• Quality Improvement in Health Care
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• v.24 no.2
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• pp.62-75
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• 2018

Purpose: The objective of this study was to publicly report the hospital-level surgical volume for 7 types of surgery including gastrectomy. Also, to investigate the changes in patient behaviors after the public reporting among patients with gastrectomy. Methods: This study used data from the National Health Insurance Service Cohort. The data comprised of 2,214 patients who were diagnosed with gastric cancer and underwent gastrectomy during 2004-2012. An interrupted time series analysis was performed to investigate the association between patients' choice and public reporting. Results: 79.27% of the patients visited a hospital with high surgical volume. The time trend after introduction of public reporting was positively associated with visiting a high volume hospital (per 1 month, RR: 1.004, p=0.0329). However, after adjusting the health policies by reducing copayment, public reporting on surgical volume was not associated with visiting a high volume hospital. Sub-group analyses had also similar results. Conclusion: Patients were more affected by policies on economic support than on public reporting, and the changes in treatment options may have been affected by the increasing preference for large size hospitals. Thus, public reporting did not significantly improve the options available for patients and their decision making on health care utilization.

• Dementia and Neurocognitive Disorders
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• v.23 no.3
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• pp.127-135
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• 2024

Background and Purpose: To ensure data privacy, the development of defacing processes, which anonymize brain images by obscuring facial features, is crucial. However, the impact of these defacing methods on brain imaging analysis poses significant concern. This study aimed to evaluate the reliability of three different defacing methods in automated brain volumetry. Methods: Magnetic resonance imaging with three-dimensional T1 sequences was performed on ten patients diagnosed with subjective cognitive decline. Defacing was executed using mri_deface, BioImage Suite Web-based defacing, and Defacer. Brain volumes were measured employing the QBraVo program and FreeSurfer, assessing intraclass correlation coefficient (ICC) and the mean differences in brain volume measurements between the original and defaced images. Results: The mean age of the patients was 71.10±6.17 years, with 4 (40.0%) being male. The total intracranial volume, total brain volume, and ventricle volume exhibited high ICCs across the three defacing methods and 2 volumetry analyses. All regional brain volumes showed high ICCs with all three defacing methods. Despite variations among some brain regions, no significant mean differences in regional brain volume were observed between the original and defaced images across all regions. Conclusions: The three defacing algorithms evaluated did not significantly affect the results of image analysis for the entire brain or specific cerebral regions. These findings suggest that these algorithms can serve as robust methods for defacing in neuroimaging analysis, thereby supporting data anonymization without compromising the integrity of brain volume measurements.

• Journal of the Korean Association of Geographic Information Studies
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• v.13 no.4
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• pp.138-147
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• 2010

As inaccurate traffic volume prediction may result in inadequate transportation planning and design, traffic volume prediction based on traffic volume data is very important in spatial decision making processes such as transportation planning and operation. In order to improve the accuracy of traffic volume prediction, recent studies are using the geostatistical approach called kriging and according to their reports, the method shows high predictability compared to conventional methods. Thus, this study estimated traffic volume data for St. Louis in the State of Missouri, USA using the kriging method, and tested its accuracy by comparing the estimates with actual measurements. In addition, we suggested a new method for enhancing the accuracy of prediction by the kriging method. In the new method, we estimated traffic volume data: first, by applying anisotropy, which is a characteristic of traffic volume data appearing in determining variogram factors; and second, by performing co-kriging analysis using interstate highway, which is in a high spatial correlation with traffic volume data, as a secondary variable. According to the results of the analysis, the analysis applying anisotropy showed higher accuracy than the kriging method, and co-kriging performed on the application of anisotropy produced the most accurate estimates.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.24 no.3 s.174
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• pp.735-742
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• 2000

Densification behaviors of mixed metal powder under high temperature were investigated. Experimental data of mixed copper and tool steel powder with various volume fractions of Cu powder were obtained under hot isostatic pressing and hot pressing. By mixing the creep potentials of McMeeking and co-workers and of Abouaf and co-workers originally for pure powder, the mixed creep potentials with various volume fractions of Cu powder were employed in the constitutive models. The constitutive equations were implemented into a finite element program (ABAQUS) to compare with experimental data for densification of mixed powder under hot isostatic pressing and hot pressing. Finite element calculations by using the creep potentials of Abouaf and co-workers agreed reasonably well with experimental data, however, those by McMeeking and co-workers underestimate experimental data as observed in the case of pure metal powders.

• Transactions of Materials Processing
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• v.32 no.6
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• pp.352-359
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• 2023

Recently, independent suspension systems have been applied not only to passenger cars but also to large commercial vehicles. Therefore, the need for research to domestically produce such independent suspensions for large commercial vehicles is gradually increasing. In this paper, we conducted research on the manufacturing technology of the relay lever, which are integral components of independent suspension systems for large commercial vehicles. Our goal was to reduce the flash volume generated during the forging process. The shape variables of the initial billet were adjusted to find proper forming conditions that could minimize flash volume while performing product forming smoothly. Shape variables were set as input variables and the flash volume was set as an output variable, and simulations were carried out to analytically predict the volume of the flash area for each variable condition. Based on the data obtained through numerical simulations, a regression model and an artificial neural network model were used to develop a prediction model that can easily predict the flash volume for variable conditions. For the corresponding prediction model, a goodness of-fit test was performed to confirm a high level of fit. By comparing and analyzing the two prediction models, the high level of fit of the ANN model was confirmed.

• Journal of Korea Multimedia Society
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• v.14 no.3
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• pp.339-347
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• 2011

As the volume visualization has been applied to render medical datasets, there has been a requirement to produce high quality images. Even though nice images can be generated by using previous linear filter, high order filter is required for better images. However, it takes much time for high order resampling, so that, overall rendering time is increased. In this paper, we perform high quality volume visualization using the cardinal interpolation. By enabling the empty space leaping which reduces the number of resampling, we achieve the efficient visualization. In detail, we divide the volume data into small blocks and leap empty blocks by referring the upper and lower bound value for each block. We propose a new method to estimate upper and lower bound value of for each block. As the result, we noticeably accelerated high quality volume visualization.

• Journal of Forest and Environmental Science
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• v.24 no.3
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• pp.165-169
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• 2008

This study attempts to analyze the relationship between forest volume and age based on 5th NFI data and spectral characteristics of satellite imagery using ASTER sensor in Korea. Forest stand volume and age had the negative correlation with the spectral reflectance in all of the band (Blue, Green, Red, SWIR). With increasing of stand volume and age, spectral reflectance decrease. The spectral reflectance of band1 showed the highest correlation between stand volume and spectral reflectance among the VNIR wavelength. The spectral reflectance band 1, 2 (visible wavelength) and stand age have high correlation compared to other bands. The correlation coefficients between forest volume and vegetation indices have low relationship. This result indicates that the reflectance of blue band may be important factor to improve the potential of optical remote sensing data to estimate forest volume and age.

• Health Policy and Management
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• v.24 no.3
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• pp.271-282
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• 2014

Background: Although the mortality rate in cancers has been decreased recently, it is still one of the leading causes of death in most of the countries. This study analyzed the relationship between surgery volume and in hospital mortality of cancer patients. The purpose of this study is to investigate the relationship in Korean healthcare environment and to provide information for the policy development in reducing cancer mortality. Methods: The study sample was the 20,517 cancer patients who underwent surgery and discharged during a month period between 2008-2011. The data were collected in Patient Survey by Korean Institute of Social Affairs. Logistic regression was used to analyse a comprehensive analytic model that includes a binary dependent variable indicating death discharge and independent variables such as surgery volume, organizational characteristics of hospitals, socio-economical characteristics of the patients, and severity of disease indicators. Results: In chi-square test, as the surgery volume increases, the in-hospitals mortality showed a downward trends. In regression analysis, the relationship between surgery volume and mortality showed significant negative associations in all types of cancer except for pancreatic cancer. Conclusion: In the absence of other information patients undergoing cancer surgery can reduce their risk of operative death by selecting a high-volume hospital. Therefore, policies to enhance centralization of cancer surgery services should be considered.

• Journal of Information Technology Services
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• v.10 no.1
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• pp.135-149
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• 2011

In this paper, we propose the high-risk group detection model for patients with high blood pressure using case-based reasoning. The proposed model can be applied for public health maintenance organizations to effectively manage knowledge related to high blood pressure and efficiently allocate limited health care resources. Especially, the focus is on the development of the model that can handle constraints such as managing large volume of data, enabling the automatic learning to adapt to external environmental changes and operating the system on a real-time basis. Using real data collected from local public health centers, the optimal high-risk group detection model was derived incorporating optimal parameter sets. The results of the performance test for the model using test data show that the prediction accuracy of the proposed model is two times better than the natural risk of high blood pressure.

• Water for future
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• v.17 no.2
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• pp.125-131
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• 1984

watershed Model by mathematical formulation is one of the powerful tool to analyze the hydrologic process in a watershed. The seasonal watershed model is one of the mathematial model from which the monthly streamflow can be simulated and forcasted for given precipitaion data. This model also enables us to compute the monthly runoff at each subbgasin when the basin is subdivided into several small subbasins. The computation of runoff volume makes a Prediction of the areal distirbution of runoff volume for a given precipitation data. Several basins in Han River basin were chosen to simulate the monthly runoff and compute the runoff at each subbasin. A simple logarithmic regression were conducted between runoff ratio and area ratio. The correlation was very high and the equation can be used for prediciting flood volume when flood at downstream gaging station is know.