检索结果-内蒙古大学图书馆

Chinese control and Decision Conference, CCDC

作者： Sichao Zhang Wei Liang Xudong Yuan Haibo An Meng Zheng Yinlong Zhang State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Science and Technology on Information Systems Engineering Laboratory the 28th Research Institute of CETC Nanjing China

Automatic Guided Vehicle (AGV) has been widely used in the warehouse for transporting the bulky and heavy cargos. However, the AGV may deviate the regular trajectories in presence of incorrect or untimely commands sent form the server due to, e.g., cyber attacks, unexpected blocks of the wireless signals. In order to ensure AGV running safely, this paper presents a visual surveillance system by making full use of the measurements from the forward and downward cameras. Specifically, the forward camera estimates the AGV positions and attitudes by tracking the surrounding landmarks detected from the forward image sequences. Besides, the downward camera is used to detect the QR codes fixed on the floor and estimate the AGV poses in the absolute reference frame. Apart from that, the AGV poses from the downward camera could correct scale and poses estimated the forward view. The proposed method has been extensively performed on the developed platform. The results proves the effectiveness in using the complementary forward-downward visual measurements for AGV security surveillance.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Charge Density Model of Silicon-nanowire GAA MOSFET Incoroperating the Source-drian Tunneling Effect for IC Design

A Charge Density Model of Silicon-nanowire GAA MOSFET Incoro...

引用

2021 International Symposium on Computer Technology and Information Science, ISCTIS 2021

作者： Cheng, He Zhang, Chao Liu, Tiefeng Xie, Chuang Yang, Zhjia Zhang, Zhipeng Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781665414418

One numerical compact model for one-dimensional electron charge density of n-Type silicon ballistic nanowire gate-All-Around metal-oxide-semiconductor field-effect transistors with ultra-short channel incorporating the source-drain tunneling is proposed. When establishing the AC model in practical device applications, compact models describing transient analysis of the carrier behaviors in the device channel are needed. When focusing on the charge density of carriers within GAA MOSFET devices, carriers transporting along the channel direction induced by the source-drain tunneling effect should also be taken into account in the subthreshold region. In this study, transmission coefficients of the source-drain tunneling effect are evaluated through expressing energy level of the lowest subband with bringing in the exact boundary conditions and using the Wentzel-Kramers-Brillouin approximation. Then, the carrier density can be derived from the charge profile in the channel using quantum statistics theory. Finally, comparisons of the calculations of the carrier densities between the source-drain tunneling and the thermionic modes in ballistic transport are demonstrated. © 2021 IEEE.

关键词： MOSFET devices

来源：评论

学校读者我要写书评

暂无评论

Fault Diagnostic Opportunities for Robot Servo Motors Using the Physics of Failure Analysis

Fault Diagnostic Opportunities for Robot Servo Motors Using ...

引用

International Conference on Reliability, Maintainability and Safety,ICRMS

作者： Bo Zhang Shan Liang Kai Wang Key Laboratory of Networked Control Systems Shenyang Institute of Automation Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China College of Computer Science and Technology University of Chemical Technology Chinese Academy of Sciences Shenyang China

ISBN: (数字)9798350329988

ISBN: (纸本)9798350329995

Joint robots are widely used in various industries, such as aviation, aerospace, and automotive manufacturing. The performance degradation of servo motors can significantly affect the overall performance of the robots because of the core component of joint robots, and therefore, it is critical to detect and address servo motor failures promptly. In this study, we analyze some common causes and mechanisms of performance degradation in robot servo motors using the physics of failure analysis. We also discuss strategies for detecting and diagnosing faults using these mechanisms before the servo motors fail completely.

关键词： Degradation Industries Service robots Failure analysis Safety Manufacturing Reliability Servomotors Physics Automotive engineering

来源：评论

学校读者我要写书评

暂无评论

Kuhn-Munkres Algorithm Based Hybrid Beamforming for Wideband Millimeter Wave MIMO systems With Dynamic Subarrays

Kuhn-Munkres Algorithm Based Hybrid Beamforming for Wideband...

引用

International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Gengshan Wang Zhijia Yang Tierui Gong Meng Zheng State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Singapore University of Technology and Design Singapore

Dynamic subarrays (DSs) is an energy-efficient and cost-effective hybrid beamforming structure for millimeter wave (mmWave) multiple-input multiple-output (MIMO) communications. In this paper, we investigate the nonconvex hybrid beam-forming problem of maximizing the average spectral efficiency of the point-to-point wideband mmWave MIMO system with DSs, where the beam squints are also considered. To address the nonconvexity of this hybrid beamforming problem, we first exploit the singular value decomposition of each subcarrier channel and water-filling strategy to get the optimal fully-digital beamforming. We then propose to leverage the Kuhn-Munkres algorithm to get the hybrid beamforming from the obtained fully-digital solutions, aiming to guarantee that every radio-frequency chain is connected to at least one antenna. Besides, we analyze the computational complexity of the proposed design. Numerical results demonstrate the superiority of this work over the state of the art.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Synthesis of Decoherence-Free Modes in Linear Quantum Passive systems via Robust Pole Placement

Synthesis of Decoherence-Free Modes in Linear Quantum Passiv...

引用

IEEE International Conference on systems, Man and Cybernetics

作者： Zibo Miao Yu Pan Qing Gao Guangdong Key Laboratory of Intelligent Morphing Mechanisms School of Mechanical Engineering and Automation Adaptive Robotics Harbin Institute of Technology Shenzhen China State Key Laboratory of Industrial Control Technology The Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou China The School of Automation Science and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing China

ISBN: (数字)9781665410205

ISBN: (纸本)9781665410212

In this paper we extend our previous research on coherent observer-based pole placement approach to study the synthesis of robust decoherence-free (DF) modes for linear quantum passive systems, which is aimed at preservation of quantum information. In particular, DF modes can be generated by placing the poles on the imaginary axis via a coherent feedback design scheme, and these modes can further be simultaneously made robust against perturbations to the system parameters by minimizing the condition number associated with imaginary poles. We develop explicit algebraic conditions for the existence of such a coherent quantum controller, with the corresponding deign procedure provided. Examples are given to illustrate the process of tuning the DF modes towards perfect robustness via the proposed pole placement technique.

关键词： Perturbation methods Design methodology Quantum optics Robustness Feedback control Closed loop systems Tuning Cybernetics

来源：评论

学校读者我要写书评

暂无评论

A DDOS Attack Traffic Classification Model for Industrial Internet Based on CNN-LSTM

A DDOS Attack Traffic Classification Model for Industrial In...

引用

2022 Chinese Automation Congress, CAC 2022

作者： Wei, Weixuan Liu, Xianda Sheng, Chuan Feng, Ansong Shenyang University of Chemical Technology College of Information Engineering Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China

ISBN: (纸本)9781665465335

With the continuous development and application of industrial Internet, the weakness of the security defense capability of industrial Internet has become increasingly prominent. This paper presents an end-to-end classification model combining Convolutional Neural Network (CNN) and Long Short-Term Memory (LSTM) network for DDoS attacks over industrial Internet. By self-learning the spatial and temporal characteristics of the original attack traffic, the model can avoid subjective errors that may occur due to manual selection of features. This method is a feasible means, with an accuracy rate of 99%. © 2022 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Short-term load forecasting of long-short term memory neural network based on genetic algorithm 4

Short-term load forecasting of long-short term memory neural...

引用

4th IEEE Conference on Energy Internet and Energy System Integration, EI2 2020

作者： Li, Wanting Zang, Chuanzhi Liu, Ding Zeng, Peng Shenyang Institute of Automation Chinese Academy of Sciences Key Laboratory of Networked Control Systems State Key Laboratory of Robotics Institutes for Robotics and Intelligent Manufacturing Beijing China

ISBN: (纸本)9781728196060

Accurate load forecasting is conducive to the reasonable arrangement of power grid dispatching plans. Traditional load forecasting methods cannot handle the time series and nonlinear characteristics of load well. Long-short term memory (LSTM) neural networks can record long-term and short-term information, which can effectively solve this kind of problem. But the parameters of LSTM network are difficult to determine. For this reason, this paper proposes a long-short term neural network based on genetic algorithm. The learning rate and iteration number of the LSTM network are used as chromosomes, and the genes are continuously selected, crossed, and mutated to obtain more good genes. Comparing this method with the standard LSTM network, the simulation results show that the LSTM network using genetic algorithm for parameter optimization improves the prediction accuracy of the standard LSTM network by 63%. © 2020 IEEE.

关键词： Genetic algorithms

来源：评论

学校读者我要写书评

暂无评论

Environment-Driven Online LiDAR-Camera Extrinsic Calibration

arXiv

引用

arXiv 2025年

作者： Huang, Zhiwei Li, Jiaqi Zhong, Ping Fan, Rui The Department of Control Science & Engineering The College of Electronics & Information Engineering Tongji University Shanghai201804 China The School of Computer Science and Engineering Central South University Hunan Changsha410083 China The National Key Laboratory of Science and Technology on Automatic Target Recognition National University of Defense Technology Hunan Changsha410073 China The Department of Control Science & Engineering The College of Electronics & Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems The State Key Laboratory of Intelligent Autonomous Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai201804 China The National Key Laboratory of Human-Machine Hybrid Augmented Intelligence Institute of Artificial Intelligence and Robotics Xi’an Jiaotong University Shaanxi Xi’an710049 China

LiDAR-camera extrinsic calibration (LCEC) is the core for data fusion in computer vision. Existing methods typically rely on customized calibration targets or fixed scene types, lacking the flexibility to handle variations in sensor data and environmental contexts. This paper introduces EdO-LCEC, the first environment-driven, online calibration approach that achieves human-like adaptability. Inspired by the human perceptual system, EdO-LCEC incorporates a generalizable scene discriminator to actively interpret environmental conditions, creating multiple virtual cameras that capture detailed spatial and textural information. To overcome cross-modal feature matching challenges between LiDAR and camera, we propose dual-path correspondence matching (DPCM), which leverages both structural and textural consistency to achieve reliable 3D-2D correspondences. Our approach formulates the calibration process as a spatial-temporal joint optimization problem, utilizing global constraints from multiple views and scenes to improve accuracy, particularly in sparse or partially overlapping sensor views. Extensive experiments on real-world datasets demonstrate that EdO-LCEC achieves state-of-the-art performance, providing reliable and precise calibration across diverse, challenging environments. Copyright © 2025, The Authors. All rights reserved.

关键词： Spatio-temporal data

来源：评论

学校读者我要写书评

暂无评论

control method of outlet moisture content of tobacco primary processing based on TVA-TCN-MPC 10

Control method of outlet moisture content of tobacco primary...

引用

10th IEEE Joint International Information Technology and Artificial Intelligence Conference, ITAIC 2022

作者： Zhu, Xuejing Peng, Hui Shu, Kuiwu Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Hongta Liaoning Tobacco Industry Limited Liability Company Yingkou China

ISBN: (数字)9781665422079

ISBN: (纸本)9781665422079

The stability of outlet moisture content of primary tobacco processing is an indicator that the tobacco industry is very concerned about. In view of the problems that most of the existing control methods need to rely on artificial experience and complex mechanism modeling, a control method of outlet moisture content of tobacco primary processing based on TVA- TCN-MPC is proposed. Firstly, the TVA- TCN outlet moisture prediction model is established with the input moisture, water addition coefficient, and outlet moisture as input. Then, its output is used as the input of the objective optimization function, which is constrained by the control error and the adjustment range of the water addition coefficient, so that the control problem is transformed into the problem of solving the objective function, and the local optimal control sequence is obtained. And then continuously rolling optimization to achieve the target outlet moisture. Experiments are carried out on the actual data of cigarette factory, and the outlet moisture control algorithm based on TVA- TCN-MPC can effectively improve the stability of outlet moisture. © 2022 IEEE.

关键词： Water supply

来源：评论

学校读者我要写书评

暂无评论

Retinal disorder diagnosis based on hybrid deep learning models

引用

Multimedia Tools and Applications 2025年 1-25页

作者： Sedik, Ahmed El-Shafai, Walid El-Hag, Noha A. El-Banby, Ghada M. Abd El-Samie, Fathi E. Smart Systems Engineering Laboratory College of Engineering Prince Sultan University Riyadh11586 Saudi Arabia Department of the Robotics and Intelligent Machines Faculty of Artificial Intelligence Kafrelsheikh University Kafr el-Sheikh Egypt Computer Science Department Prince Sultan University Riyadh11586 Saudi Arabia Department of Electronics and Electrical Communications Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt The Higher Institute of Commercial Sciences Algarbia Al Mahalla Al Kubra31951 Egypt Department of Industrial Electronics and Control Engineering Faculty of Electronic Engineering Menoufia University Menouf32952 Egypt Department of Information Technology College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University P.O. Box 84428 Riyadh11671 Saudi Arabia

Anomaly detection from medical images is badly needed for automated diagnosis. For example, medical images obtained with several modalities, such as magnetic resonance (MR) and confocal microscopy, need to be classified for anomaly detection. The MR images may contain tumors that need to be detected with anomaly detection techniques. In MR imaging, brain tumors are represented as areas composed of abnormal cells that need to be detected. On the other hand, confocal microscopy can be used for retinal imaging. Hence, there is a need to apply classification techniques for diagnosing diseases of the eye, such as Diabetic Retinopathy (DR), which leads to exudates in different regions of the retina. The detection of exudates is necessary for the diagnosis of DR. In this paper, two models are presented for the classification of MR and retinal images. Much research has been done in this area, but it did not achieve high accuracy of classification in an acceptable time. In addition, the previous models did not consider both types of image modalities considered in this paper. The suggested models are Convolutional Neural Network (CNN) and Convolutional Long Short-Term Memory (Conv-LSTM). They are used to classify normal and abnormal cases of both brain tumor and DR diseases. The CNN model is composed of six convolutional layers and six max-pooling layers. A soft-max activation function takes the classification decision. The proposed Conv-LSTM model is composed of three stages: pre-processing, feature extraction, and classification. The deep learning model performance is better than those of traditional networks. The CNN gives an accuracy of 94.26% for DR classification and 95.8% for brain tumor classification, while the Conv-LSTM gives the maximum accuracy of 96.41% for DR classification and 97.4% for brain tumor classification. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.

关键词： Confocal microscopy

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：