• Safety and Health at Work
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• v.10 no.2
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• pp.229-236
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• 2019

Background: Emerging reports suggest the potential for adverse health effects from exposure to emissions from some additive manufacturing (AM) processes. There is a paucity of real-world data on emissions from AM machines in industrial workplaces and personal exposures among AM operators. Methods: Airborne particle and organic chemical emissions and personal exposures were characterized using real-time and time-integrated sampling techniques in four manufacturing facilities using industrial-scale material extrusion and material jetting AM processes. Results: Using a condensation nuclei counter, number-based particle emission rates (ERs) (number/min) from material extrusion AM machines ranged from $4.1{\times}10^{10}$ (Ultem filament) to $2.2{\times}10^{11}$ [acrylonitrile butadiene styrene and polycarbonate filaments). For these same machines, total volatile organic compound ERs (${\mu}g/min$) ranged from $1.9{\times}10^4$ (acrylonitrile butadiene styrene and polycarbonate) to $9.4{\times}10^4$ (Ultem). For the material jetting machines, the number-based particle ER was higher when the lid was open ($2.3{\times}10^{10}number/min$) than when the lid was closed ($1.5-5.5{\times}10^9number/min$); total volatile organic compound ERs were similar regardless of the lid position. Low levels of acetone, benzene, toluene, and m,p-xylene were common to both AM processes. Carbonyl compounds were detected; however, none were specifically attributed to the AM processes. Personal exposures to metals (aluminum and iron) and eight volatile organic compounds were all below National Institute for Occupational Safety and Health (NIOSH)-recommended exposure levels. Conclusion: Industrial-scale AM machines using thermoplastics and resins released particles and organic vapors into workplace air. More research is needed to understand factors influencing real-world industrial-scale AM process emissions and exposures.

• Korean Journal of Ichthyology
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• v.31 no.1
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• pp.16-22
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• 2019

Investigations on the study of the distribution aspects and extinction threat evaluation of the Korean endemic species, Iksookimia pacifica were done from 2017 to 2018 in Korea. During the study period, the samples of I. pacifica were collected in 17 streams, 46 sites (from Baebongcheon Stream of Goseong-gun to Gunsuncheon Stream of Gangneung-si) among the noted 33 streams and 104 sampling sites investigated. The population size of I. pacifica was relatively large in streams such as Bukcheon, Baebongcheon, Hwasangcheon, Cheonjincheon, Ohhocheon Stream etc., but the population size was small in streams such as Sacheoncheon, Namcheon, Gangneung Namdaecheon Stream etc. The main habitat of I. pacifica was the downstream pool of clean water with slow velocity and sand bottoms, and their sensibility was estimated to be due to river work and water pollution. Comparing the previous records of the appearance of I. pacifica, they were first seen in Sampocheon Stream, but they did not appear in Jusucheon, Jeoncheon, Samcheok Osipcheon Stream. Given this evidence as noted for the 19.5% reduction in occupancy within 3 generations, in small appearance range ($1,343km^2$) and small occupancy area ($184km^2$), the number of locations were many (18) and the population was relatively large within the range of habitat. Therefore, I. pacifica is now considered a Near Threatened (NT) based on the IUCN Red List categories and criteria.

• Journal of the Korean Chemical Society
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• v.63 no.3
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• pp.166-182
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• 2019

This study examined teachers' difficulties that they encountered free semester science assessment and their problem solutions. Fifteen science teachers who had experiences of free semester teaching and assessment were selected by convenience sampling in this study. The participant teachers mentioned difficulties of accurate scoring in student self/peer assessment and suggested solutions of providing studetns with detailed assessment criteria and opportunities to practice assessment. The participant teachers mentioned a lack of objective assessment criteria for affective domain and suggested solutions of providing criteria prior to assessment and developing assessment framework. The participant teachers mentioned a lack of assessment tools and references for perforamnce assesement. The participant teachers mentioned difficulties of a large teacherstudent ratio for providng feedbacks to students and suggested solutions of decreasing teacher-student ratio and teaching load. The participant teachers mentioned difficulties of identifying student characteristics for assessment reporting and suggested solutions of decreaing teacher work load. The participant teachers mentioned a lack of teacher understanding of process based assessment and inactive attitude to performance assessment and suggested solutions of professional learning community and improving teacher perceptions on performance assessment. The participant teachers mentioned difficulties of a large teacher-student ratio and a lack of time for implementing assessment methods that they learned from professional development programs. With both teacher self-efforts and systematic support, these problems would be solved and success of free semester assessment would be achieved.

• 한국노년학
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• v.30 no.1
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• pp.241-260
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• 2010

This study aims to fully understand the experience of elderly men living alone in a single room occupancy(Chokbang) by identifying the meaning and essence of their experiences. This research used purposive sampling. The data were collected for 7 months from september 2008 to march 2009. Eight elderly men participated in the interview. Mainly the semi-structured in-depth interview and focus group interview were used. The data analysis was based on Giorgi's 4 types of specific steps. As a result, 4 components and 16 subordinate components were drawn from the analysis. The components resulted from the analysis are: , , , . Based on these results, I discussed the attitudes of the elderly men living alone in Chokbang in meaningful and gender-sensitive ways. Moreover, I provided social welfare connotation and future research suggestions.

• Animal Bioscience
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• v.34 no.4
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• pp.701-713
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• 2021

Objective: The present work was undertaken to evaluate the effects of storage time, choline chloride, and high concentrations of Cu and Zn on the kinetic behavior of vitamin degradation during storage in two vitamin premixes and four vitamin-trace mineral (VTM) premixes. Methods: Two vitamin premixes (with or without 160,000 mg/kg of choline) were stored at 25℃ and 60% humidity. Besides, four VTM premixes were used to evaluate the effects of choline (0 vs 40,000 mg/kg) and trace minerals (low CuSO4+ZnO vs high CuSO4+ZnO) on vitamin stability in VTM premixes stored in room, and the VTM premixes were stored in room temperature at 22℃. Subsamples from each vitamin and VTM premix were collected at 0, 1, 2, 3, 6, and 12 months. The retention of vitamin A (VA), vitamin D3 (VD3), vitamin E (VE), vitamin K3 (VK3), vitamin B1 (VB1), vitamin B2 (VB2), vitamin B3 (VB3), vitamin B5 (VB5), and vitamin B6 (VB6) in vitamin premixes and VTM premixes during storage was determined. The stability of vitamins in vitamin premixes and VTM premixes was determined and reported as the residual vitamin activity (% of initial) at each sampling point. Results: The effect of choline on VK3 retention was significant in vitamin premixes (p<0.05). The negative effect of storage time was significant for the retentions of VD3, VK3, VB1, VB2, VB5, and VB6 in vitamin premix (p<0.05). For VTM premixes, negative effect of storage time was significant (p<0.05) for the losses of vitamin in VTM premixes. Choline and high concentrations of Cu and Zn significantly increased VA, VK3, VB1, and VB2 loss during storage (p<0.05). The supplementation of high concentrations of Cu and Zn significantly decreased the concentrations of VD3 and VB6 (p<0.05) in VTM premixes at extended storage time. Conclusion: The maximum vitamin stability was detected in vitamin and VTM premixes containing no choline or excess Cu and Zn. The results indicated that extended storage time increased degradation of vitamin in vitamin or VTM premixes. These results may provide useful information for vitamin and VTM premixes to improve the knowledge of vitamin in terms of its stability.

• Geophysics and Geophysical Exploration
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• v.25 no.3
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• pp.140-161
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• 2022

Seismic data with missing traces are often obtained regularly or irregularly due to environmental and economic constraints in their acquisition. Accordingly, seismic data interpolation is an essential step in seismic data processing. Recently, research activity on machine learning-based seismic data interpolation has been flourishing. In particular, convolutional neural network (CNN) and generative adversarial network (GAN), which are widely used algorithms for super-resolution problem solving in the image processing field, are also used for seismic data interpolation. In this study, CNN-based algorithm, U-Net and GAN-based algorithm, and conditional Wasserstein GAN (cWGAN) were used as seismic data interpolation methods. The results and performances of the methods were evaluated thoroughly to find an optimal interpolation method, which reconstructs with high accuracy missing seismic data. The work process for model training and performance evaluation was divided into two cases (i.e., Cases I and II). In Case I, we trained the model using only the regularly sampled data with 50% missing traces. We evaluated the model performance by applying the trained model to a total of six different test datasets, which consisted of a combination of regular, irregular, and sampling ratios. In Case II, six different models were generated using the training datasets sampled in the same way as the six test datasets. The models were applied to the same test datasets used in Case I to compare the results. We found that cWGAN showed better prediction performance than U-Net with higher PSNR and SSIM. However, cWGAN generated additional noise to the prediction results; thus, an ensemble technique was performed to remove the noise and improve the accuracy. The cWGAN ensemble model removed successfully the noise and showed improved PSNR and SSIM compared with existing individual models.

• Journal of Korean Society for Geospatial Information Science
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• v.14 no.2 s.36
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• pp.89-94
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• 2006

Forest damage is a worldwide issue and specially, a forest fire involves damage to itself and causes secondary damage such as a flood etc. However, actually, clear analysis on forest fire damage can be hardly conducted due to difficulty in approaching a forest fire and quite a long period of time for analysis. To overcome such difficulty, recently, forest fire damage has been actively investigated with satellite image data, but it is also difficult to obtain satellite image data fitted to the time a forest fire occurred. In addition, it is burdensome to verify accuracy of the obtained image. Therefore, this study was attempted to look into the damaged districts from forest fires by reference to spectroradiometric characteristics of the obtained vegetation with a spectroradiometer as preliminary work to use satellite image data. To begin with, the researcher analyzed the field survey data each measured 3 months and 6 months after occurrence of a forest fire by judging the extent of the damage through visual observation and using a spectroradiometer in order to investigate any potential errors arising out of one-time visual observation. Besides, in this study, groups showing possibilities that trees might be restored to life and wither to death could be classified on the sampling points where forest fire damage is minor.

• Journal of the Society of Disaster Information
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• v.18 no.4
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• pp.729-745
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• 2022

Purpose: This study collects basic data on the awareness of evacuation methods and evacuation facilities in the event of a radiological disaster of residents living in the emergency planning zone. Method: The residents of emergency planning zone were sampled using a random sampling method. A 1:1 interview was conducted using a structured questionnaire, and statistical analysis was performed using the minitab program. Result: First, the survey subjects showed a relatively low and negative awareness of the local government's work on radioactive disasters. Second, in terms of resident safety education, they had little experience in education, but they felt it was necessary and wanted education on evacuation methods, action tips, and the location of relief centers. Third, the location of the relief centers related to radioactive disasters was not well known, and there were many responses that they did not receive any guidance, and that they would be with their families when using the relief centers. Satisfaction levels were generally low with regard to the relief facilities. Fourth, the necessary priorities in preparation for radioactive disasters were education and training for radioactive disasters, facility supplementation, and supply of protective chemicals. Conclusion: The residents of emergency planning zone perceived the policies and tasks of the government or local governments relatively negatively in preparation for the occurrence of radioactive disasters, and their satisfaction was low. Regarding the matters pointed out as a priority, the government and local governments should publicize and educate the residents of accurate information and policies on radioactive disasters.

• Journal of Industrial Convergence
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• v.21 no.4
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• pp.101-109
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• 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
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• v.55 no.spc1
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• pp.1295-1303
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• 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.