• Journal for History of Mathematics
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• v.23 no.2
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• pp.1-21
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• 2010

The first Korean mathematical science journal was published by Yu, Il- Sun in 1905 and the name of this journal is "Mathematical Science magazine". This monthly journal was published for 2 years. But in the existing literature, there is no information about it. We discovered its existence and studied its contents. From the historical materials, pioneering contributions of Yu, Il-Sun to mathematics were provided. In this article, the first issue of this journal was fully analyzed. We could see his affection and enthusiasm for the journal that he started. More mathematical search efforts on finding historical math materials should be continued. More efforts should be made on finding historical math literatures. Related researches will be done. Those works will be worth to be shared in ICME-12 and ICM 2014.

• Journal of radiological science and technology
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• v.46 no.3
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• pp.219-229
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• 2023

In this study, basic characteristics such as reproducibility, linearity, and directionality of RPL glass dosimeters were evaluated to improve the reliability of dose evaluation through RPL glass dosimeters, and uncertainty elements such as sensitivity by glass element and magazine slot sensitivity were evaluated. Using a mathematical model to calibrate the measured values of the RPL glass dosimeter, the measurement uncertainty was calculated assuming an example. As a result of the characteristic evaluation, the RPL glass dosimeter showed excellent performance with a standard deviation of ±1% (1 SD) for the reproducibility of the reading process, a coefficient of determination for linearity of 0.99997. And the read-out of the RPL glass dosimeter are affected by the circular rotation direction of the glass dosimeter during irradiation, fading according to the period after irradiation, the number of laser pulses of the reader, and response degradation due to repeated reading, it is judged that measurement uncertainty can be reduced by irradiation and reading in consideration of these factors. In addition, it was confirmed that the dose should be determined by calculating the correction factors for the sensitivity of each element and, the sensitivity of each reading magazine slot. It is believed that the reliability of dosimetry using glass dosimeters can be improved by using a mathematical model for correction of glass dosimeter readings and calculating measurement uncertainty.

• Electronics and Telecommunications Trends
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• v.36 no.3
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• pp.106-118
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• 2021

The field of brain science (or neuroscience in a broader sense) has inspired researchers in artificial intelligence (AI) for a long time. The outcomes of neuroscience such as Hebb's rule had profound effects on the early AI models, and the models have developed to become the current state-of-the-art artificial neural networks. However, the recent progress in AI led by deep learning architectures is mainly due to elaborate mathematical methods and the rapid growth of computing power rather than neuroscientific inspiration. Meanwhile, major limitations such as opacity, lack of common sense, narrowness, and brittleness have not been thoroughly resolved. To address those problems, many AI researchers turn their attention to neuroscience to get insights and inspirations again. Biologically plausible neural networks, spiking neural networks, and connectome-based networks exemplify such neuroscience-inspired approaches. In addition, the more recent field of brain network analysis is unveiling complex brain mechanisms by handling the brain as dynamic graph models. We argue that the progress toward the human-level AI, which is the goal of AI, can be accelerated by leveraging the novel findings of the human brain network.