检索结果-内蒙古大学图书馆

IEEE International Conference on Industrial Technology (ICIT)

作者： Chengao Bao Luefeng Chen Min Li Min Wu Witold Pedrycz Kaoru Hirota School of Automation China University of Geosciences Wuhan China the Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems School of Automation and the Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Wuhan China Department of Electrical and Computer Engineering University of Alberta Edmonton Canada Tokyo Institute of Technology Yokohama Japan Tokyo Institute of Technology Tokyo Japan

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

A multi-modal emotion recognition method based on facial multi-scale features and cross-modal attention (MS-FCA) network is proposed. The MSFCA model improves the traditional single-branch ViT network into a two-branch ViT architecture by using classification tokens in each branch to interact with picture embeddings in the other branch, which facilitates effective interactions between different scales of information. Subsequently, audio features are extracted using ResNet18 network. The cross-modal attention mechanism is used to obtain the weight matrices between different modal features, making full use of inter-modal correlation and effectively fusing visual and audio features for more accurate emotion recognition. Two datasets are used for the experiments: eNTERFACE'05 and REDVESS dataset. The experimental results show that the accuracy of the proposed method on the eNTERFACE'05 and REDVESS datasets is 85.42% and 83.84% respectively, which proves the effectiveness of the proposed method.

关键词： Emotion recognition Visualization Accuracy Service robots Semantics Human-robot interaction Speech recognition Feature extraction Data mining Facial features

来源：评论

学校读者我要写书评

暂无评论

Distributed Active Disturbance Rejection Control of Multiple Mobile Robots for Online Workload Partition

Distributed Active Disturbance Rejection Control of Multiple...

引用

Chinese Automation Congress (CAC)

作者： Xin Li Chao Zhai Hehong Zhang Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education China University of Geosciences Wuhan Campus School of Automation Wuhan China School of Computer and Data Science Fuzhou University Fuzhou China

Considering the actual multi-agent coverage process, the motion trajectories are seriously affected by disturbances and noise. In this paper, a cooperative control method based on active disturbance rejection controller (ADRC) for multiple mecanum-wheeled robots (MWMR) is proposed to improve its robustness. In particular, to suppress the total disturbances during the running of each robot and reduce large computation and observation cost of high order ADRC, a reduced-order cascaded ADRC (RC-ADRC) is proposed. Moreover, distributed controller is proposed to track the expected trajectories of multiple mecanum-wheeled robots under disturbances. Compared with the proposed RC-ADRC based cooperative control scheme and PID based cooperative control one, the favorable motion trajectory tracking performance is obtained. Simulation results verify the superiority of the method.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Structural and functional analysis of a potent human neutralizing antibody against enterovirus A71

引用

Science China(Life Sciences) 2022年第12期65卷 2517-2526页

作者： Zhe Chen Linlin Bao Bin Zhu Hua Fu Shuangli Zhu Tianjiao Ji Ying Xue Chuan Liu Xurong Wang Fengdi Li Qi Lv Feifei Qi Pin Yu Wei Deng Wenbo Xu Chuan Qin Hongrong Liu Qi Jin MOH Key Laboratory of Systems Biology of Pathogens Institute of Pathogen BiologyChinese Academy of Medical Sciences&Peking Union Medical CollegeBeijing 100730China Beijing Key Laboratory for Animal Models of Emerging and Remerging Infectious Diseases NHC Key Laboratory of Human Disease Comparative MedicineInstitute of Laboratory Animal ScienceChinese Academy of Medical Sciences and Comparative Medicine CenterPeking Union Medical CollegeBeijing 100021China School of Computer Science and Engineering Hunan University of Science and TechnologyXiangtan 411201China National Institute for Viral Disease Control and Prevention China CDCBeijing 102206China Ministry of Education Key Laboratory of Protein Sciences Beijing Advanced Innovation Center for Structural BiologyTsinghua UniversityBeijing 100084China Key Laboratory for Matter Microstructure and Function of Hunan Province Key Laboratory of Low-dimensional Quantum Structures and Quantum ControlSchool of Physics and ElectronicsHunan Normal UniversityChangsha 410081China Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases Hangzhou 310058China

Enterovirus A71(EV-A71) causes major outbreaks of hand,foot,and mouth disease(HFMD) in many countries,most frequently affecting children,and a small proportion of cases may lead to ***,no vaccine is available in most endemic regions,and no licenced treatments for EV-A71 infection are ***,we characterize a human monoclonal antibody(Hu MAb),E1,by screening a Fab antibody phage library derived from patients who recovered from EV-A71 infection.E1 exhibits strong neutralizing activity against EV-A71 virus in *** cryo-electron microscopy(cryo-EM) structures of the EV-A71 virion in complex with E1 Fab fragments demonstrated that E1 recognized an epitope formed by residues in the BC and HI loops of *** a mouse model,E1 effectively protected against lethal EV-A71 challenge in both prophylactic and therapeutic *** particular,E1 significantly reduces virus titers and muscle damage.E1 might represent a potential adjunct to EV-A71 treatment.

关键词： enterovirus A71 antibody mouse models cryo-electron microscopy

来源：评论

学校读者我要写书评

暂无评论

Safe Reinforcement Learning for Social Motor Coordination in Two Dimensional Space 26

Safe Reinforcement Learning for Social Motor Coordination in...

引用

26th International Conference on Industrial Technology, ICIT 2025

作者： Yang, Fan Huang, Yuening Zhai, Chao Zhang, Hehong China University of Geosciences School of Automation Wuhan Campus China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Rice University George R. Brown School of Engineering and Computing HoustonTX United States Fuzhou University School of Computer and Data Science Fuzhou China

ISBN: (纸本)9798331521950

This paper presents an interactive motion control method based on reinforcement learning, designed to assist children with autism who have social motor impairments through a mirror game intervention. The virtual teacher uses the Deep Deterministic Policy Gradient (DDPG) algorithm to optimize its actions, guiding the participant to follow a Lissajous trajectory. To ensure safety, a motion-correction mechanism was developed, which automatically adjusts actions when the predicted trajectory surpasses predefined safety boundaries. The reward function considers both the distance between the virtual teacher and the target trajectory, as well as the distance between the virtual teacher and the participant, with dynamic adjustments applied by the motion-correction mechanism. Experimental results demonstrate that the virtual teacher effectively guides the participant towards the target trajectory while adhering to safety constraints. © 2025 IEEE.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

Frequency multiplexed photothermal correlation tomography for non-destructive evaluation of manufactured materials

引用

International Journal of Extreme Manufacturing 2025年第3期 538-552页

作者： Pengfei Zhu Rongbang Wang Koneswaran Sivagurunathan Stefano Sfarra Fabrizio Sarasini Clemente Ibarra-Castanedo Xavier Maldague Hai Zhang Andreas Mandelis Department of Electrical and Computer Engineering Computer Vision and Systems Laboratory(CVSL)Laval University Centre for Composite Materials and Structures (CCMS) Harbin Institute of Technology Center for Advanced Diffusion-Wave and Photoacoustic Technologies (CADIPT) and Institute for Advanced Non-Destructive and Non-Invasive Diagnostic Technologies (IANDIT) Department of Mechanical and Industrial EngineeringUniversity of Toronto Department of Industrial and Information Engineering and Economics (DIIIE) University of L'Aquila Department of Chemical Engineering Materials Environment&UDR INSTM Sapienza University of Rome

Infrared thermography has been widely applied in real industrial inspection of aerospace,energy management systems,engines,and electric ***,two-dimensional imaging modality limits its ***,a technique named frequency multiplexed photothermal correlation tomography (FM-PCT) was developed to enable non-destructive and contactless cross-sectional imaging for manufactured material evaluation and *** combining advantages of photothermal tomography and pulsed thermography,FM-PCT facilitates the generation of three-dimensional thermal images through temporal superposition(stacking) of two-dimensional images from sequential subsurface ***-PCT image processing involves pulsed excitation signals to which frequency delay and matched filtering techniques are *** features of FM-PCT are high-resolution three-dimensional tomographic imaging under low camera frame-rate conditions with self-correcting capability for diffusion (blurring) correction of subsurface images due to cross-correlation processing of individual frequencies in the Fourier decomposition spectrum of the excitation ***,FM-PCT extends truncated-correlation photothermal coherence tomography from chirp and pulsed signals to more general linear heating ***-in thermography and x-ray computed tomography validation demonstrate that 3D FM-PCT imaging accurately reveals subsurface discontinuities/defects in solids despite the diffusive nature of thermal-wave imaging.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Fast accurate position control of light-responsive liquid crystal elastomer actuator

Fast accurate position control of light-responsive liquid cr...

引用

Asian Control Conference

作者： Xinyu Nie Jundong Wu Yawu Wang Chun-Yi Su Daiki Sato Jinhua She School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Gina Cody School of Engineering and Computer Science Concordia University Montreal Quebec Canada Laboratory for Future Interdisciplinary Research of Science and Technology (FIRST) Tokyo Institute of Technology Yokohama Kanagawa Japan The School of Engineering Tokyo University of Technology Tokyo Japan

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

Light-responsive liquid crystal elastomers (LCEs) are promising for soft robot actuators due to their ability to respond to light stimuli and produce deformation. In order to realize their application in soft robots, fast and accurate position control is essential. Based on the intrinsic physical nature of LCE actuator's deformation, a terminal sliding mode controller (TSMC) is designed to efficiently adjust the temperature of the actuator, thus directly controlling the actuator deformation. In order to achieve the target temperature, a prediction model is established to predict the target temperature corresponding to the target displacement. Moreover, a proportional integration controller is applied to eliminate model errors and disturbances. The feasibility of the control strategy is experimentally verified, and compared with conventional PID controller. The results prove that the proposed control strategy can achieve fast and accurate control of displacement.

关键词： Heating systems Actuators Accuracy Deformation Position control Process control Elastomers

来源：评论

学校读者我要写书评

暂无评论

PD Control for Finite-Time Passivity and Synchronization of Complex Networks with Multiple Weights

PD Control for Finite-Time Passivity and Synchronization of ...

引用

2021 IEEE International Conference on Unmanned systems, ICUS 2021

作者： Wang, Lu Zhao, Lin-Hao Wang, Jin-Liang Bian, Yougang Hu, Manjiang College of Mechanical and Vehicle Engineering Hunan University State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Changsha China Australian Artificial Intelligence Institute University of Technology Sydney Faculty of Engineering and Information Technology Sydney Australia School of Computer Science and Technology Tiangong University Tianjin Key Laboratory of Autonomous Intelligence Technology and Systems Tianjin China

ISBN: (纸本)9780738146577

This paper mainly concentrates on the finite-time passivity (FTP) and finite-time synchronization (FTS) of complex networks with multiple weights (CNMWs). First, several FTP criteria of CNMWs are given through utilizing Lyapunov functional as well as a proportional-derivative (PD) controller. Then, the FTS problem for such networks is also coped with based on the FTP and PD control approach. Finally, a numerical simulation is given to illustrate our results. © 2021 IEEE.

关键词： Complex networks

来源：评论

学校读者我要写书评

暂无评论

Complementary multi-branch CNNs towards real-world 3D point classification

Complementary multi-branch CNNs towards real-world 3D point ...

引用

2021 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2021

作者： Tang, Zifeng Hao, Fusheng Zhang, Qieshi Cheng, Jun Zhang, Jin Yuan, Shuai Shenzhen Institute of Advanced Technology Chinese Academy of Science CAS Key Laboratory of Human-Machine Intelligence-Synergy Systems China Chinese University of Hong Kong Hong Kong Shenzhen University College of Computer Science and Software Engineering China Guangdong University of Technology College of Mechanical and Electrical Engineering China

ISBN: (纸本)9781665436786

Autonomous driving requires precise and efficient point clouds processing techniques, where deep learning has shown great potential. Nonetheless, most of the existing works achieve high accuracy in synthetic data while performing unsatisfactorily in real-world datasets. On the other hand, though existing multi-view-based, volumetric-based, and point-based methods have achieved promising results, they still suffer from high computational complexity or low memory utilization efficiency. For example, the computational time and memory consumption of multi-view-based and volumetric-based methods increase at most cubically with the increasing of the input resolution, while half of the point-based methods's runtime is wasted due to their irregular memory access. To address these issues, we propose a novel method to fuse complementary CNNs, dubbed as Multi-Branch Convolutional Neural Networks (MBCNN), which achieves the current state-of-the-art performance while maintaining high efficiency. The underlying design of MBCNN is to utilize the point-based convolution as a local-feature branch and spherical convolution as a global-feature branch, to capture patterns in space and exploit the merit of the pointwise MLP, which is robust to the perturbation. Besides, we design an efficient voxel-based indexing technique to prevent the feature-extracting phase from being blocked, thus significantly accelerating the procedure of finding a point's neighbor. Experimental results show that MBCNN achieves state-of-the-art performance on the real-world 3D point clouds dataset while reducing 30% of runtime in neighbor indexing. © 2021 IEEE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Toward Robust Manufacturing Scheduling: Stochastic Job-Shop Scheduling

arXiv

引用

arXiv 2022年

作者： Bragin, Mikhail A. Wilhelm, Matthew E. Yu, Nanpeng Stuber, Matthew D. The Institute for Advanced Systems Engineering University of Connecticut StorrsCT06269 United States The Process Systems and Operations Research Laboratory Department of Chemical and Biomolecular Engineering University of Connecticut StorrsCT06269 United States The Department of Electrical and Computer Engineering University of California Riverside RiversideCA92521 United States

Manufacturing plays a significant role in economic development, production, exports, and job creation, which ultimately contribute to improving the quality of life. The presence of manufacturing defects is, however, inevitable leading to products being discarded, i.e. scrapped. In some cases, defective products can be repaired through rework. Scrap and rework cause a longer completion time, which can contribute to orders being shipped late. Moreover, the presence of uncertainties and combinatorial complexity significantly increases the difficulty of complex manufacturing scheduling. This paper tackles this challenge, exemplified by a case study on stochastic job-shop scheduling in low-volume, high-variety manufacturing contexts. To ensure on-time delivery, high-quality solutions are required, and near-optimal solutions must be obtained within strict time constraints to ensure smooth operations on the job-shop floor. To efficiently solve the stochastic job-shop scheduling (JSS) problem, a recently-developed Surrogate "Level-Based" Lagrangian Relaxation is used to reduce computational effort while efficiently exploiting the geometric convergence potential inherent to Polyak's step-sizing formula thereby leading to fast convergence. Numerical testing demonstrates that the new method is two orders of magnitude faster as compared to commercial solvers. Note to Practitioners-Manufacturing defects leading to scrap or rework create significant challenges, from both computational as well as on-time delivery standpoints. To assist practitioners in overcoming these challenges, this paper presents a case study of stochastic job-shop scheduling as well as Surrogate "Level-Based" Lagrangian Relaxation as an efficient solution methodology, which not only reduces the time required to obtain high-quality, near-optimal solutions for complex scheduling problems but also minimizes the dependence on hyperparameters. As a result, the method becomes more user-friendly, reducing the need f

关键词： Markov processes

来源：评论

学校读者我要写书评

暂无评论

SKU-Patch: Towards Efficient Instance Segmentation for Unseen Objects in Auto-Store

arXiv

引用

arXiv 2023年

作者： Yang, Biqi Tang, Weiliang Gao, Xiaojie Li, Xianzhi Liu, Yun-Hui Fu, Chi-Wing Heng, Pheng-Ann The Department of Computer Science and Engineering The Chinese University of Hong Kong Hong Kong Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences China The School of Computer Science and Technology Huazhong University of Science and Technology China The Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong

In large-scale storehouses, precise instance masks are crucial for robotic bin picking but are challenging to obtain. Existing instance segmentation methods typically rely on a tedious process of scene collection, mask annotation, and network fine-tuning for every single Stock Keeping Unit (SKU). This paper presents SKU-Patch, a new patch-guided instance segmentation solution, leveraging only a few image patches for each incoming new SKU to predict accurate and robust masks, without tedious manual effort and model re-training. Technical-wise, we design a novel transformer-based network with (i) a patch-image correlation encoder to capture multi-level image features calibrated by patch information and (ii) a patch-aware transformer decoder with parallel task heads to generate instance masks. Extensive experiments on four storehouse benchmarks manifest that SKU-Patch is able to achieve the best performance over the state-of-the-art methods. Also, SKU-Patch yields an average of nearly 100% grasping success rate on more than 50 unseen SKUs in a robot-aided auto-store logistic pipeline, showing its effectiveness and practicality. Copyright © 2023, The Authors. All rights reserved.

关键词： Benchmarking

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：