• Health Policy and Management
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• v.22 no.2
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• pp.275-296
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• 2012

Graduate School of Public Health, Seoul National University The national health insurance system in Korea is characterized as relatively high out-of-pocket payments, which are the principal source of catastrophic health expenditure (CHE). The objectives of this study are to estimate the incidence of household CHE and to clarify the characteristics that affect the occurrence and recurrence of household CHE using the Seoul Welfare Panel Survey database for 2008 and 2010. Thresholds to estimate CHE were 10% and 20% of the total household income (T/X), and 25% and 40% of the income excluding food share (T/Y). Determinants of the occurrence and recurrence of CHE at the threshold of T/X=10% were analysed using multiple logistic regression models. Out of the 3,665 households that responded in 2008 survey, households with CHE were 12.07% (T/X${\geq}$10%), 5.34% (T/X${\geq}$20%), 6.84% (T/Y${\geq}$25%), and 4.44% (T/Y${\geq}$40%). Risk factors associated with household CHE included living with a spouse, non-Medicaid beneficiary, householder unemployment, low household income, the number of disabled members, poor subjective health, and the number of chronic diseases. A total of 41.78% of households with CHE in 2008 repeatedly experienced CHE in 2010. Risk factors of CHE recurrence included decreased household income and an increase in chronic diseases over the two time periods, the number of members with disability or chronic diseases, and the presence of cancer patients in 2008. Households with lower socioeconomic and health status had a higher financial burden on health care than do their counterpart households. There is a need to enhance society-wide financial protection from health spending among vulnerable citizens in Seoul, particularly, households with low income, disabled members or cancer patients.

• Journal of KIISE:Databases
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• v.29 no.1
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• pp.1-14
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• 2002

Association rule discovery is a method of mining for the associated item set on large databases based on support and confidence threshold. The discovered association rules can be applied to the marketing pattern analysis in E-commerce, large shopping mall and so on. The association rule discovery makes multiple scan over the database storing large transaction data, thus, the algorithm requiring very high overhead might not be useful in real-time association rule discovery in dynamic environment. Therefore this paper proposes an active candidate set management model based on trigger and incremental update mechanism to overcome non-realtime limitation of association rule discovery. In order to implement the proposed model, we not only describe an implementation model for incremental updating operation, but also evaluate the performance characteristics of this model through the experiment.

• Journal of the Korean Data and Information Science Society
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• v.26 no.6
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• pp.1305-1315
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• 2015

Consider the risk score which is a function of a linear score for the classification models. The AUC optimization method can be applied to estimate the coefficients of linear score. These estimates obtained by this AUC approach method are shown to be better than the maximum likelihood estimators using logistic models under the general situation which does not fit the logistic assumptions. In this work, the VUS and HUM approach methods are suggested by extending AUC approach method for more realistic discrimination and prediction worlds. Some simulation results are obtained with both various distributions of thresholds and three kinds of link functions such as logit, complementary log-log and modified logit functions. It is found that coefficient prediction results by using the VUS and HUM approach methods for multiple categorical classification are equivalent to or better than those by using logistic models with some link functions.

• Journal of Korea Water Resources Association
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• v.32 no.4
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• pp.489-499
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• 1999

This research investigated the applicapability of an improved algorithm to calculate the topographic index, ln($\alpha$/tan B), for the topography of Korea employing channel initiation threshold area(CIT) and an exponent for the gradient(H). hanjaechun subwatershed in Cheongdochun and Dongok subwatershed in Wichun test watershed were selected as study areas. The digital elevation models(DEM) of study areas have been made with the resolution from 10m to 100m. Application of CIT to the traditional algorithm provide reasonable computation method in considering channel pixel impact. Introduction of the gradient exponent(H) made it possible to obtain better flow convergence effect in concave topography comparing with the traditional multiple flow direction algorithm. The improved algorithm shows the capability to relax the overestimation problem of rising limb of hydrograph through reducing overestimated high value of topographic index.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.12 no.2
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• pp.137-142
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• 2012

The temporal subtraction technique as one of computer aided diagnosis has been introduced in medical fields to enhance the interval changes such as formation of new lesions and changes in existing abnormalities on deference image. With the temporal subtraction technique radiologists can easily detect lung nodules on visual screening. Until now, two-dimensional temporal subtraction imaging technique has been introduced for the clinical test. We have developed new temporal subtraction method to remove the subtraction artifacts which is caused by mis-registration on temporal subtraction images of lungs on MDCT images. In this paper, we propose a new computer aided diagnosis scheme for automatic enhancing the lung nodules from the temporal subtraction of thoracic MDCT images. At first, the candidates regions included nodules are detected by the multiple threshold technique in terms of the pixel value on the temporal subtraction images. Then, a rule-base method and artificial neural networks is utilized to remove the false positives of nodule candidates which is obtained temporal subtraction images. We have applied our detection of lung nodules to 30 thoracic MDCT image sets including lung nodules. With the detection method, satisfactory experimental results are obtained. Some experimental results are shown with discussion.

• Journal of Information Technology and Architecture
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• v.9 no.4
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• pp.443-453
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• 2012

In order to minimize the damage from system failures, systems over various fields are requested to contain the safety-critical features. In this paper, we deliver the considerable issues, especially, in the cyber physical systems that is recently used as a safety-critical system, as well as we propose the model driven architecture based on time as its the important factor. Based on meta-modeling approach, we introduce the time-based architecture which is associated with deadline, transition state, and threshold, and also we work out a design for this by using model driven architecture. We propose a realizable safety-critical architecture by means of showing failure handling components with safety transaction model from the meta-model. In the detailed models and the example, we design a basic safety processing state, a multiple safety processing state, and a compound safety processing state for completing the safety-critical system architecture.

• Journal of Information Processing Systems
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• v.10 no.1
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• pp.145-161
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• 2014

Recently, many large organizations have multiple data sources (MDS') distributed over different branches of an interstate company. Local patterns analysis has become an effective strategy for MDS mining in national and international organizations. It consists of mining different datasets in order to obtain frequent patterns, which are forwarded to a centralized place for global pattern analysis. Various synthesizing models [2,3,4,5,6,7,8,26] have been proposed to build global patterns from the forwarded patterns. It is desired that the synthesized rules from such forwarded patterns must closely match with the mono-mining results (i.e., the results that would be obtained if all of the databases are put together and mining has been done). When the pattern is present in the site, but fails to satisfy the minimum support threshold value, it is not allowed to take part in the pattern synthesizing process. Therefore, this process can lose some interesting patterns, which can help the decider to make the right decision. In such situations we propose the application of a probabilistic model in the synthesizing process. An adequate choice for a probabilistic model can improve the quality of patterns that have been discovered. In this paper, we perform a comprehensive study on various probabilistic models that can be applied in the synthesizing process and we choose and improve one of them that works to ameliorate the synthesizing results. Finally, some experiments are presented in public database in order to improve the efficiency of our proposed synthesizing method.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.4
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• pp.113-124
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• 2009

A research of grid computing that is the combination of computer resources from multiple distributed administrative domains to get large amount of computing power is underway. This research is an application of grid technology on a urban facilities management system based on u-GIS. The sensors are set up in the urban facilities to make it monitoring. If an amount of sensors and gateways is increased, the server needs more computing resources to process the data. In this study we developed the skills that can distribute jobs to idle gateway, in case of the server capacity had approached threshold. It will be possible to develop of economic and efficient system that will apply to large amount of data processing about u-City.

• Korean Journal of Remote Sensing
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• v.22 no.6
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• pp.533-542
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• 2006

Lidar point clouds provide three dimensional information of terrain surface and have a great advantage to generate precise digital elevation model (DEM), particularly over forested area where some laser signals are transmitted to vegetation canopy and reflected from the bare ground. This study initially investigates the characteristics of lidar-derived height information as related to vertical structure of forest stands. Then, we propose a new filtering method to separate ground points from Lidar point clouds, which is a prerequisite process both to generate DEM surface and to extract biophysical information of forest stands. Laser points clouds over the forest stands in central Korea show that the vertical distribution of laser points greatly varies by the stand characteristics. Based on the characteristics, the proposed filtering method processes first and last returns simultaneously without setting any threshold value. The ground points separated by the proposed method are used to generate digital elevation model, furthermore, the result provides the possibilities to extract other biophysical characteristics of forest.

• Safety and Health at Work
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• v.6 no.4
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• pp.268-278
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• 2015

Background: This study aimed to assess the whole-body vibration (WBV) exposure among large blast hole drill machine operators with regard to the International Organization for Standardization (ISO) recommended threshold values and its association with machine- and rock-related factors and workers' individual characteristics. Methods: The study population included 28 drill machine operators who had worked in four opencast iron ore mines in eastern India. The study protocol comprised the following: measurements of WBV exposure [frequency weighted root mean square (RMS) acceleration ($m/s^2$)], machine-related data (manufacturer of machine, age of machine, seat height, thickness, and rest height) collected from mine management offices, measurements of rock hardness, uniaxial compressive strength and density, and workers' characteristics via face-to-face interviews. Results: More than 90% of the operators were exposed to a higher level WBV than the ISO upper limit and only 3.6% between the lower and upper limits, mainly in the vertical axis. Bivariate correlations revealed that potential predictors of total WBV exposure were: machine manufacturer (r = 0.453, p = 0.015), age of drill (r = 0.533, p = 0.003), and hardness of rock (r = 0.561, p = 0.002). The stepwise multiple regression model revealed that the potential predictors are age of operator (regression coefficient ${\beta}=-0.052$, standard error SE = 0.023), manufacturer (${\beta}=1.093$, SE = 0.227), rock hardness (${\beta}=0.045$, SE = 0.018), uniaxial compressive strength (${\beta}=0.027$, SE = 0.009), and density (${\beta}=-1.135$, SE = 0.235). Conclusion: Prevention should include using appropriate machines to handle rock hardness, rock uniaxial compressive strength and density, and seat improvement using ergonomic approaches such as including a suspension system.