• Journal of KIISE:Software and Applications
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• v.36 no.5
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• pp.411-419
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• 2009

In order to derive hidden Information (concept subsumption, concept satisfiability and realization) of OWL ontologies, a number of OWL reasoners have been introduced. Most of the reasoners were implemented to be based on tableau algorithm. However this approach has certain limitation. This paper presents architecture for Medusa. The Medusa is an extended DL-reasoner for SWRL(Semantic Web Rule Language) reasoning under well-founded semantics with ontologies specified in Description Logic. Description logic based ontology reasoners theoretically explore knowledge representation and its reasoning in concept languages. However these logics are not equipped with rule-based reasoning mechanisms for assertional knowledge base; specifically, rule and facts in logic programming, or interaction of rules and facts with terminology. In order to deal with the enriched reasoning, The Medusa provides combining DL-knowledge base and rule based reasoner. The described prototype uses $Prot{\acute{e}}g{\acute{e}}$ API[1] for controlling communication with the ontology reasoner.

• Journal of Educational Research in Mathematics
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• v.21 no.2
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• pp.165-180
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• 2011

Mathematical symbols concisely represent mathematical contents related to terms by describing their mathematical meanings implicitly. All symbols in elementary school mathematics textbooks are stated as to be read so that elementary school students could understand their mathematical meanings. The same is somewhat true as in middle school mathematics textbooks, however it is often the case that some symbols are difficult to be read and understood because their statements are unclear or different. In this study, we analyze problems and suggest implications on teaching and learning mathematics based on the statements and understanding of reading symbols in middle school mathematics textbooks.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.11a
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• pp.23-26
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• 2023

본 논문에서는 서술형 수학 문제 풀이 모델의 숫자 대소관계 파악을 위한 명시적 자질추출방식 Explicit Feature Extraction(EFE) Reasoner 모델을 제안한다. 서술형 수학 문제는 자연현상이나 일상에서 벌어지는 사건을 수학적으로 기술한 문제이다. 서술형 수학 문제 풀이를 위해서는 인공지능 모델이 문장에 함축된 논리를 파악하여 수식 또는 답을 도출해야 한다. 때문에 서술형 수학 문제 데이터셋은 인공지능 모델의 언어 이해 및 추론 능력을 평가하는 지표로 활용되고 있다. 기존 연구에서는 문제를 이해할 때 숫자의 대소관계를 파악하지 않고 문제에 등장하는 변수의 논리적인 관계만을 사용하여 수식을 도출한다는 한계점이 존재했다. 본 논문에서는 자연어 이해계열 모델 중 SVAMP 데이터셋에서 가장 높은 성능을 내고 있는 Deductive-Reasoner 모델에 숫자의 대소관계를 파악할 수 있는 방법론인 EFE 를 적용했을 때 RoBERTa-base 에서 1.1%, RoBERTa-large 에서 2.8%의 성능 향상을 얻었다. 이 결과를 통해 자연어 이해 모델이 숫자의 대소관계를 이해하는 것이 정답률 향상에 기여할 수 있음을 확인한다.

• Journal of Elementary Mathematics Education in Korea
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• v.14 no.3
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• pp.885-905
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• 2010

This study questions that mathematical evaluations strive to memorize fragmentary knowledge and have an objective test. To solve these problems on mathematical education We did descriptive test. Through the descriptive test, students think and express their ideas freely using mathematical terms. We want to know if that procedure is correct or not, and, if they understand what was being presented. We studied this because We want to analyze where and what kinds of faults they committed, and be able to correct an error so as to establish a correct mathematical concept. The result from this study can be summarized as the following; First, the mistakes students make when solving the descriptive tests can be divided into six things: error of question understanding, error of concept principle, error of data using, error of solving procedure, error of recording procedure, and solving procedure omissions. Second, students had difficulty with the part of the descriptive test that used logical thinking defined by mathematical terms. Third, errors pattern varied as did students' ability level. For high level students, there were a lot of cases of the solving procedure being correct, but simple calculations were not correct. There were also some mistakes due to some students' lack of concept understanding. For middle level students, they couldn't understand questions well, and they analyzed questions arbitrarily. They also have a tendency to solve questions using a wrong strategy with data that only they can understand. Low level students generally had difficulty understanding questions. Even when they understood questions, they couldn't derive the answers because they have a shortage of related knowledge as well as low enthusiasm on the subject.

• Journal of the Korea Convergence Society
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• v.8 no.8
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• pp.225-230
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• 2017

The Sijo provides dynamic rated therapeutic activities in our life. This study aims to search for the literary therapeutic function secreted from the Sijo that ends with a noun. As a result, the noun used at the final sentence secretes a predicative function. This kind of Sijo functions as twelve sound steps, even though it is condensed of just eleven sound steps with one sound step omitted. This functional secretion of Sijo is therapeutic predicate concerned with encoding of literary therapy. Thus it become possible to activate the therapeutic encoding in Sijo or a language by uttering only noun, instead of the predicate. That's because the noun in the last sentence of Sijo permeated in the human body and is done subject, and neuron of the body becomes a predicate, so that the Sijo's subject and the neuron's predicate are fused into a sentence. During the course the human body seems to recognize that the neuron's nucleus analyzes the information of the noun and makes a new sentence. This recognition might also be regarded as a process of encoding that has therapeutic functions secreted from the human body.

• School Mathematics
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• v.10 no.3
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• pp.401-422
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• 2008

In the current school curriculum, an alternative assessment method which focuses more on the problem solving process rather than the final solution is being investigated. The goal is to evaluate students' understanding of the subject. A descriptive evaluation is being suggested as a way of examining the thought process of the students by a structured analysis of the problem solving process. But currently, there are not enough descriptive problems available for teachers to effectively carry out the alternative assessment method in the elementary school mathematics curriculum. In this research, we surveyed 197 elementary school teachers in Seoul to determine the status of descriptive evaluation in elementary school mathematics and to understand the teachers perception about the new assessment method. The goal of the survey was to find an effective implication of the new assessment method in elementary mathematics classes. The research showed that the elementary teachers use this assessment method about 4 to 7 times per month in their classes. They give descriptive problem test anytime they think it is appropriate during the Instruction of the topic. More than 90% of the teachers were using this assessment method to improve students' creativity and mathematical thinking. The teachers in the survey also commented that the teachers' administrative responsibility should be reduced and that the school environment in general should be improved for the new assessment method to be successful. Finally the study also showed that development of more descriptive problems in each grade level is needed to progress the new assessment method.

• Proceedings of the Korea Contents Association Conference
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• 2011.05a
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• pp.189-190
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• 2011

이 연구는 브랜드 네임 스펙트럼 이론을 이용하여 병원 명칭의 특성을 분석하였다. 연구대상은 수도권 지역에 위치하는 모든 병원을 대상으로 하였고, 명칭은 의미있는 단위로 분류한 후 스펙트럼 이론에 따라 분류하였다. 분석결과 임의적 명칭의 빈도가 가장 높았고, 다음으로는 암시적, 서술적, 그리고 조어적 명칭의 순이었다. 단일 스펙트럼 구성된 명칭이 가장 많았으며, 스펙트럼이 2개와 3개로 구분된 명칭의 순이었다.

• Proceedings of the Korea Contents Association Conference
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• 2013.05a
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• pp.85-86
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• 2013

이 연구는 더글라스 서크(Douglas Sirk) 감독의 <천국이 허락한 모든 것> (1955)과 이용주 감독의 <건축학 개론>(2012)에서 집에 대한 '재현' 공간을 고찰하였다. 두 멜로드라마 장르 영화는 등장인물들이 대사로 직접 표현한 수 없는 것들을 가구, 소품 등의 미장센, 특히 리모델링을 하는 집을 통해서 보여준다. 집은 욕망을 스타일과 형식을 통해 산출한다는 점에서 멜로드라마 장르의 공간을 특징짓는 서술적 사건과 모티프를 담고 있는 구체적 장소의 역할을 한다. 이러한 맥락에서 이 연구는 멜로드라마 장르에서 집과 풍경들이 어떻게 영화적 공간(cinematic space)을 구성하고 그 재현공간이 갖는 사회적인 의미를 고찰한다.

• 한국어정보학회:학술대회논문집
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• 2016.10a
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• pp.111-116
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• 2016

의미역은 자연어 문장의 서술어와 관련된 논항의 역할을 설명하는 것으로, 주어진 서술어에 대한 논항인식(Argument Identification) 및 분류(Argument Labeling)의 과정을 거쳐 의미역 결정(Semantic Role Labeling)이 이루어진다. 이를 위해서는 격틀 사전을 이용한 방법이나 말뭉치를 이용한 지도 학습(Supervised Learning) 방법이 주를 이루고 있다. 이때, 격틀 사전 또는 의미역 주석 정보가 부착된 말뭉치를 구축하는 것은 필수적이지만, 이러한 노력을 최소화하기 위해 본 논문에서는 비모수적 베이지안 모델(Nonparametric Bayesian Model)을 기반으로 서술어에 가능한 의미역을 추론하는 비지도 학습(Unsupervised Learning)을 수행한다.

• Proceedings of the Korea Contents Association Conference
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• 2005.11a
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• pp.279-283
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• 2005

요즘 사회에 이슈가 되는 것을 꼽으라면 사람들은 주저 없이 Ubiquitous를 말할 것이다. Ubiquitous란 사용자가 네트워크나 컴퓨터를 의식하지 않고 장소에 상관없이 자유롭게 네트워크에 접속할 수 있는 정보통신 환경을 의미한다. Sensor Network과 RFID는 Ubiquitous 환경을 구축하는데 필요한 아주 중요한 요소이다. 본 논문에서는 기존에 구현된 Sensor Network과 RFID의 기술을 이용하여 Ubiquitous Healthcare system의 일환으로 '노약자 관리 시스템 구축'에 대해 서술하고자 한다. 특별한 관리가 필요한 노약자(어린아이, 치매성 질환을 가진 노인, 정신지체 장애인 등)를 대상으로 보호자와 응급센터와의 네트워크를 구축하고 기반시설과의 연동을 통해서 보다 체계적이고 효율적인 관리 시스템에 대해서 서술한다. Sensor Network과 RFID의 기본적인 개념, 노약자 관리시스템의 필요성, 제안된 관리시스템에 관해 서술한다.