• Journal of Information Technology Applications and Management
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• v.12 no.4
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• pp.1-12
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• 2005

In general, other conventional researches propose the fuzzy Petri net-based fuzzy reasoning algorithms based on the exhaustive search algorithms. If it can allow the certainty factors representing in the fuzzy production rules to use as the heuristic information, then it can allow the reasoning of rule-based systems to perform fuzzy reasoning in more effective manner. This paper presents a fuzzy Petri net(FPN) model to represent the fuzzy production rules of a rule-based system. Based on the fuzzy Petri net model, a weighted fuzzy reasoning algorithm is proposed to Perform the fuzzy reasoning automatically, This algorithm is more effective and more intelligent reasoning than other reasoning methods because it can perform fuzzy reasoning using the certainty factors which are provided by domain experts as heuristic information

• Journal of the Korean Society of Safety
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• v.20 no.3 s.71
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• pp.19-26
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• 2005

There are three reasoning method in fault diagnosis process. The shallow reasoning is based on the experiential knowledge and deep reasoning is based on physical model. Hybrid reasoning is mixing two type reasoning. This study describes about fault train embodiment of screw type air compressor that is used widely in industrial facilities by using various experimental method and shallow reasoning. We investigate macroscopic failure cause of air compressor through naked eye observation and then microscopic failure cause by various experimental method. We composed fault train with fault knowledge based on empirical data and scientific data that is acquired through several experiments. It is possible to analysis system reliability and failure rate with these fault train.

• Korean Journal of Cognitive Science
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• v.16 no.3
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• pp.213-224
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• 2005

To develop a cognitive system with the flexibility and breadth of human reasoning, it's very important to construct a large scale knowledge base which includes commonsense knowledge as well as expert knowledge. This paper introduces a cognitive system which provides a commonsense reasoning for everyday physical phenomena using qualitative reasoning. It is difficult to apply previous qualitative reasoning to commonsense reasoning since it provides reasoning based on abstract concepts which are apart from everyday real world concepts. Our research provides commonsense reasoning based on sketches and real world concepts by integrating qualitative reasoning and general large scale Cyc knowledge base. Our system has been implemented and tested on various examples.

• Journal of Korean Elementary Science Education
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• v.38 no.3
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• pp.375-386
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• 2019

This study explores how elementary school students construct food pyramid prediction models using scientific reasoning. Thirty small groups of sixth-grade students in the Kyoungki province (n=138) participated in this study; each small group constructed a food pyramid prediction model based on scientific reasoning, utilizing prior knowledge on topics such as biotic and abiotic factors, food chains, food webs, and food pyramid concepts. To understand the scientific reasoning applied by the students during the modeling process, three forms of qualitative data were collected and analyzed: each small group's discourse, their representation, and the researcher's field notes. Based on this data, the researcher categorized the students' model patterns into three categories and identified how the students used scientific reasoning in their model patterns. The study found that the model patterns consisted of the population number variation model, the biological and abiotic factors change model, and the equilibrium model. In the population number variation model, students used phenomenon-based reasoning and relation-based reasoning to predict variations in the number of producers and consumers. In the biotic and abiotic factors change model, students used relation-based reasoning to predict the effects on producers and consumers as well as on decomposers and abiotic factors. In the equilibrium model, students predicted that "the food pyramid would reach equilibrium," using relation-based reasoning and model-based reasoning. This study demonstrates that elementary school students can systematically elaborate on complicated ecology concepts using scientific reasoning and modeling processes.

• Journal of the Korean Chemical Society
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• v.58 no.6
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• pp.667-680
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• 2014

The purpose of this study was to develop teaching stratege focused on Conservational reasoning, Proportional reasoning, Variable-controlling reasoning, Probabilitic reasoning, Correlational reasoning, Combinational reasoning and investigate its effects on enhancing students' logical thinking skills through the science teaching on common education. And the teaching materials was implemented to 110 students in middle school over about six months. The results indicated that the experimental group presented statistically meaningful improvement in logical thinking skills (p<05). Especially, this teaching stratege was effective on Conservational reasoning, Variable-controlling reasoning, Combinational reasoning but was not effective on Proportional reasoning, Probabilitic reasoning, Correlational reasoning (p<.05). Logical thinking according to the teaching strategy skill was not affected by gender, cognitive level, academic achievement (p<.05).

• The Mathematical Education
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• v.41 no.3
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• pp.291-318
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• 2002

We investigated on the primary school children's abilities of formal reasoning. Seventy students in grade 5 participated in the study. They responsed their best reactions on the problems constituted of three parts requiring the informal or formal reasoning and generalization. Their reactions are classified by some criteria depending the level of reasoning. About 10 students showed that they constructed a kind of scheme for solving the problems, similar to formal reasoning and beyond naive informal reasoning. And about 30 students did so partially. We concluded that the teaching and learning of reasoning by the progressive increasing the degree of rigor from grade 5 is possible.

• Korean Journal of Child Studies
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• v.24 no.2
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• pp.15-33
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• 2003

The 120 participants of this study were 5- and 9-year-old children and their mothers. Children responded to 24 prosocial moral reasoning dilemmas and 8 prosocial decision-making tasks. Mothers' prosocial moral reasoning was assessed with questionnaires. Level of moral reasoning was higher in distant than in close relationships. 5-year-olds in preoperational stage used the complex situational cues in their reasoning, and prosocial moral reasoning of 9-year-olds was positively related to mothers' prosocial moral reasoning in the situation with conditions of distant relationship, low costs, and internal responsibility. Children made more helping decisions in close than in distant relationship situations, low rather than high cost situations, and external rather than internal responsibility situations. 5-year-olds whose mothers were high in level of prosocial moral reasoning were more helpful.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.2
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• pp.165-170
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• 2011

It is expected that the cooperation between rule-based reasoning and case-based reasoning gives us an efficient approach for flexible reasoning. In this paper, we present an integrated model of rule-base reasoning and case-base reasoning using the MVL automata model. In addition, we introduce how to handle the uncertainty in the integrated model.

• Journal of Physiology & Pathology in Korean Medicine
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• v.23 no.4
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• pp.745-750
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• 2009

The goal of this study is to examine on reasoning and search for construction of diagnosis ontology as a knowledge base of diagnosis expert system in oriental medicine. Expert system is a field of artificial intelligence. It is a system to acquire information with diverse reasoning methods after putting expert's knowledge in computer systematically. A typical model of expert system consists of knowledge base and reasoning & explanatory structure offering conclusion with the knowledge. To apply ontology as knowledge base to expert system practically, consideration on reasoning and search should be together. Therefore, this study compared and examined reasoning, search with diagnosis process in oriental medicine. Reasoning is divided into Rule-based reasoning and Case-based reasoning. The former is divided into Forward chaining and Backward chaining. Because of characteristics of diagnosis, sometimes Forward chaining or backward chaining are required. Therefore, there are a lot of cases that Hybrid chaining is effective. Case-based reasoning is a method to settle a problem in the present by comparing with the past cases. Therefore, it is suitable to diagnosis fields with abundant cases. Search is sorted into Breadth-first search, Depth-first search and Best-first search, which have respectively merits and demerits. To construct diagnosis ontology to be applied to practical expert system, reasoning and search to reflect diagnosis process and characteristics should be considered.

• Journal of The Korean Association For Science Education
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• v.29 no.3
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• pp.304-313
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• 2009

Proportional reasoning is one of the most widely used concepts in everyday life. It could be the most important basic concept in science and mathematics. In research where the subjects were animals, it has been found that learning effect rapidly decreased with any stimulation given after a optimalperiod. Therefore, it is necessary to research about optimal periods in order to instruct about proportional reasoning. The purpose of this study was to investigate the optimal periods in proportional reasoning. The three programs for proportional reasoning instruction were developed by researchers. The titles of the programs were 'Block', 'Balance scale' and 'Water glass'. The subjects were 131 3$^{rd}$ to 6$^{th}$ grade students who were not expected to have any proportional reasoning skills yet. In order to find out the optimal periods in proportional reasoning, the programs were applied to these students. After 4-5 weeks of treatment, the researchers investigated whether their proportional reasoning skills were formed or not through the instrument. The results indicated that it would be most effective to teach proportional reasoning to 6$^{th}$ grade students. Teaching of proportional reasoning is essential not only for mathematics but also for science. The findings could be used to investigate the optimal periods of controlling variables, probability, combinational and correlational logic.