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An assessment of surrogate fuel using Bayesian multiple kernel learning model in sight of sooting tendency

Frontiers in Energy 2022, Volume 16, Issue 2,   Pages 277-291 doi: 10.1007/s11708-021-0731-6

Abstract: surrogate fuels was proposed with the application of a machine learning method, named the Bayesian multiple kernel

Keywords： sooting tendency     yield sooting index     Bayesian multiple kernel learning     surrogate assessment     surrogate    

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Fast implementation of kernel simplex volume analysis based on modified Cholesky factorization for endmember

Jing LI,Xiao-run LI,Li-jiao WANG,Liao-ying ZHAO

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 3,   Pages 250-257 doi: 10.1631/FITEE.1500244

Abstract: The kernel new simplex growing algorithm (KNSGA), recently developed as a nonlinear alternative to the

Keywords： Modified Cholesky factorization     Spatial pixel purity index (SPPI)     New simplex growing algorithm (NSGA)     Kernel    

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Development of soft kernel durum wheat

Craig F. MORRIS

Frontiers of Agricultural Science and Engineering 2019, Volume 6, Issue 3,   Pages 273-278 doi: 10.15302/J-FASE-2019259

Abstract:

Kernel texture (grain hardness) is a fundamental and determining factor related to wheat ( spp.) millingThere are three kernel texture classes in wheat: soft and hard hexaploid ( ), and very hard durum ( subspPhenotypically, the easiest means of quantifying kernel texture is with the Single Kernel CharacterizationSoft kernel durum wheat was created via homeologous recombination using the mutation, which facilitatedExpression of the puroindoline genes in durum grain resulted in kernel texture and flour milling characteristics

Keywords： soft durum wheat     grain hardness     puroindolines     milling     baking     pasta     noodles    

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Boundedness of Marcinkiewicz integralwith rough kernel onTriebel-Lizorkin spaces

Chun-jie ZHANG,Fang-fang REN,Yu-huai ZHANG,Gui-lian GAO

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 8,   Pages 654-657 doi: 10.1631/FITEE.1500082

Abstract: Our result shows that the Marcinkiewicz integral, with a bounded radial function in its kernel, is still

Keywords： Marcinkiewicz integral     Triebel-Lizorkin spaces    

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Image quality assessmentmethod based on nonlinear feature extraction in kernel space Article

Yong DING,Nan LI,Yang ZHAO,Kai HUANG

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 10,   Pages 1008-1017 doi: 10.1631/FITEE.1500439

Abstract: Furthermore, by introducing kernel methods to transform the linear problem into a nonlinear one, a full-reference

Keywords： Image quality assessment     Full-reference method     Feature extraction     Kernel space     Support vector regression    

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Frequency-hopping transmitter fingerprint feature recognition with kernel projection and joint representation Research Articles

Ping SUI, Ying GUO, Kun-feng ZHANG, Hong-guang LI

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 8,   Pages 1133-1146 doi: 10.1631/FITEE.1800025

Abstract: To address these problems, we propose a novel classifier, called the kernel joint representation classifier(KJRC), for FH transmitter fingerprint feature recognition, by integrating kernel projection, collaborative

Keywords： Frequency-hopping     Fingerprint feature     Kernel function     Joint representation     Transmitter recognition    

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Kernel sparse representation for MRI image analysis in automatic brain tumor segmentation None

Ji-jun TONG, Peng ZHANG, Yu-xiang WENG, Dan-hua ZHU

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 4,   Pages 471-480 doi: 10.1631/FITEE.1620342

Abstract: We propose a fully automatic brain tumor segmentation method based on kernel sparse coding.In this method, MRI images are pre-processed first to reduce the noise, and then kernel dictionary learningA kernel-clustering algorithm based on dictionary learning is developed to code the voxels.

Keywords： Brain tumor segmentation     Kernel method     Sparse coding     Dictionary learning    

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Potential hybrid feedstock for biodiesel production in the tropics

Solomon GIWA,Oludaisi ADEKOMAYA,Collins NWAOKOCHA

Frontiers in Energy 2016, Volume 10, Issue 3,   Pages 329-336 doi: 10.1007/s11708-016-0408-8

Abstract: The tropics are renowned for abundant oil-bearing crops of which palm kernel oil (PKO) from palm seed

Keywords： groundnut oil     palm kernel oil     methyl ester     fuel properties     tropics     fatty acid composition    

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Seismic fragility curves for structures using non-parametric representations

Chu MAI, Katerina KONAKLI, Bruno SUDRET

Frontiers of Structural and Civil Engineering 2017, Volume 11, Issue 2,   Pages 169-186 doi: 10.1007/s11709-017-0385-y

Abstract: the fragility curves without employing the above assumption, namely binned Monte Carlo simulation and kernel

Keywords： earthquake engineering     fragility curves     lognormal assumption     non-parametric approach     kernel density estimation    

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Algorithm Design for Improving Feature Extraction Efficiency Based on KPCA

Xu Yong,Yangjingyu,Lu Jianfeng

Strategic Study of CAE 2005, Volume 7, Issue 10,   Pages 38-42

Abstract:

KPCA (kernel PCA) is derived from PCA. It can extract nonlinear feature components of samples.However, feature extraction for one sample requires that kernel functions between training samples andIKPCA extracts feature components of one sample efficiently, only based on kernel functions between nodes

Keywords： KPCA(Kernel PCA)     IKPCA(Improved KPCA)     feature extraction     feature space    

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Outliers detection algorithm based on nonlinear data transformation

Xu Xuesong,Zhang Xu,Song Dongming,Zhang Hong,Liu Fnegyu

Strategic Study of CAE 2008, Volume 10, Issue 9,   Pages 74-78

Abstract:

The data dimension reduction is the main method that can enhance the outliers mining efficiency based on higher-dimension data set. A novel outlier detection algorithm is proposed after analyzing the advantages and disadvantages of the classical outlier mining algorithm in the paper.In this paper, we can transform nonlinear large-scale data into linear data in the feature space,and introduce a nonlinear data transformation to reduce data dimension. On the basis of each resulting vector,it determins whether the data is outlier data or not one by one. This paper shows that the algorithm is not only used to detect linear separable outlier data,but also used to detect nonlinear inseparable outlier data. This indicate that the algorithm has its obvious superiority.

Keywords： dimension reduction     kernel function     principal component     outliers    

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A novel multimode process monitoring method integrating LDRSKM with Bayesian inference

Shi-jin REN,Yin LIANG,Xiang-jun ZHAO,Mao-yun YANG

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 8,   Pages 617-633 doi: 10.1631/FITEE.1400263

Abstract: With the data partition obtained, kernel support vector data description (KSVDD) is used to establish

Keywords： Multimode process monitoring     Local discriminant regularized soft k-means clustering     Kernel support    

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Received signal strength based indoor positioning algorithm using advanced clustering and kernel ridge Research Articles

Yanfen Le, Hena Zhang, Weibin Shi, Heng Yao,leyanfen@usst.edu.cn,hyao@usst.edu.cn

Frontiers of Information Technology & Electronic Engineering 2021, Volume 22, Issue 6,   Pages 827-838 doi: 10.1631/FITEE.2000093

Abstract: Then, a kernel-based ridge regression method is used to obtain the ultimate positioning of the target

Keywords： 室内定位；接收信号强度（RSS）指纹；核岭回归；簇匹配；改进型分簇    

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AED-Net: An Abnormal Event Detection Network Article

Tian Wang, Zichen Miao, Yuxin Chen, Yi Zhou, Guangcun Shan, Hichem Snoussi

Engineering 2019, Volume 5, Issue 5,   Pages 930-939 doi: 10.1016/j.eng.2019.02.008

Abstract: detection network (AED-Net), which is composed of a principal component analysis network (PCAnet) and kernel

Keywords： Abnormal events detection     Abnormal event detection network     Principal component analysis network     Kernel    

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Title Author Date Type Operation

An assessment of surrogate fuel using Bayesian multiple kernel learning model in sight of sooting tendency

Journal Article

Fast implementation of kernel simplex volume analysis based on modified Cholesky factorization for endmember

Jing LI,Xiao-run LI,Li-jiao WANG,Liao-ying ZHAO

Journal Article

Development of soft kernel durum wheat

Craig F. MORRIS

Journal Article

Boundedness of Marcinkiewicz integralwith rough kernel onTriebel-Lizorkin spaces

Chun-jie ZHANG,Fang-fang REN,Yu-huai ZHANG,Gui-lian GAO

Journal Article

Image quality assessmentmethod based on nonlinear feature extraction in kernel space

Yong DING,Nan LI,Yang ZHAO,Kai HUANG

Journal Article

Frequency-hopping transmitter fingerprint feature recognition with kernel projection and joint representation

Ping SUI, Ying GUO, Kun-feng ZHANG, Hong-guang LI

Journal Article

Kernel sparse representation for MRI image analysis in automatic brain tumor segmentation

Ji-jun TONG, Peng ZHANG, Yu-xiang WENG, Dan-hua ZHU

Journal Article

Potential hybrid feedstock for biodiesel production in the tropics

Solomon GIWA,Oludaisi ADEKOMAYA,Collins NWAOKOCHA

Journal Article

Seismic fragility curves for structures using non-parametric representations

Chu MAI, Katerina KONAKLI, Bruno SUDRET

Journal Article

Algorithm Design for Improving Feature Extraction Efficiency Based on KPCA

Xu Yong,Yangjingyu,Lu Jianfeng

Journal Article

Outliers detection algorithm based on nonlinear data transformation

Xu Xuesong,Zhang Xu,Song Dongming,Zhang Hong,Liu Fnegyu

Journal Article

A novel multimode process monitoring method integrating LDRSKM with Bayesian inference

Shi-jin REN,Yin LIANG,Xiang-jun ZHAO,Mao-yun YANG

Journal Article

Received signal strength based indoor positioning algorithm using advanced clustering and kernel ridge

Yanfen Le, Hena Zhang, Weibin Shi, Heng Yao,leyanfen@usst.edu.cn,hyao@usst.edu.cn

Journal Article

AED-Net: An Abnormal Event Detection Network

Tian Wang, Zichen Miao, Yuxin Chen, Yi Zhou, Guangcun Shan, Hichem Snoussi

Journal Article