• Korean Journal of Child Studies
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• v.29 no.4
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• pp.65-77
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• 2008

This study investigated differences of display rule by age and gender and the effects of theory of mind and affective perspective taking on display rule. Subjects were 64 4- to 5-year old children. Instruments were false belief, appearance-reality distinction, affective perspective taking, gift-giving, and display rule understanding task. Findings were (1) Display rule understanding differed by age; older children understood the display rules better than younger children. (2) Theory of mind influenced positive display rule behavior. (3) Theory of mind and affective perspective taking had a significant effect on display rule understanding.

• Language and Information
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• v.4 no.2
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• pp.69-92
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• 2000

It is well-known that default rules require a nonmonotonic logic. Veltman proposed one dynamic theory which interprets default rules in such a way that correct inferences can be made at each information state. But his theory has some problems. First, this theory excludes the possibility that a default rule can be true of false. Second, his representation of an information state makes it difficult to interpret a default rule embedded in another sentence. Third, the notion of a frame which is introduced in the interpretation of a default rule and the adjustment of inferential expectation has a more complex structure than is necessary, In this paper, I propose a truth-conditional theory of default rules in which the meaning of a default rule is defined as a truth-condition in a possible world and which assumes a simpler structure of a frame. This makes it possible to interpret a default rule embedded in a sentence. A dynamic theory for default rules is also proposed for correct inferences based on default rules.

• Proceedings of the IEEK Conference
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• 2003.11b
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• pp.227-230
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• 2003

We can not distinguish semantism of the feature of the current language “big”, “small”, “beautiful”. But we study artificial linguistic interface work and convert natural language to digital binary linguistic theory, we should define the basical conversion process. When we utilize the sum of product fuzzy theory and the visible numerical value, we can establish reasoning rule of input language. Fuzzy theory should be converted to general resulting rule.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.333-336
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• 2002

In many cases, fuzzy modeling has a defect that the design procedure cannot be theoretically justified. To overcome this difficulty, we suggest a new design method for fuzzy model by combining genetic algorithm(GA) and mush set theory. GA, which has the advantages is optimization, and rule base. However, it is some what time consuming, so are introduce rough set theory to the rule reduction procedure. As a result, the decrease of learning time and the considerable rate of rule reduction is achieved without loss of useful information. The preposed algorithm is composed of three stages; First stage is quasi-optimization of fuzzy model using GA(coarse tuning). Next the obtained rule base is reduced by rough set concept(rule reduction). Finally we perform re-optimization of the membership functions by GA(fine tuning). To check the effectiveness of the suggested algorithm, examples for time series prediction are examined.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.16 no.4
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• pp.308-317
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• 2016

Multiple evidences based decision making is an important functionality for computers and robots. To combine multiple evidences, mathematical theory of evidence has been developed, and it involves the most vital part called Dempster's rule of combination. The rule is used for combining multiple evidences. However, the combined result gives a counterintuitive conclusion when highly conflicting evidences exist. In particular, when we obtain two different sources of evidence for a single hypothesis, only one of the sources may contain evidence. In this paper, we introduce a modified combination rule based on the partial conflict measurement by using an absolute difference between two evidences' basic probability numbers. The basic probability number is described in details in Section 2 "Mathematical Theory of Evidence". As a result, the proposed combination rule outperforms Dempster's rule of combination. More precisely, the modified combination rule provides a reasonable conclusion when combining highly conflicting evidences and shows similar results with Dempster's rule of combination in the case of the both sources of evidence are not conflicting. In addition, when obtained evidences contain multiple hypotheses, our proposed combination rule shows more logically acceptable results in compared with the results of Dempster's rule.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.302-304
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• 2011

Rule based machine learning techniques are very important in our real world now. We can list out some important application which we can apply rule based machine learning algorithm such as medical data mining, business transaction mining. The different between rules based machine learning and model based machine learning is that model based machine learning out put some models, which often are very difficult to understand by expert or human. But rule based techniques output are the rule sets which is in IF THEN format. For example IF blood pressure=90 and kidney problem=yes then take this drug. By this way, medical doctor can easy modify and update some usable rule. This is the scenario in medical decision support system. Currently, Rough set is one of the most famous theory which can be used for produce the rule. LEM2 is the algorithm use this theory and can produce the small set of rule on the database. In this paper, we present an improvement of LEM2 algorithm which incorporates the variable precision techniques.

• Journal of Educational Research in Mathematics
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• v.26 no.3
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• pp.355-370
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• 2016

This research intends to and understand a prospective teacher, Kim's mathematics lesson in the perspective of Activity Theory. In this study, Kim's mathematics lesson was explored in the aspects of subject, object, tools, division of labor, community, and rule which are main constituent of Activity Theory and Activity System suggested by $Engestr{\ddot{o}}m$. As the result of study, we discussed the phenomena such as the fluctuation between object and tool, the multi-voicedness between object, rule, outcome and student subject, and the dissonance between division of labor, community and rule were appeared in Kim's mathematics lesson as an activity system.

• Bulletin of the Korean Chemical Society
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• v.16 no.9
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• pp.850-858
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• 1995

Golden-rule like formulas have been used without theoretical basis to calculate the resonance lifetimes and final state distributions in the predissociation of van der Waals molecules. Here we present their theoretical basis by extending Fano's configuration interaction theory. Such extensions were independently done by Farnonux [Phys. Rev. 1985, 25, 287] but his work, unfortunately, was not well known outside some small group of people in the field of Auger spectroscopy. Since my extension is easier to understand than his, it is presented here. Theoretical basis of Golden rule like formulas used in the predissociation of van der Waals molecules was obtained by using such extensions. Factors responsible for several aspects of predissociation dynamics, such as variations of dynamics as functions of resonance lifetimes, or variations in shapes of final quantum state distributions of photofragments around resonances, were identified. Parameters, or dynamical information that could be obtained from the measurement of partial cross section spectra were accordingly determined. The theory was applied to the vibrational predissociation of triatomic van der Waals molecules and its result was compared with those calculated by close-coupling method. An example where Golden-rule like expression fails and branching ratios vary greatly around a resonance was considered.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.965-967
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• 2013

The paper proposed the DRCS(Disease Rule Creation Scheme) which generates the disease rules for efficient disease management in Healthcare system. The DRCS uses basically Rough Set Theory and computes support between each attributes and decision attributes. It creates the disease rules that judges disease after it removes the attribute which is the lowest support. Therefore, it reduces the number of disease rules and improves the exactness, compared with C4.5 algorithm.

• Korean Journal of Computational Design and Engineering
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• v.5 no.4
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• pp.319-326
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• 2000

Expert systems using uncertain and ambiguous knowledge are not of the recent interests about uncertainty problem for performing inference similar to the decision making of a human expert. Human factors on rule-based systems often involve uncertain information. Expert systems had been used the methods of conflict resolution in a rule conflict situation, but this methods not properly solved the rule conflict. If a human expert appends a new rule to an original rule base, the rule base rightly causes a rule conflict. In this paper, the problem of rule conflict is regarded as one in which uncertainty of information is fundamentally involved. In the reduction of problem with uncertainty, we propose an enhanced rule ordering method, which improve the rule ordering method using Dempster-Shafer theory. We also propose a combinative index, which involve human factors of experts decision making.