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Virtual network embedding based on real-time topological attributes

Jian DING,Tao HUANG,Jiang LIU,Yun-jie LIU

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 2,   Pages 109-118 doi: 10.1631/FITEE.1400147

Abstract: As a great challenge of network virtualization, virtual network embedding/mapping is increasingly importantsubstrate network.considering the topological attributes which may pose significant impact on the performance of the embeddingIn this paper, a new embedding algorithm is proposed based on real-time topological attributes.A simulator is built to evaluate the performance of the proposed virtual network embedding (VNE) algorithm

Keywords： Virtual network embedding (VNE)     Real-time topological attributes     Betweenness centrality     Correlationproperties     Network virtualization    

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A forwarding graph embedding algorithm exploiting regional topology information Article

Hong-chao HU, Fan ZHANG, Yu-xing MAO, Zhen-peng WANG

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 11,   Pages 1854-1866 doi: 10.1631/FITEE.1601404

Abstract: Network function virtualization (NFV) is a newly proposed technique designed to construct and managenetwork functions dynamically and efficiently.Allocating physical resources to the virtual network function forwarding graph is a critical issue inWe formulate the forwarding graph embedding (FGE) problem as a binary integer programming problem, whichWe then design a novel regional resource clustering metric to quantify the embedding potential of each

Keywords： Network function virtualization     Virtual network function     Forwarding graph embedding    

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An artificial intelligence based method for evaluating power grid node importance using network embedding Research Papers

Hui-fang WANG, Chen-yu ZHANG, Dong-yang LIN, Ben-teng HE

Frontiers of Information Technology & Electronic Engineering 2019, Volume 20, Issue 6,   Pages 816-828 doi: 10.1631/FITEE.1800146

Abstract: First, using a network embedding approach, a feature extraction method is designed for power grid nodesThen, for a specific power network, steady-state and node fault transient simulations under various operationIn addition, a particular sample set for each specific power network can be established under this artificial

Keywords： Power grid     Artificial intelligence     Node importance     Text-associated DeepWalk     Network embedding     Support    

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Joint entity–relation knowledge embedding via cost-sensitive learning Article

Sheng-kang YU, Xue-yi ZHAO, Xi LI, Zhong-fei ZHANG

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 11,   Pages 1867-1873 doi: 10.1631/FITEE.1601255

Abstract: As a joint-optimization problem which simultaneously fulfills two different but correlated embeddingtasks (i.e., entity embedding and relation embedding), knowledge embedding problem is solved in a jointembedding scheme.In this embedding scheme, we design a joint compatibility scoring function to quantitatively evaluateExperimental results demonstrate the effectiveness of our embedding scheme in characterizing the semantic

Keywords： Knowledge embedding     Joint embedding     Cost-sensitive learning    

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Learning embeddings of a heterogeneous behavior network for potential behavior prediction Article

Yue-yang WANG, Wei-hao JIANG, Shi-liang PU, Yue-ting ZHUANG

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 3,   Pages 422-435 doi: 10.1631/FITEE.1800493

Abstract: In this paper, we examine behavior data obtained in realworld scenarios as an information network composedrelationships (human-human, human-action, and action-action), which we call the heterogeneous behavior networkTo exploit the abundance and heterogeneity of the HBN, we propose a novel network embedding method, human-action-attribute-awareheterogeneous network embedding (a4HNE), which jointly considers structural proximity, attribute resemblancedatasets show that this approach outperforms other similar methods on various heterogeneous information network

Keywords： Network embedding     Representation learning     Human behavior     Social networks     Heterogeneous information network    

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Local uncorrelated local discriminant embedding for face recognition

Xiao-hu MA,Meng YANG,Zhao ZHANG

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 3,   Pages 212-223 doi: 10.1631/FITEE.1500255

Abstract: paper, we introduce a novel feature extraction method called local uncorrelated local discriminant embeddingThe proposed approach can be seen as an extension of a local discriminant embedding (LDE) framework in

Keywords： Feature extraction     Local discriminant embedding     Local uncorrelated criterion     Face recognition    

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Preparation and characterization of a novel microorganism embedding material for simultaneous nitrification

Ming Zeng, Ping Li, Nan Wu, Xiaofang Li, Chang Wang

Frontiers of Environmental Science & Engineering 2017, Volume 11, Issue 6, doi: 10.1007/s11783-017-0961-3

Abstract: A novel microorganism embedding material was prepared to enhance the biological nitrogen removal throughrate and high nitrogen removal efficiency, which is a favorable additional agent to the traditional embedding

Keywords： Immobilization technology     Nitrogen removal     Cyclodextrin     Microbial community     Wastewater treatment    

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Achieving Cognitive Mass Personalization via the Self-X Cognitive Manufacturing Network: An IndustrialKnowledge Graph- and Graph Embedding-Enabled Pathway

Xinyu Li, Pai Zheng, Jinsong Bao, Liang Gao, Xun Xu

Engineering 2023, Volume 22, Issue 3,   Pages 14-19 doi: 10.1016/j.eng.2021.08.018

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Improvement of impact resistance of plain-woven composite by embedding superelastic shape memory alloy

Xiaojun GU, Xiuzhong SU, Jun WANG, Yingjie XU, Jihong ZHU, Weihong ZHANG

Frontiers of Mechanical Engineering 2020, Volume 15, Issue 4,   Pages 547-557 doi: 10.1007/s11465-020-0595-1

Abstract: Carbon fiber reinforced polymer (CFRP) composites have excellent mechanical properties, specifically, high specific stiffness and strength. However, most CFRP composites exhibit poor impact resistance. To overcome this limitation, this study presents a new plain-woven CFRP composite embedded with superelastic shape memory alloy (SMA) wires. Composite specimens are fabricated using the vacuum-assisted resin injection method. Drop-weight impact tests are conducted on composite specimens with and without SMA wires to evaluate the improvement of impact resistance. The material models of the CFRP composite and superelastic SMA wire are introduced and implemented into a finite element (FE) software by the explicit user-defined material subroutine. FE simulations of the drop-weight impact tests are performed to reveal the superelastic deformation and debonding failure of the SMA inserts. Improvement of the energy absorption capacity and toughness of the SMA-CFRP composite is confirmed by the comparison results.

Keywords： carbon fiber reinforced polymer composite     shape memory alloy wire     impact resistance     drop-weight test     finite element simulation    

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Hybrid embedding and joint training of stacked encoder for opinion question machine reading comprehension

Xiang-zhou Huang, Si-liang Tang, Yin Zhang, Bao-gang Wei,huangxiangzhou@zju.edu.cn,siliang@zju.edu.cn,yinzh@zju.edu.cn

Frontiers of Information Technology & Electronic Engineering 2020, Volume 21, Issue 9,   Pages 1267-1412 doi: 10.1631/FITEE.1900571

Abstract: this study, a novel framework based on is proposed to address such problems, in which a new hybrid embedding
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Reversible data hiding using a transformer predictor and an adaptive embedding strategy Research Article

Linna ZHOU, Zhigao LU, Weike YOU, Xiaofei FANG,zhoulinna@bupt.edu.cn,luchen@uir.edu.cn,ywk@bupt.edu.cn

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 8,   Pages 1143-1155 doi: 10.1631/FITEE.2300041

Abstract: In the field of (RDH), designing a high-precision predictor to reduce the embedding distortion and developingan effective embedding strategy to minimize the distortion caused by embedding information are the twoIn this paper, we propose a new RDH method, including a predictor based on a and a novel embedding strategywith multiple embedding rules.Finally, we provide an embedding strategy including multiple embedding rules for the first time.

Keywords： Reversible data hiding     Transformer     Adaptive embedding strategy    

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Multimethod Collaborative Optimization Algorithm Based on Embedding Collaboration

Luo Wencai,Luo Shishan,Wang Zhenguo

Strategic Study of CAE 2004, Volume 6, Issue 4,   Pages 51-55

Abstract:

Multi-method collaborative optimization algorithm based on embedding collaboration is advanced.It uses embedding structure to collaborate different kinds of optimization methods, and makes use ofA multimethod collaborative optimization algorithm base on embedding collaboration is designed, whichResults show that multi-method collaborative optimization algorithm based on embedding collaboration

Keywords： multimethod collaborative optimization algorithm     embedding collaboration     genetic algorithm     pattern search    

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1 Project supported by the National Natural Science Foundation of China (Nos. 61201209 and 61401499), the Natural Science Foundation of Shaanxi Province, China (No. 2015JM6340), and the Industrial Science and Technology Project of Shaanxi Province, China (No. 2016GY-087) Article

Shui-qing GONG,Jing CHEN,Qiao-yan KANG,Qing-wei MENG,Qing-chao ZHU,Si-yi ZHAO

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 7,   Pages 701-716 doi: 10.1631/FITEE.1500387

Abstract: Software-defined networking (SDN) enables the network virtualization through SDN hypervisors to sharethe underlying physical SDN network among multiple logically isolated virtual SDN networks (vSDNs),The vSDN embedding, which refers to mapping a number of vSDNs to the same substrate SDN network, is aIn this paper, we consider controller placement and virtual network embedding as a joint vSDN embeddingMoreover, we propose a novel online vSDN embedding algorithm called CO-vSDNE, which consists of a node

Keywords： Software-defined networking (SDN)     Network virtualization     Controller placement     Virtual network embedding    

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Syntactic word embedding based on dependency syntax and polysemous analysis None

Zhong-lin YE, Hai-xing ZHAO

Frontiers of Information Technology & Electronic Engineering 2018, Volume 19, Issue 4,   Pages 524-535 doi: 10.1631/FITEE.1601846

Abstract: Most word embedding models have the following problems: (1) In the models based on bag-of-words contexts, the structural relations of sentences are completely neglected; (2) Each word uses a single embeddingTo solve these problems, we propose an easy-to-use representation algorithm of syntactic word embeddingExperimental results show that our model generates desirable word embedding in similarity evaluationWe conclude that SWE outperforms single embedding learning models.

Keywords： Dependency-based context     Polysemous word representation     Representation learning     Syntactic word embedding    

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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: tremendous achievements of meta-learning in various fields, this paper proposes the local quadratic embedding

Keywords： Local quadratic embedding     Metric learning     Regression machine     Soft sensor    

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Title Author Date Type Operation

Virtual network embedding based on real-time topological attributes

Jian DING,Tao HUANG,Jiang LIU,Yun-jie LIU

Journal Article

A forwarding graph embedding algorithm exploiting regional topology information

Hong-chao HU, Fan ZHANG, Yu-xing MAO, Zhen-peng WANG

Journal Article

An artificial intelligence based method for evaluating power grid node importance using network embedding

Hui-fang WANG, Chen-yu ZHANG, Dong-yang LIN, Ben-teng HE

Journal Article

Joint entity–relation knowledge embedding via cost-sensitive learning

Sheng-kang YU, Xue-yi ZHAO, Xi LI, Zhong-fei ZHANG

Journal Article

Learning embeddings of a heterogeneous behavior network for potential behavior prediction

Yue-yang WANG, Wei-hao JIANG, Shi-liang PU, Yue-ting ZHUANG

Journal Article

Local uncorrelated local discriminant embedding for face recognition

Xiao-hu MA,Meng YANG,Zhao ZHANG

Journal Article

Preparation and characterization of a novel microorganism embedding material for simultaneous nitrification

Ming Zeng, Ping Li, Nan Wu, Xiaofang Li, Chang Wang

Journal Article

Achieving Cognitive Mass Personalization via the Self-X Cognitive Manufacturing Network: An IndustrialKnowledge Graph- and Graph Embedding-Enabled Pathway

Xinyu Li, Pai Zheng, Jinsong Bao, Liang Gao, Xun Xu

Journal Article

Improvement of impact resistance of plain-woven composite by embedding superelastic shape memory alloy

Xiaojun GU, Xiuzhong SU, Jun WANG, Yingjie XU, Jihong ZHU, Weihong ZHANG

Journal Article

Hybrid embedding and joint training of stacked encoder for opinion question machine reading comprehension

Xiang-zhou Huang, Si-liang Tang, Yin Zhang, Bao-gang Wei,huangxiangzhou@zju.edu.cn,siliang@zju.edu.cn,yinzh@zju.edu.cn

Journal Article

Reversible data hiding using a transformer predictor and an adaptive embedding strategy

Linna ZHOU, Zhigao LU, Weike YOU, Xiaofei FANG,zhoulinna@bupt.edu.cn,luchen@uir.edu.cn,ywk@bupt.edu.cn

Journal Article

Multimethod Collaborative Optimization Algorithm Based on Embedding Collaboration

Luo Wencai,Luo Shishan,Wang Zhenguo

Journal Article

1 Project supported by the National Natural Science Foundation of China (Nos. 61201209 and 61401499), the Natural Science Foundation of Shaanxi Province, China (No. 2015JM6340), and the Industrial Science and Technology Project of Shaanxi Province, China (No. 2016GY-087)

Shui-qing GONG,Jing CHEN,Qiao-yan KANG,Qing-wei MENG,Qing-chao ZHU,Si-yi ZHAO

Journal Article

Syntactic word embedding based on dependency syntax and polysemous analysis

Zhong-lin YE, Hai-xing ZHAO

Journal Article

A Local Quadratic Embedding Learning Algorithm and Applications for Soft Sensing

Yaoyao Bao, Yuanming Zhu, Feng Qian

Journal Article