From Stars to Baht: Broadening the economic impact of astronomical data handling techniques in Thailand - Phase II

从星星到泰铢：扩大泰国天文数据处理技术的经济影响 - 第二阶段

• 批准号: ST/S002820/1
• 负责人: James Mullaney
• 金额: $ 18.56万
• 依托单位: University of Sheffield
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=ST%2FS002820%2F1
• 关键词: Stars; Baht; Broadening; economic; impact

The most effective way of reducing levels of poverty in developing countries is through their continued economic development, which leads to increased levels of income per person. Research has shown that one of the main ways of achieving this is through maintained increases in levels of productivity (defined as output per hour worked) within businesses and organisations. For an upper-middle income economy such as Thailand's, productivity growth will increasingly rely on innovation, which today requires access to high-tech skills. With more and more Thai industries collecting data on their customers, production lines, distribution networks, stock prices, etc., one of the most crucially needed high-tech skill is the ability to handle large amounts of digital data. Our ongoing project aims to provide such skills for businesses and organisations across Thailand, especially those regions outside Bangkok which have traditionally suffered from weaker economic growth. The first step in this project - for which we received Newton funding - was to use large astronomical datasets to expose Thai data scientists based at Mae Fah Luang University (MFU) to "Big Data". This was followed by a GCRF Foundation Award to facilitate working with five pre-selected regional businesses and organisations, during which we worked with undergraduate students to research how to adapt our technologies and skills to meet the data handling and analysis needs of these external partners. Following the success of our Foundation Award project, we now request GCRF funds to support the expansion of the project to include a broader range of larger external partners with a more national presence. This will provide MFU with the exposure needed to become a self-sustaning hub for data science research and training within Northern Thailand.

降低发展中国家贫困水平的最有效方法是通过其持续的经济发展，这导致人均收入水平增加。研究表明，实现此目的的主要方法之一是通过在企业和组织中维持生产率水平（定义为每小时工作的产出）的水平提高。对于像泰国这样的中上层收入经济，生产率的增长将越来越依赖创新，这今天需要获得高科技技能。随着越来越多的泰国行业收集有关其客户，生产线，分销网络，股票价格等的数据，最重要的高科技技能之一就是能够处理大量数字数据。我们正在进行的项目旨在为泰国各地的企业和组织提供此类技能，尤其是曼谷以外的那些传统上经济增长较弱的地区。该项目的第一步 - 我们获得了牛顿资金 - 是使用大型天文数据集将基于Mae Fah Luang大学（MFU）的泰国数据科学家揭示“大数据”。接下来是GCRF基金会奖，以促进与五个预先选择的区域企业和组织合作，在此期间，我们与本科生一起研究了如何适应我们的技术和技能，以满足这些外部合作伙伴的数据处理和分析需求。在我们的基金会奖项项目成功之后，我们现在要求GCRF资金支持该项目的扩展，以包括更广泛的更大外部合作伙伴，并拥有更多的国家业务。这将为MFU提供成为泰国北部数据科学研究和培训的自定义枢纽所需的接触。

项目成果

Exploiting Consensus Clustering for Light Curve Data Analysis

利用共识聚类进行光曲线数据分析

• DOI: 10.1109/ecice47484.2019.8942715
• 发表时间: 2019
• 作者: Panwong P

Classification of Astronomical Objects Using Light Curve Profile

使用光曲线轮廓对天体进行分类

• DOI: 10.1109/ecice47484.2019.8942673
• 发表时间: 2019
• 作者: Sangjan T