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Research Square 2021年

作者： Zhang, Yijin Li, Honggang Jin, Maoming Lin, Zongbing Nanjing Changjiang Waterway Engineering Bureau China Key Lab of Intelligent Analysis and Decision on Complex Systems Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing University of Posts and Telecommunications Chongqing400065 China Pass College Chongqing Technology and Business University Chongqing401520 China Institute of Nonlinear Analysis Research Changjiang Normal University Chongqing400803 China School of Mathematics and Computer Science Panzhihua University Panzhihua617000 China

In this paper, a new concept, the fuzzy rate of an operator in linear spaces is proposed for the very first time. Some properties and basic principles of it are studied. Fuzzy rate of an operator B which is specific i... 详细信息

关键词： Membership functions

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Exponentially Convergent Algorithm Design for Constrained Distributed Optimization via Non-smooth Approach

arXiv

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arXiv 2020年

作者： Li, Weijian Zeng, Xianlin Liang, Shu Hong, Yiguang Department of Automation University of Science and Technology of China HefeiAnhui230027 China Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China Key Laboratory of Knowledge Automation for Industrial Processes of Ministry of Education School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China Institute of Artificial Intelligence University of Science and Technology Beijing Beijing100083 China

We consider minimizing a sum of non-smooth objective functions with set constraints in a distributed manner. As to this problem, we propose a distributed algorithm with an exponential convergence rate for the first time. By the exact penalty method, we reformulate the problem equivalently as a standard distributed one without consensus constraints. Then we design a distributed projected subgradient algorithm with the help of differential inclusions. Furthermore, we show that the algorithm converges to the optimal solution exponentially for strongly convex objective functions. Copyright © 2020, The Authors. All rights reserved.

关键词： Constrained optimization

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ORB-Based Fast Anti-Viewing Image Feature Matching Algorithm

ORB-Based Fast Anti-Viewing Image Feature Matching Algorithm

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2018 Chinese Automation Congress, CAC 2018

作者： Oi, Liangliang Liu, Wei Liu, Ding Crystal Growth Equipment and System Integration Engineering Research Center Laboratory for Complex System Control and Intelligent of Information Processing Xi'An University of Technology Xi'an710048 China

ISBN: (纸本)9781728113128

Aiming at the problem that the original ORB algorithm is difficult to solve the effective matching problem under large angle of view transformation. This paper proposes an image feature matching algorithm based on ORB to resist the change of view according to the principle of ASIFT. The basic idea of the algorithm is as follows, Firstly, the longitude angle and latitude angle caused by the rotation of the camera are simulated, and the simulated image sequence set which is deformed by the change of the optical axis direction of the camera is accurately simulated. Then the feature points are extracted and mapped them into the original image by combining the FAST feature point detection method with the BRISK feature descriptors. Finally, the Brute-Force Matcher and the Random Sampling Consistency (RANSAC) method were used for feature matching and optimization. The experimental results show that the proposed algorithm can solve the problem that the image features cannot be matched under the large change of viewing angle (greater than 60°), and it has a significant improvement in real-time performance compared with ASIFT. © 2018 IEEE.

关键词： Cameras

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Fault Diagnosis of SOFC Stack Based on Neural Network Algorithm

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Energy Procedia 2019年 158卷 1798-1803页

作者： Tao Xue Xiaolong Wu Yuanwu Xu Suwen Jing Zehua Li Jianhua Jiang Zhonghua Deng Xiaowei Fu Li Xi School of Automation Key Laboratory of Education Ministry for Image Processing and Intelligent Control Huazhong University of Science & Technology Wuhan 430074 China College of Computer Science and Technology Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan University of Science and Technology Wuhan 430065 China

To realize the commercialization of SOFC, it must be ensured that it can work efficiently and stably. SOFC fault diagnosis becomes an essential part of the research. Due to the strong coupling of faults in the stack, this paper uses neural network algorithm to detect and diagnose faults. The simulation results verify that through the diagnosis of the test sample, the recognition rate of the test sample by the network is found to be 95%, which explains the neural network fault diagnosis model established in this paper on identifying the normal working state of the stack, the electrode stacking of the stack, and the gas leakage fault of the stack has good effectiveness and accuracy.

关键词： SOFC fault diagnosis neural network

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HRPGAN: A GAN-based Model to Generate High-resolution Remote Sensing Images 7

HRPGAN: A GAN-based Model to Generate High-resolution Remote...

引用

7th Annual International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2019

作者： Sun, Hai Wang, Ping Chang, Yifan Qi, Li Wang, Hailei Xiao, Dan Zhong, Cheng Wu, Xuelian Li, Wenbo Sun, Bingyu Co.Ltd Shanghai China Department of Airborne Remote Sensing National Disaster Reduction Center of China Beijing China Institute of Technology Innovation Hefei Institute of Physical Science Chinese Academy of Sciences Hefei China Third Research Institute of the Ministry of Public Security Shanghai China Guizhou Key Laboratory of Economics System Simulation Guizhou University of Finance and Economics Guiyang China Beijing Aerospace Flight Control Center Beijing China Institute of Intelligent Machines Chinese Academy of Sciences Hefei China

Generative adversarial networks (GAN) has been mainly used in the generation of natural images such as MNIST, CIFAR10 as well as Imagenet datasets and achieves satisfying generation results. However, GAN always fails in generating high quality high-resolution remote sensing images because remote sensing images are large in size and have various ground objects. To address this issue, a novel framework called High-Resolution PatchGAN (HRPGAN) is introduced in this paper. The structure of HRPGAN follows PatchGAN, but the batch normalization layers are removed and the ReLU activation is replaced by the SELU activation. In addition, a new loss function consisting of the adversarial loss, perceptual reconstruction loss and regularization loss is used in HRPGAN. Experiment results show that the proposed HRPGAN model generates the more diverse and lifelike images in HR remote sensing generation than Bicubic method and TGAN model. © Published under licence by IOP Publishing Ltd.

关键词： Chemical activation

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End-to-End AI-Based Point-of-Care Diagnosis system for Classifying Respiratory Illnesses and Early Detection of COVID-19

arXiv

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arXiv 2020年

作者： Belkacem, Abdelkader Nasreddine Ouhbi, Sofia Lakas, Abderrahmane Benkhelifa, Elhadj Chen, Chao Department of Computer and Network Engineering CIT UAEU UAE Department of Computer Science and Software Engineering CIT UAEU UAE Cloud Computing and Applications Reseach Lab Staffordshire University United Kingdom Key Laboratory of Complex System Control Theory and Application Tianjin University of Technology China

Respiratory symptoms can be a caused by different underlying conditions, and are often caused by viral infections, such as Influenza-like illnesses or other emerging viruses like the Coronavirus. These respiratory viruses, often, have common symptoms, including coughing, high temperature, congested nose, and difficulty breathing. However, early diagnosis of the type of the virus, can be crucial, especially in cases such as the recent COVID-19 pandemic. One of the factors that contributed to the spread of the pandemic, was the late diagnosis or confusing it with regular flu-like symptoms. science has proved that one of the possible differentiators of the underlying causes of these different respiratory diseases is coughing, which comes in different types and forms. Therefore, a reliable lab-free tool for early and more accurate diagnosis that can differentiate between different respiratory diseases is very much needed. This paper proposes an end-to-end portable system that can record data from patients with symptom, including coughs (voluntary or involuntary) and translate them into health data for diagnosis, and with the aid of machine learning, classify them into different respiratory illnesses, including COVID-19. With the ongoing efforts to stop the spread of the COVID-19 disease everywhere today, and against similar diseases in the future, our proposed low cost and user-friendly solution can play an important part in the early diagnosis. Copyright © 2020, The Authors. All rights reserved.

关键词： Diagnosis

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SmartPV-AIoT: an AIoT-integrated framework for fault diagnosis and remote monitoring in photovoltaic systems

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Energy Conversion and Management: X 2025年

作者： Ehtisham Lodhi Xiaoli Liu Gang Xiong M. Adil Khan Zeeshan Lodhi Tahir Nawaz Adil Dilawar Sasu Tarkoma Feiyue Wang Zhejiang University-University of Illinois Urbana-Champaign Institute International Campus Haining 314400 China The SKL for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Department of Computer Science University of Helsinki Helsinki 00560 Finland School of Transportation Fujian University of Technology Fuzhou China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China Department of Computer Science COMSATS University Islamabad Abbottabad Campus 22060 Pakistan Department of Electronics Technology University of Technology Nowshera 24100 Pakistan Department of Mechatronics Engineering National University of Sciences and Technology H-12 Islamabad 44000 Pakistan The SKL of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China The Beijing Engineering Research Center of Intelligent Systems and Technology Institute of Automation Chinese Academy of Sciences Beijing 100190 China

This paper presents SmartPV-AIoT, a cost-effective and edge-computing-based framework for real-time fault detection and environmental monitoring in photovoltaic (PV) systems. Addressing the challenges faced in remote or intermittently connected environments, the proposed system integrates electrical and environmental sensor data using a Raspberry Pi 4 and NodeMCU microcontroller. A lightweight Res-BiLSTM model, combining residual learning and bidirectional long short-term memory (BiLSTM) layers, is deployed at the edge to perform local fault classification by analyzing seven key parameters derived from I to V curve measurements and ambient conditions. Additionally, the framework employs multi-sensor data fusion by integrating voltage, current, irradiance, and temperature measurements to support comprehensive fault detection and predictive maintenance. The framework was validated on a 4.56  kW PV installation using a dataset of 2400 labeled samples representing normal operation, open-circuit, short-circuit, and partial shading conditions. The classifier achieved a fault detection accuracy of 96.67 %, with a maximum inference latency of 290  ms and low power overhead, making it suitable for real-time, on-site diagnostics. The system supports offline operation with automatic data synchronization upon connectivity restoration and includes mobile-based monitoring for remote accessibility. The proposed framework is designed for modular deployment and scales linearly with array size. Overall, SmartPV-AIoT offers a scalable, resilient, and practical solution for intelligent PV monitoring, particularly in resource-constrained or off-grid environments.

关键词： Photovoltaic (PV) Artificial Intelligence of Things (AIoT) Green energy resources Deep learning Fault detection Fault classification Monitoring system Edge intelligence

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A class of elliptic mixed boundary value problems with (p,q)-Laplacian: existence, comparison and optimal control

arXiv

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arXiv 2023年

作者： Zeng, Shengda Migórski, Stanislaw Tarzia, Domingo A. Zou, Lang Nguyen, Van Thien Guangxi Colleges Universities Key Laboratory of Complex System Optimization and Big Data Processing Yulin Normal University Yulin537000 China Department of Mathematics Nanjing University Jiangsu Nanjing210093 China Jagiellonian University in Krakow Faculty of Mathematics and Computer Science ul. Lojasiewicza 6 Krakow30348 Poland College of Applied Mathematics Chengdu University of Information Technology Sichuan Province Chengdu610225 China Jagiellonian University in Krakow Chair of Optimization and Control ul. Lojasiewicza 6 Krakow30348 Poland Depto. Matemática FCE Universidad Austral Paraguay 1950 RosarioS2000FZF Argentina CONICET Argentina School of Mathematics and Computational Science Xiangtan University Hunan Province Xiangtan City210000 China Department of Mathematics FPT University Education zone Hoa Lac High Tech Park Km29 Thang Long Highway Thach That ward Hanoi Viet Nam

The paper deals with two nonlinear elliptic equations with (p, q)-Laplacian and the Dirichlet-Neumann-Dirichlet (DND) boundary conditions, and Dirichlet-Neumann-Neumann (DNN) boundary conditions, respectively. Under mild hypotheses, we prove the unique weak solvability of the elliptic mixed boundary value problems. Then, a comparison and a monotonicity results for the solutions of elliptic mixed boundary value problems are established. We examine a convergence result which shows that the solution of (DND) can be approached by the solution of (DNN). Moreover, two optimal control problems governed by (DND) and (DNN), respectively, are considered, and an existence result for optimal control problems is obtained. Finally, we provide a result on asymptotic behavior of optimal controls and system states, when a parameter tends to *** Codes 35J25, 35J66, 35J92, 49J20, 35Bxx © 2023, CC BY.

关键词： Nonlinear equations

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Graph Optimization Based Long-distance GPS/IMU Integrated Navigation

Graph Optimization Based Long-distance GPS/IMU Integrated Na...

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第三十八届中国控制会议

作者： Xiaojie Gu Fengdi Zhang Jian Xu Qing Yuan Hongwei Ma Xiangdong Liu Zhen Li School of Automation and Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology Beijing Aerospace Automatic Control Institute National Key Laboratory of Science and Technology on Aerospace Intelligence Control Beijing

The accurate position estimation plays an critical role in the autonomous navigation for Micro Aerial Vehicles(MAV).Global positioning system(GPS) and inertial measurement unit(IMU) are two common sensors for navigation widely used on MAVs in the urban environment. Both of them have its distinct disadvantages that the GPS is susceptible to environmental interference and the IMU has accumulative errors. To overcome these problems, a GPS/IMU integrated system based on the factor graph optimization is developed in this paper. Unlike the conventional extended Kalman filter(EKF)-based method, the graph optimization method takes the whole trajectory into consideration so that it can achieve enough accuracy even after a long distance. Furthermore, the IMU preintegration method is used to avoid the repeated computation of high-rate IMU *** with the EKF method, the experimental results on the Zurich urban micro aerial vehicle dataset show the superior accuracy of the proposed factor graph optimization algorithm.

关键词： Global positioning system(GPS) inertial measurement unit(IMU) IMU preintegration graph optimization integrated navigation

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Intranasal hybrid vesicles delivering personalized in situ nano-vaccines induce glioblastoma remodeling to sensitize immunotherapy

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Nano Today 2025年 65卷

作者： Xue Wang Hanwen Zhang Mingzhi Han Fucai Chen Yingjie Zhang Kuanhan Feng Jinghuang Wang Yali Shi Peng Cao Liuqing Di Ruoning Wang State Key Laboratory on Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture Nanjing University of Chinese Medicine Nanjing 210023 China School of Pharmacy Jiangsu Provincial TCM Engineering Technology Research Center of High Efficient Drug Delivery System (DDS) Nanjing University of Chinese Medicine Nanjing 210023 China Department of Neurosurgery Qilu Hospital Cheeloo College of Medicine and Institute of Brain and Brain-Inspired Science Shandong University Jinan 250012 China

Personalized in situ tumor vaccine (PISTV), an attractive type of cancer immunotherapy, promotes a potent T cell anti-cancer immune response in multiple malignancies. Nevertheless, the limited cancer elimination efficacy of PISTV was exhibited in glioblastoma (GBM). Herein, an intranasal hybrid vesicle is designed based on ginseng-derived nanoparticles (GDNPs) fusing with liposomes, encapsulating shikosin (SKN), muscone, and MAN-CpG ODN (mCpG) to enable personalized in situ tumor vaccination for amplifying anti-GBM immune response. Following intranasal administration, the hybrid vesicles penetrated the nasal mucosal barrier and circumvented the blood-brain-barrier via the olfactory bulbar pathway. Subsequently, these nano-vaccines reached the tumor site, attributed to ginsenoside Rg3 in GDNPs. SKN-mediated whole tumor cell lysis served as a tumor-antigen pool to combine with immune adjuvant mCpG, resulting in the personalized in situ tumor vaccination, then recruiting dendritic cells (DCs) and promoting DCs maturation. Afterwards, DCs antigen presentation was enhanced to mobilize T cells, differentiating into cytotoxic T lymphocytes, thus inducing adaptive anti-tumor immunity. Furthermore, the GDNPs-mediated tumor-associated macrophages repolarization combines with SKN-blocked glycolytic pathway to reverse the immunosuppressive TME from “cold” into “hot”, thereby inducing innate immunity. We developed a nanoplatform that can deliver immunogenic cell death activators and Toll-like receptor agonists to antigen-capturing cells, synchronously conveying glycolysis inhibitors and TAM repolarization inducers to TME. This work demonstrated its robust capacity to activate innate and adaptive immune responses in distal metastasis, rechallenge, and humanized patient-derived xenograft tumor-bearing mice, providing a promising pathway for immunotherapeutic sensitization of GBM.

关键词： Glioblastoma Glycolysis inhibition Hybrid vesicles Immunosuppressive microenvironment In situ vaccines Intranasal administration

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