• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.11a
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• pp.701-707
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• 2000

In this work, we propose to employ magnetostrictive sensors to develop a new non-contacting modal testing method. Specific applications are made in the modal testing of a beam in bending. The role of bias magnetic fields in measuring bending waves is addressed and an approximate analysis to explain the principle to measure bending signals is carried out. The measured modal data by the present method agree well with those by conventional methods using accelerometers.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.43 no.1
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• pp.88-95
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• 2015

This paper considers the effects of propellant mixture ratio and loading errors on the performance of a liquid rocket. Propellant residuals generated by error sources are analyzed for a launch vehicle model whose first stage consists of a cluster rocket of four 75-tonf class engines using a statistical Monte-Carlo approach and then the optimal fuel biases minimizing residuals are computed. The results are validated through comparison with analytic method using approximate formula, which have been applied for other space launch vehicles.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.17 no.11
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• pp.2621-2626
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• 2013

This paper has presented the potential distribution for asymmetric double gate(DG) MOSFET, and sloved Poisson equation to obtain the analytical solution of potential distribution. The symmetric DGMOSFET where both the front and the back gates are tied together is three terminal device and has the same current controllability for front and back gates. Meanwhile the asymmetric DGMOSFET is four terminal device and can separately determine current controllability for front and back gates. To approximate with experimental values, we have used the Gaussian function as doping distribution in Poisson equation. The potential distribution has been observed for gate bias voltage and gate oxide thickness and channel doping concentration of the asymmetric DGMOSFET. As a results, we know potential distribution is greatly changed for gate bias voltage and gate oxide thickness, especially for gate to increase gate oxide thickness. Also the potential distribution for source is changed greater than one of drain with increasing of channel doping concentration.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.691-694
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• 2013

This paper has presented the potential distribution for asymmetric double gate(DG) MOSFET, and sloved Poisson equation to obtain the analytical solution of potential distribution. The symmetric DGMOSFET where both the front and the back gates are tied together is three terminal device and has the same current controllability for front and back gates. Meanwhile the asymmetric DGMOSFET is four terminal device and can separately determine current controllability for front and back gates. To approximate with experimental values, we have used the Gaussian function as charge distribution in Poisson equation. The potential distribution has been observed for gate bias voltage and gate oxide thickness and channel doping concentration of the asymmetric DGMOSFET. As a results, we know potential distribution is greatly changed for gate bias voltage and gate oxide thickness, especially for gate to increase gate oxide thickness. Also the potential distribution for source is changed greater than one of drain with increasing of channel doping concentration.

• Nuclear Engineering and Technology
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• v.53 no.7
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• pp.2377-2386
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• 2021

To model the atmospheric dispersion of radionuclides released from nuclear accident is very important for nuclear emergency. But the uncertainty of model parameters, such as source term and meteorological data, may significantly affect the prediction accuracy. Data assimilation (DA) is usually used to improve the model prediction with the measurements. The paper proposed a parameter bias transformation method combined with Lagrangian puff model to perform DA. The method uses the transformation of coordinates to approximate the effect of parameters bias. The uncertainty of four model parameters is considered in the paper: release rate, wind speed, wind direction and plume height. And particle swarm optimization is used for searching the optimal parameters. Twin experiment and Kincaid experiment are used to evaluate the performance of the proposed method. The results show that the proposed method can effectively increase the reliability of model prediction and estimate the parameters. It has the advantage of clear concept and simple calculation. It will be useful for improving the result of atmospheric dispersion model at the early stage of nuclear emergency.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1205-1215
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• 2017

In this paper, we aim to estimate two scale-parameters of exponentiated Pareto distribution (EPD) based on lower record values. Record values arise naturally in many real life applications involving data relating to weather, sport, economics and life testing studies. We calculate the Bayesian estimators for the two parameters of EPD based on lower record values. The Bayes estimators of two parameters for the EPD with lower record values under the squared error loss (SEL), linex loss (LL) and entropy loss (EL) functions are provided. Lindley's approximate method is used to compute these estimators. We compare the Bayesian estimators in the sense of the bias and root mean squared estimates (RMSE).

• The Journal of Information Systems
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• v.29 no.3
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• pp.103-117
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• 2020

Purpose Recently, various issues related to toxic comments on web portal sites and SNS are becoming a major social problem. Toxic comments can threaten Internet users in the type of defamation, personal attacks, and invasion of privacy. Over past few years, academia and industry have been conducting research in various ways to solve this problem. The purpose of this study is to develop the deep learning modeling for toxic comments classification. Design/methodology/approach This study analyzed 7,878 internet news comments through CNN classification modeling based on Highway Network and OOV process. Findings The bias and hate expressions of toxic comments were classified into three classes, and achieved 67.49% of the weighted f1 score. In terms of weighted f1 score performance level, this was superior to approximate 50~60% of the previous studies.

• Communications for Statistical Applications and Methods
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• v.17 no.2
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• pp.165-181
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• 2010

This paper presents some chain ratio-type estimators for estimating finite population variance using two auxiliary variables in two phase sampling set up. The expressions for biases and mean squared errors of the suggested c1asses of estimators are given. Asymptotic optimum estimators(AOE's) in each class are identified with their approximate mean squared error formulae. The theoretical and empirical properties of the suggested classes of estimators are investigated. In the simulation study, we took a real dataset related to pulmonary disease available on the CD with the book by Rosner, (2005).

• Communications for Statistical Applications and Methods
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• v.30 no.4
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• pp.403-410
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• 2023

Two-Phase sampling, which was first introduced by Neyman (1938), has various applications in different forms. Variance estimation for two-phase sampling has been an important research topic because conventional variance estimators used in most softwares are not working. In this paper, we considered a variance estimation for two-phase sampling in which stratified two-stage cluster sampling designs are used in both phases. By defining a conditionally unbiased estimator of an approximate variance estimator, which is calculable when all elements in the first phase sample are observed, we propose an explicit form of variance estimator of the double expanded estimator for a two-phase sample. A small simulation study shows the proposed variance estimator has a negligible bias with small variance. The suggested variance estimator is also applicable to other linear estimators of the population total or mean if appropriate residuals are defined.

• Journal of Microbiology
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• v.37 no.3
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• pp.154-158
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• 1999

The arginine residue at position 243 (Arg 243) of the yeast transcription factor, Gcn4p, is invariably conserved among bZIP transcription factors. Using site-directed oligonucleotide saturation mutagenesis involving two-step polymerase chain reaction (PCR) amplification, random mutations were successfully introduced at the codon of 243 in the basic domain of Gcn4p. This mutant library was transformed ito Gcn4p defective yeast strain and selected for the transcriptionally active colonies. All colonies which were transcriptionally active had arginines in the codon 243. In this study, the strand preference by Taq polymerase during mutagenesis was also tested. Oligonucleotides were specially designed to test whether or not the polymerase was preferred using the strand as a template. A population of randomly mutated products were cloned into an appropriate vector and characterized by DNA sequencing analysis. Saturation mutagenesis which was performed efficiently by this method revealed a strong bias in terms of strand preference of Taq polymerase by an approximate ratio of 3 to 1 in this study.