检索结果-内蒙古大学图书馆

SSRN 2024年

作者： Li, Jinyue Li, Yibin Lian, Jiadi Wei, Liejiang Zhang, Renhui College of Energy and Power Engineering Lanzhou University of Technology Lanzhou730050 China Key Laboratory of Advanced Pumps Valves and Fluid Control System of the Ministry of Education Lanzhou University of Technology Lanzhou730050 China College of Mechanical and Electrical Engineering China Jiliang University Hangzhou310018 China

With the intention of studying the self-priming process and the influencing factors of self-priming performance of vacuum cam pump, a self-priming performance test device suitable for high suction range pump is designed in this paper. By recording the change of the vacuum degree at inlet and the change of external characteristic parameters during the self-priming process, the influence of different speed (200rpm, 250rpm, 300rpm, 350rpm, 400rpm) on the self-priming performance and external characteristic parameters during the self-priming process was compared and analyzed when the inlet vacuum degree was 0.07MPa. According to the phase change of the Suction medium, the self-priming process is divided into three stages: inhale, gas-liquid mixed transport and steady operation. The results show that speed has a great influence on the self-priming process, which mainly reflects the change of external characteristic parameters. The influence on the self-priming performance is mainly manifested in the inhale stage, and the gap leakage has a great influence on the duration of the inhale stage. The high speed can effectively improve the gap leakage in the pump and improve the self-priming performance. © 2024, The Authors. All rights reserved.

关键词： Cams

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GVI: Guideable Visual Interpretation on medical tomographic images to improve the performance of deep network

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Pattern Recognition Letters 2025年 196卷 162-168页

作者： Hui Liu Fan Wei Lixin Yan Sushan Wang Chongfu Jia Lina Zhang Jiansheng Peng Yi Xu School of Control Science and Engineering Dalian University of Technology Dalian China Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian University of Technology Dalian China Liaoning Key Laboratory of Integrated Circuit and Biomedical Electronic System Dalian China Department of Cardiovascular Radiology The First Affiliated Hospital of Dalian Medical University Dalian China Department of Radiology The First Affiliated Hospital of Dalian Medical University Dalian China Department of Artificial Intelligence and Manufacturing Hechi University Hechi China

In medical image analysis, the demand for interpretable deep neural networks is rapidly growing. However, a major challenge is that most existing interpretative methods are applied after training, leading to a lack of integration with the model’s learning process. As a result, these methods often fail to highlight regions within complex medical images critical for decision-making, such as abnormal tissues or lesions, which are essential for accurate diagnoses and treatment planning. This paper introduces Guided Visual Interpretation (GVI), a framework designed to enhance both the performance and interpretability of deep networks. Building on a deep network model with image-level labels, GVI incorporates a small amount of pixel-level annotations combined with attention mechanisms. These mechanisms facilitate visual interpretation through forward propagation, directing the model’s focus to the most relevant regions. By aligning the network’s decision-making with human cognitive processes, GVI improves interpretability. In our study, an attention layer was added after the convolutional layers of a pre-trained classification network. GVI is trained using a mixed supervision approach that integrates pixel-level annotations with a large amount of image-level data. Experimental results on both private and public datasets show that GVI generates visual explanations consistent with human decision-making principles and achieves superior classification accuracy compared to traditional methods. These findings highlight GVI’s potential to improve interpretability and diagnostic performance in critical fields like medical imaging.

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Research and application of Transformer based anomaly detection model: A literature review

arXiv

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arXiv 2024年

作者： Ma, Mingrui Han, Lansheng Zhou, Chunjie Hubei Key Laboratory of Distributed System Security Hubei Engineering Research Center on Big Data Security School of Cyber Science and Engineering Huazhong University of Science and Technology Hubei Wuhan430074 China The Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Hubei Wuhan430074 China

Transformer, as one of the most advanced neural network models in Natural Language Processing (NLP), exhibits diverse applications in the field of anomaly detection. To inspire research on Transformer-based anomaly detection, this review offers a fresh perspective on the concept of anomaly detection. We explore the current challenges of anomaly detection and provide detailed insights into the operating principles of Transformer and its variants in anomaly detection tasks. Additionally, we delineate various application scenarios for Transformer-based anomaly detection models and discuss the datasets and evaluation metrics employed. Furthermore, this review highlights the key challenges in Transformer-based anomaly detection research and conducts a comprehensive analysis of future research trends in this domain. The review includes an extensive compilation of over 100 core references related to Transformer-based anomaly detection. To the best of our knowledge, this is the first comprehensive review that focuses on the research related to Transformer in the context of anomaly detection. We hope that this paper can provide detailed technical information to researchers interested in Transformer-based anomaly detection tasks. Copyright © 2024, The Authors. All rights reserved.

关键词： Anomaly detection

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Fourier Transform-based Wavenumber Domain 3D Imaging in RIS-aided Communication systems

arXiv

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arXiv 2024年

作者： Huang, Yixuan Yang, Jie Tang, Wankai Wen, Chao-Kai Jin, Shi The National Mobile Communications Research Laboratory Southeast University Nanjing210096 China The Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education The Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China The National Mobile Communications Research Laboratory The Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China The Institute of Communications Engineering National Sun Yat-Sen University Kaohsiung80424 Taiwan

Radio imaging is rapidly gaining prominence in the design of future communication systems, with the potential to utilize reconfigurable intelligent surfaces (RISs) as imaging apertures. Although the sparsity of targets in three-dimensional (3D) space has led most research to adopt compressed sensing (CS)-based imaging algorithms, these often require substantial computational and memory burdens. Drawing inspiration from conventional Fourier transform (FT)-based imaging methods, our research seeks to accelerate radio imaging in RIS-aided communication systems. To begin, we introduce a two-stage wavenumber domain 3D imaging technique: first, we modify RIS phase shifts to recover the equivalent channel response from the user equipment to the RIS array, subsequently employing traditional FT-based wavenumber domain methods to produce target images. We also determine the diffraction resolution limits of the system through k-space analysis, taking into account factors including system bandwidth, transmission direction, operating frequency, and the angle subtended by the RIS. Addressing the challenge of limited pilots in communication systems, we unveil an innovative algorithm that merges the strengths of both FT- and CS-based techniques by substituting the expansive sensing matrix with FT-based operators. Our simulation outcomes confirm that our proposed FT-based methods achieve high-quality images while demanding few time, memory, and communication resources. Copyright © 2024, The Authors. All rights reserved.

关键词： Fourier transforms

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ASTARS Aided NOMA Covert Communication Networks

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IEEE Transactions on Vehicular Technology 2025年

作者： Yue, Xinwei Song, Xinlong Zhao, Jingjing Huang, Chongwen Jin, Hongxu Xiang, Wei Key Laboratory of Information and Communication Systems Ministry of Information Industry Beijing102206 China Beijing Information Science and Technology University Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing102206 China Beihang University School of Electronic and Information Engineering Beijing100191 China Zhejiang University College of Information Science and Electronic Engineering Hangzhou310027 China Xidian University State Key Laboratory of Integrated Service Networks Xi'an710071 China Hangzhou310027 China Zunyi Normal University School of Information Engineering Zunyi563006 China La Trobe University School of Computing Engineering and Mathmatical Sciences MelbourneVIC3086 Australia

The active simultaneously transmitting and reflecting surface (STARS) has been proposed as a complement of passive STARS (PSTARS) to inhibit the double path-loss. This paper applies the active STARS (ASTARS) to aid in non-orthogonal multiple access (NOMA) covert communications over cascaded rice fading channels, where two wardens are located on the opposite sides of ASTARS to monitor the transmission information. More specifically, we derive approximate expressions for detection error probability of two wardens. The optimal detection threshold and minimum detection error probability are presented in the worst covert scenarios. The covert transmission rate expressions for a coupe of covert users are further deduced by taking into account imperfect/perfect successive interference cancellation. The experimental simulation results are presented to confirm that: 1) The detection error probability of ASTARS-NOMA networks is superior to that of ASTARS assisted-orthogonal multiple access (ASTARS-OMA) and PSTARS aided NOMA networks;2) As the number of active elements increases, the covert transmission rates of ASTARS-NOMA networks become larger relative to ASTARS-OMA;and 3) ASTARS-NOMA has ability to provide the enhanced system throughput in delay-tolerant transmission mode. © 2025 IEEE.

关键词： Fading channels

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Learning-Based Model Predictive Secondary Frequency control of Pv-Ess-Ev Microgrid

SSRN

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SSRN 2024年

作者： Zhong, Cheng Zhao, Hailong Liu, Yudong Liu, Chuang Key Laboratory of Modern Power System Simulation and Control &Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin Province Jilin132012 China Northeast Electric Power University College of Electrical Engineering Jilin Province Jilin132012 China

Microgrids comprising photovoltaic (PV), energy-storage systems and electric vehicles have received increasing attention. However, the increase in renewable energy sources, such as PVs, will introduce uncertainty factors to the frequency response, resulting in frequency fluctuations that can reduce power quality. Hence, we propose an outstanding learning-based control approach that combines a model of physical principles with a Gaussian Process (GP) learning approach. The learning model corrects the physical principles model and estimates its uncertainty. Simulations are performed by comparing the proposed controller with conventional model-predictive controllers. The results indicate that the learning-based controller proposed can adjust the frequency with less overshooting and a lower root mean square error compared to the conventional MPC control method. © 2024, The Authors. All rights reserved.

关键词： Model predictive control

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How Regulatory Orders and Public Fear Affect Vehicle Mobility Under Covid-19: A Global Perspective from Urban Overall Vehicles Using Multisource Data

SSRN

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SSRN 2024年

作者： Tang, Li Tang, Chuanli Luo, Hao He, Zhengbing Vehicle Measurement Control and Safety Key Laboratory of Sichuan Province Xihua University Chengdu China Engineering Research Center of Ministry of Education for Intelligent Air-Ground Fusion Vehicles and Control Xihua University Chengdu China School of Automobile and Transportation Xihua University Chengdu China Laboratory for Information and Decision Systems Massachusetts Institute of Technology CambridgeMA United States

As one of the largest pandemics in human history, COVID-19 has dealt a heavy blow to the global economy and social life. Although the pandemic situations in most countries have been stable, lessons are highly needed to learn to get more prepared for the future. In the field of transportation, the impact of COVID-19 on public transit and shared travel has been extensively studied with a relatively consistent conclusion. However, how and why the overall vehicle travel demand (including public and private) changes have not been fully addressed. This paper investigates the impact of COVID-19 on urban overall vehicle mobility as to the magnitude, duration, and driving factors. To this end, the Prophet time series model was introduced to predict vehicle mobility without COVID-19. By comparing the predicted with the real value, the mobility loss was obtained. The causes of the loss were deeply explored by applying multiple linear regression, especially focusing on the interaction effects of the strictness of regulatory orders and public fear. A large-scale dataset with more than 4 billion raw data was built for the empirical analysis from different sources, including a three-year city-level Automatic Number Plate Recognition data and data crawled from websites relating to explanatory variables. Results show that urban vehicle mobility loss almost all occurs during the national outbreak period, which is 29.66%. The factor that represents nationwide confirmed cases has a positive lagging effect on travel mobility loss, and the lag time is around seven days. Loss of urban motorized travel demand is largely caused by the interaction of perceived risks and control policy. The marginal effects of the factors work differently, indicating strong evidence of the existence of caution fatigue and shedding light on the impact mechanism. © 2024, The Authors. All rights reserved.

关键词： Multiple linear regression

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RIS-aided Single-frequency 3D Imaging by Exploiting Multi-view Image Correlations

arXiv

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arXiv 2024年

作者： Huang, Yixuan Yang, Jie Wen, Chao-Kai Jin, Shi The National Mobile Communications Research Laboratory Southeast University Nanjing210096 China The Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education The Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China The Institute of Communications Engineering National Sun Yat-sen University Kaohsiung80424 Taiwan The National Mobile Communications Research Laboratory The Frontiers Science Center for Mobile Information Communication and Security Southeast University Nanjing210096 China

Retrieving range information in three-dimensional (3D) radio imaging is particularly challenging due to the limited communication bandwidth and pilot resources. To address this issue, we consider a reconfigurable intelligent surface (RIS)-aided uplink communication scenario, generating multiple measurements through RIS phase adjustment. This study successfully realizes 3D single-frequency imaging by exploiting the near-field multi-view image correlations deduced from user mobility. We first highlight the significance of considering anisotropy in multi-view image formation by investigating radar cross-section properties and diffraction resolution limits. We then propose a novel model for joint multi-view 3D imaging that incorporates occlusion effects and anisotropic scattering. These factors lead to slow image support variation and smooth coefficient evolution, which are mathematically modeled as Markov processes. Based on this model, we employ the Expectation Maximization-Turbo-Generalized Approximate Message Passing algorithm for joint multi-view single-frequency 3D imaging with limited measurements. Simulation results reveal the superiority of joint multi-view imaging in terms of enhanced imaging ranges, accuracies, and anisotropy characterization compared to single-view imaging. Combining adjacent observations for joint multi-view imaging enables a reduction in the measurement overhead by 80%. Copyright © 2024, The Authors. All rights reserved.

关键词： Anisotropy

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Data-Driven Source Term Estimation of Hazardous Gas Leakages Under Variable Meteorological Conditions

SSRN

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SSRN 2024年

作者： Ni, Chuantao Lang, Ziqiang Wang, Bing Li, Ang Cao, Chenxi Du, Wenli Qian, Feng Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China Department of Automatic Control and System Engineering University of Sheffield SheffieldS1 3JD United Kingdom

Source term estimation (STE) of hazardous gas leakages in chemical industrial parks (CIPs) is important for addressing environmental pollution and improving engineering safety and reliability. For this purpose, some least squares-based STE methods have recently been developed, which performs the real-time STE using an off-line determined response matrix that represents the relationship between the sensor measurements and strengths of hazardous gas leakages. However, these methods require the number and locations of potential hazardous gas leakage sources are known a priori, which is difficult in many practical applications. To resolve this issue, in the present study, a novel multi-sensor data-driven STE (MSDD-STE) approach is proposed, which overcomes the difficulties with existing least squares-based STE methods and can, for the first time, address the MSDD-STE problems in complicated scenarios where meteorological conditions such as wind directions change over a considerable range. A detailed analysis is introduced to evaluate the performance of the proposed approach. The effectiveness of the proposed approach is verified by comprehensive numerical simulation studies. © 2024, The Authors. All rights reserved.

关键词： Least squares approximations

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Bald Eagle Search Algorithm for Parameter Identification of Proton Exchange Membrane Fuel Cell

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FRONTIERS IN ENERGY RESEARCH 2022年 10卷

作者： Yang, Bo Li, Danyang Zeng, Chunyuan Han, Yiming Li, Junhui Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin China Faculty of Electric Power Engineering Kunming University of Science and Technology Kunming China

A precise and reliable proton exchange membrane fuel cell (PEMFC) parameter identification performs an essential function in simulation analysis, optimal control, and performance research of actual PEMFC systems. Unfortunately, achieving an accurate, efficient, and stable parameter identification can sometimes be problematic for traditional optimization methods, owing to its strong coupling, inherent nonlinear, and multi-variable characteristics. Therefore, an advanced bald eagle search (BES) algorithm is designed to dependably identify the unknown parameters of the electrochemical PEMFC model in this work. For evaluating and analyzing the overall optimization performance of the BES comprehensively, it is compared with the genetic algorithm (GA) based on MATLAB under three cases. According to the simulation results, the optimum root mean square error (RMSE) achieved by BES is 96.27% less than that achieved by GA in parameter identification, which fully indicates that the precision, accuracy, and stability of the optimization results can be remarkably improved via the application of BES.

关键词： proton exchange membrane fuel cell parameter identification bald eagle search algorithm metaheuristic algorithm MATLAB

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