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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 byAfter the metric has been learned, a neighborhood graph is constructed in the projected space.

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

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Discoverymethod for distributed denial-of-service attack behavior inSDNs using a feature-pattern graphmodel Special Feature on Future Network-Research Article

Ya XIAO, Zhi-jie FAN, Amiya NAYAK, Cheng-xiang TAN

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 9,   Pages 1195-1208 doi: 10.1631/FITEE.1800436

Abstract: The similarity between nodes is modeled by metric learning and the Mahalanobis distance.

Keywords： Software-defined network     Distributed denial-of-service (DDoS)     Behavior discovery     Distance metric learning    

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A software defect prediction method with metric compensation based on feature selection and transferlearning Research Article

Jinfu CHEN, Xiaoli WANG, Saihua CAI, Jiaping XU, Jingyi CHEN, Haibo CHEN,caisaih@ujs.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 5,   Pages 715-731 doi: 10.1631/FITEE.2100468

Abstract: training efficiency and thus decrease the prediction accuracy of the model; (2) the distribution of metricbetter results on area under the receiver operating characteristic curve (AUC) value and F1-measure metric

Keywords： Defect prediction     Feature selection     Transfer learning     Metric compensation    

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A Local Quadratic Embedding Learning Algorithm and Applications for Soft Sensing Article

Yaoyao Bao, Yuanming Zhu, Feng Qian

Engineering 2022, Volume 18, Issue 11,   Pages 186-196 doi: 10.1016/j.eng.2022.04.025

Abstract:

Inspired by the tremendous achievements of meta-learning in various fields, this paper proposes thelocal quadratic embedding learning (LQEL) algorithm for regression problems based on metric learningFirst, Mahalanobis metric learning is improved by optimizing the global consistency of the metrics betweenThen, we further prove that the improved metric learning problem is equivalent to a convex programming

Keywords： Local quadratic embedding     Metric learning     Regression machine     Soft sensor    

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Improved directional-distance filter

JIN Lianghai, LI Dehua

Frontiers of Mechanical Engineering 2008, Volume 3, Issue 2,   Pages 205-211 doi: 10.1007/s11465-008-0025-2

Abstract: This paper proposes a new spatial-distance weighting function.By combining the weighting function and the traditional directional-distance filter (DDF) in a novelway, a new vector filter - the adaptive distance-weighted directional-distance filter (ADWDDF) - is presented

Keywords： information     distance-weighted directional-distance     ADWDDF     traditional DDF     spatial-distance weighting    

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One-against-all-based Hellinger distance decision tree for multiclass imbalanced learning Research Articles

Minggang DONG, Ming LIU, Chao JING,jingchao@glut.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 2,   Pages 278-290 doi: 10.1631/FITEE.2000417

Abstract: Since traditional machine learning methods are sensitive to skewed distribution and do not consider themulticlass imbalance problems, the skewed distribution of multiclass data poses a major challenge to machine learningcollect 20 public real-world imbalanced data sets from the Knowledge Extraction based on Evolutionary Learning

Keywords： Decision trees     Multiclass imbalanced learning     Node splitting criterion     Hellinger distance     One-against-all    

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Application and evaluation of optical distance measurements in geometrical quality testing of microgears

Albert ALBERS, Duotai PAN, Leif MARXEN, Claudia BECKE,

Frontiers of Mechanical Engineering 2010, Volume 5, Issue 3,   Pages 261-269 doi: 10.1007/s11465-010-0100-3

Abstract: Microgears are increasingly important in industry. Compared to normal gears, the quality assurance of microgears needs more accurately measured data and simple but feasible measurement methods because of their dimension particula

Keywords： microgear     optical distance measurement     profile deviation     CWL sensor     micromechanical technology (MMT)    

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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: Thus, the image-based 3D model retrieval is reduced to a problem of Euclid-to-Riemann metric learningFinally, we design an optimization algorithm to learn a metric in this Hilbert space using a kernel trickAny 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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New method of fault diagnosis of rotating machinery based on distance of information entropy

Houjun SU, Tielin SHI, Fei CHEN, Shuhong HUANG

Frontiers of Mechanical Engineering 2011, Volume 6, Issue 2,   Pages 249-253 doi: 10.1007/s11465-011-0124-3

Abstract: feature index monitoring and diagnosing the vibration fault of rotating machinery, which is called distanceThe mathematic deduction suggests that the conception of distance of information entropy is accordantThen, the accuracy of rotor fault diagnosis can be improved through the curve chart of the distance of

Keywords： rotating machinery     information fusion     fault diagnosis     Information entropy     distance of the information    

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Efficient utilization of wind power: Long-distance transmission or local consumption?

Yuanzhang SUN, Xiyuan MA, Jian XU, Yi BAO, Siyang LIAO

Frontiers of Mechanical Engineering 2017, Volume 12, Issue 3,   Pages 440-455 doi: 10.1007/s11465-017-0440-3

Abstract: Excess wind power produced in wind-intensive areas is normally delivered to remote load centers via long-distanceThis paper presents a comparison between long-distance transmission, which has gained popularity, andFirst, the challenges and solutions to the long-distance transmission and local consumption of wind power

Keywords： wind power     long-distance transmission     local consumption     supermicrogrid    

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Vibration-based hypervelocity impact identification and localization Research Article

Jiao BAO, Lifu LIU, Jiuwen CAO,jwcao@hdu.edu.cn

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 4,   Pages 515-529 doi: 10.1631/FITEE.2000483

Abstract: Hypervelocity impact (HVI) vibration source identification and localization have found wide applications in many fields, such as manned spacecraft protection and machine tool collision damage detection and localization. In this paper, we study the synchrosqueezed transform (SST) algorithm and the texture color distribution (TCD) based HVI source identification and localization using impact images. The extracted SST and TCD image features are fused for HVI image representation. To achieve more accurate detection and localization, the optimal selective stitching features OSSST+TCD are obtained by correlating and evaluating the similarity between the sample label and each dimension of the features. Popular conventional classification and regression models are merged by voting and stacking to achieve the final detection and localization. To demonstrate the effectiveness of the proposed algorithm, the HVI data recorded from three kinds of high-speed bullet striking on an aluminum alloy plate is used for experimentation. The experimental results show that the proposed HVI identification and localization algorithm is more accurate than other algorithms. Finally, based on sensor distribution, an accurate four-circle centroid localization algorithm is developed for HVI source coordinate localization.

Keywords： Ensemble learning     Synchrosqueezied transform     Gray-level co-occurrence matrix     Image entropy     Distance    

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Cracking resistance performance of super vertical-distance pumped SFRC

JIANG Jinyang, SUN Wei, ZHANG Yunsheng, CHEN Cuicui, WANG Jing

Frontiers of Structural and Civil Engineering 2008, Volume 2, Issue 2,   Pages 179-183 doi: 10.1007/s11709-008-0018-6

Abstract: The mix ratio of steel fiber reinforced concrete (SFRC) was optimized using the principles that workability must meet the pumping demand and anti-cracking performance should be optimal. The effect of SFRC on the initial cracking load, the ultimate load and the crack width of the reinforced concrete (RC) member were analyzed in this paper. It was found that the admixture had good preservation of moisture and adhesion and the fibers distributed homogeneously in one hour out of the machine. According to the pumping results, the SFRC could be pumped vertically up to 306 m. Based on the standard computation formula of cracks, the maximum crack width of an RC member with 0.8% steel fiber (by volume) is about 32% lower than that of standard RC member. Through an experimental research on full-scale model tests for the steel and concrete composite anchorage zone on a pylon, the SFRC not only remarkably increases the crack resistance and the ultimate load, but the initial load also improves 33% approximately. It is also indicated that plastic shrinkage cracking of SFRC in which volume fraction of steel fibers is 0.8% can be restrained obviously and the unrestrained drying shrinkage can be diminished by about 50% at early age. The results confirmed that the SFRC can lessen the shrinkage crack of concrete and enhance markedly the direct tensile strength. Therefore, the SFRC can solve the key question of crack resistance for the anchorage zone of a bridge tower.
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Variable eccentric distance-based tool path generation for orthogonal turn-milling

Fangyu PENG,Wei WANG,Rong YAN,Xianyin DUAN,Bin LI

Frontiers of Mechanical Engineering 2015, Volume 10, Issue 4,   Pages 352-366 doi: 10.1007/s11465-015-0361-y

Abstract: proposes an algorithm for maximizing strip width in orthogonal turn-milling based on variable eccentric distanceThe optimized model for maximum machining strip width is formulated by adopting a variable eccentric distanceHausdorff distance and Fréchet distance are introduced in this study to implement the constraint

Keywords： orthogonal turn-milling     variable eccentric distance     local cutting profile     machining strip-width maximization    

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Equitableness to long-distance of disaster reduction systems

Yao Qinglin

Strategic Study of CAE 2009, Volume 11, Issue 6,   Pages 153-158

Abstract:

The equitableness to long-distance of the disaster reduction aims atby partition and deformation of the territory, localization of the center and the corresponding long-distanceachieving-degree of the technical indexes in a weaker condition can be improved.The equitableness to long-distancecan remedy system's flaw by the long-distance mechanism or construct the complete system in an incomplete

Keywords： equitableness to long-distance     disaster reduction     management     earthquake    

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Representation learning via a semi-supervised stacked distance autoencoder for image classification Research Articles

Liang Hou, Xiao-yi Luo, Zi-yang Wang, Jun Liang,jliang@zju.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 7,   Pages 963-1118 doi: 10.1631/FITEE.1900116

Abstract: is an important application of deep learning.classification task, the classification accuracy is strongly related to the features that are extracted via deep learningThe proposed method is based on the traditional , incorporating the “distance” information between samplesThe model is called a semi-supervised distance .The proposed semi-supervised distance method is compared with the traditional , sparse , and supervised

Keywords： 自动编码器；图像分类；半监督学习；神经网络    

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Title Author Date Type Operation

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

Discoverymethod for distributed denial-of-service attack behavior inSDNs using a feature-pattern graphmodel

Ya XIAO, Zhi-jie FAN, Amiya NAYAK, Cheng-xiang TAN

Journal Article

A software defect prediction method with metric compensation based on feature selection and transferlearning

Jinfu CHEN, Xiaoli WANG, Saihua CAI, Jiaping XU, Jingyi CHEN, Haibo CHEN,caisaih@ujs.edu.cn

Journal Article

A Local Quadratic Embedding Learning Algorithm and Applications for Soft Sensing

Yaoyao Bao, Yuanming Zhu, Feng Qian

Journal Article

Improved directional-distance filter

JIN Lianghai, LI Dehua

Journal Article

One-against-all-based Hellinger distance decision tree for multiclass imbalanced learning

Minggang DONG, Ming LIU, Chao JING,jingchao@glut.edu.cn

Journal Article

Application and evaluation of optical distance measurements in geometrical quality testing of microgears

Albert ALBERS, Duotai PAN, Leif MARXEN, Claudia BECKE,

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

New method of fault diagnosis of rotating machinery based on distance of information entropy

Houjun SU, Tielin SHI, Fei CHEN, Shuhong HUANG

Journal Article

Efficient utilization of wind power: Long-distance transmission or local consumption?

Yuanzhang SUN, Xiyuan MA, Jian XU, Yi BAO, Siyang LIAO

Journal Article

Vibration-based hypervelocity impact identification and localization

Jiao BAO, Lifu LIU, Jiuwen CAO,jwcao@hdu.edu.cn

Journal Article

Cracking resistance performance of super vertical-distance pumped SFRC

JIANG Jinyang, SUN Wei, ZHANG Yunsheng, CHEN Cuicui, WANG Jing

Journal Article

Variable eccentric distance-based tool path generation for orthogonal turn-milling

Fangyu PENG,Wei WANG,Rong YAN,Xianyin DUAN,Bin LI

Journal Article

Equitableness to long-distance of disaster reduction systems

Yao Qinglin

Journal Article

Representation learning via a semi-supervised stacked distance autoencoder for image classification

Liang Hou, Xiao-yi Luo, Zi-yang Wang, Jun Liang,jliang@zju.edu.cn

Journal Article