• The Korean Journal of Applied Statistics
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• v.30 no.4
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• pp.555-566
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• 2017

For multivariate datasets with large number of variables, classical dimensional reduction methods such as principal component analysis may not be effective for data visualization. The underlying reason is that the dimensionality of the space of variables is often larger than two or three, while the visualization to the human eye is most effective with two or three dimensions. This paper proposes a working procedure which first partitions the variables into several "latent" clusters, explores individual data subsets, and finally integrates findings. We use R pakacage "ClustOfVar" for partitioning variables around latent dimensions and the principal component biplot method to visualize within-cluster patterns. Additionally, we use the technique for embedding supplementary variables to figure out the relationships between within-cluster variables and outside variables.

• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.6
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• pp.1252-1264
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• 1988

Recently industrial robots together with positioners are often used to enhance the system performance for arc welding. In this paper, a redundancy control method is proposed to the robot-positioner system with seven degrees of freedom, where one kinematic modelling technique is employed. Also, manipulability in the given cutting plane of the workspace. An algorithm maximizing the manipulability is applied to the robot and the positioner and the simulation results are shown for the task following a linear path.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.8
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• pp.1774-1779
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• 2005

This paper propose the design method of the constructing the digital logic systems over galois fields using by the galois field decision diagram(GFDD) that is based on the graph theory. The proposed design method is as following. First of all, we discuss the mathematical properties of the galois fields and the basic properties of the graph theory. After we discuss the operational domain and the functional domain, we obtain the transformation matrixes, $\psi$GF(P)(1) and $\xi$GF(P)(1), in the case of one variable, that easily manipulate the relationship between two domains. And we extend above transformation matrixes to n-variable case, we obtain $\psi$GF(P)(1) and $\xi$GF(P)(1). We discuss the Reed-Muller expansion in order to obtain the digital switching functions of the P-valued single variable. And for the purpose of the extend above Reed-Muller expansion to more two variables, we describe the Kronecker product arithmetic operation.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.15 no.1
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• pp.105-116
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• 2002

In this paper, an analytical model to predict the resisting capacity of slender RC columns is introduced. Material and geometric nonlinearities are taken into account, and the layer approach is adopted to simulate the different material properties across the sectional depth. On the basis of the obtained numerical analysis results, an improved design equation as a function of concrete strength, slenderness ratio, steel ratio and eccentricity for slender RC columns, which can be used effectively in the preliminary design stage, is introduced. Finally, P-M interaction diagrams constructed by the introduced equation are compared with the ACI method with the objective of establishing the relative efficiencies of the introduced equation.

• Proceedings of the KIEE Conference
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• 2005.07b
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• pp.1123-1125
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• 2005

본 논문에서는 3차원 공간에 종이와 같은 박막형 유전체가 있을 때 임의의 점에서의 전계$\vec{E}$를 구하기 위해 유전체의 분극벡터$\vec{P}$를 미지수로 하는 경계적분법(Boundary integral method)을 사용한다. 경계적분법의 사용으로 FEM 3차원 해석에 있어서의 요소분할의 난이성 및 계수 행렬의 대형화로 인한 컴퓨터 수행능력의 한계를 극복할 수 있다. 여기서 분극벡터$\vec{P}$를 구하기 위해 전하에서의 전계${ves{E}}_s$에 의한 유전체내의 분극벡터$\vec{P}$를 수식으로 정리하여 $[\vec{K}][\vec{P}]=[\vec{E}]$ 형태의 $\vec{P}$를 미지수로 하는 system matrix를 구성한다. 위의 system matrix 통해 구해진 분극벡터 $\vec{P}$를 이용하여 유전체 밖의 한 점에서의 전계세기 ${\vec{E}}_m$를 구한 후 우리가 구하고자 하는 전계$\vec{E}$를 계산한다.

• Journal of Korean Society of Steel Construction
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• v.12 no.5 s.48
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• pp.527-535
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• 2000

Accurate determination of the relative restraint of beam-to-column connections is important for both the strength and the serviceability of structural frames. But steel frame analysis is carried out under the assumption that the connections are either fixed or pinned. Overestimating the connection restraint can result in underestimating lateral sway and underestimating the connection restraint can lead to underestimating forces developed in the beams and columns. This implies that the exact stiffness of connections as well as the geometric effects should be considered in the frame analysis and the overall behavior of connections could be described adequately. Therefore, the stiffness matrix which is able to consider the moment-rotation of connection was derived previously and the modified exponential model, power model and the proposed log model are adopted for modeling the semi-rigid connections. The main purpose of this study is to examine the feasibility of the derived stiffness matrix and to show the validity of log model proposed.

• The Journal of the Korea Contents Association
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• v.18 no.1
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• pp.173-184
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• 2018

In human walking, muscle co-contraction which produces simultaneous activities of multiple muscles is important in motor control mechanism of the central nervous system. This study aims to understand positive and negative covariation mechanism of inter-muscle activities during walking. In this study, we measured electromyography (EMG) in leg muscles. To identify motor modules, we recored EMG from 4 leg muscles bilaterally (the tibialis anterior, medial gastrocnemius, rectus femoris and medial hamstring muscles) and performed non-negative matrix factorization (NMF) and principa component analysis (PCA). Then, we computed covariation values from various combinations between muscles or motor modules and used two-way repeated measures analysis of variance to identify significantly different covariation patterns between muscle combinations. As the results, we found significant differences between covariation values of muscle combinations (p < 0.05). muscle groups within the same motor modules produced the positive covariations. However, there were strong negative covariation between motor modules. There was negative covariation in all muscle combination. Stable inter-module negative covariation suggests that motor modules may be the control unit in the complex motor coordination.

• Journal of the Korean Geotechnical Society
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• v.21 no.4
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• pp.145-154
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• 2005

Love wave and Rayleigh wave are the major elastic waves belonging to the category of the surface wave. Those waves are used to determine the ground stiffness profile using their dispersion characteristics. The fact that Love wave is not contaminated by P-wave makes Love wave superior to Rayleigh wave and other body waves. Therefore, the information that Love wave carries is more distinct and clearer than that of others. Based on theoretical research, the joint inversion analysis that uses the dispersion information of both Love and Rayleigh wave was proposed. This analysis consists of the forward modeling using transfer matrix, the sensitivity matrix for evaluating the ground system and DLSS (Damped Least Square Solution) as an inversion technique. The technique of joint inversion uses the dispersion characteristics of Love wave and Rayleigh wave simultaneously making the sensitivity matrix. The sensitivity matrix was used for inversion analysis repeatedly to find the approximate ground stiffness profile. The purpose of the joint inversion analysis is to improve accuracy and convergency of inversion results by utilizing that frequency contribution of each wave is different.

• Communications for Statistical Applications and Methods
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• v.18 no.3
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• pp.377-389
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• 2011

A higher quality level is generally perceived by customers as improved performance by assigning a correspondingly higher satisfaction score. The third generation index $C_{pmk}$ is more powerful than two useful indices $C_p$ and $C_{pk}$ that have been widely used in six sigma industries to assess process performance. In actual manufacturing industries, process capability analysis often entails characterizing or assessing processes or products based on more than one engineering specification or quality characteristic. Since these characteristics are related, it is a risky undertaking to represent the variation of even a univariate characteristic by a single index. Therefore, the desirability of using vector-valued process capability index(PCI) arises quite naturally. In this paper, we consider more powerful vector-valued process capability index $C_{pmk}$ = ($C_{pmkx}$, $C_{pmky}$)$^t$ that consider the univariate process capability index $C_{pmk}$. First, we examine the process capability index $C_{pmk}$ and plug-in estimator $\hat{C}_{pmk}$. In addition, we derive its asymptotic distribution and variance-covariance matrix $V_{pmk}$ for the vector valued process capability index $C_{pmk}$. Under the assumption of bivariate normal distribution, we study asymptotic confidence regions of our vector-valued process capability index $C_{pmk}$ = ($C_{pmkx}$, $C_{pmky}$)$^t$.

• Journal of the Korean Geotechnical Society
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• v.21 no.6
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• pp.19-30
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• 2005

A coupled three-dimensional pile group analysis method was developed by considering complex behavior of sub-structures (pile-soil-cap) which included soil nonlinearity and the behavior of super-structure (pier). As an intermediate analysis method between FBPier 3.0 and Group 0.0, it took advantages of each method. Among the components of a pile group, individual piles were modeled with stiffness matrices of pile heads and soils with nonlinear load-transfer curves (t-z, q-z and p-y curves). A pile cap was modeled with modified four-node flat shell elements and a pier with three-dimensional beam element, so that a unified analysis could be possible. A nonlinear analysis method was proposed in this study with a mixed incremental and iteration techniques. The proposed method for a pile group subjected to axial and lateral loads was compared with othe. analytical methods (i.e., Group 6.0 and FBPier 3.0). It was found that the proposed method could predict the complex behavior of a pile group well, even though piles were modelled simply in this study by using pile head stiffness matrices which were different from the method introduced in FBPier 3.0.