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Consensus control of Multi-Agent Systems With Two-Way Switching Directed Topology ⁎

IFAC-PapersOnLine 2020年第5期53卷 669-674页

作者： Xin Wang Qinglai Wei Ruizhuo Song The 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

In this paper, a novel control protocol method is developed to solve distributed consensus control problems for multi-agent systems with switching directed topologies. Because of the external disturbance, the information cannot transmit completely so that the proposition of two-way topology is necessary. Besides, the external disturbance is considered naturally and we give a control protocol and parameters of noise intensity function in this paper. Furthermore, an example is given to support the proposed theorem. Finally, the simulation results prove the correctness of the theory.

关键词： Distributed consensus control multi–agent systems two–way topology fixed switching directed topologies

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Fault Diagnosis Method of Motor Bearing Based on Information Entropy and Multi-scale Wavelet Entropy

Fault Diagnosis Method of Motor Bearing Based on Information...

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computer Information Science and Artificial Intelligence (CISAI), International Conference on

作者： Xiaotong Wang Huixiang Dai Zhou Zhang International Education Institute North China Electric Power University Beijing China Electrical Engineering Institute North China Electric Power University Baoding China School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (纸本)9781665406932

The bearing condition of electrical equipment has a great impact on the reliability of the power system operation. The operating conditions of electrical equipment are complex and variable, and the vibration signal of its bearings is unstable and non-linear. The traditional time-domain characteristics are not longitudinally comparable, and it is impossible to discern whether the vibration changes come from the inner ring, outer ring or rolling body of the bearing when only using the time-domain characteristics. To solve this problem, a method of extracting characteristic parameters of vibration signal by multi-scale wavelet entropy and information entropy is further introduced in this paper. The multi-scale wavelet entropy and information entropy of bearing vibration signals in different states are used as the training set of the model. And the fault state recognition model of the electrical equipment is established by training the support vector machine (SVM) model. After wavelet entropy and information entropy feature extraction, the training time is considerably shortened, and the diagnosis accuracy is significantly improved, which shows that the method is effective and practical for the fault diagnosis of electrical equipment and provides a new idea for fault diagnosis of electrical equipment.

关键词： Support vector machines Vibrations Training Fault diagnosis Wavelet domain Feature extraction Entropy

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Shifting dynamics of self-immolation in the capital of Iran? The rising trend among young, unmarried, less-educated men

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Burns Open 2025年 11卷 100406-100406页

作者： Shokri, MohammadAli Khalili, SaeedehSadat Vahabie, Abdol-Hossein Ghanbari Jolfaei, Atefeh Keshavarz-Akhlaghi, Amir-Abbas Dehmardei, Mostafa Mirfazeli, Fatemeh Sadat National Brain Centre Iran University of Medical Sciences Tehran Iraq Department of Neuroscience Faculty of Advanced Technologies in Medicine Iran University of Medical Sciences Tehran Iraq Cognitive Systems Laboratory Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iraq Mental Health Research Center Psychosocial Health Research Institute Department of Psychiatry School of Medicine Iran University of Medical Sciences Tehran Iraq School of Medicine Iran University of Medical Sciences Tehran Iraq Department of Cognitive Sciences Faculty of Psychology and Education University of Tehran Tehran Iraq School of Cognitive Sciences Institute for Research in Fundamental Sciences (IPM) Tehran Iraq

In our study, we aimed to explore the psychiatric disorders, risk factors, and predictors of self-immolation among individuals admitted to Shahid Motahari Hospital in Tehran from 2019 to 2020. This cross-sectional study examines 64 hospitalized patients who received psychiatric counseling following self-immolation incidents. The rate of self-immolation varies significantly based on specific demographics. It is observed that in our population men had a higher rate of being unmarried (70.96 % vs 15.15 %), lower levels of education (70.96 % vs 63.63 % did not have a university degree), higher level of unemployment (54.83 % vs 30.30 %), younger age average with most men aging 15–24 (29.06 (SD = 9.33)) vs women 35–44 (35.27(SD = 10.27)) and higher prevalence of addiction (67.74 % vs 36.36 %) compared to women. On the other hand, women who attempted self-immolation mainly were married, involved in housekeeping, and tended to exhibit higher rates of depression (63.63 % vs 32.25 %) than men. Furthermore, these self-immolation incidents are often impulsive (64.1 %) and occur shortly (under an hour) after experiencing a stressor (39.1 %). Self-immolation accidents are frequently carried out using gasoline (50 %). Geographically, the majority of self-immolation cases of our study are concentrated in the central region of Iran (76.6 %), followed by the western region (15.6 %) this may be due to the proximity of these regions to our center while patients of other regions were hospitalized in their referral hospitals and were rarely transferred to the capital. To effectively address the issue of self-immolation and reduce its prevalence, it is essential to identify vulnerable populations and explore targeted preventive measures. Based on our findings, future pilot studies could investigate the feasibility of specific interventions, such as crisis hotlines to reduce impulsivity-related acts of self-immolation. Additionally, small-scale feasibility projects could explore the effect

关键词： Contributing factors Psychiatric disorders Self-immolation

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A precision diagnostic framework of renal cell carcinoma on whole-slide images using deep learning

arXiv

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arXiv 2021年

作者： Wu, Jialun Zhang, Haichuan Gao, Zeyu Bao, Xinrui Gong, Tieliang Wang, Chunbao Li, Chen School of Computer Science and Technology Xi’an Jiaotong University Xi’an China National Engineering Lab for Big Data Analytics Xi’an Jiaotong University Xi’an China School of Electrical Engineering and Computer Science Pennsylvania State University University Park PA United States School of Automation Science and Engineering Xi’an Jiaotong University Xi’an China Department of Pathology The First Affiliated Hospital of Xi’an Jiaotong University Xi’an China

Diagnostic pathology, which is the basis and gold standard of cancer diagnosis, provides essential information on the prognosis of the disease and vital evidence for clinical treatment. Tumor region detection, subtype and grade classification are the fundamental diagnostic indicators for renal cell carcinoma (RCC) in whole-slide images (WSIs). However, pathological diagnosis is subjective, differences in observation and diagnosis between pathologists is common in hospitals with inadequate diagnostic capacity. The main challenge for developing deep learning based RCC diagnostic system is the lack of large-scale datasets with precise annotations. In this work, we proposed a deep learning-based framework for analyzing histopathological images of patients with renal cell carcinoma, which has the potential to achieve pathologist-level accuracy in diagnosis. A deep convolutional neural network (InceptionV3) was trained on the high-quality annotated dataset of The Cancer Genome Atlas (TCGA) whole-slide histopathological image for accurate tumor area detection, classification of RCC subtypes, and ISUP grades classification of clear cell carcinoma subtypes. These results suggest that our framework can help pathologists in the detection of cancer region and classification of subtypes and grades, which could be applied to any cancer type, providing auxiliary diagnosis and promoting clinical consensus. © 2021, CC BY.

关键词： Classification (of information)

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Estimation of roof photovoltaic potential and carbon reduction potential based on semantic segmentation method

Estimation of roof photovoltaic potential and carbon reducti...

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Sustainable Power and Energy Conference (iSPEC)

作者： Yan Huang Han Ding Jiaming Chen Yunkang Chen Suchuan Quan Yongkang Zhu School of Software(Suzhou) Southeast University Suzhou China State Grid Wuxi Power Supply Company Wuxi China School of Electrical and Electronic Engineering Southeast University Nanjing China School of information science and technology Nanjing Forestry University Nanjing China School of computer science and technology Nanjing University of Aeronautics and Astronautics Nanjing China School of Electrical and Automation Engineering Nanjing Normal University Nanjing China

ISBN: (纸本)9781665414401

Since industrialization, the global surface temperature has been on an upward trend, and so far it has had a serious impact on the global ecosystem and socio-economic environment. Therefore, it is necessary to reduce carbon emissions through global joint efforts, maintain the stability of the surface temperature not exceeding 2°C, and achieve global carbon neutrality as soon as possible. Solar energy is the cleanest renewable energy and has good prospects for sustainable development in the future. Installing solar photovoltaic (PV) systems on the roofs of buildings has become the most extensive method of utilizing solar energy. In this study, we used the semantic segmentation method to estimate the solar photovoltaic potential based on identifying roofs from remote sensing images, and then combined the photovoltaic module parameters derived from building features with solar radiation data to evaluate the solar photovoltaic potential. We did experiments in Haizhou Economic Development Zone, Lianyungang City, Jiangsu Province. The results show that the number of available roofs of the photovoltaic system is 671, the available roof area is 925,810 square meters, and the annual photovoltaic power generation potential of the study area is 119,300.97 MW$\cdot$h/year, which has a large solar photovoltaic potential. The method to perform precise calculation of specific rooftop solar PV potential developed in this study will guide the formulation of energy policy for solar PV in the future.

关键词： Photovoltaic systems Image segmentation Semantics Buildings Urban areas Solar energy Carbon dioxide

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Finite sample guarantees for quantile estimation: An application to detector threshold tuning

arXiv

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arXiv 2021年

作者： Umsonst, David Ruths, Justin Sandberg, Henrik The Division of Decision and Control Systems The School of Electrical Engineering and Computer Science The KTH Royal Institute of Technology Stockholm10044 Sweden The Department of Mechanical Engineering The University of Texas at Dallas 800 W. Campbell Rd RichardsonTX United States

In threshold-based anomaly detection, we want to tune the threshold of a detector to achieve an acceptable false alarm rate. However, tuning the threshold is often a non-trivial task due to unknown detector output distributions. A detector threshold that provides an acceptable false alarm rate is equivalent to a specific quantile of the detector output distribution. Therefore, we use quantile estimators based on order statistics to estimate the detector threshold. The estimation of quantiles from sample data has a more than a century long tradition and we provide three different distribution-free finite sample guarantees for a class of quantile estimators. The first is based on the Dworetzky-Kiefer-Wolfowitz inequality, the second utilizes the Vysochanskij-Petunin inequality, and the third is based on exact confidence intervals for a beta distribution. These guarantees are then compared and used in the detector threshold tuning problem. We use both simulated data as well as data obtained from an experimental setup with the Temperature control Lab to validate the guarantees provided. Copyright © 2021, The Authors. All rights reserved.

关键词： Sampling

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Stealthy False Data Injection Attacks against Extended Kalman Filter Detection in Power Grids

Stealthy False Data Injection Attacks against Extended Kalma...

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International Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)

作者： Yifa Liu Wenchao Xue Shuping He Long Cheng State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China Key Laboratory of System and Control Academy of Mathematics and System Science Chinese Academy of Sciences Beijing China School of Electrical Engineering and Automation Anhui University Hefei China

ISBN: (纸本)9781665402460

The power grid is a kind of national critical infrastructure directly affiliated to human daily life. Because of the vital functions and potentially significant losses, the power grid becomes an excellent target for many malicious attacks. Due to the special nonlinear measurements, many detection methods do not match the grid very well. The extended Kalman filter based detection is one of the few methods suitable for nonlinear system detection, and therefore can be used in power system to spot malicious attacks. However, the reliability and effectiveness of the extended Kalman filter based detection have not been fully studied and adequately guaranteed. By proposing a two-step false data injection attack strategy, this paper gives a stealthy way to inject false data of increasing magnitude into the power grid, which can eventually cause a certain degree of deviation of the grid state without being detected. In the simulation, the method proposed in this paper caused a voltage deviation of more than 25% before being discovered in the power system.

关键词： Power measurement Cyber-physical systems Information filters Power grids Safety Power system reliability Kalman filters

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PIMIP: An open source platform for pathology information management and integration

arXiv

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arXiv 2021年

作者： Wu, Jialun Mao, Anyu Bao, Xinrui Zhang, Haichuan Gao, Zeyu Wang, Chunbao Gong, Tieliang Li, Chen School of Computer Science and Technology Xi’an Jiaotong University Xi’an China National Engineering Lab for Big Data Analytics Xi’an Jiaotong University Xi’an China School of Automation Science and Engineering Xi’an Jiaotong University Xi’an China School of Electrical Engineering and Computer Science Pennsylvania State University University ParkPA United States Department of Pathology First Affiliated Hospital of Xi’an Jiaotong University Xi’an China

Digital pathology plays a crucial role in the development of artificial intelligence in the medical field. The digital pathology platform can make the pathological resources digital and networked, and realize the permanent storage of visual data and the synchronous browsing processing without the limitation of time and space. It has been widely used in various fields of pathology. However, there is still a lack of an open and universal digital pathology platform to assist doctors in the management and analysis of digital pathological sections, as well as the management and structured description of relevant patient information. Most platforms cannot integrate image viewing, annotation and analysis, and text information management. To solve the above problems, we propose a comprehensive and extensible platform, PIMIP (Pathology Information Management & Integration Platform). Our PIMIP has developed the image annotation functions based on the visualization of digital pathological sections. Our annotation functions support multi-user collaborative annotation and multi-device annotation, and realize the automation of some annotation tasks. In the annotation task, we invited a professional pathologist for guidance. We introduce a machine learning module for image analysis. The data we collected included public data from local hospitals and clinical examples. Our platform is more clinical and suitable for clinical use. In addition to image data, we also structured the management and display of text information. So our platform is comprehensive. The platform framework is built in a modular way to support users to add machine learning modules independently, which makes our platform extensible. © 2021, CC BY.

关键词： Information management

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Master equation emulation and coherence preservation with classical control of a superconducting qubit

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Physical Review A 2022年第6期106卷 062620-062620页

作者： Evangelos Vlachos Haimeng Zhang Vivek Maurya Jeffrey Marshall Tameem Albash E. M. Levenson-Falk Department of Physics and Astronomy Dornsife College of Letters Arts and Sciences University of Southern California Los Angeles California 90089 USA Center for Quantum Information Science & Technology University of Southern California Los Angeles California 90089 USA Department of Electrical Engineering Viterbi School of Engineering University of Southern California Los Angeles California 90089 USA Quantum Artificial Intelligence Laboratory (QuAIL) NASA Ames Research Center Moffett Field California 94035 USA USRA Research Institute for Advanced Computer Science (RIACS) Mountain View California 94043 USA Department of Electrical and Computer Engineering University of New Mexico Albuquerque New Mexico 87131 USA Department of Physics and Astronomy and Center for Quantum Information and Control University of New Mexico Albuquerque New Mexico 87131 USA

Open quantum systems are a topic of intense theoretical research. The use of master equations to model a system's evolution subject to an interaction with an external environment is one of the most successful theoretical paradigms. General experimental tools to study different open system realizations have been limited, and so it is highly desirable to develop experimental tools which emulate diverse master equation dynamics and give a way to test open systems theories. In this paper we demonstrate a systematic method for engineering specific system-environment interactions and emulating master equations of a particular form using classical stochastic noise in a superconducting transmon qubit. We also demonstrate that non-Markovian noise can be used as a resource to extend the coherence of a quantum system and counteract the adversarial effects of Markovian environments.

关键词： Open quantum systems & decoherence Quantum control Quantum engineering Quantum simulation Superconducting qubits Quantum master equation

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MoTransFrame:Model Transfer Framework for CNNs on Low-Resource Edge Computing Node

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computers, Materials & Continua 2020年第12期65卷 2321-2334页

作者： Panyu Liu Huilin Ren Xiaojun Shi Yangyang Li Zhiping Cai Fang Liu Huacheng Zeng National University of Defense Technology Changsha410073China Training and Administration Department the Central Military CommissionBeijing100851China Department of Science and Technology China Electronics Technology Group CorporationBeijing100846China National Engineering Laboratory for Public Safety Risk Perception and Control by Big Data Beijing100041China School of Design Hunan UniversityChangsha410082China Department of Electrical and Computer Engineering University of LouisvilleLouisvilleKY 40292USA

Deep learning technology has been widely used in computer vision,speech recognition,natural language processing,and other related *** deep learning algorithm has high precision and high ***,the lack of resources in the edge terminal equipment makes it difficult to run deep learning algorithms that require more memory and computing *** this paper,we propose MoTransFrame,a general model processing framework for deep learning *** of designing a model compression algorithm with a high compression ratio,MoTransFrame can transplant popular convolutional neural networks models to resources-starved edge devices promptly and *** the integration method,Deep learning models can be converted into portable projects for Arduino,a typical edge device with limited *** experiments show that MoTransFrame has good adaptability in edge devices with limited *** is more flexible than other model transplantation *** can keep a small loss of model accuracy when the number of parameters is compressed by tens of *** the same time,the computational resources needed in the reasoning process are less than what the edge node could handle.

关键词： Edge computing convolutional neural network model transformation model compression

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