• 한국환경농학회지
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• 제34권3호
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• pp.168-177
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• 2015

BACKGROUND: In recent year, there has been great concern regarding agricultural land uses and their importance for the conservation of biodiversity. Rice fields are managed unique wetland for wildlife, especially waterbirds. A comprehensive monitoring of the waterbird assemblage to understand patterning changes was attempted for rice ecosystem in South Korea. This rice ecosystem has been recognized as one of the most important for waterbirds conservation. METHODS AND RESULTS: Biweekly monitoring was implemented for the 4 years from April 2009 to March 2010, from April 2011 to March 2014. 32 species of waterbirds were observed. Self-organizing map (SOM) and random forest were applied to the waterbirds dataset to identify the characteristics in waterbirds distribution. SOM and random forest analysis clearly classified into four clusters and extract ecological information from waterbird dataset. Waterbird assemblages represented strong seasonality and habitat use according to waterbird group such as shorebirds, herons and waterfowl. CONCLUSION: Our results showed that the combination of SOM and random forest analysis could be useful for ecosystem assessment and management. Furthermore, we strongly suggested that a strict management strategy for the rice fields to conserve the waterbirds. The strategy could be seasonally and species specific.

• 대한음성학회지:말소리
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• 제57호
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• pp.139-152
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• 2006

In this paper, we present a phrase break prediction method using CRF(Conditional Random Fields), which has good performance at classification problems. The phrase break prediction problem was mapped into a classification problem in our research. We trained the CRF using the various linguistic features which was extracted from POS(Part Of Speech) tag, lexicon, length of word, and location of word in the sentences. Combined linguistic features were used in the experiments, and we could collect some linguistic features which generate good performance in the phrase break prediction. From the results of experiments, we can see that the proposed method shows improved performance on previous methods. Additionally, because the linguistic features are independent of each other in our research, the proposed method has higher flexibility than other methods.

• 대한기계학회논문집B
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• 제23권9호
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• pp.1163-1171
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• 1999

Superdiffusive transport motions of passive scalars are numerically considered for various advection velocity fields. Calculated exponents ${\alpha}$ in the superdiffusion-defining relation ${\sigma}^2(t){\sim}t^{\alpha}$ for model flow fields agree to the theoretically predicted values. Simulation results show that the superdiffusion takes place as the tracers' motion become less random, compared to their motion at the pure molecular diffusion. Whether the flow field is random or not, degrees of superdiffusion are directly related to the velocity autocorrelation functions along the tracers Lagrangian trajectories that characterize degrees of randomness of the tracers' motion.

• Structural Engineering and Mechanics
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• 제86권3호
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• pp.349-359
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• 2023

This paper presents a technique for determining the optimal number of elements in stochastic finite element analysis based on reliability analysis. Using the change-of-variable perturbation stochastic finite element approach, the probability density function of the dynamic responses of stochastic structures is explicitly determined. This method combines the perturbation stochastic finite element method with the change-of-variable technique into a united model. To further examine the relationships between the random fields, discretization of the random field parameters, such as the variance function and the scale of fluctuation, is also performed. Accordingly, the reliability index is calculated based on the explicit probability density function of responses with Gaussian or non-Gaussian random fields in any number of elements corresponding to the random field discretization. The numerical examples illustrate the effectiveness of the proposed method for a one-dimensional cantilever reinforced concrete column and a two-dimensional steel plate shear wall. The benefit of this method is that the probability density function of responses can be obtained explicitly without the use simulation techniques. Any type of random variable with any statistical distribution can be incorporated into the calculations, regardless of the restrictions imposed by the type of statistical distribution of random variables. Consequently, this method can be utilized as a suitable guideline for the efficient implementation of stochastic finite element analysis of structures, regardless of the statistical distribution of random variables.

• 충청수학회지
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• 제22권3호
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• pp.507-517
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• 2009

We prove a functional central limit theorem for a linear random field generated by negatively associated multi-dimensional random variables. Under finite second moment condition we extend the result in Kim, Ko and Choi[Kim,T.S, Ko,M.H and Choi, Y.K.,2008. The invariance principle for linear multi-parameter stochastic processes generated by associated fields. Statist. Probab. Lett. 78, 3298-3303] to the negatively associated case.

• Structural Engineering and Mechanics
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• 제3권1호
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• pp.1-10
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• 1995

This study presents a methodology for the system reliability analysis of cracked structures with random material properties, which are modeled as random fields, and crack geometry under random static loads. The finite element method provides the computational framework to obtain the stress intensity solutions, and the first-order reliability method provides the basis for modeling and analysis of uncertainties. The ultimate structural system reliability is effectively evaluated by the stable configuration approach. Numerical examples are given for the case of random fracture toughness and load.

• Structural Engineering and Mechanics
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• 제82권1호
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• pp.31-40
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• 2022

In structural engineering, the material properties of the structures such as elastic modulus, shear modulus, density, and size may not be deterministic and may vary at different locations. The dynamic response analysis of such structures may need to consider these properties as stochastic. This paper introduces a stochastic finite element method (SFEM) approach to analyze moving loads problems. Firstly, Karhunen-Loéve expansion (KLE) is applied for expressing the stochastic field of material properties. Then the mathematical expression of the random field is substituted into the finite element model to formulate the corresponding random matrix. Finally, the statistical moment of the dynamic response is calculated by the point estimation method (PEM). The accuracy and efficiency of the dynamic response obtained from the KLE-PEM are demonstrated by the example of a moving load passing through a simply supported Euler-Bernoulli beam, in which the material properties (including elastic modulus and density) are considered as random fields. The results from the KLE-PEM are compared with those from the Monte Carlo simulation. The results demonstrate that the proposed method of KLE-PEM has high accuracy and efficiency. By using the proposed SFEM, the random vertical deflection of a high-speed railway (HSR) bridge is analyzed by considering the random fields of material properties under the moving load of a train.

• 대한수학회지
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• 제35권3호
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• pp.575-581
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• 1998

We are interested in random phenomena that will vary as time goes by, being interfered with by fluctuation. These phenomena are often expressed as functionals of white noise. We therefore discuss the analysis of those functionals, where the white noise is understood as a system of idealized elementary random variables. The system is, in many cases, taken to be the innovation of the given random phenomena. The use of the innovation provides a powerful tool to investigate stochastic processes and random fields in line with white noise analysis.

• 대한수학회지
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• 제34권1호
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• pp.1-12
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• 1997

Complementaity problem theory developed by Lemke [10], Cottle and Dantzig [8] and others in the early 1960s and thereafter, has numerous applications in diverse fields of mathematical and engineering sciences. And it is closely related to variational inquality theory and fixed point theory. Recently, fixed point methods for the solving of nonlinear complementarity problems were considered by Noor et al. [11, 12]. Also complementarity problems related to variational inequality problems were investigated by Chang [1], Cottle [7] and others.

• 대한전자공학회논문지SP
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• 제44권1호
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• pp.40-48
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• 2007

이 논문은 다중 스케일 베이지안 관점에서 다층 퍼셉트론과 마코프 랜덤 필드를 사용한 새로운 결 분할 방법을 제안한다. 다층 퍼셉트론의 출력은 사후 확률을 모델링하므로 본 논문에서는 다중 스케일 웨이블릿 계수들을 다층 퍼셉트론의 입력으로 사용한다. 다층 퍼셉트론으로부터 구한 사후 확률과 MAP (maximum a posterior) 분류를 이용하여 각 스케일에서 결 분류를 수행한다. 또한 가장 섬세한 스케일에서 더 개선된 분할 결과를 얻기 위하여 모든 스케일에서 MAP 분류 결과들을 거친 스케일에서 섬세한 스케일까지 차례로 융합한다. 이런 과정은 한 스케일에서의 분류 정보와 그 인접한 보다 거친 스케일에서 얻어지는 문맥과 관련한 연역적 정보를 이용하여 MAP 분류를 행함으로써 이루어진다. 이 융합 과정에서, MRF (Markov random fields) 사전 모델이 평탄화 제한자로서 동작하고, 깁스 샘플러 (Gibbs sampler)는 MAP 분류기로서 동작한다. 제안한 분할 방법은 HMT (Hidden Markov Trees) 모델과 HMTseg 알고리즘을 이용한 결 분할 방법보다 더 좋은 성능을 보인다.