• Korean Journal of Radiology
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• v.24 no.8
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• pp.807-820
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• 2023

Objective: To assess whether computed tomography (CT) conversion across different scan parameters and manufacturers using a routable generative adversarial network (RouteGAN) can improve the accuracy and variability in quantifying interstitial lung disease (ILD) using a deep learning-based automated software. Materials and Methods: This study included patients with ILD who underwent thin-section CT. Unmatched CT images obtained using scanners from four manufacturers (vendors A-D), standard- or low-radiation doses, and sharp or medium kernels were classified into groups 1-7 according to acquisition conditions. CT images in groups 2-7 were converted into the target CT style (Group 1: vendor A, standard dose, and sharp kernel) using a RouteGAN. ILD was quantified on original and converted CT images using a deep learning-based software (Aview, Coreline Soft). The accuracy of quantification was analyzed using the dice similarity coefficient (DSC) and pixel-wise overlap accuracy metrics against manual quantification by a radiologist. Five radiologists evaluated quantification accuracy using a 10-point visual scoring system. Results: Three hundred and fifty CT slices from 150 patients (mean age: 67.6 ± 10.7 years; 56 females) were included. The overlap accuracies for quantifying total abnormalities in groups 2-7 improved after CT conversion (original vs. converted: 0.63 vs. 0.68 for DSC, 0.66 vs. 0.70 for pixel-wise recall, and 0.68 vs. 0.73 for pixel-wise precision; P < 0.002 for all). The DSCs of fibrosis score, honeycombing, and reticulation significantly increased after CT conversion (0.32 vs. 0.64, 0.19 vs. 0.47, and 0.23 vs. 0.54, P < 0.002 for all), whereas those of ground-glass opacity, consolidation, and emphysema did not change significantly or decreased slightly. The radiologists' scores were significantly higher (P < 0.001) and less variable on converted CT. Conclusion: CT conversion using a RouteGAN can improve the accuracy and variability of CT images obtained using different scan parameters and manufacturers in deep learning-based quantification of ILD.

• Education of Primary School Mathematics
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• v.27 no.2
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• pp.111-137
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• 2024

The purpose of this study is to identify the expected difficulties and necessary support when applying the 2022 revised mathematics curriculum to elementary schools, and to support the establishment of the field. To this end, we explored the major changes in the 2022 revised mathematics curriculum, and based on this, we conducted a survey of elementary school teachers to identify the expected difficulties and necessary support when applying it in the field. In particular, when analyzing the results, we also examined whether there were any differences in the expected difficulties and necessary support depending on the size of the school where it is located and the teaching experience of the teacher. The research results are as follows. First, the proportion of teachers who expect difficulties in applying the 2022 revised mathematics curriculum was mostly below 50%, but the proportion of teachers who demand support was much higher, at around 80%. Second, the difficulty of elementary school teachers in applying the 2022 revised mathematics curriculum was found to be the greatest in evaluation. Third, in relation to the use of edutech, teachers in elementary schools are also expected to have difficulties in teaching and learning methods to foster students' digital literacy, assessment using teaching materials or engineering tools, and assessment in online environments. Fourth, the difficulty of elementary school teachers in applying the 2022 revised mathematics curriculum was also significant in relation to mathematics subject competencies. Fifth, it was found that there is also difficulty in understanding the major changes of the achievement standards, including the addition, deletion, and adjustment of the achievement standards, and the impact on the learning of other achievement standards. Finally, the responses of elementary school teachers to the expected difficulties and necessary support in applying the 2022 revised mathematics curriculum did not differ depending on the size of the school where it is located, but statistically significant differences were found in a number of items depending on the teaching experience of the teacher. Based on these research results, we hope that various support will be provided for the 2022 revised mathematics curriculum, which will be applied annually from 2024.

• The Mathematical Education
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• v.63 no.2
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• pp.123-138
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• 2024

This study described the utilization of ChatGPT in teaching and students' learning processes for the course "Introductory Mathematics for Artificial Intelligence (Math4AI)" at 'S' University. We developed a customized ChatGPT and presented a learning model in which students supplement their knowledge of the topic at hand by utilizing this model. More specifically, first, students learn the concepts and questions of the course textbook by themselves. Then, for any question they are unsure of, students may submit any questions (keywords or open problem numbers from the textbook) to our own ChatGPT at https://math4ai.solgitmath.com/ to get help. Notably, we optimized ChatGPT and minimized inaccurate information by fully utilizing various types of data related to the subject, such as textbooks, labs, discussion records, and codes at http://matrix.skku.ac.kr/Math4AI-ChatGPT/. In this model, when students have questions while studying the textbook by themselves, they can ask mathematical concepts, keywords, theorems, examples, and problems in natural language through the ChatGPT interface. Our customized ChatGPT then provides the relevant terms, concepts, and sample answers based on previous students' discussions and/or samples of Python or R code that have been used in the discussion. Furthermore, by providing students with real-time, optimized advice based on their level, we can provide personalized education not only for the Math4AI course, but also for any other courses in college math education. The present study, which incorporates our ChatGPT model into the teaching and learning process in the course, shows promising applicability of AI technology to other college math courses (for instance, calculus, linear algebra, discrete mathematics, engineering mathematics, and basic statistics) and in K-12 math education as well as the Lifespan Learning and Continuing Education.

• Journal of the Korean Society of Radiology
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• v.84 no.1
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• pp.185-196
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• 2023

Purpose This study aimed to investigate radiomics analysis of ultrasonographic images to develop a potential biomarker for predicting lymph node metastasis in papillary thyroid carcinoma (PTC) patients. Materials and Methods This study included 431 PTC patients from August 2013 to May 2014 and classified them into the training and validation sets. A total of 730 radiomics features, including texture matrices of gray-level co-occurrence matrix and gray-level run-length matrix and single-level discrete two-dimensional wavelet transform and other functions, were obtained. The least absolute shrinkage and selection operator method was used for selecting the most predictive features in the training data set. Results Lymph node metastasis was associated with the radiomics score (p < 0.001). It was also associated with other clinical variables such as young age (p = 0.007) and large tumor size (p = 0.007). The area under the receiver operating characteristic curve was 0.687 (95% confidence interval: 0.616-0.759) for the training set and 0.650 (95% confidence interval: 0.575-0.726) for the validation set. Conclusion This study showed the potential of ultrasonography-based radiomics to predict cervical lymph node metastasis in patients with PTC; thus, ultrasonography-based radiomics can act as a biomarker for PTC.

• Journal of the Korean Society of Radiology
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• v.84 no.3
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• pp.638-652
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• 2023

Purpose To investigate the MRI markers for the prediction of amyloid β (Aβ)-positivity in mild cognitive impairment (MCI) and Alzheimer's disease (AD), and to evaluate the differences in MRI markers between Aβ-positive (Aβ [+]) and -negative groups using the machine learning (ML) method. Materials and Methods This study included 139 patients with MCI and AD who underwent amyloid PET-CT and brain MRI. Patients were divided into Aβ (+) (n = 84) and Aβ-negative (n = 55) groups. Visual analysis was performed with the Fazekas scale of white matter hyperintensity (WMH) and cerebral microbleeds (CMB) scores. The WMH volume and regional brain volume were quantitatively measured. The multivariable logistic regression and ML using support vector machine, and logistic regression were used to identify the best MRI predictors of Aβ-positivity. Results The Fazekas scale of WMH (p = 0.02) and CMB scores (p = 0.04) were higher in Aβ (+). The volumes of hippocampus, entorhinal cortex, and precuneus were smaller in Aβ (+) (p < 0.05). The third ventricle volume was larger in Aβ (+) (p = 0.002). The logistic regression of ML showed a good accuracy (81.1%) with mini-mental state examination (MMSE) and regional brain volumes. Conclusion The application of ML using the MMSE, third ventricle, and hippocampal volume is helpful in predicting Aβ-positivity with a good accuracy.

• Journal of The Korean Association For Science Education
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• v.44 no.2
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• pp.167-178
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• 2024

In this study, we investigated the perceptions of science-related careers and career education among middle school science teachers. Sixty-four science teachers experienced in teaching unit 7 in the first year of middle school participated. The results of the study revealed that not only careers in science but also careers with science were found to be quite high when teachers were asked to provide examples of science-related careers. Jobs related to research/engineering, which are careers in science, comprised the highest proportion of teachers' answers, followed by jobs related to education/law/social welfare/police/firefighting/military, and health/medical, which are careers with science. However, the proportion of jobs mentioned related to installation/maintenance/production was extremely low. The skills required for science-related careers were mainly perceived to consist of tools for working and ways of working. The number of skills classified under living in the world was perceived to be extremely low across most careers, irrespective of career type. Most teachers only taught unit 7 for two to four sessions and devoted little time to science-related career education, even in general science classes. In the free semester system, a significant number of teachers responded that they provide science-related career education for more than 8 hours. Teachers mainly utilize lecture, discussion/debate, and self-study activities. Meanwhile, in the free semester system, the resource-based learning method was utilized at a high proportion compared to other class situations. Teachers generally made much use of media materials, with the use of textbooks and teacher guides found to be lower than expected. There were also cases of using materials supported by science museums or the Ministry of Education. Teachers preferred to implementing student-centered classes and utilizing various teaching and learning methods. Based on the above research results, discussions were proposed to improve teachers' perceptions of science-related careers and career education.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.11 no.3
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• pp.108-116
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• 2006

To investigate the factors controlling the spring population of Acartia hongi, egg production, hatching time of egg and predation pressure were measured. Egg production was maintained the superior position between winter and spring. Egg production was positively correlated with not only water temperature when water temperature was below $7^{\circ}C$ but also chlorophyll-a concentration when it was from $7^{\circ}C$ to $21^{\circ}C$. A regressive equation of development time$(D_e,\;day)$ of eggs derived from water temperature$(T,\;^{\circ}C)$ was obtained as $D_e=18.9(T-0.4)^{-1.0}$, showing longer development time at water temperature below $5^{\circ}C$. In Cross Correlation Analysis(CCA) to examine the time-lag relationship among abundances of developmental stages of A. hongi, egg production rate calculated by multiplying population egg production rate by hatching time showed more significant correlation with nauplii abundance than population egg production rate. Therefore, it suggests that hatching time is also recognized by a factor controlling formation of population and especially, in winter, high abundance of egg derived from high daily egg production rate and delayed hatch by low water temperature become the origin of initial spring population of nauplii. Egg predation by Noctiluca scintillans, suggesting a negative factor in formation of A. hongi spring population, was observed. During spring, A. hongi eggs were found in $2.9\sim21.1%$ of individuals of N. scintillans. It was deduced that $1.2\sim49.5%$ of the eggs produced by A. hongi was preyed on by N. scintillans. In conclusion, the factors controlling spring population of A. hongi were regarded as high egg production by winter generation, the delayed development time of egg by low temperature, and egg predation of N. scintillans.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.11 no.4
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• pp.158-164
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• 2006

Yongdam Lake is the fifth largest artificial lake in Korea newly formed by the first impounding the Yongdam Multi-purpose Dam on December, 2002. Yongdam Lake, with her total water storage of 820 million M/T, is located at the roof-top region of the streams flowing into the just-constructed new Saemankeum Lake. Seasonal succession of phytoplakton in Yongdam Lake might affect cyanobacterial blooms in Saemankeum Lake by inoculating seasonal dominants. During 2002-2003 when the first impounding after the construction of Yongdam Multi-purpose Dam was still undergoing, summer cyanobacterial blooms by Anabaena, Microcystis, and Aphanizomenon were observed. Among these three, filamentous Anabaena is well known to have its species with $N_2-fixing$ ability and special cells such as heterocysts and akinetes as well as the vegetative cells. We established a clonal culture of Anabaena spiroides v. crasse (KNU-YD0310) from the live water samples collected at the bloom site of Yongdam Lake. The N- and P-nutrient requirement of the KNU-YD0310 was explored by the experimental cultivation of the laboratory strain. Ratio of heterocysts to vegetative cells increased as N-deficiency extended with its maximum at $N_2-fixing$ condition. The strain KNU-YD0310 exhibited considerable growth under N-limiting conditions while its growth was proportional to the initial phosphate-P concentration under P-deficient conditions. Under P-limiting conditions akinete density increased, which could be interpreted as an adaptation strategy to survive severe environment by transforming into resting stage. The above eco-physiological characteristics of Anabaena spiroides v. crassa might be useful as an ecological criterion in controlling cyanobacterial blooms at Shaemankeum Lake in near future.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.15 no.1
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• pp.8-15
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• 2010

An experiment was conducted to evaluate the biologically adverse effect of increased carbon dioxide in seawater on marine bacteria, Vibrio fischeri. We measured the bioluminescence and cell density at every 6 hours for 24 hours of the whole incubation period after exposing test microbes to a range of $CO_2$ concentration such as 380(Control), 1,000, 3,000, 10,000 and 30,000 ppm, respectively. Significant effect on relative luminescence(RLU) of V. fischeri was observed in treatments with $CO_2$ concentration higher than 3,000 ppm at t=12 h. However, the difference of RLU among treatments significantly decreased with the incubation time until t=24 h. Similar trend was observed for the variation of cell density, which was measured as optical density using spectrophotometer. The results showed that a significant relationship between $CO_2$ concentration and bioluminescence of test microbes was observed for the mean time. However, the inhibition of relative bioluminescence and also cell density could be recovered at the concentration levels higher than 3,000 ppm. The dissolved $CO_2$ can be absorbed directly by cell and it can decrease the intracellular pH. Our results implied that microbes might be adversely affected at the initial growing phase by increased $CO_2$. However, they could adapt by increasing ion transport including bicarbonate and then could make their pH back to normal level. Results of this study could be supported to understand the possible influence on marine bacteria by atmospheric increase of $CO_2$ in near future and also by released $CO_2$ during the marine $CO_2$ sequestration activity.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.15 no.1
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• pp.41-50
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• 2010

We have developed an in-situ benthic chamber (BelcI) for use in coastal studies that can be deployed from a small boat. It is expected that BelcI will be useful in studying the benthic boundary layer because of its flexibility. BelcI is divided into three main areas: 1) frame and body chamber, 2) water sampler, and 3) stirring devices, electric controller, and data acquisition technology. To maximize in-situ use, the frame is constructed from two layers that consist of square cells. All electronic parts (motor controller, pA meter, data acquisition, etc.) are low-power consumers so that the external power supply can be safely removed from the system. The hydrodynamics of BelcI, measured by PIV (particle image velocimetry), show a typical "radial-flow impeller" pattern. Mixing time of water in the chamber is about 30 s, and shear velocity ($u^*$) near the bottom layer was calculated at $0.32\;cm\;s^{-1}$. Measurements of diffusivity boundary layer thickness showed a range of $180-230\;{\mu}m$. Sediment oxygen consumption rate, measured in-situ，was $84\;mmol\;O_2\;m^{-2}\;d_{-1}$, more than two times higher than on-board incubation results. Benthic fluxes assessed from in-situ incubation were estimated as follows: nitrate + nitrite = $0.18\;{\pm}\;0.07\;mmol\;m^{-2}\;d^{-1}$ ammonium $23\;{\pm}\;1\;mmol\;m^{-2}\;d^{-1}$ phosphate = $0.09\;{\pm}\;0.02\;mmol\;m^{-2}\;d^{-1}$ and silicate = $23\;{\pm}\;1\;mmol\;m^{-2}\;d^{-1}$.