• Proceedings of the Korean Society of Applied Entomolohy Conference
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• 2005.05a
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• pp.92-92
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• 2005

• 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 Korean Journal of Applied Statistics
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• v.17 no.2
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• pp.327-336
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• 2004

Many researchers have used the robust variogram to reduce the effect of outliers in spatial data analysis. Recently it is known that estimating the variogram after replacing outliers is more efficient. In this paper, we suggest a new data cleaner for geostatistic data analysis and compare the efficiency of outlier cleaners.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.495-504
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• 2015

The Gaussian geostatistical model has been widely used for modeling spatial data. However, this model suffers from a severe difficulty in computation because inference requires to invert a large covariance matrix in evaluating log-likelihood. In addressing this computational challenge, three strategies have been employed: likelihood approximation, lower dimensional space approximation, and Markov random field approximation. In this paper, we reviewed statistical approaches attacking the computational challenge. As an illustration, we also applied integrated nested Laplace approximation (INLA) technology, one of Markov approximation approach, to real data to provide an example of its use in practice dealing with large spatial data.

• Journal of the Korea Society of Computer and Information
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• v.21 no.8
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• pp.1-12
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• 2016

In this paper, we propose a very efficient reversible data hiding algorithm using spatial locality and the surface characteristics of image. Spacial locality and a variety of surface characteristics are present in natural images. So, it is possible to precisely predict the pixel value using the locality and surface characteristics of image. Therefore, the frequency is increased significantly at the peak point of the difference histogram using the precisely predicted pixel values. Thus, it is possible to increase the amount of data to be embedded in image using the spatial locality and surface characteristics of image. By using the proposed reversible data hiding algorithm, visually high quality stego-image can be generated, the embedded data and the original cover image can be extracted without distortion from the stego-image, and the embedding data are much greater than that of the previous algorithm. The experimental results show the superiority of the proposed algorithm.

• Journal of Animal Environmental Science
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• v.7 no.1
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• pp.45-56
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• 2001

The following statistics are the results of a survey that analyzed the classification of livestock area and spatial mobility based upon the number of livestock and an area of 151 towns and cities from 1975 to 1995. 1. As a results of analysis about the degree of location concentration using C.V., Korean native cattles (HanWoo) and swines are becoming more centralized while dairies and chickens are becoming decentralized. 2. 49 regions, that is 32.5%, were classified as growing regions, 30 regions (19.9%) were stagnant regions and 72 regions (47.7%) were withering regions. The classification was based upon the calculation according to the numbers of converted grown animals and growth index. Kyonggi-do and Chungchongnam-do, specifically, took up 26.6% and 24.5% of the developing regions which shows that these two regions are the dominant regions for livestock. 3. Kyongsangbuk-do and Chungchongnam-do play significant roles for overall livestock, and Chollanam-do is considering a transition from swines to Korean native cattles and Kyongsangbuk-do is shifting from Korean native cattles to swines.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.738-739
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• 2015

The main objective of this study, "Spatial Downscaling of Precipitation from GCMs for Assessing Climate Change over Han River and Imjin River Watersheds", is to carry out over Han River and Imjin River watersheds. To this end, a statistical regression method with MOS (Model Output Statistics) corrections at every downscaling step was developed and applied for downscaling the spatially-coarse Global Climate Model Projections (GCMPs) from CCSM3 and CSIRO with respect to precipitation into 0.1 degree (about 11 km) spatial grid over study regions. The spatially archived hydro-climate data sets such as Willmott, GsMap and APHRODITE datasets were used for MOS corrections by means of monthly climatology between observations and downscaled values. Precipitation values downscaled in this study were validated against ground observations and then future climate simulation results on precipitation were evaluated for the projections.

• Journal of the Korean association of regional geographers
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• v.16 no.5
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• pp.590-609
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• 2010

The purpose of the study is to propose and evaluate Exploratory Spatial Data Analysis(ESDA) methods for examining age-specific population migration characteristics. First, population migration pyramid which is a pyramid-shaped graph designed with in-migration, out-migration, and net migration by age (or age group), was developed as a tool exploring age-specific migration propensities and structures. Second, various spatial statistics techniques based on local indicators of spatial association(LISA) such as Local Moran''s $I_i$, Getis-Ord ${G_i}^*$, and AMOEBA were suggested as ways to detect spatial dusters of age-specific net migration rate. These ESDA techniques were applied to age-specific population migration of Daegu Metropolitan City. Application results demonstrated that suggested ESDA methods can effectively detect new information and patterns such as contribution of age-specific migration propensities to population changes in a given region, relationship among different age groups, hot and cold spot of age-specific net migration rate, and similarity between age-specific spatial clusters.

• Journal of Korean Society for Geospatial Information Science
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• v.15 no.1 s.39
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• pp.23-29
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• 2007

Spatial outliers in remotely sensed imagery represent observed quantities showing unusual values compared to their neighbor pixel values. There have been various methods to detect the spatial outliers based on spatial autocorrelations in statistics and data mining. These methods may be applied in detecting forest fire pixels in the MODIS imageries from NASA's AQUA satellite. This is because the forest fire detection can be referred to as finding spatial outliers using spatial variation of brightness temperature. In this paper, we propose a new forest fire detection algorithm which is based on local spatial association analysis, and test the proposed algorithm to evaluate its applicability. In order to evaluate the proposed algorithm, the results were compared with the MODIS fire product provided by the NASA MODIS Science Team, which showed the possibility of the proposed algorithm in detecting the fire pixels.

• The Bulletin of The Korean Astronomical Society
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• v.42 no.1
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• pp.56.1-56.1
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• 2017

When turbulent motions perturb magnetic field lines and produce magnetic fluctuations, the perturbations leave imprints of turbulence statistics on magnetic field. Observation of synchrotron radiation is one of the easiest ways to study turbulent magnetic field. Therefore, we study statistical properties of synchrotron polarization emitted from media with magnetohydrodynamic (MHD) turbulence, using both synthetic and MHD turbulence simulation data. First, we obtain the spatial spectrum and its derivative with respect to wavelength of synchrotron polarization arising from both synchrotron radiation and Faraday rotation. The study of spatial spectrum shows how the spectrum is affected by Faraday rotation and how we can recover the statistics of underlying turbulent magnetic field as well as turbulent density of electrons from interferometric observations that incorporate the effects of noise and finite telescopic beam size. Second, we study quadrupole ratio to quantitatively describe the degree of anisotropy introduced by magnetic field in the presence of MHD turbulence. We consider the case that the synchrotron emission and Faraday rotation are spatially separated, as well as the situation that the sources of the synchrotron radiation and thermal electrons causing Faraday rotation exist in the same region. In this study, we demonstrate that the spectrum and quadrupole ratio of synchrotron polarization can be very informative tools to get detailed information about the statistical properties of MHD turbulence from radio observations of diffuse synchrotron polarization.