• Journal of Korea Spatial Information System Society
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• v.11 no.4
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• pp.74-84
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• 2009

GIS based new postal marketing method is presented in this paper with spatiotemporal mining to cope with domestic mail volume decline and to strengthening competitiveness of postal business. Market segmentation technique for socialogy of population and spatiotemporal prediction of consumer propensity to purchase through spatiotemporal multi-dimensional analysis are suggested to provide meaningful and accurate marketing information with customers. Internal postal acceptance & external statistical data of local districts in the Seoul Metropolis are used for the evaluation of geo-lifestyle clustering and spatiotemporal cube mining. Successfully optimal 14 maketing clusters and spatiotemporal patterns are extracted for the prediction of consumer propensity to purchase.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.4
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• pp.89-97
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• 2015

In this paper, a method of color image segmentation based on DBSCAN(Density Based Spatial Clustering of Applications with Noise) using compactness of superpixels and texture information is presented. The DBSCAN algorithm can generate clusters in large data sets by looking at the local density of data samples, using only two input parameters which called minimum number of data and distance of neighborhood data. Superpixel algorithms group pixels into perceptually meaningful atomic regions, which can be used to replace the rigid structure of the pixel grid. Each superpixel is consist of pixels with similar features such as luminance, color, textures etc. Superpixels are more efficient than pixels in case of large scale image processing. In this paper, superpixels are generated by SLIC(simple linear iterative clustering) as known popular. Superpixel characteristics are described by compactness, uniformity, boundary precision and recall. The compactness is important features to depict superpixel characteristics. Each superpixel is represented by Lab color spaces, compactness and texture information. DBSCAN clustering method applied to these feature spaces to segment a color image. To evaluate the performance of the proposed method, computer simulation is carried out to several outdoor images. The experimental results show that the proposed algorithm can provide good segmentation results on various images.

• The Bulletin of The Korean Astronomical Society
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• v.38 no.1
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• pp.58.2-58.2
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• 2013

We present a photometric study of the globular clusters (GCs) in the giant elliptical galaxy M86 in the Virgo Cluster, using the Washington $CT_1$ images taken at the KPNO 4 m telescope. The color distribution of the GCs in M86 is bimodal. The radial number density profile of the blue GCs decreases more slowly as the galactocentric distance increases than that of the red GCs. The density profile of the red GCs is similar to the surface brightness profile of M86 stellar halo. The blue GCs have a roughly circular spatial distribution, while the red GCs have a spatial distribution somewhat elongated, which is consistent with the distribution of the galaxy stellar light. M86 GCs have the negative radial color gradient because the number ratio of the blue GCs to the red GCs increases as galactocentric radius increases. The mean color of the red GCs is similar to that of the stellar halo. The bright blue GCs in the outer region of M86 reveal a blue tilt that the mean colors of the blue GCs get redder as they get brighter. We discuss these results in comparison with other giant elliptical galaxies in the Virgo Cluster.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.43 no.6 s.312
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• pp.20-27
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• 2006

Multi-level thresholding is a method that is widely used in image segmentation. However most of the existing methods are not suited to be directly used in applicable fields and moreover expanded until a step of image segmentation. This paper proposes region-based multi-level thresholding as an image segmentation method. At first we classify pixels of each color channel to two clusters by using EWFCM(Entropy-based Weighted Fuzzy C-Means) algorithm that is an improved FCM algorithm with spatial information between pixels. To obtain better segmentation results, a reduction of clusters is then performed by a region-based reclassification step based on a similarity between regions existing in a cluster and the other clusters. The clusters are created using the classification information of pixels according to color channel. We finally perform a region merging by Bayesian algorithm based on Kullback-Leibler distance between a region and the neighboring regions as a post-processing method as many regions still exist in image. Experiments show that region-based multi-level thresholding is superior to cluster-, pixel-based multi-level thresholding, and the existing mettled. And much better segmentation results are obtained by the post-processing method.

• Journal of the Korean Geographical Society
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• v.43 no.3
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• pp.392-411
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• 2008

The purpose of this paper is to develop a method for exploring hotspot patterns of house price volatility where there is a high fluctuation in price and homogeneity of direction of price volatility. These patterns are formed when the majority of householders in an area show an adaptive tendency in their decision making. This paper suggests a method that consists of two analytical parts. The first part uses spatial scan statistics to detect spatial clusters of houses with a positive range of price volatility. The second part utilizes local Moran's I to evaluate the homogeneity of direction of price volatility within each cluster. The method is applied to the areas of Gangnam-Gu, Seocho-Gu, and Songpa-Gu in Seoul from August to November of 2003; the Participatory Government of Korea designated these areas and this period as the most speculative. The results of the analysis show that the area around Gaepo-Dong was as a hotspot before the Government's anti-speculative 10.29 policy in 2003; the house prices in the same area stabilized in October, 2003 and the area was identified as a coldspot in December, 2003. This case study shows that the suggested method enables exploration of hotspot of house price volatility at micro spatial scales which had not been detected by visual analysis.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.17 no.4
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• pp.124-137
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• 2018

The main purpose of this study is to find the hotspots of crimes that occur frequently in the space and to derive the appropriate CCTV installation location. One of the characteristics of crime is clustered around past occurrence area, and these crimes are strongly correlated. It is also possible to find the cause of the clusters and the variables that affect the crime through the history of the crime. In addition to the traditional OLS model, spatial differential model including spatial autocorrelation and spatial error model were used to select the variables influencing the five major crime rate, the theft rate and the foreign resident rate. The variables affecting the Five major crimes were positive (+) sign for the welfare and the rate of the bar cluster rate, and negative (-) for the street density. The CCTV area occupies 46% of the hotspots based on the overlapping of the areas where the elderly people are crowded, the bar cluster, many multicultural families, and the areas with low density of street lamps. It turned out. Taking into account the current CCTV operation, the total number of new cases to cover the risk point was 89.

• Journal of the Korean Geographical Society
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• v.48 no.6
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• pp.879-896
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• 2013

The assessed land values and housing prices have been widely utilized as a basic information for the land and house trades and for evaluating governmental and local taxes. However, there exists a price difference in actual markets between the assessment level and assessed land values or housing prices. This paper emphasizes the spatial mismatch between the assessed land values and housing market prices and particularly addresses the following two aspects by focusing on spatial effects of the modifiable areal units, which would substantially affect the estimation of the assessed land values and housing prices. First, we examine the spatial distributions of the assessed land values and housing market prices, and the gap between those prices, on the basis of the aggregated spatial units(i.e., aggregation districts). Second, we explore the scale effect of the MAUP(modifiable areal unit problem) generally embedded in estimating the prices of the sampled standard lands and houses, and calibrating the correction index for the land values and housing prices for the individuals. For the application, we analysed the land values and housing prices in Seoul utilizing GIS and statistical software. As a result, some spatial clusters that the housing market prices are significantly higher than the assessed land values were identified at a finer geographic level. Also, it was empirically revealed that the statistical results from the regression of regional variables on the assessed land values for the individuals are significantly affected by the aggregation levels of the spatial units.

• Journal of Cadastre & Land InformatiX
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• v.46 no.2
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• pp.57-77
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• 2016

This paper analysis spatial correlation applying commercial activating factor and categories clusters among have homogeneity in garosu street which are rising commercial issue in residential district. Based on this research we can draw several implications. Firstly, Garosu street are forming unique space around fassion feature like clothes and food and Beverage stores are supporting main functions. secondly, in terms of utilization of semi-public space in individual buildings, main Street are using display goods and put product.Also restaurants and cafes are using public space as terrace seats. These results mean principal road emphasizes displaying and passing but inner road emphasizes taking a break and staying. Third, repetitive action between high rising vacancy and new building cause negative effects city decline and lossing identity. So residents and merchants should cooperate and make communities for sustainable district.

• Journal of the Korean Geographical Society
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• v.48 no.1
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• pp.56-71
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• 2013

The purpose of this study is to examine the spatial distributional characteristics of industries among the Korean cities and to conduct industry classification using the findings. For this purpose, 82 cities in Korea are investigated with respect to 15 industrial sectors. In the analysis, concentration of and association between industries are recognized using both geographic and non-geographic measures. In order to measure concentration and association, locational Gini coefficient, Moran's I, correlation coefficient, and bivatiate Moran are used and 15 industrial sectors are classified based on these estimates. The findings reveal that the chemical sector shows strong geographic and non-geographic concentrations while the assembly, machinery and electronics sector only shows a strong geographic concentration. Printing and publishing, wholesale, and business services show a strong non-geographic association with other sectors. The remaining ten sectors show no explicit distribution patterns among cities. This study contributes to providing the methodology that analyzes the spatial distribution patterns of industries in a comprehensive way and is able to provide useful information in implementing industrial location policies including industrial clusters.

• Journal of The Korean Astronomical Society
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• v.40 no.3
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• pp.67-82
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• 2007

The basic building block of solar filaments/prominences is thin threads of cool plasma. We have studied the spectral properties of velocity threads, clusters of thinner density threads moving together, by analyzing a sequence of $H{\alpha}$ images of a quiescent filament. The images were taken at Big Bear Solar Observatory with the Lyot filter being successively tuned to wavelengths of -0.6, -0.3, 0.0, +0.3, and +0.6 ${\AA}$ from the centerline. The spectra of contrast constructed from the image data at each spatial point were analyzed using cloud models with a single velocity component, or three velocity components. As a result, we have identified a couple of velocity threads that are characterized by a narrow Doppler width($\Delta\lambda_D=0.27{\AA}$), a moderate value of optical thickness at the $H{\alpha}$ absorption peak($\tau_0=0.3$), and a spatial width(FWHM) of about 1". It has also been inferred that there exist 4-6 velocity threads along the line of sight at each spatial resolution element inside the filament. In about half of the threads, matter moves fast with a line-of-sight speed of $15{\pm}3km\;s^{-1}$, but in the other half it is either at rest or slowly moving with a line-of-sight velocity of $0{\pm}3km\;s^{-1}$. It is found that a statistical balance approximately holds between the numbers of blue-shifted threads and red-shifted threads, and any imbalance between the two numbers is responsible for the non-zero line-of-sight velocity determined using a single-component model fit. Our results support the existence not only of high speed counter-streaming flows, but also of a significant amount of cool matter either being at rest or moving slowly inside the filament.