• Journal of Korean Society of Archives and Records Management
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• v.24 no.1
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• pp.31-46
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• 2024

This study provides a synthesis of the fundamental concepts of "art archives" and "archival art" while undertaking a reconsideration of the latter. Archival art refers to "artworks or art practices that utilize archival structures or methodologies." Accepted as a new trend in contemporary art, archival art is evaluated as a counternarrative and reconstructs histories that are marginalized and omitted from the public sphere. This approach reveals the contradictory nature of criticizing the contemporary archive from an anti-archival perspective while simultaneously presenting the archive as a core identity of the work. Given the limited research on archival art, often with potential contradictions regarding record authenticity, this study expands the concept of archival art, includes archaeological aspects, classifies types, and analyzes their characteristics. By approaching artists' use of archives from a traditional archaeological lens, this study broadens the scope of the examination.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.21 no.7
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• pp.607-615
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• 2020

The purpose of this study was to analyze the research status and trends related to the industrial mathematics based on text mining techniques with a sample of 4910 papers collected in the SIAM Journal on Applied Mathematics from 1970 to 2019. The R program was used to collect titles, abstracts, and key words from the papers and to analyze topic modeling techniques based on LDA algorithm. As a result of the coherence score on the collected papers, 20 topics were determined optimally using the Gibbs sampling methods. The main results were as follows. First, studies on industrial mathematics were conducted in a variety of mathematics fields, including computational mathematics, geometry, mathematical modeling, topology, discrete mathematics, probability and statistics, with a focus on analysis and algebra. Second, 5 hot topics (mathematical biology, nonlinear partial differential equation, discrete mathematics, statistics, topology) and 1 cold topic (probability theory) were found based on time series regression analysis. Third, among the fields that were not reflected in the 2015 revised mathematics curriculum, numeral system, matrix, vector in space, and complex numbers were extracted as the contents to be covered in the high school mathematical curriculum. Finally, this study suggested strategies to activate industrial mathematics in Korea, described the study limitations, and proposed directions for future research.

• Journal of Platform Technology
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• v.11 no.4
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• pp.19-34
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• 2023

In order to identify the trends and insights of 'startups' in the global era, we conducted an in-depth trend analysis of the global startup ecosystem using Google Trends, a big data analysis platform. For the validity of the analysis, we verified the correlation between the keywords 'startup' and 'global' through BIGKinds. We also conducted a network analysis based on the data extracted using Google Trends to determine the frequency of searches for the keyword or term 'startup'. The results showed a strong positive linear relationship between the keywords, indicating a statistically significant correlation (correlation coefficient: +0.8906). When exploring global startup trends using Google Trends, we found a terribly similar linear pattern of increasing and decreasing interest in each country over time, as shown in Figure 4. In particular, startup interest was low in the range of 35 to 76 from mid-2020 due to the COVID-19 pandemic, but there was a noticeable upward trend in startup interest after March 2022. In addition, we found that the interest in startups in each country except South Korea is very similar, and the related topics are startup company, technology, investment, funding, and keyword search terms such as best startup, tech, business, invest, health, and fintech are highly correlated.

• Korean Journal of Child Education & Care
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• v.18 no.2
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• pp.147-165
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• 2018

The purpose of this study was to investigate how to develop of pre-service childcare teachers' perception about the image of childcare center teachers and self-image. In this study, participants' self-analysis method and in-depth interview were adopted to analyze the aspects of pre-service teachers' teacher image. Also, the narrative of pre-service teachers' a famous painting analysis were reported. The results of this study were divided into nine categories. Findings indicated that participants' self-image analysis work made pre-service teachers more enabled them to expend the significance of teacher's image of role in relation to their career decision and future their teacher's job. Moreover, through the experience of self-analysis work the pre-service teachers recognize their own ability to build up unique and healthy image. To foster the ability of pre-service teachers' self- image, special class teaching methods for pre-service teachers should be developed focusing on evoking them to have more positive self-image. This study suggested that self-image analysis work experiences should be emphasized in university class for pre-service teachers.

• The Korean Journal of Archival Studies
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• no.43
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• pp.5-42
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• 2015

Korean wave 3.0 is focused on 'K-Culture' which includes traditional culture, cultural art as well as existing culture contents as a keyword. It considers everything about Korean culture as materials of Korean wave culture contents. Since Korean wave culture contents reflect contemporary social aspect, it needs to preserve those contents as archives and records which have the important value of evidence. With this social environment, this study aims to implement RMS based on AtoM that manages various kinds of Korean wave culture contents through analysis of management situation of those materials. Recently, it is in progress individually to manage them through organizations dealing with korean cultures such as K-Pop, K-Food, K-Movie. However, it has problems in accumulating information and reproducing high quality contents because of lack of coordination among organizations. To solve the problems, this study proposed RMS based on open source software Access to Memory(AtoM) for managing and recording Korean wave culture contents. AtoM provides various functions for managing records and archives such as accumulation, classification, description and browsing. Furthermore AtoM is for free as open source software and easy to implement and use. Thus, this study implemented RMS based on AtoM to methodically manage korean wave culture contents by functional requirements of RMS. Also, this study considered contents relating K-Food as an object to collect, classify, and describe. To describe it, this study selected ISAD(G) standard.

• Journal of Music and Human Behavior
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• v.17 no.1
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• pp.71-96
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• 2020

The purpose of this study was to identify research that included the rhythmic auditory stimulation (RAS) technique and to compare this body of research within the field of music therapy with that in physical therapy. Forty-five studies were identified that were published from January 1999 through November 2018, and these were analyzed in terms of intervention procedure, type of rhythmic cueing, and therapeutic basis described by the researcher. While research in both fields used rhythmic cueing as the primary therapeutic agent, differences were found in the area targeted by training and specific type of rhythmic cueing used. Research conducted in the field of music therapy focused primarily on gait function, while research in the field of physical therapy tended to address gait-related physical issues, such as balance, muscle strength, and proprioceptive sensation as well as gait. While all of the identified studies from the field of music therapy used music for cueing, a metronome was used more often for cueing in physical therapy research. In terms of description of theoretical basis, theory of entrainment was more sufficiently described in music therapy research. These results indicate that while music therapy research maximized the role of various elements of music in intervening in gait function, physical therapy research addressed gait in relation to other physical functions. Considering that both aspects are essential for gait training, this study supports the need for a multidisciplinary approach to neurological rehabilitation with RAS.

• Journal of Practical Agriculture & Fisheries Research
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• v.22 no.1
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• pp.113-129
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• 2020

In this study we examined the topic analysis and correlation analysis by text mining to extract meaningful information or rules from the self introduction letter of freshman at Korea National College of Agriculture and Fisheries in 2020. The analysis items are described in items related to 'academic' and 'in-school activities' during high school. In the text mining results, the keywords of 'academic' items were 'study', 'thought', 'effort', 'problem', 'friend', and the key words of 'in-school activities' were 'activity', 'thought', 'friend', 'club', 'school' in order. As a result of the correlation analysis, the key words of 'thinking', 'studying', 'effort', and 'time' played a central role in the 'academic' item. And the key words of 'in-school activities' were 'thought', 'activity', 'school', 'time', and 'friend'. The results of frequency analysis and association analysis were visualized with word cloud and correlation graphs to make it easier to understand all the results. In the next study, TF-IDF(Term Frequency-Inverse Document Frequency) analysis using 'frequency of keywords' and 'reverse of document frequency' will be performed as a method of extracting key words from a large amount of documents.

• Journal of Intelligence and Information Systems
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• v.20 no.3
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• pp.109-131
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• 2014

As the demand of nuclear power plant equipment is continuously growing worldwide, the importance of handling nuclear strategic materials is also increasing. While the number of cases submitted for the exports of nuclear-power commodity and technology is dramatically increasing, preadjudication (or prescreening to be simple) of strategic materials has been done so far by experts of a long-time experience and extensive field knowledge. However, there is severe shortage of experts in this domain, not to mention that it takes a long time to develop an expert. Because human experts must manually evaluate all the documents submitted for export permission, the current practice of nuclear material export is neither time-efficient nor cost-effective. Toward alleviating the problem of relying on costly human experts only, our research proposes a new system designed to help field experts make their decisions more effectively and efficiently. The proposed system is built upon case-based reasoning, which in essence extracts key features from the existing cases, compares the features with the features of a new case, and derives a solution for the new case by referencing similar cases and their solutions. Our research proposes a framework of case-based reasoning system, designs a case-based reasoning system for the control of nuclear material exports, and evaluates the performance of alternative keyword extraction methods (full automatic, full manual, and semi-automatic). A keyword extraction method is an essential component of the case-based reasoning system as it is used to extract key features of the cases. The full automatic method was conducted using TF-IDF, which is a widely used de facto standard method for representative keyword extraction in text mining. TF (Term Frequency) is based on the frequency count of the term within a document, showing how important the term is within a document while IDF (Inverted Document Frequency) is based on the infrequency of the term within a document set, showing how uniquely the term represents the document. The results show that the semi-automatic approach, which is based on the collaboration of machine and human, is the most effective solution regardless of whether the human is a field expert or a student who majors in nuclear engineering. Moreover, we propose a new approach of computing nuclear document similarity along with a new framework of document analysis. The proposed algorithm of nuclear document similarity considers both document-to-document similarity (${\alpha}$) and document-to-nuclear system similarity (${\beta}$), in order to derive the final score (${\gamma}$) for the decision of whether the presented case is of strategic material or not. The final score (${\gamma}$) represents a document similarity between the past cases and the new case. The score is induced by not only exploiting conventional TF-IDF, but utilizing a nuclear system similarity score, which takes the context of nuclear system domain into account. Finally, the system retrieves top-3 documents stored in the case base that are considered as the most similar cases with regard to the new case, and provides them with the degree of credibility. With this final score and the credibility score, it becomes easier for a user to see which documents in the case base are more worthy of looking up so that the user can make a proper decision with relatively lower cost. The evaluation of the system has been conducted by developing a prototype and testing with field data. The system workflows and outcomes have been verified by the field experts. This research is expected to contribute the growth of knowledge service industry by proposing a new system that can effectively reduce the burden of relying on costly human experts for the export control of nuclear materials and that can be considered as a meaningful example of knowledge service application.

• Korean Journal of Environment and Ecology
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• v.31 no.1
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• pp.30-41
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• 2017

Mammals in Korea have been studied in various fields such as animal science, veterinary medicine, laboratory animal science, ecology, and genetics. As the importance of biodiversity has been emphasized recently, conservation and management of mammals have attracted much public attention. However, in spite of such an increase in scientific research and public interest, it is still difficult to find a report or summary to grasp the trend of mammalian research in Korea. The purpose of this study is to provide the basic data for future plans of the detailed research area and the related policies by grasping the research trends of mammals in Korea. Using text-ming and co-word analysis, we analyzed 392 mammalian research papers published in Korean national journals as of 2015. Our results showed that the number of mammalian research papers published in Korea has gradually increased and that the research target species have also become increasingly diverse. The major research areas identified through text-mining and co-word analysis are (1) evolution/phylogenetics/genetics, (2) environmental science/ecology, (3) embryology/reproductive biology/cell biology, (4) veterinary medicine related to parasites, (5) parasitology related to rodents, (6) bacteriology/virology, (7) anatomy/cell biology/laboratory animal science, (8) veterinary science related to morphology and anatomy, (9) animal science, (10) marine mammalogy, and (11) Chiroptera (bat) research. Environmental science/ecology has been the most active field among the 11 research areas in recent times, and the proportion of research has increased sharply compared to the past. Environmental science/ecology is the core of biodiversity conservation, and as the importance of biodiversity has been emphasized in recent years, researchers' interest in mammal ecology appears to have increased. We expect that the results of this study will be useful for future research plan and related policies on mammals in Korea.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.41-48
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• 2023

In this paper, we propose an analysis of recent trends in the NFT (Non-Fungible Token) industry using topic modeling techniques, focusing on their universal application across various industrial fields. For this study, patent data was utilized to understand industry trends. We collected data on 371 domestic and 454 international NFT-related patents registered in the patent information search service KIPRIS from 2017, when the first NFT standard was introduced, to October 2023. In the preprocessing stage, stopwords and lemmas were removed, and only noun words were extracted. For the analysis, the top 50 words by frequency were listed, and their corresponding TF-IDF values were examined to derive key keywords of the industry trends. Next, Using the LDA algorithm, we identified four major latent topics within the patent data, both domestically and internationally. We analyzed these topics and presented our findings on NFT industry trends, underpinned by real-world industry cases. While previous review presented trends from an academic perspective using paper data, this study is significant as it provides practical trend information based on data rooted in field practice. It is expected to be a useful reference for professionals in the NFT industry for understanding market conditions and generating new items.