• 전자공학회논문지A
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• 제30A권3호
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• pp.139-145
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• 1993

Partitioning is an important step in the hierarchical design of very large scale integrated circuits. In this research, a new effective partitioning algorithm based on 2-level hierarchy is presented. At the beginning, clusters are formed to reduce the problem size. To overcome the weakness of the iterative improvement techniques that the partitioning result is dependent on the initial partitioning and to consistently produce good results, the cluster-level partitioning is performed several times using several sets of parameters. Then the best result of cluster-partitioning is used as the initial solution for lower level partitioning. For each partitioning, the gradual constraint enforcing partitioning method has been used. The clustering-based partitioning algorithm has been applied to several benchmark examples and produced promising results which show that this algorithm is efficient and effective.

• Bulletin of the Korean Chemical Society
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• 제30권4호
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• pp.794-796
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• 2009

We have studied the structures and stabilities of Au6 to explore the origin of the large discrepancy between relative energies obtained from the density functional theory (DFT) and ab initio correlated levels of theory. The MP2 methods significantly overestimate the stability of the non-planar isomer when the double-$\zeta$ polarization quality of basis sets, such as LANL2DZ+1f and CEP31G+1f, are used. However, we show that such preference for the non-planar structure at the MP2 level mainly originates from the large basis set superposition error.

• International Journal of Control, Automation, and Systems
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• 제6권6호
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• pp.928-938
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• 2008

This study presents an approach for approximation an unknown function from a numerical data set based on the synthesis of a neuro-fuzzy model. An adaptive input data space parting method, which is used for building hyperbox-shaped clusters in the input data space, is proposed. Each data cluster is implemented here as a fuzzy set using a membership function MF with a hyperbox core that is constructed from a min vertex and a max vertex. The focus of interest in proposed approach is to increase degree of fit between characteristics of the given numerical data set and the established fuzzy sets used to approximate it. A new cutting procedure, named NCP, is proposed. The NCP is an adaptive cutting procedure using a pure function $\Psi$ and a penalty function $\tau$ for direction the input data space parting process. New algorithms named CSHL, HLM1 and HLM2 are presented. The first new algorithm, CSHL, built based on the cutting procedure NCP, is used to create hyperbox-shaped data clusters. The second and the third algorithm are used to establish adaptive neuro- fuzzy inference systems. A series of numerical experiments are performed to assess the efficiency of the proposed approach.

• 한국의류학회지
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• 제20권6호
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• pp.1062-1070
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• 1996

Concept of the comfort and fitness has become a major concern in the basic function of the ready-made clothes. Until now, ready-made clothes were not made by on the basis of the bodytype, but by the body size only. This research was performed to classify and characterize the bodytypes of Korean adult males. Sample size was 1290 subjects and their age range was from 19 to 54 years old. 15 variables from the photographic data of 1112 subjects were applied to analyse the bodytype of th\ulcorner lower part of trunk. Data were analyzed by the multivariate method, especially factor and cluster analysis. The groups forming a cluster can be subdivided into 5 sets by crosstabulation extracted by the hierarchical cluster analysis. 5 bodytypes classified by the photographic sources could be combined with the anthropcmetric data and were demonstrated with 5 silhouette. Type 2 and 3 in the lower part of trunk were dominant and were composed of the majority of 56.8% of the subjects. Bodytypes of Korean males were influenced by the degree of posture erectness and of curvature of the front side of the body in waist and abdomen.

• 한국의류학회지
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• 제17권2호
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• pp.281-289
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• 1993

Concept of the comfort and fitness becomes a major concern in the basic function of the ready-made clothes. Accordingly a more sophiscated classification of the human morphological characteristics is strongly required for the effective clothing construction. This research was performed to classify and characterize Korean adult males anthropometrically. Sample size was 1290 subjects and their age range was from 19 to 54 years old. Sampling was carried out by the stratified sampling method. Data were collected by the direct anthropometric measurement. 75 variables in total were applied to classify the bodytypes. Data were analyzed by the multivariate method, especially factor and cluster analysis. The high factor loading items extracted by factor analysis were based to determine the variables of the cluster analysis for the similar bodytypes respectively. In the part of the trunk, 19 variables from the data were applied to classify the bodytypes of trunk by Ward's minimum variance method. The groups forming a cluster were subdivided into 5 sets by cross-tabulation extracted by the hierarchical culster analysis. Type 3 and 4 in trunk were composed of the majority of 55.6% of the subjects. The Korean adult males had relatively well-balanced bodytypes in trunk.

• 천문학회지
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• 제37권5호
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• pp.605-609
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• 2004

We present a set of high-resolution 3D MHD simulations exploring the evolution of light, supersonic jets in cluster environments. We model sets of high- and low-Mach jets entering both uniform surroundings and King-type atmospheres and propagating distances more than 100 times the initial jet radius. Through complimentary analyses of synthetic observations and energy flow, we explore the detailed interactions between these jets and their environments. We find that jet cocoon morphology is strongly influenced by the structure of the ambient medium. Jets moving into uniform atmospheres have more pronounced backflow than their non-uniform counterparts, and this difference is clearly reflected by morphological differences in the synthetic observations. Additionally, synthetic observations illustrate differences in the appearances of terminal hotspots and the x-ray and radio correlations between the high- and low-Mach runs. Exploration of energy flow in these systems illustrates the general conversion of kinetic to thermal and magnetic energy in all of our simulations. Specifically, we examine conversion of energy type and the spatial transport of energy to the ambient medium. Determination of the evolution of the energy distribution in these objects will enhance our understanding of the role of AGN feedback in cluster environments.

• 한국지능시스템학회논문지
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• 제13권4호
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• pp.455-460
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• 2003

본 논문에서는 퍼지 클러스터링 알고리즘에 의해 구해진 퍼지 분할에 대한 최적 클러스터 수를 결정하는 방법을 제안한다. 제안된 척도는 퍼지 클러스터들간의 중첩성과 분리성을 이용한다. 중첩성은 클러스터간 인접도를 이용하여 계산하며, 분리성은 데이터에 대한 상관성 정도로 나타낸다. 따라서 중첩성이 낮고 분리성이 높을수록 좋은 클러스터 결과라고 할 수 있다. 표준 데이터 집합을 대상으로 기존의 척도들과 비교 실험함으로써 제안된 척도의 신뢰성을 검증하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권9호
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• pp.4063-4086
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• 2016

Cloud computing is a robust technology, which facilitate to resolve many parallel distributed computing issues in the modern Big Data environment. Hadoop is an ecosystem, which process large data-sets in distributed computing environment. The HDFS is a filesystem of Hadoop, which process data blocks to the cluster nodes. The data block placement has become a bottleneck to overall performance in a Hadoop cluster. The current placement policy assumes that, all Datanodes have equal computing capacity to process data blocks. This computing capacity includes availability of same storage media and same processing performances of a node. As a result, Hadoop cluster performance gets effected with unbalanced workloads, inefficient storage-tier, network traffic congestion and HDFS integrity issues. This paper proposes a storage-tier-aware Robust Data Placement (RDP) scheme, which systematically resolves unbalanced workloads, reduces network congestion to an optimal state, utilizes storage-tier in a useful manner and minimizes the HDFS integrity issues. The experimental results show that the proposed approach reduced unbalanced workload issue to 72%. Moreover, the presented approach resolve storage-tier compatibility problem to 81% by predicting storage for block jobs and improved overall data block placement by 78% through pre-calculated computing capacity allocations and execution of map files over respective Namenode and Datanodes.

• Journal of Information Processing Systems
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• 제16권2호
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• pp.277-300
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• 2020

This paper presents a method for clustering short text documents, such as news headlines, social media statuses, or instant messages. Due to the characteristics of these documents, which are usually short and sparse, an appropriate technique is required to discover hidden knowledge. The objective of this paper is to identify the combination of document representation, document distance, and document clustering that yields the best clustering quality. Document representations are expanded by external knowledge sources represented by a Distributed Representation. To cluster documents, a K-means partitioning-based clustering technique is applied, where the similarities of documents are measured by word mover's distance. To validate the effectiveness of the proposed method, experiments were conducted to compare the clustering quality against several leading methods. The proposed method produced clusters of documents that resulted in higher precision, recall, F1-score, and adjusted Rand index for both real-world and standard data sets. Furthermore, manual inspection of the clustering results was conducted to observe the efficacy of the proposed method. The topics of each document cluster are undoubtedly reflected by members in the cluster.

• Environmental Engineering Research
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• 제19권3호
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• pp.197-203
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• 2014

This study estimated spatial and seasonal variation of water quality to understand characteristics of Nakdong river basin, Korea. All together 11 parameters (discharge, water temperature, dissolved oxygen, 5-day biochemical oxygen demand, chemical oxygen demand, pH, suspended solids, electrical conductivity, total nitrogen, total phosphorus, and total organic carbon) at 22 different sites for the period of 2003-2011 were analyzed using multivariate statistical techniques (cluster analysis, principal component analysis and factor analysis). Hierarchical cluster analysis grouped whole river basin into three zones, i.e., relatively less polluted (LP), medium polluted (MP) and highly polluted (HP) based on similarity of water quality characteristics. The results of factor analysis/principal component analysis explained up to 83.0%, 81.7% and 82.7% of total variance in water quality data of LP, MP, and HP zones, respectively. The rotated components of PCA obtained from factor analysis indicate that the parameters responsible for water quality variations were mainly related to discharge and total pollution loads (non-point pollution source) in LP, MP and HP areas; organic and nutrient pollution in LP and HP zones; and temperature, DO and TN in LP zone. This study demonstrates the usefulness of multivariate statistical techniques for analysis and interpretation of multi-parameter, multi-location and multi-year data sets.