• Korean Journal of Materials Research
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• v.5 no.2
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• pp.232-238
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• 1995

The thermal stress distribution of WC and Ni binder phases In WC-26st.%Ni and WC-6wt.%Ni composites has been investigated over the temperature range 100-900 K using a time-of-flight neutron diffractometer. To determine the stress distribution, the breadths of WC and Ni peaks in the reference powder and the composites were analyzed. The peak breadths were corrected for particle size effect using a procedure based on the integral peak breadth method of particle size-strain analysis. The result shows a broad range of strain, and thus stress, is present in the WC and Ni binder phases of the composites. The strain distribution of both phases broadens as the temperature decreases, and some fraction of total strain distribution of the WC phase remains tensile regardless of the temperature. The strain distribution of the WC phase broadens as the binder content increases, and that of Ni binder phase broadens as the binder content decreases, which means the strain distribution broadens as the absolute value of residual stress increase.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.42.5-42
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• 2002

1. Introduction for whole aspects. 2. Filtering for Fault Current Waveform 3. Estimation for relay operation. 4. Wavelet transform and ANN. 5. Identification for operated protection device. 6. Conclusion. Reference.

• Structural Engineering and Mechanics
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• v.74 no.1
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• pp.55-67
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• 2020

The common practice to predict the characteristic structural load effects (LEs) in long reference periods is to employ the extreme value theory (EVT) for building limit distributions. However, most applications ignore that LEs are driven by multiple loading events and thus do not have the identical distribution, a prerequisite for EVT. In this study, we propose the composite extreme value modeling approach using clustering to (a) cluster initial blended samples into finite identical distributed subsamples using the finite mixture model, expectation-maximization algorithm, and the Akaike information criterion; (b) combine limit distributions of subsamples into a composite prediction equation using the generalized Pareto distribution based on a joint threshold. The proposed approach was validated both through numerical examples with known solutions and engineering applications of bridge traffic LEs on a long-span bridge. The results indicate that a joint threshold largely benefits the composite extreme value modeling, many appropriate tail approaching models can be used, and the equation form is simply the sum of the weighted models. In numerical examples, the proposed approach using clustering generated accurate extrema prediction of any reference period compared with the known solutions, whereas the common practice of employing EVT without clustering on the mixture data showed large deviations. Real-world bridge traffic LEs are driven by multi-events and present multipeak distributions, and the proposed approach is more capable of capturing the tendency of tailed LEs than the conventional approach. The proposed approach is expected to have wide applications to general problems such as samples that are driven by multiple events and that do not have the identical distribution.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.43 no.2 s.308
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• pp.33-39
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• 2006

This paper presents the modified LVQ method for performance improvement of pattern classification. The proposed method uses the skewness of probability distribution between the input vectors and the reference vectors. During training, the reference vectors are closest to the input vectors using the probabilistic distribution of the input vectors, and they are positioned to approximate the decision surfaces of the theoretical Bayes classifier. In order to verify the effectiveness of the proposed method, we performed experiments on the Gaussian distribution data set, and the Fisher's IRIS data set. The experimental results show that the proposed method considerably improves on the performance of the LVQ1, LVQ2, and GLVQ.

• The Korean Journal of Applied Statistics
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• v.17 no.1
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• pp.49-60
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• 2004

In this paper, when the observations are distributed as inverse gaussian, we developed the noninformative priors for ratio of the parameters of inverse gaussian distribution. We developed the first order matching prior and proved that the second order matching prior does not exist. It turns out that one-at-a-time reference prior satisfies a first order matching criterion. Some simulation study is performed.

• Nuclear Engineering and Technology
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• v.51 no.7
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• pp.1729-1737
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• 2019

This paper presents neutronics design of VVER-1000 fuel assembly using burnable poison particles (BPPs) for controlling excess reactivity and pin-wise power distribution. The advantage of using BPPs is that the thermal conductivity of BPP-dispersed fuel pin could be improved. Numerical calculations have been conducted for optimizing the BPP parameters using the MVP code and the JENDL-3.3 data library. The results show that by using $Gd_2O_3$ particles with the diameter of $60{\mu}m$ and the packing fraction of 5%, the burnup reactivity curve and pin-wise power distribution are obtained approximately that of the reference design. To minimize power peaking factor (PPF), total BP amount has been distributed in a larger number of fuel rods. Optimization has been conducted for the number of BPP-dispersed rods, their distribution, BPP diameter and packing fraction. Two models of assembly consisting of 18 BPP-dispersed rods have been selected. The diameter of $300{\mu}m$ and the packing fraction of 3.33% were determined so that the burnup reactivity curve is approximate that of the reference one, while the PPF can be decreased from 1.167 to 1.105 and 1.113, respectively. Application of BPPs for compensating the reduction of soluble boron content to 50% and 0% is also investigated.

• Nuclear Engineering and Technology
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• v.48 no.3
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• pp.624-634
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• 2016

Nuclear criticality safety analyses (NCSAs) considering burnup credit were performed for the GBC-32 cask. The used nuclear fuel assemblies (UNFAs) discharged from Hanbit Nuclear Power Plant Unit 3 Cycle 6 were loaded into the cask. Their axial burnup distributions and average discharge burnups were evaluated using the DeCART and Multi-purpose Analyzer for Static and Transient Effects of Reactors (MASTER) codes, and NCSAs were performed using SCALE 6.1/STandardized Analysis of Reactivity for Burnup Credit using SCALE (STARBUCS) and Monte Carlo N-Particle transport code, version 6 (MCNP 6). The axial burnup distributions were determined for 20 UNFAs with various initial enrichments and burnups, which were applied to the criticality analysis for the cask system. The UNFAs for 20- and 30-year cooling times were assumed to be stored in the cask. The criticality analyses indicated that $k_{eff}$ values for UNFAs with nonuniform axial burnup distributions were larger than those with a uniform distribution, that is, the end effects were positive but much smaller than those with the reference distribution. The axial burnup distributions for 20 UNFAs had shapes that were more symmetrical with a less steep gradient in the upper region than the reference ones of the United States Department of Energy. These differences in the axial burnup distributions resulted in a significant reduction in end effects compared with the reference.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2004.08a
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• pp.359-367
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• 2004

In this research on-line model for the prediction of the effective strain distribution in strip on finishing mill process is presented. To describe the effective strain distribution in strip, three guide points and a distribution fitting variable are used. On-line models to get these points and fitting variable non-dimensionalization method and least square method were used with FEM simulation results. The model is developed using strip only FEM simulation as reference sets and compared with roll coupled FEM simulation results as perturbed sets. The on-line model to describe effective strain distribution shows good agreement with coupled FEM analysis results.

• Journal of Biomedical Engineering Research
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• v.32 no.2
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• pp.134-143
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• 2011

The selection of meaningful clinical tests and its reference values from a high-dimensional clinical data with imbalanced class distribution, one class is represented by a large number of examples while the other is represented by only a few, is an important issue for differential diagnosis between similar diseases, but difficult. For this purpose, this study introduces methods based on the concepts of both discernibility matrix and function in rough set theory (RST) with two discretization approaches, equal width and frequency discretization. Here these discretization approaches are used to define the reference values for clinical tests, and the discernibility matrix and function are used to extract a subset of significant clinical tests from the translated nominal attribute values. To show its applicability in the differential diagnosis problem, we have applied it to extract the significant clinical tests and its reference values between normal (N = 351) and abnormal group (N = 101) with either cholecystitis or cholelithiasis disease. In addition, we investigated not only the selected significant clinical tests and the variations of its reference values, but also the average predictive accuracies on four evaluation criteria, i.e., accuracy, sensitivity, specificity, and geometric mean, during l0-fold cross validation. From the experimental results, we confirmed that two discretization approaches based rough set approximation methods with relative frequency give better results than those with absolute frequency, in the evaluation criteria (i.e., average geometric mean). Thus it shows that the prediction model using relative frequency can be used effectively in classification and prediction problems of the clinical data with imbalanced class distribution.

• Journal of Platform Technology
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• v.11 no.5
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• pp.59-71
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• 2023

This paper proposes a method of estimating the illumination chromaticity of a scene in which an image is taken. Storring and Bianco proposed a method of estimating illuminant chromaticity using skin color. Storring et al. used skin color distribution characteristics and black body locus, but there is a problem that the link between the locus and CIE-xy data is reduced. Bianco et al. estimated the illuminant chromaticity by comparing the skin color distribution in standard lighting with the skin color distribution in the input image. This method is difficult to measure and secure as much skin color as possible in various illumination. The proposed method can estimate the illuminant chromaticity for any input image by analyzing the relationship between the skin color information and the illuminant chromaticity. The estimation method is divided into an analysis stage and a test stage, and the data set was classified into an analysis group and a test group and used. Skin chromaticity is calculated by obtaining skin color areas from all input images of the analysis group, respectively. A mapping is obtained by analyzing the correlation between the average set of skin chromaticity and the reference illuminant chromaticity set. The calculated mapping is applied to all input images of the analysis group to estimate the illuminant chromaticity, calculate the error with the reference illuminant chromaticity, and repeat the above process until there is no change in the error to obtain a stable mapping. The obtained mapping is applied to the test group images similar to the analysis stage to estimate the illuminant chromaticity. Since there is no independent data set containing skin area and illuminant reference information, the experimental data set was made using some of the images of the Intel TAU data set. Compared to Finlayson, a similar theory-based existing method, it showed performance improvement of more than 40%, Zhang 11%, and Kim 16%.