• Journal of Engineering Education Research
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• v.24 no.4
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• pp.30-40
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• 2021

The purpose of this study is to verify the effectiveness the IoT program in online, and explore the applicability of the design course in consideration of design elements and realistic constraints for engineering education accreditation in online. For this study, IoT programs developed based on online classes were operated, and the effectiveness as a subject was verified through satisfaction surveys, competency test, and interview of participating students. In addition, by presenting design elements and realistic constraints in a online environment required to apply to engineering design courses, it is expected that they can be used as basic data in developing and operating actual design curriculum.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.2
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• pp.78.3-78.3
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• 2019

We develop a novel technique that can constrain the evolutionary track of the epoch of reionization (EoR) by applying the convolutional neural network (CNN) to the 21-cm differential brightness temperature. We use 21cmFAST, a fast semi-numerical cosmological 21-cm signal simulator, to produce mock 21-cm map between z=6-13. We design a CNN architecture that predicts the volume-averaged neutral hydrogen fraction from the given 21-cm map. The estimated neutral fraction has a good agreement with its truth value even after smoothing the 21-cm map with somewhat realistic choices of beam size and the frequency bandwidth of the Square Kilometre Array (SKA). Our technique could be further utilized to denoise the 21-cm map or constrain the properties of the radiation sources.