• Journal of Soil and Groundwater Environment
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• v.26 no.6
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• pp.47-64
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• 2021

In this study, the annual and monthly groundwater recharge for the Sapgyo-cheon upstream basin in Chungnam Province was evaluated by water balance analysis utilizing WetSpass-M model. The modeling input data such as topography, climate parameters, LAI (Leaf Area Index), land use, and soil characteristics were established using ArcGIS, QGIS, and Python programs. The results showed that the annual average groundwater recharge in 2001 - 2020 was 251 mm, while the monthly groundwater recharge significantly varied over time, fluctuating between 1 and 47 mm. The variation was high in summer, and relatively low in winter. Variation in groundwater recharge was the largest in July in which precipitation was heavily concentrated, and the variation was closely associated with several factors including the total amount of precipitation, the number of days of the precipitation, and the daily average precipitation. This suggests the extent of groundwater recharge is greatly influenced not only by quantity of precipitation but also the precipitation pattern. Since climate condition has a profound effect on the monthly groundwater recharge, evaluation of monthly groundwater recharge need to be carried out by considering both seasonal and regional variability for better groundwater usage and management. In addition, the mathematical tools for groundwater recharge analysis need to be improved for more accurate prediction of groundwater recharge.

• Journal of the Korean Physical Society
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• v.73 no.12
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• pp.1821-1826
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• 2018

Uniformity is a key feature of state-of-the-art infrared focal planed array (IRFPA) and infrared imaging system. Unlike traditional infrared telescope facility, a ground-based infrared radiant characteristics measurement system with an IRFPA not only provides a series of high signal-to-noise ratio (SNR) infrared image but also ensures the validity of radiant measurement data. Normally, a long integration time tends to produce a high SNR infrared image for infrared radiant characteristics radiometry system. In view of the variability of and uncertainty in the measured target's energy, the operation of switching the integration time and attenuators usually guarantees the guality of the infrared radiation measurement data obtainted during the infrared radiant characteristics radiometry process. Non-uniformity correction (NUC) coefficients in a given integration time are often applied to a specified integration time. If the integration time is switched, the SNR for the infrared imaging will degenerate rapidly. Considering the effect of the SNR for the infrared image and the infrared radiant characteristics radiometry above, we propose a-wide-dynamic-range NUC algorithm. In addition, this essasy derives and establishes the mathematical modal of the algorithm in detail. Then, we conduct verification experiments by using a ground-based MWIR(Mid-wave Infared) radiant characteristics radiometry system with an Ø400 mm aperture. The experimental results obtained using the proposed algorithm and the traditional algorithm for different integration time are compared. The statistical data shows that the average non-uniformity for the proposed algorithm decreased from 0.77% to 0.21% at 2.5 ms and from 1.33% to 0.26% at 5.5 ms. The testing results demonstrate that the usage of suggested algorithm can improve infrared imaging quality and radiation measurement accuracy.

• Journal of Educational Research in Mathematics
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• v.21 no.4
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• pp.327-344
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• 2011

This study is the first step for us toward improving high school students' capability of statistical inferences, such as obtaining and interpreting the confidence interval on the population mean that is currently learned in high school. We suggest 5 underlying concepts of 'discretion of contingency and inevitability', 'discretion of induction and deduction', 'likelihood principle', 'variability of a statistic' and 'statistical model', those are necessary to appreciate statistical inferences as a reliable arguing tools in spite of its occasional erroneous conclusions. We assume those 5 concepts above are to be gradually developing in their school periods and Korean mathematics textbooks of grades 1-12 were analyzed. Followings were found. For the right choice of solving methodology of the given problem, no elementary textbook but a few high school textbooks describe its difference between the contingent circumstance and the inevitable one. Formal definitions of population and sample are not introduced until high school grades, so that the developments of critical thoughts on the reliability of inductive reasoning could not be observed. On the contrary of it, strong emphasis lies on the calculation stuff of the sample data without any inference on the population prospective based upon the sample. Instead of the representative properties of a random sample, more emphasis lies on how to get a random sample. As a result of it, the fact that 'the random variability of the value of a statistic which is calculated from the sample ought to be inherited from the randomness of the sample' could neither be noticed nor be explained as well. No comparative descriptions on the statistical inferences against the mathematical(deductive) reasoning were found. Few explanations on the likelihood principle and its probabilistic applications in accordance with students' cognitive developmental growth were found. It was hard to find the explanation of a random variability of statistics and on the existence of its sampling distribution. It is worthwhile to explain it because, nevertheless obtaining the sampling distribution of a particular statistic, like a sample mean, is a very difficult job, mere noticing its existence may cause a drastic change of understanding in a statistical inference.

• Toxicological Research
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• v.6 no.2
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• pp.205-213
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• 1990

The regulation of neurotoxicants has usually been based upon setting reference doses by dividing a no observed adverse effect level (NOAEL) by uncertainty factors that theoretically account for interspecies and intraspecies extraploation of experimental results in animals to humans. Recently, we have proposed a four-step alternative procedure which provides quantitative estimates of risk as a function of dose. The first step is to establish a mathematical relationship between a biological effect or biomarker and the dose of chemical administered. The second step is to determine the distribution (variability) of individual measurements of biological effects or their biomarkers about the dose response curve. The third step is to define an adverse or abnormal level of a biological effect or biomarker in an untreated population. The fourth and final step is to combine the information from the first three steps to estimate the risk (proportion of individuals exceeding on adverse or abnormal level of a biological effect or biomarker) as a function of dose. The primary purpose of this report is to enhance the certainty of the first step of this procedure by improving our understanding of the relationship between a biomarker and dose of administered chemical. Several factors which need to be considered include: 1) the pharmacokinetics of the parent chemical, 2) the target tissue concentrations of the parent chemical or its bioactivated proximate toxicant, 3) the uptake kinetics of the parent chemical or metabolite into the target cell(s) and/or membrane interactions, and 4) the interaction of the chemical or metabolite with presumed receptor site(s). Because these theoretical factors each contain a saturable step due to definitive amounts of required enzyme, reuptake or receptor site(s), a nonlinear, saturable dose-response curve would be predicted. In order to exemplify this process, effects of the neurotoxicant, methlenedioxymethamphetamine (MDMA), were reviewed and analyzed. Our results and those of others indicate that: 1) peak concentrations of MDMA and metabolites are ochieved in rat brain by 30 min and are negligible by 24 hr, 2) a metabolite of MDMA is probably responsible for its neurotoxic effects, and 3) pretreatment with monoamine uptake blockers prevents MDMA neurotoxicity. When data generated from rats administerde MDMA were plotted as bilolgical effect (decreases in hippocampal serotonin concentrations) versus dose, a saturation curve best described the observed relationship. These results support the hypothesis that at least one saturable step is involved in MDMA neurotoxicity. We conclude that the mathematical relationship between biological effect and dose of MDMA, the first step of our quantitative neurotoxicity risk assessment procedure, should reflect this biological model information generated from the whole of the dose-response curve.

• Communications of Mathematical Education
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• v.23 no.1
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• pp.109-128
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• 2009

This study aimed to investigate students' learning process by examining their perception process of problem structure and mathematization, and further to suggest an effective teaching and learning of mathematics to improve students' problem-solving ability. Using the qualitative research method, the researcher observed the collaborative learning of two middle school students by providing problem-posing activities of five lessons and interviewed the students during their performance. The results indicated the student with a high achievement tended to make a similar problem and a new problem where a problem structure should be found first, had a flexible approach in changing its variability of the problem because he had advanced algebraic thinking of quantitative reasoning and reversibility in dealing with making a formula, which related to developing creativity. In conclusion, it was observed that the process of problem posing required accurate understanding of problem structures, providing students an opportunity to understand elements and principles of the problem to find the relation of the problem. Teachers may use a strategy of simplifying external structure of the problem and analyzing algebraical thinking necessary to internal structure according to students' level so that students are able to recognize the problem.

• Journal of the Korea Concrete Institute
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• v.15 no.1
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• pp.25-34
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• 2003

The degradation of reinforced concrete (RC) structures due to physical and chemical attacks has been a major issue in construction engineering. Deterioration of RC structures by chloride attack followed by reinforcement corrosion is one of the serious problems. An objective of this study is to develop a form of mathematical model of chloride ingress into concrete. In order to overcome some limits of the previous approaches, a chloride ingress model, consisting of chloride solution intrusion through the capillary pore and chloride ion diffusion through the pore water, was proposed. Moreover, the variability of chloride ion diffusivity due to the degree of hydration of cement, relative humidity in pore, exposure condition, and variation of chloride binding, was considered in the model. In order to verify the proposed model, the results predicted by the proposed model were compared with analysis results of Life-365, a computer program for predicting the service life of reinforced concrete structures exposed to chlorides. In conclusion, the proposed model would be promising to predict the chloride ion profile and to estimate the service life of RC structures.

• 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.

• Horticultural Science & Technology
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• v.30 no.3
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• pp.270-277
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• 2012

Greenhouse industry has been growing in many countries due to both the advantage of stable year-round crop production and increased demand for fresh vegetables. In greenhouse cultivation, $CO_2$ concentration plays an essential role in the photosynthesis process of crops. Continuous and accurate monitoring of $CO_2$ level in the greenhouse would improve profitability and reduce environmental impact, through optimum control of greenhouse $CO_2$ enrichment and efficient crop production, as compared with the conventional management practices without monitoring and control of $CO_2$ level. In this study, a mathematical model was developed to estimate the $CO_2$ emission from soil as affected by environmental factors in greenhouses. Among various model types evaluated, a linear regression model provided the best coefficient of determination. Selected predictor variables were solar radiation and relative humidity and exponential transformation of both. As a response variable in the model, the difference between $CO_2$ concentrations at the soil surface and 5-cm depth showed are latively strong relationship with the predictor variables. Segmented regression analysis showed that better models were obtained when the entire daily dataset was divided into segments of shorter time ranges, and best models were obtained for segmented data where more variability in solar radiation and humidity were present (i.e., after sun-rise, before sun-set) than other segments. To consider time delay in the response of $CO_2$ concentration, concept of time lag was implemented in the regression analysis. As a result, there was an improvement in the performance of the models as the coefficients of determination were 0.93 and 0.87 with segmented time frames for sun-rise and sun-set periods, respectively. Validation tests of the models to predict $CO_2$ emission from soil showed that the developed empirical model would be applicable to real-time monitoring and diagnosis of significant factors for $CO_2$ enrichment in a soil-based greenhouse.

• Education of Primary School Mathematics
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• v.22 no.4
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• pp.205-221
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• 2019

The study aimed at investigating preservice elementary school teachers' statistical reasoning when they posed survey questions as they engaged in statistical problem solving, and analyzing how their statistical reasoning affect the subsequent stages. 24 groups of sophomore students(80 students) from two education universities conducted statistical problem solving and completed statistical report, and 22 of them were analyzed. As a result, 9 statistical reasoning were shown when preservice teachers posed survey questions. Among them, question clarification oriented reasoning and variability based reasoning were not exclusively focused upon in the previous research. In order to investigate how statistical reasoning in posing survey questions affected subsequent stages, we examined difficulties and issues that preservice teachers had when they engaged in analyses and conclusion stage described in their report. Consequently, preservice teachers' difficulties were related to population relevant reasoning, category level reasoning, standardization reasoning, alignment to question reasoning, and question clarification oriented reasoning. While previous studies did not focus on question posing stage, this study claimed the necessity of emphasizing various statistical reasoning in question posing and importance of teaching and learning method of appropriate statistical reasoning in question posing.

• Korean Journal of Radiology
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• v.22 no.8
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• pp.1266-1278
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• 2021

Objective: We aimed to compare the aortic valve area (AVA) calculated using fast high-resolution three-dimensional (3D) magnetic resonance (MR) image acquisition with that of the conventional two-dimensional (2D) cine MR technique. Materials and Methods: We included 139 consecutive patients (mean age ± standard deviation [SD], 68.5 ± 9.4 years) with aortic valvular stenosis (AS) and 21 asymptomatic controls (52.3 ± 14.2 years). High-resolution T2-prepared 3D steady-state free precession (SSFP) images (2.0 mm slice thickness, 10 contiguous slices) for 3D planimetry (3DP) were acquired with a single breath hold during mid-systole. 2D SSFP cine MR images (6.0 mm slice thickness) for 2D planimetry (2DP) were also obtained at three aortic valve levels. The calculations for the effective AVA based on the MR images were compared with the transthoracic echocardiographic (TTE) measurements using the continuity equation. Results: The mean AVA ± SD derived by 3DP, 2DP, and TTE in the AS group were 0.81 ± 0.26 cm², 0.82 ± 0.34 cm², and 0.80 ± 0.26 cm², respectively (p = 0.366). The intra-observer agreement was higher for 3DP than 2DP in one observer: intraclass correlation coefficient (ICC) of 0.95 (95% confidence interval [CI], 0.94-0.97) and 0.87 (95% CI, 0.82-0.91), respectively, for observer 1 and 0.97 (95% CI, 0.96-0.98) and 0.98 (95% CI, 0.97-0.99), respectively, for observer 2. Inter-observer agreement was similar between 3DP and 2DP, with the ICC of 0.92 (95% CI, 0.89-0.94) and 0.91 (95% CI, 0.88-0.93), respectively. 3DP-derived AVA showed a slightly higher agreement with AVA measured by TTE than the 2DP-derived AVA, with the ICC of 0.87 (95% CI, 0.82-0.91) vs. 0.85 (95% CI, 0.79-0.89). Conclusion: High-resolution 3D MR image acquisition, with single-breath-hold SSFP sequences, gave AVA measurement with low observer variability that correlated highly with those obtained by TTE.