• Atmosphere
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• v.31 no.2
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• pp.185-198
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• 2021

In this study, we examined a spatial downscaling method based on Gradient and Inverse Distance Squared (GIDS) weighting to produce high-resolution grid data from a numerical weather prediction model over Korean Peninsula with complex terrain. The GIDS is a simple and effective geostatistical downscaling method using horizontal distance gradients and an elevation. The predicted meteorological variables (e.g., temperature and 3-hr accumulated rainfall amount) from the Limited-area ENsemble prediction System (LENS; horizontal grid spacing of 3 km) are used for the GIDS to produce a higher horizontal resolution (1.5 km) data set. The obtained results were compared to those from the bilinear interpolation. The GIDS effectively produced high-resolution gridded data for temperature with the continuous spatial distribution and high dependence on topography. The results showed a better agreement with the observation by increasing a searching radius from 10 to 30 km. However, the GIDS showed relatively lower performance for the precipitation variable. Although the GIDS has a significant efficiency in producing a higher resolution gridded temperature data, it requires further study to be applied for rainfall events.

• The Korean Journal of Applied Statistics
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• v.27 no.4
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• pp.655-665
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• 2014

An adequate understanding and response to natural hazards such as heat wave, heavy rainfall and severe drought is required. We apply extreme value theory to analyze these abnormal weather phenomena. It is common for extremes in climatic data to be nonstationary in space and time. In this paper, we analyze summer rainfall data in South Korea using exceedance values over thresholds estimated by quantile regression with location information and time as covariates. We group weather stations in South Korea into 5 clusters and t extreme value models to threshold exceedances for each cluster under the assumption of independence in space and time as well as estimates of uncertainty for spatial dependence as proposed in Northrop and Jonathan (2011).

• Journal of the Korean housing association
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• v.25 no.2
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• pp.63-70
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• 2014

The dependence on cars for urban mobility and the exponential increase in traffic and urban infrastructure to sustain traffic have lead to an encapsulated way of life, where the connection with the natural environment is much more reduced and programmed. In a previous study, a process based on estimating distances showed that children who move around their city by automobile do not appreciate their environment as a spatial continuum, but rather as a series of independent spaces that are reached by automobile or bus, thereby evidencing a different way of conceptualizing urban space in the light of different cognitive structures (Goluboff, Garc$\acute{i}$a-Mira, and Garc$\acute{i}$a-Font$\acute{a}$n, 2002). The present study is concerned with the process of understanding and knowledge of urban space, and contrasting the cognitive structure of different groups. The implications that this study may have for urban planning are discussed.

• Korean Journal of Remote Sensing
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• v.36 no.1
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• pp.83-92
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• 2020

The purpose of this work was to apply geographical information system (GIS) for geostatistical analyzing by selecting a semi-variogram model to quantify the spatial correlation of the population distribution with residential neighborhoods in the both sides of Mosul city. Two hundred and sixty-eight sample sites in 240 ㎢ are adopted. After determining the population distribution with respect to neighborhoods, data were inserted to ArcGIS10.3 software. Afterward, the datasets was subjected to the semi-variogram model using ordinary kriging interpolation. The results obtained from interpolation method showed that among the various models, Spherical model gives best fit of the data by cross-validation. The kriging prediction map obtained by this study, shows a particular spatial dependence of the population distribution with the neighborhoods. The results obtained from interpolation method also indicates an unbalanced population distribution, as there is no balance between the size of the population neighborhoods and their share of the size of the population, where the results showed that the right side is more densely populated because of the small area of residential homes which occupied by more than one family, as well as the right side is concentrated in economic and social activities.

• Journal of the Korean Vacuum Society
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• v.12 no.S1
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• pp.113-115
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• 2003

We investigate transmission of light in nanoscale structures. We present spatial and temporal domain measurements of the dephasing of surface plasmon excitations in metal films with periodic nano-hole arrays. By probing coherent spatial SP propagation lengths of a few f1. $\mu$m and an ultrafast decay of the SP polarization on a 10 fs timescale, we demonstrate that the SP transmission peaks are homogeneously broadened by the SP radiative lifetime. The pronounced wavelength and hole size dependence of the dephasing rate shows that the microscopic origin of the conversion of SP into light is a Rayleigh-like scattering by the periodic hole array. We have experimentally studied the dephasing of surface plasmon excitations in metallic nano-hole arrays. By relating nanoscopic SP propagation, ultrafast light transmission and optical spectra, we demonstrate that the transmission spectra of these plasmonic bandgap structures are homogeneously broadened. The spectral line shape and dephasing time are dominated by Rayleigh scattering of SP into light and can varied over a wide range by controlling the resonance energy and/or hole radius. This opens the way towards designing SP nano-optic devices and spatially and spectrally tailoring light -matter interactions on nanometer length scales.

• Communications for Statistical Applications and Methods
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• v.26 no.3
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• pp.261-272
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• 2019

In this paper, we propose a procedure to build a prediction interval of the sum of dependent binary random variables over a graph to account for the dependence among binary variables. Our main interest is to find a prediction interval of the weighted sum of dependent binary random variables indexed by a graph. This problem is motivated by the prediction problem of various elections including Korean National Assembly and US presidential election. Traditional and popular approaches to construct the prediction interval of the seats won by major parties are normal approximation by the CLT and Monte Carlo method by generating many independent Bernoulli random variables assuming that those binary random variables are independent and the success probabilities are known constants. However, in practice, the survey results (also the exit polls) on the election are random and hardly independent to each other. They are more often spatially correlated random variables. To take this into account, we suggest a spatial auto-regressive (AR) model for the surveyed success probabilities, and propose a residual based bootstrap procedure to construct the prediction interval of the sum of the binary outcomes. Finally, we apply the procedure to building the prediction intervals of the number of legislative seats won by each party from the exit poll data in the $19^{th}$ and $20^{th}$ Korea National Assembly elections.

• Journal of Korean Association for Spatial Structures
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• v.21 no.2
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• pp.99-110
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• 2021

This study presents the estimation of crack depth by analyzing temperatures extracted from thermal images and environmental parameters such as air temperature, air humidity, illumination. The statistics of all acquired features and the correlation coefficient among thermal images and environmental parameters are presented. The concrete crack depths were predicted by four different machine learning models: Multi-Layer Perceptron (MLP), Random Forest (RF), Gradient Boosting (GB), and AdaBoost (AB). The machine learning algorithms are validated by the coefficient of determination, accuracy, and Mean Absolute Percentage Error (MAPE). The AB model had a great performance among the four models due to the non-linearity of features and weak learner aggregation with weights on misclassified data. The maximum depth 11 of the base estimator in the AB model is efficient with high performance with 97.6% of accuracy and 0.07% of MAPE. Feature importances, permutation importance, and partial dependence are analyzed in the AB model. The results show that the marginal effect of air humidity, crack depth, and crack temperature in order is higher than that of the others.

• Journal of Environmental Science International
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• v.13 no.5
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• pp.479-488
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• 2004

Five sediment cores from the tidal flat of artificial Lake Shihwa are analyzed in terms of sedimentology and geochemistry to evaluate the heavy metal contamination and redox condition of surficial sediment following the Shihwa seawall construction. The variability of concentrations of various elements depends on the depositional environment, and reflects the various redox conditions and sediment provenances. The amounts of Ti and Al and their ratio of Ti/ Al with respect to Li clearly indicate that there is an anthropogenic contribution to the surficial sediment. The high concentrations of heavy metals suggest an anthropogenic contribution at ST. 34 and ST. 22. Concentrations of most elements (Cr, Cu, Zn and Pb) are higher near the Shihwa-Banwol industrial complex than in the central part of Lake Shihwa. Concentrations of heavy metal in surficial sediment near the Shihwa-Banwol industrial complex are two to eight times higher than in the center of Lake Shihwa. Enrichment factors (EF), which are normalized by the unpolluted shale, suggests a significant metallic contamination near the Shihwa-Banwol industrial complex (SBIC). The redox condition is divided into two anoxic and mixed oxi $c_oxic zones based on the carbon:sulfur (C/S) ratios of organic matter and elemental relationships. Correlations among geochemical elements Mn, U and Mo are significantly different from site to site, and may therefore be an indicator of the spatial redox condition. Controlling factors for switching anoxic/oxic conditions are thought to be water depth and the differences in industrial effluent supply. The variations of the Cu/Mn ratio in the sediments confirms above mentioned spatial differences of a redox condition in part, and therefore shows a location-dependence redox condition in sediments at four other sites. The redox condition of the surficial sediment characteristics of the Shihwa Lake are controlled by its geographic location and water depth.th.

• The Korean Journal of Applied Statistics
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• v.27 no.6
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• pp.947-958
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• 2014

Understanding extreme precipitation events is very important for flood planning purposes. Especially, the r-year return level is a common measure of extreme events. In this paper, we present a spatial analysis of precipitation return level using hierarchical Bayesian modeling. For intensity, we model annual maximum daily precipitations and daily precipitation above a high threshold at 62 stations in Korea with generalized extreme value(GEV) and generalized Pareto distribution(GPD), respectively. The spatial dependence among return levels is incorporated to the model through a latent Gaussian process of the GEV and GPD model parameters. We apply the proposed model to precipitation data collected at 62 stations in Korea from 1973 to 2011.

• Journal of the Economic Geographical Society of Korea
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• v.21 no.4
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• pp.273-288
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• 2018

The protected horticulture sector was evaluated as achieving the highest level of agricultural industrialization, this study examined the structural changes in the field of Korea oriental melon farming, where cultivation under structure has advanced through its long history, with the focus on intensification and concentration of agriculture. From the 1970's, the oriental melon farming labor were replaced by capital due to the increase of dependence on input industries and the decrease in labor input, thus intensification improved the productivity. Through the development, Seongju-gun of Gyeongsangbuk-do, experienced faster growth of cultivation compared to other regions, and gained a competitive edge in productivity which led to the spatial concentration as well as the concentration of farms. In this restructuring process of oriental melon farming, spatial inequality intensified throughout the agricultural development as the existing farming spaces underwent a dynamic shift.