• Korean Medical Education Review
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• v.23 no.2
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• pp.90-103
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• 2021

This study examined the current status of the medical professionalism curriculum in Korea to suggest a plan to move towards the formation of a professional identity. Professionalism education data from 28 Korean medical schools were analyzed, including the number of courses, required or elective status, corresponding credits, major course contents, and teaching and evaluation methods. Considerable variation was found in the number of courses and credits in the professionalism curriculum between medical schools. The course contents were structured to expand learners' experiences, including the essence and knowledge of professionalism, understanding of oneself, social interaction with others, and the role of doctors in society and the healthcare system. The most common teaching methods were lectures and discussions, while reflective writing, coaching, feedback, and role models were used by fewer than 50% of medical schools. Written tests, assignments and reports, discussions, and presentations were frequently used as evaluation methods, but portfolio and self-evaluation rates were relatively low. White coat ceremonies were conducted in 96.2% of medical schools, and 22.2% had no code of conduct. Based on the above results, the author suggests that professional identity formation should be explicitly included in learning outcomes and educational contents, and that professional identity formation courses need to be added to each year of the program. The author also proposes the need to expand teaching methods such as reflective writing, feedback, dilemma discussion, and positive role models, to incorporate various evaluation methods such as portfolios, self-assessment, and moral reasoning, and to strengthen faculty development.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.1
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• pp.180-194
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• 2021

For small image registration, feature-based approaches are likely to fail as feature detectors cannot detect enough feature points from low-resolution images. The classic FFT approach's prediction accuracy is high, but the registration time can be relatively long, about several seconds to register one image pair. To achieve real-time and high-precision rigid registration for small images, we apply deep neural networks for supervised rigid transformation prediction, which directly predicts the transformation parameters. We train deep registration models with rigidly transformed CIFAR-10 images and STL-10 images, and evaluate the generalization ability of deep registration models with transformed CIFAR-10 images, STL-10 images, and randomly generated images. Experimental results show that the deep registration models we propose can achieve comparable accuracy to the classic FFT approach for small CIFAR-10 images (32×32) and our LSTM registration model takes less than 1ms to register one pair of images. For moderate size STL-10 images (96×96), FFT significantly outperforms deep registration models in terms of accuracy but is also considerably slower. Our results suggest that deep registration models have competitive advantages over conventional approaches, at least for small images.

• Journal of Korean Public Health Nursing
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• v.36 no.1
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• pp.47-58
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• 2022

Purpose: This study was undertaken to present an effective plan for the development of an educational program and a strategy to promote patient safety management activities for nursing students by identifying factors that affect these activities based on the theory of planned behavior. Methods: A self-report questionnaire was distributed to 300 nursing students who had clinical practice experience at three nursing colleges in Daejeon, Gyeongbuk, and Jeonbuk. The significance of the model fit, and the path effect was confirmed by confirmatory factor analysis. Results: The hypothetical model for patient safety management activities was appropriate. Among the 5 pathways, 4 were significant. It was found that behavioral intention had a direct influence on patient safety management activities, and perceived behavioral control and attitude had an influence on behavioral intention. Conclusion: To strengthen the perceived behavioral control of nursing students' patient safety management activities, it is necessary to analyze and remove obstacles and provide education that reflects the characteristics of the subject's health problems. In addition, through self-directed learning involving simulation practice, nursing students should be exposed to patient safety accidents, so that they can recognize the risks early and solve problems through critical thinking while bringing about the necessary changes in their attitude.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.6
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• pp.1833-1848
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• 2022

Named entity recognition (NER) is an important basic task in the field of Natural Language Processing (NLP). Recently deep learning approaches by extracting word segmentation or character features have been proved to be effective for Chinese Named Entity Recognition (CNER). However, since this method of extracting features only focuses on extracting some of the features, it lacks textual information mining from multiple perspectives and dimensions, resulting in the model not being able to fully capture semantic features. To tackle this problem, we propose a novel Multi-view Semantic Feature Fusion Model (MSFM). The proposed model mainly consists of two core components, that is, Multi-view Semantic Feature Fusion Embedding Module (MFEM) and Multi-head Self-Attention Mechanism Module (MSAM). Specifically, the MFEM extracts character features, word boundary features, radical features, and pinyin features of Chinese characters. The acquired font shape, font sound, and font meaning features are fused to enhance the semantic information of Chinese characters with different granularities. Moreover, the MSAM is used to capture the dependencies between characters in a multi-dimensional subspace to better understand the semantic features of the context. Extensive experimental results on four benchmark datasets show that our method improves the overall performance of the CNER model.

• Physical Therapy Rehabilitation Science
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• v.11 no.2
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• pp.224-234
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• 2022

Objective: The purpose of this study was to identify the practitioner and organizational characteristics that either detracted from or encouraged the use of evidence-based practice (EBP) by physical therapists. Design: A cross-sectional survey study Methods: Participants were 260 physical therapists currently practicing in South Korea. They completed a questionnaire designed to determine attitudes, beliefs, interest, self-efficacy and barriers to EBP, as well as demographic information about themselves and their practice settings. Logistic regression was used to examine relationships between socio-demographic and work environment characteristics and each practitioner factor. Results: Respondents agreed that the use of evidence in practice was necessary. Although 80% of them agreed that research findings are useful, 71% felt that a divide exists between research and practice. In terms of confidence in their skills, the ability to interpret results of statistical procedures ranked lowest. Despite internet access at work for 63% of respondents, only 14% were given protected work time to search and appraise the literature. Only 2% of respondents stated that their organization had a written requirement to use current evidence in their practice. The primary barrier to implementing EBP was a reported lack of time. Conclusions: In conclusion, most physical therapists stated they had a positive attitude toward EBP and were interested in learning or improving the skills necessary for implementation. Most recognized a need to increase the use of evidence in their daily practice, but a lack of ability to understand the results of research represents a significant barrier to implementing EBP.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.4
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• pp.109-120
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• 2022

This study has incorporated the mechanics-dynamics-emotions (MDE) and two behavioral learning paths to investigate the customers' co-creation behavior in Taiwan. The intuitive path begins with a gamification design that reflects the customers' proactive and innovative behavior; the cognitive path begins with persuasion knowledge remarks based on rational and reactive reasoning. These two paths conclude what forms user co-creation. The study collects data of 505 active social media users in Taiwan and employs structural equation modeling. The empirical findings demonstrate persuasive knowledge and gamification design are significantly associated with self-reference, and in turn, positively associated with co-creation. It indicates that cognitive behavior plays the main role in forming co-creation. Participants are more drawn to co-creation behaviors by the marketing contents that prompt reactive behaviors than proactive ones. Therefore, marketing managers can use appropriate stimuli to enhance co-creation behavior. Companies can design activities related to users, and more accessible for reactive, instead of proactive behavior, i.e., asking for their initiatives. It also suggests that companies' marketing campaigns should involve key opinion leaders matching the product image and the target audience's preferences. The novelty of this study is to introduce a novel augmented MDE framework to extend the "dynamics" into the incubation and implementation stage.

• Journal of Engineering Education Research
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• v.25 no.1
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• pp.33-45
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• 2022

This study aims to investigate effects of scaffolding on writing apprehension and media literacy in engineering freshmen's synchronous online writing course, and the relationships between the two variables. 'Scaffolding' is in-time support provided by a teacher/tutor or competent peer that enables students to meaningfully gain skills at problem solving process. Also, it is one of the most frequently mentioned concepts in education as well as one of the more necessary teaching strategies in an online writing course. In this study, provided treatments for the experiment were supportive scaffolding for domain-specific knowledge and reflective scaffolding for meta-cognitive knowledge. Participants were 102 engineering undergraduate students, who were assigned to two experimental groups by scaffolding types. A process-based writing course in online learning environment was conducted for 8 weeks. The writing tasks were given according to writing process. The findings were that, firstly, there were statistically significant writing apprehension's reduction and self-expression's improvement through the scaffolding provided in writing class. Secondly, writing apprehension's reduction and self-expression's improvement were significant in supportive scaffolding group. Thirdly, media literacy predicted writing apprehension. The practical implications of these findings are discussed herein, with particular attention on ways for writing apprehension's reduction as well as media literacy's enhancement.

• Korean Medical Education Review
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• v.23 no.2
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• pp.108-117
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• 2021

This study investigated medical students' perceptions of good jobs. We classified medical students' perceptions of good jobs and analyzed the characteristics of each type. The Q methodology was used to extract medical students' subjective thoughts. After extracting statements based on previous studies, 46 Q samples were selected. The P sample consisted of 40 medical students divided evenly by gender and grade. They performed a Q sort of the 46 Q sample questionnaire and the results were analyzed using the QUANL ver. 1.2 program. Very few consensus statements were found in the replies. We divided answers into four types, each of which was clearly distinguished: (1) quality of life-oriented jobs, (2) reward-oriented jobs, (3) service-oriented jobs, and (4) self-realization-oriented jobs. Medical students in type 1 prioritized quality of life equally at work and at home. Medical students in type 2 preferred high-paying jobs. Medical students in type 3 placed importance on serving others. Finally, medical students in type 4 viewed good jobs as involving learning and development. The types of jobs sought were classified according to individual students' values and subjectivity. Medical schools may use the results of this study as a basis for career guidance.

• The Journal of Korea Robotics Society
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• v.18 no.3
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• pp.346-351
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• 2023

With the release of numerous open driving datasets, the demand for domain adaptation in perception tasks has increased, particularly when transferring knowledge from rich datasets to novel domains. However, it is difficult to solve the change 1) in the sensor domain caused by heterogeneous LiDAR sensors and 2) in the environmental domain caused by different environmental factors. We overcome domain differences in the semi-supervised setting with 3-stage model parameter training. First, we pre-train the model with the source dataset with object scaling based on statistics of the object size. Then we fine-tine the partially frozen model weights with copy-and-paste augmentation. The 3D points in the box labels are copied from one scene and pasted to the other scenes. Finally, we use the knowledge distillation method to update the student network with a moving average from the teacher network along with a self-training method with pseudo labels. Test-Time Augmentation with varying z values is employed to predict the final results. Our method achieved 3rd place in ECCV 2022 workshop on the 3D Perception for Autonomous Driving challenge.

• Journal of Distribution Science
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• v.20 no.6
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• pp.75-86
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• 2022

Purpose: This research aims to provide empirical evidence on the impact of digital literacy on behavioural intention regarding using technology for distribution of higher education. Design, Methodology, and Approach: Quantitative analysis was carried out using Covariance-Based Structural Equation Model with data collected from 901 students who fully experienced 2-year study online at different universities in Vietnam. The structural model was built with digital literacy as the primary indicator and other variables were included based on modified version of Unified Theory of Acceptance and Use of Technology (UTAUT2) by adopting performance expectancy, effort expectancy, social influence, habit, and hedonic motivation variables specifically for education sector. Self-efficacy was added to eliminate possible bias in technology acceptance. Results: From the results of model estimation, digital literacy presented positive impact on the online distribution of higher education in Vietnam. The mediating effects of various indicators such as performance expectancy, effort expectancy, social influence, habit, hedonic motivation, and self-efficacy are significantly determined by research model. Conclusion: The higher level of digital literacy of the students, the more likely that they will use technology in higher education study, especially online learning. Additionally, the mediating effects of indicators from the UTAUT2 theoretical model were also evident to be positively significant.