• Journal of the Korean School Mathematics Society
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• v.15 no.3
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• pp.511-533
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• 2012

In order to determine whether there is a significant correlation between relational understanding and creative math. problem finding ability, this study performed relational understanding and problem finding ability tests on a sample of 186 8th grade middle school students. According to the study results, we found a very significant positive correlation between relational understanding and the creativity of the mathematising ability and the combining ability of mathematical concepts in the problem finding ability. Although there was no statistically significant correlation between relational understanding and the extension ability of mathematical facts, the results from analyzing the students response rate and actual scores in each test showed that students with high relational understanding scores also had high response rate and high scores in analogical reasoning and inductive reasoning. Through this study, therefore, relational understanding is found to have a positive impact on the creative mathematics problem finding ability.

• KIPS Transactions on Software and Data Engineering
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• v.7 no.12
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• pp.485-496
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• 2018

So far, the deep learning, a field of artificial intelligence, has achieved remarkable results in solving problems from unstructured data. However, it is difficult to comprehensively judge situations like humans, and did not reach the level of intelligence that deduced their relations and predicted the next situation. Recently, deep neural networks show that artificial intelligence can possess powerful relational reasoning that is core intellectual ability of human being. In this paper, to analyze and observe the performance of Relation Networks (RN) among the neural networks for relational reasoning, two types of RN-based deep neural network models were constructed and compared with the baseline model. One is a visual question answering RN model using Sort-of-CLEVR and the other is a text-based question answering RN model using bAbI task. In order to maximize the performance of the RN-based model, various performance improvement experiments such as hyper parameters tuning have been proposed and performed. The effectiveness of the proposed performance improvement methods has been verified by applying to the visual QA RN model and the text-based QA RN model, and the new domain model using the dialogue-based LL dataset. As a result of the various experiments, it is found that the initial learning rate is a key factor in determining the performance of the model in both types of RN models. We have observed that the optimal initial learning rate setting found by the proposed random search method can improve the performance of the model up to 99.8%.

• Journal of Educational Research in Mathematics
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• v.19 no.3
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• pp.355-369
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• 2009

Though there is no agreement on the definition of analogical reasoning, there is no doubt that analogical reasoning is the means of mathematical knowledge construction. Mathematicians generally have a tendency or desire to find similarities between new and existing Ideas, and new and existing representations. They construct appropriate links to new ideas or new representations by focusing on common relational structures of mathematical situations rather than on superficial details. This focus is analogical reasoning at work in the construction of mathematical knowledge. Since analogical reasoning is the means by which mathematicians do mathematics and is close]y linked to measures of intelligence, it should be considered important in mathematics education. This study investigates how mathematicians used analogical reasoning, what role did it flay when they construct new concept or problem solving strategy.

• Journal of Korea Society of Digital Industry and Information Management
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• v.7 no.3
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• pp.25-35
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• 2011

In the Semantic Web, storage models are required to efficiently store and retrieve metadata and ontology represented using OWL that can provide expressive power and reasoning support. In this paper, we propose an OWL storage model that can store and retrieve many restrictions and semantic relations defined on ontology with metadata. In addition, we propose some methods and rules to improve query processing efficiency of the proposed storage model. The proposed storage model can store and process large amounts of ontology and metadata because it consists of tables based on the relational database. And the proposed model can quickly provide more accurate results to users because of performing two different types of ontology reasoning and using the prime number labeling scheme to easily identify hierarchy relationships between classes or properties. The comparative evaluation results show that our storage model provides better performance than the existing storage model.

• Korean Journal of Child Studies
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• v.35 no.3
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• pp.49-69
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• 2014

The purposes of this study were (1) to investigate children's moral judgment, justification reasoning in terms of aggressive behavior, and (2) it examined the relationship to false belief understanding. Children aged between 3 to 5 years(N = 120) participated in this study. Each child was interviewed individually and responded questions designed to measure his/her moral judgment and justification reasoning and false belief understanding. The 12 pictorial tasks consisted of selfish and altruistic intentions and three different types of acts (physical, verbal, relational) as responses to aggressive behavior. The results indicated that the kind of moral judgment used was different according to the intention and the types of acts. There were significant differences in children's justification reasoning according to the age and the types of acts. There was a positive relationship between false belief understanding and moral judgment, justification reasoning. This paper also provided a detailed discussion of the results and recommendations in the context of more general cognitive developmental changes.

• Korean Journal of Child Studies
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• v.9 no.1
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• pp.47-61
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• 1988

The primary purpose of this study was to investigate the relation between paternal self-esteem, child-rearing behaviors and child's self-esteem. The secondary purpose was to examine whether there were significant relational differences according to child's sex. 272 dyads consisting of fifth and sixth grade children in elementary school and their measured by the Self-Esteem Inventory (for children), the Self-Esteem Scale (for fathers), and the Iowa Parent Behavior Inventory: Father form. Pearson's r., F-test, and Ducan's multiple range test were used for data analysis. Paternal self-esteem was significantly associated with 'parental involvement', 'reasoning guidance', and 'intimacy'. Paternal self-esteem was positively correlated with girl's self-esteem. Child's self-esteem was positively related to 'parental involvement', 'limit setting', 'responsiveness', 'reasoning guidance' and 'intimacy'. In sex differences, only boy's self-esteem wasn't related to paternal 'limit setting'. Boys' self-esteem was strongly related to 'parental involvement', and girls' self-esteem was strongly related to 'reasoning guidance'.

• School Mathematics
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• v.11 no.2
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• pp.227-241
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• 2009

The isoperimetric problem has been known from the time of antiquity. But the problem was not rigorously solved until Steiner published several proofs in 1841. At the time it stood at the center of controversy between analytic and geometric methods. The geometric approach give us more productive thinking (insight, structural understanding) than the analytic method (using Calculus). The purpose of this paper is to analysis and then to construct the isoperimetric problem which can be applied to the mathematically gifted students in the elementary school. The theoretical backgrounds of our analysis about our problem are based on the Gestalt psychology and mathematical reasoning. Our active program about the isoperimetric problem constructed by the Gestalt's view will contribute to improving a mathematical reasoning and to serving structural (relational) understanding of geometric figures.

• 한국IT서비스학회:학술대회논문집
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• 2009.05a
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• pp.353-356
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• 2009

OWL 온톨로지의 확장 가능한(scalable) 추론(reasoning)에 대한 접근 방법으로 SQL로 구축된 논리 규칙을 관계형 데이터베이스에 저장되어있는 개체(individual)에 대한 사실(facts)과 공리(axioms)들에 적용하는 것이다. 예로서 미네르바(Minerva)는 서술 논리 프로그램(Description Logic Program, DLP)을 적용함으로써 ABox 추론을 수행한다. 본 연구에서는 관계형 데이터베이스를 기반으로 추론을 시도하며, 대규모 논리 규칙 집합을 사용한 추론을 시도한다. 뿐만 아니라, 특정 클래스에 속한 익명(anonymous)의 개체들과 개체들의 묵시적(implicit)인 관계성 추론을 시도하며, 필요한 경우 새로운 개체를 생성함으로써 명시화하여 추론을 시도한다. 더욱이, 추론의 논리 패러다임(paradigm)에서부터 데이터베이스 패러다임에 이르기까지 변화 시켜가면서 카디널리티(cardinality) 제약을 만족하는 개체들에 대한 제약적인 추정 추론을 시도하며, 벤치마크 테스트 결과 향상된 추론 능력을 얻을 수 있음을 보인다.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2001.05a
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• pp.184-197
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• 2001

In this paper, we provide the formal specification of a fuzzy object inference language and propose ICOT(Integrated C-Object Tool) as its implementation for knowledge-based programming with the disjunctive fuzzy information. The novelty of our model is that it seamlessly combines object inference and fuzzy reasoning into a unified framework without compromising a compatibility with extant databases, especially object-relational ones. In this model most of the object-oriented paradigm is successfully expressed in terms of relational constructs, tailoring fuzzy reasoning style to be well suited to the framework of the databases. It turns out to be useful in preserving its conceptual simplicity as well, since simple-to-use is one of important criteria in designing the databases. Additionally this model considerably enhanced the semantic expressiveness of data allowing disjunctive fuzzy information.

• Journal of the Korean Society of Safety
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• v.21 no.3 s.75
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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.