• Journal of Environmental Health Sciences
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• v.45 no.1
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• pp.82-96
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• 2019

Objective: The aims of this study were to provide the basic data for establishing a precautionary management policy and to develop a methodology for selecting a radon management priority target area suitable for the Korean domestic environment. Methods: A suitable mapping method for the domestic environment was derived by conducting a quantitative comparison of predicted values and measured values that were calculated through implementation of two models such as IDW and RBF methods. And a qualitative comparison including the clarity of information transmission of the written radon map was carried out. Results: The predicted and measured values were obtained through the implementation of the spatial analysis models. The IDW method showed the lowest in the calculated mean square error and had a higher correlation coefficient than the other methods. As results of comparing the uncertainty using the jackknife concept and the concept of error distance for comparison of the differences according to the model interpolation method, the sum of the error distances showed a modest increase compared with the RBF method. As a result of qualitatively comparing the information transfer clarity between the radon maps prepared with the predicted values through the model implementation, it was found that the maps plotted using the predicted values by the implementation of the IDW method had greater clarity in terms of highness and lowness of radon concentration per area compared with the maps plotted by other methods. Conclusions: The radon management priority area suggests selecting a metropolitan city including an area with a high radon concentration.

• Geotechnical Engineering
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• v.3 no.2
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• pp.17-28
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• 1987

Reliability of the cone penetration test (CPT) for estimating shear strength of marine soils is investigated in this paper. For sands, the uncertainty about the angle of internal friction is analyzed. It includes the spatial variation of the soil and the model error in the equation used for interpretation. The most serious uncertainty encountered was the error in the interpretative models. Different methods of interpretation gave quite different values. Subjective opinion was introduced to combine all the interpretative models in a systematic manner. For clays, the undrained Shear Strength from the CPT results is usually =derived by empirical correlations between cone resistance and untrained shear strength from laboratory tests or field vane tests, expressed in terms of cone factor and function of overburden pressure. The uncertainty of the undrained shear strength is caused by data scatter of the cone factor in the correlation, model error of the cone factor, effect of anisotropy, and spatial variability of cone resistance. Among these uncertainties, the most serious one was the data scatter of the cone factor in the .correlation. Between the laboratory test and the field vane test used for correlation, the field vane test was more reliable.

• Journal of Wetlands Research
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• v.21 no.spc
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• pp.51-60
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• 2019

In this study, we performed At-site Frequency Analysis(AFA) and Regional Frequency Analysis(RFA) using the observed and climate change scenario data, and the relative root mean squared error(RMMSE) was compared and analyzed for both approaches through Monte Carlo simulation. To evaluate the rainfall quantile, the daily rainfall data were extracted for 615 points in Korea from HadGEM3-RA(12.5km) climate model data, one of the RCM(Regional Climate Model) data provided by the Korea Meteorological Administration(KMA). Quantile mapping(QM) and inverse distance squared methods(IDSM) were applied for bias correction and spatial disaggregation. As a result, it is shown that the RFA estimates more accurate rainfall quantile than AFA, and it is expected that the RFA could be reasonable when estimating the rainfall quantile based on climate change scenarios.

• Journal of Korean Society of Forest Science
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• v.102 no.4
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• pp.467-476
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• 2013

Site index information given from forest site map only exist in the sampled locations. In this study, site index for unsampled locations were estimated using kriging interpolation method which can interpolate values between point samples to generate a continuous surface. Site index of Pinus densiplora in Danyang area were calculated using Chapman-Richards model by plot unit. Then site index for unsampled locations were interpolated by theoretical variogram models and ordinary kriging. Also in order to assess parameter selection, cross-validation was performed by calculating mean error (ME), average standard error (ASE) and root mean square error (RMSE). In result, gaussian model was excluded because of the biggest relative nugget (37.40%). Then spherical model (16.80%) and exponential model (8.77%) were selected. Site index estimates of Pinus densiplora throughout the entire area in Danyang showed 4.39~19.53 based on exponential model, and 4.54~19.23 based on spherical model. By cross-validation, RMSE had almost no difference. But ME and ASE from spherical model were slightly lower than exponential model. Therefore site index prediction map from spherical model were finally selected. Average site index from site prediction map was 10.78. It can be expected that regional variance can be considered by site index prediction map in order to estimate forest biomass which has big spatial variance and eventually it is helpful to improve an accuracy of forest carbon estimation.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.22 no.3
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• pp.74-81
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• 2014

The coverage area of GNSS regional ionospheric correction model is mainly determined by the disribution of GNSS ground monitoring stations. Outside the coverage area, GNSS users may receive ionospheric correction signals but the correction does not contain valid correction information. Extrapolation of the correction information can extend the coverage area to some extent. Three interpolation methods, Kriging, biharmonic spline and cubic spline, are tested to evaluate the extrapolation accuracy of the ionospheric delay corrections outside the correction coverage area. IGS (International GNSS Service) ionosphere map data is used to simulate the corrections and to compute the extrapolation error statistics. Among the three methods, biharmonic method yields the best accuracy. The estimation error has a high value during Spring and Fall. The error has a high value in South and East sides and has a low value in North side.

• Journal of Environmental Science International
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• v.20 no.1
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• pp.93-106
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• 2011

Physically-based resampling scheme for roughness coefficient of surface runoff considering the spatial landuse distribution was suggested for the purpose of effective operational application of recent grid-based distributed rainfall runoff model. Generally grid scale(mother scale) of hydrologic modeling can be greater than the scale (child scale) of original GIS thematic digital map when the objective basin is wide or topographically simple, so the modeler uses large grid scale. The resampled roughness coefficient was estimated and compared using 3 different schemes of Predominant, Composite and Mosaic approaches and total runoff volume and peak streamflow were computed through distributed rainfall-runoff model. For quantitative assessment of biases between computational simulation and observation, runoff responses for the roughness estimated using the 3 different schemes were evaluated using MAPE(Mean Areal Percentage Error), RMSE(Root-Mean Squared Error), and COE(Coefficient of Efficiency). As a result, in the case of 500m scale Mosaic resampling for the natural and urban basin, the distribution of surface runoff roughness coefficient shows biggest difference from that of original scale but surface runoff simulation shows smallest, especially in peakflow rather than total runoff volume.

• Korean Journal of Childcare and Education
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• v.15 no.6
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• pp.139-167
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• 2019

Objective: This study aims to investigate the effects of a learning cycle model-based early childhood education program using physical motion on young children's scientific inquiry ability, scientific attitude, object manipulation ability and spatial ability. Methods: The subjects of this study were 60 five-year-old children who were attending K-G City Childcare Center. The SPSS Window 21.0 program and content analysis method were used, and post-validation Tukey was conducted to examine the differences between the one-way ANOVA and the group. Results: Activities using body movement were practiced systematically based on the circle learning. Children could revise their pre-concept and concept of error by interacting with other children, teachers and the environment. Furthermore, children were attaining new knowledge while they were doing body movement activities, assessing and applying them to actual activities. Conclusion/Implications: This study is investigated a cyclic learning-based early childhood science education program using physical motion, which has significance in systematic and practical early childhood centered education for young children.

• The Journal of Asian Finance, Economics and Business
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• v.6 no.4
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• pp.179-187
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• 2019

This study aims to investigate the effects of market commonality and resource similarity on price competition and the recursive consequences in the Korean lodging market. Price comparison among hotels in the same geographic market has been facilitated through the development of information technology, rendering little search cost of consumers. While the literature implies the heterogeneous price attack and response among hotels, a limited number of empirical researches focus on the asymmetric and recursive pattern in the competitive dynamics. This study empirically examines the price interactions in the Korean lodging market based on the theoretical framework of competitive price interactions and countervailing power. Demonstrating superiority to the spatial lag model and the ordinary least squares in the estimation, the results from spatial error model suggest that the hotels with longer operational history pose an asymmetric impact on the price of the newer hotels. The asymmetry is also found in chain hotels over the independent, further implying the possibility of predatory pricing. The findings of this study provide the evidence of a hierarchical structure in the price competition, with different countervailing power by the resources of the hotels. Theoretical and managerial implications are discussed, with suggestions for future study.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.164-164
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• 2016

Radar rainfall estimates have been widely used in calculating rainfall amount approximately and predicting flood risks. The radar rainfall estimates have a number of error sources such as beam blockage and ground clutter hinder their applications to hydrological flood forecasting. Moreover, it has been reported in paper that those errors are inter-correlated spatially and temporally. Therefore, in the current study, we tested influence about spatio-temporal errors in radar rainfall estimates. Spatio-temporal errors were simulated through a stochastic simulation model, called Multivariate Autoregressive (MAR). For runoff simulation, the Nam River basin in South Korea was used with the distributed rainfall-runoff model, Vflo. The results indicated that spatio-temporal dependent errors caused much higher variations in peak discharge than spatial dependent errors. To further investigate the effect of the magnitude of time correlation among radar errors, different magnitudes of temporal correlations were employed during the rainfall-runoff simulation. The results indicated that strong correlation caused a higher variation in peak discharge. This concluded that the effects on reducing temporal and spatial correlation must be taken in addition to correcting the biases in radar rainfall estimates. Acknowledgements This research was supported by a grant from a Strategic Research Project (Development of Flood Warning and Snowfall Estimation Platform Using Hydrological Radars), which was funded by the Korea Institute of Construction Technology.

• Journal of the Korean Data and Information Science Society
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• v.28 no.1
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• pp.11-20
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• 2017

In this paper, we introduced linear spatial time series (space-time autoregressive and moving average model) and nonlinear spatial time series (space-time bilinear model). Also we estimated the parameters by Kalman Filter method and made comparative studies of power of forecast in the final model. We proposed several weight matrices such as equal proportion allocation, reciprocal proportion between distances, and proportion of population sizes. For applications, we collected Mumps data at Korea Center for Disease Control and Prevention from January 2001 until August 2008. We compared three approaches of weight matrices using the Mumps data. Finally, we also decided the most effective model based on sum of square forecast error.