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A New Sufficient Conditions and Hamiltonian graphs

Zhao Kewen

Strategic Study of CAE 2003, Volume 5, Issue 11,   Pages 61-64

Abstract:

Let G be a simple graph, δ and a be minimum degree and independence number of G, respectively, Faudree et al showed, in 1991, the Hamiltonian result with condition | N(x)∪ N(y) | ≥n-8.In 1993, Chen further considered the Hamiltonian with condition max |d{x) , d(y)| n/2 for each pair ofIn this paper a sufficient condition for a graph to be Hamiltonian graph is shown and the following resultis obtained ： let G be a 2-connected graph of order n , if| N(x) U N(y) |≥ n-δ-1 for each pair

Keywords： Hamiltonian graph     neighborhood union conditions     minimum degree     independence number    

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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 review on different theoretical models of electrocaloric effect for refrigeration

Frontiers in Energy 2023, Volume 17, Issue 4,   Pages 478-503 doi: 10.1007/s11708-023-0884-6

Abstract: First, it provides four different calculation scales (the first-principle-based effective Hamiltonian

Keywords： electrocaloric effect     effective Hamiltonian     phase-field modeling     different theoretical models    

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Large-scale graph processing systems: a survey Review

Ning LIU, Dong-sheng LI, Yi-ming ZHANG, Xiong-lve LI

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 3,   Pages 384-404 doi: 10.1631/FITEE.1900127

Abstract: Graph is a significant data structure that describes the relationship between entries.Many application domains in the real world are heavily dependent on graph data.However, graph applications are vastly different from traditional applications.of specific graph processing platforms.In this survey, we systematically categorize the graph workloads and applications, and provide a detailed

Keywords： Graph workloads     Graph applications     Graph processing systems    

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Modelling of dynamic contact length in rail grinding process

Shaodan ZHI,Jianyong LI,A. M. ZAREMBSKI

Frontiers of Mechanical Engineering 2014, Volume 9, Issue 3,   Pages 242-248 doi: 10.1007/s11465-014-0305-y

Abstract:

Rails endure frequent dynamic loads from the passing trains for supporting trains and guiding wheels. The accumulated stress concentrations will cause the plastic deformation of rail towards generating corrugations, contact fatigue cracks and also other defects, resulting in more dangerous status even the derailment risks. So the rail grinding technology has been invented with rotating grinding stones pressed on the rail with defects removal. Such rail grinding works are directed by experiences rather than scientifically guidance, lacking of flexible and scientific operating methods. With grinding control unit holding the grinding stones, the rail grinding process has the characteristics not only the surface grinding but also the running railway vehicles. First of all, it’s important to analyze the contact length between the grinding stone and the rail, because the contact length is a critical parameter to measure the grinding capabilities of stones. Moreover, it’s needed to build up models of railway vehicle unit bonded with the grinding stone to represent the rail grinding car. Therefore the theoretical model for contact length is developed based on the geometrical analysis. And the calculating models are improved considering the grinding car’s dynamic behaviors during the grinding process. Eventually, results are obtained based on the models by taking both the operation parameters and the structure parameters into the calculation, which are suitable for revealing the process of rail grinding by combining the grinding mechanism and the railway vehicle systems.

Keywords： rail grinding     contact length     dynamic model     Hamiltonian system     grinding stone     rail grinding car    

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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.

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

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Distributed coordination inmulti-agent systems: a graph Laplacian perspective

Zhi-min HAN,Zhi-yun LIN,Min-yue FU,Zhi-yong CHEN

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 6,   Pages 429-448 doi: 10.1631/FITEE.1500118

Abstract: This paper reviews some main results and progress in distributed multi-agent coordination from a graphsurvey of existing literature in distributed multi-agent coordination and a new perspective in terms of graphFor different types of graph Laplacians, we summarize their inherent coordination features and specific

Keywords： Multi-agent systems     Distributed coordination     Graph Laplacian    

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Efficacy of intelligent diagnosis with a dynamic uncertain causality graph model for rare disorders of

Dongping Ning, Zhan Zhang, Kun Qiu, Lin Lu, Qin Zhang, Yan Zhu, Renzhi Wang

Frontiers of Medicine 2020, Volume 14, Issue 4,   Pages 498-505 doi: 10.1007/s11684-020-0791-8

Abstract: On the basis of the principles and algorithms of dynamic uncertain causality graph (DUCG), a diagnosis

Keywords： disorders of sex development (DSD)     intelligent diagnosis     dynamic uncertain causality graph    

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A Practical Approach to Constructing a Knowledge Graph for Cybersecurity Article

Yan Jia, Yulu Qi, Huaijun Shang, Rong Jiang, Aiping Li

Engineering 2018, Volume 4, Issue 1,   Pages 53-60 doi: 10.1016/j.eng.2018.01.004

Abstract: At present, it is very significant that certain scholars have combined the concept of the knowledge graph

Keywords： Cybersecurity     Knowledge graph     Knowledge deduction    

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Erratum to: Soft-HGRNs: soft hierarchical graph recurrent networks for multi-agent partially observable

Yixiang REN, Zhenhui YE, Yining CHEN, Xiaohong JIANG, Guanghua SONG

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 3,   Pages 480-480 doi: 10.1631/FITEE.22e0073

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A DNA Computing Model for the Graph Vertex Coloring Problem Based on a Probe Graph Article

Jin Xu, Xiaoli Qiang, Kai Zhang, Cheng Zhang, Jing Yang

Engineering 2018, Volume 4, Issue 1,   Pages 61-77 doi: 10.1016/j.eng.2018.02.011

Abstract: overcome this bottleneck and improve the processing speed, we propose a DNA computing model to solve the graphIn this article, a 3-colorable graph with 61 vertices is used to illustrate the capability of the DNAThe experiment showed that not only are all the solutions of the graph found, but also more than 99%

Keywords： DNA computing     Graph vertex coloring problem     Polymerase chain reaction    

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Stochastic extra-gradient based alternating direction methods for graph-guided regularizedminimization None

Qiang LAN, Lin-bo QIAO, Yi-jie WANG

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 6,   Pages 755-762 doi: 10.1631/FITEE.1601771

Abstract: extra-gradient alternating direction method with augmented Lagrangian function (SEGAL), to minimize the graph-guidedA number of important applications in machine learning follow the graph-guided optimization formulationWe conduct experiments on fused logistic regression and graph-guided regularized regression.

Keywords： Stochastic optimization     Graph-guided minimization     Extra-gradient method     Fused logistic regression     Graph-guided    

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Interpreting the vulnerability of power systems in cascading failures using multi-graph convolutional Research Article

Supaporn LONAPALAWONG, Changsheng CHEN, Can WANG, Wei CHEN

Frontiers of Information Technology & Electronic Engineering 2022, Volume 23, Issue 12,   Pages 1848-1861 doi: 10.1631/FITEE.2200035

Abstract: system's spatial information such as the electrical distance to increase the accuracy in the process of graphuses power system topology and spatial information to optimize the edge weight assignment of the line graphThen we propose a multi-graph convolutional network (MGCN) based on a graph classification task, which

Keywords： Power systems     Vulnerability     Cascading failures     Multi-graph convolutional networks     Weighted line graph    

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Erratum to: Efficient keyword search over graph-structured data based on minimal covered Erratum

Asieh Ghanbarpour, Abbas Niknafs, Hassan Naderi,naderi@iust.ac.ir

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 6,   Pages 809-962 doi: 10.1631/FITEE.18e0133

Abstract: Unfortunately the second author’s name has been misspelt. It should be read: Abbas NIKNAFS.
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Paper evolution graph: multi-view structural retrieval for academic literature None

Dan-ping LIAO, Yun-tao QIAN

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 2,   Pages 187-205 doi: 10.1631/FITEE.1700105

Abstract: method to build structural retrieval results for academic literature, which we call a paper evolution graph

Keywords： Paper evolution graph     Academic literature retrieval     Metagraph factorization     Topic coherence    

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Title Author Date Type Operation

A New Sufficient Conditions and Hamiltonian graphs

Zhao Kewen

Journal Article

Classifying multiclass relationships between ASes using graph convolutional network

Journal Article

A review on different theoretical models of electrocaloric effect for refrigeration

Journal Article

Large-scale graph processing systems: a survey

Ning LIU, Dong-sheng LI, Yi-ming ZHANG, Xiong-lve LI

Journal Article

Modelling of dynamic contact length in rail grinding process

Shaodan ZHI,Jianyong LI,A. M. ZAREMBSKI

Journal Article

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

Wenxuan CAO; Junjie LI

Journal Article

Distributed coordination inmulti-agent systems: a graph Laplacian perspective

Zhi-min HAN,Zhi-yun LIN,Min-yue FU,Zhi-yong CHEN

Journal Article

Efficacy of intelligent diagnosis with a dynamic uncertain causality graph model for rare disorders of

Dongping Ning, Zhan Zhang, Kun Qiu, Lin Lu, Qin Zhang, Yan Zhu, Renzhi Wang

Journal Article

A Practical Approach to Constructing a Knowledge Graph for Cybersecurity

Yan Jia, Yulu Qi, Huaijun Shang, Rong Jiang, Aiping Li

Journal Article

Erratum to: Soft-HGRNs: soft hierarchical graph recurrent networks for multi-agent partially observable

Yixiang REN, Zhenhui YE, Yining CHEN, Xiaohong JIANG, Guanghua SONG

Journal Article

A DNA Computing Model for the Graph Vertex Coloring Problem Based on a Probe Graph

Jin Xu, Xiaoli Qiang, Kai Zhang, Cheng Zhang, Jing Yang

Journal Article

Stochastic extra-gradient based alternating direction methods for graph-guided regularizedminimization

Qiang LAN, Lin-bo QIAO, Yi-jie WANG

Journal Article

Interpreting the vulnerability of power systems in cascading failures using multi-graph convolutional

Supaporn LONAPALAWONG, Changsheng CHEN, Can WANG, Wei CHEN

Journal Article

Erratum to: Efficient keyword search over graph-structured data based on minimal covered

Asieh Ghanbarpour, Abbas Niknafs, Hassan Naderi,naderi@iust.ac.ir

Journal Article

Paper evolution graph: multi-view structural retrieval for academic literature

Dan-ping LIAO, Yun-tao QIAN

Journal Article