• KSCE Journal of Civil and Environmental Engineering Research
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• v.28 no.4B
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• pp.375-381
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• 2008

In this research, a physics based grid-multi layer distributed flood runoff model was developed to analyze discharge for the Namgang Dam Watershed ($2,293km^2$) and applied for sensitivity analysis for estimation of parameters, mainly initial soil moisture condition and saturate infiltration coefficient, which have a strong influence on discharge. Capability of the model was evaluated using VER and QER from the results of rainfall-runoff analysis and showed enhanced results of 6% compared to parameters before calibration. As the result with the sensitivity analysis of parameters, the part of the most influence on the runoff was the infiltration coefficient and ratio of layer partition. The total discharge and peak time showed comparatively precise runoff results without the initial calibration of the parameters.

• Proceedings of the Korea Institute of Fire Science and Engineering Conference
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• 2011.11a
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• pp.163-166
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• 2011

본 연구는 Zone Model을 활용하여 장대도로터널의 화재성상 예측방법의 고찰을 목적으로 1/5 Scale 모형실험 및 MLZSUZUKI 결과 분석과 CFD와 MLZ의 비교 분석을 실시하였다. Modeling한 모형터널의 해석시간이 MLZ 1분, FDS 약 6시간으로 CFD에 비하여 360배의 시간 감소와 다층으로 구분하여 구간의 온도변화 및 환기풍에 의한 열기류의 움직임 등의 상황이 해석됨으로 향후 MLZ을 활용하여 터널화재의 위험성 예측에 용이할 것으로 판단된다.

• Journal of The Korean Association of Information Education
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• v.22 no.4
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• pp.457-471
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• 2018

This study examined student- and school-level background and ICT factors that affected PISA 2015 Collaborative Problem Solving (CPS) for Korean students (4863 students from 142 high schools). A two-level hierarchical linear model (HLM) was analyzed from the basic model (model 1) with no predictors to the final model (model 5) with all predictors. Results showed that first, gender, socioeconomic/cultural backgrounds, cooperation level positively predicted CPS scores while perceived unfairness of teacher negatively predicted the outcome. Second, the more frequently ICT was used for out-of-school learning purposes, the less frequently ICT was used for entertainment purposes, and the less frequently ICT was used in schools, the higher CPS scores were. Considering ICT autonomy and social interaction variables measured for the first time in PISA 2015, students who were more interested in ICT and more autonomous in using ICT devices achieved higher CPS scores. On the other hand, the more students considered ICT important as social interaction, the less they gained CPS scores. Third, in terms of school-level characteristics, the smaller the students behavior detrimental to learning, the higher the teachers perceived positive working environment, and the fewer the number of computers available per student, the higher CPS scores were. To facilitate computer-based collaborative problem-solving competence, it is important for students to have interest and autonomy in using ICT. In addition, the guidelines of ICT use and SW curriculum need to be established in order to increase the effectiveness of using ICT device in school.

• Korean Journal of Social Welfare
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• v.58 no.2
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• pp.119-141
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• 2006

This study aims to explore the status and characteristics of the working poor and to identify the major determinants of their statistic status. For this, longitudinal panel data (from 2nd wave(1999) data to 7th wave(2004) data) from Korean Labor and Income Panel Study (KLIPS), is used. The data is analyzed by adopting Hierarchical Generalized Linear Model (HGLM), which is known as an app.opriate data analysis method for the hierarchically structured data, to look at the factors that affect on the poverty status of the working people. The results show that 1) it is estimated that about 1 out of 10 working people (about 10.0%) are poor, and 2) sex, education level, marital status, region where they lives, employment status, occupation type, and industry type that they are working at are significant predictors in determining their poverty status. Unlike the results of the previous studies, however, the number of the household member, age are not influenced on their poverty status. Based on these results, several policy implications are presented at the end of this paper.

• Journal of the Korea Society of Computer and Information
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• v.26 no.5
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• pp.111-117
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• 2021

The object of this study is through an empirical analysis, how cultural capital at the individual level and social welfare expenditure at the national level affect the life satisfaction of the elderly. In this study method, a Hierarchical Linear Model(HLM) analysis was performed on 3,297 elderly people aged 65 and older and 9 OECD countries. As a result of analysis, first, it was confirmed that life satisfaction and social class had a significant effect. Therefore, in to increase the satisfaction of the life of the elderly, policy and practical intervention measures that can narrow the gap between social classes should be prepared. Second, the old-age pension and survivor's pension had no significant effect on life satisfaction. However, as a result of the interaction, social class has a positive effect on life satisfaction, and it was confirmed that the lower the income inequality, the more positive the life satisfaction was. In conclusion, this implies that both individuals and countries should make efforts to variously increase the life satisfaction of the elderly.

• Journal of the Korean GEO-environmental Society
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• v.3 no.4
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• pp.11-17
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• 2002

The purpose of this study is the prediction of pollutant loads into Seomjin river watershed using neural networks model. The pollutant loads into river watershed depend upon the water quantity of inflow from the upstream as well as the water quality of the inflow into the river. For the estimation of pollutants into river, a neural networks model which has the features of multi-layered structure and parallel multi-connections is used. The used water quality parameters are BOD, COD and SS into Seomjin river. The results of calibration are satisfactory, and proved the availability of a proposed neural networks model to estimate short-term water quality pollutants into river system.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10b
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• pp.310-312
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• 2001

본 연구에서는 정보시스템의 지능형 인터페이스를 위하여 사용자의 개인성을 학습하는 방법론으로서 신경망 이론의 활용가능성을 고찰한다. 입력형식의 유연성, 입력의 왜곡 및 소실가능성 등 시스템의 실용성과 연관하여 나타나는 자료의 특성을 수용하기 위하여, 학습과정에서 신호표현의 다양화와 부분 패턴의 의한 분류 기능 등을 개선한 신경망모델을 제안한다. 이를 위하여 퍼지 양방향 연상기억장치와 구간연산으로 일반화된 다층 신경망모델을 결합하여 혼합형 분류모형을 제시하고 그 유용성을 고찰한다. 실험은 전공분야 선택을 위한 개인의 적성분석시스템을 대상으로 구현하였다.

• Korean Journal of Comparative Education
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• v.28 no.1
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• pp.135-151
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• 2018

This study was conducted to help establish the status of comparative education as an academic discipline by investigating its relationship with educational evaluation. Comparative education as a subfield of education covers other areas of study in education, while educational evaluation is a study of methodology. First, international comparative study was investigated, and recent methodologies in educational evaluation were introduced. International comparative study started in 1960's, and is being expanded. The participating countries hope for better education by comparing their educational curricula and practices with others. For international comparative studies, a differential item functioning analysis as a multigroup analysis can provide information on what sociocultural factors other than the construct are affecting the measurement results. The study dataset has a hierarchical structure so that multilevel item response theory is suitable to obtain multidimensional national profiles. Although there have been methodological advances in educational evaluation, the methods are not available in comparative education. In order to reduce the gap, scholars in educational evaluation should try to make the methods easily available, while those in comparative education should try to use the exact and precise methods in their studies.

• Journal of the Korean Society of Child Welfare
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• no.56
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• pp.101-132
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• 2016

Fandom is a meaningful social phenomenon that represents a significant dimension of contemporary Korean youth culture. Previous research, however, has considered fandom as a deviant activity that is negative in nature, and there is scant research on the positive effects of fandom activity. This study examined the effects of off-line and on-line fandom activity participation on adolescents' academic time management capability. Data were collected from three waves (2010, 2012, and 2014) of the Korean Children and Youth Panel Survey (middle school cohort; N=2,206 at baseline). Results from the multi-level growth curve analysis were as follows. First, more than half of the adolescents reported participating in fandom activities, and the majority of them participated in both online and offline activities. Second, adolescents' academic time management capability improved over time. Third, both off-line and on-line fandom activity participation was positively associated with adolescents' academic time management capability at the baseline (first year of middle school). The size of this relationship, however, decreased over time (from middle school to high school). This study presented the importance of appropriate guidance by adults to develop and promote the positive aspects of fandom activity, and highlighted the need for further research that focuses on the positive aspects of fandom activities.

• Journal of Korea Water Resources Association
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• v.33 no.5
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• pp.537-550
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• 2000

In this study, Neural Networks models were used to forecast daily streamflow at Jindong station of the Nakdong River basin. Neural Networks models consist of CASE 1(5-5-1) and CASE 2(5-5-5-1). The criteria which separates two models is the number of hidden layers. Each model has Fletcher-Reeves Conjugate Gradient BackPropagation(FR-CGBP) and Scaled Conjugate Gradient BackPropagation(SCGBP) algorithms, which are better than original BackPropagation(BP) in convergence of global error and training tolerance. The data which are available for model training and validation were composed of wet, average, dry, wet+average, wet+dry, average+dry and wet+average+dry year respectively. During model training, the optimal connection weights and biases were determined using each data set and the daily streamflow was calculated at the same time. Except for wet+dry year, the results of training were good conditions by statistical analysis of forecast errors. And, model validation was carried out using the connection weights and biases which were calculated from model training. The results of validation were satisfactory like those of training. Daily streamflow forecasting using Neural Networks models were compared with those forecasted by Multiple Regression Analysis Mode(MRAM). Neural Networks models were displayed slightly better results than MRAM in this study. Thus, Neural Networks models have much advantage to provide a more sysmatic approach, reduce model parameters, and shorten the time spent in the model development.