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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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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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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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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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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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Lung function and air pollution exposure in adults with asthma in Beijing: a 2-year longitudinal panel

Frontiers of Medicine 2022, Volume 16, Issue 4, Pages 574-583 doi: 10.1007/s11684-021-0882-1

Abstract: The effect of air pollution on the lung function of adults with asthma remains unclear to date.The participants were divided into three groups according to their lung function level at every visitA linear mixed-effect model was applied to predict the change in lung function with each unit changeExposure to CO and PM_2.5 was negatively associated with the large airway function of adultsPatients with asthma react differently to air pollutants as evidenced by their lung function levels.

Keywords： lung function asthma air pollution adult

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The function and regulation of OTU deubiquitinases

Jiansen Du, Lin Fu, Yingli Sui, Lingqiang Zhang

Frontiers of Medicine 2020, Volume 14, Issue 5, Pages 542-563 doi: 10.1007/s11684-019-0734-4

Abstract: These OTUs show great variation in structure and function, which display a series of mechanistic featuresIn this review, we provide a comprehensive analysis of current progress in character, structure and functionFinally, we summarize the structure of viral OTUs and their function in immune escape and viral survival

Keywords： ubiquitin OTU deubiquitinases structure function regulation

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Analogue Difference Balanced Function and Its Applications

Zhang Wenying,Li Shiqu

Strategic Study of CAE 2004, Volume 6, Issue 3, Pages 45-52

Abstract:

This paper presents the concept of analogous difference of Boolean function, and call the Booleanfunction an analogue difference balanced function if whose analogous difference is balanced at any nonzeroof analogue bent functions, the paper proposes an efficient and sufficient condition for a logical function

Keywords： Bent function perfect nonlinear function 2-radical expansion analogue difference analogue auto-correlationfunction analogue difference balanced function

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Quality Function Deployment Implementation in Construction: A Systematic Literature Review

Elizabeth A. Cudney,William L. Gillis

Frontiers of Engineering Management 2016, Volume 3, Issue 3, Pages 224-230 doi: 10.15302/J-FEM-2016036

Abstract: Quality function deployment has been successfully used in product development to capture the voice ofQuality function deployment then carries these parameters into production and service to ensure the voiceThe house of quality, a tool within quality function deployment, can provide a means for comparison ofQuality function deployment can effectively link the project phases through design and construction andThe research method used is a systematic literature review from databases related to quality function

Keywords： construction engineering management quality function deployment systematic review

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Design and evaluation of a novel biopsy needle with hemostatic function

Frontiers of Mechanical Engineering 2023, Volume 18, Issue 2, doi: 10.1007/s11465-022-0738-7

Abstract: Biopsy is a method commonly used for early cancer diagnosis. However, bleeding complications of widely available biopsy are risky for patients. Safer biopsy will result in a more accurate cancer diagnosis and a decrease in the risk of complications. In this article, we propose a novel biopsy needle that can reduce bleeding during biopsy procedures and achieve stable hemostasis. The proposed biopsy needle features a compact structure and can be operated easily by left and right hands. A predictive model for puncture force and tip deflection based on coupled Eulerian–Lagrangian (CEL) method is developed. Experimental results show that the biopsy needle can smoothly deliver the gelatin sponge hemostatic plug into the tissue. Although the hemostatic plug bends, the overall delivery process is stable, and the hemostatic plug retains in the tissue without being affected by the withdrawal of the needle. Further experiments indicate that the specimens are well obtained and evenly distributed in the groove of the outer needle without scattering. Our proposed design of biopsy needle possesses strong ability of hemostasis, tissue cutting, and tissue retention. The CEL model accurately predicts the peak of puncture force and produces close estimation of the insertion force at the postpuncture stage and tip position.

Keywords： cancer diagnosis biopsy needle hemostatic function predictive model coupled Eulerian−Lagrangian

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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 maximal inter-storey drift of a building exceeding a certain threshold) is represented as a functionthe 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