• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.1-12
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• 2022

Traditional methods of measuring corneal ulcers were difficult to present objective basis for diagnosis because of the subjective judgment of the medical staff through photographs taken with special equipment. In this paper, we propose a method to detect the ulcer area on a pixel basis in corneal ulcer images using a semantic segmentation model. In order to solve this problem, we performed the experiment to detect the ulcer area based on the DeepLab model which has the highest performance in semantic segmentation model. For the experiment, the training and test data were selected and the backbone network of DeepLab model which set as Xception and ResNet, respectively were evaluated and compared the performances. We used Dice similarity coefficient and IoU value as an indicator to evaluate the performances. Experimental results show that when 'crop & resized' images are added to the dataset, it segment the ulcer area with an average accuracy about 93% of Dice similarity coefficient on the DeepLab model with ResNet101 as the backbone network. This study shows that the semantic segmentation model used for object detection also has an ability to make significant results when classifying objects with irregular shapes such as corneal ulcers. Ultimately, we will perform the extension of datasets and experiment with adaptive learning methods through future studies so that they can be implemented in real medical diagnosis environment.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.675-683
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• 2022

Blockchain, which is the basis of virtual assets such as cryptocurrency, is receiving great attention as one of the cornerstone technologies of the 4th industrial revolution. Blockchain is a technology that can fundamentally change our lives not only in finance, but also in politics, logistics, and culture. However, it shows lower-than-expected usability because it is complicated to learn and is continuously being developed. In this study, we tried to investigate whether the Technology Acceptance Model(TAM) of virtual assets can be changed through education on the underlying technology, blockchain. A video-based online experiment was conducted with a total of 103 participants and examined how the type of training(positive, negative) and measurement timing(before, after) affect perceived usefulness, perceived ease of use, acceptance, which are TAM variables, and trust and security, which are related to blockchain characteristics. As a result of the experiment, interactions were found in all dependent variables according to the type of education and measurement timing. Specifically, groups that received negative education had no difference in all variables before and after, but it was found that groups that received positive education showed an increase afterwards. Through this, it can be seen that the effect of education based on the anchoring effect is also shown in the intention to use virtual assets using block chain technology, suggesting that the intention to use blockchain related technology can be increased through positive education.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.5
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• pp.57-66
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• 2022

The Road Management Administration is cracking down on overloaded vehicles by installing low-speed or high-speed WIMs at toll gates and main lines on expressways. However, in recent years, the act of intelligently evading the overloaded-vehicle control system of the Road Management Administration by illegally manipulating the variable axle of an overloaded truck is increasing. In this manipulation, when entering the overloaded-vehicle checkpoint, all axles of the vehicle are lowered to pass normally, and when driving on the main road, the variable axle of the vehicle is illegally lifted with the axle load exceeding 10 tons alarmingly. Therefore, this study developed a technology to detect the state of the variable axle of a truck driving on the road using roadside camera images. In particular, this technology formed the basis for cracking down on overloaded vehicles by lifting the variable axle after entering the checkpoint and linking the vehicle with the account information of the checkpoint. Fundamentally, in this study, the tires of the vehicle were recognized using the Mask RCNN algorithm, the recognized tires were virtually arranged before and after the checkpoint, and the height difference of the vehicle was measured from the arrangement to determine whether the variable axle was lifted after the vehicle left the checkpoint.

• Journal of Korean Elementary Science Education
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• v.41 no.3
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• pp.569-591
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• 2022

This study aims to investigate the educational effects of the visualization of heat conduction using a thermal imaging camera on elementary school students through small group activities. It endeavors to explain the reason for why metal feels cold. The scholars conducted in-depth interviews before and after learning the unit "Temperature and Heat" for four students in fifth grade in Seoul. Recorded video and audio materials of the activities, their outputs, and journals of scholars were collected, reviewed, and analyzed. The result demonstrated that visualizing heat conduction using the thermal imaging camera aroused curiosity and provided an opportunity for sophisticated observation and integrated thinking. In addition, the visualization of the heat conduction phenomenon was used as the basis for interpretation and rebuttal for active communication during the small group activities of the students. Consequently, the students changed their non-scientific beliefs, refined their knowledge, and developed their mental models through a small group discussion based on a thermal image video.

• Journal of Science Education
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• v.46 no.3
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• pp.312-325
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• 2022

This study aims to provide a science history content system necessary in the course design process of liberal arts subjects, along with the application of flip learning in liberal arts science classes for humanities and social sciences students. For the research, we analyzed the current state of the liberal arts and history of science classes at universities. Then we developed the 'Understanding the History of Science' subject by applying the flip learning method through the analysis of various previous studies. As the goal of science history lectures that can reach the essential purposes of science liberal arts education, including knowledge acquisition and strengthening various competencies, scientific attitude cultivation was set, and the content system of week 15 was designed to consider this. The four topics corresponding to the "History of Science" part of the "Understanding Science History" content system consisted of flipped learning classes and teaching and learning activities, including online video materials and group discussion activities. As a result of opening courses for students in the humanities and social sciences and operating classes for 56 college students, it was confirmed that students' interest and awareness of science increased. This study provides educational evidence for science history and liberal arts education.

• Journal of radiological science and technology
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• v.46 no.4
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• pp.315-323
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• 2023

Post-mortem computed tomography (PMCT) is commonly employed in the field of forensic pathology. PMCT was mainly performed using a whole-body scan with a wide field of view (FOV), which lead to a decrease in spatial resolution due to the increased pixel size. This study aims to evaluate the potential for developing a super-resolution model based on conditional generative adversarial networks (CGAN) to enhance the image quality of CT. 1761 low-resolution images were obtained using a whole-body scan with a wide FOV of the head phantom, and 341 high-resolution images were obtained using the appropriate FOV for the head phantom. Of the 150 paired images in the total dataset, which were divided into training set (96 paired images) and validation set (54 paired images). Data augmentation was perform to improve the effectiveness of training by implementing rotations and flips. To evaluate the performance of the proposed model, we used the Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM) and Deep Image Structure and Texture Similarity (DISTS). Obtained the PSNR, SSIM, and DISTS values of the entire image and the Medial orbital wall, the zygomatic arch, and the temporal bone, where fractures often occur during head trauma. The proposed method demonstrated improvements in values of PSNR by 13.14%, SSIM by 13.10% and DISTS by 45.45% when compared to low-resolution images. The image quality of the three areas where fractures commonly occur during head trauma has also improved compared to low-resolution images.

• Journal of Korean Elementary Science Education
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• v.42 no.1
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• pp.194-209
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• 2023

This study aims to present implications for the appropriate establishment and development of a science-authorized textbook system through an understanding of the process of selecting science-authorized textbooks and analyzing the perception of teachers. Toward this end, this study conducted interviews with five elementary school teachers who participated in the science textbook selection process, surveys on 32 teachers, and analysis on the authors of the textbooks. The result demonstrated, first, that the "opinion gathering" stage was the most important one, and a council was formed in consideration of career and major. Moreover, the evaluation standard was reorganized and used according to the situation of the school. Second, in the process of opinion gathering, the teachers used a method for reviewing the entire textbook for each teacher. Inquiry activities and textbook composition (readability) were crucially considered as internal factors, and teaching and learning materials, such as videos, were deemed extremely important as external factors. The variable of the author, which is an indicator of the reliability and expertise of textbooks, was also recognized as vital. Third, the deliberation by the School Committee and the report by the principal were recognized as the administrative final step after selection. Finally, selecting the most suitable textbooks for each grade group was recognized as more important than arbitrarily unifying textbooks for the third and fourth grades and for the fifth and sixth grades.

• Journal of the Korean Geotechnical Society
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• v.24 no.10
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• pp.57-70
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• 2008

The advantage of piezocone penetration test is a guarantee of continuous data, which is a source of reliable interpretation of target soil layer. Many researches have been carried out f3r several decades and several classification charts have been developed to classify in-situ soil from the cone penetration test result. Since most present classification charts or methods were developed based on the data which were compiled over the world except Korea, they should be verified to be feasible for Korean soil. Furthermore, sometimes their charts provide different soil classification results according to the different input parameters. However, unfortunately, revision of those charts is quite difficult or almost impossible. In this research a new soil classification model is proposed by using fuzzy C-mean clustering and neuro-fuzzy theory based on the 5371 CPT results and soil logging results compiled from 17 local sites around Korea. Proposed neuro-fuzzy soil classification model was verified by comparing the classification results f3r new data, which were not used during learning process of neuro-fuzzy model, with real soil log. Efficiency of proposed neuro-fuzzy model was compared with other soft computing classification models and Robertson method for new data.

• Geophysics and Geophysical Exploration
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• v.26 no.2
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• pp.37-51
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• 2023

The ground roll is the most common coherent noise in land seismic data and has an amplitude much larger than the reflection event we usually want to obtain. Therefore, ground roll suppression is a crucial step in seismic data processing. Several techniques, such as f-k filtering and curvelet transform, have been developed to suppress the ground roll. However, the existing methods still require improvements in suppression performance and efficiency. Various studies on the suppression of ground roll in seismic data have recently been conducted using deep learning methods developed for image processing. In this paper, we introduce three models (DnCNN (De-noiseCNN), pix2pix, and CycleGAN), based on convolutional neural network (CNN) or conditional generative adversarial network (cGAN), for ground roll suppression and explain them in detail through numerical examples. Common shot gathers from the same field were divided into training and test datasets to compare the algorithms. We trained the models using the training data and evaluated their performances using the test data. When training these models with field data, ground roll removed data are required; therefore, the ground roll is suppressed by f-k filtering and used as the ground-truth data. To evaluate the performance of the deep learning models and compare the training results, we utilized quantitative indicators such as the correlation coefficient and structural similarity index measure (SSIM) based on the similarity to the ground-truth data. The DnCNN model exhibited the best performance, and we confirmed that other models could also be applied to suppress the ground roll.

• The Journal of the Convergence on Culture Technology
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• v.9 no.3
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• pp.425-433
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• 2023

In this study, we developed a virtual artist play lesson model using gamification concepts and AI-generated art programs to foster creative thinking in freshman art majors. Targeting first-year students in the Digital Media Art Department at Sichuan Film & Television University in China, this course aims to alleviate fear of artistic creation and enhance problem-solving abilities. The educational model consists of four stages: persona creation, creative writing, text visualization, and virtual exhibitions. Through persona creation, students established their artist identities, and by introducing game-like elements into writing experiences, they discovered their latent creativity. Using AI-generated art programs for text visualization, students gained confidence in their creations, and in the virtual exhibitions, they were able to enhance their self-esteem as artists by appreciating and evaluating each other's works. This educational model offers a new approach to promoting creative thinking and problem-solving skills while increasing learner engagement and interest. Based on these research findings, we expect that by developing and implementing educational strategies that cultivate creative thinking, more students will grow their artistic capacities and creativity, benefiting not only art majors but also students from various fields.