• Journal of the Korean Statistical Society
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• v.30 no.4
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• pp.613-635
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• 2001

This paper proposes a skewed multivariate probit model for analyzing a correlated binary response data with covariates. The proposed model is formulated by introducing an asymmetric link based upon a skewed multivariate normal distribution. The model connected to the asymmetric multivariate link, allows for flexible modeling of the correlation structure among binary responses and straightforward interpretation of the parameters. However, complex likelihood function of the model prevents us from fitting and analyzing the model analytically. Simulation-based Bayesian inference methodologies are provided to overcome the problem. We examine the suggested methods through two data sets in order to demonstrate their performances.

• Transactions of the Korean Society of Automotive Engineers
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• v.12 no.4
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• pp.110-118
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• 2004

In this paper, a blackbox approach is carried out to model the nonlinear dynamic bushing model. One-axis durability test is performed to describe the mechanical behavior of typical vehicle elastomeric components. The results of the tests are used to develop an empirical bushing model with an artificial neural network. The back propagation algorithm is used to obtain the weighting factor of the neural network. Since the output for a dynamic system depends on the histories of inputs and outputs, Narendra's algorithm of ‘NARMAX’ form is employed in the neural network bushing module. A numerical example is carried out to verify the developed bushing model.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.12
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• pp.159-167
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• 2003

In this paper, a two-dimensional multibody DADS model of a moving walk is developed to improve the ride quality of a moving walk system. The proposed DADS model is able to estimate the longitudinal acceleration of moving walk system, which is the more sensitive and important than other accelerations. To show the validity of the developed model, the longitudinal accelerations of pallet obtained from the computer simulations are compared to the experimental data in frequency domain. Then, the factorial design technique is applied to determine the main design factor and to improve the ride quality. The change of the spring compression in the lower part of the tension generating system improved the ride quality of the moving walk system.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.830-832
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• 2014

In this study, friction stick-slip vibration're interpretation of the phenomenon, we used a statistical model of friction. In a previous study using a definite friction factor, but to a dynamic simulation using a constantly changing during the integration time by a Monte Carlo simulation method, not the average coefficient of friction and the dynamic friction coefficient and a constant value in this study.

• Journal of Biosystems Engineering
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• v.24 no.1
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• pp.31-40
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• 1999

The objective of this study were to develop a cooling simulation model for fixed-bed of rough rice and to analyze the factors affecting cooling time of rough rice. A computer simulation model based on equilibrium conditions between grain and air was developed to predict temperature and moisture content changes during cooling of rough rice. the result of t-test showed that there were no significant differences between predicted and measured temperature changes on significance model agreed well with measured values. This cooling simulation model was applied to analyze the effect of some factors, such as air flow rate, cooling air temperature and humidity, initial grain temperature and moisture content, and bed depth, on cooling time of rough rice. Cooling rate increased with increase of air flow rate and bed depth whereas it decreased with increase of cooling air temperature and humidity and initial grain temperature. Among these factors, the most important factor was air flow rate. Specific air flow rate of 0.35㎥/min㎥ was required for cooling rough rice in 24 hours.

• Culinary science and hospitality research
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• v.13 no.2
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• pp.163-173
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• 2007

The purpose of this study is to measure the effects of behavioral intention. A total of 273 questionnaires were completed. The equation model was used to measure the causal effect. The results demonstrated that the confirmatory factor analysis model provided an excellent model fit. The comprehensive model yielded a significantly better fit to the data and accounted for a greater share of the variance in behavioral intentions than the five competing models. The effects of satisfaction, perceived value and service quality on behavioral intention were statistically significant. As expected, service quality and value had significant effects on satisfaction. Service quality and perceived sacrifice had significant effects on value. Moreover, service quality and value perceptions had an indirect influence on behavioral intentions. The overall findings offer strong empirical support for the intuitive notion that improving service quality can increase favorable behavioral intentions and decrease unfavorable intentions.

• Journal of Information Technology Applications and Management
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• v.10 no.1
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• pp.71-89
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• 2003

This paper firstly introduces a classification model for designing the architecture of backup centers in terms of business continuity management. We propose that the replication solution, the level of disaster recovery, and the outsourcing style as three important factors that help explain the architecture of backup centers. We provide the details of each factor of the model and apply them to the real world cases of backup centers in Korea. We conclude that the model is well fitted to many cases of currently available backup centers and can provide backup center architects with a well classified architecture model with specific guidelines.

• Journal of the Korea Society of Computer and Information
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• v.22 no.10
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• pp.9-17
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• 2017

The student dropout prediction is an indispensable for many intelligent systems to measure the educational system and success rate of all university. Therefore, in this paper, we propose an intelligent dropout prediction system that minimizes the situation by adopting the proactive process through an effective model that predicts the students who are at risk of dropout. In this paper, the main data sets for students dropout predictions was used as questionnaires and university information. The questionnaire was constructed based on theoretical and empirical grounds about factor affecting student's performance and causes of dropout. University Information included student grade, interviews, attendance in university life. Through these data sets, the proposed dropout prediction model techniques was classified into the risk group and the normal group using statistical methods and Naive Bays algorithm. And the intelligence dropout prediction system was constructed by applying the proposed dropout prediction model. We expect the proposed study would be used effectively to reduce the students dropout in university.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.1
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• pp.143-150
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• 2006

Box-Cox model and T-factor method have been widely used to measure economic depreciations for industrial property. The Box-Cox model which combines economic efficiency with depreciation pattern is here extended to the reliability function. To do so a Rayleigh distribution which has been used to estimate the reliability of current assets was chosen as an efficiency curve of marginal productivity. Such an approach provides the possibility to classify the efficiency curves into four categories. It is also possible to analyze the types of depreciation curves. Therefore, the power family of a non-linear Box-Cox model could be set at certain constant values, then the model can be transformed into a linear model to estimate the economic depreciation rates by utilizing the reliability function. Estimating the resultant linear regression equation requires minimal number of observations, while at the same time facilitating the test of hypothesis on depreciation rates.

• 연구논문집
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• s.30
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• pp.67-77
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• 2000

This study was performed to investigate the characteristics and performance of model Decanter for separating swine wastewater to solid and liquid which is slurry state with 12.6% TS. Swine wastewater of the slurry tank was pumped into model Decanter which capacity was $2m^3$/hr in 10% TS Slurry inside of bowl was separated to solid-liquid by centrifugal acceleration. Sampling was done in the section of slurry feed pipe, supernatant outflow pipe, cake discharge pipe. After solid-liquid separation TS, $COD_cr$ and slurry volume reduction effect represented 38%, 40%, 19.6% respectively. Relation factor of model Decanter operation slurry concentration, optimum retention time of slurry, overflow velocity of supernatant, supernatant concentration, sludge removal rate etc. Optimal operation conditions can be set and evaluated efficiency based on the experimental results in the case of Decanter adopted for solid-liquid separation in highly concentrated swine wastewater.