• Journal of the Korean Statistical Society
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• v.27 no.4
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• pp.507-514
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• 1998

The minimum distance estimation based on the L$_2$ distance between a model density and a density estimator is studied from M-estimation point of view. We will show that how a model density and a density estimator are incorporated in order to create an M-estimation function. This method enables us to create an M-estimating function reflecting the natures of both an assumed model density and a given set of data. Some new types of M-estimation functions for estimating a location and scale parameters are introduced.

• Journal of Korea Multimedia Society
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• v.6 no.3
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• pp.375-383
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• 2003

Clustering in spatial mining is to group similar objects based on their distance, connectivity or their relative density in space. In the real world. there exist many physical objects such as rivers, lakes and highways, and their presence may affect the result of clustering. In this paper, we define distance to handle obstacles, and using that we propose the density based clustering algorithm called DBSCAN-O to handle obstacles. We show that DBSCAN-O produce different clustering results from previous density based clustering algorithm DBSCAN by our experiment result.

• Journal of computational fluids engineering
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• v.12 no.2
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• pp.53-62
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• 2007

A high resolution numerical method aimed at solving cavitating flow is proposed and applied to gas-liquid two-phase shock tube problem. The present method employs a finite-difference 4th-order Runge-Kutta method and Roe's flux difference splitting approximation with the MUSCL TVD scheme. By applying the homogeneous equilibrium cavitation model, the present density-based numerical method permits simple treatment of the whole gas-liquid two-phase flow field, including wave propagation and large density changes. The speed of sound for gas-liquid two-phase media is derived on the basis of thermodynamic relations and compared with that by eigenvalues. By this method, a Riemann problem for Euler equations of one dimensional shock tube was computed. Numerical results such as detailed observations of shock and expansion wave propagations through the gas-liquid two-phase media at isothermal condition and some data related to computational efficiency are made. Comparisons of predicted results and exact solutions are provided and discussed.

• Journal of Science Education
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• v.37 no.1
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• pp.221-232
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• 2013

The purpose of this study was to examine the effect of the CoRe-based density unit class on conceptual formation and on learner satisfaction with the class. For this study, two hundred and forty 8th grade students were chosen from six classes. The students were divided into two groups: an experimental group, which received a CoRe-based density unit lesson, and a control group, which was taught based on traditional teaching method. The CoRe-based density unit classes consisted of 4 periods based on the analysis of the previous studies on CoRe about density. The results showed the meaningful significant difference between the CoRe-based classes and the classes based on traditional teaching method both in the posttest on the extent of the conceptual formation on the density and in the retention test. The difference suggests that the lesson with CoRe is based on the consideration of the difficulties and limitations students face in various fields such as the students themselves, teachers, learning environment, evaluation, etc. during their learning process and even in the types of preconception they have, and the CoRe-based lesson is centered around the best teaching strategies to solve such difficulties. As a result of the analysis on the experimental group's class satisfaction, it is revealed that the students with a high level of attitudes related science or with a high level of science achievement showed especially high satisfaction in their learning. Analysis of questionnaire survey showed that the students in the experimental group got the opportunity through CoRe-based lesson to stretch their thoughts and ideas in a free way and preferred a teaching method which didn't just show the concept, but allowed them to find it for themselves or which let them predict the solution and then confirm the result on their own and a lesson which encouraged their active participation.

• Journal of Korea Multimedia Society
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• v.22 no.11
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• pp.1233-1241
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• 2019

The goal of the sound-based mechanical fault diagnosis technique is to automatically find abnormal signals in the machine using acoustic emission. Conventional methods of using mathematical models have been found to be inaccurate due to the complexity of industrial mechanical systems and the existence of nonlinear factors such as noise. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We propose an automatic fault diagnosis method using discrete wavelet transform and power spectrum density using multi pattern recognition. First, we perform DWT-based filtering analysis for noise cancelling and effective feature extraction. Next, the power spectral density(PSD) is performed on each subband of the DWT in order to effectively extract feature vectors of sound. Finally, each PSD data is extracted with the features of the classifier using multi pattern recognition. The results show that the proposed method can not only be used effectively to detect faults as well as apply to various automatic diagnosis system based on sound.

• Journal of Environmental Science International
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• v.22 no.8
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• pp.965-977
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• 2013

Reliable long-term streamflow forecasting is invaluable for water resource planning and management which allocates water supply according to the demand of water users. It is necessary to get probabilistic forecasts to establish risk-based reservoir operation policies. Probabilistic forecasts may be useful for the users who assess and manage risks according to decision-making responding forecasting results. Probabilistic forecasting of seasonal inflow to Andong dam is performed and assessed using selected predictors from sea surface temperature and 500 hPa geopotential height data. Categorical probability forecast by Piechota's method and logistic regression analysis, and probability forecast by conditional probability density function are used to forecast seasonal inflow. Kernel density function is used in categorical probability forecast by Piechota's method and probability forecast by conditional probability density function. The results of categorical probability forecasts are assessed by Brier skill score. The assessment reveals that the categorical probability forecasts are better than the reference forecasts. The results of forecasts using conditional probability density function are assessed by qualitative approach and transformed categorical probability forecasts. The assessment of the forecasts which are transformed to categorical probability forecasts shows that the results of the forecasts by conditional probability density function are much better than those of the forecasts by Piechota's method and logistic regression analysis except for winter season data.

• Journal of the Korean Data and Information Science Society
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• v.15 no.1
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• pp.107-117
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• 2004

Change point testing problem is considered. Kernel density estimators are used for constructing proposed change point test statistics. The proposed method can be used to the hypothesis testing of not only parameter change but also distributional change. Bootstrap method is applied to get the sampling distribution of proposed test statistic. Small sample Monte Carlo Simulation were also conducted in order to show the performance of proposed method.

• Journal of the Korean Data and Information Science Society
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• v.25 no.4
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• pp.951-959
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• 2014

Recently Hazelton and Turlach (2009) proposed a weighted kernel density estimator for the deconvolution problem. In the case of Gaussian kernels and measurement error, they argued that the weighted kernel density estimator is a competitive estimator over the classical deconvolution kernel estimator. In this paper we consider weighted kernel density estimators when sample observations are contaminated by double exponentially distributed errors. The performance of the weighted kernel density estimators is compared over the classical deconvolution kernel estimator and the kernel density estimator based on the support vector regression method by means of a simulation study. The weighted density estimator with the Gaussian kernel shows numerical instability in practical implementation of optimization function. However the weighted density estimates with the double exponential kernel has very similar patterns to the classical kernel density estimates in the simulations, but the shape is less satisfactory than the classical kernel density estimator with the Gaussian kernel.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2002.05a
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• pp.652-655
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• 2002

The embedded atom method based on the density functional theory is used for calculating ground state properties of realistic metal systems. In this paper, we had corrected constitutive formulae and parameters on the palladium for the purpose of doing Embedded Atom Method analysis. And then we have computed the properties of the palladium on the fundamental scale of the atomic structure. In result, simulated ground state properties, such as the lattice constant, elastics constants and the sublimation energy, show good agreement with Daw's simulation data and with experimental data.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.572-575
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• 1997

The embedded atom method based on density functional theory was developed as a new means for calculating ground state properties of realistic metal system by Murray S. Daw, Stephen M. Foiles and Michael I. Baskes. In the paper, we had corrected constitutive formulae and parameters on the nickel for the purpose of doing Embedded Atom Method analysis. And then we have computed the properties of the nickel on the fundamental scale of the atomic structure. In result, simulated ground state properties, such as the lattice constant, elastics constants and sublimation energy, show good agreement with Daw's simulation data and with experimental data.