• Nuclear Engineering and Technology
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• v.54 no.1
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• pp.414-422
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• 2022

Presented in this paper is a methodology for combining a Bayesian statistical approach with Data Quality Objectives (a structured decision-making method) to provide increased levels of confidence in analytical data when approaching a waste boundary. Development of sampling and analysis plans for the characterisation of radioactive waste often use a simple, one pass statistical approach as underpinning for the sampling schedule. Using a Bayesian statistical approach introduces the concept of Prior information giving an adaptive sample strategy based on previous knowledge. This aligns more closely with the iterative approach demanded of the most commonly used structured decision-making tool in this area (Data Quality Objectives) and the potential to provide a more fully underpinned justification than the more traditional statistical approach. The approach described has been developed in a UK regulatory context but is translated to a waste stream from the Fukushima Daiichi Nuclear Power Station to demonstrate how the methodology can be applied in this context to support decision making regarding the ultimate disposal option for radioactive waste in a more global context.

• Journal of Korean Society for Quality Management
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• v.23 no.4
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• pp.100-112
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• 1995

Data on nearly one hundred thousands of Korean quality circles, registered with KSA(Korean standard association), are classified by regional groups, size, and industry. The classified data are analyzed in order to investigate the actual state of quality circles. Some international comparisons such as managerial objectives for introducing quality circles are also included.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.10
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• pp.5013-5034
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• 2019

In the Peer-to-Peer (P2P) streaming systems, peers randomly form a network overlay to share video resources with a data scheduling scheme. A data scheduling scheme can have a great impact on system performance, which should achieve two optimal objectives at the same time ideally. The two optimization objectives are to improve the perceived video quality and maximize the network throughput, respectively. Maximizing network throughput means improving the utilization of peer's upload bandwidth. However, maximizing network throughput will result in a reduction in the perceived video quality, and vice versa. Therefore, to achieve the above two objects simultaneously, we proposed a new data scheduling scheme based on multi-objective particle swarm optimization data scheduling scheme, called MOPSO-DS scheme. To design the MOPSO-DS scheme, we first formulated the data scheduling optimization problem as a multi-objective optimization problem. Then, a multi-objective particle swarm optimization algorithm is proposed by encoding the neighbors of peers as the position vector of the particles. Through extensive simulations, we demonstrated the MOPSO-DS scheme could improve the system performance effectively.

• Journal of Korean Society for Atmospheric Environment
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• v.23 no.5
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• pp.526-538
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• 2007

Since air quality monitoring data sets are important base for developing of air quality management strategies including policy making and policy performance assessment, the environmental protection authorities need to organize and operate monitoring network properly. Air quality monitoring network of Busan, consisting of 18 stations, was allocated under unscientific and irrational principles. Thus the current state of air quality monitoring networks was reassessed the effect and appropriateness of monitoring objectives such as population protection and sources surveillance. In the process of the reassessment, a GIS-based decision support system was constructed and used to simulate air quality over complex terrain and to conduct optimization analysis for air quality monitoring network with multi-objective. The maximization of protection capability for population appears to be the most effective and principal objective among various objectives. The relocation of current monitoring stations through optimization analysis of multi-objective appears to be better than the network building for maximization of population protection capability. The decision support system developed in this study on the basis of GIS-based database appear to be useful for the environmental protection authorities to plan and manage air quality monitoring network over complex terrain.

• Journal of the Korea Institute of Military Science and Technology
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• v.25 no.1
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• pp.96-107
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• 2022

When setting the RAM objectives, various data such as expert opinions and the historical data of similar types of equipment are used. However, many times subjectivity is involved in the process of merging and utilizing data, and there are many cases where some information is omitted or an ambiguous method is used. Most of the previous work focused only on the process or method of calculating values using well-organized data rather than manipulating raw data. But if the data manipulation process is not objective, it is difficult to guarantee the accuracy of the results even if the calculation logic and method are accurate. This study proposes a systematic data merging process used to set the RAM objectives using the evidence theory. The proposed method can be used to avoid information loss and merge the data objectively. Moreover, contribute to improving the accuracy of setting the RAM objectives in the future.

• The Korean Journal of Health Service Management
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• v.9 no.4
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• pp.171-182
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• 2015

Objectives : The aim of this study was to identify the effect of employment type on health-related quality of life. Methods : This study used data from the Sixth Korea National Health and Nutrition Examination Survey. Data were analyzed with the ${\chi}^2$ test, t-test, ANOVA and multiple regression. Results : There were significant statistical differences the health-related quality of life according to employment type. The health-related quality of life of temporary workers was lower than that of regular workers. The significant predictors of the health-related quality of life of regular workers were the subjective health status, stress, age, and education. The significant predictors of the health-related quality of life of temporary workers were the subjective health status, education, stress, sleeping time, and gender. Conclusions : These results suggest that employment type affects the health-related quality of life. The research on social policy is recommended to resolve health inequalities.

• Magazine of the Korean Society of Agricultural Engineers
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• v.45 no.1
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• pp.102-114
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• 2003

The objectives of the paper are to evaluate cell based pollutant loadings for different storm events, to monitor the hydrology and water quality of the Baran HP#6 watershed, and to validate AGNPS with the field data. Simplification was made to AGNPS in estimating storm erosivity factors from a triangular rainfall distribution. GIS-AGNPS interface model consists of three subsystems; the input data processor based on a geographic information system. the models. and the post processor Land use patten at the tested watershed was classified from the Landsat TM data using the artificial neural network model that adopts an error back propagation algorithm. AGNPS model parameters were obtained from the GIS databases, and additional parameters calibrated with field data. It was then tested with ungauged conditions. The simulated runoff was reasonably in good agreement as compared with the observed data. And simulated water quality parameters appear to be reasonably comparable to the field data.

• The Korean Journal of Health Service Management
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• v.12 no.4
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• pp.139-154
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• 2018

Objectives: The aim of this study was to examine factors influencing health-related quality of life of waged workers. Methods: This study used data from the Seventh Korea National Health and Nutrition Examination Survey. Data were analyzed with the $x^2-test$, t-test, ANOVA, and multiple regression. Results: The significant predictors of health-related quality of life were depression, subjective health status, age, activity limitation, education, worker status, monthly income, drinking, smoking, physical injury, stress, and moderate physical activity. Conclusions: Personal health characteristics, psychological characteristics, socioeconomic characetrictics and working characetrictics affect health-related quality of life. Health-related quality of life is also affected by social structural problems such as socioeconomic factors and employment instabilitye. In addition to the development of health care programs to improve health-related quality of life of twaged workers, policy changes are needed to improve the social structure.

• The Korean Journal of Health Service Management
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• v.13 no.3
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• pp.127-136
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• 2019

Objectives: This study examined the determinants of quality of life, depending on the presence or absence of asthma in adults, based on secondary wave data. Methods: Among the 21,724 people participating in the 6th Korea National Health and Nutrition Examination Survey as it was conducted from the first to third period, 495 participants who were aged 19 or older and responded to the question of the presence or absence of asthma were included in the final analysis. Demographic characteristics were examined using the SPSS/WIN 23.0 software tool for analysis of complex sample survey data. Health-related characteristics were presented using descriptive and multivariate analysis of data. Rao_Scott ${\chi}^2$ was used for the analysis of differences in quality of life, and multiple regression analysis of complex sample survey data was used to analyze factors affecting quality of life. Results: The variable factors negatively influencing quality of life were aging, cognition of their ill health, and limited activities. Conclusions: Based on the analysis, the study suggests that practical and ongoing nursing intervention proposals to improve the quality of life of asthmatic patients should be implemented not only for physical limitations and aging but also for psychological factors that reflect subjective health statuses.

• The Korean Journal of Health Service Management
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• v.10 no.3
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• pp.63-74
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• 2016

Objectives : There is a need to develop a data quality management algorithm to improve the quality of healthcare data using a data quality management system. In this study, we developed a data quality control algorithms associated with diseases related to hypertension in patients with diabetes mellitus. Methods : To make a data quality algorithm, we extracted the 2011 and 2012 discharge damage survey data from diabetes mellitus patients. Derived variables were created using the primary diagnosis, diagnostic unit, primary surgery and treatment, minor surgery and treatment items. Results : Significant factors in diabetes mellitus patients with hypertension were sex, age, ischemic heart disease, and diagnostic ultrasound of the heart. Depending on the decision tree results, we found four groups with extreme values for diabetes accompanying hypertension patients. Conclusions : There is a need to check the actual data contained in the Outlier (extreme value) groups to improve the quality of the data.