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Iterative HOEO fusion strategy: a promising tool for enhancing bearing fault feature

Frontiers of Mechanical Engineering 2023, Volume 18, Issue 1, doi: 10.1007/s11465-022-0725-z

Abstract: Second, an enhanced manifold learning algorithm is performed on the normalized MDIM to extract the intrinsic

Keywords： higher order energy operator     fault diagnosis     manifold learning     rolling element bearing     information    

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Passive millimeter-wave target recognition based on Laplacian eigenmaps

Luo Lei,Li Yuehua,Luan Yinghong

Strategic Study of CAE 2010, Volume 12, Issue 3,   Pages 77-81

Abstract: millimeter-wave (MMW) metal target recognition, the existence and characteristics of low dimensional manifoldof the short-time Fourier spectrum of metal target echo signal are explored using manifold learningcomparing the similarity of the test samples and the positive class in terms of the low dimensional manifold

Keywords： manifold learning     Laplacian eigenmaps     nonlinear dimensionality reduction     low dimensional manifold     MMW    

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The research of detection of outliers based on manifold lear ning

Xu Xuesong,Song Dongming,Zhang Xu,Xu Manwu,Liu Fengyu

Strategic Study of CAE 2009, Volume 11, Issue 2,   Pages 82-87

Abstract: The research of detection of outliers based on manifold learning is proposed after analyzing the advantagesLinear Embedding algorithm (LLE) is an effective technique for nonlinear dimensionality reduction in manifoldlearning.

Keywords： manifold learning     detection of outliers     high dimensional data     dimensionality reduction     outliers    

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Face recognition based on subset selection via metric learning on manifold

Hong SHAO,Shuang CHEN,Jie-yi ZHAO,Wen-cheng CUI,Tian-shu YU

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 12,   Pages 1046-1058 doi: 10.1631/FITEE.1500085

Abstract: In this paper, we employ a metric learning approach which helps find the active elements correctly bytaking into account the interclass/intraclass relationship and manifold structure of face images.

Keywords： Face recognition     Sparse representation     Manifold structure     Metric learning     Subset selection    

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Laplacian sparse dictionary learning for image classification based on sparse representation Article

Fang LI, Jia SHENG, San-yuan ZHANG

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 11,   Pages 1795-1805 doi: 10.1631/FITEE.1600039

Abstract: proved to be a powerful tool for solving problems in various fields such as pattern recognition, machine learningAs one of the building blocks of the sparse representation method, dictionary learning plays an importantrepresentative dictionary, in this paper, we propose an approach called Laplacian sparse dictionary (LSD) learningOur method is based on manifold learning and double sparsity.

Keywords： Sparse representation     Laplacian regularizer     Dictionary learning     Double sparsity     Manifold    

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Image-based 3D model retrieval using manifold learning None

Pan-pan MU, San-yuan ZHANG, Yin ZHANG, Xiu-zi YE, Xiang PAN

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 11,   Pages 1397-1408 doi: 10.1631/FITEE.1601764

Abstract: views of a 3D model as a symmetric positive definite (SPD) matrix, which is a point on a Riemannian manifoldThus, the image-based 3D model retrieval is reduced to a problem of Euclid-to-Riemann metric learningTo solve this heterogeneous matching problem, we map the Euclidean space and SPD Riemannian manifoldAny new image descriptors, such as the features from deep learning, can be easily embedded in our framework

Keywords： Model retrieval     Euclidean space     Riemannian manifold     Hilbert space     Metric learning    

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Simulation of viscoelastic behavior of defected rock by using numerical manifold method

Feng REN, Lifeng FAN, Guowei MA

Frontiers of Structural and Civil Engineering 2011, Volume 5, Issue 2,   Pages 199-207 doi: 10.1007/s11709-011-0102-1

Abstract: of longitudinal wave propagation in a rock bar with microcracks are conducted by using the numerical manifoldFirstly, validation of the numerical manifold method is carried out by simulations of a longitudinal

Keywords： stress wave propagation     defected rock     numerical manifold method     viscoelastic behavior     storage modulus    

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Rotation errors in numerical manifold method and a correction based on large deformation theory

Ning ZHANG, Xu LI, Qinghui JIANG, Xingchao LIN

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 5,   Pages 1036-1053 doi: 10.1007/s11709-019-0535-5

Abstract: Numerical manifold method (NMM) is an effective method for simulating block system, however, significant

Keywords： numerical manifold method     rotation     large deformation     Green strain     open-close iteration    

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Actor–Critic Reinforcement Learning and Application in Developing Computer-Vision-Based Interface Tracking Article

Oguzhan Dogru, Kirubakaran Velswamy, Biao Huang

Engineering 2021, Volume 7, Issue 9,   Pages 1248-1261 doi: 10.1016/j.eng.2021.04.027

Abstract: A reinforcement learning (RL) agent successfully tracks an interface between two liquids, which is oftenUnlike supervised learning (SL) methods that rely on a huge number of parameters, this approach requires

Keywords： Interface tracking     Object tracking     Occlusion     Reinforcement learning     Uniform manifold approximation    

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Intrinsic feature extraction using discriminant diffusion mapping analysis for automated tool wear evaluation None

Yi-xiang HUANG, Xiao LIU, Cheng-liang LIU, Yan-ming LI

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 11,   Pages 1352-1361 doi: 10.1631/FITEE.1601512

Abstract:

We present a method of discriminant diffusion maps analysis (DDMA) for evaluating tool wear during milling processes. As a dimensionality reduction technique, the DDMA method is used to fuse and reduce the original features extracted from both the time and frequency domains, by preserving the diffusion distances within the intrinsic feature space and coupling the features to a discriminant kernel to refine the information from the high-dimensional feature space. The proposed DDMA method consists of three main steps: (1) signal processing and feature extraction; (2) intrinsic dimensionality estimation; (3) feature fusion implementation through feature space mapping with diffusion distance preservation. DDMA has been applied to current signals measured from the spindle in a machine center during a milling experiment to evaluate the tool wear status. Compared with the popular principle component analysis method, DDMA can better preserve the useful intrinsic information related to tool wear status. Thus, two important aspects are highlighted in this study: the benefits of the significantly lower dimension of the intrinsic features that are sensitive to tool wear, and the convenient availability of current signals in most industrial machine centers.

Keywords： Tool condition monitoring     Manifold learning     Dimensionality reduction     Diffusion mapping analysis     Intrinsic    

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Aircraft safety analysis based on differential manifold theory and bifurcation method None

Chi ZHOU, Ying-hui LI, Wu-ji ZHENG, Peng-wei WU

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 2,   Pages 292-299 doi: 10.1631/FITEE.1700435

Abstract: To solve this issue, the differential manifold theory is introduced to determine the safety envelope.

Keywords： Loss of control     Safety envelope     Aircraft dynamic     Bifurcation analysis     Differential manifold theory    

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Application of New Technology in Underground Engineering

Ma Hongqi

Strategic Study of CAE 2002, Volume 4, Issue 11,   Pages 37-41

Abstract:

Although the PD value of high-pressure manifold in Guangzhou Pumped-storage Project reaches 58 000kN.m, the reinforcement concrete manifold is applied in the project instead of the conventional steelmanifold.The design principle for such kind of manifold is based on bearing the water pressure mainly by the surroundingThe practice proves that this kind of manifold is reliable in performance, efficient in cost and excellent

Keywords： hydropower     underground engineering     manifold     inclined-shaft     new technology    

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MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 6, doi: 10.1007/s11783-023-1677-1

Abstract:

● MSWNet was proposed to classify municipal solid waste.

Keywords： Municipal solid waste sorting     Deep residual network     Transfer learning     Cyclic learning rate     Visualization    

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Spatial prediction of soil contamination based on machine learning: a review

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 8, doi: 10.1007/s11783-023-1693-1

Abstract:

● A review of machine learning (ML) for spatial prediction of soil

Keywords： Soil contamination     Machine learning     Prediction     Spatial distribution    

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Study on emissions reduction of DMCC engine with oxidation catalyst

YAO Chunde, LIU Xibo, WANG Hongfu, LIU Xiaoping, CHENG Chuanhui, WANG Yinshan

Frontiers in Energy 2007, Volume 1, Issue 4,   Pages 441-445 doi: 10.1007/s11708-007-0064-4

Abstract: combustion model diesel/methanol compound combustion (DMCC) is presented, in which methanol is injected into manifold

Keywords： combustion     manifold     DMCC     emission     diesel/methanol compound    

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Title Author Date Type Operation

Iterative HOEO fusion strategy: a promising tool for enhancing bearing fault feature

Journal Article

Passive millimeter-wave target recognition based on Laplacian eigenmaps

Luo Lei,Li Yuehua,Luan Yinghong

Journal Article

The research of detection of outliers based on manifold lear ning

Xu Xuesong,Song Dongming,Zhang Xu,Xu Manwu,Liu Fengyu

Journal Article

Face recognition based on subset selection via metric learning on manifold

Hong SHAO,Shuang CHEN,Jie-yi ZHAO,Wen-cheng CUI,Tian-shu YU

Journal Article

Laplacian sparse dictionary learning for image classification based on sparse representation

Fang LI, Jia SHENG, San-yuan ZHANG

Journal Article

Image-based 3D model retrieval using manifold learning

Pan-pan MU, San-yuan ZHANG, Yin ZHANG, Xiu-zi YE, Xiang PAN

Journal Article

Simulation of viscoelastic behavior of defected rock by using numerical manifold method

Feng REN, Lifeng FAN, Guowei MA

Journal Article

Rotation errors in numerical manifold method and a correction based on large deformation theory

Ning ZHANG, Xu LI, Qinghui JIANG, Xingchao LIN

Journal Article

Actor–Critic Reinforcement Learning and Application in Developing Computer-Vision-Based Interface Tracking

Oguzhan Dogru, Kirubakaran Velswamy, Biao Huang

Journal Article

Intrinsic feature extraction using discriminant diffusion mapping analysis for automated tool wear evaluation

Yi-xiang HUANG, Xiao LIU, Cheng-liang LIU, Yan-ming LI

Journal Article

Aircraft safety analysis based on differential manifold theory and bifurcation method

Chi ZHOU, Ying-hui LI, Wu-ji ZHENG, Peng-wei WU

Journal Article

Application of New Technology in Underground Engineering

Ma Hongqi

Journal Article

MSWNet: A visual deep machine learning method adopting transfer learning based upon ResNet 50 for municipal

Journal Article

Spatial prediction of soil contamination based on machine learning: a review

Journal Article

Study on emissions reduction of DMCC engine with oxidation catalyst

YAO Chunde, LIU Xibo, WANG Hongfu, LIU Xiaoping, CHENG Chuanhui, WANG Yinshan

Journal Article