• 한국디지털정책학회:학술대회논문집
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• 2006.12a
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• pp.327-336
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• 2006

The odds ratio is used for assessing the disease-exposure association, because epidemiological data for case-control of cohort studies are often summarized into 2 ${\times}$ 2 tables. In this paper we define the odds ratio function(ORF) that extends odds ratio used on discrete survival event data to continuous survival time data and propose estimation procedures with censored data. The first one is a nonparametric estimator based on the Nelson-Aalen estimator of comulative hazard function, and the others are obtained using the concept of empirical odds ratio. Asymptotic properties such as consistency and weak convergence results are also provided. The ORF provides a simple interpretation and is comparable to survival function or comulative hazard function in comparing two groups. The mean square errors are investigated via Monte Carlo simulation. The result are finally illustrated using the Melanoma data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.3C
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• pp.157-170
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• 2006

Downhole method is considered as giving a little unreliable Vs profile when the signal to noise ratio(S/N) is low and the travel time information is erroneous although it is economical and ease of operation. Direct method has been applied for obtaining adequate result in this case. But it is difficult to determine optimum result by using direct method which is subjective and considering straight ray path. Therefore, in this paper, Mean Refracted Ray Path Method(MRM) was proposed, which is automated and considering refracted ray path. Artificial travel time data adding some travel time error was generated by forward modeling based on Snell's Law and travel time data was also obtained from numerical signal traces using FEM modelling. Using these travel time data, reliability of MRM was verified in the manner of comparing the results determined by MRM with the model. Finally, proposed method was applied to the real field data and it was considered as improved method for obtaining the optimum result in downhole seismic method.

• Journal of Fisheries and Marine Sciences Education
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• v.17 no.3
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• pp.427-433
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• 2005

The study of Web GUI(Graphic User Information) system for Virtual Reality System is mainly performed on effective methodology which transform real world data to computing world data. MGIS(Marine Geographic Information System) has its own target on reliable data service by acquisition of geometric information using accurate measurement and graphical visualization. This type of raw data visualization can be built without software tools, yet is incredibly useful for interpreting and communicating data. Even simple visualizations can aid in the interpretation of complex 3D relationships that are frequently encountered in the geosciences. The Virtual Reality Modeling Language provides an easy way for geoscientists to construct complex visualizations that can be viewed with free software. This study propose a three dimensional Web GUI system using MGIS-based three dimensional data models and virtual imaging system. Finally, we design a Web GUI system integrating above data models.

• Proceedings of the Korea Concrete Institute Conference
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• 2000.10b
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• pp.1291-1296
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• 2000

A basis for the direct use of data from nondestructive evaluation methods in bridge management systems is presented. Bridge management systems use integer-valued condition ratings to recognize conditions of bridge elements, to model progression of deterioration, and to determine repair needs. Data from nondestructive evaluation methods can inform management systems on the extent of damage, on the initiation of deterioration processes, and on the exposure of bridge elements to aggressive agents. In addition, data obtained through nondestructive evaluation methods allow the formation of models of specific deterioration process. The use of these data in bridge management systems requires redefinition of condition ratings together with the creation of procedures for automated interpretation of data. By these action, nondestructive evaluation methods are directly used to assign condition ratings, and condition ratings are made into terse form of NDE data that are compatible with present day bridge management systems. This paper reports work in progress to strategic use of nondestructive evaluation methods in bridge management system.

• Economic and Environmental Geology
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• v.33 no.2
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• pp.111-116
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• 2000

Indentifying anomaly correlations between data sets is the basis for rationalizig geopotential interpretation and theory. A procedure is presented that constitutes an effective process for identifying correlative features between the two or more geopotential data sets. Anomaly features that show direct, inverse, or no correlations between the data may be separated by applying filters in the frequency domains of the data sets. The correlation filter passes or rejects wavenumbers between co-registered data sets based on the correlation coefficient between common wavenumbers as given by the cosine of their phase difference. This study includes an example of Magsat magnetic anomaly profile that illustrates the usefulness of the procedure for extracting correlative features between the data sets.

• 한국지구물리탐사학회:학술대회논문집
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• 2003.11a
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• pp.340-343
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• 2003

This study presents a practical procedure for the Bayesian inversion of geophysical data by Markov chain Monte Carlo (MCMC) sampling and geostatistics. We have applied geostatistical techniques for the acquisition of prior model information, and then the MCMC method was adopted to infer the characteristics of the marginal distributions of model parameters. For the Bayesian inversion of dipole-dipole array resistivity data, we have used the indicator kriging and simulation techniques to generate cumulative density functions from Schlumberger array resistivity data and well logging data, and obtained prior information by cokriging and simulations from covariogram models. The indicator approach makes it possible to incorporate non-parametric information into the probabilistic density function. We have also adopted the MCMC approach, based on Gibbs sampling, to examine the characteristics of a posteriori probability density function and the marginal distribution of each parameter. This approach provides an effective way to treat Bayesian inversion of geophysical data and reduce the non-uniqueness by incorporating various prior information.

• Communications for Statistical Applications and Methods
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• v.8 no.3
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• pp.643-650
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• 2001

Some classical plots like scatterplot matrices and parallel coordinates are valuable tools for data visualization. These tools are extensively used in the modern data mining softwares to explore the inherent data structure, and hence to visually classify or cluster the database into appropriate groups. However, the interpretation of these plots are very sensitive to the arrangement of variables. In this work, we introduce two methods to arrange the variables for data visualization. First method is based on the work of Wegman (1999), and this is to arrange the variables using minimum distance among all the pairwise permutation of the variables. Second method is using the idea of principal components. We Investigate the effectiveness of these methods with parallel coordinates using real data sets, and show that each of the two proposed methods has its own strength from different aspects respectively.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2000.11a
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• pp.103-106
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• 2000

Geophysical data sets from the Chojeong area in the Chungbuk-Do are compositely studied in terms of multi-attribute interpretation for the subsurface mapping of shallow fracture zones, associated with groundwater reservoir. Utilizing a GIS software, the attribute data are implemented to a database; a lineament from the satellite image, electrical resistivities and its standard deviation, radioactivity, seismic velocity, bedrock depth from exploration data. In an attempt to interpret 1-D electrical sounding data in 2-D and 3-D views, 2-D resistivities structures are firstly made by interpolating 1-D plots. Reconstruction of a resistivity volume is found to be an effective scheme for subsurface mapping of shallow fracture zones. Shallow fracture zones in the southeastern part of the study area are commonly correlated in the various exploration data.

• Genomics & Informatics
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• v.16 no.4
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• pp.33.1-33.9
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• 2018

Recently, there have been many studies in medicine related to genetic analysis. Many genetic studies have been performed to find genes associated with complex diseases. To find out how genes are related to disease, we need to understand not only the simple relationship of genotypes but also the way they are related to phenotype. Multi-block data, which is a summation form of variable sets, is used for enhancing the analysis of the relationships of different blocks. By identifying relationships through a multi-block data form, we can understand the association between the blocks in comprehending the correlation between them. Several statistical analysis methods have been developed to understand the relationship between multi-block data. In this paper, we will use generalized canonical correlation methodology to analyze multi-block data from the Korean Association Resource project, which has a combination of single nucleotide polymorphism blocks, phenotype blocks, and disease blocks.

• 한국지구물리탐사학회:학술대회논문집
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• 2007.06a
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• pp.48-53
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• 2007

A new way to integrate various geophysical information for evaluation of RQD was developed. In this study, we did not directly define the RQD value where borehole data are not sampled. Instead, we infer the probability of RQD values with prior probability from borehole direct data, and secondary supporting probability from resistivity and seismic tomography data. For the integration, we applied the geostatstical indicator kriging to get prior probability of RQD value, and indicator kriging with soft data to get the supporting probability from resistivity and seismic data. And we finally use the permanence ratio rule to integrate these information. The finally obtained result was also analyzed to fully utilize the probabilistic features. We show the probability of wrongly classifying the RQD evaluation and vice versa. This result may be used for decision making process based on the geophysical exploration.