• Journal of Korean Institute of Industrial Engineers
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• v.40 no.4
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• pp.375-381
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• 2014

Data mining is a process of discovering useful patterns or information from large amount of data. Decision tree is one of the data mining algorithms that can be used for both classification and prediction and has been widely used for various applications because of its flexibility and interpretability. Decision trees for classification generally generate a number of rules that belong to one of the predefined category and some rules may belong to the same category. In this case, it is necessary to determine the significance of each rule so as to provide the priority of the rule with users. The purpose of this paper is to propose a rule selection method in classification tree models that accommodate the umber of observation, accuracy, and effectiveness in each rule. Our experiments demonstrate that the proposed method produce better performance compared to other existing rule selection methods.

• The Korean Journal of Community Living Science
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• v.20 no.2
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• pp.169-180
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• 2009

This study was performed to examine the emotion expectations and explanations of four participants(an actor, a recipient, a child observer, and an adult observer) in moral, social-conventional, and personal rule transgression situations. Six vignettes describing the rule transgressions were presented to 200 children who were either five or seven years old. The children were asked to predict and explain each participant's emotions. The children's emotion expectations were different depending on the domain of the rule transgressions and on the type of the participant. The actors were predicted to feel happy during all transgressions, while the recipients and two observers(a child and an adult) were predicted to feel unhappy. The seven-year-old children attributed more happiness to the actors, and more negative affect to the recipients compared to the five-year-olds. This result was inconsistent with the previous findings that older children attributed more happiness to actors. This finding was discussed in relation to the 'happy victimizer'. Some categories of emotion explanations were differentiated according to the domain of rule transgressions. The personal rule transgressions, newly defined and examined in this study, were judged to be less serious than the moral rule transgressions in terms of the intensity of the negative affect.

• Journal for History of Mathematics
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• v.18 no.1
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• pp.33-48
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• 2005

The Rule of False Position is known as an arithmetical solution of algebraical equations. On the other hand, the Excess-Deficit Rule is an algorithm for calculating about excessive or deficient quantitative relations, which is found in the ancient eastern mathematical books, including the nine chapters on the mathematical arts. It is usually said that the origin of the Rule of False Position is the Excess-Deficit Rule in ancient Chinese mathematics. In relation to these facts, we pose two questions: - As many authors explain, the excess-deficit rule is a solution of simultaneous linear equations？ - Which relation is there between the two rules explicitly？ To answer these Questions, we consider the Rule of Single/Double False Position and research the Excess-Deficit Rule in some ancient mathematical books of Chosun Dynasty that was heavily affected by Chinese mathematics. And we pursue their historical traces in Egypt, Arab and Europe. As a result, we can make sure of the status of the Excess-Deficit Rule differing from the Rectangular Arrays(the solution of simultaneous linear equations) and identify the relation of the two rules: the application of the Excess-Deficit Rule including supposition in ancient Chinese mathematics corresponds to the Rule of Double False Position in western mathematics. In addition, we try to appreciate didactical value of the Rule of False Position which is apt to be considered as a historical by-product.

• The KIPS Transactions:PartD
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• v.17D no.6
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• pp.405-414
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• 2010

A rule is defined as a case to determine the target values according to combination of various Business factors. The information system is used to represent enterprise's business, which includes and implements the amount of these rules to Rule-Based System. A Rule-Based System can be constructed by using the rules engine method or Relational Database technology. Because the rules engine method has some disadvantages, the Rule-Based System is mostly developed with Relational Database technology. When business scales become larger and more complex, a large number of various rule cases must be operated in system, and processing these rule cases requires additional time, overhead and storage space, and the speed of execution slows down. To solve these problems, we propose a simplification algorithm that converts a large amount of rule cases to simplification rule cases with same effects. The proposed algorithm is applied to hypothetical business rule data and a large number of simplification experiments and tests are conducted. The final results proved that the number of rows can be reduced to some extent. The proposed algorithm can be used to simplify business rule data for improving performance of the Rule-Based System implemented with the Relational Database.

• Journal of Korea Multimedia Society
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• v.23 no.2
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• pp.155-165
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• 2020

In this paper, we propose a smart thermostat temperature set-point control method based on machine learning and rule engine, which controls thermostat's temperature set-point so that it can achieve energy savings as much as possible without sacrifice of occupants' comfort while users' preference usage pattern is respected. First, the proposed method periodically mines data about how user likes for heating (winter)/cooling (summer) his or her home by learning his or her usage pattern of setting temperature set-point of the thermostat during the past several weeks. Then, from this learning, the proposed method establishes a weekly schedule about temperature setting. Next, by referring to thermal comfort chart by ASHRAE, it makes rules about how to adjust temperature set-points as much as low (winter) or high (summer) while the newly adjusted temperature set-point satisfies thermal comfort zone for predicted humidity. In order to make rules work on time or events, we adopt rule engine so that it can achieve energy savings properly without sacrifice of occupants' comfort. Through experiments, it is shown that the proposed smart thermostat temperature set-point control method can achieve better energy savings while keeping human comfort compared to other conventional thermostat.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.36C no.3
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• pp.47-56
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• 1999

Various phonological alteration occurs when we pronounce continuously in korean. This phonological alteration is one of the major reasons which make the speech recognition of korean difficult. This paper presents a rule-based system which converts a speech recognition character string to a text-based character string. The recovery results are morphologically analyzed and only a correct text string is generated. Recovery is executed according to four kinds of rules, i.e., a syllable boundary final-consonant initial-consonant recovery rule, a vowel-process recovery rule, a last syllable final-consonant recovery rule and a monosyllable process rule. We use a x-clustering information for an efficient recovery and use a postfix-syllable frequency information for restricting recovery candidates to enter morphological analyzer. Because this system is a rule-based system, it doesn't necessitate a large pronouncing dictionary or a phoneme dictionary and the advantage of this system is that we can use the being text based morphological analyzer.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.3
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• pp.233-238
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• 2010

This paper describes a multi-mobile robot system with fuzzy rule based structure in collision avoidance. Collision avoidance is an important function to perform a given task collaboratively and cooperatively in multi-mobile robot environments. So the important but challenging problem is handled in this paper. Considered obstacles for collision avoidance between multi mobile robots are static, dynamic, or both of them at the same time. Using the fuzzy rule based structure, distance and angle from a robot to obstacles are described as fuzzy linguistic values and steering angle for the robot are updated from the collision environments. As a result, the multi-mobile robot can modify a global path from a robot itself to its own target. In addition, avoiding collision with static or dynamic obstacles for the robot system can be achieved. Simulation based experimental results are given to show usefulness of this method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2000.05a
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• pp.86-89
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• 2000

In this paper, we consider a fuzzy system representation for polynomials of two variables. The representation we use is an exact transformation of the corresponding cubic spline interpolation function. We examine some of the properties of their fuzzy rule tables md prove that the rule table is symmetric or antisymmetric depending on whether the polynomial is symmetric or antisymmetric. A few examples are included to verify our proof. These results not only provide some insights on properties of the cubic spline interpolation coefficients but also provide some help in setting up fuzzy rule tables for functions of two variables.

• Journal of the Korean Data and Information Science Society
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• v.19 no.4
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• pp.1141-1151
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• 2008

Data mining is the process of sorting through large amounts of data and picking out useful information. One of the well-studied problems in data mining is the exploration of association rules. An association rule technique finds the relation among each items in massive volume database. Some interestingness measures have been developed in association rule mining. Interestingness measures are useful in that it shows the causes for pruning uninteresting rules statistically or logically. This paper propose a conditional pure confidence to evaluate association rules and then describe some properties for a proposed measure. The comparative studies with confidence and pure confidence are shown by numerical example. The results show that the conditional pure confidence is better than confidence or pure confidence.

• East Asian Economic Review
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• v.17 no.1
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• pp.27-53
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• 2013

In this paper, we look at the relationship between international trade and the rule of law, using the World Justice Project Rule of Law Index, which include index figures on human rights, limits on government powers, transparency and regulatory efficiency. Based on regression analyses using the rule of law index figures and international trade figures (merchandise trade, service trade, exports and imports as percentage of GDP,) international trade and basic human rights seem to have little relationship; but trade has a close positive relationship with strong order and security. Somewhat surprisingly, regulatory transparency and effective implementation seems to have little or no effect on international trade and vice versa. International trade shows a clear positive relationship with the country's criminal justice system, but the relationship with the civil justice system is not as clear as such. For regulatory implementation and civil justice, services trade positively affect these institutions, but these institutions in turn affect exports more strongly than services trade. Finally, the effect of trade on rule of law is stronger on a medium to long term (10-20 year) time horizon.