• Korean Journal of Cognitive Science
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• v.10 no.1
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• pp.57-66
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• 1999

We believe that science experiments in a laboratory are essential for science education. Scientific experiments begin with situations set by selecting and locating tools and reagents. and by proper experimental behavior, and thereafter situations are changed by natural laws and intermediate experimental behavior. While scientists and students do experiments, they build a cognitive model internally, do causal reasoning on the model to derive system behavior, and then learn scientific truth. We suggest not only a representation method for a 2-dimentional model and for ontological entities necessary in causal reasoning, but also an inferencing method to derive behavior. Chemistry experiments are chosen for the implementation. For the ontological entities, we consider experimental tools, reagents and their heirarchical structures, physics and chemistry natural laws, and functional abstraction knowledge. In order to show the usefulness of our methods, we have developed a program, called ACUArtificial Chemistry Laboratory), which provides an experiment environment where students can do non-predetermined experiments, and shows experiment려 system behavior similar to what happens in the same situation in a real world and descriptions about why it happens.

• Journal of Intelligence and Information Systems
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• v.4 no.1
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• pp.103-114
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• 1998

본 논문은 화력발전소 적용을 위한 경보처리 기반 고장진단 전문가 시스템(APDX(Alarm Processing and Diagnosis Expert System)개발에 관하여 논의한다. 본 연구에서 제시된 경보처리 알고리즘은 근본적으로는 경보 인과관계 트리를 사용하고 있으나 최종 원인 경보선택에 있어서는 경보 발생시간과 경보 우선순위 Meta-Rul를 활용한다. 경보처리 모듈에서 처리된 원인경보를 근거로 하여 본 원인경보와 관련된 고장부위를 진단하게 된다. 진단모듈에서는 경보에 관련된 센서들과 고장들 사이의 관계를 정상적으로 모델링하고 센서들의 트랜드를 정성적 해석기로 분석하여 증가, 정상, 감소의 세가지 상태에 대한 신뢰도를 출력한다. 또한 각 경보로부터 고장이 예상되는 고장타입을 센서 천이도로 모델링하여 진단에 활용된다. 최종적으로 추론모듈에서 퍼지(Fuzzy) 추론 알고리즘을 이용하여 모델된 고장 타입과 계산된 고장과의 매칭과정을 통하여 진단을 수행하게 되며, 계산 창 (Window)를 변경하면서 고장을 재 확인하게 된다.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.287-295
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• 2007

This paper proposes a novel data editing techniques with genetic algorithm (GA) in case-based reasoning (CBR) for the prediction of Korea Stock Price Index (KOSPI). CBR has been widely used in various areas because of its convenience and strength in compelax problem solving. Nonetheless, compared to other machine teaming techniques, CBR has been criticized because of its low prediction accuracy. Generally, in order to obtain successful results from CBR, effective retrieval of useful prior cases for the given problem is essential. However. designing a good matching and retrieval mechanism for CBR system is still a controversial research issue. In this paper, the GA optimizes simultaneously feature weights and a selection task for relevant instances for achieving good matching and retrieval in a CBR system. This study applies the proposed model to stock market analysis. Experimental results show that the GA approach is a promising method for data editing in CBR.

• The Journal of Society for e-Business Studies
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• v.13 no.4
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• pp.173-191
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• 2008

As volumes of electronic commerce increase rapidly, customers are faced with information overload, and it becomes difficult for them to find necessary information and select what they need. In this situation, recommender systems can help the customers search and select the products and services they need more conveniently. These days, the recommender systems play important roles in customer relationship management. In this research, we develop a recommender system that recommends the books to the customers of Internet bookstore. In previous researches on recommender systems, collaborative filtering technique has been often employed. For the collaborative filtering technique to be used, the rating scores on books given by previous purchasers have to be collected. However, the collection of rating scores is not an easy task in reality. Therefore, in this research, we employed case-based reasoning technique that can work only with the book purchase history of customers. The accuracy of recommendation of the resulting book recommender system was about 40% on the level 3 classification code.

• 전기의세계
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• v.39 no.12
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• pp.21-32
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• 1990

퍼지 논리를 이용한 제어시스템에 관하여 핵심 개념을 중심으로 기술하고자 한다. 요약컨데 이 퍼지제어기의 특징은 1) Parallel(distributed) control 2) logic control 3) linguistic control등이며 퍼지 제어가 효과적일 수 있는 제어대상(plant)로서는 수학적 모델을 적용하기 힘든 시스템으로서 경험적으로 또는 수동적인 방법으로 제어가 잘되고 있는 대상을 들 수 있다. 그 뿐만 아니라 간단한 제어기가 필요한 경우로서 보다 효과적인 제어측 Software를 쓰거나 센서 또는 필터없이 사용가능하고, Inverted Penedulum의 자세 제어처럼 정확성보다는 속도 응답 제어가 요구되는 경우 등에 효과적으로 쓸 수 있는 것으로 알려지고 있다. Fuzzy 제어는 지식 베이스의 규모에서 인공지능형 Expert System보다 Compact하고 선형.비선형 플랜트에 공히 이용될 수 있으며, 설계자는 오퍼레이터와의 접촉을 통해 룰을 구축하므로 사용자가 시스템을 이해하기 쉬운 잇점등이 있기도 한다. 그러나 가장 큰 문제는 구축해 놓은 시스템의 안전성(Stability)를 이론적으로 사전에 검증하기가 어렵고, 같은 제어대상이라 할지라도 추론방법, 소속함수의 형태선택, 룰수 등에 따라 제어성능이 바뀔수 있으나, 무엇이 어떤 영향을 주는지 규명되지 않은점 등 여러가지 연구되어야 할 내용이 많이 있다.

• Journal of Advanced Navigation Technology
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• v.12 no.1
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• pp.74-81
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• 2008

In this paper, adaptive watermarking algorithm which based on fuzzy reasoning and hybrid scheme is presented. To enforce the time and space complexity, hybrid scheme which utilize a color information as well as visual characteristics is also addressed. Proposed approach have double-aim: in first to use the visual characteristics so as to enforce the robustness of watermarking, and in second to select the optimal sub-band which is to be embedded a watermark. One of the principal advantage is that this approach involved the fuzzy inference module which is designed to select an optimal sub-band from the DWT coefficient blocks. In order to demonstrate the effectiveness of proposed algorithm, some numerical experiments of robustness and imperceptibility are evaluated with respect to such attacks as JPEG compression, noise and cropping.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.148-150
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• 2006

최근 모바일 디바이스의 기능이 다양해지면서 현대인에게 없어서는 안 될 필수품이 되었다. 모바일 디바이스의 사용영역이 널어지면서 늘어나는 개인 정보의 활용에 대한 관심이 집중되고 있다. 본 논문에서는 모바일 디바이스에서 사용자의 행동 패턴 분석 및 요약을 위한 지능형 에이전트를 제안한다 사용자의 다양한 행동 및 상태 패턴 분석을 위해 협력적 모듈 베이지안 네트워크를 사용한다. 협력적 모들 베이지안 네트워크는 비슷한 유형의 패턴끼리 모듈로 설계해 상호 협력적으로 작동하여 사용자의 특이성을 추론한다. 사용자에 기억에 남을 만한 특이성를 선택하기 위해 Noisy-OR gate를 적응하여 계산한 특이성간의 연결 강도와 특이성의 우선순위를 바탕으로 사용자의 하루 동안의 행동을 요약하여 구성한다. 추론을 위한 프로토타입을 작성하고 시나리오를 바탕으로 제안한 방법의 유용성을 보인다.

• Journal of Korean Home Economics Education Association
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• v.24 no.4
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• pp.133-144
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• 2012

The purpose of this study was to investigate Home Economics(HE) teachers' stages of concern, levels of use, and needs about the practical reasoning instruction focusing on the Concerns Based Adoption Model(CBAM). Questionnaires were administrated to HE teachers who worked for middle or high school in Korea and used HE textbooks according to the revised 2007 HE curriculum through mailing and visiting HE teacher training centers. 350 data collected from the responses were finally analyzed using SPSS 12.0. The results of the study were as follows: First, HE teachers' stages of concern about the Practical Reasoning Instruction(PRI) were demonstrated by the following order: awareness stage 0(97.05%), informational stage 1(87.06%), personal stage 2(86.23%), management stage 3(79.85%), refocusing stage 6(63.22%), consequence stage 4(61.26%), and collaboration stage 5(60.12%). Second, HE teachers' levels of use for PRI were demonstrated by the following order: preparation level 2(30.3%), orientation level 1(18.30%), refinement level 5 (18.30%), mechanical level 3: (16.0%), routine level 4(10.09%), nonuse level 0(4.0%), integration level 6(1.70%), and renewal level 7(0.60%). Third, needs for HE teachers' practical reasoning process were shown as the following order: '(O)Outline and implement a plan for action'(1.89), '(A)Analyze choices and consequences'(1.75), '(N)Note the results of your action(s)'(1.57), '(E)Evaluate information needed to solve the problem'(1.44), '(R)Recognize the problem'(1.39), and '(S)Select the best choices'(1.36).

• Journal of Internet Computing and Services
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• v.12 no.5
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• pp.113-125
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• 2011

As information resources have become more various and the number of the resources has increased, knowledge customization on the social web has been becoming more difficult. To reduce the burden, we offer a framework for context-based similarity calculation for knowledge customization using ontology on the CBR. Thereby, we newly developed context- and intensity-based similarity calculation methods which are applied to extraction of the most similar case considered semantic similarity and syntactic, and effective creation of the user-tailored knowledge using the selected case. The process is comprised of conversion of unstructured web information into cases, extraction of an appropriate case according to the user requirements, and customization of the knowledge using the selected case. In the experimental section, the effectiveness of the developed similarity methods are compared with other edge-counting similarity methods using two classes which are compared with each other. It shows that our framework leads higher similarity values for conceptually close classes compared with other methods.

• Communications of Mathematical Education
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• v.18 no.1 s.18
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• pp.89-98
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• 2004

한국과 미국(North Carolina주)의 확률과 통계 교육 내용을 고찰한 결과 한국과 미국(North Carolina주)은 내용적인 면에서 많은 차이를 보였다. 한국의 경우, 9-가 단계와 10-가 단계, 선택과목 중 수학 I, 실용수학, 이산수학 과목에 제시되어 있는 확률과 통계 영역은 심화선택과목인 확률과 통계 과목의 내용을 축소하여 재구성한 내용을 제시하고 있다. 미국(North Carolina주)은 한국과는 달리, Introductory Mathematics, Algebra(I, II), Technical Mathematics(1, 2) Advanced Mathematics, Advanced Placement Calculus, Discrete Mathematics, Integrated Mathematics(1, 2, 3), Geometry 과목에서 확률과 통계 영역은 각 과목과 연관성 있는 내용으로 구성되어 있다. 한국의 심화 선택과목인 확률과 통계 과목과 미국(North Carolina주)의 AP통계(Advanced Placement Statistics)를 비교한 결과, 전체적으로, 자료의 정리, 확률변수와 확률분포 영역에서 한국과 미국(North Carolina주)은 거의 유사성을 보이고 있지만, 통계적 추론에서는 미국(North Carolina주)이 한국에 비하여 강화되어 있음을 알 수 있다.