• Child Health Nursing Research
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• v.9 no.4
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• pp.359-367
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• 2003

Purpose: This study is designed to test the effects of a full body massage on Apgar score, postpartum mother's childbirth experience, and mother-infant attachment for primipara during labor. Method: Data were collected using a quasi-experiment method (nonequivalent control group, pre-post test design) from November 1, 2001 to July 31, 2002. The subjects for this experiment consist of 28 women in the experimental group and 29 in the control group, out of 57 primipara hospitalized at the U OB & GYN hospital in Inchon. A 20 minute full body massage was given to the experimental group on each of three delivery phases (latent, active, and transition), and a conventional delivery care to the control group. The experimental tools for the study are Apgar score scale developed by Apgar(1958), postpartum mother's childbirth experience scale developed by Marut and Mercer(1979), and mother-infant attachment scale developed by Cropley et al(1981). The data collected were analyzed using t-test, χ2 test, and ANCOVA on the SPSS program. Result: The results of the experiment are as follows: One minute(t=6.756, p=.000; F=9.181, p=.004), and five minute(t=6.129, p=.000; F=7.918, p=.007) Apgar score are increased significantly. Postpartum mother's childbirth experience is significantly increased(t=11.691, p=.000; F=11.741, p=.001). Verbal touch score(t=5.256, p=.000; F=7.169, p=.010), skin touch score(t=11.332, p=.000; F=27.073, p=.000), and total score(t=12.105, p=.000; F=30.104, p=.000) of postpartum mother's childbirth experience are significantly increased, but not for eye touch score(t=3.236, p=.002; F=.800, p=.375). Conclusion: This study shows that a full body massage has a significant positive effect on Apgar score, postpartum mother's childbirth experience. and mother-infant attachment. Therefore, it is suggested that the full body massage might be used clinically to help primipara during labor.

• Research in Community and Public Health Nursing
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• v.13 no.2
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• pp.332-342
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• 2002

Purpose: The purpose of this study was to assess the level of activities of daily living (ADL) in a group of community dwelling elderly. Methods: The subjects were 100 low-income elderly registered in a public health center. The data were analyzed using the SPSS/PC program. Results: The results were as follows: 1. The basic ADLs of the subjects were scored at 7 levels, and the mean score was 6.24 out of 7 points. The subjects did not necessarily require help from others, but might have needed more times or instrumental assists to perform ADLs. The lowest ADL score was reported on walking up to the stairs (5.05), for which the subjects did not need physical assistance, but needed a certain degree of supervision. The highest score was reported on self eating (6.74), followed by bowel management (6.60). 2. The mean IADL score of the subjects was 1.77 out of 4 points. indicating that the subjects were very independent in performing IADLs, without help from others. 3. In relation to general characteristics, the level of ADLs of the subjects was significantly different by age (F=6.65, P=.000), main activities (F=6.36, P=.001), perceived health status (P=4.66, P=.012), educational background (F=4.64, P=.03), marital status(F=4.62, P=.005), and major household income (F=4.15, P=.002). 4. The subjects' level of IADLs in relation to their general characteristics was significantly different by perceived health status (F=8.08, P=.001), major activities (F=7.33, P=.000), age (F=6.18, P=.000), family context (F=3.53, P=.018), religion (F=3.10, P=.019), marital status(F=2.62, P=.055), and major household income (F=2.31, P=.049).

• Phonetics and Speech Sciences
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• v.11 no.4
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• pp.89-96
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• 2019

In this paper, we propose a deep learning architecture that can effectively detect speech segmentation in broadcast contents. We also propose a multi-scale time-dilated layer for learning the temporal changes of feature vectors. We implement several comparison models to verify the performance of proposed model and calculated the frame-by-frame F-score, precision, and recall. Both the proposed model and the comparison model are trained with the same training data, and we train the model using 32 hours of Korean broadcast data which is composed of various genres (drama, news, documentary, and so on). Our proposed model shows the best performance with F-score 91.7% in Korean broadcast data. The British and Spanish broadcast data also show the highest performance with F-score 87.9% and 92.6%. As a result, our proposed model can contribute to the improvement of performance of speech detection by learning the temporal changes of the feature vectors.

• Korean Journal of Adult Nursing
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• v.14 no.3
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• pp.378-389
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• 2002

Purpose: The purpose of this study was to identify the relationship of fatigue and quality of sleep in patients with cancer. Method: The data was collected from January to February 2001. Study objects were recruited K university hospital in Busan, Korea. Their fatigue was measured using the Revised Piper Fatigue Scale developed by Piper et. al(1998), and quality of sleep was measured using Quality of Sleep Questionare by Oh et. al(1998). Result: 1) The fatigue score was mean $114.80{\pm}34.88$(range: 22-220). The sub dimension that showed behavior/severity score at $33.70{\pm}13.89$, affective score at $24.23{\pm}3.33$, sensory score at $27.74{\pm}12.51$, and cognitive/mood score at $29.11{\pm}3.71$. And sleep quality score was mean $37.32{\pm}8.18$. 2) There was a significant difference in religion(F=4.157, P= .008), present therapy(F=2.536, P= .043), past therapy(F=6.625, P= .000), major caregiver(F=3.133, P= .028), and change of weight(F=7.965, P=.006), according to general characteristics in the fatigue in patients with cancer. 3) There was a significant difference in present pain(t=-2.103, P= .037) and change of weight(F=5.484, P=.005), according to general characteristics in the sleep quality in patients with cancer. 4) There was a significant negative correlation between fatigue and quality of sleep(r=- .340, P= .000). Conclusion: Patients with cancer experience in fatigue. Increase in fatigue are associated with decreases in quality of sleep. Nurses must provide patients with nursing care about the occurrence of fatigue and interventions to deal with sleep disturbance.

• Korean Journal of Rural Living Science
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• v.9 no.1
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• pp.9-18
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• 1998

This study aimed to find out the relationship between the body shape and the degree of obesity and the eating attitude influenced by the eating disorder among male and female college students. Followings are the summary of the results obtained in this study : 1. Male students perceived their own body shape properly, however female students perceived their body shape fatter than their real one even if almost all of them were maintaining normal weight. 2. For both male and female students the EAT-26 score was high when they perceived themselves fat, and in the group of students perceiving themselves fat the F I score was high and the F III score was low. Contray to this, in the group of students perceiving themselves thin the F nt score was high. The EAT-26 of female students marked higher than that of males in total questionares. 3. The EAT-26 score was high for both male and female students whose degree of obesity was high. The higher the degree of obesity the higher the F I score, and the lower the degree of obesity the higher the F III score. 4. For both male and female students the dieting frequency was high when they were in the group perceiving themselves fat and in the group with the high degree of obesity. And the number of females' is higher than that of males'. For male students there was no significant difference of dieting frequency in accordance with the perceived body shape and the degree of obesity. However, for female students the frequency was high when they were in the group perceiving themselves fat and in the group with the high degree of obesity. The frequency was high when they were in the group perceiving themselves thin and in the group with the low degree of obesity. 5. For the matter of relationship between the degree of obesity and the frequency of buying meals there was significant difference only in the female students and the frequency of buying meals was higher when the degree of obesity was higher.

• Journal of Korean Academy of Nursing
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• v.27 no.1
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• pp.36-48
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• 1997

This survey was performed to evaluate and compare cognitive function, self-esteem and depression in the elderly related to aging. The data were collected from 200 elders in eight homes for the elderly in Taegu. Data collection was done from June 1 to 31, 1996. The scale used to measure cognitive function was the MMSE-K(Mini-Mental State Examination-Korea), Self-esteem was measmed using Rosenberg's self-esteem scale and depression using SDS(Self-rating Depression Scale). A comparison of cognitive function, self-esteem and depression by aging were summarised as follows : 1. There were significant differences on the cognitive function score in the elderly according to age group(F=24.81, P<.01). 2. There were significant differences on the self-esteem score in the elderly according to age group(F=3.84, P<.5). 3. There were significant differences on the depression score in the elderly according to age group (F=5.90, P<.1). 4. The general characteristics which affected the cognitive function scores of the elders were sex (F=8.45, P<.5), educational level(F=8.86, P<.5), spousing(F=34.59. P<.01), and the perception of health(F=4.63, P<.5). 5. The general characteristic which affected the self-esteem scores of the elders was the perception of health(F=3.81. P<.5). 6. The general characteristic which affected the depression scores was the educational level(F=3.96, P<.5).

• Korean Journal of Remote Sensing
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• v.38 no.6_1
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• pp.1109-1124
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• 2022

This study proposes a marine debris monitoring methods using satellite and drone multispectral images. A multi-layer perceptron (MLP) model was applied to detect marine debris using Sentinel-2 satellite image. And for the detection of marine debris using drone multispectral images, performance evaluation and comparison of U-Net, DeepLabv3+ (ResNet50) and DeepLabv3+ (Inceptionv3) among deep learning models were performed (mIoU 0.68). As a result of marine debris detection using satellite image, the F1-Score was 0.97. Marine debris detection using drone multispectral images was performed on vegetative debris and plastics. As a result of detection, when DeepLabv3+ (Inceptionv3) was used, the most model accuracy, mean intersection over union (mIoU), was 0.68. Vegetative debris showed an F1-Score of 0.93 and IoU of 0.86, while plastics showed low performance with an F1-Score of 0.5 and IoU of 0.33. However, the F1-Score of the spectral index applied to generate plastic mask images was 0.81, which was higher than the plastics detection performance of DeepLabv3+ (Inceptionv3), and it was confirmed that plastics monitoring using the spectral index was possible. The marine debris monitoring technique proposed in this study can be used to establish a plan for marine debris collection and treatment as well as to provide quantitative data on marine debris generation.

• The Korean Journal of Rehabilitation Nursing
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• v.9 no.1
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• pp.15-24
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• 2006

Purpose: This study was to explore the cognitive function of Korean-Chinese stroke patient in China. Method: The study sample was 100 who were possible to communicate and agreed. The data were collected from one Brain's hospital at Yanji in China and by trained nurse from December 12, 2005 to April 28, 2006. The measurement tools were Digit span, Trail making, and MMSE-K. The data were analysed by SPSS Win 11.5 using frequency, t-test, ANOVA, and Pearson's correlation coefficients. Results: The mean score of DSF was 5.07, 3.42 of DSB, 161.37 of TMA, 229.28 of TMB, 22.64 of MMSE-K. There was a significant difference in DSF (F=6.35, p=.001), DSB (F=6.10, p=.001), TMA (F=3.53, p=.018), TMB (F=3.26, p=.025), MMSE-K score (F=12.97, p=.000) according to age, and DSF (F=6.67, p=.000), DSB (F=6.01, p=.000), TMA (F=5.82, p=.001), TMB (F=6.23, p=.001), and MMSE-K score (F=13.02, p=.000) according to educational level, and DSF (F=5.35, p=.006), DSB (F=3.16, p=.047), TMA (F=3.30, p=.041), TMB (F=3.42, p=.037), and MMSE-K score (F=4.95, p=.009) according to duration of disease, and DSB (F=3.54, p=.018), and MMSE-K (F=6.05, p=.001) according to frequencies of hospitalization. There was high correlation between DSF and DSB (r=.581, p=.000), TMA and TMB (r=.936, p=.000), MMSE-K and DSF (r=.579, p=.000), MMSE-K and DSB (r=.591, p=.000), DSF and TMA (r=.727, p=.000), and DSF and TMB (r=.721, p=.000). Conclusion: The cognitive evaluation score of Korean-Chinese stroke patients in China was in normal limit. The age, educational level, duration of disease and income were significant demographic characteristic affecting cognitive function. Further study need to compare the cognitive function of Korean-Chinese stoke patients in China and stoke patients in Korea.

• The Korean Journal of Emergency Medical Services
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• v.4 no.1
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• pp.47-55
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• 2000

The study was conducted to investigate the burnout of firefighters. The subjects were 223 firefighters in C-Do. The instruments used for this study were a survey of general characteristics(10 items), burnout(23 items). Analysis of data was done by use of mean percentage, t-test, ANOVA, stepwise multiple regression with SAS program. The results of this study are as follows; 1. Burnout according to general characteristics were showed significant difference in job-aptitude(F＝6.30, P<.001), health status(F＝5.92, P<.001), education(t＝6.09, P<.01), working place rotation(t＝2.59, P<.01), call number/week(F＝3.28, P<.01), job-burden(F＝4.45, P<.01), paper-job burden(F＝3.87, P<.05). 2. Category score of burnout were showed the higher score in the lowed personal accomplishment(3.29). 3. Category score of burnout according to aptitude were showed difference each other. 4. Predicting factor of burnout were paper-job burden, health status, job-burden(20.99%).

• Korean Journal of Materials Research
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• v.33 no.7
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• pp.273-278
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• 2023

In this study, based on the saturation magnetic flux density experimental values (B_s) of 622 Fe-based bulk metallic glasses (BMGs), regression models were applied to predict B_s using artificial neural networks (ANN), and prediction performance was evaluated. Model performance evaluation was investigated by using the F1 score together with the coefficient of determination (R² score), which is mainly used in regression models. The coefficient of determination can be used as a performance indicator, since it shows the predicted results of the saturation magnetic flux density of full material datasets in a balanced way. However, the BMG alloy contains iron and requires a high saturation magnetic flux density to have excellent applicability as a soft magnetic material, and in this study F1 score was used as a performance indicator to better predict B_s above the threshold value of B_s (1.4 T). After obtaining two ANN models optimized for the R² and F1 score conditions, respectively, their prediction performance was compared for the test data. As a case study to evaluate the prediction performance, new Fe-based BMG datasets that were not included in the training and test datasets were predicted using the two ANN models. The results showed that the model with an excellent F1 score achieved a more accurate prediction for a material with a high saturation magnetic flux density.