• Journal of Radiation Protection and Research
• /
• v.48 no.2
• /
• pp.90-99
• /
• 2023

Background: Quantitative risk assessments should be accompanied by uncertainty analyses of the risk models employed in the calculations. In this study, we aim to develop a computational code named SUMRAY for use in cancer risk projections from radiation exposure taking into account uncertainties. We also aim to make SUMRAY publicly available as a resource for further improvement of risk projection. Materials and Methods: SUMRAY has two versions of code written in R and Python. The risk models used in SUMRAY for all-solid-cancer mortality and incidence were those published in the Life Span Study of a cohort of the atomic bomb survivors in Hiroshima and Nagasaki. The confidence intervals associated with the evaluated risks were derived by propagating the statistical uncertainties in the risk model parameter estimates by the Monte Carlo method. Results and Discussion: SUMRAY was used to calculate the lifetime or time-integrated attributable risks of cancer under an exposure scenario (baseline rates, dose[s], age[s] at exposure, age at the end of follow-up, sex) specified by the user. The results were compared with those calculated using another well-known web-based tool, Radiation Risk Assessment Tool (RadRAT; National Institutes of Health), and showed a reasonable agreement within the estimated confidential interval. Compared with RadRAT, SUMRAY can be used for a wide range of applications, as it allows the risk projection with arbitrarily specified risk models and/or population reference data. Conclusion: The reliabilities of SUMRAY with the present risk-model parameters and their variance-covariance matrices were verified by comparing them with those of the other codes. The SUMRAY code is distributed to the public as an open-source code under the Massachusetts Institute of Technology license.

• Journal of the Korean Data and Information Science Society
• /
• v.24 no.2
• /
• pp.303-310
• /
• 2013

Forty two female students whose fat mass ratio was over 30% were participated in the experiment of fat mass loss of two treatments for 8 weeks. They kept diary for foods they ate every day, took a picture of the foods, transmitted the picture to the experimenter by the camera phone. Among those, 28 students took the picture by regular camera phone (Treatment A), and the other students used smart phone (Treatment B). Fat mass weight and its related variables had been measured repeatedly four times at an interval of two weeks during 8 weeks. It was shown from mixed model analysis of repeated measurements data that AR(1) covariance matrix was selected as the optimal covariance matrix pattern. The correlation between two successive times is highly correlated as 0.838. Based upon the AR(1) covariance matrix structure, the students using smart phones were somewhat more effective in losing fat mass weight than the students using regular camera phones. The time effect was highly significant, but the treatment-time interaction effect was insignificant. The baseline effect and total cholesterol were found to be significant, but the calories with taking foods were somewhat significant, but the waist to hip ratio was found to be insignificant.

• Wind and Structures
• /
• v.7 no.3
• /
• pp.173-186
• /
• 2004

Flutter derivatives provide the basis of predicting the critical wind speed in flutter and buffeting analysis of long-span cable-supported bridges. In this paper, one popular stochastic system identification technique, covariance-driven Stochastic Subspace Identification(SSI in short), is firstly presented for estimation of the flutter derivatives of bridge decks from their random responses in turbulent flow. Secondly, wind tunnel tests of a streamlined thin plate model and a ${\Pi}$ type blunt bridge section model are conducted in turbulent flow and the flutter derivatives are determined by SSI. The flutter derivatives of the thin plate model identified by SSI are very comparable to those identified by the unifying least-square method and Theodorson's theoretical values. As to the ${\Pi}$ type section model, the effect of turbulence on aerodynamic damping seems to be somewhat notable, therefore perhaps the wind tunnel tests for flutter derivative estimation of those models with similar blunt sections should be conducted in turbulent flow.

• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.36 no.1
• /
• pp.43-51
• /
• 1987

In this paper, a state-space model of the burnthrough point control system of an industrial sintering process is derived. The model is then used in designing a self-tuning controller which consists of the receding horizon control law and a least-squares prediction algorithm with covariance resetting. By applying this controller to POSCO IV sintering process, satisfactory experimental results have been obtained. This paper presents some of these real-time experimental results and analyzes the control performance through productivity, operation indices, quality, sintered material composition, etc. From these experimental results and simulation results, the validity of the model can be observed. Moreover, the properties of the controller, e.g. stability, steady-state error, are shown based on the model.

• Journal of Biomedical Engineering Research
• /
• v.10 no.1
• /
• pp.11-16
• /
• 1989

This paper describes the AR model of EMG signal during maximum voluntary contraction. By comparing the AR coefficients and the reflection coefficients of the AR model with the median frequency of power spectrum, it is proved that muscle fatigue can be measured by the AR and the reflection coefficients. In the estimation procedure of AR model parameter, the autocorrelation method is superior to the covariance method, and it is determined that the optimal order is six. As the muscle becomes fatigue, the median frequency of power spectrum is declined, and the AR coefficient [$a_1$] and the reflection coefficient [$k_1$] are also decreased. Therefore the muscle fatigue can be measured by the AR parameter.

• The Korean Journal of Ecology
• /
• v.28 no.6
• /
• pp.353-363
• /
• 2005

We developed a local-scale ecophysiological model, Sim-CYCLE Fine by modifying Sim-CYCLE which was developed for a global scale simulation. Sim-CYCLE fine is able to simulate not only carbon fluxes but also plant growth with various time-steps from an hour to a month. The model outputs of $CO_2$ flux and biomass/LAI were highly reliable; we validated the model results with measurements from the eddy covariance technique and the harvest method ($R^2$ values of around 0.9 for both). The results suggested that the phonology and the seasonal dynamics of the $C_3/C4$ plant communities affected significantly the carbon fluxes and the plant growth during the plant growing season.

• Journal of the Korean Home Economics Association
• /
• v.40 no.9
• /
• pp.175-189
• /
• 2002

The purpose of this study was to test a structural model about family income as causally related to family hardiness, pile-up stress, communication, and family adaptation in families of children with disabilities. 250 families of children with disabilities participated as subjects. The models were developed on the basis of confirmatory factor analysis and compared using covariance structure modeling(LISREL). Adequate fitness of the model was observed. Family income showed negative effect on pile-up stress and positive effect on family adaptation. Pile-up stress showed negative effect on family hardiness. Family hardiness showed positive effect on family communication, and family communication showed positive effect on family adaptation.

• Communications for Statistical Applications and Methods
• /
• v.29 no.6
• /
• pp.721-733
• /
• 2022

In this paper we compare parameter estimation by Grassmann manifold optimization and sequential candidate set algorithm in a structured principal fitted component (PFC) model. The structured PFC model extends the form of the covariance matrix of a random error to relieve the limits that occur due to too simple form of the matrix. However, unlike other PFC models, structured PFC model does not have a closed form for parameter estimation in dimension reduction which signals the need of numerical computation. The numerical computation can be done through Grassmann manifold optimization and sequential candidate set algorithm. We conducted numerical studies to compare the two methods by computing the results of sequential dimension testing and trace correlation values where we can compare the performance in determining dimension and estimating the basis. We could conclude that Grassmann manifold optimization outperforms sequential candidate set algorithm in dimension determination, while sequential candidate set algorithm is better in basis estimation when conducting dimension reduction. We also applied the methods in real data which derived the same result.

• Communications for Statistical Applications and Methods
• /
• v.22 no.6
• /
• pp.575-587
• /
• 2015

The development in data collection techniques results in high dimensional data sets, where discrimination is an important and commonly encountered problem that are crucial to resolve when high dimensional data is heterogeneous (non-common variance covariance structure for classes). An example of this is to classify microbial habitat preferences based on codon/bi-codon usage. Habitat preference is important to study for evolutionary genetic relationships and may help industry produce specific enzymes. Most classification procedures assume homogeneity (common variance covariance structure for all classes), which is not guaranteed in most high dimensional data sets. We have introduced regularized elimination in partial least square coupled with QDA (rePLS-QDA) for the parsimonious variable selection and classification of high dimensional heterogeneous data sets based on recently introduced regularized elimination for variable selection in partial least square (rePLS) and heterogeneous classification procedure quadratic discriminant analysis (QDA). A comparison of proposed and existing methods is conducted over the simulated data set; in addition, the proposed procedure is implemented to classify microbial habitat preferences by their codon/bi-codon usage. Five bacterial habitats (Aquatic, Host Associated, Multiple, Specialized and Terrestrial) are modeled. The classification accuracy of each habitat is satisfactory and ranges from 89.1% to 100% on test data. Interesting codon/bi-codons usage, their mutual interactions influential for respective habitat preference are identified. The proposed method also produced results that concurred with known biological characteristics that will help researchers better understand divergence of species.

• Journal of the Korean Society for Aeronautical & Space Sciences
• /
• v.34 no.11
• /
• pp.42-46
• /
• 2006

As an application of SDINS/GPS integration for its synergistic results, the SDINS alignments utilizing GPS carrier phase rate measurements. A measurement model of GPS carrier phase rate is derived in order to be used with SDINS alignment process. For in-flight alignment, the performance of the suggested SDINS/GPS integration method is analyzed using the covariance analysis and its results are confirmed by those of van test. Consequently, it is shown that all states of the SDINS integrated system by utilizing GPS carrier phase rate measurements can be estimated more efficiently than a general SDINS/GPS during in-flight alignment.