• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제5권5호
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• pp.231-242
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• 2016

빠른 웹 정보의 변화에 잘 대응하기 위해서는, 사실과 지식이 실제로 유효한 시간과 장소들도 함께 표현하고 그들 간의 관계도 추론할 수 있도록 웹 기술의 확장이 필요하다. 본 논문에서는 그동안 소규모 지식 베이스를 이용한 실험실 수준의 정성 시간 추론 연구들에서 벗어나, 웹 스케일의 대규모 지식 베이스를 추론할 수 있는 병렬 정성 시간 추론기인 MRQUTER의 설계와 구현을 소개한다. Hadoop 클러스터 시스템과 MapReduce 병렬 프로그래밍 프레임워크를 이용해 개발된 MRQUTER에서는 정성 시간 추론 과정을 인코딩 및 디코딩 작업, 역 관계 및 동일 관계 추론 작업, 이행 관계 추론 작업, 관계 정제 작업 등 몇 개의 MapReduce 작업으로 나누고, 맵 함수와 리듀스 함수로 구현되는 각각의 단위 추론 작업을 효율화하기 위한 최적화 기술들을 적용하였다. 대규모 벤치마킹 시간 지식 베이스를 이용한 실험을 통해, MRQUTER의 높은 추론 성능과 확장성을 확인하였다.

• 한국안전학회지
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• 제21권3호
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• pp.16-21
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• 2006

This paper presents a knowledge-based electrical fire cause diagnosis system using the fuzzy reasoning. The cause diagnosis of electrical fires may be approached either by studying electric facilities or by investigating cause using precision instruments at the fire site. However, cause diagnosis methods for electrical fires haven't been systematized yet. The system focused on database(DB) construction and cause diagnosis can diagnose the causes of electrical fires easily and efficiently. The cause diagnosis system for the electrical fire was implemented with entity-relational DB systems using Access 2000, one of DB development tools. Visual Basic is used as a DB building tool. The inference to confirm fire causes is conducted on the knowledge-based by combined approach of a case-based and a rule-based reasoning. A case-based cause diagnosis is designed to match the newly occurred fire case with the past fire cases stored in a DB by a kind of pattern recognition. The rule-based cause diagnosis includes intelligent objects having fuzzy attributes and rules, and is used for handling knowledge about cause reasoning. A rule-based using a fuzzy reasoning has been adopted. To infer the results from fire signs, a fuzzy operation of Yager sum was adopted. The reasoning is conducted on the rule-based reasoning that a rule-based DB system built with many rules derived from the existing diagnosis methods and the expertise in fire investigation. The cause diagnosis system proposes the causes obtained from the diagnosis process and showed possibility of electrical fire causes.

• Journal of the Korean Data and Information Science Society
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• 제10권2호
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• pp.359-367
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• 1999

본 논문에서는 의료용 전문가 시스템에 사용 가능한 의료지식을 수리논리적으로 표현하고 이에 대한 연역 및 진단추론을 행하는 방법을 제시하였다. 문제해결을 위해서는 연역추론을 행하며 원인의 규명을 위해서는 진단추론을 행하지만 일차논리 언어로 표현된 의료지식에서 두 종류의 추론을 병행할 수 있다. 그리고 의료지식에 자주 발생하는 시간에 따라 가변적인 결과의 추론방법도 함께 고찰하였다.

• 한국지구과학회지
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• 제24권6호
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• pp.524-532
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• 2003

이 연구의 목적은 진자 과제에서 학생들의 가설 생성에 있어서 귀추적 추론 능력이 중요한 역할을 한다는 가설을 검증하고자 하는 것이다. 가설을 검증하기 위하여 5학년 학생들을 대상으로 하여 진자 운동에 대한 가설 생성 검사와 진자의 길이에 대한 선지식 검사를 실시하였다. 진자의 길이에 대해 선지식을 가지고 있는 많은 학생들이 그네 과제에 대한 가설 생성에 선지식을 적용하지 못하였다. 이러한 결과는 학생들이 가설 생성에 실패한 이유가 단지 선지식이 없어서가 아니라 오히려 귀추적 추론 능력이 부족한 것과 관련된다. 학생들이 성공적으로 가설 생성을 하기 위해서는 선지식 뿐만 아니라 귀추적 추론능력도 요구된다. 그러므로 이 연구는 가설 생성 과정에 있어서 선지식 이외에도 귀추적 추론 능력이 중요한 역할을 한다는 주장을 지지한다. 이 연구는 학생들의 가설 생성 능력을 계발하기 위해서는 과학 교육에서 과학적 선언적 지식 뿐만 아니라 귀추적 추론 능력에 대한 교육도 함께 제공되어야 함을 시사한다.

• 한국수학교육학회지시리즈D:수학교육연구
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• 제25권2호
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• pp.135-158
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• 2022

This study aimed to building models to understand the relationships between reasoning resources and content knowledge. We applied Support Vector Machine and linear models to the data including fifth graders' scores in the Cornel Critical Thinking Test and the Iowa Assessments, demographic information, and learning science approach (a student-centered approach to learning called the Science Writing Heuristic [SWH] or traditional). The SWH model showing the relationships between critical thinking domains and academic achievement at grade 5 was developed, and its validity was tested across different learning environments. We also evaluated the stability of the model by applying the SWH models to the data of the grade levels. The findings can help mathematics educators understand how critical thinking and achievement relate to each other. Furthermore, the findings suggested that reasoning in mathematics classrooms can promote performance on standardized tests.

• International Journal of Safety
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• 제6권2호
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• pp.27-32
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• 2007

For last several decades with the achievement of fast economic development, the electrical fires occupies over 30 percent of total fire incidents almost every year in Korea and not decreased in spite of much times and efforts. Electrical fire cause diagnostics are to confirm a cause for the fire by examination of fire scene. Cause diagnosis methods haven't been systematized yet, because of limits for available information, investigator's biased knowledge, etc. Therefore, in order to assist the investigators and to find out the exact causes of electrical fires, required is research for an electrical fire cause diagnosis system using DB, computer programming and some mathematical tools. The electrical fire cause diagnosis system has two functions of DB and electrical fire cause diagnosis. The cause diagnosis is conducted by a case-based reasoning on a case base and rule-based reasoning on a rule base. For the diagnosis with high reliability, a mixed reasoning approach of a case-based reasoning and fuzzy rule-based reasoning has been adopted. The electrical fire cause diagnosis system proposes the electrical fire causes inferred from the diagnosis processes, and possibility of the causes as well.

• 한국과학교육학회지
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• 제23권4호
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• pp.430-441
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• 2003

The purpose of this study was to investigate the effects of students' prior knowledge on scientific reasoning in solving a pendulum task with a computer simulation. Subjects were 60 Korean students: 27 fifth-grade students from an elementary school and 33 seventh grade students from a middle school located in a city with 300,000 people. This study adapted a pendulum task presented with a computer simulation on which subjects would use a pattern of multivariable causal inferences. The subjects were interviewed individually in a three-phase structured interview by the researcher and three assistants while he/she was investigating the pendulum task. This study showed that most students across grades focused heavily on demonstrating the primacy of their prior knowledge or their current hypothesis. In addition, students' theories that are part of one's prior knowledge have a significant impact on formulating, testing, and revising hypotheses. Therefore, this study supported the notion that students' prior knowledge had a strong effect on students' experimental intent and hypothesis evaluation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권6호
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• pp.1996-2011
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• 2021

To understand a trend is to explore the intricate process of how something or a particular situation is constantly changing or developing in a certain direction. This exploration is about observing and describing an unknown field of knowledge, not testing theories or models with a preconceived hypothesis. The purpose is to gain knowledge we did not expect and to recognize the associations among the elements that were suspected or not. This generally requires examining a massive amount of data to find information that could be transformed into meaningful knowledge. That is, looking through the lens of big-data analytics with an inductive reasoning approach will help expand our understanding of the complex nature of a trend. The current study explored the trend of well-being in South Korea using big-data analytic techniques to discover hidden search patterns, associative rules, and keyword signals. Thereafter, a theory was developed based on inductive reasoning - namely the hook, upward push, and downward pull to elucidate a holistic picture of how big-data implications alongside social phenomena may have influenced the well-being trend.

• 한국수학교육학회지시리즈D:수학교육연구
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• 제18권3호
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• pp.171-185
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• 2014

Mathematically deductive reasoning skill is one of the major learning objectives stated in senior secondary curriculum (CDC & HKEAA, 2007, page 15). Ironically, student performance during routine assessments on geometric reasoning, such as proving geometric propositions and justifying geometric properties, is far below teacher expectations. One might argue that this is caused by teachers' lack of relevant subject content knowledge. However, recent research findings have revealed that teachers' knowledge of teaching (e.g., Ball et al., 2009) and their deductive reasoning skills also play a crucial role in student learning. Prior to a comprehensive investigation on teacher competency, we use a case study to investigate teachers' knowledge competency on how to teach their students to mathematically argue that, for example, two triangles are congruent. Deductive reasoning skill is essential to geometry. The initial findings indicate that both subject and pedagogical content knowledge are essential for effectively teaching this challenging topic. We conclude our study by suggesting a method that teachers can use to further improve their teaching effectiveness.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2005년도 추계학술대회 및 정기총회
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• pp.237-240
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• 2005

This paper describer a design expert system which determines the design values of shadow mask using Case-Based Reasoning. In Case-Based Reasoning, it is important to both retrieve similar cases and adapt the cases to meet the design specifications exactly. Especially, the difficulty in automating the adaptation process will prevent the designers from using the design expert systems efficiently and easily. This paper explains knowledge-based design support systems for shadow mask through neural network-based case adaptation. Specifically, we developed 1) representing design knowledge and 2) adaptive case-based reasoning method using RBFN (Radial Basis Function Network).