• Korean Journal of Child Studies
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• v.29 no.5
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• pp.243-269
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• 2008

The role of domain-specific causal mechanism information and domain-general conditional probability in young children's causal reasoning on physics and psychology was investigated with the participation of 121 3-year-olds and 121 4-year-olds recruited from seven child care centers in Seoul, Kyonggi Province, and Busan. Children watched moving pictures on physical and psychological phenomena, and were asked to choose an appropriate cause and justify their choice. Results showed that young children's causal reasoning differed depending on domain-specific mechanism. In addition, their causal reasoning on physics and psychology differed by the developmental level of causal mechanism. The interaction of domain-specific mechanism and domain-general conditional probability influenced children's causal reasoning : evident conditional probability between domain-appropriate cause and effect helped children make more inferences based on domain-specific causal mechanism.

• Journal of Korean Elementary Science Education
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• v.17 no.2
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• pp.23-31
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• 1998

The purpose of the present study was to investigate the development of elementary school student's reasoning strategies used in proportional tasks. Three hundred and ninety elementary students were sampled to investigate their reasoning strategies used in Pouring Water Tasks. Results showed that 4 percentage of students used proportional reasoning strategy. By the way, about 80 % of students used qualitative guess or additive strategies to solve proportion tasks. Further, about fifth-grade or 11-year-old students began to use proportional reasoning strategy. Also, female and malt students' development of reasoning strategies improved from 1st grade across 5th grade and from 6-year-old across 11-year-old. However, female did not show the improvement of strategy development after 5th-grade or 11-year-old. However, male students showed a continuous improvement after the grade or age. In addition, students showed developmental patterns of spurts and plateau, ra thor than a linear developmental pattern. The present study also discussed educational implications of this findings in school curriculum.

• The Journal of Korean Physical Therapy
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• v.24 no.5
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• pp.370-376
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• 2012

Purpose: This study examined whether there are differences in cognitive styles between orthopedic and neurological physical therapists, and whether these differences change with clinical experience in clinical reasoning. Methods: A survey study was conducted on 88 orthopedic and neurologic physical therapists working in South Korea. The survey items used by May and Dennis (1991) were translated, and only those items related to data-gathering and information-processing were used. Results: The cognitive style was similar in the orthopedic and neurologic physical therapists, but the clinical experience affected the cognitive styles of clinical reasoning. Physical therapists with more than 60 months clinical experience responded most positively to the preceptive and systematic styles in clinical reasoning. Conclusion: These results suggest that physical therapy education should provide physical therapy students with a clinical reasoning process related specifically to a particular clinical field.

• Journal of the Korean Society of Safety
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• v.18 no.1
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• pp.50-55
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• 2003

This paper presents an intelligent computer system, which can easily diagnose electrical fire causes, without the help of human experts of electrical fires diagnosis. For this system, a database is built with facts and rules driven from real electrical fires, and an intellectual database system which even a beginner can diagnose fire causes has been developed, named as an Electrical Fire Causes Diagnosis System : EFCDS. The database system has adopted, as an inference engine, a mixed reasoning approach which is constituted with the rule-based reasoning and the case-based reasoning. The system for a reasoning model was implemented using Delphi 3, one of program development tools, and Paradox is used as a database building tool. To verify effectiveness and performance of this newly developed diagnosis system, several simulated fire examples were tested and the causes of fire examples were detected effectively by this system. Additional researches will be needed to decide the minimal significant level of the solution and the weighting level of important factors.

• Journal of Korean Elementary Science Education
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• v.34 no.1
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• pp.58-71
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• 2015

Ability of understanding students' ideas and thinking is critical to teachers' professional growth. In this study, 'pedagogical reasoning' was conceptualized as teachers' reasoning ability of students' misconceptions and possible causes of misconceptions when they hear and observe students' science discourses. To investigate elementary pre-service teachers' pedagogical reasoning levels, children's science discourses on light reflection and electric circuit were video recorded and 43 pre-service elementary teachers were asked to identify children's misconceptions and possible causes of misconceptions after watching the video clips. In conclusion, pedagogical reasoning levels of pre-service elementary teachers were not high enough, showing significant difference in light reflection and electric circuit. Possible explanations of this difference and educational implications were discussed.

• Journal of Intelligence and Information Systems
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• v.6 no.1
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• pp.97-112
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• 2000

The basic idea of case-based reasoning is to solve a new problem using the previous problem-solving experiences. In this research we develop a case-based reasoning system for equipment malfunction diagnosis. We first divide the case base into clusters using the case-based clustering technique. Then we develop an appropriate case-based diagnostic system for each cluster. In other words for individual cluster a different case-based diagnostic system which uses different weights for attributes is developed. As a result multiple case-based reasoning system are operating to solve a diagnostic problem. In comparison to the performance of the single case-based reasoning system our system reduces the computation time by 50% and increases the accuracy by 5% point.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.3
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• pp.92-100
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• 1995

Fuzzy reasoning has been applied to analysis of traffic problems on urban arterial road. As the analysis on factors of route choice has been already carried out, its result can be used for construction of the model. Route choice rate estimation by fuzzy reasoning was discussed from its structure and accuracy. The major objective of the study is to introduce some kinds of methods with fuzzy reasoning and to make their feature obvious. First, the production system model is introduced with consideration of reality to actual travel behavior. Second, overlapping areas of fuzzy language function are investigated. Finally, process of fuzzy reasoning was also considered. Five kinds of Fuzzy reasoning are compared to investigate in relation between shapes of membership function and estimation validity.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.543-545
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• 1999

In this paper, the composition method of global and local fuzzy reasoning concepts is researched for reducing the number of rules, not losing the performance for fuzzy controller. A new method is proposed in details that controls the interaction between global reasoning and local reasoning. In order to automatically acquire and optimize the method, the DNA coding algorithm is introduced to the local fuzzy reasoning of the proposed composition fuzzy reasoning method. The method is applied to the real liquid level control system for the purpose of evaluating the Performance. The simulation results show that the proposed technique can produce the fuzzy rules with higher accuracy and feasibility than the conventional methods.

• Journal of Korea Game Society
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• v.9 no.6
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• pp.117-125
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• 2009

This paper describes the result of applying neuro-fuzzy reasoning, which conducts Go term knowledge based on pattern knowledge, to the opening game of Go. We discuss the implementation of neuro-fuzzy reasoning for deciding the best next move to proceed through the opening game. We also let neuro-fuzzy reasoning play against TD($\lambda$) learning to test the performance. The experimental result reveals that even the simple neuro-fuzzy reasoning model can compete against TD($\lambda$) learning and it shows great potential to be applied to the real game of Go.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.8 no.4
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• pp.254-259
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• 2008

Uncertainty of result of context awareness always exists in any context-awareness computing. This falling-off in accuracy of context awareness result is mostly caused by the imperfectness and incompleteness of sensed data, because of this reasons, we must improve the accuracy of context awareness. In this article, we propose a novel approach to model the uncertain context by using ontology and context reasoning method based on Bayesian Network. Our context aware processing is divided into two parts; context modeling and context reasoning. The context modeling is based on ontology for facilitating knowledge reuse and sharing. The ontology facilitates the share and reuse of information over similar domains of not only the logical knowledge but also the uncertain knowledge. Also the ontology can be used to structure learning for Bayesian network. The context reasoning is based on Bayesian Networks for probabilistic inference to solve the uncertain reasoning in context-aware processing problem in a flexible and adaptive situation.