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International Conference on Intelligent Transportation

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

Intelligent Transportation systems (ITS) are heavily dependent on private user data. However, most ITS fails to harness the potential of this invaluable data due to the absence of effective data governance mechanisms promoting users' contributions. Moreover, data contributors face security risks such as privacy preservation, data leakage, etc., as well as high costs in data sharing, while benefits are disproportionately reaped by system operators and interaction. This systemic imbalance could indirectly incentivize a surge in inactions and even malicious actions. In response to these challenges, we propose the design of a True Autonomous Organization (TAO) for ITS, namely ITS TAO. Utilizing the newly designed decision models with decentralized organization structures and the three-power structure, ITS TAO aims to realize the fair distribution of rights and benefits for ITS data contributors. Furthermore, we design a real-time evaluation system based on parallel intelligence capable of identifying potential hazards.

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CDP-GAN:Near-Infrared and Visible Image Fusion Via Color Distribution Preserved GAN

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1698-1701页

作者： Jun Chen Kangle Wu Yang Yu Linbo Luo the School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex SystemsEngineering Research Center of Intelligent Technology for Geo-ExplorationMinistry of EducationChina University of GeosciencesWuhan 430074China the Shanghai Institute of Technical Physics Key Laboratory of Infrared System Detecting and Imaging TechnologyChinese Academy of SciencesShanghai 200083China the School of Mechanical Engineering and Electronic Information China University of GeosciencesWuhan 430074China

Dear Editor,This letter is concerned with dealing with the great discrepancy between near-infrared(NIR)and visible(VS)image fusion via color distribution preserved generative adversarial network(CDP-GAN).Different from the global discriminator in prior GAN,conflict of preserving NIR details and VS color is resolved by introducing an attention guidance mechanism into the ***。

关键词： details dealing preserving

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Quantitative analysis of the impact of various urban socioeconomic indicators on search-engine-based estimation of COVID-19 prevalence

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Infectious Disease Modelling 2022年第2期7卷 117-126页

作者： Ligui Wang Mengxuan Lin Jiaojiao Wang Hui Chen Mingjuan Yang Shaofu Qiu Tao Zheng Zhenjun Li Hongbin Song Department of Infectious Disease Prevention and Control Center for Disease Control and Prevention of Chinese People's Liberation ArmyBeijingChina Academy of Military Medical Sciences Academy of Military Science of Chinese PLABeijingChina The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijingChina State Key Laboratory for Infectious Disease Prevention and Control National Institute for Communicable Disease Control and PreventionChinese Center for Disease Control and PreventionBeijingChina

Numerous studies have proposed search engine-based estimation of COVID-19 prevalence during the COVID-19 pandemic;however,their estimation models do not consider the impact of various urban socioeconomic indicators(USIs).This study quantitatively analysed the impact of various USIs on search engine-based estimation of COVID-19 prevalence using 15 USIs(including total population,gross regional product(GRP),and population density)from 369 cities in *** results suggested that 13 USIs affected either the correlation(SC-corr)or time lag(SC-lag)between search engine query volume and new COVID-19 cases(p<0.05).Total population and GRP impacted SC-corr considerably,with their correlation coefficients r for SC-corr being 0.65 and 0.59,*** population,GRP per capita,and proportion of the population with a high school diploma or higher had simultaneous positive impacts on SC-corr and SC-lag(p<0.05);these three indicators explained 37e50%of the total variation in SC-corr and *** for different urban agglomerations revealed that the goodness of fit,R2,for search engine-based estimation was more than 0.6 only when total urban population,GRP per capita,and proportion of the population with a high school diploma or higher exceeded 11.08 million,120,700,and 38.13%,respectively.A greater urban size indicated higher accuracy of search engine-based estimation of COVID-19 ***,the accuracy and time lag for search engine-based estimation of infectious disease prevalence can be improved only when the total urban population,GRP per capita,and proportion of the population with a high school diploma or higher are greater than the aforementioned thresholds.

关键词： Urban socioeconomic indicators Search engine-based estimation Effectiveness evaluation

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Unsupervised Learning of Gaussian Mixture Model with Application to Image Segmentation

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Chinese Journal of Electronics 2023年第3期19卷 451-456页

作者： Bo Li Wenju Liu Lihua Dou School of Automation Beijing Institute of Technology Beijing China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing Institute of Technology Beijing China National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing China

Density estimation via Gaussian mixture modeling has been successfully applied to image segmentation, speech processing and other fields relevant to clustering analysis and Probability density function (PDF) modeling. Finite Gaussian mixture model is usually used in practice and the selection of number of mixture components is a significant problem in its application. For example, in image segmentation, it is the donation of the number of segmentation regions. The determination of the optimal model order therefore is a problem that achieves widely attention. This paper proposes a degenerating model algorithm that could simultaneously select the optimal number of mixture components and estimate the parameters for Gaussian mixture model. Unlike traditional model order selection method, it does not need to select the optimal number of components from a set of candidate models. Based on the investigation on the property of the elliptically contoured distributions of generalized multivariate analysis, it select the correct model order in a different way that needs less operation times and less sensitive to the initial value of EM. The experimental results show the effectiveness of the algorithm.

关键词： Training Image segmentation Analytical models Parameter estimation Estimation Probability density function Speech processing

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Securing the Future after Pager Bombs:Lifecycle Protection of Smart Devices via Blockchain Intelligence

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IEEE/CAA Journal of Automatica Sinica 2024年第12期11卷 2355-2358页

作者： Fei Lin Qinghua Ni Jing Yang Juanjuan Li Nan Zheng Levente Kovács Radu Prodan Mariagrazia Dotoli Qing-Long Han Fei-Yue Wang the Department of Engineering Science Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078China the State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China the School of Artificial Intelligence University of Chinese Academy of SciencesBei-jing 100049China IEEE Obuda University John von Neumann Faculty of InformaticsBecsi Str.96/bH-1034 BudapestHungary the Institute of Information Technology University of Klagenfurt9020 Klagenfurt am WortherseeAustria the Department of Electrical and Information Engineering Polytechnic of Bari70126 BariItaly the School of Science Computing and Engineering TechnologiesSwinburne University of TechnologyMelbourne VIC 3122Australia the State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190

THE Lebanese wireless device explosion incident has drawn widespread attention,involving devices such as pagers,walkie-talkies,and other common devices[1].This event has revealed and highlighted the security vulnerabilities in global supply chains from raw material manufacturing and distribution to the usage of devices and equipment,signaling the onset of a new wave of"supply chain warfare"[2].

关键词： Smart cycle chains

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Autonomous Navigation and Obstacle Avoidance for Mobile Robots in a Tax Environment 13

Autonomous Navigation and Obstacle Avoidance for Mobile Robo...

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13th IEEE International Conference on CYBER Technology in automation, control, and Intelligent systems, CYBER 2023

作者： Yu, Lianyi Wu, Zhengxing Jiang, Yang Tan, Min Yu, Junzhi Institute of Automation Chinese Academy of Sciences Laboratory of Cognitive and Decision Intelligence for Complex System Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China Northeastern University Shenyang110000 China BIC-ESAT State Key Laboratory for Turbulence and Complex System College of Engineering Peking University Department of Mechanics and Engineering Science Beijing100871 China

ISBN: (纸本)9798350315196

This paper focuses on the navigation and obstacle avoidance problems of intelligent mobile robots in a tax environment. Through combining the improved jump point search (JPS) and dynamic window approach (DWA) algorithms, a fusion path planning method is proposed for the mobile robots in tax services. Specially, a bi-directional JPS algorithm with an adaptive heuristic function is provided to decrease the search complexity and improve search flexibility in the global path planning. Meanwhile, considering the features of the tax environment, several evaluation subfunctions are particularly designed to leverage the global information and optimize the local path planning. Finally, various simulations and experiments in a Turtlebot3 robot validate the feasibility and effectiveness of the proposed method. The obtained results provide valuable guidance for the autonomous navigation research of the tax service robots. © 2023 IEEE.

关键词： Taxation

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A DAOs-Based Publishing system for Advancing Open Access

A DAOs-Based Publishing System for Advancing Open Access

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

作者： Siji Ma Juanjuan Li Sangtian Guan Qinghua Ni Fei Lin Tengchao Zhang Jun Huang Fei-Yue Wang Faculty of Innovation Engineering Macau University of Science and Technology Macau 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

ISBN: (数字)9798350349252

ISBN: (纸本)9798350349269

The development of the scientific publishing system has remarkably enhanced global accessibility to research findings and substantially increased the visibility and dissemination of academic publications. However, significant challenges still exist in effectively safeguarding the intellectual property rights of contributors, such as the unauthorized usage of materials, the complexity of enforcing intellectual property rights across various legal jurisdictions, and high instances of plagiarism and content misuse. Additionally, financial barriers related to open access may restrict the participation of economically disadvantaged researchers, potentially biasing scientific records towards more affluent research initiatives. To address these issues, a novel decentralized framework is formulated to ensure truly open access. This framework leverages blockchain for immutable record-keeping and clear attribution of authorship, to prevent unauthorized usage and plagiarism. Besides, it also utilizes a copyright-sharing model based on decentralized autonomous organizations and operations (DAOs), where smart contracts automatically enforce copyright and access policies to ensure fair compensation for authors and researchers. Furthermore, the copyright sharing model based on non-fungible tokens (NFT) and gradual ownership optimization (GOO) mechanism is proposed to ensure fair and accurate recognition and compensation for scholarly contributions.

关键词： Open Access Law Plagiarism Smart contracts Intellectual property Research initiatives Scientific publishing Nonfungible tokens Remuneration Optimization

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A Vehicle-to-Vehicle Cooperative control Method for Intersections with Cav- Dedicated Lane

SSRN

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SSRN 2024年

作者： Zhang, Xiqiao Cui, Leqi Yang, Longhai Lv, Yisheng School of Transportation Science and Engineering Harbin Institute of Technology Harbin150090 China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

With the development of intelligent connected technology and autonomous driving technology, connected autonomous vehicles (CAV) and connected human-driven vehicles (CHV) will coexist for a long time in the future. The popularization of vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication enables the improvement of CAV platooning efficiency and the joint control of CAV trajectory and signal timing. Therefore, this paper proposes a CAV-dedicated lane-based vehicle-to-vehicle interactive intersection control method, which is suitable for managing mixed traffic flow of CHV and CAV at a single intersection. In the proposed method, the road capacity is enhanced by separating the mixed traffic flow with a CAV-dedicated lane. Through vehicle-to-vehicle interaction and CHV induction, the traffic flow spatiotemporal distribution is regulated by a limited number of controlled vehicles. Furthermore, by jointly controlling CAV trajectory and signal timing, vehicles can efficiently pass through the intersection in the CHV phase without the dedicated CAV phase. The optimization of signal timing and vehicle trajectory at the intersection aims to improve intersection capacity and smooth vehicle trajectories. In addition, the car-following and lane-changing models of CHV are revised based on the prospect theory to validate the performance of platooning strategies under cooperative induction information in practical traffic operations. Simulation results demonstrate that compared to control methods without considering vehicle-to-vehicle interaction, the proposed method in this paper has significant advantages in reducing average vehicle delay and improving intersection efficiency. © 2024, The Authors. All rights reserved.

关键词： Autonomous vehicles

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Adaptive Decentralized Asymptotic Tracking control for Large-Scale Nonlinear systems With Unknown Strong Interconnections

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 173-186页

作者： Ben Niu Jidong Liu Ding Wang Xudong Zhao Huanqing Wang College of Information Science and Engineering Shandong Normal UniversityJinan 250014China School of Artificial Intelligence Nankai UniversityTianjin 300071China Faculty of Information Technology Beijing University of TechnologyBeijing 100124 State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Control Science and Engineering Dalian University of TechnologyDalian 116023China Department of Mathematical Science and Automatization Institute Bohai UniversityJinzhou 121000China

An adaptive decentralized asymptotic tracking control scheme is developed in this paper for a class of large-scale nonlinear systems with unknown strong interconnections,unknown time-varying parameters,and ***,by employing the intrinsic properties of Gaussian functions for the interconnection terms for the first time,all extra signals in the framework of decentralized control are filtered out,thereby removing all additional assumptions imposed on the interconnec-tions,such as upper bounding functions and matching ***,by introducing two integral bounded functions,asymptotic tracking control is ***,the nonlinear filters with the compensation terms are introduced to circumvent the issue of“explosion of complexity”.It is shown that all the closed-loop signals are bounded and the tracking errors converge to zero *** the end,a simulation example is carried out to demonstrate the effectiveness of the proposed approach.

关键词： Adaptive decentralized control asymptotic tracking control large-scale nonlinear systems unknown strong interconnections

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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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2021 International Conference on Information, Cybernetics, and Computational Social systems, ICCSS 2021

作者： Liu, Yifa Xue, Wenchao He, Shuping Cheng, Long Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Institute of Automation Beijing100190 China Chinese Academy of Sciences Key Laboratory of System and Control Academy of Mathematics and System Science Beijing100190 China Anhui University School of Electrical Engineering and Automation Hefei230601 China

ISBN: (纸本)9781665402453

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. © 2021 IEEE.

关键词： Extended Kalman filters

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