• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.664-671
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• 2023

최근 다양한 거대 언어모델(Large Language Model)들이 개발되면서 프롬프트 엔지니어링의 대한 다양한 연구가 진행되고 있다. 본 논문에서는 퓨삿 학습 환경에서 개체명 인식의 성능을 높이기 위해서 제안된 템플릿이 필요 없는 프롬프트 튜닝(Template-free Prompt Tuning) 방법을 이용하고, 이 방법에서 사용된 라벨 단어 집합 생성 방법에 Maximal Marginal Relevance 알고리즘을 적용하여 해당 개체명에 대해 보다 다양하고 구체적인 라벨 단어 집합을 생성하도록 개선하였다. 실험 결과, 'LOC' 타입을 제외한 나머지 개체명 타입에서 'PER' 타입은 0.60%p, 'ORG' 타입은 4.98%p, 'MISC' 타입은 1.38%p 성능이 향상되었고, 전체 개체명 인식 성능은 1.26%p 향상되었다. 이를 통해 본 논문에서 제안한 라벨 단어 집합 생성 기법이 개체명 인식 성능 향상에 도움이 됨을 보였다.

• The Mathematical Education
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• v.51 no.3
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• pp.301-321
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• 2012

Since research has barely been done on the minority with low-achievement & low-SES in probability, this research attempted to search the change of their thinking level in the classes of probability and motivate them on the mathematical learning to feel confident in mathematics. We can say that the problems of the educational discriminations are due to the overlook on the individual conditions, situations, and environments. Therefore, in order to resolve some discrimination, 4 students who belonged to the minority group, engaged in the research, based on 10 units of the instructional materials designed for the research. As a result, for the student's thinking level, it was observed that they were improved from the 1st to the 3rd level in probability. Also, the researcher found that the adequate use of the encouragement, the praise, the direct explanation, and the scaffolding enabled them to prompt their learning motives and the increased responsibility on the learning. As time passed, the participants could share their mathematical knowledge and its concept with others, in the increased confidence.

• Journal of Medicine and Life Science
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• v.20 no.4
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• pp.141-157
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• 2023

Stroke is a leading cause of disability and death. The condition requires prompt diagnosis and treatment. The quality of care provided to patients with stroke can vary depending on the availability of medical resources, which in turn, can affect prognosis. Recently, there has been growing interest in using machine learning (ML) to support stroke diagnosis and treatment decisions based on large medical data sets. Current ML applications in stroke care can be divided into two categories: analysis of neuroimaging data and clinical information-based predictive models. Using ML to analyze neuroimaging data can increase the efficiency and accuracy of diagnoses. Commercial software that uses ML algorithms is already being used in the medical field. Additionally, the accuracy of predictive ML models is improving with the integration of radiomics and clinical data. is expected to be important for improving the quality of care for patients with stroke.

• Korean Journal of Artificial Intelligence
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• v.5 no.1
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• pp.10-17
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• 2017

This study is the first attempt to raise face recognition ability through machine learning algorithm and apply to CRM's information gathering, analysis and application. In other words, through face recognition of VIP customer in distribution field, we can proceed more prompt and subdivided customized services. The interest in machine learning, which is used to implement artificial intelligence, has increased, and it has become an age to automate it by using machine learning beyond the way that a person directly models an object recognition process. Among them, Deep Learning is evaluated as an advanced technology that shows amazing performance in various fields, and is applied to various fields of image recognition. Face recognition, which is widely used in real life, has been developed to recognize criminals' faces and catch criminals. In this study, two image analysis models, TF-SLIM and Inception-V3, which are likely to be used for criminal face recognition, were selected, analyzed, and implemented. As an evaluation criterion, the image recognition model was evaluated based on the accuracy of the face recognition program which is already being commercialized. In this experiment, it was evaluated that the recognition accuracy was good when the accuracy of the image classification was more than 90%. A limit of our study which is a way to raise face recognition is left as a further research subjects.

• Journal of the Ergonomics Society of Korea
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• v.25 no.2
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• pp.125-134
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• 2006

Most users learn new, complex systems through trial-and-error experience rather than referring to the manuals in a cognitive process that is called 'exploratory learning'. While exploring a system, people find prototypical rules for using the system based especially on frequent tasks. The rules are formed from consistent task procedures and well-expected interface elements on the designed system. These rules play the role of the basis of users' knowledge for performing tasks. The decision making to select and apply those rules interacting with an interface can be aided by properly provided hints on the interface. With appropriate hints, users can learn new systems easily and use them with reduced usability problems. This paper first reports an observation of user behavior performing tasks with prototypical interaction rules and finds a sound set of criteria to extract prototypical interaction rules systematically. Two types of hints are defined. Extending hints prompt users to apply prototypical interaction rules beyond well-known tasks. Preventive hints guide users out of possible capture errors by drawing attention to the variation of rules. A systematic and practical method is proposed to identify the opportunities for both types in designing interfaces. It is then verified through a usability test that the proposed method is effective in identifying the locations and types of appropriate hints to reduce or mitigate usability problems.

• Journal of the Korea Society of Computer and Information
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• v.25 no.10
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• pp.15-22
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• 2020

In this study, we propose an improvement method that can create U-Net model which detect fine concrete cracks by applying a weighted loss function. Because cracks in concrete are a factor that threatens safety, it is important to periodically check the condition and take prompt initial measures. However, currently, the visual inspection is mainly used in which the inspector directly inspects and evaluates with naked eyes. This has limitations not only in terms of accuracy, but also in terms of cost, time and safety. Accordingly, technologies using deep learning is being researched so that minute cracks generated in concrete structures can be detected quickly and accurately. As a result of attempting crack detection using U-Net in this study, it was confirmed that it could not detect minute cracks. Accordingly, as a result of verifying the performance of the model trained by applying the suggested weighted loss function, a highly reliable value (Accuracy) of 99% or higher and a harmonic average (F1_Score) of 89% to 92% was derived. The performance of the learning improvement plan was verified through the results of accurately and clearly detecting cracks.

• 전자공학회논문지 IE
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• v.48 no.1
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• pp.36-44
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• 2011

The purpose of this study was to develop the basic design principles for the engineering mathematics teaching model that supported college students to become collaborative problem solvers. For this purpose, the following four design principles were drawn from the steps of systems approach, especially with consideration of needs of engineering students, professors, curriculum and relevant research on mathematical education. As a result, the four design principles for the engineeering mathematics teaching model were drawn as follows: (1) Improve students' basic mathematical learning abilities through repetition and elaborative practice of the basic mathematical concepts and principles, (2) Develop students' problem solving abilities through collaborative projects or learning activities with peers, (3) Facilitate students' reflection and provide teacher's monitoring and prompt feedback during their learning process, and (4) Build up online learning environments that enable students to become self-regulated learners.

• Journal of the Korea Society of Computer and Information
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• v.28 no.4
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• pp.209-216
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• 2023

In this paper, artificial intelligence agents ChatGPT and Stable Diffusion were used to explore the possibility of educational use by implementing a program to recommend picture materials for teaching and learning according to the class topic entered by teachers. The average time spent recommending all picture materials is about 6 minutes. In general, pictures related to keywords were recommended, and the letters in the recommended pictures could only know the intention to represent the letters, and the letters could not be recognized and the meaning could not be known. However, further research seems to be needed on the fact that the type or content of the recommended picture depends entirely on the response of ChatGPT and that it is not possible to accurately recommend the picture for all keywords. In addition, it was concluded that it is true that the recommended picture is related to the keyword, but the evaluation of whether it has educational value is the subject of discussion that should be left to the judgment of human teachers.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.449-453
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• 2008

정보와 환경의 급속한 발전에도 불구하고 고령자, 장애인 등은 웹 서비스를 포함한 보편적 서비스를 받지 못하고 소외되고 있다. 본 연구는 최근 활발하게 이루어지고 있는 공공 및 사설 교육 사이트의 E-Learning이 웹 접근성 표준 평가 항목인 '한국형 웹 콘텐츠 접근성 지침'(Korea Web Contents Accessibility Guide 1.0)을 준수 여부를 웹 접근성 평가도구를 사용하여 측정 및 분석하고, 정보격차의 해소를 위한 방향을 제시하였다.

• Korean Journal of Childcare and Education
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• v.12 no.4
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• pp.131-149
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• 2016

Teacher's practical knowledge is potentially relevant to the teaching practice in his/her classroom. The research explored early childhood teachers' practical knowledge of 'curriculum' via conceptual metaphors. The participants (N=348) completed a prompt, "Curriculum is like A because B" and then the metaphors were analyzed according to the procedure proposed by Moser (2000). The analysis found that 8 themes (i.e. 'educational basis', 'learning opportunity', 'educational material', 'difficulty', 'change', 'pre-determination', 'discordance', and 'reconstruction') were the underlying conceptions signified in those metaphors. The implications regarding early childhood teachers' practical knowledge were discussed on the perspective of post-modern curriculum. Moreover, it recommended the practical knowledge based approach for early childhood teacher education, and transformation of current policy for program evaluation relevant to curriculum conceptualization.