전국민 기반 후향 연구

학위논문 (석사)-- 서울대학교 대학원 : 행정대학원 행정학과(정책학전공), 2018. 8. Jorg Michael Dostal.Generally, socioeconomically disadvantaged populations have a different health status. Their access to medical facility and health information are more restricted than the case of the general populations. If this disparity is accumulated for decades, it can affect the mortality and diseases epidemiology. Based on these results, vulnerable groups request a different health policy for themselves. However, there are not many nationwide researches for their actual health conditions. That means that rational and proper health policy cannot be established due to absence of these data. The Korean government has been operating a national health insurance system for about 40 years. Today, this policy covers every single person residing in Korea for a period of at least one month. Due to this system, big data on national health has been built up electronically on a large scale. National health insurance offers three types of insurance programs for (1) the general population, (2) the medical aid group, (3) the patriots and wounded veterans groups. Among them, the medical aid group, patriots and wounded veterans groups could be defined as vulnerable population. Until now, there is no research on epidemiology and medical expense of vulnerable groups through nationwide health big data. Thus, the current dissertation conducts research on the frequency of each disease in vulnerable groups through big data analysis. This research can suggest more elaborate health policy for the vulnerable groups. The health status of the last two groups was markedly different from the general population. The frequency of inflammatory infectious disease observed as the most common disease in general population decreased, and senile disorders such as chronic medical illness generally increased in vulnerable populations. Furthermore, the most common five diseases group in patriots and wounded veterans group were totally differenthypertension, benign prostate hyperplasia, diabetes mellitus, gingivitis and periodontitis, and angina pectoris. With regard to medical expenses, the largest part of the budget was spent on the musculoskeletal disease group in the general population. Secondly, mental disorders such as schizophrenia and dementia consumed the largest portion in the medical aid group. Thirdly, chronic medical illnesses such as diabetes mellitus, angina pectoris, chronic kidney disease are the major medical expense items in patriots and wounded veterans. This situation might be due to the ageing phenomenon within the veterans group. Regarding differences in the health status between the three groups, they require delicate health policies such as the expansion of health security system, health care delivery system based on integrated primary complex intervention, mobile health and home care based on the high-tech technology, the globalization of health care policy, sustainable finding of the neglected class. The present study has the following limitationWe could not control other independent variable such as age, sex, chart review and laboratory findings. Moreover, we excluded non-insurance coverage health care and extreme poverty groups. Uncertainty of entered diagnostic codes could be another limitation because of health insurance coverage system. However, this study is the first big data study of the nationwide population based on retrospective analysis about the frequency of diseases in vulnerable groups. Thus, as the complete enumeration, it offers higher reliability and validity in comparison to single or multi - center sample studies. Henceforth, it provides fundamental information for more practical study founded on social class and each specific disease.Abstract 1 Table of Contents 3 List of Tables and Figures 5 Chapter 1. Introduction 7 1.1 Health care as public policy 1.2 The inequality of health problem across social classes 1.3 Ageing phenomenon 1.4 Health supporting policy for vulnerable groups under the present circumstances 1.5 Purpose of the research 1.6 Research questions 1.7 Hypothesis of the research Chapter 2. Literature review 15 2.1 Comparative health policy 2.2 Categorization of health care system 2.3 The introduction of the Korean National Health Insurance system 2.4 Emerging financial problem in the health care 2.5 The features of health information in medically poor group 2.6 Actual health and socioeconomic conditions of patriots and wounded veterans in Korea Chapter 3. Materials and Methods 21 3.1 Data source and study design 3.2 Study populations 3.3 The frequency of each disease and a comparison with a general population 3.4 A comparison of each groups total medical expenses 3.5 Statistical analysis Chapter 4. Results 24 4.1 The prevalent diseases of the general population 4.2 The prevalent diseases of the medical aid group 4.3 The prevalent diseases of the patriots and wounded veterans group 4.4 A comparison of each groups frequent diseases 4.5 The variable patterns of significant diseases over five years 4.6 A comparison of total required medical expenses in three groups Chapter 5. Discussions 47 5.1 Definition and socioeconomic characteristics of vulnerable populations 5.2 Different health status of two vulnerable populations(1) the medical aid group, (2) the patriots and wounded veterans group 5.3 Medical expenses depending on the social class and disease severity 5.4 Current condition of health support for vulnerable population 5.5 Policy implication for the future 5.6 The limitations and strength of this study Chapter 6. Conclusions 57 Bibliography 58 국문초록 61Maste

The Effect of Age at First Calving and Calving Interval on Productive Life and Lifetime Profit in Korean Holsteins

This study was performed to estimate the effect of age at first calving and first two calving intervals on productive life and life time profit in Korean Holsteins. Reproduction data of Korean Holsteins born from 1998 to 2004 and lactation data from 276,573 cows with birth and last dry date that calved between 2000 and 2010 were used for the analysis. Lifetime profit increased with the days of life span. Regression of Life Span on Lifetime profit indicated that there was an increase of 3,800 Won (approximately $3.45) of lifetime profit per day increase in life span. This is evidence that care of each cow is necessary to improve net return and important for farms maintaining profitable cows. The estimates of heritability of age at first calving, first two calving intervals, days in milk for lifetime, lifespan, milk income and lifetime profit were 0.111, 0.088, 0.142, 0.140, 0.143, 0.123, and 0.102, respectively. The low heritabilities indicated that the productive life and economical traits include reproductive and productive characteristics. Age at first calving and interval between first and second calving had negative genetic correlation with lifetime profit (−0.080 and −0.265, respectively). Reducing age at first calving and first calving interval had a positive effect on lifetime profit. Lifetime profit increased to approximately 2,600,000 (2,363.6) from 800,000 Won ($727.3) when age at first calving decreased to (22.3 month) from (32.8 month). Results suggested that reproductive traits such as age at first calving and calving interval might affect various economical traits and consequently influenced productive life and profitability of cows. In conclusion, regard of the age at first calving must be taken with the optimum age at first calving for maximum lifetime profit being 22.5 to 23.5 months. Moreover, considering the negative genetic correlation of first calving interval with lifetime profit, it should be reduced against the present trend of increase

Genetic Parameters of Milk β-Hydroxybutyric Acid and Acetone and Their Genetic Association with Milk Production Traits of Holstein Cattle

This study was conducted to estimate the genetic parameters of β-hydroxybutyrate (BHBA) and acetone concentration in milk by Fourier transform infrared spectroscopy along with test-day milk production traits including fat %, protein % and milk yield based on monthly samples of milk obtained as part of a routine milk recording program in Korea. Additionally, the feasibility of using such data in the official dairy cattle breeding system for selection of cows with low susceptibility of ketosis was evaluated. A total of 57,190 monthly test-day records for parities 1, 2, and 3 of 7,895 cows with pedigree information were collected from April 2012 to August 2014 from herds enrolled in the Korea Animal Improvement Association. Multi-trait random regression models were separately applied to estimate genetic parameters of test-day records for each parity. The model included fixed herd test-day effects, calving age and season effects, and random regressions for additive genetic and permanent environmental effects. Abundance of variation of acetone may provide a more sensitive indication of ketosis than many zero observations in concentration of milk BHBA. Heritabilities of milk BHBA levels ranged from 0.04 to 0.17 with a mean of 0.09 for the interval between 4 and 305 days in milk during three lactations. The average heritabilities for milk acetone concentration were 0.29, 0.29, and 0.22 for parities 1, 2, and 3, respectively. There was no clear genetic association of the concentration of two ketone bodies with three test-day milk production traits, even if some correlations among breeding values of the test-day records in this study were observed. These results suggest that genetic selection for low susceptibility of ketosis in early lactation is possible. Further, it is desirable for the breeding scheme of dairy cattle to include the records of milk acetone rather than the records of milk BHBA

Population health outcomes in South Korea 1990-2019, and projections up to 2040: a systematic analysis for the Global Burden of Disease Study 2019

BACKGROUND: South Korea has one of the longest operating universal health coverage (UHC) systems. A comprehensive analysis of long-term trajectories of morbidity and mortality in the South Korean population after the inception of UHC is needed to inform health-care policy and practice. METHODS: We used data from the Global Burden of Disease Study (GBD) 2019 to present estimates of cause-specific mortality, incidence, prevalence, years of life lost (YLLs), years of life lived with disability, and disability-adjusted life-years (DALYs) in South Korea from 1990 to 2019. We also examined forecasted estimates of YLLs up to 2040 to investigate likely future changes in disease burden. Finally, we evaluated GBD estimates from seven comparator countries to place disease burden in South Korea within a broader context. FINDINGS: Age-standardised DALYs related to non-communicable diseases (NCDs) decreased by 43·6% (95% uncertainty interval [UI] 39·4-47·9) and mortality by 58·8% (55·9-60·5) from 1990 to 2019. In 2019, the ratio of male to female age-standardised rates of YLLs in South Korea was higher than the global average for 75·9% (22 of 29 diseases) of leading causes, indicating a disproportional disease burden on males in South Korea. Among risk factors, tobacco use accounted for the highest number of 2019 deaths (44 470 [95% UI 37 432-53 989]) in males and high systolic blood pressure for the highest number (21 014 [15 553-26 723]) in females. Among the top ten leading causes of YLLs forecast in South Korea in 2040, nine were NCDs, for both males and females. INTERPRETATION: Our report shows a positive landscape of population health outcomes in South Korea following the establishment of UHC. However, due in part to the effects of population ageing driving up medical expenditures for NCDs, financial pressures and sustainability challenges associated with UHC are pressing concerns. Policy makers should work to tackle population ageing and allocate resources efficiently by prioritising interventions that address the leading causes of death and disability identified in this study. FUNDING: Bill & Melinda Gates Foundation

Probabilistic Ship Detection and Classification Using Deep Learning

For an autonomous ship to navigate safely and avoid collisions with other ships, reliably detecting and classifying nearby ships under various maritime meteorological environments is essential. In this paper, a novel probabilistic ship detection and classification system based on deep learning is proposed. The proposed method aims to detect and classify nearby ships from a sequence of images. The method considers the confidence of a deep learning detector as a probability; the probabilities from the consecutive images are combined over time by Bayesian fusion. The proposed ship detection system involves three steps. In the first step, ships are detected in each image using Faster region-based convolutional neural network (Faster R-CNN). In the second step, the detected ships are gathered over time and the missed ships are recovered using the Intersection over Union of the bounding boxes between consecutive frames. In the third step, the probabilities from the Faster R-CNN are combined over time and the classes of the ships are determined by Bayesian fusion. To train and evaluate the proposed system, we collected thousands of ship images from Google image search and created our own ship dataset. The proposed method was tested with the collected videos and the mean average precision increased by 89.38 to 93.92% in experimental results

Design and Performance Evaluation of an Electro-Hydraulic Camless Engine Valve Actuator for Future Vehicle Applications

This paper details the new design and dynamic simulation of an electro-hydraulic camless engine valve actuator (EH-CEVA) and experimental verification with lift position sensors. In general, camless engine technologies have been known for improving fuel efficiency, enhancing power output, and reducing emissions of internal combustion engines. Electro-hydraulic valve actuators are used to eliminate the camshaft of an existing internal combustion engines and used to control the valve timing and valve duration independently. This paper presents novel electro-hydraulic actuator design, dynamic simulations, and analysis based on design specifications required to satisfy the operation performances. An EH-CEVA has initially been designed and modeled by means of a powerful hydraulic simulation software, AMESim, which is useful for the dynamic simulations and analysis of hydraulic systems. Fundamental functions and performances of the EH-CEVA have been validated through comparisons with experimental results obtained in a prototype test bench

Relative importance of major job performance dimensions in determining supervisors' overall job performance ratings

This study explores the factor structure of job performance and each performance dimension's relative importance in determining supervisors' overall job performance ratings. We found that the optimal factor structure of job performance includes five dimensions: task performance, organizational citizenship behaviour directed toward the organization and individuals (OCB‐O and OCB‐I, respectively), and counterproductive work behaviour directed toward the organization and individuals (CWB‐O and CWB‐I, respectively). The percent‐based relative weight (%RW) is the highest for task performance in determining job performance, followed by OCB and CWB. Interestingly, the %RW of non‐task performance dimensions directed toward the organization (OCB‐O and CWB‐O) is similar to the %RW of task performance but greater than the %RW of non‐task performance dimensions directed toward individuals (OCB‐I and CWB‐I)

Ro 90-7501 inhibits PP5 through a novel, TPR-dependent mechanism

Protein phosphatase 5 (PP5) is a serine/threonine phosphatase that belongs to the PPP family phosphatases. PP5 and the other phosphatases of the PPP family share significantly similar catalytic domain structure. Due to this structural similarity, natural competitive inhibitors such as okadaic acid and cantharidin exhibit broad specificity over the PPP family phosphatases. In this study, we report the identification of three PP5 inhibitors, Ro 90-7501, aurothioglucose, and N-oleoyldopamine, along with a novel inhibitory mechanism of Ro 90-7501. Unlike other inhibitors binding to the phosphatase domain, Ro 90-7501 inhibited PP5 in a TPR-dependent manner. This TPR-dependent PP5 inhibition shown by Ro 90-7501 is a unique and novel inhibitory mechanism, which might be a useful tool for studies of PP5 on both regulatory mechanism and drug discovery. (C) 2016 Elsevier Inc. All rights reserved.OAIID:RECH_ACHV_DSTSH_NO:T201725797RECH_ACHV_FG:RR00200001ADJUST_YN:EMP_ID:A076390CITE_RATE:2.559DEPT_NM:화학생물공학부EMAIL:[email protected]_YN:YN

Modelling localized charge-injection region of the p-channel low-temperature polycrystalline silicon thin-film transistor

The low-temperature polycrystalline silicon (LTPS) thin-film transistor (TFT) is the optimal device for the backplane of the organic light-emitting diode display. At the end the p-channel LTPS TFT fabrication, a charge-injection stress with a strong negative drain bias and a positive gate bias are applied to reduce the off-current by injecting electrons into the gate insulator near the drain. In this study, the charge density and the length of the charge-injection region in the gate insulator were estimated by comparing the measured TFT characteristics with the simulation models with various charge-injection lengths and charge densities. It was found that the effective length of the charge-injection region was 0.96 µm and the charge density was −3 × 1012/cm2 for the 2-µm-channel-length device when VGS was +20 V and VDS was −10 V under the charge-injection stress condition. It was also found, based on the analysis of the electric field distribution under the bias stress condition, that the charge density and the length of the charge-injection region were invariant against the channel length variation. Therefore, the measured TFT characteristics also accorded closely with the simulation models for different channel lengths, such as 4 and 10 µm, when the same characteristic values of the charge-injection region were employed

Development of prediction model for body weight and energy balance indicators from milk traits in lactating dairy cows based on deep neural networks

To develop a body weight (BW) prediction model using milk production traits and present a useful indicator for energy balance (EB) evaluation in dairy cows. Data were collected from 30 Holstein cows using an automatic milking system. BW prediction models were developed using multiple linear regression (MLR), local regression (LOESS), and deep neural networks (DNN). Milk production traits readily available on commercial dairy farms, such as energy-corrected milk (ECM), fat-to-protein ratio, days in milk (DIM), and parity, were used as input variables for BW prediction. The EB was evaluated as the difference between energy intake and energy demand. The DNN model showed the greatest predictive accuracy for BW compared with the LOESS and MLR models. The BW predicted using the DNN model was used to calculate the energy demand. Our results revealed that the day on which the EB status transitioned from negative to positive differed among cows. The cows were assigned to one of the three EB index groups. EB index 1 indicated that the day of EB transition was within DIM ≤ 70. The EB indexes 2 and 3 were 70 < DIM ≤ 140 and 140 < DIM ≤ 305, respectively. EB index 3 had the lowest EB, which is the slowest to transition from a negative to a positive energy balance compared with EB indexes 1 and 2. The highest ECM and feed efficiency were observed for EB index 3. The calving interval was the shortest for EB index 1. EB of individual cows during lactation can be estimated and monitored with moderately high accuracy using EB indexes