• Korean Journal of Childcare and Education
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• v.14 no.6
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• pp.219-239
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• 2018

Objective: This study aims to analyze the research trend of domestic child care education, and to seek directions for future research related to child care education based on analysis results. Methods: A total of 91 theses were selected in journals released in Korea from January 2006 to August 2018. The analysis standards for the research trend were established as research period, theme, target and method. Results: First, the amount of research on child care education has gradually increased since 2006. Second, action research for improvement was the most common research theme for child care education, while activities utilizing fairy tales and picture books were the most frequently used education activities. Third, research that targeted five-year-olds accounted for the largest part of research. Fourth, when it came to research type, most research was based on quantitative research. Conclusion/Implications: Based on the analysis results above, the direction for the development of future child care education and relevant research was discussed.

• Current Optics and Photonics
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• v.7 no.6
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• pp.761-765
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• 2023

We analyzed the absorption spectra of acetone in the 3.37 ㎛ mid-infrared range using the off-axis integrated cavity output spectroscopy technique to develop a real-time, in-line breath analysis device. The linear relationship between acetone concentration and absorption increase was confirmed as 0.32%/ppm, indicating that the developed device allows for a quantitative analysis of acetone concentration in exhaled breath. To further confirm the feasibility of using our device for breath analysis, we measured the acetone concentration of human breath samples at the sub-ppm level.

• Knowledge Management Research
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• v.19 no.2
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• pp.47-68
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• 2018

Business environment is shifting from industrial economy to knowledge based economy. Enterprises go through numerous trials for successful management in changing environment. Along with trial tests, research area has been growing simultaneously. Unlike initial research which focused on basic concepts such as: form of business model and success points. Current research emphasizes on actualization of business that enterprises plan, which brought academic research with perplex form of knowledge structure. On the other hand, there is limitation in understanding business model systematically due to preceding research primarily centered on analyzing definition and case study. In order to analyze knowledge structure, this study utilized social network analysis based on "relationship". For the analysis, 13,412 keywords were extracted from 36years worth of article or research related to business model stored in SCOPUS database. From the analysis, it was shown core research subject was INNOVATION and the number of co-authors has increased due to the academic diversity. Business model research is divided into five sub-categories (E-commerce, SMEs, sustainability, open-source, and e-book). Through cognitive map analysis on each of research characteristics of sub-category, it has shown that E-commerce, SMEs, sustainability, and open-source are core categories.

• Korea Trade Review
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• v.45 no.5
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• pp.239-260
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• 2020

This research was conducted on 176 GVCs-related research papers listed in the Index of Korean Academic Writers. The analysis methodology used the keyword network analysis methodology of big data analysis. For the comprehensive analysis of research trends, the research trends through word frequency (TF), important topic (TF-IDF), and topical modeling were analyzed in 176 papers. In addition, the research period of GVCs was divided into the early stages of the first study (2003-2014), the second phase of the study (2015-2017), and the third phase of the study (2018-2020). According to the comprehensive analysis, the GVCs research was conducted with the keyword 'value added' as the center, focusing on the keywords of export (trade), Korea, business, influence, and production. Major research topics were 'supporting corporate cooperation and capacity building' and 'comparative advantage with added value of overseas direct investment'. According to the analysis of major period-specific research trends, GVCs were studied in the early stages of the first phase of the study with global value chain trends and corporate production strategies. In the second research propulsion period, research was done in terms of trade value added. In the recent third phase of the study, small and medium-sized enterprises actively participated in the global value chain and actively researched ways to support the government. Through this study, the importance of the global value chain has been confirmed quantitatively and qualitatively, and it is recognized as an important factor to be considered in the strategy of enhancing industrial competitiveness and entering overseas markets. In particular, small and medium-sized companies' participation in the global value chain and support measures are being presented as important research topics in the future.

• Journal of Electrical Engineering and Technology
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• v.9 no.1
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• pp.114-120
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• 2014

In this paper, a method for multi-physics analysis of the temperature-dependent properties of an oil-immersed transformer is discussed. To couple thermal fields with electromagnetic and fluid fields, an algorithm employing a user defined function (UDF) is proposed. Using electromagnetic analysis, electric power loss dependent on temperature rise is calculated; these are used as input data for multi-physics analysis in order to predict the temperature rise. A heat transfer coefficient is applied only at the outermost boundary between transformer and the atmosphere in order to reduce the analysis region. To verify the validity of the proposed method, the predicted temperature rises in high-voltage (HV) and low-voltage (LV) windings and radiators were compared with the experimental values.

• Genomics & Informatics
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• v.18 no.4
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• pp.46.1-46.4
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• 2020

We developed the BaSDAS (Barcode-Seq Data Analysis System), a GUI-based pooled knockout screening data analysis system, to facilitate the analysis of pooled knockout screen data easily and effectively by researchers with limited bioinformatics skills. The BaSDAS supports the analysis of various pooled screening libraries, including yeast, human, and mouse libraries, and provides many useful statistical and visualization functions with a user-friendly web interface for convenience. We expect that BaSDAS will be a useful tool for the analysis of genome-wide screening data and will support the development of novel drugs based on functional genomics information.

• Perspectives in Nursing Science
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• v.16 no.1
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• pp.12-24
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• 2019

Purpose: This study examined the suitability of using text network analysis (TNA) methodology for topic analysis of academic papers related to nursing. Methods: TNA background theories, software programs, and research processes have been described in this paper. Additionally, the research methodology that applied TNA to the topic analysis of the academic nursing papers was analyzed. Results: As background theories for the study, we explained information theory, word co-occurrence analysis, graph theory, network theory, and social network analysis. The TNA procedure was described as follows: 1) collection of academic articles, 2) text extraction, 3) preprocessing, 4) generation of word co-occurrence matrices, 5) social network analysis, and 6) interpretation and discussion. Conclusion: TNA using author-keywords has several advantages. It can utilize recognized terms such as MeSH headings or terms chosen by professionals, and it saves time and effort. Additionally, the study emphasizes the necessity of developing a sophisticated research design that explores nursing research trends in a multidimensional method by applying TNA methodology.

• ETRI Journal
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• v.46 no.1
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• pp.137-153
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• 2024

This study introduces a new approach in Korean morphological analysis combining dictionary-based techniques with Transformer-based deep learning models. The key innovation is the use of a BERT-based reranking system, significantly enhancing the accuracy of traditional morphological analysis. The method generates multiple suboptimal paths, then employs BERT models for reranking, leveraging their advanced language comprehension. Results show remarkable performance improvements, with the first-stage reranking achieving over 20% improvement in error reduction rate compared with existing models. The second stage, using another BERT variant, further increases this improvement to over 30%. This indicates a significant leap in accuracy, validating the effectiveness of merging dictionary-based analysis with contemporary deep learning. The study suggests future exploration in refined integrations of dictionary and deep learning methods as well as using probabilistic models for enhanced morphological analysis. This hybrid approach sets a new benchmark in the field and offers insights for similar challenges in language processing applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4467-4488
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• 2014

The bibliometric analysis is widely used for understanding research domains, trends, and knowledge structures in a particular field. The analysis has majorly been used in the field of information science, and it is currently applied to other academic fields. This paper describes the analysis of academic literatures for classifying research domains and for suggesting empty research areas in the telecommunications policy. The application software is developed for retrieving Thomson Reuters' Web of Knowledge (WoK) data via web services. It also used for conducting text mining analysis from contents and citations of publications. We used three text mining techniques: the Keyword Extraction Algorithm (KEA) analysis, the co-occurrence analysis, and the citation analysis. Also, R software is used for visualizing the term frequencies and the co-occurrence network among publications. We found that policies related to social communication services, the distribution of telecommunications infrastructures, and more practical and data-driven analysis researches are conducted in a recent decade. The citation analysis results presented that the publications are generally received citations, but most of them did not receive high citations in the telecommunications policy. However, although recent publications did not receive high citations, the productivity of papers in terms of citations was increased in recent ten years compared to the researches before 2004. Also, the distribution methods of infrastructures, and the inequity and gap appeared as topics in important references. We proposed the necessity of new research domains since the analysis results implies that the decrease of political approaches for technical problems is an issue in past researches. Also, insufficient researches on policies for new technologies exist in the field of telecommunications. This research is significant in regard to the first bibliometric analysis with abstracts and citation data in telecommunications as well as the development of software which has functions of web services and text mining techniques. Further research will be conducted with Big Data techniques and more text mining techniques.

• Plant Biotechnology Reports
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• v.3 no.1
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• pp.87-93
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• 2009

To determine whether pattern recognition based on metabolite fingerprinting for whole cell extracts can be used to discriminate cultivars metabolically, leaves and fruits of five commercial strawberry cultivars were subjected to Fourier transform infrared (FT-IR) spectroscopy. FT-IR spectral data from leaves were analyzed by principal component analysis (PCA) and Fisher's linear discriminant function analysis. The dendrogram based on hierarchical clustering analysis of these spectral data separated the five commercial cultivars into two major groups with originality. The first group consisted of Korean cultivars including 'Maehyang', 'Seolhyang', and 'Gumhyang', whereas in the second group, 'Ryukbo' clustered with 'Janghee', both Japanese cultivars. The results from analysis of fruits were the same as of leaves. We therefore conclude that the hierarchical dendrogram based on PCA of FT-IR data from leaves represents the most probable chemotaxonomical relationship between cultivars, enabling discrimination of cultivars in a rapid and simple manner.