• Korean Journal of Remote Sensing
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• v.37 no.2
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• pp.291-304
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• 2021

Updating a forest type map is essential for sustainable forest resource management and monitoring to cope with climate change and various environmental problems. According to the necessity of efficient and wide-area forestry remote sensing, CAS500-4 (Compact Advanced Satellite 500-4; The agriculture and forestry satellite) project has been confirmed and scheduled for launch in 2023. Before launching and utilizing CAS500-4, this study aimed to pre-evaluation the possibility of satellite-based tree species classification using RapidEye, which has similar specifications to the CAS500-4. In this study, the study area was the Chuncheon forest management complex, Gangwon-do. The spectral information was extracted from the growing season image. And the GLCM texture information was derived from the growing and non-growing seasons NIR bands. Both information were used to classification with random forest machine learning method. In this study, tree species were classified into nine classes to the coniferous tree (Korean red pine, Korean pine, Japanese larch), broad-leaved trees (Mongolian oak, Oriental cork oak, East Asian white birch, Korean Castanea, and other broad-leaved trees), and mixed forest. Finally, the classification accuracy was calculated by comparing the forest type map and classification results. As a result, the accuracy was 39.41% when only spectral information was used and 69.29% when both spectral information and texture information was used. For future study, the applicability of the CAS500-4 will be improved by substituting additional variables that more effectively reflect vegetation's ecological characteristics.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.2
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• pp.259-266
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• 2021

Recently, the financial industry has seen a dramatic change due to the development of innovative technologies such as FinTech, but there is a lack of research on the digital level of financial institution workers. This study analyzes factors that affect the willingness of financial institution workers to accept digital innovation and to examine the relationship between acceptance intention and business performance. Based on the theoretical basis of UTAUT, independent variables were divided into internal expectations, external influences, facilitation conditions, and employment risks. Survey data of 100 bankers at N bank were analyzed using SPSS and AMOS 18. Studies have shown that internal expectations and external influences have positive effects on the acceptance intention of financial institution workers, and that facilitation conditions, employment risks do not. This study found a significant relationship between acceptance intention and business performance and confirming that acceptance intention has a direct and indirect impact on business performance. Study findings could be a reference to enhancing the willingness to accept digital innovation technologies and developing ways to improve business performance by validating factors that affect the willingness of financial institution workers to accept digital innovation.

• Korean Journal of Environmental Biology
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• v.40 no.2
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• pp.214-223
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• 2022

Among migratory insect pests, Mythimna seperata and Cnaphalocrocis medinalis are invasive pests introduced into South Korea through westerlies from southern China. M. seperata and C. medinalis are insect pests that use rice as a host. They injure rice leaves and inhibit rice growth. To understand the distribution of M. seperata and C. medinalis, it is important to understand environmental factors such as temperature and humidity of their habitat. This study predicted current and future habitat suitability models for understanding the distribution of M. seperata and C. medinalis. Occurrence data, SSPs (Shared Socio-economic Pathways) scenario, and RCP (Representative Concentration Pathway) were applied to MaxEnt (Maximum Entropy), a machine learning model among SDM (Species Distribution Model). As a result, M. seperata and C. medinalis are aggregated on the west and south coasts where they have a host after migration from China. As a result of MaxEnt analysis, the contribution was high in the order of Land-cover data and DEM (Digital Elevation Model). In bioclimatic variables, BIO_4 (Temperature seasonality) was high in M. seperata and BIO_2 (Mean Diurnal Range) was found in C. medinalis. The habitat suitability model predicted that M. seperata and C. medinalis could inhabit most rice paddies.

• Asia Marketing Journal
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• v.10 no.2
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• pp.31-69
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• 2008

The purpose of this study is to identify the organizational characteristics that enhance CRM performances of a company. Based on a review of diverse definitions of CRM performance, this study examines the relationships among CRM performance measures and organizational characteristics. A questionnaire survey of 123 CRM managers of Korean companies was conducted to test the proposed research model, and a series of structural equation modeling identified the strong effects of organizational characteristics on CRM performance. It was found that top management commitment to CRM and a firm's strategic readiness lead to high levels of CRM investment, which, in turn, enhance directly task-related performance and indirectly customer-related performance. This study also confirmed that customer orientation is significantly related to task-related CRM performance and that the variables of CRM commitment and organizational culture may enhance customerrelated performance indirectly through their effects on the task-related performance. However, organizational members' resistance to change was found to have no effects on CRM performance. Overall our research broadly supports the role of organizational characteristics revealed in the CRM literature.

• The Mathematical Education
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• v.63 no.1
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• pp.19-33
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• 2024

This study investigates longitudinal patterns in middle school students' mathematics interest and achievement using panel data from the 4th to 6th year of the Gyeonggi Education Panel Study. Results from the multivariate growth mixture model confirmed the existence of heterogeneous characteristics in the longitudinal trajectory of students' mathematics interest and achievement. Students were classified into four latent classes: a low-level class with weak interest and achievement, a high-level class with strong interest and achievement, a middlelevel-increasing class where interest and achievement rise with grade, and a middle-level-decreasing class where interest and achievement decline with grade. Each class exhibited distinct patterns in the change of interest and achievement. Moreover, an examination of the correlation between intercepts and slopes in the multivariate growth mixture model reveals a positive association between interest and achievement with respect to their initial values and growth rates. We further explore predictive variables influencing latent class assignment. The results indicated that students' educational ambition and time spent on private education positively affect mathematics interest and achievement, and the influence of prior learning varies based on its intensity. The perceived instruction method significantly impacts latent class assignment: teacher-centered instruction increases the likelihood of belonging to higher-level classes, while learner-centered instruction increases the likelihood of belonging to lower-level classes. This study has significant implications as it presents a new method for analyzing the longitudinal patterns of students' characteristics in mathematics education through the application of the multivariate growth mixture model.

• KDI Journal of Economic Policy
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• v.30 no.2
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• pp.185-223
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• 2008

This paper considers a heterogeneous agent dynamic general equilibrium model and analyzes effects of an increase in labor income tax rate on labor market and the aggregate variables in Korea. The fiscal policy regarding how the government uses the additional tax revenue may take the two forms: 1) general transfer and 2) earned income tax credit (EITC). The model features are as follows: 1) Workers are heterogeneous in their productivity. 2)Labor is indivisible, hence the analysis focuses on the variation in labor supply through the extensive margin in response to a change in fiscal policy. 3) The incomplete markets are introduced, so individual workers can not perfectly insure themselves against risks related to stochastic changes in income or employment status. 4) The model is of general equilibrium, hence it is equiped to analyze the feedback effect of changes in aggregate variables on individual workers' decisions. In the case of general transfer policy, the government equally distributes the additional tax revenue to all workers regardless of their employment states. Under this policy, an increase in the labor income tax rate dampens work incentives of individual workers so that the aggregate employment rate decreases by 1% compared with the benchmark economy. In the case of EITC policy, only employed workers whose labor incomes are below a certain EITC ceiling are eligible for the EITC benefits. Unlike the general transfer policy, the EITC induces low-income workers to participate the labor market to be eligible for EITC benefits. Hence, the aggregate employment rate may increase by 2.7% at the maximum. As the EITC ceiling increases, too many workers can collect the EITC but the benefits per worker becomes too little so that the increase in employment rate is negligible. By and large, this study demonstrates that EITC may effectively raise the aggregate employment rate, and that it can be a useful policy tool in response to the decrease in the labor force due to population aging as observed in Korea recently.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.747-763
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• 2022

Ocean salinity affects ocean circulation on a global scale and low salinity water around coastal areas often has an impact on aquaculture and fisheries. Microwave satellite sensors (e.g., Soil Moisture Active Passive [SMAP]) have provided sea surface salinity (SSS) based on the dielectric characteristics of water associated with SSS and sea surface temperature (SST). In this study, a Light Gradient Boosting Machine (LGBM)-based model for generating high resolution SSS from Geostationary Ocean Color Imager (GOCI) data was proposed, having machine learning-based improved SMAP SSS by Jang et al. (2022) as reference data (SMAP SSS (Jang)). Three schemes with different input variables were tested, and scheme 3 with all variables including Multi-scale Ultra-high Resolution SST yielded the best performance (coefficient of determination = 0.60, root mean square error = 0.91 psu). The proposed LGBM-based GOCI SSS had a similar spatiotemporal pattern with SMAP SSS (Jang), with much higher spatial resolution even in coastal areas, where SMAP SSS (Jang) was not available. In addition, when tested for the great flood occurred in Southern China in August 2020, GOCI SSS well simulated the spatial and temporal change of Changjiang Diluted Water. This research provided a potential that optical satellite data can be used to generate high resolution SSS associated with the improved microwave-based SSS especially in coastal areas.

• Journal of Korea Water Resources Association
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• v.57 no.1
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• pp.1-8
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• 2024

Persistent droughts due to climate change will intensify water shortage problems in Korea. According to the 1st National Water Management Plan, the shortage of domestic and industrial waters is projected to be 0.07 billion m³/year under a 50-year drought event. A long-term prediction of water demand is essential for effectively responding to water shortage problems. Unlike industrial water, which has a relatively constant monthly usage, domestic water is analyzed on monthly basis due to apparent monthly usage patterns. We analyzed monthly water usage patterns using water usage data from 2017 to 2021 in Chungcheong, South Korea. The monthly water usage rate was calculated by dividing monthly water usage by annual water usage. We also calculated the water distribution rate considering correlations between water usage rate and climate variables. The division method that divided the monthly water usage rate by monthly average temperature resulted in the smallest absolute error. Using the division method with average temperature, we calculated the water distribution rates for the Chungcheong region. Then we predicted future water usage rates in the Chungcheong region by multiplying the average temperature of the SSP5-8.5 scenario and the water distribution rate. As a result, the average of the maximum water usage rate increased from 1.16 to 1.29 and the average of the minimum water usage rate decreased from 0.86 to 0.84, and the first quartile decreased from 0.95 to 0.93 and the third quartile increased from 1.04 to 1.06. Therefore, it is expected that the variability in monthly water usage rates will increase in the future.

• Journal of Life Science
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• v.12 no.4
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• pp.442-451
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• 2002

In oder to investigate the effects of pH and temperature on the formation of bromate ion, which is ozonation by-products of bromine containing natural water. At the same intial pH condition, the increase of pH shown similar trends even if the reaction variables such as temperature and reaction time of ozonation were changed. As pH and temperature were increasing, the bromate concentration was increased but bromine components (HOBr/OBr-) were decreased with increasing pH from 3 to 10. Lipid peroxide content in the kidney was increased by bromate which was ingestion with 0.4g/L for 24 weeks in drinking water. Renal cytosolic enzyme system (XO, AO) of bromate group were significantly increased in comparison with those of normal group. But microsomal enzyme system were not affected. BUN level and urinary ${\gamma}$-glutamyltransferase activity were significantly increased in comparison with those of the normal. But, urinary lactate dehydrogenase activity was not affected. Renal glutathione content of rat was significantly decreased in comparison with those of normal rat given bromate. Renal glutathione S-transferase and ${\gamma}$-glutamylcysteine synthetase activities were significantly decreased in bromate-treated group, but change in renal glutathione reductase activity was not significantly different from any other experimental group.

• Journal of The Korean Society of Grassland and Forage Science
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• v.8 no.2
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• pp.110-116
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• 1988

The response of forage yield was studied with various growth indices to develop yield model and to determine optimum cutting time in three cultivars of orchardgrass. 1. Number of tiller per plant was the highest at 3rd cutting stage. But, it was decreased rapidly at 4th cutting stage. Leaf Area Index (LAI) was the highest at 3rd cutting stage. LAI was increased slowly during 15 days to 20 days after cutting and thereafter increased rapidly. 2. In dry matter yield over cutting stages, 1st cutting and 3rd cutting stages were higher yield than others. Change of dry matter yield was similar to that of LAI in all cutting stages. 3. Leaf Elongation Rate (LER) and Specific Leaf Weight (SLW) were reached to maximum at 20 to 25 days and 25 to 30 days after cutting, respectively. 4. Dry matte yield was highly correlated with LAI (r-0.905)and with CGR (r-0.962) over three cultivars. Also, LAI was significantly with LER. The best-fit yield model was obtained in multiple regression equation which included both dependent variables of LAI and CGR. 5. Optimum cutting times which were determined by the relationships between D.M. yield and LAI, and between D.M. yield and CGR, were ranged from 32 days to 36 days depend on each cutting stages.