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methodological tools (partially ordered set (poset) and TDEA). Then in the following section (3), we introduce the poset, TDEA, and cluster analysis models used for evaluating the countries in our dataset and the main results, which are then compared to our

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assessing more than one CSBD symptom or not clearly assessing any symptom were excluded from the new composite index. Based on this composite index, we subsequently identified individuals with CSBD through a cluster analytic approach. Cluster analysis lets

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International competitiveness is influenced by globalization processes in the world economy. This process changes the comparative advantages of each country and thus the shares of individual countries in world trade. BRICS countries have quickly strengthened their influence in international trade, and thus the European Union must face new pressure in competitiveness from their side. The aim of this paper is to define key factors of foreign trade competitiveness by an application of factor analysis and identify countries with similar characteristics of competitiveness factors by an application of cluster analysis. Factor and cluster analysis contain indicators of foreign trade which describe the driving forces of competitiveness, also in terms of long-term potentiality, and those which are direct or indirect outcomes of a competitive society and economy. Based on the results of the factor analysis, it is possible to classify the evaluated territories according to the level of foreign trade advancement by cluster analysis.

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COVID-19 crisis. The study includes 24 EU economies. The methodology is based on multidimensional cluster analysis based on the following six input variables in the year 2021: share of renewables and biofuels in the total energy consumption; 1 weight of

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used to determine the contents of gallic acid and ellagic acid in the antioxidant-active parts of E. angustifolia L. leaves at different dates and from different origins in Xinjiang. In this work, R software hierarchical clustering analysis method was

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of variety means using cluster analysis and dendrograms. Exp. Agricult. 25 :259–269. Christie B.R. Comparison of variety means using cluster analysis and dendrograms

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Journal of Behavioral Addictions
Authors:
Lucien Rochat
,
Francesco Bianchi-Demicheli
,
Elias Aboujaoude
, and
Yasser Khazaal

use, attachment style, sexual desire, and self-esteem – whether subgroups of Tinder users can be identified through cluster analysis. Compared to more traditional linear models such as regression, cluster analysis emphasizes the diversity among

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worthwhile to render. In this context, by employing a clustering analysis with the Gaussian mixture model (GMM), we suggest an empirical framework to classify research collaboration activities with developed indicators that carry on the concept of previous

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Abstract  

Possible applications of cluster analysis of bibliographic references as a scientometric method are studied. It is shown that cluster analysis made by means of bibliographic coupling byKessler and co-citation byMarshakova-Small present comparable results. Science maps on immunological topics are made. Particularly for historico-scientific studies it is useful to make clusters in rectangular coordinates taking into account the value of citing the document and the year of its publication. It is observed that at the junction points of sciences there is an almost twofold deceleration of the processes of application and spreading of knowledge. It is stated that the problem of information explosion does not exist on the level of new ideas, the number of which is less than 0.1% of the total volume of the published information flow 40% of which is formed by information noise.

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We investigated how cluster analysis and diversity-ordering can be used for the classification of geographically and historically distinct plant and insect communities. The study sites include fens and Brachypodium pinnatum dominated grasslands. The stands of the fen vegetation type could be arranged into similar groups by cluster analysis, principal component analysis and diversity ordering techniques. In the case of the B. pinnatum dominated grasslands of diverse development, however, no groups could be differentiated on the basis of either diversity ordering or ordination. Of the various cluster analyses, the result of global optimisation was similar to those of PCA ordination and diversity ordering techniques.

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