• Journal of the Korean earth science society
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• v.43 no.5
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• pp.591-603
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• 2022

The color and optical properties of seawater are determined by the interaction between dissolved organic and inorganic substances and plankton contained in it. The Ieodo - Ocean Research Institute (I-ORS), located in the East China Sea, is affected by the low salinity of the Yangtze River in the west and the Tsushima Warm Current in the south. Thus, it is a suitable site for analyzing the fluctuations in circulation and optical properties around the Korean Peninsula. In this study, seawater surrounding the I-ORS was classified according to its optical characteristics using the satellite remote reflectance observed with Moderate Resolution Imaging Spectroradiometer (MODIS)/Aqua and National Aeronautics and Space Administration (NASA) bio-Optical Marine Algorithm Dataset (NOMAD) from January 2016 to December 2020. Additionally, the variation characteristics of optical water types (OWTs) from different seasons were presented. A total of 59,532 satellite match-up data (d ≤ 10 km) collected from seawater surrounding the I-ORS were classified into 23 types using the spectral angle mapper. The OWTs appearing in relatively clear waters surrounding the I-ORS were observed to be greater than 50% of the total. The maximum OWTs frequency in summer and winter was opposite according to season. In particular, the OWTs corresponding to optically clear seawater were primarily present in the summer. However, the same OWTs were lower than overall 1% rate in winter. Considering the OWTs fluctuations in the East China Sea, the I-ORS is inferred to be located in the transition zone of seawater. This study contributes in understanding the optical characteristics of seawater and improving the accuracy of satellite ocean color variables.

• Journal of Korean Society of Forest Science
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• v.111 no.4
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• pp.461-472
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• 2022

Natural and anthropogenic factors cause forest types to continuously change. Since the ratio of forest area by forest type is important information for identifying the characteristics of national forest resources, an accurate understanding of the prospect of forest type change is required. The study aim was to use National Forest Inventory (NFI) time-series data to understand the characteristics of forest type change and to estimate future prospects of nationwide forest type change. We used forest type change information from the fifth and seventh NFI datasets, climate, topography, forest stand, and disturbance variables related to forest type change to analyze trends and characteristics of forest type change. The results showed that the forests in Korea are changing in the direction of decreasing coniferous forests and increasing mixed and broadleaf forests. The forest sites that were changing from coniferous to mixed forests or from mixed to broadleaf forests were mainly located in wet topographic environments and climatic conditions. The forest type changes occurred more frequently in sites with high disturbance potential (high temperature, young or sparse forest stands, and non-forest areas). We used a climate change scenario (RCP 8.5) to establish a forest type change model (SVM) to predict future changes. During the 40-year period from 2015 to 2055, the SVM predicted that coniferous forests will decrease from 38.1% to 28.5%, broadleaf forests will increase from 34.2% to 38.8%, and mixed forests will increase from 27.7% to 32.7%. These results can be used as basic data for establishing future forest management strategies.

• Clean Technology
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• v.28 no.4
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• pp.269-277
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• 2022

With the recent development of the biological enzymatic reaction industry, lactic acid (LA) can be mass-produced from biomass sources. In particular, a catalytic process that converts LA into acrylic acid (AA) is receiving much attention because AA is used widely in the petrochemical industry as a monomer for superabsorbent polymers (SAP) and as an adhesive for displays. In the LA conversion process, NaY zeolites have been previously shown to be a high-activity catalyst, which improves AA selectivity and long-term stability. However, NaY zeolites suffer from fast deactivation due to severe coking. Therefore, the aim of this study is to modify the acid-base properties of the NaY zeolite to address this shortcoming. First, base promoters, Ca ions, were introduced to the NaY zeolites to tune their acidity and basicity via ion exchange (IE) and incipient wetness impregnation (IWI). The IWI method showed superior catalyst selectivity and stability compared to the IE method, maintaining a high AA yield of approximately 40% during the 16 h reaction. Based on the NH₃- and CO₂-TPD results, the calcium salts that impregnated into the NaY zeolites were proposed to exit as an oxide form mainly at the exterior surface of NaY and act as additional base sites to promote the dehydration of LA to AA. The NaY zeolites were further treated with KOH before calcium impregnation to reduce the total acidity and improve the dispersion of calcium through the mesopores formed by KOH-induced desilication. However, this KOH treatment did not lead to enhanced AA selectivity. Finally, calcium loading was increased from 1wt% to 5wt% to maximize the amount of base sites. The increased basicity improved the AA selectivity substantially to 65% at 100% conversion while maintaining high activity during a 24 h reaction. Our results suggest that controlling the basicity of the catalyst is key to obtaining high AA selectivity and high catalyst stability.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.577-587
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• 2021

Room and Pillar method is an underground facility construction method that maximizes the strength of the in-situ ground. In order to secure the safety of the underground space, it is necessary to secure the safety of the room actually used in addition to the safety of pillar of the room and Pillar method. In this study, the evaluation method for the safety of the room and rock pillar in the room and pillar method was studied through numerical analysis. Numerical analysis was performed for a total of 125 cases using ground conditions, pillar width, and room width as parameters, and the results were derived. As for the safety factor of the pillar, it was confirmed that the safety factor increased when the strength of the ground increased, and it was confirmed that the increment in the safety factor decreased when the width of the pillar was widened. The room strain was evaluated by applying the Critical strain. As the width of the pillar became narrower, the Critical strain was higher, and as the width of the room became smaller, the Critical strain was smaller. As a result of the correlation analysis between the safety factor of the pillar and the room strain, it was possible to derive the upper limit of the room strain that can secure the standard safety factor of the pillar according to the width of the pillar. It is judged that the results derived from this study can be used as a guideline to secure the safety of the room when the actual design is performed in consideration of the ground conditions and room width.

• Journal of Korean Tunnelling and Underground Space Association
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• v.23 no.6
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• pp.469-484
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• 2021

Rock mass classification results have a great influence on construction schedule and budget as well as tunnel stability in tunnel design. A total of 3,526 tunnels have been constructed in Korea and the associated techniques in tunnel design and construction have been continuously developed, however, not many studies have been performed on how to assess rock mass quality and grade more accurately. Thus, numerous cases show big differences in the results according to inspectors' experience and judgement. Hence, this study aims to suggest a more reliable rock mass classification (RMR) model using machine learning algorithms, which is surging in availability, through the analyses based on various rock and rock mass information collected from boring investigations. For this, 11 learning parameters (depth, rock type, RQD, electrical resistivity, UCS, V_p, V_s, Young's modulus, unit weight, Poisson's ratio, RMR) from 13 local tunnel cases were selected, 337 learning data sets as well as 60 test data sets were prepared, and 6 machine learning algorithms (DT, SVM, ANN, PCA & ANN, RF, XGBoost) were tested for various hyperparameters for each algorithm. The results show that the mean absolute errors in RMR value from five algorithms except Decision Tree were less than 8 and a Support Vector Machine model is the best model. The applicability of the model, established through this study, was confirmed and this prediction model can be applied for more reliable rock mass classification when additional various data is continuously cumulated.

• Journal of Korean Society of Forest Science
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• v.111 no.3
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• pp.405-417
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• 2022

The purpose of this study was to describe the photosynthetic features of Prunus maximowiczii and Prunus serrulate Lindl. var. pubescens (Makino) Nakai in response to drought stress. Specifically, we studied the effects of drought on photosynthetic ability and photosystem II activity. Drought stress (DS) was induced by cutting the water supply for 30 days. DS decreased the moisture contents in the soil, and between the 10th and 12th days of DS, both species had 10% or less of x., After the 15th day of DS, it was less than 5%, which is a condition for disease to start. We observed a remarkable decrease of maximum photosynthesis rate starting from 10th day of DS; the light compensation point was also remarkable. Dark respiration and net apparent quantum yield decreased significantly on the 15th day of DS, and then increased on the 20th day. In addition, the stomatal transpiration rate of P. maximowiczii decreased significantly on the15th day of DS, and then increased on the 20th day. Water use efficiency increased on the 15th day of DS, and then decreased on the 20th day. The stomatal transpiration rate of P. serrulate decreased significantly on the 20th day of DS, and then increased afterward, while its water use efficiency increased on the 20th day of DS, and then decreased afterward. These results indicate that the closure of stoma prevented water loss, resulting in a temporary increase of water use efficiency. Chlorophyll fluorescence analysis detected remarkable decreases in the functional index (PI_ABS) and energy transfer efficiency in P. maximowiczii after the 15th day of DS. Meanwhile, photosystem II activity decreased in P. serrulate after 20 days of DS. In addition, Ts-Ta, PI_ABS, DI_O/RC, ET_O/RC followed similar trends as those of the soil moisture content and photosynthetic properties, indicating that they can be used as useful variables in predicting DS in trees.

• Journal of Korean Home Economics Education Association
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• v.33 no.4
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• pp.139-157
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• 2021

The purpose of this study is to derive implications for Korean home economics curriculum to emphasize consumer competency of adolescents by analyzing the content components of consumer competency presented in 'consumer life' area of middle school home economics curriculum of 3 states in the U.S. The analysis results and implications are summarized as follows: First, the U.S. home economics curriculum is composed of various contents, including credit management, savings/investment/ insurance, taxes, and financial situation, and financial decision-making, to improve adolescent's understanding of finance. In the next revision of Korean curriculum, for financial stability in prolonged life after retirement, it is would be necessary to include contents on basic financial knowledge and technology for financial information utilization so that students can establish financial plans for different life stages in consideration of various variables such as changes in economic environment, etc. Second, the U.S. home economics curriculum was developed to help students make better purchase decisions by applying economic concepts such as prices and interest rates, economic trends and the impact of demand and supply, purchase methods and contract conditions, etc. However, Korean home economics curriculum only focus on purchase plan and purchase decision-making process. It would be necessary to foster consumer transaction competency by introducing economic concepts suitable middle school level. Third, to emphasize "consumer civic competency", Ohio was focusing on "claim of consumer rights" and Wisconsin was focusing on the "acceptance of consumer responsibility." In order to enhance adolescent's consumer civic competency, it would be necessary for Korean curriculum to balance the claim of right and the acceptance of consumer responsibility in the following term, and to emphasize the contents on consumer policies, laws and consumer advocacy to create a consumer environment where consumer sovereignty is realized.

• Journal of Korean Home Economics Education Association
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• v.35 no.1
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• pp.1-14
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• 2023

The objective of the study was to examine the associations of dietary carbohydrate and fat intake with the prevalence of metabolic syndrome in Korean women. A cross-sectional study was employed based on data from the Korea National Health and Nutrition Examination (2007-2016). A total of 22,850 women aged 19 to 69 years were studied after excluding responses from pregnant or lactating women and those with missing metabolic values. Dietary intake data were collected with a 24-hour recall method. Dietary carbohydrate and fat intakes were divided into quintiles. After controlling for confounding variables, a multivariable logistic regression and general linear model were used. The findings indicated that HDL cholesterol levels were lower (p for trend<0.01), while triglyceride levels (p for trend=0.04), waist circumference (p for trend<0.01), and systolic blood pressure (p for trend<0.01) were higher among participants in the highest quintile of carbohydrate intake compared to those in the lowest quintile. Participants in the highest quintile of fat intake had lower waist circumference (p for trend=0.02), triglyceride level (p for trend<0.01), and systolic blood pressure (p for trend<0.01), while higher HDL cholesterol level (p for trend<0.01) compared to those in the lowest fat intake quintile. Metabolic syndrome was more likely to be present in the highest quintile of carbohydrates intake than in the lowest quintile (5^th quintile vs. 1^st quintile, OR: 1.32; 95% CI: 1.11 to 1.57). However, metabolic syndrome was less likely to be present in the highest quintile of fat intake than in the lowest quintile (5^th quintile vs. 1^st quintile, OR: 0.73; 95% CI: 0.61 to 0.86). This study revealed that high dietary carbohydrate intake and low dietary fat intake were associated with metabolic syndrome in Korean women.

• The Korean Journal of Applied Statistics
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• v.36 no.1
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• pp.49-62
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• 2023

Solar energy, which is rapidly increasing in proportion, is being continuously developed and invested. As the installation of new and renewable energy policy green new deal and home solar panels increases, the supply of solar energy in Korea is gradually expanding, and research on accurate demand prediction of power generation is actively underway. In addition, the importance of solar radiation prediction was identified in that solar radiation prediction is acting as a factor that most influences power generation demand prediction. In addition, this study can confirm the biggest difference in that it attempted to predict solar radiation using medium-term forecast weather data not used in previous studies. In this paper, we combined the multi-linear regression model, KNN, random fores, and SVR model and the clustering technique, K-means, to predict solar radiation by hour, by calculating the probability density function for each cluster. Before using medium-term forecast data, mean absolute error (MAE) and root mean squared error (RMSE) were used as indicators to compare model prediction results. The data were converted into daily data according to the medium-term forecast data format from March 1, 2017 to February 28, 2022. As a result of comparing the predictive performance of the model, the method showed the best performance by predicting daily solar radiation with random forest, classifying dates with similar climate factors, and calculating the probability density function of solar radiation by cluster. In addition, when the prediction results were checked after fitting the model to the medium-term forecast data using this methodology, it was confirmed that the prediction error increased by date. This seems to be due to a prediction error in the mid-term forecast weather data. In future studies, among the weather factors that can be used in the mid-term forecast data, studies that add exogenous variables such as precipitation or apply time series clustering techniques should be conducted.

• Korean Journal of Legislative Studies
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• v.26 no.2
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• pp.113-140
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• 2020

This study is meaningful in that it is the first analysis of Korean elections using the concept of spatial autocorrelation. Spatial autocorrelation means that an event occurring in one location in space has a high correlation with an event occurring in the surrounding area. The voter turnout rate in the 21^st general election of Seoul area was divided into the early-voting turnout and voting-day turnout, and the spatial pattern of the turnout was examined. Most of the previous studies were based on the unit of the precinct and personal data, but this study analyzed on the basis of the lower unit, Eup-myeon-dong, and analyzed using spatial data and aggregate data. Moran I index showed a fairly high spatial autocorrelation of 0.261 in the voting-day turnout, while the index of the early-voting turnout was low at 0.095, indicating that there was little spatial autocorrelation despite statistical significance. The voting-day turnout, which showed strong spatial autocorrelation, was compared and analyzed using the OLS regression model and the spatial statistics model. In the general regression model, the coefficient of determination R² rose from 0.585261 to 0.656631 in the spatial error model, showing an increase in explanatory power of about 7 percentage points. This means that the spatial statistical model has high explanatory power. The most interesting result is the relationship between the early-voting turnout and the voting-day turnout. The higher the early-voting turnout is, the lower the voting-day turnout is. When the early-voing turnout increases by about 2%, the voting-day turnout drops by about 1%. In this study, the variables affecting the early-voting turnout and the voting-day turnout are very different. This finding is different from the previous researches.