• 한국지능시스템학회논문지
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• 제14권6호
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• pp.764-770
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• 2004

This paper presents a hybrid data mining mechanism to extract expert knowledge from historical data and extend expert systems' reasoning capabilities by using fuzzy neural network (FNN)-based learning & rule extraction algorithm. Our hybrid data mining mechanism is based on association rule extraction mechanism, FNN learning and fuzzy rule extraction algorithm. Most of traditional data mining mechanisms are depended ()n association rule extraction algorithm. However, the basic association rule-based data mining systems has not the learning ability. Therefore, there is a problem to extend the knowledge base adaptively. In addition, sequential patterns of association rules can`t represent the complicate fuzzy logic in real-world. To resolve these problems, we suggest the hybrid data mining mechanism based on association rule-based data mining, FNN learning and fuzzy rule extraction algorithm. Our hybrid data mining mechanism is consisted of four phases. First, we use general association rule mining mechanism to develop an initial rule base. Then, in the second phase, we adopt the FNN learning algorithm to extract the hidden relationships or patterns embedded in the historical data. Third, after the learning of FNN, the fuzzy rule extraction algorithm will be used to extract the implicit knowledge from the FNN. Fourth, we will combine the association rules (initial rule base) and fuzzy rules. Implementation results show that the hybrid data mining mechanism can reflect both association rule-based knowledge extraction and FNN-based knowledge extension.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 2003년도 춘계공동학술대회
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• pp.884-888
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• 2003

In this paper, we introduce the hybrid data mining mechanism based in association rule and fuzzy neural networks (FNN). Most of data mining mechanisms are depended in the association rule extraction algorithm. However, the basic association rule-based data mining has not the learning ability. In addition, sequential patterns of association rules could not represent the complicate fuzzy logic. To resolve these problems, we suggest the hybrid mechanism using association rule-based data mining, and fuzzy neural networks. Our hybrid data mining mechanism was consisted of four phases. First, we used general association rule mining mechanism to develop the initial rule-base. Then, in the second phase, we used the fuzzy neural networks to learn the past historical patterns embedded in the database. Third, fuzzy rule extraction algorithm was used to extract the implicit knowledge from the FNN. Fourth, we combine the association knowledge base and fuzzy rules. Our proposed hybrid data mining mechanism can reflect both association rule-based logical inference and complicate fuzzy logic.

• 한국복합재료학회:학술대회논문집
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• 한국복합재료학회 2001년도 춘계학술발표대회 논문집
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• pp.268-271
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• 2001

When compared to other composite materials such as FRP and MMC, hybrid composite material is more attractive one due to the high specific strength and the resistance to fatigue. However, the fracture mechanism of hybrid composite material is extremely complicated because of the bonding structure of metals and FRP. Recently, nondestructive technique has been used to evaluate the fracture mechanism of these composite materials. In this study, AE technique has been used to clarify the fracture mechanism and the degree of damage for Al 7075/CFRP hybrid composite material. It was found that AE event, energy and amplitude among AE parameters were effective to evaluate fracture process of Al 7075/CFRP composite material. In addition, the relationship between the AE signal and the characteristics of failure surface using optical microscope was discussed.

• 제어로봇시스템학회논문지
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• 제5권3호
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• pp.324-337
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• 1999

In this work, a new 3-PSP type spatial 3-degree-of-freedom parallel mechanism is proposed. And a 6 DOF hybrid manipulator which consists of a 3-PPR type planar 3 DOF parallel mechanism and a new 3-PSP type spatial 3-degree-of-freedom parallel mechanism is proposed. Both 3 DOF mechanism modules have closed-form forward position solutions and particularly, 3-PSP spatial module has unique forward position solution. Firstly, the closed-form position analysis and first-order kinematic analysis for the proposed 3-PSP type module are carried out, and the first-order kinematic characteristics are examined via maximum singular value and the isotropic index of the mechanism. It is shown through these analyses that the mechanism has excellent isotrpic property throughout the workspace. Secondly, position and kinematic analysis of the 3-PPR planar module are briefly described. Thirdly, the forward position analysis for the 3-PPR 3-PSP type 6 degree-of-freedom hybrid mechanism consisting of a 3-PPR planar module and a 3-PSP spatial module is performed along with the analysis of the workspace size and first-order kinematic characteristics. The kinematic characteristics of the proposed hybrid manipulator are compared to those of geometrically similar Stewart manipulator.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2003년도 춘계학술대회
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• pp.729-733
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• 2003

Hybrid RMU is a kind of power circuit breaker and protects electric devices from over-current. In this paper we built a dynamic model of RMU driving mechanism using ADAMS and performed a optimal design of several design parameters. Finally we developed a prototype of RMU driving mechanism through results of analysis and confirmed it to satisfy design requisitions.

• 한국컴퓨터정보학회논문지
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• 제21권4호
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• pp.17-24
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• 2016

In this paper, we propose a AH LSU(Advanced Hybrid QoS Routing Link State Update) Algorithm that improves the performance of Hybrid LSU(Hybrid QoS Link State State Update) Algorithm with statistical information of flow holding time in network. AH LSU algorithm has had both advantages of LSU message control in periodic QoS routing LSU algorithm and QoS routing performance in adaptive LSU algorithm. It has the mechanism that calculate LSU message transmission priority using the flow of statistical request bandwidth and available bandwidth and include MLMR(Meaningless LSU Message Removal) mechanism. MLMR mechanism can remove the meaningless LSU message generating repeatedly in short time. We have evaluated the performance of the MLMR mechanism, the proposed algorithm and the existing algorithms on MCI simulation network. We use the performance metric as the QoS routing blocking rate and the mean update rate per link, it thus appears that we have verified the performance of this algorithm.

• 대한기계학회논문집
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• 제19권7호
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• pp.1619-1629
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• 1995

The Al/Al$_{2}$O$_{3}$ SiC and Al/Al$_{2}$O$_{3}$/C hybrid metal matrix composites (MMCs) were fabricated by squeeze infiltration method. Uniform distribution of reinforcements were found in the microstructure of metal matrix composites. Mechanical tests were carried out under various test conditions to clearly identify mechanical behavior of MMCs, and the wear mechanism of Al/Al$_{2}$O$_{3}$/(SiC or C) hybrid metal matrix composites were investigated. The tensile strength and hardness of hybrid composites was resulted in increasing compared with those of the unreinforced matrix alloy. Wear resistance was strongly dependent upon kinds of fiber, volume fraction and sliding speed. The wear resistance of metal matrix composites was remarkably improved by the addition of reinforcements. Especially, the wear resistance of the hybrid composites of carbon fibers was more effective than in the composites reinforced with alumina and SiC whiskers of reinforcements. This was due to the effect of carbon fiber on the solid lubrication. Wear mechanisms of hybrid composites were suggested from wear surface analyses. The major wear mechanism of hybrid composites was the abrasive wear at low to intermediate sliding speed, and the melting wear at intermediate to high sliding speed.

• 한국복합재료학회:학술대회논문집
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• 한국복합재료학회 1999년도 추계학술발표대회 논문집
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• pp.168-171
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• 1999

For the axial crushing tests of various shape of tubes, it was reported that composite tubes need trigger mechanism to avoid brittle failure. In this study, static axial crush tests were performed with the new aluminum/GFRP hybrid tubes. Glass/Epoxy prepregs were wrapped around aluminum tube and co-cured. The failure of hybrid tube was stable and progressive without trigger mechanism, and specific energy absorption was increased to maximum 34% in comparison with aluminum tube. Effective energy absorption is possible for inner aluminum tube because wrapped composite tube constrain the deflection of aluminum tube and reduce the folding length. The failure of hybrid composite tube was stable without trigger mechanism because inner aluminum tube could play the role of crack initiator and controller. Aluminum/Glass-Epoxy hybrid tube is suitable for the vehicle front structure due to effective energy absorption capability, easy production, and simple application for RTM process.

• 한국자동차공학회논문집
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• 제8권6호
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• pp.208-219
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• 2000

In this study, static axial crush tests were performed with the new aluminum/GFRP hybrid tube. Glass/Epoxy prepregs were wrapped around an aluminum tube and co-cured. The failure of the hybrid tube was stable and progressive without trigger mechanism, and specific energy absorption was increased to the maximum of 33% in comparison with the aluminum tube. Effective energy absorption is possible for an inner aluminum tube because a wrapped composite tube constrains the deflection of an aluminum tube. The failure of a hybrid composite tube was stable without trigger mechanism because the inner aluminum tube could play the role of the crack initiator and controller. Mean crushing load could be calculated by modifying the plastic hinge collapse model for hybrid materials. The predicted results by this analytical model showed good agreement with the experimental results. It can be said that Aluminum/Glass-Epoxy hybrid tube is suitable for the vehicle front structure because this hybrid tube shows effective energy absorption, easy production, and simple application capability for RTM process.

• 한국지능시스템학회논문지
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• 제13권3호
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• pp.366-370
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• 2003

In this research, we suggest a hybrid intelligent Web recommendation systems based on Web data mining and case-based reasoning (CBR). One of the important research topics in the field of Internet business is blending artificial intelligence (AI) techniques with knowledge discovering in database (KDD) or data mining (DM). Data mining is used as an efficient mechanism in reasoning for association knowledge between goods and customers＇ preference. In the field of data mining, the features, called attributes, are often selected primary for mining the association knowledge between related products. Therefore, most of researches, in the arena of Web data mining, used association rules extraction mechanism. However, association rules extraction mechanism has a potential limitation in flexibility of reasoning. If there are some goods, which were not retrieved by association rules-based reasoning, we can＇t present more information to customer. To overcome this limitation case, we combined CBR with Web data mining. CBR is one of the AI techniques and used in problems for which it is difficult to solve with logical (association) rules. A Web-log data gathered in real-world Web shopping mall was given to illustrate the quality of the proposed hybrid recommendation mechanism. This Web shopping mall deals with remote-controlled plastic models such as remote-controlled car, yacht, airplane, and helicopter. The experimental results showed that our hybrid recommendation mechanism could reflect both association knowledge and implicit human knowledge extracted from cases in Web databases.