• The Korean Journal of Applied Statistics
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• v.33 no.1
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• pp.25-46
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• 2020

This paper presents ordinal probit semiparametric regression models using Bayesian Spectral Analysis Regression (BSAR) method. Ordinal probit regression is a way of modeling ordinal responses - usually more than two categories - by connecting the probability of falling into each category explained by a combination of available covariates using a probit (an inverse function of normal cumulative distribution function) link. The Bayesian probit model facilitates posterior sampling by bringing a latent variable following normal distribution, therefore, the responses are categorized by the cut-off points according to values of latent variables. In this paper, we extend the latent variable approach to a semiparametric model for the Bayesian ordinal probit regression with nonparametric functions using a spectral representation of Gaussian processes based BSAR method. The latent variable is decomposed into a parametric component and a nonparametric component with or without a shape constraint for modeling ordinal responses and predicting outcomes more flexibly. We illustrate the proposed methods with simulation studies in comparison with existing methods and real data analysis applied to a Korean National Health and Nutrition Examination Survey (KNHANES) 2016 for investigating nonparametric relationship between smoking behavior and coffee intake.

• Proceedings of the Korean Information Science Society Conference
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• 2007.06c
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• pp.494-499
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• 2007

본 논문은 객체로부터 특징 벡터를 추출하고 각 객체의 행동 양식을 분석함으로써 객체의 현재 이벤트를 인식하고 확률 모델을 기반으로 한 긴급한 상황에서의 시나리오를 해석할 수 있는 방법을 제안한다. 기존의 연구에서는 시나리오 해석을 위한 이벤트 인식 방법을 사용하였기 때문에 적용되는 범위가 한정되어 있었다. 본 논문에서는 시나리오를 정의하고 인식된 객체의 이벤트를 바탕으로 미리 정의된 시나리오에 가장 근접하는 상황이 발생하는 것을 자동으로 해석할 수 있도록 한다. 이벤트 규칙, 이벤트 인식, 그리고 이벤트를 바탕으로 하는 긴급 상황 시나리오가 실내 또는 실외 환경에서 객체 추적만을 통해 얻을 수 없는 의미론적 정보를 제안된 방법을 통해 획득할 수 있다.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.614-615
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• 2018

본 연구는 심층학습 기법을 활용하여 양극 데이터에 대해 학습된 모델로부터 예측된 결과를 바탕으로 언어 장애 여부를 판단하고, 이를 바탕으로 효율적인 언어 치료를 수행할 수 있는 방법론을 제시한다. 발화자의 개별 발화에 대해 데이터화를 하여 합성곱 신경망 모델(CNN)을 학습한다. 이를 이용하여 발화자의 연령 집단을 예측하고 결과를 분석하여 발화자의 언어 연령 및 장애 여부를 판단을 할 수 있다.

• Annual Conference on Human and Language Technology
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• 2006.10e
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• pp.25-31
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• 2006

본 논문에서는 띄어쓰기 오류와 철자 오류를 동시에 교정 가능한 전처리기를 제안한다. 제시된 알고리즘은 기존의 전처리기 알고리즘이 각 오류를 따로 해결하는 데에서 오는 한계를 극복하고, 기존의 noisy-channel model을 확장하여 대화체의 띄어쓰기 오류와 철자오류를 동시에 효과적으로 교정할 수 있다. N-gram과 자소변환확률 등의 통계적 방법과 어절변환패턴 사전을 이용하여 최대한 사전을 적게 이용하면서도 효과적으로 교정 후보들을 생성할 수 있다. 실험을 통해 현재 단계에서는 만족할 만한 성능을 얻지는 못하였지만 오류 분석을 통하여 이와 같은 방법론이 실제로 효용성이 있음을 알 수 있었고 앞으로 더 많은 개선을 통해 일상적인 대화체 문장에 대해서 효과적인 전처리기로서 기능할 수 있을 것으로 기대 된다.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.19 no.40
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• pp.69-79
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• 1996

하드웨어 설계 과정에서 신뢰성 담당자들에게 당면한 문제는 요구된 임무에 필요한 기능적 요구사항의 달성 가능성과 요구된 임무를 달성할 확률의 예측여부 및 이의 적합성을 판단하는 것이다. 첫번째의 문제는 기존의 신뢰성 공학의 방법을 사용하여 해결되지만 두번째의 문제는 잦은 사후 설계 변경을 필요로 하기 때문에 항상 시스템 전체에서의 최적을 고려하여 이루어지지 못하고 있다. 본 논문에서는 그러한 잦은 사후 설계 변경등으로 인한 취약한 점을 극복하기 위한 방법론으로 하드웨어 설계 신뢰성 공학을 다루며 그 분석 도구로서 목표달성 나무(Goal-tree)의 사용과 그 응용을 제시하고자 한다.

• Korean Journal of Remote Sensing
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• v.34 no.5
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• pp.721-738
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• 2018

The purpose of this study is to create landslide vulnerability using frequency ratio (FR) and evidential belief functions (EBF) model which are two methods of probability model and to select appropriate model for each region through comparison of results in Sacheon-myeon and Jumunjin-eup of Gangneung. 762 locations in Sacheon-myeon and 548 landscapes in Jeonju-eup were constructed based on the interpretation of aerial photographs. Half of each landslide point was randomly selected for modeling and remaining landslides were used for verification purposes. Twenty landslide-inducing factors classified into five categories such as topographic elements, hydrological elements, soil maps (1:5,000), forest maps (1:5,000), and geological maps (1:25,000) were considered for the preparation of landslide vulnerability in the study. The relationship between landslide occurrence and landslide inducing factors was analyzed using FR and EBF models. The two models were then verified using the AUC (curve under area) method. According to the results of verification, the FR model (AUC = 81.2%) was more accurate than the EBF model (AUC = 78.9%) at Jeonjun-eup. In the Sacheon-myeon, the EBF model (AUC = 83.6%) was more accurate than the FR model (AUC = 81.6%). Verification results show that FR model and EBF model have high accuracy with accuracy of around 80%.

• Tunnel and Underground Space
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• v.14 no.3
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• pp.167-174
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• 2004

This paper is to introduce an article published in Rock Mechanics and Rock Engineering, 2003. In this research, a fracture mechanics model is developed to illustrate the importance of time-dependence far brittle fractured rock. In particular a model is developed fer the time-dependent degradation of rock joint cohesion. Degradation of joint cohesion is modeled as the time-dependent breaking of intact patches or rock bridges along the joint surface. A fracture mechanics model is developed utilizing subcritical crack growth, which results in a closed-form solution for joint cohesion as a function of time. As an example, a rock block containing rock bridges subjected to plane sliding is analyzed. The cohesion is found to continually decrease, at first slowly and then more rapidly. At a particular value of time the cohesion reduces to value that results in slope instability. A second example is given where variations in some of the material parameters are assumed. A probabilistic slope analysis is conducted, and the probability of failure as a function of time is predicted. The probability of failure is found to increase with time, from an initial value of 5% to a value at 100 years of over 40%. These examples show the importance of being able to predict the time-dependent behavior of a rock mass containing discontinuities, even for relatively short-term rock structures.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.195-204
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• 2008

Multi-Criteria Analysis is one method for optimizing decisions that include numerous characteristics and objective functions. The Analytic Hierarchy Process (AHP) is used as a general Multi-Criteria Analysis considering many critical issues. However, since validation procedures for the decision reliability of AHP valuers had been left off existing methodologies, a new methodology including such validation procedures is required to make more reliable decisions. In this research, idea decision results are derived using Monte Carlo Simulation in cases where AHP valuers do not have expertise in the specific project, and these results are compared with the results derived from experts to develop a new analysis model to make more reliable decisions. Finally, this new analysis is applied to various field case studies of road and rail carried out by the Korea Development Institute (KDI) between 2003 and 2006 to validate the new analysis model. The study found that approximately 20% of decisions resulting from the existing methodology are considered prudent. In future studies, the authors suggest analyzing the correlation between initial weights and final results since final results are enormously influenced by the initial weight.

• Journal of the Korean Geotechnical Society
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• v.35 no.4
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• pp.27-35
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• 2019

This study confirmed the applicability to the field of geotechnical engineering for relatively complicated space and many target design variables in back analysis. The Sharan's equation and the Blum's method were used for the tunnel field and the retaining wall as a model for the multi-variate problem of geotechnical engineering. Optimization methods are generally divided into a deterministic method and a stochastic method. In this study, Simulated Annealing Method (SA) was selected as a deterministic method and Differential Evolution Algorithm (DEA) and Particle Swarm Optimization Method (PSO) were selected as stochastic methods. The three selected optimization methods were compared by applying a multi-variate model. The problem of deterministic method has been confirmed in the multi-variate back analysis of geotechnical engineering, and the superiority of DEA can be confirmed. DEA showed an average error rate of 3.12% for Sharan's solution and 2.23% for Blum's problem. The iteration number of DEA was confirmed to be smaller than the other two optimization methods. SA was confirmed to be 117.39~167.13 times higher than DEA and PSO was confirmed to be 2.43~6.91 times higher than DEA. Applying a DEA to the multi-variate back analysis of geotechnical problems can be expected to improve computational speed and accuracy.

• Tunnel and Underground Space
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• v.12 no.1
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• pp.10-18
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• 2002

Rock joint system makes a heavy effect on the behavior of rock structures. The definition of a 3D rock joint system is very important in 2D or 3D numerical analysis for the prediction of the behavior of a discontinuous rock mass. To enhance the reality of a 3D definition of rock joint system, it is essential to estimate the unbiased statistics of basic geometric attributes of rock joints. In this study, we have proposed the statistical analysis and derived the related equations for an estimation of statistics of joint size and intensity. Geometry of rock joints in 3 dimensional space can be defined by the aggregate of location, size, orientation and intensity. The dimensional limit of survey method and its data makes 3D geometric attributes probabilistic. In the estimation of statistics of joint size, we have discussed the technique to correct the bias from a dimensional limit and derived the equation of 3D joint intensity by stereological approaches.