• Journal of the Health Care and Life Science
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• v.10 no.1
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• pp.1-14
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• 2022

This study is a study on the possibility of using big data-related education programs in health and medical administration-related departments using health and medical big data. This paper intends to examine the health and medical big data from five perspectives. 1st, in addition to the aforementioned 'Health and Medical Big Data Open System', I would like to examine the characteristics and application technologies of public big data disclosed by 'Korea Welfare Panel', 'Public Big Data', 'Seoul City Big Data', 'Statistical Office Big Data', etc. 2nd, it is intended to examine the appropriateness of whether the applicable health and medical big data can be used as living data in regular subjects of health and medical administration and health information related departments of junior colleges. 3rd, we want to select the most appropriate tool for classroom lectures using existing statistical processing packages and programming languages. Fourth, finally, by using verified health and medical big data and appropriate tools, we want to test the possibility of expressing graphs, etc. in class and the steps from writing a report. 4th, I would like to describe the relative advantages of R language that can satisfy portability, installability, cost effectiveness, compatibility, and big data processing potential.

• Smart Structures and Systems
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• v.26 no.3
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• pp.277-290
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• 2020

Disasters, including earthquakes and landslides, have enormous economic and social losses besides their impact on environmental disruption. Iran, and particularly its Western part, is known as an earthquake susceptible area due to numerous strong ground motions. Studying ecological changes due to climate change can improve the public and expert sector's awareness and response to future disastrous events. Synthetic Aperture Radar (SAR) data and Interferometric Synthetic Aperture Radar (InSAR) technologies are appropriate tools for modeling and surface deformation modeling. This paper proposes an efficient approach to detect ground deformation changes using Sentinel-1A. The focal point of this research is to map the ground surface deformation modeling is presented using InSAR technology over Sarpol-e Zahab on 25^th November 2018 as a study case. For surface deformation modeling and detection of the ground movement due to earthquake SARPROZ in MATLAB programming language is used and discussed. Results show that there is a general ground movement due to the Sarpol-e Zahab earthquake between -7 millimeter to +18 millimeter in the study area. This research verified previous researches on the advanced image analysis techniques employed for mapping ground movement, where InSAR provides a reliable tool for assisting engineers and the decision-maker in choosing proper policies in a time of disasters. Based on the result, 574 out of 682 damaged buildings and infrastructures due to the 2017 Sarpol-e Zahab earthquake have moved from -2 to +17 mm due to the 2018 earthquake with a magnitude of 6.3 Richter. Results show that mountainous areas have suffered land subsidence, where urban areas had land uplift.

• Journal of the Korea Society of Computer and Information
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• v.17 no.8
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• pp.189-201
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• 2012

The purpose of this study is to develop an effective teaching model for the "Problem solving methods and procedures" section in the revised academic high school informatics curriculum, verify its effectiveness, make the subject more effective and appealing to teachers as well as students. The model includes a middle school level informatics curriculum for the students who have yet to learn the section. This development follows the ADDIE model, and the Python programming language is adopted for the model. Using the model, classes were conducted with two groups: high school computer club students and undergraduate students majoring in computer education. Of the undergraduate students 75% responded positively to the model. This model was applied in the actual high school classroom teaching for 23 class-hours in the spring semester 2012. The Pearson correlation coefficient that verifies the correspondence between the PSI score and the informatics midterm exam grade is .247, which reflects a weak positive correlation. The result of the study showed that the developed teaching model is an effective tool in educating students about the "problem solving methods and procedures". The model is to be a cornerstone of teaching/learning plans for informatics at academic high school as well as training materials for pre-service teachers.

• Communications of Mathematical Education
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• v.33 no.1
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• pp.1-19
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• 2019

This study deals with the case of student-centered discrete mathematics class with cyber lab. First, we provided lecture notes and cyber labs we developed. In particular, discrete mathematics is a course that covers the principles of algorithms. The purpose of this study is to provide students with basic mathematics, aiming to actively participate in the learning process, to improve their abilities and to reach the ultimate goal of student success with confidence. Second, based on interactions, students were able to prepare for the lectures, review, question, answer, and discussion through an usual learning management system of the school. Third, all the students generated materials through one semester, which were reported, submitted, presented and evaluated. It was possible to improve the learning effectiveness through the discussions and implementation of using some easy open source programming language and codes. Our discrete math laboratory could be practiced without any special knowledge of coding. These lecture models allow students to develop critical thinking skills while describing and presenting their learning and problem-solving processes. We share our experience and our materials including lecture note and cyber lab as well as a possible model of student-centered mathematics class that does not give too much of work load for instructors. This study shares a model that demonstrates that any professor will be able to have an individualized, customized, and creative discrete education without spending much of extra time and assistant, unlike previous research.

• The Journal of the Korea Contents Association
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• v.8 no.11
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• pp.412-425
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• 2008

One of the important elements for improving academic achievement of learners in education through e-learning is to support learners to study by finding questions they want with providing various evaluation questions. However, most of question retrieval systems usually depend on keyword search based on only a syntactical analysis and/or a hierarchical browsing system classified by the topics of subjects. In such a system it is not easy to find integrative questions associated with each other. In order to improve this problem, in this paper we proposed a question management and retrieval system which allows users to easily manage questions and also to effectively find questions for study on the Web. Then, we implemented a system that gives to access questions for the domain of C language programming. The system makes it possible to easily search questions related to not only a single theme but also questions integrated by interrelationship between topics and questions. This is done by supporting to be able to retrieve questions according to conceptual interrelationships between questions from user query. Consequently, it is expected that the proposed system will provide learners to understand the basic theories and the concepts of the subjects as well as to improve the ability of comprehensive knowledge utilization and problem-solving.

• Journal of Intelligence and Information Systems
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• v.25 no.1
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• pp.1-19
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• 2019

Artificial intelligence (AI) is one of the main driving forces leading the Fourth Industrial Revolution. The technologies associated with AI have already shown superior abilities that are equal to or better than people in many fields including image and speech recognition. Particularly, many efforts have been actively given to identify the current technology trends and analyze development directions of it, because AI technologies can be utilized in a wide range of fields including medical, financial, manufacturing, service, and education fields. Major platforms that can develop complex AI algorithms for learning, reasoning, and recognition have been open to the public as open source projects. As a result, technologies and services that utilize them have increased rapidly. It has been confirmed as one of the major reasons for the fast development of AI technologies. Additionally, the spread of the technology is greatly in debt to open source software, developed by major global companies, supporting natural language recognition, speech recognition, and image recognition. Therefore, this study aimed to identify the practical trend of AI technology development by analyzing OSS projects associated with AI, which have been developed by the online collaboration of many parties. This study searched and collected a list of major projects related to AI, which were generated from 2000 to July 2018 on Github. This study confirmed the development trends of major technologies in detail by applying text mining technique targeting topic information, which indicates the characteristics of the collected projects and technical fields. The results of the analysis showed that the number of software development projects by year was less than 100 projects per year until 2013. However, it increased to 229 projects in 2014 and 597 projects in 2015. Particularly, the number of open source projects related to AI increased rapidly in 2016 (2,559 OSS projects). It was confirmed that the number of projects initiated in 2017 was 14,213, which is almost four-folds of the number of total projects generated from 2009 to 2016 (3,555 projects). The number of projects initiated from Jan to Jul 2018 was 8,737. The development trend of AI-related technologies was evaluated by dividing the study period into three phases. The appearance frequency of topics indicate the technology trends of AI-related OSS projects. The results showed that the natural language processing technology has continued to be at the top in all years. It implied that OSS had been developed continuously. Until 2015, Python, C ++, and Java, programming languages, were listed as the top ten frequently appeared topics. However, after 2016, programming languages other than Python disappeared from the top ten topics. Instead of them, platforms supporting the development of AI algorithms, such as TensorFlow and Keras, are showing high appearance frequency. Additionally, reinforcement learning algorithms and convolutional neural networks, which have been used in various fields, were frequently appeared topics. The results of topic network analysis showed that the most important topics of degree centrality were similar to those of appearance frequency. The main difference was that visualization and medical imaging topics were found at the top of the list, although they were not in the top of the list from 2009 to 2012. The results indicated that OSS was developed in the medical field in order to utilize the AI technology. Moreover, although the computer vision was in the top 10 of the appearance frequency list from 2013 to 2015, they were not in the top 10 of the degree centrality. The topics at the top of the degree centrality list were similar to those at the top of the appearance frequency list. It was found that the ranks of the composite neural network and reinforcement learning were changed slightly. The trend of technology development was examined using the appearance frequency of topics and degree centrality. The results showed that machine learning revealed the highest frequency and the highest degree centrality in all years. Moreover, it is noteworthy that, although the deep learning topic showed a low frequency and a low degree centrality between 2009 and 2012, their ranks abruptly increased between 2013 and 2015. It was confirmed that in recent years both technologies had high appearance frequency and degree centrality. TensorFlow first appeared during the phase of 2013-2015, and the appearance frequency and degree centrality of it soared between 2016 and 2018 to be at the top of the lists after deep learning, python. Computer vision and reinforcement learning did not show an abrupt increase or decrease, and they had relatively low appearance frequency and degree centrality compared with the above-mentioned topics. Based on these analysis results, it is possible to identify the fields in which AI technologies are actively developed. The results of this study can be used as a baseline dataset for more empirical analysis on future technology trends that can be converged.

• Journal of Gifted/Talented Education
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• v.25 no.2
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• pp.339-358
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• 2015

This study was to examine perceptions of information technology(IT) competencies among gifted and non-gifted students(i.e., information science high school students and technical high school students). Of the 370 high school students surveyed from 3 high schools(i.e., gifted academy, information science high school, and technical high school) in three metropolitan cities, Korea, 351 students completed and returned the questionnaires yielding a total response rate of 94.86%. High school students recognized the IT professional competence as being most important when recruiting IT employees. And they considered that practice-oriented education was the most importantly needed to improve their IT skills. In addition, the most important sub-factors of IT core competencies among gifted academy students and information science high school students were basic software skills. Also Technical high school students responded that the main network and security capabilities were the most importantly needed to do so. Finally, the most appropriate training courses for enhancing IT competencies were recognized differently among gifted and non-gifted students. Gifted academy students responded that the 'algorithm' was the mostly needed for enhancing IT competencies, whereas information science high school students responded that 'data structures' and 'computer architecture' were mostly needed to do. For technical high school students, they responded that a 'programming language' course was the most needed to do so. Results are discussed in relations to IT corporate and school settings.