• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.1
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• pp.43-54
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• 2023

Due to climate change, drought and flood occurrences have been increasing. Accurate projections of watershed discharges are imperative to effectively manage natural disasters caused by climate change. However, climate change and hydrological model uncertainty can lead to imprecise analysis. To address this issues, we used two lumped models, IHACRES and GR4J, to compare and analyze the changes in discharges under climate stress scenarios. The Hapcheon and Seomjingang dam basins were the study site, and the Nash-Sutcliffe efficiency (NSE) and the Kling-Gupta efficiency (KGE) were used for parameter optimizations. Twenty years of discharge, precipitation, and temperature (1995-2014) data were used and divided into training and testing data sets with a 70/30 split. The accuracies of the modeled results were relatively high during the training and testing periods (NSE>0.74, KGE>0.75), indicating that both models could reproduce the previously observed discharges. To explore the impacts of climate change on modeled discharges, we developed climate stress scenarios by changing precipitation from -50 % to +50 % by 1 % and temperature from 0 ℃ to 8 ℃ by 0.1 ℃ based on two decades of weather data, which resulted in 8,181 climate stress scenarios. We analyzed the yearly maximum, abundant, and ordinary discharges projected by the two lumped models. We found that the trends of the maximum and abundant discharges modeled by IHACRES and GR4J became pronounced as changes in precipitation and temperature increased. The opposite was true for the case of ordinary water levels. Our study demonstrated that the quantitative evaluations of the model uncertainty were important to reduce the impacts of climate change on water resources.

• Analytical Science and Technology
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• v.19 no.6
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• pp.535-543
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• 2006

Being used widely in semiconductor and display manufacturing, $NF_3$ is internationally considered as one of the regulated compounds in emission. Numerous companies have been continuously trying to reduce the emissions of $NF_3$ to comply with the global environmental regulation. This work is made to report the destruction and removal efficiency (DRE) of electrically heated scrubbers and the use rate in process chambers installed in three main LCD manufacturing companies in Korea. As the measurement techniques for $NF_3$ emission, mass flow controlled helium gas was continuously supplied into the equipment by which scrubber efficiency is being measured. The partial pressures of $NF_3$ and helium were accurately measured for each sample using a mass spectrometer, as it is emitted from inlet and outlet of the scrubber system. The results show that the DRE value for electrically heated scrubbers installed before 2004 is less than 52 %, while that for the new scrubbers modified based on measurement by scrubber manufacturer has been sigificentely improved upto more than 95 %. In additon, we have confirmed the efficiency depends on such variables as the inlet gas flow rate, water content, heater temperature, and preventative management period. The use rates of $NF_3$ in process chambers were also affected by the process type. The use rate of radio frequency source chambers, built in the $1^{st}$ and $2^{nd}$ generation process lines, was determined to be less than 75 %. In addition, that of remote plasma source chambers for the $3^{rd}$ generation was measured to be aboove 95 %. Therefore, the combined application of improved scrubber and the RPSC process chamber to the semiconductor and display process can reduce $NF_3$ emmision by 99.95 %. It is optimistic that the mission for the reduction of greenhouse gas emission can be realized in these LCD manufacturing companies in Korea.

• Journal of the Korean earth science society
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• v.44 no.1
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• pp.13-35
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• 2023

Ocean currents play the most important role in causing and controlling global climate change. The water depth of the Yellow Sea is very shallow compared to the East Sea, and the circulation and currents of seawater are quite complicated owing to the influence of various wind fields, ocean currents, and river discharge with low-salinity seawater. The Yellow Sea Warm Current (YSWC) is one of the most representative currents of the Yellow Sea in winter and is closely related to the weather of the southwest coast of the Korean Peninsula, so it needs to be treated as important in secondary-school textbooks. Based on the 2015 revised national educational curriculum, secondary-school science and earth science textbooks were analyzed for content related to the YSWC. In addition, a questionnaire survey of secondary-school science teachers was conducted to investigate their perceptions of the temporal variability of ocean currents. Most teachers appeared to have the incorrect knowledge that the YSWC moves north all year round to the west coast of the Korean Peninsula and is strong in the summer like a general warm current. The YSWC does not have strong seasonal variability in current strength, unlike the North Korean Cold Current (NKCC), but does not exist all year round and appears only in winter. These errors in teachers' subject knowledge had a background similar to why they had a misconception that the NKCC was strong in winter. Therefore, errors in textbook contents on the YSWC were analyzed and presented. In addition, to develop students' and teachers' data literacy, class materials on the YSWC that can be used in inquiry activities were developed. A graphical user interface (GUI) program that can visualize the sea surface temperature of the Yellow Sea was introduced, and a program displaying the spatial distribution of water temperature and salinity was developed using World Ocean Atlas (WOA) 2018 oceanic in-situ measurements of water temperature and salinity data and ocean numerical model reanalysis field data. This data visualization materials using oceanic data is expected to improve teachers' misunderstandings and serve as an opportunity to cultivate both students and teachers' ocean and data literacy.

• Korean small business review
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• v.31 no.1
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• pp.73-88
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• 2009

This study examines the characteristics of 24 Korean hidden champions such as key success factors, core competences, strategic problems, and desirable future directions. The study categorized them into 8 types with Danny Miller's four trajectories and top manager's decision making style(rationality and passion). Danny Miller argued in his book, Icarus paradox, that outstanding firms will extend their orientations until they reach dangerous extremes and their momentum will result in common trajectories of decline. He suggested four very common success types: Craftsmen, Builders, Pioneers, Salesmen. He also suggested common trajectories of decline:Focusing(from Craftsmen to Tinkers), Venturing(from Builders to Imperialists), Inventing(from Pioneers to Escapists), Decoupling(from Salesmen to Drifts). In Korea, successful startups appear to possess three kinds of drive: Technology-drive, Vision-drive, Market-drive. Successful technology-driven firms tend to grow as craftsmen or pioneers. Successful vision-driven and market-driven ones tend to grow as builders and salesmen respectively. Korean top managers or founders seem to have two kinds of decision making style: Passion-based and Rationality-bases. Passion-based(passionate) entrepreneurs are biased towards action or proactiveness in competing and getting things done. Rationality- based ones tend to emphasis the effort devoted to scanning and analysing information to better understand a company's threats, opportunities and options. Consequently this study suggested 4*2 types of Korean hidden champions: (1) passionate craftsmen, (2) rational craftsmen, (3) passionate builders, (4) rational builders, (5) passionate pioneers, (6) rational pioneers, (7) passionate salesmen, (8) rational salesmen. These 8 type firms showed different success stories and appeared to possess different trajectories of decline. These hidden champions have acquired competitive advantage within domestic or globally niche markets in spite of the weak market power and lack of internal resources. They have maintained their sustainable competitiveness by utilizing three types of growth strategy; (1) penetrating into the global market, (2) exploring new service market, (3) occupying the domestic market. According to the types of growth strategy, these firms showed different financial outcomes and possessed different issues for maintaining their competitiveness. This study found that Korean hidden champions were facing serious challenges from the transforming economic structure these days and possessed the decline potential from their success momentum or self-complacence. It argues that they need to take a new growth engine not to decline in the turbulent environment. It also discusses how firms overcome the economic crisis and find a new business area in promising industries for the future. It summarized the recent policy of Korean government called as "Green Growth" and discussed how small firms utilize such benefits and supports from the government. Other implications for firm strategies and governmental policies were discussed.

• 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.

• Journal of Nutrition and Health
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• v.56 no.6
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• pp.742-755
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• 2023

Purpose: This study aimed to investigate the perceptions of the dietary guidelines for Koreans (DGK) among Korean adults based on sociodemographic and lifestyle factors. Methods: A total of 514 Korean adults aged 19-64 years completed a self-administered online questionnaire assessing their perceptions of DGK, sociodemographic and lifestyle factors, and subjective assessments regarding the importance of 11 nutrients and 16 food groups. The differences in the perceptions of DGK according to the characteristics of the participants were analyzed using t-tests or ANOVA. Additionally, the differences in the subjective assessments of nutrients and food groups according to the perceptions of DGK were examined using t-tests. Results: The awareness of DGK was significantly higher among participants aged 50-64 years, living in single-person households, who were physically active, with a lower frequency of eating out, and with a higher interest in dietary information (p < 0.05 for all). The understanding of DGK was significantly higher among participants aged 19-29 years, females, individuals who were under or normal weight, non-smokers, those who self-evaluated their diet as healthy, and those with a high interest in dietary information (p < 0.05 for all). Additionally, the applicability of DGK was significantly higher among participants aged 50-64 years, who were physically active, who self-evaluated their diet as healthy, and who had a high interest in dietary information (p < 0.05 for all). Participants with a higher perception of DGK tended to attribute greater importance to most nutrients and food groups compared to those with a lower perception level. However, processed meat and foods, beverages, and alcoholic drinks consistently received lower importance ratings compared to other nutrients and food groups, regardless of the perception level. Conclusion: This research suggests that the perceptions of DGK among Korean adults may vary depending on sociodemographic and lifestyle factors. Consequently, there is a need to customize and diversify the methods for providing dietary guidelines.

• Korean Journal of Remote Sensing
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• v.39 no.5_1
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• pp.589-597
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• 2023

Floating debris in large quantities from land during heavy rainfall has adverse social, economic, and environmental impacts, but the monitoring system for the concentration area and amount is insufficient. In this study, we proposed an efficient monitoring method for floating debris entering the river during heavy rainfall in Daecheong Lake, the largest water supply source in the central region, and applied remote sensing techniques to estimate the standing-stock of floating debris. To investigate the status of floating debris in the upper of Daecheong Lake, we used a tracking buoy equipped with a low-orbit satellite communication terminal to identify the movement route and behavior characteristics, and used a drone to estimate the potential concentration area and standing-stock of floating debris. The location tracking buoys moved rapidly during the period when the cumulative rainfall for 3 days increased by more than 200 to 300 mm. In the case of Hotan Bridge, which showed the longest distance, it moved about 72.8 km for one day, and the maximum moving speed at this time was 5.71 km/h. As a result of calculating the standing-stock of floating debris using a drone after heavy rainfall, it was found to be 658.8 to 9,165.4 tons, with the largest amount occurring in the Seokhori area. In this study, we were able to identify the main concentrations of floating debris by using location-tracking buoys and drones. It is believed that remote sensing-based monitoring methods, which are more mobile and quicker than traditional monitoring methods, can contribute to reducing the cost of collecting and processing large amounts of floating debris that flows in during heavy rain periods in the future.

• Korean Journal of Remote Sensing
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• v.39 no.5_3
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• pp.1031-1042
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• 2023

In this study, a deep learning model was developed to predict the yield of cabbage and radish, one of the five major supply and demand management vegetables, using satellite images of Landsat 8. To predict the yield of cabbage and radish in Gangwon-do from 2015 to 2020, satellite images from June to September, the growing period of cabbage and radish, were used. Normalized difference vegetation index, enhanced vegetation index, lead area index, and land surface temperature were employed in this study as input data for the yield model. Crop yields can be effectively predicted using satellite images because satellites collect continuous spatiotemporal data on the global environment. Based on the model developed previous study, a model designed for input data was proposed in this study. Using time series satellite images, convolutional neural network, a deep learning model, was used to predict crop yield. Landsat 8 provides images every 16 days, but it is difficult to acquire images especially in summer due to the influence of weather such as clouds. As a result, yield prediction was conducted by splitting June to July into one part and August to September into two. Yield prediction was performed using a machine learning approach and reference models , and modeling performance was compared. The model's performance and early predictability were assessed using year-by-year cross-validation and early prediction. The findings of this study could be applied as basic studies to predict the yield of field crops in Korea.

• Journal of Korean Society of Forest Science
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• v.112 no.4
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• pp.393-404
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• 2023

The Natural Monument Forest (NMF) is a form of natural and cultural heritage that has symbolized the harmony between nature and culture in Korea for a long time. Recently, the NMF has deteriorated due to industrialization and reckless city expansion. Given this situation, it is necessary to preserve and manage the ecosystem of the NMF through preferential research regarding the forest community structure. Accordingly, this study sought to identify the community structure by analyzing the vegetation classification, stratum structure,and species diversity using vegetation data collected from the Forest of Japanese Torreyas in Pyeongdae-ri, Jeju and the Subtropical Forest of Nabeup-ri, Jeju. The results classified the forest vegetation as a Litsea japonica community group divided into two communities: a Torreya nuciferacommunity and a Quercus glauca community. The T. nuciferacommunity was subdivided into the Idesia polycarpa group and Dryopteris erythrosora group, while the Q. glauca community was subdivided into the Mercurialis leiocarpa group and Arachniodes aristata group. The T. nucifera species showed the highest level of importance in vegetation units 1 (Litsea japonicacommunity group-Torreya nucifera community-Idesia polycarpa group) and 2 (Litsea japonica community group-Torreya nucifera community-Dryopteris erythrosora group), whereas Q. glauca showed the highest level of importance in vegetation units 3 (Litsea japonica community group-Quercus glauca community-Mercurialis leiocarpa group) and 4 (Litsea japonica community group-Quercus glauca community-Arachniodes aristata group). In terms of the species diversity, vegetation units 1, 2, 3, and 4 had 2.866, 2.716, 2.222, and 2.326 species, respectively. These findings suggest that it is necessary to prepare a differentiated management plan for each vegetation unit.

• Journal of the Society of Disaster Information
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• v.19 no.4
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• pp.869-881
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• 2023

Purpose: This study aims to come up with improvement measures to improve the effectiveness of child safety measures. Method: The current status of child safety accidents was investigated and implications were deduced by analyzing major child safety measures by government department in the past. In addition, a perception survey was conducted on 1,000 people including children, guardians, and children's facility workers who are subject to child safety policies. Result: Regarding the safety of children's living space(environment), 35.3% of guardians answered that more than 1/3 of them were not safe. Both guardians(95.3%) and children's facility workers(89%) answered that there was the highest risk of 'traffic accidents', and the second risk factor was parents(carelessness of workers at children's facilities) and children's facility workers(careless of guardians at home). Looking at the risks by place, "road and sidewalk" was the most dangerous place and for child safety, guardians(64.3%) and workers (78.3%) both said that the role of "parent" is the most important. For improvements to prevent child safety accidents, the response rate of "strengthening safety management of road traffic facilities" is the most necessary with 75.8% for guardians and 65% for child use facilities. Conclusion: The reinforcement measures to strengthen the effectiveness of child safety measures are as follows. First, in order to ensure the continuity of child safety measures, it should be operated effectively so that those subject to the establishment of the Comprehensive Plan for Child Safety, which took effect in August 2022, can feel it. Second, in order to improve the sensitivity of children's policy targets, promotion measures that take into account the characteristics of each child safety field should be continuously strengthened. Third, it is necessary to expand safety infrastructure for each field to secure child safety. Fourth, it is necessary to strengthen safety education that can ensure safety for children themselves and to come up with detailed measures to make safety education for parents(guardians) mandatory.