• Korean Journal of Culture and Social Issue
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• v.26 no.2
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• pp.99-119
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• 2020

The purpose of this study was to construct and test a hypothetical model about impact of childhood trauma on Relationship Addiction of Korean adults the multiple mediating effects of rejection sensitivity and internalized shame. A purposive sample of 465 Korean adults was recruited from three provincial areas. The collected data were then analyzed using SPSS 23.0 and AMOS 23.0 programs. For data analysis, descriptive statistics and structural equation modeling were performed. Multiple mediating effects analysis using phantom variable and bootstrapping were implemented to verify the mediating effect of the research model. We found no significant direct effect of childhood trauma on relationship addiction, but the effects of childhood trauma on Relationship Addiction were successively multi-mediated by internalized shame and rejection sensitivity (B=.265, p<.01), and single-mediated by internalized shame (B=.496, p<.01). Based on the results of this study, it can be suggested that in order to prevent relationship addiction of adults, it is necessary to first explore whether he has experienced childhood trauma and thereby has not only internalized shame but also rejection sensitivity.

• Korean Journal of Culture and Social Issue
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• v.27 no.1
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• pp.35-49
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• 2021

The purpose of this study was examine the depression among Mongolians in South Korea. We also determined the effect of acculturative stress and social support on depression. In this study, total of 200 adults over age 18 completed the BDI-II of Mongolian Version, Acculturative stress scale for international student, The Multi-dimensional Scale of Perceived Social Support. Data were analyzed by using the factor analysis, correlation analysis, t-test, and hierarchical regression analysis. We used SPSS 22.0, AMOS 22.0. We found significant difference in mean scores between groups according to socio-demographic characteristics. The level of depression was high in over 3 years immigrants group (M = 8.41, SD = 9.6954), marriage immigrants group (M = 19.1, SD = 16.7649), and female groups (M = 7.61, SD = 9.2188) than compared to reference groups. Acculturative stress and social support of Mongolian immigrants had a significant impact on depression (β = .365, p <.001; β = .- 555, p <.001). There was a moderating effect of social support on the relationship between acculturative stress and depression (β = 1.080, p <.001). The limitations and implications of the study were discussed. We conclude that this study can be used to assess the depression and the mental health of Mongolians in South Korea.

• The Journal of the Korea Contents Association
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• v.22 no.6
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• pp.354-368
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• 2022

The purpose of this study was to verify whether there were significant differences in the levels and relationships of emotional intelligence, school adaptation, self-resilience, positive human relationships, and depression between elementary school students who participated in after-school music activities and those who did not. The participants of this study were 379 fourth, fifth, and sixth grade elementary school students in the Capital Area and Gyeongnam Province participated in after-school music activities and 368 students who did not, totaling 747 students. For research analysis, t-test and multi-group analysis were performed, and the analyzed results are as follows. First, the level of emotional intelligence, self-resilience, positive human relationships, and school adaptation were higher in the participating group and the level of depression was lower than the group that did not participate. Second, as a result of multiple group analysis, the participating group had stronger influences on the paths of [emotional intelligence→self-resilience], [emotional intelligence→positive human relationship], [emotional intelligence→depression], [emotional intelligence→school adaptation], and [self-resilience→school adaptation] than those of non-participating group. Third, the participating group showed mediating effects from self-resilience, positive human relationships, and depression in the relationship between emotional intelligence and school adaptation. On the other hand, the non-participating group manifested significant mediating effects only from self-resilience and depression variables in the relationship between emotional intelligence and school adaptation.

• Journal of Korea Entertainment Industry Association
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• v.15 no.4
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• pp.255-265
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• 2021

The purpose of this study was to examine the effects of Kahoot!(Game-based Student Response System) on nursing education. This study used an one group Pretest-posttest design. Participants were 179 nursing students from one D university located in Gwangju, Korea. The Kahoot!(Game-based Student Response System) was provided for 6 times. Data were collected between August 26 and October 25, 2019. The collected data was analyzed by descriptive statistics, paired t-test, pearson's correlation coefficient and stepwise multiple regression using IBM SPSS 21.0 program. The results showed that learning engagement(t=-6.257, p=.000) was significantly higher than levels before Kahoot!(Game-based Student Response System), critical thinking disposition(t=-2.163, p=.032) was significantly higher than levels before Kahoot!(Game-based Student Response System), problem solving ability(t=-3.032, p=.003) was significantly higher than levels before Kahoot!(Game-based Student Response System). Significant relationships were found among learning engagement(r=.375, p=.000), critical thinking disposition(r=.286, p=.000), problem solving ability(r=.291, p=.000) and learning satisfaction. The results of stepwise multiple regression indicates that learning engagement(β=.307, p=.000), problem solving ability(β=.158, p=.041) predicts 15.2% in learning satisfaction(F=16.905, p=.000). In conclusion, Kahoot!(Game-based Student Response System) is effective in improving learning engagement and problem solving ability to nursing education.

• Applied Chemistry for Engineering
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• v.33 no.6
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• pp.563-573
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• 2022

This work aimed to develop a new equation for turbidity (Turb) simulation and prediction using statistical methods based on principal component analysis (PCA) and multiple linear regression (MLR). For this purpose, water samples were collected monthly over a five year period from Cheurfa dam, an important reservoir in Northwestern Algeria, and analyzed for 12 parameters, including temperature (T°), pH, electrical conductivity (EC), turbidity (Turb), dissolved oxygen (DO), ammonium (NH₄⁺), nitrate (NO₃^-), nitrite (NO₂^-), phosphate (PO₄^3-), total suspended solids (TSS), biochemical oxygen demand (BOD₅) and chemical oxygen demand (COD). The results revealed a strong mineralization of the water and low dissolved oxygen (DO) content during the summer period. High levels of TSS and Turb were recorded during rainy periods. In addition, water was charged with phosphate (PO₄^3-) in the whole period of study. The PCA results revealed ten factors, three of which were significant (eigenvalues >1) and explained 75.5% of the total variance. The F1 and F2 factors explained 36.5% and 26.7% of the total variance, respectively and indicated anthropogenic pollution of domestic agricultural and industrial origin. The MLR turbidity simulation model exhibited a high coefficient of determination (R² = 92.20%), indicating that 92.20% of the data variability can be explained by the model. TSS, DO, EC, NO₃^-, NO₂^-, and COD were the most significant contributing parameters (p values << 0.05) in turbidity prediction. The present study can help with decision-making on the management and monitoring of the water quality of the dam, which is the primary source of drinking water in this region.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1709-1722
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• 2022

The rise in temperature induced by global warming caused in El Nino and La Nina, and abnormally changed the temperature of seawater. Rainfall concentrates in some locations due to abnormal variations in seawater temperature, causing frequent abnormal floods. It is important to rapidly detect flooded regions to recover and prevent human and property damage caused by floods. This is possible with synthetic aperture radar. This study aims to generate a model that directly derives flood-damaged areas by using modified U-NET and TerraSAR-X images based on Multi Kernel to reduce the effect of speckle noise through various characteristic map extraction and using two images before and after flooding as input data. To that purpose, two synthetic aperture radar (SAR) images were preprocessed to generate the model's input data, which was then applied to the modified U-NET structure to train the flood detection deep learning model. Through this method, the flood area could be detected at a high level with an average F1 score value of 0.966. This result is expected to contribute to the rapid recovery of flood-stricken areas and the derivation of flood-prevention measures.

• 한국노년학
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• v.40 no.1
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• pp.179-196
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• 2020

The purpose of this study was to identify the factors impacting fear of dementia, targeting the aged in the community. The study targeted 258 seniors aged 65 or older attending the senior college or using the senior citizen community center in areas of Jeollannam-do. Data were analyzed using descriptive statistics, t-test, ANOVA, Pearson correlation coefficient and a stepwise multiple linear regression. Fear of dementia of the aged showed significant positive correlations with dementia anxiety, and aged anxiety. dementia anxiety, aged anxiety, dementia experience, use of a hearing aid, religion, level of dementia interest were significant predictors influencing fear of dementia of aged in the community, and these variables accounted for 37.2% of the variance. Therefore, this study suggests that in order to p revent fear of dementia of aged people in the primary health care setting, it is necessary to have a nurse's assessment on the factors affecting dementia as well as a multi-faceted education strategy for proper recognition of dementia.

• The Korean Journal of Applied Statistics
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• v.35 no.4
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• pp.457-468
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• 2022

In aged society, it is important to prevent older people from being disability needing long-term care. The purpose of this study is to develop a prediction model to discover high-risk groups who are likely to be beneficiaries of Long-Term Care Insurance. This study is a retrospective study using database of National Health Insurance Service (NHIS) collected in the past of the study subjects. The study subjects are 7,724,101, the population over 65 years of age registered for medical insurance. To develop the prediction model, we used logistic regression, decision tree, random forest, and multi-layer perceptron neural network. Finally, random forest was selected as the prediction model based on the performances of models obtained through internal and external validation. Random forest could predict about 90% of the older people in need of long-term care using DB without any information from the assessment of eligibility for long-term care. The findings might be useful in evidencebased health management for prevention services and can contribute to preemptively discovering those who need preventive services in older people.

• The Journal of the Korea Contents Association
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• v.22 no.4
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• pp.379-402
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• 2022

The purpose of this study was to verify the effectiveness of the employee metacognition and it's positive effect on employee agility. Also it aims to investigate the mechanism through the cascading multi-mediating effect through the role breadth self-efficacy and learning agility in such a relationship. In order to solve the common-method bias, independent and dependent variables were measured with time lag, and the relationship between variables was clearly verified by applying the position and the length of time worked with the supervisor as control variables. In testing the hypothesis, 478 questionnaires collected from whom worked at the company has more than 300 office workers in various industries were analyzed. As the result, firstly metacognition had a significant positive(+) effect on employee agility. Second, role breadth self-efficacy was found to positively mediate the relationship between metacognition and employee agility. Third, learning agility was found to mediate metacognition and employee agility positively(+). Fourth, metacognition serially mediates role breadth self-efficacy and learning agility, and the positive(+) effect on employee agility was verified. In addition, metacognition had a greater effect on member agility when passing through role breadth self-efficacy and learning agility rather than the direct effect on employee agility.

• Korean Journal of Remote Sensing
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• v.38 no.5_1
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• pp.535-543
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• 2022

A drone is used to diagnose crop growth and to provide information through images in the agriculture field. In the case of using high spatial resolution drone images, growth information for each object can be produced. However, accurate object detection is required and adjacent objects should be efficiently classified. The purpose of this study is to develop a Chinese cabbage object detection algorithm using multispectral reflectance images observed from drone and computer vision techniques. Drone images were captured between 7 and 15 days after planting a Chinese cabbage from 2018 to 2020 years. The thresholds of object detection algorithm were set based on 2019 year, and the algorithm was evaluated based on images in 2018 and 2019 years. The vegetation area was classified using the characteristics of spectral reflectance. Then, morphology techniques such as dilatation, erosion, and image segmentation by considering the size of the object were applied to improve the object detection accuracy in the vegetation area. The precision of the developed object detection algorithm was over 95.19%, and the recall and accuracy were over 95.4% and 93.68%, respectively. The F1-Score of the algorithm was over 0.967 for 2 years. The location information about the center of the Chinese cabbage object extracted using the developed algorithm will be used as data to provide decision-making information during the growing season of crops.