• 한국전산유체공학회:학술대회논문집
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• 1998.05a
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• pp.15-28
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• 1998

As an alternative for solving the incompressible Navier-Stokes equations, we present a vorticity-based integro-differential formulation for vorticity, velocity and pressure variables. One of the most difficult problems encountered in the vorticity-based methods is the introduction of the proper value-value of vorticity or vorticity flux at the solid surface. A practical computational technique toward solving this problem is presented in connection with the coupling between the vorticity and the pressure boundary conditions. Numerical schemes based on an iterative procedure are employed to solve the governing equations with the boundary conditions for the three variables. A finite volume method is implemented to integrate the vorticity transport equation with the dynamic vorticity boundary condition . The velocity field is obtained by using the Biot-Savart integral derived from the mathematical vector identity. Green's scalar identity is used to solve the total pressure in an integral approach similar to the surface panel methods which have been well-established for potential flow analysis. The calculated results with the present mettled for two test problems are compared with data from the literature in order for its validation. The first test problem is one for the two-dimensional square cavity flow driven by shear on the top lid. Two cases are considered here: (i) one driven both by the specified non-uniform shear on the top lid and by the specified body forces acting through the cavity region, for which we find the exact solution, and (ii) one of the classical type (i.e., driven only by uniform shear). Secondly, the present mettled is applied to deal with the early development of the flow around an impulsively started circular cylinder.

• Journal of Korean Society of Forest Science
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• v.107 no.2
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• pp.158-165
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• 2018

Reach-average velocity prediction in steep mountain streams is important for understanding fluvial processes and practical applications of erosion control in mountain streams. little studies have been conducted in reach-average velocity, but hydraulic researches have been carried out to examine the relationship between discharge and reach-average velocity in torrent reaches using a relatively large amount of discharge data. In this study, a total of 87 data were measured in 8 torrent reaches. Salt-dilution method was used to estimate discharge. Reach-average velocity was calculated from harmonic mean of travel time that were measured by salt-dilution technique. In order to exlpore the hydraulic relation, both discharge and velocity were non-dimensionalized by using $D_{50}$, $D_{84}$, ${\sigma}_{pro}$ and $IPR_{90}$. It also indicated that ${\sigma}_{pro}$ and $IPR_{90}$ were good variables as roughness height for develop the relationship between non-dimensional discharge and velocity in mountain streams. Generally, reach-average velocity could increase exponentially as discharge increases.

• The Research Journal of the Costume Culture
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• v.26 no.3
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• pp.282-295
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• 2018

Hair style allows consumers to express their aesthetic sense and individual beauty. However, due to the attributes of hairdressing services and the high expectations of consumers, complaints are increasing rapidly. This study examined the complaint behavior, compensation and hair salon patronage of consumers. Then, a model is presented that explains the complaint behavior for hairstyling, forms of compensation, and hair salon patronage through empirical analysis. This study was conducted by a survey method. A total of 399 questionnaires were used for the analysis. The data were analyzed using SPSS 23.0 and AMOS 23.0 statistical software. The dimension of complaint behavior for hair style included verbal complaints, non-verbal complaints in the salon and private complaints outside the salon. The forms of compensation included re-procedure, psychological, and material compensation. Hair salon patronage was one-dimensional. These results were obtained through exploratory and confirmatory factor analysis. Then the conceptual model was empirically analyzed by covariance structure analysis and obtained in final form through model modification. Verbal complaint behavior positively influenced re-procedure compensation. In addition, non-verbal complaint behavior had positive effects on psychological and material compensation. Hair salon patronage was positively affected by re-procedure and psychological compensation. However, private complaint behavior had a negative effect on hair salon patronage. The direct and indirect effects of the paths among variables were verified by analyzing the mediating effects of different forms of compensations. It is possible to establish differentiated marketing strategies with these findings for consumers with complaint behaviors by considering the forms of compensation.

• Steel and Composite Structures
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• v.37 no.6
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• pp.663-678
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• 2020

This paper proposes a novel topology optimization method generating multiple materials for external linear plane crack structures based on the combination of IsoGeometric Analysis (IGA) and eXtended Finite Element Method (X-FEM). A so-called eXtended IsoGeometric Analysis (X-IGA) is derived for a mechanical description of a strong discontinuity state's continuous boundaries through the inherited special properties of X-FEM. In X-IGA, control points and patches play the same role with nodes and sub-domains in the finite element method. While being similar to X-FEM, enrichment functions are added to finite element approximation without any mesh generation. The geometry of structures based on basic functions of Non-Uniform Rational B-Splines (NURBS) provides accurate and reliable results. Moreover, the basis function to define the geometry becomes a systematic p-refinement to control the field approximation order without altering the geometry or its parameterization. The accuracy of analytical solutions of X-IGA for the crack problem, which is superior to a conventional X-FEM, guarantees the reliability of the optimal multi-material retrofitting against external cracks through using topology optimization. Topology optimization is applied to the minimal compliance design of two-dimensional plane linear cracked structures retrofitted by multiple distinct materials to prevent the propagation of the present crack pattern. The alternating active-phase algorithm with optimality criteria-based algorithms is employed to update design variables of element densities. Numerical results under different lengths, positions, and angles of given cracks verify the proposed method's efficiency and feasibility in using X-IGA compared to a conventional X-FEM.

• The Korean Journal of Applied Statistics
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• v.28 no.6
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• pp.1171-1180
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• 2015

Multidimensional scaling (MDS) is a graphical technique of multivariate analysis to display dissimilarities among individuals into low-dimensional space. We often have two kinds of MDS which are metric MDS and non-metric MDS. Metric MDS can be applied to quantitative data; however, we need additional information about variables because it only shows relationships among individuals. Gower (1992) proposed a method that can represent variable information using trajectories of the pseudo-points for quantitative variables on the metric MDS space. We will call his method a 'replacement method'. However, the trajectory can not be represented even though metric MDS can be applied to binary data when we apply his method to binary data. Therefore, we propose a method to represent information of binary variables using pseudo-points called a 'partition method'. The proposed method partitions pseudo-points, accounting both the rate of zeroes and ones. Our metric MDS using the proposed partition method can show the relationship between individuals and variables for binary data.

• The Korean Journal of Applied Statistics
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• v.34 no.6
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• pp.905-922
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• 2021

Cluster analysis is one of unsupervised learning techniques used for discovering clusters when there is no prior knowledge of group membership. K-means, one of the commonly used cluster analysis techniques, may fail when the number of variables becomes large. In such high-dimensional cases, it is common to perform tandem analysis, K-means cluster analysis after reducing the number of variables using dimension reduction methods. However, there is no guarantee that the reduced dimension reveals the cluster structure properly. Principal component analysis may mask the structure of clusters, especially when there are large variances for variables that are not related to cluster structure. To overcome this, techniques that perform dimension reduction and cluster analysis simultaneously have been suggested. This study proposes probabilistic reduced K-means, the transition of reduced K-means (De Soete and Caroll, 1994) into a probabilistic framework. Simulation shows that the proposed method performs better than tandem clustering or clustering without any dimension reduction. When the number of the variables is larger than the number of samples in each cluster, probabilistic reduced K-means show better formation of clusters than non-probabilistic reduced K-means. In the application to a real data set, it revealed similar or better cluster structure compared to other methods.

• Journal of muscle and joint health
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• v.2 no.1
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• pp.1-16
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• 1995

Coping patterns were investigated in a sample of 126 patients with chronic low back pain by means of self-reported questionnaire. Based on the previous researches, coping pat terns were divided into the active cognitive coping, the active behavioral coping, the passive cognitive coping, and the passive behavioral coping. While all the above coping patterns were used, the passive behavioral coping was found to be used most frequently. Six subgroups were identified by cluster analytic procedure using their scores of the coping scale : active cognitive coper, general active coper, passive behavioral coper, general passive coper, multidimensional coper, and multi dimensional non-coper. Six subgroups were compared regarding locus of control, self-efficacy, pain and demographic variables. Distinct differences appeared among subgroups in internal locus of control, self-efficacy, and pain. General active coper and active cognitive coper had higher internal locus of control, higher self-efficacy, and lower pain. General passive coper and multidimensional non-coper had lower internal locus of control, lower self-efficacy, and higher pain. Passive behavioral coper had higher internal locus of control, lower self-efficacy, and higher pain. It supports the concept of learned helplessness due to prior experiences. Multi dimensional coper had higher internal, higher powerful others, and higher self-efficacy. So it corresponds to 'believer in control' group Identified by Wallston et at(1982). Unexpectedly this group also complained more pain. It could be interpreted in two ways. The more coping methods they use, the more they complain pain ; which is the result of Folkman et al (1986). Or they might be typical 'yea sayers'. These unique groups-passive behavioral coper and multidimensional coper-identified by this study supports the suggestion of Wallston et al(1982), about locus of control : individual's pattern of responses across the three scales may be more predictive than his or her scores on each of the scale seperately. The fact that passive coping was used more than active coping also suggests that self controlled active co ping is encouraged to chronic patients as well as acute patients. And it is necessary to articulate the coping scale and self-efficacy scale. It is also necessary to study the relationship of coping and adjustment by experimental design.

• Journal of Korea Water Resources Association
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• v.51 no.12
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• pp.1273-1284
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• 2018

The flow and bed change were analyzed using the CCHE2D model, which is a two-dimensional numerical model, at a confluence of the Namhan River and Seom River where deposition occurs predominantly after the "Four Major Rivers Restoration Project." The characteristic of the junction is that the tributary of Seom River joined into the curved channel of the main reach of the Namhan River. The CCHE2D model analyzes the non-equilibrium sediment transport, and the adaptation lengths for the bed load and suspended load are important variables in the model. At the target area, the adaptation length for the bed load showed the greatest influence on the river bed change. Numerical simulation results demonstrated that the discharge ratio ($Q_r$) change affected the flow and bed change in the Namhan River and Seom river junction. When $Q_r{\leq}2.5$, the flow velocity of the main reach increased before confluence, thereby reducing the flow separation zone and decreasing the deposition inside the junction. When $Q_r$>2.5, there was a high possibility that deposition would be increased, thereby forming sand bar. Numerical simulation showed that a fixed sand bar has been formed at the junction due to the change of discharge ratio, which occurred in 2013.

• Korean Journal of Radiology
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• v.22 no.1
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• pp.106-117
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• 2021

Objective: To explore the value of magnetic resonance imaging (MRI)-based whole tumor texture analysis in differentiating borderline epithelial ovarian tumors (BEOTs) from FIGO stage I/II malignant epithelial ovarian tumors (MEOTs). Materials and Methods: A total of 88 patients with histopathologically confirmed ovarian epithelial tumors after surgical resection, including 30 BEOT and 58 MEOT patients, were divided into a training group (n = 62) and a test group (n = 26). The clinical and conventional MRI features were retrospectively reviewed. The texture features of tumors, based on T2-weighted imaging, diffusion-weighted imaging, and contrast-enhanced T1-weighted imaging, were extracted using MaZda software and the three top weighted texture features were selected by using the Random Forest algorithm. A non-texture logistic regression model in the training group was built to include those clinical and conventional MRI variables with p value < 0.10. Subsequently, a combined model integrating non-texture information and texture features was built for the training group. The model, evaluated using patients in the training group, was then applied to patients in the test group. Finally, receiver operating characteristic (ROC) curves were used to assess the diagnostic performance of the models. Results: The combined model showed superior performance in categorizing BEOTs and MEOTs (sensitivity, 92.5%; specificity, 86.4%; accuracy, 90.3%; area under the ROC curve [AUC], 0.962) than the non-texture model (sensitivity, 78.3%; specificity, 84.6%; accuracy, 82.3%; AUC, 0.818). The AUCs were statistically different (p value = 0.038). In the test group, the AUCs, sensitivity, specificity, and accuracy were 0.840, 73.3%, 90.1%, and 80.8% when the non-texture model was used and 0.896, 75.0%, 94.0%, and 88.5% when the combined model was used. Conclusion: MRI-based texture features combined with clinical and conventional MRI features may assist in differentitating between BEOT and FIGO stage I/II MEOT patients.

• Journal of the Korean Institute of Gas
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• v.18 no.3
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• pp.53-59
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• 2014

In this study, we suggest a system to build the monitoring model for compressed natural gas (CNG) stations, operated in only non-stationary modes, and perform the real-time monitoring and the abnormality diagnosis using principal component analysis (PCA) that is suitable for processing large amounts of multi-dimensional data among multivariate statistical analysis methods. We build the model by the calculation of the new characteristic variables, called as the major components, finding the factors representing the trend of process operation, or a combination of variables among 7 pressure sensor data and 5 temperature sensor data collected from a CNG station at every second. The real-time monitoring is performed reflecting the data of process operation measured in real-time against the built model. As a result of conducting the test of monitoring in order to improve the accuracy of the system and verification, all data in the normal operation were distinguished as normal. The cause of abnormality could be refined, when abnormality was detected successfully, by tracking the variables out of the score plot.