• 한국도로학회논문집
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• 제9권4호
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• pp.215-226
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• 2007

차량방호 안전시설에 대한 성능의 검증은 충돌시험의 가속도와 각속도 데이터를 사용하여 산정한 탑승자 안전지수를 평가하여 이루어진다. 탑승자 안전지수로는 THIV(Theoretical Head Impact Velocity), PHD(Post-impact Head Deceleration), ASI(Acceleration Severity Index), OIV(Occupant Impact Velocity)와 ORA(Occupant Ridedown Acceleration)가 있다. 탑승자 안전지수 계산에 상이한 데이터 처리과정과 수치절차의 적용이 가능하기 때문에 동일한 시험 데이터에 대하여 다양한 탑승자 안전지수값이 결정될 수 있어서 혼란이 초래되고 있는 실정이다. 이러한 문제를 해결하기 위하여 다양한 상세절차와 데이터 처리과정이 탑승자 안전지수에 미치는 영향을 조사하였다. 지침에 제시된 계측시간간격을 사용하여 차량충돌시험이 수행된다면 보간법과 수치적분방법은 THIV와 OIV 값에 영향을 크게 미치지 않았다. 그리고 PHD에 대한 10msec 이동평균방법과 데이터 처리과정의 영점보정은 탑승자 안전지수에 상당한 영향을 미치기 때문에 이에 관한 구체적인 방법이 지침에 규정되어야 한다.

• Perspectives in Nursing Science
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• 제11권2호
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• pp.87-93
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• 2014

Purpose: The use of salivary biomarkers for stress research is increasing based on the convenience of collection, affordability and scientific merit. This short review provides an overview of the state of the science of salivary biomarkers utilized in research related to stress. Methods: An integrative review was conducted. Results: The trend of utilizing salivary biomarkers in stress research was reviewed, specifically, focusing on the use of endocrine and inflammatory biomarkers incorporated in previous stress research. Then, a review of sampling procedures for salivary biomarkers and the analytic methods is provided. Finally, a discussion on the strengths and areas for improvement in the use of salivary biomarkers in stress research is included. Conclusion: Salivary biomarkers as an alternative to blood biomarkers are increasingly being recognized as a legitimate source for analyzing the stress response in humans.

• 대한산업공학회지
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• 제23권4호
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• pp.755-767
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• 1997

Analyzing autocorrelated data set is still an open problem. Developing on easy and efficient method for severe positive correlated data set, which is common in simulation output, is vital for the simulation society. Bootstrap is on easy and powerful tool for constructing non-parametric inferential procedures in modern statistical data analysis. Conventional bootstrap algorithm requires iid assumption in the original data set. Proper choice of resampling units for generating replicates has much to do with the structure of the original data set, iid data or autocorrelated. In this paper, a new bootstrap resampling scheme is proposed to analyze the autocorrelated data set : the Threshold Bootstrap. A thorough literature search of bootstrap method focusing on the case of autocorrelated data set is also provided. Theoretical foundations of Threshold Bootstrap is studied and compared with other leading bootstrap sampling techniques for autocorrelated data sets. The performance of TB is reported using M/M/1 queueing model, else the comparison of other resampling techniques of ARMA data set is also reported.

• Communications for Statistical Applications and Methods
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• 제10권2호
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• pp.507-517
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• 2003

Self-organizing map (SOM) has been developed mainly by T. Kohonen and his colleagues as a unsupervised learning neural network. Because of its topological ordering property, SOM is known to be very useful in pattern recognition and text information retrieval areas. Recently, data miners use Kohonen´s mapping method frequently in exploratory analyses of large data sets. One problem facing SOM builder is that there exists no sensible criterion for evaluating goodness-of-fit of the map at hand. In this short communication, we propose valid evaluation procedures for the Kohonen SOM of any size. The methods can be used in selecting the best map among several candidates.

• Journal of the Korean Data and Information Science Society
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• 제7권1호
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• pp.1-12
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• 1996

The Gibbs sampler is a substantially powerful tool in Bayesian analysis. However, it is necerssary to choose the numbert of iterations and the size of random samples. This problem has been studied by many researchers. The proposed procedures by them are generally difficult to apply to a practical problem. The attraction of the sampling based approaches is their conceptual simplicity and ease of implementation for users with available computing resources but without numerical analytic efforts. In this paper we consider the problem of determining the number of iterations t, which is simple to application.

• Korea-Australia Rheology Journal
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• 제18권2호
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• pp.91-98
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• 2006

We compare FT (Fourier Transform) and SD (Stress Decomposition), the interpretation methods for LAOS (Large Amplitude Oscillatory Shear). Although the two methods are equivalent in mathematics. they are significantly different in numerical procedures. Precision of FT greatly depends on sampling rate and length of data because FT of experimental data is the discrete version of Fourier integral theorem. FT inevitably involves unnecessary frequencies which must not appear in LAOS. On the other hand, SD is free from the problems from which FT suffers, because SD involves only odd harmonics of primary frequency. SD is based on two axioms on shear stress: [1] shear stress is a sufficiently smooth function of strain and its time derivatives; [2] shear stress satisfies macroscopic time-reversal symmetry. In this paper, we compared numerical aspects of the two interpretation methods for LAOS.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1991년도 하계학술대회 논문집
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• pp.699-702
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• 1991

A servo system requires faster and more accurate dynamic responses. Generally a PD control is mainly used to obtain the precision, and in the other hand a fuzzy control to improve the transient response and to cope with the nonlinearity of systems. Recently hybrid control, which is attempted to combine the advantages of PD control and a Fuzzy control was proposed, but this technique requires complicate design procedures. Therefore in this paper, a Fuzzy controller with a series of membership functions, and various sampling periods and rules, was designed on the basis of Lyapunov stability theory and auto tuning methods of input scale factors. And also it was showed to have the excellent adaptive performances against internal-external disturbances and the usefulness of this controller from the results of simulations.

• International Journal of Reliability and Applications
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• 제16권2호
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• pp.55-79
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• 2015

It is well known that using any additional information in the estimation of unknown parameters with new sample of observations diminishes the sampling units needed and minimizes the risk of new estimators. There are many rational reasons to assure that the existence of additional information in practice and there exists many practical cases in which additional information is available in the form of target value (initial value) about the unknown parameters. This article is described the problem of how the prior initial value about the unknown parameters can be utilized and combined with classical Bayes estimator to get a new combination of Bayes estimator and prior value to improve the properties of the new combination. In this article, two classes of Bayes-shrinkage and preliminary test Bayes-shrinkage estimators are proposed for the scale parameter of exponential distribution. The bias, risk and risk ratio expressions are derived and studied. The performance of the proposed classes of estimators is studied for different choices of constants engaged in the estimators. The comparisons, conclusions and recommendations are demonstrated.

• Journal of the Korean Data and Information Science Society
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• 제23권6호
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• pp.1271-1277
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• 2012

In this paper, we propose an estimation method of the parameter in an exponential distribution based on a progressive Type I interval censored sample with semi-missing observation. The maximum likelihood estimator (MLE) of the parameter in the exponential distribution cannot be obtained explicitly because the intervals are not equal in length under the progressive Type I interval censored sample with semi-missing data. To obtain the MLE of the parameter for the sampling scheme, we propose a method by which progressive Type I interval censored sample with semi-missing data is converted to the progressive Type II interval censored sample. Consequently, the estimation procedures in the progressive Type II interval censored sample can be applied and we obtain the MLE of the parameter and survival function. It will be shown that the obtained estimators have good performance in terms of the mean square error (MSE) and mean integrated square error (MISE).

• Journal of the Korean Data and Information Science Society
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• 제23권6호
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• pp.1241-1247
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• 2012

The paper considers empirical Bayes (EB) and hierarchical Bayes (HB) predictors of the finite population mean under a linear regression model with measurement errors We discuss how to calculate the mean squared prediction errors of the EB predictors using jackknife methods and the posterior standard deviations of the HB predictors based on the Markov Chain Monte Carlo methods. A simulation study is provided to illustrate the results of the preceding sections and compare the performances of the proposed procedures.