• Journal of Engineering Education Research
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• v.26 no.2
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• pp.45-53
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• 2023

This study conducted and evaluated the PBL-based team activity classes in contact and untact learning. Appropriate subject (Engineering communication) was also selected and evaluation methods were improved. In the qualitative evaluation results, in contact learning, similar score ranges were formed for each task, and the variability of scores for each task was not large. In untact learning, the difference in scores for each task was rather large, and the variability of scores for each task was large, indicating a large difference between teams that performed well and teams that did not. In the quantitative evaluation, contact learning showed a little low grades, but untact learning showed relatively high grades, but there were limitations in showing the conclusion that the untact learning effect was very good. As a result of the survey, there were more positive responses to the degree of understanding of the class conducted online, the degree of help to improve competence, and the team activity. However, if untact learning continues, it was analyzed that it is necessary to prepare appropriate measures to enhance learning effects and efficiently conduct team activities.

• Journal of Information Processing Systems
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• v.17 no.3
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• pp.505-517
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• 2021

This research presented an implementation of autostereoscopic virtual three-dimensional (3D) button device as non-contact style. The proposed device has several characteristics about visible feature, non-contact use and artificial intelligence (AI) engine. The device was designed to be contactless to prevent virus contamination and consists of 3D buttons in a virtual stereoscopic view. To specify the button pressed virtually by fingertip pointing, a simple deep learning network having two stages without convolution filters was designed. As confirmed in the experiment, if the input data composition is clearly designed, the deep learning network does not need to be configured so complexly. As the results of testing and evaluation by the certification institute, the proposed button device shows high reliability and stability.

• Journal of the Korean Applied Science and Technology
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• v.40 no.1
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• pp.113-122
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• 2023

This study attempted to investigate the effects of experience of non-contact lectures on learning flow against college students majoring in cosmetology and provide basic data to beauty education industry in the with-COVID-19 era. For this, a self-administered questionnaire survey was performed against 300 college students majoring in cosmetology from June 7 to 21, 2022. A total of 286 copies were collected and used for final analysis. The collected data were analyzed by frequency analysis, factor analysis, exploratory factor analysis, descriptive statistics, correlation analysis and multiple regression analysis, using SPSS 21.0, and the results found the followings: According to analysis of non-contact lecture experience factors, two course satisfaction factors were obtained. In learning flow, learning pleasure and learning flow were found. Specifically, class activities had a positive influence on 'learning pleasure (𝛽=.279, p<.007)' and 'learning flow (𝛽=.221, p<.031)' with statistical significance (p<.05). In addition, course satisfaction revealed a positive effect on 'learning flow (𝛽=.223, p<.041)' with statistical significance (p<.05). The above results confirm that experience of non-contact lectures affects learning flow. Therefore, it is anticipated that there would be more efforts to seek an efficient non-contact learning plan in this new era.

• International Journal of Advanced Culture Technology
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• v.8 no.1
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• pp.199-206
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• 2020

I suggested the design learning environment based on affordance concept approach for supporting and improving learners' behavior and outcome for convergent design education in this study. The design learning space should be applied teaching and learning activity, especially learners' behavior, physical space condition to support the design thinking process. The design learning space needs openness, individuality and connectivity to support the learners' behavioral to immerse, participate, cooperate, understand, think and fulfill the design thinking process. The composition principles of the learning environment for convergent design education supports communication and collaboration among members for independence and interaction. The spaces for design research and teaching needs high privacy while facilitating visual communications through special materials and wall structure design. Also, for connectivity to improve the learners' physical and visual contact, the environment of the classrooms requires flexibility and mobility by providing an open space integrating unit cells for realizing learning purpose. These are provided by formed of an open structure for inducing visual communication and physical contact to involve the design activities and the mutual interchange.

• Journal of Practical Engineering Education
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• v.13 no.2
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• pp.305-320
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• 2021

Due to COVID-19, the education and training environment in vocational competency development has changed significantly. In vocational education and training, where the proportion of face-to-face training is more extensive than in other areas of education, some training courses had no choice but to be converted to online. This study presents a distance training system plan for non-contact vocational training by analyzing the learner's non-contact learning experiences. Non-face-to-face education experiences were investigated for learners of private vocational training institutions, universities, and public higher vocational training institutions. The main contents of the survey were to analyze the non-face-to-face learning experiences of these learners for the educational environment and educational purposes. Based on the results of the learners' non-face-to-face learning experiences, a draft of a remote training system construction plan for non-face-to-face education was composed, and a Delphi study was conducted on the draft non-face-to-face remote training system. A method for establishing a distance training system including non-face-to-face teaching and learning strategies, learning and operation support was proposed with these results.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.3
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• pp.339-351
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• 2021

This study was designed to classify the parents' and their children's perception of contact frequency and to examine differences between career development competency and academic outcomes according to perceptional differences. Data of elementary school to high school students from the School Career Education Survey (2018) were used, and latent profile analysis (LPA) was utilized to explore the parents' and their children's perception of contact frequency. The perception of parents' and their children's contact frequency was classified into six groups in elementary and middle school and seven groups in high school. Career development competency (self-understanding and social competence, job understanding, career exploration, and career design and reparation) and academic outcomes (autonomous learning, motivation, and self-directed learning) of classified groups related to contact frequency significantly differed. In general, groups who reported a higher perception of contact frequency by children than parents showed higher vocational identity and better academic outcomes. This result implies that perceived contact frequency between parents and children can differ by school level, and its differences can be related to career development competency and academic outcomes of adolescents.

• The Journal of Korea Robotics Society
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• v.17 no.4
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• pp.455-462
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• 2022

Since electric connectors such as power connectors have a small assembly tolerance and have a complex shape, the assembly process is performed manually by workers. Especially, it is difficult to overcome the assembly error, and the assembly takes a long time due to the error correction process, which makes it difficult to automate the assembly task. To deal with this problem, a reinforcement learning-based assembly strategy using contact states was proposed to quickly perform the assembly process in an unstructured environment. This method learns to generate a search trajectory to quickly find a hole based on the contact state obtained from the force/torque data. It can also learn the stiffness needed to avoid excessive contact forces during assembly. To verify this proposed method, power connector assembly process was performed 200 times, and it was shown to have an assembly success rate of 100% in a translation error within ±4 mm and a rotation error within ±3.5°. Furthermore, it was verified that the assembly time was about 2.3 sec, including the search time of about 1 sec, which is faster than the previous methods.

• Journal of Engineering Education Research
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• v.26 no.6
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• pp.19-29
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• 2023

This study aims to develop and apply a metaverse-based instructional design model for the education in science and technology. It analyzed the concept and characteristics of metaverse, existing non-contact education models, and major teaching strategies systematically. Based on the prior researches, an instructional design model using metaverse is developed that presents metaverse-related teaching strategies and design principles for the before-, during-, and after-lesson phases. Then, this model was applied to a project-based learning program, conducted a perception survey on instructors and learners, and revised the metaverse instructional design model based on the results of the survey. In the Metaverse Instructional Design Model, before-lesson phase is a physical and psychological preparation stage for class participation, which includes familiarization with the Metaverse learning environment, formation of expectations for education, and self-directed pre-learning. During the lesson, to effectively deliver the lesson content, it is necessary to build confidence in the learning environment, promote learning participation, provide reference materials, perform team projects and provide feedback, digest learning content, and transfer learning content. The after-lesson phase provides strategies for ongoing interaction between learners and mentors. This study introduces a new instructional design model that utilizes metaverse and shows the potential of metaverse-based education in science and technology. It also has important implications in that it provides practical guidelines for the effective design and implementation of metaverse-based education.

• Steel and Composite Structures
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• v.43 no.4
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• pp.501-509
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• 2022

Cracks are common defects in concrete structures. Thus far, crack inspection has been manually performed using the contact inspection method. This manpower-dependent method inevitably increases the cost and work hours. Various non-contact studies have been conducted to overcome such difficulties. However, previous studies have focused on developing a methodology for non-contact inspection or local quantitative detection of crack width or length on concrete surfaces. However, crack depth can affect the safety of concrete structures. In particular, although macrocrack depth is structurally fatal, it is difficult to find it with the existing method. Therefore, an experimental investigation based on non-contact infrared thermography and multivariate machine learning was performed in this study to estimate the hidden macrocrack depth. To consider practical applications for inspection, an experiment was conducted that considered the simulated piloting of an unmanned aerial vehicle equipped with infrared thermography equipment. The crack depths (10-60 mm) were comparatively evaluated using linear regression, gradient boosting, and random forest (AI regression methods).

• Transactions of the Korean Society of Machine Tool Engineers
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• v.10 no.6
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• pp.95-101
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• 2001

This work is concerned with construction of the intelligence stress predictor far compression strength evaluation using neural network-ultrasonic waves. The contact pressure in jointed plates was measured by using ultrasonic technique. Neural network is used to evaluate and predict contact pressure from the results of the calibration curves. The organized neural system was leaned with the accuracy of 99%, as a result of learning the ultrasonic echo ratio to the contact pressure measurement between SM45C and STS410 materials. And it could be evaluated and predicted with the accuracy of 90% in the evaluation of ultrasonic echo ratio difference in the same surface roughness and contact pressure, and 85% in the prediction of virtual ultrasonic echo ratio. Thus the proposed stress predictor is very useful for the evaluation and prediction of the contact pressure between SM45C and STS410 materials.