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5th International Conference on Cognitive systems and Signal Processing, ICCSIP 2020

作者： Zhang, Xinyue Yang, Xu Liu, Zhiyong Zhang, Lu Ren, Dongchun Fan, Mingyu State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Meituan-Dianping Group Beijing100190 China

ISBN: (纸本)9789811623356

Visual cognitive ability is important for intelligent robots in unstructured and dynamic environments. The high reliance on large amounts of data prevents prior methods to handle this task. Therefore, we propose a model called knowledge-experience fusion graph (KEFG) network for novel inference. It exploits information from both knowledge and experience. With the employment of graph convolutional network (GCN), KEFG generates the predictive classifiers of the novel classes with few labeled samples. Experiments show that KEFG can decrease the training time by the fusion of the source information and also increase the classification accuracy in cross-task learning. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Image recognition

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Robotic Intra-Operative Ultrasound:Virtual Environments and Parallel systems

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IEEE/CAA Journal of Automatica Sinica 2021年第5期8卷 1095-1106页

作者： Shuangyi Wang James Housden Tianxiang Bai Hongbin Liu Junghwan Back Davinder Singh Kawal Rhode Zeng-Guang Hou Fei-Yue Wang the State Key Laboratory of Management and Control of Complex Systems Chinese Academy of SciencesInstitute of AutomationBeijing 100190China the School of Biomedical Engineering and Imaging Sciences King’s College LondonLondon SE17EHUK the Xtronics Ltd.Gravesend DA122ADUK

Robotic intra-operative ultrasound has the potential to improve the conventional practice of diagnosis and procedure guidance that are currently performed *** towards automatic or semi-automatic ultrasound,being able to define ultrasound views and the corresponding probe poses via intelligent approaches become *** on the concept of parallel system which incorporates the ingredients of artificial systems,computational experiments,and parallel execution,this paper utilized a recent developed robotic trans-esophageal ultrasound system as the study object to explore the method for developing the corresponding virtual environments and present the potential applications of such *** proposed virtual system includes the use of 3 D slicer as the main workspace and graphic user interface(GUI),Matlab engine to provide robotic control algorithms and customized functions,and PLUS(Public software Library for Ultra Sound imaging research)toolkit to generate simulated ultrasound *** implementation methods were presented and the proposed features of the system were *** on this virtual system,example uses and case studies were presented to demonstrate its capabilities when used together with the physical TEE *** includes standard view definition and customized view optimization for pre-planning and navigation,as well as robotic control algorithm evaluations to facilitate real-time automatic probe pose *** conclude,the proposed virtual system would be a powerful tool to facilitate the further developments and clinical uses of the robotic intra-operative ultrasound systems.

关键词： Medical robots parallel intelligence parallel systems robotic-assisted surgery robotic ultrasound

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SWDPM: A Social Welfare-Optimized Data Pricing Mechanism

arXiv

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arXiv 2023年

作者： Yu, Yi Yao, Shengyue Wang, Fei-Yue Li, Juanjuan Lin, Yilun Urban Computing Lab Shanghai AI Laboratory Shanghai China The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China The Macau Institute of Systems Engineering Macau University of Science and Technology China

Data trading has been hindered by privacy concerns associated with user-owned data and the infinite reproducibility of data, making it challenging for data owners to retain exclusive rights over their data once it has been disclosed. Traditional data pricing models relied on uniform pricing or subscription-based models. However, with the development of Privacy-Preserving Computing techniques, the market can now protect the privacy and complete transactions using progressively disclosed information, which creates a technical foundation for generating greater social welfare through data usage. In this study, we propose a novel approach to modeling multi-round data trading with progressively disclosed information using a matchmaking-based Markov Decision Process (MDP) and introduce a Social Welfare-optimized Data Pricing Mechanism (SWDPM) to find optimal pricing strategies. To the best of our knowledge, this is the first study to model multi-round data trading with progressively disclosed information. Numerical experiments demonstrate that the SWDPM can increase social welfare 3 times by up to 54% in trading feasibility, 43% in trading efficiency, and 25% in trading fairness by encouraging better matching of demand and price negotiation among traders. Copyright © 2023, The Authors. All rights reserved.

关键词： Markov processes

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From DAO to TAO: Finding The Essence of Decentralization

From DAO to TAO: Finding The Essence of Decentralization

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IEEE International Conference on systems, Man and Cybernetics

作者： Juanjuan Li Xiaolong Liang Rui Qin Fei-Yue Wang State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China Faculty of Innovation Engineering Macau University of Science and Technology Macau China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Decentralized Autonomous Organizations (DAOs) have been gaining popularity in recent years due to their promise of realizing the decentralized Web 3.0. However, most DAOs rely heavily on token-centric value systems as well as allocate decision-making authority and yield-sharing rights according to the held tokens, which often lead to monopolization of power and rights. To address this issue, this paper contributes to propose a truly democratic organization model, named True Autonomous Organizations and Operations (TAOs), that does not count upon tokens and is guided by principles of contribution-based and on-demand allocation. We first discuss the design of TAOs, including their infrastructures, power structures, and value systems, and then provide a technical roadmap for implementing TAOs in the DeSci context. This research can provide a valuable guidance for the construction and application of TAOs.

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management-Oriented Operating systems: Harnessing the Power of DAOs and Foundation Models

Management-Oriented Operating Systems: Harnessing the Power ...

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IEEE International Conference on systems, Man and Cybernetics

作者： Rui Qin Juanjuan Li Xiaolong Liang Fei-Yue Wang State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China Faculty of Innovation Engineering Macau University of Science and Technology Macau China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

This paper presents management-Oriented Operating systems (M2OS) that leverages the power of parallel intelligence theory, Decentralized Autonomous Organizations (DAOs) and foundation models to revolutionize the manner of management in Cyber-Physical-Social systems (CPSS). The parallel architecture on M2OS is proposed, including the parallel interactive actual M2OS and artificial M2OS. Among them, the artificial M2OSs provide digital infrastructures for organizations to operate, collaborate, and make decisions in the virtual space, and conduct computational experiments to evaluate management decisions and predict future states of the actual M2OS. Through parallel execution and closed-loop feedback between the artificial and actual M2OSs, the management and control, experimentation and evaluation, as well as learning and training of the actual M2OS can be realized. Moreover, the functional layers of M2OS, including the infrastructure layer, data layer, scenario layer, modeling layer, decision layer, and application layer, are discussed. These layers work together to support the intelligent, autonomous, collaborative, and adaptive nature of the M2OS, and facilitate data-driven decision-making, optimize business operations, and empower managers with real-time actionable insights. The proposed M2OS paradigm has great potential to transform the management paradigm and opens up new possibilities for intelligent and collaborative decision-making.

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A Novel Agricultural Data Sharing Mode Based on Rice Disease Identification

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Plant Diseases and Pests 2024年第2期15卷 9-16页

作者： Mengmeng ZHANG Xiujuan WANG Mengzhen KANG Jing HUA Haoyu WANG Feiyue WANG State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Beijing Engineering Research Center of Intelligent Systems and Technology Institute of AutomationChinese Academy of SciencesBeijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078China State Key Laboratory for Management and Control of Complex System Institute of AutomationChinese Academy of SciencesBeijing 100190China

In this paper,a variety of classical convolutional neural networks are trained on two different datasets using transfer learning *** demonstrated that the training dataset has a significant impact on the training results,in addition to the optimization achieved through the model ***,the lack of open-source agricultural data,combined with the absence of a comprehensive open-source data sharing platform,remains a substantial *** issue is closely related to the difficulty and high cost of obtaining high-quality agricultural data,the low level of education of most employees,underdeveloped distributed training systems and unsecured data *** address these challenges,this paper proposes a novel idea of constructing an agricultural data sharing platform based on a federated learning(FL)framework,aiming to overcome the deficiency of high-quality data in agricultural field training.

关键词： Rice disease and pest identification Convolutional neural networks Distributed training Federated learning(FL) Open-source data sharing platform

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Perception for Coupler Rod of Freight Train Based on Image and Point Clouds

Perception for Coupler Rod of Freight Train Based on Image a...

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2022 Chinese automation Congress, CAC 2022

作者： Guo, Renjie Feng, Jun Yang, Huachang Luan, Dejie Yang, Guodong Li, En Institute of Automation CAS State Key Laboratory of Management and Control for Complex Systems Beijing100190 China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing100049 China China Academy of Railway Sciences Corporation Limited Signal & Communication Research Institute Beijing100081 China

ISBN: (纸本)9781665465335

In the construction of automated marshaling yards, the automatic uncoupling operation of freight trains has always been the research and development direction. The coupler rod is the operation object of the uncoupling operation. The identification of coupler rod type and estimating position and posture are the prerequisites to realizing automatic uncoupling operation. In this paper, we propose a perception method of coupler rod by RGB image combined with the point cloud. We use an RGBD camera to synchronously collect frame-aligned RGB and depth images and generate point cloud data with colors according to the mapping relationship. Then, we use the YOLOv5 neural network to detect the collected RGB images and recognize the type of coupler rod in the image. Clear clutter in the point cloud and the bounding box is mapped to a spatial coordinate system for straight-through filtering of the point cloud. We use RANSAC for coarse registration and ICP for fine registration. The result of registration is carried out with the lower sampling point cloud model to achieve the registration of the coupler rod. Experiments show that this method can effectively segment the point cloud of the region of interest with high robustness. © 2022 IEEE.

关键词： Data fusion

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Autonomous Crowdsensing: Operating and Organizing Crowdsensing for Sensing automation

arXiv

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arXiv 2024年

作者： Wu, Wansen Yang, Weiyi Li, Juanjuan Zhao, Yong Zhu, Zhengqiu Chen, Bin Qiu, Sihang Peng, Yong Wang, Fei-Yue College of Systems Engineering National University of Defense Technology Hunan Province Changsha410073 China Hunan Institute of Advanced Technology Hunan Province Changsha410073 China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

—The precise characterization and modeling of Cyber-Physical-Social systems (CPSS) requires more comprehensive and accurate data, which imposes heightened demands on intelligent sensing capabilities. To address this issue, Crowdsensing Intelligence (CSI) has been proposed to collect data from CPSS by harnessing the collective intelligence of a diverse workforce. Our first and second Distributed/Decentralized Hybrid Workshop on Crowdsensing Intelligence (DHW-CSI) have focused on principles and high-level processes of organizing and operating CSI, as well as the participants, methods, and stages involved in CSI. This letter reports the outcomes of the latest DHW-CSI, focusing on Autonomous Crowdsensing (ACS) enabled by a range of technologies such as decentralized autonomous organizations and operations, large language models, and human-oriented operating systems. Specifically, we explain what ACS is and explore its distinctive features in comparison to traditional crowdsensing. Moreover, we present the "6A-goal" of ACS and propose potential avenues for future research. Copyright © 2024, The Authors. All rights reserved.

关键词： Cyber Physical System

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A PREA and OODA Computing Framework of Unmanned systems to Perform complex Tasks

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-18页

作者： Yang, Dongsheng Yu, Lei Zhang, Yi Zhu, Fenghua Li, Qiang Cui, Huachao Ma, Qiongmin Fan, Lili Tian, Yonglin Jinan University Guangzhou China Intelligent Science & Technology Academy Limited of CASIC Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China 28th Research Institute of China Electronics Technology Group Corporation Nanjing China National Key Laboratory for Complex Systems Simulation National University of Defense Technology Changsha China School of Information and Electronics Beijing Institute of Technology Beijing China

A C2 computing framework for unmanned systems to perform complex tasks is proposed using methods of system of systems engineering, which is formed by combining the macro-scale command and control (C2) process mechanism model (PREA loop) and micro-scale C2 process mechanism model (OODA loop). Guided by PREA loop and OODA loop, the computing framework is divided into four steps and three kinds of transformations. The four steps are design, construction, operation monitoring, and assessment. The three transformations are tactical feedback, campaign feedback, and strategic feedback. A C2 organization model of joint landing combat force is established against the background of a typical complex task of joint landing operation, and the C2 computing framework based on the PREA &OODA is used to implement the C2 activities of the joint landing combat force. The influence of the computing framework on the performance of unmanned systems under different task conditions is verified, including task coordination load, task efficiency and sensitivity of unmanned systems response. Authors

关键词： Feedback

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Exploring the Economic Feasibility of Advanced Air Mobility in the Early Stages

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年第5期9卷 4826-4830页

作者： Jingqiu Guo Long Chen Lingxi Li Xiaoxiang Na Ljubo Vlacic Fei-Yue Wang Key Laboratory of Road and Traffic Engineering of the Ministry of Education Tongji University Shanghai China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Department of Electrical and Computer Engineering Purdue School of Engineering and Technology Indiana University–Purdue University Indianapolis (IUPUI) Indianapolis IN USA Department of Engineering University of Cambridge Cambridge U.K. Institute of Intelligent and Integrated Systems and the School of Engineering and Built Environment Griffith University Nathan QLD Australia State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Institute of Engineering Macau University of Science and Technology Macau China

Advanced Air Mobility (AAM) envisages a sustainable, safe, convenient, and affordable air transport system. In socio-technical transition of AAM, there are a number of trade-offs in ecosystem that need to be studied. Three perspectives on economic feasibility are explored: first, based on history of VTOL services and value of time estimates, we discuss whether AAM can provide customers with competitive mobility services; second, what are the stakeholders’ insights on the deployment of AAM; last, the experience in the development of autonomous driving technology, such as parallel intelligence, can inform future AAM research.

关键词： Active appearance model Costs Economics Transportation Helicopters Aircraft propulsion Public transportation

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