• Proceedings of the Korean Statistical Society Conference
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• 2000.11a
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• pp.261-266
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• 2000

이변량 반복측정자료에서 Chinchilli 등(1996)이 제안한 가중일치상관계수는 두 변수의 일치성을 나타내는 측도이다. 기존에 제안된 가중일치상관계수 추정법은 변동효과 및 측정오차의 분산성분을 각각 최소제곱법으로 비편향 추정하여 구하는 것이다. 본 연구에서는 반복측정자료의 주변 우도함수를 설정한 후, 우도함수에 기초한 분산성분을 구하여 가중일치상관계수를 추정하는 방법을 제안한다. 이때, 각 분산성분은 유사/의사 우도함수 및 사후 분포에서 반복시행을 통하여 구해진다.

• The Journal of the Acoustical Society of Korea
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• v.17 no.1
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• pp.49-54
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• 1998

본 논문에서는 잡음이 존재하는 환경에 강인한 것으로 알려져 있는 투영 방법을 우 도 측정에 가중 함수와 결합하여 사용하는 방법을 제안하였다. 반연속 HMM을 이용한 고립 단어의 인식 실험 결과, 제안한 방법이 실험에 사용된 잡음의 환경들에서 모두 좋은 성능을 나타내었다. 아울러 병렬 모델 결합 방법을 반연속 HMM에 적용하였는데 이는 코드북의 변 환반으로 쉽게 잡음의 특성을 반영할 수 있다. 가중 투영 우도 측정 방법을 병렬 모델 결합 방법에 적용한 경우에도 우수한 성능을 거둘 수 있었다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.3
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• pp.937-945
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• 2013

The accuracy of flood inundation maps is determined by the uncertainty propagated from all variables involved in the overall process including input data, model parameters and modeling approaches. This study investigated the uncertainty arising from key variables (flow condition and Manning's n) among model variables in flood inundation mapping for the Missouri River near Boonville, Missouri, USA. Methodology of this study involves the generalized likelihood uncertainty estimation (GLUE) to quantify the uncertainty bounds of flood inundation area. Uncertainty bounds in the GLUE procedure are evaluated by selecting two likelihood functions, which is two statistic (inverse of sum of squared error (1/SAE) and inverse of sum of absolute error (1/SSE)) based on an observed water surface elevation and simulated water surface elevations. The results from GLUE show that likelihood measure based on 1/SSE is more sensitive on observation than likelihood measure based on 1/SAE, and that the uncertainty propagated from two variables produces an uncertainty bound of about 2% in the inundation area compared to observed inundation. Based on the results obtained form this study, it is expected that this study will be useful to identify the characteristic of flood.

• Smart Media Journal
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• v.4 no.1
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• pp.16-24
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• 2015

In this paper, we propose a method for multi-touch tracking using MRF-based particle filters and gesture likelihood estimation Each touch (of one finger) is considered to be one object. One of frequently occurring issues is the hijacking problem which means that an object tracker can be hijacked by neighboring object. If a predicted particle is close to an adjacent object then the particle's weight should be lowered by analysing the influence of neighboring objects for avoiding hijacking problem. We define a penalty function to lower the weights of those particles. MRF is a graph representation where a node is the location of a target object and an edge describes the adjacent relation of target object. It is easy to utilize MRF as data structure of adjacent objects. Moreover, since MRF graph representation is helpful to analyze multi-touch gestures, we describe how to define gesture likelihoods based on MRF. The experimental results show that the proposed method can avoid the occurrence of hijacking problems and is able to estimate gesture likelihoods with high accuracy.

• Journal of the Korean Society of Radiology
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• v.16 no.2
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• pp.151-156
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• 2022

A detector using a small number of photosensors was designed, and the position of a scintillation pixel that interacted with gamma rays through a maximum likelihood position estimation(MLPE) was measured as a digital position. For this purpose, simulation was performed using DETECT2000, which can simulate the movement of light within the scintillator, and the accuracy of position measurement was evaluated. A detector was configured using a 6 × 6 scintillation pixel array and 4 photosensors, and a gamma ray event was generated at the center of each scintillation pixel to create a look-up table through the ratio of acquired light. The gamma-ray event generated at the new position was applied as the input value of the MLPE, and the positiion of the scintillation pixel was converted into a digital positiion after comparison with the look-up table. All scintillation pixels were evaluated, and as a result, a high accuracy of 99.1% was obtained. When this method is applied to the currently usesd system, it is concidered that the process of determining the position of the scintillation pixel will be simplified.

• Magazine of the Korea Concrete Institute
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• v.11 no.2
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• pp.241-249
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• 1999

To estimate the compressive strength of concrete more realistically, relative large number of data are necessary. However, it is very common in practice that only limited data are available. The purpose of the present paper is therefore to propose a realistic method to estimate the compressive strength of concrete with limited data in actual site. The Bayesian method of statistical analysis has been applied to the problem of the estimation of compressive strength of concrete. The mean compressive strength is considered as the random parameter and a prior distribution is selected to enable updating of the Bayesian distribution of compressive strength of concrete reflecting both existing data and sampling observations. The updating of the Bayesian distribution with increasing data is illustrated in numerical application. It is shown that by combining prior estimation with information from site observation, more precise estimation is possible with relatively small sampling. It is also seen that the contribution of the prior in determining the posterior distribution depends on its sharpness or flatness in relation to the sharpness or flatness of the likelihood function. The present paper allows more realistic determination of concrete strength in site with limited data.

• Journal of Advanced Marine Engineering and Technology
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• v.40 no.1
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• pp.69-74
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• 2016

Bathymetric changes were studied in the southern sea off the Jinwoo-do Island, which is one of the deltaic barrier islands surrounding the Nakddong river estuary. In this study, 16 bathymetry data sets were obtained from June 2006 to April 2015. Two narrow channels, the one lying between Jinwoo-do and Shinja-do, and the other one lying between Nulcha-do and Jinwoo-do extended into the eastern and western parts of the study area, respectively. The eastern extension of the channel contained a passage of mixed estuarine waters of seawater and river water discharged from the Nakdong river barrier and the west Nakdong River. The western channel connected the Nakdong River estuary with the Busan New Port via a connecting pier. Total volumetric changes of sediments in study area and discharge flow of the Nakdong river barrier were analyzed. Bottom topographical changes occurred mainly in the eastern extension of the channel. These changes were initially characterized by gradual erosion or deposition followed by rapid restoration. The total volume of sediment gradually increased from June 2006 to March 2013, but experienced a sudden decrease in October 2013 because of typhoon Danas. Few fluctuations were observed from October 2013 to April 2015. Analysis of the cross-sectional bathymetry of the north-south direction showed that the deepest point of the eastern channel moved 100-130 m westward and 200 m northward between June 2006 and April 2015.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2017.06a
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• pp.105-106
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• 2017

본 논문에서는 최대 우도 기반 파라미터 생성 알고리즘을 적용하여 인공 신경망의 출력인 음향 파라미터 열의 정확성 및 자연성을 향상시키는 방법을 제안하였다. 인공 신경망의 출력으로 정적 특징벡터 뿐 만 아니라 동적 특징벡터도 함께 사용하였고, 미리 계산된 파라미터 분산을 파라미터 생성에 사용하였다. 추정된 정적, 동적 특징벡터의 평균, 분산을 EM 알고리즘에 적용하여 최대 우도 기준 파라미터를 추정할 수 있다. 제안된 알고리즘은 파라미터 생성 시 동적 특징벡터 및 분산을 함께 적용하여 시간축에서의 자연성을 향상시켰다. 제안된 알고리즘의 객관적 평가로 MCD, F0 의 RMSE 를 측정하였고, 주관적평가로 선호도 평가를 실시하였다. 그 결과 기존 알고리즘 대비 객관적, 주관적 성능이 향상되는 것을 검증하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06b
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• pp.336-338
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• 2012

본 연구에서는 고차 데이터 분류를 위해 순차적 베이지만 샘플링 기반의 진화연산 기법을 이용한 하이퍼네트워크 모델의 학습 알고리즘을 제시한다. 제시하는 방법에서는 모델의 조건부 확률의 사후(posterior) 분포를 최대화하도록 학습이 진행된다. 이를 위해 사전(prior) 분포를 문제와 관련된 사전지식(prior knowledge) 및 모델 복잡도(model complexity)로 정의하고, 측정된 모델의 분류성능을 우도(likelihood)로 사 용하며, 측정된 사전분포와 우도를 이용하여 모델의 적합도(fitness)를 정의한다. 이를 통해 하이퍼네트워크 모델은 고차원 데이터를 효율적으로 학습 가능할 뿐이 아니라 모델의 학습시간 및 분류성능이 개선될 수 있다. 또한 학습 시에 파라미터로 주어지던 하이퍼에지의 구성 및 모델의 크기가 학습과정 중에 적응적으로 결정될 수 있다. 제안하는 학습방법의 검증을 위해 본 논문에서는 약 25,000개의 유전자 발현정보 데이터셋에 대한 분류문제에 모델을 적용한다. 실험 결과를 통해 제시하는 방법이 기존 하이퍼네트워크 학습 방법 뿐 아니라 다른 모델들에 비해 우수한 분류 성능을 보여주는 것을 확인할 수 있다. 또한 다양한 실험을 통해 사전분포로 사용된 사전지식이 모델 학습에 끼치는 영향을 분석한다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.5D
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• pp.605-610
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• 2009

The either satisfaction levels or limits of tolerance levels felt by the users in the certain space/region should be examined for measuring social capacity on the total amount of vehicles. The reliability of measuring social carrying capacity depends primarily on decreasing the strategic responding biases. To induce the honest responses to preferences, Dichotomous Choice which is specifically known as the Double-Bounded Dichotomous Choice was adopted in this research to suggest the measurement methodology of social carrying capacity on the total amount of vehicles in U-do island. The empirical test was carried out the U-do island, an administrative district of Jeju Special Self-Governing Province. The number of vehicles satisfied by the 10% of residents was 390 and the satisfactory vehicle number was decreased to 132 extended to 90% of residents. This research, based on the political decision making criteria, set up the social carrying capacity in U-do island. The vehicle number satisfied by 50% of residents was 227, which meant the same number of residents turn to be supporter in case of political actions.