• Journal of the Korea Society of Computer and Information
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• v.17 no.2
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• pp.41-48
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• 2012

In modern society, the necessity of Color and Psychology Therapy is increasing for psychologically calm children who are less taken care by their parents in busy daily life, and helping them adapt to the environment. Therefore, we need to understand sensitivity status of children with paintings that they draw. Currently, most of empirical studies on their sensitivities are based on psychological and engineering perspectives. This study was designed to provide a system to extract psychological status of children from their pictures by distinguishing harmony of colors using information of solid colors and arrangement of colors in the image space. For achieving this research purpose, first of all, sensitivity database was constructed based on the image space of colors. Then, using the K-Means algorithm, the image was clustered and a wide amount of color values were divided into groups. After that, children's sensitivities were extracted by matching groups of color values with database, and color psychological status of children was observed using the color distribution chart in their paintings.

• The Korean Journal of Applied Statistics
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• v.34 no.1
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• pp.39-56
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• 2021

Many researches have been done on portfolio optimization since Markowitz (1952) published a diversified investment model. Markowitz's mean-variance portfolio optimization problem is established under the assumption that the distribution of returns follows a normal distribution. However, in real life, the distribution of returns does not follow a normal distribution, and variance is not a robust statistic as it is heavily influenced by outliers. To overcome these potential issues, mean-shortfall portfolio model was proposed that utilized downside risk, shortfall, as a risk index. In this paper, we propose a perturbation method that uses the shortfall as a risk index of the portfolio. The proposed portfolio utilizes an adaptive Lasso to obtain a sparse and stable asset selection because it can reduce management and transaction costs. The proposed optimization is easily applicable as it can be computed using an efficient linear programming. In our real data analysis, we show the validity of the proposed perturbation method.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.4 s.38
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• pp.45-51
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• 2006

Recently the coast is an important area in terms of spatial land use and natural environment conservation such as the expansion of a national land and the development of a coastal industrial zone in Korea. We can not provide a proper solution for a boundary determination raised by a land ownership dispute due to the insufficient coast land registration. We observed the status of the coast land registration and analyzed the problem through the investigation of the difference between a land title and a coast land in the study area. We selected the west coast with the big difference between the ebb and flow of the tide as the study area from a paper review, compared a cadastral line with a coast line and suggested a good guideline to solve the problem through understanding the status of the coast land title registration in Korea.

• Spatial Information Research
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• v.19 no.6
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• pp.75-86
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• 2011

This paper proposes a modified way to delimit the boundary of Busan metropolitan area and compares the empirical analysis with the existing metropolitan area boundary. More specifically, the present state of the metropolitan transportation network is reflected by service area analysis in our study area. The analysis of the linkage between the central city and its fringes considers various travel behaviors as well as commuting to work and school, based on origin-destination trip information. In addition, more diverse indices are applied to the analysis of urban characteristics, and the land cover map is used as well. Compared with the current Busan metropolitan area boundary, our empirical analysis captures the status quo of the undergoing spatial dynamics such as the newly form ed homogeneous sphere of living in our study area.

• Journal of Korea Water Resources Association
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• v.49 no.5
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• pp.439-450
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• 2016

For the design of infrastructures controlling the flood events at ungauged basins, this study tries to find the regional flood frequencies using peak flow data generated by the spatial extension of flood records. The Chungju Dam watershed is selected to validate the possibility of regional flood frequency analysis using the spatially extended flood data. Firstly, based on the index flood method, the flood event data from the spatial extension method is evaluated for 22 mid/smaller sub-basins at the Chungju Dam watershed. The homogeneity of the Chungju dam watershed was assessed in terms of the different size of watershed conditions such as accumulated and individual sub-basins. Based on the result of homogeneity analysis, this watershed is heterogeneous with respect to individual sub-basins because of the heterogeneity of rainfall distribution. To decide the regional probability distribution, goodness-of fit measure and weighted moving averages method from flood frequency analysis were adopted. Finally, GEV distribution was selected as a representative distribution and regional quantile were estimated. This research is one step further method to estimate regional flood frequency for ungauged basins.

• The Korean Journal of Applied Statistics
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• v.33 no.1
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• pp.25-46
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• 2020

This paper presents ordinal probit semiparametric regression models using Bayesian Spectral Analysis Regression (BSAR) method. Ordinal probit regression is a way of modeling ordinal responses - usually more than two categories - by connecting the probability of falling into each category explained by a combination of available covariates using a probit (an inverse function of normal cumulative distribution function) link. The Bayesian probit model facilitates posterior sampling by bringing a latent variable following normal distribution, therefore, the responses are categorized by the cut-off points according to values of latent variables. In this paper, we extend the latent variable approach to a semiparametric model for the Bayesian ordinal probit regression with nonparametric functions using a spectral representation of Gaussian processes based BSAR method. The latent variable is decomposed into a parametric component and a nonparametric component with or without a shape constraint for modeling ordinal responses and predicting outcomes more flexibly. We illustrate the proposed methods with simulation studies in comparison with existing methods and real data analysis applied to a Korean National Health and Nutrition Examination Survey (KNHANES) 2016 for investigating nonparametric relationship between smoking behavior and coffee intake.

• Economic and Environmental Geology
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• v.57 no.1
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• pp.51-71
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• 2024

Seismic exploration is one of the widely used geophysical exploration methods with various applications such as resource development, geotechnical investigation, and subsurface monitoring. It is essential for interpreting the geological characteristics of subsurface by providing accurate images of stratum structures. Typically, geological features are interpreted by visually analyzing seismic sections. However, recently, quantitative analysis of seismic data has been extensively researched to accurately extract and interpret target geological features. Seismic attribute analysis can provide quantitative information for geological interpretation based on seismic data. Therefore, it is widely used in various fields, including the analysis of oil and gas reservoirs, investigation of fault and fracture, and assessment of shallow gas distributions. However, seismic attribute analysis is sensitive to noise within the seismic data, thus additional noise attenuation is required to enhance the accuracy of the seismic attribute analysis. In this study, four kinds of seismic noise attenuation methods are applied and compared to mitigate random noise of poststack seismic data and enhance the attribute analysis results. FX deconvolution, DSMF, Noise2Noise, and DnCNN are applied to the Youngil Bay high-resolution seismic data to remove seismic random noise. Energy, sweetness, and similarity attributes are calculated from noise-removed seismic data. Subsequently, the characteristics of each noise attenuation method, noise removal results, and seismic attribute analysis results are qualitatively and quantitatively analyzed. Based on the advantages and disadvantages of each noise attenuation method and the characteristics of each seismic attribute analysis, we propose a suitable noise attenuation method to improve the result of seismic attribute analysis.

• Solar Energy
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• v.18 no.3
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• pp.51-61
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• 1998

This study attempts to suggest the architectural design methods of toplight system, which is a glass covered space on the top of building with greenhouse for instance. In this study, toplight system will be experimented, analysed and presented as a solution method for environmental control system in the summer.

• The Korean Journal of Applied Statistics
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• v.34 no.2
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• pp.239-254
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• 2021

This paper studies time series analysis with estimation and forecasting for Korean COVID-19 confirmed cases, based on the approach of a heterogeneous autoregressive (HAR) model with two-piece t (TP-T) distributed errors. We consider HAR-TP-T time series models and suggest a step-by-step method to estimate HAR coefficients as well as TP-T distribution parameters. In our proposed step-by-step estimation, the ordinary least squares method is utilized to estimate the HAR coefficients while the maximum likelihood estimation (MLE) method is adopted to estimate the TP-T error parameters. A simulation study on the step-by-step method is conducted and it shows a good performance. For the empirical analysis on the Korean COVID-19 confirmed cases, estimates in the HAR-TP-T models of order p = 2, 3, 4 are computed along with a couple of selected lags, which include the optimal lags chosen by minimizing the mean squares errors of the models. The estimation results by our proposed method and the solely MLE are compared with some criteria rules. Our proposed step-by-step method outperforms the MLE in two aspects: mean squares error of the HAR model and mean squares difference between the TP-T residuals and their densities. Moreover, forecasting for the Korean COVID-19 confirmed cases is discussed with the optimally selected HAR-TP-T model. Mean absolute percentage error of one-step ahead out-of-sample forecasts is evaluated as 0.0953% in the proposed model. We conclude that our proposed HAR-TP-T time series model with optimally selected lags and its step-by-step estimation provide an accurate forecasting performance for the Korean COVID-19 confirmed cases.

• Journal of the HCI Society of Korea
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• v.13 no.1
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• pp.21-28
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• 2018

The rapid increase of Sinlge-person household and the increase in the use of smart devices necessitate the context analysis of Sinlge-person household and specific design direction for Sinlge-person household products. Previous studies have analyzed the overall context of smart devices without distinguishing between Sinlge-person household and a household. However, since the number of family members, age distribution, and residential space are different in the case of Sinlge-person household, it is necessary to analyze the different behaviors of smart devices. Therefore, this study limits the use environment of smart device of Single-person household to the scope of investigation, and based on the theoretical background, defines the existing comprehensive context based on user's situation that lasts for a certain interval. For the concrete and empirical research results, Consolidated Flow Model was constructed through Contextual Task through user research. This shows the interaction characteristics such as the guarantee of physical space, efficiency, lifestyle reflection, and safety assurance of Single-person household.