• 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 Energy Engineering
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• v.25 no.3
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• pp.149-156
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• 2016

This paper surveyed and analyzed cases of DB development overseas to set the range of DB to be developed for analyzing energy-saving policies in the domestic transportation sector. The foregoing prerequisites were used to establish system for classification in the broad scale under which system for classification in detail indicators that suit one in the broader indicators was set based on analysis of domestic / overseas cases to determine DB development range in the transportation sector required to analysis domestic energy-saving policies. Accordingly, six items subject to the broadest classification were determined, i.e. energy consumption, energy basic unit, emissions of greenhouse gas, economic indicators, transportation volume / transportation records and basic automobile data. Large classification and sub-items determined by surveying expert opinions were set and proposed as DB classification indicators.

• Youth Facilities and Environment
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• v.17 no.1
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• pp.131-141
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• 2019

The purpose of this study is to derive and type utilization indexes by comparing public design indicators with preceding studies related to closed school facilities, and to derive preliminary classification systems through a correlation review between indicators. Pre-research was conducted in the scope of academic papers, academic journals, research reports, and special act for promoting the utilization of closed school assets. Public design indicators were set in the scope of domestic design guidelines, the Seoul city public design assessment system, the 'Good Building' designation system, and the UK Design Quality Index (DQI). and the design review of the British architects. First of all, the research method looked at laws, procedures and utilization of closed schools, and reviewed the preceding study and domestic and international public design indicators sequentially. Next, the association was reviewed through a comparison between the preceding study and the public design indicators, and a preliminary classification system for the use of closed schools was derived from this.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.962-968
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• 2018

In this study, we developed novel indicators to assess postoperative pain based on PPG derivative waveform. As the candidate indicator of postoperative pain assessment, the time from the start of beating to the n-th peak($T_n$) and the n-th peak amplitude($A_n$) of the PPG derivative were selected. In order to verify derived indicators, each candidate indicator was derived from the PPG of 78 subjects before and after surgery, and it was confirmed whether significant changes were observed after surgery. Logistic classification was performed with each proposed indicator to calculate the pain classification accuracy, then the classification performance was compared with SPI(Surgical Pleth Index, GE Healthcare, Chicago, US). The results showed that there were significant differences(p < 0.01) in all indicators except for $T_3$ and $A_3$. The coefficient of variation(CV) of every time-related indicators were lower than the CV of SPI(30.43%), however, the CV in amplitude-related parameters were higher than that of SPI. Among the candidate indicators, amplitude of the first peak, $A_1$, showed that highest accuracy in post-operative pain classification, 68.72%, and it is 15.53% higher than SPI.

• 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 Korean Academy of Nursing
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• v.46 no.3
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• pp.375-389
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• 2016

Purpose: The aim of this study was to classify nursing management competencies and develop behavioral indicators for nurse managers in hospitals. Also, levels of importance and performance based on developed criteria were to be identified and compared. Methods: Using expert survey we classified nursing management competencies and behavioral indicators with data from 34 nurse managers and professors. Subsequently, data from a survey of 216 nurse managers in 7 cities was used to analyze the importance-performance comparison of the classified nursing management competencies and behavioral indicators. Results: Forty-two nursing management competencies were identified together with 181 behavioral indicators. The mean score for importance of nursing management competency was higher than the mean score for performance. According to the importance-performance analysis, 5 of the 42 nursing management competencies require further development: vision-building, analysis, change management, human resource development, and self-management competency. Conclusion: The classification of nursing management competencies and behavioral indicators for nurse managers in hospitals provides basic data for the development and evaluation of programs designed to increase the competency of nurse managers in hospitals.

• 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.

• Journal of Internet Computing and Services
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• v.21 no.6
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• pp.81-94
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• 2020

This study developed evaluation indicators for the comfort experience of virtual reality (VR) headsets by classifying, defining, and weighting cybersickness-causing factors using the Delphi research method and analytic hierarchical process (AHP) approach. Four surveys were conducted with 20 experts on VR motion sickness. The expert surveys involved the 1) classification and definition of cybersickness-causing dimensions, classification of sub-factors for each dimension, and selection of evaluation indicators, 2) self-reassessment of the results of each step, 3) validity revaluation, and 4) final weighting calculation. Based on the surveys, the evaluation indicators for the comfort experience of VR headsets were classified into eight sub-factors: field of view (FoV)-device FoV, latency-device latency, framerate-device framerate, V-sync-device V-sync, rig-camera angle view, rig-no-parallax point, resolution-device resolution, and resolution-pixels per inch (PPI). A total of six dimensions and eight sub-factors were identified; sub-factor-based evaluation indicators were also developed.

• Korean Journal of Adult Nursing
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• v.20 no.3
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• pp.489-499
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• 2008

Purpose: The purpose of this study was to assess the importance and contribution of 9 nursing outcomes and their indicators that could be applied to cerebrovascular patients. Methods: Data were collected from 175 neurosurgical nurses working at two university affiliated hospitals and five secondary hospitals located in Gwang-ju. The Fehring method was used to estimate outcome content validity(OCV) and outcome sensitivity validity(OSV) of nursing outcomes and their indicators. Stepwise regression was used to evaluate relationship between outcome and its indicators. Results: The core outcomes identified by the OCV were Tissue Perfusion: Cerebral, Nutritional Status, Neurological Status, and Wound Healing: Primary Intention, whereas highly supportive outcomes identified by the OSV were Oral Health, Self-Care: ADL, and Nutritional Status. All the critical indicators selected for Fehring method were not included in stepwise regression model. By stepwise regression analysis, the indicators explained outcomes from 19% to 52% in importance and from 21% to 45% in contribution. Conclusion: This study identified core and supportive outcomes and their indicators which could be useful to assess the physical status of cerebrovascular patients. Further research is needed for the revision and development of nursing outcomes and their indicators at neurological nursing area.

• International Journal of Railway
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• v.5 no.4
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• pp.175-181
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• 2012

This study proposes a model for railway safety assessment with which the safety of whole railway system can be evaluated. The purpose of the assessment model is to generate safety indicators which quantitatively represent the degree of railway safety. Safety indicators were proposed as three indicators according to their functions; accident indicators, safety management indicators, and safety culture indicators. This paper describes the first result on the safety target which will be a key starting point toward the development of safety assessment model. It is recommended that the safety target to be composed of several sub-targets are apportioned to constituent components. It is concluded that the classification of safety target has influence on deciding components or attributes that constitute each sub-indicators; accident indicators, safety management indicators, and safety culture indicators. Based on this study, a railway safety assessment model will be developed in the following study.