• Nuclear Engineering and Technology
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• v.51 no.3
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• pp.904-907
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• 2019

Nuclear energy remains one of the world's major energy sources, making up over 10% of global electricity generation in 2017. Public acceptance of nuclear energy is essential for its adoption. From a practical perspective, it is beneficial to have a simple indicator that can predict the actual adoption of nuclear energy. Based on practical experience, the authors suggest tolerance and self-sufficiency as potential indicators that may predict the adoption of nuclear energy. By evaluating the cross-sectional data of 18 countries in 2013, this research assesses the actual impact of tolerance and self-sufficiency on public acceptance in order to identify the validity of the two variables. The results indicate that the two variables are statistically significant, while public acceptance is insignificant in explaining national adoption of nuclear energy. This may be because tolerance reflects national willingness to accept potential risk, while self-sufficiency explains a government's likelihood of developing non-carbon energy sources.

• Smart Structures and Systems
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• v.17 no.2
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• pp.347-361
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• 2016

A two-stage method for damage detection in truss systems is proposed. In the first stage, a modal residual vector based indicator (MRVBI) is introduced to locate the potentially damaged elements and reduce the damage variables of a truss structure. Then, in the second stage, a differential evolution (DE) based optimization method is implemented to find the actual site and extent of damage in the structure. In order to assess the efficiency of the proposed damage detection method, two numerical examples including a 2D-truss and 3D-truss are considered. Simulation results reveal the high performance of the method for accurately identifying the damage location and severity of trusses with considering the measurement noise.

• The Journal of Fisheries Business Administration
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• v.49 no.2
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• pp.49-65
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• 2018

The aim of this study is to develop suitability site indicator of urban-rural return to fishing and to analysis priority of the indicators. The study is based on literature review, expert survey and AHP(Analytic Hierarchy Process) methods. This study found 5 factors(natural environment, acceptance environment, social overhead capital, economy, fishing environment) and 21 detail variables. as a result of AHP, fisheries resources, acquisition convenience of fishing license, income(except fishing), attitude of local resident, one-person household income, high income fishing were showed high priority. This result indicate that economic foundation is most important factor for suitable site of the returning.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.1
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• pp.124-130
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• 2018

The EMG amplitude estimator, which has been investigated as an indicator of muscle force, is of high relevance not only in biomechanical studies but also more and more in clinical applications. This paper presents a new approach to estimate surface EMG amplitude by using the mean spike and mean turn amplitude(MSA and MTA) variables. Surface EMG signals, a total of 198 signals, were recorded from biceps brachii muscle over the range of 20-80%MVC isometric contraction and performance of the MSA and MTA variables applied to amplitude estimation of the EMG signals were investigated. To examine the performance, a SNR(signal-to-noise ratio) was computed from each amplitude estimate. The results of the study indicate that MSA and MTA amplitude estimations with first order whitening filter and 300[ms]-350[ms] moving average window length are optimal and show better performance(mean SNR improvement of 6%-15%) than the most frequently used variables(ARV and RMS).

• Journal of Preventive Medicine and Public Health
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• v.57 no.3
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• pp.234-241
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• 2024

Objectives: Health development is a key element of national development. The goal of improving health development at the societal level will be readily achieved if it is directed from the smallest social unit, namely the family. This was the goal of the Healthy Indonesia Program with a Family Approach. The objective of the study was to analyze variables of family health indicators across all provinces in Indonesia to identify provincial disparities based on the status of healthy families. Methods: This study examined secondary data for 2021 from the Indonesia Health Profile, provided by the Ministry of Health of the Republic of Indonesia, and from the 2021 welfare statistics by Statistics Indonesia (BPS). From these sources, we identified 10 variables for analysis using the k-means method, a non-hierarchical method of cluster analysis. Results: The results of the cluster analysis of healthy family indicators yielded 5 clusters. In general, cluster 1 (Papua and West Papua Provinces) had the lowest average achievements for healthy family indicators, while cluster 5 (Jakarta Province) had the highest indicator scores. Conclusions: In Indonesia, disparities in healthy family indicators persist. Nutrition, maternal health, and child health are among the indicators that require government attention.

• 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.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.2
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• pp.133-140
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• 2018

In this study, a correlation between execution of quality management activities and their results was verified by applying the Malcolm Baldrige model (hereafter referred to as the MB model) as a quality management performance measurement indicator for small and medium enterprises (SMEs) in South Korea. To achieve this goal, we need to determine whether the categorical requirements in the MB model are recognized consistently in SMEs, as a prerequisite. To this end, factor analysis was conducted for measurement variables in each category, which revealed that the process indicator was made up of six factors and the outcome indicator was made up of five factors, like those configured in the MB model. This result can be interpreted to mean that the requirements in each category of the MB model were well produced and recognized consistently throughout SMEs in South Korea. In addition, the analysis of causality between the process indicator (quality management activities) and the outcome indicator (management results) showed high causality between them. Although the quality management levels of SMEs in South Korea are inferior to those of conglomerates or other national quality award-winning companies, this study is significant in that the causality between quality management activities and results was verified, since this study targeted SMEs in South Korea as the target of investigation. Thus, it is empirically proven that the MB model can contribute to improved management results for SMEs in Korea.

• 한국노년학
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• v.29 no.2
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• pp.395-405
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• 2009

This study aims at providing an upgraded suggestion to improve satisfaction for the family caregiver. This study was conducted to find the relationship between satisfaction and family support and outcome indicator to investigate the factors that have influence on the satisfaction. The study population was 126 families of 5 elderly residing in institutionalized elderly homes in seoul and kyunggi. The data collection was measured satisfaction, family support, and outcome indicator instrument. The satisfaction showed meaning relationship with outcome indicator and family support. Explainary power of independent variables of product index was 23%. Factors influencing satisfaction for the family was economic level, family support and outcome indicator. This study was done to give suggestions to improve family caregiver satisfaction and to serve as a basis for policy strategies by examining the current conditions of the nursing facilities.

• Journal of the Korean earth science society
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• v.31 no.4
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• pp.301-312
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• 2010

Geochemical data have been regarded as one of the important environmental variables in the environmental management. Since they are often sampled at sparse locations, it is important not only to predict attribute values at unsampled locations, but also to assess the uncertainty attached to the prediction for further analysis. The main objective of this paper is to exemplify how indicator geostatistics can be effectively applied to geochemical data processing for providing decision-supporting information as well as spatial distribution of the geochemical data. A whole geostatistical analysis framework, which includes probabilistic uncertainty modeling, classification and risk analysis, was illustrated through a case study of cadmium mapping. A conditional cumulative distribution function (ccdf) was first modeled by indicator kriging, and then e-type estimates and conditional variance were computed for spatial distribution of cadmium and quantitative uncertainty measures, respectively. Two different classification criteria such as a probability thresholding and an attribute thresholding were applied to delineate contaminated and safe areas. Finally, additional sampling locations were extracted from the coefficient of variation that accounts for both the conditional variance and the difference between attribute values and thresholding values. It is suggested that the indicator geostatistical framework illustrated in this study be a useful tool for analyzing any environmental variables including geochemical data for decision-making in the presence of uncertainty.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.717-725
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• 2020

The purpose of this paper is to highlight the impact of the performance of private wealth management (PWM) on the growth of retail banking in Indonesia. The variables used are bank's competitiveness, risk management, performance of private wealth management, and growth of retail banking business. The data were collected from 60 respondents from 32 banks over five months, from October 2018 to March 2019. Using partial least square path modeling, the analysis shows that the performance of private wealth management has an impact on the growth of retail banking sector in Indonesia. Bank competitiveness and risk management affect the performance of personal wealth management and have an impact on the growth of the retail banking business. Bank competitiveness is the variable that most influences the performance of private wealth management in Indonesia. This research found that market share is the most significant indicator of bank competitiveness. For risk management, significant indicators are the level of bank confidence, increased bank competitiveness, and the creation of new products. In the performance of the private wealth management variable, the most significant indicator is the revenue fee-based income. For the growth of retail banking business, a clear indicator is profit growth.