• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권7호
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• pp.2957-2980
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• 2020

Ensemble clustering commonly integrates multiple basic partitions to obtain a more accurate clustering result than a single partition. Specifically, it exists an inevitable problem that the incomplete transformation from the original space to the integrated space. In this paper, a novel ensemble clustering algorithm using a newly reconstructed mapping coefficient (ECRMC) is proposed. In the algorithm, a newly reconstructed mapping coefficient between objects and micro-clusters is designed based on the principle of increasing information entropy to enhance effective information. This can reduce the information loss in the transformation from micro-clusters to the original space. Then the correlation of the micro-clusters is creatively calculated by the Spearman coefficient. Therefore, the revised co-association graph between objects can be built more accurately because the supplementary information can well ensure the completeness of the whole conversion process. Experiment results demonstrate that the ECRMC clustering algorithm has high performance, effectiveness, and feasibility.

• 한국정밀공학회지
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• 제20권11호
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• pp.47-54
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• 2003

Research during the past several years has established the effectiveness of acoustic emission (AE)-based sensing methodologies for machine condition analysis and process. AE has been proposed and evaluated for a variety of sensing tasks as well as for use as a technique for quantitative studies of manufacturing process. STD11 has been known as difficult-to-cut materials. The micro-grooving machine was developed for this study and the experiments were performed using CBN blade for machining STD11. Evaluating the machining conditions, frequency spectrum analysis of acoustic emission (AE) signals according to each conditions were applied. Fuzzy clustering method for associating the preprocessor outputs with the appropriate decisions was followed by frequency spectrum analysis. FFT is used to decompose AE signal into different frequency bands in time domain, the root mean square (RMS) values extracted from the decomposed signal of each frequency band were used as features.

• Communications for Statistical Applications and Methods
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• 제12권2호
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• pp.335-348
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• 2005

The rapid development of microarray technologies enabled the monitoring of expression levels of thousands of genes simultaneously. Recently, the time course gene expression data are often measured to study dynamic biological systems and gene regulatory networks. For the data, biologists are attempting to group genes based on the temporal pattern of their expression levels. We apply the consensus clustering algorithm to a time course gene expression data in order to infer statistically meaningful information from the measurements. We evaluate each of consensus clustering and existing clustering methods with various validation measures. In this paper, we consider hierarchical clustering and Diana of existing methods, and consensus clustering with hierarchical clustering, Diana and mixed hierachical and Diana methods and evaluate their performances on a real micro array data set and two simulated data sets.

• 대한기계학회논문집A
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• 제25권11호
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• pp.1796-1801
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• 2001

For micro-machines, very few design methodologies based on optimization hale been developed so far. To overcome the difficulties of design optimization of micro-machines, the search method for multi-dimensional design window (DW)s is proposed. The proposed method is defined as areas of satisfactory design solutions in a design parameter space, using both continuous evolutionary algorithms (CEA) and the modified K-means clustering algorithm . To demonstrate practical performance of the proposed method, it was applied to an optimal shape design of micro electrostatic actuator of optical memory. The shape design problem has 5 design parameters and 5 objective functions, and finally shows 4 specific design shapes and design characters based on the proposed DWs.

• 한국멀티미디어학회논문지
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• 제16권1호
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• pp.19-28
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• 2013

In this research, we presented an effective clustering method based on ICA for the analysis of huge Raman hyperspectral dental data. The hyperspectral dataset captured by HR800 micro Raman spectrometer at UMKC-CRISP(University of Missouri-Kansas City Center for Research on Interfacial Structure and Properties), has 569 local points. Each point has 1,005 hyperspectal dentin data. We compared the clustering effectiveness and the clustering time for the case of using all dataset directly and the cases of using the scores after PCA and ICA. As the result of experiment, the cases of using the scores after PCA and ICA showed, not only more detailed internal dentin information in the aspect of medical analysis, but also about 7~19 times much shorter processing times for clustering. ICA based approach also presented better performance than that of PCA, in terms of the detailed internal information of dentin and the clustering time. Therefore, we could confirm the effectiveness of ICA for the analysis of Raman hyperspectral dental data.

• 한국통신학회논문지
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• 제38A권6호
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• pp.504-511
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• 2013

본 논문은 지적재산권 보호를 위한 방안으로 적응형 알고리즘 기반의 초소형 전자소자 탐지 기법을 제안한다. 전자소자를 탐지하는 기본 원리는 분류기의 송신기에서 특정 기본 주파수의 전파가 은닉된 물체로 전파되면, 물체로부터 반사되어 수신기로 들어오는 2차 및 3차 고조파의 크기를 분류기가 비교함으로써 판별하게 된다. 하지만, 측정 과정에서 발생하는 잡음 및 전자파의 간섭으로 인해 분류의 성능이 저하되므로, 이러한 환경에서도 은닉된 전자소자를 적응적으로 판별하기 위해 Fuzzy c-Means 클러스터링 알고리즘과 ${\kappa}$-Nearest Neighbor 분류 알고리즘을 복합적으로 이용하는 방안을 제시한다. 모의실험 결과, 제안 기법이 잡음 및 전자파 간섭 환경에서도 적응적으로 전자소자 잘 탐지할 수 있었으며, 이에 따라 지적재산권을 효율적으로 보호할 수 있을 것으로 기대된다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권4호
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• pp.1773-1795
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• 2020

Unmanned aerial vehicles (UAVs) network are a very vibrant research area nowadays. They have many military and civil applications. Limited bandwidth, the high mobility and secure communication of micro UAVs represent their three main problems. In this paper, we try to address these problems by means of secure clustering, and a security clustering algorithm based on integrated trust value for UAVs network is proposed. First, an improved the k-means++ algorithm is presented to determine the optimal number of clusters by the network bandwidth parameter, which ensures the optimal use of network bandwidth. Second, we considered variables representing the link expiration time to improve node clustering, and used the integrated trust value to rapidly detect malicious nodes and establish a head list. Node clustering reduce impact of high mobility and head list enhance the security of clustering algorithm. Finally, combined the remaining energy ratio, relative mobility, and the relative degrees of the nodes to select the best cluster head. The results of a simulation showed that the proposed clustering algorithm incurred a smaller computational load and higher network security.

• 한국정보처리학회논문지
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• 제7권3호
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• pp.909-922
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• 2000

High sped messaging layer for application's feeling of low level network performance is needed by Clustering System based on high speed network fabrics. It should have the mechanism to directly pass messages between network card and application space, and provide flexible affodabilities for many diverse applications. In this paper, CROWN (Clustering Resources On Workstations' Network) which is designed and implemented for multi-purpose clustering system will be introduced briefly, and CLCP(CROWN Lean Communication Primitives)which is the high speed messaging layer for CROWN will be followed. CLCP consists of a firmware for controlling Myrinet card, device drier, and user libraries. CLCP supports various application domains as a result of pooling and interrupt receive mechanism. In case of polling based receive, 8 bytes short message, and no other process, CLCP has 262 micro-second response time between two nodes, and IM bytes large message, it shows 442Mbps bandwidth.

• 한국결정성장학회지
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• 제1권1호
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• pp.66-73
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• 1991

During the growth of macroscopically dislocation-free Czochralski silicon crystal, micro precipitates causing stacking faults in the silicon wafer during the oxidation are formed Thermal history the cryscausing acquire during the growth process is known to be a key factor determining the nucleation of this micro precipitates. In this article, various mechanisms suggested on the formation of microdefects in the silicon crystal are reviewed to secure the nucleation mechanism of the micro precipitates causing OSF whose pattern is normally ring or annular in CZ silicon crytal. B-defects which are known as vacancy clustering are considered to be the heterogeneous nucleation sites for the micro precipitates causing OSF in the CZ silicon crystals.

• Journal of Platform Technology
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• 제11권5호
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• pp.23-36
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• 2023

이 연구는 내용 분석 기법과 해밍 거리 측정 방법을 적용하여 <흥부전> 이본의 계열과 계통을 미시적, 거시적으로 분석하는 것을 목적으로 한다. <흥부전>의 28개 이본을 내용 단락으로 분절하고 각 단락마다 내용 유형에 따라 내용 유형의 값을 인코딩하여서, 모든 이본의 유형 차이를 비교하였다. 28개 이본의 내용 단락 유형에 따른 차이를 종합하여서 이본의 친소 관계를 분석하기 위하여 거리 행렬로 변환하였다. 거리 행렬은 차원 축소 기법의 일종인 다차원 척도법을 적용하였고 그 결과 거리 행렬을 2차원 공간으로 축소하여 2차원 좌표를 구하였다. 다차원 척도법 분석 결과를 시각화하여서 흥부전 이본은 크게 2가지 계통으로 구분이 된다는 것을 확인하였다. 동일한 거리 행렬을 활용하여 28개 이본의 친소 관계 군집을 분석하기 위한 방법으로는 계층적 군집 분석과 계통분기분석방법을 적용하였다. 그 결과 2개의 이본 계통은 친소 관계의 미시적 분석 결과에 따라 5개의 계열이 존재하는 것을 확인하였다. 이 연구에서는 디지털 인문학 연구 방법을 적용하여 고전 문학 이본의 내용을 인코딩하고 그 데이터를 분석하는 방법을 적용하여 문헌의 내용 유사도에 따른 군집 분석 기법이 유용함을 보여주었다.