• Progress in Medical Physics
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• v.30 no.4
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• pp.94-103
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• 2019

Purpose: To evaluate the clinical feasibility of knowledge-based planning (KBP) for volumetric-modulated arc radiotherapy (VMAT) in spine stereotactic body radiotherapy (SBRT). Methods: Forty-eight VMAT plans for spine SBRT was studied. Two planning target volumes (PTVs) were defined for simultaneous integrated boost: PTV for boost (PTV-B: 27 Gy/3fractions) and PTV elective (PTV-E: 24 Gy/3fractions). The expert VMAT plans were manually generated by experienced planners. Twenty-six plans were used to train the KBP model using Varian RapidPlan. With the trained KBP model each KBP plan was automatically generated by an individual with little experience and compared with the expert plan (closed-loop validation). Twenty-two plans that had not been used for KBP model training were also compared with the KBP results (open-loop validation). Results: Although the minimal dose of PTV-B and PTV-E was lower and the maximal dose was higher than those of the expert plan, the difference was no larger than 0.7 Gy. In the closed-loop validation, D_1.2cc, D_0.35cc, and D_mean of the spinal cord was decreased by 0.9 Gy, 0.6 Gy, and 0.9 Gy, respectively, in the KBP plans (P<0.05). In the open-loop validation, only D_mean of the spinal cord was significantly decreased, by 0.5 Gy (P<0.05). Conclusions: The dose coverage and uniformity for PTV was slightly worse in the KBP for spine SBRT while the dose to the spinal cord was reduced, but the differences were small. Thus, inexperienced planners could easily generate a clinically feasible plan for spine SBRT by using KBP.

• Education of Primary School Mathematics
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• v.21 no.2
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• pp.111-130
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• 2018

In this study, I compared and analyzed the contents of Korean, Japanese, Singapore, American, and Finnish textbooks about fraction which is one of the important and difficult concepts in elementary school mathematics. This is aimed to get the implications for meaningful fractional teaching and learning by analyzing the advantages and disadvantages of the methods and time of introducing the concept because fraction has the diversity of the sub-concepts and the introducing methods or process. As a result of the analysis, the fraction was introduced as part-whole(area) in all five countries' textbooks, but the use of number line, conversion between improper fraction and mixed number, whether to deal with part-whole(set) model. Furthermore, there are differences in the methods in obtaining of the equivalent fraction and the order of arrangement in comparison of fraction. Through this analysis, we discussed the reconsideration of the introducing contexts of fractions, the use of number line when introducing fractions, and the problem of segmentation and classification of contents.

• Education of Primary School Mathematics
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• v.19 no.1
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• pp.19-30
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• 2016

This study examined pre-service teachers' pedagogical content knowledge of fraction division in a context where they were asked to write a story problem for a symbolic expression illustrating a whole number divided by a proper fraction. Problem-posing is an important instructional strategy with the potential to create meaningful contexts for learning mathematical concepts, especially when real-world applications are intended. In this study, story problems written by 135 elementary pre-service teachers were analyzed with respect to mathematical correctness. error types, and division models. Patterns and tendencies in elementary pre-service teachers' knowledge of fraction division were identified. Implicaitons for teaching and teacher education are discussed.

• Journal of Elementary Mathematics Education in Korea
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• v.7 no.1
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• pp.45-64
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• 2003

This study analyzes divisor and multiple in elementary school mathematics textbooks published according to the first to the 7th curriculum, in a view point of the didactic transposition theory. In the first and second textbooks, the divisor and the multiple are taught in the chapter whose subject is on the calculations of the fractions. In the third and fourth textbooks, divisor and multiple became an independent chapter but instructed with the concept of set theory. In the fifth, the sixth, and the seventh textbooks, not only divisor multiple was educated as an independent chapter but also began to be instructed without any conjunction with set theory or a fractions. Especially, in the seventh textbook, the understanding through activities of students itself are strongly emphasized. The analysis on the each curriculum periods shows that the divisor and the multiple and the reduction of a fractions to the lowest terms and to a common denominator are treated at the same period. Learning activity elements are increase steadily as the textbooks and the mathematical systems are revised. The following conclusion can be deduced based on the textbook analysis and discussion for each curriculum periods. First, loaming instruction method also developed systematically with time. Second, teaching method of the divisor and multiple has been sophisticated during the 1st to 7th curriculum textbooks. And the variation of the teaching sequences of the divisor and multiple is identified. Third, we must present concrete models in real life and construct textbooks for students to abstract the concepts by themselves. Fourth, it is necessary to develop some didactics for students' contextualization and personalization of the greatest common divisor and least common multiple. Fifth, the 7th curriculum textbooks emphasize inquiries in real life which teaming activities by the student himself or herself.

• The Korean Journal of Food And Nutrition
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• v.34 no.5
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• pp.487-497
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• 2021

To investigate the industrial availability of liquid fermentation (PL-ferment) by Phellinus linteus mycelium as a postbiotics for the inhibition of inflammation, PL-ferment was fractionated into culture supernatant (CS), hot-water extract (HW) from PL-ferment, EtOH-precipitate (CP) fractionated from HW, and the dialysate (DCP) of CP. Compared to the other fractions, DCP which is expected to contain exopolysaccharide (EPS) as the major component, significantly decreased the production of NO, IL-6, and MCP-1 in LPS-induced RAW 264.7 cells, and IL-6 and IL-8 in TNF-α and IFN-γ-induced HaCaT cells. The general component analysis results showed that no significant difference in components was observed between the fractions, whereas sugar composition analysis revealed that DCP had decreased glucose and increased mannose contents compared to the other fractions. This suggests that mannose played an important role in the anti-inflammatory activity of the active fraction, DCP. Molecular weight distribution analysis revealed that DCP was mainly composed of low-molecular-weight material-removed high-molecular-weight polysaccharides of 18-638 kDa, suggesting that EPS originated from P. linteus EPS. In conclusion, our results suggest that the DCP of P. linteus mycelium fermentation using the anti-inflammatory activity could be used industrially as postbiotic material.

• Journal of Science Education
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• v.44 no.3
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• pp.331-344
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• 2020

This study aims to find meaningful implications for the development of Korean elementary school math education courses and textbooks by comparing and analyzing the number and arithmetic areas of Korean and Canadian math textbooks in fifth and sixth grades. To this end, the textbook composition system of Korean and Canadian elementary schools was compared and analyzed, and the number and timing of introduction of math textbooks and math textbooks by grade, and the number in fifth and sixth grade and the learning contents of math textbooks were compared and analyzed. The following conclusions were obtained from this study: First, it is necessary to organize a textbook that can solve the problem in an integrated way by introducing the learned mathematical concepts and computations naturally in the context of problems closely related to real life, regardless of the type of private calculation or mathematics area. Second, it is necessary to organize questions using materials such as real photography and mathematics, science, technology, engineering, art, etc. and to organize textbooks that make people feel the necessity and usefulness of mathematics. Third, sufficient learning of the principles of mathematics through the use of various actual teaching aids and mathematical models, and the construction of textbooks focusing on problem-solving strategies using engineering tools are needed. Fourth, in-depth discussions are needed on the timing of learning guidance for fractions and minority learning or how to organize and develop learning content.

• The Korean Journal of Food And Nutrition
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• v.36 no.1
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• pp.6-16
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• 2023

To investigate the anti-inflammatory activity of submerged culture using Cordyceps militaris mycelium, culture-including mycelia was extracted and lyophilized into postbiotics (hot-water extract; CM-HW). HW was fractionated into crude polysaccharide (CM-CP) by ethanol precipitation, and CM-CP was further dialyzed into CM-DCP by dialysis with running water using 12~14 kDa dialysis tube. When the cytotoxicity of subfractions against cells was assessed, no subfraction had a cytotoxic impact that was substantially different from the control groups. In an inflammatory model using LPS-stimulated RAW 264.7 cells, CM-DCP significantly decreased IL-6 and MCP-1 production levels compared to the LPS-control group. CM-DCP also inhibited IL-6 and IL-8 secretion in HaCaT keratinocytes stimulated with TNF-α and IFN-γ. In the meanwhile, the neutral sugar content and mannose ratio of anti-inflammatory CM-DCP were higher than the other fractions, and CM-DCP contained β-1,3/1,6-glucan of 216.1 mg/g. High pressure size exclusion chromatography revealed that CM-DCP contained molecules with a molecular weight range of 5.6 to 144.0 kDa. In conclusion, postbiotics of C. militaris mycelium significantly promoted anti-inflammatory activity, suggesting that neutral polysaccharides including Glc and Man contribute to the anti-inflammation in RAW 264.7 or HaCaT cells.

• Journal of Elementary Mathematics Education in Korea
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• v.21 no.1
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• pp.215-241
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• 2017

This study analyzed teachers' Pedagogical Content Knowledge (PCK) regarding the pedagogical aspect of the instruction of ratio and rate in order to look into teachers' problems during the process of teaching ratio and rate. This study aims to clarify problems in teachers' PCK and promote the consideration of the materialization of an effective and practical class in teaching ratio and rate by identifying the improvements based on problems indicated in PCK. We subdivided teachers' PCK into four areas: mathematical content knowledge, teaching method and evaluation knowledge, understanding knowledge about students' learning, and class situation knowledge. The conclusion of this study based on analysis of the results is as follows. First, in the 'mathematical content knowledge' aspect of PCK, teachers need to understand the concept of ratio from the perspective of multiplicative comparison of two quantities, and the concept of rate based on understanding of two quantities that are related proportionally. Also, teachers need to introduce ratio and rate by providing students with real-life context, differentiate ratios from fractions, and teach the usefulness of percentage in real life. Second, in the 'teaching method and evaluation knowledge' aspect of PCK, teachers need to establish teaching goals about the students' comprehension of the concept of ratio and rate and need to operate performance evaluation of the students' understanding of ratio and rate. Also, teachers need to improve their teaching methods such as discovery learning, research study and activity oriented methods. Third, in the 'understanding knowledge about students' learning' aspect of PCK, teachers need to diversify their teaching methods for correcting errors by suggesting activities to explore students' own errors rather than using explanation oriented correction. Also, teachers need to reflect students' affective aspects in mathematics class. Fourth, in the 'class situation knowledge' aspect of PCK, teachers need to supplement textbook activities with independent consciousness and need to diversify the form of class groups according to the character of the activities.

• Korean Journal of Radiology
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• v.23 no.12
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• pp.1251-1259
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• 2022

Objective: T1 mapping provides valuable information regarding cardiomyopathies. Manual drawing is time consuming and prone to subjective errors. Therefore, this study aimed to test a DL algorithm for the automated measurement of native T1 and extracellular volume (ECV) fractions in cardiac magnetic resonance (CMR) imaging with a temporally separated dataset. Materials and Methods: CMR images obtained for 95 participants (mean age ± standard deviation, 54.5 ± 15.2 years), including 36 left ventricular hypertrophy (12 hypertrophic cardiomyopathy, 12 Fabry disease, and 12 amyloidosis), 32 dilated cardiomyopathy, and 27 healthy volunteers, were included. A commercial deep learning (DL) algorithm based on 2D U-net (Myomics-T1 software, version 1.0.0) was used for the automated analysis of T1 maps. Four radiologists, as study readers, performed manual analysis. The reference standard was the consensus result of the manual analysis by two additional expert readers. The segmentation performance of the DL algorithm and the correlation and agreement between the automated measurement and the reference standard were assessed. Interobserver agreement among the four radiologists was analyzed. Results: DL successfully segmented the myocardium in 99.3% of slices in the native T1 map and 89.8% of slices in the post-T1 map with Dice similarity coefficients of 0.86 ± 0.05 and 0.74 ± 0.17, respectively. Native T1 and ECV showed strong correlation and agreement between DL and the reference: for T1, r = 0.967 (95% confidence interval [CI], 0.951-0.978) and bias of 9.5 msec (95% limits of agreement [LOA], -23.6-42.6 msec); for ECV, r = 0.987 (95% CI, 0.980-0.991) and bias of 0.7% (95% LOA, -2.8%-4.2%) on per-subject basis. Agreements between DL and each of the four radiologists were excellent (intraclass correlation coefficient [ICC] of 0.98-0.99 for both native T1 and ECV), comparable to the pairwise agreement between the radiologists (ICC of 0.97-1.00 and 0.99-1.00 for native T1 and ECV, respectively). Conclusion: The DL algorithm allowed automated T1 and ECV measurements comparable to those of radiologists.

• Journal of Wetlands Research
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• v.25 no.4
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• pp.306-314
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• 2023

Stream sediments are an important component of water quality management because they are receptors of various pollutants such as heavy metals and organic matters emitted from upland sources and can be secondary pollution sources, adversely affecting water environment. To effectively manage the stream sediments, identification of primary sources of sediment contamination and source-associated control strategies will be required. We evaluated the performance of machine learning models in identifying primary sources of sediment contamination based on the physico-chemical properties of stream sediments. A total of 356 stream sediment data sets of 18 quality parameters including 10 heavy metal species(Cd, Cu, Pb, Ni, As, Zn, Cr, Hg, Li, and Al), 3 soil parameters(clay, silt, and sand fractions), and 5 water quality parameters(water content, loss on ignition, total organic carbon, total nitrogen, and total phosphorous) were collected near abandoned metal mines and industrial complexes across the four major river basins in Korea. Two machine learning algorithms, linear discriminant analysis (LDA) and support vector machine (SVM) classifiers were used to classify the sediments into four cases of different combinations of the sampling period and locations (i.e., mine in dry season, mine in wet season, industrial complex in dry season, and　industrial complex in wet season). Both models showed good performance in the classification, with SVM outperformed LDA; the accuracy values of LDA and SVM were 79.5% and 88.1%, respectively. An SVM ensemble model was used for multi-label classification of the multiple contamination sources inlcuding landuses in the upland areas within 1 km radius from the sampling sites. The results showed that the multi-label classifier was comparable performance with sinlgle-label SVM in classifying mines and industrial complexes, but was less accurate in classifying dominant land uses (50~60%). The poor performance of the multi-label SVM is likely due to the overfitting caused by small data sets compared to the complexity of the model. A larger data set might increase the performance of the machine learning models in identifying contamination sources.