• Journal of Oral Medicine and Pain
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• v.41 no.2
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• pp.41-47
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• 2016

Purpose: The purpose of this study was to analyze the size and morphology of mandibular condyle and mandibular fossa between temporomandibular joint (TMJ) disc displacement (DD) patients and healthy subjects using cone-beam computed tomography (CBCT). Methods: Twenty healthy subjects and twenty TMJ DD patients participated in this study respectively. We made five measurements in mandibular condyle (medio-lateral dimension, antero-posterior dimension, condyle height, intercondylar distance and intercondylar angle) and two measurements in mandibular fossa (mandibular fossa depth and articular eminence angle) using CBCT image. Results: There was no difference between two groups in medio-lateral dimension. In case of antero-posterior dimension, average of healthy controls was larger than that of TMJ DD patients, but that was not significant statistically. There were no significant differences between two groups in condyle height. Comparing intercondylar distance and intercondylar angle between two groups, there was no significant difference between two groups. In comparison of mandibular fossa depth and articular eminence angle, there was no significant difference between two groups. Conclusions: We couldn't find any definite relationship between TMJ morphology and TMJ DD.

• Kyungpook Mathematical Journal
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• v.48 no.1
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• pp.37-43
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• 2008

The aim of the present paper is to introduce the concept "Finite dimension" in the theory of associative rings R with respect to two sided ideals. We obtain that if R has finite dimension on two sided ideals, then there exist uniform ideals $U_1,U_2,\ldots,U_n$ of R whose sum is direct and essential in R. The number n is independent of the choice of the uniform ideals $U_i$ and 'n' is called the dimension of R.

• Journal of the Korean Mathematical Society
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• v.36 no.3
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• pp.633-648
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• 1999

In this paper, for any two bipartite ordered sets P and Q, we define the convolution P * Q of P and Q. For dim(P)=s and dim(Q)=t, we prove that s+t-(U+V)-2 dim(P*Q) s+t-(U+V)+2, where U+V is the max-mn integer of the certain realizers. In particular, we also prove that dim(P)=n+k- {{{{ { n+k} over {3 } }}}} for 2 k n<2k and dim(Pn ,k)=n for n 2k, where Pn,k=Sn*Sk is the convolution of two standard ordered sets Sn and Sk.

• Wind and Structures
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• v.29 no.6
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• pp.389-403
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• 2019

In this study, two original spectral representations of stationary stochastic fields, say the continuous proper orthogonal decomposition (CPOD) and the frequency-wavenumber spectral representation (FWSR), are derived from the Fourier-Stieltjes integral at first. Meanwhile, the relations between the above two representations are discussed detailedly. However, the most widely used conventional Monte Carlo schemes associated with the two representations still leave two difficulties unsolved, say the high dimension of random variables and the incompleteness of probability with respect to the generated sample functions of the stochastic fields. In view of this, a dimension-reduction model involving merely one elementary random variable with the representative points set owing assigned probabilities is proposed, realizing the refined description of probability characteristics for the stochastic fields by generating just several hundred representative samples with assigned probabilities. In addition, for the purpose of overcoming the defects of simulation efficiency and accuracy in the FWSR, an improved scheme of non-uniform wavenumber intervals is suggested. Finally, the Fast Fourier Transform (FFT) algorithm is adopted to further enhance the simulation efficiency of the horizontal stochastic wind velocity fields. Numerical examplesfully reveal the validity and superiorityof the proposed methods.

• Korean Journal of Cognitive Science
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• v.21 no.1
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• pp.127-143
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• 2010

This study explores children's sex differences of emotion discrimination from facial expressions based on two dimensional model of emotion. The study group consisted of 92 children, of 40, 52, and 64 months of age, and the rate of male and female children was male children (50%) and female children (50%). Children of 92 were required to choose facial expressions related the twelve emotion terms. Facial expressions applied for experiment are used the photographs rated the degree of expression in each of the two dimensions (pleasure-displeasure dimension and arousal-sleep dimension) on a nine-point scale from 54 university students. The experimental findings appeared that the sex differences were distinctly the arousal-sleep dimension than the pleasure-displeasure dimension. In the arousal-sleep dimensionoussleepness, anger, comfort, and loneliness' emotions showed large sex differences over 1 value. Especially, while male children showed high arousal more than female children in the emotions like 'sleepiness, anger and loneliness', female children showed high arousal more than male children in 'comfort' emotion.

• Journal of the Chungcheong Mathematical Society
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• v.21 no.4
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• pp.527-532
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• 2008

We compare a coding space which has an ultra metric with the unit interval which has an associated generalized dyadic expansion. The two spaces are not homeomorphic but dimensionally equivalent in the sense that the Hausdorff and packing dimensions of the corresponding distribution sets in the two spaces coincide.

• Proceedings of the Korean Society of Tribologists and Lubrication Engineers Conference
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• 1998.10a
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• pp.115-123
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• 1998

The morphological analysis of wear particle is a very effective means for machine condition monitoring and fault diagnosis. In order to describe morphology of various wear particle, the wear test was carried out under different experimental conditions. And fractal descriptors was applied to boundary and surface of wear particle with image processing system. These descriptors to analyze shape and surface wear particle are shape fractal dimension and surface fractal dimension. The shape fractal dimension can be derived from the boundary profile and surface fractal dimension can be determined by sum of intensity difference of surface pixel. The morphology of wear particles can be effectively obtained by two fractal dimensions.

• Communications for Statistical Applications and Methods
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• v.23 no.2
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• pp.93-103
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• 2016

In the paper, we discuss dimension reduction of predictors ${\mathbf{X}}{\in}{{\mathbb{R}}^p}$ in a regression of $Y{\mid}{\mathbf{X}}$ with a notion of sufficiency that is called sufficient dimension reduction. In sufficient dimension reduction, the original predictors ${\mathbf{X}}$ are replaced by its lower-dimensional linear projection without loss of information on selected aspects of the conditional distribution. Depending on the aspects, the central subspace, the central mean subspace and the central $k^{th}$-moment subspace are defined and investigated as primary interests. Then the relationships among the three subspaces and the changes in the three subspaces for non-singular transformation of ${\mathbf{X}}$ are studied. We discuss the two conditions to guarantee the existence of the three subspaces that constrain the marginal distribution of ${\mathbf{X}}$ and the conditional distribution of $Y{\mid}{\mathbf{X}}$. A general approach to estimate them is also introduced along with an explanation for conditions commonly assumed in most sufficient dimension reduction methodologies.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2000.11a
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• pp.81-84
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• 2000

Two-layer aquifer system with fractional flow dimension is composed of contiguous two layers: Layer 1 (lower layer) and Layer 2 (upper layer) with different permeability and specific storage each other. For this aquifer system, we assume that groundwater flow originates only from Layer 1 on the pumping well. The aquifer system considers wellbore storage and skin effects on the pumping well. Dimensionless drawdown curves for different flow dimensions are analyzed for different lambda (λ, crossflow coefficient) values, kappa ($textsc{k}$, permeability ratio between Layer 1 and Layer 2) values and omega ($\omega$, storativity ratio between Layer 1 and Layer 2) values. The curves for Layer 1 and Layer 2 show characteristic trend each other.

• Communications for Statistical Applications and Methods
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• v.29 no.5
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• pp.615-627
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• 2022

Principal Fitted Component (PFC) is a semi-parametric sufficient dimension reduction (SDR) method, which is originally proposed in Cook (2007). According to Cook (2007), the PFC has a connection with other usual non-parametric SDR methods. The connection is limited to sliced inverse regression (Li, 1991) and ordinary least squares. Since there is no direct comparison between the two approaches in various forward regressions up to date, a practical guidance between the two approaches is necessary for usual statistical practitioners. To fill this practical necessity, in this paper, we newly derive a connection of the PFC to covariance methods (Yin and Cook, 2002), which is one of the most popular SDR methods. Also, intensive numerical studies have done closely to examine and compare the estimation performances of the semi- and non-parametric SDR methods for various forward regressions. The founding from the numerical studies are confirmed in a real data example.