• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.1
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• pp.100-104
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• 2004

In this paper, we introduce the fuzzy limit degrees in L-fuzzy topologies using complete MV-algebras. We investigate the properties of net-convergences (the degrees of fuzzy convergent, fuzzy cluster, fuzzy adherent points and fuzzy limits).

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.4
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• pp.427-436
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• 1999

This paper describes an ECG signal labeling algorithm based on fuzzy clustering, which is very useful to the automated ECG diagnosis. The existing labeling methods compares the crosscorrelations of each wave form using IF-THEN binary logic, which tends to recognize the same wave forms such as different things when the wave forms have a little morphological variation. To prevent this error, we have proposed as ECG signal labeling algorithm using fuzzy clustering. The center and the membership function of a cluster is calculated by a cluster validity function. The dominant cluster type is determined by RR interval, and the representative beat of each cluster is determined by MF (Membership Function). The problem of IF-THEN binary logic is solved by FCM (Fuzzy C-Means). The MF and the result of FCM can be effectively used in the automated fuzzy inference -ECG diagnosis.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.12
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• pp.1240-1245
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• 2009

The throughput characteristics of the cluster tool with dual blade robot are analyzed. Using equipment's cycle time chart of the equipment, simple analytic form of the throughput is derived. Then, several important throughput characteristics are analyzed by the throughput formula. First, utilization of the process chamber and the robot are maximized by assigning the equipment to the process whose processing time is near the critical process time. Second, rule for selecting optimal number of process chambers is suggested. It is desirable to select a single process chamber plus a single robot structure for relatively short time process and multi process chambers plus a single robot, namely cluster tool for relatively long time process. Third, throughput variation between equipments due to the wafer transfer time variation is analyzed, especially for the process whose processing time is less than critical process time. And the throughput and the wafer transfer time of the equipments in our fabrication line are measured and compared to the analysis.

• Publications of The Korean Astronomical Society
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• v.25 no.3
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• pp.59-64
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• 2010

The core and global properties of the early-type ("red sequence") galaxies in the Virgo and Fornax clusters are examined using high-quality HST/ACS imaging for 143 galaxies. Rather than dividing neatly into disparate populations having distinct formation and/or evolution histories, many of the core and global properties of these galaxies show smooth and systematic variations along the galaxy luminosity function. The few examples of the rare class of compact elliptical galaxies in our sample all show properties that are strongly suggestive of tidal stripping by massive galaxies; if so, then these systems should not be viewed as populating the low-luminosity extension of so-called "normal" elliptical sequences. These results demonstrate that complete and/or unbiased samples are a pre-requisite for identifying the physical mechanisms that gave rise to the early-type galaxies we observe locally, and how these mechanisms varied with mass and environment.

• Asia pacific journal of information systems
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• v.16 no.1
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• pp.127-144
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• 2006

The K-means algorithm is widely used at the initial stage of data analysis in data mining process, partly because of its low time complexity and the simplicity of practical implementation. Cluster validity indices are used along with the algorithm in order to determine the number of clusters as well as the clustering results of datasets. In this paper, we present a performance comparison of sixteen indices, which are selected from forty indices in literature, while considering their applicability to nonhierarchical clustering algorithms. Data sets used in the experiment are generated based on multivariate normal distribution. In particular, four error types including standardization, outlier generation, error perturbation, and noise dimension addition are considered in the comparison. Through the experiment the effects of varying number of points, attributes, and clusters on the performance are analyzed. The result of the simulation experiment shows that Calinski and Harabasz index performs the best through the all datasets and that Davis and Bouldin index becomes a strong competitor as the number of points increases in dataset.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.12
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• pp.985-992
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• 2001

This paper proposes a self-organizing fuzzy modeling(SOFUM)which an create a new hyperplane shaped cluster and adjust parameters of the fuzzy model in repetition. The suggested algorithm SOFUM is composed of four steps: coarse tuning. fine tuning cluster creation and optimization of learning rates. In the coarse tuning fuzzy C-regression model(FCRM) clustering and weighted recursive least squared (WRLS) algorithm are used and in the fine tuning gradient descent algorithm is used to adjust parameters of the fuzzy model precisely. In the cluster creation, a new hyperplane shaped cluster is created by applying multiple regression to input/output data with relatively large fuzzy entropy based on parameter tunings of fuzzy model. And learning rates are optimized by utilizing meiosis-genetic algorithm in the optimization of learning rates To check the effectiveness of the suggested algorithm two examples are examined and the performance of the identified fuzzy model is demonstrated via computer simulation.

• Journal of Information Technology Applications and Management
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• v.12 no.3
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• pp.41-56
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• 2005

Product recommender system is one of the most popular techniques for customer relationship management. In addition, collaborative filtering (CF) has been known to be one of the most successful recommendation techniques in product recommender systems. However, CF has some limitations such as sparsity and scalability problems. This study proposes hybrid cluster analysis and case-based reasoning (CBR) to address these problems. CBR may relieve the sparsity problem because it recommends products using customer profile and transaction data, but it may still give rise to scalability problem. Thus, this study uses cluster analysis to reduce search space prior to CBR for scalability Problem. For cluster analysis, this study employs hybrid genetic and K-Means algorithms to avoid possibility of convergence in local minima of typical cluster analyses. This study also develops a Web-based prototype system to test the superiority of the proposed model.

• Journal of Information Processing Systems
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• v.19 no.5
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• pp.702-712
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• 2023

Load balancing plays a crucial role in ensuring the stable operation of information management systems during periods of high user access requests; therefore, load balancing approaches should be reasonably selected. Moreover, appropriate load balancing techniques could also result in an appropriate allocation of system resources, improved system service, and economic benefits. Nginx is one of the most widely used loadbalancing software packages, and its deployment is representative of load-balancing application research. This study introduces Nginx into an educational administration system, builds a server cluster, and compares and sets the optimal cluster working strategy based on the characteristics of the system, Furthermore, it increases the stability of the system when user access is highly concurrent and uses the Nginx reverse proxy service function to improve the cluster's ability to resist illegal attacks. Finally, through concurrent access verification, the system cluster construction becomes stable and reliable, which significantly improves the performance of the information system service. This research could inform the selection and application of load-balancing software in information system services.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.94.1-94
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• 2002

This paper is concerned with parallel FFT and Quick-Merge Sort. They are implemented on computers interconnected by VMIC 5579 reflective memory and a cluster of workstations (PCs) interconnected via Fast Ethernet. Message passing interface (MPI) parallel library is used for communication in a cluster of workstations. An improved parallel FFT is also presented to decrease an execution time in the case of a small number of hosts. Distributed shared memory (DSM), VMIC 5579 reflective memory (RM), a cluster of workstations (COW) and message passing interface (MPI) parallel library are described.

• 한국전산유체공학회:학술대회논문집
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• 2002.05a
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• pp.1-1
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• 2002

This abstract contains information of PC-Cluster systems that Samsung Advanced Institute of Technology (SAIT) have developed and researched since 1998. This paper introduce not only the reasons that why SAIT has been interested and focused in such system, but also where to SAIT has applied. There are many other applicable areas but this paper emphasis only in the fields of high performance computing and storage system. With the result of SAIT's PC-Cluster research, we hope we can create many new applicable areas with collaborations.