Microsoft Excel is essential for the End-User Approach (EUA), offering versatility in data organization, analysis, and visualization, as well as widespread accessibility. It fosters collaboration and informed decision...Microsoft Excel is essential for the End-User Approach (EUA), offering versatility in data organization, analysis, and visualization, as well as widespread accessibility. It fosters collaboration and informed decision-making across diverse domains. Conversely, Python is indispensable for professional programming due to its versatility, readability, extensive libraries, and robust community support. It enables efficient development, advanced data analysis, data mining, and automation, catering to diverse industries and applications. However, one primary issue when using Microsoft Excel with Python libraries is compatibility and interoperability. While Excel is a widely used tool for data storage and analysis, it may not seamlessly integrate with Python libraries, leading to challenges in reading and writing data, especially in complex or large datasets. Additionally, manipulating Excel files with Python may not always preserve formatting or formulas accurately, potentially affecting data integrity. Moreover, dependency on Excel’s graphical user interface (GUI) for automation can limit scalability and reproducibility compared to Python’s scripting capabilities. This paper covers the integration solution of empowering non-programmers to leverage Python’s capabilities within the familiar Excel environment. This enables users to perform advanced data analysis and automation tasks without requiring extensive programming knowledge. Based on Soliciting feedback from non-programmers who have tested the integration solution, the case study shows how the solution evaluates the ease of implementation, performance, and compatibility of Python with Excel versions.展开更多
This research paper has provided the methodology and design for implementing the hybrid author recommender system using Azure Data Lake Analytics and Power BI. It offers a recommendation for the top 1000 Authors of co...This research paper has provided the methodology and design for implementing the hybrid author recommender system using Azure Data Lake Analytics and Power BI. It offers a recommendation for the top 1000 Authors of computer science in different fields of study. The technique used in this paper is handling the inadequate Information for citation;it removes the problem of cold start, which is encountered by very many other recommender systems. In this paper, abstracts, the titles, and the Microsoft academic graphs have been used in coming up with the recommendation list for every document, which is used to combine the content-based approaches and the co-citations. Prioritization and the blending of every technique have been allowed by the tuning system parameters, allowing for the authority in results of recommendation versus the paper novelty. In the end, we do observe that there is a direct correlation between the similarity rankings that have been produced by the system and the scores of the participant. The results coming from the associated scrips of analysis and the user survey have been made available through the recommendation system. Managers must gain the required expertise to fully utilize the benefits that come with business intelligence systems [1]. Data mining has become an important tool for managers that provides insights about their daily operations and leverage the information provided by decision support systems to improve customer relationships [2]. Additionally, managers require business intelligence systems that can rank the output in the order of priority. Ranking algorithm can replace the traditional data mining algorithms that will be discussed in-depth in the literature review [3].展开更多
以某型无人直升机为仿真对象设计了一款飞行模拟系统,该系统由飞行仿真模块、座舱仿真模块、视景仿真模块和控制台模块4部分组成。飞行仿真模块对旋翼、尾桨、机身、平尾、垂尾等各部件进行动力学建模,并使用S函数编写了Simulink模块;...以某型无人直升机为仿真对象设计了一款飞行模拟系统,该系统由飞行仿真模块、座舱仿真模块、视景仿真模块和控制台模块4部分组成。飞行仿真模块对旋翼、尾桨、机身、平尾、垂尾等各部件进行动力学建模,并使用S函数编写了Simulink模块;座舱仿真模块使用GL Studio软件设计了照片级的飞行仪表用于实时显示飞行数据;视景仿真模块是基于Vega Prime仿真平台二次开发的;采用基于MFC(microsoft foundation classes)的多线程方法搭建了基本的仿真框架并设计了控制台模块界面,可以用于和用户的实时交互。最后仿真验证了系统的可行性。展开更多
高效合理的研发管理模式对于加强企业经营管理、提升企业创新能力具有重要的推动作用。围绕微软亚洲研究院(Microsoft Research Asia,MSRA)的研发管理模式进行研究,从发展定位、组织结构、研发环境、绩效管理、人才培养、文化建设以及...高效合理的研发管理模式对于加强企业经营管理、提升企业创新能力具有重要的推动作用。围绕微软亚洲研究院(Microsoft Research Asia,MSRA)的研发管理模式进行研究,从发展定位、组织结构、研发环境、绩效管理、人才培养、文化建设以及对华合作等多个方面阐述了微软亚洲研究院在华发展状况,为中国企业在海外发展研发机构、推动研发国际化提供参考和借鉴。展开更多
文摘Microsoft Excel is essential for the End-User Approach (EUA), offering versatility in data organization, analysis, and visualization, as well as widespread accessibility. It fosters collaboration and informed decision-making across diverse domains. Conversely, Python is indispensable for professional programming due to its versatility, readability, extensive libraries, and robust community support. It enables efficient development, advanced data analysis, data mining, and automation, catering to diverse industries and applications. However, one primary issue when using Microsoft Excel with Python libraries is compatibility and interoperability. While Excel is a widely used tool for data storage and analysis, it may not seamlessly integrate with Python libraries, leading to challenges in reading and writing data, especially in complex or large datasets. Additionally, manipulating Excel files with Python may not always preserve formatting or formulas accurately, potentially affecting data integrity. Moreover, dependency on Excel’s graphical user interface (GUI) for automation can limit scalability and reproducibility compared to Python’s scripting capabilities. This paper covers the integration solution of empowering non-programmers to leverage Python’s capabilities within the familiar Excel environment. This enables users to perform advanced data analysis and automation tasks without requiring extensive programming knowledge. Based on Soliciting feedback from non-programmers who have tested the integration solution, the case study shows how the solution evaluates the ease of implementation, performance, and compatibility of Python with Excel versions.
文摘This research paper has provided the methodology and design for implementing the hybrid author recommender system using Azure Data Lake Analytics and Power BI. It offers a recommendation for the top 1000 Authors of computer science in different fields of study. The technique used in this paper is handling the inadequate Information for citation;it removes the problem of cold start, which is encountered by very many other recommender systems. In this paper, abstracts, the titles, and the Microsoft academic graphs have been used in coming up with the recommendation list for every document, which is used to combine the content-based approaches and the co-citations. Prioritization and the blending of every technique have been allowed by the tuning system parameters, allowing for the authority in results of recommendation versus the paper novelty. In the end, we do observe that there is a direct correlation between the similarity rankings that have been produced by the system and the scores of the participant. The results coming from the associated scrips of analysis and the user survey have been made available through the recommendation system. Managers must gain the required expertise to fully utilize the benefits that come with business intelligence systems [1]. Data mining has become an important tool for managers that provides insights about their daily operations and leverage the information provided by decision support systems to improve customer relationships [2]. Additionally, managers require business intelligence systems that can rank the output in the order of priority. Ranking algorithm can replace the traditional data mining algorithms that will be discussed in-depth in the literature review [3].
文摘以某型无人直升机为仿真对象设计了一款飞行模拟系统,该系统由飞行仿真模块、座舱仿真模块、视景仿真模块和控制台模块4部分组成。飞行仿真模块对旋翼、尾桨、机身、平尾、垂尾等各部件进行动力学建模,并使用S函数编写了Simulink模块;座舱仿真模块使用GL Studio软件设计了照片级的飞行仪表用于实时显示飞行数据;视景仿真模块是基于Vega Prime仿真平台二次开发的;采用基于MFC(microsoft foundation classes)的多线程方法搭建了基本的仿真框架并设计了控制台模块界面,可以用于和用户的实时交互。最后仿真验证了系统的可行性。
文摘高效合理的研发管理模式对于加强企业经营管理、提升企业创新能力具有重要的推动作用。围绕微软亚洲研究院(Microsoft Research Asia,MSRA)的研发管理模式进行研究,从发展定位、组织结构、研发环境、绩效管理、人才培养、文化建设以及对华合作等多个方面阐述了微软亚洲研究院在华发展状况,为中国企业在海外发展研发机构、推动研发国际化提供参考和借鉴。
