检索结果-内蒙古大学图书馆

A NOTE ON THE QUALITATIVE BEHAVIOUR OF AN ODE MODEL RELATED TO ENDOTOXIN TOLERANCE

UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2024年第4期86卷 127-130页

作者： Olteanu, Mircea Ştefan, Radu Department of Mathematical Methods and Models Faculty of Applied Sciences University "Politehnica" of Bucharest Romania Department of Automatic Control and Systems Engineering Faculty of Automatic Control and Computer Science University "Politehnica" of Bucharest Romania

关键词： Differential equations

来源：评论

学校读者我要写书评

暂无评论

Pneumonia Detection from X-ray Images Using Convolutional Neural Networks

Pneumonia Detection from X-ray Images Using Convolutional Ne...

引用

International Conference on control Systems and computer science (CSCS)

作者： Viorel Dediu Andreea Udrea Department of Automatic Control and Systems Engineering Faculty of Automatic Control and Computer Science Univesity Politehnica of Bucharest Bucharest Romania

Pneumonia is one of the top causes of death in Romania and early detection of this disease improves the recovery chances and shortens the length of hospitalization. In this work, we develop a solution for automatic pneumonia detection based on convolutional neural networks. Four network models are investigated. They are trained on 4.163 images from a public dataset and tested on 530 images. The best results are obtained by one of the proposed models conducting to a sensitivity of 98.72%, an accuracy of 89.81%, and ROC 93.46%. Thus, this research proposes a lightweight screening tool that can help triaging the patients with pneumonia.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Attack Stealthiness and Detection of Multiagent Systems: A Zero-Sum Formulation 63

Attack Stealthiness and Detection of Multiagent Systems: A Z...

引用

63rd IEEE Conference on Decision and control, CDC 2024

作者： Zhu, Shiyong Wang, Miaomiao Chen, Jie Rantzer, Anders City University of Hong Kong Department of Electrical Engineering Hong Kong Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Lund University Department of Automatic Control Lund Sweden

ISBN: (纸本)9798350316339

Cybersecurity has in recent years emerged as a paramount concern in the design and operation of industrial systems and civil infrastructures, due mainly to their susceptibility to malicious cyber attacks which take advantage of the vulnerability of communication networks and IT devices. In this paper, we investigate such an attack and counter attack scenario by considering multiagent systems, a somewhat basic prototype of cyberphysical systems. We study false data injection attacks launched on the agent sensors, and possible defense of such attacks at the agent actuators. The primary issue under consideration is the stealthiness of the attacks, while steering a multiagent system away from its consensual state. We propose a metric to quantify the stealthiness, and formulate the stealthiness problem as one of zero-sum games. We solve the problem explicitly, which gives rise to a fundamental bound on the stealthiness achievable, and as well optimal attack and defense strategies that achieve the optimal stealthiness, both of which can be obtained in terms of certain augmented controllability Gramians associated with the agents. The stealthiness bound is seen to depend on agent dynamics and network characteristics including a measure of connectivity. © 2024 IEEE.

关键词： Cyber attacks

来源：评论

学校读者我要写书评

暂无评论

GaitPT: Skeletons Are All You Need For Gait Recognition

arXiv

引用

arXiv 2023年

作者： Catruna, Andy Cosma, Adrian Radoi, Emilian Faculty of Automatic Control and Computer Science University Politehnica of Bucharest Romania

The analysis of patterns of walking is an important area of research that has numerous applications in security, healthcare, sports and human-computer interaction. Lately, walking patterns have been regarded as a unique fingerprinting method for automatic person identification at a distance. In this work, we propose a novel gait recognition architecture called Gait Pyramid Transformer (GaitPT) that leverages pose estimation skeletons to capture unique walking patterns, without relying on appearance information. GaitPT adopts a hierarchical transformer architecture that effectively extracts both spatial and temporal features of movement in an anatomically consistent manner, guided by the structure of the human skeleton. Our results show that GaitPT achieves state-of-the-art performance compared to other skeleton-based gait recognition works, in both controlled and in-the-wild scenarios. GaitPT obtains 82.6% average accuracy on CASIA-B, surpassing other works by a margin of 6%. Moreover, it obtains 52.16% Rank-1 accuracy on GREW, outperforming both skeleton-based and appearance-based *** Codes 68U10 © 2023, CC BY-NC-ND.

关键词： Human computer interaction

来源：评论

学校读者我要写书评

暂无评论

Performance Analysis for CRUD Operations in Relational Databases from Java Programs Using Hibernate 24

Performance Analysis for CRUD Operations in Relational Datab...

引用

24th International Conference on control Systems and computer science, CSCS 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)9798350313390

Data is information or a collection of information about something. Almost every application nowadays needs to persist data so that they can keep track of their state in case of any trouble that might appear. Databases are the main piece of an application for persisting data and they can be of two types: SQL or NoSQL. SQL (Structured Query Language) is a query language used to create, read, update, or delete (CRUD operations) the information in most relational databases. Data is structured in a set of tables in the relational database model, with rows as entries and columns as specific attributes of the entry. Over the years, new relational database management systems appeared. A comparison between some of the most used relational database management systems tied to a Java application using Hibernate is worth analyzing in the given context. The evaluation is done on timing for each CRUD operation by using Java Microbenchmark Harness, because these are the most used operations, for thousands and hundreds of thousands of entries. Depending on the majority type of operation, switching the database management system might help. © 2023 IEEE.

关键词： Query languages

来源：评论

学校读者我要写书评

暂无评论

Recognition of Red Light Running Behavior of Electric Bicycles in Monitoring Video 5

Recognition of Red Light Running Behavior of Electric Bicycl...

引用

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

作者： Bai, Xiaojun Wang, Shenhang Wang, Zongxin Duan, Jiahao Xi'an Technological University School of Computer Science and Engineering Xi'an China Beijing Aerospace Automatic Control Institution Beijing China

ISBN: (数字)9781665491099

ISBN: (纸本)9781665491099

In order to accurately and efficiently identify the behavior of running red light by electric bicycles, this paper proposed an intelligent recognition model combining target detection and tracking, cross-road analysis and red light running decision. This model takes video frame sequence as input, firstly, electric bicycles and traffic lights are detected by YOLO network, and the bicycles are tracked in real time by DeepSort algorithm to get its trajectory. Then, LSTM is used to analysis the trajectory and distinguish whether there is behavior of crossing road. Finally, make decision of illegal behavior by integrating the state of signal light and the behavior of crossing road. In YOLO, MobileNet is introduced to replace the original CSPDarknet53 backbone, which greatly simplifies the network structure and improves detection efficiency. Dropout is introduced into LSTM to improve detection accuracy. Experimental results show that the optimized model achieves balance between accuracy and efficiency, can detect in real time on the experimental data set, and the final accuracy of recognition reach 94.9 %. © 2022 IEEE.

关键词： Target tracking

来源：评论

学校读者我要写书评

暂无评论

Biological Influence of Low-Frequency Electromagnetic Field Exposition Based on Selected Cell Death Markers 15

Biological Influence of Low-Frequency Electromagnetic Field ...

引用

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

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

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：