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An IVC-Based Nuclear Emergency Parallel Evacuation System

IEEE TRANSACTIONS ON COMPUTATIONAL SOCIAL systems 2021年第4期8卷 844-855页

作者： Tan, Ke Yang, Linyao Liu, Xin Xu, Yancai Lin, Jiazhen Wang, Xiao Wang, Fei-Yue State Key Lab Nucl Power Safety Monitoring Techno Shenzhen 518108 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China Qingdao Acad Intelligent Ind Qingdao 266000 Peoples R China

Nuclear emergency evacuation is challenging and dangerous, with time constraints, resource limitations, and radiation exposure risks. The development of the Internet of Things (IoT) and artificial intelligence enables us to build an intelligent evacuation system to help mitigate this problem a great deal. In this article, we design the nuclear emergency parallel evacuation system based on the artificial systems (A), computational experiments (C), and parallel execution (P) approach and intelligent vehicle collaborative systems (IVCs). In this system, the evacuation risks of different regions under various possible scenarios are simulated and evaluated in the artificial systems. With data adversarially generated from the artificial systems and collected from sensors all over the area, an optimization model is proposed to find the optimal evacuation plans for emergent evacuation scenarios in the computational experiments. Eventually, the most suitable running strategy of autonomous buses will be selected and carried out based on the parallel execution in accordance with the real scene. A case study is conducted, and results indicate that the system can serve as an efficient tool for future nuclear emergency evacuation planning.

关键词： Computational modeling Planning Optimization Roads Mathematical model Collaboration Power generation ACP intelligent vehicle collaborative system nuclear evacuation optimization parallel intelligence

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Qingda Granule Attenuates Hypertension-Induced Cardiac Damage via Regulating Renin-Angiotensin System Pathway

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Chinese Journal of Integrative Medicine 2025年第5期31卷 402-411页

作者： LONG Lin-zi TAN Ling XU Feng-qin YANG Wen-wen LI Hong-zheng LIU Jian-gang WANG Ke ZHAO Zhi-ru WANG Yue-qi WANG Chao-ju WEN Yi-chao HUANGMing-yan QU Hua FU Chang-geng CHEN Ke-ji Department of Geriatrics Xiyuan Hospital of China Academy of Chinese Medical SciencesBeijing100091China Department of Traditional Chinese Medicine the Eighth Affiliated Hospital of Sun Yat-Sen UniversityShenzhenGuangdong Province518033China Xiyuan Hospital National Cardiovascular Clinical Medical Research Center of Traditional MedicineBeijing100091China Graduate School of Beijing University of Chinese Medicine Beijing100091China Cardiovascular Department the Second Affiliated HospitalShanxi University of Chinese MedicineTaiyuan030002China Key Laboratory of Molecular Imaging Beijing Key Laboratory of Molecular Imagingthe State Key Laboratory of Management and Control for Complex SystemsInstitute of AutomationChinese Academy of SciencesBeijing100090China Cadre 2 Ward Xinjiang Uygur Autonomous Region Institute of Traditional Chinese MedicineUrumqi830000China Academy of Integrative Medicine Fujian Univrsity of Traditional Chinese MedicineFuzhou350122China

Objective:To assess the efficacy of Qingda Granule(QDG)in ameliorating hypertensioninduced cardiac damage and investigate the underlying mechanisms ***:Twenty spontaneously hypertensive rats(SHRs)were used to develope a hypertension-induced cardiac damage *** 10Wistar Kyoto(WKY)rats were used as normotension *** were administrated intragastrically QDG[0.9 g/(kg·d)]or an equivalent volume of pure water for 8 *** pressure,histopathological changes,cardiac function,levels of oxidative stress and inflammatory response markers were ***,to gain insights into the potential mechanisms underlying the protective effects of QDG against hypertensioninduced cardiac injury,a network pharmacology study was *** results were validated by Western blot,radioimmunoassay immunohistochemistry and quantitative polymerase chain reaction,***:The administration of QDG resulted in a significant decrease in blood pressure levels in SHRs(P<0.01).Histological examinations,including hematoxylin-eosin staining and Masson trichrome staining revealed that QDG effectively attenuated hypertension-induced cardiac ***,echocardiography demonstrated that QDG improved hypertension-associated cardiac ***-linked immunosorbent assay and colorimetric method indicated that QDG significantly reduced oxidative stress and inflammatory response levels in both myocardial tissue and serum(P<0.01).Conclusion:Both network pharmacology and experimental investigations confirmed that QDG exerted its beneficial effects in decreasing hypertensioninduced cardiac damage by regulating the angiotensin converting enzyme(ACE)/angiotensinⅡ(AngⅡ)/AngⅡreceptor type 1 axis and ACE/AngⅡ/AngⅡreceptor type 2 axis.

关键词： blood pressure cardiac damage hypertension Qingda Granule renin-angiotensin system

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Real-Time Wrist Motion Decoding With High Framerate Electrical Impedance Tomography (EIT)

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IEEE TRANSACTIONS ON NEURAL systems AND REHABILITATION ENGINEERING 2023年 31卷 690-699页

作者： Liu, Xiaodong Zheng, Enhao Wang, Qining 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 Coll Engn Dept Adv Mfg & Robot Beijing 100871 Peoples R China Univ Hlth & Rehabil Sci Med Robot Lab Qingdao 266071 Peoples R China Beijing Inst Gen Artificial Intelligence Beijing 100080 Peoples R China Peking Univ Inst Artificial Intelligence Beijing 100871 Peoples R China

Human wrist motion decoding with a biological-signal-based interface is a key technique in the upper-limb exoskeleton and prosthesis control. One critical issue in this field is achieving high recognition precision and fast time response while against external disturbances of sensor re-wearing. In this study, we proposed a high-framerate Electrical Impedance Tomography (EIT) system combined with an adaptive recognition algorithm for real-time wrist kinematics decoding. The high-framerate EIT system was developed by a parallel stimulation measurement sequence, and the sampling rate was as high as 104 Hz. Compared to the most widely used myoelectric techniques, the EIT-based interface can provide extra deep muscular spatial information with similar surface electrodes. It greatly benefited the subsequent recognition algorithms, in which the key EIT regions indicating muscle morphology kept consistent after an arbitrary sensor re-donning. The designed adaptive algorithm achieved equally high performance with an automatic update of the classifier mean values with a fast self-operated calibration process. We validated the approach on 12 subjects with a 2-dimensional Fitts ' law test. The wrist gestures and joint angles were mapped to the direction and speed of the cursor movement, respectively. The average throughputs (TPs) of Fitts ' law tests were 1.0269 +/- 0.0971 bits/s and 1.0095 +/- 0.0931 bits/s without and with sensor re donning, respectively, which were comparable to the TPs of sEMG-based studies. The results showed the promise of the EIT-based interface on real-time human motion intent recognition. Future endeavors are worth being paid in this direction for more complicated robotic tasks.

关键词： Human-machine interface (HMI) electrical impedance tomography (EIT) wrist motion decoding sensor re-donning Fitts ' law test

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Crowdsensing Intelligence by Decentralized Autonomous Vehicles Organizations and Operations

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IEEE TRANSACTIONS ON INTELLIGENT VEHICLES 2022年第4期7卷 804-808页

作者： Zhu, Zhengqiu Wang, Xiao Zhao, Yong Qiu, Sihang Liu, Zhong Chen, Bin Wang, Fei-Yue Natl Univ Def Technol Coll Syst Engn Changsha 410073 Peoples R China Hunan Inst Adv Technol Changsha 410073 Peoples R China Anhui Univ China Sch Artificial intelligence Hefei 230039 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China

With the rapid growth of connected and autonomous vehicles (CAVs), vehicular crowdsensing (VCS) has emerged as an effective way in a wide range of applications, especially in intelligent transportation systems. However, centralized VCS frameworks have confronted many problems, such as privacy, security, utility, and dependability. To remedy these challenges, blockchain technology can be applied in VCS systems for effectively forming decentralized autonomous vehicles organizations and operations. This article briefly introduces blockchain-based VCS solutions addressing the current problems and presents potential directions for future research.

关键词： Blockchains Autonomous vehicles Smart contracts Privacy Crowdsensing Security Data privacy Connected vehicles Connected and autonomous vehicles vehicular crowdsensing blockchain technology

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A SINS Error Correction Approach Based on Dual-Threshold ZV Detection and Cubature Kalman Filter

A SINS Error Correction Approach Based on Dual-Threshold ZV ...

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IEEE International Conference on systems, Man and Cybernetics

作者： Ruijie Xu Shichao Chen Wenqiao Sun Yisheng Lv Jialiang Luo Ying Tang The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences College of Information Science & Technology Beijing University of Chemical Technology Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems The Center of National Railway Intelligent Transportation System Engineering and Technology Institute of Automation Chinese Academy of Sciences China Academy of Railway Sciences Corporation Limited Beijing China China Academy of Railway Sciences Corporation Limited Transportation and Economics Research Institute and the Center of National Railway Intelligent Transportation System Engineering and Technology Beijing China The State Key Laboratory for Management and Control of Complex System 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 System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences School of Information Engineering China University of Geosciences Beijing Beijing China Department of Electrical and Computer Engineering Rowan University Glassboro USA

Global Navigation Satellite systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation System (SINS) are widely used to locate people in complex interior or heavily occluded outdoor scenarios due to its light weight and low power consumption. However, IMU of SINS are noisy, and the sampling data error is large, which is a divergence of the error with time. Therefore, it will generate a positioning accumulation error, which affects the final positioning accuracy. The problem of cumulative IMU errors is usually dealt with by Zero-Velocity Update (ZUPT). The zero-velocity detection part of basic ZUPT method usually uses a single threshold to determine the gait of pedestrian, which often has the problem of gait misjudgment and omission. To address these problems, this paper proposes a composite conditional detection method to solve the problem of misjudgment in the zero-velocity interval. In addition, we redesign the zero-velocity update algorithm and uses the Cubature Kalman filter (CKF) for pedestrian positioning error correction. The experimental results demonstrate that the proposed ZUPT method based on dual-threshold detection can better detect the interval between pedestrian motion and stationery than ones with single threshold. The zero-velocity update algorithm based on CKF has higher performance than conventional EKF and UKF methods, which constrains the cumulative error of SINS to about 0.2% of the whole walking distance.

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Learning Skill Characteristics From Manipulations

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING systems 2023年第12期34卷 9727-9741页

作者： Zhou, Xiao-Hu Xie, Xiao-Liang Liu, Shi-Qi Ni, Zhen-Liang Zhou, Yan-Jie Li, Rui-Qi Gui, Mei-Jiang Fan, Chen-Chen Feng, Zhen-Qiu Bian, Gui-Bin Hou, Zeng-Guang 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 CAS Ctr Excellence Brain Sci & Intelligence Techn Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Macau Univ Sci & Technol Inst Syst Engn MUST CASIA Joint Lab Intelligence Sci & Technol Taipa Macau Peoples R China

Percutaneous coronary intervention (PCI) has increasingly become the main treatment for coronary artery disease. The procedure requires high experienced skills and dexterous manipulations. However, there are few techniques to model PCI skill so far. In this study, a learning framework with local and ensemble learning is proposed to learn skill characteristics of different skill-level subjects from their PCI manipulations. Ten interventional cardiologists (four experts and six novices) were recruited to deliver a medical guidewire to two target arteries on a porcine model for in vivo studies. Simultaneously, translation and twist manipulations of thumb, forefinger, and wrist are acquired with electromagnetic (EM) and fiber-optic bend (FOB) sensors, respectively. These behavior data are then processed with wavelet packet decomposition (WPD) under 1-10 levels for feature extraction. The feature vectors are further fed into three candidate individual classifiers in the local learning layer. Furthermore, the local learning results from different manipulation behaviors are fused in the ensemble learning layer with three rule-based ensemble learning algorithms. In subject-dependent skill characteristics learning, the ensemble learning can achieve 100% accuracy, significantly outperforming the best local result (90%). Furthermore, ensemble learning can also maintain 73% accuracy in subject-independent schemes. These promising results demonstrate the great potential of the proposed method to facilitate skill learning in surgical robotics and skill assessment in clinical practice.

关键词： Surgery Sensors In vivo Task analysis Arteries Measurement Sensor phenomena and characterization Ensemble learning in vivo porcine studies percutaneous coronary intervention skill characteristics wavelet packet decomposition (WPD)

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Adaptive Fusional Localization for Robot Fish Based on Dynamic-weight Fuzzy Inference

Adaptive Fusional Localization for Robot Fish Based on Dynam...

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2021 China Automation Congress, CAC 2021

作者： Fu, Yuzhuo Liao, Xiaocun Lu, Ben Zou, Qianqian Zhang, Zhuoliang Ou, Yarning Zhou, Chao State Key Laboratory of Management and Control for Complex Systems Institute of Automation CAS Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China

ISBN: (纸本)9781665426473

Accurate localization of robots in a specific environment often requires the cooperation of multiple sensors, and how to establish a more general data fusion model is always a difficult problem. For the localization of robot fish in an indoor pool environment, this paper proposes an adaptive fusional algorithm based on fuzzy inference of dynamic weights. This paper firstly constructs a confidence probability table of sensors' signals based on the calibration data sets of BLE and UWB nodes at different distances, as the basis for updating the weights of the BLE or UWB nodes;secondly, the data obtained by each node in a single sampling period in the robot fish movement is vectorized to form a judgment matrix, and then the estimated distance is obtained by fuzzy inference together with the sensor weight;finally, the coordinates are calculated by the four-point positioning method. In this paper, more than 40 sets of experiments have been carried out with a simplified carangidae-like robot fish. The results show that the average positioning error is about 0.189m, which is 88.3% and 31.8% lower than that of using BLE only and using UWB only. In this paper, the fusional positioning method based on statistics combines the advantages of different sensors to reduce the data scale and achieve data denoising while fusing sensor data, which provides a reference for indoor positioning of robot fish and multi-sensor data fusion. © 2021 IEEE

关键词： Fuzzy inference

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A New Constrained Cost Value Iteration for Optimal control of Discrete-Time Nonlinear systems

A New Constrained Cost Value Iteration for Optimal Control o...

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2021 China Automation Congress, CAC 2021

作者： Li, Tao Wei, Qinglai The 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

ISBN: (纸本)9781665426473

In this paper, a new constrained cost value iteration (CCVI) adaptive dynamic programming (ADP) algorithm is developed to solve optimal control problems with constrained cost function. The CCVI algorithm is initialized by a feasible control law, and the cost function of this initial feasible control constitutes the constraint condition in the policy update step. The convergence and optimality of the CCVI are analyzed. Furthermore, the feasibility of any iterative control law and the on-line evolving control law are proven. It is emphasized that the feasibility of any iterative control law and the on-line evolving control law guarantee that the CCVI algorithm can be used in situations where the cost function constraint is extremely important. Finally, a simulation example is given to verify the effect of the developed algorithm. © 2021 IEEE

关键词： control theory

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AGI in Metaverse for Smart Cities and Societies: A Cyber Physical Social Approach

AGI in Metaverse for Smart Cities and Societies: A Cyber Phy...

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Australian and New Zealand control Conference (ANZCC)

作者： Wang, Xiao Huang, Jun Tian, Yong-Lin Wang, Fei-Yue Anhui Univ Engn Res Ctr Autonomous Unmanned Syst Technol Minist Educ Hefei 230039 Peoples R China Macau Univ Sci & Technol Fac Innovat Engn Macau 999078 Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Macau Univ Sci & Technol Macao Inst Syst Engn Macau 999078 Peoples R China

ISBN: (纸本)9798350314977

The development of artificial general intelligence (AGI) and metaverse technologies hold great potential to enhance the effectiveness of smart cities and societies. we present a cyber-physical-social approach to integrating AGI into metaverse-based smart cities and societies, with a specific focus on parallel intelligence. The proposed approach considers the interplay between the physical environment, digital systems, social dynamics, and emerging forms of parallel intelligence, as well as swarm intelligence and collective intelligence. By leveraging these forms of parallel intelligence, the integration of AGI can create more responsive and proactive infrastructure, personalized and efficient services, and foster greater community engagement. The metaverse acts as a platform for simulating real-world scenarios and testing and refining AGI models before deployment in the physical world, while also facilitating the development and coordination of parallel intelligence. However, ethical considerations must be taken into account to ensure responsible deployment and avoid exacerbating existing societal inequalities or infringing upon individual privacy rights. This report provides a comprehensive framework for the integration of AGI and parallel intelligence into metaverse-based digital and smart organizations, while emphasizing the importance of human ethics, social responsibility, and ecological sustainability.

关键词： Artificial general intelligence parallel intelligence metaverse collective intelligence

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Image captioning on fine art paintings via virtual paintings 1

Image captioning on fine art paintings via virtual paintings

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

作者： Lu, Yue Guo, Chao Dai, Xingyuan Wang, Fei-Yue Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex Systems Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781665433372

Machine learning in fine art paintings is attracting increasing attention recently. Image captioning of paintings is of great importance for painting analysis, but it is rarely studied. The paintings have abstract expressions and lack annotated datasets, leading to the data-hungry problem in painting captioning. Thus, painting captioning has more significant challenges than photographic image captioning. This paper makes a novel attempt at generating content descriptions of paintings. We generate virtual paintings using the style transfer technique to deal with the data-hungry problem, then train the painting captioning model via a two-step manner. We evaluate our method on an annotated small-scale painting captioning dataset and demonstrate our improvements. © 2021 IEEE.

关键词： Painting

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