• 제목/요약/키워드: Z-Score Model

검색결과 62건 처리시간 0.02초

MedisGroups를 이용한 관상동맥우회술의 중증도 보정사망률에 관한 연구 (Severity-Adjusted Mortality Rates of Coronary Artery Bypass Graft Surgery Using MedisGroups)

  • 권영대
    • 한국의료질향상학회지
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    • 제7권2호
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    • pp.218-228
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    • 2000
  • Background : Among 'structure', 'process' and 'outcome' approaches, outcome evaluation is considered as the most direct and best approach to assess the quality of health care providers. Risk-adjustment is an essential method to compare outcome across providers. This study has aims to judge performance of hospitals by severity adjusted mortality rates of coronary artery bypass graft (CABG) surgery. Methods : Medical records of 584 patients who got the CABG surgery in 6 general hospitals during 1996 and 1997 were reviewed by trained nurses. The MedisGroups was used to quantify severity of patients. The predictive probability of death was calculated for each patient in the sample from a multivariate logistic regression model including the severity score, age and sex. For evaluation of hospital performance, we calculated ratio of observed number to expected number of deaths and z score [(observed number of deaths - expected number of deaths)/square root of the variance in the number of deaths], and compared observed mortality rate with confidence interval of adjusted mortality rate for each hospital. Results : The overall in-hospital mortality was 7.0%, ranged from 2.7% to 15.7% by hospital. After severity adjustment the mortality by hospital was from 2.7% to 10.7%. One hospital with poor performance was distinctly divided from others with good performance. Conclusion : In conclusion, severity-adjusted mortality rate of CABG surgery might be applied as an indicator for hospital performance evaluation in Korea. But more pilot studies and improvement of methodologies has to be done to use it as quality indicator.

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The Impact of Financial Inclusion on Financial Stability in Asian Countries

  • PHAM, Manh Hung;DOAN, Thi Phuong Linh
    • The Journal of Asian Finance, Economics and Business
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    • 제7권6호
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    • pp.47-59
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    • 2020
  • This paper intends to explore the relationship between financial inclusion and financial stability under the scope of Asian economies. The linkage will be thoroughly investigated with country-level and bank-level data of 42 countries in three separate years: 2011, 2014, and 2017. In this study, an inclusive financial system is assessed by two dimensions: usage of financial services and access to the financial system. Usage of financial services ranges from account to credit, savings and payment services. Access to financial system measures the financial outreach where individuals can use financial services. Meanwhile, financial stability, which proxied by Bank Z-score is regarded as the dependent variable. We apply fixed effects regression and random effects regression to capture the impacts of financial inclusion upon financial stability. To enhance the robustness of the model, the Feasible Generalized Least Squares (FGLS) regression is therefore adopted as the solution for the random effects regression. The empirical findings exhibit an overall weak positive influence of financial inclusion on financial stability. The research results also provide both financial institutions and governments with insightful information, which helps them to have an appropriate financial development strategy, improve the regulatory framework and consequently enhance financial stability for the whole system.

우리나라 광역시 도시압축성 평가에 관한 연구 (A Study on the Urban Compactness Evaluation of Korean Metropolises)

  • 이일희;이주형
    • 한국산학기술학회논문지
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    • 제13권7호
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    • pp.3224-3231
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    • 2012
  • 통합적이고 객관화된 도시압축성 평가방법에 대한 연구가 필요하다. 이를 위하여 압축도시(compact city)와 관련된 문헌 등 선행연구를 통하여 도시압축성 평가요소를 추출하였다. 이렇게 설정된 평가요소는 전문가조사를 통한 객관화 과정과 AHP계층구조모형을 통하여 평가요소별로 가중치를 결정한다. 이러한 평가분석의 틀을 토대로 우리나라 6대 광역시의 도시압축성을 평가하고 표준점수(z-score)화하여 상대적인 차이를 분석하고자 하였다. 이러한 분석결과는 압축도시에 대한 정책 결정에 필요한 기본 자료로서 구도심의 도시재생 등 압축도시계획에 활용될 수 있을 것이다.

Bankruptcy Risk and Income Smoothing Tendency of NBFIs in Bangladesh

  • JABIN, Shahima;SUMONA, Shohana Islam
    • Asian Journal of Business Environment
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    • 제11권2호
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    • pp.27-38
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    • 2021
  • Purpose: The study mainly investigates bankruptcy risk and income smoothing tendency of Non-Banking Financial Institutions (NBFIs) in Bangladesh. External parties of NBFIs take investment decisions based on financial reports. Stable and predictable income is one of their preference. On the other hand, poor income is one of the signs of NBFIs having bankruptcy risk. Hence the study tries to find whether the NBFIs having bankruptcy are involved in income smoothing or not. Research design, data and methodology: Data were collected from the annual report of twenty-two listed NBFIs in Bangladesh. Data from 2013 to 2017 were used. Altman's Z score and Eckel's model are used to detecting bankruptcy risk and income smoothing respectively. Results: Result implies that most of the NBFIs which have bankruptcy risk are not involved in income smoothing. Therefore, NBFIs which has bankruptcy risk are involved less with income smoothing. Conclusions: The present study revealed that most of the listed NBFIs in Bangladesh are facing bankruptcy risk. They didn't use any fraudulent technique to show smooth income. The findings will help the investor to take an investment decision on NBFIs in Bangladesh. It will convey signals to the stock market in Bangladesh.

갑상선 초음파 영상의 평활화 알고리즘에 따른 U-Net 기반 학습 모델 평가 (Evaluation of U-Net Based Learning Models according to Equalization Algorithm in Thyroid Ultrasound Imaging)

  • 정무진;오주영;박훈희;이주영
    • 대한방사선기술학회지:방사선기술과학
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    • 제47권1호
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    • pp.29-37
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    • 2024
  • This study aims to evaluate the performance of the U-Net based learning model that may vary depending on the histogram equalization algorithm. The subject of the experiment were 17 radiology students of this college, and 1,727 data sets in which the region of interest was set in the thyroid after acquiring ultrasound image data were used. The training set consisted of 1,383 images, the validation set consisted of 172 and the test data set consisted of 172. The equalization algorithm was divided into Histogram Equalization(HE) and Contrast Limited Adaptive Histogram Equalization(CLAHE), and according to the clip limit, it was divided into CLAHE8-1, CLAHE8-2. CLAHE8-3. Deep Learning was learned through size control, histogram equalization, Z-score normalization, and data augmentation. As a result of the experiment, the Attention U-Net showed the highest performance from CLAHE8-2 to 0.8355, and the U-Net and BSU-Net showed the highest performance from CLAHE8-3 to 0.8303 and 0.8277. In the case of mIoU, the Attention U-Net was 0.7175 in CLAHE8-2, the U-Net was 0.7098 and the BSU-Net was 0.7060 in CLAHE8-3. This study attempted to confirm the effects of U-Net, Attention U-Net, and BSU-Net models when histogram equalization is performed on ultrasound images. The increase in Clip Limit can be expected to increase the ROI match with the prediction mask by clarifying the boundaries, which affects the improvement of the contrast of the thyroid area in deep learning model learning, and consequently affects the performance improvement.

일반 장면의 정규분포 분석을 기반으로 한 화질 측정 모형 (Image Quality Assessment Model of Natural Scene Based on Normal Distribution Analysis)

  • 박형주;하동환
    • 감성과학
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    • 제16권3호
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    • pp.373-386
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    • 2013
  • 본 연구에서는 이미지 감상자가 선호하는 화질의 객관적 평가 항목들의 범위를 구체화하고 실제 이미지를 기반으로 화질의 선호도를 측정하는 방식을 따랐다. 즉, 무기준법(No-Reference)을 기반으로 하고 화질 평가 요소를 다이내믹 레인지, 컬러, 콘트라스트로 규정하였다. 샘플 사진 수집은 인터넷 갤러리에서 추천수 30회 이상을 기준으로 감상자들이 선호하는 풍경사진 200장의 이미지를 선정하였다. 그리고 세 가지 객관적 화질 평가 항목에 의한 정규분포분석을 통하여 총점을 백점 기준으로 환산하여 최종적으로 예상되는 화질의 선호도를 측정하였다. 본 실험에서 적용한 실제 사진 샘플의 다이내믹 레인지 측정값은 10 stop, LAB 평균은 L:54.7, A:2.96, B:-15.84, RSC 콘트라스트는 376.9로 나타났다. 총 200장 샘플 사진의 정규분포 z값은 다이내믹 레인지가 0.21, LAB 평균이 LAB 평균이 L:0.15, A:0.38, B:0.13, RSC 콘트라스트가 0.08을 나타냈다. 표준정규분포 표에서 위의 z값이 나타날 확률을 상위 백분율로 나타내면 실제 사진 샘플의 다이내믹 레인지는 8.32%, LAB 평균은 LAB 평균은 L:5.96%, A:14.8%, B:5.17%, RSC 콘트라스트는 3.19%를 나타낸다. 즉 화질 평가 모형에 사용된 실제 사진 샘플의 상위 백분율을 100점으로 환산한 다이내믹 레인지는 91.68점, LAB 평균은 91.36점, RSC 콘트라스트는 96.81점이다. 따라서 세 가지 객관적 화질 평가 항목에 의한 총점의 평균은 94.99점으로 나타낼 수 있었다. 즉 본 연구에서 제안한 화질 측정 모형을 통하여 실제 사진 샘플에 대한 선호도를 수치적으로 측정할 수 있었다. 이와 같은 연구를 통하여 이미지 감상자가 선호하는 화질의 재현 성능 범위를 구체화하고 예상되는 화질의 선호도를 수치화하는 실용적인 연구 결과를 제안하였다.

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머신러닝 기반 MMS Point Cloud 의미론적 분할 (Machine Learning Based MMS Point Cloud Semantic Segmentation)

  • 배재구;서동주;김진수
    • 대한원격탐사학회지
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    • 제38권5_3호
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    • pp.939-951
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    • 2022
  • 자율주행차에 있어 가장 중요한 요소는 차량 주변 환경과 정확한 위치를 인식하는 것이며, 이를 위해 다양한 센서와 항법 시스템 등이 활용된다. 하지만 센서와 항법 시스템의 한계와 오차로 인해 차량 주변 환경과 위치 인식에 어려움이 있다. 이러한 한계를 극복하고 안전하고 편리한 자율주행을 위해서 고정밀의 인프라 정보를 제공하는 정밀도로지도(high definition map, HD map)의 필요성은 증대되고 있다. 정밀도로지도는 모바일 매핑 시스템(mobile mapping system, MMS)을 통해 획득된 3차원 point cloud 데이터를 이용하여 작성된다. 하지만 정밀도로지도 작성에 많은 양의 점을 필요로 하고 작성 항목이 많아 수작업이 요구되어 많은 비용과 시간이 소요된다. 본 연구는 정밀도로지도의 필수 요소인 차선을 포함한 도로, 연석, 보도, 중앙분리대, 기타 6개의 클래스로 MMS point cloud 데이터를 유의미한정보로 분할하여 정밀도로지도의 효율적인 작성에 목적을 둔다. 분할에는 머신러닝 모델인 random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN) 그리고 gradient boosting machine (GBM)을 사용하였고 MMS point cloud 데이터의 기하학적, 색상, 강도 특성과 차선 분할을 위해 추가한 도로 설계적 특성을 고려하여 11개의 변수를 선정하였다. 부산광역시 미남역 일대 5차선도로 130 m 구간의 MMS point cloud 데이터를 사용하였으며, 분할 결과 각 모델의 평균 F1 score는 RF 95.43%, SVM 92.1%, GBM 91.05%, KNN 82.63%로 나타났다. 가장 좋은 분할 성능을 보인 모델은 RF이며 클래스 별 F1 score는 도로, 보도, 연석, 중앙분리대, 차선에서 F1 score가 각각 99.3%, 95.5%, 94.5%, 93.5%, 90.1% 로 나타났다. RF 모델의 변수 중요도 결과는 본 연구에서 추가한 도로 설계적 특성의 변수 XY dist., Z dist. 모두 mean decrease accuracy (MDA), mean decrease gini (MDG)가 높게 나타났다. 이는 도로 설계적 특성을 고려한 변수가 차선을 포함한 여러 클래스 분할에 중요하게 작용하였음을 뜻한다. 본 연구를 통해 MMS point cloud를 머신러닝 기반으로 차선을 포함한 여러 클래스로 분할 가능성을 확인하고 정밀도로지도 작성 시 수작업으로 인한 비용과 시간 소모를 줄이는데 도움이 될 것으로 기대한다.

GIS 기반 연안 용도해역 적성평가 방안 (GIS-Based Suitability Assessment Plan of Coastal Zoning System)

  • 이근상;임승현
    • 한국지리정보학회지
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    • 제16권2호
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    • pp.75-87
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    • 2013
  • 본 연구에서는 정부의 연안용도해역제 법제화에 따른 실질적인 용도해역 분류에 필요한 GIS 기반의 연안해역 적성평가 모형을 개발하였다. 먼저 본 연구에서는 연안지역과 관련된 여러 가지 법규, GIS 데이터베이스 그리고 활용시스템을 조사하였다. 또한 용도해역 적성평가 지표들을 계산하기 위한 GIS 분석 모델은 격자자료 모델을 선정하였으며, 물리적 특성을 비롯한 해역 및 공간적 입지특성을 구성하는 지표들을 계산하기 위한 격자 기반의 분석 기법을 제시하였다. 지표들의 임계치는 연안관련 법규와 토지적성평가에서 제안된 기준들을 이용하여 제시하였으며, 특히 GIS 자료의 특성을 반영하기 위해 퍼지함수와 같은 연속적인 형태의 산정 기법을 제시하였다. 그리고, 본 연구에서는 표준화점수를 이용하여 적성등급을 구분하고, 이로부터 보전관리우선해역, 이용관리우선해역 그리고 계획관리우선해역을 지정하는 모형을 개발하였다. 본 연구에서 제시된 연안 용도해역 적성평가 모형이 실무에 적용될 때, 대상지역의 공간적 범위와 GIS 데이터베이스를 고려한다면 매우 효과적인 업무 수행이 가능해질 것으로 판단된다.

Evidence-based customized nutritional intervention improves body composition and nutritional factors for highly-adherent children and adolescents with moderate to severe obesity

  • Kim, Jieun;Kim, YoonMyung;Seo, Young-Gyun;Park, Kyung-Hee;Jang, Han Byul;Lee, Hye-Ja;Park, Sang Ick;Lim, Hyunjung
    • Nutrition Research and Practice
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    • 제14권3호
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    • pp.262-275
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    • 2020
  • BACKGROUND/OBJECTIVES: Evidence-based customized nutritional interventions are required for effective treatment of moderate to severe obese children and adolescents. SUBJECTS/METHODS: Sixty six (64.1% of 103) of the eligible participants who joined the usual care or physical activity group in the clinic were involved in 16-week intervention. Customized nutritional intervention was implemented for each participant based on a nutrition care process (NCP) model. Sociodemographic assessment, anthropometrics data, health- and dietary-related behaviors, and dietary intake of the study subjects were assessed at baseline and follow-up. All participants engaged in 30-minute nutritional sessions on a monthly basis. RESULTS: After 16 weeks, there were significant improvements in body composition [BMI (-0.8 ± 0.9, P < 0.05), BMI z-score (-0.3 ± 0.2, P < 0.001), body fat (kg) (-1.3 ± 2.1, P < 0.05), and body fat (%)(-1.5 ± 1.9, P < 0.05)] as well as macronutrient intake [total energy intake (kcal) (-563.7 ± 656.8, P < 0.05), energy (%) (-26.5 ± 30.0, P < 0.05) and fat (g) (-28.3 ± 40.6, P < 0.05)] in the adherent group than the non-adherent group. The SOC was higher in both groups after the intervention (P < 0.001). CONCLUSIONS: Our results highlight the positive effects of an evidence-based approach as a multidisciplinary intervention for people-centered nutritional care and weight management.

Factors associated with Advanced Bone Age in Overweight and Obese Children

  • Oh, Min-Su;Kim, Sorina;Lee, Juyeon;Lee, Mu Sook;Kim, Yoon-Joo;Kang, Ki-Soo
    • Pediatric Gastroenterology, Hepatology & Nutrition
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    • 제23권1호
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    • pp.89-97
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    • 2020
  • Purpose: Obese children may often present with advanced bone age. We aimed to evaluate the correlation between factors associated with childhood obesity and advanced bone age. Methods: We enrolled 232 overweight or obese children. Anthropometric and laboratory data, and the degree of nonalcoholic fatty liver disease (NAFLD) were measured. We analyzed factors associated with advanced bone age by measuring the differences between bone and chronological ages. Results: The normal and advanced bone age groups were comprised of 183 (78.9%) and 49 (21.1%) children, respectively. The prevalence of advanced bone age significantly increased as the percentiles of height, weight, waist circumference, and body mass index (BMI) increased. BMI z-score was higher in the advanced bone age group than in the normal bone age group (2.43±0.52 vs. 2.10±0.46; p<0.001). The levels of insulin (27.80±26.13 μU/mL vs. 18.65±12.33 μU/mL; p=0.034) and homeostatic model assessment-insulin resistance (6.56±6.18 vs. 4.43±2.93; p=0.037) were significantly higher, while high density lipoprotein-cholesterol levels were lower (43.88±9.98 mg/dL vs. 48.95±10.50 mg/dL; p=0.005) in the advanced bone age group compared to those in the normal bone age group, respectively. The prevalence of advanced bone age was higher in obese children with metabolic syndrome than in those without (28.2% vs. 14.7%; p=0.016). The prevalence of advanced bone age was higher in obese children with a more severe degree of NAFLD. Conclusion: Advanced bone age is associated with a severe degree of obesity and its complications.