• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.1001-1004
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• 2021

Pain is an unpleasant experience for the patient. The recognition and assessment of pain help tailor the treatment to the patient, and they are also challenging in the medical. In this paper, we propose an approach for pain recognition through a deep neural network applied to pre-processed physiological. The proposed approach applies the idea of shortcut connections to concatenate the spatial information of a convolutional neural network and the temporal information of a recurrent neural network. In addition, our proposed approach applies the attention mechanism and achieves competitive performance on the BioVid Heat Pain dataset.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.732-734
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• 2023

Facial Action Units Detection (FAUs) problem focuses on identifying various detail units expressing on the human face, as defined by the Facial Action Coding System, which constitutes a fine-grained classification problem. This is a challenging task in computer vision. In this study, we propose a Prompt Tuning approach to address this problem, involving a 2-step training process. Our method demonstrates its effectiveness on the Affective in the Wild dataset, surpassing other existing methods in terms of both accuracy and efficiency.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.167-177
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• 2019

The enhancement of national competitiveness in future society is the discovery and training of excellent SW convergence gifted. In order to cultivate these SW convergence gifted, reinforcing competence of teachers in charge should be made first. Therefore, in this paper, artificial intelligence education contents, one of the core technologies of the 4th Industrial Revolution era, were developed to reinforcing competence of SW convergence gifted teachers. After setting the direction of artificial intelligence education content, we constructed educational content suitable for secondary SW convergence gifted education, and designed and developed it in detail. The composition of artificial intelligence education content consists of machine learning and tensor flow understanding, linear regression machine learning implementation for numerical prediction, and multiple linear regression-based price prediction machine learning implementations. The developed educational contents were verified by experts with qualitative aspects. In the future, we expect that the educational content of artificial intelligence proposed in this paper will be useful for strengthening the ability of SW convergence gifted teachers.

• Journal of Convergence for Information Technology
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• v.11 no.12
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• pp.168-175
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• 2021

In this study, a transdisciplinary convergence education program was developed to enhance the understanding for classification of reptiles and amphibians in biology education and also to increase AI (Artificial Intelligence) capability by using artificial intelligence education. The main content is to solve the classification of reptiles and amphibians that has been dealt with for a long time in biology education, using a decision tree and ML4K (Machine Learnig for Kids), it was designed for a total of 3 lessons. Experts review was conducted on the developed education program, as a result, the I-CVI(Item Content Validity Index) value was .88~1.00 so that can secure content validity. This education program has the advantage of being able to simultaneously learn about the learning contents of artificial intelligence in informatics and the classification of vertebrates in the biological education. In addition, since it is configured to minimize the cognitive load in the AI using part, it is characterized by the fact that all of any teachers can apply it their lesson easily.

• Journal of The Korean Association of Information Education
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• v.26 no.6
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• pp.507-515
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• 2022

In this paper, a novel-engineering-based artificial intelligence liberal arts course is proposed and its effectiveness is evaluated with an emphasis on creativity confluence competency for elementary and middle school pre-service teachers in various majors. Constructing directions such as "considering the characteristics of non-major learners" and "drawing convergence with majors" were derived by analyzing related prior research, and its relationship with Novel Engineering was presented as an appropriate educational method. As a result of 45 hours of artificial intelligence education convergence liberal arts course, a statistically significant improvement in creativity confluence competency and high satisfaction were established. This study is significant because it supported the idea that novel engineering might be used as a pre-service teacher education strategy for artificial intelligence convergence education.

• Convergence Security Journal
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• v.22 no.5
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• pp.61-67
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• 2022

The purpose of this study is to analyze research trends in artificial intelligence. For a three-dimensional analysis, an attempt was made to objectively compare and present the difference between the research direction of artificial intelligence in social science and engineering. For the research method, topic modeling was used among the big data analysis methodologies, and 1000 English papers searched with the keyword artificial intelligence (AI) in the academic research information system were used for the analysis data. As a result of the analysis, in the field of social science, it was possible to identify groups formed around the keywords of 'human', 'impact', and 'future' for artificial intelligence, and in the field of engineering, 'artificial intelligence-based technology development', 'system', 'Groups such as 'Risk-Security' were formed.

• Journal of the Korea Convergence Society
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• v.12 no.10
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• pp.203-210
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• 2021

This study was conducted to develop a convergence education program using smart farms with both input data(temperature, humidity, etc.) and output data(vegetables, fruits, etc.) that are easily accessible in everyday life so that elementary school students can intuitively and easily understand the principles of artificial intelligence(AI) learning. In order to develop this program, we conducted a prior study analysis of a horticulture, software, robot units in the 2015 Practical Arts curriculum and artificial intelligence education. Based on this, 13 components and 16 achievement criteria were selected, and AI programs of 4 sessions(a total of 8 hours). This program can be used as a reference when developing various teaching materials for artificial intelligence education in the future.

• Journal of the Korea Convergence Society
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• v.11 no.12
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• pp.1-13
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• 2020

With the advent of an intelligent information society, research toward artificial intelligence education was conducted. In previous studies, the subject of research is biased, and studies that analyze attitudes toward artificial intelligence are insufficient. So, in this study developed a test tool to measure the artificial intelligence of high school students and analyze their attitudes toward artificial intelligence. To develop the test tool, 229 high school students completed a preliminary test, of which the results were analyzed via exploratory factor analysis. To analyze the students' attitudes toward artificial intelligence, the resulting test tool was applied to 481 high school students, and their test results were analyzed according to factors. From the study's results, there was no difference according to gender in the students' attitudes toward artificial intelligence, but there was a significant difference per grade. In addition, there was a significant difference in attitudes according to artificial intelligence-related experiences: the high school students who had direct and indirect experience with artificial intelligence, programming, and more frequently used it had more positive attitudes toward artificial intelligence than students without this experience. However, artificial intelligence education experience negatively influenced the students' attitudes toward artificial intelligence. Overall, the higher their interest in artificial intelligence, the more positive the high school students' attitudes toward artificial intelligence.

• Nuclear Engineering and Technology
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• v.54 no.10
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• pp.3943-3948
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• 2022

Single-photon emission computed tomography is one of the reliable pin-by-pin verification techniques for spent-fuel assemblies. One of the challenges with this technique is to increase the total fuel assembly verification speed while maintaining high verification accuracy. The aim of the present study, therefore, was to develop an artificial intelligence (AI) algorithm-based tomographic image analysis technique for partial-defect verification of fuel assemblies. With the Monte Carlo (MC) simulation technique, a tomographic image dataset consisting of 511 fuel-rod patterns of a 3 × 3 fuel assembly was generated, and with these images, the VGG16, GoogLeNet, and ResNet models were trained. According to an evaluation of these models for different training dataset sizes, the ResNet model showed 100% pattern estimation accuracy. And, based on the different tomographic image qualities, all of the models showed almost 100% pattern estimation accuracy, even for low-quality images with unrecognizable fuel patterns. This study verified that an AI model can be effectively employed for accurate and fast partial-defect verification of fuel assemblies.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.141-147
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• 2022

In a broad sense, the definition of digital health care is an industrial area that manages personal health and diseases through the convergence of the health care industry and ICT. In a narrow sense, various medical technologies are used to manage medical services to improve patient health. This paper aims to provide design guidelines so that artificial intelligence technology can be applied stably and efficiently to more diverse digital health care fields in the future by introducing use cases of artificial intelligence and machine learning techniques applied in the digital health care field. For this purpose, in this thesis, the medical field and the daily life field are divided and examined. The two regions have different data characteristics. By further subdividing the two areas, we looked at the use cases of artificial intelligence algorithms according to data characteristics and problem definitions and characteristics. Through this, we will increase our understanding of artificial intelligence technologies used in the digital health care field and examine the possibility of using various artificial intelligence technologies.