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arXiv 2020年

作者： Wang, Wenshuo Na, Xiaoxiang Cao, Dongpu Gong, Jianwei Xi, Junqiang Xing, Yang Wang, Fei-Yue CA94720 United States Department of Engineering University of Cambridge Trumpington Street CambridgeCB2 1PZ United Kingdom Mechanical and Mechatronics Engineering University of Waterloo 200 University Ave. West Waterloo ONN2L3G1 Canada Department of Mechanical Engineering Beijing Institute of Technology Beijing100081 China School of Mechanical and Aerospace Engineering Nanyang Technological University Singapore639798 Singapore State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Research Center for Military Computational Experiments and Parallel Systems Technology National University of Defense Technology Changsha410073 China

Shared control schemes allow a human driver to work with an automated driving agent in driver-vehicle systems while retaining the driver’s abilities to control. The human driver, as an essential agent in the driver-vehicle shared control systems, should be precisely modeled regarding their cognitive processes, control strategies, and decision-making processes. The interactive strategy design between drivers and automated driving agents brings an excellent challenge for human-centric driver assistance systems due to the inherent characteristics of humans. Many open-ended questions arise, such as what proper role of human drivers should act in a shared control scheme? How to make an intelligent decision capable of balancing the benefits of agents in shared control systems? Due to the advent of these attentions and questions, it is desirable to present a survey on the decision-making between human drivers and highly automated vehicles, to understand their architectures, human driver modeling, and interaction strategies under the driver-vehicle shared schemes. Finally, we give a further discussion on the key future challenges and opportunities. They are likely to shape new potential research directions. Copyright © 2020, The Authors. All rights reserved.

关键词： Decision making

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Clinically Translatable Solid-state Dye for NIR-II Imaging of Medical Devices

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ADVANCED SCIENCE 2023年第36期10卷 e2303491页

作者： Li, Deling Shi, Hui Qi, Qingrong Chang, Baisong Jiang, Yuanwen Qian, Kun Guan, Xiudong Kang, Peng Ma, Ning Zhang, Yuan Zhang, Zeyu Shi, Xiaojing Qu, Chunrong Wu, Yilei Chen, Weiyu Chen, Hao Li, Baowang Chen, Liangpeng Li, Ziyang Ma, Shunchang Xu, Lingyun Zhang, Yanrong Tian, Jie Hu, Zhenhua Jia, Wang Cheng, Zhen Capital Med Univ Beijing Tiantan Hosp China Natl Clin Res Ctr Neurol Dis Dept NeurosurgBeijing Neurosurg Inst Beijing 100070 Peoples R China Stanford Univ Bio X Program Mol Imaging Program Stanford MIPS Stanford CA 94305 USA Stanford Univ Dept Radiol Stanford CA 94305 USA Chinese Acad Sci Shanghai Inst Mat Med Mol Imaging Ctr State Key Lab Drug Res Shanghai 201203 Peoples R China Bohai Rim Adv Res Inst Drug Discovery Shandong Lab Yantai Drug Discovery Yantai 264117 Shandong Peoples R China Northeastern Univ Inst Mol Med Coll Life & Hlth Sci Shenyang 110000 Peoples R China Sichuan Univ West China Sch Pharm Chengdu 610041 Peoples R China Wuhan Univ Technol State Key Lab Adv Technol Mat Synth & Proc Wuhan 430070 Peoples R China Stanford Univ Dept Chem Engn Stanford CA 94305 USA Capital Med Univ Beijing Tiantan Hosp Intervent Neuroradiol Ctr Beijing 100070 Peoples R China Chinese Acad Sci State Key Lab Management & Control Complex Syst CAS Key Lab Mol Imaging Beijing Key Lab Mol ImagingInst Automat Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Beihang Univ Sch Med Beijing Adv Innovat Ctr Big Data Based Precis Med Beijing 100191 Peoples R China

Medical devices are commonly implanted underneath the skin, but how to real-time noninvasively monitor their migration, integrity, and biodegradation in human body is still a formidable challenge. Here, the study demonstrates that benzyl violet 4B (BV-4B), a main component in the FDA-approved surgical suture, is found to produce fluorescence signal in the first near-infrared window (NIR-I, 700-900 nm) in polar solutions, whereas BV-4B self-assembles into highly crystalline aggregates upon a formation of ultrasmall nanodots and can emit strong fluorescence in the second near-infrared window (NIR-II, 1000-1700 nm) with a dramatic bathochromic shift in the absorption spectrum of approximate to 200 nm. Intriguingly, BV-4B-involved suture knots underneath the skin can be facilely monitored during the whole degradation process in vivo, and the rupture of the customized BV-4B-coated silicone catheter is noninvasively diagnosed by NIR-II imaging. Furthermore, BV-4B suspended in embolization glue achieves hybrid fluorescence-guided surgery (hybrid FGS) for arteriovenous malformation. As a proof-of-concept study, the solid-state BV-4B is successfully used for NIR-II imaging of surgical sutures in operations of patients. Overall, as a clinically translatable solid-state dye, BV-4B can be applied for in vivo monitoring the fate of medical devices by NIR-II imaging. Benzyl Violet 4B (BV-4B), serving as a component in the FDA-approved surgical sutures, is first discovered as a novel solid-state dye in the NIR-II window (1000-1700 nm). It can be used to non-invasively monitor the degradation process of surgical sutures, to diagnose the rupture of BV-4B-coated silicone catheter and to guide the hybrid fluorescence-guided surgery (hybrid FGS) of arteriovenous malformation (AVM) with embolization ***

关键词： aggregates in vivo imaging medical devices NIR-II fluorescence

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12.2: A 3D Display Parallel System: Light Field Re-rendering and Depth Sense Optimization

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SID Symposium Digest of Technical Papers 2018年第S1期49卷

作者： Renjing Pei Kui Ma Feiyue Wang State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences East Zhongguanchun Road No. 95 Haidian District Beijing School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing Parallel Optics Technology Innovation Center Qingdao Academy of Intelligent Industries Qingdao

The main benefit of 3D display over 2D display is the obvious ability to create a more lifelike character with high depth sense. However, the limitation of human eye's visual mechanism, unartful 3D scene structure design, or bad viewing condition always emerges poor depth perception experience or even physiological discomfort during the watching time, which is often sub-optimal for mass high-quality 3D display productions. To solve this problem, we propose a novel 3D display parallel system for depth sense optimization and it empirically guides how the light field should be re-rendered. Structurally, the parallel system consists of an artificial perception measurement system, a display evaluation model and a light field display rendering system, which includes the display calibration, scene capture, light field data processing and display. Particularly, the system can systematically analyze and model various factors affecting the depth sense which learned through the measurement system, like scene structure, objects’ speeds in 3D video and so on. And those sense factors can be personally modified or increased according to the viewer's demands or technical improvement. Moreover, the light field could be real-time re-rendered, based on some image processing technology, optical flow analysis and object segmentation (or tracking) (especially the one-shot video segmentation). Theory and algorithms are developed and experimental validation results show a superior performance.

关键词： 3D Display Parallel System Depth Sense Light Field Re-rendering 3D Video Processing One-shot Segmentation

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Special Issue on Deep Reinforcement Learning and Adaptive Dynamic Programming

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IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING systems 2018年第6期29卷 2038-2041页

作者： Zhao, Dongbin Liu, Derong Lewis, F. L. Principe, Jose C. Squartini, Stefano Chinese Acad Sci Inst Automat Beijing Peoples R China Univ Chinese Acad Sci Beijing Peoples R China Univ Arizona Tucson AZ USA IEEE Computat Intelligence Soc Adapt Dynam Programming & Reinforcement Learning Piscataway NJ USA IEEE Computat Intelligence Soc Multimedia Subcomm Piscataway NJ USA Beijing Chapter Beijing Peoples R China Univ Illinois Elect & Comp Engn & Comp Sci Chicago IL USA Int Neural Network Soc Hoffman Estates IL USA Int Assoc Pattern Recognit Hoffman Estates IL USA Inst Automat State Key Lab Management & Control Complex Syst Beijing Peoples R China Nanjing Univ Sci & Technol Nanjing Jiangsu Peoples R China Northeastern Univ Shenyang Liaoning Peoples R China Natl Acad Inventors Tampa FL USA IFAC Geneva Switzerland PE Texas UK Inst Measurement & Control Austin TX USA Univ Texas Arlington Arlington TX 76019 USA Univ Florida Elect & Comp Engn & Biomed Engn Gainesville FL USA Univ Florida ECE Gainesville FL USA Univ Florida Computat NeuroEngn Lab CNEL Gainesville FL USA Univ Florida Advisory Board Inst Brain Gainesville FL USA IEEE Signal Proc Soc Tech Comm Neural Networks Piscataway NJ USA UnivPM Dept Informat Engn Elect Circuit Theory Ancona Italy UnivPM Ancona Italy

In the first issue of Nature 2015, Google DeepMind published a paper “Human-level control through deep reinforcement learning.” Furthermore, in the first issue of Nature 2016, it published a cover paper “Mastering the game of Go with deep neural networks and tree search” and proposed the computer Go program, AlphaGo. In March 2016, AlphaGo beat the world’s top Go player Lee Sedol by 4:1. This becomes a new milestone in artificial intelligence history, the core of which is the algorithm of deep reinforcement learning (RL).

关键词： Optimal control Task analysis Heuristic algorithms Games Training data Approximation algorithms Nonlinear systems Dynamic programming Machine learning Artificial intelligence

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面向CPG驱动的仿生机器鱼容错控制方法

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Engineering 2018年第6期 253-269页

作者：杨越麒王健吴正兴喻俊志 State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences University of the Chinese Academy of Sciences

容错性能对于自推进仿生机器鱼在实际水下应用中的可操作性和生存能力至关重要。本文探讨了具有多个可活动关节和一个被卡住尾部关节的自由游动机器鱼的容错控制问题。提出的控制系统主要由两个部分组成:反馈控制器和前馈补偿器。具体而... 详细信息

容错性能对于自推进仿生机器鱼在实际水下应用中的可操作性和生存能力至关重要。本文探讨了具有多个可活动关节和一个被卡住尾部关节的自由游动机器鱼的容错控制问题。提出的控制系统主要由两个部分组成:反馈控制器和前馈补偿器。具体而言,一方面,设计了基于生物启发中心模式发生器的反馈控制器用于使机器鱼对外部干扰具有鲁棒性;另一方面,引入了基于动力学模型的前馈补偿器来加速整个控制系统的收敛。在此基础上,开展了仿真实验来完成控制系统分析和故障机器鱼游动性能验证。最后,水下实验表明,所提出的容错控制方法能够有效调整故障机器鱼,使其能够在故障情况下完成所需运动,进而提高实际机器鱼系统的稳定性和寿命。

关键词：容错控制机器鱼运动控制反馈控制器前馈补偿器

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Intraoperative near-infrared II window fluorescence imaging-assisted nephron-sparing surgery for complete resection of cystic renal masses

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CLINICAL AND TRANSLATIONAL MEDICINE 2021年第10期11卷 e604页

作者： Cao, Caiguang Deng, Shaohui Wang, Binshuai Shi, Xiaojing Ge, Liyuan Qiu, Min Zhang, Fan Lu, Min Ma, Lulin Chi, Chongwei Hu, Zhenhua Tian, Jie Zhang, Shudong Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing Key Lab Mol Imaging Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing Peoples R China Peking Univ Third Hosp Dept Urol Beijing 100191 Peoples R China Peking Univ Third Hosp Dept Pathol Beijing Peoples R China Beihang Univ Sch Med Beijing Adv Innovat Ctr Big Data Based Precis Med Beijing Peoples R China Xidian Univ Sch Life Sci & Technol Minist Educ Engn Res Ctr Mol & Neuro Imaging Xian Peoples R China

TABLE 1 Characteristics and preoperative diagnosis of patients with CRM Variable Value Patients, n 9 Age/year, M (range) 46 (35–65) Gender, n Male 8 Female 1 Affected side, n Left 5 Right 4 Tumour diameter/mm, M (range) 48 (27–61) Preoperative eGFR, M (range) 92 (68–113) RENAL score, M (range) 8 (4–9) Ischaemia time/min, M (range) 14 (10–25) Blood loss/ml, M (range) 100 (10–400) Hospital stay/day, M (range) 6 (3–6) Pathology ccRCC 4 BRC 4 PKD 1 Postoperative eGFR, M (range) 72 (41–105) Abbreviations: BRC, benign renal cyst; ccRCC, clear cell renal cell carcinoma; eGFR; estimated glomerular filtration rate; M, median; PKD, polycystic kidney disease. [...]pathological examination showed the tumour was clear cell renal cell carcinoma (ccRCC) and was completely resected (Figure 2O). First-in-human liver-tumour surgery guided by multispectral fluorescence imaging in the visible and near-infrared-I/II windows.

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Centrosymmetric- and Axisymmetric-Patterned Flexible Tactile Sensor for Roughness and Slip Intelligent Recognition

ADVANCED INTELLIGENT SYSTEMS

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ADVANCED INTELLIGENT systems 2022年第1期4卷

作者： Liu, Yafeng Cui, Shaowei Wei, Junhang Li, Haibo Hu, Jingyi Chen, Siyu Chen, Yin Ma, Yinji Wang, Shuo Feng, Xue Tsinghua Univ Appl Mech Lab Dept Engn Mech Beijing 100084 Peoples R China Tsinghua Univ Ctr Flexible Elect Technol Beijing 100084 Peoples R China Univ Chinese Acad Sci Sch Future Technol Beijing 100049 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Inst Flexible Elect Technol THU Jiaxing 314000 Zhejiang Peoples R China Qiantang Sci & Technol Innovat Ctr Hangzhou 310016 Peoples R China Chinese Acad Sci Ctr Excellence Brain Sci & Intelligence Technol Shanghai 200031 Peoples R China

Next-generation robots are being designed to function autonomously in complex and unstructured environments. In particular, based on the real-time measurement and differentiation of normal pressure and shear force, robots can be equipped with the capabilities of damage-free grasp within minimum force limits, as well as dexterous operation through surface roughness and slip information. Herein, a flexible tactile sensor with a small cylinder protrusion and four arc-shaped protrusions is developed. Due to its center symmetry and axisymmetry characteristics, the normal pressure and shear force can be decoupled from the complex stress without any interference from torsion. The flexible tactile sensor exhibits good linearity and superior cycling stability and is capable of determining the magnitude and direction of the applied force accurately. The flexible tactile sensor is comfortable to wear, and it is integrated onto the manipulator to realize various delicate and dexterous tasks, such as pressure detection, interaction with fragile objects, and roughness identification. Moreover, intelligent recognition of the sliding and stationary states can be achieved by decoding signals of sliding friction and static friction from the feedback information, leading to real time and precise adjustment of the grasping state of the manipulator.

关键词： complex stresses flexible tactile sensors intelligent recognition shear forces

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Recent Advances in Collaborative Scheduling of Computing Tasks in an Edge Computing Paradigm

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SENSORS 2021年第3期21卷 779-779页

作者： Chen, Shichao Li, Qijie Zhou, Mengchu Abusorrah, Abdullah Macau Univ Sci & Technol Fac Informat Tecnol Macau 999078 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Harbin Inst Technol Sch Mech & Elect Engn & Automat Shenzhen 518000 Peoples R China New Jersey Inst Technol Dept Elect & Comp Engn Newark NJ 07102 USA King Abdulaziz Univ Dept Elect & Comp Engn Fac Engn Jeddah 21481 Saudi Arabia King Abdulaziz Univ Ctr Res Excellence Renewable Energy & Power Syst Jeddah 21481 Saudi Arabia

In edge computing, edge devices can offload their overloaded computing tasks to an edge server. This can give full play to an edge server's advantages in computing and storage, and efficiently execute computing tasks. However, if they together offload all the overloaded computing tasks to an edge server, it can be overloaded, thereby resulting in the high processing delay of many computing tasks and unexpectedly high energy consumption. On the other hand, the resources in idle edge devices may be wasted and resource-rich cloud centers may be underutilized. Therefore, it is essential to explore a computing task collaborative scheduling mechanism with an edge server, a cloud center and edge devices according to task characteristics, optimization objectives and system status. It can help one realize efficient collaborative scheduling and precise execution of all computing tasks. This work analyzes and summarizes the edge computing scenarios in an edge computing paradigm. It then classifies the computing tasks in edge computing scenarios. Next, it formulates the optimization problem of computation offloading for an edge computing system. According to the problem formulation, the collaborative scheduling methods of computing tasks are then reviewed. Finally, future research issues for advanced collaborative scheduling in the context of edge computing are indicated.

关键词： collaborative scheduling edge computing internet of things limited resources optimization task offloading

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The impact of non-pharmaceutical interventions on the prevention and control of COVID-19 in New York City

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CHAOS 2021年第2期31卷 021101-021101页

作者： Yang, Jiannan Zhang, Qingpeng Cao, Zhidong Gao, Jianxi Pfeiffer, Dirk Zhong, Lu Zeng, Daniel Dajun City Univ Hong Kong Sch Data Sci Hong Kong 999077 Peoples R China Chinese Acad Sci Inst Automat State Key Lab Management & Control Complex Syst Beijing 100000 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100000 Peoples R China Shenzhen Artificial Intelligence & Data Sci Inst Shenzhen 518131 Peoples R China Rensselaer Polytech Inst Dept Mech Aerosp & Nucl Engn Troy NY 12180 USA City Univ Hong Kong Dept Infect Dis & Publ Hlth Hong Kong 999077 Peoples R China

The emergence of coronavirus disease 2019 (COVID-19) has infected more than 62 million people worldwide. control responses varied across countries with different outcomes in terms of epidemic size and social disruption. This study presents an age-specific susceptible-exposed-infected-recovery-death model that considers the unique characteristics of COVID-19 to examine the effectiveness of various non-pharmaceutical interventions (NPIs) in New York City (NYC). Numerical experiments from our model show that the control policies implemented in NYC reduced the number of infections by 72% [interquartile range (IQR) 53-95] and the number of deceased cases by 76% (IQR 58-96) by the end of 2020. Among all the NPIs, social distancing for the entire population and protection for the elderly in public facilities is the most effective control measure in reducing severe infections and deceased cases. School closure policy may not work as effectively as one might expect in terms of reducing the number of deceased cases. Our simulation results provide novel insights into the city-specific implementation of NPIs with minimal social disruption considering the locations and population characteristics.

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Deep learning radiomics based on contrast-enhanced ultrasound images for assisted diagnosis of pancreatic ductal adenocarcinoma and chronic pancreatitis

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BMC MEDICINE 2022年第1期20卷 74-74页

作者： Tong, Tong Gu, Jionghui Xu, Dong Song, Ling Zhao, Qiyu Cheng, Fang Yuan, Zhiqiang Tian, Shuyuan Yang, Xin Tian, Jie Wang, Kun Jiang, Tian'an Chinese Acad Sci Inst Automat CAS Key Lab Mol Imaging State Key Lab Management & Control Complex Syst Beijing 100190 Peoples R China Univ Chinese Acad Sci Sch Artificial Intelligence Beijing 100049 Peoples R China Zhejiang Univ Coll Med Affiliated Hosp 1 Dept Ultrasound Hangzhou 310003 Peoples R China Univ Chinese Acad Sci Canc Hosp Zhejiang Canc Hosp 1 East Banshan Rd Hangzhou 310022 Peoples R China Sichuan Univ West China Hosp Dept Ultrasound Chengdu 610041 Peoples R China Tongde Hosp Zhejiang Prov Dept Ultrasound Hangzhou 310012 Peoples R China Beihang Univ Beijing Adv Innovat Ctr Big Data Based Precis Med Sch Med & Engn Beijing 100191 Peoples R China Zhejiang Prov Key Lab Pulsed Elect Field Technol Hangzhou 310003 Peoples R China

Background Accurate and non-invasive diagnosis of pancreatic ductal adenocarcinoma (PDAC) and chronic pancreatitis (CP) can avoid unnecessary puncture and surgery. This study aimed to develop a deep learning radiomics (DLR) model based on contrast-enhanced ultrasound (CEUS) images to assist radiologists in identifying PDAC and CP. Methods Patients with PDAC or CP were retrospectively enrolled from three hospitals. Detailed clinicopathological data were collected for each patient. Diagnoses were confirmed pathologically using biopsy or surgery in all patients. We developed an end-to-end DLR model for diagnosing PDAC and CP using CEUS images. To verify the clinical application value of the DLR model, two rounds of reader studies were performed. Results A total of 558 patients with pancreatic lesions were enrolled and were split into the training cohort (n=351), internal validation cohort (n=109), and external validation cohorts 1 (n=50) and 2 (n=48). The DLR model achieved an area under curve (AUC) of 0.986 (95% CI 0.975-0.994), 0.978 (95% CI 0.950-0.996), 0.967 (95% CI 0.917-1.000), and 0.953 (95% CI 0.877-1.000) in the training, internal validation, and external validation cohorts 1 and 2, respectively. The sensitivity and specificity of the DLR model were higher than or comparable to the diagnoses of the five radiologists in the three validation cohorts. With the aid of the DLR model, the diagnostic sensitivity of all radiologists was further improved at the expense of a small or no decrease in specificity in the three validation cohorts. Conclusions The findings of this study suggest that our DLR model can be used as an effective tool to assist radiologists in the diagnosis of PDAC and CP.

关键词： Deep learning Artificial intelligence Pancreatic ductal adenocarcinoma Contrast-enhanced ultrasound Chronic pancreatitis

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