检索结果-内蒙古大学图书馆

15th International Conference Elektro, ELEKTRO 2024

作者： Cichorowski, Robert Kocikowska, Olga Bajtos, Marek Radil, Roman Janousek, Ladislav De Carrillo, Daria Gendosz Student, Sebastian Silesian University of Technology Faculty of Automatic Control Electronics and Computer Science Gliwice Poland Faculty of Automatic Control Electronics and Computer Science Department of Engineering and Systems Biology Gliwice Poland Silesian University of Medicine Faculty of Medical Sciences Department of Physiology Katowice Poland Faculty of Electrical Engineering and Informational Technology Department of Electromagnetic and Biomedical Engineering Žilina Slovakia Silesian University of Medicine Faculty of Medical Sciences in Zabrze Department of Histology Zabrze Poland Silesian University of Technology Biotechnology Center Gliwice Poland

ISBN: (纸本)9798350372359

This work presents the results of the examination of the HeLa cell line exposure on the ELF-EMF (extremely low-frequency electromagnetic field). In particular, the relationship between ELF-EMF exposition time and cell death. The examination of cell death hallmarks were examined by estimation levels of selected proteins - FACL4 (a protein that is a part of the ferroptosis pathway) and CK18 (Cytokeratin related to necrosis and apoptosis pathways) in the proposed model of workers exposed to ELF-EMF week. © 2024 IEEE.

关键词： Electromagnetic fields

来源：评论

学校读者我要写书评

暂无评论

Fault detection using state estimation and machine current signature analysis

UPB Scientific Bulletin, Series C: Electrical Engineering an...

引用

UPB Scientific Bulletin, Series C: Electrical Engineering and computer science 2021年第3期83卷 47-58页

作者： Gliga, Lavinius Ioan Popescu, Dumitru Chafouk, Houcine Faculty of Automatic Control and Computer Science "Politehnica" University of Bucharest Romania IRSEEM ESIGELEC UniRouen Normandy University France

Gearless wind turbines can be outfitted with Permanent Magnet Synchronous Generators. These may be affected by impairments. Machine Current Signature Analysis can be utilized to find these faults, as they insert additional harmonics. These manifestations also exist in the residuals of the generated currents, calculated via an Extended Kalman Filter. The Fast Fourier Transform is utilized to compute the residuals spectrum, to find these supplementary harmonics. In this work, the Goertzel Filter is proposed as a better substitute to the Fast Fourier Transform, for the fault detection of such a generator. The Goertzel Filter was implemented in MATLAB / Simulink and the obtained outcomes confirm its effectiveness. Moreover, a method to estimate the covariance matrix of process noise is briefly presented. This matrix is necessary for the implementation of a Kalman filter. © 2021, Politechnica University of Bucharest. All rights reserved.

关键词： Extended Kalman filters

来源：评论

学校读者我要写书评

暂无评论

Class Incremental Learning Method for Hyperspectral Images Based on Real Data Playback Mechanism and Classification Network Optimization 15th

Class Incremental Learning Method for Hyperspectral Images B...

引用

15th International Conference on Genetic and Evolutionary Computing, ICGEC 2023

作者： Liu, Xiaodong Wang, Siqi Liu, Huanyu Li, Junbao Department of Automatic Test and Control School of Electronics and Information Engineering Harbin Institute of Technology Harbin150080 China School of Computer Science and Technology Information Countermeasure Technique Institute Harbin Institute of Technology Harbin150080 China

ISBN: (纸本)9789819700677

In recent years, the hyperspectral image (HSI) classification has attracted great attention in the field of earth observation. With the expansion of application scenarios and the continuous improvement of application requirements, new classes of HSI continue to emerge. In the face of open and dynamic application scenarios, the model is required to be able to continuously learn new categories based on maintaining existing category knowledge. Class incremental learning algorithms have received extensive attention as key solutions to the problem above. In this paper, we use a regularization-based incremental learning algorithm, elastic weight consolidation (EWC) for class incremental learning for HSI classification. After data preprocessing to reduce data dimensions, we select new classes for research on class incremental learning. We combine 3D-2D convolutional structures and residual blocks as the classification network and use real data playback mechanism to improve class recognition accuracy and realize class incremental recognition of HSI data. We demonstrate the feasibility of the algorithm with extensive experiments based on three widely used hyperspectral datasets. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Learning algorithms

来源：评论

学校读者我要写书评

暂无评论

PointPillars Backbone Type Selection for Fast and Accurate LiDAR Object Detection

PointPillars Backbone Type Selection for Fast and Accurate L...

引用

International Conference on computer Vision and Graphics, ICCVG 2022

作者： Lis, Konrad Kryjak, Tomasz Embedded Vision Systems Group Computer Vision Laboratory Department of Automatic Control and Robotics AGH University of Science and Technology Al. Mickiewicza 30 Krakow30-059 Poland

ISBN: (纸本)9783031220241

3D object detection from LiDAR sensor data is an important topic in the context of autonomous cars and drones. In this paper, we present the results of experiments on the impact of backbone selection of a deep convolutional neural network on detection accuracy and computation speed. We chose the PointPillars network, which is characterised by a simple architecture, high speed, and modularity that allows for easy expansion. During the experiments, we paid particular attention to the change in detection efficiency (measured by the mAP metric) and the total number of multiply-addition operations needed to process one point cloud. We tested 10 different convolutional neural network architectures that are widely used in image-based detection problems. For a backbone like MobilenetV1, we obtained an almost 4x speedup at the cost of a 1.13% decrease in mAP. On the other hand, for CSPDarknet we got an acceleration of more than 1.5x at an increase in mAP of 0.33%. We have thus demonstrated that it is possible to significantly speed up a 3D object detector in LiDAR point clouds with a small decrease in detection efficiency. This result can be used when PointPillars or similar algorithms are implemented in embedded systems, including SoC FPGAs. The code is available at https://***/vision-agh/pointpillars-backbone. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Object detection

来源：评论

学校读者我要写书评

暂无评论

Bearing Fault Diagnosis Based on Wavelet Transform and Residual Shrinkage Network 5

Bearing Fault Diagnosis Based on Wavelet Transform and Resid...

引用

5th International Conference on computer Network, Electronic and Automation, ICCNEA 2022

作者： Bai, Xiaojun Ma, Zhenxi Meng, Gong Xi'an Technological University School of Computer Science and Engineering Xi'an China Control Institution Beijing Aerospace Automatic Beijing China

ISBN: (数字)9781665491099

ISBN: (纸本)9781665491099

Rolling bearings are frequently employed in machinery equipment, and the safely production of such equipment depend greatly on the properly work of bearing. Fault diagnosis of bearing is usually performed by means of vibration signal analysis, which are further divided into traditional analysis methods and machine learning based analysis methods. Traditional methods rely on expert knowledge, which makes it difficult to extract fault features, machine learning methods rely on huge volumes of data and need to eliminate the distraction of surrounding noise. This paper proposes a fault diagnosis method based on wavelet transform and deep residual shrinkage network. Firstly, transform the vibration signal into wavelet time-frequency map by wavelet transform method, and then expand data set by augment to create enough training samples, next, build a deep residual shrinkage network, and train the model for fault classification, thus implement the fault diagnosis task. Experiment shows that the accuracy of this model is superior to other comparable models, which reached 99.3% in low-noise environment, and 93.6% in high-noise environment. © 2022 IEEE.

关键词： Wavelet transforms

来源：评论

学校读者我要写书评

暂无评论

Multi-Platform Performance Analysis for CRUD Operations in Relational Databases from Java Programs using Spring Data JPA 13

Multi-Platform Performance Analysis for CRUD Operations in R...

引用

13th International Symposium on Advanced Topics in Electrical Engineering, ATEE 2023

作者： Bonteanu, Alexandru-Marius Tudose, Catalin Anghel, Ana Magdalena "politehnica" University of Bucharest Department of Computer Science Bucharest Romania Luxoft Romania Learning Management Department Bucharest Romania "politehnica" University of Bucharest Department of Automatic Control Bucharest Romania

ISBN: (纸本)9798350331936

Databases are the fundamental component of an application for storing data. SQL (Structured Query Language) is a query language that is used to create, read, update, and remove records in most relational databases (CRUD operations). Because new relational database management systems have arisen, it is useful to compare some of them when linked to a Java application using Spring Data JPA. The time for each CRUD activity is analyzed for thousands and hundreds of thousands of entries. The motivation is to find the most performant combination for an application, considering its size (number of entries). © 2023 IEEE.

关键词： Query languages

来源：评论

学校读者我要写书评

暂无评论

Estimating Chlorophyll Content from Hyperspectral Data Using Gradient Features 23rd

Estimating Chlorophyll Content from Hyperspectral Data Usin...

引用

23rd International Conference on Computational science, ICCS 2023

作者： Ruszczak, Bogdan Wijata, Agata M. Nalepa, Jakub Faculty of Electrical Engineering Automatic Control and Informatics Department of Informatics Opole University of Technology Opole Poland Faculty of Biomedical Engineering Silesian University of Technology Zabrze Poland Faculty of Automatic Control Electronics and Computer Science Department of Algorithmics and Software Silesian University of Technology Gliwice Poland KP Labs Gliwice Poland

ISBN: (纸本)9783031360206

Non-invasive estimation of chlorophyll content in plants plays an important role in precision agriculture. This task may be tackled using hyperspectral imaging that acquires numerous narrow bands of the electromagnetic spectrum, which may reflect subtle features of the plant, and inherently offers spatial scalability. Such imagery is, however, high-dimensional, therefore it is challenging to transfer from the imaging device, store and investigate. We propose a machine learning pipeline for estimating chlorophyll content from hyperspectral data. It benefits from the Savitzky-Golay filtering to smooth the (potentially noisy) spectral curves, and from gradient-based features extracted from such a smoothed signal. The experiments revealed that our approach significantly outperforms the state of the art according to the widely-established estimation quality metrics obtained for four chlorophyll-related parameters. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Machine learning

来源：评论

学校读者我要写书评

暂无评论

Optimized Disturbance Rejection control for Flutter Suppression of a Benchmark Active control Technology Wind-Tunnel Model

Optimized Disturbance Rejection Control for Flutter Suppres...

引用

International Conference on Guidance, Navigation and control, ICGNC 2022

作者： Piao, Minnan Li, Haifeng Lu, Biao Wang, Yongshuai Huang, Jian College of Computer Science and Technology Civil Aviation University of China Tianjin300300 China Institute of Robotics and Automatic Information System College of Artificial Intelligence Nankai University Tianjin300350 China Beijing Automatic Control & Equipment Institute Beijing100074 China

ISBN: (纸本)9789811966125

Active control of aeroservoelasticity effect is critical for future aircraft. This paper concerns the flutter suppression problem for a benchmark active control technology (BACT) wind-tunnel model, which is subject to unmodelled dynamics, parameter perturbations, turbulence disturbances, and measurement noises. After analyzing the characteristics of the BACT model, the trailing edge velocity, which combines the information of the plunge and the pitch modes, is chosen as the controlled output. Several practical filters are employed to effectively attenuate the sensor noise and drift. Based on the filtered signal, we employ the active disturbance rejection control (ADRC) to compensate the multifarious uncertainties and achieve the flutter suppression. Furthermore, to facilitate parameter tuning, the nonsmooth H∞ synthesis method is employed. Finally, extensive simulation and comparison results validate the superiority of the proposed method. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Disturbance rejection

来源：评论

学校读者我要写书评

暂无评论

A Zero-Sequence Current Analysis Approach for Rotating Machinery Fault Diagnosis of Induction Motor Drivetrain Based on Sparse Learning

引用

IEEE Transactions on Power Electronics 2025年第7期40卷 9800-9810页

作者： Liu, Zhao-Hua Long, Jun-Jie Wei, Hua-Liang Liu, Kan Zhang, Ying-Jie Li, Xiao-Hua Hunan University of Science and Technology School of Information and Electrical Engineering Xiangtan411201 China The University of Sheffield School of Electrical and Electronic Engineering Department of Automatic Control and Systems Engineering SheffieldS1 3JD United Kingdom Hunan University College of Mechanical and Vehicle Engineering Changsha410082 China Hunan University College of Computer Science and Electronic Engineering Changsha410082 China

Fault diagnosis of rotating machinery driven by induction motors has received increasing attention. Current diagnostic methods, which can be performed on existing inverters or current transformers of three-phase induction machines, have become a more economical and reliable alternative to vibration diagnostic methods. Existing references mainly focus on the stator current analysis of single-phase, but most single-phase current analysis methods utilize only a fraction of the total information accessible in the three-phase system. Field experience shows that zero-sequence current (ZSC) has more distinctive fault characteristics compared to single-phase current, and therefore it is better to use in mechanical fault detection and diagnostic tasks. This article proposes a novel sparse learning-based method for ZSC analysis for induction rotating motor drive fault diagnosis. First, it elaborates and compares the effectiveness of ZSC in revealing fault characteristics compared with single-phase current by analyzing the fault diagnosis mechanism of ZSC. In addition, the method proposes a correlation entropy-enhanced sparse learning method for the problem of high-frequency noise and interference in the ZSC signals, so as to enhance the learning of the features of the noise-containing signals. The diagnostic efficacy of the proposed method has been verified through experiments on two real datasets. © 1986-2012 IEEE.

关键词： Induction motors

来源：评论

学校读者我要写书评

暂无评论

Determining on-shelf availability based on RGB and ToF depth cameras 23

Determining on-shelf availability based on RGB and ToF depth...

引用

23rd International Conference on control Systems and computer science Technologies, CSCS 2021

作者： Craciunescu, Mihai Baicu, Diana Mocanu, Stefan Dobre, Cristian Faculty of Automatic Control and Computer Science Department of Automatic Control and Applied Informatics Bucharest Romania Rinftech Bucharest Romania

ISBN: (纸本)9781665439398

In this paper, a method of calculating the occupancy of a shelf will be presented. A vision pillar composed of two RGB cameras and two ToF depth cameras will be used to scan a shelf and determine the percentage of emptiness for the products. Since the cameras will scan a small section of the shelf at the time, a stitching method will be applied on both depth and RGB stream. In order to identify categories of products, along with their spatial delimitation within a shelf, a segmentation neural network is used. By combining the segmentation output with the depth information, the distance from the pillar to the product can be determined. Since this type of information does not help a human operator or a supervisor in understanding the state of the shelf or in making an appropriate decision, such as restocking, a method for computing the shelf occupancy is proposed. Optimization must be done to the processing algorithms to enable them to run on an embedded platform, which will allow for the implementation of the proposed architecture on a platform deployed in a production environment. All the computation is done on board of the mobile robot without transmitting the data to an external server. © 2021 IEEE.

关键词： Cameras

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：