• 구강회복응용과학지
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• 제18권3호
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• pp.185-195
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• 2002

Purpose This article describes the historic and clinical aspects of the determination of the vertical dimension of occlusion and the synoptic procedure of the determination of the vertical dimension of occlusion in complete denture. The determining procedure of the susceptible vertical dimension of occlusion is one of the most important steps in construction of complete denture and prosthodontic treatment. It is considered essential for the improvement and the recovery of facial esthetics and stomatognathic functions. Results Several methods have been suggested for measurement of the vertical dimension of occlusion in the construction of complete denture and the prosthodontic rehabilitation. These range from pre-extraction records to the use of physiologic rest position, swallowing, phonetics, esthetics and facial proportion, etc. But, there is no universally accepted or completely accurate method. There seems to be no significant advantages of one technique other than those of cost, time and equipment requirements, and seems to be in controversial in determining the vertical dimension. Conclusion The vertical dimension of occlusion should be determined and reinspected carefully by dentist for a successful prosthesis with several methods. The more investigations are necessary for more objective and scientific techniques in determining the vertical dimension of occlusion.

• 대한치과보철학회지
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• 제60권4호
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• pp.301-312
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• 2022

광범위한 전악 보철 수복 시 적절한 교합 수직 고경(occlusal vertical dimension)의 설정은 성공적인 치료를 위해 매우 중요한 단계이자 치료의 시작점이 된다. 수직 고경의 변경을 통한 술식은 치료가 침습적일 수 있으며, 환자 및 임상의들의 많은 시간과 비용, 노력을 필요로 하기 때문에, 진단 및 치료 진행 과정에 다각적인 분석과 심도 깊은 고찰이 필수적이다. 본 논문에서는 선행 문헌들의 검토를 통해 수직 고경의 개념과 관련된 여러 쟁점들에 대해 정리하고, 다양한 수직 고경 평가법들을 정리하여 전악 구강 회복 치료 시 적절한 수직 고경을 설정하기 위한 임상적 방법과 이에 대한 근거를 제시하고자 한다.

• 대한수학회보
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• 제51권2호
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• pp.519-530
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• 2014

Let (R,m) be a Noetherian local ring and M a finitely generated R-module. For an integer s > -1, we say that M is Cohen-Macaulay in dimension > s if every system of parameters of M is an M-sequence in dimension > s introduced by Brodmann-Nhan [1]. In this paper, we give some characterizations for Cohen-Macaulay modules in dimension > s in terms of the Noetherian dimension of the local cohomology modules $H^i_m(M)$, the polynomial type of M introduced by Cuong [5] and the multiplicity e($\underline{x}$;M) of M with respect to a system of parameters $\underline{x}$.

• 한국윤활학회:학술대회논문집
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• 한국윤활학회 1998년도 제28회 추계학술대회
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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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• 제31권2호
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• pp.179-189
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• 2024

In multivariate regression with a high-dimensional response Y ∈ ℝ^r and a relatively low-dimensional predictor X ∈ ℝ^p (where r ≥ 2), the statistical analysis of such data presents significant challenges due to the exponential increase in the number of parameters as the dimension of the response grows. Most existing dimension reduction techniques primarily focus on reducing the dimension of the predictors (X), not the dimension of the response variable (Y). Yoo and Cook (2008) introduced a response dimension reduction method that preserves information about the conditional mean E(Y | X). Building upon this foundational work, Yoo (2018) proposed two semi-parametric methods, principal response reduction (PRR) and principal fitted response reduction (PFRR), then expanded these methods to unstructured principal fitted response reduction (UPFRR) (Yoo, 2019). This paper reviews these four response dimension reduction methodologies mentioned above. In addition, it introduces the implementation of the mbrdr package in R. The mbrdr is a unique tool in the R community, as it is specifically designed for response dimension reduction, setting it apart from existing dimension reduction packages that focus solely on predictors.

• Communications for Statistical Applications and Methods
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• 제23권2호
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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.

• 한국의류학회지
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• 제22권5호
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• pp.597-606
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• 1998

The purposes of the study were 1) to evaluate the visual image of colored Korean traditional dress for woman 2) to analyze the colors and, color combinations effect on the image perception using gestalt theory. The research method was a quasi-experimental with a between subjects design. The experimental materials developed for the study were a set of stimuli and a response scale. The stimuli was consisted of 17 drawings of females wearing Korean tradinational dress, by using CAD simulation. A response scale consisted of semantic differential scales. The subjects were 1138 undergraduate students of Taejon city, Chungnam province and Chungbuk province. Their responses to the semantic differential scales were analyzed using factor analysis, one-way ANOVA, Duncan's multiple range test, 1-test. Results were as follows; 1) The image of the stimulus was consisted of the 4 different dimensions.(sociability, evaluation, visibility, attractiveness) 2) Clothing colors had significant effects on image perception of the evaluation dimension, visibility dimension and attractiveness dimension in the mono-color set. The blue showed the most positive image on the evaluation dimension, and the yellow and the gray showed negative image on the same dimension. The yellow showed the most salient image and the gray showed the least salient image on the visibility dimension. The red showed the most attractive image and the green showed the least attractive image on the attractiveness dimension. 3) In hi-color set stimulus, the perceived image was influenced by color combinations. The yellow blouse-the red skirt set showed the most sociable image on the sociability dimension. The blue blouse-the green skirt set showed the most positive image on the evaluation dimension. The yellow blouse-the red skirt set showed the most salient image and the blue blouse-the green skirt set showed the least salient image on the visibility dimension. And the red blouse-the yellow skirt set showed the most attractive image on the attractiveness dimension. On conclusion the visual image of Korean traditional dress wearer was affected by dress colors and color combinations.

• 응용통계연구
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• 제23권5호
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• pp.977-985
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• 2010

In this paper, we propose an approach to conduct partial sufficient dimension reduction with heavily unbalanced categorical predictors. For this, we consider integrated categorical predictors and investigate certain conditions that the integrated categorical predictor is fully informative to partial sufficient dimension reduction. For illustration, the proposed approach is implemented on optimal partial sliced inverse regression in simulation and data analysis.

• Journal of applied mathematics & informatics
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• 제5권1호
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• pp.13-22
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• 1998

Fractals which represent many of the sets in various scien-tific fields as well as in nature is geometrically too complicate. Then we usually use Hausdorff dimension to estimate their geometrical proper-ties. But to explain the fractals from the hausdorff dimension induced by the Euclidan metric are not too sufficient. For example in digi-tal communication while encoding or decoding the fractal images we must consider not only their geometric sizes but also many other fac-tors such as colours densities and energies etc. So in this paper we define the dimension matrix of the sets by redefining the new metric.

• 음성과학
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• 제3권
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• pp.148-155
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• 1998

As an application of dimensional analysis in the theory of chaos and fractals, we studied and estimated the information dimension for various phonemes. By constructing phase-space vectors from the time-series speech signals, we calculated the natural measure and the Shannon's information from the trajectories. The information dimension was finally obtained as the slope of the plot of the information versus space division order. The information dimension showed that it is so sensitive to the waveform and time delay. By averaging over frames for various phonemes, we found the information dimension ranges from 1.2 to 1.4.