• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.9-9
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• 2018

추계학적 강우생성모형 중 포아송 클러스터(Poisson Cluster) 모형은 단일지점에 대하여 시간강우량의 관측연한 문제점을 해결하기 위한 강우모형으로 강우 단계별 계층적 구조를 이해하는데 유용한 모형이다. 특히 강우 특성을 계절, 지역 등과 같이 비교하는 기준에 따라 5~6개의 비교적 적은 매개변수들로 모의 강우시계열을 생성할 수 있다는 점에서 장기간 강우분석에 필요한 관측연한 문제를 보완할 수 있다. 그러나 매개변수 최적해가 수렴되지 않는 사례가 많고, 매개변수들이 강우의 물리적 특성을 반영하는 것에 비해 내포된 불확실성에 관한 연구는 미흡하다. 본 연구에서는 포아송 클러스터 강우생성모형 중 Neyman-Scott Rectangular Pulse(NSRP) 모형을 Bayesian 모형과 연계한 Bayesian NSRP 모형을 개발하여 매개변수간 물리적 상관성을 고려한 최적화 기법을 개발하였다. Bayesian 모형은 물리적 범위가 다른 매개변수간의 결합확률분포를 산정하여 사후분포(posterior)를 추정하므로 매개변수 최적화와 불확실성 정량화 문제를 동시에 해결할 수 있다. 최종적으로 Bayesian NSRP 모형에 기후변화 시나리오의 통계적 특성을 고려한 시간단위 강우시계열 생성 모의 기법의 활용 가능성을 평가하고자 한다.

• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.150-150
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• 2017

기후변화로 인하여 극한 홍수와 극한 가뭄 발생이 증가할 것으로 전망하고 있어 이에 대한 위험이 대두되고 있는 실정이다. 홍수 및 가뭄 수문시계열의 빈도해석시에 일반적으로 활용되는 정상성 빈도해석기법은 수문자료의 정상성을 기반으로 한 빈도해석이 대부분이기 때문에 기후변화 및 수문자료의 비정상성을 반영한 새로운 빈도해석 기법이 요구되고 있는 상황이다. 본 연구에서는 5개의 대표 관측지점(서울, 포항, 추풍령, 여수, 광주)를 선별하고 1976년부터 2015년까지 일강우자료를 활용하여 기상학적 가뭄지수인 SPI(Standardized Precipitation Index)를 산정하였다. 산정한 SPI의 경향성을 Mann-Kendall 분석을 하였으며, 정상성 및 비정상성 빈도해석을 위하여 최적확률분포로 선정된 GEV 분포 적용하였다. 본 연구에서는 가뭄빈도해석을 위하여 SPI를 입력자료로 활용하였으며, 산정된 SPI의 비정상성을 반영한 비정상성 빈도해석의 경우 Bayesian 모형을 기반으로 한 MCMC(Markov Chain Monte Carlo) 모의를 이용하여 극치분포의 사후분포 매개변수를 추정하였다. 추정 값을 바탕으로 하여 가뭄의 관측소별 빈도해석을 실시하였고 재현기간별-지속기간별 가뭄심도를 추정하여 관측소별 가뭄심도-지속기간-빈도(SDF,Severity-Duration-Frequency) 곡선을 유도하였다. 본 연구를 통하여 정상성과 비정상성 빈도해석 결과의 비교연구를 수행하였으며 기후변화에 따른 비정상 시계열로 구성된 가뭄빈도해석에 매우 유용하게 적용될 수 있을 것으로 나타났다.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.214-214
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• 2020

전 세계적으로 기후변화로 인해 재난이 빈번히 대형화되고 있으며, 하수처리장과 같은 대형시설물도 자연재해의 위험성이 커지고 침수피해를 받을 확률이 높아지고 있다. 실제로 최근까지 청주 산단 폐수종말처리장, 평택 장당 하수처리장, 광주/곤지암 하수처리장 등이 폭우로 침수돼 가동이 중단되는 사태가 벌어졌다. 하수처리장이 침수될 경우 시설 자체의 1차적 피해도 문제가 되지만, 처리되지 못한 오염물질이 하천으로 흘러 들어가는 2차 피해가 더더욱 문제가 될 수 있다. 본 연구에서는 문제가 발생하기 전에 집중호우 시 각 시설의 취약성을 사전 평가하여 침수 피해를 대비하고, 평가 내용에 따라 침수 피해 사전·사후 대응을 위한 체계, 방법론을 구축, 제시함으로써 침수피해를 최소화하고자 한다. 침수피해의 취약성을 평가하기 위한 기준으로는 시설물의 침수방지를 위한 건물 턱의 높이, 하수처리시설 인근 제방의 유무, 구조적 홍수방어시설 유무, 침수 발생 시 가장 취약한 전력 설비 시설의 위치 및 피해 대책 등 실질적으로 측정 가능한 구조적 요소를 고려하며, 재난대응 매뉴얼 정비, 사전 재난훈련 수행 등 비 구조적인 측면으로도 접근하여 취약성 평가 지표를 도출하고자 한다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2023.05a
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• pp.146-147
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• 2023

해양사고는 도로교통과 달리 지속적으로 증가하고 있으며, 인명피해가 주로 발생하는 주요 사고의 치사율은 도로교통의 11.7배 이상이다. 해양사고는 외부 환경에 따라 사고 위치가 변하고 즉각적인 조치가 어려워 타 교통에 비해 대형 사고로 이어질 가능성이 매우 크다. 그러나 여전히 사고가 발생하고 난 후 대응하는 등 사후적 관리 단계에 무르고 있어 사고의 주요 요인을 사전에 식별·관리하는 선제적 관리단계로의 전환 필요성이 대두되고 있다. 따라서 본 연구에서는 해양사고 발생 지점 밀도 기반의 가변 공간 군집체계를 반영한 해양사고 예측모델을 개발하였다. 반복적인 공간 가산분석을 통해 밀도가 높을수록 작은 규모의 격자 체계를 가질 수 있도록 상세한 공간 군집체계를 구성하였으며, 단순 사고 위험도 예측뿐만 아닌 사고 인과관계를 설명할 수 있는 BN(Bayesian Network) 기반의 모형을 사용하여 해양사고 위험예측 모델을 개발하였다. 또한, Cost-of-Omission을 통해 해양사고 예측확률의 변화와 각 변수들의 영향력을 확인하였으며, 월별 해양사고예측 결과를 GIS를 활용하여 2D/3D 기반으로 시각화하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.8
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• pp.3748-3759
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• 2013

The purpose of this study was to examine the classification accuracies of ML, MAP, and EAP methods under DINA model. For this purpose, this study examined the classification accuracies of the classification methods under the various conditions: the number of attributes, the ability distribution of examinees, and test length. To accomplish this purpose, this study used a simulation method. For the simulation study, data was simulated under the various simulation conditions including the number of attributes (K= 5, 7), the ability distribution of examinees (high, middle, low), and test length (J= 15, 30, 45). Additionally, the percent of agreements between true skill patterns(true ${\alpha}$) and skill patterns estimated by the ML, MAP, and EAP methods were calculated. The summary of the main results of this study is as follows: First, When the number of attributes was 5 and 7, the EAP method showed relatively higher average in the percent of exact agreement than the ML and MAP methods. Second, under the same conditions, as the number of attributes increased, the average percent of exact agreement decreased in ML, MAP, and EAP methods. Third, when the prior distribution of examinees ability was different from low to high under the conditions of the same test length, the EAP method showed relatively higher average in the percent of exact agreement than those of the ML and MAP methods. Fourth, the average percent of exact agreement increased in all methods, ML, MAP, and EAP when the test length increased from 15 to 30 and 45 under the conditions of the same the ability distribution of examinees.

• Journal of the Korea Convergence Society
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• v.9 no.9
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• pp.229-243
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• 2018

The purpose of this study is to develop a personality education program that can enhance the virtues of elementary school students, self-esteem, Consideration communication, self-control, honesty courage by using coaching methodologically, To improve the personality virtue. The subjects of this study were 31 students from 4th grade of U elementary school in S Gu, Seoul. The experimental group was divided into 16 sessions, weekly from March 5, 2018 to June 30, 2018, 1 hour (40 minutes). The program consisted of items such as self-esteem, Consideration communication, self-control, honesty courage among the personality virtues of KEDI personality test, Each activity used a tough coaching model developed by combining the GROW model with the Empowering model and considering the developmental level of elementary school students. As a result, all four virtues of personality were significantly improved, model with the Empowering model and considering the developmental level of elementary school students. We compared pre and post test result with paired t-test. As a results, the experimental group showed improvement in all four virtues of personality at 0.05 significance level, whereas the control group did not. This suggests that the program can be usefully used as a tool to improve four virtues of personality of elementary school students. For further research, we expect that the program would be integrated with state-of-art technology such as online program or CBI(Computer-Based Instruction).

• Journal of the Korean Data and Information Science Society
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• v.28 no.6
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• pp.1337-1348
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• 2017

In this paper, we develop the high-risk drinking predictive model in Korea using the cross-sectional data from Korea Community Health Survey (2014). We perform the logistic regression analysis, the decision tree analysis, and the neural network analysis using the data mining technique. The results of logistic regression analysis showed that men in their forties had a high risk and the risk of office workers and sales workers were high. Especially, current smokers had higher risk of high-risk drinking. Neural network analysis and logistic regression were the most significant in terms of AUROC (area under a receiver operation characteristic curve) among the three models. The high-risk drinking predictive model developed in this study and the selection method of the high-risk intensive drinking group can be the basis for providing more effective health care services such as hazardous drinking prevention education, and improvement of drinking program.

• Journal of the Korean Association of Geographic Information Studies
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• v.26 no.1
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• pp.132-144
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• 2023

Recently, the frequency and intensity of heat waves due to the increase in climate change temperature are increasing. Therefore, this study tried to compare the evaluation process and evaluation results of the heat wave disaster evaluation, which is the government's analysis of the heat wave disaster vulnerability and the risk evaluation method recently emphasized by the IPCC. The analysis of climate change disaster vulnerability is evaluated based on manuals and guidelines prepared by the government. Risk evaluation can be evaluated as the product of the possibility of a disaster and its impact, and it is evaluated using the Markov chain Monte Carlo simulation based on Bayesian estimation method, which uses prior information to infer posterior probability. As a result of the analysis, the two evaluation results for Busan Metropolitan City differed slightly in the spatial distribution of areas vulnerable to heat waves. In order to properly evaluate disaster vulnerable areas due to climate change, the process and results of climate change disaster vulnerability analysis and risk assessment must be reviewed, and consider each methodology and countermeasures must be prepared.

• Journal of Animal Science and Technology
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• v.44 no.2
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• pp.151-164
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• 2002

Genetic variance and covariance components of the linear traits and the ordered categorical traits, that are usually observed as dichotomous or polychotomous outcomes, were simultaneously estimated in a multivariate threshold animal model with concepts of arbitrary underlying liability scales with Bayesian inference via Gibbs sampling algorithms. A multivariate threshold animal model in this study can be allowed in any combination of missing traits with assuming correlation among the traits considered. Gibbs sampling algorithms as a hierarchical Bayesian inference were used to get reliable point estimates to which marginal posterior means of parameters were assumed. Main point of this study is that the underlying values for the observations on the categorical traits sampled at previous round of iteration and the observations on the continuous traits can be considered to sample the underlying values for categorical data and continuous data with missing at current cycle (see appendix). This study also showed that the underlying variables for missing categorical data should be generated with taking into account for the correlated traits to satisfy the fully conditional posterior distributions of parameters although some of papers (Wang et al., 1997; VanTassell et al., 1998) presented that only the residual effects of missing traits were generated in same situation. In present study, Gibbs samplers for making the fully Bayesian inferences for unknown parameters of interests are played rolls with methodologies to enable the any combinations of the linear and categorical traits with missing observations. Moreover, two kinds of constraints to guarantee identifiability for the arbitrary underlying variables are shown with keeping the fully conditional posterior distributions of those parameters. Numerical example for a threshold animal model included the maternal and permanent environmental effects on a multiple ordered categorical trait as calving ease, a binary trait as non-return rate, and the other normally distributed trait, birth weight, is provided with simulation study.

• Therapeutic Science for Rehabilitation
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• v.3 no.2
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• pp.5-48
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• 2014

Introduction : One of the important domains in OT is performance skills which include sensory perceptual skills, motor and praxis skills, emotional regulation skills, cognitive skills, and communication/social skills. All of these skills are support ed by integrated neurological processes. Body : Stereology robust tool when employed to investigate morphological changes in neurons, cortex area, and specific parts of brain involved in special brain function. Stereology is an interdisciplinary field focused or analyzing biological tissue with the three-dimensional interpretation of planer sections by using estimating method and mathematically unbiased sampling. With the unbiased stereological method based on probability theory, researchers can estimate morphological and anatomical changes in biological reference areas accurately and efficiently. Changes in anatomical and cytoarchitectural parameters, such as volume, number, and length, affect specific brain function related to the brain area. Occupational therapists provide treatment to improve functions for participation of occupation in neurological disorder. The functional improvements in neurological disorder reflect neurobiological changes because functional difficulties, such as motor cognitive disorder, are due to neurological disturbances. Thus, combination of two kinds of evidence, neurological changes and functional improvement, provide fundamental evidence for OT intervention in neurological disorder. Even though most of stereological studies are in animal model and in postmortem human because of practical and ethical issues, stereology provides fundamental knowledge to support OT theory and practice. Conclusion : Therefore, stereology informs translation from neuroscience to OT based on structure-function relationship in performance skills and experience-dependent neural plasticity.