• The Korean Journal of Physiology and Pharmacology
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• v.13 no.5
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• pp.367-371
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• 2009

The estimation of 90% parametric confidence intervals (CIs) of mean AUC and Cmax ratios in bioequivalence (BE) tests are based upon the assumption that formulation effects in log-transformed data are normally distributed. To compare the parametric CIs with those obtained from nonparametric methods we performed repeated estimation of bootstrap-resampled datasets. The AUC and Cmax values from 3 archived datasets were used. BE tests on 1,000 resampled data sets from each archived dataset were performed using SAS (Enterprise Guide Ver.3). Bootstrap nonparametric 90% CIs of formulation effects were then compared with the parametric 90% CIs of the original datasets. The 90% CIs of formulation effects estimated from the 3 archived datasets were slightly different from nonparametric 90% CIs obtained from BE tests on resampled datasets. Histograms and density curves of formulation effects obtained from resampled datasets were similar to those of normal distribution. However, in 2 of 3 resampled log (AUC) datasets, the estimates of formulation effects did not follow the Gaussian distribution. Bias-corrected and accelerated (BCa) CIs, one of the nonparametric CIs of formulation effects, shifted outside the parametric 90% CIs of the archived datasets in these 2 non-normally distributed resampled log (AUC) datasets. Currently, the 80~125% rule based upon the parametric 90% CIs is widely accepted under the assumption of normally distributed formulation effects in log-transformed data. However, nonparametric CIs may be a better choice when data do not follow this assumption.

• International Journal of Reliability and Applications
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• v.5 no.4
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• pp.129-145
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• 2004

We use a novel, forced censoring technique that closer fits the lower tails of strenth distributions to better estimate extremly smaller percentiles for measuring progress in continuous improvement initiatives. These percentiles are of greater interest for companies, government oversight organizations, and consumers concerned with safely and preventing accidents for many products in general, but specifically for medium density fiberboard (MDF). The international industrial standard for MDF for measuring highest quality is internal bond (IB, also called tensile strengh) and its smaller percentiles are crucial, especially the first percentile and lower ones. We induce censoring at a value just above the median to weight lower observations more. Using this approach, we have better fits in the lower tails of the distribution, where these samller percentiles are impacted most. Finally, bootstrap estimates of the small percentiles are used to demonstrate improved intervals by our forced censoring approach and the fitted model. There was evidence from the study to suggest that MDF has potentially different failure modes for early failures. Overall, our approach is parsimonious and is suitable for real time manufacturing settings. The approach works for either strengths distributions or lifetime distributions.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1612-1620
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• 2003

This papers describes a nonlinear transfer function modelling of designed GaAs FET power amplifier by measured and simulated values of designed PA amplifier for multi­carrier transmission system, With the results of PA nonlinearity characteristic, we can estimates AM­AM and AM­PM of designed PA. According to the estimated nonlinear characteristics, we can analysis the ACPR of PA for spectral regrowth, the error vector measurement(EVM) of constallation signals and bit error rate of QPSK and 64­QAM. The suggested nonlinear modelling results are used to get an accurate estimate of digital characteristics between PA amplifier and wireless multi­carrier transmission system using OFDM.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1326-1328
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• 2003

An elliptical basis function (EBF) network is proposed in this study for the classification of remotely sensed images. Though similar in structure, the EBF network differs from the well-known radial basis function (RBF) network by incorporating full covariance matrices and uses the expectation-maximization (EM) algorithm to estimate the basis functions. Since remotely sensed data often take on mixture -density distributions in the feature space, the proposed network not only possesses the advantage of the RBF mechanism but also utilizes the EM algorithm to compute the maximum likelihood estimates of the mean vectors and covariance matrices of a Gaussian mixture distribution in the training phase. Experimental results show that the EM-based EBF network is faster in training, more accurate, and simpler in structure.

• Korean Journal of Remote Sensing
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• v.1 no.1
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• pp.5-27
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• 1985

A hill-sliding technique was devised to extract Gaussian clusters from the multivariate probability density estimates of sample data for the first step of iterative unsupervised classification. The underlying assumption in this approach was that each cluster possessed a unimodal normal distribution. The key idea was that a clustering function proposed could distinguish elements of a cluster under formation from the rest in the feature space. Initial clusters were extracted one by one according to the hill-sliding tactics. A dimensionless cluster compactness parameter was proposed as a universal measure of cluster goodness and used satisfactorily in test runs with Landsat multispectral scanner (MSS) data. The normalized divergence, defined by the cluster divergence divided by the entropy of the entire sample data, was utilized as a general separability measure between clusters. An overall clustering objective function was set forth in terms of cluster covariance matrices, from which the cluster compactness measure could be deduced. Minimal improvement of initial data partitioning was evaluated by this objective function in eliminating scattered sparse data points. The hill-sliding clustering technique developed herein has the potential applicability to decomposition of any multivariate mixture distribution into a number of unimodal distributions when an appropriate diatribution function to the data set is employed.

• Structural Engineering and Mechanics
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• v.50 no.5
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• pp.653-664
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• 2014

Wind fragility analysis provides a quantitative instrument for delineating the safety performance of civil structures under hazardous wind loading conditions such as cyclones and tornados. It has attracted and would be expected to continue to attract intensive research spotlight particularly in the nowadays worldwide context of adapting to the changing climate. One of the challenges encumbering efficacious assessment of the safety performance of existing civil structures is the possible incompleteness of the structural appraisal data. Addressing the issue of the data missingness, the study presented in this paper forms a first attempt to investigate the feasibility of using the expectation-maximization (EM) algorithm and Bayesian techniques to predict the wind fragilities of existing civil structures. Numerical examples of typical linear or hysteretic shear frames are introduced with the wind loads derived from a widely used power spectral density function. Specifically, the application of the maximum a posteriori estimates of the distribution parameters for the story stiffness is examined, and a surrogate model is developed and applied to facilitate the nonlinear response computation when studying the fragilities of the hysteretic shear frame involved.

• Communications for Statistical Applications and Methods
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• v.26 no.5
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• pp.445-461
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• 2019

It is possible that data are not always fitted with sufficient precision by the existing distributions; therefore this article presents a methodology that enables the use of families of asymmetric distributions as alternative probabilistic models for survival analysis, with censorship on the right, different from those usually studied (the Exponential, Gamma, Weibull, and Lognormal distributions). We use a more flexible parametric model in terms of density behavior, assuming that data can be fit by a distribution of stable distribution families considered unconventional in the analyses of survival data that are appropriate when extreme values occur, with small probabilities that should not be ignored. In the methodology, the determination of the analytical expression of the risk function h(t) of the $L{\acute{e}}vy$ distribution is included, as it is not usually reported in the literature. A simulation was conducted to evaluate the performance of the candidate distribution when modeling survival times, including the estimation of parameters via the maximum likelihood method, survival function ${\hat{S}}$(t) and Kaplan-Meier estimator. The obtained estimates did not exhibit significant changes for different sample sizes and censorship fractions in the sample. To illustrate the usefulness of the proposed methodology, an application with real data, regarding the survival times of patients with colon cancer, was considered.

• Journal of the Korean Crystal Growth and Crystal Technology
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• v.7 no.1
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• pp.81-92
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• 1997

Rear floating junction cell (RFJC), using the buried contact technology, is capable of eliminating the efficiency limitations on the single sided cells by providing betterear surface passivation. The implementation of this structure, is simpler and lower in cost and therefore viable for commercial production. However, the contributions, due to damages in the two sets of grooves, to the total dark saturation current density has limited the achievable efficiency of the RFJC to only 21.5 %. This Paper reports on the efficiency estimates of RFJC using PC-1D.

• Journal of The Korean Society of Agricultural Engineers
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• v.65 no.4
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• pp.11-23
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• 2023

In Korea, open burning of agricultural residues is prevalent due to inadequate collection systems, which have caused environmental impacts such as GHGs and particulates. This illegal treatment of agricultural residues also results in economic loss, considering that agricultural residues can be utilized as resources such as pellets and energy sources. To understand the effect of avoiding open burning, this study evaluated the economic, environmental, and social effects of two alternative management options for agricultural residues: incineration and pelletizing. The study estimates the potential amount and dry weight by region for 18 items, taking various factors into account. Regarding the economic aspect, pelletizing facilities in all regions in Korea create economic benefits. This study shows that most regions have an environmental advantage by pelletizing residues. However, incineration creates more environmental benefits than pelletizing in metropolitan cities with relatively low density of residues. It is expected that the environmental, economic, and social findings of this study can be used to inform policies for bioenergy as the need for agricultural residue increases.

• Korean Journal of Fisheries and Aquatic Sciences
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• v.57 no.3
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• pp.302-309
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• 2024

This study estimates the target strength of anchovy Engraulis japonicus required for studying their distribution and density using acoustics and evaluates the acoustic scattering characteristics of anchovies by frequency using the Kirchoff ray mode (KRM) model. The experiment was conducted on 30 anchovies with 4.7-21.5 cm total length. The maximum TS_cm (Simming angle, 9.1°; standard deviation, ± 13.1°) according to total length was -66.9, -65.2, -64.4, and -63.4 dB at 38, 70, 120, and 200 kHz, respectively. The average TS_cm (Simming angle: 9.1°, standard deviation: ± 13.1°) according to total length was -68.9, -68.8, -69.6, and -70.0 dB at 38, 70, 120, and 200 kHz, respectively. The results of this study provide an important basis for future studies that use acoustics to estimate the target strength of anchovies.