• The Journal of Korean Academic Society of Nursing Education
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• v.27 no.1
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• pp.49-58
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• 2021

Purpose: The purpose of this study was to determine relationships between academic achievement, clinical competence, and confidence in the clinical performance of nursing students, and to identify factors that influence them. Methods: This was a descriptive correlation study. Data were collected from 118 nursing students at a nursing college in Seoul. One-way variance analysis, Pearson's correlation coefficient, and multiple linear regression analysis were used to examine relationships between academic achievement, clinical competence, and confidence in clinical performance. Results: Clinical competence was related to academic achievement in students' previous semester and to students' academic scores in a fundamental of nursing course. Clinical competence showed a weak positive correlation with academic achievement in students' previous semester and academic scores in a fundamental of nursing course in both evaluations by the professor and students' self-evaluations. However, confidence in clinical performance had no significant correlation with academic achievement. The factor affecting the clinical competence was academic scores in a fundamental of nursing course, and factors affecting confidence in clinical performance were health status, personality, major suitability, and class satisfaction in a fundamental of nursing skills course. Conclusion: These findings indicate that students with high academic achievement have better clinical performance, but confidence in clinical performance is not related to academic achievement.

• Journal of Information Processing Systems
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• v.18 no.3
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• pp.374-388
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• 2022

Database systems usually have many parameters that must be configured by database administrators and users. RocksDB achieves fast data writing performance using a log-structured merged tree. This database has many parameters associated with write and space amplifications. Write amplification degrades the database performance, and space amplification leads to an increased storage space owing to the storage of unwanted data. Previously, it was proven that significant performance improvements can be achieved by tuning the database parameters. However, tuning the multiple parameters of a database is a laborious task owing to the large number of potential configuration combinations. To address this problem, we selected the important parameters that affect the performance of RocksDB using random forest. We then analyzed the effects of the selected parameters on write and space amplifications using analysis of variance. We used a genetic algorithm to obtain optimized values of the major parameters. The experimental results indicate an insignificant reduction (-5.64%) in the execution time when using these optimized values; however, write amplification, space amplification, and data processing rates improved considerably by 20.65%, 54.50%, and 89.68%, respectively, as compared to the performance when using the default settings.

• Safety and Health at Work
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• v.13 no.1
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• pp.3-8
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• 2022

Background: This study aims to allow the development of efficient measures to improve occupational health of shift-working nurses focusing on job stress, health promotion behavior, resilience, and sleep disturbance. Methods: It was conducted on a subject panel of 137 nurses who were aware of the purpose of the study and agreed to participate. They worked three shifts at a tertiary hospital or a general hospital located in metropolitan city B. The collected data were analyzed by the independent t test and one-way analysis of variance and post-tested by Scheffe's test, Pearson's correlation coefficients, and multiple linear regression analysis using SPSS/WIN 25.0. Results: The significant influencing factors on sleep disturbance were of those whose subjective health status was 'normal' (b = 0.29, p < .001), 'not healthy' (β = .40, p < .001), who have job stress (β = .22, p = .003), and who have health promotion behavior (β = -0.17, p = .023). The overall explanatory power was 31.1% (F = 16.31, p < .001). Conclusion: Through this study, nurses' subjective health status and job stress of working shifts were found to be important factors influencing the sleep disturbance level, and the most influencing factor was identified as the subjective health status.

• Journal of Korean Academy of Nursing
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• v.51 no.6
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• pp.678-688
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• 2021

Purpose: The purpose of this study was to identify factors influencing nurses' performance of care in COVID-19 wards. Methods: The participants were 132 nurses who worked in COVID-19 wards at three hospitals, and were recruited from April 1 to May 31, 2021. Data were analyzed using descriptive statistics, t-test, ANOVA, and multiple regression analysis with SPSS/WIN 24.0 program. Results: Nursing performance was significantly and positively correlated with ethical sensitivity (r = .75, p < .001), nursing professionalism (r = .67, p < .001), and social support (r = .67, p < .001). Nursing professionalism was positively correlated with ethical sensitivity (r = .64, p < .001) and social support (r = .55, p < .001). Multiple regression analysis for nursing performance revealed that the most significant factor was ethical sensitivity (β = .47, p < .001). Ethical sensitivity, nursing professionalism, and social support explained 66.0% of total variance in nursing performance. Conclusion: Ethical sensitiviy, nursing professionalism, and social support significantly influence nurses' performace of care in COVID-19 wards. It suggests that intervention programs should be directed at improving nurses' ethical sensitivity, bolstering social support, and enhancing nursing professionalism.

• Journal of information and communication convergence engineering
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• v.20 no.2
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• pp.79-89
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• 2022

To compute the mean and variance of component-based reliability software, we focused on path-based reliability analysis. System reliability depends on the transition probabilities of components within a system and reliability of the individual components as basic input parameters. The uncertainty in these parameters is estimated from the test data of the corresponding components and arises from the software architecture, failure behaviors, software growth models etc. Typically, researchers perform Monte Carlo simulations to study uncertainty. Thus, we considered a Markov chain Monte Carlo (MCMC) simulation to calculate uncertainty, as it generates random samples through sequential methods. The MCMC approach determines the input parameters from the probability distribution, and then calculates the average approximate expectations for a reliability estimation. The comparison of different techniques for uncertainty analysis helps in selecting the most suitable technique based on data requirements and reliability measures related to the number of components.

• Journal of Korean Clinical Nursing Research
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• v.15 no.1
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• pp.93-106
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• 2009

Purpose: The purpose of this study was to develop a valid and reliable instrument to explore and measure job satisfaction as perceived by perioperative nurses, specifically from the perspective of contemporary perioperative nursing in Korea. Method: Items (69) were developed from the responses to two open-ended questions by 168 perioperative nurses in one teaching hospital; (a) reasons that make work enjoyable, (b) reasons that make work unpleasant. Finally 55 items were selected, excluding items with lower correlation with the total scale. The instrument was completed by 885 perioperative nurses from 89 different hospitals nationwide who were attending the annual conference of the Korean Association Operating Room Nurses (KAORN), yielding a response rate of 95.6%. Results: Ten factors were extracted by factor analysis, which explained 60.0% of the total variance; Reliability and internal consistency were established (Cronbach's alpha=.95). A smaller sample of 39 perioperative nurses completed the instrument on two occasions, with a 2-week interval between. Mean scores were computed and two sets of scores were analyzed by Weighted Kappa (W-Kappa=0.680, p=.029). Conclusion: This instrument is a concise, highly practical and flexible tool, which can be used for the perioperative nurse in a wide range of hospital settings.

• Mood & Emotion
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• v.10 no.1
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• pp.31-36
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• 2012

Objectives : The aim of this study was to investigate the relationship between depressive symptom, spiritual well-being and state hope in early adults and middle aged patients with depression. Methods : A total of 180 outpatient were surveyed with Beck Depression Inventory (BDI), Functional Assessment of Chronic Illness Therapy-Spiritual Well-being Scale (FACIT-Sp) and The State Hope Scale (SHS). Mean scores of BDI, FACIT-Sp and SHS were compared between two groups of different age. Correlation analysis and multiple linear regression analyses were performed to identify the effect of BDI and FACIT on SHS according to age. Results : Mean scores of SHS and FACIT were higher significantly in middle aged group than early adults group, while BDI was not different between two groups. And early adults and middle aged patient's state hope showed a significantly negative correlation with spiritual well-being. In regression analysis, the effect of BDI, FACIT on SHS were significant in both groups and the regression model explained 42% of the variance of state hope in early adults group and 26% in middle aged group, respectively. Conclusion : These findings suggest that in depressive symptom and low state hope relationship, spirituality is important protective factor in both aged adult outpatients with depression.

• Journal of Hydrogen and New Energy
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• v.34 no.6
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• pp.734-740
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• 2023

Hydrogen emphasis on safety management due to its high potential for accidents from wide explosive limits and low ignition energy. To prevent accidents, appropriate explosion-proof electrical equipment with installed to safe management of ignition sources. However, designing all facilities with explosion-proof structures can significantly increase costs and impose limitations. In this study, we optimize the barrier to effectively control the initial momentum in case of hydrogen release and form the control room as a non-hazardous area. We employed response surface method (RSM), the barrier distance, width and height of the barrier were set as variables. The Box-Behnken design method the selection of 15 cases, and FLACS assessed the presence of hazardous area. Analysis of variance (ANOVA) analysis resulting in an optimized barrier area. Through this methodology, the workplace can optimize the barrier according to the actual workplace conditions and classify reasonable hazardous area, which is believed to secure safety in hydrogen facilities and minimize economic burden.

• Corrosion Science and Technology
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• v.22 no.5
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• pp.377-386
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• 2023

Aircraft washing is performed periodically for corrosion control. Currently, the aircraft washing interval is qualitatively set according to the geographical conditions of each base. We developed a washing interval determination algorithm based on atmospheric corrosion environment monitoring data at the Republic of Korea Air Force (ROKAF) bases and United States Air Force (USAF) bases to determine the optimal interval. The main factors of the washing interval decision algorithm were identified through hierarchical clustering, sensitivity analysis, and analysis of variance, and criteria were derived. To improve the classification accuracy, we developed a washing interval decision model based on an artificial neural network (ANN). The ANN model was calibrated and validated using the atmospheric corrosion environment monitoring data and washing intervals of the USAF bases. The new algorithm returned a three-level washing interval, depending on the corrosion rate of steel and the results of the ANN model. A new base-specific aircraft washing interval was proposed by inputting the atmospheric corrosion environment monitoring results of the ROKAF bases into the algorithm.

• Journal of Korean Society of Environmental Engineers
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• v.33 no.7
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• pp.501-510
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• 2011

In this study, water pollution sources of 14 major tributaries of Han river and characteristics of water quality for each target streams were evaluated based on water quality data in 2007.1-2009.12 (14 data sets) using a statistical package, SPSS-17.0. Cluster analysis over time and space for each stream resulted in 4 groups for the spatial variations in which type and density of pollution sources in the basins showed the greatest impact on grouping. Moreover, cluster analysis for the time variation in which rainfall, temperature and eutrophication were shown to contribute to the clustering, produced 2 groups, from summer to fall (July-Oct.) and from winter to early summer (Nov.-June). Four factors were found as responsible for the data structure explaining 71-90% of the total variance of the data set depending on the streams and they were organic matter, nutrients, bacterial contamination. Factor analysis showed main factors (water pollutants) changed according to the season with different pattern for each stream. This study demonstrated that water quality of each stream could produce useful outcomes when factor and pollution source of basin were evaluated together.