• Journal of Preventive Medicine and Public Health
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• v.34 no.1
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• pp.21-27
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• 2001

Objectives : To develop a model that will predict the mortality of patients undergoing Coronary Artery Bypass Graft (CABG) and evaluate the perfermance of hospitals. Methods : Data from 564 CABGs peformed in six general hospitals were collected through medical record abstraction by registered nurses. Variables studied involved risk factors determined by severity measures. Risk modeling was performed through logistic repression and validated with cross-validation. The statistical performance of the developed model was evaluated using c-statistic, $R^2$, and Hosmer-Lemeshow statistic. Hospital performance was assessed by severity-adjusted mortalities. Results : The developed model included age, sex, BUN, EKG rhythm, Congestive Heart Failure at admission. acute mental change within 24 hours, and previous angina pectoris history. The c-statistic and $R^2$ were 0.791 and 0.001, respectively. Hosmer-Lemeshow statistic was 10.3(p value=0.2415). One hospital had a significantly higher mortality rate than the average mortality rate, while others were net significantly different. Conclusion : Comparing the quality of service by severity adjusted mortality rates, there were significant differences in hospital performance. The severity adjusted mortality rate of CABG surgery may He an indicator for evaluating hospital performance in Korea.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.1
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• pp.129-136
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• 2019

In this study, we proposed a model for forecasting power energy demand by investigating how outside temperature at a given time affected power consumption and. To this end, we analyzed the time series of power consumption in terms of the power spectrum and found the periodicities of one day and one week. With these periodicities, we investigated two time series of temperature and power consumption, and found, for a given hour, an approximate linear relation between temperature and power consumption. We adopted an exponential smoothing model to examine the effect of the linearity in forecasting the power demand. In particular, we adjusted the exponential smoothing model by using the variation of power consumption due to temperature change. In this way, the proposed model became a mixture of a time series model and a regression model. We demonstrated that the adjusted model outperformed the exponential smoothing model alone in terms of the mean relative percentage error and the root mean square error in the range of 3%~8% and 4kWh~27kWh, respectively. The results of this study can be used to the energy management system in terms of the effective control of the cross usage of the electric energy together with the outside temperature.

• Geotechnical Engineering
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• v.14 no.3
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• pp.47-62
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• 1998

The disturbed state concept (DSC) proposed here is based on the idea that a deforming material element can be treated as a mixture of two constituent parts in the relative intact (Rl) and fully adjusted (FA) states, referred to as reference states. Based on this idea, DSC provides a unified constitutive model for the characteristics of saturated sands under cyclic loading. The model parameters for saturated sands are evaluated by using data from truly triaxial test device, The laboratory test results are also used for the verification of D SC model. In general, the model predictions are found to provide satisfactory correlation with the test results. From the results of this research, it can be stated that the DSC model is capable of characterizing the cyclic behavior of saturated sands under dynamic loading.

• Journal of Sasang Constitutional Medicine
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• v.25 no.3
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• pp.145-157
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• 2013

Objectives This study was aimed to reveal the characteristics of the body shape, face, voice and temperament in Taeyangin. Methods The subjects were recruited from November 2005 to August 2012. Sasang constitutional specialist in each clinics confirmed the Sasang Constitution. Taeyangin (TY) became a standard guidance to be compared with each other Sasang type. Anova test was used in analyzing continuous variables and factor analysis was conducted in temperament questionnaire in advance. Generalized propensity score with age and body mass index (BMI) was used in adjusted model. Significant level was .05 Results 1. The TY body shape were generally smaller than Taeeumin (TE) (p<0.001) and Soyangin (SY) (p<0.05) in crude. The TY body shape were still smaller than TE (p<0.05) and there was no significant difference between TY and SY except rib circumference in males and forehead circumference (p<0.05) in females in adjusted model. 2. The size of face and nose in TY was smaller than in TE and there was different between males and females' TY and others in the characteristics of eye, nose and forehead variables in crude (p<0.05). Most of differences between TY and TE were disappeared in adjusted model. 3. The vocal height and speed of TY was different other types and there was different between males and females' TY in some of frequency change rate in crude (p<0.05). Most of differences between TY and other types were similar before and after adjusted model. 4. The temperament of TY was different with SE before and after adjusted mode 1 (p<0.05). TY males showed difference in expression factor and TY females showed difference in behavior factor compared with TE respectively (p<0.05). Conclusions This study reveals characteristics of body shape, face, voice and character in the TY males females compared with each other type respectively.

• Proceedings of the Korean Society of Surveying, Geodesy, Photogrammetry, and Cartography Conference
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• 2004.04a
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• pp.279-284
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• 2004

This paper presents on adjustment methods of the vendor-provided RPC(Rational Polynomial Coefficient) of GEO-level stereo images for the IKONOS satellite. RPC are adjusted with control points by the first-order polynomial and the block adjustment method in this study. As results, the maximum error of 3D ground coordinates by the adjusted RPC model did not exceed 4m. The block adjustment method is more stability than the first-order polynomial method.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.10
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• pp.751-759
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• 2020

This study examines the impact of mergers on the financial performance of the Jordanian public shareholding companies. The study employs data collected for a sample of 10 Jordanian non-financial public firms that were engaged in legal horizontal merger deals between 2000 and 2013. The data was collected from the published annual financial reports of the merging companies and comparative companies for three years before the merger and three years after the merger. Event study methodology was applied to examine the data. Four measures of financial performance (FP) were used, which are return on assets (ROA), return on equity (ROE), earnings per share (EPS), and net profit margin (NPM). Two methods were used in the analysis - the change model and the intercept model using financial performance raw data and industry-adjusted data. The findings in general showed no significant impact of mergers on the financial performance of merging firms using the change model. However, by using the intercept model, significant impact of mergers on the financial performance was found on the sample of the study. The significant impact was found for mergers on the raw ROE of the merging firms, and on the ROA and NPM of the industry-adjusted firms.

• Quality Improvement in Health Care
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• v.10 no.2
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• pp.164-175
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• 2003

Objectives: To evaluate the performance of models to predict AMI patients death using severity adjustment measures in Korea. Methods: Medical records of 861 patients treated by AMI in 7 general hospitals during 1996 and 1997 were reviewed by trained nurses. We measured the severity of patients by APACHE III, MedisGroups, CSI and DS. Using each severity method a predictive mortality for each patient was calculated from a logistic regression model including the severity score. The statistical performance of each severity method model was evaluated by using c-statistics and R2. For each hospital, z scores compared actual and expected mortality rates. Results: The overall in-hospital mortality was 14.5%, ranged from 10.0% to 22.2%. The distributions of severity scores for each method was significantly different by hospitals. The four severity-adjusted models to predict AMI patients death varied in their statistical performance for discrimination power of patients death. Order of Severity-adjusted mortality rates and z scores by four severity measures was different. Conclusion: Severity-adjusted mortality rates of AMI patients might be applied as an indicator for hospital performance evaluation in Korea. Because different severity methods frequently produce different impressions about relative hospital performance, more studies has to be done to use it as quality indicator and more attention should be paid to select appropriate severity measures.

• Health Policy and Management
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• v.13 no.3
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• pp.129-147
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• 2003

This study is to grasp a trend of profitability classified by characteristics of hospitals and to analyze related factors. Subjects are 145 hospitals which have gotten the standardization audit by Korean Hospital Association during 1998-200l. Profitability was measured in the aspect of operation profit rate with operating margin to gross revenue as proxy variables. Independent variables were classified by general factors (ownership, number of beds, period of establishment, competition), financial factors (liabilities to total assets, current ratio, fixed ratio, total asset turnover, inventories turnover), and factors related to patient treatment (average length of stay, bed occupancy rate, new outpatient ratio, admission ratio of outpatients, number of patients per specialist, personnel costs per adjusted inpatient, administrative costs per adjusted inpatient). Hierarchical multiple regression analysis model was used in this study. As a result of hierarchical multiple regression analyzation of operating margin to gross revenue, adjustive $R^2$ of general factors was relatively more powerful. The factors had significant effect on operating margin to gross revenue were ownership(+), number of beds(+), competition(+), current ratio(+), fixed ratio(+), total asset turnover(+), personnel costs per adjusted inpatient(-).

• Proceedings of the KIEE Conference
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• 2002.07d
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• pp.2216-2218
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• 2002

A system identification is to measure the output in the presence of a adequate input for the controlled system and to estimate the mathematical model in the basic of input output data. In the system identification, it is possible to estimate the true parameter values by the adjusted least squares method in the input-output case of no observed noise, and it is possible to estimate the true parameter values by the total least squares method in the input-output case with the observed noise. In recent the adjusted least squares method is suggested as a consistent estimation method in the system identification not with the observed noise input but with the observed noise output. In this paper we have developed the adjusted least squares method from the least squares method and have made certain of the efficiency in comparing the estimating results with the generating data by the computer simulations.

• Journal of Korea Technology Innovation Society
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• v.19 no.4
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• pp.711-735
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• 2016

Drug Development is very important for promoting public health and pharmaceutical industry. There has been many studies on the efficiency of drug development, but there are few studies on the drug development R&D performed by government. Since CCR model assumes unidirectional influence of input and output, it is not appropriate to analyze the efficiency of R&D due to the time-lag and spill-over effect. Also, BBC model which assumes variable returns to scale has difficulty in deriving priorities between decision making units. Recently, Range Adjusted Measure (RAM) model has been suggested in R&D efficiency analysis. RAM model measures the efficincy by eliminating inefficiencies under variable returns to scale assumption, and its strong monotonicity enables to provide clear priorities between decision making units. In this study, we analyzed the efficiency of national R&D programs for drug development using the two-step approach, including RAM model and Tobit regression analysis, and discussed major policy implications.