• Journal of the Korean Statistical Society
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• v.6 no.1
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• pp.65-76
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• 1977

The relative importance of single-shot kill probabilities, rates of fire, weapon allocation strategies, and the size of initial force in warfare between two force with heterogeneous multiple weapon systems are considered by examining their effect on a natural measure of effectiveness, the expected number of survivors. Attrition equations are derived via stochastic formulation to represent the mean course of battle having an underlying probability distribution. It is assumed that each side uses indirect area fires. Level of intelligence activities are reflected in the availability of spontaneous information on the current enemy status. Depending on the availability of the information on the current enemy status, each participatory unit may follow 1) a prescribed attack pattern (fraction of the available units assigned to various enemy targets) or 2) an adaptive attack pattern depending on the enemy status at that time. Conditions for possible stalemate are discussed.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.801-813
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• 2005

The discretization algorithms for continuous data have been actively studied in the area of data mining. These discretizations are very important in data analysis, especially for efficient model selection in data mining. So, in this paper, we introduce the principles of some mutiway discretization algorithms including KEX, 1R and CN4 algorithm and investigate the efficiency of these algorithms through numerical study. For various underlying distribution, we compare these algorithms in view of misclassification rate.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.769-780
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• 2005

Recently, the discretization algorithms for continuous data have been actively studied. But there are few articles to compare the efficiency of these algorithms. In this paper we introduce the principles of some binary discretization algorithms including C4.5, CART and QUEST and investigate the efficiency of these algorithms through numerical study. For various underlying distribution, we compare these algorithms in view of misclassification rate and MSE. Real data examples are also included.

• Journal of the Korean Data and Information Science Society
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• v.24 no.3
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• pp.625-636
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• 2013

In this paper we study four kernel machines for estimating expected shortfall, which are constructed through combinations of support vector quantile regression (SVQR), restricted SVQR (RSVQR), least squares support vector machine (LS-SVM) and support vector expectile regression (SVER). These kernel machines have obvious advantages such that they achieve nonlinear model but they do not require the explicit form of nonlinear mapping function. Moreover they need no assumption about the underlying probability distribution of errors. Through numerical studies on two artificial an two real data sets we show their effectiveness on the estimation performance at various confidence levels.

• IEIE Transactions on Smart Processing and Computing
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• v.5 no.4
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• pp.289-293
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• 2016

As more mobile devices are equipped with multi-core CPUs and are required to execute many compute-intensive multimedia applications, it is important to optimize the systems, considering the underlying parallel hardware architecture. In this paper, we implement and optimize ray-tracing application tailored to a given mobile computing platform with multiple heterogeneous processing elements. In this paper, a lightweight ray-tracing application is specified and implemented in Kahn process network (KPN) model-of-computation, which is known to be suitable for the description of real-time applications. We take an open-source C/C++ implementation of ray-tracing and adapt it to KPN description in the Distributed Application Layer framework. Then, several possible configurations are evaluated in the target mobile computing platform (Exynos 5422), where eight heterogeneous ARM cores are integrated. We derive the optimal degree of parallelism and a suitable distribution of the replicated tasks tailored to the target architecture.

• Communications for Statistical Applications and Methods
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• v.16 no.6
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• pp.891-901
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• 2009

In this paper, we investigate the approach to estimate VaR under the transformed GARCH model. The time series are transformed to approximate to the underlying distribution of error terms and then the parameters and the one-sided prediction interval are estimated with the transformed data. The back-transformation is applied to compute the VaR in the original data scale. The analyses on the asset returns of KOSPI and KOSDAQ are presented to verify the accuracy of the coverage probabilities of the proposed VaR.

• The Korean Journal of Applied Statistics
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• v.4 no.1
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• pp.33-45
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• 1991

In the analysis of changepoint model the situation where single observation is taken at each time point has been considered. In an effort to extend this to the general situation, we may consider the changepoint model with more than one observation at each time point. These tests are developed without assuming any particular form for the underlying distribution, we propose the one-sided and two-sided nonparametric tests by extending the tests that have been considered in the changepoint model with single observation at each time point and obtain their asymptotic null distributions. We compare the empirical powers among the extended changepoint tests under one-sided or two-sided alternatives. We also compare the powers of the extended changepoint tests with those of the original test via the Monte Carlo simulation.

• Proceedings of the Korean Reliability Society Conference
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• 2004.07a
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• pp.227-232
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• 2004

The failure of geogrids can be defined as an excessive creep strain which causes the collapse of slopes and embankments. In this study, the accelerated creep tests were applied to two different types of polyester geogrids, at 75, 80, 85$^{\circ}C$ by applying 50% load of ultimate tensile strengths using a newly designed test equipment which is allowed the creep testing at higher temperatures. And then the creep curves were shifted and superposed in the time axis by applying time-temperature supposition principles. In predicting the lifetimes of geogrids, the underlying distribution for failure times were determined based on identification of the failure mechanism. The results indicate that the conventional procedures with the newly designed test equipment are shown to be effective in prediction of the lifetimes of geogrids with shorter test times. In addition, the predicted lifetimes of geogrids having different structures at various creep strains give guidelines for users to select the proper geogrids in the fields.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.3
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• pp.1-20
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• 2001

The amount of financial information in sophisticated large data bases is huge and makes interfirm performance comparisons very difficult or at least very time consuming. The purpose of this paper is to investigate whether neural networks in the form of self-organizing maps (SOM) can be successfully employed to manage the complexity for competitive financial benchmarking. SOM is known to be very effective to visualize results by projecting multi-dimensional financial data into two-dimensional output space. Using the SOM, we overcome the problems of finding an appropriate underlying distribution and the functional form of data when structuring and analyzing a large data base, and show an efficient procedure of competitive financial benchmarking through clustering firms on two-dimensional visual space according to their respective financial competitiveness. For the empirical purpose, we analyze the data base of annual reports of 100 Korean listed companies over the years 1998, 1999, and 2000.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.435-442
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• 2017

Consider the problem of estimating a $p{\times}1$ mean vector ${\theta}$ (p ${\geq}$ 3) under the quadratic loss from multi-variate normal population. We find a James-Stein type estimator which shrinks towards the projection vectors when the underlying distribution is that of a variance mixture of normals. In this case, the norm ${\parallel}{\theta}-K{\theta}{\parallel}$ is known where K is a projection vector with rank(K) = q. The class of this type estimator is quite general to include the class of the estimators proposed by Merchand and Giri (1993). We can derive the class and obtain the optimal type estimator. Also, this research can be applied to the simple and multiple regression model in the case of rank(K) ${\geq}2$.