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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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Nonlinear Virtual Inertia control of WTGs for Enhancing Primary Frequency Response and Suppressing Drive-Train Torsional Oscillations

arXiv

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arXiv 2020年

作者： Liu, Bi Huang, Qi Zhao, Junbo Milano, Federico Zhang, Yingchen Sichuan Provincial Key Lab of Power System Wide-area Measurement and Control University of Electronic Science and Technology of China Chengdu Sichuan611731 China Department of Electrical and Computer Engineering Mississippi State University StarkvilleMS39762 United States School of Electrical and Electronic Engineering University College Dublin Dublin Ireland National Renewable Energy Laboratory GoldenCO80401 United States

Virtual inertia controllers (VICs) for wind turbine generators (WTGs) have been recently developed to compensate the reduction of inertia in power systems. However, VICs can induce low frequency torsional oscillations of the drive train of WTGs. This paper addresses this issue and develops a new nonlinear VIC based on objective holographic feedbacks theory. This approach allows transforming the original nonlinear control into a completely controllable system of Brunovsky’s type. Simulation results under various scenarios demonstrate that the proposed method outperforms existing VICs in terms of suppression of low frequency drive-train torsional oscillations, enhancement of system frequency nadir as well as fast and smooth recovery of WTG rotor speed to the original MPP point before the disturbance. The proposed method is also able to coordinate multiple WTGs. Copyright © 2020, The Authors. All rights reserved.

关键词： Frequency response

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Stochastic Link Flow Model for Signalized Traffic Networks with Uncertainty in Demand

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IFAC-PapersOnLine 2018年第9期51卷 458-463页

作者： Lin, S. Pan, T.L. Lam, W.H.K. Zhong, R.X. Schutter, B. De School of Computer and Control Engineering University of Chinese Academy of Sciences Key Laboratory of System Control and Information Processing Ministry of Education BeijingShanghai China Department of Civil and Structural Engineering The Hong Kong Polytechnic University Hong KongSAR Hong Kong School of Engineering Sun Yat-Sen University Guangzhou China Delft Center for Systems and Control Delft University of Technology Delft Netherlands

In order to investigate the stochastic features in urban traffic dynamics, we propose a Stochastic Link Flow Model (SLFM) for signalized traffic networks with demand uncertainties. In the proposed model, the link traffic state is described using four different link state modes, and the probability for each link state mode is determined based on the stochastic link states. The SLFM model is expressed as a finite mixture approximation of the link state probabilities and the dynamic link flow models for all the four link state modes. Using data from microscopic traffic simulator SUMO, we illustrate that the proposed model can provide a reliable estimation of the link traffic states, and as well as good estimations on the link state uncertainties propagating within a signalized traffic network. © 2018

关键词： Stochastic models Routers Stochastic systems Street traffic control Traffic signals Vehicle actuated signals Demand uncertainty Finite mixtures Stochastic features Stochastic traffic Traffic networks Traffic simulators Uncertainty in demand Urban traffic networks

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Fault Diagnosis of SOFC Stack Based on Neural Network Algorithm

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Energy Procedia 2019年 158卷 1798-1803页

作者： Tao Xue Xiaolong Wu Yuanwu Xu Suwen Jing Zehua Li Jianhua Jiang Zhonghua Deng Xiaowei Fu Li Xi School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science & Technology Wuhan 430074 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 430065 China

To realize the commercialization of SOFC, it must be ensured that it can work efficiently and stably. SOFC fault diagnosis becomes an essential part of the research. Due to the strong coupling of faults in the stack, this paper uses neural network algorithm to detect and diagnose faults. The simulation results verify that through the diagnosis of the test sample, the recognition rate of the test sample by the network is found to be 95%, which explains the neural network fault diagnosis model established in this paper on identifying the normal working state of the stack, the electrode stacking of the stack, and the gas leakage fault of the stack has good effectiveness and accuracy.

关键词： SOFC fault diagnosis neural network

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Velocity Coordination of Multi-vehicle systems via Distributed Neighbor Selection

Velocity Coordination of Multi-vehicle Systems via Distribut...

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International Conference on Intelligent Transportation

作者： Haibin Shao Lulu Pan Yugeng Xi Dewei Li Shu Lin Department of Automation and the Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Jiao Tong University China School of Computer Science and Technology University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781538670255

In this paper, we examine a data-driven control approach to coordination of multi-vehicle systems based on the distributed neighbor selection. The core of the proposed approach is to utilize a recently developed metric called relative tempo for distributed coordination which is computable from local measurable data for each vehicle in the network. The relative tempo between each agent and its neighbors is shown to be closely related to the directed spanning tree of the underlying network in a quantitative manner. Based on this fact, a local neighbor selection protocol is subsequently provided to construct the global refined communication structure which can both maintain the connectivity and increase the efficiency of the multi-vehicle coordination. The numerical study is finally provided to demonstrate the effectiveness of our approach.

关键词： Protocols Vehicle dynamics control systems Topology Intelligent transportation systems Measurement Heuristic algorithms

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DTMC-Based Performance Evaluation of Mobile-phone User's Application Node 17

DTMC-Based Performance Evaluation of Mobile-phone User's App...

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17th IEEE/ACIS International Conference on computer and Information Science, ICIS 2018

作者： Wang, Danyu Shi, Minyong Wang, Yongbin Hong, Zhiguo School of Computer Communication University of China Beijing100024 China Key Laboratory of Acoustic Visual Technology and Intelligent Control System Ministry of Culture China Beijing Key Laboratory of Modern Entertainment Technology Beijing100024 China

ISBN: (纸本)9781538658925

New media news client now largely replaces traditional newspaper media. Mobile-phone application node is the key component of distributed mobile phone, which offers reading newspaper on mobile phone. The performance mobile-phone application node has great impact on telephone user's experience. This paper uses DTMC-based model checking methodology to evaluate mobile-phone application node's performance such as Sina or Tencent News client. Based on the analysis of news node's working process, the probability of steady-state is chosen as the performance index to study different parameters' influence on it. Furthermore, trend that the probability of steady-state of News node varies with the effect of probability from WeChat state to Weibo state and probability from Game state to Video state is derived thereby. © 2018 IEEE.

关键词： Model checking

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Efficient MedSAMs: Segment Anything in Medical Images on Laptop

arXiv

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arXiv 2024年

作者： Ma, Jun Li, Feifei Kim, Sumin Asakereh, Reza Le, Bao-Hiep Nguyen-Vu, Dang-Khoa Pfefferle, Alexander Wei, Muxin Gao, Ruochen Lyu, Donghang Yang, Songxiao Purucker, Lennart Marinov, Zdravko Staring, Marius Lu, Haisheng Dao, Thuy Thanh Ye, Xincheng Li, Zhi Brugnara, Gianluca Vollmuth, Philipp Foltyn-Dumitru, Martha Cho, Jaeyoung Mahmutoglu, Mustafa Ahmed Bendszus, Martin Pflüger, Irada Rastogi, Aditya Ni, Dong Yang, Xin Zhou, Guang-Quan Wang, Kaini Heller, Nicholas Papanikolopoulos, Nikolaos Weight, Christopher Tong, Yubing Udupa, Jayaram K. Patrick, Cahill J. Wang, Yaqi Zhang, Yifan Contijoch, Francisco McVeigh, Elliot Ye, Xin He, Shucheng Haase, Robert Pinetz, Thomas Radbruch, Alexander Krause, Inga Kobler, Erich He, Jian Tang, Yucheng Yang, Haichun Huo, Yuankai Luo, Gongning Kushibar, Kaisar Amankulov, Jandos Toleshbayev, Dias Mukhamejan, Amangeldi Egger, Jan Pepe, Antonio Gsaxner, Christina Luijten, Gijs Fujita, Shohei Kikuchi, Tomohiro Wiestler, Benedikt Kirschke, Jan S. de la Rosa, Ezequiel Bolelli, Federico Lumetti, Luca Grana, Costantino Xie, Kunpeng Wu, Guomin Puladi, Behrus Martín-Isla, Carlos Lekadir, Karim Campello, Victor M. Shao, Wei Brisbane, Wayne Jiang, Hongxu Wei, Hao Yuan, Wu Li, Shuangle Zhou, Yuyin Wang, Bo AI Collaborative Centre University Health Network Department of Laboratory Medicine and Pathobiology University of Toronto Vector Institute Toronto Canada Peter Munk Cardiac Centre University Health Network Toronto Canada Toronto General Hospital Research Institute University Health Network Department of Computer Science University of Toronto University Health Network Vector Institute Toronto Canada University of Science Vietnam National University Ho Chi Minh City Viet Nam Institute of Computer Science University of Freiburg Freiburg Germany School of Medicine and Health Harbin Institute of Technology Harbin China Division of Image Processing Department of Radiology Leiden University Medical Center Leiden Netherlands Department of System and Control Engineering School of Engineering Institute of Science Tokyo Formerly Tokyo Institute of Technology Tokyo Japan Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany School of Information and Communication Engineering University of Electronic Science and Technology of China Chengdu China School of Electrical Engineering and Computer Science University of Queensland Brisbane Australia School of Cyberspace Hangzhou Dianzi University Hangzhou China Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Division for Computational Radiology and Clinical AI The Department of Neuroradiology University Hospital Bonn Germany Department of Neuroradiology Heidelberg University Hospital Heidelberg Germany Division for Computational Radiology and Clinical AI Department of Neuroradiology University Hospital Bonn Germany School of Biomedical Engineering Shenzhen University Shenzhen China School of Biological Science and Medical Engineering Southeast University Nanjing China Department of Urology Cleveland Clinic Cleveland United States Department of Computer Science University of Minnesota Minneapolis United St

Promptable segmentation foundation models have emerged as a transformative approach to addressing the diverse needs in medical images, but most existing models require expensive computing, posing a big barrier to their adoption in clinical practice. In this work, we organized the first international competition dedicated to promptable medical image segmentation, featuring a large-scale dataset spanning nine common imaging modalities from over 20 different institutions. The top teams developed lightweight segmentation foundation models and implemented an efficient inference pipeline that substantially reduced computational requirements while maintaining state-of-the-art segmentation accuracy. Moreover, the post-challenge phase advanced the algorithms through the design of performance booster and reproducibility tasks, resulting in improved algorithms and validated reproducibility of the winning solution. Furthermore, the best-performing algorithms have been incorporated into the open-source software with a user-friendly interface to facilitate clinical adoption. The data and code are publicly available to foster the further development of medical image segmentation foundation models and pave the way for impactful real-world applications. © 2024, CC BY-NC-SA.

关键词： Open source software

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Modelling of gas turbine via discrete state-space neural networks

Modelling of gas turbine via discrete state-space neural net...

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Chinese Automation Congress (CAC)

作者： Jianhua Zhang Guanglei Cui Guolian Hou Zhiqiang Wu Jiiun Cao Penghao Fan State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing China School of Control and Computer Engineering North China Electric Power University Beijing China

In this paper, one kind of multivariate system identification algorithm based discrete state-space neural network (DSSNN) is presented for modelling gas turbine systems with non-Gaussian disturbances. An improved performance index is proposed to train DSSNNs by using Survival Information Potential (SIP) of identification errors. Compared with the traditional Mean Square Error (MSE) based identification algorithm, simulation results demonstrate that the proposed system identification algorithm can obtain better model for 8OkW gas turbine.

关键词： Power systems Turbines system identification Fuels Renewable energy sources Neural networks Handheld computers

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