• Journal of Korea Water Resources Association
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• v.55 no.11
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• pp.855-863
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• 2022

In this study, the Artificial Neural Network (ANN) was used to mapping air temperature in Seoul. MODerate resolution Imaging Spectroradiomter (MODIS) data was used as auxiliary data for mapping. For the ANN network topology optimizing, scatterplots and statistical analysis were conducted, and input-data was classified and combined that highly correlated data which surface temperature, Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), time (satellite observation time, Day of year), location (latitude, hardness), and data quality (cloudness). When machine learning was conducted only with data with a high correlation with air temperature, the average values of correlation coefficient (r) and Root Mean Squared Error (RMSE) were 0.967 and 2.708℃. In addition, the performance improved as other data were added, and when all data were utilized the average values of r and RMSE were 0.9840 and 1.883℃, which showed the best performance. In the Seoul air temperature map by the ANN model, the air temperature was appropriately calculated for each pixels topographic characteristics, and it will be possible to analyze the air temperature distribution in city-level and national-level by expanding research areas and diversifying satellite data.

• Journal of Korean Elementary Science Education
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• v.41 no.1
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• pp.44-64
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• 2022

This study explored the elementary school teachers' experiences while teaching students with low achievement in science based on the grounded theory. In-depth interviews and analysis were conducted on 13 teachers with experiences in teaching students with low achievement in science within the last three years and more than five years of field experience until the theoretical saturation of data on the teaching experiences for students with low achievement in science. The analysis results were as follows. First, the teaching experiences of elementary school teachers for underachievers in science were classified into 119 concepts, 41 subcategories, and 17 categories. Based on the paradigm model, the categories were structured and presented as causal conditions, contextual conditions, intervening conditions, action/interaction strategies and consequences based on the central phenomenon of 'difficulty in teaching students with low achievement in science'. Second, the core category of elementary school teachers' teaching underachievers in science was assumed to be 'overcoming difficulties and teaching underachievers in science'. And according to the properties and dimensions of the core category, teachers who teaching students with low achievement in science were divided into four types: 'compromising-', 'overcoming-', 'accepting-', and 'conflicting-reality type'. Third, a conditional matrix was presented to summarize and integrate the results of this study by classifying the teaching experience of elementary school teachers for underachievers in science into educational providers and educational demanders. On the basis of these findings, educational implications for teaching students with low achievement in science were discussed.

• Korean Medical Education Review
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• v.24 no.2
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• pp.141-155
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• 2022

The purpose of this study was to investigate the current status of interprofessional education (IPE) and the efforts required to promote, popularize, and implement it in Korea. The IPE status of 40 medical colleges was investigated using a survey with questions regarding the details of IPE, the future plans and necessary support required, and the reasons for not implementing IPE. Thirty-two medical colleges responded, of which 10 are implementing or have implemented IPE. Most of these colleges started IPE in 2018, and the duration of IPE was less than 9 hours. All medical colleges held classes with nursing students. As for the type of IPE, there were independent courses for IPE, one-time special lectures, or partial sessions in one course. Lectures, discussions and presentations, role playing, and high-fidelity simulations were mainly used as educational methods. The support and interest of the dean was the most important facilitating factor. No medical colleges were currently preparing to implement IPE, four colleges had planned IPE but failed to implement it, and 16 had no plans for IPE at all. All medical colleges cited scheduling or cooperation with other majors as the most significant barrier. All the colleges listed their requirements for educational materials, cases, guidelines, and teaching and learning methods for IPE from external institutions. To activate IPE, it is necessary to create an appropriate atmosphere and conditions for developing IPE competencies and a model suitable for the domestic situation. External medical education support organizations should distribute IPE development guidelines and educational materials, form a network between medical colleges with IPE experience, and make efforts to promote the importance of IPE.

• Smart Media Journal
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• v.11 no.10
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• pp.89-96
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• 2022

An open domain machine reading comprehension is a model that adds a function to search paragraphs as there are no paragraphs related to a given question. Document searches have an issue of lower performance with a lot of documents despite abundant research with word frequency based TF-IDF. Paragraph selections also have an issue of not extracting paragraph contexts, including sentence characteristics accurately despite a lot of research with word-based embedding. Document reading comprehension has an issue of slow learning due to the growing number of parameters despite a lot of research on BERT. Trying to solve these three issues, this study used BM25 which considered even sentence length and InferSent to get sentence contexts, and proposed an open domain machine reading comprehension with ALBERT to reduce the number of parameters. An experiment was conducted with SQuAD1.1 datasets. BM25 recorded a higher performance of document research than TF-IDF by 3.2%. InferSent showed a higher performance in paragraph selection than Transformer by 0.9%. Finally, as the number of paragraphs increased in document comprehension, ALBERT was 0.4% higher in EM and 0.2% higher in F1.

• 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 Internet Computing and Services
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• v.24 no.4
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• pp.57-64
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• 2023

The ROK military faces a significant challenge in its vigilance mission due to demographic problems, particularly the current aging population and population cliff. This study demonstrates the crucial role of the 4th industrial revolution and its core artificial intelligence algorithm in maximizing work efficiency within the Command&Control room by mechanizing simple tasks. To achieve a fully developed military surveillance system, we have chosen multi-object tracking (MOT) technology as an essential artificial intelligence component, aligning with our goal of an intelligent and automated surveillance system. Additionally, we have prioritized data visualization and user interface to ensure system accessibility and efficiency. These complementary elements come together to form a cohesive software application. The CCTV video data for this study was collected from the CCTV cameras installed at the 1st and 2nd main gates of the 00 unit, with the cooperation by Command&Control room. Experimental results indicate that an intelligent and automated surveillance system enables the delivery of more information to the operators in the room. However, it is important to acknowledge the limitations of the developed software system in this study. By highlighting these limitations, we can present the future direction for the development of military surveillance systems.

• Journal of Korean Elementary Science Education
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• v.42 no.3
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• pp.399-408
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• 2023

This study developed and applied a maker education program for an elementary school's science unit on 'Animal Life'. It examined the program's impact on students' academic achievement and creative problem-solving ability. The theme of the maker education program was 'creating a robot virtual reality (VR) exhibition hall mimicking animal characteristics'. It explored scientific concepts and creatively created a robot VR exhibition hall in accordance with the TMI maker education model. Findings revealed that the program significantly improved students' academic achievement and creative problem-solving ability (p<.05). This study provides evidence for the effectiveness of maker education in elementary school science classes and suggests that using maker education can increase students' interest in and engagement with science learning. To implement maker education more actively in elementary school science classes, stakeholders should develop various topics and programs. Additional research investigating the effectiveness of maker education in different age groups and various other areas of elementary science education is required to generalize the results of this study. Moreover, educational and teacher capacity building is required for educators to utilize maker education effectively.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.177-188
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• 2023

The purpose of this study is to develop and validate a scale for measuring digital literacy by identifying the factors consisting of digital literacy and extracting items for each factor. Preliminary items for the Delphi study were developed through the analysis of previous literature and the deliberation of the research team. As a result of two rounds of the expert Delphi study, 65 items were selected for the main survey. The validation of the items was carried out in the process of exploratory and confirmatory factor analyses, reliability test, and criterion validity test using the data collected in the main survey. As a result, a 4-factor structure composed of 31 questions(factor 1: digital technology & data literacy- 9 questions, factor 2: digital content & media literacy- 8 questions, factor 3: digital communication & community literacy- 9 questions, factor 4: digital wellness literacy - 5 questions) was confirmed. Also, the goodness of fit indices of the model were found to be good and the result of reliability test revealed the scale had a very appropriate level of Cronbach's alpha(α=.956). In addition, a statistically significantly positive correlations(p<.001) were found between digital literacy and internet self-efficacy and between digital literacy and self-directed learning ability, which were predicted in the existing evidence, therefore the criterion validity of the developed scale was secured. Finally, practical and academic implications of the study are provided and future study and limitations of the study are discussed.

• Nutrition Research and Practice
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• v.17 no.2
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• pp.371-385
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• 2023

BACKGROUND/OBJECTIVES: Soy isoflavone (SIF) and soy lecithin (SL) have beneficial effects on many chronic diseases, including neurodegenerative diseases. Regretfully, there is little evidence to show the combined effects of these soy extractives on the impairment of cognition and abnormal cerebral blood flow (CBF). This study examined the optimal combination dose of SIF + SL to provide evidence for improving CBF and protecting cerebrovascular endothelial cells. MATERIALS/METHODS: In vivo study, SIF50 + SL40, SIF50 + SL80 and SIF50 + SL160 groups were obtained. Morris water maze, laser speckle contrast imaging (LSCI), and hematoxylin-eosin staining were used to detect learning and memory impairment, CBF, and damage to the cerebrovascular tissue in rat. The 8-hydroxy-2'-deoxyguanosine (8-OHdG) and the oxidized glutathione (GSSG) were detected. The anti-oxidative damage index of superoxide dismutase (SOD) and glutathione (GSH) in the serum of an animal model was also tested. In vitro study, an immortalized mouse brain endothelial cell line (bEND.3 cells) was used to confirm the cerebrovascular endothelial cell protection of SIF + SL. In this study, 50 µM of Gen were used, while the 25, 50, or 100 µM of SL for different incubation times were selected first. The intracellular levels of 8-OHdG, SOD, GSH, and GSSG were also detected in the cells. RESULTS: In vivo study, SIF + SL could increase the target crossing times significantly and shorten the total swimming distance of rats. The CBF in the rats of the SIF50 + SL40 group and SIF50 + SL160 group was enhanced. Pathological changes, such as attenuation of the endothelium in cerebral vessels were much less in the SIF50 + SL40 group and SIF50 + SL160 group. The 8-OHdG was reduced in the SIF50 + SL40 group. The GSSG showed a significant decrease in all SIF + SL pretreatment groups, but the GSH showed an opposite result. SOD was upregulated by SIF + SL pretreatment. Different combinations of Genistein (Gen)+SL, the secondary proof of health benefits found in vivo study, showed they have effective anti-oxidation and less side reaction on protecting cerebrovascular endothelial cell. SIF50 + SL40 in rats experiment and Gen50 + SL25 in cell test were the optimum joint doses on alleviating cognitive impairment and regulating CBF through protecting cerebrovascular tissue by its antioxidant activity. CONCLUSIONS: SIF+SL could significantly prevent cognitive defect induced by β-Amyloid through regulating CBF. This kind of effect might be attributed to its antioxidant activity on protecting cerebral vessels.

• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1177-1185
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• 2022

The water and sewage system is an infrastructure that provides safe and clean water to people. In particular, since the water and sewage pipelines are buried underground, it is very difficult to detect system defects. For this reason, the diagnosis of pipelines is limited to post-defect detection, such as system diagnosis based on the images taken after taking pictures and videos with cameras and drones inside the pipelines. Therefore, real-time detection technology of pipelines is required. Recently, pipeline diagnosis technology using advanced equipment and artificial intelligence techniques is being developed, but AI-based defect detection technology requires a variety of learning data because the types and numbers of defect data affect the detection performance. Therefore, in this study, various defect scenarios are implemented using 3D printing model to improve the detection performance when detecting defects in pipelines. Afterwards, the collected images are performed to pre-processing such as classification according to the degree of risk and labeling of objects, and real-time defect detection is performed. The proposed technique can provide real-time feedback in the pipeline defect detection process, and it would be minimizing the possibility of missing diagnoses and improve the existing water and sewerage pipe diagnosis processing capability.