• 한국지능시스템학회논문지
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• 제17권3호
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• pp.316-321
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• 2007

본 연구에서는 베이지안 망 구조 학습에서, 학습 데이터의 특정 부분집합이 학습된 망의 각 연결 구조(edge)의 형성에 기여하는 정도를 정량화하는 방법을 제안한다. 생물학 정보의 분석 등에 베이지안 망 학습을 이용하는 경우, 제안된 방법은 망의 각 연결 구조의 형성에 특정 군집 데이터가 기여하는 정도의 정량화가 가능하다. 제안된 방법의 유효성을 보이기 위해, 벤치마크 베이지안 망을 이용하여 제안된 방법이 망 연결 구조에 대한 데이터 군집별 기여도를 효과적으로 정량화 할 수 있음을 보인다.

• International Journal of Computer Science & Network Security
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• 제22권11호
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• pp.184-188
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• 2022

The article considers the improved method and model of automated air situation assessment using a decision support system based on fuzzy networks of target installations. The advanced method of automated assessment of the air situation using the decision support system is based on the methodology of reflexive control of the first rank. With this approach, the process of assessing the air situation in the framework of the formulated task can be reduced to determining the purpose, probabilistic nature of actions and capabilities of the air target. The use of a homogeneous functional network for the formal presentation of air situation assessment processes will formally describe the process of determining classes of events during air situation assessment and the process of determining quantitative and qualitative characteristics of recognized air situation situations. To formalize the patterns of manifestation of the values of quantitative and symbolic information, it is proposed to use the mathematical apparatus of fuzzy sets.

• 한국축산식품학회지
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• 제39권4호
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• pp.565-575
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• 2019

This study evaluated Campylobacter jejuni risk in ground meat products. The C. jejuni prevalence in ground meat products was investigated. To develop the predictive model, survival data of C. jejuni were collected at $4^{\circ}C-30^{\circ}C$ during storage, and the data were fitted using the Weibull model. In addition, the storage temperature and time of ground meat products were investigated during distribution. The consumption amount and frequency of ground meat products were investigated by interviewing 1,500 adults. The prevalence, temperature, time, and consumption data were analyzed by @RISK to generate probabilistic distributions. In 224 samples of ground meat products, there were no C. jejuni-contaminated samples. A scenario with a series of probabilistic distributions, a predictive model and a dose-response model was prepared to calculate the probability of illness, and it showed that the probability of foodborne illness caused by C. jejuni per person per day from ground meat products was $5.68{\times}10^{-10}$, which can be considered low risk.

• Ocean Systems Engineering
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• 제2권1호
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• pp.1-16
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• 2012

Offshore wind turbines are complex structural and mechanical systems located in a highly demanding environment. This paper proposes a multi-level system approach for studying the structural behavior of the support structure of an offshore wind turbine. In accordance with this approach, a proper numerical modeling requires the adoption of a suitable technique in order to organize the qualitative and quantitative assessment in various sub-problems, which can be solved by means of sub-models at different levels of detail, both for the structural behavior and for the simulation of loads. Consequently, in a first place, the effects on the structural response induced by the uncertainty of the parameters used to describe the environmental actions and the finite element model of the structure are inquired. After that, a meso-level FEM model of the blade is adopted in order to obtain the detailed load stress on the blade/hub connection.

• 한국철도학회:학술대회논문집
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• 한국철도학회 2007년도 춘계학술대회 논문집
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• pp.614-619
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• 2007

The purpose of this study is to develop a LCC analysis model for selecting railroad bridge type as both of quantitative and qualitative factors to increase the effectiveness in the selecting design alternatives and is to select the optimum alternatives through a case study. This LCC analysis model adapts deterministic and probabilistic approach for increasing the reliability and includes AHP analysis considering the qualitative factors.

• 한국수자원학회논문집
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• 제43권7호
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• pp.645-655
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• 2010

본 논문에서는 각각의 시점에서의 변화확률을 산정하여 변화시점을 추정하는 Barry and Hartigan (BH)의 베이지안 변화시점 추정방법(Bayesian changing points estimation method)을 이용하여 측우기 관측자료계열(CWK)과 근대우량계 관측자료계열(MRG)간의 변화에 대한 상대확률적 절점의 발생여부를 분석하였다. 어떠한 자연 현상도 완전히 동일하게 재현되지 않기때문에 시간적인 순서를 고려하지못하는 통계적 방법은 구체적인발생시간을 예측하기 어렵다는 점에서 자료의 변화량 파악은 가능하나 변화시점을 명확히 추정하는데 한계가 있다. 이러한 배경에서, 본 논문에서는 각 시점에서의 변화확률을 산정하여 변화시점을 추정하는 BH 베이지안 방법을 적용하여 CWK와 MRG의 각 강우특성별로 상대확률적인 변화시점 분석을 통하여 CWK와 MRG 간의 동질성 분석을 실시하였다. 분석 결과, CWK의 정성적인(본질적인) 통계적 특성은 MRG와 큰 차이가 없는 것으로 나타났다. 다만, 관측정밀도의 한계로 인한 정량적인 차이가 존재하는 것으로 분석되었다.

• 한국멀티미디어학회논문지
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• 제20권2호
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• pp.205-215
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• 2017

The brain magnetic resonance images (MRI) is an important imaging biomarker in Alzheimer's disease (AD) as the cerebral atrophy has been shown to strongly associate with cognitive symptoms. The decrease of volume estimates in different structures of the medial temporal lobe related to memory correlates with the decline of cognitive functions in neurodegenerative diseases. During the past decades several methods have been developed for quantifying the disease related atrophy of hippocampus from MRI. Special effort has been dedicated to separate AD and mild cognitive impairment (MCI) related modifications from normal aging for the purpose of early detection and prediction. We trained a multi-class support vector machine (SVM) with probabilistic outputs on a sample (n = 58) of 20 normal controls (NC), 19 individuals with MCI, and 19 individuals with AD. The model was then applied to the cross-validation of same data set which no labels were known and the predictions. This study presents data on the association between MRI quantitative parameters of hippocampus and its quantitative structural changes examination use on the classification of the diseases.

• 터널과지하공간
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• 제24권2호
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• pp.155-165
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• 2014

다중 열저장공동은 열에너지의 대규모 저장, 열적 성능 향상을 위한 높은 종횡비의 저장소 설계에 활용될 수 있다. 또한 긴 터널형의 단일공동이 열생산 및 주입을 위한 지상설비와의 연결에 적합하지 않은 경우, 길이를 줄인 다중 암반공동의 활용을 고려할 필요가 있다. 다중 열저장공동 활용시 공동간의 이격거리는 저장공간 설계시 고려해야 하는 주요 설계인자 중 하나이며, 정량적인 안정성 평가기준을 토대로 적정 이격거리가 산정되어야 한다. 본 논문에서는 대규모 열에너지 저장을 위한 다중 암반공동 계획시 공동간 이격거리를 결정하기 위한 수치 해석적 접근법에 대해 기술하였다. 다중 암반공동의 안정성 평가를 위해 기존의 결정론적 접근법과 달리 확률밀도에 의해 입력 매개변수의 불확실성을 정량적으로 고려할 수 있는 확률론적 해석기법을 이용하였으며, 집단열수 공급을 위한 다중 암반공동의 개념모델 설계에 적용하였다. 본 적용을 통해 확률론적 해석기법이 다중 암반공동의 이격거리 산정을 위한 의사결정 도구로서 유용하게 활용될 수 있음을 확인할 수 있었으며, 결정론적 해석결과와의 비교 분석으로부터 결정론적 접근법 적용시 안정성 평가기준을 신중히 설정할 필요가 있는 것으로 검토되었다.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2003년도 봄 학술발표회 논문집
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• pp.123-130
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• 2003

The estimation of key soil properties and subsequent quantitative assessment of the associated uncertainties has always been an important issue in geotechnical engineering. It is well recognized that soil properties vary spatially as a result of depositional and post-depositional processes. The stochastic nature of spatially varying soil properties can be treated as a random field. A practical statistical approach that can be used to systematically model various sources of uncertainty is presented in the context of reliability analysis of slope stability Newly developed expressions for probabilistic characterization of soil properties incorporate sampling and measurement errors, as well as spatial variability and its reduced variance due to spatial averaging. Reliability analyses of the probability of slope failure using the different statistical representations of soil properties show that the incorporation of spatial correlation and conditional simulation leads to significantly lower probability of failure than obtained using simple random variable approach.

• Genomics & Informatics
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• 제2권1호
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• pp.7-18
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• 2004

Integrated genomics refers to the use of large-scale, systematically collected data from various sources to address biological and biomedical problems. A critical ingredient to a successful research program in integrated genomics is the establishment of an effective computational infrastructure. In this review, we suggest that the computational infrastructure challenges include developing tools for heterogeneous data organization and access, innovating techniques for combining the results of different analyses, and establishing a theoretical framework for integrating biological and quantitative models. For each of the three areas - data integration, analyses integration, and model integration - we review some of the current progress and suggest new topics of research. We argue that the primary computational challenges lie in developing sound theoretical foundations for understanding the genome rather than simply the development of algorithms and programs.