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arXiv 2022年

作者： Wei, Qinglai Chen, Diancheng Yuan, Beiming State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

Great endeavors have been made to study AI's ability in abstract reasoning, along with which different versions of RAVEN's progressive matrices (RPM) are proposed as benchmarks. Previous works give inkling that without sophisticated design or extra meta-data containing semantic information, neural networks may still be indecisive in making decisions regarding the RPM problems, after relentless training. Evidenced by thorough experiments, we show that, neural networks embodied with felicitous inductive bias, intentionally design or serendipitously match, can solve the RPM problems efficiently, without the augment of any extra meta-data. Our work also reveals that multiviewpoint with multi-evaluation is a key learning strategy for successful reasoning. Nevertheless, we also point out the unique role of meta-data by showing that a pre-training model supervised by the meta-data leads to a RPM solver with better performance. Source code can be found in https://***/QinglaiWeiCASIA/RavenSolver. Copyright © 2022, The Authors. All rights reserved.

关键词： Matrix algebra

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Parallel Reinforcement Learning-Based Energy Efficiency Improvement for a Cyber-Physical system

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IEEE/CAA Journal of Automatica Sinica 2020年第2期7卷 617-626页

作者： Teng Liu Bin Tian Yunfeng Ai Fei-Yue Wang Department of Automotive Engineering Chongqing UniversityChongqing 400044 the Vehicle Intelligence Pioneers Inc. Qingdao 266109China the State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 101408China

As a complex and critical cyber-physical system(CPS),the hybrid electric powertrain is significant to mitigate air pollution and improve fuel *** management strategy(EMS)is playing a key role to improve the energy efficiency of this *** paper presents a novel bidirectional long shortterm memory(LSTM)network based parallel reinforcement learning(PRL)approach to construct EMS for a hybrid tracked vehicle(HTV).This method contains two *** high-level establishes a parallel system first,which includes a real powertrain system and an artificial ***,the synthesized data from this parallel system is trained by a bidirectional LSTM *** lower-level determines the optimal EMS using the trained action state function in the model-free reinforcement learning(RL)*** is a fully data-driven and learning-enabled approach that does not depend on any prediction and predefined ***,real vehicle testing is implemented and relevant experiment data is collected and *** results validate that the proposed EMS can achieve considerable energy efficiency improvement by comparing with the conventional RL approach and deep RL.

关键词： Bidirectional long short-term memory(LSTM)network cyber-physical system(CPS) energy management parallel system reinforcement learning(RL)

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Traffic Signal control Using Offline Reinforcement Learning

Traffic Signal Control Using Offline Reinforcement Learning

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Chinese Automation Congress (CAC)

作者： Xingyuan Dai Chen Zhao Xiaoshuang Li Xiao Wang Fei-Yue Wang School of Artificial Intelligence University of Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences

ISBN: (纸本)9781665426480

The problem of traffic signal control is essential but remains unsolved. Some researchers use online reinforcement learning, including the off-policy one, to derive an optimal control policy through interaction between agents and environments in simulation. However, it is difficult to deploy the policy in real transportation systems due to the gap between simulated and real traffic data. In this paper, we consider an offline reinforcement learning method to tackle the problem. First, we construct a realistic traffic environment and obtain offline data based on a classic actuated traffic signal controller. Then, we use an offline reinforcement learning algorithm, namely conservative Q-learning, to learn an efficient control policy via offline datasets. We conduct experiments on a typical road intersection and compare the conservative Q-learning policy with the actuated policy and two data-driven policies based on off-policy reinforcement learning and imitation learning. Empirical results indicate that in the offline-learning setting the conservative Q-learning policy performs significantly better than other baselines, including the actuated policy, but the other two data-driven policies perform poorly in test scenarios.

关键词： Q-learning Automation Roads Transportation Optimal control Cloning Data models

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燃烧源氨排放对灰霾期间北京大气铵的重要贡献

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Science Bulletin 2024年第7期69卷 978-987页

作者：吴礼彬王芃张强任红 Zongbo Shi 胡伟陈静谢巧蓉李林杰越思瑶韦莲芳宋琳琳张永根王子涵陈爽韦琬王小曼章炎麟孔少飞葛宝珠杨婷方运霆任露洁邓君俊孙业乐王自发张宏亮胡建林刘丛强 Roy M.Harrison Qi Ying 傅平青 Institute of Surface-Earth System Science School of Earth System ScienceTianjin UniversityTianjin 300072China Department of Atmospheric and Oceanic Sciences Fudan UniversityShanghai 200438China IRDR ICoE on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health Fudan UniversityShanghai 200438China Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceTsinghua UniversityBeijing 100084China Air Environmental Modeling and Pollution Controlling Key Laboratory of Sichuan Higher Education Institute Chengdu University of Information TechnologyChengdu 610225China Division of Environmental Health&Risk Management School of GeographyEarth&Environmental SciencesUniversity of BirminghamBirmingham B152TTUK School of Environmental Science and Engineering Tianjin UniversityTianjin 300072China State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry Institute of Atmospheric PhysicsChinese Academy of SciencesBeijing 100029China Key Laboratory of Forest Ecology and Management Institute of Applied EcologyChinese Academy of SciencesShenyang 110164China Yale-NUIST Center on Atmospheric Environment International Joint Laboratory on Climate and Environment ChangeNanjing University of Information Science and TechnologyNanjing 210044China Department of Atmospheric Sciences School of Environmental Studies and Department of Environmental Science and TechnologySchool of Environmental StudiesChina University of GeosciencesWuhan 430074China Department of Environmental Science and Engineering Fudan UniversityShanghai 200438China Collaborative Innovation Center of Atmospheric Environment and Equipment Technology Jiangsu Key Laboratory of Atmospheric Environment Monitoring and Pollution ControlNanjing University of Information Science and TechnologyNanjing 210044China Department of Environmental Sciences/Center of Excellence in Environmental Studies King Abdulaziz UniversityJeddah 21589Saudi Arabia Zachr

Aerosol ammonium(NH_(4)^(+)),mainly produced from the reactions of ammonia(NH_(3))with acids in the atmosphere,has significant impacts on air pollution,radiative forcing,and human *** the source and formation mechanism of NH_(4)^(+)can provide scientific insights into air quality ***,the sources of NH_(3)in urban areas are not well understood,and few studies focus on NH_(3)/NH_(4)^(+)at different heights within the atmospheric boundary layer,which hinders a comprehensive understanding of aerosol NH_(4)^(+).In this study,we perform both field observation and modeling studies(the Community Multiscale Air Quality,CMAQ)to investigate regional NH_(3)emission sources and vertically resolved NH_(4)^(+)formation mechanisms during the winter in *** stable nitrogen isotope analyses and CMAQ model suggest that combustion-related NH_(3)emissions,including fossil fuel sources,NH_(3)slip,and biomass burning,are important sources of aerosol NH_(4)^(+)with more than 60%contribution occurring on heavily polluted *** contrast,volatilization-related NH_(3)sources(livestock breeding,N-fertilizer application,and human waste)are dominant on clean ***-related NH_(3)is mostly local from Beijing,and biomass burning is likely an important NH_(3)source(~15%–20%)that was previously *** effective control strategies such as the two-product(e.g.,reducing both SO_(2)and NH_(3))control policy should be considered to improve air quality.

关键词： Particulate ammonium Nitrogen isotope PM2.5 The Community Multiscale Air Quality(CMAQ) control policy

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Greenhouse Environment control based on Computational Experiments 20

Greenhouse Environment Control based on Computational Experi...

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4th High Performance Computing and Cluster Technologies Conference, HPCCT 2020 and the 3rd International Conference on Big Data and Artificial Intelligence, BDAI 2020

作者： Weng, Yuchen Wang, Xiujuan Hua, Jing Wang, Haoyu Kang, Mengzhen State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences Haidian Beijing China

ISBN: (纸本)9781450375603

Greenhouse environment control is challenging since it is a partially open system being complex, nonlinear and highly uncertain. For such a complex system, empirical knowledge is often not sufficient to control the environment well. This paper proposes an approach for environment control based on computational experiments. The data source is from the second Autonomous Greenhouses International Challenge. Descriptive model is built with lightGBM algorithm for air temperature and CO2 concentration inside greenhouse. Computational experiments were carried out to optimize the ventilation opening, which has double effect of cooling and CO2 concentration decreasing. The aim of optimization is to keep the temperature as close as possible to the set line, while keeping a necessary level of CO2 concentration. The results indicate that the temperature can be better controlled than the original empirical methods for different conditions, while the CO2 concentration is maintained. The proposed approach overcomes the shortage of controlling ventilation with static knowledge, and can be applied to the real greenhouse. © 2020 ACM.

关键词： Greenhouses

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Soft-Landing Dynamics of a Type of Four-Legged Space Lander

SSRN

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SSRN 2024年

作者： Shi, Tengfei Shi, Tengfei Yang, Yinping Zhang, Zhijuan Liu, Cuicui Liu, Caishan Ma, Daolin Applied Mechanics and Structure Safety Key Laboratory of Sichuan Province School of Mechanics and Aerospace Engineering Southwest Jiaotong University Chengdu610031 China State Key Laboratory for Turbulence and Complex Systems College of Engineering Peking University Beijing100871 China Institute of Dynamics and Control College of Mechanical Engineering and Applied Electronics Technology Beijing University of Technology Beijing100871 China China Academy of Space Technology Beijing100094 China School of Naval Architecture Ocean and Civil Engineering Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of Marine Intelligent Equipment and System Ministry of Education Shanghai200240 China

Analyzing the landing dynamics response is essential for enhancing the success rate of surface explorations on Mars, the moon, or asteroids. This paper develops a comprehensive dynamics model for a space lander equipped with four sets of buffer legs, each consisting of a primary strut, two secondary struts, and a footpad, during its soft landing process. The degrees of freedom of the main body and the footpads are defined as generalized coordinates to describe the motion of the space lander. The compression force of the buffer struts is obtained by interpolating real experimental data, and the contact force between the footpad and the ground is calculated using Archimedes law for granular media. Then, the dynamical model for the lander in terms of minimal degrees of freedom can be constructed by applying the Lagrange equations of the second kind. The proposed dynamics model is validated by the experiments of a single-legged lander vertical touchdown and a four-legged lander free touchdown. Moreover, histories of buffer force, acceleration of the main body, and other key physical quantities are computed to investigate the landing process. This highly efficient and accurate dynamics model provides a method to perform extensive simulations to design and optimize a soft landing process. © 2024, The Authors. All rights reserved.

关键词： Landing

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Stealthy False Data Injection Attacks against Extended Kalman Filter Detection in Power Grids

Stealthy False Data Injection Attacks against Extended Kalma...

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International Conference on Informative and Cybernetics for Computational Social systems (ICCSS)

作者： Yifa Liu Wenchao Xue Shuping He Long Cheng State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Key Laboratory of System and Control Academy of Mathematics and System Science Chinese Academy of Sciences Beijing China School of Electrical Engineering and Automation Anhui University Hefei China

ISBN: (纸本)9781665402460

The power grid is a kind of national critical infrastructure directly affiliated to human daily life. Because of the vital functions and potentially significant losses, the power grid becomes an excellent target for many malicious attacks. Due to the special nonlinear measurements, many detection methods do not match the grid very well. The extended Kalman filter based detection is one of the few methods suitable for nonlinear system detection, and therefore can be used in power system to spot malicious attacks. However, the reliability and effectiveness of the extended Kalman filter based detection have not been fully studied and adequately guaranteed. By proposing a two-step false data injection attack strategy, this paper gives a stealthy way to inject false data of increasing magnitude into the power grid, which can eventually cause a certain degree of deviation of the grid state without being detected. In the simulation, the method proposed in this paper caused a voltage deviation of more than 25% before being discovered in the power system.

关键词： Power measurement Cyber-physical systems Information filters Power grids Safety Power system reliability Kalman filters

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Cross-Membrane Penetration to Nucleus of Adherent Cells Using Micropipettes Made by Borosilicate Glass and Quartz 17

Cross-Membrane Penetration to Nucleus of Adherent Cells Usin...

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17th IEEE International Conference on Mechatronics and Automation, ICMA 2020

作者： Xu, Xinyue Liu, Xiaoming Lin, Yuqing Li, Pengyun Liu, Fengyu Tang, Xiaoqing Huang, Qiang Arai, Tatsuo Beijing Institute of Technology Key Laboratory of Biomimetic Robots and Systems Ministry of Education State Key Laboratory of Intelligent Control and Decision of Complex System Beijing Advanced Innovation Center for Intelligent Robots and Systems School of Mechatronical Engineering Beijing100081 China

ISBN: (纸本)9781728164151

In the biomicromanipulation field, single-cell manipulation is receiving attention due to its potential applications in many aspects of biomedicine. Cell injection, as a typical cell micromanipulation technique, is devoted to introducing foreign substances into living cells by penetrating a fine micropipette into cell membranes. Direct access to the intracellular environment, especially the nucleus, provides an ideal way to gain insight into the dynamic processes of living cells. This paper presents the comparison of controlled penetrations of two types of adherent cells and their nuclei by two types of micropipettes, made of borosilicate glass and quartz respectively. Due to the differences in the cell properties (e.g., height, adhesion strength), two corresponding penetration strategies optimizing the puncture angle and puncture height, are proposed to improve the success rate of the puncture process and the survival rate of cells after the puncture. Real nucleus puncture experiments adopting the optimal puncture strategy for each type of cells and carried out by a semi-automatic system, indicated a better puncture effect by quartz pipettes. Through this method, functional materials such as peptides and nanoparticles can be potentially introduced to perturb the cell activities and then realize its full automation. © 2020 IEEE.

关键词： Quartz

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Parallel governance for decentralized autonomous organizations enabled by blockchain and smart contracts 1

Parallel governance for decentralized autonomous organizatio...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Ding, Wen Wen Liang, Xiaolong Hou, Jiachen Wang, Ge Yuan, Yong Li, Junqing Wang, Fei-Yue Institute of Systems Engineering Macau University of Science and Technology China School of Mathematics Renmin University of China Beijing China College of Computer Science and Engineering Shandong University of Science and Technology Qingdao China Institute of Automation Chinese Academy of Sciences State Key Laboratory for Management and Control of Complex Systems Beijing China

ISBN: (纸本)9781665433372

Decentralized autonomous organizations(DAOs) enabled by blockchain and smart contracts is regarded as an effective tool to solve corporate governance problems. It can minimize the contract risks, principal-agent dilemmas, and other issues in corporate governance. However, DAOs also face a variety of governance issues, such as internal governance issues and external governance issues caused by the technical attributes of blockchain and smart contracts. DAO is a typical complex system with the characteristics of both social and engineering complexity. It is difficult for existing governance theories to solve governance problems in DAOs. The parallel intelligence theory based on the artificial systems + computational experiments + parallel execution (ACP) method is a suitable research and practical approach to solve management and control problems for complex systems. Therefore, we propose a parallel governance framework for DAO based on the parallel intelligence theory and discuss its key research issues. Finally, we construct a parallel governance system for GnosisDAO, and conduct computational experiments on its voting mechanism. The results show the defects of GnosisDAO governance mechanism and we thus propose further research directions. We consider that parallel governance represents the future trend of DAO research and practice. This paper is aimed at stimulating further effort and providing helpful guidance and reference for future research works. © 2021 IEEE.

关键词： Smart contract

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Real-time In-situ Defect Detection in 3D Printing of Continuous Fiber-Reinforced Composites

Real-time In-situ Defect Detection in 3D Printing of Continu...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Zhijian Yue Zhen Shen Xiangyang Dong Qihang Fang Weixing Wang Xisong Dong Gang Xiong Fei-Yue Wang School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing China Intelligent Manufacturing Center Qingdao Academy of Intelligent Industries Qingdao China Guangdong Engineering Research Center of 3D Printing and Intelligent Manufacturing Cloud Computing Center Chinese Academy of Sciences Dongguan China State Key Laboratory for Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

ISBN: (数字)9798350349252

ISBN: (纸本)9798350349269

With the development of continuous fiber-reinforced composites (CFRCs) 3D printing technology, timely, efficient and accurate detection of fiber path defects is essential for ensuring product quality and performance. However, challenges still need to be addressed in this field, such as inadequate training data coverage and the complexity of fiber path structures. These factors hinder the capability of traditional methods to accurately assess the status of printed products. Therefore, developing accurate and robust fiber path defect detection techniques is crucial for CFRCs 3D printing technology. In this paper, we propose a precise detection method for fiber path defects in CFRCs 3D printing using the YOLOv7 object detection model combined with a Squeeze-and-Excitation (SE) attention mechanism. By introducing the SE attention mechanism, we enhance the perception capability of the YOLOv7 model for crucial features, thereby improving the accuracy of fiber path defect detection. The experimental results show that the YOLOv7 model, when augmented with an attention mechanism, achieves an average accuracy of 93.9% in identifying fiber path defects during the printing process. Compared to models without this attention mechanism, the results show that there is 10.7% increase, with a notably enhanced learning capacity during the training phase, which substantiates the efficacy and practicality of the proposed approach.

关键词： Training Solid modeling Accuracy Attention mechanisms Training data Three-dimensional printing Real-time systems Quality assessment Optical fiber testing Defect detection

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