• Journal of Korean Society of Coastal and Ocean Engineers
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• v.23 no.6
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• pp.496-501
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• 2011

The missing data patterns of tidal elevation data in Korean coasts are analysed and provided. The missing interval of the data is displayed for all stations using the missing data indicator matrix in order to identify the overall missing pattern. The spatial and temporal missing rates are also estimated. The total missing rate of tidal elevation data is low. However, most of the missing is mainly derived from just 1 or 2 specific stations. The autocorrelation function of the consecutive missing interval data also shows that the missing interval occurs randomly.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.1
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• pp.45-56
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• 2007

Direct estimation of the pollutant load(PL) should be carried out by the data filling in the missing intervals using an appropriate method because it is impossible in which the flow discharge(water quantity) or water quality(WQ) time-series data set have the missing intervals. In this study, the several methods estimating the water quality in the missing periods are suggested and the WQ and pollutants load change patterns are compared and evaluated based on the reproducible degree of the available data change patterns. The most appropriate method is finally suggested and the contribution factor deciding the influence degree and the PL characteristics of the river estuary is also suggested. Based on the PL estimation results using the several methods, the interpolation method considering the fluctuation of the available WQ data is shown to be most efficient. The PL patterns of the Han river estuary is classified as the discharge-dominated type. The data filling process is inevitable and the WQ estimation using the efficient and effective method should be carried out in order to estimate reasonable PL.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.33 no.6
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• pp.333-344
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• 2021

Technique for the long-gap filling that occur frequently in ocean monitoring data is developed. The method estimates the unknown values of the long-gap by the summation of the estimated trend and selected residual components of the given missing intervals. The method was used to impute the data of the long-term missing interval of about 1 month, such as temperature and water temperature of the Ulleungdo ocean buoy data. The imputed data showed differences depending on the monitoring parameters, but it was found that the variation pattern was appropriately reproduced. Although this method causes bias and variance errors due to trend and residual components estimation, it was found that the bias error of statistical measure estimation due to long-term missing is greatly reduced. The mean, and the 90% confidence intervals of the gap-filling model's RMS errors are 0.93 and 0.35~1.95, respectively.

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1035-1046
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• 2022

This study evaluated the applicability of multi-resolution data fusion for land-cover classification. In the applicability evaluation, a spatial time-series geostatistical deconvolution/fusion model (STGDFM) was applied as a multi-resolution data fusion model. The study area was selected as some agricultural lands in Iowa State, United States. As input data for multi-resolution data fusion, Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat satellite images were used considering the landscape of study area. Based on this, synthetic Landsat images were generated at the missing date of Landsat images by applying STGDFM. Then, land-cover classification was performed using both the acquired Landsat images and the STGDFM fusion results as input data. In particular, to evaluate the applicability of multi-resolution data fusion, two classification results using only Landsat images and using both Landsat images and fusion results were compared and evaluated. As a result, in the classification result using only Landsat images, the mixed patterns were prominent in the corn and soybean cultivation areas, which are the main land-cover type in study area. In addition, the mixed patterns between land-cover types of vegetation such as hay and grain areas and grass areas were presented to be large. On the other hand, in the classification result using both Landsat images and fusion results, these mixed patterns between land-cover types of vegetation as well as corn and soybean were greatly alleviated. Due to this, the classification accuracy was improved by about 20%p in the classification result using both Landsat images and fusion results. It was considered that the missing of the Landsat images could be compensated for by reflecting the time-series spectral information of the MODIS images in the fusion results through STGDFM. This study confirmed that multi-resolution data fusion can be effectively applied to land-cover classification.

• Water for future
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• v.22 no.2
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• pp.201-211
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• 1989

Using the storm data which was augmented by the stochastic correlation with it's neighbors, the multiquadric equation of random surface of total storm depth is constructed. And to separate the local components from it's regionals and find the regional characteristics, a double Fourier analysis was applied to the total depths of storm data. The local components, storm residuals of each storm was assumed to be homogeneous random field and investigated with it's autocorrelation function. For the practical application, isotropic was assumed and that was identified with emprical data. Coefficients of normalized autocorrelation for all storms showed similar apperance. Using this emprical result, an example of the radial spectral distribution function which represints the spatial characteristics of rainfall over Han River Basin during 1975-1983 is presented.

• Spatial Information Research
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• v.20 no.5
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• pp.1-13
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• 2012

This study intends to evaluate the seasonal flow direction of carbon dioxide in Northeast Asia by using GOSAT, the first Greenhouse Observing SATellite, in an attempt to overcome costly, laborious and time consuming ground observation which has been frequently pointed out in existing studies. For this purpose, missing values were supplemented by applying the Kriging interpolation and the overall flow direction of carbon dioxide was determined through anisotoropy semi-variogram. As a result, it was found that the overall spatial distribution of carbon dioxide in Northeast Asia varies depending on the latitude, and that carbon dioxide mainly flows southeast or east in spring, autumn and winter, but northeast or north in summer. Similar to the flow of monsoons in Northeast Asia, these results show that carbon dioxide flows mainly from the west to the east, which proves that carbon dioxide discharged from China is influencing even the Korean Peninsula and Japan. However, as the flow of carbon dioxide varies depending on a variety of factors such as artificial sources, plant respiration, and the absorption and discharge of the ocean, follow-up studies are requested to evaluate such variables and the correlations.

• The Journal of Bigdata
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• v.5 no.2
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• pp.69-76
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• 2020

This study was conducted with the support of the Information and Communication Technology Promotion Center, funded by the government (Ministry of Science and ICT) in 2019. Highly pathogenic avian influenza (HPAI) is an acute infectious disease of birds caused by highly pathogenic avian influenza virus infection, causing serious damage to poultry such as chickens and ducks. High pathogenic avian influenza (HPAI) is caused by focusing on winter rather than year-round, and sometimes does not occur at all during a certain period of time. Due to these characteristics of HPAI, there is a problem that does not accumulate enough actual data. In this paper study, GAN network was utilized to generate actual similar data containing missing values and the process is introduced. The results of this study can be used to measure risk by generating realistic simulation data for certain times when HPAI did not occur.

• Water for future
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• v.5 no.1
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• pp.27-36
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• 1972

This thesis is the study of the rainfall probability depth in the major areas of Korea, such as Seoul, Pusan and Taegu. The purpose of the paper is to analyze the rainfall in connection with the safe planning of the hydraulic structures and with the project life. The methodology used in this paper is the statistical treatment of the rainfall data in the above three areas. The scheme of the paper is the following. 1. The complementation of the rainfall data We tried to select the maximm values among the values gained by the three methods: Fourier Series Method, Trend Diagram Method and Mean Value Method. By the selection of the maximum values we tried to complement the rainfall data lacking in order to prevent calamities. 2. The statistical treatment of the data The data are ordered by the small numbers, transformed into log, $\sqrt{}, \sqrt[3]{}, \sqrt[4], and$\sqrt[5], and calculated their statistical values through the electronic computer. 3. The examination of the distribution types and the determination of the optimum distibution types By the $x^2-Test$ the distribution types of rainfall data are examined, and rejected some part of the data in order to seek the normal rainfall distribution types. In this way, the optimum distribution types are determined. 4. The computation of rainfall probability depth in the safety project life We tried to study the interrelation between the return period and the safety project life, and to present the rainfall probability depth of the safety project life. In conclusion we set up the optimum distribution types of the rainfall depths, formulated the optimum distributions, and presented the chart of the rainfall probability depth about the factor of safety and the project life.ct life.

• Journal of agriculture & life science
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• v.46 no.3
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• pp.129-141
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• 2012

The purpose of this study was to monitor the stream flow of rural streams for investigating the status of stream depletion located downstream of irrigation reservoir. Bonghyun and Hai reservoirs area, located in Hai-myeon, the city of Gosung, Gyeongsangnam Province, were selected for study watersheds and streams. Stream flow monitoring was conducted 7 times from March to September, 2011. Stream flow was measured for 8 stations downstream from two reservoirs. The stream depletion was found in most of the downstream of reservoirs for the non-irrigation period and even in the irrigation period when there were a lot of antecedent precipitation. The correlation analysis for water quality data indicated that the correlation between BOD and T-N was highest for the reservoirs. The correlation between BOD, T-N, and turbidity was high for Hai reservoir and Bonghyeon reservoir. Continuous monitoring for rural streams located in downstream of reservoirs are required to quantify the status of stream flow depletion and determine the amount of environmental flows.

• Sleep Medicine and Psychophysiology
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• v.12 no.2
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• pp.111-116
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• 2005

Objectives: Although many reports have been written on seasonal variations in mood and behavior in foreign countries, few reports have dealt with Korean adolescents, except medical students. The goal of this study was to estimate the frequency of seasonal variations in mood and behavior among Korean high school students. Methods: A total of 656 high school students living in southeastern Seoul participated in this study. The subjects were investigated with the Korean translated version of the Seasonal Pattern Assessment Questionnaire (SPAQ), and their responses were evaluated for seasonal patterns in mood and behavior change according to Kasper's criteria to make SAD (seasonal affective disorder) or SSAD (subclinical seasonal affective disorder) diagnosis. Results: A total of 565 subjects completed the questionnaire and the responses (M：F=324：241) were collected and used for analysis. The mean age was 16.73 (SD=0.65) years, and mean global seasonality score 5.88 (SD=4.72). Of the respondents, 413 (73.1%) reported problems related with seasonal changes. Total prevalence rates were 13.6% for SAD, 10.8% for S-SAD. The estimated frequencies were 5.1% for summer SAD, 3.2% for summer S-SAD, 0.5% for winter SAD and 1.1% for winter S-SAD. The prevalence rate of summer SAD or S-SAD was higher than winter SAD or S-SAD. Conclusion: The subjects showed a higher prevalence rate of summer type than winter type in SAD or S-SAD. These results were similar to those of other studies carried out in East Asian countries. However, the unpleasant feelings resulting from high temperature and humidity in summer rather than depression may have influenced the results. Therefore, it is necessary to make new SAD criteria of the SPAQ suitable for East Asian countries.