检索结果-内蒙古大学图书馆

Failure modes determination and load-bearing capacity evaluation of concrete columns under seismic loads by ANNs

Soft Computing 2024年第13-14期28卷 8361-8377页

作者： Hao, Meijing Chang, Wei Xu, Chonghao School of Architecture and Civil Engineering Harbin University of Science and Technology Harbin150080 China Key Lab of Structures Dynamic Behavior and Control Ministry of Education Harbin Institute of Technology Harbin150090 China Key Lab of Smart Prevention and Mitigation of Civil Engineering Disasters of the Ministry of Industry and Information Technology Harbin Institute of Technology Harbin150090 China School of Civil Engineering Harbin Institute of Technology 202 Haihe Road Nangang District Harbin China

The failure modes of concrete columns can be applied to judge the ductility of concrete columns under seismic loads. In addition, the load-bearing capacity of concrete columns was an important parameter in evaluating the seismic performance of concrete columns under seismic loads. However, it was difficult to determine the failure modes and evaluate the load-bearing capacity of concrete columns under seismic loads with the application of high-strength concrete. In this paper, two ANNs, including a genetic algorithm optimization-based support vector machine (GA-SVM) and an ANFIS, were developed to determine the failure modes of concrete columns under seismic loads. The main investigated parameters, including specimens' shear span ratio, the compressive strength of concrete, the yield strength and volumetric ratio of stirrups, and the yield strength and ratio of longitudinal reinforcement, were applied as input variables to the models. The proposed models were trained and tested using 247 data sets from previous studies. The proposed models had high reliability and predictability to determine the failure modes of concrete columns under seismic loads. Furthermore, an ANFIS network was developed to evaluate the load-bearing capacity of concrete columns, which had high reliability and predictability. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Failure modes

来源：评论

学校读者我要写书评

暂无评论

Optimal Deep Reinforcement Learning for Intrusion Detection in UAVs

引用

Computers, Materials & Continua 2022年第2期70卷 2639-2653页

作者： V.Praveena A.Vijayaraj P.Chinnasamy Ihsan Ali Roobaea Alroobaea Saleh Yahya Alyahyan Muhammad Ahsan Raza Department of Computer Science and Engineering Dr.N.G.P Institute of TechnologyCoimbatore641048India Department of Information Technology Vignan’s Foundation for ScienceTechnology&ResearchGuntur522213India Department of Information Technology Sri Shakthi Institute of Engineering and TechnologyCoimbatore641062India Department of Computer System and Technology Faculty of Computer Science and Information TechnologyUniversity of MalayaKuala Lumpur50603Malaysia Department of Computer Science College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia Department of Computer Science Community College in DwadmiShaqra University11961Saudi Arabia Department of Information Technology Bahauddin Zakariya UniversityMultan60000Pakistan

In recent years,progressive developments have been observed in recent technologies and the production cost has been continuously *** such scenario,Internet of Things(IoT)network which is comprised of a set of Unmanned Aerial Vehicles(UAV),has received more attention from civilian tomilitary *** network security poses a serious challenge to UAV networks whereas the intrusion detection system(IDS)is found to be an effective process to secure the UAV *** IDSs are not adequate to handle the latest computer networks that possess maximumbandwidth and data *** order to improve the detection performance and reduce the false alarms generated by IDS,several researchers have employed Machine Learning(ML)and Deep Learning(DL)algorithms to address the intrusion detection *** this view,the current research article presents a deep reinforcement learning technique,optimized by BlackWidow Optimization(DRL-BWO)algorithm,for UAV *** addition,DRL involves an improved reinforcement learning-based Deep Belief Network(DBN)for intrusion *** parameter optimization of DRL technique,BWO algorithm is *** helps in improving the intrusion detection performance of UAV *** extensive set of experimental analysis was performed to highlight the supremacy of the proposed *** the simulation values,it is evident that the proposed method is appropriate as it attained high precision,recall,F-measure,and accuracy values such as 0.985,0.993,0.988,and 0.989 respectively.

关键词： Intrusion detection UAV networks reinforcement learning deep learning parameter optimization

来源：评论

学校读者我要写书评

暂无评论

Dataset of Large Gathering Images for Person Identification and Tracking

引用

Computers, Materials & Continua 2023年第3期74卷 6065-6080页

作者： Adnan Nadeem Amir Mehmood Kashif Rizwan Muhammad Ashraf Nauman Qadeer Ali Alzahrani Qammer H.Abbasi Fazal Noor Majed Alhaisoni Nadeem Mahmood Faculty of Computer and Information System Islamic University of MadinahMadinah42351Saudi Arabia Department of Computer Science and Information Technology Sir Syed University of Engineering and TechnologyKarachi75300Pakistan Department of Computer Science Federal Urdu University of ArtsScience&TechnologyIslamabad45570Pakistan Department of Physics Federal Urdu University of ArtsScience&TechnologyKarachi75300Pakistan James Watt School of Engineering University of GlasgowGlasgowG128QQUK Computer Sciences Department College of Computer and Information SciencesPrincess Nourah bint Abdulrahman UniversityRiyadh11671Saudi Arabia Department of Computer Science University of KarachiKarachi75270Pakistan

This paper presents a large gathering dataset of images extracted from publicly filmed videos by 24 cameras installed on the premises of Masjid Al-Nabvi,Madinah,Saudi *** dataset consists of raw and processed images reflecting a highly challenging and unconstraint *** methodology for building the dataset consists of four core phases;that include acquisition of videos,extraction of frames,localization of face regions,and cropping and resizing of detected face *** raw images in the dataset consist of a total of 4613 frames obtained fromvideo *** processed images in the dataset consist of the face regions of 250 persons extracted from raw data images to ensure the authenticity of the presented *** dataset further consists of 8 images corresponding to each of the 250 subjects(persons)for a total of 2000 *** portrays a highly unconstrained and challenging environment with human faces of varying sizes and pixel quality(resolution).Since the face regions in video sequences are severely degraded due to various unavoidable factors,it can be used as a benchmark to test and evaluate face detection and recognition algorithms for research *** have also gathered and displayed records of the presence of subjects who appear in presented frames;in a temporal *** can also be used as a temporal benchmark for tracking,finding persons,activity monitoring,and crowd counting in large crowd scenarios.

关键词： Large crowd gatherings a dataset of large crowd images highly uncontrolled environment tracking missing persons face recognition activity monitoring

来源：评论

学校读者我要写书评

暂无评论

Output Linearization of Single-Input Single-Output Fuzzy system to Improve Accuracy and Performance

引用

Computers, Materials & Continua 2023年第5期75卷 2413-2427页

作者： Salah-ud-din Khokhar QinKe Peng Muhammad Yasir Noor Department of Automation Science and Technology(System Engineering Institute) School of Electronics and Information EngineeringXi’an Jiaotong UniversityXi’anShaanxi710049China Department of Computer Science G.C.UniversityLahore54000PunjabPakistan Department of Physics(Electronics) G.C.UniversityLahore54000PunjabPakistan

For fuzzy systems to be implemented effectively,the fuzzy membership function(MF)is essential.A fuzzy system(FS)that implements precise input and output MFs is presented to enhance the performance and accuracy of single-input single-output(SISO)FSs and introduce the most applicable input and output MFs protocol to linearize the fuzzy system’s *** a variety of non-linear techniques,a SISO FS is *** results of FS experiments conducted in comparable conditions are then *** simulated results and the results of the experimental setup agree fairly *** findings of the suggested model demonstrate that the relative error is abated to a sufficient range(≤±10%)and that the mean absolute percentage error(MPAE)is reduced by around 66.2%.The proposed strategy to reduceMAPE using an FS improves the system’s performance and control *** using the best input and output MFs protocol,the energy and financial efficiency of every SISO FS can be improved with very little tuning of *** proposed fuzzy system performed far better than other modern days approaches available in the literature.

关键词： Mean absolute percentage error membership functions relative error fuzzy system

来源：评论

学校读者我要写书评

暂无评论

Brain Tumor:Hybrid Feature Extraction Based on UNet and 3DCNN

引用

Computer systems science & engineering 2023年第5期45卷 2093-2109页

作者： Sureshkumar Rajagopal Tamilvizhi Thanarajan Youseef Alotaibi Saleh Alghamdi Center for System Design Chennai Institute of TechnologyChennai600069India Department of Information Technology Vel Tech Multi Tech Dr.Rangarajan Dr.Sakunthala Engineering CollegeChennai600062India Department of Computer Science College of Computer and Information SystemsUmm Al-Qura UniversityMakkah21955Saudi Arabia Department of Information Technology College of Computers and Information TechnologyTaif UniversityTaif21944Saudi Arabia

Automated segmentation of brain tumors using Magnetic Resonance Imaging(MRI)data is critical in the analysis and monitoring of disease *** a result,gliomas are aggressive and diverse tumors that may be split into intra-tumoral groups by using effective and accurate segmentation *** is intended to extract characteristics from an image using the Gray Level Co-occurrence(GLC)matrix feature extraction method described in the proposed *** Convolutional Neural Networks(CNNs),which are commonly used in biomedical image segmentation,CNNs have significantly improved the precision of the state-of-the-art segmentation of a brain *** two segmentation networks,a U-Net and a 3D CNN,we present a major yet easy combinative technique that results in improved and more precise *** U-Net and 3D CNN are used together in this study to get better and more accurate estimates of what is going *** the dataset,two models were developed and assessed to provide segmentation maps that differed fundamentally in terms of the segmented tumour ***,the estimates was made by two separate models that were put together to produce the final *** comparison to current state-of-the-art designs,the precision(percentage)was 98.35,98.5,and 99.4 on the validation set for tumor core,enhanced tumor,and whole tumor,respectively.

关键词： Medical imaging segmentation U-net 3D CNN brain tumor

来源：评论

学校读者我要写书评

暂无评论

Video Action Recognition Method Based on Personalized Federated Learning and Spatiotemporal Features

引用

Computers, Materials & Continua 2025年第6期83卷 4961-4978页

作者： Rongsen Wu Jie Xu Yuhang Zhang Changming Zhao Yiweng Xie Zelei Wu Yunji Li Jinhong Guo Shiyang Tang School of Information and Communication Engineering University of Electronic Science and Technology of ChinaChengdu611731China School of Computer Science Chengdu University of Information TechnologyChengdu610225China Shanghai Key Lab of Intelligent Information Processing School of CSFudan UniversityShanghai200433China School of Sensing Science and Engineering Shanghai Jiao Tong UniversityShanghai200240China School of Mechanical and Manufacturing Engineering University of New South WalesSydney2052Australia School of Electronics and Computer Science University of SouthamptonSouthamptonSO171BJUK

With the rapid development of artificial intelligence and Internet of Things technologies,video action recognition technology is widely applied in various scenarios,such as personal life and industrial ***,while enjoying the convenience brought by this technology,it is crucial to effectively protect the privacy of users’video ***,this paper proposes a video action recognition method based on personalized federated learning and spatiotemporal *** the framework of federated learning,a video action recognition method leveraging spatiotemporal features is *** the local spatiotemporal features of the video,a new differential information extraction scheme is proposed to extract differential features with a single RGB frame as the center,and a spatialtemporal module based on local information is designed to improve the effectiveness of local feature extraction;for the global temporal features,a method of extracting action rhythm features using differential technology is proposed,and a timemodule based on global information is *** translational strides are used in the module to obtain bidirectional differential features under different action ***,to address user data privacy issues,the method divides model parameters into local private parameters and public parameters based on the structure of the video action recognition *** approach enhancesmodel training performance and ensures the security of video *** experimental results show that under personalized federated learning conditions,an average accuracy of 97.792%was achieved on the UCF-101 dataset,which is non-independent and identically distributed(non-IID).This research provides technical support for privacy protection in video action recognition.

关键词： Video action recognition personalized federated learning spatiotemporal features data privacy

来源：评论

学校读者我要写书评

暂无评论

ADRC Controller Design for Autonomous Vehicles Queuing systems in Zero-Trust Environment 6

ADRC Controller Design for Autonomous Vehicles Queuing Syste...

引用

6th International Conference on Robotics, Control and Automation engineering, RCAE 2023

作者： Li, Xinrong Na, Yuhong Huang, Darong Zhu, Ling School of Mathematics and Statistics Chongqing Jiaotong University Chongqing China Anhui University Engineering Research Center of Autonomous Unmanned System Technology of Ministry of Education Anhui Provincial Engineering Research Center for Unmanned System and Intelligent Technology Hefei China School of Information Science and Engineering Anhui University Chongqing Jiaotong University Engineering Research Center of Autonomous Unmanned System Technology of Ministry of Education Anhui Provincial Engineering Research Center for Unmanned System and Intelligent Technology Chongqing Hefei China School of Information Science and Engineering Chongqing Jiaotong University Chongqing China

ISBN: (纸本)9798350315301

In recent years, the integration of advanced technologies in the Intelligent Connected Vehicle (ICV) field has attracted many scholars' interests, and their safety and efficiency improved significantly. However, with the increasing number of cyber attacks and security threats in modern vehicle networks, the communication environment of vehicle is deteriorated. To solve this problem, studying the topics in zero-trust environment instead of the classic full-trust environment is becoming a effective approach. Because the traditional centralized control system is considered to be insufficient to ensure the security and reliability of ICVs, the distributed system is applied to research the ICVs. In this paper, an active disturbance rejection control (ADRC) is utilized to decrease the unknown input perturbations brought by zero-trust environment to the ICV queuing system. And it also need to ensure the stability of the vehicle formation, and to mitigate the disturbances in the dynamic driving environment. The ADRC utilizes the principles of zero-trust architecture and active disturbance rejection control to enhance the robustness and security of the queue management of ICV s. In the end, the performance of the proposed ADRC is evaluated through extensive simulations and analysis, which is to demonstrate its effectiveness and superiority in maintaining a safe and efficient vehicle queue. © 2023 IEEE.

关键词： Autonomous vehicles

来源：评论

学校读者我要写书评

暂无评论

Spatial-structural analysis of macroeconomic factors’ impact on carbon emissions in East Africa: a spatial econometric panel study

引用

Environmental science and Pollution Research 2024年第39期31卷 51883-51901页

作者： Shakiru, Twahil Hemed Liu, Xiaohui Liu, Qing Khan, Muhammad Asif Department of Statistics University of Dar Es Salaam Dar Es Salaam Tanzania United Republic of School of Statistics and Data Science Jiangxi University of Finance and Economics Jiangxi China Earth System and Global Change Lab School of Environmental Science and Engineering Southern University of Science and Technology Shenzhen China

Despite the abundance of research on reducing carbon emissions, there is a significant gap in understanding the influence of macroeconomic factors on carbon dioxide (CO2) emissions from a spatial-structural perspective. This study aims to contribute to the literature by investigating the impact of macroeconomic factors on carbon dioxide emissions in six East African countries between 1989 and 2020. Using spatial econometric panel models, the study analyzed spatial dependence among the variables. The empirical findings indicate that gross domestic product (GDP) per capita and electricity consumption have positive direct and indirect effects on carbon emissions, while fuel prices and exports have negative direct effects, but positive spillover effects on neighboring countries. Imports have a positive impact on local economies, but negative spillover effects. Additionally, the urban population has no significant impact on the environment. These findings provide important policy implications for optimizing spatial growth patterns and achieving a low-carbon economy in East African countries. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.

关键词： Carbon dioxide

来源：评论

学校读者我要写书评

暂无评论

Ground State and Its Topological Properties of Three-Dimensional Spin-Orbit Coupled Degenerate Fermi Gases

引用

Chinese Physics Letters 2023年第12期40卷 143-148页

作者： Long Xiong Ming Gong Zhao-Xiang Fang Rui Sun International Center for Quantum Materials School of PhysicsPeking UniversityBeijing 100871China Key Lab of Quantum Information of Chinese Academy of Sciences School of PhysicsUniversity of Science and Technology of ChinaHefei 230026China Synergetic Innovation Center of Quantum Information and Quantum Physics University of Science and Technology of ChinaHefei 230026China School of Physical Science and Technology Xinjiang UniversityUrumqi 830046China College of Physics and Optoelectronic Engineering Shenzhen UniversityShenzhen 518060China

Three-dimensional(3D)degenerate Fermi gases in the presence of spin-orbit coupling,inducing various kinds of physical findings and phenomena,have attracted tremendous attention in these *** investigate the 3D spin-orbit coupled degenerate Fermi gases in theory and first present the analytic expression of their ground *** study provides an innovative perspective into understanding of the topological properties of 3D unconventional superconductors,and describes the topological phase transitions in trivial and topological phase ***,such a system is provided with a richer set of Cooper pairings than traditional *** dual Cooper pairs with same spin directions emerge and exhibit peculiar behaviors,leading to topological phase *** study and discussion can be generalized to some other types of unconventional superconductors and areas of optical lattices.

关键词： Fermi topological degenerate

来源：评论

学校读者我要写书评

暂无评论

STFormer: Learning to Explore Spot Relationships for Spatial Transcriptomics Prediction from Histology of Colorectal Cancer 46

STFormer: Learning to Explore Spot Relationships for Spatial...

引用

46th Annual International Conference of the IEEE engineering in Medicine and Biology Society, EMBC 2024

作者： Zhan, Gan Du, Xiuju Liu, Jing Li, Yinhao Lin, Lanfen Li, Jingsong Chen, Yen-Wei Ritsumeikan University Graduate School of Information Science and Engineering Shiga Japan Research Center for Healthcare Data Science Zhejiang Lab Hangzhou China Ritsumeikan University College of Information Science and Engineering Shiga Japan Zhejiang University College of Computer Science and Technology Hangzhou China

ISBN: (纸本)9798350371499

Spatial transcriptomics (ST) offers insights into gene expression patterns within tumor microenvironments, but its widespread application is impeded by cost constraints. To address this, predicting ST from Histology emerges as a cost-effective alternative. However, current methods such as STNet, HistoGene, and Hist2ST exhibit limitations, either overlooking stain variation across datasets or failing to well explore inter-spot correlations in scenarios with limited Whole Slide Image (WSI) data. In response, we present STFormer, a deep learning approach that incorporates the Style-Aug module to enhance feature generalization through medically-irrelevant style transfer augmentation. Additionally, the Cross-WSI Transformer module is introduced to capture Cross-WSI spot relationships efficiently. Our experimental results, conducted on both internal and external datasets, demonstrate that STFormer surpasses existing methods by a substantial margin. This showcases its potential as a powerful tool for spatial transcriptomics predictions, addressing critical gaps in current methodologies. © 2024 IEEE.

关键词： WSI circuits

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：