• The Journal of the Korea Contents Association
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• v.21 no.5
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• pp.548-560
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• 2021

This study estimates the amount of willingness to pay of the general public by applying the contingent value method to the Korea Program for International cooperation in Agricultural technology(KOPIA), a representative project of the Rural Development Administration. Prior to measuring the amount of willingness to pay for the KOPIA project, a survey of the perception of agriculture and rural areas and respondents' basic perception of public development assistance showed a positive perception of official development assistance in general. In particular, many respondents said that aid from the international community in the past contributed to Korea's economic and social development along with the importance of the international community helping the poor in underdeveloped countries. As a result of estimating the acceptance probability regression model by including the public awareness as a variable, the higher the income of the respondents and the more positive the perception of public development aid, the higher the amount of willingness to pay. The average annual payment amount per household derived from the acceptance probability regression model was estimated to be about 30,729 won.Based on the results of this analysis, several policy implications related to the public development aid policy of Korea were presented.

• 한국노년학
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• v.32 no.3
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• pp.869-893
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• 2012

The purpose of this study was to examine the effects of relationships with family on successful aging according to the four attachment style to children. 509 elderly people over 60 years old having a spouse, non-cohabitated children were included. The main findings through this study are as follows; First, secure and preoccupied attachment style were statistically higher than dismissing and fearful attachment style in successful aging and relationship with spouse, children and grandchildren. Second, total paths of research model were different according to the attachment style of the elderly. Model fit of secure attachment style was not good and the effects of relationships with family on successful aging were not statistically significant. In case of preoccupied attachment style, the effect of relationship with spouse and grandchildren on successful aging were significant. Also the effect of relationship with spouse on relationship with children was significant and the effect of relationship with children on relationship with grandchildren was significant. Relationship with grandchildren mediates the effect of relationship with children on successful aging. In case of dismissing attachment style, the effect of relationship with spouse and grandchildren on successful aging were significant. Also the effect of relationship with children on relationship with grandchildren was significant. Relationship with grandchildren mediates the effect of relationship with children on successful aging. In case of fearful attachment style, the effect of relationship with spouse and grandchildren on successful aging were significant. Also the effect of relationship with spouse on relationship with children was significant and the effect of relationship with children on relationship with grandchildren was significant. Relationship with children mediates the effect of relationship with spouse on successful aging. This study explains the role of attachment styles as moderation variable of relationship with family on successful aging and also suggests the importance of marital and grandparents-grandchildren relationship as alternative supporter when the elderly has relational problems with adult children.

• Journal of Animal Science and Technology
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• v.63 no.2
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• pp.319-331
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• 2021

Heat stress (HS) causes adverse impacts on pig production and health. A potential biomarker of HS is required to predict its occurrence and thereby better manage pigs under HS. Information about the saliva metabolome in heat-stressed pigs is limited. Therefore, this study was aimed to investigate the effects of acute HS on the saliva metabolome and identify metabolites that could be used as potential biomarkers. Growing pigs (n = 6, 3 boars, and 3 gilts) were raised in a thermal neutral (TN; 25℃) environment for a 5-d adaptation period (CON). After adaptation, the pigs were first exposed to HS (30℃; HS30) and then exposed to higher HS (33℃; HS33) for 24 h. Saliva was collected after adaptation, first HS, and second HS, respectively, for metabolomic analysis using 1H-nuclear magnetic resonance spectroscopy. Four metabolites had significantly variable importance in the projection (VIP > 1; p < 0.05) different levels in TN compared to HS groups from all genders (boars and gilts). However, sex-specific characteristics affected metabolites (glutamate and leucine) by showing the opposite results, indicating that HS was less severe in females than in males. A decrease in creatine levels in males and an increase in creatine phosphate levels in females would have contributed to a protective effect from protein degradation by muscle damage. The results showed that HS led to an alteration in metabolites related to energy and protein. Protection from muscle damage may be attributed to the alteration in protein-related metabolites. However, energy-related metabolites showed opposing results according to sex-specific characteristics, such as sex hormone levels and subcutaneous fat layer. This study had shown that saliva samples could be used as a noninvasive method to evaluate heat-stressed pigs. And the results in this study could be contributed to the development of a diagnostic tool as a noninvasive biomarker for managing heat-stressed pigs.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.1
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• pp.713-718
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• 2021

This study was conducted to clarify the role and importance of dental hygienists in improving patient satisfaction in dental medical institutions, and to improve the social position, working conditions, and environment of dental hygienists. This study evaluated the impact of dental hygienists on dental satisfaction, revisits, and doctor recommendations for patients who had received prosthodontic treatment at dentistry in the last 10 years. This study analyzed the data from 166 survey questionnaires from June 1, to July 2, 2020. For data analysis, the SPSS Ver 23.0 program was used to calculate frequency and percentage, mean and standard deviation of the variables, Pearson correlation analysis, and multiple regression analysis. As a result, the average quality of medical services provided by dental hygienists among prosthetics was 4.05, the average dental satisfaction was 4.27, the average revisit was 3.97, and the average recommendation was 4.01. As a result of Pearson's correlation analysis, there was a significant positive correlation between each variable (P<0.01). As a result of multiple regression analysis, the level of knowledge appeared as a factor affecting dental satisfaction (P<0.05). The factors influencing both the revisits and the intention to recommend were the level of knowledge and the level of education (P<0.05).

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.719-730
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• 2020

This study examined the degree and relations of stroke literacy, health literacy, stroke knowledge, and self-management to identify the significant determining factors affecting stroke prevention among middle-aged and older adults with a high incidence of stroke. Data on the sociodemographic characteristics, stroke literacy, health literacy, stroke knowledge, and self-management of 198 participants were collected from December 5, 2019, to March 31, 2020, using a structured questionnaire. The data were analyzed using the SPSS/WIN 23.0 program. The determining factors affecting self-management in middle-aged and older adults were age (β=.190. p=.015), followed in order by smoking (β=-.226, p=.001), self-rated health status (β=.297, p<.001), and stroke knowledge (β=-.168, p=.014); the explanation power was approximately 20.3%. The results suggest that the self-rated health status and stroke knowledge should be considered when developing nursing interventions to improve self-management among middle-aged and older adults. Furthermore, it will be necessary to find the intervening variable between stroke knowledge and self-management for community-dwelling middle-aged and older adults in the community. Overall, these findings underscore the importance of systematic and ongoing education on stroke prevention.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.12
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• pp.586-594
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• 2020

This study examined the effect of self-esteem of pre-infant teachers on self-elasticity, emotional regulation, and empathy. The subjects of this study were 230 university students from W University's Early Childhood Education Department in location I. The data were analyzed using SPSS 24.0. In addition, in each sub-variable, self-elasticity was found to have the greatest positive correlation with positivity, emotional regulation ability with self-emotional regulation ability, and empathy ability with cognitive empathy ability. Second, self-esteem had a significant positive effect on self-elasticity, and among the sub-variables, this study found that general self-concept, self-responsibility, and personal integrity in order were important determinants. Third, self-esteem has an influence on personal integrity in emotional regulation ability. Fourth, as for the effect of self-esteem on empathy ability, it was found that self-assertion had a significant and positive effect on empathy ability. These research results have led to re-awareness of the importance of pre-service early childhood teachers' self-esteem, suggesting that research on various educational activities that can improve self-esteem in the curriculum is needed.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.16 no.1
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• pp.139-146
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• 2021

This study studied the network between positive psychology capital, intention of start-up, and start-up behavior for learners who are willing to start a business. The research targets were intended to study the impact of the connection relationship between each variable, targeting nail art certification learners who are willing to start their own businesses. For this study, the measurement variables of positive psychology capital, intention of start-up, and start-up behavior were set, and the collected data were analyzed for connection-centeredness and eigenvector after data collection. The findings are as follows. First, some variables affecting the intention of start-up showed optimism, resilience and hope of positive psychology capital. Second, the intention to start a business was shown to have a significant impact on the behavior of start-ups, which, unlike the preceding study, appeared to be almost outside the network structure, showing that the behavior of start-ups was not significantly affected by other variables. Third, it is important to increase self-efficacy in positive psychological capital in order to increase the behavior of start-ups. Fourth, the analysis of the eigenvactor among positive psychology capital, intention of start-up, and start-up behavior showed optimism as some of the most central variables. In other words, prospective start-ups were found to be aware of the hardships and expected positive results in the future. The implications of this study, along with the intention and behavior of prospective entrepreneurs, are important factors in positive psychology capital, and suggest the importance of various educational programs that can be enhanced by positive psychology capital in start-up education or training programs and what should be taught. In addition, this study analyzed the network by approaching it from the perspective of positive psychology capital of prospective entrepreneurs in order to enhance the effectiveness of support programs for start-ups by the government, public institutions or universities in the future.

• The Journal of the Convergence on Culture Technology
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• v.8 no.4
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• pp.45-51
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• 2022

This study aims to provide basic data on socioeconomic and social activities from the point of view that disability or disease accompanying the suffering of industrial accident subjects is directly related to individual socioeconomic activity and is a major variable affecting current health and daily life satisfaction. The purpose of this study is to investigate the relationship between pain and life satisfaction and to suggest basic data for economic and psychological rehabilitation of industrial accident insurance beneficiaries by linking factors affecting life satisfaction with industrial accident services. As a result of the study, it was found that workers' compensation insurance benefit recipients had an effect on their daily life satisfaction after becoming an industrial accident patient due to industrial accident pain. There was a positive(+) relationship between rehabilitation services and medical counseling services. Occupational accident pain lowers self-esteem, which is a characteristic of an individual, and even if current health improves, satisfaction with daily life decreases. The importance of industrial accident-related services can be seen in that the satisfaction of daily life is increased through rehabilitation services and medical consultation services. In addition, it was indirectly confirmed that satisfaction with rehabilitation services and health can be improved as a result of continuing attempts to improve self-esteem suitable for patients in various problems and situations after an industrial accident.

• Journal of the Korean GEO-environmental Society
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• v.23 no.8
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• pp.29-36
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• 2022

The importance of subsurface information is becoming crucial in urban area due to increase of underground construction. The position of underground facilities should be identified precisely before excavation work. Geophyiscal exporation method such as ground penetration radar (GPR) can be useful to investigate the subsurface facilities. GPR transmits electromagnetic waves to the ground and analyzes the reflected signals to determine the location and depth of subsurface facilities. Unfortunately, the readability of GPR signal is not favorable. To overcome this deficiency and automate the GPR signal processing, deep learning technique has been introduced recently. The accuracy of deep learning model can be improved with abundant training data. The ground is inherently heteorogeneous and the spacially variable ground properties can affact on the GPR signal. However, the effect of ground heterogeneity on the GPR signal has yet to be fully investigated. In this study, ground heterogeneity is simulated based on the fractal theory and GPR simulation is carried out by using gprMax. It is found that as the fractal dimension increases exceed 2.0, the error of fitting parameter reduces significantly. And the range of water content should be less than 0.14 to secure the validity of analysis.

• The Journal of Information Systems
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• v.31 no.3
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• pp.177-195
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• 2022

Purpose This paper aims to prepare a full operational readiness by establishing an optimal flight plan considering the weather conditions in order to effectively perform the mission and operation of military aircraft. This paper suggests a flight prediction model and rules by analyzing the correlation between flight implementation and cancellation according to weather conditions by using big data collected from historical flight information of military aircraft supplied by Korean manufacturers and meteorological information from the Korea Meteorological Administration. In addition, by deriving flight rules according to weather information, it was possible to discover an efficient flight schedule establishment method in consideration of weather information. Design/methodology/approach This study is an analytic study using data mining techniques based on flight historical data of 44,558 flights of military aircraft accumulated by the Republic of Korea Air Force for a total of 36 months from January 2013 to December 2015 and meteorological information provided by the Korea Meteorological Administration. Four steps were taken to develop optimal flight prediction models and to derive rules for flight implementation and cancellation. First, a total of 10 independent variables and one dependent variable were used to develop the optimal model for flight implementation according to weather condition. Second, optimal flight prediction models were derived using algorithms such as logistics regression, Adaboost, KNN, Random forest and LightGBM, which are data mining techniques. Third, we collected the opinions of military aircraft pilots who have more than 25 years experience and evaluated importance level about independent variables using Python heatmap to develop flight implementation and cancellation rules according to weather conditions. Finally, the decision tree model was constructed, and the flight rules were derived to see how the weather conditions at each airport affect the implementation and cancellation of the flight. Findings Based on historical flight information of military aircraft and weather information of flight zone. We developed flight prediction model using data mining techniques. As a result of optimal flight prediction model development for each airbase, it was confirmed that the LightGBM algorithm had the best prediction rate in terms of recall rate. Each flight rules were checked according to the weather condition, and it was confirmed that precipitation, humidity, and the total cloud had a significant effect on flight cancellation. Whereas, the effect of visibility was found to be relatively insignificant. When a flight schedule was established, the rules will provide some insight to decide flight training more systematically and effectively.