• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.25-34
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• 2020

In this paper, we empirically compare the effectiveness of training models to recognize beauty-related skin disease using supervised deep learning algorithms. Recently, deep learning algorithms are being actively applied for various fields such as industry, education, and medical. For instance, in the medical field, the ability to diagnose cutaneous cancer using deep learning based artificial intelligence has improved to the experts level. However, there are still insufficient cases applied to disease related to skin beauty. This study experimentally compares the effectiveness of identifying beauty-related skin disease by applying deep learning algorithms, considering CNN, ResNet, and SE-ResNet. The experimental results using these training models show that the accuracy of CNN is 71.5% on average, ResNet is 90.6% on average, and SE-ResNet is 95.3% on average. In particular, the SE-ResNet-50 model, which is a SE-ResNet algorithm with 50 hierarchical structures, showed the most effective result for identifying beauty-related skin diseases with an average accuracy of 96.2%. The purpose of this paper is to study effective training and methods of deep learning algorithms in consideration of the identification for beauty-related skin disease. Thus, it will be able to contribute to the development of services used to treat and easy the skin disease.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.3
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• pp.59-70
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• 2021

With the recent advancements in the Internet of Things, context-aware system that provides customized services become important to consider. The existing context-aware systems analyze data generated around the user and abstract the context information that expresses the state of situations. However, these datasets is mostly unstructured and have difficulty in processing with simple approaches. Therefore, providing context-aware services using the datasets should be managed in simplified method. One of examples that should be considered as the unstructured datasets is a deep learning application. Processes in deep learning applications have a strong coupling in a way of abstracting dataset from the acquisition to analysis phases, it has less flexible when the target analysis model or applications are modified in functional scalability. Therefore, an abstraction model that separates the phases and process the unstructured dataset for analysis is proposed. The proposed abstraction utilizes a description name Analysis Model Description Language(AMDL) to deploy the analysis phases by each fat client is a specifically designed instance for resource-oriented tasks in edge computing environments how to handle different analysis applications and its factors using the AMDL and Fat client profiles. The experiment shows functional scalability through examples of AMDL and Fat client profiles targeting a vehicle image recognition model for vehicle access control notification service, and conducts process-by-process monitoring for collection-preprocessing-analysis of unstructured data.

• Journal of the Daesoon Academy of Sciences
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• v.36
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• pp.201-225
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• 2020

In the late Joseon Dynasty, ideas in folk religions were closely related to Daoist themes. There were, for instance, folk ideas centered on Prophecies of Jeong Gam (鄭鑑錄 jeonggamrok) that developed into 'raising island-armies (海島起兵說 hado gibyeongseol),' the future utopian movement known as the 'South Joseon Faith (南朝鮮信仰 namjoseon sinang),' and faith around 'Maitreya's Descensionist-Birth (彌勒下生 mireuk hasaeng).' People aimed to transform their country based on these ideas. Associated folklore tended to come from fengshui (風水) and books on prophecies and divination (圖讖 docham), and both of these drew heavily upon Daoist concepts. On the other hand, Daoist texts began being translated as national projects under King Cheoljong (哲宗), and many more were translated and published later under King Gojong (高宗). The nature of these Daoist texts mostly consisted of either morality books (善書 seonseo) or precious scrolls (寶卷 bogeon). The problem was that these ordinances and the Daoist texts of regents were among the main causes of civil war during the Qing Dynasty. In this regard, the translation of the Daoist texts conducted as a national project provided a theoretical basis for the people wishing to foment civil war or transformation. This raises the question of why King Gojong implemented a Daoist translation project in his nation. In an effort to answer this question, this article summarizes the popular ideas of the late Joseon Dynasty and explains how they were closely related to Daoism. In addition, this article summarizes the facts about how Daoism has emerged from a national crisis but developed a function of protecting the state (鎭護) in Korean history. Further described is the situation under which Daoism was summoned during the Japanese Invasion of Joseon (壬辰倭亂). Analysis is provided to show that King Gojong's intention was to translate Daoism due to Daoism's role in protecting the state. In addition, the relationship between current Daoist rites and customs in Korea and King Gojong's dissemination of Daoist oaths and vouchers is confirmed.

• Journal of the Daesoon Academy of Sciences
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• v.40
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• pp.115-153
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• 2022

Korea has rapidly become an aging society, and this phenomenon is found not only in common population but also in many religious circles. In this context, interest in the welfare of retired clergy members is increasing, and some religious organizations are trying to devise and perform rules and/or policies that ensure a secure post-retirement life for their clergy. However, the welfare benefits differ from one religion to another according to the characteristics of the given religion's organizational structure. For instance, denominations with a centralized hierarchy such as Catholicism or Won Buddhism implement a relatively stable welfare system for their elderly clergy members whereas autonomous denominations like many Buddhist or Christian orders are often found to have somewhat insecure welfare systems. Clergy welfare in Daesoon Jinrihoe, one of the representative new religions in Korea, is emerging as an important issue as Daesoon Jinrihoe is also affected by the problems of Korea's aging society. However, since the order has a mixed system of a centralized hierarchy and autonomous local branches, the welfare for their elderly clergy lacks clear lines of accountability. Consequently, there have been talks to devise a proper welfare system; however, these talks have come to a standstill. In this regard, this study aims to look into and analyze how various structures and welfare systems within Korean religious organizations impact elderly clergy. Lastly, this research will provide suggestions on practical alternatives for Daesoon Jinrihoe which could resolve the problems within their welfare system that negatively impact elderly clergy members at present.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.3
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• pp.227-237
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• 2022

The most critical factors for detecting changes in very high-resolution satellite images are building positional inconsistencies and relief displacements caused by satellite side-view. To resolve the above problems, additional processing using a digital elevation model and deep learning approach have been proposed. Unfortunately, these approaches are not sufficiently effective in solving these problems. This study proposed a change detection method that considers both positional and topology information of buildings. Mask R-CNN (Region-based Convolutional Neural Network) was trained on a SpaceNet building detection v2 dataset, and the central points of each building were extracted as building nodes. Then, triangulated irregular network graphs were created on building nodes from temporal images. To extract the area, where there is a structural difference between two graphs, a change index reflecting the similarity of the graphs and differences in the location of building nodes was proposed. Finally, newly changed or deleted buildings were detected by comparing the two graphs. Three pairs of test sites were selected to evaluate the proposed method's effectiveness, and the results showed that changed buildings were detected in the case of side-view satellite images with building positional inconsistencies.

• The Korean Society of Law and Medicine
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• v.22 no.2
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• pp.3-48
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• 2021

Among the major rulings handed down in 2020, there were cases involving anaphylaxis, which is timely as a side effect of coronavirus and flu vaccine. And as a rare case, a ruling was handed down that if medical treatment was done so unfaithfully beyond the limit of patience of ordinary people, it can be an independent illegal act and a cause of compensation for emotional distress. Also, there was a ruling in the appellate court that evaluated disability rate applying the Korean Academy of Medical Sciences Guides for the Evaluation of Permanent Impairment, not McBride system. And the supreme court made it clear that telemedicine is illegitimate. In relation to duty of explanation, it is in the process of adding detail criterion on the firm principles in the individual cases. In regard of medical records, there was a case that even when a medical record is strongly suspected to be tampered with, it is not considered to be an obstruction of proof. There were cases that resulted in different conclusion between the court of first instance and the appellate court rulings. Lastly, in the face of a growing number of cases in which doctors are sentenced to prison for malpractice, we reviewed a ruling that sentenced a doctor to prison.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.2
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• pp.91-108
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• 2022

In most cases, optical images have been used as training data of DL (Deep Learning) models for object detection, recognition, identification, classification, semantic segmentation, and instance segmentation. However, properties of 3D objects in the real-world could not be fully explored with 2D images. One of the major sources of the 3D geospatial information is DSM (Digital Surface Model). In this matter, characteristic information derived from DSM would be effective to analyze 3D terrain features. Especially, man-made objects such as buildings having geometrically unique shape could be described by geometric elements that are obtained from 3D geospatial data. The background and motivation of this paper were drawn from concept of the intrinsic image that is involved in high-level visual information processing. This paper aims to extract buildings after classifying terrain features by training DL model with DSM-derived information including slope, aspect, and SRI (Shaded Relief Image). The experiments were carried out using DSM and label dataset provided by ISPRS (International Society for Photogrammetry and Remote Sensing) for CNN-based SegNet model. In particular, experiments focus on combining multi-source information to improve training performance and synergistic effect of the DL model. The results demonstrate that buildings were effectively classified and extracted by the proposed approach.

• Journal of Mushroom
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• v.20 no.3
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• pp.127-137
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• 2022

Effects of substrate bed interior environments on mushroom qualities were investigated in oyster mushroom cultivation facilities in which either Reversible Air-Circulation Fans (RACF) blowing air in two directions (upwards and downwards) or customary Convection Fans (CF) with air blowing only upwards were operated throughout the cultivation period. Two days before harvest, the deviation ranges of the bed interior temperature and relative humidity in the facility using RACF were in the ranges of 1.0-1.3℃ and 7.8-9.0% in the first growing cycle, and within 0.7-1.1℃ and 10.0-11.4% in the second cycle. In the facility using CF, the ranges of variation in the indoor environment parameters (5.8-6.4℃ and 21.3-23.1% in the first growing cycle, and 3.4-5.7℃ and 14.6-18.3% in the second growing cycle) were much enlarged compared to those associated with RACF. These results strongly indicate that RACF significantly enhances air uniformity. Some mushroom qualities differed between growing cycles. For instance RACF in the first cycle gave somewhat better qualities than CF, but some qualities, like pileus diameter and stipe length, were slightly lower than those described for CF in the second cycle when the cultivation substrate weakened. The observation that some qualities worsened under RACF conditions, despite better air uniformity during the growing cycle, revealed the possibility that downward wind may exert a non-negligible negative effect on mushroom growth. Therefore in the future, making wind measurements on the interior and exterior of substrate beds is necessary to obtain insights into their influences on mushroom qualities. The RACF operation manual needs to be edited to convey this necessity.

• The Korean Journal of Food And Nutrition
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• v.35 no.6
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• pp.491-498
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• 2022

This study compared the antioxidant and mineral properties of the leaves and seeds of fifteen Korean adzuki bean (Vigna angularisL.) breeding lines. This study was conducted in an attempt to expand the use of Korean adzuki bean leaves. The potassium, calcium, magnesium, and sodium contents of the leaves were significantly higher than the seeds, in particularly, the potassium content. The leaves had approximately 3.3 times higher potassium content than the seeds. For instance, the potassium content of YA1317 leaves was 21% higher than that of Arari. The total polyphenol content and ABTS activity of Adzuki bean leaves were significantly higher than the seeds, as opposed to the total flavonoid content and DPPH scavenging activity. Among the 15 breeding lines, YA1402 had 1.2~3.2 times higher antioxidant content and activity as compared to the Arari variety. It was concluded that adzuki bean leaves had higher mineral content, antioxidant component and activity as compared to the seeds. Therefore, adzuki bean leaves could be used an ingredient for dishes and as a medicine.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.2
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• pp.77-82
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• 2023

The Ministry of Agriculture, Food and Rural Affairs established the FarmMap, an digital map of agricultural land. In this study, using deep learning, we suggest the application of farm map reading to farmland such as paddy fields, fields, ginseng, fruit trees, facilities, and uncultivated land. The farm map is used as spatial information for planting status and drone operation by digitizing agricultural land in the real world using aerial and satellite images. A reading manual has been prepared and updated every year by demarcating the boundaries of agricultural land and reading the attributes. Human reading of agricultural land differs depending on reading ability and experience, and reading errors are difficult to verify in reality because of budget limitations. The farmmap has location information and class information of the corresponding object in the image of 5 types of farmland properties, so the suitable AI technique was tested with ResNet50, an instance segmentation model. The results of attribute reading of agricultural land using deep learning and attribute reading by humans were compared. If technology is developed by focusing on attribute reading that shows different results in the future, it is expected that it will play a big role in reducing attribute errors and improving the accuracy of digital map of agricultural land.