• Journal of The Korean Association of Information Education
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• v.25 no.5
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• pp.791-801
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• 2021

In this paper, an educational case that can be applied as artificial intelligence literacy education for preservice teachers and incumbent teachers was studied. To this end, a case of educating the operating principle of an artificial neural network that recognizes images is proposed. This training case focuses on the basic principles of artificial neural network operation and implementation, and applies the method of finding parameter optimization solutions required for artificial neural network implementation in a spreadsheet. In this paper, we focused on the artificial neural network of supervised learning method. First, as an artificial neural network principle education case, an artificial neural network education case for recognizing two types of images was proposed. Second, as an artificial neural network extension education case, an artificial neural network education case for recognizing three types of images was proposed. Finally, the results of analyzing artificial neural network training cases and training satisfaction analysis results are presented. Through the proposed training case, it is possible to learn about the operation principle of artificial neural networks, the method of writing training data, the number of parameter calculations executed according to the amount of training data, and parameter optimization. The results of the education satisfaction survey for preservice teachers and incumbent teachers showed a positive response result of over 70% for each survey item, indicating high class application suitability.

• ETRI Journal
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• v.10 no.3
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• pp.113-124
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• 1988

본 논문에서는 한글 단어를 발음 기호로 변환시키는 인공신경망의 설계와 이를 시뮬레이션한 결과에 대하여 논한다. 이 인공신경망은 multi-layer perceptron 구조를 가지며 error back-propagation 학습 알고리즘을 사용하였다. 이 인공신경망에 한글 발음 사전의 일부를 반복적으로 제시하여 학습시킨 결과, 학습한 단어에 대하여 최고 97%의 정확도로 변환 작업을 수행하였고 학습하지 않은 단어에 대해서는 91%의 정확도를 보였다. 이는 설계된 인공신경망이 발음 사전 내에 포괄적으로 내재되어 있는 발음규칙을 스스로 학습하였음을 나타낸다. 아울러 신경망의 학습 성취도와 입력 코드와의 관계도 연구하였는데, 한글단어를 발음기호로 변환하는 데에 있어서 compact 코드 보다 local 코드일 때 학습 성취도가 높은 것이 실험을 통해 밝혀졌다.

• The Mathematical Education
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• v.62 no.3
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• pp.303-326
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• 2023

Mathematics is a discipline with a strong systemic structure, and learning deficits in previous stages have a great influence on the next stages of learning. Therefore, it is necessary to frequently check whether students have learned well and to provide immediate feedback, and for this purpose, intelligent tutoring system(ITS) can be used in math education. For this reason, it is necessary to reveal how the intelligent tutoring system is effective in personalized adaptive learning. The purpose of this study is to investigate the functions and applications of intelligent tutoring system for personalized adaptive learning in mathematics. To achieve this goal, literature reviews and surveys with students were applied to derive implications. Based on the literature reviews, the functions of intelligent tutoring system for personalized adaptive learning were derived. They can be broadly divided into diagnosis and evaluation, analysis and prediction, and feedback and content delivery. The learning and lesson plans were designed by them and it was applied to fifth graders in elementary school for about three months. As a result of this study, intelligent tutoring system was mostly supporting personalized adaptive learning in mathematics in several ways. Also, the researcher suggested that more sophisticated materials and technologies should be developed for effective personalized adaptive learning in mathematics by using intelligent tutoring system.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.10a
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• pp.316-320
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• 1992

기계나 구조물등의 부재는 비금속 개재 물이나 가공과 같은 자연 결함과 함께 볼트구멍이나 기름구멍등의 인공 결함들을 가지고 있다. 이러한 인공 결함들은 초기 결함으로서 작용을 하여 반복되는 낮은 응력을 받을 경우 응력 집중원이 되고, 피로파괴의 원인이 된다. 이런 기계구조물에 대한 안전성 보장을 위하여, 금속재료의 제조 및 가공 공정상의 질적 개선과 함께 최적 설계가 강조되고 피로파괴 현상에 대한 많은 연구가 요구되고 있다.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.572-578
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• 2021

The purpose of this study was to verify the impact of cognitive and emotional factors on artificial intelligence speakers on the intention of using artificial intelligence speakers. The method for this study was online surveys of people with physical disability. The recognition and necessity of artificial intelligence speakers were also identified, the perceived intimacy, joy, and intention to use them, and a multiple linear regression analysis was conducted to check the influence of each variable on the intention of the disabled to use artificial intelligence speakers. This study have shown that the perceived enjoyment of AI speakers in people with disabilities has shown a significant static effect on their intended use. However, the recognition and necessity of artificial intelligence speakers of the physically handicapped, as well as the perceived intimacy, do not have a statistically significant impact on the intention of using artificial intelligence speakers, according to the analysis. The results of this study suggest that it is necessary to strengthen the elements of enjoyment in order to improve the intention of the disabled to use artificial intelligence speakers, and it is meaningful in that it provides basic data to develop artificial intelligence products and customized services for people with disabilities.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.175-186
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• 2023

This study was conducted to explore the necessary conditions and support for stable operation of an expanded AI curriculum in education. A high school that has implemented an AI curriculum since 2020 was targeted, and students and teachers were surveyed on their perceptions of the AI curriculum, implementation and support strategies. The survey items were categorized into 1) experience with AI education, 2) implementation direction of AI education, and 3) expected effects through AI education, and the results were derived focusing on frequency analysis to identify trends. The analysis resulted in three implications. First, it was suggested that the activation of AI education. Second, the need to develop a hands-on AI curriculum and incorporate AI throughout the entire curriculum was highlighted. Third, it was emphasized that efforts to enhance the capabilities of teachers to implement AI teaching and learning, along with the expansion of physical infrastructure for hands-on education, are necessary.

• Education of Primary School Mathematics
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• v.27 no.1
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• pp.19-38
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• 2024

This study aims to analyze the characteristics of students' understanding of artificial intelligence and mathematical concepts by developing and applying an artificial intelligence education program for mathematics convergence using robots. To this end, we analyzed the content standards of elementary artificial intelligence education to extract conceptual elements of artificial intelligence and identified mathematics achievement standards that can effectively integrate them. In particular, a five-session (15 classes in total) program was developed by selecting the units 'angle' and 'quadrilateral' suitable for utilizing the robot's movement and reorganizing the lesson to integrate the mathematics achievement standard with the artificial intelligence content elements. As a result of applying this to 22 fourth grade elementary school students over five months and analyzing the students' understanding revealed by topic of artificial intelligence content, the artificial intelligence education program for mathematics convergence using robots was helpful in students' understanding artificial intelligence principles and mathematical concepts. In addition, the use of robots was confirmed to improve students' understanding of artificial intelligence and mathematics as well as their participation in class by making them visually check a series of performing procedures.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.01a
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• pp.151-154
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• 2017

소프트웨어의 개발과정 중 결함을 제거하는 작업인 디버깅을 위해서는 가장 먼저 그 결함의 정확한 위치를 찾아야한다. 이 작업은 많은 시간이 소요되며, 이 시간을 단축시키기 위한 결함 위치 식별 기법들이 소개되었다. 많은 기법들 중 프로그램 커버리지 정보를 학습하여 규칙을 분석하는 인공신경망 기반 선행 연구가 있다. 이를 기반으로 본 논문에서는 문장들 간의 관계를 추가적으로 파악하여 학습 데이터로 사용하는 기법을 제안한다. 특정 문장이 항상 지나는 테스트케이스들 중 나머지 다른 문장들이 지나는 테스트케이스의 비율을 통해 문장들 간의 관계를 나타낸다. 해당 비율을 계산하기 위해 조건부 확률인 베이지안 확률을 사용한다. 베이지안 확률을 통해 얻은 문장들의 관계에 따라 인공신경망 내에서 의심도를 결정하는 웨이트(weight)가 기존 기법과는 다르게 학습된다. 이 차이는 문장들의 의심도를 조정하며, 결과적으로 다중 결함 위치 식별의 정확도를 향상시킨다. 본 논문에서 제안한 기법을 이용하여 실험한 결과, Tarantula 대비 평균 39.8%, 기존 역전파 인공신경망(BPNN) 기반 기법 대비 평균 60.5%의 정확도 향상이 있었음을 확인할 수 있다.

• Journal of the Korea Convergence Society
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• v.11 no.10
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• pp.187-195
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• 2020

The purpose of study is to find ways to improve online research work in the near future environment. Study methods and results are as follows. First, the basis of research was secured through theoretical consideration. Second, three types were derived by collecting examples. There are reward, execution and visualization. Third, comprehensive matrix and directions were derived through case analysis. According to the study, the most frequently used phase of AI technology were analysis, visualization, execution, casting, design, and matching, The direction of use of AI can be largely divided into work efficiency, human thought assistance, and changes in research methods. But the plan phase is generally scarce. Overall, the lack of in function is provided, including AI technology. At a time when research plans are becoming more important as users and products diversify.

• Proceedings of the Korean Vacuum Society Conference
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• 2012.02a
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• pp.137-137
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• 2012

인공관절은 노인성 질환이나 자가 면역질환, 신체적인 외상 등으로 인하여 발생하는 관절의 손상 부위를 대체하기 위하여 고안된 관절의 인공 대용물이다. 인공 관절 중 인공 고관절의 경우 라이너(Liner)와 헤드(Head) 부분이 직접적인 마모 운동을 수행하게 되므로, 이 부분의 소재 특성에 따라 인공관절의 수명이 결정 되게 된다. 현재 헤드 소재로서는 Co-Cr-Mo 합금이, 라이너 소재로서는 고분자 소재인 UHMWPE (Ultra High Molecular Weight Polyethylene)가 주로 사용되고 있다. 이러한 MOP (Metal-On-Polymer) 구조의 인공관절의 경우, 충격흡수의 장점이 있는 반면, 관절 운동시 발생하는 UHMWPE 의wear debris에 의해 골용해가 발생하게 되어 인공관절의 수명이 저하되는 문제점이 있으며, 금속 헤드의 마모로 인한 금속이온의 용출은 세포 독성의 문제를 야기하여 인공관절의 수명을 저하시키는 또 다른 원인이 되고 있다. 따라서 본 연구에서는 PIII&D (Plasma Immersion Ion Implantation & Deposition) 공정을 이용하여 금속 (Co-Cr-Mo 합금)소재 위에 세라믹 (niobium nitride) 박막을 증착하여 상대재인 UHMWPE의 마모를 줄이고자 하는 연구를 진행하였다. 금속 소재 위에 증착된 세라믹 박막은 상대재인 UHMWPE의 마모량을 줄여줄 뿐만 아니라 금속이온의 용출을 막아준다는 장점이 있으나, 장시간의 마모 운동에 의하여 발생하는 박막의 박리 현상은 인공관절의 수명을 급격히 저하시키는 또 다른 원인이 된다. 이러한 단점을 해결하기 위하여, 박막의 증착 초기에 이온주입과 증착을 동시에 수행하는 dynamic ion mixing공정을 수행하였다. Dynamic ion mixing 공정을 수행함에 따라 박막과 금속 사이의 접착력이 증가하게 되어, UHMWPE의 마모량이 2배 가까이 감소하는 것을 확인할 수 있었으며, 장시간의 마모시험에서도 우수한 결과를 얻을 수 있었다. 또한 UHMWPE의 마모량을 감소시키기 위하여 박막을 증착하기 전에 금속 소재에 질소 이온주입을 수행하는 pre-ion implantation 공정을 도입하였다. 질소 이온주입 결과 Co-Cr-Mo 합금 표면에 부분적으로 CrN, Cr2N의 세라믹 상이 형성 되는 것을 확인할 수 있었으며, 그에 따라 UHMWPE의 마모량이 2배 이상 감소 되는 것을 확인 할 수 있었다.