• Korean Journal of Acupuncture
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• 제28권2호
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• pp.87-104
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• 2011

Objectives : A safety issue on acupuncture and moxibustion treatment during pregnancy is as important as effectiveness. To establish a rationale and research strategy for future studies, a traditional literature review was performed to summarize how and for what conditions acupuncture and moxibustion treatment was given during pregnancy. Methods : An extensive traditional literature search for acupuncture and moxibustion treatment during pregnancy was conducted in texts on acupuncture and moxibustion, obstetrics and gynecology, and comprehensive medical texts. Treatment conditions, methods, and contraindications were summarized and tabulated. Results : Twenty-eight books were included in our review. Most frequent description of acupuncture and moxibustion treatment use during pregnancy was for difficult delivery including breech presentations; commonly used acupuncture points for difficult labor included LI4, SP6, BL67, BL60, KI6, ST30, SP12, LR4, LR3, PC6, CV3, CV14, KI13, and GB21, indicating that they may have to be avoided during pregnancy. Descriptions of other symptoms or conditions were sparse. For habitual abortion or recurrent miscarriage, moxibustion on GV4, BL23, CV3, KI8, and KI2 was indicated. A combination of LI4 and SP6, and CV4 were contraindicated during pregnancy consistently across the reviewed books. Conclusions : Our traditional literature review has shown that the use of acupuncture and moxibustion treatment during pregnancy has been limited. Given that more and more pregnant women are interested in safe and effective treatment, further research of acupuncture's safety and efficacy during pregnancy is urgently needed.

• 한국도서관정보학회지
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• 제49권2호
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• pp.267-300
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• 2018

본 연구의 목적은 리터러시 및 독서 정보 ICT 디지털 리터러시의 개념을 고찰하고 정의하여 이들 리터러시의 개념적 차이를 통한 독서 정보 ICT 디지털 리터러시의 개념화 모델을 개발하는 데 있다. 동시대의 사회적이고 문화적이며 정보기술의 발전에 따른 현상을 설명하는 개념으로 컴퓨터 리터러시가 등장하였으며, 이후 컴퓨터 리터러시는 IT와 ICT 리터러시로 그리고 디지털 리터러시로 변화되어 왔다. 연구결과로, 매체의 기술적 변화에 따라 용어가 변화되어 온 이들 리터러시를 매체 중심적 리터러시로 분류하였고, 텍스트나 정보를 이해하고 활용하고 평가하는 인지적 과정에 초점을 둔 독서 리터러시와 정보 리터러시를 과정 중심적 리터러시로 분류하여 독서 정보 ICT 디지털 리터러시의 개념화 모델을 개발하였다. 디지털 환경에서도 독서나 정보 리터러시는 매체에서 드러난 텍스트를 비판적으로 사고하고 평가하는 핵심적인 역량으로 독자들의 독서 및 정보 격차를 줄일 수 있는 방법에 대한 관심과 연구가 더욱 필요하다.

• Journal of the Korean Data and Information Science Society
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• 제27권4호
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• pp.845-854
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• 2016

감성분석 (sentiment analysis) 혹은 오피니언 마이닝 (opinion mining)은 블로그, 리뷰, 신문기사나 소셜네트워크 등의 문서에서 개인의 주관적인 정보 혹은 의견을 알아보는데 사용되는 텍스트 마이닝의 기법이다. 평점이 있는 온라인 리뷰에서 리뷰 텍스트에 기반한 평점의 분류문제에 대한 선행연구에서는 이진 분류만을 고려하였다. 그러나 긍정과 부정 외에도 중립적인 의견도 있을 수 있기 때문에 이진 분류보다는 다범주 분류가 더 적합할 것이다. 본 연구에서는 리뷰 텍스트에 기반한 평점의 다범주 분류문제를 고려한다. 전처리에서는 카이제곱 통계량을 이용하여 평점과 연관된 단어들을 추출하고 이를 입력변수로 삼아 지지벡터기계 (support vector machines)와 비례오즈 모형 (proportional odds model) 등 다범주 분류기의 예측력을 비교한다.

• 대한안전경영과학회지
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• 제13권3호
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• pp.29-35
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• 2011

Safety and health related information for the proper use and handling of pesticides is usually printed on the surface of the pesticide products (bottle type or bag type) in the form of texts. But, the guidelines or standards for the appropriate presentation of the texts for the pesticide products are most vague or not practical. Thus, this study aimed to provide the preliminary guidelines for the text sizes based on the legibility experiments. Total twenty subjects from two age groups (young: n=10, old: n=10, five males and five females in each group) participated in the experiment. First, subjects read the text cards presented in the distance of 50cm from the eyes of the subjects. Eight different text card sets were prepared for different font type(thick gothic-type and fine gothic-type), thickness of font(plain and bold), and number of syllables (2 and 3 syllables). When subjects read the cards, the correctness of reading (correct or wrong) was recorded and the degree of discomfort (from 1: no discomfort at all to 4: can't read at all) was also evaluated for all the text sizes. Results showed that the character size should be 4 pt or larger for the young subjects to read at least one word correctly in all the text conditions. For the old subjects to read at least one word correctly, the character size should be five pt or larder. The average of the minimum character sizes for 100% correct answer is 6.1 pt for young subjects and 10.5 pt for old subjects, respectively.

• 한국문헌정보학회지
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• 제51권2호
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• pp.23-48
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• 2017

그림책은 글과 그림으로 구성되어 언어 텍스트와 시각 텍스트 그리고 상호간의 보완작용을 통하여 의미가 전달되는 독특한 장르이다. 글 작가는 문체를 중심으로 하는 글의 내용으로 작가의 의도를 전개하고 전달하며, 그림 작가는 사물 대상 형상 등에 감정을 이입시킨 그림으로 작가의 의도를 전달한다. 그림은 표면적으로 보여지는 구조와 작가의 철학, 사상 등을 이미지화하여 변용한 심층적 구조에 관한 이해가 병행되어야 한다. 이에 행동주의 심리학자 Arnheim의 시각적 사고이론을 기반으로 그림책의 독서지원서비스를 위하여 사서들이 갖추어야 할 시각적 문식성의 이해를 돕기 위한 방법을 제안하였으며, 이는 사서들의 그림책 서평과 같은 이차자료 작성에 활용될 수 있을 것으로 기대된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권7호
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• pp.1807-1822
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• 2023

Innovation and rapid increased functionality in user friendly smartphones has encouraged shutterbugs to have picturesque image macros while in work environment or during travel. Formal signboards are placed with marketing objectives and are enriched with text for attracting people. Extracting and recognition of the text from natural images is an emerging research issue and needs consideration. When compared to conventional optical character recognition (OCR), the complex background, implicit noise, lighting, and orientation of these scenic text photos make this problem more difficult. Arabic language text scene extraction and recognition adds a number of complications and difficulties. The method described in this paper uses a two-phase methodology to extract Arabic text and word boundaries awareness from scenic images with varying text orientations. The first stage uses a convolution autoencoder, and the second uses Arabic Character Segmentation (ACS), which is followed by traditional two-layer neural networks for recognition. This study presents the way that how can an Arabic training and synthetic dataset be created for exemplify the superimposed text in different scene images. For this purpose a dataset of size 10K of cropped images has been created in the detection phase wherein Arabic text was found and 127k Arabic character dataset for the recognition phase. The phase-1 labels were generated from an Arabic corpus of quotes and sentences, which consists of 15kquotes and sentences. This study ensures that Arabic Word Awareness Region Detection (AWARD) approach with high flexibility in identifying complex Arabic text scene images, such as texts that are arbitrarily oriented, curved, or deformed, is used to detect these texts. Our research after experimentations shows that the system has a 91.8% word segmentation accuracy and a 94.2% character recognition accuracy. We believe in the future that the researchers will excel in the field of image processing while treating text images to improve or reduce noise by processing scene images in any language by enhancing the functionality of VGG-16 based model using Neural Networks.

• 한국생물정보학회:학술대회논문집
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• 한국생물정보시스템생물학회 2005년도 BIOINFO 2005
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• pp.101-106
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• 2005

Recently, as the size of genetic knowledge grows faster, automated analysis and systemization into high-throughput database has become hot issue. One essential task is to recognize and identify genomic entities and discover their relations. However, ambiguity of name entities is a serious problem because of their multiplicity of meanings and types. So far, many effective techniques have been proposed to analyze documents. Yet, accuracy is high when the data fits the model well. The purpose of this paper is to design and implement a document classification system for identifying entity problems using text/data mining combination, supplemented by rich data mining algorithms to enhance its performance. we propose RTP ost system of different style from any traditional method, which takes fault tolerant system approach and data mining strategy. This feedback cycle can enhance the performance of the text mining in terms of accuracy. We experimented our system for classifying RB-related documents on PubMed abstracts to verify the feasibility.

• Journal of the Korean Data and Information Science Society
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• 제18권4호
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• pp.859-868
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• 2007

The present paper deals with the ordering problem for how to teach mathematical concepts successfully. Main object is the concept of continuous functions which is fundamental in analysis and topology. At first, the theoretical organization of this concept is investigated through several texts in related field, calculus, analysis and topology. And next, the historical order for this concept from the viewpoint of problem-solving is considered. Based on these two materials, we suggest a lecturing organization order in order to establish a balanced unification of three concepts - intuitive, logical and formal concepts.

• Genomics & Informatics
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• 제19권3호
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• pp.25.1-25.5
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• 2021

The coronavirus disease 2019 (COVID-19) pandemic has led to a flood of research papers and the information has been updated with considerable frequency. For society to derive benefits from this research, it is necessary to promote sharing up-to-date knowledge from these papers. However, because most research papers are written in English, it is difficult for people who are not familiar with English medical terms to obtain knowledge from them. To facilitate sharing knowledge from COVID-19 papers written in English for Japanese speakers, we tried to construct a dictionary with an open license by assigning Japanese terms to MeSH unique identifiers (UIDs) annotated to words in the texts of COVID-19 papers. Using this dictionary, 98.99% of all occurrences of MeSH terms in COVID-19 papers were covered. We also created a curated version of the dictionary and uploaded it to Pub-Dictionary for wider use in the PubAnnotation system.

• International Journal of Computer Science & Network Security
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• 제22권8호
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• pp.399-403
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• 2022

Natural texts are analyzed to obtain their intended meaning to be classified depending on the problem under study. One way to represent words is by generating vectors of real values to encode the meaning; this is called word embedding. Similarities between word representations are measured to identify text class. Word embeddings can be created using word2vec technique. However, recently fastText was implemented to provide better results when it is used with classifiers. In this paper, we will study the performance of well-known classifiers when using both techniques for word embedding with Arabic dataset. We applied them to real data collected from Wikipedia, and we found that both word2vec and fastText had similar accuracy with all used classifiers.