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2023 International Symposium on Ultrafast Phenomena and Terahertz Waves, ISUPTW 2023

作者： Guan, Hanxiao Qiu, Weihang Ma, Yehao Tian, Liangfei Cao, Yuqi Zhang, Guangxin College of Control Science and Engineering Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou China Zhejiang University College of Biomedical Engineering and Instrument Science Hangzhou China Ningbo University of Technology Robotics Institute Ningbo China

ISBN: (纸本)9798350317473

Terahertz technology is a non-invasive and label-free inspection method, promising for applications in various fields, especially in biomedical diagnosis. Terahertz radiation is capable for cell physiological and pathological status recognition due to its sensitivity to cell composition and structural information of biomacromolecular. In this paper, the transmission properties of glass, polymethyl methacrylate and polypropylene in THz regime were compared and polypropylene was selected as the petri dish material for cell adhesion due to its high transmission of terahertz wave. The time-domain and frequency-domain spectra, refractive index and absorption coefficient of hepatoma cell line Huh7 and normal cell line MIHA were analyzed. The experimental results showed significant distinction between the terahertz characteristic spectra of hepatoma cells and normal cells. This work can be helpful for applying terahertz technology in cancer detection at the cellular level. © 2023 IEEE.

关键词： Terahertz waves

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Class-Imbalance and Client-Imbalance Federated Learning for Fault Diagnosis

Class-Imbalance and Client-Imbalance Federated Learning for ...

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Data Driven control and Learning Systems (DDCLS)

作者： Shu Sun Jinchuan Qian Xinmin Zhang Zhihuan Song State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

With the development of big data, data-driven fault diagnosis models have experienced rapid growth. However, as the complexity of models increases, there is a corresponding rise in the demand for data. To obtain a substantial amount of data, traditional approaches involve centralizing datasets from multiple factories for training. However, due to heightened emphasis on data privacy from enterprises and regulatory bodies, this method becomes more challenging to implement and poses risks of data leakage. In response to this challenge, this paper designs a novel federated learning-based fault diagnosis modeling approach. Each local device trains its model on its local dataset and subsequently uploads updated model parameters to a central server for global model aggregation and updating. However, it is worth noting that in industrial processes, there may be concurrent class imbalance and data client imbalance, which brings challenges to fault diagnosis modeling based on federated learning. To address this challenge, we further propose a dynamic client aggregation fault diagnosis method based on category loss in federated learning. Experimental results indicate that the proposed approach not only protects data privacy in imbalanced class and client scenarios but also achieves outstanding fault recognition accuracy and robustness.

关键词： Fault diagnosis Training Data privacy Accuracy Federated learning Heuristic algorithms Data models

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Named Entity Recognition in Chinese Medical Texts Based on RoBERTa-WWM-IDCNN-CRF 25

Named Entity Recognition in Chinese Medical Texts Based on R...

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25th IEEE China Conference on System Simulation Technology and its Application, CCSSTA 2024

作者： Tang, Lan Kong, Jie Xu, Liang Xi'an Shiyou University School of Computer Xi'an China Tianjin University of Technology Tianjin Key Laboratory for Control Theory & Applications in Complicated Systems School of Electrical Engineering and Automation Tianjin China

ISBN: (纸本)9798350366600

Electronic medical records and doctor-patient conversations contain a wealth of useful information, such as disease symptoms, drug names, and cure cycles. Traditional deep learning approaches utilize bidirectional recurrent neural networks to encode text, which cannot effectively capture long-distance dependencies in text. In order to identify medical entity types in various texts more accurately, a named entity recognition approach based on RoBERTa-WWM-IDCNN-CRF is proposed. This approach introduces the RoBERTa-WWM pre-trained model, in order to improve the overall understanding of long Chinese texts for the first time. The model generates semantic representations containing prior knowledge. Then, the generated semantic representations are feed to the IDCNN to extract sentence level characteristics. Finally, the global optimal solution is obtained and the results of the named entity are produced through the CRF. The experiment indicates that the improvement of F1 score, accuracy, and recall of RoBERTa-WWM-IDCNN-CRF model are 7.94%, 4.52% and 10.02% comparing with the classical BiLSTM-CRF model. © 2024 IEEE.

关键词： Convolutional neural networks

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A Method for Scattering Removal in Three-Dimensional Fluorescence Spectra Based on Physics-Informed Neural Networks

A Method for Scattering Removal in Three-Dimensional Fluores...

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Chinese Automation Congress (CAC)

作者： Lingke Zhang Jie Yu Xingyu Fan Shuai Cao Oiuhao Zhang Guangxin Zhang State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Three-dimensional fluorescence spectroscopy offers high-dimensional information and rapid sensitivity, making it advantageous in fields such as environmental monitoring and food testing. However, scattering effects can hinder analysis accuracy, and traditional de-scattering methods often lead to signal loss and distortion. To overcome these issues, a denoising method based on a physics-informed neural network is proposed. This method includes a physical information reconstruction module that generates theoretical values approximating actual scattering values. Integrated into a GAN framework, this module uses physical quantities to guide the generator in producing physically consistent images, thus preserving material integrity after scattering removal. Tests on a self-built dataset show that this method achieves higher physical consistency compared to traditional methods.

关键词： Spectroscopy Temperature Neural networks Scattering Turbidity Fluorescence Wastewater Water resources Image reconstruction Testing

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Path Planning Algorithm for Manipulator Based on Manipulability-Maximizing

Path Planning Algorithm for Manipulator Based on Manipulabil...

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Data Driven control and Learning Systems (DDCLS)

作者： Rui Zhang Shan Liu State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798350361674

ISBN: (纸本)9798350361681

An improved path planning algorithm based on RRT* is proposed for the manipulator to generate a collision-free path for end-effector in this paper, which maximizes the manipulator's manipulability throughout the entire path. The algorithm introduces manipulability information as prior information to guide the RRT node toward desired regions. By introducing hybrid cost into improved RRT * algorithm, the path length is minimized while the expected manipulability is maximized. Finally, the end-effector path is transformed into a configuration trajectory by solving a multi-objective optimization problem. The simulation results compared with RRT * demonstrates the effectiveness of the proposed algorithm.

关键词： Learning systems Costs Simulation Cost function control systems End effectors Trajectory

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Relabeling Abnormal Videos via Intra-Video Label Propagation for Weakly Supervised Video Anomaly Detection

Relabeling Abnormal Videos via Intra-Video Label Propagation...

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Asian control Conference

作者： Wenhao Zhou Yingxuan Li Jiancheng Zhao Chunhui Zhao State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (数字)9789887581598

ISBN: (纸本)9798331540845

Weakly supervised video anomaly detection is chal-lenging due to the lack of frame-level labels in abnormal videos. Previous work generally formulates it as a multiple instance learning (MIL) problem, in which abundant snippets especially including hard snippets in abnormal videos are underutilized, causing the training process to be dominated by redundant easy snippets. In this work, we introduce a semi-supervised learning perspective and aim to provide reliable snippet-level labels for abnormal videos to fully leverage them. Specifically, we propose a relabeling strategy by utilizing the Label Propagation Network (LPN) to propagate labels from confident snippets to hard snippets. Considering label propagation tends to be fragile and inaccurate in this case due to incorrect pseudo labels, we develop a feature relation module to enhance the intra-class compactness and inter-class dispersion, as well as a label separation module to enlarge the discrepancy of propagated labels. The overall model is designed to be concise and universal, which can be applied to existing weakly supervised methods to improve performance. Extensive experiments demonstrate that our method achieves state-of-the-art results on three benchmark datasets.

关键词： Training Accuracy Semisupervised learning Benchmark testing Stability analysis Reliability Anomaly detection

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Catalytic destruction of chlorobenzene over K-OMS-2: Inhibition of high toxic byproducts via phosphate modification

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Journal of Environmental Sciences 2023年第5期127卷 844-854页

作者： Yunpeng Long Jiajia Liu Meiling Chen Renna Li Xiaole Weng Zhongbiao Wu Key Laboratory of Environment Remediation and Ecological Health Ministry of EducationCollege of Environmental and Resource SciencesZhejiang UniversityHangzhou 310058China Zhejiang Provincial Engineering Research Center of Industrial Boiler and Furnace Flue Gas Pollution Control Zhejiang University-Hangzhou Global Scientific and Technological Innovation CenterHangzhou 311200China

In the process of catalytic destruction of chlorinated volatile organic compounds(CVOCs),the catalyst is prone to chlorine poisoning and produce polychlorinated byproducts with high toxicity and persistence,bringing great risk to atmospheric environment and human *** solve these problems,this work applied phosphate to modify K-OMS-2 *** physicochemical properties of catalysts were determined by using X-ray powder diffraction(XRD),scanning electron microscope(SEM),X-ray photoelectron spectroscopy(XPS),hydrogen temperature programmed reduction(H_(2)-TPR),pyridine adsorption Fouriertransform infrared(Py-IR)and water temperature programmed desorption(H_(2)O-TPD),and chlorobenzene was selected as a model pollutant to explore the catalytic performance and byproduct inhibition function of *** results revealed that 1 wt.%phosphate modification yielded the best catalytic activity for chlorobenzene destruction,with the 90%conversion(T90)at approximately 247℃.The phosphating significantly decreased the types and yields of polychlorinated byproducts in *** phosphating,we observed significant hydroxyl groups on catalyst surface,and the active centerwas transformed into Mn(IV)-O…H,which promoted the formation of HCl,and enhanced the dechlorination ***,the enriched Lewis acid sites by phosphating profoundly enhanced the deep oxidation ability of the catalyst,which promoted a rapid oxidation of reaction intermediates,so as to reduce byproducts *** study provided an effective strategy for inhibiting the toxic byproducts for the catalytic destruction of chlorinated organics.

关键词： Catalytic destruction Chlorinated organics Phosphoric modification K-OMS-2 Secondary pollution

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State and Input Network Reconstruction for Heterogeneous Networked Dynamical Systems

State and Input Network Reconstruction for Heterogeneous Net...

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Chinese control and Decision Conference, CCDC

作者： Weiyang Sun Jinming Xu The State Key Laboratory of Industrial Control Technology The College of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798350387780

ISBN: (纸本)9798350387797

In this paper, we address the reconstruction problem of both state network and input network for heterogeneous networked dynamical systems (NDSs). Different from most existing works, we aim to identify networks of heterogeneous NDSs without assuming any prior knowledge of external input matrices. We first establish a sufficient condition for network reconstruction in noise-free scenarios leveraging an appropriately constructed matrix equation of which parameter matrices are constructed using external inputs and external outputs of heterogeneous NDSs. We develop an identification approach that allows us to accurately reconstruct the state and input networks simultaneously once the matrix equation permits a unique solution, which can be ensured by proper rank conditions. The proposed approach demonstrates its effectiveness in network reconstruction even in the presence of process noise. Finally, we numerically verify the efficacy of the proposed method under both noiseless and noisy conditions.

关键词： Knowledge engineering Sufficient conditions Noise Reconstruction algorithms Noise measurement Dynamical systems

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Topology Reconstruction of Heterogeneous Networked Dynamical Systems with Unknown Input Matrices

Topology Reconstruction of Heterogeneous Networked Dynamical...

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American control Conference (ACC)

作者： Weiyang Sun Jinming Xu Jiming Chen State Key Laboratory of Industrial Control Technology and the College of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (数字)9798350382655

ISBN: (纸本)9798350382662

We consider the topology reconstruction problem of heterogeneous networked dynamical systems (HNDSs) with unknown input matrices. In particular, we aim to reconstruct a heterogeneous network comprising a state interaction network (SIN) and an external input network (EIN), which differs from most existing works where the EIN network is assumed to be known a priori when reconstructing the SIN network. To this end, we employ subspace analysis to establish necessary-and-sufficient conditions for ensuring the solvability of the topology reconstruction problem of heterogeneous networks. Moreover, we develop a sufficient condition based on coupled matrix equations (CMEs), which allows us to exactly reconstruct both the SIN and EIN networks of the HNDS system when the CMEs permit a unique solution. A numerical example is provided to verify the effectiveness of the proposed method.

关键词： Sufficient conditions Accuracy Network topology Heterogeneous networks Topology Noise measurement Dynamical systems

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2024 China Automation Congress, CAC 2024

作者： Lang, Yumin Wu, Jiande Lang, Xun Yu, Wanke Yang, Chuanyan Su, Hongye Department of Electronic Engineering Information School Yunnan University Kunming China Yunnan Key Laboratory of Intelligent Systems and Computing Yunnan University Kunming China School of Automation China University of Geosciences Wuhan China State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (纸本)9798350368604

Oscillation is a significant indication of the deterioration of control system performance and needs to be carefully monitored to ensure safe and stable process operations. However, industrial processes are often prone to noisy artifacts and nonstationary trends, resulting in low signal-to-noise ratios. In order to tackle this problem, this study introduces a novel framework for enhanced trend removal and noise reduction, which is featured by the following steps:(i) The circulant singular spectrum analysis (CiSSA) is used to decompose oscillation data into several reconstructed components (RCs). (ii) The estimated power spectral density (PSD) ofthese RCs is then smoothed using the Savitzky-Golay filter (SGF) to eliminate noise and identify the RCs corresponding to oscillatory components. (iii) These identified RCs are subsequently reconstructed to produce purified oscillatory data. The effectiveness of the suggested approach is validated using simulations and real-world industrial case studies. The findings indicate that the method notably enhances the quality of oscillatory data. © 2024 IEEE.

关键词： Power spectral density

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