• Korean Journal of Culture and Social Issue
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• v.13 no.4
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• pp.113-134
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• 2007

This study investigated body-related values, body-esteem, and the relationship between them based on the survey data drawn from female college students in three East Asian countries(Korea, Japan, and China). 168 Korean, 108 Chinese, and 152 Japanese female college students responded to questions designed to measure four sorts of body values (operability, inclination, locus of evaluation, and social utility) and four dimensions of body esteem (appearance, weight, health, overall). The results showed that body-related values and body-esteem differ among three countries. Japanese showed the highest acceptance level for the voluntary body alteration(operability), while chinese scored the lowest. Inclination to body appearance over health was higher in Korean than in Japanese and in Chinese. Korean also evaluated the importance of body appearance and its social utility the highest, followed by Japanese and Chinese. There were dramatic differences in body esteem between Korean and Japanese. Regarding body-esteem, Korean showed the highest appearance-esteem, but the health-esteem was the lowest. On the contrary, Japanese showed the highest health-esteem, but the appearance-esteem was lowest. Chinese showed the highest weight-esteem. Four sorts of body values showed significant correlations with appearance-esteem and weight-esteem, respectively but not with health-esteem. Overall, the result supported the prediction that different political, social, and economic backdrops in three countries would be related with different body-related values and body esteem in the female college students.

• Korean journal of applied entomology
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• v.62 no.3
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• pp.215-220
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• 2023

A recent discovery of drywood termites (Cryptotermes domesticus) in a residential facility in Seoul has raised significant concern. This exotic insect species, which can damage timber and wooden buildings, necessitates an immediate investigation of potential infestation. In this study, we assessed the climatic suitability for this termite species using a species distribution modeling approach. Global distribution data and bioclimatic variables were compiled from published sources, and predictive models for climatic suitability were developed using four modeling algorithms. An ensemble prediction was made based on the mean occurrence probability derived from the individual models. The final model suggested that this species could potentially establish itself in tropical coastal regions. While the climatic suitability in South Korea was generally found to be low, a careful investigation is still warranted due to the potential risk of colonization and establishment of this species.

• Analyses & Alternatives
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• v.7 no.3
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• pp.181-230
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• 2023

Evaluating the empirical validity of Modern Monetary Theory, this study implements panel cointegration analysis on annual panel data (2000-2022) of OECD countries. Specifically, the sample countries are divided into groups based on the presence of their own sovereign currencies, and for each group, the long-run equilibrium relation (cointegration) between the ratio of public debt or fiscal deficit and government bond rates is tested and estimated. Main findings are as follows: applying the pooled mean-group estimation for panel cointegration, it is found that both the ratios of public debt and fiscal deficit have significantly positive long-run correlation with government bond rates in countries without sovereign currency such as the Euro-zone or fixed exchange rate regime countries. However, in countries with sovereign currency such as non-Euro-zone or floating exchange rate regime countries, the long-run correlation is either negative or not statistically significant. Particularly, in countries without sovereign currency, the ratio of public debt has significantly positive correlation with the real government bond rates in the short run as well as the long run. These results are consistent with the prediction of Modern Monetary Theory, thus providing a supporting evidence for the empirical validity of the theory.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.301-307
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• 2023

Deep learning requires building a deep neural network, collecting a large amount of training data, and then training the built neural network for a long time. If training does not proceed properly or overfitting occurs, training will fail. When using deep learning tools that have been developed so far, it takes a lot of time to collect training data and learn. However, due to the rapid advent of the mobile environment and the increase in sensor data, the demand for real-time deep learning technology that can dramatically reduce the time required for neural network learning is rapidly increasing. In this study, a real-time deep learning system was implemented using an Arduino system equipped with a fine dust sensor. In the implemented system, fine dust data is measured every 30 seconds, and when up to 120 are accumulated, learning is performed using the previously accumulated data and the newly accumulated data as a dataset. The neural network for learning was composed of one input layer, one hidden layer, and one output. To evaluate the performance of the implemented system, learning time and root mean square error (RMSE) were measured. As a result of the experiment, the average learning error was 0.04053796, and the average learning time of one epoch was about 3,447 seconds.

• Explosives and Blasting
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• v.41 no.3
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• pp.26-37
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• 2023

In order to determine the amount of explosives that can minimize the vibration generated during tunnel construction using the blasting method, it is necessary to derive the blasting vibration coefficients, K and n, by analyzing the vibration records of trial blasting in the field or under similar conditions. In this study, we aimed to develop a technique that can derive reasonable K and n when trial blasting cannot be performed. To this end, we collected full-scale trial blast data and studied how to predict the blast vibration coefficient (K, n) according to the type of explosive, center cut blasting method, rock origin and type, and rock grade using deep learning (DL). In addition, the correction value between full-scale and borehole trial blasting results was calculated to compensate for the limitations of the borehole trial blasting results and to carry out a design that aligns more closely with reality. In this study, when comparing the available explosive amount according to the borehole trial blasting result equation, the predictions from deep learning (DL) exceed 50%, and the result with the correction value is similar to other blast vibration estimation equations or about 20% more, enabling more economical design.

• Journal of the Korean Society of Safety
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• v.38 no.5
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• pp.8-14
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• 2023

Lithium ions can induce the thermal runaway phenomenon and lead to reignition due to electrical, mechanical, and environmental factors such as high temperature, smoke generation, explosions, or flames, which is extremely likely to create safety concerns. Therefore, one of the ways to improve the flame retardancy of the electrolyte is to use a flame-retardant additive. Comparing the associated characteristic value of existing substances with the required experimental value, it was found that these values were either considerably different or were not documented. It is vital to know a substance's combustion characteristic values, flash point, explosion limit, and autoignition temperature (AIT) as well as its combustion characteristics before using it. In this research, the flash point and AIT of materials were measured by mixing a highly volatile and flammable substance, diethyl carbonate (DEC), with flame-retardant dimethyl methylphosphonate (DMMP). The flash point of DEC, which is a pure substance, was 29℃, and that for DMMP was 65℃. Further, the lower explosion limit calculated using the measured flash point of DEC was 1.79 Vol.%, while that for DMMP was 0.79 Vol.%. The AIT was 410℃ and 390℃ for DEC and DMMP, respectively. In particular, since the AIT of DMMP has not been discussed in any previous study, it is necessary to ensure safety through experimental values. In this study, the experimental and regression analysis revealed that the average absolute deviation (ADD) for the flash point of the DEC+DMMP DEC+DMMP system is 0.58 sec and that the flash point tends to increase according to changes in the composition employed. It also revealed that the AAD for the AIT of the mixture was 3.17 sec and that the AIT tended to decrease and then increase based on changes in the composition.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.3
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• pp.182-196
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• 2023

Accurate and timely estimation of crop yields is crucial for various purposes, including global food security planning and agricultural policy development. Remote sensing techniques, particularly using vegetation indices (VIs), have show n promise in monitoring and predicting crop conditions. However, traditional VIs such as the normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) have limitations in capturing rapid changes in vegetation photosynthesis and may not accurately represent crop productivity. An alternative vegetation index, the near-infrared reflectance of vegetation (NIRv), has been proposed as a better predictor of crop yield due to its strong correlation with gross primary productivity (GPP) and its ability to untangle confounding effects in canopies. In this study, we investigated the potential of NIRv in estimating crop yield, specifically for corn and soybean crops in major crop-producing regions in 14 states of the United States. Our results demonstrated a significant correlation between the peak value of NIRv and crop yield/area for both corn and soybean. The correlation w as slightly stronger for soybean than for corn. Moreover, most of the target states exhibited a notable relationship between NIRv peak and yield, with consistent slopes across different states. Furthermore, we observed a distinct pattern in the yearly data, where most values were closely clustered together. However, the year 2012 stood out as an outlier in several states, suggesting unique crop conditions during that period. Based on the established relationships between NIRv peak and yield, we predicted crop yield data for 2022 and evaluated the accuracy of the predictions using the Root Mean Square Percentage Error (RMSPE). Our findings indicate the potential of NIRv peak in estimating crop yield at the county level, with varying accuracy across different counties.

• Korean Journal of Radiology
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• v.21 no.4
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• pp.413-421
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• 2020

Objective: A widely applicable, non-invasive screening method for non-alcoholic fatty liver disease (NAFLD) is needed. We aimed to develop and validate an index combining computed tomography (CT) and routine clinical data for screening for NAFLD in a large cohort of adults with pathologically proven NAFLD. Materials and Methods: This retrospective study included 2218 living liver donors who had undergone liver biopsy and CT within a span of 3 days. Donors were randomized 2:1 into development and test cohorts. CTL-S was measured by subtracting splenic attenuation from hepatic attenuation on non-enhanced CT. Multivariable logistic regression analysis of the development cohort was utilized to develop a clinical-CT index predicting pathologically proven NAFLD. The diagnostic performance was evaluated by analyzing the areas under the receiver operating characteristic curve (AUC). The cutoffs for the clinical-CT index were determined for 90% sensitivity and 90% specificity in the development cohort, and their diagnostic performance was evaluated in the test cohort. Results: The clinical-CT index included CTL-S, body mass index, and aspartate transaminase and triglyceride concentrations. In the test cohort, the clinical-CT index (AUC, 0.81) outperformed CTL-S (0.74; p < 0.001) and clinical indices (0.73-0.75; p < 0.001) in diagnosing NAFLD. A cutoff of ≥ 46 had a sensitivity of 89% and a specificity of 41%, whereas a cutoff of ≥ 56.5 had a sensitivity of 57% and a specificity of 89%. Conclusion: The clinical-CT index is more accurate than CTL-S and clinical indices alone for the diagnosis of NAFLD and may be clinically useful in screening for NAFLD.

• Journal of the Korean Geosynthetics Society
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• v.23 no.2
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• pp.9-17
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• 2024

When constructing on soft ground, managing ground settlement and safety is crucial. However, there often exists a significant disparity between the actual behavior of the ground and the design plans. In this study, we aimed to compare and analyze the difference between the predicted settlement based on theoretical formulas and the measured settlement during construction, in order to predict settlement. For this purpose, we analyzed settlement data from 18 construction sites. The results indicated that the back analysis settlement values were similar to the measured settlement values, whereas the design settlement values were significantly higher compared to the measured settlement values. Specifically, the design settlement values were 1.2 to 1.4 times higher than those derived from back analysis using measured values. The RMSE analysis revealed a value of 0.6212m for the design settlement and 0.1697m for the back analysis settlement. The difference between the back analysis settlement and the measured settlement was more than 70% lower than the difference between the design settlement and the measured settlement. This indicates that the back analysis settlement values exhibit lower error rates compared to the design settlement values.

• Korean Journal of Radiology
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• v.22 no.2
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• pp.213-224
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• 2021

Objective: Clinical outcomes of patients who undergo transarterial chemoembolization (TACE) for single small hepatocellular carcinoma (HCC) are not consistent, and may differ based on certain imaging findings. This retrospective study was aimed at determining the efficacy of pre-TACE CT or MR imaging findings in predicting survival outcomes in patients with small HCC upon being treated with TACE. Besides, the study proposed to build a risk prediction model for these patients. Materials and Methods: Altogether, 750 patients with functionally good hepatic reserve who received TACE as the first-line treatment for single small HCC between 2004 and 2014 were included in the study. These patients were randomly assigned into training (n = 525) and validation (n = 225) sets. Results: According to the results of a multivariable Cox analysis, three pre-TACE imaging findings (tumor margin, tumor location, enhancement pattern) and two clinical factors (age, serum albumin level) were selected and scored to create predictive models for overall, local tumor progression (LTP)-free, and progression-free survival in the training set. The median overall survival time in the validation set were 137.5 months, 76.1 months, and 44.0 months for low-, intermediate-, and high-risk groups, respectively (p < 0.001). Time-dependent receiver operating characteristic curves of the predictive models for overall, LTP-free, and progression-free survival applied to the validation cohort showed acceptable areas under the curve values (0.734, 0.802, and 0.775 for overall survival; 0.738, 0.789, and 0.791 for LTP-free survival; and 0.671, 0.733, and 0.694 for progression-free survival at 3, 5, and 10 years, respectively). Conclusion: Pre-TACE CT or MR imaging findings could predict survival outcomes in patients with small HCC upon treatment with TACE. Our predictive models including three imaging predictors could be helpful in prognostication, identification, and selection of suitable candidates for TACE in patients with single small HCC.