• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.485-491
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• 2021

This study examined the effects of preschool teachers' social support and mindfulness on job exhaustion. The study subjects were 138 preschool teachers in OO city. As an analysis method, frequency analysis, reliability analysis, and correlation analysis were performed using the SPSS 22.0 program, and multiple regression analysis was performed on the causal relationship between the variables. An examination of the effect of social support on preschool teachers on job exhaustion found that the material support factor, a sub-factor of social support, had a negative effect (-) on job exhaustion. Second, the sub-factors of mindfulness, decentered attention, and present awareness had a significant negative effect on job exhaustion. A higher the current awareness, the decentered attention of mindfulness, and the material support factor of social support perceived by preschool teachers indicated lower job exhaustion. These results provide the basic data for the preparation of measures for reducing job exhaustion of preschool teachers.

• PNF and Movement
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• v.19 no.2
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• pp.225-231
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• 2021

Purpose: This study was conducted to investigate the type of physical therapist response work and its intensity, along with the prolonged prevalence of COVID-19, to determine the impact on physical therapists' occupational stress and occupational burnout. Methods: An online survey was conducted with 118 physiotherapists and collected the participants' gender, final educational background, clinical work experience, workplace type, additional workload, and fatigue associated with COVID-19. After excluding one participant who submitted an incomplete questionnaire, 117 respondents were included in the final data. Results: Additional COVID-19-related workloads and response reliability for fatigue, occupational burnout, and occupational stress were shown to have Cronbach's alpha measures of 0.76, 0.89, and 0.87, respectively. Groups who had experienced a new epidemic in the past showed higher fatigue levels (3.06±0.94) than those groups who had no such experience (2.49±0.84; p < 0.05). Correlation analysis of COVID-19 work fatigue and occupational burnout scales showed a positive correlation (r = 0.19; p < 0.05). The regression of occupational burnout and occupational stress showed a regression model of Y = 20.00+0.43X₁ (X₁: job stress; p< 0.05) and an explanatory power of 24.8% with an adj.R² = 0.25. Conclusion: Based on the results, it is suggested that various institutions, such as medical institutions, educational institutions, and physiotherapists' associations, should seek ways to manage and alleviate physiotherapists' stress.

• Journal of the Korea Society of Computer and Information
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• v.27 no.3
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• pp.225-238
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• 2022

Although the importance of literacy in Artificial Intelligence (AI) education is increasing, there is a lack of testing tools for measuring such competency. To address this gap, this study developed a testing tool that measures AI literacy among middle school students. This goal was achieved through the establishment of an expert group that was enlisted to determine the relevant factors and items covered by the proposed tool. To verify the reliability and validity of the developed tool, a field review, exploratory factor analysis, and confirmatory factor analysis were conducted. These procedures resulted in a testing tool comprising six domains that encompass 30 items. The domains are the social impact of AI (eight items), the understanding of AI (six items), AI execution plans (five items), problem solving with AI (five items), data literacy (four items), and AI ethics (two questions). The items are to be rated using a five-point Likert scale. The internal consistency of the tool was .970 (total), while that of the domains ranged from .861 to .939. This study can serve as reference for developing the analysis of AI literacy, teaching and learning, and evaluation in AI education.

• The Journal of the Korea Contents Association
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• v.22 no.10
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• pp.840-850
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• 2022

The purpose of this study is to translate The Digital Addiction Scale for Children(DASC) developed by Hawi, Samaha and Griffiths into Korean and to verify its validity. To translate and validate the original scale developed for 9-12 years old, 294 people aged 9-12 years who usually use digital devices, and exploratory factor analysis, confirmatory factor analysis, internal consistency, and validity analysis were conducted. In addition, reliability and validity analysis were conducted to confirm that this scale is a tool to measure the digital addiction of Korean children with high confidence level and validity. This study is meaningful in that it laid the foundations for related research by adapting and validating the digital addiction scale for children, which complements the limitations of the preceding measures, in accordance with the domestic situation in the situation where the digital addiction problem of children is getting serious.

• Journal of Sensor Science and Technology
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• v.31 no.6
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• pp.433-440
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• 2022

Recently, owing to global warming, average summer temperatures are increasing and the number of hot days is increasing is increasing, which leads to an increase in heat stroke. In particular, outdoor workers directly exposed to the heat are at higher risk of heat stroke; therefore, preventing heat-related illnesses and managing safety have become important. Although various wearable devices have been developed to prevent heat stroke for outdoor workers, applying various sensors to the safety helmets that workers must wear is an excellent alternative. In this study, we developed a smart helmet that measures various vital signs of the wearer such as body temperature, heart rate, and sweat rate; external environmental signals such as temperature and humidity; and movement signals of the wearer such as roll and pitch angles. The smart helmet can acquire the various data by connecting with a smartphone application. Environmental data can check the status of heat wave advisory, and the individual vital signs can monitor the health of workers. In addition, we developed an algorithm that classifies the risk of heat-related illness as normal and abnormal by inputting a set of vital signs of the wearer using a support vector machine technique, which is a machine learning technique that allows for rapid binary classification with high reliability. Furthermore, the classified results suggest that the safety manager can supervise the prevention of heat stroke by receiving feedback from the control system.

• The Korean Journal of Food And Nutrition
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• v.35 no.6
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• pp.481-490
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• 2022

The influence of the food value consumption type of MZ generation on food choice attribute and sustainable food consumption behavior was studied using structural equation modeling. A survey was conducted on April 11~17, 2022, among panels aged 20 to 39. A total of 350 valid replicates (100%) were analyzed using statistical program SPSS The validity of the measurement instrument was verified through exploratory factor analysis and confirmatory factor analysis. The data reliability was confirmed using Cronbach's alpha coefficient. The hypothesis was verified by performing path analysis through structural equation modeling using AMOS. Regarding the influence of food choice characteristics on sustainable food consumption behavior, health has a significant positive (+) effect on the selection consumption behavior of certified food and local food. Among food value consumption categories social value consumption has a significant negative (-) influence on the consumption behavior of certified food and the choice of local food. Ethical value consumption has a significant positive (+) influence on the selection consumption behavior of certified food and local food. This study is significant because it has identified sustainable food consumption behaviors that domestic consumers can adopt daily. It can use as baseline data for preparing political and institutional measures.

• Journal of Korean Academy of Dental Administration
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• v.10 no.1
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• pp.53-65
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• 2022

The Primary Care Patient Measure of Safety (PC-PMOS) is a measure of safety that allows patients to evaluate contributing factors related to patient safety in primary care. This study aimed to examine which questionnaire items of the PC-PMOS could be used in Korean dental institutions. A survey of the Korean translation of the PC-PMOS, a self-reported questionnaire, was conducted in August 2022 by 400 adults who had used dental-care services within the last three years. Of the 77 items, 34 were selected using principal component analysis and two experts' evaluations based on face validity. Five domains were identified from factor analysis: patient centeredness, patient information update, complaint processing, communication, and information about the complaint process. The Cronbach's alpha of the data was 0.913, indicating high reliability. As a result of the generalized multiple regression analysis, regression coefficients were not statistically significant, except for household income. This indicated that there was no bias in the patient safety scores of dental institutions evaluated by patients within the range of independent variables used in this study. The five domains with 34 items identified in this study suggested the factors that contribute to the safety of patients who used dental care services in Korea. However, validation of this study result is still important to refine questionnaires suitable for dental institutions in Korea so as to further improve the quality of dental care.

• Wind and Structures
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• v.35 no.6
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• pp.405-418
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• 2022

The aerodynamic behaviour of a CRH high-speed train under three infrastructure scenarios (flat ground, embankment, and viaduct) in the presence of a crosswind was simulated using a 1/8th scaled train model with three cars and the IDDES framework. The time-averaged and instantaneous flow field around the model were examined. The employed numerical algorithm was verified through a wind tunnel test, and the grid and timestep resolution analyses were conducted to ensure the reliability of the data. It was noted that the flow around the rail line was different under different infrastructure scenarios, especially in the case of the embankment, which degraded the aerodynamic performance of the train under the crosswind. The flow around the train on the flat ground and viaduct was different, although the aerodynamic performance of the train was similar in both cases. Moreover, the viaduct accidents were noted to have the most critical consequences, thereby requiring the most attention. The aerodynamic performance of the train on the windward track of the embankment under the crosswind was worse than that of the train on the leeward track. But for the other two infrastructure scenarios, the aerodynamic performance of the train on the windward track is relatively dangerous, which is mainly caused by the head car. These observations suggest that the aerodynamic behaviour of the train on an embankment under a crosswind must be carefully considered and that certain wind protection measures must be adopted around rail lines in windy areas.

• Journal of Digital Convergence
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• v.19 no.11
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• pp.415-424
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• 2021

The purpose of the current study is to to examine the psychometric properties of the Subjective Agingwell Scale (SAS). Three hundred and forty two elders completed the SAS and the scales assessing subjective well-being, optimism, perceived control and adhering to healthy behavior. The 11-item SAS that displays good internal reliability and good fit to the three-factor model consisting of cognitive satisfaction, positive affect, and spiritual fullness. Correlational analyses with measures of subjective agingwell, subjective well-being, and optimism provide evidence for construct validity. Moreover, the results from hierarchical regression analyses show criterion-related validity of the SAS. This scale could be used in the field to measure and promote subjective agingwell.

• Journal of the Korea Society of Computer and Information
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• v.27 no.10
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• pp.123-130
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• 2022

In this paper is one of the measures to prevent concrete collapse accidents at construction sites in advance. Analyzed based on accumulated Meteorological Agency data. It is a reliable model that confirms the prediction of the decrease rate occurrence interval, and the verification items such as p_value is 0.5 or less and ecof appears in one direction through the SARIMA model, which is suitable for regular and clear time series data models, ensure reliability. Significant results were obtained. As a result of analyzing the temperature change by time zone and the water reduce ratio by section using the data secured based on such trust, the water reduce ratio is the highest in the 29-31 ℃ section from 12:00 to 13:00 from July to August. found to show. If a factor in the research result interval occurs using the research results, it is expected that the batch plant will produce Ready-mixed concrete that reflects the water reduce ratio at the time of designing the water-cement mixture, and prevent the decrease in concrete compressive strength due to the water reduce ratio.