• Journal of Information Technology Services
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• v.11 no.1
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• pp.211-221
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• 2012

Many metric-based classification models have been proposed to predict fault-proneness of software module. This paper presents two prediction models using Bayesian classifier which is one of the most popular modern classification algorithms. Bayesian model based on Bayesian probability theory can be a promising technique for software quality prediction. This is due to the ability to represent uncertainty using probabilities and the ability to partly incorporate expert's knowledge into training data. The two models, Na$\ddot{i}$veBayes(NB) and Bayesian Belief Network(BBN), are constructed and dimensionality reduction of training data and test data are performed before model evaluation. Prediction accuracy of the model is evaluated using two prediction error measures, Type I error and Type II error, and compared with well-known prediction models, backpropagation neural network model and support vector machine model. The results show that the prediction performance of BBN model is slightly better than that of NB. For the data set with ambiguity, although the BBN model's prediction accuracy is not as good as the compared models, it achieves better performance than the compared models for the data set without ambiguity.

• Nuclear Engineering and Technology
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• v.54 no.5
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• pp.1606-1615
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• 2022

For investigating whether the MARSSIM nonparametric test has sufficient statistical power when a site has a specific contamination distribution before conducting a final status survey (FSS), a novel approach was proposed to predict the release probability of the site. Five distributions were assumed: lognormal distribution, normal distribution, maximum extreme value distribution, minimum extreme value distribution, and uniform distribution. Hypothetical radioactivity populations were generated for each distribution, and Sign tests were performed to predict the release probabilities after extracting samples using Monte Carlo simulations. The designed Type I error (0.01, 0.05, and 0.1) was always satisfied for all distributions, while the designed Type II error (0.01, 0.05, and 0.1) was not always met for the uniform, maximum extreme value, and lognormal distributions. Through detailed analyses for lognormal and normal distributions which are often found for contaminants in actual environmental or soil samples, it was found that a greater statistical power was obtained from survey units with normal distribution than with lognormal distribution. This study is expected to contribute to achieving the designed decision error when the contamination distribution of a survey unit is identified, by predicting whether the survey unit passes the statistical test before undertaking the FSS according to MARSSIM.

• Journal of Radiation Protection and Research
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• v.28 no.4
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• pp.321-325
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• 2003

The effects of AMAD, absorption type, and intake pattern were compared and analysed for the internal dose evaluation of workers who chronically inhale uranium. The committed effective doses$(E_{50})$ based on AMAD, absorption type, and intake pattern were evaluated using 3 monthly lung predicted monitoring data due to a chronic intake of uranium for 5 years. The relative error ranges of $E_{50}$ evaluated with each AMAD$(0.1{\sim}10{\mu}m)\;to\;E_{50}$ evaluated with $5{\mu}m$ AMAD were $-37.0{\sim}49.8%$, and the relative error ranges of En evaluated with Type M to $E_{50}$ evaluated with Type S were $15.9{\sim}56.6%$, and the relative error ranges of $E_{50}$ evaluated with an acute intake to $E_{50}$ evaluated with a chronic intake were $0.55{\sim}4.52%$. Thus AMAD and the absorption type affected the results of $E_{50}$, but the intake pattern didn't really affect the results of $E_{50}$.

• Journal of Interdisciplinary Genomics
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• v.1 no.2
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• pp.15-18
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• 2019

Gaucher disease (GD) is an autosomal recessive inborn error of metabolism resulting from a deficiency in ${\beta}$-glucocerebrosidase (GBA) activity that leads to the accumulation of glucocerebroside in macrophages in multiple organs, such as the bone marrow, liver, spleen, and brain. GD can be classified into three clinical types: type 1 (non-neuropathic form, OMIM #230800); type II (acute neuropathic form, OMIM #230900); and type III (chronic neuropathic form, OMIM #231000). Type III is the subacute form of neuropathic GD. The best available treatment for GD is long-term enzyme (imiglucerase) replacement therapy (ERT) performed every two weeks. This report describes the long-term clinical course of a patient with type III GD who was treated with ERT for 18 years.

• Journal of The Korean Association For Science Education
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• v.32 no.1
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• pp.160-181
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• 2012

The purpose of this study is to understand raters' errors in rating performance assessments of science inquiry. For this, 60 middle school students performed scientific inquiry about sound propagation and 4 trained raters rated their activity sheets. Variance components estimation for the result of the generalizability analysis for the person, task, rater design, the variance components for rater, rater by person and rater by task are about 25%. Among 4 raters, 2 raters' severity is higher than the other two raters and their severities were stabilized. Four raters' rating agreed with each other in 51 cases among the 240 cases. Through the raters' conferences, the rater error types for 189 disagreed cases were identified as one of three types; different salience, severity, and overlooking. The error type 1, different salience, showed 38% of the disagreed cases. Salient task and salient assessment components are different among the raters. The error type 2, severity, showed 25% and the error type 3, overlooking showed 31%. The error type 2 seemed to have happened when the students responses were on the borders of two levels. Error type 3 seemed to have happened when raters overlooked some important part of students' responses because she or he immersed her or himself in one's own salience. To reduce the above rater errors, raters' conference in salience of task and assesment components are needed before performing the holistic scoring of complex tasks. Also raters need to recognize her/his severity and efforts to keep one's own severity. Multiple raters are needed to prevent the errors from being overlooked. The further studies in raters' tendencies and sources of different interpretations on the rubric are suggested.

• Journal of the Korean School Mathematics Society
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• v.5 no.1
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• pp.111-122
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• 2002

The purpose of this study was to examine high school second graders' understanding of the basic nature of logarithm, the major type of error they made about logarithmic function and the cause of such an error, and to seek ways to instruct it better. For that purpose, three research questions were posed: 1. Investigate how much high school students in their second year comprehend the nature of logarithm. 2. Analyze what type of error they make about logarithmic function. 3. Analyze the cause of their error according to the selected error models and how it could be taught more efficiently. The findings of this study were as below: First, the natural science students had a better understanding of the basic nature of logarithm than the academic students. What produced the widest gap between the two groups' understanding was applying the nature of logarithm to the given problems, and what caused the smallest gap was the definition of logarithm and the condition of base. Second, the academic students had a poorer understanding of the basic nature of logarithmic function graph and of applying the nature of logarithm to the given problems. Third, the natural science students didn't comprehend well the basic nature of logarithmic function graph, the nature of characteristics and mantissa. Fourth, for all the students from academic and natural science courses, the most common errors were caused by the poor understanding of theorem or nature of the ［E4] model. Fifth, the academic students made more frequent errors due to the unfamiliar signs of the ［El］ model, the imperfect understanding of theorem or nature of the ［E4］ model, and the technical part of the ［E6］ model. Sixth, the natural science students made more frequent errors because of the improper problem interpretation of the ［E2］ model and the logically improper inference of the ［E3］ model.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.1
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• pp.15-20
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• 2016

The existing multiple modulus-based self-recovering equalization type has not been applied to initial equalization. Instead, it was used for steady-state performance improvement. In this paper, for the self-recovering equalization type that considers the multiple modulus as a desired response, the initial convergence performance was improved by extending the dynamics of the errors using error boosting and their characteristics were analyzed. Error boosting in the proposed method was carried out in proportion to a symbol decision for the equalizer output. Furthermore, having the initial convergence capability by extending the dynamics of errors, it showed excellent performance in the initial convergence rate and steady-state error level. In particular, the proposed method can be applied to the entire process of equalization through a single algorithm; the existing methods of switching over or the selection of other operation modes, such as concurrent operating with other algorithms, are not necessary. The usefulness of the proposed method was verified by simulations performed under the channel conditions with multipath propagation and additional noise, and for performance analysis of self-recovering equalization for high-order signal constellations.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.5
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• pp.893-898
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• 2017

A TDC(Time-to-Digital Converter) of counter-type is designed by $0.18{\mu}mCMOS$process and the supply voltage is 1.5 volts. The converted error of maximum $T_{CK}$ is occurred by the time difference between the start signal and the clock when the period of clock is $T_{CK}$ in the conventional TDC. And the converted error of -$T_{CK}$ is occurred by the time difference between the stop signal and the clock. However in order to compensate the disadvantage of the conventional TDC the clock is generated within the TDC circuit and the clock is synchronized with the start and stop signals. In the designed TDC circuit the conversion error is not occurred by the difference between the start signal and the click and the magnitude of conversion error is reduced (1/2)$T_{CK}$ by the time difference between the stop signal and the clock.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1309-1317
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• 2013

There are various parameter estimation methods for the generalized exponential distribution under progressive type I interval censoring. Chen and Lio (2010) studied the parameter estimation method by the maximum likelihood estimation method, mid-point approximation method, expectation maximization algorithm and methods of moments. Among those, mid-point approximation method has the smallest mean square error in the generalized exponential distribution under progressive type I interval censoring. However, this method is difficult to derive closed form of solution for the parameter estimation using by maximum likelihood estimation method. In this paper, we propose two type of approximate maximum likelihood estimate to solve that problem. The simulation results show the obtained estimators have good performance in the sense of the mean square error. And proposed method derive closed form of solution for the parameter estimation from the generalized exponential distribution under progressive type I interval censoring.

• Journal of the Korean Data and Information Science Society
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• v.16 no.1
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• pp.115-126
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• 2005

In this paper, we derive the approximate maximum likelihood estimators of the scale parameter and location parameter of the double exponential distribution based on Type-II censored samples. We compare the proposed estimators in the sense of the mean squared error for various censored samples.