• ALGAE
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• v.36 no.4
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• pp.299-314
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• 2021

Some species in the dinoflagellate genus Alexandrium are bioluminescent. Of the 33 formally described Alexandrium species, the bioluminescence capability of only nine species have been tested, and eight have been reported to be bioluminescent. The present study investigated the bioluminescence capability of seven Alexandrium species that had not been tested. Alexandrium mediterraneum, A. pohangense, and A. tamutum were bioluminescent, but A. andersonii, A. hiranoi, A. insuetum, and A. pseudogonyaulax were not. We also measured the bioluminescent intensity of A. affine, A. fraterculus, A. mediterraneum, A. ostenfeldii, A. pacificum, A. pohangense, A. tamarense, and A. tamutum. The mean 200-second-integrated bioluminescence intensity per cell ranged from 0.02 to 32.2 × 10⁴ relative luminescence unit per cell (RLU cell^-1), and the mean maximum bioluminescence intensity per cell per second (BL_Max) ranged from 0.01 to 10.3 × 10⁴ RLU cell^-1 s^-1. BL_Max was significantly correlated with the maximum growth rates of Alexandrium species, except for A. tamarense. A phylogenetic tree based on large subunit ribosomal DNA (LSU rDNA) showed that the bioluminescent species A. affine, A. catenella, A. fraterculus, A. mediterraneum, A. pacificum, and A. tamarense formed a large clade. However, the toxicity or mixotrophic capability of these species was split. Thus, their bioluminescence capability in this clade was more consistent than their toxicity or mixotrophic capability. Phylogenetic trees based on LSU rDNA and the luciferase gene of Alexandrium were consistent except for A. pohangense. The results of the present study can provide a basis for understanding the interspecific diversity in bioluminescence of Alexandrium.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.79-88
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• 2022

The purpose of this study was to explore which factors should be considered mainly in operating hybrid learning in which offline and synchronous online environments are integrated in elementary education. Using qualitative data through interview and so on for 8 elementary school teachers with experience in operating hybrid learning, major consideration factors were identified. Before class, it is necessary to increase the level of understanding through concrete guidance or education for what the characteristics of hybrid learning are. The redesign of the environment including hardware and software technology is considered because the foundation was not established properly so that effective operation was difficult. In particular, based on the simultaneity and interactivity between the environments, activities which learners can connect and participate in the two environments should be considered. Further, design strategies to guide the operation of teaching and learning will be developed.

• Journal of Korean Academy of Nursing
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• v.52 no.4
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• pp.435-450
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• 2022

Purpose: The purpose of the study was to understand the care experiences of the family of living donor liver transplantation (LDLT) patients where the donation had occurred within the family. Methods: Participants were eight family caregivers who cared for recipients and donors of LDLT. Data were collected through individual in-depth interviews from November, 2020 to April, 2021. Data analysis was performed through a cyclical process of data collection and analysis by applying Giorgi's phenomenological research method. Results: The five main components extracted from the experiences of the family caregivers were: "A double-edged choice to save the family", "The harsh daily life of liver transplantation care", "The yoke of double care on both shoulders", "The power to withstand the adversity of caring", and "The recovery and growth of life pursued by trusting each other". Conclusion: The participants tried to do their best in their daily lives, while providing reassurance and care to the LDLT patients in the family; however, they expressed some worry and hardship while doing so. The results of this study provide a deeper understanding of the caring experience of the family caregivers, which may contribute to the development of nursing interventions that will aid these caregivers in providing care to their LDLT family members. Furthermore, the development and application of an integrated management program for LDLT patients in the family is required.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.183-183
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• 2023

Smart water cities (SWC) are urban municipalities that utilizes modern innovations in managing and preserving the urban water cycle in the city; with the purpose of securing sustainability and improving the quality of life of the urban population. Understanding the different urban water characteristics and management strategies of cities situate a baseline in the development of evaluation scheme in determining whether the city is smart and sustainable. This research herein aims to develop measurements and evaluation for SWC Key Performance Indicators (KPIs), and set up a unified global standard and certification scheme. The assessment for SWC is performed in technical, as well as governance and prospective aspects. KPI measurements under Technical Pillar assess the cities' use of technologies in providing sufficient water supply, monitoring water quality, strengthening disaster resilience, minimizing hazard vulnerability, and maintaining and protecting the urban water ecosystem. Governance and Prospective Pillar on the other hand, evaluates the social, economic and administrative systems set in place to manage the water resources, delivering water services to different levels of society. The performance assessment is composed of a variety of procedures performed in a quantitative and qualitative manner, such as computations through established equations, interviews with authorities in charge, field survey inspections, etc. The developed SWC KPI measurements are used to evaluate the urban water management practices for Busan Eco Delta city, a Semulmeori waterfront area in Gangseo district, Busan. The evaluation and scoring process was presented and established, serving as the basis for the application of the smart water city certification all over the world. The established guideline will be used to analyze future cities, providing integrated and comprehensive information on the status of their urban water cycle, gathering new techniques and proposing solutions for smarter measures.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.164-164
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• 2023

This study investigates the importance of flood-influencing factors on the accuracy of flood risk mapping using the integration of remote sensing-based and machine learning techniques. Here, the Extreme Gradient Boosting (XGBoost) and Random Forest (RF) algorithms integrated with GIS-based techniques were considered to develop and generate flood risk maps. For the study area of NAPA County in the United States, rainfall data from the 12 stations, Sentinel-1 SAR, and Sentinel-2 optical images were applied to extract 13 flood-influencing factors including altitude, aspect, slope, topographic wetness index, normalized difference vegetation index, stream power index, sediment transport index, land use/land cover, terrain roughness index, distance from the river, soil, rainfall, and geology. These 13 raster maps were used as input data for the XGBoost and RF algorithms for modeling flood-prone areas using ArcGIS, Python, and R. As results, it indicates that XGBoost showed better performance than RF in modeling flood-prone areas with an ROC of 97.45%, Kappa of 93.65%, and accuracy score of 96.83% compared to RF's 82.21%, 70.54%, and 88%, respectively. In conclusion, XGBoost is more efficient than RF for flood risk mapping and can be potentially utilized for flood mitigation strategies. It should be noted that all flood influencing factors had a positive effect, but altitude, slope, and rainfall were the most influential features in modeling flood risk maps using XGBoost.

• Journal of Fashion Business
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• v.27 no.4
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• pp.141-162
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• 2023

With the prospect that integrating creative AI in the fashion design field will become more visible, this study considered the case of creative fashion design development through Human-AI Co-creation (HAIC). Methodologically, this research encompasses a literature review and empirical investigations. In the literature review, the fashion design and creative HAIC processes, and the possibilities of integrating AI in fashion design were considered. In the empirical study, based on the case analysis of generating fashion design through HAIC, the HAIC type according to the role and interaction method, and characteristics of humans and AI was considered, and the HAIC process for fashion design was derived. The results of this study are summarized as follows. First, HAIC types in fashion design are divided into four types: AI-driven passive HAIC, human-driven passive HAIC, flexible interaction-based HAIC, and integrated interaction-based value creation HAIC. Second, the stages of the HAIC process for creative fashion design can be broadly divided into semantic data integration, visual ideation, design creation and expansion, design presentation, and design/manufacturing solution and UX platform creation. Third, in fashion design, HAIC contributes to human ability, enhancement of creativity, achievement of efficient workflow, and creation of new values. This research suggests that HAIC has the potential to revolutionize the fashion design industry by facilitating collaboration between humans and AI; consequently, enhancing creativity, and improving the efficiency of the design process. It also offers a framework for understanding the different types of HAIC and the stages involved in the creative fashion design process.

• 한국정보교육학회:학술대회논문집
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• 2021.08a
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• pp.213-221
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• 2021

With the advent of the 4th industrial revolution, the need for artificial intelligence education has increased. The online learning environment caused by COVID-19 made it possible to use variety of artificial intelligence platforms. In this study, an aritificial intelligence class plan was developed and proposed to achieve the goal of artificial intelligence education using an AI platform. The AI platform used is AI for Oceans, With the theme of creating a program for the environment, designed a 6-hour project class using Novel Engineering-based on STEAM model. Students experience AI for Oceans enough time and learn supervised learning by experience. Based on understanding of supervised learning, students design their own programs for the environment using Entry's AI blocks. In this study, for AI convergence education, this lesson was developed and presented with the goal of acquiring the creative problem solving ability and integrated thinking ability by using the principles of artificial intelligence to solve problems.

• The Journal of the Convergence on Culture Technology
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• v.9 no.4
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• pp.423-430
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• 2023

This dissertation discusses the formulation of a nonlinear storytelling board that preserves the contextual perspective of characters. Storytelling encompasses the director's creative intention by leveraging the interaction of various elements to construct a logical narrative that explores cause and effect. Its primary objective is to enhance viewers' empathy. Consequently, there is a pressing need for comprehensive research on differentiating storytelling from storyboarding. Moreover, the integrated approach to storytelling and storyboarding holds scholarly value in understanding the process of narrative composition and visualization. Thus, a study proposes a method for constructing nonlinear storytelling boards considering the discrete camera perspective and contextual scene continuity, ultimately contributing to visual complexity and correlation comprehension. This approach enables a careful and simultaneous consideration of the correlations that deepen cognition, including the physical, emotional, and event rhythms mentioned in Karen Perlman's theory.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.192-192
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• 2022

Sweetpotato is rich in starch, which is converted to sugar during storage due to enzymatic hydrolysis. The sugar content of sweetpotato is a component related to taste and storability. In this study, the sugar content (fructose, glucose, maltose, sucrose and total sugar content) of 94 genotypes was evaluated and the GWAS (Genome-Wide Association Study) was conducted to search for candidate genes for sugar content. The fructose and glucose content were 0.2 ~ 8.8 and 0.2 ~ 9.4 g/100g, respectively. The maltose, sucrose and total sugar content were 0.2 ~ 9.1,3.2 - 30.0 and 7.9 ~ 40.2 g/100g, respectively. The fructose and glucose showed a positive correlation (0.98). The 94 genotypes were genotyped with genotyping-by-sequencing (GBS) and aligned against the reference genome sequences of sweetpotato. The GBS libraries from 94 genotypes were sequenced on an Illumina HiSeqXten system, and 1,339,892 SNPs (Single Nucleotide Polymorphism) were generated. Filtering for < 60% missing rate and > 0.05 minor allele frequency resulted in a total of 44,255 SNPs used in GWAS. The GAPIT (Genome Association and Prediction Integrated Tool) was used to conduct based on the mean of sugar content with a Bonferroni-corrected chromosome-wide significance threshold with a -logio(P) of 5.95. The significant SNPs were obtained with fructose (seven), glucose (six), maltose (four) and sucrose (nine). There were several genes related to sugar content around the significant SNPs such as sugar transport protein 8-like, probable galactose-1 -phosphate uridyltransferase-like and beta-amylase. These results will contribute to understanding of sugar content and conversion in sweetpotato.

• Journal of Practical Engineering Education
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• v.14 no.3
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• pp.459-469
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• 2022

The purpose of this study is to explore the educational effect by developing and applying a decision tree-based artificial intelligence convergence education program. To achieve the purpose of this study, the study was conducted through a three-step process of preparation, development, and improvement. In addition, it consisted of four stages of the creative problem-solving process: 'Understanding the problem', 'Idea search and development', 'realization' and 'evaluation'. In particular, the artificial intelligence convergence education program developed in this study is an unplugged activity that does not include programming. Therefore, it is very noteworthy that artificial intelligence convergence education was implemented in subjects other than technology and home economics education, and information education, which are part of junior engineering education, and practical arts education in elementary education, which is a subject that learns Artificial Intelligence technology including programming during class time. In other words, it shows that AI technology can be integrated and taught in most subjects, not specific subjects and has great significance in that it can utilize the concepts and principles of artificial intelligence technology when teaching the concept of classification, which is included in the curriculum.