• Journal of Digital Convergence
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• v.16 no.9
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• pp.279-291
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• 2018

This study is designed to demonstrate risk factors of unmet medical care for people with cerebrovascular disease. To do this, statistical analysis was performed by using hierarchical logistic regression analysis with SPSS/WIN24.0 program using Korean Medical Panel data in 2014. In the final model of the hierarchical logistic regression analysis, which is based on Anderson's Model, adjusted for the factors of the predisposing and enabling factors, the explanatory variables affecting the unmet medical development are gender, economic activity, income level, the experience of lying in a sickbed, restriction on activity, subjective health condition, and the number of chronic diseases. Based on the results of this study, the practical and policy implications for the effective management and treatment of cerebrovascular disease should be included in the countermeasures for cerebrovascular disease, a strategy to reduce the unmet medical incidence of cerebrovascular disease, in order to meet the medical needs, the necessity of comprehensive measures considering various dimensions of variables and the influential variables of unmet medical emergence have been suggested for the necessity of making a detailed service manual that can improve accessibility to medical services.

• Korean Journal of Construction Engineering and Management
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• v.17 no.3
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• pp.71-80
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• 2016

PERT(Project Evaluation and Review Technique) is typical method in order to probabilistically establish the schedule plan for large scale complex project or mega project. PERT technique is impossible to estimate relationship of each activity probabilistically when there are overlapping relationships because it is limited to Finish-to-Start(FS) relationship. In order to overcome this kind of limitation of PERT technique, PLET(Probabilistic Linkage Evaluation Technique) has been suggested to probabilistically estimate project duration for various overlapping relationships for each activity. However, estimating project duration by PLET technique only considers uncertainty of relationship between activities and not activity time, thus it is not the perfect duration estimating method. The main objective of this research is to propose the integration model of PERT and PLET and verify its probabilistic validity. By verifying application of time calculation method of integration model in practical case, this research will suggest probabilistic project duration estimating method in schedule plan of high-risk construction industry.