• Nuclear Engineering and Technology
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• v.56 no.6
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• pp.2428-2435
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• 2024

Training for radiation protection and control requires a visual understanding of radiation, which cannot be perceived by the human senses. Trainees must also master the effective use of measuring instruments. Traditionally, such training has exposed trainees to radiation sources. Here, we present a novel e-training strategy that enables safe, exposure-free handling of a radiation measuring tool called a survey meter. Our mixed reality radiation-training system merges the physical world with a digital one. Collaborating with a mixed reality headset (HoloLens 2), this system constructs a mock-up of a survey meter in real-world space. The HoloLens 2 employs a browser-based application to visualize radiation and to simulate/share the use of the survey meter, including its physical movements. To provide a dynamic learning experience, the system adjusts the survey-meter mock-up readings according to the operator's movements, distance from the radiation source, the response time of survey meter, and shielding levels. Through this approach, we expect that trainees will acquire practical skills in interpreting survey-meter readings and gain a visual understanding of radiation in real-world situations.

• Journal of Digital Contents Society
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• v.13 no.1
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• pp.67-74
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• 2012

Students with learning disabilities need special education programs. In the traditional class, those students may not be satisfied with their studies. Thus, it is important to provide individualized class for those students. Classes using smart devices may give one of the solutions for individualized class. Unlike the typical mathematical problems, written problems require students to use various cognitive strategies, mathematical reasoning, inference ability, and so on. In this sense, written problems are good tools to develop the logical minds for students with learning disabilities. In this paper, a WOE-based smart learning system is proposed to help those students develop learning abilities. The proposed system has the following characteristics. First, students can learn naturally problem-solving abilities by following the work-out examples given from experts. Second, the proposed system can invoke motivation and interests of students using attractive icons and guidance rules provided with smart phone. Third, the proposed system can provide self-directed study for those students. The proposed system is applied for some students with learning disabilities. The following results are obtained. First, the individualized study can be possible since the system can provide continuous feedbacks and level-differentiated classes. Second, students can increase written problem solving abilities with natural understanding of study contents from smart phone. Finally, satisfaction, study motivation, and self-concept of students are increased through their successful experience during study processes.

• Journal of The Korean Association of Information Education
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• v.11 no.1
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• pp.79-89
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• 2007

Considering the continuous increase of teenagers' Internet use and the high rate of their participation in online communities, educators need to devote efforts to minimize the negative function of teenagers' Internet use and to guide them to experience positive aspects of Internet. Through activities in online communities, teenagers can experience various socialities and explore their self-consciousness. However, on the other hand many communities do not provide teenagers with considerate care. This may cause conflict in their sense of value and mislead them. Through this study, online learning community is designed and developed, which can reflect teenagers' various needs and connect their needs with learning experiences. The community consists of the following categories: 'about e-Tivity'(community vision, general information, list of activities, Q&A), 'activity space for teens'(event hall, data park, e-Tivity center), 'administrative space for teachers and managers'(research room, management room), and 'teen's private space'(my room, my avatar).

• Journal of the Ergonomics Society of Korea
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• v.36 no.4
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• pp.267-280
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• 2017

Objective: The aim of this study is to investigate key user experience factors of interactions for Head Mounted Display (HMD) devices in the Virtual Reality Environment (VRE). Background: Virtual reality interaction research has been conducted steadily, while interaction methods and virtual reality devices have improved. Recently, all of the virtual reality devices are head mounted display based ones. Also, HMD-based interaction types include Remote Controller, Head Tracking, and Hand Gesture. However, there is few study on usability evaluation of virtual reality. Especially, the usability of HMD-based virtual reality was not investigated. Therefore, it is necessary to study the usability of HMD-based virtual reality. Method: HMD-based VR devices released recently have only three interaction types, 'Remote Controller', 'Head Tracking', and 'Hand Gesture'. We search 113 types of research to check the user experience factors or evaluation scales by interaction type. Finally, the key user experience factors or relevant evaluation scales are summarized considering the frequency used in the studies. Results: There are various key user experience factors by each interaction type. First, Remote controller's key user experience factors are 'Ease of learning', 'Ease of use', 'Satisfaction', 'Effectiveness', and 'Efficiency'. Also, Head tracking's key user experience factors are 'Sickness', 'Immersion', 'Intuitiveness', 'Stress', 'Fatigue', and 'Ease of learning'. Finally, Hand gesture's key user experience factors are 'Ease of learning', 'Ease of use', 'Feedback', 'Consistent', 'Simple', 'Natural', 'Efficiency', 'Responsiveness', 'Usefulness', 'Intuitiveness', and 'Adaptability'. Conclusion: We identified key user experience factors for each interaction type through literature review. However, we did not consider objective measures because each study adopted different performance factors. Application: The results of this study can be used when evaluating HMD-based interactions in virtual reality in terms of usability.

• Journal of Korean Academy of Nursing
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• v.30 no.4
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• pp.1035-1044
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• 2000

The purpose of this study was to develop and evaluate an internet based program for nursing informatics. The course subject, Nursing Informatics, was made by a computerized instructional module using the internet. The program was developed after taking into consideration the level of competence and knowledge in the subjects. It was based on 10 steps of the CAI module developed by Alessi and Trollip. The subjects consisted of 76 junior nursing students taking a Nursing Informatics course. Two sets of questionnaires were used for this study. First, a questionnaire was administered to 76 students to collect general information on their experience while using computers and the internet. Secondly, another questionnaire was administrated to 76 students after they took the course. They were asked to evaluate the program in terms of easiness of use, precision of contents, freshness of contents, motivation in learning, effectiveness of learning, enhancement of communication, precision of screen, and interest in the contents. IDs and passwords were given to the students. The students were asked to write their IDs and passwords when they connected to Nursing Informatics (http://hallym.ac.kr/~yhyom/ inform.html). They were led the menu page which was categorized into 8 icons (i. e., syllabus, lecture notes, quick test, Q & A board, assignment, on-line test, related web sites and mailing lists) after confirming their IDs and passwords. The students' responses were very positive. This program was a very useful in increasing the effectiveness of learning and motivation in the students. Suggest to be use for other nursing courses.

• Archives of Plastic Surgery
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• v.47 no.3
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• pp.242-249
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• 2020

Background The Exoscope is a novel high-definition digital camera system. There is limited evidence signifying the use of exoscopic devices in microsurgery. This trial objectively assesses the effects of the use of the Exoscope as an alternative to the standard operating microscope (OM) on the performance of experts in a simulated microvascular anastomosis. Methods Modus V Exoscope and OM were used by expert microsurgeons to perform standardized tasks. Hand-motion analyzer measured the total pathlength (TP), total movements (TM), total time (TT), and quality of end-product anastomosis. A clinical margin of TT was performed to prove non-inferiority. An expert performed consecutive microvascular anastomoses to provide the exoscopic learning curve until reached plateau in TT. Results Ten micro sutures and 10 anastomoses were performed. Analysis demonstrated statistically significant differences in performing micro sutures for TP, TM, and TT. There was statistical significance in TM and TT, however, marginal non-significant difference in TP regarding microvascular anastomoses performance. The intimal suture line analysis demonstrated no statistically significant differences. Non-inferiority results based on clinical inferiority margin (Δ) of TT=10 minutes demonstrated an absolute difference of 0.07 minutes between OM and Exoscope cohorts. A 51%, 58%, and 46% improvement or reduction was achieved in TT, TM, TP, respectively, during the exoscopic microvascular anastomosis learning curve. Conclusions This study demonstrated that experts' Exoscope anastomoses appear non-inferior to the OM anastomoses. Exoscopic microvascular anastomosis was more time consuming but end-product (patency) in not clinically inferior. Experts' "warm-up" learning curve is steep but swift and may prove to reach clinical equality.

• Journal of Broadcast Engineering
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• v.24 no.6
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• pp.1024-1034
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• 2019

Preference for music is determined by a variety of factors, and identifying characteristics that reflect specific factors is important for music recommendations. In this paper, we propose a method to extract the singing voice related music features reflecting various musical characteristics by using a model learned for singer identification. The model can be trained using a music source containing a background accompaniment, but it may provide degraded singer identification performance. In order to mitigate this problem, this study performs a preliminary work to separate the background accompaniment, and creates a data set composed of separated vocals by using the proven model structure that appeared in SiSEC, Signal Separation and Evaluation Campaign. Finally, we use the separated vocals to discover the singing voice related music features that reflect the singer's voice. We compare the effects of source separation against existing methods that use music source without source separation.

• Journal of Practical Engineering Education
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• v.11 no.1
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• pp.87-103
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• 2019

The purpose of this study is to examine the factors affecting the intention of smart device internet usage from the perspective of lifelong learning of elderly people. Survey was conducted for understanding the factors affecting the internet usage intention of smart devices with 150 elderly people who visited the Gwangju Senior Technology Center (GSTC). The empirical results show that the perceived economic value and practical value of the elderly have a significant effect on the intention of utilizing the Internet of Smart Device. Although the moderating effect of the individual innovation of the elderly is not significant, Participation in social activities significantly moderated the relationship between perceived value and intention to use internet. In addition, the elderly expected that the quality of life would be improved via the use of smart devices.

• Phonetics and Speech Sciences
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• v.14 no.3
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• pp.1-9
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• 2022

The current study examined English-speaking adult learners' production and perception of L2 Korean stops (/t/ or /t'/ or /t^h/) to investigate whether the two modalities are linked in utilizing voice onset time (VOT) and fundamental frequency (F0) for the L2 sound distinction and how the learners' L2 proficiency mediates the relationship. Twenty-two English-speaking learners of Korean living in Seoul participated in the word-reading task of producing stop-initial words and the identification task of labelling CV stimuli synthesized to vary VOT and F0. Using logistic mixed-effects regression models, we quantified group- and individual-level weights of the VOT and F0 cues in differentiating the tense-lax, lax-aspirated, and tense-aspirated stops in Korean. The results showed that the learners as a group relied on VOT more than F0 both in production and perception (except the tense-lax pair), reflecting the dominant role of VOT in their L1 stop distinction. Individual-level analyses further revealed that the learners' L2 proficiency was related to their use of F0 in L2 production and their use of VOT in L2 perception. With this effect of L2 proficiency controlled in the partial correlation tests, we found a significant correlation between production and perception in using VOT and F0 for the lax-aspirated stop contrast. However, the same correlation was absent for the other stop pairs. We discuss a contrast-specific role of acoustic cues to address the non-uniform patterns of the production-perception link in the L2 sound learning context.

• The Transactions of the Korea Information Processing Society
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• v.13 no.4
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• pp.174-180
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• 2024

In this paper, we explore an emotion classification method through multimodal learning utilizing wav2vec 2.0 and KcELECTRA models. It is known that multimodal learning, which leverages both speech and text data, can significantly enhance emotion classification performance compared to methods that solely rely on speech data. Our study conducts a comparative analysis of BERT and its derivative models, known for their superior performance in the field of natural language processing, to select the optimal model for effective feature extraction from text data for use as the text processing model. The results confirm that the KcELECTRA model exhibits outstanding performance in emotion classification tasks. Furthermore, experiments using datasets made available by AI-Hub demonstrate that the inclusion of text data enables achieving superior performance with less data than when using speech data alone. The experiments show that the use of the KcELECTRA model achieved the highest accuracy of 96.57%. This indicates that multimodal learning can offer meaningful performance improvements in complex natural language processing tasks such as emotion classification.