• Communications for Statistical Applications and Methods
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• v.12 no.3
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• pp.759-771
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• 2005

Twin studies are one of the most widely used methods for quantifying the influence of genetic and environmental factors on some traits such as a life span or a disease. In this paper we propose a genetic mixed linear model for twin survival time data, which allows us to separate the genetic component from the environmental component. Inferences are based upon the hierarchical likelihood (h-likelihood), which provides a statistically efficient and simple unified framework for various random-effect models. We also propose a simple and fast computation method for analyzing a large data set on twin survival study. The new method is illustrated to the survival data in Swedish Twin Registry. A simulation study is carried out to evaluate the performance.

• IE interfaces
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• v.24 no.2
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• pp.151-155
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• 2011

In this study, we propose a signomial classification method with ₀-regularization (₀-)which seeks a sparse signomial function by solving a mixed-integer program to minimize the weighted sum of the ₀-norm of the coefficient vector of the resulting function and the $L_1$-norm of loss caused by the function. $SC_0$ gives an explicit description of the resulting function with a small number of terms in the original input space, which can be used for prediction purposes as well as interpretation purposes. We present a practical implementation of $SC_0$ based on the mixed-integer programming and the column generation procedure previously proposed for the signomial classification method with $SL_1$-regularization. Computational study shows that $SC_0$ gives competitive performance compared to other widely used learning methods for classification.

• Journal of the Korean Society for Precision Engineering
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• v.15 no.2
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• pp.14-20
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• 1998

Automatic finishing process requires the development of high efficient and precision abrasive machining method for dies and molds. This study describes the evaluation of the finishing characteristics, such as surfrace roughness, topography and material removal depth of the electrolytic mixed abrasive machining methods. Experimental setup is composed of 3 axis machining center, a newly developed finishing attachment with constant pressure, electrode and electrolytic bath. Finally, we achieved a successful result that surface roughness is $0.01\mu$m Ra and material removal depth is $120\mu$m using electrolytic(0.8A. 30V) mixed abrasive (#400 CBN, #320 SiC) machining method.

• International Journal of Highway Engineering
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• v.14 no.5
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• pp.145-155
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• 2012

PURPOSES: This study proposes a novel method based on microscopic simulation models to evaluate bicycle passing ways in mixed traffic flow conditions at signalized intersections. METHODS: Both operational efficiency and safety are taken into consideration in the evaluation. A widely used performance measure, delay, is used for evaluating the operational efficiency. Regarding the safety evaluation, surrogate safety measures (SSM) to represent traffic conflicts and the level of crash severity, DeltaS and Max.DeltaV, are applied in the proposed method. RESULTS: Extensive simulations and statistical tests show that an integrated bike-box way is identified as the best in terms of operational efficiency and safety. CONCLUSIONS: The proposed method and outcomes of this study will be valuable for bicycle traffic operations and facility design.

• Communications for Statistical Applications and Methods
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• v.27 no.3
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• pp.301-311
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• 2020

Schwarz's Bayesian information criterion (BIC) is one of the most popular criteria for model selection, that was derived under the assumption of independent and identical distribution. For correlated data in longitudinal studies, Jones (Statistics in Medicine, 30, 3050-3056, 2011) modified the BIC to select the best linear mixed effects model based on the effective sample size where the number of parameters in covariance structure was not considered. In this paper, we propose an extended Jones' modified BIC by considering covariance parameters. We conducted simulation studies under a variety of parameter configurations for linear mixed effects models. Our simulation study indicates that our proposed BIC performs better in model selection than Schwarz's BIC and Jones' modified BIC do in most scenarios. We also illustrate an example of smoking data using a longitudinal cohort of cancer patients.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.1
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• pp.54-59
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• 2002

In the three-axis control of satellites by using on-board actuators, gyros are usually used to measure the attitude angles and angular rates. The gyros are operated by electronic parts and mechanical actuators. The digital components of the electronic parts consist of largely FPGA (Field Programmable Gate Array) as one of the methods for VLSI(Very Large Scale Integrated) circuit design, while the mechanical parts provide output signal directly by mechanical actuation of a spinning rotor. In this research, a mixed mode of gyro is implemented in FGA. In addition to the hardware implementation, the simulation study was conducted by using the SABER for the mixed mode simulator. Results for the practical implementation of the satellite ACS (Attitude Control System) interfaced with the data processing are also presented to validate the FPGA implementation.

• Communications for Statistical Applications and Methods
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• v.22 no.5
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• pp.507-518
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• 2015

It is not easy to select a linear mixed model since the main interest for model building could be different and the number of parameters in the model could not be clearly defined. In this paper, performance of conditional Akaike Information Criteria and its bias-corrected version are compared with marginal Bayesian and Akaike Information Criteria through a simulation study. The results from the simulation study indicate that bias-corrected conditional Akaike Information Criteria shows promising performance when candidate models exclude large models containing the true model, but bias-corrected one prefers over-parametrized models more intensively when a set of candidate models increases. Marginal Bayesian and Akaike Information Criteria also have some difficulty to select the true model when the design for random effects is nested.

• Structural Engineering and Mechanics
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• v.69 no.4
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• pp.427-437
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• 2019

In this study, an alternative solution procedure presented by using variational methods for analysis of shear deformable functionally graded material (FGM) beams with mixed formulation. By using the advantages of $G{\hat{a}}teaux$ differential approaches, a refined complex general functional and boundary conditions which comprises seven independent variables such as displacement, rotation, bending moment and higher-order bending moment, shear force and higher-order shear force, is derived for general thick-thin FGM beams via shear deformation beam theories. The mixed-finite element method (FEM) is employed to obtain a beam element which have a 2-nodes and total fourteen degrees-of-freedoms. A computer program is written to execute the analyses for the present study. The numerical results of analyses obtained for different boundary conditions are presented and compared with results available in the literature.

• Communications for Statistical Applications and Methods
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• v.30 no.5
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• pp.437-451
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• 2023

Generalized linear models and generalized linear mixed models (GLMMs) are fundamental tools for predictive analyses. In insurance, GLMMs are particularly important, because they provide not only a tool for prediction but also a theoretical justification for setting premiums. Although thousands of resources are available for introducing GLMMs as a classical and fundamental tool in statistical analysis, few resources seem to be available for the insurance industry. This study targets insurance professionals already familiar with basic actuarial mathematics and explains GLMMs and their linkage with classical actuarial pricing tools, such as the Buhlmann premium method. Focus of the study is mainly on the modeling aspect of GLMMs and their application to pricing, while avoiding technical issues related to statistical estimation, which can be automatically handled by most statistical software.

• Journal of Korean society of Dental Hygiene
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• v.22 no.3
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• pp.161-170
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• 2022

Objectives: This study aims to conduct in-depth research on the effect of non-surgical periodontal therapy (NSPT) with the application of a comprehensive dental hygiene care (CDHC) process, and provide basic data for the wide application of CDHC. Methods: From May 8, 2021 to September 24, 2021, mixed-methods research was conducted in 36 patients with periodontal diseases. A paired samples t-test was used to analyze the quantitative research data using IBM SPSS program(ver. 22.0; IBM Corp., Armonk, NY, USA) and qualitative research data were analyzed using the thematic analysis method. Results: With NSPT applying the CDHC process, the perception of periodontal health and self-efficacy of periodontal healthcare were increased (p<0.001). Presence of gingivitis, probing pocket depth, bleeding on probing rate, presence of subgingival calculus, and dental plaque index were reduced (p<0.001). Based on 195 meaningful statements, 26 concepts, 12 sub-themes, and 5 themes , , , and were drawn. Conclusions: The perception of periodontal health and the self-efficacy were improved, and substantial change in the clinical index. The CDHC application allowed the study participants to perceive the importance of dental care and professionalism of dental hygienists.