• Korea Journal of Hospital Management
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• v.23 no.1
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• pp.87-106
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• 2018

Objective: The objective of this study is to examine the association between process quality of inpatient care and risk-adjusted, thirty-day potentially preventable hospital readmission (PPR) rates. Data Sources/Study Setting: This was an observational cross-sectional study of nonfederal acute-care hospitals located in two states California and Florida, discharging Medicare patients with a principal discharge diagnosis of heart failure, acute myocardial infarction, or pneumonia January through December 31, 2007. Data were obtained from the Healthcare Cost and Utilization Project State Inpatient Database of the Agency for Healthcare Research and Quality, Centers for Medicare and Medicaid Services Hospital Compare database, and the American Hospital Association Annual Survey of Hospitals. Study Design: The dependent variable of this study is condition-specific, risk-adjusted, thirty-day potentially preventable hospital readmission (PPR). 3M's PPR software was utilized to determine whether a readmission was potentially preventable. The independent variable of this study is hospital performance for process quality of inpatient care, measured by hospital adherence to recommended processes of care. We used multivariate hierarchical logistic models, clustered by hospitals, to examine the relationship between condition-specific, risk-adjusted, thirty-day PPR rates and process quality of inpatient care, after taking clinical and socio-demographic characteristics of patients and structural and operational characteristics of hospitals into account. Findings: Better performance on the process quality metrics was associated with better patient outcome (i.e., low thirty-day PPR rates) in pneumonia, but not generally in two cardiovascular conditions (i.e., heart failure and acute myocardial infarction). Practical Implication: Adherence to the process quality metrics currently in use by CMS is associated with risk-adjusted, thirty-day PPR rates for patients with pneumonia, but not with cardiovascular conditions. More evidence-based process quality metrics closely linked to 30-day PPR rates, particularly for cardiovascular conditions, need to be developed to serve as a guideline to reduce potentially preventable readmissions.

• Information Systems Review
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• v.5 no.2
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• pp.53-69
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• 2003

This paper tried to find how the characteristics of purchasing items would have influence on the relational e-procurement. The characteristics of purchasing items include the importance and the complexity of purchasing items. In order to define these characteristics, this paper reviewed various literatures about purchasing strategies. The empirical analysis through the multi-nominal logistic regression shows that the importance of items has influence on relational e-procurement, while the complexity of purchasing process has little influence. And also, the relational e-procurement through EDI as a long term buying relationship is being converted toward the exchange through purchasing sites.

• Korean Journal of Computational Design and Engineering
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• v.19 no.2
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• pp.148-156
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• 2014

Generally, over 95% of manufacturing cost is determined in the design and manufacturing preparation step, especially a great part of productivity is determined in the manufacturing preparation step. In order to improve the manufacturing competitiveness, we have to verify the problems that can be occurred in the production step and remove the unnecessary factors in the manufacturing preparation step. Thus, manufacturing industries are adopting digital manufacturing system based on modeling & simulation. In this paper, we introduce e-FEED system (electronic based Front End Engineering and Design) that is the integrated design and analysis system for optimized manufacturing line development based on simulation automation and explain the work process (Design, Analysis and Optimization) about manufacturing line development using e-FEED system. Also, the effect is described through the real implementation cases.

• Nuclear Engineering and Technology
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• v.47 no.5
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• pp.624-632
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• 2015

A self-diagnostic monitoring system is a system that has the ability to measure various physical quantities such as temperature, pressure, or acceleration from sensors scattered over a mechanical system such as a power plant, in order to monitor its various states, and to make a decision about its health status. We have developed a self-diagnostic monitoring system for an air-operated valve system to be used in a nuclear power plant. In this study, we have tried to improve the self-diagnostic monitoring system to increase its reliability. We have implemented three different machine learning algorithms, i.e., logistic regression, an artificial neural network, and a support vector machine. After each algorithm performs the decision process independently, the decision-making module collects these individual decisions and makes a final decision using a majority vote scheme. With this, we performed some simulations and presented some of its results. The contribution of this study is that, by employing more robust and stable algorithms, each of the algorithms performs the recognition task more accurately. Moreover, by integrating these results and employing the majority vote scheme, we can make a definite decision, which makes the self-diagnostic monitoring system more reliable.

• Journal of Korean Public Health Nursing
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• v.30 no.1
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• pp.105-121
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• 2016

Purpose: This study examined the influencing factors from the Transtheoretical Model on the stage of change in the self-management behaviors, i.e. regular physical activity and diet, among community-residing adults with hypertension in a rural area. Methods: With a cross-sectional descriptive design, 134 adults who had registered and received a prescription for hypertension medication from a public health center in W city were recruited using convenient sampling. The instrument was an interviewer-administered questionnaire on the stage of change, process of change, self-efficacy, and decisional balance of physical activity and diet. The data were analyzed using descriptive statistics, 2-sample t-test, ${\chi}^2$ test, and logistic regression. Results: The results revealed significant differences in the process of change, self-efficacy, and decisional balance of physical activity and diet between those who were in the pre-execution stage (precontemplation, contemplation, preparation) and those who were in the execution stage (action and maintenance). Logistic regression showed that consciousness raising and self-efficacy were significant predictors of the execution stage in physical activity, and self-reevaluation, social liberation and self-efficacy were significant predictors in the diet. Conclusion: The relevant processes of change, differentiated according to the stage of change, along with self-efficacy, should be addressed to enhance the execution of self-management behaviors among hypertensive adults residing in the community.

• Earthquakes and Structures
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• v.15 no.3
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• pp.253-261
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• 2018

This article details a bridge-specific fragility method developed to enhance the seismic design and resilience of bridges. Current seismic design processes provide guidance for the design of a bridge that will not collapse during a design hazard event. However, they do not provide performance information of the bridge at different hazard levels or due to design changes. Therefore, there is a need for a supplement to this design process that will provide statistical information on the performance of a bridge, beyond traditional emphases on collapse prevention. This article proposes a bridge-specific parameterized fragility method to enable efficient estimation of various levels of damage probability for alternative bridge design parameters. A multi-parameter demand model is developed to incorporate bridge design details directly in the fragility estimation. Monte Carlo simulation and Logistic regression are used to determine the fragility of the bridge or bridge component. The resulting parameterized fragility model offers a basis for a bridge-specific design tool to explore the influence of design parameter variation on the expected performance of a bridge. When used as part of the design process, these tools can help to transform a prescriptive approach into a more performance-based approach, efficiently providing probabilistic performance information about a new bridge design. An example of the method and resulting fragility estimation is presented.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.25
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• pp.189-210
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• 2005

The application of 4PL could allow for the efficiency of many logistics operations to be greatly increased, for costs to be reduced, and for operations to become more responsive to consumer demand. It is also possible that higher services level and lower cost products could become available as a consequence. However, in order to implementing 4PL actually it is very important to be met to fundamental determinants of 4PL such as formation of logistics experts group, providing of total logistics service, capacity of IT, implementation of e-Business model, capacity of logistics consulting, higher logistics service level, logistics cost reduction, re-engineering of logistics process, focus of core competence etc.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.05a
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• pp.251-252
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• 2012

The exiting studies on the strength prediction by maturity method is mainly focused on concrete using OPC, meanwhile the study on the concrete mixing blast furnace slag powder (BFSP) is insufficient. The purpose of this study is to investigate the relationships between compressive strength and equivalent age by existing Maturity functions, i.e., Nurse-saul function Arrhenius function. This study also compared and examined the strength prediction of concrete mixing BGSP using ACI model and Logistic Curve prediction equation. Therefore, it is intended that fundamental data are presented for quality management and process management of concrete mixing BFSP.

• International Journal of Computer Science & Network Security
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• v.21 no.3
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• pp.245-256
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• 2021

Poor logistical infrastructure and agri-food supply chain management leads to significant food waste in logistic system. The concept of the sustainable value added agri-food chains requires defined approach to the analysis of the existing situation, possible improving strategies and also assessment of these changes impact on further development. The purpose of research is to provide scientific substantiation of theoretical and methodological principles and develop practical recommendations for the improvement of the agri-food logistics distribution system. A case study methodology is used in this article. The research framework is based on 4 steps: Value Stream Mapping (VSM), Gap and Process Analysis, Validation and Improvement Areas Definition and Imitation Modelling. This paper presents the appropriateness of LEAN logistics tools using, in particular, Value Stream Mapping (VSM) for minimizing logistic losses and Simulation Modeling of possible logistics distribution system improvement results. The algorithm of VSM analysis of the agri-food supply chain, which involves its optimization by implementing the principles of sustainable development at each stage, is proposed. The methodical approach to the analysis of possible ways for optimizing the operation of the logistics system of the agri-food distribution is developed. It involves the application of Value Stream Mapping, i.e. designing of stream maps of the creation of the added value in the agri-food supply chain for the current and future state based on the minimization of logistic losses. Simulation modeling of the investment project on time optimization in the agri-food supply chain and economic effect of proposed improvements in logistics product distribution system functioning at the level of the investigated agricultural enterprise has been determined. Improvement of logistics planning and coordination of operations in the supply chain and the innovative pre-cooling system proposed to be introduced have a 3-year payback period and almost 75-80% probability. Based on the conducted VSM analysis of losses in the agri-food supply chain, there have been determined the main points, where it is advisable to conduct optimization changes for the achievement of positive results and the significant economic effect from the proposed measures has been confirmed. In further studies, it is recommended to focus on identifying the synergistic effect of the agri-food supply chain optimization on the basis of sustainable development.

• The Journal of Korean Association of Computer Education
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• v.16 no.3
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• pp.49-60
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• 2013

This study is aimed to investigate that the blended e-learning could enhance the effectiveness compared to the conventional lecture performed in classroom. At first, both the CbE(Class based E-learning) and the EbC(E-learning based Class) mode have been generated in blended e-learning operation method following the process which analyze the various studies of interest. In addition, the instruction structures of Z Type(Zigzag model) and H-Type(Ladder model) were established as proposed model. The H-Blended e-learning based on CbE mode was introduced in the Excel Spread Sheet subject which held in A University to achieve the goal of this study. Learners were categorized and belonged to either the group 1(over 50% of attendance in cyber lecture) or the group 2(the rest of them). The data analysis was performed with $x^2$-test, t -test to compare the achievement of study between groups. The t -test result showed that the academic achievement in learning with group 1 was statistically significant than the learner in group 2. The effectiveness of the blended e-learning has been proved as the logistic regression analysis showed that the rate of the attendance in the cyber lecture functioned as indicator that enable to predict the acceptance.