• Journal of Digital Convergence
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• v.17 no.3
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• pp.139-152
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• 2019

In the fourth industrial revolution and the era of convergence and integration, on the situation that the internal colleges are needed active change included in the improvement of educational quality, I tested it on the purpose of empirical analysis with SPSS v.18 how colleges' efforts on the first periodic Organization Evaluation And Accreditation System(OEAAS) affects on the Perceived Management Performances on the perspective of BSC. As the test result, the Degree of Awareness of Colleges' Efforts on the OEAAS affects on just Colleges' Learning and on Growth. The Degree Propriety of Preparation of the OEAAS affects on Customer Performance, on Internal Process Performance, and, on Finance Performance. And the Degree of Satisfaction of Internal Assessment affects on all of BSC 4 performances. The results of this research could be used on making the management idea of colleges' performance on the OEAAS. In the future, it would be needed advanced researches which are able to make relatedness to the expanse of management performance with the OEAAS.

• Smart Media Journal
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• v.8 no.2
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• pp.58-65
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• 2019

Automatic text summarization is a process of shortening a text document by either extraction or abstraction. The abstraction approach inspired by deep learning methods scaling to a large amount of document is applied in recent work. Abstractive text summarization involves utilizing pre-generated word embedding information. Low-frequent but salient words such as terminologies are seldom included to dictionaries, that are so called, out-of-vocabulary(OOV) problems. OOV deteriorates the performance of Encoder-Decoder model in neural network. In order to address OOV words in abstractive text summarization, we propose a copy mechanism to facilitate copying new words in the target document and generating summary sentences. Different from the previous studies, the proposed approach combines accurate pointing information and selective copy mechanism based on bidirectional RNN and bidirectional LSTM. In addition, neural network gate model to estimate the generation probability and the loss function to optimize the entire abstraction model has been applied. The dataset has been constructed from the collection of abstractions and titles of journal articles. Experimental results demonstrate that both ROUGE-1 (based on word recall) and ROUGE-L (employed longest common subsequence) of the proposed Encoding-Decoding model have been improved to 47.01 and 29.55, respectively.

• Korean Journal of Heritage: History & Science
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• v.51 no.2
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• pp.154-169
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• 2018

In modern society, cultural heritage has played a role in constituting national identity. The Cultural Heritage Education Project started in the 2000s by the Cultural Heritage Administration was also aware of the issue of sustainable development and cultural diversity as major cultural issues at the time. However, the main purpose of previous cultural heritage education was to foster national identity. The Cultural Heritage Administration has executed cultural heritage education programs since 2006. The education program of the cultural heritage teacher visiting the school, the project to designate a cultural heritage school, and an education program to experience cultural heritage at an archaeological site were carried out. In the 2010s, the theme of cultural rights and enjoyment of cultural heritage in life was raised as an important issue. Cultural heritage education had to accept the 'new meaning of cultural heritage', 'cultural rights', and 'learnercentered education'. In this context, the local cultural heritage education project started. The region is a space where various identities are reconstructed. However, local cultural heritage education itself cannot realize cultural heritage enjoyment in life. Therefore, it is necessary to seek cultural heritage in life through the various efforts of local cultural heritage education.

• Journal of the Korean Society of Earth Science Education
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• v.11 no.3
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• pp.182-192
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• 2018

The purpose of this study was to examine the effects of school forest activities program on elementary students' science process skill and attitude toward science to make suggestions to help develop and extend the program. The subjects of the study were 49 students of two classes. One class of 24 students, experimental class, took developed 10 periods of school forest activities program. While the other class of 25 students, comparative class, took ordinary teacher driven periods using photo materials and study papers. Before and after the program, pre and post test were done. The results of this study can be summarized as follows: First, the school forest activities program didn't have a meaningful effect on students' science process skill. Second, the school forest activities program had a meaningful effect on the improvement of students' attitude toward science. From the interview with experimental class, we could know that students had a favorable impression and high satisfaction level about the activities program.

• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.803-812
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• 2021

This study explored the concept of artificial intelligence and the problem-solving process that can be explained through literature research. Through this study, the educational meaning and application plan of artificial intelligence that can be explained were presented. XAI education is a human-centered artificial intelligence education that deals with human-related artificial intelligence problems, and students can cultivate problem-solving skills. In addition, through algorithmic education, it is possible to understand the principles of artificial intelligence, explain artificial intelligence models related to real-life problem situations, and expand to the field of application of artificial intelligence. In order for such XAI education to be applied in elementary schools, examples related to real world must be used, and it is recommended to utilize those that the algorithm itself has interpretability. In addition, various teaching and learning methods and tools should be used for understanding to move toward explanation. Ahead of the introduction of artificial intelligence in the revised curriculum in 2022, we hope that this study will be meaningfully used as the basis for actual classes.

• 기호학연구
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• no.54
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• pp.7-36
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• 2018

Michael Polanyi's idea of tacit knowledge came from the realization that scientific objectivity and critical philosophy had become too restrictive for philosophy, especially in the realm of meaning, which is beyond positivistic proof and contains more non-critical elements than critical ones. In social life, people still share certain kinds of knowledge and beliefs which they obtain without making or learning those explicitly. Contemplating the role and significance of tacit knowledge, he called for a post-critical philosophy that integrates the realm of meaning and thereby appreciates the intertwined nature of tacit and explicit knowledge. Polanyi's position towards skepticism and doubt shows similarities with Charles S. Peirce's thinking about the relationship between belief and doubt. Although Peirce's semeiotics stands firmly in the tradition of critical philosophy, he affirms that doubt cannot be a constant state of mind and only belief can form a basis for a specific way of life. Polanyi's approach differs from Peirce's by focusing on the impossibility of scientific knowledge based solely on principles and precision, and his emphasis on the crucial role of the community of scientists. Nevertheless, the deeper implications of Peirce's contemplations on belief and doubt have myriad ramifications on the philosophy of science as well as the sociology of science.

• (The)Study of the Eastern Classic
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• no.32
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• pp.311-362
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• 2008

This study aimed to make clear the education process, from antenatal training to early childhood education, of Joseon Royal Family. Centered on the successors to the throne and reviewed also the education of other Royal Family members, this study carried out comparative analysis on them. Antenatal training is pregnant woman's essential physical and mental attitude. It is indispensable to the health and good nature of unborn baby. Antenatal training had been based on the theory of Oriental medical science that fetus can sympathize what mother see and feel. Such theory, combined with Confucian self-culture theory, had taken very important position in Confucianism. Not to speak of Royal Family, noble family regarded antenatal training very essential as beginning of education and root of nature formation. For firstborn son and firstborn grandson, Boyangcheong (輔養廳, special nursery agency) was set up before their age became three, but not for other sons and grandsons of Royal Family. When firstborn son or firstborn grandson grew up to read letters, Ganghakcheong (講學廳) was set up for their early education. Other sons of king also learned in their early ages at Ganghakcheong while other grandsons of king learned at Gyohakcheong (敎學廳). Education courses were almost same between successors and non-successors but there were wide difference in the ranks of their tutors; firstborn son's tutor marked 2nd Jeong(正) class, firstborn grandson's tutor marked 2nd Jong(從) class and other royal sons' tutors were just 9th Jong(從) class.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.3
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• pp.99-108
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• 2021

There are unrestricted conditions on the driver's face inside the vehicle, such as changes in lighting, partial occlusion and various changes in the driver's condition. In this paper, we propose a face identification system in an unrestricted vehicle environment. The proposed method uses a near-infrared (NIR) camera to minimize the changes in facial images that occur according to the illumination changes inside and outside the vehicle. In order to process a face exposed to extreme light, the normal face image is changed to a simulated overexposed image using mean and variance for training. Thus, facial classifiers are simultaneously generated under both normal and extreme illumination conditions. Our method identifies a face by detecting facial landmarks and aggregating the confidence score of each landmark for the final decision. In particular, the performance improvement is the highest in the class where the driver wears glasses or sunglasses, owing to the robustness to partial occlusions by recognizing each landmark. We can recognize the driver by using the scores of remaining visible landmarks. We also propose a novel robust rejection and a new evaluation method, which considers the relations between registered and unregistered drivers. The experimental results on our dataset, PolyU and ORL datasets demonstrate the effectiveness of the proposed method.

• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.433-441
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• 2020

The advent of the intelligent information society and artificial intelligence education for fostering future talents is attracting the attention of the education community, and the AI graduate course for teachers is also being opened and operated. The curriculum of the AI education graduate school, which was established this year, is self-contained considering the conditions of each university. Are organized. Accordingly, this study seeks to explore the direction of curriculum development so that AI curriculum that can be more effective and enhance educational value in the graduate school of education can be developed in the future. Based on the Backward design, the AI curriculum proposed in this study includes Bloom's digital taxonomy, Bruner's spiral curriculum composition principle, and three elements such as 'content domain', 'level', and 'teacher learning method'. It was intended to consist of. Based on the direction of AI curriculum development suggested in the study, we hope that the AI curriculum of domestic graduate schools of education will be more substantial, and this framework will be revised and supplemented in the future to be used in the composition of the AI curriculum in elementary and secondary schools.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.6
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• pp.834-841
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• 2022

Recently, applying artificial intelligence technologies in various fields of production has drawn an upsurge of research interest due to the increase for smart factory and artificial intelligence technologies. A great deal of effort is being made to introduce artificial intelligence algorithms into the defect detection task. Particularly, detection of defects on the surface of metal has a higher level of research interest compared to other materials (wood, plastics, fibers, etc.). In this paper, we compare and analyze the speed and performance of defect classification by combining machine learning techniques (Support Vector Machine, Softmax Regression, Decision Tree) with dimensionality reduction algorithms (Principal Component Analysis, AutoEncoders) and two convolutional neural networks (proposed method, ResNet). To validate and compare the performance and speed of the algorithms, we have adopted two datasets ((i) public dataset, (ii) actual dataset), and on the basis of the results, the most efficient algorithm is determined.