• 말소리와 음성과학
• /
• 제7권4호
• /
• pp.131-138
• /
• 2015

The initial syllables of a pair of Sino-Korean words are generally differentiated in their meaning by either short or long durations. They are realized differently by the dialect and generation of speakers. Recent research has reported that the temporal distinction has gradually faded away. The aim of this study is to examine whether college students with Kyungsang dialect made the distinction temporally using a statistical method of Mixed Effects Model. Thirty students participated in the recording of five pairs of Korean words in clear or casual speaking styles. Then, the author measured the durations of the initial syllables of the words and made a descriptive analysis of the data followed by applying Mixed Effects Models to the data by setting gender, length, and style as fixed effects, and subject and syllable as random effects, and tested their effects on the initial syllable durations. Results showed that college students with Kyungsang dialect did not produce the long and short syllables distinctively with any statistically significant difference between them. Secondly, there was a significant difference in the duration of the initial syllables between male and female students. Thirdly, there was also a significant difference in the duration of the initial syllables produced in the clear or casual styles. The author concluded that college students with Kyungsang dialect do not produce long and short Sino-Korean syllables distinctively, and any statistical analysis on the temporal aspect should be carefully made considering both fixed and random effects. Further studies would be desirable to examine production and perception of the initial syllables by speakers with various dialect, generation, and age groups.

• Asian-Australasian Journal of Animal Sciences
• /
• 제13권3호
• /
• pp.413-422
• /
• 2000

In the class of models which include random effects, the variance component estimates are important to obtain accurate predictors and estimators. Variance component estimation is straightforward for balanced data but not for unbalanced data. Since orthogonality among factors is absent in unbalanced data, various methods for variance component estimation are available. REML estimation is the most widely used method in animal breeding because of its attractive statistical properties. Recently, Bayesian approach became feasible through Markov Chain Monte Carlo methods with increasingly powerful computers. Furthermore, advances in variance component estimation with complicated models such as generalized linear mixed models enabled animal breeders to analyze non-normal data.

• 응용통계연구
• /
• 제28권2호
• /
• pp.241-250
• /
• 2015

경시적 자료 연구의 중요한 주제 중의 하나는 시간이 지남에 따라 개인의 건강 상태가 어떻게 변하는지를 추적하는 확률이다. 질병의 상태를 시간의 흐름에 따라 추적하는 것은 장기간에 걸친 임상적 관찰 연구의 계획과 분석, 그리고 질병의 예방과 치료에 중요한 의미를 지닌다. 본 논문에서는 두 다른 시점에서 각 개인의 건강 상태에 대한 조건부 확률을 추정해내는 순위 추적 확률에 대하여 연구하였다. 순위 추적 확률과 순위 추적 확률비를 추정하기 위하여 선형 혼합 효과 모형을 고려하였다. 본 논문의 방법은 아동을 대상으로 심혈관계 질환의 위험요인을 연구하는 역학 자료에 적용되었다.

• Computers and Concrete
• /
• 제4권2호
• /
• pp.135-156
• /
• 2007

Three 3D nonlinear finite-element models are developed to study the behavior of concrete beams and plates with and without external reinforcement by fibre-reinforced plastic (FRP). All three models are formulated based upon the 3D theory of elasticity. The stress model is modified from the element developed by Ramtekkar, et al. (2002) to incorporate material nonlinearity in the formulation. Both transverse stress and displacement components are used as nodal degrees-of-freedom to ensure the continuity of both stress and displacement components between the elements. The displacement model uses only displacement components as nodal degrees-of-freedom. The transition model has both stress and displacement components as nodal degrees-of-freedom on one surface, and only displacement components as nodal degrees-of-freedom on the opposite surface. The transition model serves as a connector between the stress and the displacement models. The developed models are validated by comparing the results of the analyses with an existing experimental result. Parametric studies of the effects of the externally reinforced FRP on the load capacity of reinforced concrete (RC) beams and concrete plates are performed to demonstrate the practicality and the efficiency of the proposed models.

• Communications for Statistical Applications and Methods
• /
• 제22권6호
• /
• pp.625-637
• /
• 2015

We develop a Bayesian clustering procedure based on a Dirichlet process prior with cluster specific random effects. Gibbs sampling of a normal mixture of linear mixed regressions with a Dirichlet process was implemented to calculate posterior probabilities when the number of clusters was unknown. Our approach (unlike its counterparts) provides simultaneous partitioning and parameter estimation with the computation of the classification probabilities. A Monte Carlo study of curve estimation results showed that the model was useful for function estimation. We find that the proposed Dirichlet process mixture model with cluster specific random effects detects clusters sensitively by combining vague edges into different clusters. Examples are given to show how these models perform on real data.

• Computers and Concrete
• /
• 제24권1호
• /
• pp.1-6
• /
• 2019

Within the scope of this study, the foam solution was prepared by properly mixing sulfonate based foam agent with water. Furthermore, this solution was mixed with the mixture of fine sand, cement, and water to produce foamed concrete. The mixture ratios which are the percentage of foam solution used in foam concrete were chosen as 0, 20, 40 and 60% by vol. After these groups reached 28 days of strength, they were heated to 20, 100, 400 and $700^{\circ}C$ respectively. Afterward, high-temperature effects on the foamed concrete were obtained by employing physical and mechanical properties tests. Additionally, SEM (scanning electron microscope) and EDX (energy-dispersive X-ray spectroscopy) tests were employed to analyze the microstructure, and ${\mu}-CT$ (micro computed tomography) images were used to reconstruct 3-D models of the heat-treated specimens. Then, these models are analyzed to examine the void structures and the changes in these structures due to the high temperatures. The study has shown that the void structures reduce the high-temperature effects and the foam solution could be mixed with concrete up to 40 % by vol. where the high strength of foamed concrete is non-mandatory.

• Journal of the Korean Data and Information Science Society
• /
• 제27권2호
• /
• pp.531-538
• /
• 2016

In this paper we deal with the small area estimation for the case that the response variables take binary values. The mixed effects models have been extensively studied for the small area estimation, which treats the spatial effects as random effects. However, when the spatial information of each area is given specifically as coordinates it is popular to use the geographically weighted logistic regression to incorporate the spatial information by assuming that the regression parameters vary spatially across areas. In this paper, relaxing the linearity assumption and propose a geographically weighted kernel logistic regression for estimating small area proportions by using basic principle of kernel machine. Numerical studies have been carried out to compare the performance of proposed method with other methods in estimating small area proportion.

• 한국컴퓨터정보학회논문지
• /
• 제27권3호
• /
• pp.13-23
• /
• 2022

Prasad et al.는 사전학습(pre-trained)한 신경망 L1 글로다바(Gulordava) 언어모델을 여러 유형의 영어 관계절과 등위절 문장들로 적응 학습(adaptation learning)시켜 문장 간 유사성(sentence similarity)을 평가할 수 있는 통사 프라이밍(syntactic priming)-기반 프로빙 방법((probing method)을 제안했다. 본 논문에서는 한국인 영어학습자가 배우는 영어 자료를 바탕으로 훈련된 L2 LSTM 신경망 언어 모델의 영어 관계절 혹은 등위절 구조의 문장들에 대한 임베딩 표현 방식을 평가하기 위하여 프로빙 방법을 적용한다. 프로빙 실험은 사전 학습한 LSTM 언어 모델을 기반으로 추가로 적응 학습을 시킨 LSTM 언어 모델을 사용하여 문장 임베딩 벡터 표현의 통사적 속성을 추적한다. 이 프로빙 실험을 위한 데이터셋은 문장의 통사 구조를 생성하는 템플릿을 사용하여 자동으로 구축했다. 특히, 프로빙 과제별 문장의 통사적 속성을 분류하기 위해 통사 프라이밍을 이용한 언어 모델의 적응 효과(adaptation effect)를 측정했다. 영어 문장에 대한 언어 모델의 적응 효과와 통사적 속성 관계를 복합적으로 통계분석하기 위해 선형 혼합효과 모형(linear mixed-effects model) 분석을 수행했다. 제안한 L2 LSTM 언어 모델이 베이스라인 L1 글로다바 언어 모델과 비교했을 때, 프로빙 과제별 동일한 양상을 공유함을 확인했다. 또한 L2 LSTM 언어 모델은 다양한 관계절 혹은 등위절이 있는 문장들을 임베딩 표현할 때 관계절 혹은 등위절 세부 유형별로 통사적 속성에 따라 계층 구조로 구분하고 있음을 확인했다.

• 응용통계연구
• /
• 제29권7호
• /
• pp.1155-1163
• /
• 2016

본 논문은 혼합효과의 선형모형에서 분산성분들의 추정방법으로 사영을 다루고 있다. 상수적합법에서 이용되는 제곱합에서의 감소(reductions in sums of squares) 대신에 사영을 이용하여 구하는 방법을 제시하고 있다. 단계별 방법에 의한 잔차모형으로부터 각 분산성분의 추정과 관련된 사영행렬을 구성하는 방법을 제공하고 있다. 사영행렬로 표현되는 이차형식의 기댓값을 이용하여 선형방정식계를 구성하고 적률법으로 분산성분을 추정하게 된다. 고정효과는 가중최소제곱법으로 추정되고 분산성분의 신뢰구간추정에 Satterthwaite의 근사과정으로 자유도를 계산하는 방법을 설명하고 있다.

• 한국데이터정보과학회:학술대회논문집
• /
• 한국데이터정보과학회 2006년도 PROCEEDINGS OF JOINT CONFERENCEOF KDISS AND KDAS
• /
• pp.37-37
• /
• 2006