• The Korean Journal of Applied Statistics
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• v.35 no.1
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• pp.35-47
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• 2022

The receiver operating characteristic (ROC) curve was developed to quantify the classification ability of marker values (covariates) on the response variable and has been extended to survival data with diverse missing data structure. When survival data is understood as binary data (status of being alive or dead) at each time point, the ROC curve expressed at every time point results in time-dependent ROC curve and time-dependent area under curve (AUC). In particular, a follow-up study brings the change of cohort and incomplete data structures such as censoring and competing risk. In this paper, we review time-dependent ROC estimators under several contexts and perform simulation to check the performance of each estimators. We analyzed a dementia dataset to compare the prognostic power of markers.

• Journal of Distribution Science
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• v.20 no.2
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• pp.55-64
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• 2022

Purpose: This research is aimed to study the level of the intellectual potential distribution, as well as the correlation between economic growth and key indicators of intellectual potential in each region of Kazakhstan. A review of the conceptual framework shows that there is a large body of research evaluating the level of intellectual potential in different ways based on different factors. Research design, data, and methodology: The research methodology is divided into two groups the integral index method using the normalization of indicators, weighting, and ranking; the method of correlation analysis. By the proposed methodological approaches, were calculated a set of factors affect the distribution of the intellectual potential. Statistics are taken for indicators of development of the intellectual potential for 2011-2020 from the Bureau of National Statistics. Results: Ranking results showed gaps between regions in Kazakhstan by the level of intellectual potential. Correlation analysis results revealed a statistically significant relationship on expenditures on R&D, computer literacy, innovative products, number of PhD students, and cultural and leisure indicators. Conclusions: Based on the obtained results of the intellectual potential level development there were given recommendations for the reproduction and regulation of the intellectual potential in the future.

• Proceedings of the Korean Institute of Building Construction Conference
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• 2020.11a
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• pp.69-70
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• 2020

Accidents in the construction industry are very high compared to other industries, and the number is also increasing steeply every year. Relevant studies were limited for solving the problems. The purpose of this study is to develop a comprehensive risk prediction process for personnel deployed at construction sites on safety management. First of all, the variables were divided into fixed, real-time and working types variables, and the relevant comprehensive data were collected. Second, the probability of a disaster was derived based on the collected data, and weights for each variable were calculated using the dummy regression analysis method using statistical methodology. Lastly, the resulting weighting and disaster probability equation was constructed, and The Final Risk Calculation Formula was developed. The Final Risk Calculation Formula presented in this study is expected to have a significant impact on the establishment of effective safety management measures to prevent possible safety accidents at construction sites

• The Journal of the Acoustical Society of Korea
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• v.25 no.1
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• pp.14-20
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• 2006

In this paper. a novel technique to set up the initial weights in BSS of delayed mixtures is proposed. After analyzing Eigendecomposition for the correlation matrix of mixing data. the initial weights are set from the Eigenvectors ith delay information. The Proposed setting of initial weighting method for conventional FDICA technique improved the separation Performance. The computer simulation shows that the Proposed method achieves the improved SIR and faster convergence speed of learning curve.

• Korean Circulation Journal
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• v.53 no.11
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• pp.775-786
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• 2023

Background and Objectives: Tricuspid valve (TV) repair techniques other than annuloplasty remain challenging and frequently end in tricuspid valve replacement (TVR) in complicated cases. However, the results of TVR are suboptimal compared with TV repair. This study aimed to evaluate the clinical effectiveness of TV edge-to-edge repair (E2E) compared to TVR for severe tricuspid regurgitation (TR). Methods: We retrospectively reviewed 230 patients with severe TR who underwent E2E (n=139) or TVR (n=91) from 2001 to 2020. Clinical and echocardiographic results were analyzed using inverse probability of treatment weighting analysis and propensity score matching. Results: The two groups showed no significant differences in early mortality and morbidities. During the mean follow-up of 106.2±68.8 months, late severe TR and TV reoperation rates were not significantly different between groups. E2E group, however, showed better outcomes in overall survival (p=0.023), freedom from significant tricuspid stenosis (TS) (trans-tricuspid pressure gradient ≥5 mmHg, p=0.021), and freedom from TV-related events (p<0.001). Matched analysis showed consistent results. Conclusions: E2E for severe TR presented more favorable clinical outcomes than TVR. Our study supports that E2E might be a valuable option in severe TR surgery, avoiding TVR.

• Journal of Radiation Protection and Research
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• v.33 no.4
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• pp.127-134
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• 2008

Potential economic impact of a hypothetical severe accident at a nuclear power plant(Uljin units 3/4) was estimated by applying the Delphi method, which is based on the expert judgements and opinions, in the process of quantifying uncertain factors. For the purpose of this study, it is assumed that the radioactive plume directs the inland direction. Since the economic risk can be divided into direct costs and indirect effects and more uncertainties are involved in the latter, the direct costs were estimated first and the indirect effects were then estimated by applying a weighting factor to the direct cost. The Delphi method however subjects to risk of distortion or discrimination of variables because of the human behavior pattern. A mathematical approach based on the Bayesian inferences was employed for data processing to improve the Delphi results. For this task, a model for data processing was developed. One-dimensional Monte Carlo Analysis was applied to get a distribution of values of the weighting factor. The mean and median values of the weighting factor for the indirect effects appeared to be 2.59 and 2.08, respectively. These values are higher than the value suggested by OECD/NEA, 1.25. Some factors such as small territory and public attitude sensitive to radiation could affect the judgement of panel. Then the parameters of the model for estimating the direct costs were classified as U- and V-types, and two-dimensional Monte Carlo analysis was applied to quantify the overall economic risk. The resulting median of the overall economic risk was about 3.9% of the gross domestic products(GDP) of Korea in 2006. When the cost of electricity loss, the highest direct cost, was not taken into account, the overall economic risk was reduced to 2.2% of GDP. This assessment can be used as a reference for justifying the radiological emergency planning and preparedness.

• Atmosphere
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• v.22 no.2
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• pp.233-243
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• 2012

The Barnes scheme is used in Digital Forecast System (DFS) of the Korea Meteorological Administration (KMA) for real-time analysis. This scheme is an objective analysis scheme with a distance-dependent weighted average. It has been widely used for mesoscale analyses in limited geographic areas. The isotropic Gaussian weight function with a constant effective radius might not be suitable for certain conditions. In particular, the analysis error can be increased for stations located near mountains. The terrain of South Korea is covered with mountains and wide plains that are between successive mountain ranges. Thus, it is needed to consider the terrain effect with the information of elevations for each station. In order to improve the accuracy of the temperature objective analysis, we modified the weight function which is dependent on a distance and elevation in the Barnes scheme. We compared the results from the Barnes scheme used in the DFS (referred to CTL) with the new scheme (referred to EXP) during a year of 2009 in this study. The analysis error of the temperature field was verified by the root-mean-square-error (RMSE), mean error (ME), and Priestley skill score (PSS) at the DFS observation stations which is not used in objective analysis. The verification result shows that the RMSE and ME values are 1.68 and -0.41 in CTL and 1.42 and -0.16 in EXP, respectively. In aspect of spatial verification, we found that the RSME and ME values of EXP decreased in the vicinity of Jirisan (Mt. Jiri) and Taebaek Mountains. This indicates that the new scheme performed better in temperature verification during the year 2009 than the previous scheme.

• Korean Journal of Remote Sensing
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• v.30 no.5
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• pp.687-701
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• 2014

Sea ice is generally accepted as an important factor to understand the process of earth climate changes and is the basis of earth system models for analysis and prediction of the climate changes. To continuously monitor sea ice changes at kilometer scale, it is demanded to create more accurate grid data from the current, limited sea ice data. In this paper we described a downscaling method for Advanced Microwave Scanning Radiometer 2 (AMSR2) Sea Ice Concentration (SIC) from 10 km to 1 km resolution using a weighting scheme of sea ice days ratio derived from Moderate Resolution Imaging Spectroradiometer (MODIS) sea ice cover product that has a high correlation with the SIC. In a case study for Okhotsk Sea, the sea ice areas of both data (before and after downscaling) were identical, and the monthly means and standard deviations of SIC exhibited almost the same values. Also, Empirical Orthogonal Function (EOF) analyses showed that three kinds of SIC data (ERA-Interim, original AMSR2, and downscaled AMSR2) had very similar principal components for spatial and temporal variations. Our method can apply to downscaling of other continuous variables in the form of ratio such as percentage and can contribute to monitoring small-scale changes of sea ice by providing finer SIC data.

• Health Policy and Management
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• v.34 no.1
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• pp.68-77
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• 2024

Background: Depressive disorders can be categorized into daily depression and clinical depression. The experience of depressive disorder can increase health care utilization due to decreased treatment compliance and somatization. On the other hand, the clinical depression group may also experience social prejudice associated with the illness, which can limit their access to health care utilization. In terms of the significance of health care utilization as a factor in individual and social issues, this study aims to compare the health care utilization of the clinical depression group with that of the non-depressed group and the daily depression group. Methods: The analysis utilized the inverse probability of treatment weighting based on the generalized propensity score. Results: As a result of the analysis, clinical depression and daily depression were higher among women, low-income groups, individuals with low education levels, and so forth. The clinical depression group was also higher among individuals who were not economically active, did not have private health insurance, or had multiple chronic diseases. The number of outpatient department visits in the depression group was significantly higher than in the non-depressed group. In addition, the number of outpatient department visits for the clinical depression group was significantly higher than that for the daily depression group. Outpatient medical expenses were higher in the depression group than in the non-depressed group, and there was no significant difference between the clinical depression group and the daily depression group. Conclusion: Health care utilization was higher in the depression group than the non-depressed group, it was also higher in the clinical depression group than the daily depression group.

• Journal of The Korean Society of Grassland and Forage Science
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• v.36 no.3
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• pp.248-256
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• 2016

The present study investigated the effect of enzyme inclusion on silage quality using meta-analysis tool. A total of 16 research papers reporting the effect of enzyme application on silage quality were employed in the meta-analysis of this study. Mixed model for integrating quantitative results from multiple studies was used first to calculate the predicted error of each study. Individual error from the estimated model was the applied into standard deviation of each study to calculate the mean difference. Finally, summary effect was determined using standard mean difference (SMD) and inversed variance weighting. Mixed model analysis and SMD analysis showed the same effect patterns in all analysis items. Enzyme inclusion in silage significantly (p < 0.05) altered all silage quality characteristics investigated compared to control when enzyme was not included. Our results showed that enzyme treatment increased dry matter content, preserved crude protein effectively, and elevated water soluble carbohydrate content. However, the pH value, acetic acid, propionic acid, neutral detergent fiber, and acid detergent fiber contents in silage with enzyme inclusion were lower than those of the control.