• Proceedings of the KAIS Fall Conference
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• 2009.12a
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• pp.597-600
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• 2009

본 논문은 동물원의 모형과 유아인형을 이용하여 유아에게 동물의 학습을 유도하는 시스템의 개발이다. 동물원의 우리에 유아의 인형을 근접시키면, 모형의 밑부분의 센서와 인형의 센서가 On 신호를 미들웨어 시스템에 전송하고 미들웨어 시스템은 PC에 동물우리의 번호를 전송함으로 동물우리에 있는 동물의 각종 학습 내용을 Display 장치를 통하여 학습할 수 있도록 하였다. 유아인형이 동물우리에 근접하였을 때 보내는 신호와 이동하였을 때의 신호을 각각 다르게 하여 학습도중에 유아의 인형이 다른곳으로 이동하게 되면 Display장치의 화면도 다른 화면을 보여줌으로 동물원에서 유아기 바라보는 시간을 최대한 유사하게 구성하였다. 또한 유아인현이 동물 우리에 근접하였을 경우 멀티미디어 효과를 통하여 동물의 울음소리 및 서식형태 등 기본적인 학습을 할 수 있도록 하였으며, 한글, 영어, 수셈 학습을 동시에 할 수 있도록 구성하였다.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11c
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• pp.1713-1716
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• 2002

HyREX는 연구용 프로토타입 XML 하이퍼미디어 문서 검색시스템으로 다국어를 지원하고 있다. HyREX는 검색을 위한 효율적인 접근 경로들을 처리하는 물리적 계층 HyPath와 질의어를 처리하는 논리적 계층 XIRQL 그리고 사용자 인터페이스인 HyGate 계층으로 이루어져 있다. 이 연구에서는 영어와 독일어 등의 검색을 지원하는 기존의 HyREX 시스템을 한글 XML 문서 검색시스템으로 확장하기 위해 먼저 한글 데이터타입을 위한 클래스를 구현하였다. 앞으로 한글 XML 문서 검색에서 정확율과 재현율을 향상하기 위해 각 문서의 인덱스에 대해 $tf{\cdot}idf$ 공식을 이용하여 가중치를 부여하고 이를 개발하고자 한다.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.05a
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• pp.911-914
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• 2005

기존 오프라인 콘텐츠는 텍스트 중심의 정보량과 신속성 등의 한계로 교육 발전에 역부족이다. 그러나 최근에는 시 공간의 제약을 탈피한 열린 학습을 제공하여 교육의 장을 확대할 수 있으며, 또한 교육의 기회를 넓힐 수 있는 무선 단말기 학습 시스템의 사용범위를 확장시키고 있다. 본 논문에서 모바일 기기를 이용하는 영어 학습 콘텐츠는 기존의 다양한 오프라인 콘텐츠에 온라인 정보 태그를 첨가함으로써, 기존의 콘텐츠에 동적인 인터랙션과 다양한 멀티미디어 정보를 융합할 수 있는 장점으로, 정적인 2차원 시각 정보만을 제공하는 기존 오프라인 책의 활용범위를 넓힌 학습 콘텐츠이다.

• Proceedings of the Korea Information Processing Society Conference
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• 2020.11a
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• pp.975-977
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• 2020

감정 분석은 문서의 주관적인 감정, 의견, 기분을 파악하기 위한 방법으로 소셜 미디어, 온라인 리뷰 등 다양한 분야에서 활용된다. 문서 내 텍스트가 나타내는 단어와 문맥을 기반으로 감정 수치를 계산하여 긍정 또는 부정 감정을 결정한다. 2015년에 구축된 네이버 영화평 데이터 20 만개에 12 만개를 추가 구축하여 감정 분석 연구를 진행하였으며 언어 모델로는 최근 자연어처리 분야에서 높은 성능을 보여주는 BERT 모델을 이용하였다. 감정 분석 기법으로는 LSTM(Long Short-Term Memory) 등 기존의 기계학습 기법과 구글의 다국어 BERT 모델, 그리고 KoBERT 모델을 이용하여 감정 분석의 성능을 비교하였으며, KoBERT 모델이 89.90%로 가장 높은 성능을 보여주었다.

• The Journal of the Convergence on Culture Technology
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• v.7 no.2
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• pp.427-436
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• 2021

The purpose of this study is to implement a machine learning language model that learns literary texts. Literary texts have an important characteristic that pairs of question-and-answer are not frequently clearly distinguished. Also, literary texts consist of pronouns, figurative expressions, soliloquies, etc. They hinder the necessity of machine learning using literary texts by making it difficult to learn algorithms. Algorithms that learn literary texts can show more human-friendly interactions than algorithms that learn general sentences. For this goal, this paper proposes three text correction tasks that must be preceded in researches using literary texts for machine learning language model: pronoun processing, dialogue pair expansion, and data amplification. Learning data for artificial intelligence should have clear meanings to facilitate machine learning and to ensure high effectiveness. The introduction of special genres of texts such as literature into natural language processing research is expected not only to expand the learning area of machine learning, but to show a new language learning method.

• The Journal of the Korea Contents Association
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• v.15 no.7
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• pp.674-683
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• 2015

One of the issues with the textbooks pertinent to the current study is whether or not the Universal Design for Learning (UDL) factors have been dealt to satisfy students with different aptitudes in learning the core objectives of the lessons. This study develops a modified version of the UDL analysis criteria from the cross curricular criteria to language teaching and learning and uses it to analyze the sequence of digital English textbooks to investigate the descriptive statistics of the UDL factors in the new textbooks. The result shows that the textbook is designed most favorably to the students with the talent of linguistic aptitude and less favorably to the students with other types of aptitudes. The sequence analysis shows that sentence/word length and appearance of new words are incrementally sequenced as students advance upper grades. However, the syntactic complexity of middle school curves up steeply which is different from the elementary school textbooks. The UDL analysis will provide learning factors to consider when designing digital English textbooks to cover different aptitudinal groups.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.9
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• pp.3510-3516
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• 2010

In this paper to make young children to learn habits of the animals, crying, features, and English and Korean language, The system was developed to target the zoo various animals exist. If young child places a doll on the front of interesting animal, then young child can learn to look through the display connected to the model. The zoo is reducing the current appearance of the zoo, sensors that can recognize animals are attached to each cage. Attached to each sensor has a unique ID, If this approach recognizes a doll baby and will transmit a unique ID to the handler. Transmitted ID search the matched value sent from the database to retrieve the content and then the content is to be output through the output device. Also if the doll near the animal's room, young children find out animal sound and basic learning by multimedia effects. At the same time Korean, English, Mathematics are learned.

• Journal of the Korea Society of Computer and Information
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• v.28 no.5
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• pp.189-196
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• 2023

This study aims to show that "Computer-assisted language learning (CALL)" and "Mobile-based language learning (MALL)" actually influence education, deviating from the traditional "drill and practice" method in foreign language education and learning due to the development of information and communication technology (IT). Specifically, for first-year college students who have relatively poor English skills and do not feel enough motivation for English learning, I will produce educational video content using multimedia authoring tools and upload it to the e-learning system. Video content is configured to be accessed and utilized through various media such as computers, smartphones, tablets, laptops, etc. Ultimately, an exploration of educational value behind the utilization of IT devices in English language Teaching(ELT) and the Second Language Acquisition (SLA) theory behind effective instructional use of such technology are presented. That is to say, the effectiveness of language learning using information and communication technology (IT) is introduced. The article closes by suggesting how to use computers and mobile media for 'Flipped Learning'.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.3
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• pp.279-288
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• 2018

In this paper, we present the results of educational innovation case study using U-Learning Box and Ubiquitous-based Test(UBT) system for 6 sample primary schools in Nepal. As Nepal is considered to be a developing country with electricity problem to the school, the U-Learning Box, consisting of a small and easy-to-use tablet PC for teacher and a small smart beam with its own battery was evaluated as the optimum solution to support continuous basic English and hygiene education for these schools. And UBT technology using tablet PC was used to evaluate and analyze basic English learning ability of the students, which helped us realized that it is necessary to improve the educational environment and develop suitable educational contents. We hope that the global educational innovation using U-Learning Box and UBT technology will become a successful model for global equality of educational opportunity project for developing countries including Nepal.

• The Journal of the Convergence on Culture Technology
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• v.7 no.4
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• pp.313-323
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• 2021

The purpose of this study is to propose rules that can identify the speaker referred by the speaker directive in the text for the realization of a machine learning-based virtual character using a literary text. Through previous studies, we found that when applying literary texts to machine learning, the machine did not properly discriminate the speaker without any specific rules for the analysis of speaker directives such as other names, nicknames, pronouns, and so on. As a way to solve this problem, this study proposes 'nine rules for finding a speaker indicated by speaker directives (including pronouns)': location, distance, pronouns, preparatory subject/preparatory object, quotations, number of speakers, non-characters directives, word compound form, dispersion of speaker names. In order to utilize characters within a literary text as virtual ones, the learning text must be presented in a machine-comprehensible way. We expect that the rules suggested in this study will reduce trial and error that may occur when using literary texts for machine learning, and enable smooth learning to produce qualitatively excellent learning results.