检索结果-内蒙古大学图书馆

8th CAA International Conference on Vehicular control and Intelligence, CVCI 2024

作者： Liu, Chen Ru, Shuangkun Qi, Lin Fang, Jiayi Zhang, Ting Yanshan University Hebei Key Laboratory of Industrial Computer Control Engineering Hebei Province Qinhuangdao066004 China School of Mechanical Engineering Beijing Institute of Technology Beijing100081 China School of Vehicle and Mobility Tsinghua University Beijing100081 China

ISBN: (纸本)9798331504892

With the development of vehicle autonomous driving technology and wireless network communication technology, the mix platoon of connected autonomous vehicles (CAVs) and connected human-driven vehicles (CHVs) is becoming inevitable. The abnormal V2V communication and uncertain vehicle dynamics may affect the CAV control performance. Considering time-varying communication delays and random packet loss, an event-trigger-based robust control strategy is proposed based on the stability theory of stochastic time-delay systems. The Bernoulli packet loss model is constructed to solve the random packet loss problem. The robust controller with the event-triggered mechanism designed using the Lyapunov functional stability theory of stochastic systems ensures the stability of the mix platoon with vehicle heterogeneity and the stability of CAV. The simulation comparison has verified that the proposed control strategy can better suppress the fluctuation of the preceding vehicle and more quickly reach the desired value when both time delay and packet loss are present. © 2024 IEEE.

关键词： Stochastic systems

来源：评论

学校读者我要写书评

暂无评论

Comparison of machine learning and deep learning methods for detection of liver abnormality 4th

Comparison of machine learning and deep learning methods for...

引用

4th Annual International Conference on Data Science, Machine Learning and Blockchain Technology, AICDMB 2023

作者： Vaidehi Nayantara, P. Kamath, Surekha Manjunath, K.N. Kadavigere, Rajagopal Department of Instrumentation and Control Engineering Manipal Institute of Technology Manipal India Department of Computer Science and Engineering Manipal Institute of Technology Manipal Academy of Higher Education Manipal India Kasturba Medical College Manipal Academy of Higher Education Manipal India

ISBN: (纸本)9781032426853

Liver is a vital organ that performs various essential functions. Liver cancer can have severe implications on human health, including death. To reduce the mortality rate, early detection of hepatic cancer is imperative. For rapid diagnosis and treatment planning, developing a computerized system that can aid in the diagnosis is essential. In this paper, machine learning and deep learning methods were compared for identifying abnormal liver from computed tomography images. The liver was segmented using DeepLabv3 + network. The machine learning method used, histogram and gray level co-occurrence matrix for feature extraction and support vector machine for classification. The deep learning methods investigated were ResNet, ShuffleNet and EfficientNet. Accuracy, sensitivity and specificity were used for performance evaluation. The results of our experiments showed that the deep learning methods outperformed the machine learning methods. Among the deep learning models, EfficientNet gave the highest accuracy of 87%. As future work, the abnormal liver can be further classified into benign and malignant classes. © 2024 The Author(s).

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Optimal Strategies to Contain Arboviruses Spread

引用

SN computer Science 2025年第5期6卷 1-13页

作者： Di Giamberardino, Paolo Iacoviello, Daniela Department of Computer Control and Management Engineering Antonio Ruberti Sapienza University of Rome Via Ariosto 25 Rome 00185 Italy

Globalization, the increase of human travelling and climate changes contribute to the emergency due to arboviruses diffusion. Generally, the infected patients show only mild symptoms, but in some cases, with fragile subjects, this kind of disease can be fatal. In this paper Dengue virus is considered and described by means of a new compartmental model in which the human and the mosquitos populations interact and can infect each other;containment measures, based both on human habits and on the reduction of mosquitoes in different phase of their lives, are determined in the framework of optimal control theory, aiming at decreasing the number of infected patients and limiting the actions to be applied. This latter aspect is particularly important, both for practical and economical aspects, and for ecological reasons, since a too strong actions against mosquitos can be dangerous for the equilibrium of the ecosystem. © The Author(s) 2025.

关键词： Containment strategies Dengue virus Epidemic control Optimal control

来源：评论

学校读者我要写书评

暂无评论

Enhancing Fault Detection in Induction Motors using LSTM-Attention Neural Networks 9

Enhancing Fault Detection in Induction Motors using LSTM-Att...

引用

9th International Conference on control, Instrumentation and Automation, ICCIA 2023

作者： Khaniki, Mohammad Ali Labbaf Mirzaeibonehkhater, Marzieh Manthouri, Mohammad K.N. Toosi University of Technology Department of Control Engineering Tehran Iran Indiana University-Purdue University Department of Electrical and Computer Engineering United States Shahed University Department of Electrical and Electronic Engineering Tehran Iran

ISBN: (纸本)9798350366013

Induction motors carry notable importance in modern machinery and industrial equipment. Hence, the imperative to establish an early fault detection system for discerning operational states and potential faults in these motors is evident. This paper introduces a pioneering methodology for fault detection in induction motors by leveraging the power of Long Short-Term Memory (LSTM) networks and attention mechanisms within a neural network framework. By combining the temporal sequence analysis capabilities of LSTMs with the selective focus feature of attention mechanisms, the proposed architecture enhances the accuracy and timeliness of fault detection, paving the way for improved machinery health monitoring and predictive maintenance. The proposed approach is rigorously evaluated alongside established methods, including simple Artificial Neural Networks (ANN) and LSTM networks to showcase the strengths of the LSTM-Attention approach. This comprehensive analysis reveals the additional advantages of attention mechanisms and positions the LSTM-Attention architecture as a robust solution for detecting faults in induction motors. © 2023 IEEE.

关键词： Long short-term memory

来源：评论

学校读者我要写书评

暂无评论

Enhancing Pneumonia Detection using Vision Transformer with Dynamic Mapping Re-Attention Mechanism 13

Enhancing Pneumonia Detection using Vision Transformer with ...

引用

13th International Conference on computer and Knowledge engineering, ICCKE 2023

作者： Labbaf Khaniki, Mohammad Ali Mirzaeibonehkhater, Marzieh Manthouri, Mohammad K.N. Toosi University of Technology Department of Control Engineering Tehran Iran Indiana University-Purdue University Department of Electrical and Computer Engineering United States Shahed University Department of Electrical and Electronic Engineering Tehran Iran

ISBN: (纸本)9798350330151

Pneumonia is a prevalent respiratory infection with potentially life-threatening consequences. In this research, we propose a novel deep learning approach to enhance pneumonia detection using the Vision Transformer (ViT) architecture with a dynamic mapping re-attention mechanism. The re-attention mechanism in the ViT architecture facilitates the flow of information between patches of the input image, enabling contextual understanding through self-attention. This mechanism captures long-range dependencies and enhances the ViT's ability to effectively recognize and interpret images. The dynamic mapping attention mechanism allows the model to dynamically assign attention weights to different regions of the input data based on their relevance to pneumonia detection. By adaptively adjusting the attention weights, the model can capture both local details and global dependencies, enabling more accurate diagnosis. The ViT utilizes the dynamic mapping re-attention mechanism with attention dropout. Here the performance of this ViT compared to the conventional ViT and the ViT incorporating the re-attention mechanism. This comparative analysis offers valuable insights into the effectiveness of the proposed dynamic mapping re-attention mechanism. Additionally, it highlights the added benefits of attention dropout in enhancing the overall performance of the model. © 2023 IEEE.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

Stochastic Programming for Hub Energy Management Considering Uncertainty Using Two-Point Estimate Method and Optimization Algorithm

引用

computer Modeling in engineering & Sciences 2023年第12期137卷 2163-2192页

作者： Ali S.Alghamdi Mohana Alanazi Abdulaziz Alanazi Yazeed Qasaymeh Muhammad Zubair Ahmed Bilal Awan M.G.B.Ashiq Department of Electrical Engineering College of EngineeringMajmaah UniversityAl-Majmaah11952Saudi Arabia Department of Electrical Engineering College of EngineeringJouf UniversitySakaka72341Saudi Arabia Department of Electrical Engineering College of EngineeringNorthern Border UniversityAr’Ar73222Saudi Arabia Automation and Control Department College of Engineering TechnologyUniversity of Doha for Science and TechnologyDoha24449Qatar Department of Electrical and Computer Engineering College of Engineering and Information TechnologyAjman UniversityAjman20550United Arab Emirates Department of Physics College of ScienceImam Abdulrahman Bin Faisal UniversityDammam31441Saudi Arabia

To maximize energy profit with the participation of electricity,natural gas,and district heating networks in the day-ahead market,stochastic scheduling of energy hubs taking into account the uncertainty of photovoltaic and wind resources,has been carried *** has been done using a new meta-heuristic algorithm,improved artificial rabbits optimization(IARO).In this study,the uncertainty of solar and wind energy sources is modeled using Hang’s two-point estimating method(TPEM).The IARO algorithm is applied to calculate the best capacity of hub energy equipment,such as solar and wind renewable energy sources,combined heat and power(CHP)systems,steamboilers,energy storage,and electric cars in the *** standard ARO algorithmis developed to mimic the foraging behavior of rabbits,and in this work,the algorithm’s effectiveness in avoiding premature convergence is improved by using the dystudynamic inertia weight *** proposed IARO-based scheduling framework’s performance is evaluated against that of traditional ARO,particle swarm optimization(PSO),and salp swarm algorithm(SSA).The findings show that,in comparison to previous approaches,the suggested meta-heuristic scheduling framework based on the IARO has increased energy profit in day-ahead electricity,gas,and heating markets by satisfying the operational and energy hub ***,the results show that TPEM approach dependability consideration decreased hub energy’s profit by 8.995%as compared to deterministic planning.

关键词： Stochastic energy hub scheduling energy profit uncertainty Hong’s two-point estimate method improved artificial rabbits optimization

来源：评论

学校读者我要写书评

暂无评论

Analog, Programmable Switched Capacitor FIR Filter Based on Rotator Architecture Implemented in CMOS Technology 26

Analog, Programmable Switched Capacitor FIR Filter Based on ...

引用

26th IEEE Signal Processing: Algorithms, Architectures, Arrangements, and Applications, SPA 2023

作者： Pawlowski, Pawel Dlugosz, Rafal Radkowski, Marek Watly, Mateusz Dabrowski, Adam Poznań University of Technology Division of Signal Processing and Electronic Systems Faculty of Control Robotics and Electrical Engineering Institute of Automatic Control and Robotics Poznań60-965 Poland Bydgoszcz University of Science and Technology Faculty of Telecommunication Computer Science and Electrical Engineering Bydgoszcz85-796 Poland

ISBN: (纸本)9798350304985

The paper presents project and its verification of a prototype integrated circuit containing an analog, programmable finite impulse response (FIR) filter, implemented in CMOS 350 nm technology. The structure of the filter is based on the switched capacitor technique. In circuits of this type, one of main challenges is an efficient implementation of filter coefficients, which result from several factors described in this work. When implementing such filters as programmable circuits, the values of their coefficients have to be limited to a selected range, i.e. a given resolution in bits. In the implemented prototype filter, the filter coefficients are represented by 6 bits in sign-magnitude notation, so they can take 63 different values only. In such filters, it is not possible to directly implement any frequency response of the filter. Each time, it is necessary to properly round the theoretical values of the coefficients so that they fit into the available range of discrete values resulting from the implementation. The authors of the work designed an algorithm that allows such matching. The paper also presents results of measurements of the prototype chip. © 2023 Division of Signal Processing and Electronic Systems, Poznan University of Technology (DSPES PUT).

关键词： FIR filters

来源：评论

学校读者我要写书评

暂无评论

引用

Chinese Journal of Electronics 2021年第5期30卷 876-884页

作者： QIAO Sibo PANG Shanchen WANG Min ZHAI Xue DAI Feng College of Computer Science and Technology China University of Petroleum College of Control Science and Engineering China University of Petroleum College of Information Science and Engineering Shandong University of Science and Technology

Popularity prediction of online video is widely used in many different scenarios. It can not only help video service providers to schedule video web sites,but also bring considerable profits on investment for both providers and advertisers if popularity of online video is predicted accurately. However, online video popularity prediction still cannot have a satisfactory result, due to the complexity of many crucial factors especially of video distribution network. In this article, we extract seven factors from huge amounts of data about user behavior,establishing a new multiple linear regression model to initially predict online video popularity. After that, a multichannel video popularity dynamic scheduling model is proposed to schedule videos on which channel and what time to be broadcast, according to its popularity predicted by multiple linear regression model, ensuring that maximum the sum value of online video popularity of each channel. Experimental results on dataset obtained from Sohu Video, a video service provider in China, and real-world video flow in Sohu Video demonstrate that the proposed model is robust and has promising performance in predicting online video popularity, which is helpful for video service providers to schedule videos on web sites effectively in the future.

关键词： regression analysis video communication Internet video signal processing Web sites real-world video flow online video popularity regression prediction model video service provider Sohu Video video distribution network user behavior video Web sites dynamic scheduling multichannel video popularity dynamic scheduling model multiple linear regression model

来源：评论

学校读者我要写书评

暂无评论

Optimizing Machine Learning Algorithms to Enhance Blood Donation for Liver Patients: A Case Study 7

Optimizing Machine Learning Algorithms to Enhance Blood Dona...

引用

7th IET Smart Cities Symposium, SCS 2023

作者： Mijwil, Maad M. El-Kenawy, El-Sayed M. Bala, Indu Aljanabi, Mohammad Abotaleb, Mostafa Ibrahim, Abdelhameed Computer Techniques Engineering Department Baghdad College of Economic Sciences University Baghdad Iraq Department of Communications and Electronics Delta Higher Institute of Engineering and Technology Egypt School of Electrical and Electronics Engineering Lovely Professional University Punjab India Department of Computer Aliraqia University Baghdad Iraq Department of System Programming South Ural State University Chelyabinsk Russia Computer Engineering and Control Systems Department Faculty of Engineering Mansoura University Mansoura Egypt

ISBN: (纸本)9781839539831

Blood is vital for transporting oxygen, nutrients, and hormones to all body parts as it circulates through arteries and veins. It removes carbon dioxide, regulates body temperature, and maintains the body's immune system. Individuals constantly need blood and its derivatives to save their lives and improve their health through medical treatments and surgical operations. Liver diseases are one of the diseases that affects the health of individuals and requires blood to continue living. These diseases cause significant damage to people's health, and early diagnosis plays a crucial role in saving lives. In this paper, machine learning algorithms (support vector machine and random forest) are involved in detecting liver diseases and determining whether donors are suitable to donate blood from blood values. This paper is applied research that found that the performance measures of the random forest algorithm achieved excellent performance in identifying suitable people to donate blood. © The Institution of engineering & Technology 2023.

关键词： Support vector machines

来源：评论

学校读者我要写书评

暂无评论

Computing Challenges of UAV Networks: A Comprehensive Survey

引用

computers, Materials & Continua 2024年第11期81卷 1999-2051页

作者： Altaf Hussain Shuaiyong Li Tariq Hussain Xianxuan Lin Farman Ali Ahmad Ali AlZubi School of Computer Science&Technology Chongqing University of Posts and TelecommunicationsChongqing400065China Key Laboratory of Industrial Internet of Things and Networked Control Ministry of EducationChongqing University of Posts and TelecommunicationsChongqing400065China School of Computer Science and Technology Zhejiang Gongshang UniversityHangzhou310018China School of Artificial Intelligence Nanjing University of Information Science&TechnologyNanjing210044China Department of Computer Science and Engineering School of ConvergenceCollege of Computing and InformaticsSungkyunkwan UniversitySeoul03063Republic of Korea Department of Computer Science Community CollegeKing Saud UniversityRiyadh11495Saudi Arabia

Devices and networks constantly upgrade,leading to rapid technological ***-dimensional(3D)point cloud transmission plays a crucial role in aerial computing terminology,facilitating information *** network types,including sensor networks and 5G mobile networks,support this ***,Flying Ad hoc Networks(FANETs)utilize Unmanned Aerial Vehicles(UAVs)as nodes,operating in a 3D environment with Six Degrees of Freedom(6DoF).This study comprehensively surveys UAV networks,focusing on models for Light Detection and Ranging(LiDAR)3D point cloud compression/*** topics covered include autonomous navigation,challenges in video streaming infrastructure,motivations for Quality of Experience(QoE)enhancement,and avenues for future ***,the paper conducts an extensive review of UAVs,encompassing current wireless technologies,applications across various sectors,routing protocols,design considerations,security measures,blockchain applications in UAVs,contributions to healthcare systems,and integration with the Internet of Things(IoT),Artificial Intelligence(AI),Machine Learning(ML),and Deep Learning(DL).Furthermore,the paper thoroughly discusses the core contributions of LiDAR 3D point clouds in UAV systems and their future prediction along with mobility *** also explores the prospects of UAV systems and presents state-of-the-art solutions.

关键词： Autonomous vehicles UAV systems UAV transmission UAV in healthcare future of UAV system security measures

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：