xu
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Optimal linear and nonlinear feature extraction based on the minimization of the increased risk of misclassification [PDF]
General classes of nonlinear and linear transformations were investigated for the reduction of the dimensionality of the classification (feature) space so that, for a prescribed dimension m of this space, the increase of the misclassification risk is ...
Defigueiredo, R. J. P.
core +1 more source
Positive‐Tone Nanolithography of Antimony Trisulfide with Femtosecond Laser Wet‐Etching
Advanced Functional Materials, EarlyView.A butyldithiocarbamic acid (BDCA) etchant is used to fabricate various micro‐ and nanoscale structures on amorphous antimony trisulfide (a‐Sb2S3) thin film via femtosecond laser etching. Numerical analysis and experimental results elucidate the patterning mechanism on gold (reflective) and quartz (transmissive) substrates.
Abhrodeep Dey +12 more
wiley +1 more source