• Transactions of the Korean Society of Mechanical Engineers A
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• v.39 no.1
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• pp.27-35
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• 2015

The material properties of crack growth models at an elevated temperature were derived from the results of numerous crack growth tests for Mod.9Cr-1Mo (ASME Grade 91) steel specimens under fatigue loading and creep loading at an elevated temperature. These crack growth models were needed for defect assessment under creep-fatigue loading. The mathematical crack growth rate models for fatigue crack growth (FCG) and creep crack growth (CCG) were determined based on the test results, and the models were compared with those of the French design code RCC-MRx to investigate the conservatism of the code. The French design code RCC-MRx provides an FCG model and a CCG model for Grade 91 steel in Section III Tome 6. It was shown that the FCG model of RCC-MRx is conservative, while the CCG model is non-conservative compared with the present test data. Thus, it was shown that further validation of the property was required. Mechanical strength tests and creep tests were also conducted, and the test results were compared with those of RCC-MRx.

• Journal of the Korean Association of Geographic Information Studies
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• v.19 no.3
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• pp.75-88
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• 2016

In this study, we used the CLUE-s model to predict the future land-use change based on the urban growth scenario in South Korea. The land-use maps of six classes (water, urban, rice paddy, upland crop, forest, and grass) for the year 2008 were obtained from the Ministry of Environment (MOE), and the land-use data for 5-year intervals between 1980 and 2010 were obtained from the Water Resources Management Information System (WAMIS), South Korea. For predicting the future land-use change, the MOE environmental conservation value assessment map (ECVAM) was considered for identifying the development-restricted areas, and various driving factors as location characteristics were prepared for the model. The predicted results were verified by comparing them with the land-use statistics of urban areas in each province for the year 2008. The prediction error rates were 9.47% in Gyeonggi, 9.96% in Gangwon, 10.63% in Chungbuk, 7.53% in Chungnam, 9.48% in Jeonbuk, 6.92% in Jeonnam, 2.50% in Gyeongbuk, and 8.09% in Gyeongnam. The sources of error might come from the gaps between the development of political decisions in reality with spatio-temporal variation and the mathematical model for urban growth rate in CLUE-s model for future scenarios. Based on the land-use scenario in 2008, the land-use predictions for the year 2100 showed that the urban area increased by 28.24%, and the rice paddy, upland crop, and forest areas decreased by 8.27, 6.72, and 1.66%, respectively, in South Korea.

• Education of Primary School Mathematics
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• v.17 no.2
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• pp.95-111
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• 2014

The purpose of this study is to determine the relationship between metacognition and math creative problem solving ability. Specific research questions set up according to the purpose of this study are as follows. First, what relation does metacognition has with creative math problem-solving ability of mathematically gifted elementary students? Second, how does each component of metacognition (i.e. metacognitive knowledge, metacognitive regulation, metacognitive experiences) influences the math creative problem solving ability of mathematically gifted elementary students? The present study was conducted with a total of 80 fifth grade mathematically gifted elementary students. For assessment tools, the study used the Math Creative Problem Solving Ability Test and the Metacognition Test. Analyses of collected data involved descriptive statistics, computation of Pearson's product moment correlation coefficient, and multiple regression analysis by using the SPSS Statistics 20. The findings from the study were as follows. First, a great deal of variability between individuals was found in math creative problem solving ability and metacognition even within the group of mathematically gifted elementary students. Second, significant correlation was found between math creative problem solving ability and metacognition. Third, according to multiple regression analysis of math creative problem solving ability by component of metacognition, it was found that metacognitive knowledge is the metacognitive component that relatively has the greatest effect on overall math creative problem-solving ability. Fourth, results indicated that metacognitive knowledge has the greatest effect on fluency and originality among subelements of math creative problem solving ability, while metacognitive regulation has the greatest effect on flexibility. It was found that metacognitive experiences relatively has little effect on math creative problem solving ability. This findings suggests the possibility of metacognitive approach in math gifted curricula and programs for cultivating mathematically gifted students' math creative problem-solving ability.

• Journal of Educational Research in Mathematics
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• v.14 no.2
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• pp.207-219
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• 2004

There have been studies reporting the increase in student confidence in mathematics when using technology. However, past studies indicating a positive correlation between technology and confidence in mathematics do not explain why they see this positive outcome. With increased availability and easy access to the Internet in schools and the development of free online virtual manipulatives, this research was interested in how the use of virtual manipulatives in mathematics can affect students confidence in their mathematical abilities. Our hypothesis was that the classes using virtual manipulatives which allows students to connecting dynamic visual image with abstract symbols will help students gain a deeper conceptual understanding of math concept thus increasing their confidence and ability in mathematics. The participants in this study were 46 fifth-grade students in three ability groups: one high, one middle and one low. During a two-week unit on fractions, students in three groups interacted with several virtual manipulative applets in a computer lab. Data sources in the project included a pre and posttest of students mathematics content knowledge, Confidence in Learning Mathematics Scale, field notes and student interviews, and classroom videotapes. Our aim was to find evidence for increased level of confidence in mathematics as students strengthened their understanding of fraction concepts. Results from the achievement score indicated an overall main effect showing significant improvement for all ability groups following the treatment and an increase in the confidence level from the preassessment of the Confidence in Learning Mathematics Scale in the middle and high ability groups. An interesting finding was that the confidence level for the low ability group students who had the highest confidence level in the beginning did not change much in the final confidence scale assessment. In the middle and high ability groups, the confidence level did increase according to the improvement of the contest posttest. Through interviews, students expressed how the virtual manipulatives assisted their understanding by verifying their answers as they worked and facilitated their ability to figure out math concept in their mind and visually.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.3 no.2
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• pp.125-133
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• 2005

Methodologies of NEWTRIT model, NRC model and AIRDOS-EPA model, which are off-site dose assessment models for regulatory compliance from routine releases of tritium into the environment, were investigated. Using the domestic data, if available, the predictive results of the models were compared. Among them, recently developed NEWTRIT model considers only doses from organically bounded tritium (OBT) due to environmental releases of tritiated water (HTO) . A total dose from all exposure pathways predicted from AIRDOS-EPA model was 1.03 and 2.46 times higher than that from NEWTRIT model and NRC model, respectively. From above result, readers should not have an understanding that a predictive dose from NRC model may be underestimated compared with a realistic dose. It is because of that both mathematical models and corresponding parameter values for regulatory compliance are based on the conservative assumptions. For a dose by food consumption predicted from NEWTRIT model, the contribution of OBT was nearly equivalent to that of HTO due to relatively high consumption of grains in Korean. Although a total dose predicted from NEWTRIT model is similar to that from AIRDOS-EPA model, NEIIfTRIT model may be have a meaning in the understanding of phenomena for the behavior of HTO released into the environment.

• School Mathematics
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• v.12 no.2
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• pp.219-237
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• 2010

On inquiry of international comparison assessment, the Korean students achieve high scores in mathematics while they achieve relatively low scores in responses of the affective questionnaire. It can be an important point in mathematics education of Korea, but there are few studies which explore the specific reasons. So in this study, we analysed the results of PISA 2003(in math domain) based on multiple regression analysis and correlation analysis to investigate the reasons and features of those phenomena. We compared the results of Korean students with students of other countries. As a result, there were 7 factors which effect on Korean students' affective domain in mathematics learning and they were statistically significant. According to this study, it needs to improve students' positive attitudes to their school, mathematical interest, and positive self-concept. And it needs to develop an actual instrument to explore the affective domain which effect on mathematics learning.

• Proceedings of the Korean Radioactive Waste Society Conference
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• 2005.06a
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• pp.464-473
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• 2005

Methodologies of NEWTRIT model, NRC model and AIRDOS-EPA model, which are off-site dose assessment models for regulatory compliance from routine releases of tritium into the environment, were investigated. Using the domestic data, if available, the predictive results of the models were compared. Among them, recently developed NEWTRIT model considers only doses from organically bounded tritium (OBT) due to environmental releases of tritiated water (HTO). A total dose from all exposure pathways predicted from AIRDOS-EPA model was 1.03 and 2.46 times higher than that from NEWTRIT model and NRC model, respectively. From above result, readers should not have an understanding that a predictive dose from NRC model may be underestimated compared with a realistic dose. It is because of that both mathematical models and corresponding parameter values for regulatory compliance are based on the conservative assumptions. For a dose by food consumption predicted from NEWTRIT model, the contribution of OBT was nearly equivalent to that of HTO due to relatively high consumption of grains in Korean. Although a total dose predicted from NEWTRIT model is similar to that from AIRDOS-EPA model, NEWTRIT model may be have a meaning in the understanding of phenomena for the behavior of HTO released into the environment.

• Korean Journal of Food Science and Technology
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• v.37 no.6
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• pp.1012-1017
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• 2005

Predictive growth model of putrefactive bacteria of surimi-based imitation crab in the modified surimi-based imitation crab (MIC) broth was investigated. The growth curves of putrefactive bacteria were obtained by measuring cell number in MIC broth under different conditions (Initial cell number, $1.0{\times}10^2,\;1.0{\times}10^3$ and $1.0{\times}10^4$ colony forming unit (CFU)/mL; temperature, $15^{\circ}C,\;20^{\circ}C\;and\;25^{\circ}C$) and applied them to Gompertz model. The microbial growth indicators, maximum specific growth rate constant (k), lag time (LT) and generation time (GT), were calculated from Gompertz model. Maximum specific growth rate (k) of putrefactive bacteria was become fast with rising temperature and fastest at $25^{\circ}C$. LT and GT were become short with rising temperature and shortest at $25^{\circ}C$. There were not significant differences in k, LT and GT by initial cell number (p>0.05). Polynomial model, $k=-0.2160+0.0241T-0.0199A_0$, and square root model, $\sqrt{k}=0.02669$ (T-3.5689), were developed to express the combination effects of temperature and initial cell number, The relative coefficient of experimental k and predicted k of polynomial model was 0.87 from response surface model. The relative coefficient of experimental k and predicted k of square root model was 0.88. From above results, we found that the growth of putrefactive bacteria was mainly affected by temperature and the square root model was more credible than the polynomial model for the prediction of the growth of putrefactive bacteria.

• Korean Journal of Food Science and Technology
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• v.37 no.2
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• pp.194-198
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• 2005

Growth curves of Listeria monocytogenes in modified surimi-based imitation crab (MIC) broth were obtained by measuring cell concentration in MIC broth at different culture conditions [initial cell numbers, $1.0{\times}10^{2},\;1.0{\times}10^{3}\;and\;1.0{\times}10^{4}$, colony forming unit (CFU)/mL; temperature, 15, 20, 25, 37, and $40^{\circ}C$] and applied to Gompertz model to determine microbial growth indicators, maximum specific growth rate constant (k), lag time (LT), and generation time (GT). Maximum specific growth rate of L. monocytogenes increased rapidly with increasing temperature and reached maximum at $37^{\circ}C$, whereas LT and GT decreased with increasing temperature and reached minimum at $37^{\circ}C$. Initial cell number had no effect on k, LT, and GT (p > 0.05). Polynomial and square root models were developed to express combined effects of temperature and initial cell number using Gauss-Newton Algorism. Relative coefficients of experimental k and predicted k of polynomial and square root models were 0.92 and 0.95, respectively, based on response surface model. Results indicate L. monocytogenes growth was mainly affected by temperature and square root model was more effective than polynomial model for growth prediction.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.34 no.5
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• pp.525-534
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• 2016

In South Korea, paddy rice has been consumed over the entire region and it is the main source of income for farmers, thus mathematical model for the estimation of rice yield is required for such decision-making processes in agriculture. The objectives of our study are to: (1) develop rice yield estimation model using Convolutional Neural Networks(CNN), (2) choose hyper-parameters for the model which show the best performance and (3) investigate whether CNN model can effectively predict the rice yield by the comparison with the model using Artificial Neural Networks(ANN). Weather and MODIS(The MOderate Resolution Imaging Spectroradiometer) products from April to September in year 2000~2013 were used for the rice yield estimation models and cross-validation was implemented for the accuracy assessment. The CNN and ANN models showed Root Mean Square Error(RMSE) of 36.10kg/10a, 48.61kg/10a based on rice points, respectively and 31.30kg/10a, 39.31kg/10a based on 'Si-Gun-Gu' districts, respectively. The CNN models outperformed ANN models and its possibility of application for the field of rice yield estimation in South Korea was proved.