• IE interfaces
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• v.17 no.3
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• pp.282-293
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• 2004

Line Balancing is the problem to assign tasks to stations while satisfying some managerial viewpoints. Most researches about the Mixed-Model Line Balancing problems are focused on the minimizing the total processing time or the number of workstations. Independently, some research reports consider the balance issues of the physical workloads on the assembly line. In this paper, we are presenting a new mathematical model to accomplish the line balance considering both the processing time and the workloads at the same time. To this, end, we propose an zero-one integer program problem, and we use the Chebyshev Goal Programming approach as the solution method. Some computational test runs are performed to compare the pay-offs between the processing time and the workloads. And, the test results show us that the reliable balanced work schedules can be obtained through the proposed model.

• Communications for Statistical Applications and Methods
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• v.27 no.5
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• pp.523-533
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• 2020

This paper suggests three available methods for finding nonnegative estimates of variance components of the random effects in mixed models. The three proposed methods based on the concepts of projections are called projection method I, II, and III. Each method derives sums of squares uniquely based on its own method of projections. All the sums of squares in quadratic forms are calculated as the squared lengths of projections of an observation vector; therefore, there is discussion on the decomposition of the observation vector into the sum of orthogonal projections for establishing a projection model. The projection model in matrix form is constructed by ascertaining the orthogonal projections defined on vector subspaces. Nonnegative estimates are then obtained by the projection model where all the coefficient matrices of the effects in the model are orthogonal to each other. Each method provides its own system of linear equations in a different way for the estimation of variance components; however, the estimates are given as the same regardless of the methods, whichever is used. Hartley's synthesis is used as a method for finding the coefficients of variance components.

• Journal of the Korea Safety Management & Science
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• v.11 no.3
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• pp.209-216
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• 2009

A development in method of evaluating the measurement precisions using approximate F tests and variance components from expected mean square (EMS) is investigated. The research proposes three-factor mixed measurement models with the fixed and random factors. Unrestricted and unconstrained design work was rarely studied, while restricted and constrained designs have been significantly discussed. The unrestricted and unconstrained designs assume to be an independence of interaction. The proposed evaluation method about the measurement precisions can be extended to four-factor random measurement model or mixed measurement model. The study also presents the three evaluation indexes of precisions such as R&RTR (Reproducibility & Repeatability-To-Total Precision Ratio), PTR (Precision-To-Tolerance Ratio), and SNR (Signal-To-Noise Ratio). Numerical examples are proposed to evaluate the approximate F tests with Satterthwaite degrees of freedom and three indexes using the measurement precisions from EMS.

• Journal of Industrial Technology
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• v.27 no.A
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• pp.149-155
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• 2007

The counter emf(electromotive forces) of a permanent magnet multi-phase brushless motor is generally a non-sinusoidal wave or a non-ideal trapezoid. So, conventional modeling using a sinusoidal wave or an ideal trapezoid counter emf can result in errors. In order to reduce modeling errors for simulation and analysis the properties of a multi-phase brushless AC motor, this paper proposes a phase variable model that is a mixed modeling technique using both Finite Element Analysis(FEA) based circuits and motor voltage equations. The phase model parameters including the counter emf voltage waveform are obtained by using of FEA, and the mixed modeling technique based on circuits and equations is used to implement a simulation model for multi-phase brushless AC motors with any counter emf voltage waveforms. Adequacy of the proposed model is established from the simulation and experimental results for a seven-phase brushless motor.

• 한국데이터정보과학회:학술대회논문집
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• 2001.10a
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• pp.25-33
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• 2001

This paper suggests a generalized logit model with mixed effects for analysing frequency data in multi-contingency table. In this model nominal response variable is assumed to be polychotomous. When some factors are fixed but condisered as ordinal and others are random, this paper shows how to use baseline-category logits to incoporate the mixed-effects of those factors into the model. A numerical algorithm was used to estimate model parameters by using marginal log-likelihood.

• 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.41 no.2
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• pp.157-181
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• 2012

The paper presents a review of the application of the newly proposed mixed finite element model for seismic simulation of different types of composite frame structures. To evaluate the performance of the element, a comparison with displacement-based and force-based models is conducted. The study revealed that the mixed model is superior to the others in terms of both speed of convergence and numerical stability, and is therefore considered the most practical approach for modeling of composite structures. In this model, the element is derived using independent force and displacement shape functions. The nonlinear response of the frame element is based on the section discretization into fibers with uniaxial material models. The interfacial behavior is modeled using an inelastic interface element. Numerical examples to clarify the advantages of the model are presented for the following structural applications: anchored reinforcing bar problems, composite steel-concrete girders with deformable shear connectors, beam on elastic foundation elements, R/C girders strengthened with FRP sheets, R/C beam-columns with bond-slip, and prestressed concrete girders. These studies confirmed that the model represents a major advancement over existing elements in simulating the inelastic behavior of composite structures.

• The Korean Journal of Applied Statistics
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• v.17 no.2
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• pp.337-346
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• 2004

The Pearson chi-square goodness-of-fit test and the likelihood ratio tests are usually used for testing independence in two-way contingency tables under random sampling. But both of these tests may provide false results for the contingency table with clustered observations. In this case we consider the generalized linear mixed model which includes random effects of clustering in addition to the fixed effects of covariates. Both the heterogeneity between clusters and the dependency within a cluster can be explained via generalized linear mixed model. In this paper we introduce several types of generalized linear mixed model for testing independence in contingency tables with clustered observations. We also discuss the fitting of these models through a real dataset.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.7
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• pp.1439-1445
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• 2009

This paper introduces a simulation model regarding the process analysis of a digital doorlock mixed assembly process. The objective of the simulation model is to evaluate the performance of various design aspects of process alternatives. To develop the simulation model, a time study is performed for each process. Next, by using ARENA, a simulation model is conducted based on the process analysis and the line balancing methodology. We found out several problems for mixed assembly process, and then suggest several alternatives to improve the system.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.465-474
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• 2015

In this paper, we study the local influence analysis of LIU type estimator in the linear mixed models. Using the method proposed by Shi (1997), the local influence of LIU type estimator in three disturbance models are investigated respectively. Furthermore, we give the generalized Cook's distance to assess the influence, and illustrate the efficiency of the proposed method by example.