• Journal of The Korean Association of Information Education
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• v.24 no.5
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• pp.433-441
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• 2020

The advent of the intelligent information society and artificial intelligence education for fostering future talents is attracting the attention of the education community, and the AI graduate course for teachers is also being opened and operated. The curriculum of the AI education graduate school, which was established this year, is self-contained considering the conditions of each university. Are organized. Accordingly, this study seeks to explore the direction of curriculum development so that AI curriculum that can be more effective and enhance educational value in the graduate school of education can be developed in the future. Based on the Backward design, the AI curriculum proposed in this study includes Bloom's digital taxonomy, Bruner's spiral curriculum composition principle, and three elements such as 'content domain', 'level', and 'teacher learning method'. It was intended to consist of. Based on the direction of AI curriculum development suggested in the study, we hope that the AI curriculum of domestic graduate schools of education will be more substantial, and this framework will be revised and supplemented in the future to be used in the composition of the AI curriculum in elementary and secondary schools.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.21 no.2
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• pp.62-73
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• 2022

As the competition among the autonomous vehicle (AV, here after) developers are getting fierce, Korean government has been supporting developers by deregulating safety standards and providing financial subsidies. Recently, some OEMs announced their plans to market Lv3 and Lv4 automated driving systems. However, these market changes raised concern among public road management sectors for monitoring road conditions and alleviating hazardous conditions for AVs and human drivers. In this regards, the authors proposed a methodology for monitoring road infrastructure to identify hazardous factors for AVs and categorizing the hazards based on their level of impact. To evaluate the degrees of the harm on AVs, the authors suggested a methodology for managing road hazard factors based on vehicle performance features including vehicle body, sensors, and algorithms. Furthermore, they proposed a method providing AVs and road management authorities with potential risk information on road by delivering them on the monitoring map with node and link structure.

• Korean Journal of Construction Engineering and Management
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• v.23 no.4
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• pp.3-14
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• 2022

Autonomous equipment requires a large amount of data from various environments. However, it takes a lot of time and cost for an experiment in a real construction sites, which are difficulties in data collection and processing. Therefore, this study aims to develop a virtual environment for autonomous tower cranes technology development and validation. The authors defined automation functions and operation conditions of tower cranes with three performance criteria: operational design domain, object and event detection and response, and minimum functional conditions. Afterward, this study developed a virtual environment for learning and validation for autonomous functions such as recognition, decision making, and control using the Unity game engine. Validation was conducted by construction industry experts with a fidelity which is the representative matrix for virtual environment assessment. Through the virtual environment platform developed in this study, it will be possible to reduce the cost and time for data collection and technology development. Also, it is also expected to contribute to autonomous driving for not only tower cranes but also other construction equipment.

• 한국노년학
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• v.40 no.2
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• pp.269-289
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• 2020

The purpose of this study was to analyze the policy and programs of the Seoul50Plus Foundation and to propose policies and programs to promote active aging of middle-aged and elderly people. A single case study was utilized as a research method. The analysis framework of case was approached with four frameworks: the context of policy and program, ideology-goal analysis of policy and program, supplier and customer analysis of policy and program, and process and domain analysis of policy and program. The analysis data included the homepage content of the Seoul50Plus Foundation, related 50+ policy and program data, active aging research papers at home and abroad, and presentation and meeting materials. The results of the research showed that the policy and program background and environment were essential elements for responding to environmental changes in the aging society. In terms of the philosophy-goal, job creation, social participation, and approach to life design were systematically carried out for the ideology of 'creating a new life vision' and promoting active aging. In terms of subject-target, the subject of policy implementation is systematically composed of three stages: 50+ foundation, 50+ campus, and 50+ center. The target was limited to 50+ generations(age 50~64) and had a problem that is limited to applicants. In the process-area analysis, programs such as educational support, work and entrepreneurship support, counseling information, and new-age cultural creation activities were designed to increase added value according to the characteristics of the middle-aged people. In conclusion, the future Seoul50Plus Foundation's policy and lifelong learning programs need to be systematically promoted through cooperation with businesses and universities, expanding the target audience, matching the characteristics of the middle-aged and elderly, and linkage among programs.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.40 no.5
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• pp.429-437
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• 2022

Recently, the demand for a QA (Question Answering) system for human-machine communication has increased. Among the QA systems, a closed domain QA system that can handle spatial-related questions is called GeoQA. In this study, a new type of graph database, LPG (Labeled Property Graph) was used to overcome the limitations of the RDF (Resource Description Framework) based database, which was mainly used in the GeoQA field. In addition, GraphQL (Graph Query Language), an API-type query language, is introduced to address the fact that the LPG query language is not standardized and the GeoQA system may depend on specific products. In this study, database was built so that answers could be retrieved when spatial-related questions were entered. Each data was obtained from the national spatial information portal and local data open service. The spatial relationships between each spatial objects were calculated in advance and stored in edge form. The user's questions were first converted to GraphQL through FOL (First Order Logic) format and delivered to the database through the GraphQL server. The LPG used in the experiment is Neo4j, the graph database that currently has the highest market share, and some of the built-in functions and QGIS were used for spatial calculations. As a result of building the system, it was confirmed that the user's question could be transformed, processed through the Apollo GraphQL server, and an appropriate answer could be obtained from the database.

• Therapeutic Science for Rehabilitation
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• v.11 no.4
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• pp.7-22
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• 2022

Objective : This study aims to provide clinical evidence by systematically reviewing domestic CO-OP intervention studies. Methods : 13 papers suitable for selection criteria were finally selected and conducted. The analysis was divided into general characteristics and qualitative levels. Results : As a result of analyzing the contents of study, research has been conducted continuously since 2015, and the level of evidence for CO-OP intervention study was mainly single subject design. The subjects of the study were applied to both children and adults, and as the target activity areas of CO-OP intervention, children were shown to be play and leisure, and adults were instrumental daily living. COPM/PQRS were frequently used for evaluation to examine effectiveness of interventions. For domain specific strategies, children used body position, attention to doing, task specification, and verbal motor mnemonic. For adults, body position, attention to doing, task specification, and feeling to movement, verbal motor mnemonic, verbal rote script were used. Conclusion : It was found that CO-OP intervention is continuously being applied in occupational therapy, and age and diagnosis group are expanding. It is significant in that it provided evidence for implementing CO-OP interventions in clinical practice through a systematic review of domestic CO-OP intervention studies.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.22 no.1
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• pp.192-207
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• 2023

Commercialization of level-4 (Lv.4) autonomous driving applications requires the definition of a safe road environment under which autonomous vehicles can operate safely. Thus, a risk assessment model is required to determine whether the operation of autonomous vehicles can provide safety to is sufficiently prepared for future real-life traffic problems. Although the risk factors of autonomous vehicles were selected and graded, the decision-making method was applied as qualitative data using a survey of experts in the field of autonomous driving due to the cause of the accident and difficulty in obtaining autonomous driving data. The fuzzy linguistic representation of decision-makers and the fuzzy analytic hierarchy process (AHP), which converts uncertainty into quantitative figures, were implemented to compensate for the AHP shortcomings of the multi-standard decision-making technique. Through the process of deriving the weights of the upper and lower attributes, the road alignment, which is a physical infrastructure, was analyzed as the most important risk factor in the operation risk of autonomous vehicles. In addition, the operation risk of autonomous vehicles was derived through the example of the risk of operating autonomous vehicles for the 5 areas to be evaluated.

• Journal of the Korea Convergence Society
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• v.13 no.1
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• pp.179-188
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• 2022

This study discovers the general characteristics of B-class Emotional Advertisements and analyses their trend. A content analysis was conducted on 498 advertisements on-aired between 2015 and 2020, which were sampled from the advertisements registered in the TVCF(www.tvcf.co.kr), the largest advertisement web portal in the Republic of Korea. The analysis concludes that the B-class Emotional Advertisements, employed in a wide range of genre, is most incorporated in comedy/exaggeration genres and is on a rising trend due to 2020 COVID-19 Pandemic. Furthermore, it is confirmed that the utilization of B-class emotional advertisement has also increased in domain of non-commercial advertisements, such as Public Service Advertisements, Governmental/Organizational Advertisements, and Corporate Public Relations (PR) Advertisements. The study validates the transformation of the B-class emotional advertisements from a demonstration of an eccentric minority subculture to an epitome of a new and adventurous mainstream culture, successfully serving a central role in both the commercial and non-commercial sectors. Depicting the caricatures of the social, cultural and economic phenomenon and the recent surge of individual's depression, fatigue and pessimism, B-class emotional advertisements provide sympathetic and emotional alleviating ground for people that contributed to its rise.

• Journal of Intelligence and Information Systems
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• v.29 no.2
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• pp.241-265
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• 2023

A corporate insolvency prediction model serves as a vital tool for objectively monitoring the financial condition of companies. It enables timely warnings, facilitates responsive actions, and supports the formulation of effective management strategies to mitigate bankruptcy risks and enhance performance. Investors and financial institutions utilize default prediction models to minimize financial losses. As the interest in utilizing artificial intelligence (AI) technology for corporate insolvency prediction grows, extensive research has been conducted in this domain. However, there is an increasing demand for explainable AI models in corporate insolvency prediction, emphasizing interpretability and reliability. The SHAP (SHapley Additive exPlanations) technique has gained significant popularity and has demonstrated strong performance in various applications. Nonetheless, it has limitations such as computational cost, processing time, and scalability concerns based on the number of variables. This study introduces a novel approach to variable selection that reduces the number of variables by averaging SHAP values from bootstrapped data subsets instead of using the entire dataset. This technique aims to improve computational efficiency while maintaining excellent predictive performance. To obtain classification results, we aim to train random forest, XGBoost, and C5.0 models using carefully selected variables with high interpretability. The classification accuracy of the ensemble model, generated through soft voting as the goal of high-performance model design, is compared with the individual models. The study leverages data from 1,698 Korean light industrial companies and employs bootstrapping to create distinct data groups. Logistic Regression is employed to calculate SHAP values for each data group, and their averages are computed to derive the final SHAP values. The proposed model enhances interpretability and aims to achieve superior predictive performance.

• Animal Bioscience
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• v.36 no.10
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• pp.1517-1529
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• 2023

Objective: The objective of this study was to investigate the phylogenetic and expression analysis of the angiopoietin-like (ANGPTL) gene family and their role in lipid metabolism in pigs. Methods: In this study, the amino acid sequence analysis, phylogenetic analysis, and chromosome adjacent gene analysis were performed to identify the ANGPTL gene family in pigs. According to the body weight data from 60 Jinhua pigs, different tissues of 6 pigs with average body weight were used to determine the expression profile of ANGPTL1-8. The ileum, subcutaneous fat, and liver of 8 pigs with distinct fatness were selected to analyze the gene expression of ANGPTL3, ANGPTL4, and ANGPTL8. Results: The sequence length of ANGPTLs in pigs was between 1,186 and 1,991 bp, and the pig ANGPTL family members shared common features with human homologous genes, including the high similarity of the amino acid sequence and chromosome flanking genes. Amino acid sequence analysis showed that ANGPTL1-7 had a highly conserved domain except for ANGPTL8. Phylogenetic analysis showed that each ANGPTL homologous gene shared a common origin. Quantitative reverse-transcription polymerase chain reaction analysis showed that ANGPTL family members had different expression patterns in different tissues. ANGPTL3 and ANGPTL8 were mainly expressed in the liver, while ANGPTL4 was expressed in many other tissues, such as the intestine and subcutaneous fat. The expression levels of ANGPTL3 in the liver and ANGPTL4 in the liver, intestine and subcutaneous fat of Jinhua pigs with low propensity for adipogenesis were significantly higher than those of high propensity for adipogenesis. Conclusion: These results increase our knowledge about the biological role of the ANGPTL family in this important economic species, it will also help to better understand the role of ANGPTL3, ANGPTL4, and ANGPTL8 in lipid metabolism of pigs, and provide innovative ideas for developing strategies to improve meat quality of pigs.