This research paper compares Excel and R language for data analysis and concludes that R language is more suitable for complex data analysis tasks.R language’s open-source nature makes it accessible to everyone,and i...This research paper compares Excel and R language for data analysis and concludes that R language is more suitable for complex data analysis tasks.R language’s open-source nature makes it accessible to everyone,and its powerful data management and analysis tools make it suitable for handling complex data analysis tasks.It is also highly customizable,allowing users to create custom functions and packages to meet their specific needs.Additionally,R language provides high reproducibility,making it easy to replicate and verify research results,and it has excellent collaboration capabilities,enabling multiple users to work on the same project simultaneously.These advantages make R language a more suitable choice for complex data analysis tasks,particularly in scientific research and business applications.The findings of this study will help people understand that R is not just a language that can handle more data than Excel and demonstrate that r is essential to the field of data analysis.At the same time,it will also help users and organizations make informed decisions regarding their data analysis needs and software preferences.展开更多
The use of open-source data and tools in disaster exposure mapping is presented in this paper. Disaster exposure is a collection of the element at risk to potential loss. Gampaha divisional secretariat (DS) is a study...The use of open-source data and tools in disaster exposure mapping is presented in this paper. Disaster exposure is a collection of the element at risk to potential loss. Gampaha divisional secretariat (DS) is a study area laid on the lower part of the Attanagalu Oya river basin. As the geospatial tools, OpenStreetMap (OSM), Java OpenStreetMap (JOSM), QGIS, GPS Essentials, and Open Map Kit (OMK) are used. The elements of disaster exposure, including the number of people or types of assets, are surveyed and inventoried using the OSM platforms. Local, national, and international agencies produce and evaluate the data. The study developed spatial data for building footprints of 165,000 households, street lengths of 2300 km, hospital units of 16, and utility units of 2300. This could overcome the main challenges of exposure mapping in the area. The procedure developed in the exposure mapping can be used in a data-sparse environment. Exposure mapping is generally used to estimate the impact of hazards or disasters, which are essential in effective disaster management. How are there still remaining challenges in disaster exposure mapping such as less awareness about the mapping procedure, lack of government support, internet access, hardware, and inability to understand the value of exposure mapping?展开更多
国家电网工程建设信息化管理模式主要以项目建设业务流为主线,当前BIM技术的引入给建设管理带来新的手段和方式。分析传统信息化管理模式的特点,遵循实用、无感、可用、智能、整体五个基本原则,重新设计电网工程在建筑信息模型(building...国家电网工程建设信息化管理模式主要以项目建设业务流为主线,当前BIM技术的引入给建设管理带来新的手段和方式。分析传统信息化管理模式的特点,遵循实用、无感、可用、智能、整体五个基本原则,重新设计电网工程在建筑信息模型(building information modeling,BIM)环境下数字化建设管理模式,提出“电网工作包”的新理念,设计新模式下数字化管理平台的整体框架,对比分析两种管理模式的应用差异并在某新区电网进行实现和应用,验证新管理模式能有效提升电网建设管理水平。展开更多
文摘This research paper compares Excel and R language for data analysis and concludes that R language is more suitable for complex data analysis tasks.R language’s open-source nature makes it accessible to everyone,and its powerful data management and analysis tools make it suitable for handling complex data analysis tasks.It is also highly customizable,allowing users to create custom functions and packages to meet their specific needs.Additionally,R language provides high reproducibility,making it easy to replicate and verify research results,and it has excellent collaboration capabilities,enabling multiple users to work on the same project simultaneously.These advantages make R language a more suitable choice for complex data analysis tasks,particularly in scientific research and business applications.The findings of this study will help people understand that R is not just a language that can handle more data than Excel and demonstrate that r is essential to the field of data analysis.At the same time,it will also help users and organizations make informed decisions regarding their data analysis needs and software preferences.
文摘The use of open-source data and tools in disaster exposure mapping is presented in this paper. Disaster exposure is a collection of the element at risk to potential loss. Gampaha divisional secretariat (DS) is a study area laid on the lower part of the Attanagalu Oya river basin. As the geospatial tools, OpenStreetMap (OSM), Java OpenStreetMap (JOSM), QGIS, GPS Essentials, and Open Map Kit (OMK) are used. The elements of disaster exposure, including the number of people or types of assets, are surveyed and inventoried using the OSM platforms. Local, national, and international agencies produce and evaluate the data. The study developed spatial data for building footprints of 165,000 households, street lengths of 2300 km, hospital units of 16, and utility units of 2300. This could overcome the main challenges of exposure mapping in the area. The procedure developed in the exposure mapping can be used in a data-sparse environment. Exposure mapping is generally used to estimate the impact of hazards or disasters, which are essential in effective disaster management. How are there still remaining challenges in disaster exposure mapping such as less awareness about the mapping procedure, lack of government support, internet access, hardware, and inability to understand the value of exposure mapping?
文摘国家电网工程建设信息化管理模式主要以项目建设业务流为主线,当前BIM技术的引入给建设管理带来新的手段和方式。分析传统信息化管理模式的特点,遵循实用、无感、可用、智能、整体五个基本原则,重新设计电网工程在建筑信息模型(building information modeling,BIM)环境下数字化建设管理模式,提出“电网工作包”的新理念,设计新模式下数字化管理平台的整体框架,对比分析两种管理模式的应用差异并在某新区电网进行实现和应用,验证新管理模式能有效提升电网建设管理水平。
