• The KIPS Transactions:PartB
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• v.17B no.2
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• pp.115-124
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• 2010

Stereo matching techniques are categorized in two major schemes, local and global matching techniques. In global matching schemes, several investigations are introduced, where cost accumulation is performed in multiple matching lines. In this paper, we introduce a new multi-line stereo matching techniques which expands a conventional single-line matching scheme to multiple one. Matching cost is based on simple normalized cross correlation. We expand the scan-line optimization technique to a multi-line scan-line optimization technique. The proposed technique first generates a reliability image, which is iteratively updated based on the previous reliability measure. After some number of iterations, the reliability image is completed by a hole-filling algorithm. The hole-filling algorithm introduces a disparity score table which records the disparity score of the current pixel. The disparity of an empty pixel is determined by comparing the scores of the neighboring pixels. The proposed technique is tested using the Middlebury and CMU stereo images. The error analysis shows that the proposed matching technique yields better performance than using conventional global matching algorithm.

• Journal of Soil and Groundwater Environment
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• v.21 no.6
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• pp.1-13
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• 2016

The programmable logic array to match the treatment technology to the soil contaminated site based on the site properties in Korea was developed. Based on the previous technology screening system of FRTR (Federal Remediation Technology Roundtable) in USA, total 9 evaluation factors indicating the site characteristics were used for the technology matching process and 8 factors among them were quantitatively weighed in the order of importance. The class interval for each evaluation factor was linearly distributed to give the weighed score and 8 scores were summed up to prioritize the treatment technology. The optimal treatment technology for a specific site was determined according to the total score acquired from 8 evaluation factors used in this technology matching process. The reliability test for the developed technology matching system was done by using information of two real cleanup sites in Korea, suggesting that this guideline will be available to determine the most effective treatment technology to cleanup the soil contaminated site and also to assist the government or the company to design a successful and cost-effective site cleanup plan in Korea.

• Health Policy and Management
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• v.25 no.1
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• pp.3-10
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• 2015

Background: Previous studies showed differences in healthcare utilization among insurance types. This study aimed to analyze the difference in healthcare utilization for percutaneous transluminal coronary angioplasty inpatients by insurance types after controlling factors affecting healthcare utilization using propensity score matching (PSM). Methods: The 2011 national inpatient sample based on health insurance claims data was used for analysis. PSM was used to control factors influencing healthcare utilization except insurance types. Length of stay and total charges were used as healthcare utilization variables. Patients were divided into National Health Insurance (NHI) and Medical Aid (MA) patients. Factors representing inpatients (gender, age, admission sources, and Elixhauser comorbidity index) and hospitals (number of doctors, number of beds, and location of hospitals) were used as covariates in PSM. Results: Tertiary hospitals didn't show significant difference in length of stay and total charges after PSM between two insurance types. However, MA patients showed significantly longer length of stay than that of NHI patients after PSM in general hospitals. Multivariate regression analysis provided that admission sources, Elixhauser comorbidity index, insurance types, number of doctors, and location of hospitals (province) had significant influences on the length of stay in general hospitals. Conclusion: Study results provided evidences that healthcare utilization was differed by insurance types in general hospitals. Health policy makers will need to prepare interventions to influence the healthcare utilization differences between insurance types.

• Genomics & Informatics
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• v.17 no.4
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• pp.47.1-47.12
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• 2019

The achievements of genome-wide association studies have suggested ways to predict diseases, such as type 2 diabetes (T2D), using single-nucleotide polymorphisms (SNPs). Most T2D risk prediction models have used SNPs in combination with demographic variables. However, it is difficult to evaluate the pure additive contribution of genetic variants to classically used demographic models. Since prediction models include some heritable traits, such as body mass index, the contribution of SNPs using unmatched case-control samples may be underestimated. In this article, we propose a method that uses propensity score matching to avoid underestimation by matching case and control samples, thereby determining the pure additive contribution of SNPs. To illustrate the proposed propensity score matching method, we used SNP data from the Korea Association Resources project and reported SNPs from the genome-wide association study catalog. We selected various SNP sets via stepwise logistic regression (SLR), least absolute shrinkage and selection operator (LASSO), and the elastic-net (EN) algorithm. Using these SNP sets, we made predictions using SLR, LASSO, and EN as logistic regression modeling techniques. The accuracy of the predictions was compared in terms of area under the receiver operating characteristic curve (AUC). The contribution of SNPs to T2D was evaluated by the difference in the AUC between models using only demographic variables and models that included the SNPs. The largest difference among our models showed that the AUC of the model using genetic variants with demographic variables could be 0.107 higher than that of the corresponding model using only demographic variables.

• Health Policy and Management
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• v.26 no.4
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• pp.343-351
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• 2016

Background: This study aims to analyze the effects of insurance types on the medical service uses for heart failure inpatients using propensity score matching (PSM). Methods: 2014 National inpatient sample based on health insurance claims data was used in the analysis. PSM was applied to control factors influencing the service uses except insurance types. Negative binomial regression was used after PSM to analyze factors that had influences on the service uses among inpatients. Subjects were divided by health insurance type, national health insurance (NHI) and medical aid (MA). Total charges and length of stay were used to represent the medical service uses. Covariance variables in PSM consist of sociodemographic characteristics (gender, age, Elixhauser comorbidity index) and hospital characteristics (hospital types, number of beds, location, number of doctors per 50 beds). These variables were also used as independent variables in negative binomial regression. Results: After the PSM, length of stay showed statistically significant difference on medical uses between insurance types. Negative binomial regression provided that insurance types, Elixhauser comorbidity index, and number of doctors per 50 beds were significant on the length of stay. Conclusion: This study provided that the service uses, especially length of stay, were differed by insurance types. Health policy makers will be required to prepare interventions to narrow the gap of the service uses between NHI and MA.

• Journal of the Korean Data and Information Science Society
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• v.27 no.1
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• pp.91-100
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• 2016

Fuzzy matching is proposed to make propensities of two groups similar with their propensity scores and a way to select control variable to make propensity scores with a process that shows how to acquire propensity scores using logic regression analysis, is presented. With such scores, it was a method to obtain an experiment group and a control group that had similar propensity employing the Fuzzy Matching. In the study, it was proven that the two groups were the same but with a different distribution chart and standardization which made edge tolerance different and we realized that the number of chosen cases decreased when the edge tolerance score became smaller. So with the idea, we were able to determine that it is possible to merge groups using fuzzy matching without a precontrol and use them when data (big data) are used while to check the pros and cons of Fuzzy Matching were made possible.

• Journal of the Korea Management Engineers Society
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• v.23 no.4
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• pp.105-123
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• 2018

The purpose of this study is to verify whether the technology grade, which is the result of technology appraisal by Technology Credit Bureau, can be extended and applied to the venture certification system. We confirmed that there was a significant difference in the average financial performance for three years after the certification and appraisal of the two groups after matching the venture certification enterprise group and the technology appraisal enterprise group in 2015 through the propensity score matching method. As a result, there was no significant difference in the financial performance of venture certified firms and technology appraisal firms, so we confirmed that the technology grade can be expanded and applied to the venture certification system. As a result of estimating the technology grade conforming to the venture certification system, it was concluded that technology outstanding firm(T1-T4) is a technology grade suitable for the venture certification system.

• The Korean Journal of Health Service Management
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• v.11 no.3
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• pp.65-78
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• 2017

Objectives : Obesity is a worldwide health concern due to an increasing obese population. This study proposed to analyze the differences in medical costs and care utilization between obese and normal group using propensity score matching. Methods : Data were collected from the sample cohort database by the Korea National Health Insurance Corporation. Propensity score matching(PSM) was applied to control selection bias, and factors affecting obesity were used as covariates in PSM. Results : The results showed higher medical costs and care utilization in the obese group than the normal group. According to gender and medical type, there were differences in the relationships between obesity and medical charges and utilization. In particular, the differences in the female population were larger in both outpatients and inpatients than the male population. Conclusions : It is important to manage obesity, because obesity has a negative effect on national health insurance costs. These findings suggest directions for future research.

• Korean Journal of Health Education and Promotion
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• v.33 no.1
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• pp.61-70
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• 2016

Objectives: It has been well documented that people on the lower socioeconomic position are significantly more likely to smoke cigarettes. The purposes of this study were (a) to identify a potential difference of socioeconomic factors, and (b) to compare a smoking rate, one of the most representative health behavior between people with/without disabilities after the controlling socioeconomic factors. Methods: The Korea Panel Survey of Employment for People of Disabilities (2012) and the Korea National Health and Nutrition Survey (2012) were employed for calculating the smoking rates of persons with/without disabilities. Results: The results demonstrated that the socioeconomic position indicators (education, occupation and household equivalent income) of persons with disabilities were lower than persons without disabilities. The smoking rates of the persons with/without disabilities were 35.9% and 19.0% respectively before propensity score matching. After propensity score matching with the socioeconomic factors, however, ATT of people with disabilities was 0.201 which is lower than ATT of people without disabilities (0.227). Conclusions: Our findings indicated that the socioeconomic level of persons with disabilities is important to improve the smoking rates and health level regardless of their disabilities.

• Journal of Korea Technology Innovation Society
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• v.14 no.3
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• pp.689-710
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• 2011

The purpose of this paper is to positively analyze firms' innovative performance enhanced by cooperation, such as industry-university or industry-government, in service industry. We use PSM method (Propensity Score Matching) based on Korea Innovation Survey data in service industry to investigate it. This empirical study finds that cooperation with university or government partially has positive effects on firm's patent applications and innovation. So, we suggest we need various policies for research institute linkage in service industry.