• Korean Journal of Cognitive Science
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• v.25 no.2
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• pp.159-187
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• 2014

Approximate number sense(hereafter, ANS) is the ability to compare and operate upon numerosity information. The numerosity comparison task is used to measure ANS. However, there is considerable variance among previous reports of ANS acuity which may be related to different task formats used. Here, we aim to investigate whether the format of the numerosity comparison task influences measurements of ANS acuity. We compared two task formats; 1) an intermixed format presenting two intermixed arrays of black and white dots, and 2) a side-by-side format showing two arrays of dots side by side. The intermixed format likely makes additional demands on general cognitive resources for inhibitory control, selective attention, or visuospatial working memory. The performance on the intermixed format was significantly lower than that of the side-by-side format resulting in an underestimation of ANS acuity compared to the expected trajectory of ANS development. In addition, the ANS acuity measured from only the side-by-side format was correlated with children's mathematical achievement and age. Our results demonstrate that measurement of ANS from the side-by-side format has higher construct and predictive validity compared to that of the intermixed format.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.3
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• pp.47-54
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• 2009

In the manufacturing industry, there has been a significant increase in the use of coordinate measuring machines(CMM). In this paper, the sources of CMM measurement performance are discussed. The effects of workpiece position, length and orientation are analyzed by using the design of experiments. Both a fractional factorial design and a factorial design are employed to conduct the experimental study. The analysis of variance is performed to determine the significance of factors in the experiment and regression analysis is applied to make the measurement approximate model. The results show that position along the Z axis, length and orientation affect the CMM measurement performance.

• The Korean Journal of Applied Statistics
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• v.23 no.6
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• pp.1125-1145
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• 2010

For modeling(skewed) semicircular data, we derive a new exponential family of distributions. We extend it to the l-axial exponential family of distributions by a projection for modeling any arc of arbitrary length. It is straightforward to generate samples from the l-axial exponential family of distributions. Asymptotic result reveals that the linear exponential family of distributions can be used to approximate the l-axial exponential family of distributions. Some trigonometric moments are also derived in closed forms. The maximum likelihood estimation is adopted to estimate model parameters. Some hypotheses tests and confidence intervals are also developed. The Kolmogorov-Smirnov test is adopted for a goodness of t test of the l-axial exponential family of distributions. Samples of orientations are used to demonstrate the proposed model.

• Korean Management Science Review
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• v.28 no.2
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• pp.1-16
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• 2011

In this study we suggested two optimization models to answer a question from an investor standpoint : how many convertible bonds should one convert, and how many keep? One model minimizes certain risk to the minimum required expected return, the other maximizes the expected return subject to the maximum acceptable risk. In comparison with Markowitz portfolio models, which use the variance of return, our models used Conditional Value-at-Risk(CVaR) for risk measurement. As a coherent measurement, CVaR overcomes the shortcomings of Value-at-Risk(VaR). But there are still difficulties in solving CVaR including optimization models. For this reason, we adopted Rockafellar and Uryasev's[18, 19] approach. Then we could approximate the models as linear programming problems with scenarios. We also suggested to extend the models with credit risk, and applied examples of our models to Hynix 207CB, a convertible bond issued by the global semiconductor company Hynix.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2004.04a
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• pp.563-566
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• 2004

An intelligent Kalman filter (IKF) is proposed for tracking an incoming anti-ship missile. In the proposed IKF, the unknown target acceleration is regarded as an additive process noise. When the target maneuver is occurred, the residual of the Kalman filter increases in proportion to its magnitude. From this fact, the overall process noise variance can be approximated from the filter residual and its variation at every sampling time. A fuzzy system is utilized to approximate this valiance, and the genetic algorithm (GA) is applied to optimize the fuzzy system. In computer simulations, the tracking performance of the proposed IKF is compared with those of conventional maneuvering target tracking methods.

• Proceedings of the Korean Association for Survey Research Conference
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• 2006.12a
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• pp.67-83
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• 2006

In successive sampling on two occasions the problem of estimating a finite population quantile has been considered. The theory developed aims at providing the optimum estimates by combining (i) three double sampling estimators viz. ratio-type, product-type and regression-type, from the matched portion of the sample and (ii) a simple quantile based on a random sample from the unmatched portion of the sample on the second occasion. The approximate variance formulae of the suggested estimators have been obtained. Optimal matching fraction is discussed. A simulation study is carried out in order to compare the three estimators and direct estimator. It is found that the performance of the regression-type estimator is the best among all the estimators discussed here.

• Journal of applied mathematics & informatics
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• v.30 no.1_2
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• pp.135-145
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• 2012

Traditionally, ERM (Equivalent Random Method) is used to determine number of circuits in an overflow circuit group with rough traffic which has vmr(variance to mean ratio) greater than one. Recently, IPP(Interrupted Poisson Process) approximate method which represents the collective feature of the overflow has been introduced. The negative binomial loss formula can be applied to determine the required number of circuits in the overflow circuit group. In this paper, we deal with the negative binomial loss formula and determination method of number of circuits. We also analyze and compare these three loss formulas.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1455-1464
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• 2013

This paper develops maximum likelihood estimators (MLEs) of unknown parameters in an exponentiated half-logistic distribution based on a progressively type-II censored sample. We obtain approximate confidence intervals for the MLEs by using asymptotic variance and covariance matrices. Using importance sampling, we obtain Bayes estimators and corresponding credible intervals with the highest posterior density and Bayes predictive intervals for unknown parameters based on progressively type-II censored data from an exponentiated half logistic distribution. For illustration purposes, we examine the validity of the proposed estimation method by using real and simulated data.

• Journal of Korea Multimedia Society
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• v.20 no.2
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• pp.163-169
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• 2017

There are various algorithms evaluating a threshold for image segmentation. Among them, Otsu's algorithm sets a threshold based on the histogram. It finds the between-class variance for all over gray levels and then sets the largest one as Otsu's optimal threshold, so we can see that Otsu's algorithm requires a lot of the computation. In this paper, we improved the amount of computational needs by using estimated Otsu's threshold rather than computing for all the threshold candidates. The proposed algorithm is compared with the original one in computation amount and accuracy. we confirm that the proposed algorithm is about 29 times faster than conventional method on single processor and about 4 times faster than on parallel processing architecture machine.

• Journal of the Korean Statistical Society
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• v.36 no.4
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• pp.543-556
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• 2007

In successive sampling on two occasions the problem of estimating a finite population quantile has been considered. The theory developed aims at providing the optimum estimates by combining (i) three double sampling estimators viz. ratio-type, product-type and regression-type, from the matched portion of the sample and (ii) a simple quantile based on a random sample from the unmatched portion of the sample on the second occasion. The approximate variance formulae of the suggested estimators have been obtained. Optimal matching fraction is discussed. A simulation study is carried out in order to compare the three estimators and direct estimator. It is found that the performance of the regression-type estimator is the best among all the estimators discussed here.