• Communications for Statistical Applications and Methods
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• v.10 no.3
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• pp.981-996
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• 2003

Bayesian inference is considered for switching mean models with the ARMA errors. We use noninformative improper priors or uniform priors. The fractional Bayes factor of O'Hagan (1995) is used as the Bayesian tool for detecting the existence of a single change or multiple changes and the usual Bayes factor is used for identifying the orders of the ARMA error. Once the model is fully identified, the Gibbs sampler with the Metropolis-Hastings subchains is constructed to estimate parameters. Finally, we perform a simulation study to support theoretical results.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.4
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• pp.286-295
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• 2007

This paper presents an intelligent PID control for stochastic systems with nonstationary nature. We optimally determine parameters of a PID controller through learning algorithm and propose an online PID control to compensate system errors possibly occurred in realtime implementations. A dynamic Bayesian network (DBN) model for system errors is additionally explored for making decision about whether an online control is carried out or not in practice. We apply our control approach to traffic control of Transmission Control Protocol (TCP) networks and demonstrate its superior performance comparing to a fixed PID from computer simulations.

• International Journal of Reliability and Applications
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• v.6 no.1
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• pp.41-51
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• 2005

The Bayes estimators of the parameters included in the complementary Weibull reliability model are obtained. In the process of deriving Bayes estimators, the scale and shape parameters of the complementary Weibull distribution are considered to be independent random variables having prior exponential distributions. The maximum likelihood estimators of the desired parameters are derived. Further, the least square estimators are obtained in closed forms. Simulation study is made using Monte Carlo method to make a comparison among the obtained estimators. The comparison is made by computing the root mean squared errors associated to each point estimation. Based on the numerical study, the Bayes procedure seems better than the maximum likelihood and least square procedures in the sense of having smaller root mean squared errors.

• Journal of the Korean Geotechnical Society
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• v.19 no.5
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• pp.7-14
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• 2003

In the back analysis of braced excavation based on displacement measurements, the accumulated errors of abnormal displacement caused by unexpected loads are usually observed. To minimize such errors, in this study, displacement increment was used fur back analysis rather than displacement for the conventional method. That is, the increment of sequential displacement is used as the objective function and the back analysis program is developed by taking advantage of sequential linear programming method by modified method of feasible directions. Based on small scale model test, the analysis of proposed method is verified.

• Journal of the Korean Data and Information Science Society
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• v.23 no.6
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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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.04a
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• pp.257-262
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• 1997

A compact measurement system is developed to measure in-process errors due to thermal deformation of a machine tool, this system is composed of a gauge, 5gap-sensors and a PC. The gauge is made of invar, which is a material that has a very low thermal expansion coefficient. A new neural network model is constructed to estimate thermally induced machine tool errors based on the measured data,the given data,that is a width of cut,a depth of cut, a feed rate, a spindel speed etc, and the calculated data. The detail of the model proposed is described in the paper together with the experimental methodologies using a proposed compact measurement system to examine the validity of the proposed approach.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.27-30
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• 1999

A spatio-temporal vector channel model is introduced for the position location (PL) estimation problem for CDMA cellular system environment. Two common ways for the PL make use of the AOA (Angle Of Arrival) and TDOA (Time Difference Of Arrival) from a subscriber to the multiple sensors (base stations). In this paper, we applied the derived vector channel to simulate the multipath channel for the angle of the signal arrival in CDMA systems. Cross-correlation method is a good candidate among other direction finding algorithms available in literature, especially in wideband modulation as in the CDMA system. The PL estimation errors are evaluated for different channels, which are obtained as a parameter of scattering radius of the suggested model. We noted that the number of sensors (base-stations) are related to the PL errors in favor of the available data.

• International Journal of Quality Innovation
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• v.1 no.1
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• pp.64-74
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• 2000

This paper investigates the issue of performance testing on web browsing environments. Among the typical non-functional characteristics, index of link validity will be deeply explored. A framework to certify link correctness in web site is proposed. All possible navigation paths are first formulated to represent a usage model with the Markov chain property, which is then used to generate test script file statistically. With collecting any existing failure information followed by tracing these testing browsed paths, certification analysis may be performed by applying Markov chain theory. The certification result will yield some significant information such as: test coverage, reliability measure, confidence interval, etc. The proposed mechanism may provide not only completed but also systemic methodologies to find any linking errors and other web technologies errors. Besides, an actual practice of the proposed approach to a web-based system will be demonstrated quantitatively through a certification tool.

• Journal of Korean Society for Quality Management
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• v.38 no.4
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• pp.491-503
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• 2010

This paper presents a research model, which identifies a relationship between medical error reduction, efficiency of organizational systems, and employee satisfaction with organizational support. The proposed model was tested through hypotheses, based on data collected from 210 respondents from the medical staff of large -sized (i.e., more than 500 beds) residential hospitals in cities of South Korea. The results of the study showed that medical error reduction is associated with corrective system and employee satisfaction with organizational support. Therefore, it is very important that organizations improve their employees' satisfaction by providing sufficient support (e.g., information support and sharing, work guide book, etc.) for their work. In addition, in organizational systems, the corrective system has positive relationship with medical error reduction. In terms of corrective procedures, leaders or managers can make improvements by providing and supporting a friendly work environment where errors may be reported without blame and discussed in order to be corrected.

• Journal of the Korean Statistical Society
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• v.24 no.2
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• pp.303-312
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• 1995

We consider the following type of general semi-parametric non-linear regression model : $y_i = f_i(\theta) + \epsilon_i, i=1, \cdots, n$ where ${f_i(\cdot)}$ represents the set of non-linear functions of the unknown parameter vector $\theta' = (\theta_1, \cdots, \theta_p)$ and ${\epsilon_i}$ represents the set of measurement errors with unknown distribution. Under suitable finite-sample, small-dispersion asymptotic framework, we derive a general lower bound for the asymptotic mean squared error (AMSE) matrix of the Gauss-consistent estimator of $\theta$. We then prove the fundamental result that the general non-linear least squares estimator (NLSE) is an optimal estimator within the class of all regular Gauss-consistent estimators irrespective of the type of the distribution of the measurement errors.