• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.334-334
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• 2017

Representative particle sizes(RPS) are commonly used for particle size distribution of heterogeneous sediment such as bed material. RPS can provide not only information of mean characteristics of sediment, but also other properties like sorting, skewness, kurtosis. For sediment including sand and clay material, RPS is estimated through two steps. The first is experimental step for calculating weight of each size class, the next is interpolation step to get RPS by using the graph plot. At the second step, graph method known as direct reading of value along the interpolation line in the graph plot is commonly used. This method is often time-consuming job. In this study we developed a new program to get RPS by using MS Excel. Simple linear and semi-log interpolation are used. When compared with conventional graph method(direct reading), simple linear shows 5.31%, while semi-log 1.29% of relative difference. We developed MS Excel program for estimation of RPS automatically.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.9C
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• pp.1323-1329
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• 2004

This paper presents an enhanced MSEA(multi-level successive elimination algorithm) which is a fast algorithm of the full-search motion estimation. We predict the SAD at the final level using the values of norms at the preceding levels in MSEA and then decide on whether the processing at the following levels should be proceeded or not. We skip the computation at the following levels where the processing is not meaningful anymore. Consequently, we take computational gain. For the purpose of predicting the values of SAD at each level, we first show the theoretical analysis of the value of norm at each level, which is verified by experiments. Based on the analysis a new motion estimation method is proposed and its performance is evaluated.

• The Korean Journal of Applied Statistics
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• v.29 no.7
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• pp.1155-1163
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• 2016

This paper deals with an estimation procedure of variance components in a mixed effects model by projections. Projections are used to obtain sums of squares instead of using reductions in sums of squares due to fitting both the assumed model and sub-models in the fitting constants method. A projection matrix can be obtained for the residual model at each step by a stepwise procedure to test the hypotheses. A weighted least squares method is used for the estimation of fixed effects. Satterthwaite's approximation is done for the confidence intervals for variance components.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.6 no.1
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• pp.53-60
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• 1996

오증 요소로부터 오류위치다항식의 계수를 계산함으로서 (23,12) Golay 부호를 복호할 수 있는 대수적 복호법이 최근 증명되었다. GF(2)상에서의 3중 오류정정 BCH부호의 복호법을 이 부호에 완벽하게 적용하여 해석하는 것을 소개한다. 그리고 GF(2)에 대한 최적의 정규기저를 구하여 이를 유한체 연산에 적용하며 단계별로 복호 회로의 구성을 제시한다. 이는 기존의 복호기보다 논리회로적으로 간단하며, 복호된 정보를 얻기까지 35번의 치환이 필요하다.

• Journal of the Korean Society of Hazard Mitigation
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• v.10 no.6
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• pp.81-87
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• 2010

In order to calculate the accurate runoff from a basin, nonlinearity in the relationship between rainfall and runoff has to be considered. Many runoff calculation models assume the linearity in the relationship or are too complicated to be analyzed. Therefore, the storage function method has been used in the prediction of flood because of the simplicity of the model. The storage function method has five parameters with related to the basin and rainfall characteristics which can be estimated by the empirical trial and error method. To optimize these parameters, regression method or optimization techniques such as genetic algorithm have been used, however, it is not easy to optimize them because of the complexity of the method. In this study, the metamodel is proposed to estimate those model parameters. The metamodel is the combination of artificial neural network and genetic algorithm. The model is consisted of two stages. In the first stage, an artificial neural network is constructed using the given rainfall-runoff relationship. In the second stage, the parameters of the storage function method are estimated using genetic algorithm and the trained artificial neural network. The proposed metamodel is applied in the Peong Chang River basin and the results are presented.

• The Journal of Engineering Geology
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• v.18 no.4
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• pp.493-499
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• 2008

In order to evaluate the lateral behavior characteristics of single drilled shaft embedded in granite gneiss, a lateral load test was conducted in field. Horizontal displacement according to lateral load were measured along with the depth by an inclinometer installed in the shaft. In this study, We have evaluated horizontal displacement characteristics comparing the measurement values with calculating results by theoretical formula. Based on the comparison, the Chang's method was similar with the measurement values even though it was slightly underestimated. However, the finite analysis method and p-y method was overestimated, especially on the upper part of the ground.

• Korean Journal of Construction Engineering and Management
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• v.16 no.4
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• pp.139-145
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• 2015

Modular construction is combined with manufacturing production process and conventional construction industry technique. Considering characteristic of modular construction production process, manufacturing facilities require indirect costs for utilities, equipment, and overall maintenance, which can affect modular units pricing. However, current modular construction cost classification is inadvertent to reflect the manufacturing overhead costs, because it is generally added as a percentage to sum of labor, material and equipment as it called in single cost pool used. This process is easy to estimate the total construction cost at the project starting points, but it brings on misunderstanding of project profit estimations by "cross subsidization phenomenon". To prevent this situation, in this research aims to provide modular construction overhead cost handling process at the detailed indirect cost calculation for manufacturing stage using Activity-Based Costing as one of the powerful method for overhead costs estimation and allocation. Using this research results, modular construction cost estimators have more detailed cost information of modular units and prevent to misallocate indirect costs. Also, it can be utilized to aid the understanding of the company's profit structure.

• Journal of the Korean Geotechnical Society
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• v.18 no.1
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• pp.71-78
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• 2002

This paper presents a back-calculation technique leer the prediction of the behavior of earth wall inserted in multi-layered soil deposit. The soil properties are back-calculated from the measured displacement at each construction stage and the behavior of earth wall far the next construction stage is predicted using back-calculated soil properties. For multi-layered soil deposit, the back-calculation would be very difficult due to the increase in the number of variables. In this study, to solve this difficulty, the back-calculation was performed successively from the lowest layer to the upper layers. An efficient elasto-plastic beam-column analysis was used for forward analysis to minimize the computation time of iterative back-calculation procedure. The coefficients of subgrade reaction and lateral earth pressure necessary for the formation of p-y curve were selected as back calculation variables, and to minimize the effect of abnormal behavior of the wall which might be caused by any unexpected action during construction, the difference between measured displacement increment and computed displacement increment at each construction stages is used as the objective function of optimization. The constrained sequential linear programming was used for the optimization technique to found values of variables minimizing the objective function. The proposed method in this study was verified using numerically generated data and measured field data.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2007.11a
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• pp.235-238
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• 2007

본 논문에서는 기존의 클러스터 기반 퍼지 모델트리에서 트리의 깊이에 따른 over-fitting으로 인한 훈련 및 검증데이터의 일관성 문제점을 해결하기 위해 상호 노드간의 정보를 고려하는 방법을 제안하고자 한다. 제안된 방법은 우선 입력과 출력변수의 속성을 고려한 퍼지 클러스터링에 의해 중심벡터를 계산한 후, 중심벡터들과 입력 속성간의 소속도를 이용하여 구간 분할된 영역별로 각각의 선형모델을 구축한다. 예측 단계에서는 입력된 데이터가 잎노드에 도달하는 노드간의 중심벡터와 입력 데이터간의 거리값에 따른 소속도를 계산한 후 최종적으로 무게 중심법을 이용하여 출력값을 예측하게 된다. 제안된 방법의 우수성을 보이기 위해 다양한 벤치마크 데이터를 대상을 실험한 결과, 기존의 클러스터 기반 퍼지 모델트리보다 향상된 성능을 보임을 알 수 있었다.

• Proceedings of the KIEE Conference
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• 2005.04a
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• pp.67-69
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• 2005

다층 매입형 영구자석 전동기의 설계에 있어서 d, q축 인덕턴스는 전동기의 특성을 결정짓는 중요한 파라미터이다. 그러나 심한 자계 포화 영역에서 동작하는 매입형 영구자석 전동기의 특성 때문에, 4축 q축 전류 조합별로 그 값들이 다를 뿐만 아니라, 설계 단계에서 정확하게 예측하기가 쉽지 않다. 따라서 본 논문에서는 매입형 영구자석 전동기의 중요한 파라미터인 d, q축 인덕턴스를 계산하는 몇 가지 방법들을 소개하였다. 또한, 해석 결과와 실험 결과와의 비교를 통하여 제안한 계산 방법의 타당성을 검증하였다.