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continuous, Mann–Whitney U tests or Spearman’s rho were used. A two-step cluster analysis was performed to determine groups of people who pay for SCG based on reported frequency of sessions and expenditure per session. An alpha level of .05 was employed
addition to the range of cluster analysis techniques available to researchers. The concept of rough sets has been introduced into clustering lately and a very few clustering algorithms have also been developed based on rough set theory [10–12] . A
more centrally. Eigenvector centrality determines a journal's overall centrality in the network (Bonacich 1972 ). Another indicator of the structure of the citation pattern is how journals cluster. Cluster analysis identifies groups within data
, multivariate statistical methods, principal component analysis (PCA) and cluster analysis (CA) [ 20 , 21 ]. By assessing of the influence of different substituents on the course of thermal decomposition of α-amino acids, the results can be useful for
genetic distances based on RAPD and SSR banding pattern had been used for cluster analysis to find the genetic relationship between 24 genotypes of moss H. involuta in the form of dendrogram. The clusters generated by UPGMA method are represented in
–142. 45 Haldar, P., Pavord, I. D., Shaw, D. E., et al.: Cluster analysis and clinical asthma phenotypes. Am. J. Respir. Crit. Care Med., 2008, 178, 218–224. 46
classification analysis) and the major associated words (χ 2 ≥ 12) on the corpus [form (χ 2 /Φ/frequency)]. Note. Theses major associated words were translated from French to English A cluster analysis of this class
Abstract
A set of 35 uranium ore and 10 yellow cake samples, collected worldwide from different mines and production sites, were analyzed for their impurity spectrum by ICP-MS. Pattern recognition techniques such as cluster analysis were applied to the data set in order to characterize samples with relation to their geographical origin. The results obtained show a clear relationship between samples taken from the same geological origin and constitute a satisfactory fingerprint for establishing the origin of the material. In addition to the impurity data, data on the isotopic composition of radiogenic lead is used to resolve ambiguity when impurity cluster analysis fails to deliver unambiguous origin data.
Abstract
This paper describes the implementation of multivariate data analysis: NEURODOC applies the axial k-means method for automatic, non-hierarchical cluster analysis and a Principal Component Analysis (PCA) for representing the clusters on a map. We next introduce Artificial Neural Networks (ANNs) to extend NEURODOC into a neural platform for the cluster analysis and cartography of bibliographic data. The ANNs tested are: the Adaptive Resonance Theory (ART 1), a Multilayer Perceptron (MLP), and an associative network with unsupervised learning (KOHONEN). This platform is intended for quantitative analysis of information.
Abstract
The concentration of 7 elements (Na, Al, Mg, Ti, Ca, V, Mn) was determined by Neutron Activation Analysis in 35 samples of pottery and 14 samples of clay. The samples were collected in Mothia (a Phoenician stronghold in Sicily during 5th–4th century B. C.) and in its neighbourhoods. Cluster analysis of the data showed that most of the samples are homogeneous and confirmed the archaeological evidence that they are mostly local ware. The detailed results of the analyses are reported and the technique used for cluster analysis is described.
