• Spatial Information Research
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• v.23 no.5
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• pp.65-73
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• 2015

Newtown Business of Seoul had been performed to reduce deterioration of Gangbuk and economic inequality between Gangnam and Gangbuk. According to this, Eunpyeong-gu was set as test-bed for Newtown business and Newtown business had been completed until 2013. This study aims to analyze the influence of social and economical factors which affect land price using GWR (Geographically Weighted Regression) considered spatial effect. As a result of analysis, GWR model demonstrated a better goodness-of-fit than OLS (Ordinary least square) model typically used in most study. Furthermore, AIC value and Moran's I of residual prove that GWR model is more suitable than OLS model. GWR model enable to explain more detailed than global regression model as coefficient and sign show different value locally. In future, this research will be helpful to develop Eunpyeong-gu considering spatial characters and strength effectiveness of development.

• Water for future
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• v.24 no.1
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• pp.109-117
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• 1991

The governing equation of flow in porous media is developed on the bases of the continuity equation of fluid for transient flow through a saturated-unsaturated zone, and substitution of Darcy's law. The numerical solutions are obtained by finite element method based on the Galerkin principles weighted residuals. The analysis are carried out by using the unsteady storm data observed and rainfall intensities which are obtained by using the rainfall excess model in considering of the initial losses. The functional relationships between the hydraulic conductivity, capillary pressure head and volumetric water content are applied to the flow of water through unsaturated soil varied with changes of water content.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.7 no.3
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• pp.89-98
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• 1987

Analyzed by using finite element method was 2-dimensional pollutant transtport phenomenon considering longitudinal and lateral direction in river. The Galerkin's finite element method based on linear interpolation is used and triangle is adopted as an element. In a number of model test attempts it has been demonstrated that the results calculated by the model are in good agreement with analytical solutions in a simplified channel where there is a known solution available. Actual application of the model is attempted along the 9km reach of the Han River considering the influx of the Tan Cheon and the Joongryang Cheon. The resultant 2-dimensional BOD concentrations profile in the reach is exhibiting more realistically the field situations than conventional 1-dimensional models are.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.15 no.1
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• pp.1-8
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• 1990

In this paper, the transient electromagneti wave scattering at dielectric cylinder is studied by new numerical analysis method. Basic formulation of boundary integral equation (BIE) for numerical method is started weighted residual technique. BIE is made to two simultaneous equation at surface inner and outside point of dielectric cylinder in extended boundary condition (EBC) and surface boundary condition (SBC). Numerical method is used Boundary element method (BEM) that is two form, one is direct method and the other is indirect method, so that this method that transformes operator inversion martics is used numerical analysis. A good agreement of this numerical solution and the other results is obtained.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.12 no.3
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• pp.133-141
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• 2007

A finite element model is developed for the extended Boussinesq equations that is capable of simulating the dynamics of long and short waves. Galerkin weighted residual method and the introduction of auxiliary variables for 3rd spatial derivative terms in the governing equations are used for the model development. The Adams-Bashforth-Moulton Predictor Corrector scheme is used as a time integration scheme for the extended Boussinesq finite element model so that the truncation error would not produce any non-physical dispersion or dissipation. This developed model is applied to the problems of solitary wave propagation. Predicted results is compared to available analytical solutions and laboratory measurements. A good agreement is observed.

• Journal of Navigation and Port Research
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• v.26 no.1
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• pp.137-145
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• 2002

Water flow simulations for environmental problems often require local detailed analyses for better understanding and accurate prediction of the fate of pollutant in water bodies. This study deals with the development and application of a two-dimensional flow an dispersion model to the coastal water area to find out possible changes due to the wide port development plan. As far as the spatial discretization is concerned, the finite element method is attractive because of its flexibility and ability to naturally treat complex coastal geometries. The model uses finite element theory and the Galerkin weighted-residual approach as its basis. Developed model is applied to the Busan New harbor Construction site. Results from the model were compared with the measured water level and flows in four stations. The flow pattern by the model shows to be similar to the observed data away from the construction site where the flow is not affected. From the simulation results, it is concluded that the model may be useful for numerous other studies for planning and management purposes, especially flow and pollution dispersion in the coastal water bodies where the flow is so complicated.

• Journal of the Korean Geographical Society
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• v.39 no.2
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• pp.212-228
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• 2004

This paper is concerned with an important aspect of regional income convergence, ${\beta}$-convergence, which refers to the negative relationship between initial income levels and income growth rates of regions over a period of time. The common research framework on ${\beta}$-convergence which is based on OLS regression models has two drawbacks. First, it ignores spatially autocorrelated residuals. Second, it does not provide any way of exploring spatial heterogeneity across regions in terms of ${\beta}$-convergence. Given that empirical studies on ${\beta}$-convergence need to be edified by spatial data analysis, this paper aims to: (1) provide a critical review of empirical studies on ${\beta}$-convergence from a spatial perspective; (2) investigate spatio-temporal income dynamics across the U.S. labor market areas for the last 30 years (1969-1999) by fitting spatial regression models and applying bivariate ESDA techniques. The major findings are as follows. First, the hypothesis of ${\beta}$-convergence was only partially evidenced, and the trend substantively varied across sub-periods. Second, a SAR model indicated that ${\beta}$-coefficient for the entire period was not significant at the 99％ confidence level, which may lead to a conclusion that there is no statistical evidence of regional income convergence in the US over the last three decades. Third, the results from bivariate ESDA techniques and a GWR model report that there was a substantive level of spatial heterogeneity in the catch-up process, and suggested possible spatial regimes. It was also observed that the sub-periods showed a substantial level of spatio-temporal heterogeneity in ${\beta}$-convergence: the catch-up scenario in a spatial sense was least pronounced during the 1980s.

• Journal of the Korean Geographical Society
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• v.46 no.2
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• pp.197-211
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• 2011

Due to the complexity of spatial interaction and the necessity of spatial representation and modeling, aggregation of spatial interaction data is indispensible. Given this, the purpose of this paper is to evaluate the effects of modifiable areal unit problem (MAUP) on a spatial interaction model. Four aggregation schemes are utilized at eight different scales: 1) randomly select seeds of district and then allocate basic spatial units to them, 2) minimize the sum of population weighted distance within a district, 3) maximize the proportion of flow within a district, and 4) minimize the proportion of flow within a district. A simple Poisson regression model with origin and destination constraints is utilized. Analysis results demonstrate that spatial characteristics of residuals, parameter values, and goodness-of-fit of the model were influenced by aggregation scale and schemes. Overall, the model responded more sensitively to aggregation scale than aggregation schemes and the scale effect on the model was varied according to aggregation schemes.

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.345-356
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• 2023

Target signal of passive sonar shows narrow band harmonic characteristic with a variation in intensity within a few seconds and long term frequency variation due to the Lloyd's mirror effect. We propose a signal classification algorithm based on Gated Recurrent Unit (GRU) that learns local and global time series features. The algorithm proposed implements a multi layer network using GRU and extracts local and global time series features via dilated connections. We learns attention mechanism to weight time series features and classify passive sonar signals. In experiments using public underwater acoustic data, the proposed network showed superior classification accuracy of 96.50 %. This result is 4.17 % higher classification accuracy compared to existing skip connected GRU network.

• Journal of Korean Society for Geospatial Information Science
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• v.21 no.4
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• pp.73-81
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• 2013

Ordinary least squares (OLS) regression is the primary statistical method in previous studies for vegetation distribution patterns in relation to landform. However, this global regression lacks the ability to uncover some local-specific relationships and spatial autocorrelation in model residuals. This study employed geographically weighted regression (GWR) to examine the spatially varying relationships between NDVI (Normalized Difference Vegetation Index) patterns and changing trends of landform (elevation, slope) and solar intensity (insolation and duration of sunshine) in Mt Geum-gang of North-Korea. Results denoted that GWR was more powerful than OLS in interpreting relationships between NDVI patterns and landform/solar intensity, since GWR was characterized by higher adjusted R2, and reduced spatial autocorrelations in model residuals. Unlike OLS regression, GWR allowed the coefficients of explanatory variables to differ by locality by giving relatively more weight to NDVI patterns which are affected by local landform and solar factors. The strength of the regression relationships in the GWR increased significantly, by showing regression coefficient of higher than 70% (0.744) in the southern ridge of the experimental area. It is anticipated that this research output will serve to increase the scientific and objective vegetation monitoring in relation to landform and solar intensity by overcoming serious constraints suffered from the past non-GWR-based approach.