• Journal of the Institute of Electronics Engineers of Korea SC
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• v.45 no.6
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• pp.108-116
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• 2008

In this paper, we propose an algorithm that can estimate the distance using disparity based on stereo vision system, even though the obstacle is located in long ranges as well as short ranges. We use sub-pixel interpolation to minimize quantization errors which deteriorate the distance accuracy when calculating the distance with integer disparity, and also we use enhanced adaptive fuzzy strong tracking Kalman filter(EAFSTKF) to improve the distance accuracy and track the path optimally. The proposed method can solve the divergence problem caused by nonlinear dynamics such as various vehicle movements in the conventional Kalman filter(CKF), and also enhance the distance accuracy and reliability. Our simulation results show that the performance of our method improves by about 13.5% compared to other methods in point of root mean square error rate(RMSER).

• The Korean Journal of Applied Statistics
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• v.16 no.2
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• pp.455-467
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• 2003

There has been a long debate on the applicability of the chi-square approximation to statistics based on small sample size. Extending comparison results among Pearson chi-square Χ$^2$, generalized likelihood .ratio G$^2$, and the power divergence Ι(2/3) statistics suggested by Rudas(1986), recently developed disparity statistics (BWHD(1/9), BWCS(1/3), NED(4/3)) we compared and analyzed in this paper. By Monte Carlo studies about the independence model of two dimension contingency tables, the conditional model and one variable independence model of three dimensional tables, simulated 90 and 95 percentage points and approximate 95% confidence intervals for the true percentage points are obtained. It is found that the Χ$^2$, Ι(2/3), BWHD(1/9) test statistics have very similar behavior and there seem to be applcable for small sample sizes than others.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1996.10a
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• pp.195-201
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• 1996

This paper is mainly forcused on the application of modal analysis In analyze the geometrically non-linear buckling behaviors of large span spatial structures, and the evaluation of each eigen mode affected post-buckling behaviors and buckling loads. Modal analysis is applied . to derivation of the system matrices transforming actual displacement space into generalized coordinates space represented by coefficients multiplied in the linear combination of eigen modes which are independent and orthogonal each other. By using modal analysis method, it will be expected to save the calculating time by computer extremely. For example, we can obtain the satisfactorily good results by using about 7% of total eigen modes only in case of single layer latticed dome. And we can decrease the possibility of divergence on the bifurcation point in the calculation of post-buckling path. Arc-length method and Newton-Raphson iteration method are used to calculate the nonlinear equilibrium path.

• Journal of Ecology and Environment
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• v.31 no.4
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• pp.255-260
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• 2008

A commonly held view in studies of character displacement is that character states of both species are shifted in areas of sympatry. This view has been confirmed in an overwhelming number of cases for ecological character displacement. Excluding species pairs in which one of the two interacting species is found only within the distribution of the other species and species displaying gynogenesis, the pattern of reproductive character displacement is asymmetrical in that the shift in character states between areas of symaptry and allopatry occurs in only one of the two interacting species. Hypotheses for the reasons behind this asymmetry in reproductive character displacement include (1) homogenization by gene flow, (2) other mechanisms of reproductive isolation, and (3) sufficient reproductive isolation being provided by one of the interacting species exhibiting a pattern of reproductive character displacement. Because reproductive isolation can be achieved by divergence at any point in a sequence of premating reproductive behaviors and postmating developments, it is necessary to understand the mechanisms of reproductive isolation of two interacting taxa in areas of sympatry and allopatry and to analyze the relative contributions of potential factors to reproductive isolation to disentangle hypotheses for the patterns of asymmetry.

• Journal of the Korean Statistical Society
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• v.25 no.2
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• pp.289-301
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• 1996

This paper suggests a new diagnostic measure for detecting influential observations in two group linear discriminant analysis(LDA). It is developed from an information theoretic point of view using the minimum discrimination information(MDI) methodology. MDI estimator of symmetric divergence by Kullback(l967) is taken as a measure of the power of discrimination in LDA. It is shown that the effect of an observation over the power of discrimination is fully explained by the diagnostic measure. Asymptotic distribution of the proposed measure is derived as a function of independent chi-squared and standard normal variables. By means of the distributions, a couple of methods are suggested for detecting the influential observations in LDA. Performance of the suggested methods are examined through a simulation study.

• Proceedings of the KIEE Conference
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• 1999.07e
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• pp.2287-2289
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• 1999

In this paper, a new method for calculating capacitance in multi-electrode system with arbitrarily shape is presented. This new approach based on divergence theorem and Gauss's law is achieved by Surface-Contacted Element(SCE) for Gaussian surface. To evaluate capacitance in multi-electrode system, two dimensional finite element method using only the elements which is contacted one nod (PE: Point-Element) or two nod (FE: Face-Element) with surface is employed. The proposed SCE method has short computing time to calculate capacitance which is because it uses only SCE elements and needs one calculation loop while exiting FEM method in servral loops. This method is verified by application in calculating capacitance using potential detection device model which is composed with anode, cathode, and floating electrode.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1565-1572
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• 2015

In this paper, we analyze the polio incidence data based on the Poisson autoregressive models, focusing particularly on change-point detection. Since the data include some strongly deviating observations, we employ the robust cumulative sum (CUSUM) test proposed by Kang and Song (2015) to perform the test for parameter change. Contrary to the result of Kang and Lee (2014), our data analysis indicates that there is no significant change in the case of the CUSUM test with strong robustness and the same result is obtained after ridding the polio data of outliers. We additionally consider the comparison of the forecasting performance. All the results demonstrate that the robust CUSUM test performs adequately in the presence of seemingly outliers.

• Nuclear Engineering and Technology
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• v.48 no.2
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• pp.434-447
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• 2016

The aim of this paper is the study of instability state of boiling water reactors with a method based in largest Lyapunov exponents (LLEs). Detecting the presence of chaos in a dynamical system is an important problem that is solved by measuring the LLE. Lyapunov exponents quantify the exponential divergence of initially close state-space trajectories and estimate the amount of chaos in a system. This method was applied to a set of signals from several nuclear power plant (NPP) reactors under commercial operating conditions that experienced instabilities events, apparently each of a different nature. Laguna Verde and Forsmark NPPs with in-phase instabilities, and Cofrentes NPP with out-of-phases instability. This study presents the results of intrinsic instability in the boiling water reactors of three NPPs. In the analyzed cases the limit cycle was not reached, which implies that the point of equilibrium exerts influence and attraction on system evolution.

• Korean Journal of Plant Resources
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• v.19 no.5
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• pp.628-633
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• 2006

ITS DNA sequences from five individuals, representative of five groups designated according to the degree of leaf teeth and lobes from simple to palmate compound leaf in the Viola albida complex, established and further analysed in order to solve the taxonomic difficulty. A total 702 bp was sequenced at the 5.8S ribosomal DNA and internal transcribed spacer 1 and 2. The 5.8S coding region is 163 bp, and has no sequence variations. The ITS1 and ITS2 noncoding regions have a little bit sequence variations, and those were further analysed by the methods of the analysis of variance (ANOVA), the analysis of sequence divergence and the phylogenetic analysis. The result of ANOVA showed no significant differences among individuals investigated. The analysis of sequence divergence with Kimura 2-parameter distance revealed that in-groups showed much less than 0.05 in absolute value among individuals, while two out groups more than 0.05, V. grypoceras and V. orientalis. This result appeared that the sequence divergence among in-groups was not yet occurred in the species level but situated at somewhere below the species level. In the phylogenetic analysis, two outgroups formed the basal clades in order. Five individuals in-groups formed a clade. The clade was, however, not very robust as around 50% in bootstrap value, suggesting that this result was not meaningful in the phylogenetic point of views.

• Journal of IKEEE
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• v.26 no.3
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• pp.408-415
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• 2022

In this paper, we propose a 3D point cloud reconstruction technique from 2D images using efficient feature map extraction network. The originality of the method proposed in this paper is as follows. First, we use a new feature map extraction network that is about 27% efficient than existing techniques in terms of memory. The proposed network does not reduce the size to the middle of the deep learning network, so important information required for 3D point cloud reconstruction is not lost. We solved the memory increase problem caused by the non-reduced image size by reducing the number of channels and by efficiently configuring the deep learning network to be shallow. Second, by preserving the high-resolution features of the 2D image, the accuracy can be further improved than that of the conventional technique. The feature map extracted from the non-reduced image contains more detailed information than the existing method, which can further improve the reconstruction accuracy of the 3D point cloud. Third, we use a divergence loss that does not require shooting information. The fact that not only the 2D image but also the shooting angle is required for learning, the dataset must contain detailed information and it is a disadvantage that makes it difficult to construct the dataset. In this paper, the accuracy of the reconstruction of the 3D point cloud can be increased by increasing the diversity of information through randomness without additional shooting information. In order to objectively evaluate the performance of the proposed method, using the ShapeNet dataset and using the same method as in the comparative papers, the CD value of the method proposed in this paper is 5.87, the EMD value is 5.81, and the FLOPs value is 2.9G. It was calculated. On the other hand, the lower the CD and EMD values, the better the accuracy of the reconstructed 3D point cloud approaches the original. In addition, the lower the number of FLOPs, the less memory is required for the deep learning network. Therefore, the CD, EMD, and FLOPs performance evaluation results of the proposed method showed about 27% improvement in memory and 6.3% in terms of accuracy compared to the methods in other papers, demonstrating objective performance.