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A multistandard and resource-efficient Viterbi decoder for a multimode communication system None

Yi-qi XIE, Zhi-guo YU, Yang FENG, Lin-na ZHAO, Xiao-feng GU

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 4,   Pages 536-543 doi: 10.1631/FITEE.1601596

Abstract: We present a novel standard convolutional symbols generator (SCSG) block for a multi-parameter reconfigurableThe SCSG block generates all the states and calculates all the possible standard convolutional symbols

Keywords： Reconfigurable Viterbi decoder     Multi-parameter     Low resource consumption     Standard convolutional symbols    

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Classifying multiclass relationships between ASes using graph convolutional network

Frontiers of Engineering Management   Pages 653-667 doi: 10.1007/s42524-022-0217-1

Abstract: We then introduce new features and propose a graph convolutional network (GCN) framework, AS-GCN, to

Keywords： autonomous system     multiclass relationship     graph convolutional network     classification algorithm     Internet    

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A novel method based on convolutional neural networks for deriving standard 12-lead ECG from serial 3 Regular Papers

Lu-di WANG, Wei ZHOU, Ying XING, Na LIU, Mahmood MOVAHEDIPOUR, Xiao-guang ZHOU

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 3,   Pages 405-413 doi: 10.1631/FITEE.1700413

Abstract: In this study, we present a novel method based on convolutional neural networks (CNNs) for the synthesisshown to be more accurate and time-saving for deployment in non-hospital situations to synthesize a standard

Keywords： Convolutional neural networks (CNNs)     Electrocardiogram (ECG) synthesis     E-health    

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A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 2, doi: 10.1007/s11465-022-0673-7

Abstract: Convolutional neural network (CNN) has achieved remarkable applications in fault diagnosis.

Keywords： deep reinforcement learning     hyper parameter optimization     convolutional neural network     fault diagnosis    

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Automated classification of civil structure defects based on convolutional neural network

Pierclaudio SAVINO, Francesco TONDOLO

Frontiers of Structural and Civil Engineering 2021, Volume 15, Issue 2,   Pages 305-317 doi: 10.1007/s11709-021-0725-9

Abstract: challenge, this paper presents a method for automating concrete damage classification using a deep convolutionalThe convolutional neural network was designed after an experimental investigation of a wide number of

Keywords： concrete structure     infrastructures     visual inspection     convolutional neural network     artificial intelligence    

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Deep convolutional neural network for multi-level non-invasive tunnel lining assessment

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 2,   Pages 214-223 doi: 10.1007/s11709-021-0800-2

Abstract: Such strategy leverages the high capacity of convolutional neural networks to identify and classify potential

Keywords： concrete structure     GPR     damage classification     convolutional neural network     transfer learning    

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Fault diagnosis of axial piston pumps with multi-sensor data and convolutional neural network

Frontiers of Mechanical Engineering 2022, Volume 17, Issue 3, doi: 10.1007/s11465-022-0692-4

Abstract: pressure signals under different pump health conditions are fused into RGB images and then recognized by a convolutional

Keywords： axial piston pump     fault diagnosis     convolutional neural network     multi-sensor data fusion    

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Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 4,   Pages 814-828 doi: 10.1007/s11465-021-0650-6

Abstract: address this issue, this paper explores a decision-tree-structured neural network, that is, the deep convolutionalThe proposed model effectively integrates the advantages of convolutional neural network (CNN) and decision

Keywords： bearing     cross-severity fault diagnosis     hierarchical fault diagnosis     convolutional neural network    

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Slope stability analysis based on big data and convolutional neural network

Yangpan FU; Mansheng LIN; You ZHANG; Gongfa CHEN; Yongjian LIU

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 7,   Pages 882-895 doi: 10.1007/s11709-022-0859-4

Abstract: In this case, the convolutional neural network (CNN) provides a better alternative.

Keywords： slope stability     limit equilibrium method     convolutional neural network     database for slopes     big data    

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Research on the ecological compensation standard of the basin pollution control project based on evolutionary

Dongbin HU, Huiwu LIU, Xiaohong CHEN, Yang CHEN

Frontiers of Engineering Management 2019, Volume 6, Issue 4,   Pages 575-583 doi: 10.1007/s42524-019-0044-1

Abstract: Ecological compensation is a new resource and environment management model. As one of the main areas for implementing ecological compensation policies, basin ecological compensation has become an important measure for encouraging basin pollution control projects and improving the quality of regional economic development. By applying the basic game analysis of evolutionary game theory and building an evolutionary game model with a “reward–punishment” mechanism, this paper compares the interest-related decision-making behaviors of the upstream and downstream stakeholders of basin ecological compensation. By using data on the water quality of Xiangjiang River Basin, this paper calculates the rewards and penalties in different intervals by building a parametric regression mathematical model and employing the local linear regression method. Results show that a decline in water quality should be fined RMB 925500 yuan, an improvement in water quality should be awarded RMB 1227800 yuan, and a deteriorating water quality should be severely fined RMB 5087600 yuan.

Keywords： evolutionary game     ecological compensation standard     Xiangjiang River Basin    

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Efficient, high-resolution topology optimization method based on convolutional neural networks

Liang XUE, Jie LIU, Guilin WEN, Hongxin WANG

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 1,   Pages 80-96 doi: 10.1007/s11465-020-0614-2

Abstract: efficient, high-resolution topology optimization method is developed based on the super-resolution convolutional

Keywords： topology optimization     convolutional neural network     high resolution     density-based    

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Detecting large-scale underwater cracks based on remote operated vehicle and graph convolutional neural

Wenxuan CAO; Junjie LI

Frontiers of Structural and Civil Engineering 2022, Volume 16, Issue 11,   Pages 1378-1396 doi: 10.1007/s11709-022-0855-8

Abstract: The graph convolutional neural network (GCN) was used to segment the stitched image.The GCN’s m-IOU is 24.02% higher than Fully convolutional networks (FCN), proving that GCN has

Keywords： underwater cracks     remote operated vehicle     image stitching     image segmentation     graph convolutional    

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Standard model of knowledge representation

Wensheng YIN

Frontiers of Mechanical Engineering 2016, Volume 11, Issue 3,   Pages 275-288 doi: 10.1007/s11465-016-0372-3

Abstract: According to ontology, system theory, and control theory, a standard model of knowledge representationIn addition, the standard model of knowledge representation provides a way to solve problems of non-precision

Keywords： knowledge representation     standard model     ontology     system theory     control theory     multidimensional representation    

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Overview of the quality standard research of traditional Chinese medicine

Huimin Gao, Zhimin Wang, Yujuan Li, Zhongzhi Qian

Frontiers of Medicine 2011, Volume 5, Issue 2,   Pages 195-202 doi: 10.1007/s11684-011-0134-x

Abstract: In this review, the progress of the development and the current status of quality standard as well as

Keywords： traditional Chinese medicine     quality standard     quality control     quantitative analysis of multi-components    

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A Standard for the Commissioning Process

William L. Gillis,Elizabeth A. Cudney

Frontiers of Engineering Management 2015, Volume 2, Issue 1,   Pages 39-51 doi: 10.15302/J-FEM-2015006

Abstract: four-phase model can accomplish this by filling the gaps among the major Cx activities and provide a standardinvestigates some potential reasons for inconsistent Cx services, presents an argument for the need of a Cx standard, and proposes a potential standard.

Keywords： construction     engineering management     quality     commissioning    

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Title Author Date Type Operation

A multistandard and resource-efficient Viterbi decoder for a multimode communication system

Yi-qi XIE, Zhi-guo YU, Yang FENG, Lin-na ZHAO, Xiao-feng GU

Journal Article

Classifying multiclass relationships between ASes using graph convolutional network

Journal Article

A novel method based on convolutional neural networks for deriving standard 12-lead ECG from serial 3

Lu-di WANG, Wei ZHOU, Ying XING, Na LIU, Mahmood MOVAHEDIPOUR, Xiao-guang ZHOU

Journal Article

A new automatic convolutional neural network based on deep reinforcement learning for fault diagnosis

Journal Article

Automated classification of civil structure defects based on convolutional neural network

Pierclaudio SAVINO, Francesco TONDOLO

Journal Article

Deep convolutional neural network for multi-level non-invasive tunnel lining assessment

Journal Article

Fault diagnosis of axial piston pumps with multi-sensor data and convolutional neural network

Journal Article

Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical

Journal Article

Slope stability analysis based on big data and convolutional neural network

Yangpan FU; Mansheng LIN; You ZHANG; Gongfa CHEN; Yongjian LIU

Journal Article

Research on the ecological compensation standard of the basin pollution control project based on evolutionary

Dongbin HU, Huiwu LIU, Xiaohong CHEN, Yang CHEN

Journal Article

Efficient, high-resolution topology optimization method based on convolutional neural networks

Liang XUE, Jie LIU, Guilin WEN, Hongxin WANG

Journal Article

Detecting large-scale underwater cracks based on remote operated vehicle and graph convolutional neural

Wenxuan CAO; Junjie LI

Journal Article

Standard model of knowledge representation

Wensheng YIN

Journal Article

Overview of the quality standard research of traditional Chinese medicine

Huimin Gao, Zhimin Wang, Yujuan Li, Zhongzhi Qian

Journal Article

A Standard for the Commissioning Process

William L. Gillis,Elizabeth A. Cudney

Journal Article