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IEEE International Conference on Multimedia and Expo (ICME)

作者： Wenbo Zheng Lan Yan Chao Gou Fei-Yue Wang School of Software Engineering Xi’an Jiaotong University Xi’an China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Intelligent Systems Engineering Sun Yat-sen University

ISBN: (数字)9781728113319

ISBN: (纸本)9781728113326

With more than 300 million people depressed worldwide annually, depression is a global problem. The goal of depression detection is to improve diagnostic accuracy and availability, leading to faster intervention. The most important and challenging problem here is to design an effective and robust depression detection model. To this end, there are two challenges to overcome: 1) Multi-modal (audio, image, text, etc.) information must be jointly considered to make accurate inferences. 2) Existing deep learning-based work suffers from multi-modal data sufficiency problem. To address these issues, we propose a graph attention model embedded with multi-modal knowledge for depression detection. This approach learns not only reasonable embeddings for nodes in the knowledge graph, but also exploits medical knowledge to improve the performance of classification and prediction with the knowledge attention mechanism. Experimental results on the real-world datasets show that the proposed approach significantly improves the classification and prediction performance compared with other major state-of-the-art approaches, with guaranteed the robustness with each modality of multi-modal data. Overall, this paper shows how multi-modal knowledge attention mechanism and deep-learning-based networks can be combined to assist mental health patients and practitioners.

关键词： Biomedical imaging Robustness Data models Machine learning Task analysis Knowledge engineering

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Reputation-based Distributed Filtering Over Sensor Networks Subject to Stochastic Nonlinearity and Network-Induced Quantization

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IEEE Transactions on Network Science and Engineering 2025年

作者： Jia, Chaoqing Wang, Zidong Hu, Jun Dong, Hongli Harbin University of Science and Technology School of Automation Harbin150080 China Harbin University of Science and Technology Heilongjiang Provincial Key Laboratory of Optimization Control and Intelligent Analysis for Complex Systems Harbin150080 China Brunel University London Department of Computer Science UxbridgeUB8 3PH United Kingdom Harbin University of Science and Technology Department of Applied Mathematics Harbin150080 China Northeast Petroleum University Artificial Intelligence Energy Research Institute Daqing163318 China Northeast Petroleum University Heilongjiang Provincial Key Laboratory of Networking and Intelligent Control Daqing163318 China

In sensor networks, due to inevitable sensor faults, malfunctions, or deliberate attacks, sensors may transmit erroneous, inaccurate, or misleading data, thereby degrading overall system performance. To address this issue, an effective approach is to assign reputation scores to sensors based on their trustworthiness, historical performance, or reliability. In this paper, the reputation-based distributed filtering (RBDF) problem is considered for a class of stochastic nonlinear systems over sensor networks with network-induced quantization. A reputation mechanism is employed to mitigate the adverse effects caused by noisy, faulty, or malicious sensors. Specifically, reputations are allocated by each sensor to the data received from its neighbors, ensuring that abnormal data are assigned smaller reputation values and may even be discarded. For the first time, a recursive RBDF algorithm is proposed, wherein an upper bound of the filtering error covariance (UBFEC) is derived by solving two matrix equations. Subsequently, the filter gain is determined by minimizing the trace of UBFEC at each step. Furthermore, a sufficient condition is presented to ensure the uniform boundedness of the filtering error dynamics. Finally, a simulation example is provided to verify the feasibility and validity of the developed RBDF algorithm. © 2013 IEEE.

关键词： Digital arithmetic

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Coverage Path Planning Design of Mapping UAVs Based on Particle Swarm Optimization Algorithm

Coverage Path Planning Design of Mapping UAVs Based on Parti...

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第三十八届中国控制会议

作者： Shouqi Wang Yongqiang Bai Chao Zhou School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems

Mapping UAVs have played a more important role in regional mapping than ever before, and coverage path planning is an important part of mapping tasks. However, there are few studies on single-region path planning in complex polygonal region. In this paper, we proposed a method that searches the optimal yaw-angle and flight height of mapping UAVs based on particle swarm optimization algorithm. Compared with traditional algorithms such as cattle farming algorithm, there are less redundant coverage and turning, and the flight path planned by the algorithm in this paper is more reasonable and convenient for photographic processing.

关键词： mapping UAVs coverage path planning particle swarm optimization

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Parallel Hospital: ACP-Based Hospital Smart Operating System

Parallel Hospital: ACP-Based Hospital Smart Operating System

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

作者： Yongjun Wang Fei-Yue Wang Xiao Wang Zhongjun Guan Liwei Ouyang Jiangong Wang Lan Yan Wenbo Zheng Wenwen Zhang Beijing Tiantan Hospital Capital Medical University Beijing Beijing China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Qingdao Academy of Intelligent Industries Qingdao China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China School of Software Engineering Xi'an Jiaotong University Xi'an China

This article aims to propose a parallel hospital based on parallel medicine. The parallel hospital takes the parallel idea of virtual and real interaction as its core concept and uses parallel idea's artificial scenarios, computational experiments, and parallel execution (ACP) theory as the guiding theory to construct a new generation of intelligent hospital management system with virtual and real interaction. We conducted a case study of the parallel hospital practice case of Tiantan Hospital-Tiantan Smart Brain, so as to confirm the feasibility and scientificity of the proposed parallel hospital.

关键词： Training Hospitals Operating systems Digital twin Conferences

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Multilane Detection and Tracking Based on Binocular Vision Stixel World Estimation and IPM

Multilane Detection and Tracking Based on Binocular Vision S...

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第三十八届中国控制会议

作者： Jing Li Junzheng Wang Guangtao Cui Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology

Road detection is the basic component of many intelligent vehicle systems. In this paper, a robust multi-lane detection method based on binocular vision is proposed. First, a fast estimation technique of the Stixel World, which is the outside environment representation of stereo-vision, is developed. Taking advantage of the estimate for free space under the plane road hypothesis, the proposed method is robust against on-road obstacles when detecting lane markings. Then, the bird-view of the transitable area is obtained through Inverse Perspective Mapping(IPM) Transform;Steerable filter, parallel parabolas modal and RANdom SAmple Consensus(RANSAC) technique are introduced for multi-lane fitting. Experimental results in real urban driving situations indicate that our algorithm is robust under various conditions.

关键词： Multilane detection and tracking Binocular vision Stixel World RANSAC

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Probabilistic Plan Recognition Under Temporal Logic Tasks

Probabilistic Plan Recognition Under Temporal Logic Tasks

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第三十八届中国控制会议

作者： Wentao Yu Hao Fang Daiying Tian School of Automation Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

In this paper, we consider the plan recognition problem in the real-time strategy game. A probabilistic plan recognition algorithm is proposed to predict the future goals and identify the temporal logic tasks of the non-cooperative agent based on the observations. In order to model the temporal logic tasks, the plan library is composed of the Finite Transition System and Nondeterministic B ¨uchi automation. Specially, we provide a unified framework to combine the plan recognition and the planning, and propose the probability calculation algorithm to calculate the posterior probability distribution of the goals and tasks. Finally, we verify the effectiveness of the proposed algorithm by the compared simulations.

关键词： Probabilistic Plan Recognition Linear Temporal Logic Büchi automation Goal Prediction

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Wearable Human Foot Mechanical Energy Harvesting Device Based on Moving-coil Generator

Wearable Human Foot Mechanical Energy Harvesting Device Base...

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第三十八届中国控制会议

作者： Ning Ding Fang Deng Yeyun Cai Peng Gui Xinyu Fan School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems

In order to solve the problem of energy supply for smart wearable devices, this paper proposes a wearable human foot mechanical energy harvesting device based on moving-coil generator, and designs a moving-coil type power generation shoes prototype. Firstly, the human foot horizontal movement is analyzed based on the human gait model. Combined with the characteristics of wearable devices, we determine that mechanical energy harvesting device installed in the heel is the most effective. Secondly, the moving-coil generator is designed and the prototype of moving-coil type power shoes is made. Finally,using the movement test platform of the laboratory, We complete the comfort test and optimize the structure, as well as analyze the basic performance of the device, which has good high-frequency characteristics.

关键词： Wearable energy harvesting Moving-coil generator Mechanical energy Human body

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A grasping CNN with image segmentation for mobile manipulating robot

A grasping CNN with image segmentation for mobile manipulati...

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2019 IEEE International Conference on Robotics and Biomimetics, ROBIO 2019

作者： Yu, Yingying Cao, Zhiqiang Liang, Shuang Liu, Zhicheng Yu, Junzhi Chen, Xuechao Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Institute of Automation Beijing100190 China University of Chinese Academy of Sciences Beijing100049 China Intelligent Robotics Institute BIT Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing100081 China

ISBN: (纸本)9781728163215

This paper presents a grasping convolutional neural network with image segmentation for mobile manipulating robot. The proposed method is cascaded by a feature pyramid network FPN and a grasping network DrGNet. The FPN network combined with point cloud clustering is used to obtain the mask of the target object. Then, the grayscale map and the depth map corresponding to the target object are combined and sent to the DrGNet network for providing multi-scale images. On this basis, depthwise separable convolution is used for encoding. The results of encoders are refined according to the light-weight RefineNet as well as sSE, which can achieve a better grasp detection. The proposed method is verified by the experiments on mobile manipulating robot. © 2019 IEEE.

关键词： Image segmentation

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Impedance Modeling of PMSG Wind Farms from the Machine Side DC-Port with Outer Power Loop

Impedance Modeling of PMSG Wind Farms from the Machine Side ...

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IEEE International Symposium on Circuits and systems (ISCAS)

作者： Jiajun Wang Xiaozhong Liao Bin Liu Xi Chen Xiangdong Liu Xiaoqin Lian Zhen Li School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing 100081 China GEIRI North America CA 95134 USA Beijing Technology and Business University Beijing 100048 China

ISBN: (数字)9781728133201

ISBN: (纸本)9781728133218

Due to the advantages of large unit capacity, high efficiency and high reliability, direct-drive permanent magnet synchronous generators (PMSGs) wind turbines (WTs) have been widely used in the offshore wind power generation. The power loop controller aims to maintain the DC-Bus voltage of each PMSG-WT is equal to the others, guaranteeing that multiple WTs can be connected in DC serial parallel collection. In this paper, the DC-Port sequence impedance model of the PMSG-WT is established based on the harmonic linearization method, which takes the outer power loop into consideration. The impedance model is further verified by point-by-point scanning in MATLAB/Simulink. The proposed DC-Port impedance model of the PMSG-WT facilitates the establishment of offshore direct-drive wind farms, and is of great significance for analyzing and improving the system stability.

关键词： Impedance Mathematical model Harmonic analysis Wind farms Generators Power system stability Topology

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Dissipativity Analysis for Markovian Jump Neural Networks with Time-Varying Delay via An Extended Relaxed Integral Inequality 37

Dissipativity Analysis for Markovian Jump Neural Networks wi...

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37th Chinese control Conference, CCC 2018

作者： Wen-Juan, Lin Yong, He Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences School of Automation Wuhan430074 China

ISBN: (纸本)9789881563941

This paper investigates the problem of the strictly (\mathcal{Q}, \mathcal{S}, \mathcal{R})-\gamma -dissipativity analysis for Markovian jump neural networks with a time-varying delay. By employing an appropriate Lyapunov-Krasovskii functional and using the extended relaxed integral inequality to estimate its derivative, a delay-dependent and mode-dependent condition that guarantee the considered Markovian jump neural networks strictly (\mathcal{Q}, \mathcal{S}, \mathcal{R})-\gamma -dissipative is derived. Finally, a numerical example is provided to illustrate the effectiveness of the proposed method. © 2018 Technical Committee on control Theory, Chinese Association of automation.

关键词： Lyapunov functions

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