• IE interfaces
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• v.20 no.1
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• pp.21-32
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• 2007

This paper deals with the simulation model for A-Mart logistic center design and operations. In developed simulation model, receiving docks, conveyor sorter, conveyor system, shipping docks, material handling devices and manual sorting stations are considered. Three types of cargo such as transfer center cargo, distribution center cargo and supermarket cargo are considered. The simulation model and process animation are developed using the simulation package ARENA. Among various design and operation alternatives consisting of the number of workers of receiving dock, allocation of receiving docks by cargo types, conveyor sorter velocity, the number of folk-lift, the number of manual sorting operators and overall layout, the best alternatives of each subsystem are selected by simulation analysis. The major performance measures such as sorter throughput, utilization of operators at each station, receiving docks utilization and folk-lift utilization are considered for the alternative evaluation.

• Journal of Nutrition and Health
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• v.28 no.5
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• pp.434-441
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• 1995

The model rats with postmenopausal osteoporosis were comparatively observed with regard to the effects of bovine ash and calcium phosphate on calcium metabolism. The modelling design involved the five week-old week-old female SD-strain rats ovariectomized and fed a low-Ca diet(20% casein, 0.06% Ca and 0.38% P) for three weeks. The rats were divided into five groups, one of which was fed the low-Ca diet(basal), and the rest of which were divided into five groups, one of which was fed the low-Ca diet(basal), and the rest of which were fed four kinds of Ca-supplemental diets(20% protein, 1.06% Ca and 0.8% P) for three weeks. The Ca-suplements diets contained two kinds of Ca sources, bovine bone ash(BBA) or calcium phosphate, tribasic [Ca3(PO4)2] and two kinds of protein sources, casein or isolated soy protein(ISP). The model rats of postmenopausal osteoporosis fed basal diet showed a significant decrease in Ca utilization in reference to serum Ca concentration, breaking force of bone, Ca and P contents of bone, and Ca absorption and retention. However, the supply of Ca for three weeks demonstrated the improved utilization of Ca. One step further, BBA was more effective than calcium phosphate in improving Ca utilization in ISP-fed groups. On the other hand, no significant difference was seen in casein-fed groups. It is to conclude that BBA could be more effective in accelerating Ca utilization under vulnerable dietary or physiological conditions such as vegetable protein intake and osteoprosis.

• Journal of Preventive Medicine and Public Health
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• v.27 no.1 s.45
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• pp.135-144
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• 1994

The purpose of this study compares determinants of eldery medical cost inflation with those of other age groups by analysing aggregated data with a deterministic model. The deterministic model of per capita medical cost inflation consists of increases in price, intensity of services, and medical utilization. We used a time series data($1985{\sim}1991$) from National Medical Insurance and analyzed by age groups. In total population, the average increase rates of inpatient and outpatient medical costs were respectively 9.5% and 8.8% during 6 years and the major cause of inflation was the increase in service intensity in both of inpatient and outpatient cases. But in the population of 65 years old and over, the average increase rates of inpatient and outpatient medical costs were respectively 13.8% and 14.8% and the major cause of inflation was the increase in per-capita medical utilization in both of inpatient and outpatient cases. Also, the increase in service intensity of 65 years old and over was the highest of other age groups. This pattern was similar during study periods. We concluded that the level of medical cost-inflation and the determinants in eldery was the highest-especially in per capita medical utilization, therfore, the inflation of medical costs in eldery will be higher than other age groups for the furture in Korea.

• Journal of Society of Preventive Korean Medicine
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• v.25 no.2
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• pp.85-98
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• 2021

Objectives : This study aimed to analyze characteristics of the Korean Medicine users aged 19-39 years, the determinants of Korean Medicine use and effects of Korean Medicine use experience on behavioral intentions among youths. Methods : We studied Korean Medicine Utilization and Herbal Medicine Consumption Survey(2017) data set by complex-sample survey data analysis. In order to derive the characteristics of younger users, Rao-scott χ² test and t-test were conducted. Through multiple logistic regression model adjusted by general characteristic variables, the determinants and behavioral intentions of the Korean Medicine utilization among youths were derived. Results : Fist of all, young users and non-users have significant differences in socio-demographic characteristics and perception on Korean Medicine. Among the general characteristic variables, region, age, marital status, occupation, chronic disease, and private health insurance plans had an effect on the Korean Medicine use in young people(Model II). And adjusted by general characteristic variables as control variables, awareness of Korean Medicine and perception of safety of herbal medicine were deduced as determinants of Korean Medicine use(Model III). Secondly, Korean Medicine use experience increased intentions to use and recommend Korean Medicine services(Model IV-1, 3). Conclusions : In order to increase the use of Korean Medicine among young people, Korean Medicine institutions should strive to increase users' satisfaction, and public health insurance coverage for Korean Medicine services needs to be expanded.

• Journal of Society of Preventive Korean Medicine
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• v.19 no.3
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• pp.57-66
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• 2015

Objective : Private health insurance coverage in Korean medicine has been reduced since October 2009 for preventing unnecessary utilization. The aim of this study is to identify how private health insurance coverage reduction affects on the Korean medicine utilization. Method : We analyzed the Korea Health Panel data from 2008 to 2012. Panel negative binominal regression model was used to analyze the relationship between private health insurance coverage reduction and utilization of outpatient service. Panel tobit regression analysis was used to identify the relationship between private health insurance coverage reduction and health expenditure of outpatient service. Results : Private health insurance coverage reduction significantly dropped both utilization and health expenditure of outpatient service by 9%, 9.22% respectively. In addition, therapeutic utilization significantly decreased up to 10%. Conclusion : Private health insurance coverage reduction seems to have an effect to reduce both utilization and the health expenditure of Korean medicine outpatient service. This effect was more noticeable in the therapeutic utilization. Thus, more elaborate policy will be needed to prevent unnecessary utilization of Korean medicine.

• East Asian Economic Review
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• v.26 no.3
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• pp.227-253
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• 2022

Despite the proliferation of free trade agreements (FTAs), many exporting firms are still confronted with several challenges in utilizing the FTA preferential tariffs. Based on the Technology-Organization-Environment (TOE) framework, this study empirically examines the factors affecting the utilization of FTA schemes by exporting firms. To clarify the key factors influencing FTA utilization, this study develops a conceptual model from the perspective of the adoption of information technology innovations. Eight factors derived from the TOE framework are proposed to explore the determinants of FTA utilization in export. Partial least squares structural equation modeling is employed to analyze the data collected from 162 exporting small- and medium-sized enterprises in the South Korean textile industry. The findings reveal that compatibility and trading partner influence are positively associated with FTA utilization, while complexity is negatively related. Factors of organizational context do not show any relationship with FTA utilization. This study is the first to theoretically analyze and empirically test the determinants of FTA utilization from the perspective of technological innovation adoptions. By examining the relative importance of TOE factors in the utilization of FTA schemes, this study expects to advance a holistic understanding on the perceived factors that could potentially affect the utilization of FTA schemes.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.31-38
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• 2023

In this paper, a basic machine learning model learning and utilization education curriculum for non-majors is proposed, and an education method using Orange machine learning model learning and analysis tools is proposed. Orange is an open-source machine learning and data visualization tool that can create machine learning models by learning data using visual widgets without complex programming. Orange is a platform that is widely used by non-major undergraduates to expert groups. In this paper, a basic machine learning model learning and utilization education curriculum and weekly practice contents for one semester are proposed. In addition, in order to demonstrate the reality of practice contents for machine learning model learning and utilization, we used the Orange tool to learn machine learning models from categorical data samples and numerical data samples, and utilized the models. Thus, use cases for predicting the outcome of the population were proposed. Finally, the educational satisfaction of this curriculum is surveyed and analyzed for non-majors.

• Health Policy and Management
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• v.4 no.2
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• pp.58-76
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• 1994

In order to study factors affecting the use of the ambulatory physician services. Andersen's model for health utilization was modified by adding the health behavior component and examined with three different approaches. Three different approaches were the multiople regression model, logistic regression model, and LISREL model. For multiple regression, dependent variable was reported illness-related visits to a physician during past one year and independent variables are variaous variables measuring predisposing factor, enabling factor, need factor and health behavior. For the logistic regression, dependent variable was visit or no-visit to a physician during past one year and independent variables were same as the multiple regression analysis. For the LISREL, five endogenous variables of health utiliztion, predisposing factor, enabling factor, need factor, and health behavior and 20 exogeneous variables which measures five endogenous variables were used. According to the multiple regression analysis, chronic illness, health status, perceived health status of the need factor; residence, sex, age, marital status, education of the predisposing factor ; health insurance, usual source for medical care of enabling factor were the siginificant exploratory variables for the health utilization. Out of the logistic regression analysis, health status, chronic illness, residence, marital status, education, drinking, use of health aid were found to be significant exploratory variables. From LISREL, need factor affect utilization most following by predisposing factor, enabling factor and health behavior. For LISREL model, age, education, and residence for predisposing factor; health status, chronic illess, and perceived health status for need factor; medical insurance for enabling factor; and doing any kind of health behavior for the health behavior were found as the significant observed variables for each theoretical variables.

• Communications for Statistical Applications and Methods
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• v.25 no.2
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• pp.173-184
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• 2018

In medical or public health research, it is common to encounter clustered or longitudinal count data that exhibit excess zeros. For example, health care utilization data often have a multi-modal distribution with excess zeroes as well as a multilevel structure where patients are nested within physicians and hospitals. To analyze this type of data, zero-inflated count models with mixed effects have been developed where a count response variable is assumed to be distributed as a mixture of a Poisson or negative binomial and a distribution with a point mass of zeros that include random effects. However, no study has considered a situation where data are also censored due to the finite nature of the observation period or follow-up. In this paper, we present a weighted version of zero-inflated Poisson model with random effects accounting for variable individual follow-up times. We suggested two different types of weight function. The performance of the proposed model is evaluated and compared to a standard zero-inflated mixed model through simulation studies. This approach is then applied to Medicaid data analysis.

• The Korean Journal of Health Service Management
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• v.11 no.3
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• pp.51-64
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• 2017

Objectives : This study examined the effect of private health insurance on medical care utilization by subscription type. Methods : The data used were the six waves of the Korea Health Panel (2009-2014), and 16,187 persons were the subjects of the analysis. We performed a panel regression with a fixed effects model. Results : Indemnity private health insurance was positively related to the number of physician visits, number of admissions, and total length of stays. However, fixed-benefit private health insurance was not related to medical care utilization. Conclusions : The result of this study, which shows the difference by subscription type in the effect of private health insurance on medical care utilization, suggests that continuous monitoring of indemnity private health insurance is needed in the future.