• KIISE Transactions on Computing Practices
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• v.22 no.10
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• pp.537-545
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• 2016

Demand for text arranged in a circular shape is increasing as devices with round display such as smart watches are now being actively released. Data visualization field is receiving a lot of attention as the era of big data evolves. However, current web standard does not support the drawing of circular text. Therefore, the objective of this study was to extend CSS3 specifications to have circular text layout in web documents. In addition, we implemented a preprocessor so that contents made with CSS3 extensions could be shown in existing browsers. To confirm the wide expression range of CSS3 extension, we prepared some sample contents and analyzed them.

• The KIPS Transactions:PartA
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• v.9A no.3
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• pp.311-316
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• 2002

LZW is a popular variant of LZ78 to compress text documents. LZW yields a high compression rate and is widely used by many commercial programs. Its core idea is to assign most probably used character group an entry in a dictionary. If a group of character which is already positioned in a dictionary appears in the streaming data, then an index of a dictionary is replaced in the position of character group. In this paper, we propose a new efficient method to find least used entries in a dictionary using counter. We also achieve higher compression rate by preassigning widely used tags in hyper-text documents. Experimental results show that the proposed method is more effective than V.42bis and Unix compression method. It gives 3∼8％ better in the standard Calgary Corpus and 23∼24％ better in HTML documents.

• The KIPS Transactions:PartB
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• v.10B no.5
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• pp.485-490
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• 2003

In this paper, we propose the possibility of introducing chaotic sequences into digital watermarking systems as potential substitutes to commonly used pseudo noise sequences. Chaotic sequences have several good properties including the availability of a great number of them, the ease of their generation, as well as their sensitive dependence on their initial conditions. And the quantization does not destroy the good property. So this paper proposes a method that transforms Hangul text to chaotic sequence. And we presents how the Hangul text is expressed by an implied data and the implied data is regenerated into the original text. In this paper, we use this implied Hangul text for watermarking.

• Journal of Digital Convergence
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• v.17 no.4
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• pp.211-217
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• 2019

As the widespread use of mobile health intervention among Korean patients with chronic disease, it is needed to identify research trends in mobile health intervention on chronic care using text mining technique. This secondary data analysis was conducted to investigate characteristics and main research topics in intervention studies from 2005 to 2018 with a total of 20 peer reviewed articles. Microsoft Excel and Text Analyzer were used for data analysis. Mobile health interventions were mainly applied to hypertension, diabetes, stroke, and coronary artery disease. The most common type of intervention was to develop mobile application. Lately, 'feasibility', 'mobile health', and 'outcome measure' were frequently presented. Future larger studies are needed to identify the relationships among key terms and the effectiveness of mobile health intervention using social network analysis.

• Phonetics and Speech Sciences
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• v.10 no.1
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• pp.39-48
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• 2018

A typical statistical parametric speech synthesis (text-to-speech, TTS) system consists of separate modules, such as a text analysis module, an acoustic modeling module, and a speech synthesis module. This causes two problems: 1) expert knowledge of each module is required, and 2) errors generated in each module accumulate passing through each module. An end-to-end TTS system could avoid such problems by synthesizing voice signals directly from an input string. In this study, we implemented an end-to-end Korean TTS system using Google's Tacotron, which is an end-to-end TTS system based on a sequence-to-sequence model with attention mechanism. We used 4392 utterances spoken by a Korean female speaker, an amount that corresponds to 37% of the dataset Google used for training Tacotron. Our system obtained mean opinion score (MOS) 2.98 and degradation mean opinion score (DMOS) 3.25. We will discuss the factors which affected training of the system. Experiments demonstrate that the post-processing network needs to be designed considering output language and input characters and that according to the amount of training data, the maximum value of n for n-grams modeled by the encoder should be small enough.

• Journal of Korean Home Economics Education Association
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• v.7 no.2
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• pp.113-123
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• 1995

The purpose of this study is to investigate teachers’ recognition in Food/Nutrition, Textile/Clothing part in Home Economics Text Book of Middle School and to provide the basic data for the improvement of its curriculum. 147 Home Economics teachers in Taegu city and Kyungsangbukdo area responded to the questionnaire. The results are summarized as follows: 1. Most of Home Economics teachers have graduated Dept. of Home Economics Education and have ever taken teacher training. And even those who ever taken teacher training are not satisfied with training curriculum contents. Therefore, the result of this study shows that teacher training curriculum contents should be improved so as to be helpful for the actual teaching and learning. 2. In terms of the suitability of contents of food & nutrition and contents of textiles & clothing to the student’s learning development levels, the degree of suitability is in the order of nutrition & health, nutrition in adolescence, food selection, kinds and functions of nutrients in food & nutrition curriculum, and in the order of suitable clothing, mixture rate of fabrics, purchase of clothing, clothing in adolescence, clothing selection. The contents of making processed foods and usage of sewing machine of the existing text book have turned out not to be appropriate. 3. Most teachers suggest that dietary guideline for health, misconception about food & nutrition selection of ready-made suit suitable clothing for situation & character as well as the contents of the existing text book should be included in the new text book.

• Journal of Information Technology Services
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• v.15 no.1
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• pp.245-253
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• 2016

Background in a novel is most important elements with characters and events, and means time, place and situation that characters appeared. Among the background, spatial background can help conveys topic of a novel. So, it may be helpful for choosing a novel that readers want to read. In this paper, we are targeting Korean historical novels. In case of English text, It can be recognize spatial background easily because it use upper and lower case and words used with the spatial information such as Bank, University and City. But, in case Korean text, it is difficult to recognize that spatial background because there is few information about usage of letter. In the previous studies, they use machine learning or dictionaries and rules to recognize about spatial information in text such as news and text messages. In this paper, we build a nation dictionaries that refer to information such as 'Korean history' and 'Google maps.' We Also propose a method for recognizing spatial background based on patterns of postposition in Korean sentences comparing to previous works. We are grasp using of postposition with spatial background because Korean characteristics. And we propose a method based on result of morpheme analyze and frequency in a novel text for raising accuracy about recognizing spatial background. The recognized spatial background can help readers to grasp the atmosphere of a novel and to understand the events and atmosphere through recognition of the spatial background of the scene that characters appeared.

• International Journal of Advanced Culture Technology
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• v.7 no.4
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• pp.246-254
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• 2019

The purpose of this study is to analyze the issues related to urban regeneration project at the present time through surveys and interviews of participants in the urban regeneration leading project of Suncheon city. Most of the comments were related to business fragmentation and things that should be improved in the future. The text network technique is applied to the subject analysis using unstructured text data. As a result of the frequency of appearance and analysis of page rank centrality between words, words of 'parking', 'need', 'lack', 'region' and 'resident' appeared at the top, and the result of analyzing the mediation centrality of key words showed 'culture', 'Need', 'region', 'inflow' and 'lack' appeared at the top. In the network analysis, the most central words appeared, and many words appeared in the important position in the sentence. Text network analysis has provided timely results in terms of sustainability after completion of the Suncheon City Regeneration Leading Project..

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.10
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• pp.3211-3229
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• 2022

To solve the problems existing in the process of Weibo disaster rumor recognition, such as lack of corpus, poor text standardization, difficult to learn semantic information, and simple semantic features of disaster rumor text, this paper takes Sina Weibo as the data source, constructs a dataset for Weibo disaster rumor recognition, and proposes a deep learning model BERT_AT_Stacked LSTM for Weibo disaster rumor recognition. First, add adversarial disturbance to the embedding vector of each word to generate adversarial samples to enhance the features of rumor text, and carry out adversarial training to solve the problem that the text features of disaster rumors are relatively single. Second, the BERT part obtains the word-level semantic information of each Weibo text and generates a hidden vector containing sentence-level feature information. Finally, the hidden complex semantic information of poorly-regulated Weibo texts is learned using a Stacked Long Short-Term Memory (Stacked LSTM) structure. The experimental results show that, compared with other comparative models, the model in this paper has more advantages in recognizing disaster rumors on Weibo, with an F1_Socre of 97.48%, and has been tested on an open general domain dataset, with an F1_Score of 94.59%, indicating that the model has better generalization.

• Korean Journal of Schizophrenia Research
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• v.23 no.2
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• pp.58-64
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• 2020

Objectives: In this study, we conducted an exploratory analysis of the current media trends on schizophrenia using text-mining methods. Methods: First, web-crawling techniques extracted text data from 575 news articles in 10 major newspapers between 2018 and 2019, which were selected by searching "schizophrenia" in the Naver News. We had developed document-term matrix (DTM) and/or term-document matrix (TDM) through pre-processing techniques. Through the use of DTM and TDM, frequency analysis, co-occurrence network analysis, and topic model analysis were conducted. Results: Frequency analysis showed that keywords such as "police," "mental illness," "admission," "patient," "crime," "apartment," "lethal weapon," "treatment," "Jinju," and "residents" were frequently mentioned in news articles on schizophrenia. Within the article text, many of these keywords were highly correlated with the term "schizophrenia" and were also interconnected with each other in the co-occurrence network. The latent Dirichlet allocation model presented 10 topics comprising a combination of keywords: "police-Jinju," "hospital-admission," "research-finding," "care-center," "schizophrenia-symptom," "society-issue," "family-mind," "woman-school," and "disabled-facilities." Conclusion: The results of the present study highlight that in recent years, the media has been reporting violence in patients with schizophrenia, thereby raising an important issue of hospitalization and community management of patients with schizophrenia.