• International Journal of Contents
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• v.10 no.1
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• pp.29-35
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• 2014

This paper proposes an approach for visualizing research trends using theme maps and extra information. The proposed algorithm includes the following steps. First, text mining is used to construct a vector space of keywords. Second, correspondence analysis is employed to reduce high-dimensionality and to express relationships between documents and keywords. Third, kernel density estimation is applied in order to generate three-dimensional data that can show the concentration of the set of documents. Fourth, a cartographical concept is adapted for visualizing research trends. Finally, relative vitalization information is provided for more accurate research trend analysis. The algorithm of the proposed approach is tested using papers about Traditional Korean Medicine.

• Journal of computational fluids engineering
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• v.10 no.1
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• pp.45-50
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• 2005

A fundamental understanding of the flow around the wind turbine is important to investigate the performance of new type of wind turbine. This study presents the simulation of three dimensional flow fields around the Darius wind turbine as an example. Incompressible Navier-Stokes equations are used for this simulation. The rotating coordinate system that rotates in the same speed of the turbine is used in order to simplify the boundary condition on the blades. Additionally, the boundary fitted coordinate system is employed in order to express the shape of the blades precisely. Fractional step method is used to solve the basic equations. Third order upwind scheme is chosen for the approximation of the non-linear terms since it can compute the flow field stably even at high Reynolds number without any turbulence models. The flow fields obtained in this study are highly complex due to the three dimensionality and are visualized effectively by using the technique of the computer graphics.

• 한국전산유체공학회:학술대회논문집
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• 2003.10a
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• pp.228-229
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• 2003

Complex flow field around the Darius turbine rotating stationally are simulated by solving the three dimensional incompressible Navier-Stokes equation numerically. The rotating coordinate system is employed so that the boundary conditions on the blades of the rotor become simple. In order to impose the boundary condition on the blades precisely, the boundary fitted coordinate system is employed. Fractional step method is used to solve the basic equations. The complex flow fields due to the three dimensionality of the geometry of the turbine and the rotation of the turbine are obtained and they are visualized effectively by using the technique of the computer graphics.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.21 no.2
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• pp.285-293
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• 1997

Numerical calculations has been performed for the flow and heat transfer to a circular cylinder from a hot circular impinging air jet. The characteristics of the flow and heat transfer are investigated and compared with the two-dimensional flow. The present study lays emphasis on the investigation on the flow and heat transfer of the three-dimensionality. The effects of the buoyancy force and the size of jet are also studied. The noticeable difference between the three and the two-dimensional cases is that there is axial flow of low temperature into the center-plane of the cylinder from the outside in the recirculation region. Local Nusselt number over the cylinder surface has higher value for the large jet as compared with that of the small jet since the energy loss of hot jet to the ambient air decreases with increase of the jet size. As buoyancy force increases the flow accelerates so that the period of cooling by the ambient air is reduced, which results in higher local Nusselt number over the surface.

• Genomics & Informatics
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• v.10 no.4
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• pp.256-262
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• 2012

Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene ($G{\times}G$) interactions. However, the biological interpretation of $G{\times}G$ interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified $G{\times}G$ interactions. The proposed network graph analysis consists of three steps. The first step is for performing $G{\times}G$ interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified $G{\times}G$ interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform $G{\times}G$ interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified $G{\times}G$ interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of $G{\times}G$ interactions.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1331-1339
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• 2013

The lipoprotein lipase (LPL) gene can be considered a functional candidate gene that regulates fatty acid composition. Oh etc (2013) investigated the relationship between unsaturated fatty acids and five novel SNPs, and had confirmed that three polymorphic SNPs (c.322G>A, c.329A>T and c.1591G>A) were associated with fatty acid composition. We have used generalized linear model for adjusted environmental effects and multifactor dimensionality reduction (MDR) method to identify gene-gene interaction effect of statistical model in general. We applied the MDR method on the identify major interaction effects of exonic single nucleotide polymorphisms (SNPs) in the LPL gene for economic traits in Korean cattles population.

• Journal of Digital Convergence
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• v.18 no.2
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• pp.249-259
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• 2020

This study presents a recently obtained social media data set based upon the case study of Electric Vehicles (EV) and looks to implement a sentiment analysis (SA) in order to gain insights. This study uses two methods in order to fully analyze the public's sentiment on EVs. First, we implement a SA tool in which we used to extract the sentiment of comments. Next we labeled the data with these sentiments obtained and classified them. While performing classification we found the problem of dimensionality and also explored the use of feature selection (FS) models in order to reduce the data set's dimensionality. We found that the use of three FS models (Chi Squared, Information Gain and ReliefF) showed the most promising results when used alongside a logistic and support vector machines classification algorithm. the contributions of this paper are in providing an real-world example of social media text analytics which can be adopted in many other areas of research and business. Moving forward researchers can use the methodological approach in this paper to further refine and improve their own case uses in text analytics.

• Geomechanics and Engineering
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• v.9 no.4
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• pp.513-530
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• 2015

Commonly, the base stability of sheeted excavation pits against seepage failure by heave is evaluated by using two-dimensional groundwater flow models and Terzaghi's failure criterion. The objective of the present study is to investigate the effect of three-dimensional groundwater flow on the heave for sheeted excavation pits with various dimensions. For this purpose, the steady-state groundwater flow analyses are performed by using the finite element program ABAQUS 6.12. It has been shown that, in homogeneous soils depending on the ratio of half of excavation width to embedment depth b/D, the ratio of safety factor obtained from 3D analyses to that obtained from 2D analyses $FS_{(3D)}/FS_{(2D)}$ can reach up to 1.56 and 1.34 for square and circular shaped excavations, respectively. As failure body, both an infinitesimal soil column adjacent to the wall (Baumgart & Davidenkoff's criterion) and a three-dimensional failure body with the width suggested by Terzaghi for two-dimensional cases are used. It has been shown that the ratio of $FS_{(Terzaghi)}/FS_{(Davidenkoff)}$ varies between 0.75 and 0.94 depending on the ratio of b/D. Additionally, the effects of model size, the shape of excavation pit and anisotropic permeability on the heave are studied. Finally, the problem is investigated for excavation pits in stratified soils, and important points are emphasized.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.10B
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• pp.1111-1116
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• 2009

In this paper, we discuss distortion-tolerant pattern recognition using computational integral imaging reconstruction. Three-dimensional object information is captured by the integral imaging pick-up process. The captured information is numerically reconstructed at arbitrary depth-levels by averaging the corresponding pixels. We apply Fisher linear discriminant analysis combined with principal component analysis to computationally reconstructed images for the distortion-tolerant recognition. Fisher linear discriminant analysis maximizes the discrimination capability between classes and principal component analysis reduces the dimensionality with the minimum mean squared errors between the original and the restored images. The presented methods provide the promising results for the classification of out-of-plane rotated objects.

• Management Science and Financial Engineering
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• v.14 no.2
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• pp.1-12
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• 2008

This study explores several donor location strategies and discusses experiment results, which contributes to the saving of time and effort required in designing data fusion processes. In particular, three concepts are introduced. The Mahalanobis distance is applied to locate the nearest neighbors more effectively; which incorporates the covariance structure of attributes. The ideal point helps reduce the dimensionality problem that arises in conjoint-type experiments. The correspondence analysis is used to derive the coordinates from non-metric attributes. The Monte Carlo simulation results show that the proposed donor location strategies provide better fusion performance, compared to the currently-in-use methods.