• Journal of the Korea Society of Computer and Information
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• v.15 no.10
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• pp.147-156
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• 2010

There are some of the studies on sensor middleware. However the standard middleware has not yet been defined. Especially, this paper focuses on the processing an intelligent service of the main functions of middleware. Several applications in the sensor network environment support not only monitoring services, but also sensor-based context-awareness and intelligent services based on sensors. However, the previous studies about USN middleware only mentioned the need for intelligent service and did not discuss the architecture and method for supporting the intelligent service in detail. Therefore this paper designs a USN middleware for providing intelligent services and proposes the method for processing the services. For this purpose, this paper proposes the Sensor-Service ontology to define the concept of services and sensors for USN applications and the relationship between them. The Sensor-Service ontology is used to infer high-level information from low-level information. To apply a variety of environmental context to intelligent services, the paper uses the rule-based reasoning. This paper implements the proposed intelligent service middleware as a prototype and then shows that the middleware can be used for a variety of USN applications through the performance evaluation.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.1
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• pp.52-64
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• 1995

Robot manipulator is a highly nonlinear-time varying system. Therefore, a lot of control theory has been applied to the system. Robot manipulator has two types of control; one is path planning, another is path tracking. In this paper, we select the path tracking, and for this purpose, propose the intelligent control¬ler which is combined with fuzzy logic and neural network. The fuzzy logic provides an inference morphorlogy that enables approximate human reasoning to apply to knowledge-based systems, and also provides a mathematical strength to capture the uncertainties associated with human cognitive processes like thinking and reasoning. Based on this fuzzy logic, the fuzzy logic controller(FLC) provides a means of converhng a linguistic control strategy based on expert knowledge into automahc control strategy. But the construction of rule-base for a nonlinear hme-varying system such as robot, becomes much more com¬plicated because of model uncertainty and parameter variations. To cope with these problems, a auto-tuning method of the fuzzy rule-base is required. In this paper, the GA-based Fuzzy-Neural control system combining Fuzzy-Neural control theory with the genetic algorithm(GA), that is known to be very effective in the optimization problem, will be proposed. The effectiveness of the proposed control system will be demonstrated by computer simulations using a two degree of freedom robot manipulator.

• Journal of KIISE:Databases
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• v.28 no.3
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• pp.279-300
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• 2001

Data mining plays an important role in knowledge discovery process and usually various existing algorithms are selected for the specific purpose of the mining. Currently, data mining techniques are actively to the statistics, business, electronic commerce, biology, and medical area and currently numerous algorithms are being researched and developed for these applications. However, in a long run, only a few algorithms, which are well-suited to specific applications with excellent performance in large database, will survive. So it is reasonable to focus our effort on those selected algorithms in the future. This paper classifies about 30 existing algorithms into 7 categories - association rule, clustering, neural network, decision tree, genetic algorithm, memory-based reasoning, and bayesian network. First of all, this work analyzes systematic hierarchy and characteristics of algorithms and we present 14 criteria for classifying the algorithms and the results based on this criteria. Finally, we propose the best algorithms among some comparable algorithms with different features and performances. The result of this paper can be used as a guideline for data mining researches as well as field applications of data mining.

• Journal of Arbitration Studies
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• v.22 no.2
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• pp.53-77
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• 2012

Competence-competence refers to an arbitratorpower to determine whether he or she has jurisdiction to decide a controversy. Although arbitrators power to rule on their own jurisdiction is generally recognized throughout the world, in the United States, neither the courts nor legislative bodies have recognized its significance or the reasoning behind its widespread adoption. Section 3 of the Federal Arbitration Act (FAA) is notorious among arbitration statues for its failure to incorporate competence-competence. When courts rule on an issue of competence-competence, it is referred to as a question of who decides the arbitrability of the case. In the United States, the use of competence-competence as a term of art is still limited to scholarly writings. The answer to the competence-competence inquiry is found in an interpretation of section 3 of the FAA which empowers the courts to decide arbitrability issues. The cases of the Supreme Court and most commentators interpreted sections 2 and 3 of the FAA as conferring issues of arbitrability on the federal courts, including the ability to rule on the validity and scope of the arbitral agreement. Traditionally, United States courts have denied the competence-competence to arbitral tribunal. Recently, however, they have confounded the rules by placing primary importance on the arbitration agreement between the parties. The Supreme Court, in a series of cases, has underscored the necessity of giving full effect to the intentions of the parties as expressed in their agreement to arbitrate. The result of the Supreme Court's emphasis on contractualism in determining the issue of arbitrability is most evident in the Courtdecision in the First Options case. Under First Options, courts are to decide arbitrability issues unless there is a clear and unmistakable contractual assignment of these issues to the tribunal itself. The Court is appraised that it has attempted to compromise between contractual freedom in the arbitration setting and the rule of law that is necessary in a society that depends on the concept of ordered liberty. In the decision in Howsam, the Court clarified the definition of arbitrability by attempting to draw a clear line between questions of arbitrability that are to be decided by courts and those matters that bear on the allocation of decisions between courts and arbitrators but are not questions of arbitrability.

• Journal of Internet Computing and Services
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• v.16 no.6
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• pp.69-78
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• 2015

Recently, research on the multi-agent system is developed actively in the various fields, especially on the control of complex system and optimization. In this study, we develop a multi-agent system for NPC simulation in game environment. The purpose of the development is to support quick and precise decision by inferencing the situation of the dynamic discrete domain, and to support an optimization process of the agent system. Our approach employed Petri-net as a basic agent model to simplify structure of the system, and used fuzzy inference engine to support decision making in various situation. Our experimentation describes situation of the virtual battlefield between the NPCs, which are divided two groups, such as fuzzy rule based agent and automata based agent. We calculate the percentage of winning and survival rate from the several simulations, and the result describes that the fuzzy rule based agent showed better performance than the automata based agent.

• School Mathematics
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• v.11 no.2
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• pp.261-280
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• 2009

This study was motivated by recognizing the weakness of teaching and learning about the concepts of statements in high school mathematics curriculum. To report the reality of students' understanding about statements, this study investigated the 33 first-year undergraduate students' understanding about the concepts of statements by giving them 22 statement problems. The problems were selected based on the conceptual framework including five types of statement concepts which are considered as the key ideas for understanding mathematical reasoning and proof in college level mathematics. The analysis of the participants' responses to the statement problems found that their understanding about the concepts of prepositions are very limited and extremely based on the instrumental understanding applying an appropriate remembered rule to the solution of a preposition problem without knowing why the rule works. The results from this study will give the information for effective teaching and learning of statements in college level mathematics, and give the direction for the future reforming the unite of statements in high school mathematics curriculum as well.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.7 no.11
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• pp.515-524
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• 2017

In this paper, we design and implement an expert system for diagnosing ADHD. As a result of the analysis with DSM-IV-TR, the ADHD diagnostic criteria are changed according to the age group. With this analyzed diagnostic, objects and their values are set and rules are created. We design a diagnostic system consisting of 'ADHD diagnostic system engine' and 'user query response program'. The ADHD diagnostic system engine is a rule-based reasoning engine that is implemented in the Prolog language and receives INPUT from the user query response program. By INPUT, the rule is executed based on the ADHD diagnostic criteria and the OUTPUT is sent back to the 'user query response program' by inferring the diagnostic result. The 'user query response program' is implemented in the Python language and serves as an interface for handling conversation with the user. The bridge between 'ADHD diagnostic system engine' and 'user query response program' is performed through the Pyswip library. As a result, the ADHD Diagnostic Expert System will help you plan your treatment with reduced diagnostic costs and use-complexity.

• Journal of the Korean earth science society
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• v.33 no.2
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• pp.170-182
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• 2012

The purpose of this study was to develop learning materials based on the Kepler's abductive reasoning and to identify high school students' rule-inferring strategies on the law of planetary motion. The learning materials including the concepts of solar magnetic field, conservation of figure skater's angular momentum and Kepler's polyhedral theory were developed and the questions about Kepler's 2nd and 3rd law of planetary motion were also created. The participants were 79science high school students and 83general high school students. The patterns and properties of their abductive inference were analyzed. The findings revealed that the students showed 'incomplete analogy abduction', 'analogy abduction' and 'reconstruction' to generate the hypotheses concerning the Mars' motion related to the solar magnetic field. There were more general high school students who showed the incomplete analogy abduction than science high school students. On the other hand, there were more science high school students who showed the analogy abduction and reconstruction strategy than general high school students. Also, they showed 'incomplete analogy abduction', 'analogy abduction' and 'model construction and manipulation' to generate the hypotheses concerning Kepler's second law. A number of general high school students showed the incomplete analogy. It is suggested that because the analogy of figure skater cause the students' alternative framework to use, more detailed demonstration is necessary in class. In addition, students combined Kepler's polyhedral theory with their prior knowledge to infer Kepler's third law.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.321-328
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• 2008

인간이 그린 그림은 자신의 심리적 상태와 성격, 정서적인 갈등과 같이 자기표현을 나타낸다. 그림을 통해서 색채 정보와 그린 물체의 위치를 통하여 그린 사람의 심리 상태를 파악하고 치료 할 수 있다. 이러한 그림 치료를 통해서 갈등을 조정하고, 자기 표현과 승화 과정을 통해 자아의 성장 과정을 도울 수 있고, 내담자들의 객관적이고 의식적인 서술만으로 파악하기 어려운 문제를 그림을 통해 무의식 세계를 쉽게 알 수 있다. 본 논문에서는 인간이 그린 그림에서 색채정보와 물체의 위치 정보를 분석하고 퍼지추론 규칙을 이용하여 감성 상태를 파악하는 방법을 제안한다. 제안된 방법을 알슈울러와 해트릭(Alschuler and Hattwick)의 색채에 따른 감성상태와 Grunwald의 그림 표현의 공간 구성에 따른 심리상태에 적용한 결과, 제안된 감성 분석 방법이 효율적인 것을 확인하였다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.3
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• pp.518-526
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• 2008

The fuzzy self-tuning PID controller is a PID controller with a fuzzy logic mechanism for tuning its gains on-line. In this structure, the proportional, integral and derivative gains are tuned on-line with respect to the change of the output of system under control. This paper deals with two types of fuzzy self-tuning PID controllers, rule-based fuzzy PID controller and learning fuzzy PID controller. As a medical application of fuzzy PID controller, the proposed controllers were implemented and evaluated in a laparoscopic surgery robot system. The proposed fuzzy PID structures maintain similar performance as conventional PID controller, and enhance the position tracking performance over wide range of varying input. For precise approximation, the fuzzy PID controller was realized using the linear reasoning method, a type of product-sum-gravity method. The proposed controllers were compared with conventional PID controller without fuzzy gain tuning and was proved to have better performance in the experiment.