• Educational Technology International
• /
• 제10권1호
• /
• pp.25-40
• /
• 2009

The purpose of this study was to explore procedures and modalities on collaborative visualization processing of text information for developing e-Learning contents. In order to investigate, two research questions were explored: 1) what are procedures on collaborative visualization processing of text information, 2) what kinds of patterns and modalities can be found in each procedure of collaborative visualization of text information. This research method was employed a qualitative research approaches by means of grounded theory. As a result of this research, collaborative visualization processing of text information were emerged six steps: identifying text, analyzing text, exploring visual clues, creating visuals, discussing visuals, elaborating visuals, and creating visuals. Collaborative visualization processing of text information came out the characteristic of systemic and systematic system like spiral sequencing. Also, another result of this study, modalities in collaborative visualization processing of text information was divided two dimensions: individual processing by internal representation, social processing by external representation. This case study suggested that collaborative visualization strategy has full possibility of providing ideal methods for sharing cognitive system or thinking system as using human visual intelligence.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2000년도 ITC-CSCC -2
• /
• pp.835-838
• /
• 2000

Popular methods for extracting a text region in video images are in general based on analysis of a whole image such as merge and split method, and comparison of two frames. Thus, they take long computing time due to the use of a whole image. Therefore, this paper suggests the faster method of extracting a text region without processing a whole image. The proposed method uses line sampling methods, FFT and neural networks in order to extract texts in real time. In general, text areas are found in the higher frequency domain, thus, can be characterized using FFT The candidate text areas can be thus found by applying the higher frequency characteristics to neural network. Therefore, the final text area is extracted by verifying the candidate areas. Experimental results show a perfect candidate extraction rate and about 92% text extraction rate. The strength of the proposed algorithm is its simplicity, real-time processing by not processing the entire image, and fast skipping of the images that do not contain a text.

• 대한예방한의학회지
• /
• 제16권3호
• /
• pp.107-117
• /
• 2012

Objective : Processing of medicinals are one of the most important part in medicinal treatment. However, in text books, there are disagreements and several terms with same meanings. Method : We tried to compare the processing of medicinals in text book, Bonchohak especially in exterior-releasing medicinal and heat-clearing medicinal. Results : The terms of processing of medicinals in introductions of text book, Bonchohak are different from those in an itemized discussion of exterior-releasing medicinal and heat-clearing medicinal. Conclusion : The terms of processing of medicinals in text book, Bonchohak should be reorganized and improved to make be clear and sure as a text book.

• Journal of Information Processing Systems
• /
• 제13권5호
• /
• pp.1397-1409
• /
• 2017

For text categorization task, distinctive text features selection is important due to feature space high dimensionality. It is important to decrease the feature space dimension to decrease processing time and increase accuracy. In the current study, for text categorization task, we introduce a novel statistical feature selection approach. This approach measures the term distribution in all collection documents, the term distribution in a certain category and the term distribution in a certain class relative to other classes. The proposed method results show its superiority over the traditional feature selection methods.

• Journal of Information Processing Systems
• /
• 제10권1호
• /
• pp.55-68
• /
• 2014

Automatic segmentation of foreground text from the background in degraded document images is very much essential for the smooth reading of the document content and recognition tasks by machine. In this paper, we present a novel approach to the binarization of degraded document images. The proposed method uses a new local contrast feature extracted based on the stroke width of text. First, a pre-processing method is carried out for noise removal. Text boundary detection is then performed on the image constructed from the contrast feature. Then local estimation follows to extract text from the background. Finally, a refinement procedure is applied to the binarized image as a post-processing step to improve the quality of the final results. Experiments and comparisons of extracting text from degraded handwriting and machine-printed document image against some well-known binarization algorithms demonstrate the effectiveness of the proposed method.

• 한국정보처리학회논문지
• /
• 제6권6호
• /
• pp.1481-1492
• /
• 1999

1990년대 웹 개념의 등장으로 인터넷을 개방형 네트？, 사용자 친근성 및 편의성이라는 특성을 바탕으로 급속히 일반화되면서 각종 정보를 제공하는 정보 시스템에서도 커다란 변화를 가져왔다. 웹은 텍스트 정보뿐만 아니라 이미지, 오디오, 비디오 등 멀티미디어 정보를 쉽게 제공함으로써 기존 정보 시스템의 웹 기반으로의 전환을 가속화시키게 되었다. 물론 정보 내용도 텍스트 위주의 단순 초록 정보에서 전문(Full-Text) 정보로 급속히 이전되기 시작하였으며, 전문 정보를 처리하는 다양한 문서 포맷들로 등장하기 시작하였다. 하지만, 전문 정보는 본질적으로 대용량의 시스템 메모리, 막대한 처리시간, 보다 많은 전송용량 등을 요구하게 되므로 웹 기반 전문 시스템의 구축시 이러한 요인들을 세밀하게 비교 평가하여야 한다. 따라서 본 연구는 웹 기반 정보 시스템에서 어떻게 전문을 처리할 것인가에 초점을 맞추어 문서의 통합 정보 기능을 제공하는 정보시스템을 설계 구현한다. 먼저 인터넷상에서 표준 문서형식으로 사용중이거나 개발중인 문서 포맷들의 특징을 검토하고, 정보 시스템의 관점에서 전문정보를 어떤 문서 포맷으로 처리하는 것이 적합한가를 실험하고 평가한다. 그리고 이를 기반으로 본 연구의 목적인 전문 정보를 PDF 문서로 제공하는 웹 기반 정보 시스템을 설계 구현한다.

• 한국정보처리학회논문지
• /
• 제3권5호
• /
• pp.1121-1129
• /
• 1996

Text-to-Speech 시스템에서 자연스럽게 음성을 합성하기 위해서는 운율과 길이 에 대한 처리가 선행되어야 한다. 이를 위해서, 자연어 처리에 의해 분석된 문장들에 대해 억양 규칙을 적용한 후, 반복적인 실험을 통해 운율 및 길이 정보를 추출하였다. 본 논문에서는 이러한 정보를 이용하여 Text-to-Speech 시스템에서 자연성을 향상 시 킬 수 있는 방법을 제안한다. 실험 결과, 본 논문에서 제안하고 구현한 무제한 Text- to-Speech 시스템이 이러한 정보들을 사용하지 않는 시스템과 비교해서 더 자연스럽게 문장들을 합성해 낸다는 것을 보였다.

• 한국정밀공학회지
• /
• 제16권7호
• /
• pp.196-202
• /
• 1999

Recent trend changes a criterion for evaluation of burner that environmental problem is raised as global issue. For efficient driving problem, the higher thermal efficiency and the lower oxygen in exhaust gas, burner is evaluated the better. For environmental problem, burner must satisfy $NO_{X}$ limit and CO limit. Consequently, 'good burner' means on whose thermal efficiency is high under the constraint of $NO_{X}$ and CO consistency. To make existing burner satisfy recent criterion, it is highly recommended to develop feedback control scheme whose output is the consistency of $NO_{X}$ and CO. This paper describes development of real time flame diagnosis technique that evaluate and diagnose combustion state such as consistency of components in exhaust gas, stability of flame in quantitative sense. This study focuses on wave length of luminescence from chemical reaction measurement of the luminescence via optical measuring apparatus and derive correlation with consistency of components in exhaust gas by image processing technique.

• Journal of Information Processing Systems
• /
• 제13권4호
• /
• pp.863-875
• /
• 2017

The traditional text similarity measurement methods based on word frequency vector ignore the semantic relationships between words, which has become the obstacle to text similarity calculation, together with the high-dimensionality and sparsity of document vector. To address the problems, the improved singular value decomposition is used to reduce dimensionality and remove noises of the text representation model. The optimal number of singular values is analyzed and the semantic relevance between words can be calculated in constructed semantic space. An inverted index construction algorithm and the similarity definitions between vectors are proposed to calculate the similarity between two documents on the semantic level. The experimental results on benchmark corpus demonstrate that the proposed method promotes the evaluation metrics of F-measure.

• 한국언어정보학회:학술대회논문집
• /
• 한국언어정보학회 2007년도 정기학술대회
• /
• pp.515-521
• /
• 2007

The text categorization is an important field for the automatic text information processing. Moreover, the authorship identification of a text can be treated as a special text categorization. This paper adopts the conceptual primitives' expression based on the Hierarchical Network of Concepts (HNC) theory, which can describe the words meaning in hierarchical symbols, in order to avoid the sparse data shortcoming that is aroused by the natural language surface features in text categorization. The KNN algorithm is used as computing classification element. Then, the experiment has been done on the Chinese text authorship identification. The experiment result gives out that the processing mode that is put forward in this paper achieves high correct rate, so it is feasible for the text authorship identification.