• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.35-51
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• 2008

Comparative studies in Phase III clinical trials quite often involve two or more equally important endpoints, and one cannot select primary endpoint from them. O'Brien(1984) proposed for continuous endpoints the OLS and GLS statistics as milti-variate test statistics. Pocock et al. (1987) mentioned the possibility of analyzing a mixture of data types, such as quantitative, binary and survival data types, with the OLS and GLS statistics, but the authors did not explore problems in combining several endpoints of different types. Furthermore, they did not perform a simulation study to assess the efficiencies of the OLS and GLS statistics for endpoints of a mixture of data types. In this paper, we propose the combining methods of correlated P-values for the analysis of multiple endpoints, and compare the efficiencies of this method with those of OLS and GLS statistics for a mixture of data types with a simulation study. Among the several methods of combining P-values that are more advantageous than combining of OLS and GLS statistics, method B maintains nominal significance levels and is more efficient, while method F and G have type I error rates that are larger than the specified significance levels, which might occasionally lead to a wrong conclusion.

• Environmental and Resource Economics Review
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• v.13 no.2
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• pp.219-243
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• 2004

Generally, electricity market has monopoly market structure because of need of enormous investment for infrastructure. However, the introduction of competition in network industry as electricity is a tendency of the world with decreasing the effects of economy of scale due to the advancement of technology. Now, electricity industry restructuring is in progress but the competition in electricity retail market is not in force yet in Korea. Whether a effective competition exist or not is very important to policy decision maker who drive restructuring, but there are small numbers of quantitative researches on that. In this study, we estimated the effectiveness of competition in the electricity retail market through switching costs. If switching costs are high, consumers actually can be locked in incumbent firm in spite of introduction of competition. Therefore switching is a critical factor to determine effectiveness of competition and to estimate the size of switching costs quantitatively can proffer the information about whether the competition in the electricity retail market is effective or not in the future. We estimated switching costs using consumer' stated-preference data by conjoint analysis. In according to estimation results, the cost of switching process is not so high, but the relative brand loyalty of an incumbent company is significantly high. And the price is considered as the most important factor choosing an electric service commodity. Based on the empirical results, it is possible to analyze the relationship between suppliers' competitiveness resulted from management efficiency and customers' switching possibilities. The paper therefore provides guidance for suppliers in deciding to enter into retail competition and for policy makers in introducing retail competition. And it has a significance of estimating the switching costs directly.

• Journal of Agricultural Extension & Community Development
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• v.19 no.4
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• pp.961-987
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• 2012

The present study is to investigate the characteristics and determinants of spatial distribution of strong small farm by defining the term, strong small farm (SSF) extracting the SSF households data dealing with apples, from 2010 Census of Agriculture, Forestry and Fisheries, Korea. Spatial distribution and concentration of SSF are analyzed based on spatial clustering techniques. We construct discrete dependent variables on strong and non-strong small farms and then analyze the determinants of the SSFs using probit model, with independent variables including population and economic characteristics and management characteristics. As of 2010, the apple SSFs, 1,529 households in total, are geographically concentrated in Gyeonsangbuk-do according to the analysis results. The determinants of SSF are similar to those of farms' earnings. When located in the apple producing area, and participating in producers organization while selling products directly, the farm is highly likely an SSF. The findings and results of the present study are expected to provide fundamental information helpful for preparing and implementing policies for SSFs in that the present study investigates the characteristics of SSF, which is a prerequisite step for SSF-related policies.

• Environmental and Resource Economics Review
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• v.14 no.2
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• pp.337-379
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• 2005

This choice experiments study values the non-market benefits of water quality improvements in Paldang Reservoir and Han River, located in Korea. A fractional factorial orthogonal design was used to produce four different choice sets per respondent, before employing choice examples to screen out irrational responses. The panel mixed logit model (with normal distributions for the attributes) fit the data best, indicating that allowing for both heterogeneous preferences across households and correlation between repeated choices may represent actual choice behaviors best of all the estimated models. The significant standard deviations of the random attributes suggest that the taste for each attribute may vary considerably in the population. The annual benefits to the Seoul Metropolitan area for a small (large) enhancement of the clarity of water, a gradual removal of unpleasant waters, and a gradual improvement in biodiversity, were estimated to be some 1.5 trillion (1.7 trillion) Won, 2 trillion Won, and 1.7 trillion Won, respectively, with 1.8~2.6 trillion Won for at least two of them occurring together. The study also discusses potential biases germane to choice experiments studies of this type.

• Journal of Conservation Science
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• v.33 no.5
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• pp.371-380
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• 2017

To investigate the pigments used in modern and contemporary oil paintings, thirty-two paintings by Jiho Oh and Bonung Gu were selected. The white pigment found in the ground and painting layers was identified as lead white (hydrocerussite), zinc white (zinc oxide), titanium white (titanium dioxide in anatase or rutile forms), calcite (calcium carbonate), and barite (barium sulfate). Further, this indicated that pigments differ according to the artist and date of the painting's creation. However, both Oh and Gu used zinc white during the modern and contemporary period, while lead white was replaced by titanium white, barite and calcite. Compared with the overseas studies on pigments and oil paints, the change patterns of pigments were the same with them but the periods of the use were partially different. It seems to be due to the fact that South Korea is linked to the historical background of the art material which was imported from Japan instead of Western countries. Therefore, it is inevitable that any change in the white pigments used for domestic oil paintings occurred at a different time from global transitions. If the results of this study are used in the analysis of art works it is suggested that a database recording such aspects as material properties of oil paints, artistic techniques, and chronology would become important for future conservation science and the study of art history.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.967-977
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• 2022

The occurrence and intensity of wildfires are increasing with climate change. Emissions from forest fire smoke are recognized as one of the major causes affecting air quality and the greenhouse effect. The use of satellite product and machine learning is essential for detection of forest fire smoke. Until now, research on forest fire smoke detection has had difficulties due to difficulties in cloud identification and vague standards of boundaries. The purpose of this study is to detect forest fire smoke using Level 1 and Level 2 data of Geostationary Environment Monitoring Spectrometer (GEMS), a Korean environmental satellite sensor, and machine learning. In March 2022, the forest fire in Gangwon-do was selected as a case. Smoke pixel classification modeling was performed by producing wildfire smoke label images and inputting GEMS Level 1 and Level 2 data to the random forest model. In the trained model, the importance of input variables is Aerosol Optical Depth (AOD), 380 nm and 340 nm radiance difference, Ultra-Violet Aerosol Index (UVAI), Visible Aerosol Index (VisAI), Single Scattering Albedo (SSA), formaldehyde (HCHO), nitrogen dioxide (NO₂), 380 nm radiance, and 340 nm radiance were shown in that order. In addition, in the estimation of the forest fire smoke probability (0 ≤ p ≤ 1) for 2,704 pixels, Mean Bias Error (MBE) is -0.002, Mean Absolute Error (MAE) is 0.026, Root Mean Square Error (RMSE) is 0.087, and Correlation Coefficient (CC) showed an accuracy of 0.981.

• Journal of the Korean earth science society
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• v.43 no.1
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• pp.60-76
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• 2022

This study presents a software full setup and the following test execution times in a Linux cluster for the United Kingdom Earth System Model (UKESM) and then compares the model results from control and experimental simulations of the UKESM relative to various observations. Despite its low resolution, the latest version of the UKESM can simulate tropospheric chemistry-aerosol processes and the stratospheric ozone chemistry using the United Kingdom Chemistry and Aerosol (UKCA) module. The UKESM with UKCA (UKESM-UKCA) can treat atmospheric chemistryaerosol-cloud-radiation interactions throughout the whole atmosphere. In addition to the control UKESM run with the default CMIP5 SO₂ emission dataset, an experimental run was conducted to evaluate the aerosol effects on meteorology by changing atmospheric SO₂ loading with the newest REAS data over East Asia. The simulation period of the two model runs was 28 years, from January 1, 1982 to December 31, 2009. Spatial distributions of monthly mean aerosol optical depth, 2-m temperature, and precipitation intensity from model simulations and observations over East Asia were compared. The spatial patterns of surface temperature and precipitation from the two model simulations were generally in reasonable agreement with the observations. The simulated ozone concentration and total column ozone also agreed reasonably with the ERA5 reanalyzed one. Comparisons of spatial patterns and linear trends led to the conclusion that the model simulation with the newest SO₂ emission dataset over East Asia showed better temporal changes in temperature and precipitation over the western Pacific and inland China. Our results are in line with previous finding that SO₂ emissions over East Asia are an important factor for the atmospheric environment and climate change. This study confirms that the UKESM can be installed and operated in a Linux cluster-computing environment. Thus, researchers in various fields would have better access to the UKESM, which can handle the carbon cycle and atmospheric environment on Earth with interactions between the atmosphere, ocean, sea ice, and land.

• Korean Journal of Remote Sensing
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• v.36 no.5_3
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• pp.1053-1066
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• 2020

Sulfur dioxide (SO₂) is primarily released through industrial, residential, and transportation activities, and creates secondary air pollutants through chemical reactions in the atmosphere. Long-term exposure to SO₂ can result in a negative effect on the human body causing respiratory or cardiovascular disease, which makes the effective and continuous monitoring of SO₂ crucial. In South Korea, SO₂ monitoring at ground stations has been performed, but this does not provide spatially continuous information of SO₂ concentrations. Thus, this research estimated spatially continuous ground-level SO₂ concentrations at 1 km resolution over South Korea through the synergistic use of satellite data and numerical models. A stacking ensemble approach, fusing multiple machine learning algorithms at two levels (i.e., base and meta), was adopted for ground-level SO₂ estimation using data from January 2015 to April 2019. Random forest and extreme gradient boosting were used as based models and multiple linear regression was adopted for the meta-model. The cross-validation results showed that the meta-model produced the improved performance by 25% compared to the base models, resulting in the correlation coefficient of 0.48 and root-mean-square-error of 0.0032 ppm. In addition, the temporal transferability of the approach was evaluated for one-year data which were not used in the model development. The spatial distribution of ground-level SO₂ concentrations based on the proposed model agreed with the general seasonality of SO₂ and the temporal patterns of emission sources.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.3
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• pp.147-153
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• 2013

There exist various types of the WEC (Wave Energy Converter), and among them, the point absorber is the most popularly investigated type. However, it is difficult to find examples of systematically measured data analysis for the design of the point absorber type of power buoy in the world. The study investigates the wave load acting on the point absorber type resonance power buoy wave energy extraction system proposed by Kweon et al. (2010). This study analyzes the time series spectra with respect to the three-year wave data (2002.05.01~2005.03.29) measured using the pressure type wave gage at the seaside of north breakwater of Hupo harbor located in the east coast of the Korean peninsula. From the analysis results, it could be deduced that monthly wave period and wave height variations were apparent and that monthly wave powers were unevenly distributed annually. The average wave steepness of the usual wave was 0.01, lower than that of the wind wave range of 0.02-0.04. The mode of the average wave period has the value of 5.31 sec, while mode of the wave height of the applicable period has the value of 0.29 m. The occurrence probability of the peak period is a bi-modal type, with a mode value between 4.47 sec and 6.78 sec. The design wave period can be selected from the above four values of 0.01, 5.31, 4.47, 6.78. About 95% of measured wave heights are below 1 m. Through this study, it was found that a resonance power buoy system is necessary in coastal areas with low wave energy and that the optimal design for overcoming the uneven monthly distribution of wave power is a major task in the development of a WEF (Wave Energy Farm). Finding it impossible to express the average spectrum of the usual wave in terms of the standard spectrum equation, this study proposes a new spectrum equation with three parameters, with which basic data for the prediction of the power production using wave power buoy and the fatigue analysis of the system can be given.

• Proceedings of the KSR Conference
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• 2011.10a
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• pp.1730-1738
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• 2011

Personal Rapid Transit (PRT) has emerged as a promising alternative transportation mode for transit-oriented sustainable communities by creating compact and walkable environments with competitive construction and operational costs. This study seeks to capture the changes in travel mode choice behavior in response to the introduction of PRT to travelers who have no previous experience of using it. A critical issue in modeling the PRT mode choice is how to capture travelers' perception and evaluation of the unexperienced travel mode. The data used come from questionnaire surveys, in which RP (Revealed Preference) and SP (Stated Preference) data were collected in relation to travel mode choices with and without PRT systems. The questionnaire was designed especially for mitigating the potential bias in favor of or against choosing PRT. In addition, an efficient approach was proposed to reduce the number of SP questions by avoiding the complex fractional factorial design which tends to make it difficult for respondents to keep their attention throughout the survey. The analysis results show that the proposed approach is able to realistically capture the effects of explanatory variables on the travel mode choice. Discrete choice models are developed to predict travelers' mode choices under different choice scenarios by varying PRT system specifications and operational characteristics. PRT patronages are projected for two different test sites using the developed PRT mode choice models.