• Proceedings of the Korean Institute of Building Construction Conference
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• 2021.11a
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• pp.223-224
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• 2021

The process before the model learning stage in AI R&D can be subdivided into data collection/cleansing-data purification-data labeling. After that, according to the purpose of development, it goes through a stage of verifying the model by performing learning by using the algorithm of the artificial intelligence model. Several studies describe an important part of AI research as the learning stage, and try to increase the accuracy by changing the structure and layer of the AI model. However, if the refinement and labeling process of the learning data is tailored only to the model format and is not made for the purpose of development, the desired AI model cannot be obtained. The latest research reveals that most AI research failures are the failure of the learning data rather than the structure of the AI model. analyzed.

• Journal of Practical Engineering Education
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• v.15 no.1
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• pp.223-232
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• 2023

The Work-Study parallel program has been promoted as a key policy to resolve the mismatch between industrial sites and school education and realize a competency-centered society, and as of December 2022, 16,664 companies participated in the training. Learning companies play a very important role as education and training supply organizations that conduct field training. In this study, for the evaluation of learning companies participating in work-study program, the authors derive important factors that determine the quality of on-site education and training by analyzing the cognitive structure of experts in charge of the company and present evaluation indicators for learning enterprises. Therefore, it is intended to lay the foundation for promoting the quality of work-study parallel program.

• Journal of Korea Multimedia Society
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• v.20 no.12
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• pp.2000-2008
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• 2017

The purpose of this study is to analyze the misconception flowchart of programming control structure and to suggest it as a method for improving computational thinking. In this study, we divide programming control structure concept into sequential, iteration, selection, and function, analyze what concept and principle are difficult for each learner, and what kind of misconception flowchart is drawn in the Introduction of C Programming course for beginners' programming learning. As an example, we show that a lesson learned from the process of correcting the misconception flowchart to the correct flowchart in the course.

• IEIE Transactions on Smart Processing and Computing
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• v.6 no.1
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• pp.53-59
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• 2017

Optical character recognition (OCR) automatically recognizes text in an image. OCR is still a challenging problem in computer vision. A successful solution to OCR has important device applications, such as text-to-speech conversion and automatic document classification. In this work, we analyze character recognition performance using the current state-of-the-art deep-learning structures. One is the AlexNet structure, another is the LeNet structure, and the other one is the SPNet structure. For this, we have built our own dataset that contains digits and upper- and lower-case characters. We experiment in the presence of salt-and-pepper noise or Gaussian noise, and report the performance comparison in terms of recognition error. Experimental results indicate by five-fold cross-validation that the SPNet structure (our approach) outperforms AlexNet and LeNet in recognition error.

• Journal of IKEEE
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• v.23 no.4
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• pp.1408-1414
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• 2019

Deep artificial neural network with transfer learning is applied to compressed sensing cardiovascular MRI. Transfer learning is a method that utilizes structure, filter kernels, and weights of the network used in prior learning for current learning or application. The transfer learning is useful in accelerating learning speed, and in generalization of the neural network when learning data is limited. From a cardiac MRI experiment, with 8 healthy volunteers, the neural network with transfer learning was able to reduce learning time by a factor of more than five compared to that with standalone learning. Using test data set, reconstructed images with transfer learning showed lower normalized mean square error and better image quality compared to those without transfer learning.

• Journal of Korea Society of Industrial Information Systems
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• v.11 no.5
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• pp.181-189
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• 2006

The ubiquitous technology has requested many changes both to the way of learning and to the way of convergence learning content development. However, until now most of e-Learning contents can not meet the requirements of technology convergence and are not developed from the user's perspectives. In this paper, we focus a convergence learning model that is learner-oriented structure, active use of formal and informal learning. Furthermore, examine carefully importance about task analysis, storytelling, and feedback design strategy of learning management system for e-Learning content development. In this context, this paper suggests the effective e-Learning content development method in a convergence era.

• Journal of Information Processing Systems
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• v.8 no.3
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• pp.521-538
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• 2012

As the knowledge society matures, not only distant, but also off-line universities are trying to provide learners with on-line educational contents. Particularly, high effectiveness of mobile devices for e-Learning has been demonstrated by the university sector, which uses distant learning that is based on blended learning. In this paper, we analyzed previous m-Learning scenarios and future technology prospects. Based on the proposed m-Learning scenario, we designed cellular phone-based educational contents and service structure, implemented m-Learning system, and analyzed m-Learning service satisfaction. The design principles of the m-Learning service are 1) to provide learners with m-Learning environment with both cellular phones and desktop computers; 2) to serve announcements, discussion boards, Q&A boards, course materials, and exercises on cellular phones and desktop computers; and 3) to serve learning activities like the reviewing of full lectures, discussions, and writing term papers using desktop computers and cellular phones. The m-Learning service was developed on a cellular phone that supports H.264 codex in 3G communication technology. Some of the functions of the m-Learning design principles are implemented in a 3G cellular phone. The contents of lectures are provided in the forms of video, text, audio, and video with text. One-way educational contents are complemented by exercises (quizzes).

• Proceedings of the KSME Conference
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• 2003.04a
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• pp.816-821
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• 2003

Researchers have utilized artificial evolution techniques and learning techniques for studying the interactions between learning and evolution. Adaptation in dynamic environments gains a significant advantage by combining evolution and learning. We propose an on-line, realtime evolutionary learning mechanism to determine the structure and the synaptic weights of a neural network controller for mobile robot navigations. We support our method, based on (1+1) evolutionary strategy which produces changes during the lifetime of an individual to increase the adaptability of the individual itself, with a set of experiments on evolutionary neural controller for physical robots behaviors. We investigate the effects of learning in evolutionary process by comparing the performance of the proposed realtime evolutionary learning method with that of evolutionary method only. Also, we investigate an interactive evolutionary algorithm to overcome the difficulties in evaluating complicated tasks.

• Journal of The Korean Association For Science Education
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• v.12 no.2
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• pp.19-29
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• 1992

In this study, five learning models were compared and discussed in terms of their learning procedures and learning strateies. After a brief introduction of each model, the author discussed the differences and similarities among the five learning models. As a result, Kwon's procedual learning (Kwon, 1989) seemed to encompass almost all the learning models proposed by the other four author. All the models emphasized the importance of cognitive conflict. However, I. K.Kim(1991), Park(1992) and Y.M.Kim(1991) seemed to be concentrated their attention on the cognitive conflict between concepts ; while Hashweh and Kwon emphasized cognitive conflict between cognitive structure and environment. The study also suggested more study on the empirical evidence of the three kinds of the cognitive conflicts proposed by Kwon(1989) and on the development of learning strategies to induce and overcome the cognitive conflicts.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.612-615
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• 2018

The undergraduate structure based on flip learning should be a necessary course to cultivate value creation capability based on students' problem solving capability through the change of university education in the fourth industrial revolution era. Introduction and spread of Flipping Learning combining project-based learning with MOOC is requied. As the introduction and spread of AI-based learning consulting (E-Advisor), which is becoming increasingly advanced, the transition to "personalized education" that meets the 4th Industrial Revolution should be made.