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摘要： The article discusses the gender gap in published computer science research in the U.S. in 2019, according to a study by researchers at the Allen Institute for Artificial Intelligence in Seattle, Washington.

关键词： columns   commentaries   computer science   general news   history   information technology   languages   opinions   political   software programming tools  

关键词： columns   commentaries   computer science   general news   history   information technology   languages   opinions   political   software programming tools  

关键词： columns   commentaries   computer science   general news   history   information technology   languages   opinions   political   software programming tools  

摘要： A comprehensive and up-to-date analysis of Computer Science literature (2.87 million papers through 2018) reveals that, if current trends continue, parity between the number of male and female authors will not be reached in this century. Under our most optimistic projection models, gender parity is forecast to be reached by 2100, and significantly later under more realistic assumptions. In contrast, parity is projected to be reached within two to three decades in the biomedical literature. Finally, our analysis of collaboration trends in Computer Science reveals decreasing rates of collaboration between authors of different genders. Copyright © 2019, The Authors. All rights reserved.

关键词： 新工科   计算机科学与技术专业   协同育人机制  

摘要： 为了深入推动新工科建设,落实教育部产学合作协同育人政策,针对计算机科学与技术专业建设的特点,在此基础上探索和构建纵向贯通育人与横向联合育人相结合,校企、校地、校所、校校、校内“五维双向”的协同育人运行机制,并将其运用到人才培养的具体实践中。最后,通过湖南商学院计算机与信息工程学院协同育人的实施效果,分析“五维双向”协同育人运行机制的优势。

关键词： Computer science   Physics   Software  

摘要： Manufacturers are ditching equation editors in word-processing software in favour of the LaTeX typesetting language. Here's how to get started.

关键词： Arts   Computer science   History  

摘要： Can artificial intelligence crack long-standing puzzles in art history? David Adam finds out.

关键词： Forecasting  

摘要： —Global gender disparity in science is an unsolved problem. Predicting gender has an important role in analysing the gender gap through online data. We study this problem within the UK, Malaysia and China. We enhance the accuracy of an existing gender prediction tools of names that can predict the sex of Chinese characters and English characters simultaneously and with more precision. During our research, we found that there is no free gender forecasting tool to predict an arbitrary number of names. We addressed this shortcoming by providing a tool that can predict an arbitrary number of names with free requests. We demonstrate our tool through a number of experimental results. We show that this tool is better than other gender prediction tools of names for analysing social problems with big data. In our approach, lists of data can be dynamically processed and the results of the data can be displayed with a dynamic graph. We present experiments of using this tool to analyse the gender disparity in computer science in the UK, Malaysia and China. Copyright © 2019, The Authors. All rights reserved.