Level: Advanced
【Presenter】
Interuniversity Research Institute Corporation Research Organization of Information and Systems Institute of Statistical Mathematics Risk Analysis Strategy Research Center Takenori Takahashi
[Presentation summary]
A paradigm is the foundation on which a way of thinking is based, or in other words, it is a way of looking at the essence of a subject. And if you change your perspective, your approach will change significantly. Paradigm shifts have occurred many times in various fields throughout their respective histories. A typical example is the paradigm shift from geocentric to heliocentric. Paradigms have no absolute destiny, and it is inevitable that they will shift to the next paradigm over time.
This study discusses the current paradigm shift in the design field. In conventional mathematical design theory, optimization is based on multivariate multiple regression equations. This study introduces a paradigm called superdesign, which is optimization using superstructure functions of multilayer structures based on superfactors. The design under this condition is significantly different from previous designs.
Superfactors are design factors that can be specified and changed freely. The multilayered superstructure function based on superfactors allows differentiation and integration with respect to superfactors, making it possible to perform mathematically advanced designs. Furthermore, the formulation becomes confusing when the number of parameters related to the superstructure function is large. In this case, a multiparameter problem is solved using a method called an assignment function.
[Presenter profile]
After serving as a professor at Tokyo University of Science's Faculty of Engineering, Keio University's Graduate School, and then Mejiro University's Faculty of Business Administration, he currently continues his research and data science education as a visiting professor at the Institute of Statistical Mathematics. In terms of research, he proposes a new design paradigm, superdesign, in the field of engineering, and new analysis methods, two-sided causal analysis and virtual experiments, in the field of social science.
On the other hand, while I was a graduate student, I developed the theory of competitive skiing (mainly slalom and giant slalom) and taught practical skills to a certain university's ski club for several years, and published the contents as a book on competitive skiing theory, in parallel with my specialized research. Based on this experience, we have been implementing active data science education, which is statistical education based on practical training, at universities, graduate schools, companies, and various seminars for about half a century.
During his sabbatical, he advanced his research on super-design at Yale University in the United States and developed an assembling biplane helicopter as a real teaching material. The former is the main theme of the author's research, and the latter is a full-fledged actual teaching material that can take more than a dozen variables (factors) and can also handle quadratic models. In addition, we have also developed a paper glider as an extremely advanced real-life teaching material, and coin shooting, a general-purpose real-life teaching material aimed at everyone from beginners to experts.
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[Collection of papers]
Go to the collection website
https://community.jmp.com/t5/Discovery-Summit-Japan-2023/Discovery-Summit-Japan-2023-%E8%AB%96%E6%96%87%E9%9B%86/ta-p /718363
