• Journal of Korean Society of Transportation
• /
• v.29 no.6
• /
• pp.67-74
• /
• 2011

This study deals with the traffic accidents data from the Korean rotaries (circular intersections) to verify their characteristics affected by different vehicle types. This paper categorized the data into three groups based on vehicle types, and developed a set of accident models. The paper proposed two ZIP models and one negative binomial model through a statistical analysis for three vehicle types: automobile, truck and van, and others. The differences among those models were then statistically compared.

• Proceedings of the KIEE Conference
• /
• 2001.05a
• /
• pp.176-179
• /
• 2001

RTDS는 실시간 디지털 시뮬레이터로서 전력계통에서 발생되는 각종 현상의 실시간 재현과 분석이 가능하다. 특히, 계통 모의를 효율적으로 수행할 수 있도록 자동모의기능 및 고장순서 지정을 위한 시퀀스 기능 등이 포함되어 있다 최근에는 계통의 과도 및 전압안정도의 효율적인 모의를 위한, RTDS ZIP 부하모델과 동적(Dynamic)부하 모델이 개발되었다. 따라서, 본 논문에서는 이러한 다양한 기능들과 RTDS 부하모델을 이용하여 계통의 안정도 모의를 훈련할 수 있는 케이스를 개발하였다.

• The Korean Journal of Franchise Management
• /
• v.11 no.3
• /
• pp.7-18
• /
• 2020

Purpose: Recently, information on 'Delicious Restaurants (Mat-zip)' and 'Famous Bakeries' can be obtained through various media such as TV, Internet search, and SNS, and the culture of finding and sharing them has become a trend. Since PZB's SERVQUAL, there have been many studies measuring service quality, leading to hotels, restaurants and coffee shops. These studies of service quality include product quality in the service quality dimension. Hotels, restaurants, and coffee shops are provided with intangible services while customers visit and stay, but 'Delicious Restaurants (Mat-zip)' and 'Famous Bakeries' often stop by to buy products and return home. Therefore, the study on the effect of quality on customer behavior on 'Delicious Restaurants (Mat-zip)' should consider product quality separately. In this study, we want to study how each quality element affects the perceived value and response of customers by separating product quality and service quality. Research design, data, and methodology: This study tested the structural model of how the quality of products and services of famous bakeries affect customers' perceived value and response. As the quality factors, products, tangible services, and employee services were adopted, and perceived values adopted utilitarian and hedonic values, and customer responses adopted customer satisfaction and behavior intention. For this study, 203 survey data with experience using famous bakeries were analyzed using SPSS 22.0 and AMOS 22.0. Result: The research results are as follows. First, product quality positively influenced utilitarian value, hedonic value, and customer satisfaction, tangible service quality positively influenced utilitarian value, and employee service quality positively influenced hedonic value. Second, utilitarian value had a positive effect on behavioral intention, and hedonic value had a positive effect on customer satisfaction. Conclusions: In a famous bakery, it is basic that product quality should be given priority, and for customer satisfaction, employee service quality is half as important. In addition, for Behavior Intension (revisit by the customer), in addition to product quality, the quality of tangible services and employee services should be maintained at a quarter level.

• The Korean Journal of Applied Statistics
• /
• v.28 no.2
• /
• pp.231-239
• /
• 2015

A Poisson model is the first choice for counts data. Quasi Poisson or negative binomial models are usually used in cases of over (or under) dispersed data. However, these models might be unsuitable if the data consist of excessive number of zeros (zero inflated data). For zero inflated counts data, Zero Inflated Poisson (ZIP) or Zero Inflated Negative Binomial (ZINB) models are recommended to address the issue. In this paper, we further considered a situation where zero inflated data are spatially correlated. A mixed effect model with random effects that account for spatial autocorrelation is used to fit the data.

• The Pure and Applied Mathematics
• /
• v.20 no.1
• /
• pp.59-70
• /
• 2013

The purpose of this study was to develop a zero-inflated Rasch (ZI-Rasch) model, a combination of the Rasch model and the ZIP model. The ZI-Rasch model was considered in this study as an appropriate alternative to the Rasch model for zero-inflated data. To investigate the relative appropriateness of the ZI-Rasch model, several analyses were conducted using PROC NLMIXED procedures in SAS under various simulation conditions. Sets of criteria for model evaluations (-2LL, AIC, AICC, and BIC) and parameter estimations (RMSE, and $r$) from the ZI-Rasch model were compared with those from the Rasch model. In the data-model fit indices, regardless of the simulation conditions, the ZI-Rasch model produced better fit statistics than did the Rasch model, even when the response data were generated from the Rasch model. In terms of item parameter ${\lambda}$ estimations, the ZI-Rasch model produced estimates similar to those of the Rasch model.

• Journal of East-West Nursing Research
• /
• v.28 no.2
• /
• pp.160-169
• /
• 2022

Purpose: This study was conducted to identify predictors related to aggressive behavior of patients with mental illness admitted to a closed psychiatric ward. Methods: This study adopted a retrospective design which analyzed the hospital medical records of 363 patients with mental illness admitted to the psychiatric closed ward of a university hospital in Seoul, Korea. The collected data were analyzed using SPSS IBM 20.0 and STATA 12.0 SE. ZIP (Zero-Inflated Poisson) and count data analysis were used for the factor influencing the occurrence and frequency of aggressive behavior. Results: The results of ZIP model showed that the factors influencing non-probability of aggressive behavior were anxiety, non-adherence, and frustration. In addition, the factors influencing frequency of aggressive behavior were bipolar disorder and personality disorder trait. Conclusion: We found that bipolar disorder, frustration, and non-adherence are more likely to increase the likelihood of aggressive behavior in patients with mental illness. In particular, patients diagnosed with bipolar disorder were 1.95 times more likely to engage in repetitive aggressive behavior compared to those without a diagnose. However, since the results were different form previous studies, further studies on the traits of anxiety and personality disorders are needed.

• Journal of Electrical Engineering and Technology
• /
• v.7 no.6
• /
• pp.845-851
• /
• 2012

Power system loads have a significant impact on a system. Although it is difficult to precisely describe loads in a mathematical model, accurately modeling them is important for a system analysis. The traditional load modeling method is based on the load components of a bus. Recently, the load modeling method based on measurements from a system has been introduced and developed by researchers. The two major components of a load modeling problem are determining the mathematical model for the target system and estimating the parameters of the determined model. We use the composite load model, which has both static and dynamic load characteristics. The ZIP model and the induction motor model are used for the static and dynamic load models, respectively. In this work, we propose the measurement-based parameter estimation method for the composite load model. The test system and related measurements are obtained using transient security assessment tool(TSAT) simulation program and PSS/E. The parameter estimation is then verified using these measurements. Cases are tested and verified using the sample system and its related measurements.

• Communications for Statistical Applications and Methods
• /
• v.29 no.2
• /
• pp.239-250
• /
• 2022

In many applications, we frequently encounter correlated multiple outcomes measured on the same subject. Joint modeling of such multiple outcomes can improve efficiency of inference compared to independent modeling. For instance, in developmental toxicity studies, fetal weight and number of malformed pups are measured on the pregnant dams exposed to different levels of a toxic substance, in which the association between such outcomes should be taken into account in the model. The number of malformations may possibly have many zeros, which should be analyzed via zero-inflated count models. Motivated by applications in developmental toxicity studies, we propose a Bayesian joint modeling framework for continuous and count outcomes with excess zeros. In our model, zero-inflated Poisson (ZIP) regression model would be used to describe count data, and a subject-specific random effects would account for the correlation across the two outcomes. We implement a Bayesian approach using MCMC procedure with data augmentation method and adaptive rejection sampling. We apply our proposed model to dose-response analysis in a developmental toxicity study to estimate the benchmark dose in a risk assessment.

• Journal of Electrical Engineering and Technology
• /
• v.1 no.2
• /
• pp.161-169
• /
• 2006

Load representation has a significant impact on power system analysis and control results. In this paper, composite load models are developed based on on-line measurement data from a practical power system. Three types of static-dynamic load models are derived: general ZIP-induction motor model, Exponential-induction motor model and Z-induction motor model. For the dynamic induction motor model, two different third-order induction motor models are studied. The performances in modeling real and reactive power behaviors by composite load models are compared with other dynamic load models in terms of relative mismatch error. In addition, numerical consideration of ill-conditioned parameters is addressed based on trajectory sensitivity. Numerical studies indicate that the developed composite load models can accurately capture the dynamic behaviors of loads during disturbance.

• Proceedings of the KIEE Conference
• /
• 2011.07a
• /
• pp.187-188
• /
• 2011

This paper proposes the hybrid Complex-PSO algorithm based on the complex search method and particle swarm optimization (PSO) for unconstrained optimization. This hybridization intends to produce faster and more accurate convergence to the optimum value. These hybrid will concentrate on determining the dynamic load model parameters, the ZIP model and induction motor model parameters. Measurement-based parameter estimation, which employs measurement data to derive load model parameters, is used. The theoretical foundation of the measurement-based approach is system identification. The main objective of this paper is to demonstrate how the standard particle swarm optimization and complex method can be improved through hybridization of the two methods and the results will be compared with that of their original forms.