• Journal of Physiology & Pathology in Korean Medicine
• /
• v.35 no.1
• /
• pp.22-27
• /
• 2021

This study conducted a questionnaire for students of Pusan National University Graduate School of Korean Medicine who practiced using the Oriental Medicine Diagnosis System (ODS). From the questionnaire, this study investigated current state of application and perception of AI in Korean Medicine and explored the direction of ODS improvement and utilization. The survey questions consisted of six questions examining the satisfaction of the diagnostic expert system, five questions evaluating the availability of the diagnostic expert system, and six questions to predict the impact of AI on the Korean medicine community. The survey analysis showed high satisfaction with practice using ODS. On the other hand, the possibility of using ODS, especially in clinical use, was evaluated as relatively low compared to the satisfaction of the practice. Therefore, the overall impact of AI on the Korean medical community is not expected to be large. Although there are difficulties in standardization of clinical data due to the academic characteristics of Korean medicine, it is necessary to continue attempts to apply AI. By actively introducing educational tools using the latest AI techniques to the diagnosis experience and doctor-patient role in a practice, students will be able to increase their satisfaction with their practice and respond appropriately to the state-of-the-art medical environment.

• The Research Journal of the Costume Culture
• /
• v.29 no.6
• /
• pp.779-794
• /
• 2021

In this study, the sales status of female ball-jointed dolls and their parts were investi- gated and analyzed. Baseline data from 194 products and 54 brands on domestic and international Internet sites was gathered for the manufacture of ball-jointed dolls and the development of prototype costumes for them. The results are as follows. First, the sizes used for ball-jointed dolls are SD, USD, MSD, 13SD, and 70SD together with height. This study analyzed 39 sizes (15~70cm) by classifying them into numbered groups: 1 (15~22cm), 2 (23~33cm), 3 (35~51cm), 4 (53~62cm), and 5 (63~70cm). The price varied depending on the size; for example, 50cm dolls were approximately 45,000 won, while limited editions were sold at high prices, regardless of their size. They were classified into designs according to their body proportions and facial features as follows: 7- or 8-head-figure, 5-head figure, and 3-head figure, and were presented proportionally as images of women, adolescents, and infants. Second, the head was incised so that the top could be removed horizontally or the facial region vertically, allowing attachment of the eyeballs (which were either glass, resin, or acrylic) to the inside. More than 30 different colors were sold. Various wig styles were provided, including cut, short hair, and perm. These were made from human hair, heat-resistant fiber, and artificial hair. For the hands, there was a design expressing human hand gestures. For the feet, heels were in the form of wearing either high-heels or flat soles.

• The Journal of the Korea institute of electronic communication sciences
• /
• v.17 no.1
• /
• pp.111-118
• /
• 2022

In computer vision research, the two-dimensional human pose is a very extensive research direction, especially in pose tracking and behavior recognition, which has very important research significance. The acquisition of human pose targets, which is essentially the study of how to accurately identify human targets from pictures, is of great research significance and has been a hot research topic of great interest in recent years. Human pose recognition is used in artificial intelligence on the one hand and in daily life on the other. The excellent effect of pose recognition is mainly determined by the success rate and the accuracy of the recognition process, so it reflects the importance of human pose recognition in terms of recognition rate. In this human body gesture recognition, the human body is divided into 17 key points for labeling. Not only that but also the key points are segmented to ensure the accuracy of the labeling information. In the recognition design, use the comprehensive data set MS COCO for deep learning to design a neural network model to train a large number of samples, from simple step-by-step to efficient training, so that a good accuracy rate can be obtained.

• Journal of Biomedical Engineering Research
• /
• v.43 no.1
• /
• pp.45-51
• /
• 2022

The purpose of this study is to improve the classification accuracy compared to the existing InceptionV3 model by proposing a new model modified with the fully connected hierarchical structure of InceptionV3, which showed excellent performance in medical image classification. The data used for model training were trained after data augmentation on a total of 1026 chest X-ray images of patients diagnosed with normal heart and Cardiomegaly at Kyungpook National University Hospital. As a result of the experiment, the learning classification accuracy and loss of the InceptionV3 model were 99.57% and 1.42, and the accuracy and loss of the proposed model were 99.81% and 0.92. As a result of the classification performance evaluation for precision, recall, and F1 score of Inception V3, the precision of the normal heart was 78%, the recall rate was 100%, and the F1 score was 88. The classification accuracy for Cardiomegaly was 100%, the recall rate was 78%, and the F1 score was 88. On the other hand, in the case of the proposed model, the accuracy for a normal heart was 100%, the recall rate was 92%, and the F1 score was 96. The classification accuracy for Cardiomegaly was 95%, the recall rate was 100%, and the F1 score was 97. If the chest X-ray image for normal heart and Cardiomegaly can be classified using the model proposed based on the study results, better classification will be possible and the reliability of classification performance will gradually increase.

• Journal of The Korean Association of Information Education
• /
• v.26 no.3
• /
• pp.153-165
• /
• 2022

This study is about the Novel Engineering(NE) education program : a class model that combines reading and engineering. By including the process of directly designing and programming a virtual reality using CospacesEdu (a VR authoring tool for the NE class), the effects of the educational program on learners' STEAM literacy and Learning immersion are demonstrated. Moreover, the subject of this education is Dokdo in South Korea. As a result, the average of STEAM literacy is increased, and a significant change is confirmed statistically in Convergence. Learning immersion shows significant improvement in Challenges-skills balance. On the other hand, some students experience difficulties due to the long research stages, from reading a book to researching for information to designing VR and rewriting a story with the collected information. In conclusion, this study will help generalise other education using NE, and this developed program will be a reference that would suggest a new way of teaching.

• Journal of Ecology and Environment
• /
• v.46 no.3
• /
• pp.161-171
• /
• 2022

Background: Epilobium hirsutum L. is designated as an endangered plant in South Korea located in Asia, due to the destruction of its habitats through the development of wetlands. Therefore, in this study, in order to find a light condition suitable for the growth and ecophysiological responses of Epilobium hirsutum L., those of this plant under treatment with various light qualities in a smart farm were measured. Results: In order to examine the changes in the physiological and growth responses of Epilobium hirsutum L. according to the light qualities, the treatment with light qualities of the smart farm was carried out using the red light: blue light irradiation time ratios of 1:1, 1:1/2, and 1:1/5 and a red light: blue light: white light irradiation time ratio of 1:1:1. As a result, the ecophysiological responses (difference between leaf temperature and atmospheric temperature, transpiration rate, net photosynthetic rate, intercellular CO₂ partial pressure, photosynthetic quantum efficiency) to light qualities appeared differently according to the treatments with light qualities. The increase in the blue light ratio increased the difference between the leaf temperature and the atmospheric temperature and the photosynthetic quantum efficiency and decreased the transpiration rate and the intercellular CO₂ partial pressure. On the other hand, the white light treatment increased the transpiration rate and intercellular CO₂ partial pressure and decreased the temperature difference between the leaf temperature and the ambient temperature and photosynthetic quantum efficiency. Conclusions: The light condition suitable for the propagation by the stolons, which are the propagules of Epilobium hirsutum L., in the smart farm, is red, blue and white mixed light with high net photosynthetic rates and low difference between leaf temperature and atmospheric temperature.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
• /
• v.39 no.6
• /
• pp.419-427
• /
• 2021

Due to the effects of climate change and the reduction of the labor force due to COVID-19, the crop yield, harvest time, and cultivated area are rapidly changing every year. In order to respond flexibly to this situation, attempts to apply smart farm technology based on ICT (Information and Communication Technology) to individual farms are increasing. On the other hand, various stakeholders are trying to predict the yield of crops using artificial intelligence and IoT technology, but accurate prediction is difficult due to the lack of learning data. In this study, in order to overcome the data collection problem limited to a specific institution, a smart farmer service technology based on community mapping was developed in which farmers directly participate, input and share accurate data to predict production. In the process, analysis was performed on napa cabbage, which is a vegetable with a large price change compared to production.

• KIPS Transactions on Software and Data Engineering
• /
• v.12 no.6
• /
• pp.251-258
• /
• 2023

It is necessary to predict peak load accurately in order to supply electric power and operate the power system stably. Especially, it is more important to predict peak load accurately in winter and summer because peak load is higher than other seasons. If peak load is predicted to be higher than actual peak load, the start-up costs of power plants would increase. It causes economic loss to the company. On the other hand, if the peak load is predicted to be lower than the actual peak load, blackout may occur due to a lack of power plants capable of generating electricity. Economic losses and blackouts can be prevented by minimizing the prediction error of the peak load. In this paper, the latest deep learning model such as TCN is used to minimize the prediction error of peak load. Even if the same deep learning model is used, there is a difference in performance depending on the hyper-parameters. So, I propose methods for optimizing hyper-parameters of TCN for predicting the peak load. Data from 2006 to 2021 were input into the model and trained, and prediction error was tested using data in 2022. It was confirmed that the performance of the deep learning model optimized by the methods proposed in this study is superior to other deep learning models.

• The Journal of the Convergence on Culture Technology
• /
• v.9 no.3
• /
• pp.183-192
• /
• 2023

Digital transformation is taking place rapidly around the world. As the development of digital technology becomes very fast, more information is expected to be digitized. Therefore, the possibility of cyber threats is increasing in transmitting and storing sensitive information such as personal and financial information online. In this paper, we compared and analyzed information security textbooks for elementary and secondary school students in China, where the recent development of artificial intelligence and digital transformation are rapidly occurring. After we collected related textbooks, textbooks suitable for analysis were selected. Then, we analyzed the external and internal systems of the textbooks separately. As a result of the external system analysis, all the textbook covers were properly produced, but the quality difference was significant among textbooks. In the case of textbooks for elementary school students, the excellence of layout and content placement was noticed. On the other hand, due to the internal system analysis, various contents were not included evenly when looking at the learning contents based on the "information society responsibility" learning goals presented in China. Through this paper, we hope to provide implications for information security-related education and textbook development research.

• The Plant Pathology Journal
• /
• v.39 no.4
• /
• pp.351-360
• /
• 2023

Citrus melanose, caused by Diaporthe citri, has been one of the serious diseases, and chemical fungicides were used for protection in many citrus orchards of Jeju Island. Establishing a disinfectant resistance management system and reducing pesticide usage would be important for contributing to safe agricultural production. In this study, monitoring of chemical resistance was performed with 40 representative D. citri isolates from many citrus orchards in Jeju Island. Four different fungicides, kresoxim-methyl, benomyl, fluazinam, and prochloraz manganese, with seven different concentrations were tested in vitro by growing the mycelium of the fungal isolates on the artificial medium potato dextrose agar. Among the 40 fungal isolates, 12 isolates were investigated as resistant to kresoxim-methyl which could not inhibit the mycelium growth to more than 50%. Especially isolate NEL21-2 was also resistant against benomyl, whose hyphae grew well even on the highest chemical concentration. However, any chemical resistance of fungal isolates was found against neither fluazinam nor prochloraz manganese. On the other hand, in vivo bio-testing of some resistant isolates was performed against both kresoxim-methyl and benomyl on young citrus leaves. Typical melanose symptoms developed on the citrus leaves pre-treated with both agrochemicals after inoculation with the resistant isolates. However, no or less symptoms were observed when the susceptible isolates were inoculated. Based on these results, it was suggested that some resistant isolates of D. citri occurred against both systemic fungicides, which may be valuable to build a strategy for protecting citrus disease.