• Proceedings of the Korean Information Science Society Conference
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• 2010.06a
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• pp.144-145
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• 2010

• Proceedings of the Korean Information Science Society Conference
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• 2000.10a
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• pp.54-56
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• 2000

데이터 마이닝 작업에서 사용되는 데이터의 크기는 그 특성상 대규모를 이루고 있다. 이러한 대규모의 데이터로부터 규칙을 추출하는 작업은 많은 배용이 소모된다. 또한 급변하는 데이터는 이미 발견된 마이닝 패턴에 대하여 현저한 패턴은 약한 패턴으로, 반면 약한 패턴은 현저한 패턴으로 변화시키는 요인이 되고 있다. 이러한 동적 환경에서는 기존의 데이터베이스 특정시간의 스냅 샷 형태의 데이터를 이용하였던 마이닝 방법으로는 적당하지 못하다. 따라서 이 논문에서는 동적인 환경에서 적용할 수 있는 점진적 마이닝 방법을 제시하고, 점진적 마이닝 작업이 효과적으로 수행 가능한 능동시스템 모델을 제시한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.5
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• pp.569-574
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• 2011

In this paper, we introduce the subspace contrasting group identification problem and propose an algorithm to solve the problem. In order to identify contrasting groups, the algorithm first determines two groups of which attribute values are in one of the contrasting ranges specified by the analyst, and searches for the contrasting groups while increasing the dimension of subspaces with an association rule mining strategy. Because the dimension of microarray data is likely to be tens of thousands, it is burdensome to find all contrasting groups over all possible subspaces by query generation. It is very useful in the sense that the proposed method allows to find those contrasting groups without analyst's involvement.

• Smart Structures and Systems
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• v.30 no.6
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• pp.639-648
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• 2022

This study aims at numerically and experimentally investigating torsional guided wave mixing with weak material nonlinearity under acoustoelastic effect in tubular structures. The acoustoelastic effect on single central frequency guided wave propagation in structures has been well-established. However, the acoustoelastic on guided wave mixing has not been fully explored. This study employs a three-dimensional (3D) finite element (FE) model to simulate the effect of stress on guided wave mixing in tubular structures. The nonlinear strain energy function and theory of incremental deformation are implemented in the 3D FE model to simulate the guided wave mixing with weak material nonlinearity under acoustoelastic effect. Experiments are carried out to measure the nonlinear features, such as combinational harmonics and second harmonics in related to different levels of applied stresses. The experimental results are compared with the 3D FE simulation. The results show that the generation combinational harmonic at sum frequency provides valuable stress information for tubular structures, and also useful for damage diagnosis. The findings of this study provide physical insights into the effect of applied stresses on the combinational harmonic generation due to wave mixing. The results are important for applying the guided wave mixing for in-situ monitoring of structures, which are subjected to different levels of loadings under operational condition.

• Journal of Korea Multimedia Society
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• v.9 no.1
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• pp.1-10
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• 2006

In document clustering methods, the k-means algorithm and the Hierarchical Alglomerative Clustering(HAC) are often used. The k-means algorithm has the advantage of a processing time and HAC has also the advantage of a precision of classification. But both methods have mutual drawbacks, a slow processing time and a low quality of classification for the k-means algorithm and the HAC, respectively. Also both methods have the serious problem which is to compute a document similarity whenever new document is inserted into a cluster. A main property of web resource is to accumulate an information by adding new documents frequently. Therefore, we propose a new method of transitive closure tree based on the HAC method which can improve a processing time for a document clustering, and also propose a superior incremental clustering method for an insertion of a new document and a deletion of a document contained in a cluster. The proposed method is compared with those existing algorithms on the basis of a pre챠sion, a recall, a F-Measure, and a processing time and we present the experimental results.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.21 no.45
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• pp.121-133
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• 1998

This study suggests an efficient algorithm for updating discovered association rules in large database, because a database may allow frequent or occasional updates, and such updates may not only invalidate some existing strong association rules, but also turn some weak rules into strong ones. FUP and DMI update efficiently strong association rules in the whole updated database reusing the information of the old large item-sets. Moreover, these algorithms use a pruning technique for reducing the database size in the update process. This study updates strong association rules efficiently in the whole updated database reusing the information of the old large item-sets. An updating algorithm that is suggested in this study generates the whole candidate item-sets at once in an incremental database in view of the fact that it is difficult to find the new set of large item-sets in the whole updated database after an incremental database is added to the original database. This method of generating candidate item-sets is different from that of FUP and DMI. After generating the whole candidate item-sets, if each item-set in the whole candidate item-sets is large at an incremental database, the original database is scanned and the support of each item-set in the whole candidate item-sets is updated. So, the whole large item-sets in the whole updated database is found out. An updating algorithm that is suggested in this study does not use a pruning technique for reducing the database size in the update process. As a result, an updating algoritm that is suggested updates fast and efficiently discovered large item-sets.

• Journal of Navigation and Port Research
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• v.34 no.3
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• pp.195-203
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• 2010

This paper concerns about total dynamic analysis of integrated mining system. This system consists of vertical steel pipe, intermediate buffer station, flexible pipe and self-propelled miner. The self-propelled miner and buffer are assumed as rigid-body of 6-dof. Discrete models of vertical steel pipe and flexible pipe are adopted, which are obtained by means of lumped-parameter method. The motion of mining vessel is not considered. Instead, the motion of mining vessel is taken into account in form of various boundary conditions (e.g. forced excitation in slow motion and/or fast oscillation and so on). A terramechanics model of extremely cohesive soft soil is applied to the self-propelled miner. Hinged and ball constraints are used to define the connections between sub-systems (vertical steel pipe, buffer, flexible pipe, self-propelled miner). Equations of motion of the coupled model are derived with respect to the each local coordinates system. Four Euler parameters are used to express the orientations of the sub-systems. To solve the equations of motion of the total dynamic model, an incremental-iterative formulation is employed. Newmark-${\beta}$ method is used for time-domain integration. The total dynamic responses of integrated mining system are investigated.

• Geomechanics and Engineering
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• v.14 no.2
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• pp.141-149
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• 2018

In this paper, the creep behavior of bolted rock was analyzed by using the unconfined creep tests and the numerical results. Based on the test results, the Bolted Burgers creep model (B-B model) was proposed to clarify the creep mechanism of rock mass due to rock bolts. As to the simulation of the creep behaviour of bolted rock, a new user-defined incremental iterative format of the B-B model was established and the open-source $FLAC^{3D}$ code was written by using the object-oriented language (C++). To check the reliability of the present B-B creep constitutive model program, a numerical model of a tunnel with buried depth of 1000 m was established to analyze the creep response of the tunnel with the B-B model support, the non-support and the bolt element support. The simulation results show that the present B-B model is consistent with the calculated results of the inherent bolt element in $FLAC^{3D}$, and the convergence deformation can be more effectively controlled when the proposed B-B model is used in the $FLAC^{3D}$ software. The big advantage of the present B-B creep model secondarily developed in the $FLAC^{3D}$ software is the high computational efficiency.

• The KIPS Transactions:PartB
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• v.12B no.4 s.100
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• pp.487-498
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• 2005

Recently, It has focused on decision tree algorithm that can handle large dataset. However, because most of these algorithms for large datasets process data in a batch mode, if new data is added, they have to rebuild the tree from scratch. h more efficient approach to reducing the cost problem of rebuilding is an approach that builds a tree incrementally. Representative algorithms for incremental tree construction methods are BOAT and ITI and most of these algorithms use a local discretization method to handle the numeric data type. However, because a discretization requires sorted numeric data in situation of processing large data sets, a global discretization method that sorts all data only once is more suitable than a local discretization method that sorts in every node. This paper proposes an incremental tree construction method that efficiently rebuilds a tree using a global discretization method to handle the numeric data type. When new data is added, new categories influenced by the data should be recreated, and then the tree structure should be changed in accordance with category changes. This paper proposes a method that extracts sample points and performs discretiration from these sample points to recreate categories efficiently and uses confidence intervals and a tree restructuring method to adjust tree structure to category changes. In this study, an experiment using people database was made to compare the proposed method with the existing one that uses a local discretization.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.1
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• pp.40-44
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• 2005

Applying artificial intelligence, machine learning and data mining techniques to intrusion detection system are increasing. But most of researches are focused on improving the performance of classifier. These classifiers are performed by batch way and it is not proper method for realtime intrusion detection system. We propose an incremental feature extraction and classification technique for realtime intrusion detection system. Applying proposed system to KDD CUP 99 data, experimental result shows that it has similar capability compared to batch way intrusion detection system.