• Journal of information and communication convergence engineering
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• v.8 no.3
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• pp.281-288
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• 2010

This paper investigates the performance of IEEE 802.11p wireless access in vehicular environments (WAVE) system in small-scale fading models reported by Georgia Institute of Technology (Georgia Tech). We redesign the small-scale fading models to be applied to the computer simulation and develop the IEEE 802.11p WAVE physical layer simulator to provide the bit error rate and packet error rate performances. Moreover, a new channel estimator using decision directed channel estimation and linear minimum mean square error smoothing is proposed in order to improve the performance of the conventional least square channel estimator using two identical long training symbols. The simulation results are satisfactorily coincident with the scenarios of Georgia Tech report, and the proposed channel estimator significantly outperforms the conventional channel estimator.

• Communications for Statistical Applications and Methods
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• v.24 no.4
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• pp.397-419
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• 2017

A four-parameter extended fatigue lifetime model called the odd Birnbaum-Saunders geometric distribution is proposed. This model extends the odd Birnbaum-Saunders and Birnbaum-Saunders distributions. We derive some properties of the new distribution that include expressions for the ordinary moments and generating and quantile functions. The method of maximum likelihood and a Bayesian approach are adopted to estimate the model parameters; in addition, various simulations are performed for different parameter settings and sample sizes. We propose two new models with a cure rate called the odd Birnbaum-Saunders mixture and odd Birnbaum-Saunders geometric models by assuming that the number of competing causes for the event of interest has a geometric distribution. The applicability of the new models are illustrated by means of ethylene data and melanoma data with cure fraction.

• Proceedings of the KSRS Conference
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• 1998.09a
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• pp.49-57
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• 1998

CO2 transfer velocity is one of the key parameters for CO2 flux estimation at air - sea interface. However, current studies show that significant inconsistency still exists in its estimation when using different models and remotely sensed data sets, which acts as one of the main uncertainties involved in the computation of CO2 exchange coefficient between air - sea interface. In this study, wind data collected from SSM/I and scatterometer onboard ERS-1, in conjunction with operational NOAA/AVHRR, are applied to different models for calculating CO2 exchange coefficient in the world ocean. Their interrelationship and discrepancies inherent with different models and satellite data are analyzed. Finally, the seasonal and inter-annual variation of CO2 exchanges coefficient for different ocean basins are presented and discussed.

• Communications for Statistical Applications and Methods
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• v.10 no.1
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• pp.19-30
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• 2003

Spatiotemporal statistical models are used for analyzing space-time data in many fields, such as environmental sciences, meteorology, geology, epidemiology, forestry, hydrology, fishery, and so on. It is well known that classical spatiotemporal process modeling requires the estimation of space-time variogram or covariance functions. In practice, the estimation of such variogram or covariance functions are computationally difficult and highly sensitive to data structures. We investigate a Bayesian hierarchical model which allows the specification of a more realistic series of conditional distributions instead of computationally difficult and less realistic joint covariance functions. The spatiotemporal model investigated in this study allows both spatial component and autoregressive temporal component. These two features overcome the inability of pure time series models to adequately predict changes in trends in individual sites.

• East Asian mathematical journal
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• v.5 no.1
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• pp.95-110
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• 1989

In a general variance component model, nonnegative quadratic estimators of the components of variance are considered which are invariant with respect to mean value translaion and have minimum bias (analogously to estimation theory of mean value parameters). Here the minimum is taken over an appropriate cone of positive semidefinite matrices, after having made a reduction by invariance. Among these estimators, which always exist the one of minimum norm is characterized. This characterization is achieved by systems of necessary and sufficient condition, and by a cone restricted pseudoinverse. In models where the decomposing covariance matrices span a commutative quadratic subspace, a representation of the considered estimator is derived that requires merely to solve an ordinary convex quadratic optimization problem. As an example, we present the two way nested classification random model. An unbiased estimator is derived for the mean squared error of any unbiased or biased estimator that is expressible as a linear combination of independent sums of squares. Further, it is shown that, for the classical balanced variance component models, this estimator is the best invariant unbiased estimator, for the variance of the ANOVA estimator and for the mean squared error of the nonnegative minimum biased estimator. As an example, the balanced two way nested classification model with ramdom effects if considered.

• Communications for Statistical Applications and Methods
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• v.17 no.6
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• pp.811-827
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• 2010

This paper deals with a density estimation method in binary choice models that can be regarded as a statistical inverse problem. We use an orthogonal basis to estimate density function and consider the choice of an appropriate truncation parameter to reflect the model complexity and the prediction accuracy. We propose a data-dependent rule to choose the truncation parameter in the context of binary choice models. A numerical simulation is provided to illustrate the performance of the proposed method.

• Transactions of the Korean hydrogen and new energy society
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• v.32 no.3
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• pp.189-195
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• 2021

A compressed hydrogen tank is to be repressurized to 40 bar by being connected to a high-pressure line containing hydrogen at 50 bar and 25℃. Hydrogen filling time and the corresponding hydrogen temperature has been estimated when the filling process stopped according to several thermodynamic models. During the process of cooling the hydrogen tank, hydrogen temperature and pressure vs. time estimation was performed using Aspen Dynamics. Filling time, hydrogen temperature after filling hydrogen gas, cooling time and the final tank pressure after tank filling process have been completed according to the thermodynamic models are almost same.

• The Korean Journal of Applied Statistics
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• v.23 no.4
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• pp.669-681
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• 2010

Value-at-Risk(VaR) is an important part of risk management in the financial industry. This paper present a VaR forecasting for financial time series based on the quantile regression for GARCH models recently developed by Lee and Noh (2009). The proposed VaR forecasting features the direct conditional quantile estimation for GARCH models that is well connected with the model parameters. Empirical performance is measured by several backtesting procedures, and is reported in comparison with existing methods using sample quantiles.

• Korean Management Science Review
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• v.11 no.3
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• pp.153-167
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• 1994

Credibility theory has provided with a useful tool the assignment of weighting factor that reflects the credibility of the observed individual and collective experience to secure fair experience rate-,making. We review credibility models which can effectively estimate risk premiums using credibility theory, and suggest an empirical Bayed model based on the collective statistics to estimate the structural parameters. To illustrate the use of evolutionary models, the models are applied to the actual data, such as loss ratio, claim frequencies and severity, in the Korean automobile insurance. Also the possibilities of generalizations and applications of empirical models are discussed.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 2001.04a
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• pp.461-467
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• 2001

Shaking table tests were performed with full scale models of stone parapet on the ancient rampart. The objectives of these tests are to study the seismic behavior of the parapet and to obtain quantitative estimation of the intensities of historical earthquakes. Two test models were made based on the structure of the parapet remnant of a mountain fortress in Bukhan-San located in Seoul. Two types of infilling material are considered. The responses to models were tested subjected to three kinds of input motion.