• The Korean Nurse
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• v.33 no.3
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• pp.79-91
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• 1994

The purpose of this study was to identify the meaningful nursing diagnosis in maternity unit and to suggest formally the basal data to the nursing service with scientific approach. The subject for this paper were 64 patients who admitted to Chung Ang University Hospital, Located in Seoul, from Mar. 10, to July 21, 1993. The results were as follows: 1. The number of nursing diagnosis from 64 patients were 892 and average number of nursing diagnosis per patient was 13.9. 2. Applying the division of nursing diagnosis to Roy's Adaptation Model, determined nursing diagnosis from the 64 patients were 621 (69.6%) in physiological adaptation mode and (Comfort, altered r/t), (Injury, potential for r/t), (Infection, potential for r/t), (Bowel elimination, altered patterns r/t), (Breathing pattern, ineffective r/t), (Nutrition, altered r/t less than body requirement) in order, and 139 (15.6%) in role function mode, (Self care deficit r/t), (Knowledge deficit r/t), (Mobility, impaired physical r/t) in order, 122 (13.7%) in interdependence adaptation mode, (Anxiety r/t), (Family Process, altered r/t) in order, 10(1.1%) in self concept adaptation mode, (Powerlessness r/t), (Grieving, dysfunctional r/t) in order. 3. Nursing diagnosis in maternity unit by the medical diagnosis, the average hospital dates were 3.8 days in normal delivery and majority of used nursing diagnosis, (Comfort, altered r/t) 64.6%, (Self care deficit r/t) 13.6% in order, and the average hospital dates were 9.6 days in cesarean section delivery and majority of used nursing diagnosis, (Comfort, altered r/t) 51.6%, (Self care deficit r/t) 15.2%, (Infection, potential for r/t) 9.9%, (Injury, potential "for r/t) 8.1%, (Anxiety r/t) 5.0%, (Mobility, impaired physical r/t) 3.3% in order, and the average hospital dates were 15.8days in preterm labor and majority of used nursing diagnosis, (Comfort, altered r/ t), (Anxiety r/t), (Injury, potential for r/t) in order, and the average short-term hospital dates were 2.5days, long-term hospital dates were 11.5days in gynecologic diseases and majority of used nursing diagnosis, (Comfort, altered r/t). (Self care deficit r/t), (Injury, potential for r/t), (Infection, potential for r/t) in order.

• Journal of Information Technology Services
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• v.19 no.6
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• pp.55-82
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• 2020

This study examined the factors that influence the turnover intention, job performance of call center representatives based on the adaptive structuration theory (AST). This study intended to empirically examine how individual characteristics of representative affect the technological and task adaptation, how they affect job performance and turnover intention. On the other hand, this study also explains how rational culture and organization a reputation which are considered as dimensions of organizational characteristics affects organizational commitment, and verifies the relationship between organizational commitment and job performance and turnover intention. Finally this paper aim to provide academic and practical implications. In order to solve the above research problems, this research proposed a model based on the adaptive structuration theory. In order to identify the relationship between the proposed variables and the AST for individual, we conducted an empirical test on the call center representatives. The structural equation model was used to verify the research model and hypotheses. The results of the empirical analysis show that the personal characteristics of counselors, such as communication skills, multitasking abilities, and innovativeness have a positive effect on skill adaptation, and skill adaptation has a positive effect on task adaptation, furthermore, it influences on job performance and turnover intention Respectively. In addition, among the factors of organizational environmental dimensions of the call center, it was found that organizational reputation not only increase continuance commitment but also increase normative commitment. Contrary to our expectations, perceived rational culture didn't have a positive effect on organizational commitment. Also, continuance commitment and normative commitment are valid predictors of job performance, but they have nothing to do with turnover intention. On the contrary, emotional commitment is the only one variable among three dimensions of organizational commitment have a positive effect on turnover intention, but is not a valid predictor of job performance.

• Journal of Korean Academy of Nursing
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• v.53 no.4
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• pp.480-495
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• 2023

Purpose: This study aimed to develop and test a structural equation model on social re-adjustment of individuals with stroke based on a literature review and Roy's adaptation model. Methods: This study involved 321 participants who had a stroke and visited the outpatient department after discharge. The hypothetical model was developed based on Roy's adaptation model and a comprehensive review of previous literature on the topic. The model comprised four exogenous variables (neurological damage, gender [man], age, and social support) and five endogenous variables (activities of daily living, acceptance of disability, depression, rehabilitation motivation, and social re-adjustment). The data were analyzed using SPSS Windows software version 22.0 and AMOS 23.0. Results: Out of 28 research hypotheses, 18 were supported, and they indicated approximately 64% probability of social re-adjustment. Social re-adjustment is directly and significantly affected by age, social support, activities of daily living, and depression. Social re-adjustment is indirectly affected by neurological impairment, gender (men), age, social support, and rehabilitation motivation. Conclusion: Continuous assistance and care should be provided for individuals with disabilities caused by sudden neurological damage to facilitate gradual improvement in their social re-adjustment. To enhance social re-adjustment, especially among older adults, newly developed interventions should focus on improving their activities of daily living, preventing depression, and enhancing support from family and healthcare personnel.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.37 no.12
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• pp.884-893
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• 1988

Adaptive controllers for linear unknown coefficient system, that is corrupted by disturbance, are designed by parameter adaptation model reference adaptive control(MRAC). This design is stemmed from the Lyapunov direct method. To reduce the model following error and to improve the convergence rate of the design, an indirect-suboptimal control law is derived. Proper compensation for the effects of time-varying coefficients and plant disturbance are suggested. In the design procedure no complete identification of unknown coefficients are required.

• Journal of Korean Academy of Nursing
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• v.35 no.7
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• pp.1353-1361
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• 2005

Purpose: This study was done to provide fundamental data for developing a depression prediction model by discovering main factors that affect depression in patients who do maintenance hemodialysis. Method: The subjects were 191 patients doing maintenance hemodialysis selected from outpatient dialysis clinics at 9 major general hospitals, The Instrument tools utilized in this study were adapted from depression, fatigue, sleep disturbance, stress, adaptation, symptoms, daily activities, and role limitation and thoroughly modified to verify reliability and validity. The collected data was analyzed with a SPSS-PC 11.0 Window Statistics Program for real numbers, percentage, average, standard deviation, and multiple regression. Results: The correlation factor for depression was (M=2.54) fatigue(M=3.12), sleep disturbance (M=2.82), stress(M=3.04), adaptation(M=2.53), daily activities(M=2.24), symptoms(M=2.37), and role limitation(M=2.24). The strongest factor that affected depression was explained by symptoms of the patients who performed hemodialysis. The analysis of the factors that affected depression revealed a $58.4\%$ prediction in symptoms, stress, role limitation, and adaptation. Conclusion: It has been confirmed that the regression equation model(Depression=7.351 + .266$^{\ast}$symptoms + .260$^{\ast}$stress -.l89$^{\ast}$adaptation + .057$^{\ast}$fatigue) of this research may serve as a prediction factor for depression in Hemodialysis Patients.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.947-949
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• 1995

In this paper, model reference adaptive fuzzy controller (MRAFC) was proposed in order to overcome the difficulty of extracting rules and defects of the adaptation performance in the FLC. MRAFC comprised inner feedback loop consisting of the FLC and plant, and outer loop consisting of an adaptation mechanism which is designed for tuning a control rule of the FLC. A reference-model was used for design criteria of a fuzzy controller which characterizes and quantizes the control performance required in the overall control system. Tuning control rules of FLC is performed by the adaptation mechanism. For this, the fuzzy model for tuning the contorl rules is designed in accordance with the feature of error information. And DC servo motor was selected for case study of actual industrial plant and tested on various loads.

• Proceedings of the KSPS conference
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• 2003.05a
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• pp.83-86
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• 2003

This paper presents our style-based language model adaptation for Korean conversational speech recognition. Korean conversational speech is observed various characteristics of content and style such as filled pauses, word omission, and contraction as compared with the written text corpora. For style-based language model adaptation, we report two approaches. Our approaches focus on improving the estimation of domain-dependent n-gram models by relevance weighting out-of-domain text data, where style is represented by n-gram based tf*idf similarity. In addition to relevance weighting, we use disfluencies as predictor to the neighboring words. The best result reduces 6.5％ word error rate absolutely and shows that n-gram based relevance weighting reflects style difference greatly and disfluencies are good predictor.

• Journal of Korean Academy of Nursing
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• v.15 no.2
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• pp.5-15
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• 1985

This study was conducted for the purpose of fin-ding out the variance explaining the medical facilities utilization behavior, which is defined adaptation behavior Process by focal, contextual, residual stimuli in Roy's Adaptation Model. What kinds of characteristics can explain adaptation behavior in Roy's Model? And which is the relative importance of input variables? For this analysis, stepwise multiple regression and path analysis was used. The data come from the 1981 Baseline Household Interview Survey in remote rural area. The findings of the analysis can be summarized as follows: First, Total variance of independant variables for adaptation behavior, that is medical facilities utilization including clinic, drug store, health center, herb medicine was shown 16.2 percent. The most important variable which explain the dependent variable was the occurance of illness with the Ra of value 0.112. The illness symptom, living level, regular care source was shown important variables with relatively high the R²value and significant beta coefficient. Second, in the path analysis of variables which is selected important variables, the occurance of illness was shown variable which has the highest direct effect which 0.297 path coefficient. Also the education level of household was shown variable which has the highest indirect effect through living level and the occurance of illness in causal model. Third, This analysis suggests that the occurance of illness belonging focal stimuli are more influenced than others. To sum up, It is seem to the occurance of illness, illness symptom belonging focal stimuli have high explanation ability through direct effect, education level of household among contextual stimuli have explanation ability through indirect effect.

• Journal of Climate Change Research
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• v.8 no.3
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• pp.187-199
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• 2017

We attempted to assess the impact of climate change on rice yields in Cambodia and to investigate adaptation strategies to climate change including more drastically shifting the planting dates and considering more fertilizer application levels. The potential yields of two wet season rice cultivars (Sen Pidao and Phka Rumduol) under two climate change scenarios in Cambodia were simulated using the CERES-Rice model. Field experiments conducted at the Cambodian Agricultural Research and Development Institute (CARDI), in 2010, 2011, and 2013 and climate variables from the HadGEM3-RA model were collected for this study. Compared with the baseline (1991-2000), yields of Sen Pidao rice will decrease under climate change and yields of Phka Rumduol rice could increase or decrease depending on fertilizer rates and the periods (2040s, 2050s, and 2080s). In general, the variations in the simulated effects of climate change on yields were more sensitive at fertilizer N100-N200 and less sensitive at fertilizer N0-N50. It is likely that forward shifts of planting date from the baseline plating date for the two cultivars in the future can be more benefitted than backward shifts. It is concluded that the CERES-Rice model can be useful to provide efficacious adaptation strategies in Cambodia.

• Journal of Korea Multimedia Society
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• v.25 no.10
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• pp.1375-1385
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• 2022

In this paper, we propose a semi-supervised domain adaptation solution to deal with practical face recognition (FR) scenarios where a single face image for each target identity (to be recognized) is only available in the training phase. Main goal of the proposed method is to reduce the discrepancy between the target and the source domain face images, which ultimately improves FR performances. The proposed method is based on the Domain Adatation network (DAN) using an MMD loss function to reduce the discrepancy between domains. In order to train more effectively, we develop a novel loss function learning strategy in which MMD loss and cross-entropy loss functions are adopted by using different weights according to the progress of each epoch during the learning. The proposed weight adoptation focuses on the training of the source domain in the initial learning phase to learn facial feature information such as eyes, nose, and mouth. After the initial learning is completed, the resulting feature information is used to training a deep network using the target domain images. To evaluate the effectiveness of the proposed method, FR performances were evaluated with pretrained model trained only with CASIA-webface (source images) and fine-tuned model trained only with FERET's gallery (target images) under the same FR scenarios. The experimental results showed that the proposed semi-supervised domain adaptation can be improved by 24.78% compared to the pre-trained model and 28.42% compared to the fine-tuned model. In addition, the proposed method outperformed other state-of-the-arts domain adaptation approaches by 9.41%.