• Proceedings of the KSME Conference
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• 2008.11a
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• pp.412-417
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• 2008

In a traditional topology optimization method, material properties are usually distributed by finite element density and visualized by a gray level image. The distribution method based on element density is adequate for a great mass of 2-D topology optimization problems. However, when it is used for 3-D topology optimization, it is always difficult to obtain a smooth model representation, and easily appears a virtualconnect phenomenon especially in a low-density domain. The 3-D structural topology optimization method has been developed using the node density instead of the element density that is based on SIMP (solid isotropic microstructure with penalization) algorithm. A computer code based on Matlab was written to validate the proposed method. When it was compared to the element density as design variable, this method could get a more uniform density distribution. To show the usefulness of this method, several typical examples of structure topology optimization are presented.

• Journal of the Korean Operations Research and Management Science Society
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• v.35 no.2
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• pp.71-88
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• 2010

A density-based outlier detection such as an LOF (Local Outlier Factor) tries to find an outlying observation by using density of its surrounding space. In spite of several advantages of a density-based outlier detection method, the computational complexity of outlier detection has been one of major barriers in its application. In this paper, we present an LOF algorithm that can reduce computation time of a density based outlier detection algorithm. A kd-tree indexing and approximated k-nearest neighbor search algorithm (ANN) are adopted in the proposed method. A set of experiments was conducted to examine performance of the proposed algorithm. The results show that the proposed method can effectively detect local outliers in reduced computation time.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3815-3835
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• 2022

Density-based outlier detection is one of the hot issues in data mining. A point is determined as outlier on basis of the density of points near them. The existing density-based detection algorithms have high time complexity, in order to reduce the time complexity, a new outlier detection algorithm DODMD (Density-based Outlier Detection in Multidimensional Datasets) is proposed. Firstly, on the basis of ZH-tree, the concept of micro-cluster is introduced. Each leaf node is regarded as a micro-cluster, and the micro-cluster is calculated to achieve the purpose of batch filtering. In order to obtain n sets of approximate outliers quickly, a greedy method is used to calculate the boundary of LOF and mark the minimum value as LOF_min. Secondly, the outliers can filtered out by LOF_min, the real outliers are calculated, and then the result set is updated to make the boundary closer. Finally, the accuracy and efficiency of DODMD algorithm are verified on real dataset and synthetic dataset respectively.

• Journal of Medicine and Life Science
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• v.20 no.1
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• pp.21-31
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• 2023

We aimed (a) to investigate the associations between age, body mass index (BMI), and breast size with mammographic density based on the breast imaging reporting and data system (BI-RADS) and volumetric breast density measurement (VBDM) with Volpara, (b) to evaluate the associations of age, BMI, and breast size with fibroglandular tissue volume (FGV), and (c) to demonstrate the association of mammographic density grade with FGV. From April 2012 to May 2012, 1,203 women consecutively underwent mammography, and their breast density was calculated using the density grade and volume determined by Volpara. In total, 427 women were included in this study. The BMI and breast size of the 427 women were determined. The associations between mammographic density and age, BMI, and bra cup size were assessed. In addition, the associations between FGV and age, BMI, bra cup size, and mammographic density were assessed. The mean age of the women was 51 years (range, 27-83). Age was associated with mammographic density based on BI-RADS (P<0.0001), and both age and BMI were associated with mammographic density based on Volpara (P<0.0001). The mean FGV significantly decreased as age increased (P<0.0001) and increased as BMI and bra cup size increased (P<0.0001 and P=0.0007, respectively). Age was associated with mammographic density, according to both the BI-RADS and VBDM; however, BMI was only associated with mammographic density based on the VBDM. Larger FGV was associated with younger age, higher BMI, larger bra cup size, and higher mammographic density

• Journal of the Korean Statistical Society
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• v.29 no.3
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• pp.307-313
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• 2000

Suppose we have a set of data X1, ···, Xn and employ kernel density estimator to estimate the marginal density of X. in this article bandwith selection problem for kernel density estimator is examined closely. In particular the Kullback-Leibler method (a bandwith selection methods based on average square error (ASE)) is considered.

• Proceedings of the Korean Vacuum Society Conference
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• 1998.02a
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• pp.105-106
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• 1998

Evaluation of def3ects by etch-ppit formation was studied. A NaOH(30 mol%) etchant was found useful for etch-ppit developpment on ZnSe-based eppilayers grown on (001) gaAs. And a H3ppO4(85 mol%) was used in order to developp etch-ppits on GaN-base eppilayers grown on (0001) Al2O3 After etch-ppit formation on the surfsce. Transmission Electron Microscoppy(TEM) was cppmdicted. By etch-ppit developpment and TEM observation we could determine the defect typpes by etch-ppit configurfations and found origin of etch-ppit in the cse of ZnSe-based materials. Based uppon these results we can do defect identification by etch-ppit test simpply. In the case of GaN-based materials we could evaluate nanoppippe density. however high density of threading dislocations in GaN eppilayers were not revealed by etch-ppit developpment. Based uppon these results we can evaluate the nanoppippe density which difficult to evaluate using TEM beacause of its small size(diameter). And at ppresent status direct matching of etch-ppit density to dislocation density would make severe mistake.

• The Journal of the Acoustical Society of Korea
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• v.34 no.4
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• pp.303-309
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• 2015

Speaker diarization is the task of determining the speakers for unlabeled data, and DBSCAN (Density-Based Spatial Clustering of Applications with Noise) has been widely used in the field of speaker diarization for its simplicity and computational efficiency. One challenging issue, however, is that if different clusters in non-spatial dataset are adjacent to each other, over-clustering may occur which subsequently degrades the performance of DBSCAN. In this paper, we identify the drawbacks of DBSCAN and propose a new density clustering algorithm based on local distribution property around object. Variable density criterions for local density and spreadness of object are used for effective data clustering. We compare the proposed algorithm to DBSCAN in terms of clustering accuracy. Experimental results confirm that the proposed algorithm exhibits higher accuracy than DBSCAN without over-clustering and confirm that the new approach based on local density and object spreadness is efficient.

• Applied Science and Convergence Technology
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• v.23 no.3
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• pp.151-159
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• 2014

We investigated the effects of the chemical composition and the relative density on the plastic deformation behavior of sintered Fe-based alloys by means of compressive tests. Overall compressive stresses increased as the amount of alloying elements and the relative density were respectively increased. Addition of alloying elements except for Mo increased the yield stress regardless of the relative density. The relationship between the effects of the chemical composition and the relative density and the mean rate of the stress increase was analyzed. A constitutive equation based on the Ludwik equation with the regressed parameters was proposed to predict the compressive true stress-true strain curves of the sintered Fe-based alloys. The K and n values used in the proposed equation were regressed as a function of the alloying elements and the relative density based on the individual K and n values. The plastic deformation behavior predicted using the proposed constitutive equation showed reliable accuracy compared with experimental data.

• Proceedings of the Korean Statistical Society Conference
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• 2003.05a
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• pp.287-293
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• 2003

In this paper we consider the problem of parameter change based on the cusum test proposed by Lee et al. (2003). The cusum test statistic is constructed utilizing the estimator minimizing density-based divergence measures. It is shown that under regularity conditions, the test statistic has the limiting distribution of the sup of standard Brownian bridge. Simulation results demonstrate that the cusum test is robust when there arc outliers.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.9
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• pp.547-553
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• 2003

In this paper, we designed the PC-based analyzer of the power spectral density that could estimate the heart rate variability from time series data of R-R interval. The power spectral density estimated that it applied the autoregressive model to the measured electrocardiogram during a short period. Also, the characteristics of the designed analyzer are that it could process of the signal filtering, the generation and recomposition of time series and the feature extraction at the same time. Especially the analyzer reconstructed which applied the lowpass filter of the time series composed by the linear interpolation so as to enhance the signal-to-noise feature. We could estimate the power spectral density that confirmed a variety of power peak with low frequency range and high frequency rang of autonomic nerve by the heart rate variability.