• Journal of Industrial Convergence
• /
• v.21 no.4
• /
• pp.101-109
• /
• 2023

The aim of this study is to verify the relationships of factors affecting nursing performance of clinical nurses focused on positive affective events. The subjects of this study were 275 clinical nurses from secondary and tertiary general hospitals. Data collection was conducted for two months from May 2021 through an online survey through snowball sampling. Data analyzed was using SPSS 26.0 and AMOS 26.0. The variables affecting job satisfaction included direct effect of positive affective events (β=.65, p<.001), and direct effect of positive affectivity (β=.10, p=.038). Job satisfaction (β=.47, p<.001) had statistically significant direct effects on nursing performance. Positive affective events (β=.32, p=.003) and positive affectivity (β=.05, p=.039) had statistically significant indirect effects on nursing performance. These variables explained for 22% of nursing performance. However, emotional labor had no significant effect on job satisfaction and nursing performance. The results indicate that positive affective events and positive affectivity result in high degree of job satisfaction. Job satisfaction would increase the level of nursing performance. Therefore, in order to improve nursing performance, it is necessary to provide educational opportunities and interventions that can promote positive work environment and positive affectivity.

• Journal of Korea Water Resources Association
• /
• v.55 no.spc1
• /
• pp.1295-1303
• /
• 2022

As the role of water distribution networks (WDNs) becomes more important, identifying abnormal events (e.g., pipe burst) rapidly and accurately is required. Since existing approaches such as field equipment-based detection methods have several limitations, model-based methods (e.g., machine learning based detection model) that identify abnormal events using hydraulic simulation models have been developed. However, no previous work has examined the impact of data uncertainties on the results. Thus, this study compares the effects of measurement error-induced pressure data uncertainty in WDNs. An artificial neural network (ANN) is used to predict nodal pressures and measurement errors are generated by using cumulative density function inverse sampling method that follows Gaussian distribution. Total of nine conditions (3 input datasets × 3 output datasets) are considered in the ANN model to investigate the impact of measurement error size on the prediction results. The results have shown that higher data uncertainty decreased ANN model's prediction accuracy. Also, the measurement error of output data had more impact on the model performance than input data that for a same measurement error size on the input and output data, the prediction accuracy was 72.25% and 38.61%, respectively. Thus, to increase ANN models prediction performance, reducing the magnitude of measurement errors of the output pressure node is considered to be more important than input node.

• Industry Promotion Research
• /
• v.8 no.2
• /
• pp.37-43
• /
• 2023

Sampling In this study, we examined the problems and their improvement plans associated with the reliability management sector in quality management engineer test conducted in Korea. First of all, there seems to be a problem in that the terminology is not unified and some techniques essential for reliability analysis are not included. We also looked at quality and reliability tests performed in foreign countries (especially USA) that Koreans often acquire. In particular, it can be seen that the CRE test almost overlaps with the contents of the reliability management engineer test in Korea. However, while the USA is an open book test, Korea is not, so the problem is that there are too many formulas to memorize on the part of the test takers. In addition, the analysis of the data is done manually without using computer software. If the test were an open book test like the CRE test in USA, it will be a test that can go beyond fragmentary knowledge and check whether test takers have the essential elements in reliability management. Lastly, if we adopt re-certification system through education and work within a certain period of time, as in USA, it will be a qualification test suitable for modern people living in a flood of information.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.40 no.1
• /
• pp.51-66
• /
• 2022

SST (Sea Surface Temperature) is based on the atmosphere-ocean interaction, one of the most important mechanisms for the Earth system. Because it is a crucial oceanic and meteorological factor for understanding climate change, gap-free grid data at a specific spatial and temporal resolution is beneficial in SST studies. This paper examined the production of daily SST grid maps from 137 stations in 2020 through the ordinary kriging with variogram optimization and their accuracy assessment. The variogram optimization was achieved by WLS (Weighted Least Squares) method, and the blind tests for the interpolation accuracy assessment were conducted by an objective and spatially unbiased sampling scheme. The four-round blind tests showed a pretty high accuracy: a root mean square error between 0.995 and 1.035℃ and a correlation coefficient between 0.981 and 0.982. In terms of season, the accuracy in summer was a bit lower, presumably because of the abrupt change in SST affected by the typhoon. The accuracy was better in the far seas than in the near seas. West Sea showed better accuracy than East or South Sea. It is because the semi-enclosed sea in the near seas can have different physical characteristics. The seasonal and regional factors should be considered for accuracy improvement in future work, and the improved SST can be a member of the SST ensemble around South Korea.

• Journal of Korean Society of Occupational and Environmental Hygiene
• /
• v.33 no.2
• /
• pp.171-187
• /
• 2023

Objectives: Aircraft cabin cleaning work is characterized by being performed within a limited time in a narrow and enclosed space. The objective of this study was to evaluate the exposure levels to dust, ultra fine dust(PM2.5) and black carbon(BC) among aircraft cabin cleaners. Methods: Active personal air sampling for respirable dust(n=73) and BC(n=47) was conducted during quick transit cleaning(cabin general and vacuum-specific) and seat cover replacement and total dust and PM2.5 were area-air-sampled as well. Also, size distribution of particle was identified with the cleaning workers targeted. Dusts were collected with PVC filters using gravimetric analysis. The concentration of PM2.5 and the particle size distribution were measured with real-time direct reading portable equipment using light scattering analysis. The concentration of BC was measured by aethalometer(filter-based real-time light absorption analysis instrument). Results: The geometric mean of respirable dust was the highest at vacuum cleaning as 74.4 ㎍/m³, following by replacing seat covers as 49.3 ㎍/m³ and cabin general cleaning as 47.8 ㎍/m³ . The arithmetic mean of PM2.5 was 4.83 ~ 9.89 ㎍/m³ inside the cabin, and 28.5~44.5 ㎍/m³ outside the cabin(from bus and outdoor waiting space). From size distribution, PM_2.5/PM₁₀ ratio was 0.54 at quick transit cleaning and 0.41 at replacing seat covers. The average concentration of BC was 2~7 ㎍/m³, showing a high correlation with the PM2.5 concentration. Conclusions: The hazards concentration levels of aircraft cabin cleaners were very similar to those of roadside outdoor workers. As the main source of pollution is estimated to be diesel vehicles operating at airports, and it is necessary to replace older vehicles, strengthen pollutant emission control regulations, and introduce electric vehicles. In addition, it is necessary to provide as part of airport-inftastructure a stable standby waiting space for aircraft cabin cleaners and introduce a systematic safety and health management system for all workers in the aviation industry.

• 한국체육학회지인문사회과학편
• /
• v.55 no.2
• /
• pp.35-46
• /
• 2016

This study aims to observe the operation aspect of physical education during before class and further, to search for the utmost improvement direction using IPA (Importance-Performance Analysis). 500 middle & high school students have chosen through a purposeful sampling method, and 430 was used for analysis. The results were as follows. The quadrant I is "the keep up the good work" part. And the quadrant I includes "de-stress", "the pleasure of school life", "improvement in performance", "peer relationship", "help for P.E.", "health promotion", "sport facility surroundings", "rules", "teacher leadership", "passionate coaching", "fair coaching", "improvement in exercise ability", "understanding P.E." The quadrant II is "the concentrate here" part. And the quadrant II includes "develop talent", "excercise time", "safety management for exercise facility", "new sports event", "consider needs and interests", "consider level" "consider gender". The quadrant III is "the low priority" part. And the quadrant III includes "change of personality", "ability to do various sports event", "develope thinking ability". "communication with peer" "an intelligible explanation" In order to improve the quality of before classes, first, "safety connected program" second, "emotional and intellectual development program", third, "divided classes per level and gender", and the last, "professional manpower for developing the quality of class" are needed.

• 한국체육학회지인문사회과학편
• /
• v.55 no.4
• /
• pp.241-252
• /
• 2016

The purpose of this study was to suggest rating factors of the importance and the satisfaction for selecting physical education institutes for preschoolers and to provide an implication of vitalizing physical education class for preschooler with comparative analysis between importance and satisfaction using IPA analysis. 253 directors of educational institutes for preschooler have chosen through a convenience sampling method, and 430 was used for analysis. The results were as follows. First, the instructor qualification items and the program items ranked highly positions in physical education institute for preschooler. Second, the instructor qualification items, the program items, tuition items of discount benefit and institution image items of reputation had the significant difference between importance and satisfaction. Lastly, The quadrant I is "the keep up the good work" part and includes 8 items such as the expertise of the physical education teacher for preschooler. The quadrant II is "the concentrate here" part and includes 2 items such as teaching ability of the physical education teacher for preschooler. The quadrant III is "the low priority" part and includes 6 items such as reasonable prices of tuitions.

• Journal of Preventive Medicine and Public Health
• /
• v.56 no.4
• /
• pp.319-326
• /
• 2023

Objectives: The coronavirus disease 2019 (COVID-19) pandemic has increased the workload of healthcare workers (HCWs), impacting their health. This study aimed to assess sleep quality using the Pittsburgh Sleep Quality Index (PSQI) and identify factors associated with poor sleep among HCWs in Vietnam during the COVID-19 pandemic. Methods: In this cross-sectional study, 1000 frontline HCWs were recruited from various healthcare facilities in Vietnam between October 2021 and November 2021. Data were collected using a 3-part self-administered questionnaire, which covered demographics, sleep quality, and factors related to poor sleep. Poor sleep quality was defined as a total PSQI score of 5 or higher. Results: Participants' mean age was 33.20±6.81 years (range, 20.0-61.0), and 63.0% were women. The median work experience was 8.54±6.30 years. Approximately 6.3% had chronic comorbidities, such as hypertension and diabetes mellitus. About 59.5% were directly responsible for patient care and treatment, while 7.1% worked in tracing and sampling. A total of 73.8% reported poor sleep quality. Multivariate logistic regression revealed significant associations between poor sleep quality and the presence of chronic comorbidities (odds ratio [OR], 2.34; 95% confidence interval [CI], 1.17 to 5.24), being a frontline HCW directly involved in patient care and treatment (OR, 1.59; 95% CI, 1.16 to 2.16), increased working hours (OR, 1.84; 95% CI,1.37 to 2.48), and a higher frequency of encountering critically ill and dying patients (OR, 1.42; 95% CI, 1.03 to 1.95). Conclusions: The high prevalence of poor sleep among HCWs in Vietnam during the COVID-19 pandemic was similar to that in other countries. Working conditions should be adjusted to improve sleep quality among this population.

• Korean Journal of Ichthyology
• /
• v.34 no.4
• /
• pp.262-269
• /
• 2022

A distribution survey was conducted from 2018 to 2020 to evaluate the distribution status, habitat characteristics, and extinction threat of the short ninespine stickleback Pungitius kaibarae (Gasterosteidae). Literature reports of P. kaibarae distribution have been sorted by each period, 1980~1996, 1997~2005, and 2007~2017, and the samples were collected in 32, 43, and 64 stations for each period. Among the 75 streams and 193 sampling sites investigated during the study period, 1,400 P. kaibarae individuals were collected from 26 streams at 39 sites. The main habitat of P. kaibarae was downstream or brackish water zones with a low altitude, slow water velocity, and many aquatic plants. The main reasons for the decline in population size were assumed to be drought and flood, river work for flood restoration and river maintenance, bridges construction, and predation by the exotic fish species Micropterus salmoides. Previous evidence reported a 42.6% reduction in occupancy within 10 years, a decline in habitat quality, and the spread and impact of the exotic fish species Micropterus salmoides. Therefore, P. kaibarae is now considered a Vulnerable (VU A2ace) species based on the IUCN Red List categories and criteria. Therefore, P. kaibarae should be redesignated as an endangered species by the Ministry of Environment and systematically managed.

• Journal of the Korea institute for structural maintenance and inspection
• /
• v.27 no.5
• /
• pp.30-39
• /
• 2023

Large dams, which are critical infrastructures for disaster prevention, are exposed to various risks such as aging, floods, and earthquakes. Better dam safety inspection and diagnosis using digital transformation technologies are needed. Traditional visual inspection methods by human inspectors have several limitations, including many inaccessible areas, danger of working at heights, and know-how based subjective inspections. In this study, drone photogrammetry was performed on two large dams to evaluate the applicability of digital data-based dam safety inspection and propose a data management methodology for continuous use. High-quality 3D digital models with GSD (ground sampling distance) within 2.5 cm/pixel were generated by flat double grid missions and manual photography methods, despite reservoir water surface and electromagnetic interferences, and severe altitude differences ranging from 42 m to 99.9 m of dam heights. Geometry profiles of the as-built conditions were easily extracted from the generated 3D mesh models, orthomosaic images, and digital surface models. The effectiveness of monitoring dam deformation by photogrammetry was confirmed. Cracks and deterioration of dam concrete structures, such as spillways and intake towers, were detected and visualized efficiently using the digital 3D models. This can be used for safe inspection of inaccessible areas and avoiding risky tasks at heights. Furthermore, a methodology for mapping the inspection result onto the 3D digital model and structuring a relational database for managing deterioration information history was proposed. As a result of measuring the labor and time required for safety inspection at the SYG Dam spillway, the drone photogrammetry method was found to have a 48% productivity improvement effect compared to the conventional manpower visual inspection method. The drone photogrammetry-based dam safety inspection is considered very effective in improving work productivity and data reliability.