Science and technology fields and higher education institutions with mathematically trained contributors: Metadata analysis of IEEE papers
Science and technology fields and higher education institutions with mathematically trained contributors: Metadata analysis of IEEE papers
复制标题
拥有受过数学训练的贡献者的科技领域和高等教育机构：IEEE 论文的元数据分析
DOI：
10.1109/fie49875.2021.9637271
复制
发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Ikegawa Takashi
中科院分区：
文献类型：
--
作者：
山根由子;齊藤知範;齊藤知範;中迫由実;齊藤知範;Tomonori Saito;齊藤知範;菅澤貴之;桑畑洋一郎;菅澤貴之;菅澤貴之;桑畑洋一郎;Ikegawa Takashi;Ikegawa Takashi
最近，缺乏受过数学训练的个人，他们可以将数学知识和技能与其他类型的知识和技能相结合，从而有助于创新，这一点已经变得很明显。为了找到解决这个问题的线索，我们确定了科学和技术领域（STFs），需要数学训练的贡献者，并确定高等教育机构（HEIs），为学生提供机会，发展所需的数学知识的STFs。我们通过分析IEEE期刊中大量论文的元数据来执行此操作，这些元数据可以通过Scopus API轻松访问。元数据包含作者的从属关系信息，这对于识别具有数学系的高等院校是有用的。例如，如果作者的隶属关系信息包含与数学相关的术语，例如“数学系”或“系”。数学，”可以认为提交人受过高等数学训练。我们证明，1）数学训练的个人所发表的IEEE论文所涵盖的研究领域的贡献继续增加，2）他们的贡献是特别重要的微STFs，如信息论，可靠性，模糊系统和神经网络，和3）他们的贡献程度不同的各种STF集中的期刊之间的高校。
Recently, the shortage of mathematically trained individuals who can integrate mathematical knowledge and skills with other types of knowledge and skills and thereby contribute to innovation has become apparent. To find clues for solving this problem, we identify scientific and technology fields (STFs) that require mathematically trained contributors and identify higher education institutions (HEIs) that provide students an opportunity to develop the mathematical knowledge needed in the STFs. We perform this by analyzing a large amount of metadata of papers in IEEE journals, which is easily accessible via the Scopus API. The metadata contains author's affiliation information, which is useful for identifying HEIs with a mathematical faculty. For example, if an author's affiliation information contains terms related to mathematics such as “Department of Mathematics” or “Dept. of Math.,” the author can be considered to have had advanced mathematical training. We demonstrate that 1) the contributions of mathematically trained individuals to research fields covered by published IEEE papers have continued to increase, 2) their contributions are particularly important to micro-STFs such as information theory, reliability, fuzzy systems, and neural networks, and 3) the degree of their contributions to the various STF-focused journals differs between HEIs.