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Learning module that provides an analogy to chemical kinetics and is designed to easily understand its mechanisms. The program handles a basic kinetic reactions A → B and the progress of the reactinons including monomolecular, bimolecular, catalytic, autocatalytic, consecutive, and equilibrium reactions. https://masayukinagai.shinyapps.io/kineticgames/
Web application that allows users to simulate enzyme kinetics data and Michaelis-Menten plots, designed to help the teaching and learning of chemistry. https://masayukinagai.shinyapps.io/enzyme/
Web application that provides extraction of Variants of Uncertain Significance (VUS) entries on ClinVar together with relevant information such as prediction score from CADD, allele frequency from gnomAD, structural data from PDB.
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Published in Proceedings of the AAAI Conference on Artificial Intelligence, 2021
This paper presents the design and training of an autonomous Gin Rummy player. The system consists of three core components responsible for decision-making in card drawing, discarding, and game termination. An ensemble-based strategy is employed to improve discard decisions, and a genetic algorithm is used for model tuning. The paper concludes with an analysis of parameter optimization and performance evaluation across three experimental configurations.
Nagai, Masayuki, Kavya Shrivastava, Kien Ta, Steven Bogaerts, and Chad Byers. "A Highly-Parameterized Ensemble to Play Gin Rummy." Proceedings of the AAAI Conference on Artificial Intelligence, vol. 35, no. 17, pp. 15614-15621. 2021.
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Undergraduate course, University 1, Department, 2014
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Workshop, University 1, Department, 2015
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