• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.12 no.6
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• pp.22-28
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• 2013

This study aims to propose the location selection method of car-sharing services in Daejeon Metropolitan city. In order to select locations for car-sharing, Daejoen area was divided in $500m{\times}500m$ cell size using GIS Arc/Info 10, and input factors which may affect car-sharing service were determined, and then each input factor was standardized for analysis. The weight for each input factor was determined through experts' survey and index of goodness of fit was estimated in each cell ($500m{\times}500m$ size) using AHP method. Also, This study proposed the method to select 30 service facility location using Location-allocation Model in Network Analysis module. The proposed method for the location selection of car-sharing service in this study can be used for preliminary data for initial car-sharing introduction. Henceforward, appropriate demand forecasting and economic evaluation for the location selection of car-sharing service are needed for the further study.

• Journal of the Korea Convergence Society
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• v.11 no.4
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• pp.303-310
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• 2020

The purpose of this study was to verify the relationship between students' exercise ability beliefs, academic engagement and self-handicap in physical education class. To this end, this study selected a total of 437 copies of questionnaires as final valid samples using the convenience sampling method targeting middle school students at 4 schools in metropolitan area. For data processing, this study confirmed the goodness of fit test of the whole model using SPSS 20.0 and AMOS 20.0, and then did hypothesis testing; the study results are as follows: First, the increased belief of exercise ability beliefs was shown to have a static effect on the academic engagement, and a fixed belief did not have a significant effect on the academic engagement. Second, the increased belief was shown to have no significant effect on self-handicap, while the fixed belief had a static and significant effect on self-handicap. Third, the students' academic engagement has been confirmed to have a negative effect on self-handicap.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.11 no.2
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• pp.10-20
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• 2012

This study shows how to estimate AADT(Annual Average Daily Traffic) on temporary count data using new grouping method. This study deals with clustering permanent traffic counts using monthly adjustment factor, daily adjustment factor and a percentage of hourly volume. This study uses a percentage of hourly volume comparing with other studies. Cluster analysis is used and 5 groups is suitable. First, make average of monthly adjustment factor, average of daily adjustment factor, a percentage of hourly volume for each group. Next estimate AADT using 24 hour volume(not holiday) and two adjustment factors. Goodness of fit test is used to find what groups are applicable. MAPE(Mean Absolute Percentage Error) is 8.7% in this method. It is under 1.5% comparing with other method(using adjustment factors in same section). This method is better than other studies because it can apply all temporary counts data.

• Journal of Korean Society of Transportation
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• v.28 no.4
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• pp.119-128
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• 2010

Mode choice behavior is associated with travelers' latent behavior that is an unobservable preference to travel behavior or mode characteristics. This paper specifically addresses the problem of unobservable factors, that is latent behavior, in mode choice models. Consideration of latent behavior in mode choice models reduces the errors that come from unobservable factors. In this study, the authors defined the latent variables that mean a quantitative latent behavior factors, and developed the combined RP/SP model with latent variables using the mode choice behavior survey data. The data has traveler's revealed preference of existent modes along the Han River and stated preference of new water transit on the Han River. Also, The data has travelers' latent behavior. Latent variables were defined by factor analysis using the latent behaviour data. In conclusion, it is significant that the relationship between traveler's latent behavior and mode choice behavior. In addition, the goodness-of-fit of the mode choice models with latent variables are better than the model without latent variables.

• Journal of the Korean Society of Propulsion Engineers
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• v.20 no.6
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• pp.29-37
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• 2016

This paper proposes a shape optimization of the metal boss for a composite motor case using finite element analysis. For the structural safety and the weight reduction of the composite motor case, under the internal pressure, the fiber stress in the dome area and the tightening bolt stress are constrained and the boss weight is set to objective function, respectively. The response surface models are constructed for the performance characteristics by using response surface method. The significance of the design variables about the performance characteristics is evaluated through the ANOVA(analysis of variance) and the goodness of fit test for the constructed model is performed through the regression analysis. The SQP(sequential quadratic programming) algorithm is used for the optimization and the proposed method is verified by performing structural analysis for the optimum shape.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.3 s.37
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• pp.87-95
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• 2006

Recently, local heavy rain for a short term is caused by unusual changing in the weather. This phenomenon has, several times, caused an extensive flash flood, casualties, and material damage. This study is aimed at calculating the characteristics of flash floods in streams. For this purpose, the analysis of topographical characteristics of water basin through applying GIS techniques will be conducted. The flash flood prediction model we used is made with GCIUH (geomorphoclimatic instantaneous unit hydrograph). The database is established by the use of GIS and by the extraction of streams and watersheds from DEM. The streams studied are included small, middle and large scale watersheds. For the first, for the establishment or criteria on the flash flood warning, peak discharge and trigger runoff must be decided. This study analyzed the degree or aptitude of topographical factors to the trigger runoff calculated by GCUH model.

• Journal of Digital Contents Society
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• v.9 no.3
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• pp.379-388
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• 2008

This paper is to redefine the concept of Cyber Career Counseling Activation(=C-C-C-A) and verify the effects of the factors affecting the C-C-C-A at Korean academic high school level in Kyunggi Province. In this research, we hypothesize that the three independent variables increase the effects of Cyber Career Counseling Activation.. To discuss the hypothesis, we analyzed survey data of 322 students who had taken Cyber Career Counseling in December 2007 based on Structural Equation Model. The results are as follows: First, the three crucial factors(Expanding C-C-C Opportunities, Improving C-C-C Service, Establishing C-C-C Service System) increase the C-C-C-A effectiveness. Second, as a result of Confirmatory Factor Analysis(CFA), the goodness of fit indices(GFI, AGFI, CFI, RMSEA) demonstrate statistical significance and fitness of the C-C-C-A Model. Therefore, the outcomes show that the three factors are the significant ones of Cyber Career Counseling Activation Model.

• Journal of Korea Water Resources Association
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• v.34 no.2
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• pp.119-130
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• 2001

At-site and regional frequency analyses of annual maximum 1-, 2-, and 3-days rainfall in Han River basin was performed and compared based on the regional L-moments algorithm. To perform regional frequency analysis, Han River basin was subdivided into 3 sub-basins such as South Han River, North Han River, and downstream regions. For each sub-basin, the discordancy and homogeneity tests were performed. As the results of goodness of fit tests, lognormal model was selected as an appropriate probability distribution for both South Han River and downstream regions and gamma-3 model for North han River region. From Monte carlo simulation, RBIAS and RRMSE of the estimated quantiles from regional frequency analysis and at-site frequency analysis were calculated and compared each other. Regional frequency analysis shows less RRMSE of the estimated quantiles than at-sites frequency analysis in overall return periods. The differences of BRMSE between two approaches increase as the return period increases. As a result, it is shown that regional frequency analysis performs better than at-site analysis for annual maximum rainfall data in Han River basin.

• Journal of the Korea Convergence Society
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• v.10 no.3
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• pp.249-256
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• 2019

The purpose of this study was to inquire into the structural relations between teachers' attitudes, academic engagement, task-solving behavior which are perceived in a physical education class. To this end, this study selected a total of 434 copies of questionnaires as final valid samples using the convenience sampling method targeting middle school students at 5 schools located at a metropolitan area. For data processing, this study confirmed the goodness of fit test of the whole model using SPSS 20.0 and AMOS 20.0, and then did hypothesis testing; the study results are as follows: first, teachers' attitudes was to have influence on academic engagement. Second, academic engagement had positive influence on help-seeking, while self-handicapping had significantly negative influence. Third, teachers' attitudes had positive influence on help-seeking, while self-handicapping had significantly negative influence. Lastly, in the relationship between teachers' attitudes and task-solving behavior, academic engagement was found to play an intermediary role.

• Journal of Korea Planning Association
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• v.54 no.2
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• pp.93-108
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• 2019

This study examines the relationship between three-dimensional urban built environment and urban surface temperature using LANDSAT 8 satellite image data in Seoul city. The image was divided into 600m×600m grid units as an unit of analysis. Due to the high level of spatial dependency in surface temperature, this study uses spatial statistics to take into account spatial auto-correlation. The spatial error model shows the best goodness of fit. The analysis results show that the three-dimensional built environment and transport environment as well as natural environment have statistically significant associations with surface temperature. First, natural environment variables such as green space, streams and river, and average elevation show statistically significant negative association with surface temperature. Second, the building area shows a positive association with surface temperature. In addition, while sky view factor (SVF) has a positive association with surface temperature, surface roughness (SR) shows a negative association with it. Third, transportation related variables such as road density, railway density, and traffic volume show positive associations with surface temperature. Moreover, this study finds that SVF and SR have different effects on surface temperature in regard to the levels of total floor areas in built environment. The results indicate that interactions between floor area ratio (FAR) and three-dimensional built environmental variables such as SVF and SR should be considered to reduce urban surface temperature.