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Inside Cover: A novel in vivo Cerenkov luminescence image-guided surgery on primary and metastatic colorectal cancer (J. Biophotonics 3/2020)

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Journal of Biophotonics 2020年第3期13卷

作者： Zeyu Zhang Yawei Qu Yu Cao Xiaojing Shi Hongbo Guo Xiaojun Zhang Sheng Zheng Haifeng Liu Zhenhua Hu Jie Tian Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education School of Life Science and Technology Xidian University Xi'an China CAS Key Laboratory of Molecular Imaging Beijing Key Laboratory of Molecular Imaging The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Department of Gastroenterology the Third Medical Centre Chinese PLA General Hospital Beijing China Department of Control Science and Engineering Harbin Institute of Technology Harbin China Department of Anorectal the Third medical Centre Chinese PLA General Hospital Beijing China University of Chinese Academy of Sciences Beijing China School of Information Sciences and Technology Northwest University Xi'an China Department of Nuclear Medicine Chinese PLA General Hospital Beijing China Beijing Advanced Innovation Center for Big Data-Based Precision Medicine School of Medicine Beihang University Beijing China

This study presents a novel intraoperative in vivo imaging approach which harnessed Cerenkov luminescence (CL) to detect primary and metastatic colorectal cancer (CRC) using clinically approved radiopharmaceuticals. In the mice and swine experiments, the proposed approach effectively improved the effect of CRC surgery. The approach is believed to be promising for utilizing CL in open surgery. Further details can be found in the article by Zeyu Zhang, Yawei Qu, Yu Cao et al. ( e201960152 )

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Traffic Flow Data Forecasting Based on Interval Type-2 Fuzzy Sets Theory

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IEEE/CAA Journal of Automatica Sinica 2016年第2期3卷 141-148页

作者： Runmei Li Chaoyang Jiang Fenghua Zhu Xiaolong Chen Beijing Jiaotong University the State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences

This paper proposes a long-term forecasting scheme and implementation method based on the interval type-2 fuzzy sets theory for traffic flow data. The type-2 fuzzy sets have advantages in modeling uncertainties because their membership functions are fuzzy. The scheme includes traffic flow data preprocessing module, type-2 fuzzification operation module and long-term traffic flow data forecasting output module, in which the Interval Approach acts as the core algorithm. The central limit theorem is adopted to convert point data of mass traffic flow in some time range into interval data of the same time range (also called confidence interval data) which is being used as the input of interval approach. The confidence interval data retain the uncertainty and randomness of traffic flow, meanwhile reduce the influence of noise from the detection data. The proposed scheme gets not only the traffic flow forecasting result but also can show the possible range of traffic flow variation with high precision using upper and lower limit forecasting result. The effectiveness of the proposed scheme is verified using the actual sample application. © 2014 Chinese Association of Automation.

关键词： Data handling Forecasting Fuzzy sets Membership functions Uncertainty analysis

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Motion characterization of a relaxor-based single crystals actuator for Na-nomanipulation system

Motion characterization of a relaxor-based single crystals a...

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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Tianlu Zhang Zhangming Du Chao Zhou Lu Deng Zhiqiang Cao Shuo Wang Min Tan State Key Laboratory of Management and Control for Complex Systems University of Chinese Academy of Sciences Beijing China State Key Laboratory of Management and Control for Complex Systems Chinese Academy of Sciences Beijing China School of Statistics and Mathematics Central University of Finance and Economics Beijing China

ISBN: (纸本)9781538629024

The micro-operation technology is developing rapidly since the miniaturization of the research object and the precision of the operation. As the actuator of micro-operation, the piezoelectric material with the inverse piezoelectric effect has been widely used in this field. A new type of actuator based on piezoelectric single crystals is characterized in this paper, and a set of test system is designed to obtain the displacement of the actuator under different voltage waveforms. The relationship between the induced voltage and output displacement is analyzed. It is found that the dynamic voltage and the output displacement show a good linear relationship, and the hysteresis of the motion is smaller than the traditional piezoelectric ceramics. This good performance of the piezoelectric single crystal actuator is expected to directly use open-loop control, greatly improve the actuator control frequency and accuracy, which can reduce the complexity of the application system.

关键词： Crystals Actuators Ceramics Hysteresis Sensors Electric fields Drives

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End-to-End Driving Activities and Secondary Tasks Recognition Using Deep Convolutional Neural Network and Transfer Learning

End-to-End Driving Activities and Secondary Tasks Recognitio...

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2018 IEEE Intelligent Vehicles Symposium, IV 2018

作者： Xing, Yang Tang, Jianlin Liu, Hong Lv, Chen Cao, Dongpu Velenis, Efstathios Wang, Fei-Yue Advanced Vehicle Engineering Centre Cranfield University BedfordMK43 0AL United Kingdom Vehicle Intelligence Pioneers Ltd Qingdao China Jiangsu XCMG Construction Machinery Research Institute Ltd. No. 26 Tuolanshan Road Economic Development Zone Xuzhou Jiangsu221004 China School of Mechanical and Mechatronics Engineering University of Waterloo 200 University Avenue West WaterlooONN2L 3G1 Canada State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

ISBN: (纸本)9781538644522

Drivers' decision and their corresponding behaviors are important aspects that can affect the driving safety, and it is necessary to understand the driver behaviors in real-time. In this study, an end-to-end driving-related tasks recognition system is proposed. Specifically, seven common driving activities are identified, which are normal driving, right mirror checking, rear mirror checking, left mirror checking, using in-vehicle video device, texting, and answering mobile phone. Among these, the first four activities are regarded as normal driving tasks, while the rest three are divided into distraction group. The images are collected using a consumer range camera, namely, Kinect. In total, five drivers are involved in the naturalistic data collection. Before training the identification model, the raw images are first segmented using a Gaussian mixture model (GMM) to extract the driver region from the background. Then, a pre-trained deep convolutional neural network (CNN) model is trained to classify the behaviors, which directly takes the processed RGB images as the input and outputs the identified label. In this work, the AIexNet is selected as the pre-trained CNN model. Then, to reduce the training cost, the transfer learning mechanism is applied to the CNN model. An average of 79\% detection accuracy is achieved for the seven driving tasks. The proposed integration model can be used as a low-cost driver distraction and dangerous tasks recognition modeL. © 2018 IEEE.

关键词： Neural network models

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Dual refinement networks for accurate and fast object detection in real-world scenes

arXiv

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arXiv 2018年

作者： Chen, Xingyu Yu, Junzhi Kong, Shihan Wu, Zhengxing Wen, Li State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 University of Chinese Academy of Sciences Beijing100049 China Beijing Innovation Center for Engineering Science and Advanced Technology Peking University Beijing100871 China School of Mechanical Engineering and Automation Beihang University Beijing100191 China

Object detection has been vigorously studied for years but fast accurate detection for real-world scenes remains a very challenging problem. Overcoming drawbacks of singlestage detectors, we take aim at precisely detecting objects for static and temporal scenes in real time. Firstly, as a dual refinement mechanism, a novel anchor-offset detection including an anchor refinement, a feature offset refinement, and a deformable detection head is designed for two-step regression and capture of accurate detection features. Based on the anchoroffset detection, a dual refinement network (DRN) is developed for high-performance static detection, where a multi-deformable head is further designed to leverage contextual information for describing objects. As for temporal detection in real-world scenes, temporal refinement networks (TRN) and temporal dual refinement networks (TDRN) are developed by propagating the refinement information across time, where we also propose a loose refinement strategy to match object motion with the previous refinement. Our proposed methods are evaluated on PASCAL VOC, COCO, and ImageNet VID datasets. Extensive comparison on static and temporal detection verify the superiority of DRN, TRN, and TDRN. Consequently, our developed approaches run in a fairly fast speed, and in the meantime achieve a significantly enhanced detection accuracy, i.e., a mAP of 82.8% on VOC 2007, 80.6% on VOC 2012, 69.4% on VID 2017, and an AP of 34.3% on COCO. Ultimately, producing encouraging results, our methods are applied to underwater object grasping with an autonomous system. Codes are publicly available at http://***/SeanChenxy/TDRN. Copyright © 2018, The Authors. All rights reserved.

关键词： Computer vision

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Kalman and Smooth Variable Structure Filters for Pose Estimation in Robotic Visual Servoing

Kalman and Smooth Variable Structure Filters for Pose Estima...

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2017 3rd International Conference on Artificial Intelligence and Industrial Engineering (AIIE2017)

作者： Xi-yuan LU Liang DU Xiao-lin REN Bo DONG Yuan-chun LI Department of Control Science and Engineering Changchun University of Technology State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

Pose estimation problem of an object in real time is an important issue for robotic visual servoing(RVS). Many pose estimation schemes in RVS rely on an extended Kalman filter(EKF) that provides good accurate estimation. However, it may cause the estimation to become unstable because of nonlinear modeling uncertainties. While, smooth variable structure filter(SVSF) is a new method that is more robust to disturbances and uncertainties. In this paper, a novel pose estimate method is developed based on the EKF and SVSF. It is combined the accuracy of the EKF and the robustness provided by the SVSF that will lead to more accurate state estimates and improve robustness to modeling errors and uncertainties. The resulting algorithms are called the EKF-SVSF. The simulation results are provided to demonstrate the robustness and accuracy.

关键词： Pose estimation Robotic visual servoing(RVS) Kalman filter(KF) Smooth variable structure filter

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A new framework of science and technology innovation education for k-12 in Qingdao, China

A new framework of science and technology innovation educati...

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2017 ASEE International Forum

作者： Liu, Xiwei Gong, Xiaoyan Wang, Fei-Yue Sun, Rui Gao, Yanqing Zhang, Yu Zhou, Jiehan Deng, Xiaofei State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences China Intelligent Education Institution Qingdao Academy of Intelligent Industries China Qingdao Experimental High School China Oregon Institute of Technology United States University of Oulu Finland

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Hydrodynamic Analysis of a Gliding Robotic Dolphin Based on Computational Fluid Dynamics 35

Hydrodynamic Analysis of a Gliding Robotic Dolphin Based on ...

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第35届中国控制会议

作者： LI Kang YU Junzhi WU Zhengxing TAN Min State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

ISBN: (纸本)9781509009107

This paper presents a concrete and practical hydrodynamic analysis for a hybrid gliding robotic *** order to obtain the accurate hydrodynamic performance of both dolphin-like swimming and gliding motion,a Computational Fluid Dynamics(CFD) method is ***,based on the F1 UENT dynamic mesh interface,a novel dynamic mesh and user-defined function(UDF) are developed to describe the dorsoventral oscillations of the ***,the corresponding turbulent model and SIMPLE algorithm suited to dolphin-like swimming are also meticulously selected for great accuracy and high ***,the FLUENT simulation results reveal the pressure distribution and velocity field distribution around the robotic ***,some important hydrodynamic coefficients including lift coefficients and drag coefficients at different frequencies are also *** simulation results illustrate an expected hydrodynamic performance of the gliding robotic dolphin.

关键词： Gliding Robotic Dolphin Computational Fluid Dynamics(CFD) Dynamic Mesh Hydrodynamic Analysis

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Design of a Camera Stabilizer System for Robotic Fish Based on Feedback-Feedforward control 35

Design of a Camera Stabilizer System for Robotic Fish Based ...

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第35届中国控制会议

作者： YANG Xiang Wu Zhengxing Liu Jincun YU Junzhi State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

ISBN: (纸本)9781509009107

This paper presents a novel approach for a visual system of robotic fish to reduce the instability of camera image caused by the inherent periodic yawing of the fish *** order to acquire the stable image from the camera located inside of the fish head,a camera stabilizer for the visual system is ***,an Inertial Measurement Unit(IMU) with nine degrees-of-freedom(DoFs) is employed to maintain the attitude of the camera stable with respect to the inertial *** accurately describe the stabilizer system characteristics,a simple and effective system model is ***,a feedbackfeedforward controller is proposed to mitigate the periodic swing effect and obtain stable and clear camera image when the robotic fish is ***,the simulation and experiments both verified the effectiveness of the mechanism design for camera stabilizer and the corresponding feedback-feedforward control approach for enhancing the stability of images.

关键词： Robotic fish camera stabilizer feedback-feedforward controller underwater vision underwater robot

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Way-point Tracking control for a Biomimetic Underwater Vehicle Based on Backstepping 35

Way-point Tracking Control for a Biomimetic Underwater Vehic...

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第35届中国控制会议

作者： WANG Rui WANG Shuo WANG Yu WEI Qingping State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

ISBN: (纸本)9781509009107

In this paper,a new approach of way-point tracking control is investigated for a biomimetic underwater vehicle(BUV)propelled by undulatory ***,the system design and the model of the BUV are *** with traditional autonomous underwater vehicles(AUVs) propelled by screw propellers,the concept design enhances the maneuverability and stability of AUVs at low *** the way-point tracking problem of the BUV is ***,a way-point tracking control scheme combining a guidance system of low complexity with backstepping technique is proposed to achieve fast and effective convergence to the desired path composed of a series of given way-points for this *** the end,simulations demonstrate the performance of the proposed way-point tracking controller.

关键词： Biomimetic underwater vehicle Undulatory fin Way-point tracking control Backstepping Guidance system

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