• 한국지구과학회:학술대회논문집
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• 2001.09a
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• pp.51-51
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• 2001

• Therapeutic Science for Rehabilitation
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• v.11 no.3
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• pp.93-106
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• 2022

Objective : The COVID-19 pandemic has brought non-face-to-face healthcare service delivery system. Research into telehealth system and its efficacy remains unclear. Methods : Seven healthy adults participated in this study to investigate effects of tele-monitoring with the speech-to-text (STT) application to induce changes in occupational activities on occupational balance in healthy adults. Subjects were requested to choose occupational activities they wanted to have researched and then register them to the STT application. The STT application provided an alarm to check whether the pre-registered activities were performed on time, and whether the subjects performed it by their voice. The subjects were followed for 1 week, with assessments at baseline, and after 1-week's tele-monitoring. Results : Our findings showed that the subjects were willing to participate in tele-monitoring with the STT application with high adherence and satisfaction. In addition, there was a significant improvement in occupational activities related to health (p<.05). Specifically, adherence, satisfaction, and efficacy of the tele-monitoring with the STT application could successfully bring occupational balance in short-term periods. Conclusion : These findings highlight that tele-monitoring with a smartphone could be considered as one promising way to restore occupational balance in lockdown after the COVID-19 outbreak.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.420-438
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• 2004

Artificially or naturally contained texts in the natural images have significant and detailed information about the scenes. If we develop a method that can extract and recognize those texts in real-time, the method can be applied to many important applications. In this paper, we suggest a new method that extracts the text areas in the natural images using the low-level image features of color continuity. gray-level variation and color valiance and that verifies the extracted candidate regions by using the high-level text feature such as stroke. And the two level features are combined hierarchically. The color continuity is used since most of the characters in the same text lesion have the same color, and the gray-level variation is used since the text strokes are distinctive in their gray-values to the background. Also, the color variance is used since the text strokes are distinctive in their gray-values to the background, and this value is more sensitive than the gray-level variations. The text level stroke features are extracted using a multi-resolution wavelet transforms on the local image areas and the feature vectors are input to a SVM(Support Vector Machine) classifier for the verification. We have tested the proposed method using various kinds of the natural images and have confirmed that the extraction rates are very high even in complex background images.

• Science of Emotion and Sensibility
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• v.16 no.2
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• pp.167-176
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• 2013

User-created text data are increasing rapidly caused by development of social media. In opinion mining, User's opinions are extracted by analyzing user's text. A primary goal of sentiment analysis as a branch of opinion mining is to extract user's opinions from a text that is required to build a list of emotion terms. In this paper, we built a list of emotion terms to analyse a sentiment of social media using Facebook as a representative social media. We collected data from Facebook and selected a emotion terms, and measured the dimensions of valence and activation through a survey. As a result, we built a list of 267 emotion terms including the dimension of valence and activation.

• Korean Journal of Cognitive Science
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• v.4 no.2
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• pp.5-28
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• 1994

In this thesis we attempt to analyze modern Korean poetic texts in the franmeworks of text limgisitics and cognitive pragmatics. Both frameworks describe and explai human verbal communicantion in terms of congnitive information-processing procedures.By utilizing analytical devices provided by seven standards of textuality we can analyze any type of text,especially in terms of the cognitive operations underlying the production and reception processes.It is clamed in cognitive pragmatic framework that human ostensive inforential communication is regulated by the Principle of Relevance.We claim that the relevance-based framework of pragmatics provides evidence and rationale for those cognitive operations identified in the text linguistic framework. poetic texts involve every kind of cognitive strategies and processing procedures underlying human verbal communication.So,if modern Korean poetic texts are satisfactorily analyzed by text linguistics and cognitive pragmatics,it means that both frameworks are very useful tools for analyzing texts and that all the other text types which are less complicated than poetic text will also be analyzed by these frameworks. Researchers of poetry,and poets,are sensitive to poetic effects.They feel more of poeticity while reading poetic texts than ordinary readers do.However,these researchers or poets sometimes give different interpretation of a single poetic text.The interpretation of poetry cannot be anything,because poets write poems with particular intertions and do not just throw them out so as to be interpreted at ramdom.This thesis suggersts that the poeticity felt by the reader can be described and accounted for in a scientific way.In other words,text linguistics and cognitive pragmatics enable the researchers of poetry to become objective in interpreting poetic texts. It will be clearly shown that we have to see poetic texts from a cognitive perspective,since they are by-products of cognitive processing performed by discourse participants.

• Proceedings of the Korea Information Processing Society Conference
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• 2021.11a
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• pp.466-469
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• 2021

최근 자연어 처리에 대한 관심이 증가함에 따라 자연어 처리 기술을 활용한 다양한 추천 시스템이 등장하고 있다. 본 논문에서는 자연어 처리를 이용한 서비스를 개발한다. 본 논문에서 개발한 서비스는 KoNLPy 와 Word2Vec 을 이용하여 크라우드 펀딩 프로젝트 창작자 및 후원자에게 키워드 및 키워드와 유사한 단어가 제목에 포함되는 프로젝트를 추천해준다. 단문 텍스트로서 프로젝트 제목을 사용하여 데이터를 자연어 처리 한 후, 딥러닝 모델에 적용시켜 추출한 데이터를 기반으로 창작자와 후원자에게 추천해주는 방식이다. 따라서 본 서비스는 프로젝트 제목 정보를 통한 추천 시스템의 개발로, 나아가 영화, 도서와 같은 콘텐츠 추천 분야에도 적용할 수 있을 것으로 기대한다.

• Journal of KIISE:Software and Applications
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• v.34 no.3
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• pp.275-302
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• 2007

We propose a novel still image compression system which supports a high quality text compression function. The system segments the text from the image and compresses the text with a high quality. The system shows 48:1 high compression ratio using context-based adaptive binary arithmetic coding. The arithmetic coding performs the high compression by the codeblocks in the bitplane. The input of the system consists of a segmentation mode and a ROI(Region Of Interest) mode. In segmentation mode, the input image is segmented into a foreground consisting of text and a background consisting of the remaining region. In ROI mode, the input image is represented by the region of interest window. The high quality text compression function with a high compression ratio shows that the proposed system can be comparable with the JPEG2000 products. This system also uses gray coding to improve the compression ratio.

• KIISE Transactions on Computing Practices
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• v.21 no.9
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• pp.596-603
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• 2015

A concept network is an essential knowledge base for semantic search engines, personalized search systems, recommendation systems, and text mining. Recently, studies of extending concept representation using external ontology have been frequently conducted. We thus propose a new way of building 3-dimensional text model-based concept networks using the world knowledge-level Wikipedia ontology. In fact, it is desirable that 'concepts' derived from text documents are defined according to the theoretical framework of formal concept analysis, since relationships among concepts generally change over time. In this paper, concept networks hidden in a given document collection are extracted more reasonably by representing a concept as a term-by-document matrix.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.72-74
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• 2022

The National Science and Technology Knowledge Information Service (NTIS) provides information on national R&D projects. Project information consists of meta-information such as 'project name', 'project performance institution', 'research manager name', and text explaining projects such as 'research goal', 'research content', and 'expected effect'. There is a problem that it takes a lot of time to find the desired project information by checking all of the "research goals" or "research contents" in the list of results of searching for 1 million project information. To solve this problem, this paper proposes a project information summary system that summarizes the parts consisting of long texts within the national R&D project information. By analyzing the linguistic characteristics of the Korean language, a preprocessor was built and a project information summary model based on natural language processing technology was developed to process preprocessed text information. Through this, project information composed of long sentences is provided in a compressed and summarized form, which will help users to easily and quickly infer the overall content with the summary information alone.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.33 no.4
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• pp.24-29
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• 2015