• Journal of Korea Society of Industrial Information Systems
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• v.26 no.4
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• pp.19-32
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• 2021

It is well known that any maintenance works for aircrafts must be carried out strictly in accordance with the specified maintenance manuals, especially for military airplanes. According to our previous studies, the largest portion of the maintenance jobs for military aircrafts is found to be related to the assembly/disassembly of various parts, which requires precise understanding of the work procedures as well as correlation between interconnected parts let alone grasping of the exact shapes of parts involved. However, the conventional manuals for aircraft maintenance have failed to provide enough information required for the efficient maintenance except for simple texts and vague pictures, which are far from being sufficient sets of information. On the contrary, unlike incomplete conventional manuals with poor contents, 3D modeling SW could provide us with not only powerful visualization tool even to see through inside any assembly but also freedom to watch parts under test from any angle we want. In addition, the maintenance personnels could learn the precise maintenance procedures through repeatedly watching 3D animated version of the maintenance work as if they were on the field. In this study, we have suggested the efficient procedures to develop 3D manual for aircraft maintenance using 3D modeling SW, Solidworks and implemented a 3D maintenance manual for Integrated Drive Generator(IDG) in Boeing 747. Characteristics of the developed 3D manual has been analyzed in comparison with the conventional ones as well. It is shown that the suggested method could be easily applied to develop a 3D maintenance manual for commercial airplanes since the maintenance works involving assembly/disassembly of major parts are very similar regardless of aircraft types.

• Journal of The Korean Association of Information Education
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• v.20 no.3
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• pp.293-302
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• 2016

It is the latest fashion of interesting with software education in public school environment and also consider as high priority issue of curriculum for college freshman with programming 101 courses. The block-based programming tool is used widely for the beginner and provides several positive features compare than text-based programming language tools. To measure quality of programming code elaborately which is based script language, it is need to very tough manual process. As a result the previously research related with evaluation of block-based script code has been focused very simple methods in which normalize the number of blocks used which is related with programming concept. In such cases in this, it is difficult to measure structural vulnerability of script code and implicit programming concept which does not expose. In this research, the framework is proposed which enable to measure and evaluate quality of code script of block-based programming tools and also provides method to find of vulnerability of script code. In this framework, the quality metrics is constructed to structuralize implicit programming concept and then developed the quality measure and vulnerability model of script to improve level of programming. Consequently, the proposed methods enable to check of level of programming and predict the heuristic target level.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.2
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• pp.51-62
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• 2022

This study suggests a design of predictive modeling for a hospital fall risk based on inpatients' posture. Inpatient's profile, medical history, and body measurement data along with basic information about a bed they use, were used to predict a fall risk and suggest an algorithm to determine the level of risk. Fall risk prediction is largely divided into two parts: a real-time fall risk evaluation and a qualitative fall risk exposure assessment, which is mostly based on the inpatient's profile. The former is carried out by recognizing an inpatient's posture in bed and extracting rule-based information to measure fall risk while the latter is conducted by medical staff who examines an inpatient's health status related to hospital fall risk and assesses the level of risk exposure. The inpatient fall risk is determined using a sigmoid function with recognized inpatient posture information, body measurement data and qualitative risk assessment results combined. The procedure and prediction model suggested in this study is expected to significantly contribute to tailored services for inpatients and help ensure hospital fall prevention and inpatient safety.

• Journal of Information Technology Applications and Management
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• v.27 no.4
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• pp.49-62
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• 2020

In this study, the research model of VR·AR contents convergence education for solving social problems was presented after benchmarking the domestic and foreign realistic educational contents industry and policy trends and Fishbone diagram analysis. The goal was to create VR·AR content convergence talent for co-prosperity in the era of the fourth industrial revolution, and the target of education was students, researchers, and business personnel who are interested in VR AR technology education and contents business such as game animation, etc. The education model is based on understanding about storytelling of the socially disadvantaged, such as children and the elderly, and is technology education for content production including the application of virtual and augmented reality SW, and is a convergence education for content planning and business model strategy development.

• The Journal of Korean Association of Computer Education
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• v.23 no.4
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• pp.49-59
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• 2020

At the beginning of the discussion of AI education in K-12 education, the study was conducted to develop and apply an AI education program based on Design Thinking and analyze the effects of the AI education programs. In the AI education program, students explored and defined the AI problems they were interested in, gathered the necessary data to build an AI model, and then developed a project using scratch. In order to analyze the effectiveness of the AI education program, the change of learner's perception of the value of AI and the change of AI efficacy were analyzed. The overall perception of the AI project was also analyzed. As a result, AI efficacy was significantly increased through the experience of carrying out the project according to the Design Thinking process. In addition, the efficacy of solving problems with AI was influenced by the level of use of programming languages. The learner's overall perception of the AI project was positive, and the perceptions of each stage of the AI project (AI problem understanding and problem exploration, practice, problem definition, problem solving idea implementation, evaluation and presentation) was also positive. This positive perception was higher among students with high level of programming language use. Based on these results, the implications for AI education were suggested.

• Journal of The Korean Association of Information Education
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• v.26 no.5
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• pp.341-352
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• 2022

The wave of a knowledge and information society led by AI, Big Data, and so on is having an all-round impact on our way of life. Therefore the Ministry of Education is in a hurry to strengthen Digital Literacy, including AI and SW Education, by improving the curriculum that can cultivate basic knowledge and capabilities to respond to changes in the future society. It can be seen that establishing a foundation for cultivating Digital Literacy through all subjects and improving basic and in-depth learning in new technology fields such as AI linked to the information curriculum is an essential part for future society. However, research on each content for cultivating Digital and AI literacy is relatively active, while research on teaching and learning strategies is insufficient. Therefore in this study, a CT-based Digital and AI teaching and learning strategy that can foster that was developed and Delphi expert verification was conducted, and the final teaching and learning strategy was completed after evaluating instructor usability and analyzing learner effectiveness.

• Smart Media Journal
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• v.9 no.4
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• pp.66-72
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• 2020

As the online education market expands, educational contents with various presentation methods are being developed and released. In addition, it is imperative to develop content that reflects the usability and user environment of users who use this educational content. However, for qualitative growth of contents that will support quantitative expansion of markets, existing model analysis methods are urgently needed at a time when development direction of newly developed contents is secured. In this process of content development, a typical model for setting development goals is needed, as the rules of the prototype affect the entire development process and the final development outcome. It can also provide a positive benefit that screens the issue of performance dualization between processes due to the absence of communication between a single entity or between a number of entities. In the case of AR-based educational content which is effective to secure data necessary for development by securing samples of similar categories because there are not enough ready-made samples released. Therefore, a big data statistical analysis service is needed that can easily collect data and make decisions using big data. In this paper, we would like to design analysis services that enable the selection and detection of intuitive multidimensional factors and attributes, and propose big data-based statistical analysis services that can assist cooperative activities within an organization or among many companies.

• Journal of the Korean earth science society
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• v.39 no.6
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• pp.545-554
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• 2018

The Cretaceous Eumsung (Eumseong) Basin is a pull-apart basin, formed along a series of the Gongju strike-slip faults trending NE-SW. The Nongdari-Meer forest of the Gugokri area in the southwestern part of the basin is comprised of thick purple mudstone, intercalating conglomerate, pebbly sandstone, and green mudstone beds. The succession mainly consists of seven sedimentary facies: stratified conglomerate (C2), conglomerate encased in siltstone (CE), stratified pebbly sandstone encased in siltstone (PSE2), purple sandy siltstone (Zp), green sandy siltstone (Zg), purple mudstone (Mp), and green mudstone (Mg). Sedimentary environment is mainly indicative of alluvial-plain setting in an alluvial-to-lacustrine sedimentary system, developed in the southwestern part of the basin. Geological survey was fulfilled in succession of the Gugokri sedimentary system using 1:5000 topographic map, which resulted in a geological route map. This study newly suggested that there be fluvial systems showing ENE and NNE trends in the study area, based on data of palaeocurrent direction and sedimentary characteristics in new outcrops of the forest. The study also revised the precedent sedimentation model of the Gugokri system.

• Journal of Digital Convergence
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• v.17 no.10
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• pp.259-264
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• 2019

This paper proposes an image prediction system architecture for deep running in enterprise environment. Easily transform into an artificial intelligence platform for an enterprise environment, and allow sufficient deep-running services to be developed and modified even in Java-centric architectures to improve the shortcomings of Java-centric enterprise development because artificial intelligence platforms are concentrated in the pipeline. In addition, based on the proposed environment, we propose a more accurate prediction system in the deep running architecture environment that has been previously learned through image forecasting experiments. Experiments show 95.23% accuracy in the image example provided for deep running to be performed, and the proposed model shows 96.54% accuracy compared to other similar models.

• Journal of The Korean Association of Information Education
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• v.24 no.1
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• pp.49-57
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• 2020

The society we are living in has being changed to the age of the intelligent information society after passing through the knowledge-based information society in the early 21st century. In this study, we have developed the instructional model for software education based on the machine learning which is a field of artificial intelligence(AI) to enhance the core competencies of learners required in the intelligent information society. This model is focusing on enhancing the core competencies through the process of problem-solving as well as reducing the burden of learning about AI itself. The specific stages of the developed model are consisted of seven levels which are 'Problem Recognition and Analysis', 'Data Collection', 'Data Processing and Feature Extraction', 'ML Model Training and Evaluation', 'ML Programming', 'Application and Problem Solving', and 'Share and Feedback'. As a result of applying the developed model in this study, we were able to observe the positive response about learning from the students and parents. We hope that this research could suggest the future direction of not only the instructional design but also operation of software education program based on machine learning.