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An Improved Adaptive Exponential Smoothing Model for Short-term Travel Time Forecasting of Urban Arterial Street

Acta Automatica Sinica 2008年第11期34卷 1404-1409页

作者： Zhi-Peng LI Hong YU Yun-Cai LIU Fu-Qiang LIU Key Laboratory of Embedded System and Service Computing Ministry of Education Tongji University Shanghai 200092 P. R. China Intelligent Transportation System Department Shanghai Electrical Apparatus Research Institute Shanghai 200063 P. R. China Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai 200240 P. R. China

Short-term forecasting of travel time is essential for the success of intelligent transportation system. In this paper, we review the state-of-art of short-term traffic forecasting models and outline their basic ideas, related works, advantages and disadvantages of each model. An improved adaptive exponential smoothing (IAES) model is also proposed to overcome the drawbacks of the previous adaptive exponential smoothing model. Then, comparing experiments are carried out under normal traffic condition and abnormal traffic condition to evaluate the performance of four main branches of forecasting models on direct travel time data obtained by license plate matching (LPM). The results of experiments show each model seems to have its own strength and weakness. The forecasting performance of IASE is superior to other models in shorter forecasting horizon (one and two step forecasting) and the IASE is capable of dealing with all kind of traffic conditions.

关键词： Travel time short-term forecasting license plate matching (LPM) exponential smoothing

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Design of interval type-2 fuzzy logic controller for mobile wheeled inverted pendulum

Design of interval type-2 fuzzy logic controller for mobile ...

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World Congress on intelligent control and Automation (WCICA)

作者： MyongHyok Ri Jian Huang Songhyok Ri HyonSu Yun ChangSik Kim Department of Control Science KimChaek University of Technology Pyongyang Wuhan Democratic People's Republic of Korea Key Laboratory of Ministry of Education for Image Processing and Intelligent Control Huazhong University of Science and Technology Wuhan CHINA Department of Computer Science Hamhung University of Chemical Industry Hamhung Wuhan Democratic People's Republic of Korea Department of Computer Science KimChaek University of Technology Pyongyang Democratic People's Republic of Korea

ISBN: (纸本)9781467384155

In this paper, a novel interval type-2 fuzzy logic controller (IT2FLC) is proposed for controlling a mobile wheeled inverted pendulum(MWIP) with model uncertainties and external disturbances. The MWIP is a typical underactuated system which is generally composed of two subsystems, an invert pendulum and a mobile robot system. The IT2FLC proposed in this paper is composed of a balancing controller, a velocity controller and a yaw steering controller. The proposed integrated IT2FLC is linear combination of the three individual IT2FLCs which uses simplified type reduce method. The proposed controller has simple structure and requires less computation, also it is expected to have robustness to uncertainties and external disturbances in the practical implementation. Considering the model uncertainties and external disturbances, simulation results proved the effectiveness and robustness of the proposed IT2FLC compared with type-1 fuzzy logic controller (T1FLC).

关键词： Fuzzy logic Wheels Uncertainty Robustness Mobile communication control systems Automation

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Robust quantum teleportation via a non-Markovian channel

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Physical Review A 2023年第6期108卷 062406-062406页

作者： Yanfang Wang Shibei Xue Hongbin Song Min Jiang Department of Automation Shanghai Jiao Tong University Shanghai 200240 People's Republic of China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 People's Republic of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240 People's Republic of China General Education Division and Shenzhen Key Laboratory of Semiconductor Lasers The Chinese University of Hong Kong Shenzhen Guang Dong 518116 People's Republic of China School of Electronics and Information Engineering Soochow University Suzhou 215006 People's Republic of China

In this paper we propose a non-Markovian quantum channel approach to mitigating the degradation of the average fidelity in continuous-variable quantum teleportation. The non-Markovian quantum channel is modeled by an augmented system where ancillary systems are introduced to represent the internal modes of non-Markovian environments. With a proper non-Markovianity, enhanced effects of the channels on continuous-variable quantum teleportation are observed. Also, the logarithmic negativity of entangled states can be effectively maintained so that the decay of the average fidelity of quantum teleportation is mitigated. In addition, the analysis on different teleported quantum states shows that coherent states exhibit stronger robustness than those of squeezed states and cat states in quantum teleportation with a non-Markovian channel.

关键词： Quantum control Quantum engineering Quantum teleportation

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Understanding the Robustness of 3D Object Detection with Bird'View Representations in Autonomous Driving

Understanding the Robustness of 3D Object Detection with Bir...

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Zijian Zhu Yichi Zhang Hai Chen Yinpeng Dong Shu Zhao Wenbo Ding Jiachen Zhong Shibao Zheng Institute of Image Communication and Network Engineering Shanghai Jiao Tong University Dept. of Comp. Sci. and Tech. THBI Lab Institute for AI Tsinghua University BNRist Center Zhongguancun Laboratory Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Information Materials and Intelligent Sensing Laboratory of Anhui Province School of Computer Science and Technology Anhui University SAIC Motor AI Lab

3D object detection is an essential perception task in autonomous driving to understand the environments. The Bird's-Eye-View (BEV) representations have significantly improved the performance of 3D detectors with camera inputs on popular benchmarks. However, there still lacks a systematic understanding of the robustness of these vision-dependent BEV models, which is closely related to the safety of autonomous driving systems. In this paper, we evaluate the natural and adversarial robustness of various representative models under extensive settings, to fully understand their behaviors influenced by explicit BEV features compared with those without BEV. In addition to the classic settings, we propose a 3D consistent patch attack by applying adversarial patches in the 3D space to guarantee the spatiotemporal consistency, which is more realistic for the scenario of autonomous driving. With substantial experiments, we draw several findings: 1) BEV models tend to be more stable than previous methods under different natural conditions and common corruptions due to the expressive spatial representations; 2) BEV models are more vulnerable to adversarial noises, mainly caused by the redundant BEV features; 3) Camera-LiDARfusion models have superior performance under different settings with multi-modal inputs, but BEV fusion model is still vulnerable to adversarial noises of both point cloud and image. These findings alert the safety issue in the applications of BEV detectors and could facilitate the development of more robust models.

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Robotic Electrospinning Actuated by Non-Circular Joint Continuum Manipulator for Endoluminal Therapy

Robotic Electrospinning Actuated by Non-Circular Joint Conti...

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2021 IEEE International Conference on Robotics and Automation, ICRA 2021

作者： Wu, Zicong Lou, Chuqian Jin, Zhu Huang, Shaoping Liu, Ning Zou, Yun Kovac, Mirko Gao, Anzhu Yang, Guang-Zhong The Institute of Medical Robotics Department of Bioengineering Shanghai Jiao Tong University Shanghai200240 China Imperial College London Empa-Swiss Federal Laboratories for Materials Science and Technology United Kingdom Limited 999077 Hong Kong Aerial Robotics Laboratory Imperial College London LondonSW7 2AZ United Kingdom The Institute of Medical Robotics Department of Automation Shanghai Jiao Tong University The Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China The Institute of Medical Robotics Shanghai Jiao Tong University Shanghai200240 China

ISBN: (纸本)9781728190778

Electrospinning has exhibited excellent benefits to treat the trauma for tissue engineering due to its produced micro/nano fibrous structure. It can effectively adhere to the tissue surface for long-term continuous therapy. This paper develops a robotic electrospinning platform for endoluminal therapy. The platform consists of a continuum manipulator, the electrospinning device, and the actuation unit. The continuum manipulator has two bending sections to facilitate the steering of the tip needle for a controllable spinning direction. Non-circular joint profile is carefully designed to enable a constant length of the centreline of a continuum manipulator for stable fluid transmission inside it. Experiments are performed on a bronchus phantom, and the steering ability and bending limitation in each direction are also investigated. The endoluminal electrospinning is also fulfilled by a trajectory following and points targeting experiments. The effective adhesive area of the produced fibre is also illustrated. The proposed robotic electrospinning shows its feasibility to precisely spread more therapeutic drug to construct fibrous structure for potential endoluminal treatments. © 2021 IEEE

关键词： Electrospinning

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A Real-time Framework of Multi-Camera Vehicle Tracking System

A Real-time Framework of Multi-Camera Vehicle Tracking Syste...

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2024 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2024

作者： Zhuang, Hanyang Chen, Xingyuan Lan, Jianglin Wang, Ying Lu, Zhaoxuan Wang, Chunxiang Yang, Ming University of Michigan Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai200240 China University of Glasgow James Watt School of Engineering GlasgowG12 8QQ United Kingdom Shanghai Jiao Tong University School of Mechanical Engineering Shanghai200040 China Shanghai Intelligent and Connected Vehicle R and D Center Co. LTD Shanghai201400 China Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9798350372601

Multi-camera vehicle tracking (MCVT) system is a key technology to build an intelligent city and intelligent transportation system. The MCVT system utilizes roadside monitoring devices and computing platforms to achieve city-level road traffic perception at a finer scale by tracking each vehicle on the road to obtain the trajectory. The existing MCVT system mainly focuses on dealing with the algorithm modules separately, without studying the real-time performance and system architecture of the entire pipeline. However, in real-world applications, many of the tricks in improving evaluation metrics are not applicable since there is endless traffic flow running all the time. Therefore, this paper proposes a real-time framework of the MCVT system to streamline all the algorithm modules with proper data flow. Firstly, a multi-threaded multi-vehicle tracking (MVT) module is developed to detect vehicles in each camera. Re-identification is implemented during MVT to provide the feature for tracking in the same camera and across different cameras. Then, after the vehicle leaves the camera field of view, the feature of vehicle trajectory is calculated by averaging the feature at each frame. Meanwhile, a background thread runs continuously to match the incoming feature of vehicle trajectory with past features by conducting a topology searching method. In the end, the vehicle trajectories with well-matched features are considered to be the same vehicle. The entire pipeline has been validated on two different datasets, the precision is 0.64 in the CityFlow dataset which uses 6 cameras simultaneously. In the customized dataset, the same method can still reach real-time when using 16 cameras at the same time with smaller network modules. © 2024 IEEE.

关键词： Vehicle locating systems

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Dynamic Ca2+ sensitivity of BK channels

Dynamic Ca2+ sensitivity of BK channels

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The 10th Chinese Symposium on Calcium Signaling(第十届全国钙信号和细胞功能研讨会)

作者： Pan-Pan Hou Feng Xiao Hao-Wen Liu Ming Yuchi Guo-Hui Zhang Ying Wu Wei Wang Wen-Ping Zeng Ming-Yue Ding Zheng-Xing Wu Jian-Ming Cui Jiu-Ping Ding Key Laboratory of Image Processing and Intelligent Control Huazhong University of Science and Technology Ministry of Education Department of Biomedical Engineering College of Life Science and Technology Wuhan Hubei China Department of pharmacology Soochow University college of pharmaceutical Sciences Suzhou 215123China Key Laboratory of Molecular Biophysics Huazhong University of Science and Technology Ministry of Education College of Life Science and Technology Wuhan Hubei China Department of Biomedical Engineering Center for the Investigation of Membrane Excitability DisordersCardiac Bioelectricity and Arrhythmia Center Washington University St Louis MO 63130 USA

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Extended State Observer Based Fault-Tolerant Predictive control for a Four-Mecanum Wheels Mobile Robot

Extended State Observer Based Fault-Tolerant Predictive Cont...

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IEEE International Conference on Cyber Technology in Automation, control, and intelligent Systems

作者： Binghao Yang Dongliang Wang Ziling Wen Wu Wei Wenji Li Zhun Fan Key Lab of Digital Signal and Image Processing of Guangdong Province Shantou University Guangdong China School of Department of Electronic and Information Engineering Shantou University Guangdong China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Guangzhou Guangdong China School of Automation Science and Engineering South China University of Technology Guangzhou Guangdong China

ISBN: (数字)9798331506056

ISBN: (纸本)9798331506063

The application of unmanned vehicles in industrial cargo transportation is becoming increasingly widespread, particularly playing a significant role in transporting heavy-duty goods. However, when performing such tasks, whether in single-vehicle transportation or multi-vehicle collaborative transportation, the occurrence of wheel failures can potentially lead to serious safety accidents. Therefore, this paper proposes a fault-tolerant control scheme, establishing a kinematic model considering disturbances and failures, and adopts model predictive control for trajectory tracking. Additionally, an extended state observer is introduced to observe system states and counteract disturbances. To address potential failure issues, a controller reconstruction strategy is proposed. Finally, the effectiveness and superiority of the controller is validated through numerical simulation and comparative experiment.

关键词： Fault tolerance Trajectory tracking Fault tolerant systems Wheels Transportation Kinematics Predictive models Safety State estimation Predictive control

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Multisensor image adaptive fusion based on nonsubsampled contourlet

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Jisuanji Xuebao/Chinese Journal of Computers 2009年第11期32卷 2227-2238页

作者： Chang, Xia Jiao, Li-Cheng Jia, Jian-Hua Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China School of Information Engineering Jingdezhen Ceramic Institute Jingdezhen Jiangxi 333002 China

An adaptive fusion method of multisensor images based on nonsubsampled contourlet transform is proposed in this paper, which can select the fusion weights of the low-frequency coefficients adaptively via golden section algorithm. The nonsubsampled contourlet transform is a flexible multi-scale, multi-direction and shift-invariant image decomposition, which is suitable for representing images bearing abundant detail and directional information. This is employed for fusing the directional high-frequency coefficients. For the directional high-frequency coefficients, the higher adding level of the directional subbands is used to select the better coefficient for fusion. The nonsubsampled contourlet transform can also avoids introducing ringing artifacts to fused images compared to ordinary method. Experimental results show that the proposed method achieves better fusion efficiency compared to image fusion methods based on Laplacian pyramid transform, wavelet transform, stationary wavelet transform and contourlet transform respectively.

关键词： Contourlet transform

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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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