• Communications for Statistical Applications and Methods
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• v.25 no.1
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• pp.61-70
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• 2018

Modeling of the random effects covariance matrix in generalized linear mixed models (GLMMs) is an issue in analysis of longitudinal categorical data because the covariance matrix can be high-dimensional and its estimate must satisfy positive-definiteness. To satisfy these constraints, we consider the autoregressive and moving average Cholesky decomposition (ARMACD) to model the covariance matrix. The ARMACD creates a more flexible decomposition of the covariance matrix that provides generalized autoregressive parameters, generalized moving average parameters, and innovation variances. In this paper, we analyze longitudinal count data with overdispersion using GLMMs. We propose negative binomial loglinear mixed models to analyze longitudinal count data and we also present modeling of the random effects covariance matrix using the ARMACD. Epilepsy data are analyzed using our proposed model.

• Bulletin of the Korean Chemical Society
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• v.8 no.6
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• pp.462-465
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• 1987

The aggregation between cationic and anionic surfactants was studied by turbidimetric and nephelometric methods with emphasis on facile analysis of the surfactants and understanding of the mixed micellization. The turbidimetric titration of sodium dodecylsulfate (SDS) with cetyltrimethylammonium bromide (CTAB) or cetylpyridinium bromide (CPB) showed maximum turbidity at equimolar composition in the SDS concentration range of 0.1-0.9 mM. The nephelometric titration of the same systems extended the limit of analysis to 0.001 mM. The sodium salts of decylsulfate and sulfonate gave similar maxima, but not at equimolar composition. The coexistence of equimolar aggregates and mixed micelles were shown over broad composition range. The aggregation and mixed micellization of the anionic/cationic surfactants mixtures depended sensitively on the hydrophobic character of the surfactants.

• 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.

• Journal of Korea Society of Industrial Information Systems
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• v.15 no.3
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• pp.59-65
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• 2010

This paper proposes a modified heuristic mixed model assembly line (MMAL) balancing algorithm that provides consistent station assignments on a model by model basis as well as on a station by station. Basically, some of single model line balancing techniques are modified and incorporated to be fit into the MMAL. The proposed algorithm is based on N.T. Thomopoulos' [8] method and supplemented with several well proven single model line balancing techniques proposed in the literature until recently. Hoffman's precedence matrix [2] is used to indicate the ordering relations among tasks. Arcus' Rule IX [1] is applied to generate rapidly a fairly large number of feasible solutions. Consequently, this proposed algorithm reduces the fluctuations in operation times among the models as well as the stations and the balance delays. A numerical example shows that the proposed algorithm can provide a good feasible solution in a relatively short time and generate relatively better solutions comparing to other three existing methods.

• 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 Information Processing Systems
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• v.19 no.6
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• pp.858-869
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• 2023

As one of the pivotal techniques of image restoration, single-channel blind source separation (SCBSS) is capable of converting a visual-only image into multi-source images. However, image degradation often results from multiple mixing methods. Therefore, this paper introduces an innovative SCBSS algorithm to effectively separate source images from a composite image in various mixed modes. The cornerstone of this approach is a novel triple generative adversarial network (TriGAN), designed based on dual learning principles. The TriGAN redefines the discriminator's function to optimize the separation process. Extensive experiments have demonstrated the algorithm's capability to distinctly separate source images from a composite image in diverse mixed modes and to facilitate effective image restoration. The effectiveness of the proposed method is quantitatively supported by achieving an average peak signal-to-noise ratio exceeding 30 dB, and the average structural similarity index surpassing 0.95 across multiple datasets.

• Journal of the Korean Institute of Educational Facilities
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• v.6 no.2
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• pp.77-85
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• 1999

• Education of Primary School Mathematics
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• v.21 no.3
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• pp.289-307
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• 2018

Although mixed calculation of natural numbers is important in that it completes arithmetic calculation of natural numbers in elementary school, few studies have been conducted regarding its instruction methods. Given this, this study analyzed Korean mathematics textbooks (from the fifth textbooks to the 2009 revised textbooks) along with Japanese and Singaporean textbooks in terms of the parentheses and the order of operations regarding mixed calculation of natural numbers. The results of this study showed that there were differences in introducing the parentheses and representing them in an explicit way per textbooks. In the Korean textbooks, the order of operations was presented mostly with the real-life contexts but it was not always in a diagrammatic representation. In contrast, in the Singaporean textbooks, the order of operations was presented without the real-life contexts and the use of calculators was emphasized. In the Japanese textbooks, the order of operations was presented with the real-life contexts and a hierarchy of operations was emphasized. Based on these results, this study suggested several implications of textbook development and instructional methods regarding mixed calculations of natural numbers.

• Journal of the korean academy of Pediatric Dentistry
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• v.49 no.1
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• pp.85-94
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• 2022

This retrospective study aimed to evaluate the difference in measurement between conventional orthodontic analysis and artificial intelligence orthodontic analysis in pediatric and adolescent patients aged 7 - 15 with the mixed and permanent dentition. A total of 60 pediatric and adolescent patients (30 mixed dentition, 30 permanent dentition) who underwent lateral cephalometric radiograph for orthodontic diagnosis were randomly selected. Seventeen cephalometric landmarks were identified, and 22 measurements were calculated by 1 examiner, using both conventional analysis method and deep learning-based analysis method. Errors due to repeated measurements were assessed by Pearson's correlation coefficient. For the mixed dentition group and the permanent dentition group, respectively, a paired t-test was used to evaluate the difference between the 2 methods. The difference between the 2 methods for 8 measurements were statistically significant in mixed dentition group: APDI, SNA, SNB, Mandibular plane angle, LAFH (p < 0.001), Facial ratio (p = 0.001), U1 to SN (p = 0.012), and U1 to A-Pg (p = 0.021). In the permanent dentition group, 4 measurements showed a statistically significant difference between the 2 methods: ODI (p = 0.020), Wits appraisal (p = 0.025), Facial ratio (p = 0.026), and U1 to A-Pg (p = 0.001). Compared with the time-consuming conventional orthodontic analysis, the deep learning-based cephalometric system can be clinically acceptable in terms of reliability and validity. However, it is essential to understand the limitations of the deep learning-based programs for orthodontic analysis of pediatric and adolescent patients and use these programs with the proper assessment.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2009.05c
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• pp.65-68
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• 2009

Recently, the knowledge access about concrete might be 2 methods. One is approach about advanced and new technical development through the institute journal, the other is construction technology which is using at construction fields. However, there is no research for the interrelationship between them. So, this paper investigates the demands on construction fields at the ready mixed concrete plants on the 4 cities, the characteristics of the products like the maximum size of coarse aggregate and slump, and the extension of market on the high strength and flow ability concrete in 2000 and 2008. Moreover, this study would like to propose the investigation about diversification of construction materials for the fine construction cultures and development of the ready mixed concrete to the engineers at the construction fields.