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23rd International Conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2020

作者： Zhang, Hao Xia, Likun Song, Ran Yang, Jianlong Hao, Huaying Liu, Jiang Zhao, Yitian College of Information Engineering Capital Normal University Beijing China Cixi Institute of Biomedical Engineering Ningbo Institute of Industrial Technology Chinese Academy of Sciences Ningbo China School of Control Science and Engineering Shandong University Jinan China Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen China International Science and Technology Cooperation Base of Electronic System Reliability and Mathematical Interdisciplinary Capital Normal University Beijing China Laboratory of Neural Computing and Intelligent Perception Capital Normal University Beijing China Beijing Advanced Innovation Center for Imaging Theory and Technology Capital Normal University Beijing China

ISBN: (纸本)9783030597245

Automated extraction of cerebrovascular is of great importance in understanding the mechanism, diagnosis, and treatment of many cerebrovascular pathologies. However, segmentation of cerebrovascular networks from magnetic resonance angiography (MRA) imagery continues to be challenging because of relatively poor contrast and inhomogeneous backgrounds, and the anatomical variations, complex geometry and topology of the networks themselves. In this paper, we present a novel cerebrovascular segmentation framework that consists of image enhancement and segmentation phases. We aim to remove redundant features, while retaining edge information in shallow features when combining these with deep features. We first employ a Retinex model, which is able to model noise explicitly to aid removal of imaging noise, as well as reducing redundancy within an image and emphasizing the vessel regions, thereby simplifying the subsequent segmentation problem. Subsequently, a reverse edge attention module is employed to discover edge information by paying particular attention to the regions that are not salient in high-level semantic features. The experimental results show that the proposed framework enables the reverse edge attention network to deliver a reliable cerebrovascular segmentation. © 2020, Springer Nature Switzerland AG.

关键词： Image enhancement

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control-oriented fault detection of solid oxide fuel cell system unknown input on fuel supply

Control-oriented fault detection of solid oxide fuel cell sy...

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作者： Wu, Xiao-long Xu, Yuan-wu Xue, Tao Shuai, Junchao Jiang, Jianhua Deng, Zhonghua Fu, Xiaowei Li, Xi School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science & Technology Wuhan China College of Computer Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan China Wuhan Industrial Economic Development Research Center Wuhan China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen China

As the solid oxide fuel cell (SOFC) system work environment is a high-temperature environment for a long time, it is difficult to obtain the SOFC stack internal state change directly. When the fault occurs, it is difficult to determine where the fault occurs. Moreover, the existing literature ignores the impact of faults, which creates many problems for SOFC system control. Therefore, a state observer-based fault detection method, which is used to detect the input flow sensor fault and the fuel input fault, is proposed. Their advantage is that they do not need data processing. To realize the fault detection, the observer is used to track the changes of SOFC stack chamber temperature. To obtain the observer estimation parameter, an approach from the actual stack structure parameters is employed to approximate the observer parameters. The results show the proposed fault detect method can judge fuel input fault type quickly and shield the disturbances signals from the sensor effectively. The proposed method also can be used to other operating points or air input fault. © 2018 Chinese Automatic control Society and John Wiley & Sons Australia, Ltd

关键词： Fault detection

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Transactive energy system deployment over insecure communication links

arXiv

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arXiv 2020年

作者： Lu, Yang Lian, Jianming Zhu, Minghui Ma, Ke The System Security Group Lancaster University LancasterLA1 4YW United Kingdom The Grid-Interactive Controls Group Oak Ridge National Laboratory Oak RidgeTN37831 United States The School of Electrical Engineering and Computer Science Pennsylvania State University University ParkPA16802 United States The Optimization and Control Group Pacific Northwest National Laboratory RichlandWA99354 United States

In this paper, the privacy and security issues associated with the transactive energy system (TES) deployment over insecure communication links are addressed. In particular, it is ensured that (1) individual agents' bidding information is kept private throughout hierarchical market-based interactions;and (2) any extraneous data injection attack can be quickly and easily detected. An implementation framework is proposed to enable the cryptography-based enhancement of privacy and security for the deployment of any general hierarchical systems including TESs. Under the proposed framework, a unified cryptography-based approach is developed to achieve both privacy and security simultaneously. Specifically, privacy preservation is realized by an enhanced Paillier encryption scheme, where a block design is proposed to significantly improve computational efficiency. Attack detection is further achieved by an enhanced Paillier digital signature scheme, where a stamp-concatenation mechanism is proposed to enable detection of data replace and reorder attacks. Simulation results verify the effectiveness of the proposed cyber-resilient design for transactive energy systems. Copyright © 2020, The Authors. All rights reserved.

关键词： Cryptography

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Multi-objective optimal control of micro-grid based on economic model predictive control

Multi-objective optimal control of micro-grid based on econo...

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第三十八届中国控制会议

作者： Shijia Ren Jiajun Wang Miaomiao Ma School of Control & Computer Engineering North China Electric Power University State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University

This paper presents an economic model predictive control(EMPC) scheme to manage the grid-connected micro-grid in an economic way. The grid-connected micro-grid system is composed of wind generation unit, photovoltaic generation unit,energy storage battery, micro-turbines and load. The generation units are scheduled optimally to achieve the three objectives of power balance, economic performance and environmental protection. Moreover, the analytic hierarchy process(AHP) is used to determine the weight coefficients of the objective function. Simulation and analysis results for the economic optimization of micro-grid system are given to illustrate the effectiveness of the proposed economic model predictive control framework.

关键词： Micro-grid multi-objective optimization EMPC AHP power balance

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QoE-aware user association and resource allocation for mixed services in heterogeneous networks

QoE-aware user association and resource allocation for mixed...

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第二届材料科学应用与能源材料国际研讨会

作者： Shuxian Li Liangrui Tang Jiangyu Yan State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University School of Control and Computer Engineering North China Electric Power University

In heterogeneous networks(HetNets),user association and resource allocation(UARA) is a great challenge for radio resource management(RRM).In this paper,a novel QoE-aware UARA scheme is *** delay factor is introduced to QoE metric to weight delays' effect on service *** the UARA scheme based on QoE is formulated as an optimization problem which is a mixed integer nonlinear programming(MINLP) *** solve the problem,we adopt the genetic algorithm(GA) and associate the user association and the resource with population and fitness *** the evolutions of genetic algorithm,the optimal UARA scheme can be worked *** simulation results indicate that the proposed scheme can reduce packet loss rate,and improve the system load balancing performance.

关键词： service QoE-aware user association and resource allocation for mixed services in heterogeneous networks

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Sparse generalized canonical correlation analysis: Distributed alternating iteration based approach

arXiv

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arXiv 2020年

作者： Cai, Jia Lv, Kexin Huo, Junyi Huang, Xiaolin Yang, Jie School of Statistics and Mathematics Guangdong University of Finance & Economics Big Data and Educational Statistics Application Laboratory 21 Chisha Road Guangzhou Guangdong510320 China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University MOE Key Laboratory of System Control and Information Processing 800 Dongchuan Road Shanghai200240 China School of Electronics and Computer Science University of Southampton University Road SouthamptonSO17 1BJ United Kingdom

Sparse canonical correlation analysis (CCA) is a useful statistical tool to detect latent information with sparse structures. However, sparse CCA works only for two datasets, i.e., there are only two views or two distinct objects. To overcome this limitation, in this paper, we propose a sparse generalized canonical correlation analysis (GCCA), which could detect the latent relations of multiview data with sparse structures. Moreover, the introduced sparsity could be considered as Laplace prior on the canonical variates. Specifically, we convert the GCCA into a linear system of equations and impose 1 minimization penalty for sparsity pursuit. This results in a nonconvex problem on Stiefel manifold, which is difficult to solve. Motivated by Boyd’s consensus problem, an algorithm based on distributed alternating iteration approach is developed and theoretical consistency analysis is investigated elaborately under mild conditions. Experiments on several synthetic and real world datasets demonstrate the effectiveness of the proposed algorithm. Copyright © 2020, The Authors. All rights reserved.

关键词： Statistical mechanics

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Application of Image Processing Technology in Building Surface Crack Detection 6

Application of Image Processing Technology in Building Surfa...

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2019 6th International Conference on Advanced Composite Materials and Manufacturing Engineering, ACMME 2019

作者： Xiong, Xin Huang, Li Tian, Jinrong Infrastructure and Logistics Management Wuhan University of Science and Technology Wuhan Hubei430081 China College of Computer Science and Technology Wuhan University of Science and Technology Wuhan Hubei430081 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan Hubei430081 China Key Laboratory of Metallurgical Equipment and Control Technology Ministry of Education Wuhan University of Science and Technology Wuhan Hubei430081 China

The phenomenon of cracks on the surface of buildings is widespread. The existence of cracks affects the normal use of buildings, shortening the service life, seriously damaging the structure of buildings, resulting in safety accidents. Therefore, regular detection and reinforcement of cracks on the surface of buildings is a necessary link to ensure safety. At present, the detection of building surface cracks is mainly carried out by manpower with means of equipment assisted. However, there are some problems in manpower detection, such as high manpower consumption, low *** paper presents a method of detecting and inspecting cracks on building surface based on image processing technology in machine vision, which includes image gray transformation, image denoising etc. Curve fitting and least square method are used to obtain crack parameters, so as to improve the inspecting efficiency and realize the automation of building surface inspection. © Published under licence by IOP Publishing Ltd.

关键词： Curve fitting

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Generating infrared image from visible image using Generative Adversarial Networks

Generating infrared image from visible image using Generativ...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Lei An Jiajia Zhao Huijun Di School of Computer Science & Technology Beijing Institute of Technology Beijing China Science and Technology on Complex System Control and Intelligent Agent Coorperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing China

ISBN: (纸本)9781728137933

Infrared images have properties that are unaffected by illumination compared to visible images, object can be clearly recognized at day or night. Therefore, it is a better choice to use infrared images when training deep learning algorithms in unmanned systems. However, how to obtain a large number of infrared images makes it possible to train deep learning algorithm, which is the focus of our attention. In contrast to difficulties in direct shooting, computer simulations can generate large infrared images from visible images. But models that are trained on simulated data usually do not translate well to real scenarios. To bridge the domain gap between simulated and real infrared images, we exploit recent advances in paired image-to-image translation. We extend Pixel2Pixel to generate infrared image from visible image and propose a novel way of multilayer semantic information fusion, which significantly improves the quality of generated images. Finally, the image generated by our proposed PixelPro network is almost consistent with the real image distribution, achieved the purpose of expanding the dataset.

关键词： Image translation Infrared image Generative adversarial networks Infrared imaging Visible Imagery images Infrared radiation Information fusion

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A Hierarchical Bidirectional LSTM Sequence Model for Extractive Text Summarization in Electric Power systems

A Hierarchical Bidirectional LSTM Sequence Model for Extract...

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International Symposium on Computational Intelligence and Design, ISCID

作者： Wei Jiang Yunfeng Zou Ting Zhao Qiang Zhang Yinglong Ma State Grid Corporation of China Beijing China Marketing Service Center of State Grid Jiangsu Electric Power Co. Ltd Global Energy Interconnection Research Institute Co. Ltd Artificial Intelligence on Electric Power System State Grid Corporation Joint Laboratory Beijing China School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (数字)9781728184463

ISBN: (纸本)9781728184470

With the increasing volume of documents in electric power systems, it is urgent and necessary for electric power systems managers to efficiently analyze the massive documents and make reasonable decisions by capturing the main points of the document as quickly as possible. The text summarization technique provides a feasible way to efficiently analyze and obtain the main contents residing in the document. In this paper, we present a Hierarchical Bidirectional Long Term Short Memory Sequence model for extractive text summarization in electric power systems in order to efficiently and accurately summarize electric power documents and obtain a summary of the document. Our model is divided into four layers including the embedding layer, the word layer, the sentence layer, and the classification layer in a hierarchical manner. The related experiments were made based on the electric power data set that contains more than 2000 electrical papers, in comparison with the existing approaches based on the CRF, CNN, and RNN models. The experimental results show that the performance based on our approach is superior to the three approaches against the three performance indexes ROUGE-1, ROUGE-2, and ROUGE-L.

关键词： Power systems Feature extraction Mathematical model Logic gates Task analysis Data mining Bit error rate

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Research on collaborative frequency regulation control strategy of wind farm based on decentralized exit 8

Research on collaborative frequency regulation control strat...

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8th Renewable Power Generation Conference, RPG 2019

作者： Ren, Y.H. Song, P. Wang, X.S. Shi, R.F. School of Control and Computer Engineering North China Electric Power University Beijing102206 China State Grid Jibei Electric Power Research Institute North China Electric Power Research Institute Co.Ltd. Beijing100045 China Grid-connected Operation Technology for Wind-Solar Storage Hybrid System State Grid Corporation Key Laboratory Beijing100045 China

ISBN: (纸本)9781839531255

When the wind turbine adopts the rotor inertia control to participate in grid frequency regulation, it is easy to cause the second frequency drop, which will be more serious when applied to the wind farm. To solve this problem, the influence of wind speed on the unit's ultimate support time under the constant power support mode is analyzed quantitatively and wind turbine recovery time is defined. The functional relationship between the unit's support time and recovery time suitable for engineering application is given. A wind farm frequency regulation optimization model aiming at the longest supporting time of all units in the whole station is established, and the wind farm coordinated frequency regulation control strategy based on decentralized exit is proposed, taking full account of capacity differences of units under different working conditions. Simulation examples show that the real-time coordination of the exit of the wind turbine frequency regulation can effectively alleviate the secondary frequency drop problem of a wind farm. © 2019 Institution of Engineering and Technology. All rights reserved.

关键词： Wind turbines

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