• Communications for Statistical Applications and Methods
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• v.16 no.5
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• pp.851-858
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• 2009

In the last decades, there has been much interest in climate variability because its change has dramatic effects on humanity. Especially, the precipitation data are measured over space and their spatial association is so complicated. So we should take into account such a spatial dependency structure while analyzing the data. However, in linear models for analyzing the data, data sets show severely skewed distribution. In the paper, we consider the Box-Cox transformation to satisfy the normal distribution prior to the analysis, and employ a Bayesian hierarchical framework to investigate the spatial patterns. The data set we considered is monthly average precipitation of the third quarter of 2007 obtained from 347 automated monitoring stations in Contiguous South Korea.

• Journal of KIISE
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• v.42 no.2
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• pp.162-168
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• 2015

Image data is mostly stored in compressed form because of its huge size. Therefore, a series of cumbersome procedures is required to apply a transformation to image data: decompression, extraction of spatial data, transformation and recompression. In this paper, we employ DCT(Discrete Cosine Transform) coefficients to change the spatial presentation of images. DCT is commonly used in still image compression standards such as JPEG and moving picture compression standards such as MPEG-2, MPEG-4, and H.264. In this paper, we derived mathematically the relationship between the geometry transformation in the spatial domain and coefficient changes in the DCT domain and verified it with images in the JPEG file format. Because of the efficiency of transformation in the frequency domain, our findings can be utilized for light-weight partial image encryption for privacy data protection or entertainment contents protection.

• Communications for Statistical Applications and Methods
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• v.11 no.1
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• pp.189-196
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• 2004

The sensitivity of the multivariate Box-Cox transformation model to simultaneous perturbations of all the data based on the likelihood displacement is studied in order to detect outliers. An example is given for illustration.

• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.527-530
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• 1998

In this paper, a transformation-based English part of speech tagging system is designed and implemented. The tagging system tags raw corpus at first and the transformation rule correct the errors. Apart from traditional rule based tagging system, this system makes rules automatically. Using 60,000 words of corpus as a training corpus, the transformation rules are generated automatically by iterative training. The idea how to calculate positive effect of transformation and select transformation rules is proposed to generate more effective and correct transformations. In this paper, part of the Brown corpus and English text is used for experimental data. And the performance of transformation based tagging system is demonstrated by the calculation of accuracy.

• Journal of Digital Contents Society
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• v.5 no.3
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• pp.180-186
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• 2004

XML has an essential funtion of dealing with standardized document to be used in all academic areas and industrial areas as well as e-commerce. The transformation of XML data into Relation Database table is also necessary for data search using SQL language. Mapping relation between XMLand Table in Relation Database is required for transformation of XML. This arti치e studies the mapping relation between XML and Relation Database using DTD which enables to check the unity automatically whenever document is read so that it studied mapping design for the transformation of XML data info Relation Database table.

• The Korean Journal of Applied Statistics
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• v.6 no.2
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• pp.253-263
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• 1993

Recent interest in Taguchi's methods have led to developments of joint modelling of the mean and dispersion in generalized linear models. Since a single data transformation cannot produce all the necessary conditions for an analysis, for the analysis of the Taguchi data, the use of the generalized linear models is preferred to a commonly used data transformation method. In this paper, we will illustrate this point and provide GLIM macros to implement the joint modelling of the mean and dispersion in generalized linear models.

• Journal of the Korean Data and Information Science Society
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• v.15 no.3
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• pp.617-624
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• 2004

In this article the fuzzy number rank and the fuzzy rank transformation method are introduced in order to analyse the non-parametric fuzzy regression model which cannot be described as a specific functional form such as the crisp data and fuzzy data as a independent and dependent variables respectively. The effectiveness of fuzzy rank transformation methods is compared with other methods through the numerical examples.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2007.04a
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• pp.59-63
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• 2007

Each country uses its own datum which well represent its topography. The uses of the space technology such as GPS and the effort of establishing the consistent data over the world, Korea changed the survey act to use a world geodetic system from January 1, 2007. In this study, spatial analysis carried out to transform the GIS DB of electric power distribution system based on the old Tokyo datum the new world geodetic system, KGD 2002. Based on the study, problems on the transformation had been identified and efficient solutions are suggested. The data used for the 7 parameter similarity transformation in this study is the blueprints of the electric equipment and base maps. It is expected that this study provide general scheme and procedure for efficient GIS DB transformation to the new world geodetic system.

• Economic and Environmental Geology
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• v.18 no.3
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• pp.217-224
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• 1985

A Householder's transformation is applied to the resistivity inversion problem. The conventional resistivity inversion method is sometimes numerically unstable in interpreting a resistivity sounding data because it usually solves the normal equation derived from an observation equation. The resistivity inversion method using Householder's transformation solves the observation equation directly, so that it is numerically more stable than the conventional method. A theoretical, ill-conditioned Schlumberger sounding data was chosen to test the inversion scheme with Householder's transformation.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.195-205
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• 2005

In decision tree analysis, C4.5 and CART algorithm have some problems of computational complexity and bias on variable selection. But QUEST algorithm solves these problems by dividing the step of variable selection and split point selection. When input variables are continuous, QUEST algorithm uses ANOVA F-test under the assumption of normality and homogeneity of variances. In this paper, we investigate the influence of violation of normality assumption and effect of the transformation of variables in the QUEST algorithm. In the simulation study, we obtained the empirical powers of variable selection and the empirical bias of variable selection after transformation of variables having various type of underlying distributions.