• International Journal of Computer Science & Network Security
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• 제24권6호
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• pp.1-7
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• 2024

Comparing text features involves evaluating the "similarity" between texts. It is crucial to use appropriate similarity measures when comparing similarities. This study utilized various techniques to assess the similarities between newspaper articles, including deep learning and a previously proposed method: a combination of Pointwise Mutual Information (PMI) and Word Pair Matching (WPM), denoted as PMI+WPM. For performance comparison, law data from medical research in Japan were utilized as validation data in evaluating the PMI+WPM method. The distribution of similarities in text data varies depending on the evaluation technique and genre, as revealed by the comparative analysis. For newspaper data, non-deep learning methods demonstrated better similarity evaluation accuracy than deep learning methods. Additionally, evaluating similarities in law data is more challenging than in newspaper articles. Despite deep learning being the prevalent method for evaluating textual similarities, this study demonstrates that non-deep learning methods can be effective regarding Japanese-based texts.

• 한국영어학회지:영어학
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• 제4권2호
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• pp.117-149
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• 2004

The paper is to argue against the asymmetric CP-V2 analysis of Old English, according to which finite verbs invariably undergo movement into a clause-final T within subordinate clauses and reach the functional head C within main clauses. The asymmetric CP-V2 analysis, first of all, faces difficulty in explaining a wide range of post-verbal elements within subordinate clauses. To resolve the problem, the analysis has to abandon the obligatoriness of V-to-T movement or introduce various types of extraposition whose status is dubious as a legitimate syntactic operation. Obligatory V-to-T movement in Old English lacks conceptual justification as well. Crosslinguistic evidence reveals that morphological richness in verbal inflection cannot entail overt verb movement. Moreover, the operation is always string-vacuous under the asymmetric CP- V2 analysis and has no effect at the interfaces, in violation of the principle of economy. The distribution of Old English finite verbs in main clauses also undermines the asymmetric CP-V2 analysis. Conceptually speaking, a proper syntactic trigger cannot be confirmed to motivate obligatory verb movement to C. The operation not only gets little support from nominative Case marking, the distribution of expletives, or complementizer agreement but also requires the unconvincing stipulation that expletives as well as sentence-initial subjects result from string-vacuous topicalization. Finally, textual evidence testifies that Old English sometimes permits non-V2 ordering patterns, many of which remain unexplained under the asymmetric CP-V2 analysis.

• 한국의류학회지
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• 제47권3호
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• pp.544-559
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• 2023

Social discourses surrounding diversity, equity, and inclusion (DE&I) in the fashion industry are vital as they extend beyond language and encompass social practices. This study aimed to understand how discourses on DE&I with in the fashion industry are reconstructed and practiced in society. Therefore, this paper analyzed DE&I in the fashion industry, by focusing on the New York Times articles, employing a quantitative research model based on corpus analysis and a qualitative approach through critical discourse analysis. Results of the analysis of textual practice, showed that the New York Times emphasized black individuals as the central discourse and created a critical racial narrative regarding DE&I in the fashion industry characterized by a dichotomy of black vs. white confrontation. Furthermore, results of the discourse practice analysis revealed that the dichotomy of racial confrontation in the New York Times article tended to select the subject of discourse related to racial DE&I in the fashion industry according based on social and historical context. Thirdly, the analytical results of sociocultural practices indicated that the dichotomous racial discourse between black and white, propagated by the New York Times, spread across social media, transforming fashion from an industry to a domain where black individuals struggle for human rights.

• 여성건강간호학회지
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• 제29권2호
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• pp.128-136
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• 2023

Purpose: Topic modeling is a text mining technique that extracts concepts from textual data and uncovers semantic structures and potential knowledge frameworks within context. This study aimed to identify major keywords and network structures for each major topic to discern research trends in women's health nursing published in the Korean Journal of Women Health Nursing (KJWHN) using text network analysis and topic modeling. Methods: The study targeted papers with English abstracts among 373 articles published in KJWHN from January 2011 to December 2021. Text network analysis and topic modeling were employed, and the analysis consisted of five steps: (1) data collection, (2) word extraction and refinement, (3) extraction of keywords and creation of networks, (4) network centrality analysis and key topic selection, and (5) topic modeling. Results: Six major keywords, each corresponding to a topic, were extracted through topic modeling analysis: "gynecologic neoplasms," "menopausal health," "health behavior," "infertility," "women's health in transition," and "nursing education for women." Conclusion: The latent topics from the target studies primarily focused on the health of women across all age groups. Research related to women's health is evolving with changing times and warrants further progress in the future. Future research on women's health nursing should explore various topics that reflect changes in social trends, and research methods should be diversified accordingly.

• Journal of Korea Trade
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• 제24권5호
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• pp.71-86
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• 2020

Purpose - This study investigates research trends by searching for English keywords and abstracts in 1,511 Korean journal articles in the Korea Citation Index from the 2002-2019 period using the term "Port." The study aims to lay the foundation for a more balanced development of port research. Design/methodology - Using abstract and keyword data, we perform frequency analysis and word embedding (Word2vec). A t-SNE plot shows the main keywords extracted using the TextRank algorithm. To analyze which words were used in what context in our two nine-year subperiods (2002-2010 and 2010-2019), we use Scattertext and scaled F-scores. Findings - First, during the 18-year study period, port research has developed through the convergence of diverse academic fields, covering 102 subject areas and 219 journals. Second, our frequency analysis of 4,431 keywords in 1,511 papers shows that the words "Port" (60 times), "Port Competitiveness" (33 times), and "Port Authority" (29 times), among others, are attractive to most researchers. Third, a word embedding analysis identifies the words highly correlated with the top eight keywords and visually shows four different subject clusters in a t-SNE plot. Fourth, we use Scattertext to compare words used in the two research sub-periods. Originality/value - This study is the first to apply abstract and keyword analysis and various text mining techniques to Korean journal articles in port research and thus has important implications. Further in-depth studies should collect a greater variety of textual data and analyze and compare port studies from different countries.

• 한국수학교육학회지시리즈E:수학교육논문집
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• 제32권3호
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• pp.407-433
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• 2018

본 연구의 목적은 담론적 관점에서 수학 교과서를 분석하기 위해 선행 연구를 바탕으로 분석틀을 재구성하고, 중1수학 교과서의 '그래프 정의'에서 단어와 시각적 매개체가 생성하는 의미와 그 통합 관계를 분석하는데 적용하는 것이다. 담론적 관점은 Sfard(2008)의 의사소통학적 관점과 Halliday(1985/2004)의 체계기능언어학을 바탕으로 발전된 사회기호학적 관점이 통합된 것으로 이를 바탕으로 본 연구에서는 단어와 시각적 매개체가 생성하는 의미는 교과서에 구현된 수학을 관념적 메타기능이 실현하는 의미 측면과 학생의 수학적 활동의 참여 유도성을 대인관계적 메타기능이 실현하는 의미 측면으로 구분하여 분석하였고, 단어와 시각적 매개체의 통합 관계는 텍스트적 메타기능 측면에서 분석하였다. 그 결과 첫째, 단어의 관념적 의미는 수학 담론의 밀도가 높았을 뿐 아니라 수학적 활동의 주체가 모호하였고 학생 참여를 요구하는 단어의 대인관계적 의미는 사고보다는 주로 행동 측면이 강조되었다. 시각적 매개체가 구성하는 관념적 의미에서는 내러티브 다이어그램이 결여되었고 대인관계적 의미에서는 정보 제공에 질적 차이가 있었다. 둘째, 단어와 시각적 매개체의 통합 관계는 구체화, 설명, 유사, 보완처럼 다양한 방식을 통한 풍부한 수학 의미 형성을 위해 통합 관계의 다양성을 지향할 필요가 있었다. 이러한 결과는 수학 교과서를 분석하는데 의미를 생성하는 도구로서 단어와 함께 시각적 매개체의 사용을 분석하고 단어와 시각적 매개체의 통합 관계를 분석하였기 때문에 담론적 관점에서 교과서 분석의 새로운 분석틀을 제공한 의미가 있다.

• 영어어문교육
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• 제17권3호
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• pp.161-175
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• 2011

This paper examines Korean EFL high school students' reader responses on an expository text and a narrative text with the same topic. The purpose of the study is to investigate whether they have different reading models depending on the two genres and whether there are any differences depending on the learners' proficiency levels. The analysis focuses on textual, critical, and aesthetic reading models in the reader responses written in English by science-gifted high school students (N=30). The results show that the participants have different reading models in reading an expository text and a narrative text. They tend to read the expository text in a more critical way while reading the narrative text in a more personal and emotional way. Moreover, regardless of the proficiency levels, they wrote longer responses on the narrative text than the expository text. However, the proficiency level of English does not support any significant differences in the types of reading models. The findings provide Korean EFL high school students' characteristics in L2 reading and suggest the pedagogical implication to pursue linguistic development as well as reading for pleasure.

• 한국조리학회지
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• 제22권1호
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• pp.42-51
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• 2016

This study investigated the quality characteristics of sponge cake added with pine leaf powder. The pine leaf powder sponge cake was prepared with different ration of pine leaf powder(0, 10, 20, 30, 40%). The specific gravity, baking loss rate and cake weight increased significantly with increasing the levels of pine leaf powder. In terms of color, lightness and yellowness increased with increasing levels of pine leaf powder. The sponge cake added with ratio of 40% pine leaf powder appeared to be the highest. In terms of textual property evaluation, sponge cake were increased by the level of pine leaf powder. The substance's level of springiness, and cohesiveness decreased by increasing of the level of pine leaf powder. In sensory evaluation, 10% pine leaf e sponge cake was better on taste, overall acceptability, and flavor. The results showed that sponge cake quality with 10% pine leaf powder was considered the best.

• International Journal of Contents
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• 제14권1호
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• pp.1-6
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• 2018

Text, as one of the most influential inventions of humanity, has played an important role in human life since ancient times. The rich and precise information embodied in text is very useful in a wide range of vision-based applications such as the text data extracted from images that can provide information for automatic annotation, indexing, language translation, and the assistance systems for impaired persons. Therefore, natural-scene text detection with active research topics regarding computer vision and document analysis is very important. Previous methods have poor performances due to numerous false-positive and true-negative regions. In this paper, a fully-convolutional-network (FCN)-based method that uses supervised architecture is used to localize textual regions. The model was trained directly using images wherein pixel values were used as inputs and binary ground truth was used as label. The method was evaluated using ICDAR-2013 dataset and proved to be comparable to other feature-based methods. It could expedite research on text detection using deep-learning based approach in the future.

• 한국정보과학회논문지:소프트웨어및응용
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• 제37권1호
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• pp.54-59
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• 2010

산업자동화 분야에는 특수목적 마이크로콘트롤러인 PLC가 널리 사용된다. PLC 프로그램 분석과 검증을 위한 연구에서 우선적으로 해야 할 일은 PLC 프로그래밍 언어의 의미구조를 정형적으로 제시하는 것이다. 본 논문은 PLC 프로그래밍에 널리 사용하는 LD 언어의 의미구조를 정의한다. LD 언어는 그래픽 언어이기 때문에 먼저 텍스트 언어 Symbolic LD로 구문구조를 정형화한 다음에, Symbolic LD에 대한 의미구조를 정의할 수가 있다. 본 논문은 Symbolic LD의 의미구조를 자연 의미구조 기법으로 정의하고, 증명 보조기 Coq을 이용하여 정형화하였다.