检索结果-内蒙古大学图书馆

IEEE International Conference on Civil Aviation Safety and Information technology (ICCASIT)

作者： Ying Liu Dongqin Feng State Key Laboratory of Industrial Control Technology Zhejiang University Institute of Intelligent Systems and Control Zhejiang China

ISBN: (纸本)9781728125992

Computer network technology has been increasingly infiltrated into the industrial control system and made the security problems more complex and changeable. Network security situation awareness technology can perceive the real-time threats that the network faced, and provide reliable basis for decision-making. This paper mainly focuses on the situation assessment and introduces finite state machine and fuzzy logic theory. Finite state machine can intuitively show the internal state transition of the industrial control system and detect the malicious packet attack's type and severity. Fuzzy logic balances the semantic fuzziness and event uncertainty in the process of situation assessment, fuses the output data of the state machine and obtains the threat level which is helpful for decision analysis. Proved, the method proposed in this paper can give a reasonable and accurate security assessment of industrial control system.

关键词： Malicious packet attack detection industrial control system Finite state machine Fuzzy logic industrial control systems finite state machines state machines Fuzzy logic state Change

来源：评论

学校读者我要写书评

暂无评论

Conflict Detection of Device Linkage Rules in Smart Home systems

Conflict Detection of Device Linkage Rules in Smart Home Sys...

引用

Chinese Automation Congress (CAC)

作者： Ye Fu Daojuan Zhang Chonghua Wang Xi Luo Wenxin Liu Tianjie Luo Fuyang Fang Cyber space Institute of Advanced Technology Guangzhou University Guangzhou China State Grid Key Laboratory of Information&Network Security Global Energy Interconnection Research Institute co. Ltd Beijing China China Industrial Control Systems Cyber Emergency Response Team Beijing China Information Science Academy China Electronics Technology Group Corporation Beijing China

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

With the increasing types and functions of smart home devices, due to the lack of experience of users, they may cause unexpected errors and risks when configuring a large number of device linkage *** response to the above problems, in this paper, we propose an efficient conflict detection method to avoid unexpected ***, to reduce the complexity of subsequent rule conflict detection, we divide each rule into five categories according to its functions and characteristics. At the same time, we configure the priority, user rights, and execution area for each rule. Second, we filter out the rules of the same priority, user rights, and execution area. Third, we define five types of rule conflicts. Finally, the conflict detection algorithm is used to determine whether the filtered rules conflict with the rules in the corresponding database. We have created 379 non-conflicting rules in each type of rule storage database to detect whether the newly created rules conflict with them. Through experimental comparison, we find that our approach has more advantages than previous work in terms of performance and conflict detection types.

关键词： Couplings Actuators Smart homes Sensors Databases Security Data mining

来源：评论

学校读者我要写书评

暂无评论

$\mathcal H_{2}$ Performance Analysis and Applications of 2-D Hidden Bernoulli Jump System

引用

IEEE Transactions on systems, Man, and cybernetics: systems 2019年第10期49卷 2097-2107页

作者： Zheng-Guang Wu Ying Shen Hongye Su Renquan Lu Tingwen Huang State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Guangdong Key Laboratory of IoT Information Processing School of Automation Guangdong University of Technology Guangzhou China Texas A&M University at Qatar Doha Qatar

The asymptotic mean square stability and H 2 performance of the 2-D hidden Bernoulli jump system is analyzed in this paper. This system, essentially, has a bi-jumping property, in other words, its jumps depend on two jumping parameters, one is the Bernoulli process, the other is dependent on the Bernoulli process via a conditional probability matrix, they together determine which subsystem is active and are coined as hidden Bernoulli model. By means of Lyapunov function method, a sufficient condition is derived, which reveals that the system is asymptotically mean square stable and has a certain H 2 performance if a set of matrix inequalities are satisfied. Furthermore, the issues of asynchronous control and filtering are addressed for 2-D Bernoulli jump system based on the hidden Bernoulli model and the derived result. Finally, numerical simulations indicate that these proposed theories and methods are reliable and efficient.

关键词： Markov processes Switches Performance analysis Boundary conditions Indexes Switched systems

来源：评论

学校读者我要写书评

暂无评论

Convolutional Neural Network applied in mime speech recognition using sEMG data

Convolutional Neural Network applied in mime speech recognit...

引用

Chinese Automation Congress (CAC)

作者： Qing Ai Wei Zhang Bixuan Zhang Guang Li Meng Yang State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Department of Computer Science and Technology China University of Mining and Technology Beijing China

Decoding speaking intention from the cervical and facial muscle activity enables speech recognition independent of acoustic signals, thus allowing silent communication between human and computing devices. This research aims to design and optimize the convolutional network classifier for sEMG mime speech signals. The muscles involved in the vocalization and timbre modulation are found according to the anatomical map. Six-channel signals have been collected from the corresponding position using the sEMG signal acquisition device. The original signals are subjected to pre-processing, including noise reduction, active segment detection and interpolation, to form training and testing sets. Convolutional network models are applied to Figure out the influence of structural parameters, such as convolution kernel size, the number of convolution kernels and the depth of network, on the recognition accuracy. Based on repeated trials, the optimal convolution network is provided, which provide above 80% accuracy rate.

关键词： Speech recognition Convolution Electromyography Task analysis Training Kernel Interference

来源：评论

学校读者我要写书评

暂无评论

Silent Speech Recognition Based on Surface Electromyography

Silent Speech Recognition Based on Surface Electromyography

引用

Chinese Automation Congress (CAC)

作者： Siyuan Ma Dantong Jin Ming Zhang Bixuan Zhang You Wang Guang Li Meng Yang Institute of Cyber-Systems and Control State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China Department of Computer Science and Technology China University of Mining and Technology Beijing China

Silent speech recognition (SSR) can decode the activities of electromyography (EMG) from surface of articulatory muscles to the according brain information. As the essentials in SSR, feature extraction and recognition are directly related to the final decoding effects, which requires careful research, especially on small datasets. This paper collected the surface EMG (sEMG) of 10 isolated Chinese words by 6 surface electrodes on face and around, and based on which sEMG features were extracted by wavelet packet transform, principal component analysis and XGBoost (an implementation of gradient boosted decision trees) respectively. Then Support Vector Machine, K-Nearest Neighbor and Random Forest were explored for recognition on the 10 words. The results indicated that the highest accuracy of 72% was achieved by the method of Random Forest based on XGBoost.

关键词： Feature extraction Principal component analysis Support vector machines Training Speech recognition Electromyography Forestry

来源：评论

学校读者我要写书评

暂无评论

Corrections to “Starfish Inspired Milli Soft Robot With Omnidirectional Adaptive Locomotion Ability”

引用

IEEE Robotics and Automation Letters 2021年第3期6卷 5348-5348页

作者： Xiong Yang Rong Tan Haojian Lu Yajing Shen Biomedical Engineering Department City University of Hong Kong Kowloon Hong Kong State Key Laboratory of Industrial Control and Technology and Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Shenzhen Research Institute City University of Hong Kong Shenzhen China

Presents corrections to the declaration of equal contribution that was missed in the above named paper.

关键词： Soft robotics

来源：评论

学校读者我要写书评

暂无评论

DeepGoal: Learning to drive with driving intention from human control demonstration

arXiv

引用

arXiv 2019年

作者： Ma, Huifang Wang, Yue Xiong, Rong Kodagoda, Sarath Tang, Li 38 Zheda Road Zhejiang310027 China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Zhejiang China Centre for automotive Systems University of Technology Sydney Australia

Recent research on automotive driving developed an efficient end-to-end learning mode that directly maps visual input to control commands. However, it models distinct driving variations in a single network, which increases learning complexity and is less adaptive for modular integration. In this paper, we re-investigate human’s driving style and propose to learn an intermediate driving intention region to relax difficulties in end-to-end approach. The intention region follows both road structure in image and direction towards goal in public route planner, which addresses visual variations only and figures out where to go without conventional precise localization. Then the learned visual intention is projected on vehicle local coordinate and fused with reliable obstacle perception to render a navigation score map widely used for motion planning. The core of the proposed system is a weakly-supervised cGAN-LSTM model trained to learn driving intention from human demonstration. The adversarial loss learns from limited demonstration data with one local planned route and enables reasoning of multi-modal behavior with diverse routes while testing. Comprehensive experiments are conducted with real-world datasets. Results show the proposed paradigm can produce more consistent motion commands with human demonstration, and indicates better reliability and robustness to environment change. Our code is available at https://***/HuifangZJU/visual-navigation. Copyright © 2019, The Authors. All rights reserved.

关键词： Motion planning

来源：评论

学校读者我要写书评

暂无评论

An Approach for Peg-in-Hole Assembling Based on Force Feedback control

An Approach for Peg-in-Hole Assembling Based on Force Feedba...

引用

Chinese Automation Congress (CAC)

作者： Peng Zou Qiuguo Zhu Jun Wu Jianxiang Jin State Key Laboratory of Industrial Control and Technology Zhejiang University Institute of Cyber-System and Control Zhejiang University Hangzhou P. R. China

In this paper, an intuitive and effective method is proposed for a sensor guided industrial robot to carry out the Peg-in-Hole assembly. This method contains two main steps. The first step is calibrating the wrist force sensor to compensate the load gravity and the bias of sensor so that the external force on the load can be precisely obtained. Secondly an impedance controller is designed to realize the compliant behavior between the manipulator and external environment. Different from the traditional method based on the position control loop, the force control strategy is based on the robot end-effector velocity control loop, which is easier and convenient to implement. Finally, a Peg-in-Hole experiment using an industrial manipulator with wrist sensor and a Peg-in-Hole mould with a tiny clearance was successfully completed. The experimental results verified the effectiveness and practicability of the proposed method.

关键词： Robot sensing systems Service robots Robot kinematics Gravity Task analysis

来源：评论

学校读者我要写书评

暂无评论

Batch Normalization Masked Sparse Autoencoder for Robotic Grasping Detection

Batch Normalization Masked Sparse Autoencoder for Robotic Gr...

引用

2020 IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Zhenzhou Shao Ying Qu Guangli Ren Guohui Wang Yong Guan Zhiping Shi Jindong Tan Beijing Advanced Innovation Center for Imaging Technology and Beijing Key Laboratory of Light Industrial Robot and Safety Verification Capital Normal University Beijing China The Engineering College The University of Tennessee Knoxville TN USA State Key Laboratory for Management and Control of Complex Systems Institute of Automation Beijing China

ISBN: (数字)9781728162126

ISBN: (纸本)9781728162133

To improve the accuracy of the grasping detection, this paper proposes a novel detector with batch normalization masked evaluation model. It is designed with a two-layer sparse autoencoder, and a Batch Normalization based mask is incorporated into the second layer of the model to effectively reduce the features with weak correlation. The extracted features from such model are more distinctive, which guarantees the higher accuracy of the grasping detection. Extensive experiments show that the proposed evaluation model outperforms the state-of- the-art, and the recognition accuracy can reach 95.51% for robotic grasping detection.

关键词： Training Redundancy Grasping Detectors Feature extraction Intelligent robots Load modeling

来源：评论

学校读者我要写书评

暂无评论

An augmented regression model for tensors with missing values

arXiv

引用

arXiv 2020年

作者： Wang, Feng Gahrooei, Mostafa Reisi Zhong, Zhen Tang, Tao Shi, Jianjun State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China Department of Industrial and Systems Engineering University of Florida GainesvilleFL32611 United States H. Milton Stewart School of Industrial and Systems Engineering Georgia Institute of Technology AtlantaGA30332 United States

Heterogeneous but complementary sources of data provide an unprecedented opportunity for developing accurate statistical models of systems. Although the existing methods have shown promising results, they are mostly applicable to situations where the system output is measured in its complete form. In reality, however, it may not be feasible to obtain the complete output measurement of a system, which results in observations that contain missing values. This paper introduces a general framework that integrates tensor regression with tensor completion and proposes an efficient optimization framework that alternates between two steps for parameter estimation. Through multiple simulations and a case study, we evaluate the performance of the proposed method. The results indicate the superiority of the proposed method in comparison to a benchmark. Copyright © 2020, The Authors. All rights reserved.

关键词： Tensors

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：