• Journal of the Korea Society for Simulation
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• v.17 no.2
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• pp.75-82
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• 2008

The times of service commencement and service completion had been used for inferring the queueing systems. However, the service commencement times are difficult to measure because of unobservable nature in queueing systems. In this paper, for inferring queueing systems, the service commencement times are replaced for arrival times which can be easily observed. Determining the service commencement time is very important in our methods. The methods for first come first served(FCFS), last come first served(LCFS) queueing discipline are already developed in our previous work. In this paper, we extend to random selection for service(RSS) queueing discipline. The performance measures we used are mean queueing time and mean service time, the variances of two. The simulation results verify our proposed methods to infer queueing systems under RSS discipline.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1087-1097
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• 2017

This study aims to find the best model to fit the number of insurance solicitor's turnovers of life insurance companies using count data regression models such as poisson regression, negative binomial regression, zero-inflated poisson regression, or zero-inflated negative binomial regression. Out of the four models, zero-inflated negative binomial model has been selected based on AIC and SBC criteria, which is due to over-dispersion and high proportion of zero-counts. The significant factors to affect insurance solicitor's turnover found to be a work period in current company, a total work period as financial planner, an affiliated corporation, and channel management satisfaction. We also have found that as the job satisfaction or the channel management satisfaction gets lower as channel management satisfaction, the number of insurance solicitor's turnovers increases. In addition, the total work period as financial planner has positive relationship with the number of insurance solicitor's turnovers, but the work period in current company has negative relationship with it.

• Journal of Korean Society of Transportation
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• v.21 no.3
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• pp.15-22
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• 2003

In general, the linear regression model has been used to estimate trip generation in the travel demand forecasting procedure. However, the model suffers from several methodological limitations. First, trips as a dependent variable with non-negative integer show discrete distribution but the model assumes that the dependent variable is continuously distributed between -$\infty$ and +$\infty$. Second, the model may produce negative estimates. Third, even if estimated trips are within the valid range, the model offers only forecasted trips without discrete probability distribution of them. To overcome these limitations, a poisson model with a assumption of equidispersion has frequently been used to analyze count data such as trip frequencies. However, if the variance of data is greater than the mean. the poisson model tends to underestimate errors, resulting in unreliable estimates. Using overdispersion test, this study proved that the poisson model is not appropriate and by using Vuong test, zero inflated negative binomial model is optimal. Model reliability was checked by likelihood test and the accuracy of model by Theil inequality coefficient as well. Finally, marginal effect of the change of socio-demographic characteristics of households on trips was analyzed.

• Journal of Korean Society for Quality Management
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• v.13 no.1
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• pp.77-83
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• 1985

This paper deals with a normality test to determine whether the data are sampled from normal population or not. In this paper the property that the mean and variance are independently distributed only for the normal distribution is used as a basis for developing a new test using the simple regression analysis. Considering the redan and variance of a random sample as independent and dependent variables, if it has not the regression relationship we conclude that the data were sampled from the normal distribution. The Monte-Carlo power study shows that the new test using the simple regression analysis has good power property relative to 6 well-known test methods for 11 distributions.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.5C
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• pp.413-421
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• 2008

The paper derives asymptotic formulas for the MSE distortion and the signal-to-noise ratio of a mismatched fixed-rate minimum MSE Laplacian quantizer. These closed-form formulas are expressed in terms of the number N of quantization points, the mean displacement $\mu$, and the ratio $\rho$ of the standard deviation of the source to that for which the quantizer is optimally designed. Numerical results show that the principal formula is accurate in that, for rate R=$log_2N{\geq}6$, it predicts signal-to-noise ratios within 1% of the true values for a wide range of $\mu$, and $\rho$. The new findings herein include the fact that, for heavy variance mismatch of ${\rho}>3/2$, the signal-to-noise ratio increases at the rate of $9/\rho$ dB/bit, which is slower than the usual 6 dB/bit, and the fact that an optimal uniform quantizer, though optimally designed, is slightly more than critically mismatched to the source. It is also found that signal-to-noise ratio loss due to $\mu$ is moderate. The derived formulas can be useful in quantization of speech or music signals, which are modeled well as Laplacian sources and have changing short-term variances.

• The Journal of Korean Academy of Sensory Integration
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• v.17 no.1
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• pp.19-29
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• 2019

Objective : The aim of this study was to verify validity of the Activity Participation Assessment for school-age children. Methods : A questionnaire consisting of 30 items from the APA, 75 items from the PACS, and 55 items from the CAPE was administered to elementary school students. A total of 207 questionnaires were analyzed. Confirmatory factor analysis was performed to confirm the construct validity of the APA. Convergence validity and discriminant validity were verified with the average variance extracted (AVE) and the square of the correlation coefficient. The discriminant validity was the Pearson correlation coefficient of the APA, PACS, and CAPE. Results : The results of the analysis were as follows: 1) For construct validity, the goodness of fit of the modified hierarchical second-order factor model was found to be appropriate (p < .001), 2) For convergent validity, the AVE was higher than .50 for all latent variables, 3) For discriminant validity, the AVE of the latent variable was greater than the square of the correlation coefficient (0.239), 4) For concurrent validity, the correlation between the total sum of the APA and PACS scores showed a positive correlation in all domains, and the correlation coefficient ranged from .303 to .647 at a statistically significant level (p < .01), 5) The correlation coefficient between the total sum of the APA and CAPE scores was .490 for recreational activities, .329 for physical activities, .571 for social activities, .401 for skill-based activities, and .390 for self-improvement activities. All domains showed a positive correlation, and were statistically significant (p < .01). Conclusion : APA can be used as a valid assessment tool to measure the participation of school aged children.

• Journal of Korean Library and Information Science Society
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• v.45 no.3
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• pp.271-295
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• 2014

The purpose of this study is to analyze factors that influence adolescents' reading effectiveness and to structuralize the relationship between those factors. In consequence, reading attitude is the greatest factor that influences reading effectiveness, followed by library positivity and the reading role model. According to ANOVA, there is a difference in average between personality types, but PLS(Partial Least Squares) shows that personality types do not affect reading attitudes and reading effectiveness.

• Proceedings of the Korean Statistical Society Conference
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• 2001.11a
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• pp.115-120
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• 2001

라틴 하이퍼큐브 실험계획은 전산실험을 위하여 Mckay, Beckman과 Conover(1979)에 의해 고안된 방법으로 실험을 한번 시행하는데 많은 시간과 비용이 들거나 인자가 많은 실험에 효율적으로 사용할 수 있다. 하지만 이 실험계획 역시 실험영역 전체에서 골고루 배치되지 않을 가능성이 있으므로 이를 보완하려는 시도가 이루어져 왔으며, 여기서는 good lattice points(glp)와 계통추출을 응용하여 격자기반(lattice-based) Lhd의 두 가지 방법을 제안하였다. 모의실험 결과 glp 실험계획을 응용한 "방법 1"은 모형을 가정한 엔트로피에 기초한 최적 기준으로 검토한 경우 우수하였다. "방법 2"는 표본조사에 널리 쓰이는 계통추출을 응용하였으며 입력변수가 각기 다른 9개의 실험함수에 관하여 표본 평균의 추정치와 분산, MSE를 비교한 결과, 다른 실험계획들보다 우수하였다. 이 결과는 실험점이 실험영역 전체에서 골고루 퍼져서 나타난 것으로 보이며, 향후 전산실험계획에서의 응용을 기대할 수 있다.

• Korean Journal of Social Welfare
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• v.68 no.3
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• pp.29-50
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• 2016

This study examined the determinants of housing affordability using the 2014 fact-finding survey of housing. This study identified the effects of characters of districts as well as the effects of characters of family and housing, taking advantage of HGLM(Hierarchical General Linear Model). The results of this study showed that male householder, higher education level, the monthly housing, higher satisfaction of environment of housing are the factors that increased the odds of living at unaffordable housing, but higher income, public transfer recipient, living at sub-standard housing, the Jensei housing are the factors that decreased the odds of living at unaffordable housing. And the higher housing price, the higher rent of the districts increased significantly the odds of living at unaffordable housing, but the higher rate of public housing of the districts decreased the odds of living at unaffordable housing. This study provides the basis that the price of housing and rent should be controled and the policy of public housing should be expanded for housing welfare.

• Journal of the Korean Data and Information Science Society
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• v.22 no.2
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• pp.287-296
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• 2011

Thirty six female students participated in the experiment of the fat mass weight loss. they kept diary for foods they ate every day, took a picture of the foods, transmitted the picture to the experimenter by the camera phone, and consulted him about fat mass loss once a week for 8 weeks period. Fat mass weight and its related factors of the students had been measured repeatedly every week during 8 weeks, The repeated measurement data were used for applying various random coefficient models. And hence optimal random coefficient model was selected. From the optimal model, the baseline, body mass index, diastolic blood pressure, total cholesterol and time of the fixed factors were very significant. The fixed quadratic time effect existed. The variance components corresponding to the subject effect, linear time effect of the random coefficients were all positive. Thus random coefficients up to the linear terms were considered as the optimal model. The treatment effect reduced the weight loss to an average of 2.1kg at the end of the period.