• The Journal of Korean Association of Computer Education
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• v.5 no.4
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• pp.111-121
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• 2002

With advancement of computer and network, world wide web(WWW) as medium of information communication is generalized in many fields. In educational aspect, applications of WWW as alternative media for class teaching or printed matter are increasing. In this article, we demonstrate a web based electronic text on the 'probability and statistics' which is one of six fields of mathematics in 7th curriculum. This text places importance on comprehension of concepts and fundamentals of probability and statistics as applied sciences and not on simple calculations of probability and statistics.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.632-637
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• 2009

Recently Renku (Haikai no Renga) is getting popular as well as Haiku in Japan. It was built up by Basho Matsuo, who was the most famous Haiku poet. It is said that Kyoshi Takahama proposed the name of "Renku" to distinguish it from "Renga" and "Haiku" in 1904. Renku meetings are held like Haiku ones regularly now in each place, and in several universities, they conduct a class exercise of Renku continuously. It is very important for plural persons to work together cooperatively. Poetry, Tanka, Haiku and Renku are usually composed of only letters. It sometimes happens that we add pictures to make them more attractive and to aim at synergy by collaboration (letters and pictures). However, the study to produce 3DCG animations of Renku has not been reported very much. Sowe studied to produce 3DCG animations work based on the rule of Renku and its evaluation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2012.07a
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• pp.176-177
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• 2012

사람의 음성을 압축하는 방법으로 Code Excited Linear Prediction (CELP) 코더가 주로 사용되어 왔다. CELP 코더의 수신단에서는 양자화 된 여기신호를 LPC 필터로 합성하여 신호를 복원한다. LPC 합성필터의 영향으로 양자화 된 여기신호의 보로노이 셀 모양이 변형되는 문제점이 있기 때문에 이런 문제점을 해결하기 위해서 Karhunen-Loeve-Transform based Classify vector Quantization (KLT-CVQ) 코더가 제안되었다. 기존 KLT-CVQ 코더는 KLT 변환과 class 선택을 위해서 Eigen Value Decomposition (EVD)을 이용해서 eigen vector와 eigen value를 계산한다. 본 논문에서는 EVD 대신에 UTV Decomposition (UTVD)을 이용하여 KLT-CVQ의 계산량 문제점을 개선하는 방법을 제안한다.

• Journal of the Korea Society of Computer and Information
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• v.22 no.1
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• pp.135-141
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• 2017

This thesis progressed research on the improvements of NCS multimedia utilization for preliminary teachers. A national module has not been developed yet in terms of child education, so this thesis suggests a curriculum according to the courses taught for freshmen and sophomores of K University Child Education majors. To lessen the burden of tremendous work and classes, provide motivation and interest in learning and maximize the effect, this thesis provides NCS based curriculum. It expects to improve task performance of teachers and help them with better skills to make class materials using up-to-date multimedia, regardless of the computer literacy of preliminary teachers. This thesis does prior research on the abilities to make use of computers and understand the level of computer literacy. Then it suggests NCS based curriculum goals and its performance standards to utilize task-suitable software. It aims to enable efficient multimedia usage, and optimize the learning efficiency of education linked to Nuri precesses.

• English Language & Literature Teaching
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• v.15 no.2
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• pp.27-49
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• 2009

This study aimed to explore EFL learners' beliefs and preferences about reading tasks and to examine the reading processes that they use for making sense of text. The subjects were comprised of 107 college students who were non-English majors and aged 19-28 years. Based on scores achieved on a reading comprehension test, they were divided into two groups (more-skilled and less-skilled readers) and asked to respond to a survey in class. The results of the survey revealed that: (1) a majority rate themselves as fair readers, which might be indicative of the insecurity they feel toward L2 reading; (2) authentic texts (especially magazines) and popular media appear to be their favorite reading materials; (3) unknown vocabulary is a major impediment to their L2 reading comprehension; (4) the more-skilled readers manifest a meaning centered view of reading, whereas the less-skilled readers center on vocabulary; and (5) both groups employ a multistrategic approach to L2 reading; however, the less-skilled readers are less successful in determining the meaning of unknown vocabulary. Pedagogical implications for EFL classroom teachers are provided.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1999.06a
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• pp.97.1-102
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• 1999

This paper porposes and efficient coding scheme for remote medical communication systems, or“telemedicine systems”. These systems require a technique which is able to transfer large volume of data such as X-ray images effectively. We have already developed a hierarchical image coding and transmission scheme (HITS), which achieves an efficient transmission of medical images simply[1]. In this paper, a new coding scheme for HITS is proposed, which used hierarchical context modeling for the purpose of improving the coding efficiency. The hierarchical context modeling divides wavelet coefficients into several sets by the value of a correspondent coefficient in their higher class, or“a parent”, optimizes a Golomb-Rice (GR) code parameter in each set, and then encodes the coefficients with the parameter. Computer simulation shows that the proposed scheme is effective with simple implementation. This is due to fact that a wavelet coefficient has dependence on its parent. As a result, high speed data transmission is achieved even if the telemedicine system consists of simple personal computers.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2018.06a
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• pp.334-335
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• 2018

최근 수 년간 비디오 콘텐츠 소비 공간이 인터넷으로 확장되며 지능적 비디오 콘텐츠 추천 기술 개발이 진행되어 왔다. 하지만 지능적 비디오 콘텐츠 추천 기술은 사용자의 기호나 업로드된 비디오 콘텐츠의 제목 등을 기반으로 하여 비디오 콘텐츠 클래스에 대한 분석 없이 유사한 비디오 콘텐츠를 탐색하고 추천해주는 기술이 대부분이다. 본 논문에서는 지능적 콘텐츠 추천을 위한 딥러닝 기반 방송 콘텐츠 클래스 분류 시스템을 제안한다. 방송 콘텐츠 내 영상 정보를 이용하여 방송 콘텐츠 클래스를 분류하며 높은 분류 정확도를 보여주는 것을 확인할 수 있다.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1437-1446
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• 2020

For the last few years, smart devices have begun to occupy an essential place in the life of children, by allowing them to access a variety of language activities and books. Various studies are being conducted on using smart devices for education. Our study extracts images and texts from kids' book with smart devices and matches the extracted images and texts to create new images that are not represented in these books. The proposed system will enable the use of smart devices as educational media for children. A deep convolutional generative adversarial network (DCGAN) is used for generating a new image. Three steps are involved in training DCGAN. Firstly, images with 11 titles and 1,164 images on ImageNet are learned. Secondly, Tesseract, an optical character recognition engine, is used to extract images and text from kids' book and classify the text using a morpheme analyzer. Thirdly, the classified word class is matched with the latent vector of the image. The learned DCGAN creates an image associated with the text.

• Journal of Engineering Education Research
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• v.25 no.1
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• pp.46-54
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• 2022

This study attempted non-face-to-face collaborative product development practice that can respond to the spread of COVID-19 by expanding existing product data management system-based product development practice. For the complete non-face-to-face product development practice, it utilized prototype development using a 3D paper model, an online class management system and social media for classes and meetings. As a result of applying the non-face-to-face method, product developments of 26 practice teams have been completed without any failures. Therefore, through this study, the author can confirm that it is possible to provide the complete non-face-to-face collaborative product development practice based on product data management systems.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.2
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• pp.177-197
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• 2020

Colleges have been forced to take non-face-to-face classes this year due to the COVID-19, and the situation is expected to continue unless the development of treatments and vaccines is carried out as soon as possible. In the situation where non-face-to-face classes are required under compulsion, two methodologies have been suggested as most representative alternatives to face-to-face classes: online real-time classes and on-demand contents classes. The purpose of this study is to compare the perceived convenience, self-fidelity, and preference of students between online real-time and on-demand contents classes by gender, school year grade, mostly using class media, and number of courses taken. Comparative results between online real-time and on-demand contents classes were statistically analyzed by surveying students at a university.