• 성인간호학회지
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• 제25권6호
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• pp.655-664
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• 2013

Purpose: This study was undertaken to identify which delirium screening instrument would be more useful in clinical practice. Methods: Data were collected from 118 nurses from six hospitals in five provinces in Korea. For the delirium screening three instruments were compared: NEECHAM Confusion Scale (NEECHAM), Nursing Delirium Screening Scale (Nu-DESC), Delirium Observation Scale (DOS). The MMSE-K was used for concurrent validity. The nurse subjects were surveyed as to the practical clinical value of each instrument. Cronbach's ${\alpha}$ coefficient and Kuder-Richardson 20 were used to confirm the reliability. Results: The range of three scales reliability was .70~.82 and the range of correlation coefficient was .63~.82 with MMSE-K. For sensitivity of NEECHAM, Nu-DESC and DOS was 1.00, 1.00 and 0.81 respectively and specificity NEECHAM, Nu-DESC and DOS was 0.88, 0.89 and 0.89 respectively. Nurses rated the practical use of the DOS scale as significantly easier to use than the NEECHAM and Nu-DESC. Conclusion: NEECHAM, Nu-DESC and DOS scales were acceptable in terms of reliability, validity, sensitivity and specificity. However, nurses rated the DOS scale as easier scale to use and had more relevance to their practice.

• Wind and Structures
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• 제28권1호
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• pp.63-70
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• 2019

Due to developing environmental concern use of renewable energy source is very essential. The great demand for the energy supply coupled with inadequate energy sources creates an emergency to find a new solution for the energy shortage. The appropriate wind energy distribution is the fundamental requirement for the assessment of wind energy potential available at the particular site essential for the design of wind farms. Hence the proper specification of the wind speed distribution plays a vital role. In this paper the Bimodal Weibull distribution is used to estimate the Capacity factor at the proposed site. The shape and scale parameters estimated using Maximum likelihood method is used as the initial value for extrapolation. Application of this model will give an accurate result overwhelming the concept of overestimation or underestimation of Capacity factor.