• Health Policy and Management
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• v.27 no.2
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• pp.128-138
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• 2017

Background: The purpose of this study is to analyze the effects of differential coinsurance policy on prescription drug coverage of outpatients by types of medical institutions. Methods: In this study, we used a sample cohort database of the National Health Insurance Service and frequency analysis and marginal logistic regression model using generalized estimating equation were used for statistical analysis. Results: The summary on the major research is followed. First, about 16% of patients who used only tertiary or general hospital due to 52 ambulatory care sensitive conditions before policy implementation moved to hospitals and clinics. However, about 57% of them still use tertiary or general hospital. Second, the factors influencing the utilization of hospitals and clinics after the implementation of the policy were gender, age, and income level. As a result, the policy is effective to reduce the medical use of outpatient mental patients in tertiary or general hospital, but the effect is not significant. Conclusion: Therefore, in order to achieve the purpose of the policy for establishing the health care delivery system, it is necessary to adjust the co-payment so as to feel the burden on the co-payment when the outpatient for 52 ambulatory care sensitive conditions is used at the tertiary or general hospital.

• Journal of the Korean Geosynthetics Society
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• v.18 no.4
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• pp.39-52
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• 2019

In this paper the development and implementation of an artificial intelligence (AI)-based Tunnelling Impact prediction and assessment program (SKKU-iTunnel) is presented. Program predicts tunnelling induced surface settlement and groundwater drawdown by utilizing well trained ANNs and uses these predicted values to perform the damage assessment likely to occur in nearby structures and pipelines/utilities for a given tunnel problem. Generalised artificial neural networks (ANNs) were trained, to predict the induced parameters, through databases generated by combining real field data and numerical analysis for cases that represented real field conditions. It is shown that program equipped with carefully trained ANN can predict tunnel impact assessments and perform damage assessments quiet efficiently and comparable accuracy to that of numerical analysis. This paper describes the idea and implementation details of the SKKU-iTunnel with an example for demonstration.

• International Journal of Highway Engineering
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• v.17 no.4
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• pp.25-31
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• 2015

PURPOSES: Implementation and verification of the simple linear cohesive viscoelastic contact model that can be used to simulate dynamic behavior of sticky aggregates. METHODS: The differential equations were derived and the initial conditions were determined to simulate a free falling ball with a sticky surface from a ground. To describe this behavior, a combination of linear contact model and a cohesive contact model was used. The general solution for the differential equation was used to verify the implemented linear cohesive viscoelastic API model in the DEM. Sensitivity analysis was also performed using the derived analytical solutions for several combinations of damping coefficients and cohesive coefficients. RESULTS : The numerical solution obtained using the DEM showed good agreement with the analytical solution for two extreme conditions. It was observed that the linear cohesive model can be successfully implemented with a linear spring in the DEM API for dynamic analysis of the aggregates. CONCLUSIONS: It can be concluded that the derived closed form solutions are applicable for the analysis of the rebounding behavior of sticky particles, and for verification of the implemented API model in the DEM. The assumption of underdamped condition for the viscous behavior of the particles seems to be reasonable. Several factors have to be additionally identified in order to develop an enhanced contact model for an asphalt mixture.

• Journal of Information Technology Applications and Management
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• v.10 no.3
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• pp.121-142
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• 2003

Most of companies related to the area of B2B electronic commerce are making their efforts to innovate their existing business process into new designed process based on the concept of virtual enterprise. Virtual enterprise can take on many forms and definitions. Nevertheless, the rationale for this business model is clear cooperate to compete, the virtual organization advocates collaboration, partnerships, alliance and similar ideas. This studyintends to suggest an empirical clue to test several hypotheses related to the influence of environmental. organizational, and technological factor to the successful implementation of virtual enterprise in automobile industry. This research surveyed 91 corporations in Korean automobile part industry. Among those samples 86 data of corporate general managers turned out to be statistically valid. This study performed the factor analysis, Cronbach-alpha test. Pearson correlation analysis for testing the validity and the reliability of this research. The results of factor analysis and reliability test indicate that thirty issues to be surveyed are to be grouped into nine factors. The result of multiple regression shows that the influencing factors of eight independent variables on a dependent variable are cooperation between partners, information intensity, IT compatibility, IS maturity. The partners in the strategic alliance will have to trust each other in carrying out their designated roles and responsibilities. and supplying the correct information critical for creating value in virtual business environment.

• Journal of Korean Society for Quality Management
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• v.46 no.3
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• pp.539-550
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• 2018

Purpose: The purpose of this study was to find meaningful patient groups of disease using foreign patients data and analyze implemented test of the patient groups. Methods: The data was collected by foreign patients' EMR data of K university hospital. The author proposed tree-form patients' characteristic diagram through statistical methods that association rule, proportion test, clustering using prescription information and questionnaire information. Results: This study's analysis process was applied high blood data and diabetes data. Analysis showed other characteristic of meaningful patient groups in high blood and diabetes. In high blood, test implementation rate of patient group showed the differences. And in diabetes, test implementation rate of patient group and implemented test list showed differences. Conclusion: The result of this study can play a role as basic data that can be clinical testing standard in preventive aspect. Eventually, 5 dimensions of SERVQUAL will be improved by this study's process.

• Informatization Policy
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• v.27 no.2
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• pp.20-39
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• 2020

This paper introduces the Cryptocurrency Market Potential Index (CMPI) in order to measure the potential of the blockchain-backed cryptocurrency. Adopting the Distributed Ledger Technology (DLT) system as a conceptual framework, the whole process from development to implementation and adoption of blockchain-backed cryptocurrency are examined. This paper selects 30 variables and employs factor analysis for multivariate analysis to produce the CMPI for a total of 213 countries. The results show that although cryptocurrency is decentralized, its development and usage might still be very centralized in Europe, North America, hotspots in the Asia-Pacific, Middle East, and CIS regions. This result also highlights how important development and implementation are before adoption so that consequent financial transactions can take place.

• Environmental and Resource Economics Review
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• v.17 no.4
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• pp.691-717
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• 2008

The Kyoto Mechanisms allows a supplementary means for compliance, CDM(Clean Development Mechanism) and JI(Joint Implementation) projects. The investment in CDM projects is increasing rapidly as the first implementation period began in 2008. This paper seeks to determine factors affecting the price of primary CER using UNFCCC CDM Project Development Document(PDD) data. This study employs the Cluster analysis and the GLS(Generalized Least Squares) method.

• The KIPS Transactions:PartD
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• v.18D no.1
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• pp.57-66
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• 2011

Recently, the necessity of new methods of spatial data integration and analysis in CRM has been increased since it is acknowledged that about eighty percent of all data stored in corporate databases has a spatial component. But conventional CRM systems are either incapable of managing spatial data or are not user-friendly when doing so. This paper has designed and implemented spatially-enabled integration management system that can manage consistently both enterprise and spatial data through a legacy CRM system and object-oriented database and additionally support spatial analysis and map visualization for a gCRM. Through implementation, it is demonstrated that the proposed system can facilitate effectively spatial data management and analysis in a legacy CRM system.

• ETRI Journal
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• v.34 no.1
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• pp.76-86
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• 2012

The block cipher ARIA has been threatened by side-channel analysis, and much research on countermeasures of this attack has also been produced. However, studies on countermeasures of ARIA are focused on software implementation, and there are no reports about hardware designs and their performance evaluation. Therefore, this article presents an advanced masking algorithm which is strong against second-order differential power analysis (SODPA) and implements a secure ARIA hardware. As there is no comparable report, the proposed masking algorithm used in our hardware module is evaluated using a comparison result of software implementations. Furthermore, we implement the proposed algorithm in three types of hardware architectures and compare them. The smallest module is 10,740 gates in size and consumes an average of 47.47 ${\mu}W$ in power consumption. Finally, we make ASIC chips with the proposed design, and then perform security verification. As a result, the proposed module is small, energy efficient, and secure against SODPA.

• Korea Journal of Hospital Management
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• v.23 no.2
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• pp.18-27
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• 2018

Purposes: This study aims to investigate the policy effect of mandatory application of DRG for 7 disease groups in general and tertiary hospitals. Methodology: As DRG was fully implemented in July 2013, this study compares two periods before and after the change(from July 2012 to June 2013, and from July 2013 to June 2014). The benefit claim data of the National Health Insurance Service was used for the comparison. Target patients were those who visited general or tertiary hospitals between July 2012 to June 2014. For pharmaceutical consumption, Interrupted Time Series (ITS) analysis was used to see the effect of DRG mandatory application. Findings: The number of drugs prescribed per patient and pharmaceutical expenditure both showed significant reduction compared to before the DRG implementation. Practical Implications: This study used 2 sets of 1 year period data from before and after the full implementation of DRG to analyze pharmaceutical consumption. When the comparison data accumulates further, it would be possible to conduct more diverse analysis to assess policy effect and to provide way forward for the future.