• Journal of Intelligence and Information Systems
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• v.21 no.4
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• pp.79-92
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• 2015

Knowledge map is widely used to represent knowledge in many domains. This paper presents a method of integrating the national R&D data and assists of users to navigate the integrated data via using a knowledge map service. The knowledge map service is built by using a lightweight ontology and a topic modeling method. The national R&D data is integrated with the research project as its center, i.e., the other R&D data such as research papers, patents, and reports are connected with the research project as its outputs. The lightweight ontology is used to represent the simple relationships between the integrated data such as project-outputs relationships, document-author relationships, and document-topic relationships. Knowledge map enables us to infer further relationships such as co-author and co-topic relationships. To extract the relationships between the integrated data, a Relational Data-to-Triples transformer is implemented. Also, a topic modeling approach is introduced to extract the document-topic relationships. A triple store is used to manage and process the ontology data while preserving the network characteristics of knowledge map service. Knowledge map can be divided into two types: one is a knowledge map used in the area of knowledge management to store, manage and process the organizations' data as knowledge, the other is a knowledge map for analyzing and representing knowledge extracted from the science & technology documents. This research focuses on the latter one. In this research, a knowledge map service is introduced for integrating the national R&D data obtained from National Digital Science Library (NDSL) and National Science & Technology Information Service (NTIS), which are two major repository and service of national R&D data servicing in Korea. A lightweight ontology is used to design and build a knowledge map. Using the lightweight ontology enables us to represent and process knowledge as a simple network and it fits in with the knowledge navigation and visualization characteristics of the knowledge map. The lightweight ontology is used to represent the entities and their relationships in the knowledge maps, and an ontology repository is created to store and process the ontology. In the ontologies, researchers are implicitly connected by the national R&D data as the author relationships and the performer relationships. A knowledge map for displaying researchers' network is created, and the researchers' network is created by the co-authoring relationships of the national R&D documents and the co-participation relationships of the national R&D projects. To sum up, a knowledge map-service system based on topic modeling and ontology is introduced for processing knowledge about the national R&D data such as research projects, papers, patent, project reports, and Global Trends Briefing (GTB) data. The system has goals 1) to integrate the national R&D data obtained from NDSL and NTIS, 2) to provide a semantic & topic based information search on the integrated data, and 3) to provide a knowledge map services based on the semantic analysis and knowledge processing. The S&T information such as research papers, research reports, patents and GTB are daily updated from NDSL, and the R&D projects information including their participants and output information are updated from the NTIS. The S&T information and the national R&D information are obtained and integrated to the integrated database. Knowledge base is constructed by transforming the relational data into triples referencing R&D ontology. In addition, a topic modeling method is employed to extract the relationships between the S&T documents and topic keyword/s representing the documents. The topic modeling approach enables us to extract the relationships and topic keyword/s based on the semantics, not based on the simple keyword/s. Lastly, we show an experiment on the construction of the integrated knowledge base using the lightweight ontology and topic modeling, and the knowledge map services created based on the knowledge base are also introduced.

• Archives of design research
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• v.13 no.1
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• pp.219-225
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• 2000

Most of designers use applied software of computer programs instead of traditional tools such as brushes, poster colors, etc. for drawing and designing. For example applied software programs for design are applied the workings printing, presentation, movie, animation, character design as well as industrial design. Especially, quality of applied software programs in the field of visual communication design influence on the design results in future. Therefore, many college attempt to invest budget to inhrence the quality of software program in design education. However, effectiveness of investment is lowered due to the professional lack of software knowledge. This study tries to explore how the investment for software program in visual communication design becomes more effective, and to suggest how the order of software program, design curriculum through the affective computer usage in design education will be more useful than now. By comparing and contrasting the different cases in the computer environments of the colleges, this study was processing, the result of this study will contribute to the design education of visual communication.

• Journal of Popular Narrative
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• v.27 no.3
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• pp.127-150
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• 2021

This study focuses on analyzing the epic characteristics of a korean sports cartoon called "Burning Ground" in the 1970s. Through this, we would like to reveal that only "Burning Ground" has a unique narrative. We hope that such research will accumulate and serve as the basis for the study of Korean sports cartoon. In the 1970s and 1980s, Korean sports cartoons were narratives of the main characters. The story of the family is central to the narrative. Family revenge is mainly the central narrative. Plural narratives are serious, and sports act as auxiliary narratives. It uses 'Spocon', a characteristic of Japanese sports cartoons, to show its efforts to get revenge. Therefore, it is extremely rare to use professional knowledge in Korean sports cartoons in the 1970s. Burning Ground uses an escalating system to construct incremental narratives. The three-dimensional narrative is composed by utilizing various narratives of surrounding characters. The use of expertise in football is a feature of the 1990s, and showing this in the 1970s means that the work is ahead of its time. There are limitations of Japanese cartoon theft and plagiarism. However, through this, it provides evidence to examine the relationship between Korea and Japan. And timeless epic speciality must be recognized. The study is meaningful in that it can broaden the perspective of Korean cartoon research in the 1970s.

• Journal of The Korean Association For Science Education
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• v.38 no.1
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• pp.1-9
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• 2018

The goal of this study is to analyze and understand invention classes, student's experiences, and motivation to suggest a future direction for K-12 Maker Education in Makerspace. We collected qualitative data using open-ended survey from 100 Invention class students. Through data analysis, we could explore perceptions of students about their inventions and meaningful experiences when they used technologies for enhancing their idea and problem finding ability using interpretive approach. We found that the main themes are (1) Perception and motivation to join in the invention class courses, (2) Perception and the normal method of obtaining the idea on invention, (3) Finding new technology for enhancing of knowledge for the invention, and (4) Relevance of the learning experience and invention activities in Makerspace. As a result of this study, we found that the educational programs using technologies should focus on supporting implement of prototypes instead of helping students create their own ideas in Makerspace.

• Korean Journal of Construction Engineering and Management
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• v.9 no.6
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• pp.257-267
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• 2008

In order to encourage construction practitioners to acknowledge failures and disseminate the information, the failure information must be documented and accumulated with a well-structured format, which contains not only the fact and result but also the circumstance and cause of the failure. In the Korean construction industry, many failures are not explained clearly and often not even reported publicly, partly because due to the lack of understanding positive aspects of failures, which can improve construction practices as a result of learning from failures. The purpose of this study is to develop a web-based construction failure information system using the case-based reasoning techniques, which can systematically accumulate, manage, and share the valuable failure information using a structured failure cases database. It can be utilized for planning proactive solutions on future failures by searching the very similar past failure cases.

• The Journal of the Convergence on Culture Technology
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• v.10 no.4
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• pp.607-612
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• 2024

Generative AI is a type of artificial intelligence technology that produces various types of data. With the success of ChatGPT, the generative AI market is blooming. As the generative AI market develops, generative AI is being applied in various industries. In this paper, we discuss the trends, applications, and directions for improvement. Currently, generative AI is trained on domain knowledge and data, and it is evolving towards Vertical AI. In the future, generative AI could be extended to AGI, which makes decisions and processes on its own like a human, to be used flexibly in various environments.

• Journal of Intelligence and Information Systems
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• v.28 no.2
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• pp.207-235
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• 2022

In a knowledge-based society where knowledge and information industries are the main pillars of the economy, knowledge sharing and diffusion and its systematic management are recognized as essential strategies for improving national competitiveness and sustainable social development. In the field of Information Systems (IS) research, where the convergence of information technology and management takes place in various ways, the evolution of knowledge occurs only when researchers cooperate in turning old knowledge into new knowledge from the perspective of the scientific knowledge network. In particular, it is possible to derive new insights by identifying topics of interest in the relevant research field, applied methodologies, and research trends through network-based interdisciplinary graftings such as citations, co-authorships, and keywords. In previous studies, various attempts have been made to understand the structure of the knowledge system and the research trends of the relevant community by revealing the relationship between research topics, methodologies, and co-authors. However, most studies have compared two or more journals and been limited to a certain period; hence, there is a lack of research that looked at research trends covering the entire history of IS research. Therefore, this study was conducted in the following order for all the papers (from its first issue in 1977 to the first quarter of 2022) published in the MIS Quarterly (MISQ) Journal, which plays a leading role in revealing knowledge in the IS research field: (1) After extracting keywords, (2) classifying the extracted keywords into research topics, methodologies, and theories, and (3) using topic modeling and keyword network analysis in order to identify the changes from the beginning to the present of the IS research in a chronological manner. Through this study, it is expected that by examining the changes in IS research published in MISQ, the developing patterns of IS research can be revealed, and a new research direction can be presented to IS researchers, nurturing the sustainability of future research.

• Communications of Mathematical Education
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• v.35 no.2
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• pp.153-172
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• 2021

Various competencies such as critical thinking, systems thinking, problem solving competence, communication skill, and data literacy are likely to be required in the 4th industrial revolution. The competency regarding data literacy is one of those competencies. To nurture citizens who will live in the future, it is timely to consider research on teacher education for supporting teachers' development of statistical thinking as well as statistical knowledge. Therefore, in this study we developed and implemented a data analysis project for pre-service teachers to understand their changes in statistical knowledge in addition to their experiences of data-driven decision making process that required them utilizing their statistical thinking. We used a mixed method (i.e., sequential explanatory design) research to analyze the quantitative and qualitative data collected. The findings indicated that pre-service teachers have low knowledge level of their understanding on the relationship between population means and sample means, and estimation of the population mean and its interpretation. When it comes to the data-driven decision making process, we found that the pre-service teachers' experiences varied even when they worked as a small group for the project. We end this paper by presenting implications of the study for the fields of teacher education and statistics education.

• Journal of Korea Water Resources Association
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• v.56 no.12
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• pp.939-953
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• 2023

Shallow water equations (SWE) serve as fundamental equations governing the movement of the water. Traditional numerical approaches for solving these equations generally face various challenges, such as sensitivity to mesh generation, and numerical oscillation, or become more computationally unstable around shock and discontinuities regions. In this study, we present a novel approach that leverages the power of physics-informed neural networks (PINNs) to approximate the solution of the SWE. PINNs integrate physical law directly into the neural network architecture, enabling the accurate approximation of solutions to the SWE. We provide a comprehensive methodology for formulating the SWE within the PINNs framework, encompassing network architecture, training strategy, and data generation techniques. Through the results obtained from experiments, we found that PINNs could be an accurate output solution of SWE when its results were compared with the analytical method. In addition, PINNs also present better performance over the Artificial Neural Network. This study highlights the transformative potential of PINNs in revolutionizing water resources research, offering a new paradigm for accurate and efficient solutions to the SVE.

• Asia-Pacific Journal of Business Venturing and Entrepreneurship
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• v.17 no.2
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• pp.53-64
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• 2022

The purpose of this study is to analyze the difference in importance and performance of the university start-up support system focusing on D university students to grasp the perception of the start-up support system provided the university from the perspective of students who are real users. Through this, a plan for qualitative growth and advancement of the university start-up system was derived using the IPA (importance-performance analysis) analysis. The findings are as follows. The importance of all elements of university start-up education and start-up support system is higher than the performance, which means that the start-up education and support programs currently implemented by universities are recognized as important, but do not play a big role in terms of performance for students. In addition, the highest priority factors for improvement in the importance-performance matrix were funding and investment support, start-up space and facilities support, management advisory, patent and intellectual property support, and entrepreneurship field practice. Therefore, This study can be used as objective data to identify the factors that universities should focus on and establish a start-up support system from a long-term perspective, and to build and operate a start-up support system that reflects the needs of students.