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A Secure Medical Information Storage and Sharing Method Based on Multiblockchain Architecture

IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL systems 2024年第5期11卷 6392-6406页

作者： Hu, Jian Zhu, Peng Li, Juanjuan Qi, Yong Xia, Youbing Wang, Fei-Yue Nanjing Univ Sci & Technol Nanjing 210094 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Multimodal Artificial Intelligence Beijing 100190 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Nanjing Med Univ Affiliated Hosp 1 Nanjing 211166 Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Macau Univ Sci & Technol Fac Innovat Engn Macau 999078 Peoples R China

With the increasing application of technology in the healthcare industry, it has become imperative to establish a robust medical information ecosystem for effective management of medical information secure storage and sharing. This article proposes a healthier ecosystem in collaboration with the main consortium chain and data side chain, using multiblockchain architecture. In the implementation methods for this ecosystem, we store medical information in JavaScript Object Notation (JSON) format within different side chain structures. Additionally, we introduce an improved Practical Byzantine Fault Tolerant (PBFT) consensus mechanism based on a point nomination system and a dynamic RBAC access mechanism. By simulating a blockchain environment with multiple nodes, we analyze the efficiency of this method in terms of record retrieval, consensus mechanism, and storage execution time. The results demonstrate that compared to a single chain structure, the proposed method in this article achieves a substantial 30% improvement in query time efficiency. Moreover, the improved PBFT outperforms the traditional PBFT algorithm without dishonest nodes. Medical records stored in JSON format require shorter storage and execution time compared to text format records. This research contributes toward enhancing the security and efficiency of medical information storage and sharing among different medical subject information systems, thereby fostering a healthier healthcare alliance ecosystem.

关键词： Blockchain information storage and sharing medical information multiblockchain architecture

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Personality Shaping: A Prescriptive Approach Based on Virtual-Real Human Interaction

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IEEE TRANSACTIONS ON systems MAN CYBERNETICS-systems 2024年第12期54卷 7548-7557页

作者： Ye, Peijun Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Multimodal Artificial Intelligence S Beijing 100190 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Macau Univ Sci & Technol Inst Engn Macau Peoples R China

The era has been witnessing our entering into a more professional and cooperative society and also a bloom of various digital humans that help us complete more challenging industrial work than ever. As a major human-machine communication channel, virtual-real interaction between digital and real humans is an efficient way to adjust the mismatch between specialized tasks and participants with unsuitable personalities, elevating the overall performance of such human participated systems. This article proposes a new paradigm for temporary personality shaping by prescriptively interacting the human operator/user with his "digital assistant" in cyber space. As a first proposed personality shaping with AI-aided approach, the new paradigm involves digital human modeling with uncertain personality, computational experiments on personality evolution, and prescriptive interaction with user counterpart. By iteratively and repeatedly executing the three steps, the personality of human participants is gradually tailored and prescribed so that he can well undertake specific tasks. Experiments based on online social media data and human-machine shared driving have indicated that our new personality shaping paradigm is feasible and effective in performing representative tasks.

关键词： Digital humans Task analysis Computational modeling Psychology Data preprocessing Cognition Data models Digital human human-machine cooperation personality

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New Paradigm for Economic and Financial Research With Generative AI: Impact and Perspective

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IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL systems 2024年第3期11卷 3457-3467页

作者： Zheng, Xiaolong Li, Jingyu Lu, Mengyao Wang, Fei-Yue Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 101408 Peoples R China Inst Automat State Key Lab Multimodal Artificial Intelligence S Beijing 100190 Peoples R China Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Beijing Univ Technol Sch Econ & Management Beijing 100124 Peoples R China

In the past few years, we have witnessed the rapid development and exponential growth of generative artificial intelligence (GAI) technologies including large language models (LLMs)-enabled ChatGPT and peripheral innovations. These technologies are designed to be humanlike intelligence and intuitive by providing direct access to systems using application programming interfaces (APIs). The GAI applications can fundamentally change economic and financial activities, through revolutionizing the ways that humans interact with machines and giving rise to new modes of production and behavior patterns. It is imperative to develop a new research paradigm that is more suitable than the currently dominating conventional research paradigms. This article presents the new paradigm for economic and financial research with GAI, covering the research objectives, scientific data, and models, and explores the underlying impact and perspective that bring to this field. We elaborate on the potential five scenarios including portfolio management, economic and financial prediction, extreme scenario analysis, policy analysis, and financial fraud detection. The new research paradigm with GAI proposed in this article can provide significant insights for a comprehensive understanding of innovation and transformation in this domain.

关键词： Economics Biological system modeling Data models Task analysis Behavioral sciences Big Data Analytical models finance generative artificial intelligence (GAI) reinforcement learning from human feedback (RLHF) research paradigm

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MetaEconomics and Metamanagement for MetaCities and MetaSocieties in Metaverse

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IEEE TRANSACTIONS ON systems MAN CYBERNETICS-systems 2024年第11期54卷 6849-6858页

作者： Qin, Rui Li, Juanjuan Wang, Fei-Yue Chinese Acad Sci Inst Automat State Key Lab Multimodal Artificial Intelligence Beijing 100190 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Macau Univ Sci & Technol Fac Innovat Engn Macau Peoples R China

With the advent of Web 3.0, the evolution of cities and societies is increasingly oriented toward virtual spaces. This shift signifies an inevitable trend where the integration of virtual and real elements becomes vital to their development. Such a transition will bring huge changes to the organizational structure and methods, development modes, as well as operating mechanisms of cities and societies. In the virtual-real integrated cities and societies, traditional economic and management principles and models are no longer applicable. Consequently, it is crucial to explore new economic and management models tailored to Web 3.0. This article integrates virtual cities/societies with actual cities/societies, and proposes the innovative paradigm of MetaCities/MetaSocieties. Based on parallel intelligence theory and metaverse technologies, the research framework of MetaCities/MetaSocieties is established, and its main participants and operating mode are discussed. In addition, in view of the new economic and management issues faced in MetaCities/MetaSocieties, the innovative paradigms of MetaEconomics and Metamanagement are proposed, and the operational logic and models of MetaEconomics, as well as the Metamanagement big models and management-oriented operating systems, are proposed. This work aims to offer valuable insights for the evolution of cities and societies in the upcoming intelligent era, and inspire the development of new MetaEconomics and Metamanagement models in MetaCities/MetaSocieties.

关键词： Urban areas Decision making Biological system modeling Economics Real-time systems Training Metaverse Blockchain decentralized autonomous organization and operation (DAO) metaverse parallel intelligence Web 3 0

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Asynchronous Threshold ECDSA With Batch Processing

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IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL systems 2024年第1期11卷 566-575页

作者： Zhang, Hongxin Xie, Guanghuan Zou, Xin Zhang, Chi Li, Zhuo Qin, Rui Xiong, Gang Wang, Fei-Yue Zhejiang Univ State Key Lab CAD & CG Hangzhou 310058 Peoples R China State St Technol Zhejiang Ltd Global Technol Serv Dept Hangzhou 310000 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China 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 Macau Univ Sci & Technol Macao Inst Syst Engn Macau 999078 Peoples R China

Threshold Elliptic Curve Digital Signature Algorithm (ECDSA) has attracted a lot of attention due to the wide applications of ECDSA in crypto asset. Although several variants of threshold signature protocols can provide functions, such as key generation and signing, they suffer from two shortfalls. First, these schemes only discuss a single signature computation task in a synchronous algorithm context, which is difficult to adapt to real crypto-asset applications, such as custody. Second, these schemes are computing intensive and not scalable, hence can hardly support large-scale processing operations in real life even after traditional optimization, such as multithreading, is applied. In this article, we propose an innovative computation method called asynchronous threshold ECDSA with batch processing, based on the interactive threshold signature protocols. The method provides a reliable solution for critical operational scenarios, such as threshold signing and distributed key generation (DKG) in crypto-asset custody, and can be a future reference in secure data distribution mechanisms. The performance and scalability of our methods are validated through a benchmark testing.

关键词： Protocols Peer-to-peer computing Batch production systems Digital signatures Blockchains Electronic mail Urban areas Blockchain crypto-asset custody secure multiparty computation (MPC) threshold signature

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Integration of Train Regulation and Speed Profile Optimization Based on Feature Learning and Hybrid Search Algorithm

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IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL systems 2024年第2期11卷 2535-2544页

作者： Zhou, Min Hou, Zhuopu Wu, Xingtang Dong, Hairong Wang, Fei-Yue Beijing Jiaotong Univ State Key Lab Adv Rail Autonomous Operat Beijing 100044 Peoples R China Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

The independent hierarchy of train dispatching command and train operation control in the existing urban rail transit systems restricts the improvement of operational efficiency and emergency handling capability. This article focuses on integrating train regulation and speed profile optimization by utilizing a feature learning and hybrid search algorithm. Specifically, a genetic algorithm (GA) is used to optimize the train speed profile for a fixed interval running time, and then, the generated labeled sample data are used to train a convolutional neural network (CNN) to learn and extract the features of the optimal speed profile. The nonlinear mapping relationship between input and output variables in trajectory optimization is characterized by a well-trained CNN to reduce the computation time of the optimal speed profile during train regulation. The input variables comprise line conditions and interval running times, while the output variables include the corresponding energy consumption and operating condition switching points of the optimal speed profile. An integrated model of train regulation and operation control is developed with the objective of minimizing total train delay time and energy consumption. To ensure convergence and global search capability, we design a hybrid search algorithm-based train regulation algorithm. Simulation experiments are conducted using data from the Beijing Yizhuang line to validate the effectiveness of the proposed model and algorithms. The experimental results demonstrate that the proposed method can provide an optimal scheme for train regulation and speed profiles.

关键词： Convolutional neural network (CNN) hybrid search algorithm integration speed profile train control train regulation

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eVTOL Performance Analysis: A Review From control Perspectives

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年第5期9卷 1-13页

作者： Su, Jiangcheng Huang, Hailong Zhang, Hong Wang, Yutong Wang, Fei-Yue Department of Aeronautical and Aviation Engineering Hong Kong Polytechnic University Hong Kong China Co. Ltd. Guangzhou China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Electric Vertical Takeoff and Landing (eVTOL) aircraft has gained significant attention as a basic element of urban air mobility (UAM), a potential solution for urban transportation challenges using low-altitude urban airspace. Ensuring the safe operation of eVTOL is crucial for UAM applications, which are related to various professional fields such as aerodynamics, control, structures, and power systems. This article systematically analyzes the characteristics of different design configurations, including multi-rotor, lift+cruise, and tilt-rotor types of eVTOL. The advantages and limitations of each type of eVTOL are analyzed. After that, the overall design problems are analyzed, and challenges of eVTOL control system design are discussed from aspects of overall control structure and subsystems, such as controller, sensors, actuators, and command generator. This article tries to fill the gap in the eVTOL design from a control perspective and provides some resolutions for the eVTOL application. IEEE

关键词： Air mobility

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Photoelectric Intelligent Detection Platform Based on Multifunctional Edge Computing Equipment 43

Photoelectric Intelligent Detection Platform Based on Multif...

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43rd Chinese control Conference, CCC 2024

作者： Xu, Qianjing Chen, Wenjie Xue, Zhijun State Key Lab of Intelligent Control and Decision of Complex Systems Beijing10081 China Beijing Institute of Technology School of Automation Beijing100081 China

ISBN: (纸本)9789887581581

In order to study to design a photoelectric intelligent platform based on multifunctional edge computing equipment by using photoelectric detection equipment TC505C, RK-Series Development Kits computing platform and Nvidia Jetson Series. The photoelectric intelligent platform can be used to run multiple target detection algorithms after design and implementation. Completed as follows. First of all, after the first stage of the photoelectric intelligent platform is completed, the host computer can establish communication with the photoelectric detection equipment, carry out automatic or manual servo control on the photoelectric detection equipment, switch its visible and infrared field of view and view it in real time through the monitor, and realize simple tracking function through the image processing box. Secondly, after the second stage of the photoelectric intelligent platform is built, under the premise of ensuring the normal availability of servo function, a variety of target detection algorithms can be debugged on multifunctional edge computing equipment. Overall, this paper uses the modular design concept to design, debug and implement the system in stages. Pay attention to the synchronous debugging of hardware and software functions of each module to ensure the stability of each module. Finally completed the design goals of each stage. © 2024 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Program debugging

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Heterogeneous Image Knowledge Driven Visual Perception

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IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 255-257页

作者： Lan Yan Wenbo Zheng Fei-Yue Wang IEEE the College of Computer Science and Electronic Engineering Hunan UniversityChangsha 410082China the School of Computer Science and Artificial Intelligence Wuhan University of TechnologyWuhan 430070China the State Key Laboratory for Management and Control of Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China

Dear Editor,This letter is concerned with visual perception closely related to heterogeneous *** the huge challenge brought by different image modalities,we propose a visual perception framework based on heterogeneous image knowledge,i.e.,the domain knowledge associated with specific vision tasks,to better address the corresponding visual perception problems.

关键词： Visual visual knowledge

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AGGREGATION AND ADJUSTMENT MECHANISMS FOR DISASTER RELIEF TASK ALLOCATION WITH UNEVEN DISTRIBUTION

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JOURNAL OF INDUSTRIAL AND management OPTIMIZATION 2023年第3期19卷 1734-1754页

作者： Ma, Xinwei Wang, Danli Zheng, Nan Zhang, Song Univ Chinese Acad Sci Sch Artificial Intelligence Beijing Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China

The use of unmanned aerial vehicles (UAVs) to perform disaster relief task is becoming more and more popular. Generally, UAVs for rescuing are required to be heterogeneous, since the types of rescue missions are diverse. There are many researches on the task allocation of heterogeneous UAVs, in which they setup tasks to be randomly distributed when simulation. However, in most cases the distribution of tasks is regular rather than random. Therefore, we setup a set of special scenarios to simulate real disaster relief tasks, where most tasks concentrate in a few small areas and others are distributed randomly. LAL algorithm is an appropriate alternative to deal with assignment problems in scenarios where tasks are completely randomly distributed, but with a bit poor performance in the scenarios above mentioned. In order to obtain better results, this paper proposes three algorithms based on LAL algorithm in such scenarios. They are the Aggregation-LAL (A-LAL) using aggregation mechanism, Dynamic Adjustment-LAL (DA-LAL) using dynamic adjustment mechanism and Aggregation and Adjustment (AA-LAL) *** the experiments in the NetLogo simulation environment, the proposed algorithms are evaluated. The result shows improvements, which are average 5% obtained by AA-LAL, of task allocation in our special scenarios compared with existing algorithms.

关键词： Task allocation Swarm intelligence Heterogeneous UAVs Threshold-based method Disaster relief

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