• 한국노년학
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• v.28 no.4
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• pp.1147-1164
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• 2008

There has been a sharp increase in the number of grandmothers raising grandchildren in contemporary Korean society. However, little is known about the complexity of the experiences of the custodial grandparenting. Most of the studies mainly examined burden/cost and have paid little attention to the positive aspects of custodial grandparenting. In order to overcome this limitation of previous research, this study aims 1) to examine not only the costs but also the rewards of custodial grandparenting and to explore related factors, 2) to develop the typology based on relative rewards-burden perception of grandmothers about custodial grandparenting and explore the group differences. The data were gathered from 449 grandmothers raising their grandchildren as a primary caregiver, using a structured questionnaire. The data were analyzed using descriptive statistics, correlation, hierarchical multiple regression and ANOVA, with SPSS WIN 12.0 program. Main findings are as follows: First, custodial grandmothers report not only care-giving burden such as physical burnout and economic burden but also various rewards such as joy of watching their grandchildren grow and feeling good about themselves to be a help with their adult children, i.e. grandchildren's father or mother. Second, factors related to the level of perceived cost of grandparenting are different from the factors affecting the positive aspects of grandparenting. Third, results of the two by two cross-tab analysis based on the level of rewards and burden show that about 32 percent of the grandparents belong to Type II group(high rewards-low cost). This result is quite contrary to the assumption of previous research focusing mostly on cost and burden of custodial grandparenting. Fourth, four groups were different in terms of grandmother & grandchildren's characteristics. Implications of these results are discussed.

• Therapeutic Science for Rehabilitation
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• v.8 no.1
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• pp.7-25
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• 2019

Objective: The purpose of this study was to perform a systematic literature review focusing on international studies to identify various factors affecting the quality of life(QOL) of dementia patients admitted to long-term care facilities. Methods: From January 2000 to July 2018, the articles published in foreign journals were searched through CINAHL and MEDLINE databases. The main search terms were'dementia or Alzheimer's'. 'quality of life', 'long-term care', 'care home', 'nursing home', 'care institution', 'residential care', 'small- scale setting'. The first 1706 articles were searched, but 10 studies were selected using the selection and exclusion criteria. Results: Analysis of ten cross-sectional studies showed that factors such as physical functioning status, ability to perform activities of daily living, and cognition showed a positive correlation with QOL. Depression and anxiety, severity of dementia, and neuropsychiatric symptoms were found to be negatively correlated with QOL. In addition, two longitudinal studies have confirmed that factors affecting QOL are affected by individual functional status and social environmental factors rather than the size and form of care facilities. Conclusion: This study summarized 10 papers and analyzed them through a systematic review of literature. We found that factors such as individual characteristics and social environment determine QOL of patients with dementia. In this study, various intervention methods to improve QOL of patients with dementia should be developed and used in long-term care facilities by identifying the factors affecting QOL of dementia patients and using them.

• Women's Health Nursing
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• v.25 no.3
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• pp.329-344
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• 2019

Purpose: This study aimed to identify utilization of the work-family support policy (WFSP) and factors affecting retention intention among Korean female military officers. Methods: This cross-sectional survey recruited 103 married female officers from the Korean Army, Navy, and Air force with preschool-aged children through convenience and snowball sampling. Via online surveys from June to November, 2018, the participants self-reported retention intention, work-family conflict, job satisfaction, and utilization of the WFSP. The data were analyzed using descriptive statistics, independent t-tests, one-way analysis of variance, Pearson's correlation coefficient, and multiple linear regression. Results: Retention intention ($22.29{\pm}5.98$) was reported at the mid-level, lower than scores reported in the literature for female workers. Work-family conflict ($32.51{\pm}5.29$) and job satisfaction ($63.10{\pm}7.45$) were above the midpoint levels. Use of maternity leave (100.0%) and parental leave (92.2%) was high, especially compared to the rates of child-care day off (20.4%) and parenting time (20.4%). 'Noticeable increases in childcare services within the army' (22.8%) was reported as the supportive measure needed the most by female military officers. Job satisfaction (${\beta}=.43$, $p{\leq}.001$), the use of parenting time (${\beta}=-0.29$, p=.002), living type (${\beta}=-.18$, p=.043), and service type (${\beta}=-.16$, p=.035) significantly influenced retention intention. Conclusions: The findings highlight the priority areas of importance within the WFSP and suggest that a family-friendly culture can improve female officers' retention intention. Accordingly, policy changes at the Ministry of National Defense improving the system to enhance a family-friendly culture in the military is expected to strengthen the retention intention of female officers and contribute to excellence in the military workforce.

• Journal of Navigation and Port Research
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• v.43 no.1
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• pp.72-78
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• 2019

The second-hand ship market provides immediate access to the freight market for shipping investors. When introducing second-hand vessels, the precise estimate of the price is crucial to the decision-making process because it directly affects the burden of capital cost to investors in the future. Previous studies on the second-hand market have mainly focused on the market efficiency. The number of papers on the estimation of second-hand vessel values is very limited. This study proposes an artificial neural network model that has not been attempted in previous studies. Six factors, freight, new-building price, orderbook, scrap price, age and vessel size, that affect the second-hand ship price were identified through literature review. The employed data is 366 real trading records of Panamax second-hand vessels reported to Clarkson between January 2016 and December 2018. Statistical filtering was carried out through correlation analysis and stepwise regression analysis, and three parameters, which are freight, age and size, were selected. Ten-fold cross validation was used to estimate the hyper-parameters of the artificial neural network model. The result of this study confirmed that the performance of the artificial neural network model is better than that of simple stepwise regression analysis. The application of the statistical verification process and artificial neural network model differentiates this paper from others. In addition, it is expected that a scientific model that satisfies both statistical rationality and accuracy of the results will make a contribution to real-life practices.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.24 no.2
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• pp.282-297
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• 2019

Detection of mesoscale oceanic eddies using satellite data can utilize various ocean parameters such as sea surface temperature (SST), chlorophyll-a pigment concentration in phytoplankton, and sea level altimetry measurements. Observation methods vary for each satellite dataset, as it is obtained using different temporal and spatial resolution, and optimized data processing. Different detection results can be derived for the same oceanic eddies; therefore, fundamental research on eddy detection using satellite data is required. In this study, we used ocean color satellite data, sea level altimetry data, and infrared SST data to detect mesoscale eddies in the East Sea and compared results from different detection methods. The sea surface current field derived from the consecutive ocean color chlorophyll-a concentration images using the maximum cross correlation coefficient and the geostrophic current field obtained from the sea level altimetry data were used to detect the mesoscale eddies in the East Sea. In order to compare the eddy detection from satellite data, the results were divided into three cases as follows: 1) the eddy was detected in both the ocean color and altimeter images simultaneously; 2) the eddy was detected from ocean color and SST images, but no eddy was detected in the altimeter data; 3) the eddy was not detected in ocean color image, while the altimeter data detected the eddy. Through these three cases, we described the difficulties with satellite altimetry data and the limitations of ocean color and infrared SST data for eddy detection. It was also emphasized that study on eddy detection and related research required an in-depth understanding of the mesoscale oceanic phenomenon and the principles of satellite observation.

• Asian-Australasian Journal of Animal Sciences
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• v.32 no.7
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• pp.913-921
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• 2019

Objective: The objectives of this study were to compare identified informative regions through two genome-wide association study (GWAS) approaches and determine the accuracy and bias of the direct genomic value (DGV) for milk production traits in Korean Holstein cattle, using two genomic prediction approaches: single-step genomic best linear unbiased prediction (ss-GBLUP) and Bayesian Bayes-B. Methods: Records on production traits such as adjusted 305-day milk (MY305), fat (FY305), and protein (PY305) yields were collected from 265,271 first parity cows. After quality control, 50,765 single-nucleotide polymorphic genotypes were available for analysis. In GWAS for ss-GBLUP (ssGWAS) and Bayes-B (BayesGWAS), the proportion of genetic variance for each 1-Mb genomic window was calculated and used to identify informative genomic regions. Accuracy of the DGV was estimated by a five-fold cross-validation with random clustering. As a measure of accuracy for DGV, we also assessed the correlation between DGV and deregressed-estimated breeding value (DEBV). The bias of DGV for each method was obtained by determining regression coefficients. Results: A total of nine and five significant windows (1 Mb) were identified for MY305 using ssGWAS and BayesGWAS, respectively. Using ssGWAS and BayesGWAS, we also detected multiple significant regions for FY305 (12 and 7) and PY305 (14 and 2), respectively. Both single-step DGV and Bayes DGV also showed somewhat moderate accuracy ranges for MY305 (0.32 to 0.34), FY305 (0.37 to 0.39), and PY305 (0.35 to 0.36) traits, respectively. The mean biases of DGVs determined using the single-step and Bayesian methods were $1.50{\pm}0.21$ and $1.18{\pm}0.26$ for MY305, $1.75{\pm}0.33$ and $1.14{\pm}0.20$ for FY305, and $1.59{\pm}0.20$ and $1.14{\pm}0.15$ for PY305, respectively. Conclusion: From the bias perspective, we believe that genomic selection based on the application of Bayesian approaches would be more suitable than application of ss-GBLUP in Korean Holstein populations.

• Journal of the Korean Society of School Health
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• v.34 no.1
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• pp.22-32
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• 2021

Purpose: Discrimination experienced in the early stages of life among ethnic minority adolescents is known to affect depression and also adversely affect health throughout adulthood and old age. The purpose of this study was to identify whether discrimination experienced by ethnic minority adolescents and their mothers and depression among mothers affect depression in ethnic minority adolescents according to gender. Methods: This was a cross-sectional study using the data of 2018 National Multicultural Family Survey in Korea. The study sample comprised 2,446 ethnic minority adolescents aged 11~18 and their mothers. The data were analyzed using descriptive statistics, pearson correlation analysis, and ordinal logistic regression with SPSS/WIN 25.0 and STATA IC 16. Results: 18.4% of the adolescents (boys: 15.1%, girls: 20.5 %) felt sad or frustrated sometimes or more often for at least two weeks during the past year. Also, 8.3% of the adolescents and 29.6% of their mothers experienced discrimination during the past year. Boys were influenced more than girls by bullying at school (OR=5.17, 95% CI: 2.85~9.38), academic performance (very bad's OR=5.79, 95% CI: 1.54~21.63) and mother's depression (often's OR=2.31, 95% CI: 1.14~4.64). Girls were influenced more than boys by experience of discrimination (OR=2.72, 95% CI: 1.69~4.39). Conclusion: The findings showed that discrimination experienced by ethnic minority adolescents and their mothers in Korean society increases depression in ethnic minority adolescents and has different effects by gender. Therefore, a gender-specific and mother-inclusive intervention is recommended to prevent depression in ethnic minority adolescents.

• Journal of Conservation Science
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• v.37 no.3
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• pp.232-244
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• 2021

This study examined the physical attributes and heat treatment characteristics of glass beads excavated from the Gimhae area, which is the location of Geumgwan Gaya. This enabled classification of surface characteristics of the beads based on the investigation of the color, size, and shape. The glass beads were classified into eight color systems, with purplish-blue beads as the representative color. Bead size was categorized into three types depending on the outer diameter and how it increased over time. Bead shapes were categorized as round, tubular, or doughnut-shaped based on the inner diameter and length, with round being the typical shape. According to the degree of heat treatment, there are three types of cross-section for glass beads that are manufactured by the drawing technique, most of which are the HT-III type. In addition, it is estimated that the heat treatment technology has more considerable effects than other methods. Through non-destructive analysis, the chemical composition was obtained and categorized as flux, stabilizer, and colorant. Analysis confirmed the presence of 63 and 9 pieces in the potash and soda glass groups, respectively. Overall findings from the study highlighted a correlation between the chemical composition and the external factors such as color, size, shape, and manufacturing technology of glass beads recovered from Geumgwan Gaya, revealing characteristics related to that time and region.

• Ecology and Resilient Infrastructure
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• v.8 no.1
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• pp.1-8
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• 2021

A surface image velocimeter (SIV) measures the velocity of a particle group by calculating the intensity distribution of the particle group in two consecutive images of the water surface using a cross-correlation method. Therefore, to increase the accuracy of the flow velocity calculated by a SIV, it is important to accurately calculate the displacement of the particle group in the images. In other words, the change in the physical distance of the particle group in the two images to be analyzed must be accurately calculated. In the image of an actual river taken using a camera, camera lens distortion inevitably occurs, which affects the displacement calculation in the image. In this study, we analyzed the effect of camera lens distortion on the displacement calculation using a dense and uniformly spaced grid board. The results showed that the camera lens distortion gradually increased in the radial direction from the center of the image. The displacement calculation error reached 8.10% at the outer edge of the image and was within 5% at the center of the image. In the future, camera lens distortion correction can be applied to improve the accuracy of river surface flow rate measurements.

• The Journal of Information Systems
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• v.30 no.1
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• pp.151-177
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• 2021

Purpose This paper aims to improve management performance by effectively responding to production needs and reducing inventory through synchronizing production planning and procurement in the aviation industry. In this study, the differences in production planning and execution were first analyzed in terms of demand, supply, inventory, and process using the big data collected from a domestic aircraft manufacturers. This paper analyzed the problems in procurement and inventory management using legacy big data from ERP system in the company. Based on the analysis, we performed a simulation to derive an efficient procurement and inventory management plan. Through analysis and simulation of operational data, we were able to discover procurement and inventory policies to effectively respond to production needs. Design/methodology/approach This is an empirical study to analyze the cause of decrease in inventory turnover and increase in inventory cost due to dis-synchronize between production requirements and procurement. The actual operation data, a total of 21,306,611 transaction data which are 18 months data from January 2019 to June 2020, were extracted from the ERP system. All them are such as basic information on materials, material consumption and movement history, inventory/receipt/shipment status, and production orders. To perform data analysis, it went through three steps. At first, we identified the current states and problems of production process to grasp the situation of what happened, and secondly, analyzed the data to identify expected problems through cross-link analysis between transactions, and finally, defined what to do. Many analysis techniques such as correlation analysis, moving average analysis, and linear regression analysis were applied to predict the status of inventory. A simulation was performed to analyze the appropriate inventory level according to the control of fluctuations in the production planing. In the simulation, we tested four alternatives how to coordinate the synchronization between the procurement plan and the production plan. All the alternatives give us more plausible results than actual operation in the past. Findings Based on the big data extracted from the ERP system, the relationship between the level of delivery and the distribution of fluctuations was analyzed in terms of demand, supply, inventory, and process. As a result of analyzing the inventory turnover rate, the root cause of the inventory increase were identified. In addition, based on the data on delivery and receipt performance, it was possible to accurately analyze how much gap occurs between supply and demand, and to figure out how much this affects the inventory level. Moreover, we were able to obtain the more predictable and insightful results through simulation that organizational performance such as inventory cost and lead time can be improved by synchronizing the production planning and purchase procurement with supply and demand information. The results of big data analysis and simulation gave us more insights in production planning, procurement, and inventory management for smart manufacturing and performance improvement.