• Journal of Wetlands Research
• /
• v.15 no.3
• /
• pp.367-380
• /
• 2013

In this study, sub-indicators, and thematic mid-indexes to evaluate the water use characteristics were selected through historical data analysis and factor analysis, and consisted of the subject approach framework. And the integrated index was developed to evaluate water use characteristics of the watershed. Using developed index, the water use characteristics were assessed for 812 standard basins with the exception for North Korea using data of 1990 to 2007 from the relevant agencies. A sensitivity analysis is conducted for this study to determine the proper way through various normalization and weighting methods. To increase the objectivity of developed index, the history of the damage indicators are excluded in the analysis. In addition, in order to ensure its reliability, results from index with and without consideration of the damage history were compared. Also, the index is also applied to real data for 2008 Gangwon region to verify its field applicability. Through the validation process this index confirmed the adequacy for the indicators selection and calculation method. The results of this study were analyzed based on the spatial and time vulnerability of the basin's water use, which can be applied to various parts such as priority decision-making for water business or policy, mitigations for the vulnerable components of the basin, and supporting measures to establishment by providing relevant information about it.

• Korean Journal of Cognitive Science
• /
• v.30 no.3
• /
• pp.105-132
• /
• 2019

This study quantitatively analyzed the speeches of the former 8 Presidents of the Republic of Korea. Unlike the previous studies, this study analyzed both the content word and the functional word related to the psychological phenomenon. In Study 1, six language style indicators such as clout, authenticity, presidentiality, cognitive complexity, femininity, and psychological health were developed. Also, as presidential speeches have been made recently, authenticity, presidentiality, psychological health tended to increase, but cognitive complexity tended to decrease. These tendencies were supported by linear trend analysis. The linguistic differences were distinct not only among individual presidents but also by groups based on the political orientation of the president. In the progressive presidential speech, more clout, cognitive complexity, femininity were observed. In contrast, more authenticity and presidentiality were observed in the conservative presidential speech. In Study 2, it was demonstrated whether the developed language style indicators show reliability in the most recent President's speeches. Finally, it was discussed that the relationship between language style indicators, fitness of the political tendency between the regime and the general public since 2000s, and the characteristics of femininity indicator.

• Journal of dental hygiene science
• /
• v.3 no.2
• /
• pp.83-88
• /
• 2003

Patient satisfaction is now recognized as a outcome indicator of health care quality. The objective of this research was to evaluate a patient satisfaction survey instrument specially applicable to dental care, and to examines the reliability and the effect of response biases on reported satisfaction. The acceptability of satisfaction as a quality indicators was qualified by several measurement problems. The patient questionnaire was administered in four different study samples to examine the consistency of data. Cronbach's alpha was used as the measure of internal consistency. A aquiesent bias was found in the sample of 80(20%) respondents. Response biases affacted level of measured satisfaction. Highly acquiesent respondents were older, less well educated than nonaquiesent subject.

• Korean Journal of Community Nutrition
• /
• v.2 no.3
• /
• pp.349-365
• /
• 1997

Using data obtained from 1, 473 adults aged 18-68 yrs, residing in large cities and by use of a semi-quantitative food frequency questionnaire, we assessed the relative importance of various foods as indicators of both the amount and the variability of selected nutrient intake to develop a simple food frequency questionnaire. Since Cronba- ch's alpha value of the questionnaire including 78 food items was 0.76, the reliability of this questionnaire was acceptable. A large fraction of the variability of nutrient intake in this population could be explained by the small number of food items. The estimation of dietary nutrient intake such as total calories or protein content, which are derived from almost all foods, will require more food items with nutrients such as calcium or vitamin A, which are concentrated in a few food items. A dietary history ascertaining the intake of as few as 5-19 food items mighted be all needed in order to determent the associa- tion between disease outcome and the intake of a single nutrient. There was certainly a high level of agreement with nutrient intake by the sbujects who were cross-classified by quartiles of nutrient indices based on all the food items(78) and by quartiles of nutrient indices based on food items selected by stepwise multiple regression for selected nutrients. The data provided further evidence that useful information on dietary intake over an extended period can be obtained by a simple and relatively inexpensive food frequency questionnaire.

• Journal of Korean Academy of Nursing
• /
• v.48 no.3
• /
• pp.362-374
• /
• 2018

Purpose: This study aimed to develop a triage competency scale (TCS) for emergency nurses, and to evaluate its validity and reliability. Methods: Preliminary items were derived based on the attributes and indicators elicited from a concept analysis study on triage competency. Ten experts assessed whether the preliminary items belonged to the construct factor and determined the appropriateness of each item. A revised questionnaire was administered to 250 nurses in 18 emergency departments to evaluate the reliability and validity of the scale. Data analysis comprised item analysis, confirmatory factor analysis, contrasted group validity, and criterion-related validity, including criterion-related validity of the problem solving method using video scenarios. Results: The item analysis and confirmatory factor analysis yielded 5 factors with 30 items; the fit index of the derived model was good (${\chi}^2/df=2.46$, Root Mean squared Residual=.04, Root Mean Squared Error of Approximation=.08). Additionally, contrasted group validity was assessed. Participants were classified as novice, advanced beginner, competent, and proficient, and significant differences were observed in the mean score for each group (F=6.02, p=.001). With reference to criterion-related validity, there was a positive correlation between scores on the TCS and the Clinical Decision Making in Nursing Scale (r=.48, p<.001). Further, the total score on the problem solving method using video scenarios was positively correlated with the TCS score (r=.13, p=.04). The Cronbach's ${\alpha}$ of the final model was .91. Conclusion: Our TCS is useful for the objective assessment of triage competency among emergency nurses and the evaluation of triage education programs.

• Proceedings of the KSR Conference
• /
• 2010.06a
• /
• pp.2166-2178
• /
• 2010

The Korea Transportation Database (KTDB) is used to obtain data on the origin and destination (OD) of inter-city travel, which are currently used in railroad planning when estimating traffic demand. The KTDB employs the trip assignment method, whereby the total traffic volume researched for inter-city travel in Korea is divided into road, rail and air traffic, etc. However, as regards rail travel, the railroad stations are not identical to the existing zones or the connector has not been established because there are several stations in one zone as such, certain problems with the applicable methods have been identified. Therefore, estimates of the volume of railroad traffic using the KTDB display low reliability compared to other modes of transportation. In this study, these problems are reviewed and analyzed, and use of the aggregate model method to estimate the direct demand for rail travel is proposed in order to improve the reliability of estimation. In addition, a method of minimizing error in traffic demand estimation for the railroad field is proposed via an analysis of the relationship between the aggregate model and various social-economic indicators including population, distances, numbers of industrial employees, numbers of automobiles, and the extension of roads between cities.

• Health Policy and Management
• /
• v.15 no.3
• /
• pp.60-78
• /
• 2005

The main objective of this study is to define the nature of the patient service quality of Health Centers, and based on that, to examine the causal relationship of Health Center visitor's perceived service quality with overall satisfaction, intention to revisit and intention to recommend. Data are collected on the basis of the second field survey of '3rd Regional Health Care Planning' operated by the Ministry of Health and Welfare(MOHW). In this study, the 24 patient satisfaction questions are used as outcome indicators. The samples are 3,091 patients who visited 68 Health Centers. The reliability and validity of patient service quality items was evaluated. Finally, the Structural Equation Modeling(SEM) analysis was conducted to find a causal relationship of service quality, patient satisfaction, intention to revisit and intention to recommend. This study shows firstly, the dimension of patient service quality was categorized into 3 dimensions, that is, facilities and environment, staff kindness, and convenience of utilization process. Secondly, the reliability and validity of patient service quality items was satisfied. Lastly, the total effect of convenience of utilization process factor on satisfaction(path coefficients=1.721), intention to revisit(0.843) and intention to recommend(0.696) is more higher than other variables. These findings imply that the quality of various services concerning convenience of utilization process at Health Centers should be improved to satisfy the health need of community people and improve the service quality of Health Centers.

• Journal of Korea Water Resources Association
• /
• v.50 no.8
• /
• pp.563-577
• /
• 2017

As the uncertainty of precipitation increases due to climate change, seasonal forecasting and the use of weather forecasts become essential for efficient water resources management. In this study, the categorical probabilistic long-term forecasts implemented by KMA (Korea Meteorological Administration) since June 2014 was evaluated using assessment indicators of Hit Rate, Reliability Diagram, and Relative Operating Curve (ROC) and a technique for obtaining quantitative precipitation estimates based on probabilistic forecasts was proposed. The probabilistic long-term forecasts showed its maximum predictability of 48% and the quantified precipitation estimates were closely matched with actual observations; maximum correlation coefficient (R) in predictability evaluation for 100% accurate and actual weather forecasts were 0.98 and 0.71, respectively. A precipitation quantification approach utilizing probabilistic forecasts proposed in this study is expected to enable water management considering the uncertainty of precipitation. This method is also expected to be a useful tool for supporting decision-making in the long-term planning for water resources management and reservoir operations.

• Journal of Convergence for Information Technology
• /
• v.8 no.6
• /
• pp.173-186
• /
• 2018

While cloud services are expanding, many users are having difficulty in adopting cloud services. This is because there is no information as to which cloud services can be trusted by users. loud service level agreement (Cloud SLA) is an agreement between cloud service providers and cloud service consumers using qualitative and quantitative indicators including quality and performance, etc. of cloud services. In this study, we propose a framework for cloud SLA that can be applied to the domestic cloud industry to improve service levels for cloud service providers and to protect users and also derive the detailed components of cloud SLA applicable to the domestic cloud industry using the proposed framework. Through this result, it is expected that the government will utilize the policy to enhance the reliability between cloud service providers and users under "the Act on the Development of Cloud Computing and Protection of Users", and eventually to activate cloud services by improving the quality and performance level of domestic cloud services and building a user trust.

• Journal of Biomedical Engineering Research
• /
• v.42 no.5
• /
• pp.241-249
• /
• 2021

Recently, artificial intelligence for diagnosis system of obstetric diseases have been actively studied. Artificial intelligence diagnostic assist systems, which support medical diagnosis benefits of efficiency and accuracy, may experience problems of poor learning accuracy and reliability when inappropriate images are the model's input data. For this reason, before learning, We proposed an algorithm to exclude unread cervical imaging. 2,000 images of read cervical imaging and 257 images of unread cervical imaging were used for this study. Experiments were conducted based on the statistical method Radiomics to extract feature values of the entire images for classification of unread images from the entire images and to obtain a range of read threshold values. The degree to which brightness, blur, and cervical regions were photographed adequately in the image was determined as classification indicators. We compared the classification performance by learning read cervical imaging classified by the algorithm proposed in this paper and unread cervical imaging for deep learning classification model. We evaluate the classification accuracy for unread Cervical imaging of the algorithm by comparing the performance. Images for the algorithm showed higher accuracy of 91.6% on average. It is expected that the algorithm proposed in this paper will improve reliability by effectively excluding unread cervical imaging and ultimately reducing errors in artificial intelligence diagnosis.