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An Improved Result on Stabilization of Switched Linear Systems with Time-varying Delay ⁎

IFAC-PapersOnLine 2021年第18期54卷 96-101页

作者： Tan Hou Yuanlong Li Zongli Lin Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China and Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia P.O. Box 400743 Charlottesville VA 22904-4743 U.S.A.

This paper revisits the stabilization problem of switched linear systems with time-varying delay via state dependent switching strategies. In contrast to the existing works, the commonly adopted stable convex combination assumption is relaxed in this paper. For switched systems satisfying the relaxed assumption, we design a state dependent switching strategy, under which the considered system is asymptotically stable at the origin in the presence of time-varying delay. An optimization problem is formulated to estimate the upper bound of tolerable time delay. Numerical examples are presented to show that our method is applicable to a larger class of switched systems and leads to greater delay bound.

关键词： Asymptotic stability delay bound state dependent switching switched system time-varying delay

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Natural grasp intention recognition based on gaze fixation in human-robot interaction

arXiv

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arXiv 2020年

作者： Yang, Bo Huang, Jian Li, Xiaolong Chen, Xinxing Xiong, Caihua Hasegawa, Yasuhisa Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China School of Mechanical Science and Engineering The State Key Laboratory of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China Department of Micro-Nano Mechanical Secience and Engineering Nagoya University Furo-cho Chikusa-ku Nagoya464-8603 Japan

Eye movement is closely related to limb actions, so it can be used to infer movement intentions. More importantly, in some cases, eye movement is the only way for paralyzed and impaired patients with severe movement disorders to communicate and interact with the environment. Despite this, eye-tracking technology still has very limited application scenarios as an intention recognition method. The goal of this paper is to achieve a natural fixation-based grasping intention recognition method, with which a user with hand movement disorders can intuitively express what tasks he/she wants to do by directly looking at the object of interest. Toward this goal, we design experiments to study the relationships of fixations in different tasks. We propose some quantitative features from these relationships and analyze them statistically. Then we design a natural method for grasping intention recognition. The experimental results prove that the accuracy of the proposed method for the grasping intention recognition exceeds 89% on the training objects. When this method is extendedly applied to objects not included in the training set, the average accuracy exceeds 85%. The grasping experiment in the actual environment verifies the effectiveness of the proposed method. Copyright © 2020, The Authors. All rights reserved.

关键词： Eye movements

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Edge-Aware Graph Attention Network for Ratio of Edge-User Estimation in Mobile Networks

Edge-Aware Graph Attention Network for Ratio of Edge-User Es...

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International Conference on Pattern Recognition

作者： Jiehui Deng Sheng Wan Xiang Wang Enmei Tu Xiaolin Huang Jie Yang Chen Gong PCA Lab the Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai China Hong Kong Polytechnic University Hong Kong SAR China

Estimating the Ratio of Edge-Users (REU) is an important issue in mobile networks, as it helps the subsequent adjustment of loads in different cells. However, existing approaches usually determine the REU manually, which are experience-dependent and labor-intensive, and thus the estimated REU might be imprecise. Considering the inherited graph structure of mobile networks, in this paper, we utilize a graph-based deep learning method for automatic REU estimation, where the practical cells are deemed as nodes and the load switchings among them constitute edges. Concretely, Graph Attention Network (GAT) is employed as the backbone of our method due to its impressive generalizability in dealing with networked data. Nevertheless, conventional GAT cannot make full use of the information in mobile networks, since it only incorporates node features to infer the pairwise importance and conduct graph convolutions, while the edge features that are actually critical in our problem are disregarded. To accommodate this issue, we propose an Edge-Aware Graph Attention Network (EAGAT), which is able to fuse the node features and edge features for REU estimation. Extensive experimental results on two real-world mobile network datasets demonstrate the superiority of our EAGAT approach to several state-of-the-art methods.

关键词： Deep learning Fuses Estimation Switches Pattern recognition

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C64x-based multi-DSP real-time image processing system

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Jisuanji Gongcheng/Computer Engineering 2006年第11期32卷 268-270页

作者： Hu, Junhong Jiang, Haoyang Fan, Rong Zhang, Tianxu Institute of Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan 430074 China Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan 430074 China

A C64x-based multi-DSP real-time image processing system is introduced, which uses high performance TMS320C6414 DSP to process image and FPGA device to realize LINK port to transport image data with LVDS signal. Requirements of image processing performance and image data communication of image fusion are met. Based on the hardware system, a real time microkernel based distributed operating system is designed and implemented. At the end, its real-time performance is analyzed from three aspects. It's shown that the real time image processing system can reach the requirements of real time image processing.

关键词： FPGA Multi-DSP system Real-time image processing

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An Improved Method for Approximating the Infinite-horizon Value Function of the Discrete-time Switched LQR Problem

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IFAC-PapersOnLine 2023年第2期56卷 4138-4143页

作者： Tan Hou Yuanlong Li Zongli Lin Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia P.O. Box 400743 Charlottesville VA 22904-4743 U.S.A.

This paper considers the problem of approximating the infinite-horizon value function of the discrete-time switched LQR problem. In particular, we propose a new value iteration method to generate a sequence of monotonically decreasing functions that converges exponentially to the value function. This method facilitates us to use coarse approximations resulting from faster but less accurate algorithms for further value iteration, and thus, our method is capable of achieving a better approximation for a given computation time compared with the existing methods. Two numerical examples are presented in this paper to illustrate the effectiveness of our method.

关键词： Switched linear systems optimal control switched LQR problem

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Syndrome Classification Based on Multi-Graph Attention Network

Syndrome Classification Based on Multi-Graph Attention Netwo...

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IEEE International Symposium on information (IT) in Medicine and Education, ITME

作者： Jishun Ma Weikai Lu Changen Zhou Shenghua Teng Zuoyong Li College of Electronic and Information Engineering Shandong University of Science and Technology Qingdao China School of Electronic Electrical Engineering and Physics Fujian University of Technology Fuzhou China Research Base of Traditional Chinese Medicine Syndrome Fujian University of Traditional Chinese Medicine Fuzhou China Fujian Provincial Key Laboratory of Information Processing and Intelligent Control College of Computer and Control Engineering Minjiang University Fuzhou China

Syndrome classification is an important step in Traditional Chinese Medicine (TCM) for diagnosis and treatment. In this paper, we propose a multi-graph attention network (MGAT) based method to simulate TCM doctors to infer the syndromes. Specifically, the complex relationships between symptoms and state elements are aggregated using graph attention networks (GAT) and syndromes are classified by a multilayer perceptron (MLP). To verify the effectiveness of the model, extensive experiments are conducted on the Treatise on Febrile Diseases dataset. The experimental results show that the proposed method outperforms several typical methods in terms of accuracy, precision, recall, and F1-score. The MGAT model has high accuracy in syndrome classification and has practical application value.

关键词： Computational modeling Education Medical services Multilayer perceptrons Feature extraction Computer aided diagnosis information technology

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Prediction of exosomal piRNAs based on deep learning for sequence embedding with attention mechanism

Prediction of exosomal piRNAs based on deep learning for seq...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Yajun Liu Yulian Ding Aimin Li Rong Fei Xie Guo Fangxiang Wu Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an University of Technology Xi'an China Division of Biomedical Engineering University of Saskatchewan Saskatoon Canada Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China Department of Computer Science Department of Mechanical Engineering Division of Biomedical Engineering University of Saskatchewan Saskatoon Canada

ISBN: (数字)9781665468190

ISBN: (纸本)9781665468206

PIWI-interacting RNAs (piRNAs) are a type of small non-coding RNAs which bind with the PIWI proteins to exert biological effects in various regulatory mechanisms. A growing amount of evidence reveals that exosomal piRNAs are potential biomarkers for diagnosis and treatment of complex diseases. Effective methods for the prediction of exosomal piRNAs are the foundation of piRNA functional research. In this study, we propose an end-to-end deep network for identifying exosomal piRNAs based on features learned from natural language processing (NLP) models for sequence embedding with attention mechanism. First, a benchmark dataset is constructed by processing piRNA subcellular localization annotated data and sequence data. Moreover, bagging positive unlabeled learning is applied to get the reliable negative set. Finally, we treat a piRNA sequence as a sentence and its k-mer subsequence as a token. Sequence embedding models with self-attention mechanism is designed to extract features from exosome piRNA sequences, which are used for the prediction task. Compared with three competing methods, our model achieves the best performance and reveals the key factors of exosomal piRNA sequences by the attention mechanism. Our model characterizes exosomal piRNAs and could be beneficial for researchers to investigate exosomal piRNAs’ functions.

关键词： Proteins Location awareness RNA Biological system modeling Predictive models Feature extraction Natural language processing

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Heterogeneous influence of individuals’ behavior on mask efficacy in gathering environments

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Frontiers of Engineering Management 2022年第4期9卷 550-562页

作者： Haochen SUN Xiaofan LIU Zhanwei DU Ye WU Haifeng ZHANG Xiaoke XU College of Information and Communication Engineering Dalian Minzu UniversityDalian 116600China Web Mining Laboratory Department of Media and CommunicationCity University of Hong KongHong KongChina WHO Collaborating Centre for Infectious Disease Epidemiology and Control School of Public HealthLi Ka Shing Faculty of MedicineThe University of Hong KongHong KongChina Laboratory of Data Discovery for Health Hong Kong Science and Technology ParkHong KongChina Computational Communication Research Center Beijing Normal University(Zhuhai)Zhuhai 519087China School of Journalism and Communication Beijing Normal UniversityBeijing 100875China Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Mathematical ScienceAnhui UniversityHefei 230601China

Wearing masks is an easy way to operate and popular measure for preventing *** masks can slow down the spread of viruses,their efficacy in gathering environments involving heterogeneous person-to-person contacts remains ***,we aim to investigate the epidemic prevention effect of masks in different real-life gathering *** study uses four real interpersonal contact datasets to construct four empirical networks to represent four gathering *** transmission of COVID-19 is simulated using the Monte Carlo simulation *** heterogeneity of individuals can cause mask efficacy in a specific gathering environment to be different from the baseline efficacy in general ***,the heterogeneity of gathering environments causes the epidemic prevention effect of masks to *** masks can greatly reduce the probability of clustered epidemics and the infection scale in primary schools,high schools,and ***,the use of masks alone in primary schools and hospitals cannot control *** high schools with social distancing between classes and in workplaces where the interpersonal contact is relatively sparse,masks can meet the need for *** the heterogeneity of individual behavior,if individuals who are more active in terms of interpersonal contact are prioritized for mask-wearing,the epidemic prevention effect of masks can be ***,asymptomatic infection has varying effects on the prevention effect of masks in different *** effect can be weakened or eliminated by increasing the usage rate of masks in high schools and ***,the effect on primary schools and hospitals cannot be *** study contributes to the accurate evaluation of mask efficacy in various gathering environments to provide scientific guidance for epidemic prevention.

关键词： COVID-19 masks behavioral heterogeneity asymptomatic infection

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3D Gaussian Splatting in Robotics: A Survey

arXiv

引用

arXiv 2024年

作者： Zhu, Siting Wang, Guangming Kong, Xin Kong, Dezhi Wang, Hesheng Department of Automation Shanghai Jiao Tong University Shanghai China University of Cambridge United Kingdom Imperial College London United Kingdom Shanghai Jiao Tong University Shanghai China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong University China

Dense 3D representations of the environment have been a long-term goal in the robotics field. While previous Neural Radiance Fields (NeRF) representation have been prevalent for its implicit, coordinate-based model, the recent emergence of 3D Gaussian Splatting (3DGS) has demonstrated remarkable potential in its explicit radiance field representation. By leveraging 3D Gaussian primitives for explicit scene representation and enabling differentiable rendering, 3DGS has shown significant advantages over other radiance fields in real-time rendering and photo-realistic performance, which is beneficial for robotic applications. In this survey, we provide a comprehensive understanding of 3DGS in the field of robotics. We divide our discussion of the related works into two main categories: the application of 3DGS and the advancements in 3DGS techniques. In the application section, we explore how 3DGS has been utilized in various robotics tasks from scene understanding and interaction perspectives. The advance of 3DGS section focuses on the improvements of 3DGS own properties in its adaptability and efficiency, aiming to enhance its performance in robotics. We then summarize the most commonly used datasets and evaluation metrics in robotics. Finally, we identify the challenges and limitations of current 3DGS methods and discuss the future development of 3DGS in robotics. The paper lists of our survey are available at 3D Gaussian Splatting in Robotics. Copyright © 2024, The Authors. All rights reserved.

关键词： Rendering (computer graphics)

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A registration-aided domain adaptation network for 3D Point cloud based place recognition

arXiv

引用

arXiv 2020年

作者： Qiao, Zhijian Hu, Hanjiang Shi, Weiang Chen, Siyuan Liu, Zhe Wang, Hesheng Department of Automation Insititue of Medical Robotics Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology China Department of Mechanical Engineering Carnegie Mellon University United States Department of Computer Science and Technology University of Cambridge United Kingdom

In the field of large-scale SLAM for autonomous driving and mobile robotics, 3D point cloud based place recognition has aroused significant research interest due to its robustness to changing environments with drastic daytime and weather variance. However, it is time-consuming and effort-costly to obtain high-quality point cloud data for place recognition model training and ground truth for registration in the real world. To this end, a novel registration-aided 3D domain adaptation network for point cloud based place recognition is proposed. A structure-aware registration network is introduced to help to learn features with geometric information and a 6-DoFs pose between two point clouds with partial overlap can be estimated. The model is trained through a synthetic virtual LiDAR dataset through GTA-V with diverse weather and daytime conditions and domain adaptation is implemented to the real-world domain by aligning the global features. Our results outperform state-of-the-art 3D place recognition baselines or achieve comparable on the real-world Oxford RobotCar dataset with the visualization of registration on the virtual dataset. Copyright © 2020, The Authors. All rights reserved.

关键词： Three dimensional computer graphics

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