• Journal of the Korea Institute of Information and Communication Engineering
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• 제23권3호
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• pp.333-340
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• 2019

A combat system performs a given mission enduring various threats. It is important to analyze the reliability of combat systems in order to increase their ability to perform a given mission. Most of studies considered no threat or on threat and didn't analyze all the dependent relationships among the components. In this paper, we analyze the loss probability of the function of the combat system and use it to analyze the reliability. The proposed method is divided into two layers, A lower layer and a upper layer. In lower layer, the failure probability of each components is derived by using FTA to consider various threats. In the upper layer, The loss probability of function is analyzed using the failure probability of the component derived from lower layer and BBN in order to consider the dependent relationships among the components. Using the proposed method, it is possible to analyze considering various threats and the dependency between components.

• Proceedings of the Korea Water Resources Association Conference
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• 한국수자원학회 2021년도 학술발표회
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• pp.79-79
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• 2021

기상학적 측면에서 강수 부족으로 인한 수생태환경(하천), 호소환경(저수지) 및 유역환경(중권역)으로 미치는 환경학적 가뭄의 영향을 평가하기 위한 시도는 매우 중요하다. 만약 동일한 규모의 강수부족 현상이 발생할지라도, 환경적 측면에서의 수질 및 수생태에 미치는 영향이 매우 큰 유역이 있고, 반면 어느 정도의 복원력을 유지할 수 있는 유역이 있을 것이다. 즉, 서로 다른 유역환경에 따라 가뭄으로 인한 환경적 영향은 달라질 가능성이 크며, 이처럼 환경적 가뭄에 취약한 지역을 위해서는 지속적인 환경가뭄 모니터링이 중요하다. 환경적 측면에서 가뭄의 영향을 평가하기 위해서는 다양한 수질 관련 항목을 연계한 환경가뭄 감시가 중요하며, 이와 더불어 가뭄과 관련한 다양한 이해관계자 간의 효율적인 의사결정 도구가 필요하다. 따라서 본 연구에서는 다양한 시나리오 정보를 제공할 수 있는 베이지안 네트워크 모형을 적용하여 환경가뭄 민감도 평가 방안을 제시하고자 한다. 본 모형에서는 수질 문제가 가장 심하게 대두되고 있는 낙동강 유역을 대상으로, 기상학적 가뭄에 의한 수생태 및 환경 관련 변수들(BOD, T-P, TOC)의 복잡한 상호의존성을 파악할 수 있는 베이지안 네트워크 모형을 활용하였다. 또한, 기상학적 가뭄에 의한 상류와 하류 간의 환경적 영향을 연계하여 해석하기 위한 모형을 구축하였다. 그 결과, 기상학적 가뭄으로 인한 환경적 민감도가 크게 나타나는 중권역(예: 임하댐유역)과 이와 반대인 중권역(예: 병성천유역)의 구분이 가능하였다. 또한, 상류에서 발생한 심한 기상학적 가뭄이 하류 지역 내 환경적인 영향을 지속할 가능성이 있음을 확인되었다. 따라서 본 연구에서 제안한 방법은 환경적 가뭄의 취약지역을 우선 선정하고, 나아가 상-하류 간의 환경적 가뭄을 감시하는 데 있어 활용도가 있을 것으로 기대된다.

• Transactions of the Korean Society of Mechanical Engineers B
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• 제38권7호
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• pp.647-656
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• 2014

To supplement the ISO-GUM method for the evaluation of measurement uncertainty, a simulation program using the Monte Carlo method (MCM) was developed, and the MCM and GUM methods were compared. The results are as follows: (1) Even under a non-normal probability distribution of the measurand, MCM provides an accurate coverage interval; (2) Even if a probability distribution that emerged from combining a few non-normal distributions looks as normal, there are cases in which the actual distribution is not normal and the non-normality can be determined by the probability distribution of the combined variance; and (3) If type-A standard uncertainties are involved in the evaluation of measurement uncertainty, GUM generally offers an under-valued coverage interval. However, this problem can be solved by the Bayesian evaluation of type-A standard uncertainty. In this case, the effective degree of freedom for the combined variance is not required in the evaluation of expanded uncertainty, and the appropriate coverage factor for 95% level of confidence was determined to be 1.96.

• Korean Journal of Plant Taxonomy
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• 제39권1호
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• pp.35-41
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• 2009

Astilbe (Saxifragaceae) is a genus well known for its disjunctive distribution in Asia and eastern North America. In this study, we reconstructed a molecular phylogeny of the genus using the sequences of ITS regions of nuclear ribosomal DNA. A total of 17 species representing major lineage of Astilbe and closely related taxa were included in the phylogenetic analyses. We obtained a Bayesian phylogenetic tree in which Saxifragopsis was positioned as a sister group to Astilbe. The Japanese endemic species, A.platyphylla was the most basal lineage within the genus. This species is well known for its distinct morphological features such as unisexual flowers, apetaly, and calyx with 7-11 lobes. Two species, A. biternata, a New World representative of the genus, and A. rivularis widely distributed in S. Asia, branched off early in the evolution of Astilbe. The remaining species formed a strongly supported core clade, which diverged into two robust geographical lineages: the first ("Japonica" clade) of species distributed in Japan, Taiwan, and Philippines and the other ("Rubra" clade), of taxa in China and Korea. The ITS phylogeny indicates that the Bering land bridges were the major route for the origin and dispersal of A. biternata. The two Taiwanese taxa and A. philippinensis were found to derive from the Japanese member, as the genus advanced southwards. The ITS phylogeny suggests that apetaly originated independently at least two times within the genus. Our results do not support Engler's classification system of the genus based on the leaf type (simple vs. compound), but reaffirm Hara's taxonomic idea which primarily considered the features of calyx.

• Geotechnical Engineering
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• 제11권1호
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• pp.9-22
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• 1995

The purpose of this study is to propose safety factors of pile bearing capacity based on the reliability analysis. Each prediction method involves various degrees of uncertainties. To account for these uncertainties in a systematic way, the ratios of the measured bearing capacity from pile load tests to the predicted bearing capacity are represented in the form of a probability density function. The safety factor for each design method is obtained so that the probability of pile foundation failure is less than 10-3. The Bayesian theorem is applied in a way that the distribution using static formulae is assumed to be the A-prior and the distribution using dynamic formulae or wave equation based methods is assumed to be the likelihood, and these two are combined to obtain the posterior which has the reduced uncertainty. The results of this study show that static formulae of the pile bearing capacity using the 5.p.7. N-value as well as dynamic formulae are highly unreliable and have to have the safety factor more than 7.4 : the wave equation analysis using PDA(Pile Driving Analyzer) system the most reliable with the safety factor close to 2.7. The safety factor could be reduced certain amount by adoption the Bayes methodology in pile design.

• Composites Research
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• 제35권5호
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• pp.317-321
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• 2022

In this study, the PIC design method with machine learning that automatically assigning different stacking sequences according to loading types was applied bumper beam. The input value and labels of the training data for applying machine learning were defined as coordinates and loading types of reference elements that are part of the total elements, respectively. In order to compare the 2D and 3D implementation method, which are methods of representing coordinate value, training data were generated, and machine learning models were trained with each method. The 2D implementation method is divided FE model into each face and generating learning data and training machine learning models accordingly. The 3D implementation method is training one machine learning model by generating training data from the entire finite element model. The hyperparameter were tuned to optimal values through the Bayesian algorithm, and the k-NN classification method showed the highest prediction rate and AUC-ROC among the tuned models. The 3D implementation method revealed higher performance than the 2D implementation method. The loading type data predicted through the machine learning model were mapped to the finite element model and comparatively verified through FE analysis. It was found that 3D implementation PIC bumper beam was superior to 2D implementation and uni-stacking sequence composite bumper.

• The Korean Journal of Applied Statistics
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• 제37권3호
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• pp.339-353
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• 2024

In cases where the response variable in proportional data is confined to a limited interval, a regression model based on the assumption of normality can yield inaccurate results due to issues such as asymmetry and heteroscedasticity. In such cases, the beta regression model can be considered as an alternative. This model reparametrizes the beta distribution in terms of mean and precision parameters, assuming that the response variable follows a beta distribution. This allows for easy consideration of heteroscedasticity in the data. In this paper, we therefore aim to analyze proportional data using the beta regression model in two empirical analyses. Specifically, we investigate the relationship between smoking rates and coffee consumption using data from the 6th National Health Survey, and examine the association between regional characteristics in the U.S. and cumulative mortality rates based on COVID-19 data. In each analysis, we apply the ordinary least squares regression model, the beta regression model, and the extended beta regression model to analyze the data and interpret the results with the selected optimal model. The results demonstrate the appropriateness of applying the beta regression model and its extended version in proportional data.

• Journal of Korea Water Resources Association
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• 제53권2호
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• pp.107-119
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• 2020

This study analyzed past drought characteristics based on the observed rainfall data and performed a long-term outlook for future extreme droughts using Representative Concentration Pathways 8.5 (RCP 8.5) climate change scenarios. Standardized Precipitation Index (SPI) used duration of 1, 3, 6, 9 and 12 months, a meteorological drought index, was applied for quantitative drought analysis. A single long-term time series was constructed by combining daily rainfall observation data and RCP scenario. The constructed data was used as SPI input factors for each different duration. For the analysis of meteorological drought observed relatively long-term since 1954 in Korea, 12 rainfall stations were selected and applied 10 general circulation models (GCM) at the same point. In order to analyze drought characteristics according to climate change, trend analysis and clustering were performed. For non-stationary frequency analysis using sampling technique, we adopted the technique DEMC that combines Bayesian-based differential evolution ("DE") and Markov chain Monte Carlo ("MCMC"). A non-stationary drought frequency analysis was used to derive Severity-Duration-Frequency (SDF) curves for the 12 locations. A quantitative outlook for future droughts was carried out by deriving SDF curves with long-term hydrologic data assuming non-stationarity, and by quantitatively identifying potential drought risks. As a result of performing cluster analysis to identify the spatial characteristics, it was analyzed that there is a high risk of drought in the future in Jeonju, Gwangju, Yeosun, Mokpo, and Chupyeongryeong except Jeju corresponding to Zone 1-2, 2, and 3-2. They could be efficiently utilized in future drought management policies.

• Journal of the Korean Recycled Construction Resources Institute
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• 제1권1호
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• pp.8-16
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• 2013

Currently, global warming has advanced by the usage of fossil fuels such as coal and petroleum. and the atmosphere temperature in the world of 100 years(1906~2005) has been risen $0.74^{\circ}C{\pm}0.18^{\circ}C$, IPCC announced that the global warming effect of last decade was nearly doubled compared to the changes($0.07^{\circ}C{\pm}0.02^{\circ}C$/10year) in the past 100 years. Moreover, due to the global warming, heat wave, heavy snow, heavy rain, super typhoon, were caused and are increasing to happen in the world continuously causing damages and destruction of social infrastructures, where concrete structures are suffering deterioration by long-term extreme climate changes. to solve these problems, the new construction technology and codes are necessary. In this study, to solve these problems, experiments on a variety of cases considering the temperature and humidity, the main factors of climate factors, were performed, and the cases are decided by temperature and humidity. The specimens were tested in compressive strength test and split tensile test by the curing age(3,7,28 days) morever, performance based design(PBD) method was applied by using the satisfaction curve developed from the experiment date. PBD is the design method that gathers the current experimental analysis and past experimental analysis and develops the material properties required for the structure, and carries out the design of concrete mix, and it is recently studied actively worldwide. Also, it is the ultimate goal of PBD to design and perform on structures have sufficient performance during usage and to provide the problem solving for various situations, Also, it can achieve maximum effect in terms of functionality and economy.

• Korean Journal of Ecology and Environment
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• 제49권4호
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• pp.279-288
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• 2016

Stable Isotope Analysis(SIA) of carbon and nitrogen is useful tool for the understanding functional roles of target organisms in biological interactions in the food web. Recently, mixing model based on SIA is frequently used to determine which of the potential food sources predominantly assimilated by consumers, however, application of model is often limited and difficult for non-expert users of software. In the present study, we suggest easy manual of R software and package SIAR with example data regarding selective feeding of crustaceans dominated freshwater zooplankton community. We collected SIA data from the experimental mesocosms set up at the littoral area of eutrophic Chodae Reservoir, and analyzed the dominant crustacean species main food sources among small sized particulate organic matters (POM, <$50{\mu}m$), large sized POM (>$50{\mu}m$), and attached POM using mixing model. From the results obtained by SIAR model, Daphnia galeata and Ostracoda mainly consumed small sized POM while Simocephalus vetulus consumed both small and large sized POM simultaneously. Copepods collected from the reservoir showed no preferences on various food items, but in the mesocosm tanks, main food sources for the copepods was attached POM rather than planktonic preys including rotifers. The results have suggested that their roles as grazers in food web of eutrophicated reservoirs are different, and S. vetulus is more efficient grazer on wide range of food items such as large colony of phytoplankton and cyanobacteria during water bloom period.