• Speech Sciences
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• v.11 no.4
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• pp.223-232
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• 2004

This study investigated and compared the acoustic characteristics of the Korean stop sound [k'] in three different phonological environments: the tensified lenis stop [k'] as observed in /prek+kaci/, the fortis stop /k'/ as in /pre+k'aci/, and the fortis stop /k'/ following an obstruent as in /prek+k'aci/. The specific research question was whether or not the tensified lenis stop shares all the acoustic features with the other two kinds of fortis stops. The acoustic measures adopted in this study were H1*-H2*, VOT, length of stop closure, and $F_0$. The major findings were that the three stops showed no significant difference in all the acoustic measures except the length of stop closure. The fortis stop /k'/ following an obstruent showed significantly longer duration of stop closure than the other two stops, both of which showed no significant difference. Based on these phonetic results, this study argued that, for the proper phonological description of post-obstruent tensification, the phonological feature [slack vocal folds] of a lenis stop should be changed into [stiff vocal folds, constricted glottis] that the fortis stops should have.

• Speech Sciences
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• v.14 no.2
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• pp.139-155
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• 2007

Old Korean regulated poems have a typical prosodic structure characterized by a pitch contour. This work applies Jun's finding in Seoul Korean(Jun 1993, 2000, 2005) to old Korean regulated poems, and reports some other significant phonetic characteristics, arguing that old Korean regulated poems have a regular rhythm based on the pitch contour implementing the typically hierarchical prosodic structure. The major prosodic units defined are a foot, a phrase, and a line. Next, this work proposes pitch contour characterizing prominence in a unit, boundary tones, and pauses at the boundary position, as the basic and significant cues of rhythm of a Korean poem. Specifically, some significant characteristics are discussed as follows: first, the tonal pattern of a foot is HL, starting high and ending low; second, the lowering boundary tones of HL% and L% are perceived at the end of a phrase and a line; and finally, a gradient degree of pause is observed at each unit-final position.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.4
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• pp.360-373
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• 1991

Since 70's, efficient speech recognition methods such as HMM or DTW have been introduced primarily for speaker dependent isolated words. These methods however have confronted with difficulties in recognizing continuous speech. Since early 80's, there has been a growing awareness that neural networks might be more appropriate for English and Japanese phoneme recognition using neural networks. Dealing with only a part of vowel or consonant set, Korean phoneme recognition still remains on the elementary level. In this light, we develop a system based on neural networks which can recognize major Korean phonemes. Through experiments using two neural networks, SOFM and TDNN, we obtained remarkable results. Especially in the case of using TDNN, the recognition rate was estimated about 93.78% for training data and 89.83% for test data.

• Korean Journal of Head & Neck Oncology
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• v.24 no.1
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• pp.76-79
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• 2008

Adenoid cystic carcinoma(ACC) is one of the common malignant tumor of the major and minor salivary glands. ACC arising from the larynx is relatively rare(less than 1% of laryngeal malignant tumors) and only about eighty cases have been reported in the English literature. Definite diagnosis of these lesions is made only from a histological analysis, because findings and symptoms are non-specific. The diagnosis progresses very slowly, therefore it often presents at an advanced stage with regional and distant metastasis. Here, we present one case of ACC of the supraglottic region with a review of literature.

• Journal of Information Technology Services
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• v.18 no.2
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• pp.123-141
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• 2019

The goal of this study is to review the major research trend on the convergence studies of AI and healthcare technologies. For the study, 15,260 English articles on AI and healthcare related topics were collected from Scopus for 55 years from 1963, and text mining techniques were conducted. As a result, seven key research topics were defined : "AI for Clinical Decision Support System (CDSS)", "AI for Medical Image", "Internet of Healthcare Things (IoHT)", "Big Data Analytics in Healthcare", "Medical Robotics", "Blockchain in Healthcare", and "Evidence Based Medicine (EBM)". The result of this study can be utilized to set up and develop the appropriate healthcare R&D strategies for the researchers and government. In this study, text mining techniques such as Text Analysis, Frequency Analysis, Topic Modeling on LDA (Latent Dirichlet Allocation), Word Cloud, and Ego Network Analysis were conducted.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.05a
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• pp.278-281
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• 2021

For a long time, CAPTCHA Recognition has been a major challenge in the field of artificial intelligence. Although there are many related technologies that can solve this identification problem, further breakthroughs are still needed. Based on the existing SSD network, this paper adds a non-block module. Compared with the original SSD network, the recognition rate of SSD + Non-local is improved from 86.12% to 88.47%.In addition, it is worth noting that the recognized character verification code consists of Arabic numerals, uppercase and lowercase English letters.

• Journal of Information Science Theory and Practice
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• v.12 no.2
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• pp.36-48
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• 2024

For consumers making health decisions, Wikipedia is a popular source for health information. This study investigated major factors influencing consumer satisfaction with Wikipedia medical/health articles. Using a crowdsourcing method, data were collected from 322 adults who read/edit English Wikipedia medical/health articles and reside in the US. The results showed that the presentation of information was the most influential factor. Trustworthiness was the second most important factor for consumer satisfaction with the quality of information, followed by reliability, and topic coverage. Study participants did not consider other factors such as accuracy and currency to be crucial factors. Moderating effects of the control variables such as editing experience with Wikipedia articles, gender, and age were also examined to enhance the internal validity of the study. Implications for the Wikipedia editor community and researchers, and directions of future research are presented.

• Korean Journal of Acupuncture
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• v.37 no.2
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• pp.76-87
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• 2020

Objectives : Bee venom has been widely practiced in many countries around the world. The number of clinical trials and biochemical researches on bee venom has been constantly increasing. The objective of this study is to analyze the trend of research on bee venom using bibliometric approach, a quantitative analytical method. Methods : We searched articles about bee venom which were published from 2000 to 2019 from Web of Science Database. Original and review articles published in English were included and data were extracted in terms of publication year, country, journal, keywords, organizations, and authors. Trends in bee venom research were visualized using VOSviewer program. Results : 1,547 English articles about bee venom were identified and analyzed. South Korea is a main hub in the field of bee venom research. Research organizations in South Korea showed high link strength with domestic organizations as well as with international organizations. A keyword analysis showed the following three major types of studies: studies on components of bee venom, studies on allergy and immune response, and clinical research of bee venom therapy. Conclusions : This study provides a macroscopic overview of the research on bee venom. This bibliometric analysis has identified influential authors and organizations in the field on bee venom research and provides a useful guideline to researchers who are in search of contributory research topics.

• The Mathematical Education
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• v.45 no.4 s.115
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• pp.407-438
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• 2006

This study investigated school mathematics curriculum of England, newly revised in 1998, focused on the 'shape, space, and measures' domain among three major domains of the English curriculum. On the basis of its understanding, this domain was compared and analyzed with school mathematics curriculum of Korea. In doing so, this study explored its plans and procedures and established a frame of comparison for the curriculums between the two countries. The structure of the National Curriculum in England is composed of programmes of study and attainment targets. The former sets out what should be taught in mathematics at key stages 1, 2, 3, and 4 and provides the basis for planning schemes of work, and the latter sets out the knowledge, skills, and understanding that pupils of different abilities and matures are expected to have by the end of each key stage. Attainment targets are composed of eight levels and an additional level of increasing difficulty. According to the results of the present study, Korea focuses on the formal and systematic mathematical knowledge on the basis of sound understanding of certain mathematical terms or concepts. On the other hand, England curriculum tends to deal with the content which can be understood more intuitively, flexibly, and naturally through the experience and aquisition based on the concrete manipulation. Particularly, it emphasizes that mathematics be realistic and useful in solving a diverse problems confronted in everyday life.

• Journal of the Korea Convergence Society
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• v.11 no.6
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• pp.1-6
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• 2020

In this study, research on character recognition, which is one of the fields of computer vision, was conducted. Optical character recognition, which is one of the most widely used character recognition techniques, suffers from decreasing recognition rate if the recognition target deviates from a certain standard and format. Hence, this study aimed to address this limitation by applying deep learning techniques to character recognition. In addition, as most character recognition studies have been limited to English or number recognition, the recognition range has been expanded through additional data training on Korean text. As a result, this study derived a deep learning-based character recognition algorithm for Korean text recognition. The algorithm obtained a score of 0.841 on the 1-NED evaluation method, which is a similar result to that of English recognition. Further, based on the analysis of the results, major issues with Korean text recognition and possible future study tasks are introduced.