• The Research Journal of the Costume Culture
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• v.13 no.5 s.58
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• pp.699-711
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• 2005

This study was following one of 'A study on the consciousness of fashion industries internship'. The purposes of this study were to develop the internship program which focused on practical use to introduce and carry out for fashion industries, and secondly to propose some regime for government to activate fashion internship. Reference searching method and depth interviewing method were used for this study. The results were as follows : Fashion industry internship was grouped into two classes, 'on-the-job training'; educating students fields and 'talent hunting'; selecting good persons. Internship of industry-academic world was classified into two types; the one is 'credit type' which has curriculums between universities and industries and the other is 'non-credit type' which has not any credit and is operated by industry own system. This study provided the development courses of pragmatic program to perform internship systematically and it also provided the program models for guide line in fashion industries. Six grades such as ready step, introduction step, selection step, management step, evaluation step and feed-back step were proposed for the internship program development steps of fashion industries. A virtual organization, 'The Fashion Industry and Academy Association' was proposed as a policy for activating internship between universities, industries and government.

• The Journal of Information Systems
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• v.15 no.2
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• pp.1-29
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• 2006

The recent development of IT, consolidation of communication and multimedia technology have brought enormous changes in many organizations. Theses changes are enabling the new educational opportunities such as distance teaming and virtual class room. Recently, e-Learning has grown rapidly in business training field, In the context of companies, e-Learning has merits in terms of access convenience, costs reduction self-directed learning, reciprocity, and flexibility. In this regard, the primary purpose of this study is to investigate which factors of e-Learning influence the effectiveness of education and transfer of loaming in business organizations. Based on the prior studies of the education and business training field, research model and research hypotheses were developed. Factors studied in this paper were as follows: 1) learners' characteristics, 2) organizational support and 3) system environments. The results of our study are as follows. (1) Motivation perceived usefulness in Learner factors had an significant influence on both learning effectiveness and transfer of teaming, whereas Ability, expectation had an influence on transfer of teaming. (2) Support from peer, support from supervisor in Organization factors had an significant influence on both Loaming effectiveness and transfer of teaming, whereas support from organization had influence on learning effectiveness. (3) Appropriate contents in system circumstance had an significant influence on both teaming effectiveness and transfer of teaming, whereas interface design had an influence on learning effectiveness.

• Annual Conference of KIPS
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• 2014.11a
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• pp.1113-1115
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• 2014

본 프로젝트팀에서 개발한 'VTK'(Virtual Training by Kinect)는 아이부터 노인까지 모든 연령이 이용 가능한 기능성 게임으로써 동작인식 컨트롤러인 키넥트를 이용하여 불필요한 장비가 없이 동작인식을 통해 인터페이스가 가능하게 했다. 주요기능은 평가와 트레이닝, 통계분석 세 가지로 이루어져 있다. 사용자는 6분 걷기와 폐안시 외발서기를 통해 개인별 심폐지구력과 평형감각 수준을 알 수 있으며 조깅과 인라인 스케이트를 통해 기능 향상을 위한 트레이닝을 할 수 있다. 통계분석은 별도의 용용프로그램을 통해 확인 할 수 있다. 성장하고 있는 기능성 게임 시장에 새로운 방향성 제시를 목표로 하였다.

• Journal of information and communication convergence engineering
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• v.21 no.1
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• pp.98-102
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• 2023

This paper presents a study on how augmenting semi-synthetic image data improves the performance of human detection algorithms. In the field of object detection, securing a high-quality data set plays the most important role in training deep learning algorithms. Recently, the acquisition of real image data has become time consuming and expensive; therefore, research using synthesized data has been conducted. Synthetic data haves the advantage of being able to generate a vast amount of data and accurately label it. However, the utility of synthetic data in human detection has not yet been demonstrated. Therefore, we use You Only Look Once (YOLO), the object detection algorithm most commonly used, to experimentally analyze the effect of synthetic data augmentation on human detection performance. As a result of training YOLO using the Penn-Fudan dataset, it was shown that the YOLO network model trained on a dataset augmented with synthetic data provided high-performance results in terms of the Precision-Recall Curve and F1-Confidence Curve.

• Archives of Plastic Surgery
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• v.50 no.2
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• pp.200-209
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• 2023

Background As the coronavirus disease 2019 virus made its way throughout the world, there was a complete overhaul of our day-to-day personal and professional lives. All aspects of health care were affected including academics. During the pandemic, teaching opportunities for resident training were drastically reduced. Consequently, medical universities in many parts across the globe implemented online learning, in which students are taught remotely and via digital platforms. Given these developments, evaluating the existing mode of teaching via digital platforms as well as incorporation of new models is critical to improve and implement. Methods We reviewed different online learning platforms used to continue regular academic teaching of the plastic surgery residency curriculum. This study compares the four popular Web conferencing platforms used for online learning and evaluated their suitability for providing plastic surgery education. Results In this study with a response rate of 59.9%, we found a 64% agreement rate to online classes being more convenient than normal classroom teaching. Conclusion Zoom was the most user-friendly, with a simple and intuitive interface that was ideal for online instruction. With a better understanding of factors related to online teaching and learning, we will be able to deliver quality education in residency programs in the future.

• Journal of IKEEE
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• v.27 no.1
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• pp.38-44
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• 2023

Performance of a STAP(space-time adaptive processing) algorithm highly depends on how closely the estimated covariance matrix(CM) resembles the actual CM by the interference in CUT(cell under test). A STAP has 2 dimensional data structure determined by the number of array elements and the number of transmitting pulses and both numbers are generally not small. Thus, to meet the degree of freedom(DOF) of the CM, a huge amount of training data is required. This paper presents an algorithm to generate virtual training data from small received data, via converting them into the data in spatial frequency-Doppler plane. We theoretically derive where the clutter exist in the plane and present the procedure to implement the proposed algorithm. Finally, with the simulated scenario of small received data, we show the proposed algorithm can improve STAP performance.

• Journal of Astronomy and Space Sciences
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• v.41 no.2
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• pp.61-78
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• 2024

This study developed a real-time spacecraft pose estimation algorithm that combined a deep learning model and the least-squares method. Pose estimation in space is crucial for automatic rendezvous docking and inter-spacecraft communication. Owing to the difficulty in training deep learning models in space, we showed that actual experimental results could be predicted through software simulations on the ground. We integrated deep learning with nonlinear least squares (NLS) to predict the pose from a single spacecraft image in real time. We constructed a virtual environment capable of mass-producing synthetic images to train a deep learning model. This study proposed a method for training a deep learning model using pure synthetic images. Further, a visual-based real-time estimation system suitable for use in a flight testbed was constructed. Consequently, it was verified that the hardware experimental results could be predicted from software simulations with the same environment and relative distance. This study showed that a deep learning model trained using only synthetic images can be sufficiently applied to real images. Thus, this study proposed a real-time pose estimation software for automatic docking and demonstrated that the method constructed with only synthetic data was applicable in space.

• Proceedings of the Korean Institute Of Construction Engineering and Management
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• 2008.11a
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• pp.170-175
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• 2008

The research team for the virtual construction development was established with the support of Korea Ministry of Construction and Transportation, and KICTEP (Korea Institute of Construction and Transportation Technology Evaluation and Planning). Its aims are to develop system that is to improve productivity & quality, to create a higher value-added business, and to cultivate international competitiveness in the construction industry. The virtual construction system is a design, engineering, and construction management information system that allows the project participants to effectively share the information throughout the construction life cycle with the support of 3D and design information. To achieve this, the research team focuses on developing several systems. First, the team focuses on developing for the pre-planning, the structural engineering, MEP, and the 3D based estimation system. Second, they focus on developing a simulation system for the construction process planning and feasibility study with help of the virtual reality technologies. Third, they focus on developing the CPLM (Construction Project Life-cycle Management) system for managing construction project data, and the decision support system that makes the collaboration among the project participants based on 3D technologies and information. We also focus on developing the SDAI (Standard Data Access Interface), the localized guideline for 3D design, and a training program. In addition, we focus on developing the undeveloped area of the commercial system and building an environment that can support the communication and collaboration in the construction life-cycle rather than developing the existing and commercialized system.

• Journal of the Korea Convergence Society
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• v.10 no.3
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• pp.157-165
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• 2019

The purpose of this study was to verify effects of virtual reality based intervention program on communication skills in cafe and class attitudes of students with intellectual disabilities. To do this, 30 students with intellectual disabilities were participated in this study and placed an experimental group and a control group. An experimental group took part in the virtual reality based intervention program on communication skills in cafe and a control group joined in the traditional intervention program at summer vacation from July, 22 to August, 24. Intervention programs of an experimental group and an control group were conducted 5 times in a week for 4 weeks and a class time of each class was 50 minutes. Evaluations of two groups were carried out in pre-test and post-test and data of evaluation was analyzed by independent t-test. In Results of study, communication skills of experimental group were improved higher than control group's. Also, class attitudes of experimental group were changed more positive than control group's on job training class. We knew that virtual reality based intervention program was effectively utilized in transitional education for students with intellectual disabilities.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.675-683
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• 2022

Blockchain, which is the basis of virtual assets such as cryptocurrency, is receiving great attention as one of the cornerstone technologies of the 4th industrial revolution. Blockchain is a technology that can fundamentally change our lives not only in finance, but also in politics, logistics, and culture. However, it shows lower-than-expected usability because it is complicated to learn and is continuously being developed. In this study, we tried to investigate whether the Technology Acceptance Model(TAM) of virtual assets can be changed through education on the underlying technology, blockchain. A video-based online experiment was conducted with a total of 103 participants and examined how the type of training(positive, negative) and measurement timing(before, after) affect perceived usefulness, perceived ease of use, acceptance, which are TAM variables, and trust and security, which are related to blockchain characteristics. As a result of the experiment, interactions were found in all dependent variables according to the type of education and measurement timing. Specifically, groups that received negative education had no difference in all variables before and after, but it was found that groups that received positive education showed an increase afterwards. Through this, it can be seen that the effect of education based on the anchoring effect is also shown in the intention to use virtual assets using block chain technology, suggesting that the intention to use blockchain related technology can be increased through positive education.