检索结果-内蒙古大学图书馆

IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Chao Ma Wei Wu Yidao Ji Wei Wang School of Mechanical Engineering University of Science and Technology Beijing Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China

ISBN: (数字)9781728172934

ISBN: (纸本)9781728172941

This paper is concerned with the tracking control for robotic manipulators with switching loads and parameter uncertainties. More precisely, the neural network approximation method is adopted with adaptive control to deal with the unmodeled dynamics. Multiple Lyapunov function method is used based on mode-dependent average dwell time, such that the tracking error can converge with desired region. A numerical example is finally provided for illustrating our proposed tracking strategy.

关键词： Switches Robots Manipulators Neural networks control systems Manipulator dynamics Uncertain systems

来源：评论

学校读者我要写书评

暂无评论

Attacking DNN-based Intrusion Detection Models

引用

IFAC-PapersOnLine 2020年第5期53卷 415-419页

作者： Xingwei Zhang Xiaolong Zheng Desheng Dash Wu The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China School of Economics and Management University of Chinese Academy of Sciences Beijing 100190 China and also with the Stockholm Business School Stockholm University SE-106 91 Stockholm Sweden

Intrusion detection plays an important role in public security domains. Dynamic deep neural network(DNN)-based intrusion detection models have been demonstrated to show effective performance for timely detecting network intrusions. While DNN-based intrusion detection models have shown powerful performance, in this paper, we verify that they could be easily attacked by well-designed small adversarial perturbations. We design an effective procedure to employ commonly used adversarial perturbations for attacking well-trained DNN detection models on NSL-KDD dataset. We further find that the performance of DNN models for recognizing real labels of abnormal data suffers more from attacks compared with that on normal samples.

关键词： public security intrusion detection deep neural networks adversarial perturbations

来源：评论

学校读者我要写书评

暂无评论

Neural-based Inverse Kinematical Analysis for Bio-inspired Cable-driven Robotic Manipulator

Neural-based Inverse Kinematical Analysis for Bio-inspired C...

引用

IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Hang Fu Yang Liu Wei Wu Xiaoqing Li School of Mechanical Engineering University of Science and Technology Beijing Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing China

ISBN: (数字)9781728172934

ISBN: (纸本)9781728172941

In this paper, the inverse kinematical analysis problem is investigated for a class of bio-inspired cable-driven robotic manipulator. Moreover, the modeling of the redundant cable-driven robotic manipulator is performed. In particular, the RBF neural network is adopted to deal with the unmodeled parameters uncertainties such that the inverse kinematic analysis precision can be improved. In the end, an illustrative example is presented for showing the usefulness of the developed analysis approach.

关键词： Manipulators Clustering algorithms Entropy Robot kinematics Kinematics Training Radial basis function networks

来源：评论

学校读者我要写书评

暂无评论

Design of a low-cost miniature robot to assist the COVID-19 nasopharyngeal swab sampling

arXiv

引用

arXiv 2020年

作者： Wang, Shuangyi Wang, Kehao Liu, Hongbin Hou, Zengguang The State Key Laboratory of Management and Control of Complex Systems Chinese Academy of Sciences Institute of Automation China Beijing Advanced Innovation Center for Biomedical Engineering Beihang University China The School of Biomedical Engineering and Imaging Sciences King's College London United Kingdom

Nasopharyngeal (NP) swab sampling is an effective approach for the diagnosis of coronavirus disease 2019 (COVID-19). Medical staffs carrying out the task of collecting NP specimens are in close contact with the suspected patient, thereby posing a high risk of cross-infection. We propose a low-cost miniature robot that can be easily assembled and remotely controlled. The system includes an active end-effector, a passive positioning arm, and a detachable swab gripper with integrated force sensing capability. The cost of the materials for building this robot is 55 USD and the total weight of the functional part is 0.23kg. The design of the force sensing swab gripper was justified using Finite Element (FE) modeling and the performances of the robot were validated with a simulation phantom and three pig noses. FE analysis indicated a 0.5mm magnitude displacement of the gripper's sensing beam, which meets the ideal detecting range of the optoelectronic sensor. Studies on both the phantom and the pig nose demonstrated the successful operation of the robot during the collection task. The average forces were found to be 0.35N and 0.85N, respectively. It is concluded that the proposed robot is promising and could be further developed to be used in vivo. Copyright © 2020, The Authors. All rights reserved.

关键词： Coronavirus

来源：评论

学校读者我要写书评

暂无评论

FSD-10: A dataset for competitive sports content analysis

arXiv

引用

arXiv 2020年

作者： Liu, Shenglan Liu, Xiang Huang, Gao Feng, Lin Hu, Lianyu Jiang, Dong Zhang, Aibin Liu, Yang Qiao, Hong Faculty of Electronic Information and Electrical Engineering Dalian University of Technology Dalian Liaoning116024 China Faculty of Tsinghua University of Technology Beijing China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

Action recognition is an important and challenging problem in video analysis. Although the past decade has witnessed progress in action recognition with the development of deep learning, such process has been slow in competitive sports content analysis. To promote the research on action recognition from competitive sports video clips, we introduce a Figure Skating Dataset (FSD-10) for finegrained sports content analysis. To this end, we collect 1484 clips from the worldwide figure skating championships in 2017-2018, which consist of 10 different actions in men/ladies programs. Each clip is at a rate of 30 frames per second with resolution 1080 × 720. These clips are then annotated by experts in type, grade of execution, skater info,.etc. To build a baseline for action recognition in figure skating, we evaluate state-of-the-art action recognition methods on FSD-10. Motivated by the idea that domain knowledge is of great concern in sports field, we propose a keyframe based temporal segment network (KTSN) for classification and achieve remarkable performance. Experimental results demonstrate that FSD-10 is an ideal dataset for benchmarking action recognition algorithms, as it requires to accurately extract action motions rather than action poses. We hope FSD-10, which is designed to have a large collection of finegrained actions, can serve as a new challenge to develop more robust and advanced action recognition models. Copyright © 2020, The Authors. All rights reserved.

关键词： Sports

来源：评论

学校读者我要写书评

暂无评论

3D Deep Learning for 3D Printing of Tooth Model

3D Deep Learning for 3D Printing of Tooth Model

引用

2019 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2019

作者： Liu, Yiwen Shang, Xiuqin Shen, Zhen Hu, Bin Wang, Zhihai Xiong, Gang State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing University of Technology Faculty of Information Beijing China Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of Sciences Beijing China Beijing University of Technology Faculty of Information Beijing China

ISBN: (纸本)9781728128535

Recently, with the development of both 3D sensors and 3D virtual network that bring the needs of interaction with the real world, many 3D applications burst out. However, it is difficult to understanding these three-dimensional scenes with a fixed program. Then, a data-driven method is required to process these 3D data, which brings a strong demand of 3D Deep Learning in 3D data. Towards this goal, with an end-to-end deep learning, the experiment is based on PointNet++, a well proposed method for feature extraction. The experiment optimizes the network structure and parameters to improve the classification results. Finally, the network is applied to tooth model for classification and identification so that the dental model can be found from different perspectives. © 2019 IEEE.

关键词： 3D printers

来源：评论

学校读者我要写书评

暂无评论

ModuleNet: Knowledge-inherited Neural Architecture Search

arXiv

引用

arXiv 2020年

作者： Chen, Yaran Gao, Ruiyuan Liu, Fenggang Zhao, Dongbin State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 College of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China Beihang Univercity Beijing China Beijing Institute of Technology Beijing China

—Although Neural Architecture Search (NAS) can bring improvement to deep models, they always neglect precious knowledge of existing models. The computation and time costing property in NAS also means that we should not start from scratch to search, but make every attempt to reuse the existing knowledge. In this paper, we discuss what kind of knowledge in a model can and should be used for new architecture design. Then, we propose a new NAS algorithm, namely ModuleNet, which can fully inherit knowledge from existing convolutional neural networks. To make full use of existing models, we decompose existing models into different modules which also keep their weights, consisting of a knowledge base. Then we sample and search for new architecture according to the knowledge base. Unlike previous search algorithms, and benefiting from inherited knowledge, our method is able to directly search for architectures in the macro space by NSGA-II algorithm without tuning parameters in these modules. Experiments show that our strategy can efficiently evaluate the performance of new architecture even without tuning weights in convolutional layers. With the help of knowledge we inherited, our search results can always achieve better performance on various datasets (CIFAR10, CIFAR100) over original architectures. Copyright © 2020, The Authors. All rights reserved.

关键词： Knowledge based systems

来源：评论

学校读者我要写书评

暂无评论

A Blockchain-based Framework for Central Bank Digital Currency

A Blockchain-based Framework for Central Bank Digital Curren...

引用

2019 IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI 2019

作者： Han, Xuan Yuan, Yong Wang, Fei-Yue 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 Research Center of Military Computational Experiments and Parallel System National University of Defense Technology Changsha China

ISBN: (纸本)9781728128535

Cryptocurrency and blockchain technologies have developed in parallel in recent years, with technological breakthroughs in currency issuance, payment methods, and currency storage. However, the existing cryptocurrencies cannot replace fiat money. There is a huge gap between decentralized cryptocurrency and central bank digital currency, namely CBDC, in terms of monetary governance and circulation. In this paper, we propose the function and security requirements of CBDC, through a comprehensive analysis of the existing typical cryptocurrency and the prototype of the CBDC scheme. On this basis, we present a blockchain-based framework for CBDC with three layers, including supervisory layer, network layer and user layer, and describe the key business processes of the CBDC's entire lifecycle of issuance-circulation-withdrawal in detail. Finally, we take cross-border payment as an example to explain the transaction process of CBDC. We aim to provide theoretical guidance for CBDC design. © 2019 IEEE.

关键词： Blockchain

来源：评论

学校读者我要写书评

暂无评论

Short Term Traffic Flow Forecast Based on CM-GRU Networks

Short Term Traffic Flow Forecast Based on CM-GRU Networks

引用

IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Zhongzheng Guo Weifeng Zhong Fenghua Zhu Xiaoshuang Li Fei-Yue Wang Gang Xiong the State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Institute of Automation Harbin University of Science And Technology Harbin China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Intelligent transportation systems (ITS) have developed for a long time. The rise of deep learning has brought new vitality of the ITS. However, traffic flow data is usually time-correlated and highly randomized. The data distribution will also change dynamically. To actualize the forecasting of traffic flow accurately, we use the historical traffic information to predict the messages of the traffic flow at any time interval. This paper proposes an efficient traffic flow forecast architecture based on deep learning. The method combines the gated recurrent unit (GRU, a type of recurrent neural network) layers and one-dimension convolution layers. Since the performance of these models has a strong dependence on hyper-parameters, this paper conducts a large-scale search of the hyper-parameter space. At the same time, experiments on flow data show that the method proposed in this paper can achieve a better prediction accuracy. Experiments also show lower test errors compared with the existing approaches.

关键词： Feature extraction Predictive models Automation Logic gates Convolution Training complex systems

来源：评论

学校读者我要写书评

暂无评论

Performance evaluation of faults in a photovoltaic array based on V-I and V-P characteristic curve 12

Performance evaluation of faults in a photovoltaic array bas...

引用

12th International Conference on Measuring Technology and Mechatronics Automation, ICMTMA 2020

作者： Lodhi, Ehtisham Lina, Wang Pu, Yang Javed, M. Yaqoob Lodhi, Zeeshan Zhijie, Jiao Javed, Usman School of Automation Science and Electrical Engineering Beihang University Beijing100191 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Department of Electrical and Computer Engineering COMSATS University Islamabad Lahore54000 Pakistan Department of Electrical and Computer Engineering COMSATS University Islamabad Abbottabad22060 Pakistan Guo China-US Photonics Lab Changchun Institute of Optics Fine Mechanics and Physics Chinese Academy of Sciences Changchun130033 China

ISBN: (纸本)9781728170817

The prediction and forecasting of faults occurring in photovoltaic (PV) system is one of the important aspect to escalate the reliability, output power generation, proficiency, lifetime and effectiveness of overall system. In this article, the behavior of PV array is studied under various faulty circumstances and new approach has offered for the better performance assessment of PV array. This approach is established on the analysis of peculiarities displayed by voltage power (V-P) and voltage-current (V-I) characteristics curves of PV array under different faulty conditions. The proposed technique can be used to identify and classify the five common faults in PV system. These progressive faults (includes open circuit, line-to-line, partial shading, degradation and bridging faults) have been occurred at the basic components of PV cell and at the connection point between PV modules. The characteristic curves under normal and faulty conditions have been compared by utilizing Matlab/Simulink environment. Hence, the suggested method can be utilized to determine the important fact about the health PV array. © 2020 IEEE.

关键词： Solar panels

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：