• Korean Journal of Cognitive Science
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• v.10 no.3
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• pp.1.2-1.2
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• 1999

시각적 선택에 대한 과거 정신물리학적, 신경 생리학적 연구결과를 토대로 Feature Gate 라는 신경 망 모형을 제안하였다. 이 모형에는 공간 배치도가 위계 적으로 구성되어 있으며, 정보의 흐름이 위계의 각 수준으로부터 그 다음 수준으로 넘어갈 때 주의 게이트에 의해 조절되도록 되어 있다. 주의 게이트들은 독특한 세부 특징을 가진 위치에 반응하는 상향식 시스템과 표적 세부 특징이 있는 위치에 반응하는 하향식 기제 모두에 의해 조절된다. 본 연구는 Feature Gate 모형의 하향식 기제에 초점을 맞추어 모형을 설명하고, 현재 다른 모형들이 설명하지 못하는 Moran & Desimone(1985)의 연구결과를 이 모형이 어떻게 설명하는지를 제시하고자 한다. Feature Gate 모형은 병렬 적인 세부특징 검색, 계열 적 접합표적 검색, 단서에 의한 주의의 점진적 감소 모형, 세부특징-주도적인 공간적 선택, 주의의 분할, 방해자극 위치의 억제, 주변 억제 등을 포함한 시각적 주의 연구의 여러 가지 많은 현상들을 설명하는데 하나의 일관적인 해석을 제공해 준다. 앞으로 이 모형을 더욱 확장, 발전 시켜 세부특징의 조합된 배열에 반응하는 상위 수준의 유닛을 사용한다면 시각적 선택과정이 포함된 형태 재인 모형으로 개발될 수 있다.

• Proceedings of the Korea Water Resources Association Conference
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• 2005.05b
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• pp.654-658
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• 2005

최종 유출지점에서의 해석 결과뿐 아니라 해석하고자 하는 유역내의 시간적, 공간적 수문 요소 분포 특성을 이해하기 위해서는 분포형 수문모형을 적용해야 하며, 최근 이에 대한 활용이 늘어나고 있다. 본 연구에서는 분포형 수문모형인 WEP 모형을 서로 다른 크기의 격자단위로 해석하여 그 결과를 비교하였다. 격자는 가로, 세로 50m, 200m격자를 사용하였으며, 각각의 연간 물수지, 하천 유출, 모의 시간, 수문 요소의 공간분포 양상 등을 비교, 분석하였다.

• The Korean Journal of Applied Statistics
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• v.27 no.3
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• pp.475-485
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• 2014

A stochastic weather generator based on a generalized linear model (GLM) approach is a commonly used tools to simulate a time series of daily weather. In this paper, we propose a multi-site weather generator with applications to historical data in South Korea. The proposed method extends the approach of Kim et al. (2012) by considering spatial dependence in the model. To reduce this phenomenon, we also incorporate a time series of seasonal mean precipitations of South Korea in the GLM weather generator as a covariate. Spatial dependence was incorporated into the model through a latent Gaussian process. We apply the proposed model to precipitation data provided by 62 stations in Korea from 1973{2011.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.23 no.4
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• pp.437-455
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• 2012

The purpose of the study is to design a space-based locality documentation model. It begins with analysing the changes of directions and strategies of locality documentation through literature surveys. Based on the analysis, a new paradigm of locality documentation is suggested in digital environment. It then suggests space-based documentation model, i.e., 'spanDoc Model (SPAace-based Networked Documentation Model)' which represent the new paradigm. The model focuses on planning the framework of use and accumulation of locality documentation.

• Journal of the Korean Geographical Society
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• v.45 no.6
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• pp.806-819
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• 2010

Population data has been essential and fundamental in spatial analysis and commonly aggregated into political boundaries. A conventional method for population distribution estimation was a regression model with land use data, but the estimation process has limitation because of spatial autocorrelation of the population data. This study aimed to improve the accuracy of population distribution estimation by adopting a Regression-Kriging method, namely RK Model, which combines a regression model with Kriging for the residuals. RK Model was applied to a part of Seoul metropolitan area to estimate population distribution based on the residential zones. Comparative results of regression model and RK model using RMSE, MAE, and G statistics revealed that RK model could substantially improve the accuracy of population distribution. It is expected that RK model could be adopted actively for further population distribution estimation.

• International Area Studies Review
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• v.20 no.1
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• pp.53-78
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• 2016

This study is to analyze the effects of both the bilateral FTA and a home and its trade partner's FTAs on the trade with 62 country-pair panel data over the period of 2003-2013 using the gravity model and the spatial autoregressive model. First, the study analyzes how the bilateral FTAs affect the trade using the gravity model and the spatial model. Next, the article analyzes how the home and its trade partners' FTAs affect their trade using only the spatial model under controlling the bilateral FTA. The empirical results are summarized as the followings: first, the spatial mode fits well more than the gravity model in analyzing the relationship between the bilateral FTA and trade. It implies that the spatial spillover effect of FTA is important in the international trade with FTA. Second, the bilateral FTA plays a role in expanding the trade between or among the FTA members as proved by the previous studies. Third, the more the home and its trade partners' FTAs, the more the bilateral trade are extended. Fourth, with the bilateral FTAs, as the home and its trade partners enter into more FTAs, the bilateral trade reduces due to trade diversion effects. In conclusion, this study provides a political implication that in order to increase the trade volume, a country enters into as many FTAs as possible because the effects of the bilateral FTAs would decrease.

• The Korean Journal of Applied Statistics
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• v.29 no.5
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• pp.873-885
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• 2016

Onions are grown in a few specific regions of Korea that depend on the climate and the regional characteristic of the production area. Therefore, when onion yields are to be estimated, it is reasonable to use a statistical model in which both the climate and the region are considered simultaneously. In this paper, using a spatial panel regression model, we predicted onion yields with the different weather conditions of the regions. We used the spatial auto regressive (SAR) model that reflects the spatial lag, and panel data of several climate variables for 13 main onion production areas from 2006 to 2015. The spatial weight matrix was considered for the model by the threshold value method and the nearest neighbor method, respectively. Autocorrelation was detected to be significant for the best fitted model using the nearest neighbor method. The random effects model was chosen by the Hausman test, and the significant climate variables of the model were the cumulative duration time of sunshine (January), the average relative humidity (April), the average minimum temperature (June), and the cumulative precipitation (November).

• Proceedings of the Korean Association of Geographic Inforamtion Studies Conference
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• 2008.06a
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• pp.101-108
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• 2008

본 연구의 목적은 분포형 추문모형에 있어 공간변수의 디테일함을 고려하기 위해 GIS와 결합된 SCS-CN 값 산정 모형을 개하는데 있다. 모형은 (주)한국공간정보통신의 GIS 소프트웨어 개발도구인 IntraMap/Objects를 사용하였고 마이크로소프트사의 닷넷 플랫폼 개발 언어인 C#으로 개발하였다. 모형의 입력자료인 토지이용도와 토양도의 지형학적 가공을 위해 클립(Clip), 디졸브(Dissolve), 인터섹션(Intersection)과 같은 지형전처리 모듈(GeoPreprocessing Module)을 개발하였다. 또한 전처리된 토지이용도(토지이용항목필드)와 토양도(추문학적 토양그룹필드)를 CN 값 기준도표에 매치시킴으로서 유역의 선행토양함수조건에 따른 분포형 CN 값 및 개략적인 유출량을 산정하는 모형을 개발하였다. 본 연구의 모형은 지형, 토양도 토지이용도, 토지피복도 변화에 따른 미래 유출량을 예측하는데 사용될 수 있을 것이다.

• The Korean Journal of Applied Statistics
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• v.23 no.2
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• pp.335-344
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• 2010

Reliability of the estimation is usually damaged in the situation where a linear regression model without spatial dependencies is employed to the spatial data analysis. In this study, we considered the conditional autoregressive model in order to construct spatial association structures and estimate the parameters via the Bayesian approaches. Finally, we compared the performances of the models with spatial effects and the ones without spatial effects. We analyzed the yearly total crime count data measured from each of 25 districts in Seoul, South Korea in 2007.

• Journal of the Korean Data and Information Science Society
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• v.27 no.5
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• pp.1203-1214
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• 2016

Obesity is a risk factor for various diseases as well as itself a disease and associated with socioeconomic factors. The obesity proportion has been increasing in Korea over about 15 years so that investigation of the socioeconomic factors related with obesity is important in terms of preventation of obesity. In particular, the association between obesity and socioeconomic status varies with gender and has spatial dependency. In the paper, we estimate the effects of socioeconomic factors on obesity proportion by gender, considering the spatial correlation. Here, a conditional autoregressive model under the Bayesian framework is used in order to take into account the spatial dependency. For the real applicaiton, we use the obestiy proportion dataset at 25 districts of Seoul in 2010. We compare the proposed spatial model with a non-spatial model in terms of the goodness-of-fit and prediction measures so the spatial model performs well.