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7th International Conference on Data Mining and Big Data, DMBD 2022

作者： Li, Ding Zhang, Qichao Lu, Shuai Pan, Yifeng Zhao, Dongbin School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Baidu Inc. Beijing100085 China

ISBN: (纸本)9789811992964

Predicting the future trajectories of surrounding vehicles plays a vital role in ensuring the safety of autonomous driving. It is extremely challenging for the pure imitation method due to the high degree of multimodality and uncertainty in the future. In fact, when driving in most traffic scenarios, vehicles should obey some traffic rules such as "vehicles follow the lane and do not collide with each other". Inspired by this, this paper proposes a goal-aware prediction (GAP) framework to predict the multimodal trajectories, where goals are chosen in the lanes with hierarchical interactive representation and a multi-task loss. Based on the graph-based vectorized input, a novel hierarchical interactive representation module is first designed to obtain the fine-grained goal features, which progressively models interactions between goal-to-goal, goal-to-lane, and lane-to-agent, corresponding to the individual, local and global levels, respectively. Then, an auxiliary collision loss is developed to take into account learning from demonstration and injecting common sense of collision avoidance, and is served as a part of the multi-task loss to guide the generation of multimodal plausible trajectories. In the end, the proposed method is verified on the Baidu In-house Cut-in dataset, which includes more than 370K interactive scenarios collected in the real road testing. The comparative results demonstrate the superior performance of our proposed GAP model than the mainstream prediction methods. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Trajectories

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A Parallel control Method for Zero-Sum Game with Unknown Time-Varying System

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The International Journal of Intelligent control and systems 2024年第1期29卷 37-41页

作者： Qinglai Wei Zhenhua Zhu Jie Zhang Fei-Yue Wang State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China

In this paper,based on ACP(ACP:artificial societies,computational experiments,and parallel execution)approach,a parallel control method is proposed for zero-sum games of unknown time-varying *** process of constructing a sequence of artificial systems,implementing the computational experiments,and conducting the parallel execution is *** artificial systems are constructed to model the real *** experiments adopting adaptive dynamic programming(ADP)are shown to derive control laws for a sequence of artificial *** purpose of the parallel execution step is to derive the control laws for the real ***,simulation experiments are provided to show the effectiveness of the proposed method.

关键词： Zero-sum games parallel control ACP(ACP:artificial societies computational experiments and parallel execution) adaptive dynamic programming(ADP)

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A New Self-Learning Optimization management Scheme for Smart Grid systems

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The International Journal of Intelligent control and systems 2024年第2期29卷 66-70页

作者： Qinglai Wei Zehua Liao School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China Institute of Systems Engineering Macao University of Science and TechnologyMacao 999078China

This paper presents a new energy optimization management scheme for the smart grid system(SGS),which considers not only the inclusion of renewable energy in energy management but also the feedback sale of redundant renewable energy to the grid,so as to obtain better optimization management results and avoid energy waste.A new performance index function is constructed,which aims to save users’electricity costs and protect energy storage *** construct a periodic iterative self-learning method based on the characteristics that the relevant data of SGS are approximately *** proposed self-learning optimization method is based on adaptive dynamic programming(ADP).The initial iterative control law is obtained by pre-training,and the designed method can be realized by neural *** experiments are carried out by using the relevant data of SGS for four *** experimental results show that the new energy management scheme can help users save a lot of electricity costs,and is more effective than some common methods.

关键词： Smart grid system energy management renewable energy self-learning adaptive dynamic programming

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Parallel Treasury for TRUE DAOs: Model, Indicators and Mechanism*

Parallel Treasury for TRUE DAOs: Model, Indicators and Mecha...

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control Conference (ANZCC), Australian and New Zealand

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

In response to concerns over the centralization tendency in the decentralized autonomous organizations (DAOs), TRUE autonomous organizations and operations (TAOs or TRUE DAOs) have been proposed recently. TAOs aim at spreading equitable value distribution and democratized decision-making, distinguishing them from their DAOs counterparts. This study focuses on the treasury within TAOs, which acts as a central fund pool and a crucial element in the decentralized economy (DeEco) system. First, against a backdrop of potential black swan events and other long-tail unforeseen challenges, a reference model for the intelligent treasury management of TAOs is proposed. Then, an evaluation system, namely VALID, is presented with metrics including verifiability, anti-volatility, legitimacy, inclusiveness, and decentralization. Furthermore, a novel parallel treasury management mechanism is proposed to demonstrate a virtual-real interactive closed-loop management and control paradigm of the treasury, thereby fostering the formulation and development of DeEco. This research provides a comprehensive perspective on intelligent treasury management of TAOs and their role in sustainable advancement of DeEco.

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MoB-NetV2-RVFL: Diagnosis of Coronavirus (COVID-19) from CT images via a Deep Learning Architecture

MoB-NetV2-RVFL: Diagnosis of Coronavirus (COVID-19) from CT ...

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2024 Jiangsu Annual Conference on automation, JACA 2024

作者： Tang, Xiaoyu Chai, Lin Song, Chengze School of Automation Southeast University Jiangsu Nanjing210096 China Ministry of Education Key Laboratory of Measurement and Control of Complex Systems of Engineering Southeast University Jiangsu Nanjing210096 China School of Sino-french Engineering Institute Nanjing University of Science and Technology Jiangsu Nanjing China

ISBN: (纸本)9781837242689

Computer-aided diagnosis has emerged as a crucial trend in modern medicine. Recently, CT-based automatic detection algorithms for lung infectious diseases suffer from issues of low accuracy and complex architecture. In this paper, three MoB-NetV2 models (MoB-NetV2-SNN, MoB-NetV2-ELM, and MoB-NetV2-RVFL) for the detection of COVID-19 in CTs are proposed. the MoB-NetV2 model is proposed by inserting batch normalization layers between bottlenecks in MobileNetV2 and substituting the fully connected layer with the Net-1 model (SNN, ELM, RVFL), i.e. MoB-NetV2-SNN, MoB-NetV2-ELM, and MoB-NetV2-RVFL. After comparison, it is found that the proposed MoB-NetV2-RVFL achieves an average accuracy of 93.42% on a private dataset comprising of 2392 images, while the precision is reached at 97.33%. Furthermore, it is demonstrated that our MoB-NetV2-RVFL outperforms other existing algorithms in the literature. High classification accuracy and precision and low computing amount are achieved, thereby enhancing the potential application of the model in the field of medical image-aided diagnosis of COVID-19 virus. © The Institution of Engineering & Technology 2024.

关键词： COVID-19

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Enhancing sensitivity of ultrasmall rotation velocity measurements with biased quantum weak measurement 41

Enhancing sensitivity of ultrasmall rotation velocity measur...

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第41届中国控制会议

作者： Guang-Jun Wang Xue-Ying Duan Jing-Hui Huang Xiang-Yun Hu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Institute of Geophysics and Geomatics China University of Geosciences Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Recently,biased quantum weak measurement has shown higher precision than both conventional measurement and standard quantum weak measurement in optical *** this work,a scheme of detecting the ultrasmall rotation velocity in Sagnac's interferometer with biased quantum weak measurement is *** biased quantum weak measurement,additional progress of pre-coupling is introduced in standard quantum weak measurement to enhance the sensitivity for the estimated parameter,and the cost of the reduction of photons in the post-selection by pre-coupling may not impact the measurement because eliminating the saturation effect of the detector *** addition,our numerical results show that the scheme with biased quantum weak measurement can obtain a higher sensitivity for rotation velocity measurement than the scheme with standard quantum weak measurement.

关键词： quantum measurement quantum weak measurement quantum optical rotation velocity sensitivity enhanced

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Evaluating the Generalization of 3D Detectors with Hybrid Point Clouds 2

Evaluating the Generalization of 3D Detectors with Hybrid Po...

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2nd International Conference on Computer Science and management Technology, ICCSMT 2021

作者： Tian, Yonglin Wang, Xiao University of Science and Technology of China Department of Automation Hefei China Institute of Automation Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Beijing China

ISBN: (纸本)9781665420631

With the development of LiDAR technologies and deep learning algorithms, tremendous methods have been proposed for 3D detection in intelligent transportation. However, the generalization of 3D detectors under different environments is not fully evaluated due to the lack of diverse testing datasets. Two of the main obstacles in building testing benchmark of point clouds are the huge cost of the annotation of point clouds and the low flexibility in data collection. In this paper, we propose to use hybrid point clouds to evaluate the generalization of multiple 3D detectors when they are transferred from real data to hybrid data. Compared with evaluating 3D detectors with real point clouds dataset, our approach is much more flexible and demands less human labor. © 2021 IEEE.

关键词： Deep learning

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Haptic-Aided Navigation Vehicle: Enhancing Obstacle Detection in Blind Spots and Transparent Object Scenarios

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Journal of Shanghai Jiaotong University (Science) 2025年 1-9页

作者： Li, Mingwang Li, Xinde Zhang, Zhentong Zhang, Zeyu Zhao, Haoming School of Software Southeast University Suzhou Jiangsu215000 China School of Automation Southeast University Nanjing210018 China School of Cyber Science and Engineering Southeast University Nanjing211102 China Key Laboratory of Measurement and Control of Complex Systems of Engineering of Ministry of Education Nanjing214135 China Nanjing Center for Applied Mathematics Nanjing211135 China Southeast University Shenzhen Research Institute Shenzhen Guangdong518063 China

As autonomous mobile robots are increasingly deployed in complex environments, traditional vision sensors and LiDAR encounter considerable limitations, particularly in detecting obstacles in blind spots or transparent objects. To address the issue of blind spots, we design a specialized haptic sensing structure and develop the haptic-aided navigation vehicle (HANV). This system integrates haptic sensors and LiDAR to deliver comprehensive perception, significantly enhancing close-range obstacle detection in areas that are typically beyond the range of conventional sensors. To tackle the challenge of transparent obstacles, which are often undetected by both vision and LiDAR sensors, we employ a fusion of haptic sensors and LiDAR. The haptic system provides physical contact feedback, ensuring reliable detection of transparent obstacles such as glass, while LiDAR offers long-range sensing capabilities. This combination enables HANV to navigate effectively in environments with transparent obstacles, overcoming the limitations of traditional sensing systems. Experiment results indicate that the proposed haptic and LiDAR integration substantially improves obstacle detection in both blind spots and environments with transparent obstacles. HANV achieves high success rates, minimal collisions, and efficient obstacle avoidance, particularly excelling in complex, confined spaces where conventional systems prove inadequate. These findings emphasize the efficacy of our approach in enhancing navigation performance in dynamic and challenging environments. (Figure presented.) © Shanghai Jiao Tong University 2025.

关键词： Mobile robots

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Anomaly detection in digital twin model 1

Anomaly detection in digital twin model

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

作者： Wang, Yutong Cao, Yansong Wang, Fei-Yue Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex Systems Beijing China Macau Institute of Systems Engineering Macau University of Science and Technology China

ISBN: (纸本)9781665433372

As the simulation model of a physical system, digital twin has been widely used in many complicated control systems. Providing an effective way to perform simulation, digital twin makes the evaluation, prediction and optimization process cheaper and easier than on physical systems. For smart manufacturing, digital twin achieves high productivity with less operation and maintenance cost. However, the advantages of digital twin in anomaly detection during manufacturing are always neglected. Taking a two-speed transmission system as an example, we generate three kinds of faults on this digital twin model. After extracting features from the system output, we train an anomaly detection model on these features to classify each type of fault. By this digital twin model, we can find the fault in the whole system at the very beginning, and reduce the time and cost of debugging and diagnosing. © 2021 IEEE.

关键词： Anomaly detection

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Traditional Chinese medicine diagnosis and treatment based on systematics

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iLIVER 2023年第4期2卷 181-187页

作者： Zhanhong Wang Danli Wang Wen Liu Zhongxia Wang The State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of SciencesBeijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China Beijing Hospital of Traditional Chinese Medicine Capital Medical UniversityBeijing 100010China Department of Nutrition Fifth Medical CenterPLA General HospitalBeijing 100039China

Background:Traditional Chinese Medicine(TCM)is a well-established medical system with a long ***,the overall concept and systematic thinking in TCM are not comprehensively understood and applied in its inheritance and *** This study aims to provide a basic theory for TCM diagnosis using systematics as the guiding *** modern scientific and technological achievements,we aim to explore a new TCM diagnosis ***:We analyzed previous studies on TCM diagnosis and treatment,and reviewed clinical research on TCM diagnosis and treatment from the viewpoint of *** propose a new process model based on systematics for TCM diagnosis and *** is a generalized model that summarizes the process of“establishing an image to express meaning”.Results:The proposed model was implemented in the clinical practice of *** monitored the detailed treatment process of patients in the Department of Liver Diseases at Beijing *** patient underwent a treatment program that lasted 1 year and 45 days,consisting of 12 iterative cycles,each guided by the proposed diagnostic model and tailored to the patient's evolving *** case study validates the effectiveness of the proposed model in the diagnosis and treatment of liver disease in *** therapeutic efficacy has been validated through the examination of both TCM indicators and Western medical auxiliary *** these,the TCM indicators consist of 2 components:tongue diagnosis and pulse ***,the Western medical auxiliary indicators encompass a range of assessments,including whole blood cell analysis,professional liver function examination,a series of liver function assessments,a high-sensitivity hepatitis B pentathlete test,as well as color Doppler ultrasound evaluations of the liver,bile duct,pancreas,spleen,and assessments of liver elasticity,among other related examination *** conclusion,it is evident that the syndrome of l

关键词： Traditional Chinesemedicine Systematics Diagnosis and treatment model Liver disease

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