Machine learning-based inverse design methods considering data characteristics and design space size in materials design and manufacturing: a review.

In the last few decades, the influence of machine learning has permeated many areas of science and technology, including the field of materials science. This toolkit of data driven methods accelerated the discovery and production of new materials by accurately predicting the complicated physical processes and mechanisms that are not fully described by existing materials theories. However, the availability of a growing number of increasingly complex machine learning models confronts us with the question of "which machine learning algorithm to employ".

Development and Utilization of a Rapid and Accurate Epidemic Investigation Support System for COVID-19.

Objectives: In this pandemic situation caused by a novel coronavirus disease in 2019 (COVID-19), an electronic support system that can rapidly and accurately perform epidemic investigations, is needed. It would systematically secure and analyze patients' data (who have been confirmed to have the infection), location information, and credit card usage.

Methods: The "Infectious Disease Prevention and Control Act" in South Korea, established a legal basis for the securement, handling procedure, and disclosure of information required for epidemic investigations.

Design of a Broadband Solar Thermal Absorber Using a Deep Neural Network and Experimental Demonstration of Its Performance.

In using nanostructures to design solar thermal absorbers, computational methods, such as rigorous coupled-wave analysis and the finite-difference time-domain method, are often employed to simulate light-structure interactions in the solar spectrum. However, those methods require heavy computational resources and CPU time. In this study, using a state-of-the-art modeling technique, i.

Bayesian inference of the flow resistivity of a sound absorber and the room's influence on the Sabine absorption coefficients.

A Bayesian analysis is applied to determine the flow resistivity of a porous sample and the influence of the test chamber based on measured Sabine absorption coefficient data. The Sabine absorption coefficient measured in a reverberation chamber according to ISO 354 is influenced by the test chamber significantly, whereas the flow resistivity is a rather reproducible material property, from which the absorptive characteristics can be calculated through reliable models. Using Sabine absorption coefficients measured in 13 European reverberation chambers, the maximum a posteriori and the uncertainty of the flow resistivity and the test chamber's influence are estimated.

Respiratory effects of the hebei spirit oil spill on children in taean, Korea.

Purpose: The oil spill from the Heibei Spirit in December 2007 contaminated the Yellow Coast of South Korea. We evaluated the respiratory effects of that spill on children who lived along the Yellow Coast.

Methods: Of 662 children living in the area exposed to the oil spill, 436 (65.