• The Journal of the Korea Contents Association
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• v.17 no.2
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• pp.55-70
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• 2017

In order to understand job burnout, it is necessary to consider not only the working environment according to the market environment but also the social situation of the team or the organization. This study analyzed the effects of job demands and job resources on job burnout based on JD-R theory. In other words, the team-level variables, servant leadership and HRM control types, were tested for the effect of moderating the individual workload, emotional labor and job burnout. The results of empirical analysis showed that the higher the self-efficacy, the less job burnout, whereas the higher the workload and emotional labor, the more job burnout. Second, the more positive the team level input and result oriented HRM are, the less positive regression relation of workload and job burnout is. Finally, it was found that the intensity of the regression relation of negative self-efficacy and job burnout was amplified in the team with servant leadership.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.221-231
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• 2021

This paper identify factors of migration of employees' household who work for relocated public institutions. As a factors of migration, we consider individual and household characteristics, the gravity model of distance and population and so on. Considering discrete dependant variable and structure of data, we employ the logistic multilevel model and random intercept model. The result indicates employees' who are female, 30s and 40s, higher education level(PhD) and whose spouse are unemployed tend to transfer their residential registration to new city near relocated public institution. Regarding regional variable, the distance from employee's previous residential location and number of migration of prior year are statistically significant. Also the model indicate regional economy, educational and residential environment of new city influence employee's decision for transferring residential registration.

• Korea Real Estate Review
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• v.27 no.3
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• pp.51-70
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• 2017

This study aimed to measure street centralities with the street width, and to analyze their effects on the residential and non-residential land prices in Seoul, South Korea. Most of the studies on urban economics and policy focusing on the urban spatial structure have evolved in terms of their perspective from monocentric to polycentric models. Recently, their themes shifted to measuring street centralities and capturing their effects on urban phenomena. To expand the existing studies and discussion, this study analyzed the street centralities with the street width, and how they changed the land prices. Multilevel regression models generated a few key findings relevant to the relationship between street centralities and land prices. While a higher detour volume and closeness to wider streets commanded premium residential land prices, higher visibility and detour volume to wider streets were associated with higher non-residential land prices. These findings suggest a robust connection between street configuration and near-land prices. Thus, the results of this study suggest a few insightful policy implications for urban planners, urban designers, real estate developers, and appraisers.

• The Korean Journal of Applied Statistics
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• v.36 no.5
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• pp.361-380
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• 2023

Magnetoencephalography (MEG) is a technique to record oscillatory magnetic fields coming from ongoing neuronal activity. Functional brain activities performing cognitive or physiological tasks are performed on structural connections between neurons or brain regions. MEG data can be characterized as highly correlated, spatio-temporal, multidimensional, multilayered dynamic networks. Due to its complex structure, many studies on MEG network have not yet been conducted. In this study, we will explain the concept, necessity, and possible approaches of MEG network analysis. We reviewed the characteristics of MEG data. Network measures and potential network models in MEG and clinical studies are also reviewed.

• Survey Research
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• v.18 no.2
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• pp.67-98
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• 2017

The purposes of this study are to identify the latent classes of school violence depending on bullying and victimized experience by type and the influences of individual-level and school-level variables on determining these latent profiles. For these research goals, the present study utilized data from the Seoul Education Longitudinal Study(SELS) 5th wave, containing data from 2,195 middle school students who experienced school violences more than once. Multilevel latent profile models were applied to examine school violence among students. Our results indicated that there were four latent classes; high-level bullying and victimized group (1.7%), mainly bullying group(2.1%), mainly victimized group(3.7%), verbal bullying and victimized group(92.5%). Gender, resilience, self-control, peer relationship, parental relationship were significant determinants of the latent profiles at student level. Teacher-student relationships, school violence prevention, gender ratio of school were significant determinants of the latent profiles at school level. The present study contributed to extending theoretical discussions by classifying students into groups based on frequency and different forms of bullying and victimization. Moreover, this study examined determinants of student and school level simultaneously by dealing with multilevel data.

• Korean Journal of Social Welfare
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• v.68 no.3
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• pp.29-50
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• 2016

This study examined the determinants of housing affordability using the 2014 fact-finding survey of housing. This study identified the effects of characters of districts as well as the effects of characters of family and housing, taking advantage of HGLM(Hierarchical General Linear Model). The results of this study showed that male householder, higher education level, the monthly housing, higher satisfaction of environment of housing are the factors that increased the odds of living at unaffordable housing, but higher income, public transfer recipient, living at sub-standard housing, the Jensei housing are the factors that decreased the odds of living at unaffordable housing. And the higher housing price, the higher rent of the districts increased significantly the odds of living at unaffordable housing, but the higher rate of public housing of the districts decreased the odds of living at unaffordable housing. This study provides the basis that the price of housing and rent should be controled and the policy of public housing should be expanded for housing welfare.

• Journal of Digital Convergence
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• v.15 no.5
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• pp.89-98
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• 2017

This study aims to examine whether the life satisfaction of the elderly living alone is influenced by demographic background, economic activity, productive leisure participation and the moderating effect of social support. Data in this study was from 5th Korean Retirement Income Study, and 890 elderly living alone were extracted and analyzed, and a multi-level analysis was used to analyze the data because the life satisfaction of the elderly living alone has a random effect according to the region. The results of this study were as follows; First, the elderly living alone showed high life satisfaction when they live in province rather than Seoul or metropolitan city, spend higher living expenses, do economic activities, and they are economically independent. Second, those who participated in productive leisure activity were more satisfied with life than those who did not, and those who have social support are more satisfied with their life. Third, the relationship between productive leisure participation and life satisfaction was moderated by social support. When the elderly living alone participate in productive leisure activities, they feel more life satisfaction according to social support given to them.

• 한국노년학
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• v.36 no.3
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• pp.581-594
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• 2016

This study aims to observe the effect of age friendliness of cities on life satisfaction and to suggest ways to improve quality of life of older people. The secondary data sets were used in this study, which were '2014 Survey of Living Conditions and Welfare Needs of Korean Older People.' It's a nationwide data collected by the Korean Institute of Health and Social Affairs. A multilevel analysis model was used to analyze the data because the level of age friendliness has a hierarchical data structure. Results showed as follows: First, life satisfaction of older adults is affected by the level of age-friendliness of cities in which they live. Second, on the personal level, older people showed low life satisfaction when they are more older and have more chronic diseases and more depressed. On the contrary, life satisfaction of older adults increased when they have higher education and income. Third, on the city level, older people showed higher life satisfaction when they live in high employment rate area and participation rate of lifelong education. Cautions should be placed when interpret the result because the variables that represent the characteristics of age friendless of cities were constituted arbitrary. Based on the results, suggestions for improving the city environment age-friendly and implications for social welfare practice were provided.

• Journal of Korea Water Resources Association
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• v.55 no.2
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• pp.121-133
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• 2022

The drought resulting from insufficient rainfall compared to the amount in an ordinary year can significantly impact a broad area at the same time. Another feature of this disaster is hard to recognize its onset and disappearance. Therefore, a reliable and fast way of predicting both the suffering area and the amount of water shortage from the upcoming drought is a key issue to develop a countermeasure of the disaster. However, the available drought scenarios are about 50 events that have been observed in the past. Due to the limited number of events, it is difficult to predict the water shortage in a case where the pattern of a natural disaster is different from the one in the past. To overcome the limitation, in this study, we applied the four RCP climate change scenarios to the water balance model and the annual amount of water shortage from 360 drought events was estimated. In the following chapter, the deep neural network model was trained with the SPEI values from the RCP scenarios and the amount of water shortage as the input and output, respectively. The trained model in each sub-basin enables us to easily and reliably predict the water shortage with the SPEI values in the past and the predicted meteorological conditions in the upcoming season. It can be helpful for decision-makers to respond to future droughts before their onset.

• Smart Media Journal
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• v.11 no.3
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• pp.74-89
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• 2022

Due to the unique recipes and processes of each company, not only differences among the results of dyeing textile materials exist but they are also difficult to predict. This study attempted to develop a color prediction model based on deep learning to optimize color realization in the dyeing process. For this purpose, deep learning-based models such as multilayer perceptron, CNN and LSTM models were selected. Three forecasting models were trained by collecting a total of 376 data sets. The three predictive models were compared and analyzed using the cross-validation method. The mean of the CMC (2:1) color difference for the prediction results of the LSTM model was found to be the best.