为了支持GIG体系结构、设计和工程学中的应用,研究了可重复使用的GIG(Global Information Grid)仿真平台工具的开发。首先,利用传统的系统工程方法来设计GIG仿真平台,通过大量有用的性能分析完成相关GIG体系结构和设计。其次,在考虑自...为了支持GIG体系结构、设计和工程学中的应用,研究了可重复使用的GIG(Global Information Grid)仿真平台工具的开发。首先,利用传统的系统工程方法来设计GIG仿真平台,通过大量有用的性能分析完成相关GIG体系结构和设计。其次,在考虑自动化模拟构造的基础上设计了GIG仿真平台、开发了GIG拓扑模型。接着,讨论了GIG网络环境中最初研究BGP(Border Gateway Protocol)的性能,并且通过仿真实验进行验证平台的有效性。最后,提出了未来仿真平台研究的几点工作,以此来改进仿真平台在解决GIG体系结构、设计和工程学应用中的使用范围。展开更多
We investigate the design of satellite network slicing for the first time to provide customized services for the diversified applications,and propose a novel scheme for satellite end-to-end(E2E) network slicing based ...We investigate the design of satellite network slicing for the first time to provide customized services for the diversified applications,and propose a novel scheme for satellite end-to-end(E2E) network slicing based on 5G technology,which provides a view of common satellite network slicing and supports flexible network deployment between the satellite and the ground.Specifically,considering the limited satellite network resource and the characteristics of the satellite channel,we propose a novel satellite E2E network slicing architecture.Therein,the deployment of the network functions between the satellite and the ground is coordinately considered.Subsequently,the classification and the isolation technologies of satellite network sub-slices are proposed adaptively based on 5G technology to support resource allocation on demand.Then,we develop the management technologies for the satellite E2E network slicing including slicing key performance indicator(KPI) design,slicing deployment,and slicing management.Finally,the analysis of the challenges and future work shows the potential research in the future.展开更多
汽车开放系统架构AUTOSAR (Automotive Open System Architecture)由于其软硬解耦、重用性强等特点,受到越来越多主机厂的青睐。而基于AUTOSAR架构的E2E (End To End)安全通信机制,和传统架构添加循环冗余校验以及信息序列号标识等机制...汽车开放系统架构AUTOSAR (Automotive Open System Architecture)由于其软硬解耦、重用性强等特点,受到越来越多主机厂的青睐。而基于AUTOSAR架构的E2E (End To End)安全通信机制,和传统架构添加循环冗余校验以及信息序列号标识等机制相比,E2E能够实现跨ECU平台的安全通行,兼容性和实用性较强。本文主要介绍车载通信故障类型、E2E保护和文件配置形式,同时进行整车环境的端对端保护通信机制的搭建,在实车环境中对E2E保护进行测试和验证,通过实践案例来促进对E2E深层次的应用。展开更多
Human Activity Recognition(HAR)has become increasingly critical in civic surveillance,medical care monitoring,and institutional protection.Current deep learning-based approaches often suffer from excessive computation...Human Activity Recognition(HAR)has become increasingly critical in civic surveillance,medical care monitoring,and institutional protection.Current deep learning-based approaches often suffer from excessive computational complexity,limited generalizability under varying conditions,and compromised real-time performance.To counter these,this paper introduces an Active Learning-aided Heuristic Deep Spatio-Textural Ensemble Learning(ALH-DSEL)framework.The model initially identifies keyframes from the surveillance videos with a Multi-Constraint Active Learning(MCAL)approach,with features extracted from DenseNet121.The frames are then segmented employing an optimized Fuzzy C-Means clustering algorithm with Firefly to identify areas of interest.A deep ensemble feature extractor,comprising DenseNet121,EfficientNet-B7,MobileNet,and GLCM,extracts varied spatial and textural features.Fused characteristics are enhanced through PCA and Min-Max normalization and discriminated by a maximum voting ensemble of RF,AdaBoost,and XGBoost.The experimental results show that ALH-DSEL provides higher accuracy,precision,recall,and F1-score,validating its superiority for real-time HAR in surveillance scenarios.展开更多
文摘为了支持GIG体系结构、设计和工程学中的应用,研究了可重复使用的GIG(Global Information Grid)仿真平台工具的开发。首先,利用传统的系统工程方法来设计GIG仿真平台,通过大量有用的性能分析完成相关GIG体系结构和设计。其次,在考虑自动化模拟构造的基础上设计了GIG仿真平台、开发了GIG拓扑模型。接着,讨论了GIG网络环境中最初研究BGP(Border Gateway Protocol)的性能,并且通过仿真实验进行验证平台的有效性。最后,提出了未来仿真平台研究的几点工作,以此来改进仿真平台在解决GIG体系结构、设计和工程学应用中的使用范围。
文摘We investigate the design of satellite network slicing for the first time to provide customized services for the diversified applications,and propose a novel scheme for satellite end-to-end(E2E) network slicing based on 5G technology,which provides a view of common satellite network slicing and supports flexible network deployment between the satellite and the ground.Specifically,considering the limited satellite network resource and the characteristics of the satellite channel,we propose a novel satellite E2E network slicing architecture.Therein,the deployment of the network functions between the satellite and the ground is coordinately considered.Subsequently,the classification and the isolation technologies of satellite network sub-slices are proposed adaptively based on 5G technology to support resource allocation on demand.Then,we develop the management technologies for the satellite E2E network slicing including slicing key performance indicator(KPI) design,slicing deployment,and slicing management.Finally,the analysis of the challenges and future work shows the potential research in the future.
文摘汽车开放系统架构AUTOSAR (Automotive Open System Architecture)由于其软硬解耦、重用性强等特点,受到越来越多主机厂的青睐。而基于AUTOSAR架构的E2E (End To End)安全通信机制,和传统架构添加循环冗余校验以及信息序列号标识等机制相比,E2E能够实现跨ECU平台的安全通行,兼容性和实用性较强。本文主要介绍车载通信故障类型、E2E保护和文件配置形式,同时进行整车环境的端对端保护通信机制的搭建,在实车环境中对E2E保护进行测试和验证,通过实践案例来促进对E2E深层次的应用。
文摘Human Activity Recognition(HAR)has become increasingly critical in civic surveillance,medical care monitoring,and institutional protection.Current deep learning-based approaches often suffer from excessive computational complexity,limited generalizability under varying conditions,and compromised real-time performance.To counter these,this paper introduces an Active Learning-aided Heuristic Deep Spatio-Textural Ensemble Learning(ALH-DSEL)framework.The model initially identifies keyframes from the surveillance videos with a Multi-Constraint Active Learning(MCAL)approach,with features extracted from DenseNet121.The frames are then segmented employing an optimized Fuzzy C-Means clustering algorithm with Firefly to identify areas of interest.A deep ensemble feature extractor,comprising DenseNet121,EfficientNet-B7,MobileNet,and GLCM,extracts varied spatial and textural features.Fused characteristics are enhanced through PCA and Min-Max normalization and discriminated by a maximum voting ensemble of RF,AdaBoost,and XGBoost.The experimental results show that ALH-DSEL provides higher accuracy,precision,recall,and F1-score,validating its superiority for real-time HAR in surveillance scenarios.
