• Journal of Intelligence and Information Systems
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• v.11 no.2
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• pp.151-173
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• 2005

We developed a methodology of rule acquisition from texts such as Web pages which utilizes ontology in identification of rule components. We expect that the proposed methodology can reduce the bottleneck of rule acquisition and contribute to the utilization of rule based systems. As parts of our research, we designed an ontology for rule acquisition named OntoRule and proposed a rule acquisition methodology through OntoXRML which is an acquisition tool using OntoRule. Also, we evaluated our approach by calculating missed recommendations and wrong recommendations of rule components in rule acquisition experiments over three online bookstores.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.162-164
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• 2004

This paper proposes a new classification system combining the adaptive feature weighting algorithm using the genetic algorithm and the modified KNN rule. GA is employed to choose the middle value of weights and weights of features for high performance of the system. The modified KNN rule is proposed to estimate the class of test pattern using adaptive feature space. Experiments with the unconstrained handwritten digit database of Concordia University in Canada are conducted to show the performance of the proposed method.

• Proceedings of the KIEE Conference
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• 2004.07d
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• pp.2474-2476
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• 2004

지폐 인식 자동화기기가 여러 분야에 보편화되면서 다양한 지폐를 고속으로 처리할 수 있는 고속지폐 인식 자동화 기기가 요구되고 있다. 하지만 대부분의 지폐 인식 자동화 기기가 고속화에 적합하지 않은 구조로 설계되어 있고 신권 추가가 용이하지 않다. 본 논문은 고속 Paper Currency 인식 시스템에 적합한 범용 하드웨어 시스템과 Bayes Rule 기반의 고속 인식 알고리즘을 제안한다. 제안된 범용 하드웨어 구조는 고속의 CIS(Contact Image Sensor)와 DSP(Digital Signal Processor) 그리고 Dual Memory System으로 구성되었다. Bayes Rule에 기초한 고속 인식 알고리즘은 기존의 Paper Currency 인식 시스템에 사용되었던 기계학습 방법에 비해 신권 추가가 쉽고 적은 연산으로 권종을 판별할 수 있어 고속 지폐 인식 자동화기기에 적합하다. 본 논문에서는 제안된 방법들을 실제 자동화기기로 구현하여 그 유용성을 검증한다.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.1
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• pp.18-25
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• 1992

In this paper, a rule checker which aids in composing a consistent knowledge base by checking redundancies and inconsistencies in a knowledge base is proposed. The proposed algorithm checks the rules by representing the rule connections as a network . The standard model of the rules adapted in this algorithm is in the Conjunctive Normal Form which includes NOT's, and rules of conventional expert system can be checked by converting them into the standard form by a rule form at converter. When compared with Ginsberg's KB-reducer which is conceptually most similar to the proposed algorithm among existing methods,it is shown by a computer simulation that with 360 rules, the checking time is three times faster and the rate increased as the number of rules increased, but the total memory requirement of the proposed agorithm is 1.2 times larger. The proposed algorithm has further advantages in that it can check circular rule chains and can find the paths of the redundant and inconsistent rules.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.28 no.2
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• pp.46-52
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• 2005

In this paper, we present a temporal association rule based on item time intervals. A temporal association rule is an association rule that holds specific time intervals. If we consider itemset in the frequently purchased period, we can discover more significant itemset satisfying minimum support. Because the previous study did not consider the time interval between purchased item, it could find itemset that did not satisfy the minimum support in case some item was frequently purchased in a specific period and rarely or not purchased in other period. Our approach uses interval support which is counted by period with support and confidence in the association rule to discovery large itemset.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.48 no.4
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• pp.444-451
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• 1999

A diagnostic rule-base design method for enhancing fault detection and isolation performance of multiple obsever based fault detection isolation schemes (FIDS) is presented. The diagnostic rule-base has a hierarchical framework to perform detection and isolation of faults of interest, and diagnosis of process faults. The decision unit comprises a rule base and a fuzzy inference engine and removes some difficulties of conventional decision unit which includes crisp logic with threshold values. Emphasis is placed on the design and evaluation methods of the diagnostic rult-base. The suggested scheme is applied to the FDIS design for a DC motor driven centrifugal pump system.

• Structural Engineering and Mechanics
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• v.87 no.1
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• pp.57-68
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• 2023

Response spectrum method is still an effective approach for the design of buildings with supplemental dampers. In practice, complex complete quadratic combination (CCQC) rule is always used in the response spectrum method to consider the effect of non-classical damping. The conventional CCQC rule is based on exact complex mode vectors. Sometimes the calculated complex mode vectors may be not excited by the external loading and errors in the structural responses always arise due to the mode truncation. Load-dependent Ritz (LDR) vectors are associated with the external loading and LDR vectors not excited can be automatically excluded. Also, contributions of higher modes are implicitly contained in the LDR vectors in terms of static responses. To improve the calculation efficiency and accuracy, LDR vectors are introduced in the CCQC rule in the present study. Firstly, the generation procedure of LDR vectors suitable for non-classical damping system is presented. Compared to the conventional LDR vectors, the LDR vectors herein are complex-valued and named as complex LDR (CLDR) vectors. Based on the CLDR vectors, the CCQC rule is then rederived and an improved response spectrum method is developed. Finally, the effectiveness of the proposed method in this paper is verified through three typical non-classical damping buildings. Numerical results show that the CLDR vector is superior to the complex mode with the same number in the calculation. Since the generation of CLDR vectors requires less computational cost and storage space, the method proposed in this paper offers an attractive alternative, especially for structures with a large number of degrees of freedom.

• Journal of the Korea Institute of Military Science and Technology
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• v.14 no.1
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• pp.123-131
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• 2011

In this paper, modeling and design of a distributed detection system are considered for an active sonar sensor network. The sensor network has a parallel configuration and it consists of a fusion center and a set of receiver nodes. A system with two receiver nodes is considered to investigate a theoretical aspect of design. To be specific, AND rule and OR rule are considered as the fusion rules of the sensor network. For the fusion rules, it is shown that a threshold rule of each sensor node has uniformly most powerful properties. Optimum threshold for each sensor is obtained that maximizes the probability of detection given probability of false alarm. Numerical experiments were also performed to investigate the detection characteristics of a distributed detection system with multiple sensor nodes. The experimental results show how signal strength, false alarm probability, and the distance between nodes in a sensor field affect the system detection performances.

• The Transactions of the Korea Information Processing Society
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• v.5 no.8
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• pp.2075-2082
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• 1998

Rule-based knowledge representHtion is, the most popular technique for ,storage and manipulation of domain knowledge in expert system. By the way, the amount of knowledge increases more and more in this representatiun technique, it, relationship becomes complex, and even its contents can be modified. This is the reason why rule-based knowledge representation technique requires a verification ,system which can maintain consistency and completeness of knowledge base. This paper is to propose a verification system for consistency and completeness of knowledge base to promote the efficiency and reliability of expert system. After verifying the potential errors both in structure and in semantics whenever a new rule is added, this system renders knowledge base consistent and complete by correcting them automatically or by making expert correct them if it fails.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 1998.06a
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• pp.417-422
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• 1998

This paper presents a method of object classification from dynamic image based on fuzzy inference algorithm which is suitable for low speed such as, conveyor, uninhabited transportation. At first, by using feature parameters of moving object, fuzzy if - then rule that can be able to adapt the wide variety of surroundings is developed. Secondly, implication function for fuzzy inference are compared with respect the proposed algorithm. Simulation results are presented to testify the performance and applicability of the proposed system.