• Journal of Korean Society for Quality Management
• /
• v.42 no.2
• /
• pp.221-234
• /
• 2014

Purpose: The Purpose of this study is to develop a model for predicting agent churn group in the cosmetics industry. We develope two models, pattern model and matrix model, which are compared regarding the prediction accuracy of churn agents. Finally, we try to conclude if there is statistically significant difference between two models by empirical study. Methods: We develop two models using the part of RFM(Recency, Frequency, Monetary) method which is one of customer segmentation method in traditional CRM study. In order to ensure which model can predict churn agents more precisely between two models, we used CRM data of cosmetics company A in China. Results: Pattern model and matrix model have been developed. we find out that there is statistically significant differences between two models regarding the prediction accuracy. Conclusion: Pattern model and matrix model predict churn agents. Although pattern model employed the trend of monetary mount for six months, matrix model that used the amount of sales per month and the duration of the employment is better than pattern model in prediction accuracy.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.13 no.6
• /
• pp.187-194
• /
• 2005

The objective of this study is to validate the hybrid breakup model and the vaporization model for GDI spray analysis at vaporization and non-vaporization conditions. The atomization process is modeled by using hybrid breakup model that is composed of Linearized Instability Sheet Atomization (LISA) model and Aerodynamically Progressed Taylor Analogy Breakup (APTAB) model. The vaporization process is modeled by using modified Abramzon & Sirignano model. The exciplex fluorescence method was used for comparing the calculated results with the experimental ones. The experiment and the calculation were performed at the ambient pressures of 0.1 MPa, 0.5 MPa and 1.0 MPa and the ambient temperature of 293K and 473K.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.5
• /
• pp.2142-2161
• /
• 2018

Distance dynamics model is an excellent model for uncovering the community structure of a complex network. However, the model has poor robustness. To improve the robustness, we design an enhanced distance dynamics model based on Ego-Leader and propose a corresponding community detection algorithm, called E-Attractor. The main contributions of E-Attractor are as follows. First, to get rid of sensitive parameter ${\lambda}$, Ego-Leader is introduced into the distance dynamics model to determine the influence of an exclusive neighbor on the distance. Second, based on top-k Ego-Leader, we design an enhanced distance dynamics model. In contrast to the traditional model, enhanced model has better robustness for all networks. Extensive experiments show that E-Attractor has good performance relative to several state-of-the-art algorithms.

• Transactions of the Korean Society of Mechanical Engineers B
• /
• v.27 no.12
• /
• pp.1681-1690
• /
• 2003

The effect of roughness is a change in the velocity and turbulence distributions near the surface. Turbulence models with surface roughness effect are applied to the fully developed flow in a two-dimensional, rough wall channel. Modified wall function model, low-Reynolds number k-$\varepsilon$ model, and k-$\omega$ model are selected for comparison. In order to make a fair comparison, the calculation results are compared with the experimental data. The modified wall function model and the low-Reynolds number k-$\varepsilon$ model require further refinement, while the k-$\omega$ model of Wilcox performs remarkably well over a wide range of roughness values.

• Journal of computational fluids engineering
• /
• v.7 no.4
• /
• pp.8-18
• /
• 2002

The primary objective of the present study is evaluation of the k-ε-vv-f turbulence model for prediction of natural convection in a rectangular cavity. As a comparative study, the two-layer k-ε model is also considered. Both models, with and without algebraic heat flux model, are applied to the analysis of natural convection in a rectangular cavity. The performances of turbulence models are investigated through comparison with available experimental data. The predicted results of vertical velocity component, turbulent heat fluxes, turbulent shear stress, local Nusselt number and wall shear stress are compared with experimental data. It is shown that, among the turbulence models considered in the present study, the k-ε-vv-f model with an algebraic heat flux model predicts best the vertical mean velocity and velocity fluctuation, and the inclusion of algebraic heat flux model slightly improves the accuracy of results.

• Journal of Animal Science and Technology
• /
• v.48 no.1
• /
• pp.29-38
• /
• 2006

The objective of this study was to estimate genetic variances of growth curve parameters in Hanwoo cows. The data used in this study were records from 1,083 Hanwoo cows raised at Hanwoo Experiment Station, National Livestock Research Institute(NLRI). First evaluation model(Model I) fit year-season of birth and age of dam as fixed effects and second model(Model II) added age at the final weight as a linear covariate to Model I. Heritability estimates of A, b and k from Gompertz model were 0.22, 0.11 and 0.07 using modelⅠ and 0.28, 0.11 and 0.12 using modelⅡ. Those from Von Bertalanffy model were 0.22, 0.11 and 0.07 using modelⅠ, 0.28, 0.11 and 0.12 using modelⅡ. Heritability estimates of A, b and k from Logistic model were 0.14, 0.07 and 0.05 using modelⅠ, 0.18, 0.07 and 0.12 using modelⅡ. Heritability estimates of A from Gompertz model were higher than those from Von Bertalanffy model or Logistic model in both model Ⅰand model Ⅱ. Heritability estimates of b from Logistic model were higher than those from Gompertz model or Von Bertalanffy model in both modelⅠand model Ⅱ. Heritability estimates of birth weight, weaning weight, 3 month weight, 6 month weight, 9 month weight, 12 month weight, 18 month weight, 24 month weight, 36 month weight were after linear age adjustment 0.27, 0.11, 0.19, 0.14, 0.16, 0.23, 0.52 and 0.32, respectively. Heritability estimates of birth weight, weaning weight, 3 month weight, 6 month weight, 9 month weight and 24 month weight fit by Gompertz model were larger than those estimated from linearly adjusted data. Heritability estimates of 12 month weight, 18 month weight and 36 month weight fit by Von Bertalanffy model were larger than those estimated from linearly adjusted data. In the multitrait analyses for parameters from Gompertz model, genetic and phenotypic correlations between A and k parameters were －0.47 and －0.67 using modelⅠand －0.56 and －0.63 using model Ⅱ. Those between the A and b parameters were 0.69 and 0.34 using modelⅠand 0.72 and 0.37 using model Ⅱ. Those between the b and k parameters were －0.26 and 0.01 using modelⅠand －0.30 and 0.01 using model Ⅱ. In the multitrait analyses for parameters from Von Bertalanffy model, genetic and phenotypic correlations between A and k parameters were －0.49 and －0.67 suing model Ⅰ and －0.57 and －0.70 using modelⅡ. Those between the A and b parameters were 0.61 and 0.33 using modelⅠ and 0.60 and 0.30 using model Ⅱ. Those between the b and k parameters were －0.20 and 0.02 using modelⅠ and 0.16 and 0.00 using modelⅡ. In the multitrait analyses for parameters from Logistic model, genetic and phenotypic correlations between A and k parameters were －0.43 and －0.67 using model Ⅰ and －0.50 and －0.63 using modelⅡ. Those between the A and b parameters were 0.47 and 0.22 using modelⅠ and 0.38 and 0.24 using modelⅡ. Those between the b and k parameters were －0.09 and 0.02 using model Ⅰ and －0.02 and 0.13 using model Ⅱ.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.23 no.5
• /
• pp.486-493
• /
• 2015

In this paper, a battery model for electric vehicle virtual platform was developed. A battery model consisted of a battery cell model and battery thermal management system. A battery cell model was developed based on Randles equivalent circuit model. Circuit parameters in the form of 3D map data was obtained by charge-discharge experiment of Li-Polymer battery in various temperature condition. The developed battery cell model was experimentally verified by comparing voltages. Thermal management system model was also developed using heat generator, heat transfer and convection model, and cooling fan. For verification of the developed battery model in vehicle level, the integrated battery model was applied in to EV(electric vehicle) virtual platform, and virtual driving simulation using UDDS velocity profile was conducted. The accuracy of the developed battery model has been verified by comparing the simulation results from EV platform with the experimental data.

• Journal of The Korean Association For Science Education
• /
• v.16 no.1
• /
• pp.13-34
• /
• 1996

The purpose of this study is to develop appropriate science teaching models which can be applied effectively to relevant situations. Five science teaching models; cognitive conflict teaching models, generative teaching model, learning cycle teaching model, hypothesis verification teaching model and discovery teaching model, were identified from the existing models. The teaching models were modified and in primary and secondary students using a nonequivalent pretest-posttest control group design. Major findings of this study were as follows: 1. For teaching science concepts, three teaching models were found more effective; cognitive conflict teaching model, generative teaching model and discovery teaching model. 2. For teaching inquiry skills, two teaching models were found more effective; learning cycle teaching model and hypothesis verification teaching model. 3. For teaching scientific attitudes, two teaching models were found more effective; learning cycle teaching models and discovery teaching model. Each teaching model requires specific learning environment. It is strongly suggested that teachers should select a suitable teaching model carefully after evaluating the learning environment including teacher and student variables, learning objectives and curricular materials.

• Proceedings of the KOSOMBE Conference
• /
• v.1997 no.05
• /
• pp.165-170
• /
• 1997

In this paper, we consider the aortic sinus baroreceptor, which is the most representative baroreceptors sensing the variance of pressure in the cardiovascular system(CVS), and propose heart activity control model to observe the effect of delay time in heart period and stroke volume under the regulation of baroreflex in arotic sinus. The proposed heart activity baroreflex regulation model contains CVS electric circuit sub-model, baroreflex regulation sub-model and time delay sub-model. In these models, applied electric circuit sub-model is researched by B.C.Choi and the baroreflex regulation sub-model transforms the input, the arotic pressure of CVS electric circuit sub-model, to outputs, heart period and stroke volume by mathematical nonlinear feedback. We constituted the time delay sub-model to observe sensitivity of heart activity baroreflex regulation model by using the variable value to represent the control signal transmission time from the output of baroreflex regulation model to efferent nerve through central nervous system. The simulation object of this model is to observe variability of the CVS by variable value in time delay sub-model. As simulation results, we observe three patterns of CVS variability by the time delay. First, if the time delay is over 2.5 sec, arotic pressure, stroke volume and heart rate is observed nonperiodically and irregularly. Second, if the time delay is from between 0.1 sec and 0.25 sec, the regular oscillation is observed. Finally, if time delay is under 0.1 sec, then heart rate and arotic pressure-heart rate trajectory is maintained in stable state.

• Journal of the Korean Data and Information Science Society
• /
• v.6 no.2
• /
• pp.29-39
• /
• 1995

A model used in the past may be altered at will in modeling for the future. For this situation, the multiprocess dynamic model provides a general framework. In this paper we consider the multiprocess discount normal model with parameters having a time dependent non-linear structure. This model has nice properties such as insensitivity to outliers and quick reaction to abrupt changes of pattern.