• The Journal of Korean Society for Radiation Therapy
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• v.25 no.1
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• pp.25-31
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• 2013

Purpose: The aim of this study is to evaluate the dosimetric properties of robust planning strategy for plain intensity-modulated proton therapy (IMPT) taking into account of the uncertainties of effective proton range and set up error as compared to photon intensity-modulated radiation therapy (photon-IMRT) in prostate cancer treatment. Materials and Methods: The photon-IMRT (7 beams, step & shoot), plain-IMPT (2, 4, and 7 portals), and robust- IMPT plans, which was recalculated the plain-IMPT based on the uncertainties of range error (${\pm}5%$) and set up error (0.5 cm), were evaluated for five prostate cancer patients prescribed by 70 Gy/35 fractions. To quantitatively evaluate the dose distributions, several parameters such as maximum dose, minimum dose, mean dose, conformity index (CI), and homogeneity index (HI) for PTV as well as dose-volume index of VxGy for OARs were calculated from dose-volume histograms. Results: Robust-IMPT showed superior dose distributios in the PTV and OARs as compared to plain-IMPT and photon-IMRT. Like plain-IMPT, robust-IMPT were resulted in dose fluctuation around OARs, while better homogeneity and conformity in PTVs and lower mean dose in OARs as compared to photon-IMRT. Conclusion: In consideration with the effective range correction and set up movement using robustness in IMPT plan, the dosimetric uncertainties from plain-IMPT could substantially reduce and suggest more effective solutions than photon-IMRT in prostate cancer treatment.

• Analytical Science and Technology
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• v.26 no.3
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• pp.165-173
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• 2013

To establishment of PT Program for Indoor air quality field that manufacture of confidential development PTMs (proficiency testing materials) and examined of proficiency testing evaluation included sampling process whether or not that is valid. Confirmation of homogeneity and stability of PTMs prepared. PTMs were confirmed to be homogeneous enough to be used as proficiency testing materials since withinbottle homogeneities of the RMs were lower than 0.3 times of targeted standard deviation of proficiency testing. The result of this study showed that the Robust RSD of proficiency testing for VOCs (volatile organic compounds) appeared 23~43% in concentration of 50~320 ${\mu}g/m^3$ for Method A(Distribution by adsorption in Tenax-tube of VOCs), but less 13~42% in concentration of 200~1200 ${\mu}g/m^3$, 16~31% in concentration of 100~450 ${\mu}g/m^3$ for Method B (distribution by VOCs of gas phase in 10L Tedalr bag), C (directly sampling of cylinder with high pressure) respectively. The result of this study showed that method C with sampling is most adequate to the proficiency testing for VOCs in indoor air.

• The Korean Journal of Applied Statistics
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• v.22 no.2
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• pp.329-340
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• 2009

For complex diseases such as diabetes, hypertension, it is believed that model-free methods might work better because they do not require a precise knowledge of the mode of inheritance controlling the disease trait. This is done by estimating the sharing probabilities that a pair shares zero, one, or two alleles identical by descent(IBD) and has some specific branches of test procedure, i.e., the mean test, the proportion test, and the minmax test. Among them, the minmax test is known to be more robust than others regardless of genetic mode of inheritance in current use. In this study, we compared the power of the methods which are based on minmax test and considering weighting schemes for sib-pairs to analyze sibship data. In simulation result, we found that the method based on Suarez' was more powerful than any others without respect to marker allele frequency, genetic mode of inheritance, sibship size. Also, The power of both Suarez- and Hodge-based methods was higher when marker allele frequency and sibship size were higher, and this result was remarkable in dominant mode of inheritance especially.

• Economic and Environmental Geology
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• v.38 no.2 s.171
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• pp.155-163
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• 2005

For an unbiased TF (Tansfer Function) estimations we investigate geomagnetic TF derived from ICHEON and YONGIN sites, employing RR (Remote Reference) and SNS (Signal Noise Separation) techniques. The Rh technique, which requires synchronized field variations recorded at a clean remote site, is a reliable method to minimize the bias of TF by uncorrelated noises in magnetic channels. Meanwhile, SNS technique based on the assumption of noise-free remote data can improve the signal-noise level by separating signal TF and noise TF, which is successfully applied to the environments with strong correlated noises. In this study, TF at YONGIN is analyzed using geomagnetic data from ICHEON site as a remote reference, which seem to have somewhat better data quality. The application of Rh technique reduces the bias of TF, which appears in single site robust estimation, and makes curves in the amplitude and phase of TF more smooth as frequency. Futhermore, in order to investigate noise source quantitatively, SNS technique is applied. The results of SNS suggest that dominant noise source seems to be located at western region of YONGIN. This noise source is considered to originate from railway system such as KTX and national subway. which passes through the west regions of YONGIN.

• The Korean Journal of Applied Statistics
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• v.21 no.1
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• pp.81-94
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• 2008

Family-based tests such as the transmission and disequilibrium tests(TDT) have proved to be powerful tools in the search for disease genes. Unlike case-control studies, the tests are not affected by population admixture, which can lead to spurious association of multiple highly linked makers with disease-susceptible genes. Those tests have largely required knowledge of parental marker genotypes. However, parental data are often not available for late-onset diseases. In this article we propose sib-TDTs that overcome this problem by use of marker data from unaffected sib(s) instead of parents. To do this end, we fist defined a Mantel-Haenszel-type statistic for each haplotype and then proposed two tests based on this statistic. Simulation studies suggest that the proposed tests are robust to population admixture and are monotone increasing as a relative risk increases irrespective of mode of inheritance. We also illustrated the proposed tests with data adopted from Yonsei Cardiovascular Genome Center.

• The Korean Journal of Applied Statistics
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• v.31 no.1
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• pp.123-137
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• 2018

A nonlinear mixed effects model is mainly used to analyze repeated measurement data in various fields. A nonlinear mixed effects model consists of two stages: the first-stage individual-level model considers intra-individual variation and the second-stage population model considers inter-individual variation. The individual-level model, which is the first stage of the nonlinear mixed effects model, estimates the parameters of the nonlinear regression model. It is the same as the general nonlinear regression model, and usually estimates parameters using the least squares estimation method. However, the least squares estimation method may have a problem that the estimated value of the parameters and standard errors become extremely large if the assumed nonlinear function is not explicitly revealed by the data. In this paper, a new estimation method is proposed to solve this problem by introducing the ridge regression method recently proposed in the nonlinear regression model into the first-stage individual-level model of the nonlinear mixed effects model. The performance of the proposed estimator is compared with the performance with the standard estimator through a simulation study. The proposed methodology is also illustrated using quantitative high throughput screening data obtained from the US National Toxicology Program.

• Analytical Science and Technology
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• v.23 no.3
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• pp.284-294
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• 2010

In this study, river water-based reference materials (RMs), NIER-I08RW and NIER-I09, for trace metal analysis were prepared and certified for Pb, Cd, Cr and Cu with evaluation of uncertainties. The RMs were confirmed to be homogeneous enough to be used as proficiency testing materials since within-bottle homogenieties of the RMs were lower than 0.3 times of targeted standard deviation of proficiency testing. The RMs were distributed to environmental testing laboratories for the proficiency testing and the variation of Z scores of the proficiency testing results were compared for different assigned values. The relative bias, $B_{relative}$, deviations between reference values and consensus values, were lower than ${\pm}$1 except for cadmium of NIERI08RW. The results showed both values were in a good agreement and only 2.9% of Z scores changed by using a different assigned values such as consensus and reference values.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.1_2
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• pp.15-34
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• 2006

This paper introduces an empirical modeling technique. This technique uses a set of sample results which are collected from a few small scale simulations. Empirical models are developed by applying a couple of statistical estimation techniques to these samples. We built two types of models for cache miss rates in Symmetric Multiprocessor systems. One is for the changes of input data set size while the specification of target system is fixed. The other is for the changes of the number of processors in target system while the input data set size is fixed. To develop accurate models, we built individual model for every kind of cache misses for each shared data structure in a program. The final model is then obtained by integrating them. Besides, combined use of Least Mean Squares and Robust Estimations enhances the quality of models by minimizing the distortion due to outliers. Empirical modeling technique produces extremely accurate models without analysis on sample data. In addition, since only snail scale simulations are necessary, once a set of samples can be collected, empirical method can be adopted in any research areas. In 17 cases among 24 trials, empirical models present extremely low prediction errors below $1\%$. In the remaining cases, the accuracy is excellent, as well. The models sustain high quality even when the behavioral characteristics of programs are irregular and the number of samples are barely enough.

• The Korean Journal of Applied Statistics
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• v.29 no.4
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• pp.595-611
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• 2016

We use nonlinear regression models (such as the Hill Model) when we analyze data in toxicology and/or pharmacology. In nonlinear regression models an estimator of parameters and estimation of measurement about uncertainty of the estimator are influenced by the variance structure of the error. Thus, estimation methods should be different depending on whether the data are homoscedastic or heteroscedastic. However, we do not know the variance structure of the error until we actually analyze the data. Therefore, developing estimation methods robust to the variance structure of the error is an important problem. In this paper we propose a method to estimate parameters in nonlinear regression models based on a preliminary test. We define an estimator which uses either the ordinary least square estimation method or the iterative weighted least square estimation method according to the results of a simple preliminary test for the equality of the error variance. The performance of the proposed estimator is compared to those of existing estimators by simulation studies. We also compare estimation methods using real data obtained from the National Toxicology program of the United States.

• Journal of the Korean Society for Library and Information Science
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• v.55 no.4
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• pp.219-243
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• 2021

This study analyzes the effects of community-level socioeconomic deprivations (SED) on public libraries' book circulation in the Seoul metropolitan area. The study design draws upon the theory of local information landscapes, which explains the relationship between community characteristics and information behavior. Using four-year (2015-2018) open government and public library circulation data, we constructed a socioeconomic deprivation index by adjusting a multi-dimensional deprivation index and generated other variables. Multi-level robust linear regression models were used to examine the relationship between SED and public library circulation. In addition, we tested the moderating effects of the library collection size and the number of libraries per unit area, respectively, on library circulation. The results show that there is a significant negative relationship between socioeconomic deprivation and library circulation rate. Also, we found that the size of the library collection negatively moderates the effects of SED in areas with a large number of books, and the number of libraries per unit area was positvely related to the library book circulation, not moderating the effects of SED. These findings suggest that public libraries and policymakers should consider community characteristics in designing strategic plans for public libraries.