• 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 Families and Better Life
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• v.26 no.5
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• pp.333-354
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• 2008

This study aimed to investigate the role of domain-specific causal mechanism information and domain-general conditional probability in young children's causal reasoning on psychology and biology. Participants were 121 3-year-olds and 121 4-year-olds recruited from seven childcare centers in Seoul, Kyonggi Province, and Busan. After participants watched moving pictures on psychological and biological phenomena, they were asked to choose appropriate cause and justify their choices. Results of this study were as follows: First, young children made different inferences according to domain-specific causal mechanisms. Second, the developmental level of causal mechanisms has a gap between psychology and biology, and biological knowledge was proved to be separate from psychological knowledge during the preschool period. Third, young children's causal reasoning was different depending on the interaction effect of domain-specific mechanisms and domain-general conditional probability: children could make more inferences based on domain-specific causal mechanisms if conditional probability between domain-appropriate cause and effect was evident. To conclude, it can be inferred that the role of domain-specific causal mechanisms and domain-general conditional probability is not competitive but complementary in young children's causal reasoning.

• Journal of Educational Research in Mathematics
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• v.19 no.2
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• pp.233-256
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• 2009

The notions of conditional probability and independence are fundamental to all aspects of probabilistic reasoning. Several previous studies identified some misconceptions in students' thinking in conditional probability. However, they have not analyzed enough the nature of conditional probability. The purpose of this study was to analyze conditional probability and students' knowledge on conditional probability. First, we analyzed the conditional probability from mathematical, historico-genetic, psychological, epistemological points of view, and identified the essential aspects of the conditional probability. Second, we investigated the high school students' and undergraduate students' thinking m conditional probability and independence. The results showed that the students have some misconceptions and difficulties to solve some tasks with regard to conditional probability. Based on these analysis, the characteristics of reasoning about conditional probability are investigated and some suggestions are elicited.

• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.1058-1062
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• 1993

A fuzzy reasoning method is proposed for the implementation of control systems based on non-fuzzy microprocessors. The essence of the proposed method is to search the local active miles instead of the global rule base. Thus the reasoning is conveniently performed on a master cell as a fuzzy accelerating kernel, which is transformed from an active fuzzy cell. The interpolative reasoning is simplified via adopting the algebraic product of fulfillment for the conditional connective AND and the weighted average for the rule sentence connective ALSO.

• Korean Journal of Logic
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• v.17 no.1
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• pp.197-217
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• 2014

In my previous papers, I have argued that the so-called 'Uncontested Principle' does not hold for indicative conditionals based on inductive reasoning. This is mainly because if we accept that a material conditional '$A{\supset}C$' can be inferred from an indicative conditional based on inductive reasoning '$A{\rightarrow}_iC$', we get an absurd consequence such that we cannot distinguish between claiming 'C' to be probably true and claiming 'C' to be absolutely true on the assumption 'A'. However, in his recent paper "Uncontested Principle and Inductive Argument", Eunsuk Yang objects that my argument is unsuccessful in disputing the Uncontested Principle. In this paper, I show that his objections are irrelevant to my argument against the Uncontested Principle.

• Journal of the Korean School Mathematics Society
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• v.12 no.3
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• pp.307-317
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• 2009

Formally p$\rightarrow$q means that affirming p one implicitly affirms q and that denying q one implicitly denies p. Denying p or affirming q do not lead to certain conclusions. Middle school students can recognize practical implication p$\rightarrow$q is true whenever p is false, but they don't recognize theoretical implication p$\rightarrow$q is true whenever p is false. They have not assimilated intuitively the complete structure of implication. Thus they do not distinguish naturally between the uncertain conclusion which can be drawn by affirming p and the certain rejection of p which follows from the negation of q. Also they can not recognize the uncertain conclusion which can be drawn by negation of p. There is no significant difference between practical conditional statements, formal conditional statements and conditional Inferences in advanced mathematics students. But there is a significant difference between formal conditional inferences and specific conditional inferences with statement p$\rightarrow$q is true when p is false.

• Asia pacific journal of information systems
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• v.8 no.3
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• pp.135-145
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• 1998

There exists popular approach using certainty factor (CF) for the development of effective reasoning mechanism under uncertainty in Expert System, However, there is a problem with CF. The CF values could be resulted in the opposite of given conditional probabilities. In this paper, a method for, reasoning under uncertainty using reliability theory to overcome the problem is proposed. And the proposed method is used in the development of Expert System for the selection of equipment for automated warehouses.

• Journal of KIISE:Software and Applications
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• v.36 no.1
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• pp.82-91
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• 2009

Sign language spotting is the task of detecting and recognizing the signs in a signed utterance. The difficulty of sign language spotting is that the occurrences of signs vary in both motion and shape. Moreover, the signs appear within a continuous gesture stream, interspersed with transitional movements between signs in a vocabulary and non-sign patterns(which include out-of-vocabulary signs, epentheses, and other movements that do not correspond to signs). In this paper, a novel method for designing a threshold model in a conditional random field(CRF) model is proposed. The proposed model performs an adaptive threshold for distinguishing between signs in the vocabulary and non-sign patterns. A hand appearance-based sign verification method, a short-sign detector, and a subsign reasoning method are included to further improve sign language spotting accuracy. Experimental results show that the proposed method can detect signs from continuous data with an 88% spotting rate and can recognize signs from isolated data with a 94% recognition rate, versus 74% and 90% respectively for CRFs without a threshold model, short-sign detector, subsign reasoning, and hand appearance-based sign verification.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.512-517
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• 2008

It is show that increasing of aged and handicapped people requires development of Ubiquitous computing technique to offer the specialized service for handicapped-people. For this, we need a development of Context Awareness and Service Reasoning Technique that the technique is supplied interaction between user and U-environment instead of the old unilateral relation. The old research of context awareness needed probabilistic presentation model like a Bayesian Network based on expert Systems for recognize given circumstance by a domain of uncertain real world. In this article, we define a domain of disorder activity assistant service application and context model based on ontology in diversified environment and minimized intervention of user and developer. By use this context model, we apply the structure learning of Bayesian Network and decide the service and activity to development of application service for handicapped people. Finally, we define the proper Conditional Probability Table of the structured Bayesian Network and if random situation is given to user, then present state variable of Activity and Service by given Causal relation of Bayesian Network based on Conditional Probability Table and it can be result of context awareness.

• Korean Journal of Logic
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• v.15 no.2
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• pp.273-294
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• 2012

In my previous article "An Inferentialist Account of Indicative Conditionals" and "An Inferentialist Account of Indicative Conditionals and Hasuk Song's Objections", I argued that the so-called Uncontested Principle is not uncontestable. According to the Uncontested Principle, an indicative conditional '$A{\rightarrow}C$' logically implies a material conditional '$A{\supset}C$'. In his recent paper "On the Recent Controversies surrounding the Uncontested Principle" Wonbae Choi presents three objections to my claim. First, my denial of the Uncontested Principle implies rejecting modus ponens. Second, my denial of the Uncontested Principle is tantamount to taking the truth-conditions of an indicative conditional as weaker than those of a material conditional, which are usually taken to be the weakest among conditionals. Third, my view that we can warrantedly assert '$A{\rightarrow}C$' even when 'A ${\therefore}$ C' is inductively justified is based on a misunderstanding of the way in which indicative conditionals are justified. In this paper I argue that Choi's objections are all based on misunderstandings of my view. First, I do not deny the validity of modus ponens (as a form of deductive reasoning). Second, the fact that the inductive warrantability of 'A ${\therefore}$ C' does not imply the truth of '$A{\supset}C$' does not show that the truth-conditions of an indicative conditional is weaker than those of a material conditional. Third, Choi's claim that a contingent conditional '$A{\rightarrow}C$' is true only when 'C' can be deductively derived from 'A' in conjunction with a hidden premiss is not well grounded, nor does it fit the facts.