• Journal of the Earthquake Engineering Society of Korea
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• v.7 no.6
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• pp.49-57
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• 2003

Although there are several experimental techniques to evaluate the seismic behavior and performance of civil structures, small-scale models in mast of physical tests, instead of prototypes or large-scale models, would be used due to a limitation on capacities of testing equipments. However, the inelastic seismic response prediction of small-scale models has some discrepancies inherently because the similitude law is generally derived in the elastic range. Thus, a special attention is required to regard the seismic behavior of small-scale models as one of prototypes. In this paper, differences between prototypes and small-scale models pseudodynamically tested on steel column specimens are investigated and an alternative to minimize them is suggested. In general, small-scale models could have the distorted stiffness induced from some experimental errors on test setup, steel fabrication and so on. Therefore, a modified similitude law considering both a scale factor for length and a stiffness ratio of small-scale model to prototype is proposed. Using the modified similitude law to compensate experimental errors, the pseudodynamic test results from modified small-scale model are much improved as compared with the results of prototype. According to the pseudodynamic test results of small-scale steel models, it can be concluded that the modified similitude law proposed could be effective in simulating the seismic response of prototype structures.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2008.10a
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• pp.262-262
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• 2008

• International Journal of Highway Engineering
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• v.10 no.1
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• pp.31-39
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• 2008

Preventing the traffic accident by accurately predicting it in advance can greatly improve road traffic safety. The accurate traffic accident prediction model requires not only understanding of the factors that cause the accident but also having the transferability of the model. So, this paper suggest the traffic accident diagram using CART(Classification And Regression Tree) analysis, developed Model is compared with the existing accident prediction models in order to test the goodness of fit. The results of this study are summarized below. First, traffic accident prediction model using CART analysis is developed. Second, distance(D), pedestrian shoulder(m) and traffic volume among the geometrical factors are the most influential to the traffic accident. Third. CART analysis model show high predictability in comparative analysis between models. This study suggest the basic ideas to evaluate the investment priority for the road design and improvement projects of the traffic accident blackspots.

• Journal of Korean Society of Transportation
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• v.32 no.2
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• pp.170-178
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• 2014

Until now, several research on the relationship of traffic crash occurrences and geometric had been conducted and revealed that projects of road alignment, geometric improvement and hazardous segment selection reduced the number of accidents and accident severities. However, such variables did not consider the non-homogeneous characteristics of roadway segments due to the difficulty of data collection, which results in under-estimation of the standard error affecting the overall modeling goodness-of-fit. This study highlights the importance of non-homogeneity by looking at the effect of the non-homogeneous geometric variables through the modeling process. The model delivers meaningful results when using some geometric variables without relevant geometrics' variables.

• Korean Journal of Cognitive Science
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• v.17 no.1
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• pp.53-74
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• 2006

Similarity has been considered as one of basic concepts of cognitive psychology which is useful for explaining cognitive structure and process. MDS models(Shepard, 1964; Nosofsky, 1991) and Contrast model(Tversky, 1977) were proposed as early models of similarity comparison process. But, there have been a lot of theoretical doubts about the conceptual validity of similarity as a result of empirical findings which could not be explained by early models. Goldstone(1994) assumed that similarity could be defined by alignment processes, and suggested structural alignment as a prospective alternative for solving conceptual controversies so far. In this study, basic assumption and algorithms of MDS models(Shepard, 1944; Nosofsky, 1991) and Contrast model(Tversky, 1977) were described shortly and some theoretical limitations such as arbitrariness of selective attention and correlated structures were discussed as well. The conceptual characteristics and algorithms of SIAM(Goldstone, 1994) were described and how it has been applied to cognitive psychology areas such as categorization, conceptual combination, and analogical reasoning were reviewed. Finally, some theoretical limitations related with data-driven processing and alternative processing and possible directions for structural alignment were discussed.

• The Korean Journal of Applied Statistics
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• v.28 no.1
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• pp.61-74
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• 2015

Structural equation modeling (SEM) is a widely used in social sciences such as education, business administration, and psychology. In SEM, the latent variable score is the estimate of the latent variable which cannot be observed directly. This study uses stagewise structural equation modeling(stagewise SEM; SSEM) by partitioning the whole model into several stages. The traditional estimation method minimizes the discrepancy function using the variance-covariance of all observed variables. This method can lead to inappropriate situations where exogenous latent variables may be affected by endogenous latent variables. The SSEM approach can avoid such situations and reduce the complexity of the whole SEM in estimating parameters.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.101-101
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• 2023

지난 수십 년 동안 다양한 딥러닝 방법이 개발되고 있으며 수문 분야에서는 이러한 딥러닝 모형이 기존의 수문모형의 역할을 대체하여 사용할 수 있다는 가능성이 제시되고 있다. 본 연구에서는 딥러닝 모형 중에 트랜스포머 모형에 다중 인코더를 사용하여 중장기 기간 (1 ~ 10일)의 리드 타임에 대한 한국의 유출량 예측 전망의 가능성을 확인하고자 하였다. 트랜스포머 모형은 인코더와 디코더 구조로 구성되어 있으며 어텐션 (attention) 기법을 사용하여 기존 모형의 정보를 손실하는 단점을 보완한 모형이다. 본 연구에서 사용된 다중 인코더 기반의 트랜스포머 모델은 트랜스포머의 인코더와 디코더 구조에서 인코더를 하나 더 추가한 모형이다. 그리고 결과 비교를 위해 기존에 수문모형을 활용한 스태킹 앙상블 모형 (Stacking ensemble model) 기반의 예측모형을 추가로 구축하였다. 구축된 모형들은 남한 전체를 총 469개의 대규모 격자로 나누어 각 격자의 유출량을 비교하여 평가하였다. 결과적으로 수문모형보다 딥러닝 모형인 다중 인코더 기반의 트랜스포머 모형이 더 긴 리드 타임에서 높은 성능을 나타냈으며 이를 통해 수문모형의 역할을 딥러닝 모형이 어느 정도는 대신할 수 있고 높은 성능을 가질 수 있는 것을 확인하였다.

• Korean Business Review
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• v.12
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• pp.103-118
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• 1999

Many security companies in Korea play the same role as the broker who can do dual trading in the American securities market. It seems that the proper model for the Korean market microstructure should contain the existence of broker. But the broker occupied little attention in U.S. until the early 1990. The purpose of this paper is to review and evaluate the strategic trader models of market microstructure theory which contain the broker as player. Three major models, Sarkar(1995), Chakravarty(1994), Chun, Oh, and Weller(1996) were compared and evaluated critically in the context of the Korean security market microstructure. The model of Sarkar(1995) was evaluated to be more appropriate for the Korean securities market context. Finally, limitations of this paper were indicated and some directions for the further research were suggested.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2011.11a
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• pp.125-127
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• 2011

구조물의 동적특성인 모드형상을 통해 국부적인 손상을 탐지하는 손상평가 기법은 많은 연구자에 의해 발전되고 있다. 하지만 플로팅 구조물에 대한 손상탐지 기법은 그 사례를 찾아보기 힘들다. 본 논문에서는 플로팅 구조물의 축소모형을 제작하고, 손상을 모사하여 손상전과 손상 후 구조물의 모드형상에서 얻을 수 있는 모달 변위로 나타낸 손상지수를 통해 플로팅 구조물의 손상을 탐지 하였다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2012.10a
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• pp.279-281
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• 2012

구조물의 동적특성인 모드형상을 통해 국부적인 손상을 탐지하는 손상평가 기법은 많은 연구자에 의해 발전되고 있다. 하지만 플로팅 구조물에 대한 손상탐지 기법은 그 사례를 찾아보기 힘들다. 본 논문에서는 콘크리트재질의 플로팅 구조물의 축소모형을 제작하고 손상을 모사하여 손상 전, 후 구조물의 모드형상에서 얻을 수 있는 모달 변위로 나타낸 손상지수를 통해 플로팅 구조물의 손상을 탐지하였다.