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DeSci Based on Web3 and DAO: A Comprehensive Overview and Reference Model

IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL systems 2022年第5期9卷 1563-1573页

作者： Ding, Wenwen Hou, Jiachen Li, Juanjuan Guo, Chao Qin, Jirong Kozma, Robert Wang, Fei-Yue Macau Univ Sci & Technol Macao Inst Syst Engn Macau 999078 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China North Automat Control Technol Inst Taiyuan 030006 Shanxi Peoples R China Chinese Inst Command & Control CICC Beijing 100089 Peoples R China Univ Memphis Dept Comp Sci & Math Memphis TN 38152 USA

Decentralized science (DeSci) is a hot topic emerging with the development of Web3 or Web3.0 and decentralized autonomous organizations (DAOs) and operations. DeSci fundamentally differs from the centralized science (CeSci) and Open Science (OS) movement built in the centralized way with centralized protocols. It changes the basic structure and legacy norms of current scientific systems via reshaping the cooperation mode, value system, and incentive mechanism. As such, it can provide a viable path for solving bottleneck problems in the development of science, such as oligarchy, silos, and so on, and make science more fair, free, responsible, and sensitive. However, DeSci itself still faces many challenges, including scaling, balancing the quality of participants, system suboptimal loops, lack of accountability mechanism, and so on. Taking these into consideration, this article presents a systematic introduction of DeSci, proposes a novel reference model with a six-layer architecture, addresses the potential applications, and also outlines the key research directions in this emerging field. This article is committed to providing helpful guidance and reference for future research efforts on DeSci.

关键词： Analytical models Systematics Protocols Decentralized autonomous organization Computational modeling Education Computer architecture CPSS DAO decentralized autonomous operations decentralized autonomous organizations decentralized funding decentralized science DeSci metaverses parallel DeSci parallel intelligence Web3

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Analyzing Bitcoin transaction fees using a queueing game model

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ELECTRONIC COMMERCE RESEARCH 2022年第1期22卷 135-155页

作者： Li, Juanjuan Yuan, Yong Wang, Fei-Yue Beijing Inst Technol Sch Automat Beijing 100081 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

In the Bitcoin system, large numbers of miners invest massive computing resources in the blockchain mining process in pursuit of Bitcoin rewards, which are comprised of a fixed amount of system-generated new block reward and a variable amount of user-submitted transaction fees. Here, transaction fees serve as the important tuner for the Bitcoin system to define the priorities in users' transaction confirmation. In this paper, we aim to study the priority rule for queueing transactions based on their associated fees, and in turn users' strategies in formulating their fees in the transaction confirmation game. We first establish a full-information game-theoretical model to study users' equilibrium fee decisions;and then discuss three types of Nash equilibria, under which no, all and some users submit transaction fees. Moreover, we conduct empirical studies and design computational experiments to validate our theoretical analysis. The experimental results show that (1) users' fee decisions will be significantly affected by their waiting time;(2) the reduced time costs, instead of transaction values, are the basis for users to evaluate their revenues;(3) longer waiting time and higher unit time cost drive users to submit transaction fees in pursuit of desired priorities;(4) with the required transaction fee increasing, the proportion of fee-submitting users decreases slowly at first followed by a sharp decline, and over-high required fees will make the transaction confirmation game end up with no users submitting fees.

关键词： Bitcoin Blockchain Transaction fees Transaction confirmation queueing game

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Federated Vehicular Transformers and Their Federations: Privacy-Preserving Computing and Cooperation for Autonomous Driving

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IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2022年第3期7卷 456-465页

作者： Tian, Yonglin Wang, Jiangong Wang, Yutong Zhao, Chen Yao, Fei Wang, Xiao Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China North Automat Control Technol Inst Taiyuan 030006 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266109 Peoples R China

Cooperative computing is promising to enhance the performance and safety of autonomous vehicles benefiting from the increase in the amount, diversity as well as scope of data resources. However, effective and privacy-preserving utilization of multi-modal and multi-source data remains an open challenge during the construction of cooperative mechanisms. Recently, Transformers have demonstrated their potential in the unified representation of multi-modal features, which provides a new perspective for effective representation and fusion of diverse inputs of intelligent vehicles. Federated learning proposes a distributed learning scheme and is hopeful to achieve privacy-secure sharing of data resources among different vehicles. Towards privacy-preserving computing and cooperation in autonomous driving, this paper reviews recent progress of Transformers, federated learning as well as cooperative perception, and proposes a hierarchical structure of Transformers for intelligent vehicles which is comprised of Vehicular Transformers, Federated Vehicular Transformers and the Federation of Vehicular Transformers to exploit their potential in privacy-preserving collaboration.

关键词： Transformers Autonomous vehicles Collaborative work Point cloud compression Trajectory Computational modeling Vehicle dynamics Cooperative autonomous driving Federated Vehicular Transformers Federation of Vehicular Transformers Vehicular Transformers

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AUTOSIM:Automated Urban Traffic Operation Simulation via Meta-Learning

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IEEE/CAA Journal of Automatica Sinica 2023年第9期10卷 1871-1881页

作者： Yuanqi Qin Wen Hua Junchen Jin Jun Ge Xingyuan Dai Lingxi Li Xiao Wang Fei-Yue Wang Zhejiang Lab Hangzhou 310030China ECARX Technology Co. Ltd.Shanghai 201811China IEEE Zhejiang Supcon Information Company Ltd. Hangzhou 310052China the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Indiana University-Purdue University Indianapolis(IUPUI) IndianapolisIndiana 46202 USA School of Artificial Intelligence Anhui UniversityHefei 230039China

Online traffic simulation that feeds from online information to simulate vehicle movement in real-time has recently seen substantial advancement in the development of intelligent transportation systems and urban traffic *** has been a challenging problem due to three aspects:1)The diversity of traffic patterns due to heterogeneous layouts of urban intersections;2)The nature of complex spatiotemporal correlations;3)The requirement of dynamically adjusting the parameters of traffic models in a real-time *** cater to these challenges,this paper proposes an online traffic simulation framework called automated urban traffic operation simulation via meta-learning(AUTOSIM).In particular,simulation models with various intersection layouts are automatically generated using an open-source simulation tool based on static traffic geometry *** a meta-learning technique,AUTOSIM enables an automated learning process for dynamic model settings of traffic scenarios featured with different spatiotemporal ***,AUTOSIM is capable of adapting traffic model parameters according to dynamic traffic information in real-time by using a *** computational experiments,we demonstrate the effectiveness of the meta-learningbased framework that is capable of providing reliable supports to real-time traffic simulation and dynamic traffic operations.

关键词： Conditional generative adversarial network signalized urban networks short-term link speed prediction

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Testing Intelligence: Accelerating the Verification and Validation of Intelligent Vehicles

IEEE TRANSACTIONS ON INTELLIGENT VEHICLES

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IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2023年第2期8卷 1003-1016页

作者： Wang, Fei-Yue Hu, Jia Lai, Jintao Chinese Acad Sci State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Tongji Univ ZhongTe Distinguished Chair Cooperat Automat Key Lab Rd & Traff Engn Minist Educ Shanghai 201804 Peoples R China Tongji Univ Key Lab Rd & Traff Engn Minist Educ Shanghai 201804 Peoples R China

form only. Presents a summary of articles presented in this issue of the publication.

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Simultaneously Calibration of Multi Hand-Eye Robot System Based on Graph

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IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS 2023年第5期71卷 5010-5020页

作者： Zhou, Zishun Ma, Liping Liu, Xilong Cao, Zhiqiang Yu, Junzhi Chinese Acad Sci Inst Automat Beijing 100190 Peoples R China Australian Natl Univ Coll Engn Comp & Cybernet Canberra ACT 2601 Australia Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Peking Univ Dept Adv Mfg & Robot Coll Engn State Key Lab Turbulence & Complex SystBIC ESAT Beijing 100871 Peoples R China

Precise calibration is the basis for the vision-guided robot system to achieve high-precision operations. systems with multieyes (cameras) and multihands (robots) are particularly sensitive to calibration errors. Most existing methods focus on the calibration of a single unit of the whole system, such as poses between hand and eye, or between two hands. These methods can be used to determine the pose between each unit, but the serialized incremental calibration strategy cannot avoid the error accumulation problem in a large-scale system. Instead of focusing on a single unit, this article models the multieye and multihand system calibration problem as a graph and proposes a method based on the minimum spanning tree and graph optimization. This method can automatically plan the serialized optimal calibration strategy in accordance with the system settings to get coarse calibration results initially. Then, with these initial values, the closed-loop constraints are introduced to carry out global optimization with different sensor's accuracy considered. As a general calibration method, it can be applied to different multirobot systems. Simulation experiments demonstrate the performance of the proposed algorithm under different noises and various hand-eye configurations. In addition, experiments on real robot systems are presented to further verify the proposed method.

关键词： Calibration error correction graph theory multirobot systems robot vision systems.

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An Automatic Deep Segmentation Network for Pixel-Level Welding Defect Detection

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IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2022年 71卷 1-10页

作者： Yang, Lei Song, Shouan Fan, Junfeng Huo, Benyan Li, En Liu, Yanhong Zhengzhou Univ Sch Elect Engn Zhengzhou 450001 Henan Peoples R China Zhengzhou Univ Robot Percept & Control Engn Lab Zhengzhou 450001 Henan Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

Accurate welding defect location is of great significance to modern manufacturing, which could be used for accurate quality evaluation and precise repairing decision-making basis of different products. Nevertheless, accurate welding defect location is still a challenging task due to some complex factors, such as complex backgrounds, low contrast, weak texture, and class imbalance issue. Recently, deep learning has got great development due to its strong feature expression ability, which has been widely applied into defect detection, but it still exists certain shortcomings on segmentation tasks with the class unbalanced issue or microdefects. To address these issues, with the encoder & x2013;decoder network architecture, a novel welding defect location method is proposed with an attention-guided segmentation network. To reduce the contextual information loss of the deep encoder module after multiple convolution and pooling operations, a multiscale feature fusion block is proposed to embed into a U-shaped network (U-Net) to acquire more information. On the basis, combined with a bidirectional convolutional long short-term memory (BiConvLSTM) block, an improved attention block is integrated into the skip connections between the encoder path and the decoder path to capture the global, long-range contexts and emphasize target regions, contributing to locate welding defect areas and enhance the segmentation ability on microdefects. Meanwhile, to address the foreground & x2013;background class imbalance issue, a hybrid loss function combined with binary cross-entropy (BCE) and loss functions is proposed to effectively utilize their unique excellent characteristics for accurate defect segmentation. Experiment results on the public GDXray dataset show that the proposed segmentation method could obtain a competitive segmentation performance compared with other advanced segmentation models.

关键词： Welding Feature extraction Image segmentation Inspection X-ray imaging Manufacturing Task analysis Attention model convolutional long short-term memory (ConvLSTM) defect detection feature fusion hybrid loss image segmentation

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A Method of Touchable 3d Model Reconstruction based on Mixed Reality -A Case Study of Medical Training Applications 23

A Method of Touchable 3d Model Reconstruction based on Mixed...

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6th International Conference on Image and Graphics Processing, ICIGP 2023

作者： Liu, Mingyang Guo, Dalei Zhang, Zhicheng The School of Artificial Intelligence University of Chinese Academy of Sciences China The State Key Lab. of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences China Department of Orthopedic The 7th Medical Center of PLA General Hospital China

ISBN: (纸本)9781450398572

The application of trauma and hemorrhage medical treatment training has generated higher and higher requirements for the authenticity of the medical model. With the increasing integration of mixed reality technology and the medical field, multi-view-based 3D reconstruction technology can generate trauma medical object models not limited to specific targets, with low cost and high precision. However, the current reconstruction methods have weak points such as the inability to build the object surface beyond the direct view of humans, the uneven distribution of reconstructed point clouds, many holes, and reconstructed triangles. And it is time-consuming and laborious to fill and modify manually and requires highly skilled modeling expertise. Therefore, the models generated by traditional 3D reconstruction methods cannot meet the needs of interaction and touch in mixed reality applications. In order to solve these problems, we propose a new model generation method based on multi-view and point cloud processing, which enables the model to reduce the computational cost under the premise of meeting the need for direct interaction and touch in mixed reality applications. Finally, based on the reconstruction method proposed in this paper, a new medical trauma hemorrhage control and rescue training system is designed and implemented, which proves the effectiveness of the method proposed in this paper. © 2023 Owner/Author.

关键词： Mixed reality

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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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2023 IEEE International Conference on systems, Man, and Cybernetics, SMC 2023

作者： Li, Juanjuan Liang, Xiaolong Qin, Rui Wang, Fei-Yue Institute of Automation State Key Laboratory of Multimodal Artificial Intelligence Systems Chinese Academy of Sciences Beijing100190 China Macau University of Science and Technology Faculty of Innovation Engineering Macau999078 China Institute of Automation State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9798350337020

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. © 2023 IEEE.

关键词： Decentralized Autonomous Organizations and Operations (DAOs) governance systems open consortium blockchain True Autonomous Organizations and Operations (TAOs) value systems

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Integrated Timetable Rescheduling for Multidispatching Sections of High-Speed Railways During Large-Scale Disruptions

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IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL systems 2022年第2期9卷 366-375页

作者： Zhou, Min Dong, Hairong Liu, Xuan Zhang, Hongjie Wang, Fei-Yue Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China China Railway Beijing Grp Co Ltd Dept Dispatching Beijing 100038 Peoples R China Chinese Acad Sci CASIA Inst Automat State Key Lab Management & Control Complex Syst S Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Econ & Management Beijing 100049 Peoples R China

Under the condition of network operation of high-speed railways (HSRs), the influence of disruptions on the train control and dispatching at the current line and related lines is more and more significant. This article focuses on the timetable cooperative rescheduling problem with multidispatching sections of HSRs from a macroscopic perspective in the case of large disruptions. The problem is formulated as a mixed-integer linear program (MILP) model on the objectives of minimizing the weighted sum of the arrival delay time of trains, the delay time of depart trains at the handover station, and the number of delays of trains at all stations. The strategies of retiming and reordering are adopted to generate the rescheduling scheme and reduce delay propagation by making full use of three kinds of buffer time reserved in the timetable, i.e., buffer times of train operation in the station, train running in the section, and electric multiple unit (EMU) connection. A case study of the timetable rescheduling at the two adjacent dispatching sections of the Beijing-Shanghai HSRs line is conducted to evaluate the performance of the proposed integrated rescheduling approach. The relationship between computing time and the quality of rescheduling schemes is also investigated. The computational results show that the proposed approach can generate a conflict-free timetable with the minimum arrival delay time and the number of delays of all trains at all stations compared to the nonintegrated rescheduling approach and the benchmark solution of the first-come-first-serve (FCFS) approach. The propagation of delay between dispatching sections is also greatly suppressed. The results can provide support for dispatchers to making reasonable rescheduling decisions in the case of large disruptions.

关键词： Delays Dispatching Rail transportation Rails Safety Routing Real-time systems Delay propagation high-speed railways (HSRs) integrated timetable rescheduling large-scale disruptions multidispatching sections

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