为保障铁路系统的信息安全,文章提出一种铁路运行环境下可信根实体(Entity of Root of Trust,ERT)的软件化技术,在内核中实现强制访问控制功能,通过操作系统内核的修改或扩展,实现更为细粒度和强大的权限管理。同时考虑到轻量级场景下...为保障铁路系统的信息安全,文章提出一种铁路运行环境下可信根实体(Entity of Root of Trust,ERT)的软件化技术,在内核中实现强制访问控制功能,通过操作系统内核的修改或扩展,实现更为细粒度和强大的权限管理。同时考虑到轻量级场景下部分设备存在计算能力弱、存储空间有限和电源供应不稳定等问题,提出一种轻量级可信计算体系,最大程度满足可信计算要求。通过实施内核级的强制访问控制和轻量级的可信计算体系改造,缓解未知风险对关键信息基础设施的威胁,为铁路系统的安全性提供保障。展开更多
Brazil annually faces significant challenges with mass movements, particularly in areas with poorly constructed housing, inadequate engineering, and lacking sanitation infrastructure. Campos do Jordão, in Sã...Brazil annually faces significant challenges with mass movements, particularly in areas with poorly constructed housing, inadequate engineering, and lacking sanitation infrastructure. Campos do Jordão, in São Paulo state, is a city currently grappling with these issues. This paper details a study conducted within a pilot area in Campos do Jordão, where geophysical surveys and geotechnical borehole data were integrated. The geophysical surveys provided 2D profiles, and samples were collected to analyse soil moisture and plasticity. These datasets were combined using a Cokriging-based model to produce an accurate representation of the subsurface conditions. The enhanced modelling of subsurface variability facilitates a deeper understanding of soil behavior, which can be used to improve landslide risk assessments. This approach is innovative, particularly within the international context where similar studies often do not address the complexities associated with urban planning deficits such as those observed in some areas of Brazil. These conditions, including the lack of proper sanitation and irregular housing, significantly influence the geological stability of the region, adding layers of complexity to subsurface assessments. Adapting geotechnical evaluation methods to local challenges offers the potential to increase the efficacy and relevance of geological risk management in regions with similar socio-economic and urban characteristics.展开更多
针对未知的污染场地,为了准确估计污染物运移模型的参数,提出一种基于多重数据同化集合平滑器(ensemble smoother with multiple data assimilation,ES-MDA)算法的地下水模型参数反演方法,通过融合由高密度电阻率(electrical resistance...针对未知的污染场地,为了准确估计污染物运移模型的参数,提出一种基于多重数据同化集合平滑器(ensemble smoother with multiple data assimilation,ES-MDA)算法的地下水模型参数反演方法,通过融合由高密度电阻率(electrical resistance tomography,ERT)法采集的ERT观测数据,实现对污染源源强和渗透系数场的联合反演。以此为基础设计3组数值算例,比较不同类型观测数据对反演精度的影响。研究结果表明:融合ERT数据的ES-MDA算法对模型参数的反演精度更高,并且将ERT数据和传统的质量浓度与水头观测数据相结合,能进一步优化反演结果。展开更多
文摘为保障铁路系统的信息安全,文章提出一种铁路运行环境下可信根实体(Entity of Root of Trust,ERT)的软件化技术,在内核中实现强制访问控制功能,通过操作系统内核的修改或扩展,实现更为细粒度和强大的权限管理。同时考虑到轻量级场景下部分设备存在计算能力弱、存储空间有限和电源供应不稳定等问题,提出一种轻量级可信计算体系,最大程度满足可信计算要求。通过实施内核级的强制访问控制和轻量级的可信计算体系改造,缓解未知风险对关键信息基础设施的威胁,为铁路系统的安全性提供保障。
文摘Brazil annually faces significant challenges with mass movements, particularly in areas with poorly constructed housing, inadequate engineering, and lacking sanitation infrastructure. Campos do Jordão, in São Paulo state, is a city currently grappling with these issues. This paper details a study conducted within a pilot area in Campos do Jordão, where geophysical surveys and geotechnical borehole data were integrated. The geophysical surveys provided 2D profiles, and samples were collected to analyse soil moisture and plasticity. These datasets were combined using a Cokriging-based model to produce an accurate representation of the subsurface conditions. The enhanced modelling of subsurface variability facilitates a deeper understanding of soil behavior, which can be used to improve landslide risk assessments. This approach is innovative, particularly within the international context where similar studies often do not address the complexities associated with urban planning deficits such as those observed in some areas of Brazil. These conditions, including the lack of proper sanitation and irregular housing, significantly influence the geological stability of the region, adding layers of complexity to subsurface assessments. Adapting geotechnical evaluation methods to local challenges offers the potential to increase the efficacy and relevance of geological risk management in regions with similar socio-economic and urban characteristics.
基金Supported by National Natural Science Foundation of China(11102142)The Fundamental Research Funds for the Central Universities(2012-IV-0572013-la-008)
基金国家自然科学基金(the National Natural Science Foundation of Chinaunder Grant No.60572153)黑龙江省自然科学基金(the Natural Science Foundation of Helongjiang Province of Chinaunder Grant No.F200609)+2 种基金国家教育部重点科技项目(No.204043)黑龙江省重点科技攻关项目(No.GC05A510)哈尔滨市重点科技攻关项目(No.2005AA1CG035)。
文摘针对未知的污染场地,为了准确估计污染物运移模型的参数,提出一种基于多重数据同化集合平滑器(ensemble smoother with multiple data assimilation,ES-MDA)算法的地下水模型参数反演方法,通过融合由高密度电阻率(electrical resistance tomography,ERT)法采集的ERT观测数据,实现对污染源源强和渗透系数场的联合反演。以此为基础设计3组数值算例,比较不同类型观测数据对反演精度的影响。研究结果表明:融合ERT数据的ES-MDA算法对模型参数的反演精度更高,并且将ERT数据和传统的质量浓度与水头观测数据相结合,能进一步优化反演结果。
