• 한국멀티미디어학회논문지
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• 제4권2호
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• pp.189-196
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• 2001

퍼지 논리의 추론과정에서 일부의 정보가 무시되어 적절하지 못한 추론 결과를 초래 할 수 있다. 한편 신경망은 패턴 처리에는 적합하지만 인간의 지식을 모델링하기 위해서 필요한 논리적인 추론에는 부적합하다. 그러나 신경망의 변형인 신경 논리망을 이용하면 논리적인 추론이 가능하다. 따라서 본 논문에서는 기존의 신경 논리망을 기반으로 하는 추론네트워크를 확장하여 퍼지 추론 네트워크를 구성한다. 그리고 기존의 추론 네트워크에서 사용되는 전파규칙을 보완하여 적용한다. 퍼지 추론 네트워크상에서 퍼지 규칙의 실행부에 해당하는 명제의 믿음 값을 결정하기 위해서는 추론하고자 하는 명제에 연결된 노드들을 탐색해야 한다.

• 한국지능정보시스템학회:학술대회논문집
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• 한국지능정보시스템학회 2006년도 춘계학술대회
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• pp.122-129
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• 2006

The context-awareness has become the one of core technologies and the indispensable function. for application services in ubiquitous computing environment. In this research, we incorporated the capability of context-awareness in a music recommendation system. Our proposed system consists of such components as Intention Module, Mood Module and Recommendation Module. Among these modules, the Intention Module infers whether a user wants to listen to the music or not from the environmental context information. We built the Intention Module using data mining techniques such as decision tree, support vector machine and case-based reasoning. The results showed that the case-based reasoning model outperformed the other models and its accuracy was 84.1%.

• 한국산업정보학회:학술대회논문집
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• 한국산업정보학회 2000년도 추계공동학술대회논문집
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• pp.375-389
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• 2000

Fuzzy logic ignores some information in the reasoning process. Neural networks are powerful tools for the pattern processing, but, not appropriate for the logical reasoning. To model human knowledge, besides pattern processing capability, the logical reasoning capability is equally important. Another new neural network called neural logic network is able to do the logical reasoning. Because the fuzzy inference is a fuzzy logical reasoning, we construct fuzzy inference network based on the neural logic network, extending the existing rule- inference. network. And the traditional propagation rule is modified. For the search strategies to find out the belief value of a conclusion in the fuzzy inference network, we conduct a simulation to evaluate the search costs for searching sequentially and searching by means of search priorities.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제9권3호
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• pp.91-100
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• 2020

기존의 영상 기반 질문-응답(VQA) 문제들과는 달리, 새로운 영상 기반 상식 추론(VCR) 문제들은 영상에 포함된 사물들 간의 관계 파악과 답변 근거 제시 등과 같이 추가적인 심층 상식 추론을 요구한다. 본 논문에서는 영상 기반 상식 추론 문제들을 위한 새로운 심층 신경망 모델인 KG_VCR을 제안한다. KG_VCR 모델은 입력 데이터(영상, 자연어 질문, 응답 리스트 등)에서 추출하는 사물들 간의 관계와 맥락 정보들을 이용할 뿐만 아니라, 외부 지식 베이스인 ConceptNet으로부터 구해내는 상식 임베딩을 함께 활용한다. 특히 제안 모델은 ConceptNet으로부터 검색해낸 연관 지식 그래프를 효과적으로 임베딩하기 위해 그래프 합성곱 신경망(GCN) 모듈을 채용한다. VCR 벤치마크 데이터 집합을 이용한 다양한 실험들을 통해, 본 논문에서는 제안 모델인 KG_VCR이 기존의 VQA 최고 모델과 R2C VCR 모델보다 더 높은 성능을 보인다는 것을 입증한다.

• 한국과학교육학회지
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• 제37권1호
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• pp.25-37
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• 2017

이 연구의 목적은 초등학교 6학년 1학기 4. 여러 가지 기체 단원에서 입자 개념을 학습할 때 효과적인 방안을 제시하여 현장의 교사와 학생들에게 도움을 주고자 하는 것이다. 연구자는 입자 개념을 도입하는 효과적인 방법으로 귀추적 추론법에 주목하였다. 실험집단(N=26)은 귀추적 추론 모형(Kim, 2003)을 바탕으로 재구성된 총 열두 차시 수업을 실시하였으며 비교집단((N=26)은 일반적인 교과서의 순서와 내용대로 수업을 실시하였다. 입자 개념을 살펴보기 위하여 기체 개념 이해도 검사를, 입자라는 추상적 실체를 다루는 단원이므로 인지 수준을 알기 위하여 GALT 검사를 실시하였다. 연구 결과 첫째, 처치 후 두 집단의 효과 차이를 알아본 독립표본 t 검정에서 21점 만점에 비교집단의 기체 개념 이해도 평균은 10.76, 처치집단의 기체 개념 이해도 평균은 14.65이며 t 통계값 2.890, 유의확률은 0.006으로 유의수준 .05에서 유의한 차이가 있는 것으로 나타났다. 또한 기체 개념 이해도 검사지에 입자로 표현한 횟수를 살펴보았는데 일반 집단 53회, 실험집단 114회로 두 배 이상 차이가 나타났다. 둘째, 학생들의 인지 수준과 처치 유무의 상호작용 효과에 대한 이원분산 교차설계 검증을 하였는데 상호작용 효과는 없었고, 실험집단이 인지 수준에 관계없이 비교집단보다 점수가 모두 높게 나타났다. 연구 결과를 통하여 귀추적 추론 모형을 적용하여 입자 개념을 다룬 수업의 효과를 확인할 수 있었다.

• 토지주택연구
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• 제1권1호
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• pp.1-7
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• 2010

Case-based reasoning (CBR) method can make estimators understand the estimation process more clearly. Thus, CBR is widely used as a methodology for cost estimation. In CBR, the quality of case retrieval affects the relevance of retrieved cases and hence the overall quality of the reminding capability of CBR system. Thus, it is essential to retrieve relevant past cases for establishing a robust CBR system. Case retrieval needs the following tasks to obtain appropriate case(s); indexing, search, and matching (Aamodt and Plaza 1994). However, the previous CBR researches mostly deal with matching process that has limits such as accuracy and efficiency of case retrieval. In order to address this issue, this research presents a CBR cost model for building projects that has two-step retrieval process: decision tree and nearest neighbor methods. Specifically, the proposed cost model has indexing, search and matching modules. Features in the model are divided into shape-based and scale-based attributes. Based on these, decision tree is established for facilitating the search task and nearest neighbor method was utilized for matching task. In regard to applying nearest neighbor method, attribute weights are assigned using GA optimization and similarity is calculated using the principle of distance measuring. Thereafter, the proposed CBR cost model is developed using 174 cases and validated using 12 test cases.

• 성인간호학회지
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• 제27권5호
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• pp.604-611
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• 2015

Purpose: Knowledge, clinical reasoning, and self-confidence are the basis for undergraduate education, and determine students' level of competence. The purpose of this study was to assess the effects of the addition of a one-time simulation experience to the didactic curriculum on nursing students' knowledge acquisition, clinical reasoning skill, and self-confidence. Methods: Using a quasi-experimental crossover design consisted of intervention and wait-list control groups. Participants were non-randomly assigned to the first intervention group (Group A, n=48) or the wait-list control group (Group B, n=46). Knowledge level was assessed through a multiple choice written test, and clinical reasoning skill was measured using a nursing process model-based rubric. Self-confidence was measured using a self-reported questionnaire. Results: Results indicated that students in the simulation group scored significantly higher on clinical reasoning skill and related knowledge than those in the didactic lecture group; no difference was found for self-confidence. Conclusion: Findings suggest that undergraduate nursing education requires a simulation-based curriculum for clinical reasoning development and knowledge acquisition.

• 한국수학교육학회지시리즈A:수학교육
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• 제49권2호
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• pp.223-246
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• 2010

Goos(2004) introduced educational researchers' demand for change on the way that mathematics is taught in schools and the series of curriculum documents produced by the National council of Teachers of Mathematics. The documents have placed emphasis on the processes of problem solving, reasoning, and communication. In Korea, the national curriculum documents have also placed increased emphasis on mathematical activities such as reasoning and communication(1997, 2007).The purpose of this study is to analyze the impact of inquiry-oriented instruction with guided reinvention on students' mathematical activities containing communication and reasoning for science high school students. In this paper, we introduce an inquiry-oriented instruction containing Polya's plausible reasoning, Freudenthal's guided reinvention, Forman's sociocultural approach of learning, and Vygotsky's zone of proximal development. We analyze the impact of mathematical findings from inquiry-oriented instruction on students' mathematical activities containing communication and reasoning.

• 한국지능시스템학회논문지
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• 제2권2호
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• pp.3-33
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• 1992

The successful application of fuzzy reasoning models to fuzzy control systems depends on a number of parameters, such as fuzzy membership functions, that are usually decided upon subjectively. It is shown ill this paper that the performance of fuzzy control systems call be improved if the fuzzy reasoning model is supplemented by a genetic-based learning mechanism. The genetic algorithm enables us to generate all optimal set of parameters for the fuzzy reasoning model based either on their initial subjective selection or on a random selection. It is shown that if knowledge of the domain is available, it is exploited by the genetic algorithm leading to an even better performance of the fuzzy controller.

• Nuclear Engineering and Technology
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• 제46권6호
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• pp.753-772
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• 2014

The paper presents functional modelling and its application for diagnosis in nuclear power plants. Functional modelling is defined and its relevance for coping with the complexity of diagnosis in large scale systems like nuclear plants is explained. The diagnosis task is analyzed and it is demonstrated that the levels of abstraction in models for diagnosis must reflect plant knowledge about goals and functions which is represented in functional modelling. Multilevel flow modelling (MFM), which is a method for functional modelling, is introduced briefly and illustrated with a cooling system example. The use of MFM for reasoning about causes and consequences is explained in detail and demonstrated using the reasoning tool, the MFMSuite. MFM applications in nuclear power systems are described by two examples: a PWR; and an FBR reactor. The PWR example show how MFM can be used to model and reason about operating modes. The FBR example illustrates how the modelling development effort can be managed by proper strategies including decomposition and reuse.