排序方式： 共有6条查询结果，搜索用时 46 毫秒
1
1.
《地震研究进展（英文）》2021,1(3):100029
We developed an automatic seismic wave and phase detection software based on PhaseNet, an efficient and highly generalized deep learning neural network for P- and S-wave phase picking. The software organically combines multiple modules including application terminal interface, docker container, data visualization, SSH protocol data transmission and other auxiliary modules. Characterized by a series of technologically powerful functions, the software is highly convenient for all users. To obtain the P- and S-wave picks, one only needs to prepare three-component seismic data as input and customize some parameters in the interface. In particular, the software can automatically identify complex waveforms (i.e. continuous or truncated waves) and support multiple types of input data such as SAC, MSEED, NumPy array, etc. A test on the dataset of the Wenchuan aftershocks shows the generalization ability and detection accuracy of the software. The software is expected to increase the efficiency and subjectivity in the manual processing of large amounts of seismic data, thereby providing convenience to regional network monitoring staffs and researchers in the study of Earth's interior. 相似文献
2.
Docker等容器技术给GIS的部署带来了极大便利,并使快速规模部署成为可能.本文讨论了在容器环境中GIS服务状态的最佳同步方式、发现方式,以及如何更智能地实现GIS服务的负载均衡,并提出了一种应对负载均衡中单点失效的机制,为GIS服务的动态伸缩、故障恢复提供了借鉴. 相似文献
3.
随着天文技术的发展,天文数据处理软件的需求也不断更迭变化,导致软件运行环境渐趋复杂。对于开发者和使用者,急需提出一种对复杂天文数据处理软件敏捷化封装和部署的方法。我国明安图射电频谱日像仪已进入常规观测,与之配套的数据处理软件也已完成开发并投入使用。由于该软件的部署涉及操作系统环境、图形处理器运行环境及底层依赖软件等配置问题,导致安装过程既繁琐又容易出错。结合容器技术的特点,提出了一种基于Docker容器对日像仪软件系统进行敏捷封装与部署的方法,并对该方法的设计进行介绍,通过实验验证了其可用性,以及相比于传统虚拟机可获得较优异的性能表现。该方法可为未来天文数据处理软件的封装部署提供参考。可以预见,未来容器技术将成为天文海量数据处理的基础支撑技术。 相似文献
4.
5.
微服务架构围绕具体的业务领域组件可创建多个应用,这些应用可以独立开发、部署、管理和加速.在分散的组件中使用微服务和云平台架构,使部署、管理和服务功能交付变得更加简单.本文基于主流公有云平台和Docker容器,以微服务架构和SuperMap云GIS平台技术为框架,构建了企业级在线GIS公有云开发平台Su-perMap Online.该平台在线提供构建GIS Web应用所需的资源,包括Web Apps、GIS数据、开发APIs以及GIS云主机等.其中,GIS云主机内置了GIS服务器软件、许可,不需要安装、部署,在线购买就可以获取完整的GIS服务器. 相似文献
6.
To tackle Big Data challenges such as Volume, Variety, and Velocity, the Earth Observations Data Cube (EODC) concept has emerged as a solution for lowering barriers and offering new possibilities to harness the information power of satellite EO data. However, installing, configuring, and managing an EODC instance is still difficult requiring specific knowledge and capabilities. Consequently, facilitating and automating the generation and provision of EODC given specific user’s requirements can be beneficial.In response to this issue, this paper presents the Data Cube on Demand (DCoD) approach, a proof-of-concept that aims at facilitating the generation and use of an EODC instance virtually anywhere in the World. Users are only required to specify an area of interest; select the types of sensors between Landsat 5-7-8 and Sentinel-2; choose a desired temporal frame; and provide their email address to receive notifications. Then automatically an empty ODC instance is instantiated and desired data are ingested.The proposed approach has been successfully tested in two sites in Bolivia and DRC in the field of environmental monitoring. It has lowered many complexity barriers of such a new technology; greatly facilitated the generation and use of the Data Cube technology; enhanced data sovereignty; and ultimately can help reaching large adoption and acceptance. 相似文献
1