• Communications of Mathematical Education
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• v.34 no.1
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• pp.1-15
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• 2020

Today's healthcare, intelligent robots, smart home systems, and car sharing are already innovating with cutting-edge information and communication technologies such as Artificial Intelligence (AI), the Internet of Things, the Internet of Intelligent Things, and Big data. It is deeply affecting our lives. In the factory, robots have been working for humans more than several decades (FA, OA), AI doctors are also working in hospitals (Dr. Watson), AI speakers (Giga Genie) and AI assistants (Siri, Bixby, Google Assistant) are working to improve Natural Language Process. Now, in order to understand AI, knowledge of mathematics becomes essential, not a choice. Thus, mathematicians have been given a role in explaining such mathematics that make these things possible behind AI. Therefore, the authors wrote a textbook 'Basic Mathematics for Artificial Intelligence' by arranging the mathematics concepts and tools needed to understand AI and machine learning in one or two semesters, and organized lectures for undergraduate and graduate students of various majors to explore careers in artificial intelligence. In this paper, we share our experience of conducting this class with the full contents in http://matrix.skku.ac.kr/math4ai/.

• Journal of Distribution Science
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• v.15 no.6
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• pp.77-96
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• 2017

Purpose - This study aims to develop correspondence strategies to the environment change in domestic retail store types. Recently, new types of retails have emerged in retail industries. Therefore, trade area platform has developed focusing on the speed of data, no longer trade area from district border. Besides, 'trade area smart' brings about change in retail types with the development of giga internet. Thus, context shopping is changing the way of consumers' purchase pattern through data capture, technology capability, and algorithm development. For these reasons, the sales estimation model has been shown to be flawed using the notion of former scale and time, and it is necessary to construct a new model. Research design, data, and methodology - This study focuses on measuring retail change in large multi-shopping mall for the outlook for retail industry and competition for trade area with the theoretical background understanding of retail store types and overall domestic retail conditions. The competition among retail store types are strong, whereas the borders among them are fading. There is a greater need to analyze on a new model because sales expectation can be hard to get with business area competition. For comprehensive research, therefore, the research method based on the statistical analysis was excluded, and field survey and literature investigation method were used to identify problems and propose an alternative. In research material, research fidelity has improved with complementing research data related with retail specialists' as well as department stores. Results - This study analyzed trade area survival and its pattern through sales estimation and empirical studies on trade areas. The sales estimation, based on Huff model system, counts the number of households shopping absorption expectation from trade areas. Based on the results, this paper estimated sales scale, and then deducted modified probability model. Conclusions - In times of retail store chain destruction and off-line store reorganization, modified Huff model has problems in estimating sales. Transformation probability model, supplemented by the existing problems, was analyzed to be more effective in competitiveness business condition. This study offers a viable alternative to figure out related trade areas' sale estimation by reconstructing new-modified probability model. As a result, the future task is to enlarge the borders from IT infrastructure with data and evidence based business into DT infrastructure.