• The Journal of Korean Medical History
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• v.14 no.2
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• pp.45-57
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• 2001

Started to get over the political difficulties, Juhee put his heart into solving the mystery of "I-Chingchamdonggye", and the final answer he got was right this. In his coordinate ideology system, he positioned "I-Chingchamdonggye", in other word Dan. No, actually he reconfirmed the uprightness of his ideology system through "I-Chingchamdonggye" and Dan. Justness of Juhee's scholarship which was accused to be false study is ascertained even in trifling Dan and the classics of Dan. The fruit seems to be "I-Chingchamdonggyegoi".

• Korean Journal of English Language and Linguistics
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• v.2 no.1
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• pp.53-76
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• 2002

This paper aims to review Hammond's (1999) analysis of English word stress and propose an alternative by exploring two questions: Why English words display flexible stress patterns and what are the conditions all English words have to obey. As answers to the questions I propose an invisible suffix after words with final stress, foot structures with two levels, and four constraints, two of them are attained by revision of Hammond's. As long as words satisfy the constraints, more than one foot structures are allowed. That is why the English lexicon displays flexibility.

• Journal of the Korean Data and Information Science Society
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• v.16 no.2
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• pp.301-311
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• 2005

This study has conducted to measure the internet banking customer satisfaction using structured equation model. Data was collected by e-mail system. Among survey panel who had experience of using Hanwha-Bank internet banking service, final samples were 2,848 respondents. The results showed that usage convenience and economy factor was most correlated with customer satisfaction. And we found that word-of-mouth behavior was affected customer satisfaction.

• The Journal of Korean Association of Computer Education
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• v.6 no.2
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• pp.9-21
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• 2003

This paper proposes an automatic construction system for transliteration dictionary from English-Korean parallel corpus. The system works in 3 steps: it extracts all nouns from Korean documents as the first step, filters transliterated foreign word nouns out of them with the language identification method as the second step, and extracts the corresponding English words by using a probabilistic alignment method as the final step. Specially, the fact that there is a corresponding English word in most cases, is utilized to extract the purely transliterated part from a Koreans word phrase, which is usually used in combined forms with Korean endings(Eomi) or particles(Josa). Moreover, the direct phonetic comparison is done to the words in two different alphabet systems without converting them to the same alphabet system. The experiment showed that the performance was influenced by the first and the second preprocessing steps; the most efficient model among manually preprocessed ones showed 85.4% recall, 91.0% precision and the most efficient model among fully automated ones got 68.3% recall, 89.2% precision.

• Journal of Korean Society for Quality Management
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• v.50 no.4
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• pp.751-776
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• 2022

Purpose: The purpose of this paper is to present implications by analyzing research trends on CSR, CSV and ESG by text analysis and visual analysis(Comprehensive/ Fields / Years-based) which are big data analyses, by collecting data based on previous studies on CSR, CSV and ESG. Methods: For the collection of analysis data, deep learning was used in the integrated search on the Academic Research Information Service (www.riss.kr) to search for "CSR", "CSV" and "ESG" as search terms, and the Korean abstracts and keyword were scrapped out of the extracted paper and they are organize into EXCEL. For the final step, CSR 2,847 papers, CSV 395 papers, ESG 555 papers derived were analyzed using the Rx64 4.0.2 program and Rstudio using text mining, one of the big data analysis techniques, and Word Cloud for visualization. Results: The results of this study are as follows; CSR, CSV, and ESG studies showed that research slowed down somewhat before 2010, but research increased rapidly until recently in 2019. Research have been found to be heavily researched in the fields of social science, art and physical education, and engineering. As a result of the study, there were many keyword of 'corporate', 'social', and 'responsibility', which were similar in the word cloud analysis. Looking at the frequent keyword and word cloud analysis by field and year, overall keyword were derived similar to all keyword by year. However, some differences appeared in each field. Conclusion: Government support and expert support for CSR, CSV and ESG should be activated, and researches on technology-based strategies are needed. In the future, it is necessary to take various approaches to them. If researches are conducted in consideration of the environment or energy, it is judged that bigger implications can be presented.

• Education of Primary School Mathematics
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• v.26 no.1
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• pp.29-43
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• 2023

The purpose of this study was to synthesize intervention studies, which utilized single case experimental design, on teaching mathematical word problems for elementary school students with disabilities and evaluate each of their methodological rigor. The researchers reviewed all studies from 2000 to 2022 that involved teaching mathematical word problems to individuals with disabilities. A total of 12 studies was included for a final analysis. Most of the interventions were delivered by researchers for about 30-40 minutes per session to elementary school students with disabilities. Schema-based instruction, cognitive-metacognitive strategy, and technology-based instruction were used as intervention methods, and explicit instruction was mostly used in conjunction with them. On the other hand, the researchers found that none of research articles met quality indicators for single case experimental design according to Cook et al. (2015). Limitation and directions for future research were also discussed.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.555-559
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• 2006

This paper will intend to contribute to extracting and storing various form of information on user interests by using structural rules user makes and XML-based word document converting techniques. The system named PPE consists of three essential element. One is converting element which converts word documents like HWP, DOC into XML documents, another is extracting element to prepare structural rules and extract concerned information from XML document by structural rules, and the other is storing element to make final XML document or store it into database system. For word document converting, we developed OCX based word converting daemon. Helping user to extracting information, we developed script language having native function/variable processing engine extended from XSLT. This system can be used in the area of constructing word document contents DB or providing various information service based on RAW word documents. We really applied it to project management system and project result management system.

• Language and Information
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• v.18 no.2
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• pp.59-79
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• 2014

This paper aims at exploring the processing mechanism of filler-gap dependency resolution and feature checking in Korean wh-constructions. Based on their findings on Japanese sentence processing, Aoshima et al. (2004) have argued that the parser posits a gap in the embedded clause in head-final languages, unlike in head-initial languages, where the parser posits a gap in the matrix clause. In order to verify their findings in the Korean context, and to further explore the mechanisms involved in processing Korean wh-constructions, the present study replicated the study done by Aoshima et al., with some modifications of problematic areas in their original design. Sixty-four Korean native speakers were presented Korean sentences containing a wh-phrase in four conditions, with word order and complementizer type as the two main factors. The participants read sentences segment-by-segment, and the reading times at each segment were measured. The reading time analysis showed that there was no such slowdown at the embedded verb in the scrambled conditions as observed in Aoshima et al. Instead, there was a clear indication of the wh-feature checking process in terms of a major slowdown at the relevant region.

• Journal of the Korean Society of Clothing and Textiles
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• v.44 no.3
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• pp.413-426
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• 2020

This study researches the association between associative vocabulary and fashion image language in order to extract ideas that can be used as basic data for design ideas. Classic - avant-garde imaged language were chosen as theme words and each 70 questionnaires per a final image word were used for analysis. We obtained the following results by researching keywords that explained classic image words through a word cloud technique. It was found to have high central representation in the order of suit, classical, basic, music, Chanel, black and traditional. The core key words explaining avant-garde image language were found to have a central representation in the order of : peculiar, huge, Comme des Garçons, artistic, creative, deconstruction and individuality. We extracted the necessary idea dimensions needed for design ideas through associative network graph analysis. In the case of classical image language, it was named as the Mannish Item, Music, Modern Color, and the Traditional Classicality dimensions. In the case of avant-garde image language, it was named as the Key Image, Artistic Aura, Key Design and Designers dimensions.

• Journal of KIISE:Computing Practices and Letters
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• v.13 no.5
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• pp.338-342
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• 2007

In this paper we propose a user adaptive post-processing method to improve the accuracy of speaker dependent, isolated word speech recognition, particularly for mobile devices. Our method considers the recognition result of the basic recognizer simply as a high-level speech feature and processes it further for correct recognition result. Our method learns correlation between the output of the basic recognizer and the correct final results and uses it to correct the erroneous output of the basic recognizer. A multi-layer perceptron model is built for each incorrectly recognized word with high frequency. As the result of experiments, we achieved a significant improvement of 41% in recognition accuracy (41% error correction rate).