• Stress
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• v.26 no.4
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• pp.319-326
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• 2018

Background: This study investigated whether pre- and peri-disaster experiences influence on PostTraumatic Stress Disorder (PTSD) and whether post-disaster stress by life changes have impact on PTSD after controlling pre- and peri-disaster factors. Methods: Data came from a sample of 1,182 respondents who experienced natural disasters (flood and typhoon) in South Korea from 2012 to 2015. The SPSS Win 22.0 program was used for descriptive analysis, t-test, Chi-square test, Pearson's correlation and logistic regression analysis. Results: The results indicated that 24.3% of the disaster victims were in PTSD risk group. Compared with non-PTSD, PTSD risk group showed lower interpersonal trust and satisfaction, higher depression and anxiety, and lower subjective well-being. The results of hierarchical logistc regression revealed that all pre-, peri-, and post-disaster factors increased the probability of developing PTSD, except for relocation of residence. Moreover, a primary post-disaster predictor of PTSD was economic distress after controlling for pre- and peri-disaster. Conclusions: This study tested relative contributions of post-disaster factors on PTSD.

• Journal of Korean Academy of Nursing
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• v.49 no.4
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• pp.423-436
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• 2019

Purpose: The aim of the study was to explore nurses' experience of person-centered relational care in the context of critical care. Methods: Key interview questions were developed based on the human-to-human relationship model suggested by Travelbee. Data were collected through indepth interviews with a purposive sample of 11 nurses having more than 2 years of working experience in intensive care units. An interpretative phenomenological analysis was conducted to analyze the data. Results: Four super-ordinate and nine sub-ordinate themes were identified. Emerged super-ordinate themes were as follows: (1) encountering a live person via patient monitoring systems; (2) deep empathic connection; (3) humanistic and compassionate care, and (4) accompanying the journey to the end. Study findings revealed that nurses in intensive care units experienced 'balancing emotions' and 'authenticity' in caring when entering human-to-human relationships with dying patients. The phenomenon of person-centered relational care in intensive care units was found to subsume intrinsic attributes of empathy, compassion, and trust, similar to the central concepts of Travelbee's theory. Conclusion: The interpretative findings in this study provide deeper understanding of Travelbee's human-to-human relationship model. The technological environment in intensive care units did not hinder experienced nurses from forming human-to-human relationships. These themes need to be emphasized in critical care nursing education as well as in nursing management. The results of this study will contribute to understanding nurse-patient caring relationships in depth, and help improve the quality of nursing care in intensive care units.

• The Journal of Information Systems
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• v.28 no.3
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• pp.1-23
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• 2019

Purpose This study examines the role of corporate image and privacy concerns in intention to use of online travel services using data from Vietnam. Design/methodology/approach The data collection was implemented to a student sample at the Foreign Trade University in Hanoi, which has a high concentration of young people who are interested in online travel in Vietnam. The paper based questionnaire was directly delivered to the respondents. After sorting to eliminate unfit samples, the number of responses was 541, which exceeds 500, the minimum number typically required. To test the hypotheses, we applied structural equation modeling (SEM) and Confirmatory Factor Analysis (CFA) was used to evaluate the reliability and validity of constructs in the model. We also used direct, indirect and total effect coefficient to evaluate the total impact of factors on the intention to use online services. Findings This study found that corporate image is positively associated to intention to use online services. It found a link between corporate image and privacy concerns, which suggests another way for firms to address their customers' privacy concerns; corporate image, which has received great attention in traditional offline sales channels, but not in online services, should receive higher attention in IS research. Online travel businesses, besides increasing ease of use, perceived usefulness and trust in their services, should focus on build a reliable corporate image, which can not only promote the service use but also help to eliminate users' the privacy concerns.

• The Journal of the Korean dental association
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• v.57 no.3
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• pp.124-148
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• 2019

Recently, there has been an increasing interest in the regulation of medical & dental profession in South Korea due to various medical scandals & exacerbated commercialism. Consequently, the voice asking for strengthening the license management of medical & dental profession is rising. However, there is an absolutely lacking discussion on self-regulation of the Korean dentist community. This study investigated International Society of Dental Regulators and dental regulatory authorities in the U.K., Ontario in Canada, California in the U.S. and Australia. In addition, this study examined what situations Japan was in, which was similar to Korea in terms of systems. In the U.K., the U.S., Canada and Australia, there are independent dental regulatory authorities, which place emphasis on lay personnel participation. In addition, the organizations prepared very specific and detailed ethics, standards, and punishment guidelines to be followed by professionals. And, various efforts are being made to secure transparency and trust. As a result of this study, self-regulation in Korea seems to require an open approach that embraces civil society, and it is considered that dentist should lead social discussion more positively.

• Journal of Digital Convergence
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• v.17 no.4
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• pp.355-364
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• 2019

The purpose of this study is to present the implications of analyzing users' market segmentation and characteristics based on the tourism SNS lovemarks experience. The results are as follows. First as a result of conducting factor analysis of tourism SNS lovemarks experience, five factors explained namely, mystery, sensuality, intimacy, trust, reputation. Second, as a result of conducting cluster analysis, four cluster groups were identified (reputation/sensuality centered experience group, high lovemarks experience group, intimacy centered experience group, low lovemarks experience group) and each characteristics were profiled. Third, as a result of Chi-square analysis and correspondence analysis, there was a difference in the characteristics of tourism SNS usage by cluster. Fourth, higher tourism SNS lovemarks experience segmented groups were more likely to recognize the degree of experiential value, satisfaction, behavioral intention.

• Journal of Digital Convergence
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• v.19 no.2
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• pp.299-305
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• 2021

This study examined to identify the factors influencing on inpatients' satisfaction with hospitalization and willingness to recommend hospital to others. Data from the 2018 National Patient Experience Survey were used for the analysis. Of the 593 patients experiencing inpatient services, multivariate linear regression analysis was conducted to explore the factors such as physician care, nursing care, facility and administrative support, and healthcare system on inpatients' satisfaction after controlling for their socio-demographic and health related factors. The study found that physician care, nursing care, administrative support and healthcare system were related to inpatients' satisfaction and willingness to recommend hospital. To improve inpatients' satisfaction, it is necessary to improve healthcare professionals' overall patient-centerdness attitude, user friendly hospital facilities and administrative support services and efforts to trust and satisfaction on healthcare system from the patients' perspectives.

• Journal of Digital Convergence
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• v.19 no.3
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• pp.195-202
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• 2021

This study is a systematic review study to confirm the characteristics, effects, and application strategies of domestic and foreign virtual reality programs provided by dementia education. This study is based on the literature published up to July 2020, CINAHL, Cochrane, EMBASE, and Pubmed electronic databases were used overseas, and RISS, KISS, and DBpia were searched in Korea. Based on the selection criteria and exclusion criteria, the final six papers were used for analysis. As a result of the analysis, the subjects of the selected literature were two informal caregivers (33.3%), one general (16.7%), and three students (50.0%) including nursing students and medical and pharmacy students. The virtual reality program was effective in a total of five areas(empathy ability, dementia attitude including knowledge and comfort of dementia, trust in own abilities, dyadic relationship scale), of which 75% of the studies measured empathy ability had significant effects. The results of this study confirm that virtual reality technology can be used for human-centered nursing based on empathy.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.227-233
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• 2021

Predictive maintenance has been one of important applications of data science technology that creates a predictive model by collecting numerous data related to management targeted equipment. It does not predict equipment failure with just one or two signs, but quantifies and models numerous symptoms and historical data of actual failure. Statistical methods were used a lot in the past as this predictive maintenance method, but recently, many machine learning-based methods have been proposed. Such proposed machine learning-based methods are preferable in that they show more accurate prediction performance. However, with the exception of some learning models such as decision tree-based models, it is very difficult to explicitly know the structure of learning models (Black-Box Model) and to explain to what extent certain attributes (features or variables) of the learning model affected the prediction results. To overcome this problem, a recently proposed study is an explainable artificial intelligence (AI). It is a methodology that makes it easy for users to understand and trust the results of machine learning-based learning models. In this paper, we propose an explainable AI method to further enhance the explanatory power of the existing learning model by targeting the previously proposedpredictive model [5] that learned data from a core facility (Hyper Compressor) of a domestic chemical plant that produces polyethylene. The ensemble prediction model, which is a black box model, wasconverted to a white box model using the Explainable AI. The proposed methodology explains the direction of control for the major features in the failure prediction results through the Explainable AI. Through this methodology, it is possible to flexibly replace the timing of maintenance of the machine and supply and demand of parts, and to improve the efficiency of the facility operation through proper pre-control.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1157-1169
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• 2021

The disaster recovery refers to policies and procedures to ensure continuity of services and minimize loss of resources and finances in case of emergency situations such as natural disasters. In particular, the disaster recovery method by the cloud service provider has advantages such as management flexibility, high availability, and cost effectiveness. However, this method has a dependency on a service provider and has a structural limitation in which a user cannot be involved in personal data. In this paper, we propose a protocol using proxy re-encryption for data confidentiality by removing dependency on service providers by backing up user data using blockchain and distributed storage. The proposed method is implemented in Ethereum and IPFS environments, and presents the performance and cost required for backup and recovery operations.

• Journal of Digital Convergence
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• v.20 no.5
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• pp.703-712
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• 2022

The purpose of this study is to present practical implications for employment of people with developmental disabilities by analyzing the moderating effect of family employment support in the relationship between discrimination experience and employment of people with developmental disabilities. The subjects of the study were 394 people with developmental disabilities who participated in the 2nd wave 4th survey of the 2019 Employment Panel Survey for the Disabled, and a hierarchical binary logistic regression analysis was conducted to verify the hypothesis. As a result of the study, it was found that the experience of discrimination among people with developmental disabilities negative effects employment, and family employment support has a significant moderating effect, strengthening the negative effect of discrimination on employment. Therefore, the importance of improving the working environment reflecting the needs of families with developmental disabilities, the necessity of employment support policies, and strengthening trust with the state and local communities were discussed.