• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.941-946
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• 2005

In this paper an active random noise control using adaptive learning rate neural networks is presented. The adaptive learning rate strategy increases the learning rate by a small constant if the current partial derivative of the objective function with respect to the weight and the exponential average of the previous derivatives have the same sign, otherwise the learning rate is decreased by a proportion of its value. The use of an adaptive learning rate attempts to keep the learning step size as large as possible without leading to oscillation. It is expected that a cost function minimize rapidly and training time is decreased. Numerical simulations and experiments of active random noise control with the transfer function of the error path will be performed, to validate the convergence properties of the adaptive learning rate Neural Networks. Control results show that adaptive learning rate Neural Networks control structure can outperform linear controllers and conventional neural network controller for the active random noise control.

• Journal of Information Technology Applications and Management
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• v.15 no.3
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• pp.261-273
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• 2008

The starting point of knowledge generation and management is the enhancement of learning capability and capacity of organizational members. Organizational change for learning environment should be aligned with the change of organizational strategy, structure and processes. The study employed action learning methodology to constitute learning organization processes. The treatment effect to institute learning organization has been successful thanks to the members' zeal and consensus to change the processes. However, not every learning team has been so successful. Some cases complained time consuming where others expect to be helpful for their incentives. The researchers concluded that the most important point for success of the learning organization project should be the support of top management.

• Journal of Korea Multimedia Society
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• v.24 no.7
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• pp.868-879
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• 2021

PCB (Printed Circuit Board) inspection using a deep learning model requires a large amount of data and storage. When the amount of stored data increases, problems such as learning time and insufficient storage space occur. In this study, the existing object detection model is changed to a continual learning model to enable the recognition and classification of PCB components that are constantly increasing. By changing the structure of the object detection model to a knowledge distillation model, we propose a method that allows knowledge distillation of information on existing classified parts while simultaneously learning information on new components. In classification scenario, the transfer learning model result is 75.9%, and the continual learning model proposed in this study shows 90.7%.

• Educational Technology International
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• v.24 no.2
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• pp.295-329
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• 2023

The recent development of metaverse-related technology has led to efforts to overcome the limitations of time and space in education by creating a virtual educational environment. To make use of this platform efficiently, applying learning analytics has been proposed as an optimal instructional and learning decision support approach to address these issues by identifying specific rules and patterns generated from learning data, and providing a systematic framework as a guideline to instructors. To achieve this, we employed an inductive, bottom-up approach for framework modeling. During the modeling process, based on the activity system model, we specifically derived the fundamental components of the learning analytics framework centered on learning activities and their contexts. We developed a prototype of the framework through deduplication, categorization, and proceduralization from the components, and refined the learning analytics framework into a 7-stage framework suitable for application in the metaverse through 3 steps of Delphi surveys. Lastly, through a framework model evaluation consisting of seven items, we validated the metaverse learning analytics framework, ensuring its validity.

• Smart Media Journal
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• v.13 no.4
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• pp.104-113
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• 2024

This study is a model study on the contents and methods of intercultural learning. Starting with a discussion of the intercultural learning model construct, it presents key contents important for intercultural learning and learning methods that can increase the effectiveness of intercultural learning. Also, we actually conducted the above learning program at the learning site and discussed the observations and results. It was a case study that allowed us to test the effectiveness of cultural intelligence theory, the latest theory that can improve intercultural competency. In addition, in order for the cultural intelligence theory to be effective in the learning process, it was found that the PBL method, which allows learners to solve problems on their own, rather than cramming education, is useful. Additionally, it was found that the ARCS model was also very effective in motivating and maintaining learners' continuous motivation. At this time, the instructor was also able to see that the effect increases when the role of catalyst becomes the main one.

• The Journal of Korean Institute for Practical Engineering Education
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• v.2 no.1
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• pp.1-7
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• 2010

Recently, interest in u-learning to pursue effective learning by using ubiquitous environment in teaching and learning activities. In u-learning environment, learners should be able to push necessary information at the right time and the right place. Also calm technology oriented to, and this means that it can recognize learners' terminal information and to provide adaptive interface. In u-learning environment, main learning terminals would be mobile terminals which support mobility. However, learning in the existing PC environment should not be excluded. Thus, by providing adaptive interface according to various learners' terminal in LMS for u-learning, learners are able to learn through consistent and natural learning interface with any computer or any network at any place and at any time. The purpose of this study is to propose the interface adaptation based on terminal information focusing on the layout transformation process in the development environment.

• Journal of the Korea Convergence Society
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• v.10 no.7
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• pp.325-333
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• 2019

This study was conducted to investigate the factors affecting satisfaction and dissatisfaction of e-learning learner students using Kano model and Timko's customer satisfaction coefficient. The results of the analysis showed that firstly, the students are highly satisfied when it is convenient to learn visually and audibly, when the students can ask questions at any time, and when the professor was interested in the students. Second, the rational criteria and accurate evaluation of grades and assignments were confirmed as factors that should be satisfied. Third, unlike the results of the basic study that the students use e-learning due to the convenience of learning time and learning space and the ease of learning process, it is no longer an attractive factor to use e-learning. The results of this study suggest that it is possible to present effective directions for the development of e-learning education and strategic application of each factor classified by the two-dimensional recognition method.

• Human Ecology Research
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• v.60 no.2
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• pp.187-209
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• 2022

The objective of this study was to conduct a 'Theory of Home Economics Education' class using online problem-based learning(PBL) for prospective home economics(HE) teachers. The aim was to enable teachers to analyze the learning experience in the classroom, and to prepare operational strategies for online PBL on this basis. In order to achieve this, online PBL was applied to 31 students participating in the 'Theory of Home Economics Education' at the Department of HE in a university in Seoul, and the results were collected from the learning process. This also involved a reflective journal, a survey on the learning experience and the impacts was conducted. Moreover, analysis was undertaken on the learning activities, learning difficulties, and improvements. The main research results are as follows. Firstly, students accessed Webex, an online video conferencing program, and performed two PBL tasks: 'Making Home Economics Promotion Materials' and 'Presenting Teaching Strategies to Improve Learner's Immersion in Online Classes'. Secondly, learners established their own identity of HE learned about the HE class plans themselves. They also encountered realistic experience as HE teachers and learned communication and collaboration skills. Furthermore, they acquired creative problem-solving and self-directed learning ability, community consciousness, as well as the attitude of consideration and respect. Thirdly, students lacked knowledge of learning content and encountered difficulty in solving data research, analysis processes, and unstructured problems. They were affected by a lack of time and encountered problem in communicating with other team members in an online environment. As an improvement in online class operation, it was considrered necessary to reduce the learning burden by securing time and reducing the number of assignments, as well as to explain active interaction with instructors and PBL.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.845-850
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• 2023

In this paper, we propose a method for diagnosing ball bearing vibration using transfer learning. STFT, which can analyze vibration signals in time-frequency, was used as input to CNN to diagnose failures. In order to rapidly learn CNN-based deep artificial neural networks and improve diagnostic performance, we proposed a transfer learning-based deep learning learning technique. For transfer learning, the feature extractor and classifier were selectively learned using a VGG-based image classification model, the data set for learning was publicly available ball bearing vibration data provided by Case Western Reserve University, and performance was evaluated by comparing the proposed method with the existing CNN model. Experimental results not only prove that transfer learning is useful for condition diagnosis in ball bearing vibration data, but also allow other industries to use transfer learning to improve condition diagnosis.

• The Korean Journal of Coaching Psychology
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• v.6 no.1
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• pp.33-55
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• 2022

This study examined the effects of 1:1 online coaching for college students on self-directed learning, learning motivation and time management. The coaching program consisted of motivation, behavior and cognitive control, which are sub-factors of self-directed learning. Total of 7 sessions(80 minutes per session) were progressed. Seven participants who wanted coaching, out of the total 16 participants, were assigned to the experimental group. A non-equal control group experimental design was applied. Dependent variables were measured by questionnaire before and after the coaching, and satisfaction survey and post-interview were also conducted after the coaching. ANCOVA was adopted to test the effectiveness of the program. The statistical results indicated that the learning coaching of this study has positive effect on self-directed learning and learning motivation of university students, and has partially positive effect on time management. In addition, the mean of satisfaction survey was 4.85 and participants showed positive responses on the program.