• Cartoon and Animation Studies
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• s.44
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• pp.285-306
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• 2016

With the increase use of smartphones, users can consume contents such as webtoon, webnovel and TV drama directly provided by the producers. In this Direct-to-Consumer era, webdrama services from the portal websites are increasing rapidly. Webdramas such as , , and can be analyzed in real time using responses such as unique users, likes, and comments. The analyses used in this research were Social Media Big Data Mining Method and Opinion Mining Method. Specific key words from webdrama can be extracted and viewers positive, neutral or negative emotion can be predicted from the words. The analyses of popular webdramas showed that the established K-Pop Idol member appearance and servicing portal site greatly influence the views, traffics, comments, and likes. Also, 'Mobile TV' proved the effectiveness as another platform other than television. Mobile targeted contents and robust business models still to be developed and identified. Overcoming these few tasks, Korea will be proven to be a webdrama content powerhouse.

• Hwankyungkyoyuk
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• v.14 no.2
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• pp.1-14
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• 2001

This study analyzed and compared the number of students activities, contents scope, and organizing system of the three textbooks(A, B, and C) which had been developed and published for the 'Environment'subject in the 7th National Curriculum. The results of this study can be summarized as follows; There were differences in the size, the total number of pages and the quality of print between two groups of 'Environment'textbooks of the 6th and the 7th national curriculum. New textbooks were found bigger than the previous ones by 125%. The total number of pages increased by the average of 16.4%. A and C textbooks were composed of three parts, seven chapters, and 17 sections, whereas B textbook consisted of ten chapters and 23 sections. All of the three textbooks appeared to put an emphasis on the chapters of 'environment protection'and 'environmental problems of the Earth ' A comparative analysis on the number of data included in the three textbooks showed that almost half of data took a form of picture, averaging 48% of the total. A had 297 pictures, and 234 pictures for B, 194 pictures for C, respectively. In terms of the number of students'activities, C was found to include the largest number of activities that is 91, comparing to text A of 85, text B of 78. The number of students'activities in every content is found'environment awaiting protection', tile 'environmental problems of the earth'and'things to be done for the protection of environment'much more than any other parts. It should be noted that this study focused ell only a set of quantitative measures so that teachers are recommended to consider detailed contents that each textbook contains as well as environmental conditions of the school region.

• Journal of The Korean Association of Information Education
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• v.22 no.2
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• pp.205-212
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• 2018

As a way to improve the software education ability of the pre - service teachers, we conducted programming learning using two types of programming tools (Python and Scratch) at the regular course time. In programming learning, various types of errors, which are factors that continuously hinder interest, achievement and creativity, were collected and analyzed by type. By using the analyzed data, it is possible to improve the ability of pre-service teachers to cope with the errors that can occur in the software education to be taught in the elementary school, and to improve the learning effect. In this study, logic error (37.63%) was the most frequent type that caused the most errors in programming in both conventional language that input text and language that assembles block. In addition, the detailed errors that show a lot of differences in the two languages are the errors of Python (14.3%) and scratch (3.5%) due to insufficient use of grammar and other errors.

• Journal of Korean Academy of Nursing Administration
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• v.23 no.1
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• pp.101-110
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• 2017

Purpose: This study aimed to identify research trends in the Journal of Korean Academy of Nursing Administration from 2013 to 2015. Methods: For this study, 171 articles were analyzed. Research designs, participants, research settings, sampling, and data analyses methods were reviewed using established analysis criteria. Keyword centrality and clusters were generated by keyword network analysis. Results: Most of studies used quantitative methods (82.5%), and sampling mainly focused on nurses (68.8%). The most commonly used data analyses methods were t-test, ANOVA, correlation, and regression. The most central keywords were turnover and empowerment. Network analysis generated four network groups: 1) burnout; 2) turnover; 3) happiness; and 4) nursing professionalism. Conclusion: The results of this study identify current trends and interests in Korean nursing administration research. The findings from this study suggest that future studies include a variety of research methods and maintain appropriate research ethics.

• Journal of KIISE:Software and Applications
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• v.32 no.5
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• pp.396-405
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• 2005

Since sentences are the basic propositional units of text, their themes would be helpful for various tasks that require knowledge about the semantic content of text. Despite the importance of determining the theme of a sentence, however, few studies have investigated the problem of automatically assigning the theme to a sentence. Therefore, we propose a sentence theme allocation scheme based on the head-driven patterns of sentences in encyclopedia. In a serious of experiments using Dusan Dong-A encyclopedia, the proposed method outperformed the baseline of the theme allocation performance. The head-driven pattern 4, which is reconfigured based on the predicate, showed superior performance in the theme allocation with the average F-score of $98.96\%$ for the training data, and $88.57\%$ for the test data.

• Archives of Plastic Surgery
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• v.40 no.1
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• pp.44-50
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• 2013

Background The aim of this investigation was to systematically review the current literature to provide the best data for indications, outcomes, survival, and complication rates of pedicled propeller perforator flaps for upper body defects. Methods A comprehensive literature review for articles published from January 1991 to December 2011 was performed using the PubMed, Medline, and Cochrane Databases. Articles without available full-text, single case reports or papers with excessive missing data were excluded. Papers reporting pedicle-perforator (propeller) flaps used for lower extremity reconstruction were excluded from meta-analysis. Results From the initial 1,736 studies our search yielded, 343 studies qualified for the second stage of selection. Of 117 full-text reports screened, 41 studies, met the definitive inclusion and exclusion criteria. Of the selected 41 articles, 26 were case series, original papers or retrospective reviews and were included, whereas 15 were case report papers and therefore were excluded. Two hundred ninety-five propeller flaps were reported to have been used in a total of 283 patients. Indications include repair of trauma-induced injuries, post-trauma revision surgery, cancer resection, chronic infection, pressure sores, and chronic ulcers with a major complication rate (3.3%) comparable to that of free flaps. No specific exclusion criteria for the procedure were presented in the studies reviewed. Conclusions Pedicled propeller flaps are a versatile and safe reconstructive option that are easy and quick to raise and that provide unlimited clinical solutions because of the theoretical possibility of harvesting them based on any perforator chosen among those classified in the body.

• Journal of the Korean Data and Information Science Society
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• v.26 no.2
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• pp.419-427
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• 2015

Despite of correlation between climate changes and food-related information, it is still not easy for many users to get access to the information with interest. This study investigated how much climate change and food-related information are correlated with each other and how often they are exposed through frequency and correlation analysis on news articles on the internet portals. Through analysis on the frequency of climate change and food-related news articles, this study was able to figure out how often they are exposed at the same time by the internet news portals. In addition, a total of 59 correlation rules regarding the climate change and food-related vocabularies were derived from these news articles using the climate change and food-related glossaries. Then, a correlation between certain climate change-related and food-related words was analyzed in order to package the related words.

• Journal of Digital Contents Society
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• v.19 no.5
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• pp.981-993
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• 2018

Smart healthcare is convergence of ICT and healthcare services, and interdisciplinary research has been actively conducted in various fields. The objective of this study is to investigate trends of smart healthcare research using topic modeling and ego network analysis. Text analysis, frequency analysis, topic modeling, word cloud, and ego network analysis were conducted for the abstracts of 2,690 articles in Scopus from 2001 to April 2018. Topic Modeling analysis resulted in eight topics, Topics included "AI in healthcare", "Smart hospital", "Healthcare platform", "Blockchain in healthcare", "Smart health data", "Mobile healthcare", " Wellness care", "Cognitive healthcare". In order to examine the topic modeling results core deeply, we analyzed word cloud and ego network analysis for eight topics. This study aims to identify trends in smart healthcare research and suggest implications for establishing future research direction.

• The Journal of the Korea Contents Association
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• v.10 no.12
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• pp.70-76
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• 2010

This paper Extended ELZW(EBCDIC Lempel Ziv Welch) algorithm uses 2 byte prefix field for pointer of a table and 1 byte suffix field for repeat counter. where, a prefix field uses a pointer(index) of compression table and a suffix field uses a counter of overlapping or recursion text data in compression table. To increase compression ratio, after construction of compression table, table data are properly packed as different bit string in accordance with a alphabet, Hangeul, and pointer respectively. Therefore, proposed ELZW algorithm is superior to 1byte LZW algorithm as 5.22 percent and superior to 2byte LZW algorithm as 8.96 percent.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.225-230
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• 2012

The opinion mining is that to use the existing data mining technology also uploaded blog to web, to use product comment, the opinion mining can extract the author's opinion therefore it not judge text's subject, only judge subject's emotion. In this paper, published opinion mining algorithms and the text using speech recognition API for non-voice data to judge the emotions suggested. The system is open and the Subject associated with Google Voice Recognition API sunwihwa algorithm, the algorithm determines the polarity through improved design, based on this interview, speech recognition, which implements the model.