no code implementations • 29 Aug 2022 • Yi-Lin Tsai, Dymasius Y. Sitepu, Karyn E. Chappell, Rishi P. Mediratta, C. Jason Wang, Peter K. Kitanidis, Christopher B. Field
Therefore, we applied an age-structured epidemiological model, known as the Susceptible-Exposed-Infectious-Recovered (SEIR) model, to investigate to what extent different vaccine uptake levels and the Diversion protocol implemented in Taiwan decrease infections and delay pandemic peak occurrences.
no code implementations • 27 Aug 2022 • Yi-Lin Tsai, Jeremy Irvin, Suhas Chundi, Andrew Y. Ng, Christopher B. Field, Peter K. Kitanidis
Towards improving this system, we implemented five machine learning models that input historical rainfall data and predict whether a debris flow will occur within a selected time.
no code implementations • 5 Mar 2021 • Yi-Lin Tsai, Chetanya Rastogi, Peter K. Kitanidis, Christopher B. Field
One of the lessons from the COVID-19 pandemic is the importance of social distancing, even in challenging circumstances such as pre-hurricane evacuation.
no code implementations • 18 Jun 2020 • Chang-Shing Lee, Mei-Hui Wang, Wen-Kai Kuan, Zong-Han Ciou, Yi-Lin Tsai, Wei-Shan Chang, Lian-Chao Li, Naoyuki Kubota, Tzong-Xiang Huang, Eri Sato-Shimokawara, Toru Yamaguchi
In this paper, we propose an AI-FML robotic agent for student learning behavior ontology construction which can be applied in English speaking and listening domain.
no code implementations • 10 Jan 2019 • Chang-Shing Lee, Mei-Hui Wang, Li-Wei Ko, Bo-Yu Tsai, Yi-Lin Tsai, Sheng-Chi Yang, Lu-An Lin, Yi-Hsiu Lee, Hirofumi Ohashi, Naoyuki Kubota, Nan Shuo
This paper presents a semantic brain computer interface (BCI) agent with particle swarm optimization (PSO) based on a Fuzzy Markup Language (FML) for Go learning and prediction applications.