• The Journal of Advanced Prosthodontics
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• v.2 no.3
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• pp.106-110
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• 2010

The severe wear of anterior teeth facilitates the loss of anterior guidance, which protects the posterior teeth from wear during excursive movement. The collapse of posterior teeth also results in the loss of normal occlusal plane and the reduction of the vertical dimension. This case report describes 77-year-old female, who had the loss of anterior guidance, the severe wear of dentition, and the reduction of the vertical dimension. Occlusal overlay splint was used after the decision of increasing vertical dimension by anatomical landmark, facial and physiologic measurement. Once the compatibility of the new vertical dimension had been confirmed, interim fixed restoration and the permanent reconstruction was initiated. This case reports that a satisfactory clinical result was achieved by restoring the vertical dimension with an improvement in esthetics and function.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.12
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• pp.143-151
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• 1999

The shape of surface micro-crack is very irregular due to nonhomogeneous microstructure but is very important in respect to qualitative estimation of fatigue life. Fractal geomety can quantify the shape of surface mciro-crack. Fractal dimension is measured for surface micro-cracks with coast line and box counting method and estimates cycle ration in Al 2024-T3. The average fractal dimension $D_{favg}$ of surface micro-cracks has 3-parameter weibull distribution and location parameter is nearly constant but shape parameter decreases as cycle ration increases. The fractal dimension by coast line method is measured for individual surface micro-crack but the fractal dimension by box countin method is measured for all the surface micro-cracks under sampling area. Therefore, This paper shows fractal dimension $D_{fb}$ can predict cycle ratio $N/N_f$ more convenient than fractal dimension $D_{favg}$.

• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2005.11a
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• pp.69-72
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• 2005

As life style becomes to be complicated, lots of support technologies were developed. The bar code technology is one of them. It was renovating approach to goods industry. However, data storage ability in one dimension bar code came in limit because of industry growth. Two-dimension bar code was proposed to overcome one-dimension bar code. PDF417 bar code most commonly used in standard two-dimension bar codes is well defined at data decoding and error correction area. More works could be done in bar code image acquisition process. Applying various image enhancement algorithms, the recognition rate of PDF417 bar code is improved.

• Korean Institute of Interior Design Journal
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• no.11
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• pp.20-25
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• 1997

The purpose of this study is to find out the correlation between Truth(道) and dimension through the understanding of architectural point of value in the aspect of correlation between modern western thoughts and the thoughts of Truth and also through the reading of what kind of composite trend of the Truth can be seen in a Korea traditional house. This stduy takes the following procedure with reference books and traditional house that we have. 1) Making foundation for this study by finding out the fundamental meaning of the thoughts of Truth through the comparing and analyzing between modern western thoughts and the thoughts of Truth. 2) Reviewing the understanding of dimension in the thoughts of Truth. 3) Traslation of the organic correlation through the analysis of composition, placement and characteristics of dimension in a real present traditional Korea house. 4) Finding out the meaning of each dimension through the adaptation of the fundamental rules of nature of Jane(藏:store), Sang(生:life), Jang(長:long), Su(收obtain) to the dimension composite of a traditional house and concluding that the cyclical process in the oriental thoughts could be made.

• Bulletin of the Korean Mathematical Society
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• v.48 no.2
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• pp.261-275
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• 2011

We give characterizations of the differentiability points and the non-differentiability points of the Riesz-N$\'{a}$gy-Tak$\'{a}$cs(RNT) singulr function using the distribution sets in the unit interval. Using characterizations, we show that the Hausdorff dimension of the non-differentiability points of the RNT singular function is greater than 0 and the packing dimension of the infinite derivative points of the RNT singular function is less than 1. Further the RNT singular function is nowhere differentiable in the sense of topological magnitude, which leads to that the packing dimension of the non-differentiability points of the RNT singular function is 1. Finally we show that our characterizations generalize a recent result from the ($\tau$, $\tau$ - 1)-expansion associated with the RNT singular function adding a new result for a sufficient condition for the non-differentiability points.

• Communications for Statistical Applications and Methods
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• v.22 no.3
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• pp.285-294
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• 2015

A permutation test is the popular and attractive alternative to derive asymptotic distributions of dimension test statistics in sufficient dimension reduction methodologies; however, recent studies show that a bootstrapping technique also can be used. We consider two types of bootstrapping dimension determination, which are partial and whole bootstrapping procedures. Numerical studies compare the permutation test and the two bootstrapping procedures; subsequently, real data application is presented. Considering two additional bootstrapping procedures to the existing permutation test, one has more supporting evidence for the dimension estimation of the central subspace that allow it to be determined more convincingly.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.8
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• pp.361-368
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• 2016

While dimension reduction methods on high dimensional data have been widely studied, research on dimension reduction methods for high dimensional streaming data with concept drift is limited. In this paper, we review incremental dimension reduction methods and propose a method to apply dimension reduction efficiently in order to improve classification performance on high dimensional streaming data with concept drift.

• Communications for Statistical Applications and Methods
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• v.23 no.2
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• pp.105-117
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• 2016

In the paper, as a sequence of the first tutorial, we discuss sufficient dimension reduction methodologies used to estimate central subspace (sliced inverse regression, sliced average variance estimation), central mean subspace (ordinary least square, principal Hessian direction, iterative Hessian transformation), and central $k^{th}$-moment subspace (covariance method). Large-sample tests to determine the structural dimensions of the three target subspaces are well derived in most of the methodologies; however, a permutation test (which does not require large-sample distributions) is introduced. The test can be applied to the methodologies discussed in the paper. Theoretical relationships among the sufficient dimension reduction methodologies are also investigated and real data analysis is presented for illustration purposes. A seeded dimension reduction approach is then introduced for the methodologies to apply to large p small n regressions.

• Tribology and Lubricants
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• v.18 no.2
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• pp.147-152
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• 2002

The morphological analysis of wear particle is a very effective means fur machine condition monitoring and fault diagnosis. In order to describe morphology of various wear particle, the wear test was carried out under friction experimental conditions. And fractal descriptors was applied to boundary and surface of wear particle with image processing. These descriptors to analyze shape and surface of wear particle are shape fractal dimension and surface fractal dimension. The boundary 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 parameter.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1993.06a
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• pp.857-860
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• 1993

In this paper, we apply the self generating neuro fuzzy model (SGNFM) to the dimension analysis of the chaotic time series. Firstly, we formulate a nonlinear time series identification problem with nonlinear autoregressive (NARMAX) model. Secondly, we propose an identification algorithm using SGNFM. We apply this method to the estimation of embedding dimension for chaotic time series, since the embedding dimension plays an essential role for the identification and the prediction of chaotic time series. In this estimation method, identification problems with gradually increasing embedding dimension are solved, and the identified result is used for computing correlation coefficients between the predicted time series and the observed one. We apply this method to the dimension estimation of a chaotic pulsation in a finger's capillary vessels.