• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.83-91
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• 2020

This study aims to identify research topics and examine the trend of Covid19-related papers on DBpia. Applying latent Dirichlet allocation (LDA), we have extracted seven research topics, each of which concerns "International Dynamics", "Technology & Security", "Psychological Impact", "Biomedical-Related", "Economic Impact", "Online Education", and "Religion-Related". In addition, we used the multinomial logistic model to examine the trend of research topics. We found that the papers mainly cover topics related to "International Dynamics" and "Biomedical-Related" before June 2020, but the topics have become diverse since then. In particular, topics regarding "Economic Impact", "Online Education" and "Psychological Impact" has drawn increased attention of researchers. The findings would provide a guideline for collaboration in Covid19-related research, and could serve as a reference work for active research.

• The Korean Journal of Food And Nutrition
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• v.34 no.6
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• pp.576-583
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• 2021

The purpose of this study was to estimate the influence of the determinants for home meal replacement (HMR) purchase frequency before and after COVID-19. Multinomial logistic regression was applied to the 2018~2020 Consumer Behavior Survey for Food data from the Korea Rural Economic Institute (KREI). Gender, age, number of households, monthly income, use of eating out, delivery and takeout order service, HMR food safety concern, the frequency of cooking at home, grocery shopping, and eating alone were applied as the explanatory variables to explain HMR purchase frequency. The results are as below. Compared to the previous year, the growth rate of HMR purchase frequency in 2020 was relatively high, indicating that the COVID-19 outbreak acted as a catalyst. Unlike in 2018 and 2019, there was no statistical difference in the HMR purchase frequency between single- and multi-person households in 2020, with indicating multi-person households began to emerge as one of the major HMR consumption groups. Unlike 2018, the 2020 HMR purchase frequency showed a statistically positive relationship with those of grocery shopping and eating alone. There was a positive relationship between the frequency of eating out/food delivery orders and HMR purchases. The more often cooking at home occurred, the less HMR food was purchased.

• Research in Community and Public Health Nursing
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• v.33 no.3
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• pp.299-311
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• 2022

Purpose: Untreated depression in adolescents affects their entire life. It is important to detect and intervene early depression in adolescence considering the characteristics of adolescent's depressive symptoms accompanied by internalization and externalization. The aim of this study was to identify latent classes of depressive symptom trajectories of adolescents and determinants of classes in Korea. Methods: The three time-point (2018~2020) data derived from the Korean Children and Youth Panel Survey 2018 were used (N=2,325). Latent Growth Curve Modeling (LGCM) was conducted to explore the depressive symptom trajectories in all adolescents, and Latent Class Growth Modeling (LCGM) was conducted to identify each latent class. Multinomial logistic regression analysis was performed to confirm the determinants of each latent class. Results: The LGCM results showed that there was no statistically significant change in all adolescents' depressive symptoms for 3 years. However, the LCGM results showed that four latent classes showing different trajectories were distinguished: 1) Low-stable (intercept=14.39, non-significant slope), 2) moderate-increasing (intercept=19.62, significantly increasing slope), 3) high-stable (intercept=26.30, non-significant slope), and 4) high-rapidly decreasing (intercept=26.34, significantly rapidly decreasing slope). The multinomial logistic regression analysis showed that the significant determinants (i.e., gender, self-esteem, aggression, somatization, peer relationship) of each latent class were different. Conclusion: When screening adolescent's depression, it is necessary to monitor not only direct depression symptoms but also self-esteem, aggression, somatization symptoms, and peer relationships. The findings of this study may be valuable for nurses and policy makers to develop mental health programs for adolescents.

• The Korean Journal of Food And Nutrition
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• v.36 no.4
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• pp.309-320
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• 2023

This study examined the determinants of healthy food purchases before and after COVID-19 in Korea. Binomial and multinomial logistic regression models were applied to Korea Rural Economic Institute's Food Consumer Behavior Survey data from 2019 to 2021. The analysis revealed a significant decrease in the non-intake of healthy food in 2021 compared to 2019, suggesting the impact of COVID-19 on healthy food consumption. Consumption patterns also changed, with a decrease in direct purchases and an increase in gift-based purchases. Several variables showed significant effects on healthy food intake. Single-person households exhibited a higher probability of eating healthy food after COVID-19. The group perceiving themselves as healthy had a lower likelihood of consuming healthy food pre-COVID-19, but this changed after the pandemic. Online food purchases, eco-friendly food purchases, and nut consumption showed a gradual decrease in the probability of non-intake over time. Gender and age also influenced healthy food intake. The probability of eating healthy food increased in the older age group compared to the younger group, and the probability increased significantly after COVID-19. The probability of buying gifts was significantly higher in those in their 60s, indicating that the path to obtaining healthy food differed by age.

• Quality Improvement in Health Care
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• v.30 no.1
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• pp.3-14
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• 2024

Purpose: We conducted this study with the aim of characterizing safety attitudes (SA) among medical staff in a disadvantaged area of Vietnam and examining associated factors with SA. Methods: A cross-sectional survey was conducted on 442 health staff members at four hospitals in Son La Province from June until August 2021. We used the Vietnamese shortened edition of the Safety Attitudes Questionnaire to measure the SA of study participations. We chose latent class analysis (LCA) to identifying the number of latent classes of SA among the study subjects. Multinomial logistic regression was used to examine factors associated with the identified SA classes. Results: The results of our LCA showed that there were three latent classes, namely high SA group (n=150, 33.9%), moderate SA group (n=236, 53.4%), and low SA group (n=56, 12.7%). The multinomial logistic regression analysis found that medical staff who had university education and above, who were nurses, and who served in non-clinical areas were more likely to be in the moderate SA group and in the high SA group than in the low SA group. Conclusion: Based on these results, several recommendations could be made to improve the SA of healthcare workers in disadvantaged areas. Further research with larger sample sizes and more diverse populations is needed to confirm these findings and to develop effective interventions to improve the SA of healthcare workers in disadvantaged areas.

• Journal of the Korean Data and Information Science Society
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• v.24 no.6
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• pp.1465-1475
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• 2013

The chi-square type test statistic is the most commonly used test in terms of measuring testing goodness-of-fit for multinomial logistic regression model, which has its grouped data (binomial data) and ungrouped (binary) data classified by a covariate pattern. Chi-square type statistic is not a satisfactory gauge, however, because the ungrouped Pearson chi-square statistic does not adhere well to the chi-square statistic and the ungrouped Pearson chi-square statistic is also not a satisfactory form of measurement in itself. Currently, goodness-of-fit in the ordinal setting is often assessed using the Pearson chi-square statistic and deviance tests. These tests involve creating a contingency table in which rows consist of all possible cross-classifications of the model covariates, and columns consist of the levels of the ordinal response. I examined goodness-of-fit tests for a proportional odds logistic regression model-the most commonly used regression model for an ordinal response variable. Using a simulation study, I investigated the distribution and power properties of this test and compared these with those of three other goodness-of-fit tests. The new test had lower power than the existing tests; however, it was able to detect a greater number of the different types of lack of fit considered in this study. I illustrated the ability of the tests to detect lack of fit using a study of aftercare decisions for psychiatrically hospitalized adolescents.

• Journal of the Korean Society of School Health
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• v.35 no.3
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• pp.133-142
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• 2022

Purpose: The purpose of the study was to investigate the effect of the environment on adolescent binge drinking. Methods: The study was designed as a cross-sectional study. Using statistics from the 17th (20201) Korea Youth Risk Behavior Web-based Survey, the raw data target population was 2,629,588 people, and the sample group used for analysis as the final data was 54,848 people. A Rao-scott 𝑥² test and univariate multinomial logistic regression analysis were performed using IBM SPSS 27.0. Results: In the results of univariate logistic regression analysis and multivariate logistic regression analysis, common related variables were gender, school level, academic achievement, sleep satisfaction, current smoking, daily smoking, and alcohol education experience. Conclusion: As a result of confirming the factors influencing binge drinking in Korean adolescents, some variables that increase the possibility of problematic drinking behavior in the socio-environmental areas such as individuals, communities, and national policies were identified. For effective prevention and intervention, it is necessary to develop programs to build a healthy environmental support system with support from national policies, including individuals, peer groups, and communities.

• The Korean Journal of Applied Statistics
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• v.23 no.5
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• pp.857-870
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• 2010

This study was conducted to investigate the relationship between the socio-demographic factors and the Korean consumers palatability evaluation grades with Hanwoo sensory evaluation data from 2006 to 2008 by National Institute of Animal Science. The dichotomy logistic regression model and the multinomial logistic regression model are fitted with the independent variables such as the consumer living location, age, gender occupation, monthly income, beef cut and the the palatability grade as the categorical dependent variable and tenderness, 리avor and juiciness as the continuous dependent variable. Stepwise variable selection procedure is incorporated to find the final model and odds ratios are calculated to nd the associations between categories.

• Journal of the East Asian Society of Dietary Life
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• v.16 no.4
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• pp.488-495
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• 2006

The purposes of this study were to measure respondent's demographic characteristics, respondent's attitudes toward chicken meat, and factors influencing the level of perceived helpfulness of country of origin in predicting the safety of chicken. The data was collected through a consumer survey during the March 2006. Two hundred fifty meat consumers living in Suncheon, the eastern part of Chonnam, were randomly selected as respondents. Eleven respondents did not complete the survey instrument, resulting in a final sample size of 239. All estimations were carried out using correlation, logistic procedure of SAS package, and plum procedure of SPSS. The level of perceived helpfulness of country of origin in predicting the safety of chicken meat was significantly correlated with trust, antibiotics and salmonella/bacteria among the attitude variables. The proportional odds assumption of the model was violated at p<0.05. The estimated results of the multinomial logit model indicated that income, single, occupation, and education significantly affected helpful perception over not helpful perception, while gender and occupation significantly affected very helpful perception over not helpful perception in the case of the extended model. These study results from this study could be useful in developing marketing and health promotion strategies, as well as government trade policy.

• Journal of Sensor Science and Technology
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• v.29 no.5
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• pp.348-353
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• 2020

This paper presents an adaptive method to avoid obstacles in various environmental settings, using a two-dimensional (2D) LiDAR sensor for mobile robots. While the conventional reaction based smooth nearness diagram (SND) algorithms use a fixed safety distance criterion, the proposed algorithm autonomously changes the safety criterion considering the obstacle density around a robot. The fixed safety criterion for the whole SND obstacle avoidance process can induce inefficient motion controls in terms of the travel distance and action smoothness. We applied a multinomial logistic regression algorithm, softmax regression, to classify 2D LiDAR point clouds into seven obstacle structure classes. The trained model was used to recognize a current obstacle density situation using newly obtained 2D LiDAR data. Through the classification, the robot adaptively modifies the safety distance criterion according to the change in its environment. We experimentally verified that the motion controls generated by the proposed adaptive algorithm were smoother and more efficient compared to those of the conventional SND algorithms.