• Journal of the Korea Society of Computer and Information
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• v.24 no.11
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• pp.209-218
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• 2019

The purpose of this study is to longitudinally analyze the relationship between parenting effectiveness of parents of multicultural families and self-esteem and achievement motivation of multicultural adolescents. The study used the data of Multi-cultural Adolescent Panel Survey (MAPS). Of the six years of data from the 1st survey (elementary grade 4 students) in 2011 to the 6th survey ($3^{rd}$ year middle school students) in 2016, this study employed and analyzed the data from year 2012 ($2^{nd}$ survey, fifth graders), year 2014 ($4^{th}$ survey, 1st year middle school students), and year 2016 ($6^{th}$ survey, $3^{rd}$ year middle school students). The results of applying the Autoregressive Cross-lagged Model to examine the longitudinal relationship between parenting effectiveness of multicultural families and self-esteem and achievement motivation of multicultural adolescents are as follows. First, parenting effectiveness of parents of multicultural families, and self-esteem of multicultural adolescents, and autoregressive effects of achievement motivation were found to have a positive (+) effect with the passage of time. Second, the parenting effectiveness of parents of multicultural families at the previous time was found to have a significant positive (+) effect on the cross-lagged effect on self-esteem and achievement motivation of multicultural adolescents at a later time. Third, the self-esteem of multicultural adolescents at the previous time at the previous time was found to have a significant effect in the positive (+) direction on the cross-lagged effect affecting achievement motivation of multicultural adolescents at a later time. Fourth, it was found that the cross-lagged effect of the parenting effectiveness of parents of multicultural families on achievement motivation of multicultural adolescents was greater than the cross-lagged effect of self-esteem on achievement motivation of multicultural adolescents. This study is meaningful in that the longitudinal data are used to verify the causal orientation between three variables over time to examine the relationship between parenting effectiveness of parents of multicultural families and self-esteem and achievement motivation of multicultural adolescents.

• The Journal of Society for e-Business Studies
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• v.26 no.3
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• pp.33-53
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• 2021

In the crossroads of social change caused by the spread of the Fourth Industrial Revolution and the prolonged COVID-19, the Korean government announced the Digital New Deal policy on July 14, 2020. The Digital New Deal policy's primary goal is to create new businesses by accelerating digital transformation in the public sector and industries around data, networks, and artificial intelligence technologies. However, in a rapidly changing social environment, information asymmetry of the future benefits of technology can cause differences in the public's ability to analyze the direction and effectiveness of policies, resulting in uncertainty about the practical effects of policies. On the other hand, the media leads the formation of discourse through communicators' role to disseminate government policies to the public and provides knowledge about specific issues through the news. In other words, as the media coverage of a particular policy increases, the issue concentration increases, which also affects public decision-making. Therefore, the purpose of this study is to verify the dynamic relationship between the media coverage and the stock market on the Korean government's digital New Deal policy using Granger causality, impulse response functions, and variance decomposition analysis. To this end, the daily stock turnover ratio, daily price-earnings ratio, and EWMA volatility of digital technology-based companies related to the digital new deal policy among KOSDAQ listed companies were set as variables. As a result, keyword search volume, daily stock turnover ratio, EWMA volatility have a bi-directional Granger causal relationship with media coverage. And an increase in media coverage has a high impact on keyword search volume on digital new deal policies. Also, the impulse response analysis on media coverage showed a sharp drop in EWMA volatility. The influence gradually increased over time and played a role in mitigating stock market volatility. Based on this study's findings, the amount of media coverage of digital new deals policy has a significant dynamic relationship with the stock market.

• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.2
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• pp.85-96
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• 2019

Solar radiation is an important variable for estimation of energy balance and water cycle in natural and agricultural ecosystems. A deep neural network (DNN) model has been developed in order to estimate the daily global solar radiation. Temperature and precipitation, which would have wider availability from weather stations than other variables such as sunshine duration, were used as inputs to the DNN model. Five-fold cross-validation was applied to train and test the DNN models. Meteorological data at 15 weather stations were collected for a long term period, e.g., > 30 years in Korea. The DNN model obtained from the cross-validation had relatively small value of RMSE ($3.75MJ\;m^{-2}\;d^{-1}$) for estimates of the daily solar radiation at the weather station in Suwon. The DNN model explained about 68% of variation in observed solar radiation at the Suwon weather station. It was found that the measurements of solar radiation in 1985 and 1998 were considerably low for a small period of time compared with sunshine duration. This suggested that assessment of the quality for the observation data for solar radiation would be needed in further studies. When data for those years were excluded from the data analysis, the DNN model had slightly greater degree of agreement statistics. For example, the values of $R^2$ and RMSE were 0.72 and $3.55MJ\;m^{-2}\;d^{-1}$, respectively. Our results indicate that a DNN would be useful for the development a solar radiation estimation model using temperature and precipitation, which are usually available for downscaled scenario data for future climate conditions. Thus, such a DNN model would be useful for the impact assessment of climate change on crop production where solar radiation is used as a required input variable to a crop model.

• Journal of Dental Rehabilitation and Applied Science
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• v.36 no.4
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• pp.254-261
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• 2020

Purpose: The purpose of this study was to assess the marginal and internal fit of interim crowns fabricated by two different manufacturing method (subtractive manufacturing technology and additive manufacturing technology). Materials and Methods: Forty study models were fabricated with plasters by making an impression of a master model of the maxillary right first molar for ceramic crown. On each study model, interim crowns (n = 40) were fabricated using three types of 3D printers (Meg-printer 2; Megagen, Zenith U; Dentis, and Zenith D; Dentis) and one type milling machine (imes-icore 450i; imes-icore GmbH). The internal of the interim crowns were filled with silicon and fitted to the study model. Internal scan data was obtained using an intraoral scanner. The fit of interim crowns were evaluated in the margin, absolute margin, axial, cusp, and occlusal area by using the superimposition of 3D scan data (Geomagic control X; 3D Systems). The Kruskal-wallis test, Mann-Whitney U test and Bonferroni correction method were used to compare the results among groups (α = 0.05). Results: There was no significant difference in the absolute marginal discrepancy of the temporary crown manufactured by three 3D printers and one milling machine (P = 0.812). There was a significant difference between the milling machine and the 3D printer in the axial and occlusal area (P < 0.001). The temporary crown with the milling machine showed smaller axial gap and higher occlusal gap than 3D printer. Conclusion: Since the marginal fit of the temporary crown produced by three types of 3D printers were all with in clinically acceptable range (< 120 ㎛), it can be sufficiently used for the fabrication of the temporary crown.

• Journal of Internet Computing and Services
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• v.22 no.6
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• pp.25-32
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• 2021

In line with future changes in the marine environment, Aids to Navigation has been used in various fields and their use is increasing. The term "Aids to Navigation" means an aid to navigation prescribed by Ordinance of the Ministry of Oceans and Fisheries which shows navigating ships the position and direction of the ships, position of obstacles, etc. through lights, shapes, colors, sound, radio waves, etc. Also now the use of Aids to Navigation is transforming into a means of identifying and recording the marine weather environment by mounting various sensors and cameras. However, Aids to Navigation are mainly lost due to collisions with ships, and in particular, safety accidents occur because of poor observation visibility due to sea fog. The inflow of sea fog poses risks to ports and sea transportation, and it is not easy to predict sea fog because of the large difference in the possibility of occurrence depending on time and region. In addition, it is difficult to manage individually due to the features of Aids to Navigation distributed throughout the sea. To solve this problem, this paper aims to identify the marine weather environment by estimating sea fog level approximately with images taken by cameras mounted on Aids to Navigation and to resolve safety accidents caused by weather. Instead of optical and temperature sensors that are difficult to install and expensive to measure sea fog level, sea fog level is measured through the use of general images of cameras mounted on Aids to Navigation. Furthermore, as a prior study for real-time sea fog level estimation in various seas, the sea fog level criteria are presented using the Haze Model and Dark Channel Prior. A specific threshold value is set in the image through Dark Channel Prior(DCP), and based on this, the number of pixels without sea fog is found in the entire image to estimate the sea fog level. Experimental results demonstrate the possibility of estimating the sea fog level using synthetic haze image dataset and real haze image dataset.

• Journal of the Korean Institute of Landscape Architecture
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• v.49 no.6
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• pp.27-36
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• 2021

At a time when the equitable use of urban parks is gradually emerging as a social issue, this study was initiated to expand the influence of urban parks by improving the quality of park services, thereby resolving areas not covered by urban park services. This study targeted the Hangang Park in Seoul, where the qualitative service of parks shows the greatest difference. The influence relationship between the qualitative services of the park and the user's sphere of influence, which indicates the distribution of park users, was proposed to assess the influence of improvements in the quality of service. As a research method, the top three districts and the bottom three districts were selected through the Han River Park user satisfaction survey conducted from 2017 to 2019, and a qualitative service evaluation was carried out. It was derived using the data acquired in September. Afterward, by performing a spatial autocorrelation analysis on the user's sphere of influence, additional verification of the user's sphere of influence was performed numerically and visually. As a result of the study, the user influence in the top three districts, with high-quality service, was stronger and wider than that of the lower three districts. It was confirmed that the quality of service of the park affects the user influence. This shows that to realize park equity, it is necessary to improve the quality of services through continuous management and improvement of individual parks and the creation of new parks. This study has significance in that it recognizes the limitations of research on park services from a supplier's point of view and evaluates the qualitative services of parks from the perspective of actual park users. We propose an alternative to deal with the lower the park deprivation index.

• Korean Journal of Agricultural and Forest Meteorology
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• v.25 no.1
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• pp.1-16
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• 2023

As the Intergovernmental Panel on Climate Change (IPCC) emphasized the transition to a carbon-neutral society globally by 205 0, major countries such as Korea, Japan, and Europe declared carbon-neutral goals. The agricultural sector is a carbon-absorbing sector, and its importance has increased as the General Assembly of the Parties to the Climate Change Convention (COP 26) held in the UK in November 2021 emphasized the role of agriculture to discuss climate change. However, GHG reduction projects in the agricultural sector are not properly monitored considering the domestic situation, and a system for quantitative evaluation of the effectiveness or basis of implementing the project program is not in place. Therefore, a priori study is needed to understand the current status of existing policies and to review matters that need to be improved in order to facilitate policy design, implementation, and monitoring for GHG reduction in the agricultural sector. The purpose of this study is to examine the opinions of stakeholders by applying a semi-structured interview method to diagnose the current status of Korea's GHG reduction policy in the agricultural sector and identify factors that hinder policy implementation. As a result of the semi-structured interview, this study presented factors that hinder the promotion of GHG reduction policies in the agricultural sector according to four types of data and technology, finance, institutions, and perceptions. Some stakeholders also stressed that the pilot project could be helpful as a way to comprehensively consider the implications of this study, such as securing technology data, establishing a system for verifying effectiveness, and providing incentives and promoting them. Rather than drawing specific conclusions, this study is an exploratory study that diagnoses and reviews the progress of GHG reduction policies, and it can be used as useful basic data if it secures enough interview respondents and balances the number of samples by group.

• Journal of Cadastre & Land InformatiX
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• v.52 no.2
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• pp.171-187
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• 2022

Recently, the demand and development for non-face-to-face services are rapidly progressing due to the pandemic caused by the COVID-19, and attention is focused on the metaverse at the center. Entering the era of the 4th industrial revolution, Metaverse, which means a world beyond virtual and reality, combines various sensing technologies and 3D reconstruction technologies to provide various information and services to users easily and quickly. In particular, due to the miniaturization and economic increase of convergence sensors such as unmanned aerial vehicle(UAV) capable of high-resolution imaging and high-precision LiDAR(Light Detection and Ranging) sensors, research on digital-Twin is actively underway to create and simulate real-life twins. In addition, Game engines in the field of computer graphics are developing into metaverse engines by expanding strong 3D graphics reconstuction and simulation based on dynamic operations. This study constructed a mirror-world type metaverse that reflects real-world coordinate-based reality using Unreal Engine 5, a recently announced metaverse engine, with accurate 3D spatial information data of convergence sensors based on unmanned aerial system(UAS) and LiDAR. and then, spatial information contents and simulations for users were produced based on various public data to verify the accuracy of reconstruction, and through this, it was possible to confirm the construction of a more realistic and highly utilizable metaverse. In addition, when constructing a metaverse that users can intuitively and easily access through the unreal engine, various contents utilization and effectiveness could be confirmed through coordinate-based 3D spatial information with high reproducibility.

• Korea Trade Review
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• v.48 no.4
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• pp.303-320
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• 2023

Recently, import and export companies have been using T/T remittance and Surrender B/L more frequently than L/C when selecting the process and method of trade payment settlement. The new trade and logistics environment is thriving in the era of the Fourth Industrial Revolution (4IR). Document-based trade transactions are undergoing a digitalization as bills of lading or smart contracts are being developed. The purpose of this study is to verify whether exporters choose export payment types based on negotiating factors. In addition, we would like to discuss the application of the characteristics of the new trade and logistics environment. Data for analysis was collected through surveys. The collection method consisted of direct visits to the company, e-mail, fax, and online surveys. The survey distribution period is from February 1, 2023, to April 30, 2023. The questionnaire was distributed in 2,000 copies, and 447 copies were collected. The final 336 copies were used for analysis, excluding 111 copies that were deemed inappropriate for the purpose of this study. The results of the study are shown below. First, among the negotiating factors, the product differentiation of exporters did not significantly affect the selection of export payment types. Second, among the negotiating factors, the greater the purchasing advantage recognized by exporters, the higher the possibility of using the post-transfer method. In addition to analyzing the results, this study suggests that exporters should consider adopting new payment methods, such as blockchain technology-based bills of lading and trade finance platforms, to adapt to the characteristics of the evolving trade and logistics environment. Therefore, exporters should continue to show interest in initiatives aimed at digitizing trade documents as a response to the challenges posed by bills of lading. In future studies, it is necessary to address the lack of social awareness in Korea by conducting advanced research abroad.

• Journal of Wetlands Research
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• v.26 no.2
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• pp.147-159
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• 2024

Lack of streamflow observations makes model calibration difficult and limits model performance improvement. Satellite-based remote sensing products offer a new alternative as they can be actively utilized to obtain hydrological data. Recently, several studies have shown that artificial intelligence-based solutions are more appropriate than traditional conceptual and physical models. In this study, a data-driven approach combining various recurrent neural networks and decision tree-based algorithms is proposed, and the utilization of satellite remote sensing information for AI training is investigated. The satellite imagery used in this study is from MODIS and SMAP. The proposed approach is validated using publicly available data from 25 watersheds. Inspired by the traditional regionalization approach, a strategy is adopted to learn one data-driven model by integrating data from all basins, and the potential of the proposed approach is evaluated by using a leave-one-out cross-validation regionalization setting to predict streamflow from different basins with one model. The GRU + Light GBM model was found to be a suitable model combination for target basins and showed good streamflow prediction performance in ungauged basins (The average model efficiency coefficient for predicting daily streamflow in 25 ungauged basins is 0.7187) except for the period when streamflow is very small. The influence of satellite remote sensing information was found to be up to 10%, with the additional application of satellite information having a greater impact on streamflow prediction during low or dry seasons than during wet or normal seasons.