• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2019.11a
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• pp.14-16
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• 2019

명시적지식(Explicit Knowledge) 및 암시적지식(Implicit Knowledge) 등 외국어학습 이론을 적용한 선박교통관제사 영어교육 개선 방향을 연구하여 선박교통관제사 현장직무교육의 실효성을 증대하는 등 선박교통안전강화의 기반을 마련하고자 하였다.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.13 no.1
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• pp.355-363
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• 2012

The Integration of multi-agent architecture and blackboard architecture may lead to a new architecture to cope with new application areas which need some good and strong points of both the architectures. This paper suggests an integrated architecture of blackboard architecture and multi-agent architecture by using event-based implicit invocation pattern and a blackboard event detection mechanism based on Rete network. From the viewpoints of weak couplings of system components and flexible control of knowledge source agents, it is desirable to use the event-based implicit invocation pattern in the integrated architecture. But the pattern itself does not concern the performance of the architecture, and it is very critical to the performance of the integrated architecture to detect efficiently the blackboard events which can activate knowledge source agents which can contribute to the problem-solving processes of the integrated architecture. The integrated architecture suggested in this paper uses a blackboard event detection mechanism based on Rete network to detect efficiently blackboard events which can activate knowledge source agents.

• The Bulletin of The Korean Astronomical Society
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• v.37 no.2
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• pp.102.2-102.2
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• 2012

이 연구의 목적은 거시적인 관점에서 NOS의 중요한 요소들을 강조한 Flow map(oh, 2011)를 이용한 명시적이고 암시적인 교육의 본성교육이 얼마나 이루어졌는가를 알아본다. 과학의 본성은 지식의 내용뿐만 아니라 지식이 어떻게 형성되었는가에 있다. 이러한 과학의 본성을 이해한다는 것이 현대의 과학의 중요한 목적중의 하나인 과학적 소양을 얻는 것이다. 이를 구체적으로 실현하는 교수 모형으로 가장 중요한 이론의 생성과 실험에 의한 확증과 이론의 확증을 미시적인 관점으로 연구를 전개하였다. 따라서 먼저 Kuhn(1996)의 과학철학 이론과 NOS를 통한 Flow map 개발에 이론적 배경이 된 과학의 본성의 정의, 과학의 본성에 대해 합의된 핵심 요소들, Kuhn(1996)의 과학철학 이론을 바탕으로 한 Oh(2011)가 제안한 Flow map의 구조를 알아본다. 연구방법은 귀추(abduction)를 통한 가설의 생성과정과 확증을 보여주는 Oh(2012)의 자연과학의 추리과정을 이용하여 충북대학교 천문우주학과에서 자연과학캠프에 참여한 고등학생들을 대상으로, "Galileo의 흑점발견과정"으로부터 현대의 태양의 흑점 모형을 이해하도록 한다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.514-516
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• 2005

인간을 상대하는 자율장치는 고객의 자발적인 협조를 얻기 위해 암시적인 신호에 포함된 감정과 태도를 인지할 수 있어야 한다. 인간에게 음성은 가장 쉽고 자연스럽게 정보를 교환할 수 있는 수단이다. 지금까지 감정과 태도를 이해할 수 있는 자동시스템은 발성문장의 피치와 에너지에 기반한 특징을 활용하였다. 이와 같은 기존의 감정인식 시스템의 성능은 문장의 특정한 억양구간이 감정과 태도와 관련을 갖는다는 언어학적 지식의 활용으로 보다 높은 향상이 가능하다. 본 논문에서는 한국어 문미억양에 대한 언어학적 지식을 피치기반 특징과 다층신경망을 활용하여 구현한 자동시스템에 적용하여 감정인식률을 향상시킨다. 한국어 감정음성 데이터베이스를 대상으로 실험을 실시한 결과 $4\%$의 인식률 향상을 확인하였다.

• Journal of Korean language education
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• v.29 no.4
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• pp.93-112
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• 2018

The purpose of this study is to deal with vocabulary in KFL. As a result of this study, learners learned vocabulary on average 43 points through contextual inference and introduction of the class to activate background knowledge. In particular, the implicit method showed the highest learning rate of 52 points, and the thematic method had a 41 point-learning rate. In contrast, the semantic method was the lowest with a 25 point-learning rate. There was no significant difference in the improvement rate of upper vocabulary learners, but in the case of the lower learner, there was significant difference in the improvement rate. The difference was not significant in the post-test relative gain rate of upper learners, but there was significant in lower learners. In the delayed test relative gain rate, the difference was significant in all groups. There was correlation between vocabulary difficulty and score, but there was no correlation with the thematic method. And there was no correlation between vocabulary difficulty, improvement rate and relative gain rate in all three classes. However, content understanding, lexical grade, improvement rate, and relative gain rate showed a significant correlation.

• The Journal of Korean Academy of Orthopedic Manual Physical Therapy
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• v.14 no.2
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• pp.41-49
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• 2008

임상추론은 환자를 평가하고 관리하는데 사용되는 임상가의 필수적인 생각 또는 동적인 인지과정이라고 할 수 있다. 임상추론은 환자의 문제를 인식하고 식별하며 더 나은 환자관리가 이루어지도록 환자의 상태에 대처하며 정보를 해석하고 분석하는 것으로서 이를 위해 임상가는 적절한 지식을 가지고 있어야 하며 임상추론 기술과 관련된 폭넓은 이해가 요구된다. 임상추론은 치료사, 환자, 그리고 환경간의 상호관계를 가진 복잡한 과정으로 임상추론과정에서 치료사와 환자간에는 충분한 협조가 이루어져야 한다. 임상추론에서의 해석적 모델로는 진단적 추론, 상호작용의 추론, 이야기적 추론, 협조적 추론, 예언적 추론, 윤리적 추론, 추론의 교육 등이 제시된다. 임상추론 과정에서 필수적인 주요 요소는 충분한 지식, 인지와 초인지 기술을 포함하며 이들 요소는 치료사와 환자간의 관계에서 발달되어야 한다. 이들 기술 중에 어떠한 실수라도 임상추론의 오류를 초래할 수 있다. 추론에서 오류의 원인으로는 암시된 정보의 잘못된 인지, 임상페턴에 대한 지식부족, 특정 상태에 대해 알려진 사실을 잘못 적용하는 경우를 들 수 있다. 오류는 임상추론 과정의 어떤 단계에서도 일어날 수 있으므로 효과적인 학습전략을 통하여 이들 오류를 예방할 수 있을 것이다.

• Journal of The Korean Association For Science Education
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• v.40 no.2
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• pp.127-140
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• 2020

This study investigated the influence of an explicit and reflective modeling instruction on the metamodeling knowledge of fourth-graders. Two fourth-grade classes in an elementary school in Seoul were selected and each class was assigned to an experimental group and a control group, respectively. The experimental group was engaged in explicit and reflective modeling instruction, whereas the control group was engaged in implicit modeling instruction. The two groups were surveyed before and after instruction on the basis of five metamodeling knowledge categories: definition, purpose, design/construction, changeability, and multiplicity. The experimental group showed positive changes in model's meaning, examples, purpose, changeability as well as multiplicity. In contrast, fewer students in the control group understood the meaning of the model and modeling. They also showed limited changes in their understandings with regards to the modeling instruction, and could not expand their understanding of the nature of model and modeling. The findings indicate that an explicit and reflective modeling instruction has positive influence on elementary students' metamodeling knowledge.

• Journal of KIISE:Databases
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• v.28 no.4
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• pp.577-586
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• 2001

Recently data mining, which is analyzing the stored data and discovering potential knowledge and information in large database is a key research topic in database research data In this paper, we study methods of discovering association rules which are one of data mining techniques. And we propose a technique of discovering association rules using the relative support to consider significant rare data which have the high relative support among some data. And we compare and evaluate existing methods and the proposed method of discovering association rules for discovering significant rare data.

• Journal of KIISE:Software and Applications
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• v.37 no.4
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• pp.282-296
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• 2010

OWL is an ontology language for the Semantic Web, and suited to modelling the knowledge of a specific domain in the real-world. Ontology also can infer new implicit knowledge from the explicit knowledge. However, the modeled knowledge cannot be complete as the whole of the common-sense of the human cannot be represented totally. Ontology do not concern handling nonmonotonic reasoning to detect incomplete modeling such as the integrity constraints and exceptions. A default rule can handle the exception about a specific class in ontology. Integrity constraint can be clear that restrictions on class define which and how many relationships the instances of that class must hold. In this paper, we propose a practical reasoning system for open and closed-world reasoning that supports a novel hybrid integration of ontology based on open world assumption (OWA) and non-monotonic rule based on closed-world assumption (CWA). The system utilizes a method to solve the problem which occurs when dealing with the incomplete knowledge under the OWA. The method uses the answer set programming (ASP) to find a solution. ASP is a logic-program, which can be seen as the computational embodiment of non-monotonic reasoning, and enables a query based on CWA to knowledge base (KB) of description logic. Our system not only finds practical cases from examples by the Protege, which require non-monotonic reasoning, but also estimates novel reasoning results for the cases based on KB which realizes a transparent integration of rules and ontologies supported by some well-known projects.

• Journal of Korea Spatial Information System Society
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• v.1 no.1 s.1
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• pp.5-18
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• 1999

Recently, the necessity of automatic knowledge extraction from spatial data stored in spatial databases has been increased. Spatial data mining can be defined as the extraction of implicit knowledge, spatial relationships, or other knowledge not explicitly stored in spatial databases. In order to extract useful knowledge from spatial data, an object management system that can store spatial data efficiently, provide very fast indexing & searching mechanisms, and support a distributed computing environment is needed. In this paper, we designed and implemented an open object management system for spatial data mining, that supports efficient management of spatial, aspatial, and knowledge data. In order to develop this system, we used Open OODB that is a widely used object management system. However, the lark of facilities for spatial data mining in Open OODB, we extended it to support spatial data type, dynamic class generation, object-oriented inheritance, spatial index, spatial operations, etc. In addition, for further increasement of interoperability with other spatial database management systems or data mining systems, we adopted international standards such as ODMG 2.0 for data modeling, SDTS(Spatial Data Transfer Standard) for modeling and exchanging spatial data, and OpenGIS Simple Features Specification for CORBA for connecting clients and servers efficiently.