• Journal of Environmental Impact Assessment
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• v.23 no.3
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• pp.187-196
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• 2014

The objective of this study is to evaluate and analyze Osu stream watershed water environment system. The data were collected from January 2009 to December 2011 including water temperature, pH, DO, EC, BOD, COD, TOC, SS, T-N, T-P and discharge. The data were used for principle component analysis and factor analysis. The results are as followes. The primary factors obtained from both the principal component analysis and the factor analysis were BOD, COD, TOC, SS and T-P. Once principal component analysis and factor analysis have been performed with the collected data and then the results will be applied to both simple regression model and multiple regression model. The regression model was developed into case 1 using concentrations of water quality parameters and case 2 using delivery loads. The value of the coefficient of determination on case 1 fell between 0.629 and 0.866; this was lower than case 2 value which fell between 0.946 and 0.998. Therefore, case 2 model would be a reliable choice.The coefficient of determination between the estimated figure using data which was developed to the regression model in 2012 and the actual measurement value was over 0.6, overall. It can be safely deduced that the correlation value between the two findings was high. The same model can be applied to get TOC concentrations in future.

• Journal of the Korean Geotechnical Society
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• v.30 no.9
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• pp.29-39
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• 2014

In this study, model pile-load test with numerical analysis was carried out to compare and analyze pile behaviour according to interface properties. In the model test, Close Range Photogrammetry (CRP) was chosen to measure the ground deformation. In addition, model steel and concrete piles were used. Based on the model pile test, interface elements around the model pile were used to simulate the slip effect. Interface properties were adopted as interface reduction factor $R_{inter}$. Interface reduction factor, $R_{inter}$ plays a key role in the interface properties. Through this study, it was found that the model ground behaviour measured by CRP corresponded well to the one predicted by the numerical analysis. And, the interface strength reduction factor, $R_{inter}$ value of the steel pile was higher than that of the concrete pile.

• The KIPS Transactions:PartD
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• v.13D no.7 s.110
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• pp.923-930
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• 2006

In this paper we design the system test model for the weapon system embedded software based on the Time Factor Method(TFM) considering time factors and suggest the results through the case study. For doing this, we discuss the features, system tests and the object-oriented model based UML notations of the weapon system embedded software. And we give a test method considering time factors, a measuring method to time factors, and a test case selection algorithm as an approach to the TFM for designing the system test model. The TFM based system test model consists of three factors (X, Y, Z) in the weapon system embedded software. With this model, we can extract test cases through the selection algorithm for a maximum time path in 'X', identify the objects related to the Sequence Diagram in 'Y' and measure the execution time of each objects which is identified by the Timing Diagram in 'Z' Also, we present the method of extracting the system test cases by applying the proposed system test model to the 'Multi-function missile defense system'.

• The Journal of the Acoustical Society of Korea
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• v.28 no.3
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• pp.268-272
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• 2009

In this paper, we propose a Gaussian Mixture Model (GMM) based incremental robust adaptation with a forgetting factor for the speaker verification. Speaker recognition system uses a speaker model adaptation method with small amounts of data in order to obtain a good performance. However, a conventional adaptation method has vulnerable to the outlier from the irregular utterance variations and the presence noise, which results in inaccurate speaker model. As time goes by, a rate in which new data are adapted to a model is reduced. The proposed algorithm uses an incremental robust adaptation in order to reduce effect of outlier and use forgetting factor in order to maintain adaptive rate of new data on GMM based speaker model. The incremental robust adaptation uses a method which registers small amount of data in a speaker recognition model and adapts a model to new data to be tested. Experimental results from the data set gathered over seven months show that the proposed algorithm is robust against outliers and maintains adaptive rate of new data.

• Nuclear Engineering and Technology
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• v.33 no.1
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• pp.102-110
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• 2001

In this work, the model predictive control method was applied to a linear model and a nonlinear model of steam generators. The parameters of a linear model for steam generators are very different according to the power levels. The model predictive controller was designed for the linear steam generator model at a fixed power level. The proposed controller at the fixed power level showed good performance for any other power levels by designed changing only the input-weighting factor. As the input-weighting factor usually increases, its relative stability does so. The steam generator has some nonlinear characteristics. Therefore, the proposed algorithm has been implemented for a nonlinear model of the nuclear steam generator to verify its real performance and also, showed good performance.

• Journal of Radiation Protection and Research
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• v.15 no.2
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• pp.101-112
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• 1990

For the performance assessment of the radioactive waste disposal system (repository), a biosphere model is suggested. This biosphere model is intended to calculate the annual doses to man caused by the contaminated river water for eight pathways and four radionuclides. This model can also be applied to assess the radiological effects of contaminated well water. To account for the uncertainties on the model parameter values, parameter distributions are assigned to these model parameters. Then, Monte Carlo simulation method with Latin Hypercube sampling technique is used. Also, sensitivity analysis is performed by using the Spearman rank correlation coefficients. It is found that these methods are a very useful tool to treat uncertainties and sensitivities on the model parameter values and to analyze the biosphere model. A conversion factor is proposed to calculate the annual dose rate to humans arising from a unit radionuclide concentration in river water. This conversion factor allows for the substitution of the biosphere model in a probabilistic performance assessment computer code by one single variable.

• Communications for Statistical Applications and Methods
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• v.28 no.5
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• pp.521-536
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• 2021

As life expectancies increase continuously over the world, the accuracy of forecasting mortality is more and more important to maintain social systems in the aging era. Currently, the most popular model used is the Lee-Carter model but various studies have been conducted to improve this model with one of them being 6-parametric factor model (6-PFM) which is introduced in this paper. To this new model, long short-term memory (LSTM) and regularized LSTM are applied in addition to vector autoregression (VAR), which is a traditional time-series method. Forecasting accuracies of several models, including the LC model, 4-PFM, 5-PFM, and 3 6-PFM's, are compared by using the U.S. and Korea life-tables. The results show that 6-PFM forecasts better than the other models (LC model, 4-PFM, and 5-PFM). Among the three 6-PFMs studied, regularized LSTM performs better than the other two methods for most of the tests.

• Journal of dental hygiene science
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• v.15 no.1
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• pp.67-76
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• 2015

This study aims to determine the factors affecting the dental service utilization of adults. The subjects in this study were 455 adults, whom a survey was conducted form May 7 to June 7, 2013. Statistical verification conducted through PASW Statistics was 18.0. The difference in the distribution of independent variables related with the dental service utilization was verified with chi-square test. Relevant factors were determined using Hierarchical logistic regression analysis. Model I is predisposing factor, Model II is predisposing factor and enabling factor. Model III is predisposing, enabling, need factor. Andersen model factor which infuences dental service utilization of adults resulted that use dental floss (OR, 2.32; CI, 1.39~3.86), use electric toothbrush (OR, 2.98; CI, 1.0~8.89), use interdental brush (OR, 2.55; CI, 1.36~4.78), self-efficacy (OR, 0.68; CI, 0.48~0.96), barriers (OR, 1.45; CI, 1.04~2.04). Predisposing factor and need factor were found to be determinants for dental service utilization in adult.

• Korean Journal of Culture and Social Issue
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• v.26 no.3
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• pp.259-282
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• 2020

This study examines the validity of the Filial Responsibility Scale-Adult (Past), developed by Jurkovic and Thirkield (1999), among Korean university students in their twenties. First, a preliminary scale consisting of 30 items was developed by translating the original scale into Korean and item analysis and exploratory factor analysis were conducted on 249 subjects. Based on the exploratory factor analysis, items in the emotional parentification factor were either deleted or included in the other remaining factors, resulting in a two-factor model containing 15 items. In order to confirm this, a confirmatory factor analysis was conducted on 318 independent subjects. As a result of a confirmatory factor analysis of the two competing models - the three-factor model consisting of 30 items based on the original scale and the two-factor(emotional experience and caring behavior) model consisting of 15 items gained as a result of the exploratory factor analysis - the two-factor model showed more suitable and the original scale was revised accordingly. The convergent validity, discriminant validity and predictive validity were all found to be satisfactory. Based on such results, implications, limitations and suggestions on follow-up studies are discussed.

• Korean Journal of Health Education and Promotion
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• v.33 no.2
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• pp.77-87
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• 2016

Objectives: This study was conducted to provide data in order to develop effective family planning programs by analyzing the factors which affect contraceptive use among women in Ethiopia. Methods: The community health survey was conducted on women of childbearing age. The research model was developed based on Andersen's Model. A total of 320 respondents were analyzed through Chi-square analysis, t-tests and logistic regression analysis. Results: Contraceptive prevalence rate was 43.1% and most of them were using modern and short-term methods. Among three factor categories, the need factor(unwanted pregnancy experience) was revealed as the most important factor, following enabling factor which was knowing the FP services in health center. Conclusions: These results lead to several conclusions. First, the results imply that programs should focus on women who are in the over 30yr. as well as the poorer economic group and urban residents. Second, to improve the effectiveness of the program, it is important to help them to be motivated themselves and to promote knowledge on various methods. Third, in terms of service delivery, community health workers are expected to take a crucial role. To improve the availability of services, they should provide practical services as those in health center.