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12th International Conference on Computer engineering and Networks, CENet 2022

作者： Lei, Suqin Deng, Xing Shao, Haijian Xia, Wang Department of Computer Jiangsu University of Science and Technology Jiangsu Zhenjiang212003 China College of Automation Key Laboratory of Ministry of Education of Complex Engineering System Measurement and Control Southeast University Jiangsu Nanjing210009 China School of Information Science and Technology Nantong University Nantong Jiangsu226019 China Department of Electrical and Computer Engineering National University of Singapore Singapore117583 Singapore

ISBN: (纸本)9789811969003

Breast cancer is one of the most common cancers among female diseases. Since the classification accuracy of pathological images is crucial to the diagnosis of breast cancer, in order to reduce the error of manual diagnosis and improve the automatic classification accuracy of pathological images, this paper proposes a high-accuracy breast cancer classification method based on multi-scale attention mechanism enhanced Res2Net. By constructing a multi-channel residual connection in the residual block, and introducing a convolutional attention mechanism to enhance the feature extraction ability of Res2Net, and using group convolution to replace part of the ordinary convolution. In addition, since the channel information interaction across groups cannot be realized in the group convolution, which reduces the feature extraction ability. In this paper, the channel shuffling operation is used to reorganize the feature maps after the group convolution to achieve the information interaction between different groups. The evaluation results on the BreaKHis dataset show that, the accuracy and precision of the method in this paper have reached 98.5% and 98.9% respectively, in binary classification of histopathological images compared with the benchmark method, and the advantages of recall rate and F1 value are also more obvious. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Image classification

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Landslide Sensitivity Mapping Based on One-Dimensional Residual Convolutional Neural Networks

Landslide Sensitivity Mapping Based on One-Dimensional Resid...

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2022 Chinese Automation Congress, CAC 2022

作者： Ke, Yougang Lu, Chengda Wu, Min Yu, Wanke Niu, Ruiqing School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Institute of Geophysics and Geomatics China University of Geosciences Wuhan China

ISBN: (纸本)9781665465335

Landslide is a common geological disaster. Landslide sensitivity mapping (LSM) is the key technology for landslide monitoring, early warning and risk assessment. Deep learning shows good performance in feature extraction. This paper proposes a one-dimensional residual convolution neural network (1DRCNN), which takes Yunyang County, Chongqing City, China, located in the Three Gorges Reservoir area as the research area. Extracting 12 evaluation factors from multi-source remote sensing data and building a training set. The spatial probability of landslide occurrence is quantitatively predicted by the proposed model, and finally, the landslide sensitivity mapping is generated. Compared with the common machine learning models SVM and logistic regression, the results show that the AUC (area under curve) and accuracy of 1D-RCNN are 0.9860 and 93.38%, respectively, which proving that this method is effective and can provide a reference for disaster prevention and reduction. © 2022 IEEE.

关键词： Landslides

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A Cyclic Small Phase Theorem for MIMO LTI systems*

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IFAC-PapersOnLine 2023年第2期56卷 1883-1888页

作者： Chao Chen Wei Chen Di Zhao Jianqi Chen Li Qiu Department of Electronic and Computer Engineering The Hong Kong University of Science and Technology Hong Kong China Department of Mechanics and Engineering Science & State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China Department of Control Science and Engineering & Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai China

This paper introduces a brand-new phase definition called the segmental phase for multi-input multi-output linear time-invariant systems. The underpinning of the definition lies in the matrix segmental phase which, as its name implies, is graphically based on the smallest circular segment covering the matrix normalized numerical range in the unit disk. The matrix segmental phase has the crucial product eigen-phase bound, which makes itself stand out from several existing phase notions in the literature. The proposed bound paves the way for stability analysis of a cyclic feedback system consisting of multiple subsystems. A cyclic small phase theorem is then established as our main result, which requires the loop system phase to lie between -π and π. The proposed theorem complements the celebrated small gain theorem.

关键词： Small phase theorem segmental phase cyclic feedback systems stability analysis lead-lag compensation

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Framework and key Technologies for High-speed Railway Comprehensive Transport Hub

Framework and Key Technologies for High-speed Railway Compre...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Gang Xiong Wei Zhang Xiaoming Liu Zhiming Yuan Fenghua Zhu Zundong Zhang State Key Laboratory for Multimodal Artificial Intelligence Systems Chinese Academy of Sciences Beijing China School of Electrical and Control Engineering North China University of Technology Beijing China Communication Signal Research Institute China Academy of Railway Science Beijing China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing China

The surge in urban population density in China has underscored the vital role of high-speed rail and subway systems in urban transit. Comprehensive transportation hubs, notably high-speed rail passenger terminals, have emerged as linchpins for seamless multimodal transit both within and beyond urban centers. China's railway sector vigorously champions the innovative concept of "station-city integration" and has articulated a forward-looking "16-word policy" for modern railway stations: "Seamless integration, environmental friendliness, economic viability, and intelligent accessibility". The judicious allocation of resources and the augmentation of coordination and control capabilities within comprehensive transportation hubs are imperative for the harmonious evolution of urban transit. The implementation of intelligent control systems for transportation hubs has emerged as a pivotal area of research. This study delves into the framework and critical technologies for high-speed railway comprehensive transport hubs, encompassing various components and their intricate interplay, including transport modalities, infrastructure, travelers, environmental factors, and information systems, thus forming a prototypical cyber-physical-social system. Addressing the prevalent and pressing imperative for the advancement of "station-city integration" high-speed railway comprehensive transport hubs, this research endeavor aims to surmount bottleneck challenges and refine the oversight of passenger flows at high-speed rail terminals. The findings hold noteworthy theoretical import and portend promising practical applications.

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Muscle Synergy Analysis Based on NMF for Lower Limb Motor Function Assessment

Muscle Synergy Analysis Based on NMF for Lower Limb Motor Fu...

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2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Xiang, Kexin Wang, Weiqun Hou, Zeng-Guang Zhang, Chutian Wang, Jiaxing Shi, Weiguo Jiao, Yuze Lin, Tianyu The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China The School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China The School of Intelligence University of Chinese Academy of Sciences Beijing100049 China CASIA-MUST Joint Laboratory of Intelligence Science and Technology Institute of Systems Engineering Macau University of Science and Technology 999078 China Macau Institute of Systems Engineering Macau University of Science and Technology China The CASIAMUST Joint Laboratory of Intelligence Science and Technology Institute of Systems Engineering Macau University of Science and Technology China

ISBN: (纸本)9781665481090

Accurate rehabilitation assessments are essential for designing effective rehabilitation methods and helping patients recover better. It's well known that commonly used scale assessment methods for neurorehabilitation suffer from the issue of subjectivity, thus investigation of objective assessment methods is very necessary. Muscle synergy analysis can be uesd to assess limb motor functions from the perspective of neuromuscular control. In this paper, a method for evaluation of human lower limb motor functions based on muscle synergy analysis is presented. Muscle synergy modules are designed using surface electromyography (sEMG) signals of the subjects' lower limbs by non-negative matrix factorizations (NMF). By comparing the cosine similarities of these synergy modules, it can be seen that muscle synergies of healthy subjects and patients are significantly different, while they are similar among healthy subjects. Therefore, a reference synergy module (RSM) is designed by averaging the muscle synergy modules for healthy subjects, and the similarities can be calculated by comparing the synergy modules for healthy subjects or patients with the RSM. In the experiment carried out in this study, average similarities of the three synergy modules for healthy subjects are respectively 0.97166, 0.87368 and 0.84932, and on the other hand, the average similarities for the three synergy modules for patients are respectively 0.59979, 0.56426 and 0.69042. Therefore, the similarities for healthy subjects are much higher than those for SCI patients, which denotes that the similarity between an individual synergy module and the RSM can be used as an objective assessing index for evaluating patients' motor function. © 2022 IEEE.

关键词： Non-negative matrix factorization

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Autonomous Crowdsensing: Operating and Organizing Crowdsensing for Sensing Automation

arXiv

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arXiv 2024年

作者： Wu, Wansen Yang, Weiyi Li, Juanjuan Zhao, Yong Zhu, Zhengqiu Chen, Bin Qiu, Sihang Peng, Yong Wang, Fei-Yue College of Systems Engineering National University of Defense Technology Hunan Province Changsha410073 China Hunan Institute of Advanced Technology Hunan Province Changsha410073 China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China

—The precise characterization and modeling of Cyber-Physical-Social systems (CPSS) requires more comprehensive and accurate data, which imposes heightened demands on intelligent sensing capabilities. To address this issue, Crowdsensing Intelligence (CSI) has been proposed to collect data from CPSS by harnessing the collective intelligence of a diverse workforce. Our first and second Distributed/Decentralized Hybrid Workshop on Crowdsensing Intelligence (DHW-CSI) have focused on principles and high-level processes of organizing and operating CSI, as well as the participants, methods, and stages involved in CSI. This letter reports the outcomes of the latest DHW-CSI, focusing on Autonomous Crowdsensing (ACS) enabled by a range of technologies such as decentralized autonomous organizations and operations, large language models, and human-oriented operating systems. Specifically, we explain what ACS is and explore its distinctive features in comparison to traditional crowdsensing. Moreover, we present the "6A-goal" of ACS and propose potential avenues for future research. Copyright © 2024, The Authors. All rights reserved.

关键词： Cyber Physical System

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Thermoelastic Modeling and Transient Responses with Piezoelectric and Size Effects

SSRN

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SSRN 2024年

作者： Li, Si-Yang Wu, Hua Yu, Ya-Jun School of Mechanics Civil Engineering and Architecture Northwestern Polytechnical University Xi’an710072 China MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical University Xi’an710072 China School of Aeronautics Northwestern Polytechnical University Xi’an710072 China National Key Laboratory of Strength and Structural Integrity Xi’an710072 China

Generalized piezoelectric thermoelastic models play significantly important role in multi-field coupling analysis, especially in extreme environments, of nanosensors, nanogenerators and superconductivity. In this work, generalized thermoelastic theory is firstly proposed by considering higher-order thermal lagging and size effect. Then, unified generalized piezoelectric thermoelastic coupling model is obtained by further combining piezoelectric effect. Transient piezoelectric thermoelastic responses of piezoelectric materials under thermal shock are investigated. Numerical results are obtained from analytical solution in Laplace domain by adopting numerical inverse Laplace transform. The obtained results are graphically illustrated, from which the effects of lagging effect and size effect are clarified. This work provides theoretical model and numerical method to predict transient thermoelastic behaviors of piezoelectric materials across different time and space scales. © 2024, The Authors. All rights reserved.

关键词： Transient analysis

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Optimization of the Landslide Susceptibility Model based on Deep Forest and Twice-Sample

Optimization of the Landslide Susceptibility Model based on ...

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2022 Chinese Automation Congress, CAC 2022

作者： Yang, Yuelin Yu, Wanke Liu, Zepeng Zhao, Lingran Lu, Chengda Wu, Min Niu, Ruiqing China University of Geosciences School of Automation Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan China China University of Geosciences Institute of Geophysics and Geomatics Wuhan China

ISBN: (纸本)9781665465335

In the analysis of regional landslide susceptibility, the geological data used usually have the characteristics of multiplicity and nonlinearity. At the same time, in the past researches, the selection of non-landslide units in the training set is usually random or subjective, and there is no guarantee sample accuracy. In this paper, the deep forest algorithm combined with the twice-sample method is used to evaluate the landslide susceptibility in the Zigui Badong area of the Three Gorges Reservoir area. First, 11 landslide impact factors were selected according to the geological data to initially construct a sample set, and the cleaned data set was obtained by twice-sample. After dividing the training set and the test set, the deep forest model was used to predict the landslide susceptibility and evaluate the accuracy. The results show that the AUC of the susceptibility prediction model built using the deep forest is 1%-10% higher than that of GBDT, MLP and other methods, while the Twice-Sample method improves the AUC by 2%. © 2022 IEEE.

关键词： Landslides

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Tracking Performance of Networked systems with Limited Bandwidth and Colored Noise

Tracking Performance of Networked Systems with Limited Bandw...

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2022 Chinese Automation Congress, CAC 2022

作者： Zhang, Bin Jiang, Xiaowei Sun, Li Zhang, Xianhe School of Automation China University of Geosciences Wuhan430074 China Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China School of Statistics and Mathematics Zhongnan University of Economics and Law Wuhan430074 China School of Electrical Engineering and Automation Hubei Normal University Huangshi435002 China

ISBN: (纸本)9781665465335

This study investigated the optimal tracking performance (OTP) of multi-input multi-output (MIMO), discrete- time networked control systems (NCSs). The limits of tracking performance (TP) under the influences of bandwidth, encoding- decoding, and additive coloured Gaussian noise (ACGN) are derived using the techniques of coprime decomposition and all-pass decomposition. The results reveal the negative impact of non-minimum phase (NMP) zeros and unstable poles of the plant as well as network communication constraints on the TP of NCSs. Finally, a numerical simulation is discussed and verifies our conclusions. © 2022 IEEE.

关键词： Networked control systems

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Voltage-controlled robust topological states in perforated beams

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engineering Structures 2025年 338卷

作者： Hong, Fang Zhang, Kai Yao, Yuxin Tang, Lihua Deng, Zichen School of Mechanics Civil Engineering and Architecture Northwestern Polytechnical University Xi'an710072 China MIIT Key Laboratory of Dynamics and Control of Complex Systems Northwestern Polytechnical University Xi'an710072 China Department of Mechanical and Mechatronics Engineering University of Auckland 20 Symonds Street Auckland1010 New Zealand

Topological metamaterials possess waveguiding and energy concentration properties even under perturbations such as defects or disorders. Tunable topological materials offer enhanced flexibility to these properties. In this study, a voltage-controlled strategy is presented to realize the tunable robust topological states. First, a perforated beam with piezoelectric patches and additional steel columns is proposed to analyze the topological properties, and the corresponding numerical model based on Timoshenko beam theory is introduced to analyze the band gap properties and transmission spectra by spectral element method (SEM). Then the effects of the applied voltage on the resonance frequency and equivalent stiffness of piezoelectric patches are characterized. Two new band gaps emerge around the locally resonant band gap and topological phase transition can be achieved by altering the collective displacement of the perforations and resonators. Subsequently, the finite element simulations are presented to validate the accuracy of SEM results, and the equivalent voltage-controlled stiffness is used in SEM to simplify the relationship between voltage and topological properties. The Zak phase calculations demonstrate the topological properties of opened band gaps and further indicate the existence of topologically protected interface states (TPISs). Finally, the transmission spectra are used to analyze the characteristics of TPISs, and the robustness of TPISs is examined by introducing different perturbation factors. The results show that the frequency of topological states can be simply tuned by varying the voltage on the piezoelectric patch, and the topological rainbow trapping can be realized in a designed gradient system without changing the geometric configuration. © 2025 Elsevier Ltd

关键词： Metamaterials

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