• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.1069-1076
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• 2014

Rainfall weather patterns have changed due to global warming and sudden heavy rainfalls have become more frequent. Economic loss due to heavy rainfall has increased. We study the generalized Pareto distribution for modelling rainfall in Seoul based on data from 1973 to 2008. We use several priors including Jeffrey's noninformative prior and Gibbs sampling method to derive Bayesian posterior predictive distributions. The probability of heavy rainfall has increased over the last ten years based on estimated posterior predictive distribution.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.6
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• pp.1316-1322
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• 2005

Specially, though electronic commerce and electron signature technology through internet rose, PKI (Public Key Ifrastructure) is one of technologies. PKI brought several kind of new standards in encryption base technology. In spite of several kind of standardizations consist lively, shortcoming of solutions that apply PKI is expensive and slow. If main interest of encryption technology including PKI is the fast speed and security that improve, this is very serious problem. The various kinds alternatives about these problem are presented. But, we must consider about replace expense and stability etc. still. So, I propose that use suitable encryption policy by method to solve such problem. I improved some problems of existent PKI structure. Subject of this treatise designs and embody communication component could use easily and simply short message communication or simplicity way encryption communication.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.433-433
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• 2018

한국은 지진에 대한 관심이 낮았으나, 2016년 09월 12일 경상북도 경주에서 가장 큰 규모인 5.8의 지진이 발생하였으며, 강력한 지진이 발생할 수 있다는 경고가 이어지고 있다. 지진과 관련된 정확한 원인 분석과 정량적인 평가가 체계적으로 이루어지지 않고 있어, 규모와 빈도, 위험지역 분석 등 정밀한 평가와 예방대책을 마련해야 한다. 정량적인 지진 발생 분석을 위해 본 연구에서는 지진 발생과 지하수와 같은 수문기상학적인 인자에 의해 영향을 받는다는 가설을 세우고 지하수의 변동 패턴과 지진의 발생 패턴의 유사점을 추정하였다. 이를 위해 지진자료의 통계적인 특성을 분석하였다. 그리고 지질특성이나 지각 판 운동 외에도 수문순환이 영향을 미치는지 확인하기 위해 육지와 바다에서 발생한 지진으로 구분하여 지진발생횟수와 에너지를 분석하였다. 분석결과, 육지와 바다로 구분했을 때 바다에서 더 많은 지진이 일어났다. 또한 Wilcoxon rank-sum test 비모수 추정기법을 통하여 분석한 결과 서로 다른 성질을 보여 따로 분석하였다. 그 결과, 동해와 남해, 서해와 동해가 같은 성질을 보이는 것으로 분석되었다. 그리고 육지는 8월부터 이듬해 7월까지 지진발생의 한 주기를 이룰 가능성을 보였다. 그러나 바다는 육지와 정반대로 2월부터 7월까지 많은 지진 에너지가 발생하고 있으며, 1월까지는 에너지 수준이 상대적으로 낮은 것으로 분석되었다. 이와 같이 지하수가 육지에서 바다까지 유동하는 시간으로 인해 6개월의 시간지연이 발생하는 것으로 판단된다.

• Korean Journal of Agricultural and Forest Meteorology
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• v.22 no.2
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• pp.68-78
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• 2020

Crop models have been used to predict vegetable crop yield, which would have a considerable economic impact on consumers as well as producers. A small number of models have been developed to estimate growth and yield of vegetables due to limited availability of growth observation data in high-quality. In this study, we aimed to analyze the protocols designed for collection of the observation data for major vegetable crops including cabbage, radish, garlic, onion and pepper. We also designed the protocols suitable for development and verification of a vegetable crop growth model. In particular, different measures were proposed to improve the existing protocol used by Statistics Korea (KOSTAT) and Rural Development Administration (RDA), which would enhance reliability of parameter estimation for the crop model. It would be advantageous to select sampling sites in areas where reliable weather observation data can be obtained because crop models quantify the response of crop growth to given weather conditions. It is recommended to choose multiple sampling sites where climate conditions would differ. It is crucial to collect time series data for comparison between observed and simulated crop growth and yield. A crop model can be developed to predict actual yield rather than attainable yield using data for crop damage caused by diseases and pests as well as weather anomalies. A bigdata platform where the observation data are to be shared would facilitate the development of crop models for vegetable crops.

• Journal of the Korean Data and Information Science Society
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• v.21 no.3
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• pp.387-395
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• 2010

It is important to identify the interaction of genes about human disease and characteristic value. Many studies as like logistic analysis, have associated being pursued, but, previous methods did not consider the sub-group of the genotypes. So, QTL interactions and the GMM (genotype matrix mapping) have been developed. In this study, we detect the superior genotype combination to have an impact on economic traits of Korean cattle based on the study over GMM method. Thus, we identified interaction effects of single nucleotide polymorphisms (SNPs) responsible for average daily gain(ADG), marbling score (MS), carcass cold weight (CWT), longissimus muscle dorsiarea (LMA) using GMM method. In addition, we examine significance of the major genotype combination selected by implementing permutation test of the F-measure which was not obtained by Sachiko et al.

• The Korean Journal of Applied Statistics
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• v.21 no.4
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• pp.665-674
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• 2008

Most of existing studies about the small area estimation deal with the estimation of parameters based on cross-sectional data. However, since many official statistics are repeatedly collected at a regular interval of time, for instance, monthly, quarterly, or yearly, we need an alternative model which can handle characteristics of these kinds of data. In this paper, we investigate the generalized estimating equation which can model time-dependency among response variables and is useful to analyze repeated measurement or longitudinal data. We compare with the generalized linear model and the generalized estimating equation through the estimation of unemployment rates of 25 areas in Gyeongsangnam-do and Ulsan. The data consist of the status of employment and some covariates from January to December 2005.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.29 no.1
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• pp.62-66
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• 2017

The interest on the potential earthquake magnitude and the request on the earthquake-resistant design examination for coastal structures are emerged because of the recently occurred magnitude 5.8 earthquake in Gyeoung-Ju, Korea. In this study, the magnitude and its confidence intervals with the return periods are estimated using the KMA earthquake magnitude data (over 3.5 and 4.0 in magnitude) by the non-parametric extreme value analysis. In case of using the "over 4.0" data set, the estimated magnitudes on the 50- and 100-years return periods are 5.81 and 5.94, respectively. Their 90% confidence intervals are estimated to be 5.52-6.11, 5.62-6.29, respectively. Even though the estimated magnitudes have limitations not considering the spatial distribution, it can be used to check the stability of the diverse coastal structures in the perspective of the life design because the potential magnitude and its confidence intervals in Korea are estimated based on the available 38-years data by the extreme value analysis.

• Communications of Mathematical Education
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• v.34 no.2
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• pp.161-177
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• 2020

This study constructed an experiment group and a comparative group, composed of high school students preparing for "Na" type math exam and provided one-to-many tutoring cooperative learning. This study tested the differences between group and between pre- and post-treatment scores by group using non-parametric statistics techniques. Moreover, this study conducted an open-type survey twice and had individual interviews to examine the affective domains of students. The difference in scores between the experimental group and the comparative group was not significant. However, the difference between pre- and post-treatment math scores was only significant in the experiment group among the three groups. Additionally, the student-teacher could reflect on him or her and improve self-efficacy while teaching other ordinary students. The ordinary students were more interested and motivated in the lessons and became more confident. In terms of mathematics competency, we could see that communication, problem-solving, reasoning, and attitude & practice were improved.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.49 no.2
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• pp.83-89
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• 2012

Natural Vegetation cover, which is very important earth resource, has been significantly altered by humans in some manner. Since this has currently resulted in a significant effect on global climate, various studies on vegetation environment including forest have been performed and the results are utilized in policy decision making. Remotely sensed data can detect, identify and map vegetation cover change based on the analysis of spectral characteristics and thus are vigorously utilized for monitoring vegetation resources. Among various vegetation indices extracted from spectral reponses of remotely sensed data, NDVI is the most popular index which provides a measure of how much photosynthetically active vegetation is present in the scene. In this study, for change detection in vegetation cover, a Multi-layer Perceptron Network (MLPN) as a nonparametric approach has been designed and applied to MODIS/Aqua vegetation indices 16-day L3 global 250m SIN Grid(v005) (MYD13Q1) data. The feature vector for change detection is constructed with the direct NDVI diffenrence at a pixel as well as the differences in some subset of NDVI series data. The research covered 5 years (2006-20110) over Korean peninsular.

• Journal of the Korean Data and Information Science Society
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• v.27 no.4
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• pp.993-1000
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• 2016

Semi-supervised learning makes it easy to use an unlabeled data in the supervised learning such as classification. Applying the semi-supervised learning on the regression analysis, we propose two methods for a better regression function estimation. The proposed methods have been assumed different marginal densities of independent variables and different smoothing parameters in unlabeled and labeled data. We shows that the overfitted pilot estimator should be used to achieve the fastest convergence rate and unlabeled data may help to improve the convergence rate with well estimated smoothing parameters. We also find the conditions of smoothing parameters to achieve optimal convergence rate.