• International Journal of Ocean System Engineering
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• v.2 no.4
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• pp.250-258
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• 2012

The distribution of wave heights is assumed to be a Rayleigh distribution, based on the assumption of a narrow band and Gaussian distribution of wave elevation. The present study was started with doubts about the narrow band assumption. We selected the wave spectra widely used to simulate irregular random waves. The wave spectra used in this study included the Pierson-Moskowitz spectrum, Bretschneider-Mitsuyasu spectrum, and JONSWAP spectrum. The directionality of the waves was considered. The cosine 2-l type directional spreading function and mixed form of the half-cosine 2-s type with Mitsuyasu type directional spreading are considered here to investigate the effects of a directional spreading function on random waves. The simulated wave height distribution is compared with a Rayleigh distribution.

• Structural Engineering and Mechanics
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• v.33 no.5
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• pp.589-604
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• 2009

In the field of predicting structural safety and reliability the operating conditions play an essential role. Since the time and cost limitations are a significant factors in engineering it is important to predict the future operating conditions as close to the actual state as possible from small amount of available data. Because of the randomness of the environment the shape of measured load spectra can vary considerably and therefore simple distribution functions are frequently not sufficient for their modelling. Thus mixed distribution functions have to be used. In general their major weakness is the complicated calculation of unknown parameters. The scope of the paper is to investigate the load spectra growth for actual operating conditions and to investigate the modelling and extrapolation of load spectra with algorithm for mixed distribution estimation, REBMIX. The data obtained from the measurements of wheel forces and the braking moment on proving ground is used to generate load spectra.

• The Korean Journal of Applied Statistics
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• v.25 no.6
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• pp.1037-1047
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• 2012

The generalized linear mixed model(GLMM) is widely used in fitting categorical responses of clustered data. In the numerical approximation of likelihood function the normality is assumed for the random effects distribution; subsequently, the commercial statistical packages also routinely fit GLMM under this normality assumption. We may also encounter departures from the distributional assumption on the response variable. It would be interesting to investigate the impact on the estimates of parameters under misspecification of distributions; however, there has been limited researche on these topics. We study the sensitivity or robustness of the maximum likelihood estimators(MLEs) of GLMM for counts data when the true underlying distribution is normal, gamma, exponential, and a mixture of two normal distributions. We also consider the effects on the MLEs when we fit Poisson-normal GLMM whereas the outcomes are generated from the negative binomial distribution with overdispersion. Through a small scale Monte Carlo study we check the empirical coverage probabilities of parameters and biases of MLEs of GLMM.

• Journal of the Korean Institute of Educational Facilities
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• v.16 no.1
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• pp.51-58
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• 2009

The purpose of this study is to have a guideline for mixed-use between school buildings and the community facilities as one of the suggestions to satisfy the needs of the society and to overcome the limitations of the supply of regional facilities. Main contents of this study are as a follow : 1) Arrangement of concept for mixed-use facilities, 2) Classification of community facilities for school buildings. 3) Distribution of school buildings in Nowon-Gu 4) Distribution of community facilities in Nowon-Gu 5) A proposal of mixed-use guide line between school buildings and public office.

• Industrial Engineering and Management Systems
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• v.8 no.3
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• pp.131-138
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• 2009

The variable sampling inspection scheme with screening for the purpose of assuring the upper limit of maximum expected surplus loss after inspection has been proposed. In this inspection scheme, it has been assumed that a product lot consists of products manufactured through a single production line and lot quality characteristics follow a normal distribution. In the previous literature with respect to inspection schemes, it has been commonly assumed that lot quality characteristics obey a single normal distribution under the condition that all products are manufactured in the same condition. On the other hand, the production line is designed in order that the workload of respective processes becomes uniform from the viewpoint of line balancing. One of the solutions for the bottleneck process is to arrange the workshops in parallel. The lot quality characteristics from such a production line with the process consisting of some parallel workshops might not follow strictly the single normal distribution. Therefore, we expand an applicable scope of the above mentioned variable sampling inspection scheme with screening in this article. Concretely, we consider the variable sampling inspection with screening for the purpose of assuring the upper limit of average outgoing surplus quality loss in the production lots when the lot quality follows the mixed normal distribution.

• Communications for Statistical Applications and Methods
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• v.25 no.2
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• pp.173-184
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• 2018

In medical or public health research, it is common to encounter clustered or longitudinal count data that exhibit excess zeros. For example, health care utilization data often have a multi-modal distribution with excess zeroes as well as a multilevel structure where patients are nested within physicians and hospitals. To analyze this type of data, zero-inflated count models with mixed effects have been developed where a count response variable is assumed to be distributed as a mixture of a Poisson or negative binomial and a distribution with a point mass of zeros that include random effects. However, no study has considered a situation where data are also censored due to the finite nature of the observation period or follow-up. In this paper, we present a weighted version of zero-inflated Poisson model with random effects accounting for variable individual follow-up times. We suggested two different types of weight function. The performance of the proposed model is evaluated and compared to a standard zero-inflated mixed model through simulation studies. This approach is then applied to Medicaid data analysis.

• Tribology and Lubricants
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• v.16 no.2
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• pp.106-113
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• 2000

Effects of surface roughness on bearing performances are investigated numerically in this study, especially for the parallel thrust bearing. Although mating surfaces are parallel and separated by thin fluid film, the pressure distribution is formed due to asperities. Model surface is generated numerically with given autocorrelation function and some surface profile parameters. Then the average Reynolds equation is applied to predict the effects of surface roughness between hydrodynamic and mixed lubrication regimes. In this equation, flow factors are defined as correction terms to smooth out high frequency surface roughness. The correlation length is proposed to get the minimum load for the parallel thrust bearing for various sliding conditions.

• Steel and Composite Structures
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• v.27 no.6
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• pp.789-801
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• 2018

A weak-form formulation of finite annular prism methods (FAPM) based on Reissner's mixed variational theorem (RMVT), is developed for the quasi three-dimensional (3D) static analysis of two-directional functionally graded (FG) circular plates with various boundary conditions and under mechanical loads. The material properties of the circular plate are assumed to obey either a two-directional power-law distribution of the volume fractions of the constituents through the radial-thickness surface or an exponential function distribution varying doubly exponentially through it. These FAPM solutions of the loaded FG circular plates with both simply-supported and clamped edges are in excellent agreement with the solutions obtained using the 3D analytical approach and two-dimensional advanced plate theories available in the literature.

• Proceedings of the KSME Conference
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• 2001.06d
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• pp.104-109
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• 2001

The time to measure the size distribution using Condensation Nuclei Counter(CNC) and Differential Mobility Analyzer(DMA) can be shortened by classifying particles ramping the DMA voltage exponentially and continuously. In measurement, particles sampled at different time are mixed together going through sampling tube and CNC. Because the size distribution is inversed by using detector responses to sampling time intervals in this accelerated method, the mixing effects give inversion errors to the size distribution. The mixing effects can be considered by appling the transfer function with mixing effects to the data inversion. The inversion considering this effects gives birth to the size distribution shifted to the opposite direction of the size scanning.

• Communications for Statistical Applications and Methods
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• v.27 no.3
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• pp.349-363
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• 2020

Penalized spline is a suitable nonparametric approach in estimating mean model in small area. However, application of the approach in informative sampling in a published article is uncommon. We propose a semiparametric mixed-model using penalized spline under informative sampling to estimate mean of small area. The response variable is explained in terms of mean model, informative sample effect, area random effect and unit error. We approach the mean model by penalized spline and utilize a penalized spline function of the inclusion probability to account for the informative sample effect. We determine the best and unbiased estimators for coefficient model and derive the restricted maximum likelihood estimators for the variance components. A simulation study shows a decrease in the average absolute bias produced by the proposed model. A decrease in the root mean square error also occurred except in some quadratic cases. The use of linear and quadratic penalized spline to approach the function of the inclusion probability provides no significant difference distribution of root mean square error, except for few smaller samples.