• Korean Journal of Construction Engineering and Management
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• v.23 no.3
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• pp.45-55
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• 2022

BIM models allow building spaces to be instantiated and recognized as unique objects independently of model elements. These instantiated spaces provide the required semantics that can be leveraged for building code checking, energy analysis, and evacuation route analysis. However, theses spaces or rooms need to be designated manually, which in practice, lead to errors and omissions. Thus, most BIM models today does not guarantee the semantic integrity of space designations, limiting their potential applicability. Recent studies have explored ways to automate space allocation in BIM models using artificial intelligence algorithms, but they are limited in their scope and relatively low classification accuracy. This study explored the use of Graph Convolutional Networks, an algorithm exclusively tailored for graph data structures. The goal was to utilize not only geometry information but also the semantic relational data between spaces and elements in the BIM model. Results of the study confirmed that the accuracy was improved by about 8% compared to algorithms that only used geometric distinctions of the individual spaces.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.703-708
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• 2022

Tables and figures in academic literature contain important and valuable information. Tables and figures represent the essence of the refined study, which is the closest to the raw dataset. If so, can researchers easily access and utilize these image data through the search system? In this study, we try to identify user perceptions and needs for image data through user and case studies. Through this study we also explore expected effects and utilizations of image search systems. It was found that the majority of researchers prefer a system that combines table and figure indexing functions with traditional search functions. They valued the provision of an advanced search function that would allow them to limit their searches to specific object types (pictures and tables). Overall, researchers discovered many potential uses of the system for indexing tables and figures. It has been shown to be helpful in finding special types of information for teaching, presentation, research and learning. It should be also noticed that the usefulness of these systems is highest when features are integrated into existing systems, seamlessly link to fulltexts, and include high-quality images with full captions. Expected effects and utilizations for user-centered image search systems are also discussed.

• Journal of Korean Home Economics Education Association
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• v.33 no.4
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• pp.1-13
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• 2021

The purpose of this study is to identify trends and potential themes of research on consumption of children and adolescents for 20 years by analyzing keywords. The keywords of 869 studies on consumption of children and adolescents published in journals listed in Korean Citation Index were analyzed using text mining techniques. The most frequent keywords were found in the order of youth, youth consumers, consumer education, conspicuous consumption, consumption behavior, and character. As a result of analyzing the frequency of keywords by dividing into five-year periods, it was confirmed that the frequency of consumer education was significantly higher betwn 2006 and 2010. Research on ethical consumption has been active since 2011, and research has been conducted on various topics instead of without a prominent keyword during the most recent 5-year period. Looking at the keywords based on the TF-IDF, the keywords related to the environment and the Internet were the main keywords between 2001 and 2005. From 2006 to 2010, the TF-IDF values of media use, advertisement education, and Internet items were high. From 2011 to 2015, fair trade, green growth, green consumption, North Korean defector youths, social media, and from 2016 to 2020, text mining, sustainable development education, maker education, and the 2015 revised curriculum appeared as important themes. As a result of topic modeling, eight topics were derived: consumer education, mass media/peer culture, rational consumption, Hallyu/cultural industry, consumer competency, economic education, teaching and learning method, and eco-friendly/ethical consumption. As a result of network analysis, it was found that conspicuous consumption and consumer education are important topics in consumption research of children and adolescents.

• Journal of Korean Elementary Science Education
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• v.41 no.3
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• pp.501-520
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• 2022

Considering the importance of spatial thinking in the process of learning astronomy, it is necessary to educate pre-service teachers on teaching methods that consider spatial thinking from the teacher training program stage. Accordingly, after providing education on spatial thinking to pre-service science teachers, problems and improvement plans perceived by them were explored for the images and inquiry activities of astronomy textbook units. In this study, spatial thinking in the astronomical domain was defined as the amalgam of the concepts of space, representation tools, and reasoning processes. The juniors attending the University of Education in the metropolitan area were educated on spatial thinking for two weeks in October 2021. They were then asked to voluntarily select one of the astronomy units to analyze problems in the textbooks and present modification plans to address those problems. Finally, 33 cases presented by 22 pre-service science teachers were analyzed, and the results of the study were as follows. Pre-service teachers recognized the problems in textbooks in terms of the concepts of space and reasoning processes, and proposed improvement plans to supplement them. However, in some cases, even if pre-service teachers properly recognized a problem, the improvement plan was not appropriate, or they were not able to analyze the images or inquiry activities in terms of spatial thinking. This study is significant in that it shows that pre-service teachers have the potential to properly reorganize and revise textbooks by participating in teacher training programs on spatial thinking. Furthermore, based on the results of this study, the direction of the teacher training program concerning spatial thinking was discussed.

• Journal of the Korean Society of Earth Science Education
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• v.15 no.2
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• pp.263-272
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• 2022

The purpose of this study is to investigate the effect of developing and applying a program in the field of astronomy that can improve the spatial perception ability and task commitment of elementary science gifted students. The subjects of this study were 22 students in the advanced course in the elementary science gifted class affiliated with the Gifted and Talented Center of University B. In order to improve spatial perception ability and task attachment to students in elementary school science gifted class, a total of 12 educational learning programs were developed and applied. The results of this study were interpreted as quantitative analysis. The results of this study are as follows. First, the astronomy class had a positive effect on the spatial perception ability improvement of elementary science gifted students. Second, the astronomy class had a positive effect on improving the task commitment of elementary school science gifted students. Third, astronomy class of elementary school science gifted students was more effective in improving spatial perception than improving task commitment. Since elementary school science gifted students are selected with excellent intelligence, creativity, and task commitment, an Individualized Education Program (IEP) is developed and applied to better express their potential giftedness. In addition, in order to express more in-depth giftedness in gifted education, it is necessary to pay attention to the development of programs that can express individual gifted characteristics.

• Journal of Intelligence and Information Systems
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• v.29 no.3
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• pp.383-400
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• 2023

Air pollution-related diseases are escalating worldwide, with the World Health Organization (WHO) estimating approximately 7 million annual deaths in 2022. The rapid expansion of industrial facilities, increased emissions from various sources, and uncontrolled release of odorous substances have brought air pollution to the forefront of societal concerns. In South Korea, odor is categorized as an independent environmental pollutant, alongside air and water pollution, directly impacting the health of local residents by causing discomfort and aversion. However, the current odor management system in Korea remains inadequate, necessitating improvements. This study aims to enhance the odor management system by analyzing 1,010,749 data points collected from odor sensors located in Osong, Chungcheongbuk-do, using an Ensemble-Based Multi-Region Integrated Odor Concentration Prediction Model. The research results demonstrate that the model based on the XGBoost algorithm exhibited superior performance, with an RMSE of 0.0096, significantly outperforming the single-region model (0.0146) with a 51.9% reduction in mean error size. This underscores the potential for increasing data volume, improving accuracy, and enabling odor prediction in diverse regions using a unified model through the standardization of odor concentration data collected from various regions.

• Journal of radiological science and technology
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• v.46 no.4
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• pp.315-323
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• 2023

Post-mortem computed tomography (PMCT) is commonly employed in the field of forensic pathology. PMCT was mainly performed using a whole-body scan with a wide field of view (FOV), which lead to a decrease in spatial resolution due to the increased pixel size. This study aims to evaluate the potential for developing a super-resolution model based on conditional generative adversarial networks (CGAN) to enhance the image quality of CT. 1761 low-resolution images were obtained using a whole-body scan with a wide FOV of the head phantom, and 341 high-resolution images were obtained using the appropriate FOV for the head phantom. Of the 150 paired images in the total dataset, which were divided into training set (96 paired images) and validation set (54 paired images). Data augmentation was perform to improve the effectiveness of training by implementing rotations and flips. To evaluate the performance of the proposed model, we used the Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM) and Deep Image Structure and Texture Similarity (DISTS). Obtained the PSNR, SSIM, and DISTS values of the entire image and the Medial orbital wall, the zygomatic arch, and the temporal bone, where fractures often occur during head trauma. The proposed method demonstrated improvements in values of PSNR by 13.14%, SSIM by 13.10% and DISTS by 45.45% when compared to low-resolution images. The image quality of the three areas where fractures commonly occur during head trauma has also improved compared to low-resolution images.

• Journal of Korean Home Economics Education Association
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• v.35 no.2
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• pp.1-20
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• 2023

The purpose of this study is to extract and analyze ecological citizenship elements in the middle school home economics textbook used in the 2015 national curriculum for the introduction of ecological transformation education in the 2022 national curriculum. As a result of the analysis, the content analysis of the ecological citizenship factor was validated by six experts who are incumbent middle school home economics teachers, and the S-CVI value was 0.97, ensuring the validity of the ecological citizenship factor analysis. The results of analyzing 242 ecological citizenship factors extracted from home economics textbooks are as follows. According to the content area of the 2015 national home economics curriculum, the 'human development and family' area had the highest presence of ecological citizenship factors followed by the 'resource management and self-reliance' area and the 'home life and safety' area. Among the categories of ecological citizenship factors, 'value⋅attitude' was the most frequent, followed by 'process⋅function' and 'knowledge⋅understanding'. For each textbook composition system, ecological citizenship elements were extracted in the order of pictures, text, activities, and supplementary materials. There was a significant variation in the number of ecological citizenship factors among publishers, indicating the importance of the textbook writers' perception, interpretation, and direction of writing. Based on these analysis results, ecological citizenship teaching and learning activities applicable to home economics education were presented. This study highlights the potential for practicing ecological citizenship education in line with the new orientation of the curriculum on ecological transformation education through home economics education. Furthermore, it provides valuable baseline data for the development and implementation of textbooks for the 2022 national curriculum.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.43 no.5
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• pp.667-674
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• 2023

In the event of a disaster occurring within a building, the prompt and efficient evacuation and rescue of occupants within the building becomes the foremost priority to minimize casualties. For the purpose of such rescue operations, it is essential to ascertain the distribution of individuals within the building. Nevertheless, there is a primary dependence on accounts provided by pertinent individuals like building proprietors or security staff, alongside fundamental data encompassing floor dimensions and maximum capacity. Consequently, accurate determination of the number of occupants within the building holds paramount significance in reducing uncertainties at the site and facilitating effective rescue activities during the golden hour. This research introduces a methodology employing computer vision algorithms to count the number of occupants within distinct building locations based on images captured by installed multiple CCTV cameras. The counting methodology consists of three stages: (1) establishing virtual Lines of Interest (LOI) for each camera to construct a multi-camera network environment, (2) detecting and tracking people within the monitoring area using deep learning, and (3) aggregating counts across the multi-camera network. The proposed methodology was validated through experiments conducted in a five-story building with the average accurary of 89.9% and the average MAE of 0.178 and RMSE of 0.339, and the advantages of using multiple cameras for occupant counting were explained. This paper showed the potential of the proposed methodology for more effective and timely disaster management through common surveillance systems by providing prompt occupancy information.

• Journal of Korean Biological Nursing Science
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• v.25 no.1
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• pp.20-31
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• 2023

Purpose: This study aimed to determine the consistency of 1-day and 3-day average dietary intake using the 24-hour diet recall method and to investigate the relationship of diet intake with physiological indicators potentially associated with diabetic complications in patients with diabetes. Methods: This study conducted a secondary data analysis using pretest data of a nursing intervention study entitled "Development of deep learning based AI coaching program for diabetic patients with high risk and examination of its effects." Data were analyzed through descriptive analysis, one-way repeated-measures analysis of variance, and Pearson correlation coefficients using SPSS 26.0. Results: The average total daily calorie intake over 3 days was 1,494.48 ± 436.47 kcal/day: 1,510.90 ± 547.76 kcal/day on the first day, 1,414.22 ± 527.58 kcal/day on the second day, 1,558.34 ± 645.83 kcal/ day on the third day, showing significant differences (F = 3.59, p = .031). The correlation coefficient between the 1-day and 3-day average dietary intake was 0.41-0.77 for each nutrient and 0.62-0.80 for each food group. Vegetable intake showed negative correlations with body mass index (BMI; r = -.19, p = .023) and triglycerides (r = -.18, p = .036), whereas dairy intake was positively associated with low-density lipoprotein-cholesterol (LDL; r = -0.18, p = .034) and triglycerides (r = .40, p<.001). Conclusion: This study demonstrated that 1-day dietary intake was highly correlated with 3-day average dietary intake using the 24-hour diet recall method. Food groups showed significant associations with physiological indicators of potential diabetic complications such as BMI, triglycerides, and LDL levels. Further studies are needed to improve the knowledge base on the relationships between physiological indicators and food groups.