• Journal of the Korea Society of Computer and Information
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• v.27 no.9
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• pp.191-203
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• 2022

In this paper, we developed a system that intelligently identifies skin image data from big data collected from social media Instagram and extracts standardized skin sample data for skin condition diagnosis and management. The system proposed in this paper consists of big data collection and analysis stage, skin image analysis stage, training data preparation stage, artificial neural network training stage, and skin image identification stage. In the big data collection and analysis stage, big data is collected from Instagram and image information for skin condition diagnosis and management is stored as an analysis result. In the skin image analysis stage, the evaluation and analysis results of the skin image are obtained using a traditional image processing technique. In the training data preparation stage, the training data were prepared by extracting the skin sample data from the skin image analysis result. And in the artificial neural network training stage, an artificial neural network AnnSampleSkin that intelligently predicts the skin image type using this training data was built up, and the model was completed through training. In the skin image identification step, skin samples are extracted from images collected from social media, and the image type prediction results of the trained artificial neural network AnnSampleSkin are integrated to intelligently identify the final skin image type. The skin image identification method proposed in this paper shows explain high skin image identification accuracy of about 92% or more, and can provide standardized skin sample image big data. The extracted skin sample set is expected to be used as standardized skin image data that is very efficient and useful for diagnosing and managing skin conditions.

• Korean Journal of Remote Sensing
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• v.38 no.5_2
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• pp.707-723
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• 2022

Although satellite-based sea surface temperature (SST) is advantageous for monitoring large areas, spatiotemporal data gaps frequently occur due to various environmental or mechanical causes. Thus, it is crucial to fill in the gaps to maximize its usability. In this study, daily SST composite fields with a resolution of 4 km were produced through a two-step machine learning approach using polar-orbiting and geostationary satellite SST data. The first step was SST reconstruction based on Data Interpolate Convolutional AutoEncoder (DINCAE) using multi-satellite-derived SST data. The second step improved the reconstructed SST targeting in situ measurements based on light gradient boosting machine (LGBM) to finally produce daily SST composite fields. The DINCAE model was validated using random masks for 50 days, whereas the LGBM model was evaluated using leave-one-year-out cross-validation (LOYOCV). The SST reconstruction accuracy was high, resulting in R² of 0.98, and a root-mean-square-error (RMSE) of 0.97℃. The accuracy increase by the second step was also high when compared to in situ measurements, resulting in an RMSE decrease of 0.21-0.29℃ and an MAE decrease of 0.17-0.24℃. The SST composite fields generated using all in situ data in this study were comparable with the existing data assimilated SST composite fields. In addition, the LGBM model in the second step greatly reduced the overfitting, which was reported as a limitation in the previous study that used random forest. The spatial distribution of the corrected SST was similar to those of existing high resolution SST composite fields, revealing that spatial details of oceanic phenomena such as fronts, eddies and SST gradients were well simulated. This research demonstrated the potential to produce high resolution seamless SST composite fields using multi-satellite data and artificial intelligence.

• Korean Journal of Plant Resources
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• v.35 no.5
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• pp.641-651
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• 2022

The biodiversity research of barley, a functional food, is proceeding to conserve germplasms and develop new cultivar of barley to improve its functional effects. In this study, with 25,104 barley germplasms in the National Agrobiodiversity Center, South Korea, the biodiversity index of species was much lower (1.17) than the origins (24.73) because of the presence of a biased species, Hordeum vulgare subsp. vulgare, but the species and origin of germplasms were significantly different with regard to genetic traits. In the clustering analysis based on genetic traits, we found that 97% barley germplasms could mostly be distributed between 1~7 clusters out of a total of 15 clusters; 'normal and uzu type', 'lodging', and 'loose smut' were commonly represented in the 1~7 clusters and some clusters showed specific differences in five genetic traits including 'growth habit'. In correlation of each genetic trait, the infection of 'barley yellow mosaic virus' was highly correlated to 'number of grains per spike'. '1000 grain weight' was weakly correlated with seven genetic traits including 'number of grains per spike'. Our analysis for barley's biodiversity can provide a useful guide to the species' phenotypes that need to be collected to conserve biodiversity and to breed new barley varieties.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.939-951
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• 2022

The most important factor in designing autonomous driving systems is to recognize the exact location of the vehicle within the surrounding environment. To date, various sensors and navigation systems have been used for autonomous driving systems; however, all have limitations. Therefore, the need for high-definition (HD) maps that provide high-precision infrastructure information for safe and convenient autonomous driving is increasing. HD maps are drawn using three-dimensional point cloud data acquired through a mobile mapping system (MMS). However, this process requires manual work due to the large numbers of points and drawing layers, increasing the cost and effort associated with HD mapping. The objective of this study was to improve the efficiency of HD mapping by segmenting semantic information in an MMS point cloud into six classes: roads, curbs, sidewalks, medians, lanes, and other elements. Segmentation was performed using various machine learning techniques including random forest (RF), support vector machine (SVM), k-nearest neighbor (KNN), and gradient-boosting machine (GBM), and 11 variables including geometry, color, intensity, and other road design features. MMS point cloud data for a 130-m section of a five-lane road near Minam Station in Busan, were used to evaluate the segmentation models; the average F1 scores of the models were 95.43% for RF, 92.1% for SVM, 91.05% for GBM, and 82.63% for KNN. The RF model showed the best segmentation performance, with F1 scores of 99.3%, 95.5%, 94.5%, 93.5%, and 90.1% for roads, sidewalks, curbs, medians, and lanes, respectively. The variable importance results of the RF model showed high mean decrease accuracy and mean decrease gini for XY dist. and Z dist. variables related to road design, respectively. Thus, variables related to road design contributed significantly to the segmentation of semantic information. The results of this study demonstrate the applicability of segmentation of MMS point cloud data based on machine learning, and will help to reduce the cost and effort associated with HD mapping.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.925-938
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• 2022

Agricultural reservoirs are an important water resource nationwide and vulnerable to abnormal climate effects such as drought caused by climate change. Therefore, it is required enhanced management for appropriate operation. Although water-level tracking is necessary through continuous monitoring, it is challenging to measure and observe on-site due to practical problems. This study presents an objective comparison between multiple AI models for water-body extraction using radar images that have the advantages of wide coverage, and frequent revisit time. The proposed methods in this study used Sentinel-1 Synthetic Aperture Radar (SAR) images, and unlike common methods of water extraction based on optical images, they are suitable for long-term monitoring because they are less affected by the weather conditions. We built four AI models such as Support Vector Machine (SVM), Random Forest (RF), Artificial Neural Network (ANN), and Automated Machine Learning (AutoML) using drone images, sentinel-1 SAR and DSM data. There are total of 22 reservoirs of less than 1 million tons for the study, including small and medium-sized reservoirs with an effective storage capacity of less than 300,000 tons. 45 images from 22 reservoirs were used for model training and verification, and the results show that the AutoML model was 0.01 to 0.03 better in the water Intersection over Union (IoU) than the other three models, with Accuracy=0.92 and mIoU=0.81 in a test. As the result, AutoML performed as well as the classical machine learning methods and it is expected that the applicability of the water-body extraction technique by AutoML to monitor reservoirs automatically.

• Journal of Christian Education in Korea
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• v.66
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• pp.179-208
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• 2021

Due to COVID-19, the entire world is facing the unprecedented phenomenon. Amid the threat of the virus, the global community is struggling for life. In such circumstances, churches in Korea have been criticised as selfish groups threatening the community by spreading the virus. With such criticism, they are disregarded by Korean society because their immorality and exclusive attitude towards other religions and cultures were also mentioned in public. There are many reasons for Korean churches to lose trust from people. One of the reasons for that is the quantitative growth of church and expansion of the power of church, which is a direction that has been practised so far as a missionary goal. The zeal for spreading gospel has undermined the trust of church and become a deteriorating factor for mission, which is irony. In such problematic situations, the change of paradigm is required for new mission. The passion for evangelisation should not only focus on the quantitative growth of church; it should change its direction for serving the world in lieu with the plan of God for the activity of redemption on this land. A hint of such mission can be found in ecumenical mission. Ecumenical mission is a new paradigm which was discussed in ecumenical movement led mainly by WCC, and its aim is to participate in activities of redemption of God for life in this world. Christian education has been a tool for the expansion of Christian power in the context of traditional mission. Reflecting on the role of Christian education as such, the change of direction as practical movement for the kingdom of God was tried in ecumenical movement: the beginning of the discussion of Christian education based on ecumenical mission. Due to exclusivity, aggressive mission, and the excessive attention to the system of ecclesiastical authority rather than life, Korean churches, which have lost trust in this society, should recover themselves as the model of the kingdom of God, and the establishment of mission education based on ecumenical mission is required for them to become a community towards life. Furthermore, this is an urgent task for Korean churches to implement such mission education in a church community.

• Journal of Christian Education in Korea
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• v.66
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• pp.243-272
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• 2021

Corona 19 brought about a major shift in the Korean church's pastoral style. Contact and non-contact ministry styles using the Internet and media devices are being held together. The elderly, who have been classified as digital vulnerable, need to see whether they are properly adapting to these changes and they have any difficulties in their religious lives. This study is to organize the current status of Corona 19 related to Korean churches, look at the current state of church programs for Christian elderly people, look at how important the religious life is to their lives, and to suggest educational pastoral methods for their religious lives based on the theory of Maria Harris' educational ministry. First, in terms of Koinonia, it was suggested that the heritage, beliefs, values and ways of life held by the Christian elderly be shared with people inside and outside the church in order to entertain and embrace everyone without alienation. Second, from the perspective of Leiturgia, educational ministry was proposed to expand prayer life from a personal area to a public area to become a life of practicing prayer and justice by providing public prayer content with media that can be used by the elderly to perform spirituality. Third, it was suggested that in terms of Didache, it should be required that the elderly should be educated to be familiar with the changing technologies, that teaching environment should be extended from church to online, and that the educational content of tradition and new forms should be dealt with extensively. Fourth, from the perspective of Kerigma, Christian elderly people who have suffered in various life environments, both personally and socially, should listen to the words again and gain the power to overcome the corona crisis through the God's words, so that they can be melted into the curriculum of koinonia, leiturgia, didache, and diakonia. Fifth, it was suggested that senior citizens should switch their consciousness to become subjects of service, not objects of service, and that digital literacy education should be provided individually at eye level to narrow the digital gap for Diakonia curriculum.

• Journal of the Korean Institute of Traditional Landscape Architecture
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• v.39 no.1
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• pp.1-9
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• 2021

The purpose of this study is to analyze Zhangjingxiu(張敬修 1823~1864), who made Keyuan(可園) in Lingnan, China, to find out how traditional gardens were created. This study focused on the analysis of the relationship between garden designer and space creation. To this purpose, the analysis was divided into garden designer life analysis, garden making background analysis, garden analysis as a space for interaction with local artists, garden analysis as art activity space for garden designer, and garden designer's unique garden creation. the results are as follow. Zhangjingxiu was born in Dongwan City in 1823, participated in the civil war at the age of 22(1845), returned home at the age of 26(1849) and made Keyuan. However, he again went through the Opium War(1856), and at the age of 38(1861) he returned home with a war-illness. A garden designer Zhangjingxiu died at the age of 41(1864). Since Zhangjingxiu was a soldier, he healed the wounds caused by the war and created a garden in order to realize the ideal world that Zhangjingxiu normally had. The garden making background can be found in the garden's name Keyuan(可園). Zhangjingxiu tried to express in the garden the meaning of 'there is nothing possible and nothing impossible in the world' learned through the war. Therefore, Zhangjingxiu named the garden housing and the lake as Gadang(可堂), Gaheon(可軒), Gajeong(可亭), Galu(可樓), and Gaho(可湖). In addition, he returned from the war and making a garden with love and filial piety for his mother. Zhangjingxiu left many poetry and oriental paintings in Keyuan with local artists. The places created as a base as a space to interact with local artists in the garden are 'Gaheon(可軒) and Galu(可樓)', and 'Chuwoljigwan(雛月池館) and Gajeong(可亭)'. In particular, Jasudae(滋樹臺), which can produce various miniascapes of orchids, is considered to be the core space of Zhangjingxiu's artistic space. Zhangjingxiu is considered to have become a famous garden by creating a very characteristic garden using Jasudae, Sokgasan(石假山) and Baewoldae(拜月臺) on the court in front of Gadang.

• Korean Journal of Poultry Science
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• v.48 no.2
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• pp.91-100
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• 2021

The study determined the effects of stock density (SD) and energy level (EL) on growth performance, serum biochemistry, and meat quality in Korean native chickens. A total of 240 chickens were randomly assigned to one of the four treatments including two stock density (low, 14, and high, 16 chickens per m²) and two energy level (low, 2,950, 3,000, 3050 ME kcal/kg, and high 3,150, 3,200, 3,250 ME kcal/kg, for starter, grower, and finisher, respectively). During the whole period of the experiment, the chickens were fed ad libitum. The greater final body weight and weight gain were achieved in chickens fed high energy diet, whereas the final body weight and weight gain were significantly reduced in high-density treatment compared with the low density. Chickens in low-density groups had a higher feed intake compared with high-density treatment, however, the energy level did not affect the feed intake. An improved overall feed conversion ratio was detected in the high energy treatment. There was a significant interaction between stock density and energy level on cholesterol concentration. The concentration of aspartate transaminase in serum was increased by higher stock density. There was a significant treatment interaction on IgM levels. Moreover, the carcass rate was significantly increased in the high energy level treatment. Based on the findings, we suggest that rearing chickens in low density with high dietary energy levels could be beneficial by improving the growth performance.

• The Journal of Korean Academy of Prosthodontics
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• v.59 no.3
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• pp.305-313
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• 2021

Purpose. The purpose of this pilot study is to evaluate the reliability and validity of the Korean version of the oral health impact profile (OHIP-EDENT K) for edentulous patients. Materials and methods. The study was conducted on 12 patients who fabricated overdenture in the Department of Prosthodontics, Korea University, Guro Hospital. All subjects completed the Korean version of Oral Health Impact Profile (OHIP K) questionnaire. Shorten version of the OHIP called OHIP-14 K and OHIP-EDENT K were derived from the datasets. Cronbach's alpha was used to measure internal consistency of the summary scores for OHIP-EDENT K. The Spearman's correlation coefficient between the summary scores for OHIP-EDENT K and OHIP K was calculated to evaluate concurrent validity. Results. The reliability of the summary scores for OHIP-EDENT K was acceptable (α=.736). The Spearman's correlation coefficient of the summary scores for OHIP-EDENT K and OHIP K was 0.966, which was statistically significant (P<.001). OHIP-EDENT K exhibited less susceptibility to floor effects than OHIP-14 K and appeared to measure change as effectively as OHIP K. In order to prove the reliability, responsiveness and validity of OHIP-EDENT K, further studies with more samples are needed. Conclusion. The OHIP-EDENT K, a questionnaire on oral health-related QOL comprising 19 items, has measurement properties comparable with the full 49-item version. This modified shortened version can be an alternative questionnaire to full version of OHIP K and OHIP-14 K in edentulous patients.