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arXiv 2021年

作者： Sun, Zemin Liu, Yanheng Wang, Jian Li, Guofa Anil, Carie Li, Keqiang Guo, Xinyu Sun, Geng Tian, Daxin Cao, Dongpu College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun130012 China Institute of Human Factors and Ergonomics College of Mechatronics and Control Engineering Shenzhen University Guangdong Shenzhen518060 China School of Computer Science and Engineering VIT-AP Andhra Pradesh Amaravati522237 India College of Engineering Nanjing Agricultural University Nanjing210031 China State Key Laboratory of Automotive Safety and Energy Department of Automotive Engineering Tsinghua University Beijing100084 China Beijing Advanced Innovation Center for Big Data and Brain Computing Beijing Key Laboratory for Cooperative Vehicle Infrastructure Systems and Safety Control School of Transportation Science and Engineering Beihang University Beijing100191 China Waterloo Cognitive Autonomous Driving Lab University of Waterloo N2L 3G1 Canada

In the Internet of things (IoT) era, vehicles and other intelligent components in an intelligent transportation system (ITS) are connected, forming vehicular networks (VNs) that provide efficient and safe traffic and ubiquitous access to various applications. However, as the number of nodes in an ITS increases, it is challenging to satisfy a varied and large number of service requests with different quality of service (QoS) and security requirements in highly dynamic VNs. Intelligent nodes in VNs can compete or cooperate for limited network resources to achieve the objective for either an individual or a group. Game theory (GT), a theoretical framework designed for strategic interactions among rational decision makers sharing scarce resources, can be used to model and analyze individual or group behaviors of communicating entities in VNs. This paper primarily surveys the recent developments of GT in solving various challenges of VNs. This survey starts with an introduction to the background of VNs. A review of GT models studied in the VNs is then introduced, including the basic concepts, classifications, and applicable vehicular issues. After discussing the requirements of VNs and the motivation of using GT, a comprehensive literature review on GT applications in dealing with the challenges of current VNs is provided. Furthermore, recent contributions of GT to VNs that are integrated with diverse emerging 5G technologies are surveyed. Finally, the lessons learned are given, and several key research challenges and possible solutions of applying GT in VNs are outlined. Copyright © 2021, The Authors. All rights reserved.

关键词： Quality of service

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Subtropical vegetation damage and recovery dynamics after the great 2008 Chinese ice storm

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Agricultural and Forest Meteorology 2025年 372卷

作者： Yujiu Xiong Wenjie Yan Xu Wang Yong Luo Hanhua Feng Wenli Zhao Biqing Zhu Zhenhua Ye Hao Li School of Civil Engineering Sun Yat-Sen University Zhuhai 519082 Guangdong China Guangdong Engineering Technology Research Center of Water Security Regulation and Control for Southern China Sun Yat-sen University Guangzhou 510275 China Research Institute of Tropical Forestry Chinese Academy of Forestry Guangzhou 510520 China Beijiangyuan National Forest Ecosystem Research Station Nanling Mts Guangzhou 510520 China Guangdong Forestry Survey and Planning Institute Guangzhou 510520 China Department of Earth and Environmental Engineering Columbia University NY 10027 USA Max Planck Institute for Biogeochemistry Jena Germany The International Institute for Applied Systems Analysis (IIASA) Vienna Austria Guangzhou Institute of Forestry and Landscape architecture Guangzhou 510405 China

In early 2008, an extreme ice storm struck southern China, including the subtropical Guangdong Province, causing substantial ecological damage and economic losses. Previous evaluations of vegetation damage during this event primarily focused on the immediate physical structure damage caused by ice, overlooking the delayed physiological damage from extreme low-temperature stress, especially in adjacent non-frozen regions. Combining remotely-sensed (i.e., MODIS Gross Primary Productivity (GPP) and Enhanced Vegetation index (EVI)) and in-situ data, we conducted a more complete assessment of subtropical vegetation damage and recovery following the 2008 Chinese ice storm by considering time-lag effects. We found vegetation damage and subsequent recovery exhibited distinct spatial patterns correlated to ice storm severity. Assessments that accounted for time-lag effects were more aligned with ground truth, revealing that vegetation damage signal typically lagged the event onset by 1–2 months. The time-lag effect showed distinct patterns in non-frozen regions experiencing secondary low-temperature stress (without direct ice storm exposure). Physiological damage dominated these areas, reducing GPP by 62 %. In contrast, physical structural damage caused a comparatively smaller decline (51 %) in EVI. We also found a positive correlation between frozen time and the severity of vegetation damage, with 37 % of vegetation damaged in less frozen zone versus 70 % in severe frozen zone. Subsequent recovery of GPP and EVI to pre-ice storm conditions took 4–9 months, with GPP recovering faster than EVI, especially in severe frozen forests. Such positive correlation also existed between damage severity (or recovery time) and elevation and slope, but the pattern varied across different freezing zones. Our findings highlight the delayed physiological damage from extreme low-temperature stress and provide new insights into subtropical vegetation dynamics following extreme ice storms.

关键词： EVI Extreme climate event GPP Guangdong Nanling mountain region Subtropical ecosystem

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Correction: Bubble-enhanced ultrasonic microfluidic chip for rapid DNA fragmentation

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Lab on a chip 2023年第8期23卷 2141页

作者： Lin Sun Thomas Lehnert Songjing Li Martin A M Gijs Laboratory of Microsystems Ecole Polytechnique Fédérale de Lausanne CH-1015 Switzerland. martin.gijs@epfl.ch. Department of Fluid Control and Automation School of Mechatronics Engineering Harbin Institute of Technology Harbin Heilongjiang 150000 P. R. China.

Correction for 'Bubble-enhanced ultrasonic microfluidic chip for rapid DNA fragmentation' by Lin Sun , , 2022, , 560-572, https://***/10.1039/D1LC00933H.

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Development of power drive technology for high lift system of commercial aircraft

Development of power drive technology for high lift system o...

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CSAA/IET International Conference on Aircraft Utility systems (AUS 2020)

作者： T. Liu Y. Zhang W. Wang J. Ju W. Yu Shanghai Aircraft Design and Research Institute Department of Flight Control System China Commercial Aircraft Corporation of China Ltd. Department of Science and Technology Management China Shanghai Jiaotong University Department of Automation School of Electronic Information and Electrical Engineering China

In this paper, the development of power driving technology for high lift system of modern commercial aircraft is presented. Three kinds of power driving technical schemes of high lift system are demonstrated together with their characteristics. Various applications of power drive technology on present mainstream aircrafts have been addressed and analyzed respectively. In addition to the analysis of existing power drive technology, this work presented that distributed electric power drive technology could be a potential future development trend. The paper can be read as a reference for selecting power driving technical scheme of high lift systems at conceptual design phase of a commercial aircraft.

关键词： aircraft power systems aircraft design engineering electric drives

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Face hallucination with finishing touches

arXiv

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arXiv 2020年

作者： Zhang, Yang Tsang, Ivor W. Li, Jun Liu, Ping Lu, Xiaobo Yu, Xin The School of Automation Southeast University Nanjing210096 China The Australian Artificial Intelligence Institute University of Technology Sydney UltimoNSW2007 Australia The Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Singapore138634 Singapore The Research School of Engineering Australian National University Canberra Australia

Obtaining a high-quality frontal face image from a low-resolution (LR) non-frontal face image is primarily important for many facial analysis applications. However, mainstreams either focus on super-resolving near-frontal LR faces or frontalizing non-frontal high-resolution (HR) faces. It is desirable to perform both tasks seamlessly for daily-life unconstrained face images. In this paper, we present a novel Vivid Face Hallucination Generative Adversarial Network (VividGAN) for simultaneously super-resolving and frontalizing tiny non-frontal face images. VividGAN consists of coarse-level and fine-level Face Hallucination Networks (FHnet) and two discriminators, i.e., Coarse-D and Fine-D. The coarse-level FHnet generates a frontal coarse HR face and then the fine-level FHnet makes use of the facial component appearance prior, i.e., fine-grained facial components, to attain a frontal HR face image with authentic details. In the fine-level FHnet, we also design a facial component-aware module that adopts the facial geometry guidance as clues to accurately align and merge the frontal coarse HR face and prior information. Meanwhile, two-level discriminators are designed to capture both the global outline of a face image as well as detailed facial characteristics. The Coarse-D enforces the coarsely hallucinated faces to be upright and complete while the Fine-D focuses on the fine hallucinated ones for sharper details. Extensive experiments demonstrate that our VividGAN achieves photo-realistic frontal HR faces, reaching superior performance in downstream tasks, i.e., face recognition and expression classification, compared with other state-of-the-art methods. Copyright © 2020, The Authors. All rights reserved.

关键词： Generative adversarial networks

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Distributed Adaptive Observer for Discrete-Time LTI SISO System with Completely Unknown Periodic Input

Distributed Adaptive Observer for Discrete-Time LTI SISO Sys...

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第三十八届中国控制会议

作者： Yaoyao Wen Donghua Chen Ya Zhang School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Architecture Engineering Nanjing Institute of Technology

This paper focuses on designing a distributed observer for multiple sensors to estimate the input and state of a linear-time-invariant(LTI) single-input-single-output(SISO) discrete-time system with completely unknown periodic input. A consensus based adaptive observer to estimate the unknown input. The observer assumes the form of an adaptive finite impulse response(FIR) filter, which requires the agent to get the model and output of the target. In this paper, an adaptive distributed estimation algorithm is designed for some agents that cannot get the target model and output to estimate the target state, output and unknown input simply by relying on the information of its neighbors. Experimental results are provided to further verify and testify the effectiveness of the algorithm.

关键词： distributed estimation adaptive FIR unknown input sensor network

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Complex systems Modelling of UK Winter Wheat Yield

SSRN

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SSRN 2022年

作者： Pearson, Simon Hall, R.J. Wei, H.-L. Ma, Y. Fang, Shibo Hanna, Edward School of Geography and Lincoln Centre for Water and Planetary Health University of Lincoln LincolnLN6 7FL United Kingdom Department of Automatic Control and Systems Engineering University of Sheffield SheffieldS1 3JD United Kingdom Lincoln Institute of Agri-Food Technology University of Lincoln Riseholme Campus LincolnLN2 2NG United Kingdom Institute of Ecological and Agricultural Meteorology Chinese Academy of Meteorological Science No. 46 Zhongguancun South Road Beijing100081 China

Wheat is one of the most important global crops and understanding the drivers of wheat yield has important societal benefits. Climate variables are particularly important in determining interannual variations in wheat yield, either as primary factors which directly influence the stages of wheat growth, or as secondary factors through their influence on pests, diseases and soil conditions. Here we present a new approach to model wheat yield modelling;an empirical method based on nonlinear complex systems identification, known as NARMAX (Nonlinear AutoRegressive Moving Average with eXogenous inputs). We demonstrate the NARMAX analytical approach for a specific site, Rothamsted, UK, where detailed meteorological variables are available, together with specific information on site conditions and crop growth stages. An illustrative comparison of NARMAX yield forecasts is made with the WOFOST crop model. We also demonstrate how regional wheat yield forecasts might be derived from a new gridded meteorological data product. © 2022, The Authors. All rights reserved.

关键词： Machine learning

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Delays in Model Reduction of Chemical Reaction Networks

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IFAC-PapersOnLine 2018年第14期51卷 100-105页

作者： Lipták, György Hangos, Katalin M. Process Control Research Group Systems and Control Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences P.O. Box 63 BudapestH-1518 Hungary Department of Electrical Engineering and Information Systems University of Pannonia Veszprém Hungary

A novel engineering model reduction method is proposed in this paper that can be applied to a chemical reaction network (CRN) with chains of linear reactions. The reduced model is a delayed CRN with possibly different delays but with less state variables than the original model. As the first step of the model reduction, a decomposition method is also developed to transform chains with joint reactions into independent chains of linear reactions. The well known example of McKeithan's network is used as a case study to illustrate the basic concepts and the design method. © 2018

关键词： Reduction

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Enabling predictive analytics for smart manufacturing through an IIoT platform ⁎

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IFAC-PapersOnLine 2020年第3期53卷 179-184页

作者： T. Cerquitelli N. Nikolakis P. Bethaz S. Panicucci F. Ventura E. Macii S. Andolina A. Marguglio K. Alexopoulos P. Petrali A. Pagani P. van Wilgen M. Ippolito Department of Control and Computer Engineering Politecnico di Torino Turin ITALY Laboratory for Manufacturing Systems & Automation Department of Mechanical Engineering and Aeronautics University of Patras Patras GREECE COMAU S.p.A. Turin ITALY Interuniversity Department of Regional and Urban Studies and Planning Politecnico di Torino Turin ITALY SynArea Consultants S.r.l. Turin ITALY Engineering Ingegneria Informatica S.p.A. Palermo ITALY Whirlpool EMEA S.p.A. Biandronno ITALY VDL Weweler Apeldoorn NETHERLANDS

In the last few years, manufacturing systems are getting gradually transformed into smart factories. In this context, an increasing number of information and communication technologies is incorporated towards facilitating management, production, and control processes. The introduction of advanced embedded systems with enhanced connectivity produces a vast amount of data, posing a challenge in terms of data analytics. However, the in-time collection and analysis of acquired data can create insight into the manufacturing process as well as its assets. One aspect of major importance for every production system is preserving its equipment in operational condition, and within those limits that could minimize unplanned breakdowns and production stoppages. This paper details the predictive analytics methodology integrated into the SERENA platform able to: (i) streamline the prognostics of the industrial components, (ii) characterize the health status of the monitored equipment, (iii) generate an early warning related to the condition of the equipment, and (iv) forecast the future evolution of the monitored equipment’s degradation. To demonstrate the effectiveness of the proposed methodology, different use cases are discussed with results obtained on real-data collected in real-time from the industrial environments.

关键词： Data analytics data management analytics architecture predictive analytics production systems

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Hybrid protocol for distributed non-differentiable extended monotropic optimization

Hybrid protocol for distributed non-differentiable extended ...

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International Conference on control and automation (ICCA)

作者： Xia Jiang Xianlin Zeng Jian Sun Jie Chen Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China Beijing Advanced Innovation Center for Intelligent Robots and Systems (Beijing Institute of Technology) Key Laboratory of Biomimetic Robots and Systems (Beijing Institute of Technology) Ministry of Education Beijing China School of Electronic and Information Engineering Tongji University Shanghai China

ISBN: (数字)9781728190938

ISBN: (纸本)9781728190945

This paper presents a hybrid protocol design for distributed non-differentiable extended monotropic optimization problems, which have various applications in large-scale optimization and evolutionary computation. The considered objective function is the sum of local non-differentiable objective functions, which are assigned to different agents in multi-agent networks, with local set constraints and affine equality constraints. Each agent can only access to its local non-differentiable objective function, local set constraint and equality constraint, and exchange information with its neighbors to obtain the global optimal solution. For this type of optimization problems, we propose a distributed state-dependent hybrid method over multi-agent networks. In addition, we properly design the jump map and jump set to improve the transient performance and accelerate the consensus process of existing distributed continuous-time methods. With invariance principle of hybrid dynamical systems, we prove that the proposed hybrid protocol converges to the global optimal solution. We verify that the proposed hybrid method has a good convergence property and transient performance through numerical experiments.

关键词： Optimization Protocols Linear programming Dynamical systems Heuristic algorithms Convergence Transient analysis

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