• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.953-966
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• 2022

Since aerosols adversely affect human health, such as deteriorating air quality, quantitative observation of the distribution and characteristics of aerosols is essential. Recently, satellite-based Aerosol Optical Depth (AOD) data is used in various studies as periodic and quantitative information acquisition means on the global scale, but optical sensor-based satellite AOD images are missing in some areas with cloud conditions. In this study, we produced gap-free GeoKompsat 2A (GK-2A) Advanced Meteorological Imager (AMI) AOD hourly images after generating a Random Forest based gap-filling model using grid meteorological and geographic elements as input variables. The accuracy of the model is Mean Bias Error (MBE) of -0.002 and Root Mean Square Error (RMSE) of 0.145, which is higher than the target accuracy of the original data and considering that the target object is an atmospheric variable with Correlation Coefficient (CC) of 0.714, it is a model with sufficient explanatory power. The high temporal resolution of geostationary satellites is suitable for diurnal variation observation and is an important model for other research such as input for atmospheric correction, estimation of ground PM, analysis of small fires or pollutants.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.31 no.6
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• pp.1215-1225
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• 2021

Although Artificial Intelligence (AI) techniques have shown impressive performance in various fields, they are vulnerable to adversarial examples which induce misclassification by adding human-imperceptible perturbations to the input. Previous studies to defend the adversarial examples can be classified into three categories: (1) model retraining methods; (2) input transformation methods; and (3) adversarial examples detection methods. However, even though the defense methods against adversarial examples have constantly been proposed, there is no research to classify the type of adversarial attack. In this paper, we proposed an adversarial attack family classification method based on dimensionality reduction and clustering. Specifically, after extracting adversarial perturbation from adversarial example, we performed Linear Discriminant Analysis (LDA) to reduce the dimensionality of adversarial perturbation and performed K-means algorithm to classify the type of adversarial attack family. From the experimental results using MNIST dataset and CIFAR-10 dataset, we show that the proposed method can efficiently classify five tyeps of adversarial attack(FGSM, BIM, PGD, DeepFool, C&W). We also show that the proposed method provides good classification performance even in a situation where the legitimate input to the adversarial example is unknown.

• Journal of the Korea Society of Computer and Information
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• v.28 no.2
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• pp.235-246
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• 2023

In this paper, we propose suggestions for developing a Metaverse platform for educational purpose utilizing a Delphi study method with experts on Metaverse and digital education. 17 experts participated in the 1st study and 16 took part in the 2nd study, and data was collected via emails from January 5th to 10th for the 1st study and from January 12th to 17th for the 2nd study in 2022. Collected data in the 1st study was analyzed by applying content analysis. The results for the 1st study indicated that there were 120 sub-factors were derived from 7 main questions(the necessity of a Metaverse platform for future education, how to use the Metaverse platform for education to improve the capacities needed for future human resources, problems that may arise during education using the Metaverse platform, the functions that the Metaverse platform for education should have, the infrastructure and environment required when using the Metaverse platform for education, how to use the Metaverse effectively as a learning space, subjects and educational contents that will be effective if conducted on the Metaverse platform for education). The results for the 2nd study were presented by being ranked with calculated means of sub-factors for each question. Finally, based on the results, suggestions for building a Metaverse platform for educational purpose are stated and limitations of the study and possible future study are discussed.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.4
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• pp.5-25
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• 2022

The purpose of this study is to analyze the duties and competencies of the teacher librarian required by schools as consumers to operate the curriculum, and to suggest ways to improve their professionality. To this end, the duties and competencies included in 20 job advertisements posted by IB schools to select teacher librarians were analyzed based on the IFLA School Library Guidelines. As a result of the analysis, it was found that the duties and competencies of IB schools are based on the IB curriculum guidelines and this guideline is based on the educational philosophy and learner image that IBO curriculum aims. And the job that schools want the most from the teacher librarian is teaching through library collection management and collaboration, and the main competencies for this are communication and collaboration skills, teaching-learning·curriculum·education design and operation, and digital & media literacy. The results of this analysis show that the professionalism should be based on the vision for the educated person and learner capabilities presented in the curriculum. Based on this results, in this study the ways for developing teacher librarians' professionalism were presented in the following aspects. First, including the educational responsibilities of the school library in the Arrangement and Implementation Guideline of National Level Curriculum. Second, Classifying human resources' duties through revision of the Enforcement Decree of the School Library Promotion Act. Third, reorganizing of basic courses to acquire teacher librarian qualifications and introducing a demonstration of collaborative teaching in the eduactional practice and the certification examination.

• Journal of the Korean Applied Science and Technology
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• v.38 no.6
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• pp.1466-1475
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• 2021

Compound K (20-O-β-(_D-glucopyranosyl)-20(S)-protopanaxadiol) is an active ingredient of ginsenosides. Compound K has been known to produce from biotransformation by β-glucosidase action of human intestinal microbes after oral admistration of ginseng. We have investigated the cytotoxicity of compound K obtained from bio-converted ginseng extract. As a result, compound K showed no significant cytotoxicity in the concentration of 0.001 to 1 ㎍/mL and inhibited the production of TNF-α, MCP-1, IL-6 and NO in RAW 264.7 cells induced by LPS inflamation. In the same concentration, HaCaT cells induced by inflammation with TNF-α and IFN-γ decreased IL-8 production due to compound K treatment. In the brine shrimp lethality assay, the LC₅₀ of compound K was 0.37 mg/mL indicating some toxicity, but the bioconverted product containing 35% compound K showed relatively low toxicity with an LC₅₀ of 0.87 mg/mL. These results suggest that the compound K enriched extract is a potential functional material for acne relief cosmetic products.

• Journal of Internet Computing and Services
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• v.23 no.2
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• pp.29-35
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• 2022

UV rays have beneficial or harmful effects on the human body depending on the degree of exposure. An accurate UV information is required for proper exposure to UV rays per individual. The UV rays' information is provided by the Korea Meteorological Administration as one component of daily weather information in Korea. However, it does not provide an accurate UVI at the user's location based on the region's Ultraviolet index. Some operate measuring instrument to obtain an accurate UVI, but it would be costly and inconvenient. Studies which assumed the UVI through environmental factors such as solar radiation and amount of cloud have been introduced, but those studies also could not provide service to individual. Therefore, this paper proposes a deep learning model to calculate UVI using solar object information and sunlight characteristics to provide an accurate UVI at individual location. After selecting the factors, which were considered as highly correlated with UVI such as location and size and illuminance of sun and which were obtained through the analysis of sky images and solar characteristics data, a data set for DNN model was constructed. A DNN model that calculates the UVI was finally realized by entering the solar object information and sunlight characteristics extracted through Mask R-CNN. In consideration of the domestic UVI recommendation standards, it was possible to accurately calculate UVI within the range of MAE 0.26 compared to the standard equipment in the performance evaluation for days with UVI above and below 8.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.3
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• pp.74-99
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• 2022

Surface ozone is produced by photochemical reactions of nitrogen oxides(NOx) and volatile organic compounds(VOCs) emitted from vehicles and industrial sites, adversely affecting vegetation and the human body. In South Korea, ozone is monitored in real-time at stations(i.e., point measurements), but it is difficult to monitor and analyze its continuous spatial distribution. In this study, surface ozone concentrations were interpolated to have a spatial resolution of 1.5km every hour using the stacking ensemble technique, followed by a 5-fold cross-validation. Base models for the stacking ensemble were cokriging, multi-linear regression(MLR), random forest(RF), and support vector regression(SVR), while MLR was used as the meta model, having all base model results as additional input variables. The results showed that the stacking ensemble model yielded the better performance than the individual base models, resulting in an averaged R of 0.76 and RMSE of 0.0065ppm during the study period of 2020. The surface ozone concentration distribution generated by the stacking ensemble model had a wider range with a spatial pattern similar with terrain and urbanization variables, compared to those by the base models. Not only should the proposed model be capable of producing the hourly spatial distribution of ozone, but it should also be highly applicable for calculating the daily maximum 8-hour ozone concentrations.

• Journal of Music and Human Behavior
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• v.20 no.1
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• pp.47-74
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• 2023

The purpose of this study was to develop a music teacher training program for global citizenship education and explore its effects on the participants' capacity for global citizenship. The program focused on multicultural education, including diversity and tolerance, among various topics in global citizenship education and consisted of practice to develop lesson plans for middle school music classes as well as theory about music in diverse sociocultural environments. The results showed that this program positively affected the participants' attitudes about a music teacher's role in the multicultural classroom. This program enabled participants to identify and reflect on any prejudice they may have against diversity and multiculturalism and to consider the role of music teachers in multicultural learning environments. The program also helped the participants develop greater self-efficacy as music teachers in multicultural environments and see music as a symbolic expression and a social and cultural product. Finally, the participants showed their positive attitude toward transformative pedagogy and considered various topics in global citizenship education beyond diversity and multiculturalism through multilateral understanding and exploration about music based on theory and practice in global citizenship education.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.125-144
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• 2023

Recently, the use of Large Language Models (LLMs) such as ChatGPT has been increasing in various fields such as interactive commerce and mobile financial services. However, LMMs, which are mainly created by learning existing documents, can also learn various human biases inherent in documents. Nevertheless, there have been few comparative studies on the aspects of bias and discrimination in LLMs. The purpose of this study is to examine the existence and extent of nine types of discrimination (Age, Disability status, Gender identity, Nationality, Physical appearance, Race ethnicity, Religion, Socio-economic status, Sexual orientation) in LLMs and suggest ways to improve them. For this purpose, we utilized BBQ (Bias Benchmark for QA), a tool for identifying discrimination, to compare three large-scale language models including ChatGPT, GPT-3, and Bing Chat. As a result of the evaluation, a large number of discriminatory responses were observed in the mega-language models, and the patterns differed depending on the mega-language model. In particular, problems were exposed in elder discrimination and disability discrimination, which are not traditional AI ethics issues such as sexism, racism, and economic inequality, and a new perspective on AI ethics was found. Based on the results of the comparison, this paper describes how to improve and develop large-scale language models in the future.

• Journal of Korean Home Economics Education Association
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• v.34 no.4
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• pp.93-111
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• 2022

This study started with the question of 'What innovative task should elementary and secondary school clothing life education perform in accordance with the changes in the future educational environment?' It is time to prepare for a major shift in the educational paradigm that improves the quality of life for all everyone, based on social innovations such as the 4th industrial revolution and the transition to the post-corona era. This study examined the literature for the characteristics of changes in the future educational environment from an educational perspective, and examined the curriculum focusing on the clothing life with the porpose of presenting the direction for the clothing life education. In order to carry out this study, various literature including previous studies related to clothing life education and the national curriculum from the first curriculum to the 2015 revision were analyzed. In conclusion, the direction of the clothing life education curriculum according to the changes in the future educational environment is proposed as follows: First, nurturing convergence education experts that can combine human emotion, environment, and clothing life culture to artificial intelligence(AI); second, developing a clothing life education curriculum that links software competency and practical problem-solving competency; and lastly, implementing fashion maker education using artificial intelligence(AI) and value-oriented clothing life education. In the future, it is expected that the direction of teaching/learning methods and evaluation in clothing life education curriculum is proposed, and that this educational discussion process will help establish the identity of clothing life education in school education.