• Journal of Distribution Science
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• v.19 no.6
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• pp.5-19
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• 2021

Purpose: O2O Service is a major internet-based distribution industry. The purpose of this study is to confirm the effects of positive psychological capital on job intensity, customer orientation, and the mediating effects of trust of O2O employee. Research design, data and methodology: This study aims to identify the effect of positive psychological capital on customer orientation and job intensity through empirical analysis. 475 questionnaires were used for the final analysis using random sampling methods from O2O employees working at leading distribution companies for hypothesis verification. The analysis methods used for hypothesis testing in this study were analyzed using the SPSS 21.0 statistical package. Results: Empirical analysis shows that it is an important factor in increasing job intensity and customer orientation, and that company trust has a significant influence through mediating effects among variables. Conclusions: In order to enhance job intensity and customer orientation for O2O distribution workers, it is necessary to change efforts with management efforts for positive psychological factors and trust. It is also believed that company trust should be considered as an important factor in the future leadership competency development system in that it can promote positive psychological capital, further strengthening job intensity and customer orientation.

• Journal of Korean Society for Quality Management
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• v.26 no.4
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• pp.111-123
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• 1998

We consider the problem of modeling count data where the observation period is determined by the life time of the system under study. We assume random effects or a frailty model to allow for a possible association between the death times and the counts. We assume that, given a random effect or a frailty, the death times follow a Weibull distribution with a hazard rate. For the counts, given a frailty, a Poisson process is assumed with the intensity depending on time. A gamma distribution is assumed for the frailty model. Maximum likelihood estimators of the model parameters are obtained. A model for the time to death and the number of failures system received is constructed and consequences of the model are examined.

• The Korean Journal of Applied Statistics
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• v.13 no.1
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• pp.115-131
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• 2000

이 논문에서는 평균-이동모형(mean-shift model)을 이상점을 위한 대립모형으로 사용하여 변량모형(random effect model)에서의 이상점 검출을 위한 베이즈인자(Bayes factor)를 제시한다. 그러나 가능한 사전 정보가 없어서 무정보사전분포(noninformative prior distribution)가 사용되어야만 할 때, 대부분의 무정보사전분포는 부적절분포(improper distribution)이기 때문에 베이즌 인자에는 사전분포로부터 나온 미지의 상수가 포함되어 잇다. 이 문제를 해결하기 위해 이 논문에서는 Berger와 Pericchi (1996)가 제시한 내재베이즈인자(the intrinsic Bayes factor;IBF)를 사용한다. 또한 이 베이즈인자를 계산상 어려움을 해결하기 위해 Verdinellidh Wasserman(1995)의 일반화 세비디지키 밀도비를 이용하여 수정하고 이것을 이용하여 이상점을 검출하는 방법을 제시한다. 마지막으로 인위적으로 이상점을 포함하고 있는 데이터를 만들고 제시된 방법으로 가상실험을 하고 또한 실제 데이터에서 제시한 방법으로 이상점을 찾아보았다.

• International Journal of Precision Engineering and Manufacturing
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• v.4 no.6
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• pp.12-19
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• 2003

This paper presents the effect of boundary conditions in various failure pressure models published for the estimation of failure pressure. Furthermore, this approach is extended to the failure prediction with the aid of a failure probability model. The first order Taylor series expansion of the limit state function is used in order to estimate the probability of failure associated with each corrosion defect in buried pipelines for long exposure period with unit of years. A failure probability model based on the von-Mises failure criterion is adapted. The log-normal and standard normal probability functions for varying random variables are adapted. The effects of random variables such as defect depth, pipe diameter, defect length, fluid pressure, corrosion rate, material yield stress, material ultimate tensile strength and pipe thickness on the failure probability of the buried pipelines are systematically investigated for the corrosion pipeline by using an adapted failure probability model and varying failure pressure model.

• Journal of the Semiconductor & Display Technology
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• v.18 no.4
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• pp.25-29
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• 2019

Microstructure pattern generation on light guides in backlight unit (BLU) is an essential process for designing flat panel display, but efficient designing algorithm is still limited to achieve uniform luminescence while maintaining fully random distribution to avoid interference effects. In this study, a molecular dynamics model based pattern generation algorithm has been developed. The proposed algorithm allows a fast and efficient distribution of patterns at specified density within the user-defined computational cells, and its efficiency and performance has been demonstrated with sample cases.

• The Korean Journal of Applied Statistics
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• v.6 no.2
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• pp.355-370
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• 1993

The estimations of variance components for the unbalanced one way random effects model when the underlying distributions are not necessarily normal are considered. ANOVA, REML, ML, MIVQUE, and MINQE estimators are compared with respect to their mean squared errors and biases through a simulation study. Explicit, computable expressions with no matrix inversion necessary are given for these estimators. An efficient rule to provide a prior guess of MINQE is given. Our results indicate that the efficiency of MINQE is excellent for arbitrary underlying distribution in the sense of MSE even in the presence of nontrivial bias. Also, MINQE is a worthwhile improvement over other estimators when kurtosis of underlying distributions become large 1.

• Journal of Electrical Engineering and Technology
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• v.9 no.5
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• pp.1482-1488
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• 2014

The reliability evaluation of the electrical distribution networks (EDN) requires sufficient consideration of the effects of planned outages. The planned outages of the EDN can be divided, by outage models and their effects on the reliability into two major categories: by equipment and by feeder. After studying the characteristics of different categories of planned outages, this paper expands the classification of load points by outage time from 4 types to 7 types and defines corresponding reliability parameters for the different types. By using the section algorithm, this paper proposes a reliability evaluation technique of EDN considering equipment random failures and two categories of planned outages. The proposed technique has been applied to the RBTS-BUS6 test system and some practical EDNs in China. The study results demonstrate that the proposed technique is of higher practical value and can be used for evaluating the reliability performance of EDN more efficiently considering the planned outages.

• IEIE Transactions on Smart Processing and Computing
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• v.2 no.4
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• pp.216-225
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• 2013

This paper discusses the issues regarding an abnormal V-shaped error confronting algebraic-based deconvolution process. Deconvolution was applied to an analysis of the effects of the Random Telegraph Noise (RTN) and Random Dopant Fluctuation (RDF) on the overall SRAM margin variations. This paper proposes a technique to suppress the problematic phenomena in the algebraic-based RDF/RTN deconvolution process. The proposed technique can reduce its relative errors by $10^{10}$ to $10^{16}$ fold, which is a sufficient reduction for avoiding the abnormal ringing errors in the RTN deconvolution process. The proposed algebraic-based analyses allowed the following: (1) detection of the truncating point of the TD-MV distributions by the screening test, and (2) predicting the MV-shift-amount by the assisted circuit schemes needed to avoid the out of specs after shipment.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.31 no.5
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• pp.278-293
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• 2019

The joint distribution of wave height and period has been maltreated despite of its great engineering value due to the absence of any analytical model for wave period, and as a result, no consensus has been reached about the effect of nonlinearity on these joint distribution. On the other hand, there was a great deal of efforts to study the effects of non-linearity on the wave height distribution over the last decades, and big strides has been made. However, these achievements has not been extended to the joint distribution of wave height and period. In this rationale, we first express the joint distribution of wave height and period as the product of the marginal distribution of wave heights with the conditional distribution of associated periods, and proceed to derive the joint distribution of wave heights and periods utilizing the models of Longuet-Higgins (1975, 1983), and Cavanie et al. (1976) for conditional distribution of wave periods, and height distribution derived in this study. The verification was carried out using numerically simulated data based on the Wallops spectrum, and the nonlinear wave data obtained via the numerical simulation of random waves approaching toward the uniform beach of 1:15 slope. It turns out that the joint distribution based on the height distribution for finite banded nonlinear waves, and Cavanie et al.'s model (1976) is most promising.

• The Korean Journal of Applied Statistics
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• v.22 no.1
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• pp.153-161
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• 2009

We consider a logistic model with random effects as the superpopulation for estimating the small area pro-portions. The best linear unbiased predictor under linear mired model is popular in small area estimation. We use this type of estimator under logistic mixed motel for the small area proportions, on which the estimation of mean squared error is also discussed. Two kinds of estimation methods, the parametric bootstrap and the linear approximation will be compared through a Monte Carlo study in the respects of the normality assumption on the random effects distribution and also the magnitude of sample sizes on the approximation.