• Journal of the Korean Data and Information Science Society
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• v.9 no.1
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• pp.63-70
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• 1998

The singular value decomposition is a tool which is used to find a linear structure of reduced dimension and to give interpretation of the lower dimensional structure about multivariate data. In this paper the singular value decomposition is reviewed from both algebraic and geometric point of view and, is illustrated the way which the tool is used in the multivariate techniques finding a simpler geometric structure for the data.

• Journal of Intelligence and Information Systems
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• v.10 no.1
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• pp.27-45
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• 2004

While on-line shopping is increasing, the "Consumer Protection Law in Electronic Commerce" obliges each internet shopping mall to provide its business information. Although most internet shopping malls provide their business information in the semi-structured format on the bottom of their homepages, the attributes and expression forms of business information are different each other. It makes consumers difficult to identify their business information and lowers public confidence. Hence this study proposes three approaches - HTML-based structure, XML-based structure, and XML data island-based structure - to structuralizing business information for correct expression. The experiment results showed that the business information extraction time by XML data island-based structure is independent of the size of the web document, while the time by HTML-based structure is dependent on the size. By comparing the business information extraction times, we show that XML data island-based structure is more efficient and effective than HTML-based structure.structure.

• Proceedings of the KIEE Conference
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• 2006.10c
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• pp.521-523
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• 2006

This paper proposes an algorithm and its data structure to support real-time full-text search for the streamed or broadcasted multimedia data containing real-time stenograph text. Since the traditional indexing method used at information retrieval area uses the linguistic information, there is a heavy cost. Therefore, we propose the algorithm and its data structure based on suffix array, which is a simple data structure and has low space complexity. Suffix array is useful frequently to search for huge text. However, subtitle text of multimedia data is to get longer by time. Therefore, suffix array must be reconstructed because subtitle text is continually changed. We propose the data structure called prefix array and search algorithm using it.

• Communications for Statistical Applications and Methods
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• v.21 no.6
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• pp.521-528
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• 2014

A stochastic Gompertz diffusion model for tumor growth is a topic of active interest as cancer is a leading cause of death in Korea. The direct maximum likelihood estimation of stochastic differential equations would be possible based on the continuous path likelihood on condition that a continuous sample path of the process is recorded over the interval. This likelihood is useful in providing a basis for the so-called continuous record or infill likelihood function and infill asymptotic. In practice, we do not have fully continuous data except a few special cases. As a result, the exact ML method is not applicable. In this paper we proposed a method of parameter estimation of stochastic Gompertz differential equation via Markov chain Monte Carlo methods that is applicable for several data structures. We compared a Markov transition data structure with a data structure that have an initial point.

• Journal of Korea Multimedia Society
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• v.8 no.6
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• pp.827-835
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• 2005

In this paper, self-networking and replaceable structure in vector graphics contents are presented for wireless internet service. The wireless networks over 2G or 3G are limited in the sense of the speed and the cost. Considering these characteristics of wireless network, self-networking method and replaceable structure in downloaded contents are introduced in order to save the amount of data and provide variations for contents. During the display of contents, a certain data for the contents is downloaded from the server and it is managed appropriately for the operation of the contents. The downloaded materials are reflected to the original contents using replaceable structure. Also, the downloading and modification are independent of the play. In this implementation, the data consists of control data for control and resource data for image, sound or text. Comparing to the conventional methods which download the whole data, the amount of the transmitted data is very small since only the difference is downloaded. Also, during the play of the contents, the changes are adopted immediately. The whole functions are implemented in wireless handset and the various applications are discussed.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.689-698
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• 2020

The aim of this article is to determine the influence of factors on the capital structure of construction companies listed on the Hanoi Stock Exchange. The data of the article were collected and calculated from the financial statements of 54 construction companies listed on Hanoi Stock Exchange from 2012 to 2019. With the application of E-view software in quantitative analysis to build panel data regression model (panel data), the article has built a regression model to determine the relationship of intrinsic factors affecting the capital structure of construction companies listed on Hanoi Stock Exchange. In the study, dependent variable is capital structure, determined by the debt-to-equity ratio. Profitability, coefficient of solvency, size, loan interest rate, structure of tangible assets, and growth are independent variables. The results showed that the two factors of growth and firm size positively affect the capital structure, the profitability factor has the opposite effect on capital structure. Factors of short-term debt solvency, average loan interest rate and tangible asset structure have no correlation with capital structure. The findings of this article are useful for business administrators, helping business managers make the right financial decisions to make capital structure decisions in their own conditions.

• Journal of the Korean Data and Information Science Society
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• v.19 no.2
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• pp.577-585
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• 2008

This paper suggests a marginal probability model for analyzing repeated polytomous response data when some factors are nested in others in treatment structures on a larger experimental unit. As a repeated measures factor, time is considered on a smaller experimental unit. So, two different experiment sizes are considered. Each size of experimental unit has its own design structure and treatment structure, and the marginal probability model can be constructed from the structures for each size of experimental unit. Weighted least squares(WLS) methods are used for estimating fixed effects in the suggested model.

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.1013-1021
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• 2003

Huffer and Park (2002) proposed a chi-squared test for multivariate structure. Their test detects the deviation of data from mutual independence or multivariate normality. We will compute the Rao-Robson chi-squared version of the test, which is easy to apply in practice since it has a limiting chi-squared distribution. We will provide a self-contained argument that it has a limiting chi-squared distribution. We study the accuracy in finite samples of the limiting distribution. We finally compare the power of our test with those of other popular normality tests in an application to a real data.

• Journal of the Earthquake Engineering Society of Korea
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• v.7 no.4
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• pp.89-95
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• 2003

In this paper, an algorithm to locate and size damage in a complex truss structure using the time domain response is presented. Sampled response data for specific time interval is spatially expanded over the structure to obtain the mean train energy for each element of the structure. The mean strain energy for each element is, in turn, used to build a damage index that represents the ratio of the stiffness parameter of the pre-damaged to the post-damaged structure. The validity of the methodology is demonstrated using data from a numerical example of a space truss structure with simulated damage. Also in the example, the effects of noisy data on the proposed algorithm are examined by adding random noised to the response data.

• Korean Journal of Remote Sensing
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• v.40 no.2
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• pp.123-139
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• 2024

Forest vertical structure is vital for comprehending ecosystems and biodiversity, in addition to fundamental forest information. Currently, the forest vertical structure is predominantly assessed via an in-situ method, which is not only difficult to apply to inaccessible locations or large areas but also costly and requires substantial human resources. Therefore, mapping systems based on remote sensing data have been actively explored. Recently, research on analyzing and classifying images using machine learning techniques has been actively conducted and applied to map the vertical structure of forests accurately. In this study, Sentinel-2 and digital surface model images were obtained on two different dates separated by approximately one month, and the spectral index and tree height maps were generated separately. Furthermore, according to the acquisition time, the input data were separated into cases 1 and 2, which were then combined to generate case 3. Using these data, forest vetical structure mapping models based on random forest, support vector machine, and extreme gradient boost(XGBoost)were generated. Consequently, nine models were generated, with the XGBoost model in Case 3 performing the best, with an average precision of 0.99 and an F1 score of 0.91. We confirmed that generating a forest vertical structure mapping model utilizing bi-seasonal data and an appropriate model can result in an accuracy of 90% or higher.