• Quality Improvement in Health Care
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• v.7 no.2
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• pp.204-216
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• 2000

Background : There has been a concern that the quality of care provided to end-stage renal disease (ESRD) patients in the United States may not be as good as recommended. This paper illustrates a composite measure to assess, the quality of care received by ESRD patients undergoing in-center hemodialysis by incorporating outcomes for 4 major treatment areas. The 4 treatment areas are: dialysis treatments, anemia control, nutritional management, and blood pressure control. Methods : The major data source for the study was the United States Renal Data System (USRDS) Dialysis Morbidity and Mortality Study Wave 1 (DMMS-1) d Sixteen categories of a composite quality indicator were constructed by combining 4 dichotomous variables (16=2*2*2*2). representing the optimal vs. less than optimal level of outcome for each of the 4 treatment outcome measure respectively. Optimal outcome level for each treatment area was defined based on the recommendation from the National Kidney Foundation: (a) delivered dialysis doses (Kt/V) ${\geq}$ 1.2; (b) hematocrit level ${\geq}$ 30%; (c) serum albumin concentration ${\geq}$ 3.8g/dl ; and (d) blood pressure of <140 / <90mmHg. The 16 quality indicator were ranked according to their relative quality weights, which were estimated from its association with the relative risk of survival, adjusting for patient's baseline severity and dialysis facility characteristics. Results : Out of the entire sample of 2,179 patients, only 229 (10%) meet th recommended outcome levels for all 4 treatment areas. Overall, the study patients were distributed evenly over the 16 quality indicators, indicating a great variation in the quality of ESRD care. It appears that the rank of the 16 quality-indicators is driven by serum albumin concentration, suggesting that serum albumin concentration may be the most powerful predictor of ESRD patient survival among the 4 outcome measures. Conclusion : The developed quality indicator has the advantage of describin a range of care for dialysis patients and thus providing a more complete picture of care as compared to previous studies that have focused on only single or few components of the ESRD care.

• Steel and Composite Structures
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• v.29 no.1
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• pp.139-149
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• 2018

In this paper a new multi-step damage detection approach is provided. In the first step, condensed modal residual vector based indicator (CMRVBI) has been proposed to locate the suspected damaged elements of structures that have rotational degrees of freedom (DOFs). The CMRVBI is a new indicator that uses only translational DOFs of the structures to localize damaged elements. In the next step, salp swarm algorithm is applied to quantify damage severity of the suspected damaged elements. In order to assess the performance of the proposed approach, a numerical example including a three-layer square laminated composite plate is studied. The numerical results demonstrated that the proposed CMRVBI is effective for locating damage, regardless of the effect of noise. The efficiency of proposed approach is also compared during both steps. The results demonstrate that in noisy condition, the damage identification approach is capable for the studied structure.

• Journal of Korea Technology Innovation Society
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• v.9 no.1
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• pp.26-51
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• 2006

Recently technology commercialization has been the focus of technology Promotion Policy in Korea. This paper tries to develop a composite indicator for measuring trends and prospects of national technology commercialization through integrating large amount of information into easily understood formats. The indicator is composed of five sector indicators including activity, cooperation or networking, performance, environment, and psychology indicators, each of which aggregates five individual variables. The statistical method of standardizing and weighting variables in the aggregation process are also mentioned. This indicator is expected to be a useful monitoring and policy tool for the Korean technology market.

• Journal of Labour Economics
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• v.37 no.1
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• pp.87-116
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• 2014

Forecasting of short-term employment fluctuations provides a useful tool for policy makers in risk managing the labor market. Following the process of producing the composite leading indicator for macro economy, the paper develops the employment leading indicator(ELI) for the purpose of short-term forecasting non-farm payroll employment in private sectors. ELI focuses on early detecting the point of time and the speed in phase change of employment level.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.745-758
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• 2011

An Economic Sentiment Indicator(ESI) is a composite indicator of business survey indices(BSI) and consumer survey indices(CSI). The ESI designed to reflect economic agents' (this includes producers and consumers) overall perceptions of economic activity in a one-dimensional index. The European Commission has published an ESI since 1985. This paper demonstrates the construction of an ESI for the Korean economy. The BSI and CSI components (having a high correlation and a leading feature with respect to GDP) are selected to construct the ESI and they are aggregated using a weighted average and then scaled to have a long-term average of 100 and a standard deviation of 10. Thus values greater than 100 indicate an above-average economic sentiment and vice versa. The newly constructed Korean ESI that extends to January 2003 shows a good tracking performance of GDP and adequately reflects the overall perception of economic activity.

• Steel and Composite Structures
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• v.24 no.4
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• pp.391-397
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• 2017

With the increasing application of explosive composite structure in many engineering fields, its interface bonding state detection is more and more significant to avoid catastrophic accidents. However, this task still faces challenges due to the complexity of the bonding interface. In this paper, the concept of nonlinear output frequency response functions (NOFRFs) is introduced to detect the bonding state of explosive composite structure. The NOFRFs can describe the nonlinear characteristics of nonlinear vibrating system. Because of the presence of the bonding interface, explosive composite structure itself is a nonlinear system; when bonding interface of the structure is damaged, its dynamic characteristics show enhanced nonlinear characteristic. Therefore, the NOFRFs-based detection index is proposed as indicator to detect the bonding state of explosive composite pipes. The experimental results verify the effectiveness of the detection approach.

• Smart Media Journal
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• v.13 no.2
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• pp.108-121
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• 2024

In the IT industry, the complexity and volatility of corporate networks are gradually evolving, and concurrently, the significance of corporate networks is increasing. Previous research has employed network analysis to scrutinize inter-corporate trade relationships for strategic and policy making. However, previous studies focused on the overall network structure from a macroscopic perspective, presenting limitations in applicability at the individual IT corporation level. This study develops a novel research model incorporating sector and region-level network analysis based on connection strength, along with the derivation of a composite node centrality indicator. Using this methodology, we analyzed corporate networks across nine metropolitan areas using IT corporate transaction data. The results means that cities with a manufacturing base, such as Incheon, Busan, and Daegu, have recently established cooperative networks with IT companies. We also found that in the IT industry in Gwangju and Daejeon, certain companies dominate the transaction network.

• Journal of Korean Society for Quality Management
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• v.51 no.3
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• pp.363-379
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• 2023

Purpose: The main objective of this research is to construct an AI-based Composite Supplementary Index (ACSI) model to achieve accurate predictions of the Composite Index of Business Indicators. By incorporating various economic indicators as independent variables, the ACSI model enables the prediction and analysis of both the leading index (CLI) and coincident index (CCI). Methods: This study proposes an AI-based Composite Supplementary Index (ACSI) model that leverages diverse economic indicators as independent variables to forecast leading and coincident economic indicators. To evaluate the model's performance, advanced machine learning techniques including MLP, RNN, LSTM, and GRU were employed. Furthermore, the study explores the potential of employing deep learning models to train the weights associated with the independent variables that constitute the composite supplementary index. Results: The experimental results demonstrate the superior accuracy of the proposed composite supple- mentary index model in predicting leading and coincident economic indicators. Consequently, this model proves to be highly effective in forecasting economic cycles. Conclusion: In conclusion, the developed AI-based Composite Supplementary Index (ACSI) model successfully predicts the Composite Index of Business Indicators. Apart from its utility in management, economics, and investment domains, this model serves as a valuable indicator supporting policy-making and decision-making processes related to the economy.

• Journal of Korean Society of Rural Planning
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• v.20 no.2
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• pp.127-137
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• 2014

Self-sufficiency rate of food in South Korea is almost at the lowest level among OECD countries, and the decrease tend of farmland is expected to be continued. In this situation, the government has been revised the target self-sufficiency rate of food, and carried forward various policies in order to achieve it. One of those policies is the restoration business of idle farmland which is planned to carry forward after 2015. This study set up indicators evaluating effective use of idle farmland, and tried to apply in the field before carrying forward restoration business. The result of this study may be summarized as follows. First of all, it reset an evaluation indicator that was based on the evaluation indicator developed in order to set application directions of idle farmland. Next, it selected 30 idle farmlands with reset evaluation indicator among 11,635 which were inspected nationwide in 2012. Before applying indicator, it measured the condition of recycling such as accessibility of farmland, condition of irrigation and drainage system, land state, and surroundings by field investigation. Then, it calculated composite score in each target area through applying indicators, and verified the indicator by comparing calculated result with the one which was decided from field investigation. Finally, it carried out field investigation, correct and upgrade some problems of the standard of score calculation that was found during applying previously set evaluation indicator to target area, and established the final standard of calculation for evaluation indicator.

• The Journal of Asian Finance, Economics and Business
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• v.3 no.3
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• pp.27-37
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• 2016

This study uses an endogenous economic growth model to determine the long run relationship between trade openness and economic growth in China by using the data 1975-2009.It contributes to the literature by developing trade openness index. An autoregressive distributed lag approach to cointegration and rolling regression method are employed. This study tests the link between trade openness and economic growth in the case of China by using the framework of endogenous economic growth model. This study also employs the rolling window regression method in order to examine the stability of coefficients throughout the sample span. The autoregressive distributed lag (ARDL) cointegration technique and rolling regression method are used. The empirical findings indicate that trade openness (i.e. Both individual trade indicator and composite trade openness index) are positively related to economic growth in the long run and short run. Our results indicate that trade openness as measured by individual trade indicator and composite trade openness index are positively related to economic growth in the long run and short run. However, results from the rolling window suggest that trade openness is negatively linked to economic growth only for a number of years.