• The Journal of Fisheries Business Administration
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• v.42 no.1
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• pp.71-83
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• 2011

An ecosystem-based fisheries management (EBFM) approach becomes more important as an alternative management method for a sustainable development of fisheries domestically and internationally. Many methods of applying a practical EBFM to fisheries management have been investigated, and considerable attention has been given to developing effective indicators of the present status of and changes in ecosystems and putting them to practical use. Among ecosystem indicators, developing socioeconomic indicators for EBFM is particularly important. This is because socioeconomic factors have direct effects on ecosystems, and ecosystems have direct effects on socioeconomic factors. Therefore, it is imperative that socioeconomic indicators are developed and evaluated in order to predict changes in ecosystems and to provide advice for effective fisheries management. This study is aimed to develop socioeconomic indicators which can be combined with biological and ecological indicators, in order to conduct the ecosystem-based fisheries assessment. In terms of socioeconomic indicators, five socioeconomic criteria were considered as important attributes of socioeconomic changes. These criteria include economical production, business conditions, income, market, and employment indicators. For evaluation of newly developed socioeconomic indicators, the Traffic Light System (TLS) method was used. In addition, on the basis of the application of developed indicators to the Korean large purse seine fishery, the socioeconomic conditions of the fishery and the usefulness of the indicators were evaluated and management implications were discussed.

• Journal of Korean Academy of Nursing
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• v.33 no.5
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• pp.625-632
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• 2003

Purpose: The purpose of this study was to assess the importance and sensitivity to nursing interventions of four nursing sensitive nursing outcomes selected from the Nursing Outcomes Classification (NOC). Outcomes for this study were 'Knowledge: Diet', 'Knowledge: Disease Process', 'Knowledge: Energy Conservation', and 'Knowledge: Health Behaviors'. Method: Data were collected from 183 nurses working in 2 university hospitals. Fehring method was used to estimate outcome and indicators' content and sensitivity validity. Multiple and stepwise regression were used to evaluate relationships between each outcome and its indicators. Result: Results confirmed the importance and nursing sensitivity of outcomes and their indicators. Key indicators of each outcomes were found by multiple regression. 'Knowledge: Diet' was suggested for adding new indicators because the variance explained by indicators was relatively low. Not all of the indicators selected for stepwise regression model were rated for highly in Fehring method. The R² statistics of the stepwise regression models were between 18 and 63% in importance by selected indicators and between 34 and 68% in contribution by selected indicators. Conclusion: This study refined what outcomes and indicators will be useful in clinical practice. Further research will be required for the revision of outcome and indicators of NOC. However, this study refined what outcomes and indicators will be useful in clinical practice.

• Journal of Korea Multimedia Society
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• v.19 no.8
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• pp.1248-1259
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• 2016

Classification methods based on dual energy X-ray absorptiometry, ultrasonic waves, and quantitative computed tomography have been proposed. Also, a classification method based on machine learning with bone mineral density and structural indicators extracted from the CT images has been proposed. We propose a method which enhances the performance of existing classification method based on bone mineral density and structural indicators by extending structural indicators and using principal component analysis. Experimental result shows that the proposed method in this paper improves the correctness of osteoporosis classification 2.8% with extended structural indicators only and 4.8% with both extended structural indicators and principal component analysis. In addition, this paper proposes a method of automatic phantom analysis needed to convert the CT values to BMD values. While existing method requires manual operation to mark the bone region within the phantom, the proposed method detects the bone region automatically by detecting circles in the CT image. The proposed method and the existing method gave the same conversion formula for converting CT value to bone mineral density.

• Journal of Korean Academy of Nursing
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• v.35 no.3
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• pp.451-460
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• 2005

Purpose: The purpose of this study was to develop performance measure indicators for hospital nursing units based on a Balanced Scorecard (BSC). Method: This study was a methodological study, The development process consisted of 3 stages. The first stage was setting up strategies for nursing units from a nursing department's mission and vision. The second stage was developing performance measure indicators after a validity check. The third stage was modifying developed performance measure indicators and classifying them. Results: 7 strategies were set up according to 4 perspectives of a BSC. 15 performance measure indicators for hospital nursing units were developed, and the indicators were divided into 8 independent indicators and 7 shared indicators according to the degree of performance responsibility. In addition, they were classified into two groups, 7 leading indicators and lagging indicators. Conclusions: The result of this study suggests that performance measure indicators for hospital nursing units provide a framework and method for nursing organizations' performance management. Also, the developed indicators are expected to provide valuable information for successful organization management.

• Journal of applied mathematics & informatics
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• v.40 no.1_2
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• pp.289-303
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• 2022

This article examines the multidimensional index extraction method of the disability social security system based on data mining. While creating the data warehouse of the social security system for the disabled, we need to know the elements of the social security indicators for the disabled. In this context, a clustering algorithm was used to extract the indicators of the social security system for the disabled by investigating the historical dimension of social security for the disabled. The simulation results show that the index extraction method has high coverage, sensitivity and reliability. In this paper, a multidimensional extraction method is introduced to extract the indicators of the social security system for the disabled based on data mining. The simulation experiments show that the method presented in this paper is more reliable, and the indicators of social security system for the disabled extracted are more effective in practical application.

• Environmental and Resource Economics Review
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• v.9 no.5
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• pp.903-924
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• 2000

This paper examines the alternative method to measure the state of overall economic activity. The macroeconomic variables, used for business cycle, take more than a month after a period for collection and aggregation. The electricity generation data is compiled in mechanical ways just after the period. Based on this fact, we develop the two stage estimation method for coincident economic indicators in order to detect the business cycle in an earlier period, using Stock-Watson's Dynamic Factor Model. Using monthly data from 1970 to 1999, it is found that the experimental coincidence economic indicators are well-fitted to data and also that the estimates of two stage estimation method have good explanatory power, equivalent to the experimental coincidence economic indicators. While the RMSE of coincidence economic indicators is found to be 1.27%, that of the experimental coincidence economic indicators is found to be 1.31% and that of the two stage estimation method is around 1.44%. If we take consideration into the fact that it measures the business cycle in one month earlier, we come to the conclusion that the two stage estimation is of great use.

• Journal of Korean Society of Rural Planning
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• v.14 no.3
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• pp.53-61
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• 2008

This study has intended to elicit the definition of rural landscape, to classify rural landscape type, and to develop the evaluation indicators of rural landscape, meeting the definition through delphi expert survey method. The survey was performed five times for 80 days by 20 experts. The delphi expert survey asked experts as follows: 1) to fill out open-ended questions regarding the definition of rural landscape, and classification of rural landscape types, and evaluation indicators; 2) to provide their own feasibility evaluation regarding the results of the previous answer; and 3) to reevaluate the feasibility of the definition, types, and indicators. Based on the survey results, this study has found the appropriate definition of rural landscape like the comprehensive complex of physical (objective) and nonphysical (subjective) factors characterizing natural and/or artificial scenary of rural village itself Also, this study has developed the evaluation indicators of rural landscape in accordance with space types and landscape units classified. The developed indicators included areal ratio, the degree of green naturality, the building coverage ratio for physical landscape field, and skyline, landscape adjectives, color landscape, semantic scale.

• Proceedings of the Korean Society of Rural Planning Conference
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• 1998.03a
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• pp.21-24
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• 1998

The objective of this study is to enforce systematic evaluation on the present condition and ecosystem of coastal wetland to use frame of environmental indicators. For this, the indicators for evaluation of coastal wetland are established and are applied to the present condition. Then, the application possibility of this evaluation indicators and management method by group of coastal method are presented.

• Journal of Korean Academy of Nursing Administration
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• v.13 no.4
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• pp.462-472
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• 2007

Purpose: Purpose of the this study is to define the hemodialysis noncompliance Indicators and discriminant standards levels for low Flux Hemodialysis patients and development of Hemodialysis noncompliance measurement - brief form. Method: Data was collected from 269 hemodialysis patients. To establish the hemodialysis noncompliance Indicators and to discriminate standards, 13 hemodialysis nurses and 2 nephrology doctors are participated in professional group. To verify the indicators and discriminant standards, data was ananlyzed by the canonical discriminant analysis method using by SAS 8.3 program. Result: 4 Indicators- interdialysis weight gain(IWG); average of recent 4weeks, serum phophate level, skipping of hemodialysis and hemodialysis time shortening without permission- of hemodialysis noncompliance are established and discriminant standards are developed. Discriminant ability of these 4 noncompliance indicators is 99.7%(p=.000). Hemodialysis noncompliance measurement - brief form has 96.3% discriminant accuracy. Conclusion: Hemodialysis noncompliant patients have high risks. It means that special intervention to noncompliance is needed. Also continuous and objective assessment and standards of noncompliance are needed.

• Research in Community and Public Health Nursing
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• v.13 no.3
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• pp.523-531
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• 2002

Purpose: The purpose of this study was to assess the importance and sensitivity to nursing interventions of six sensitive nursing outcomes selected from the Nursing Outcomes Classification. The outcomes in this study were Self-Care: Activities of Daily Living, Self-Care: Instrumental Activities of Daily Living, Treatment Behavior: Illness or Injury, Knowledge: Health Promotion, Caregiver Performance: Direct Care, and Caregiver Physical Health. Method: Data were collected from 97 visiting nurses working in public health centers located in a province and a capital city. The Fehring method was used to estimate outcomes and indicators for content validity. Simultaneous multiple regression and stepwise regression were used to evaluate relationships between each outcome and its indicators. Results: Results confirmed the importance and nursing sensitivity of the outcomes and their indicators. Multiple regression revealed key indicators of each outcome. Self-Care: Instrumental Activity of Daily Living needed to be revised. Neither all of the indicators nor the indicators showing the highest importance and contribution ratio were selected as independent variables for the stepwise regression model. The R2 of the regression models ranged from 29 to 56% in importance by selected indicators and from 56 to 83% in contribution. Conclusion: Further research is needed for the revision of outcomes and their indicators.