scholarly journals Classification of University Students by Personality Using Cluster Analysis

Author(s):  
Hisamitsu Tsuda
2006 ◽  
Vol 37 (01) ◽  
Author(s):  
W Hermann ◽  
T Villmann ◽  
HJ Kühn ◽  
P Baum ◽  
G Reichel ◽  
...  

Author(s):  
Hyeuk Kim

Unsupervised learning in machine learning divides data into several groups. The observations in the same group have similar characteristics and the observations in the different groups have the different characteristics. In the paper, we classify data by partitioning around medoids which have some advantages over the k-means clustering. We apply it to baseball players in Korea Baseball League. We also apply the principal component analysis to data and draw the graph using two components for axis. We interpret the meaning of the clustering graphically through the procedure. The combination of the partitioning around medoids and the principal component analysis can be used to any other data and the approach makes us to figure out the characteristics easily.


Crop Science ◽  
1994 ◽  
Vol 34 (4) ◽  
pp. 852-865 ◽  
Author(s):  
Rita Hogan Mumm ◽  
Lawrence J. Hubert ◽  
J. W. Dudley

2011 ◽  
Vol 8 (1) ◽  
pp. 201-210
Author(s):  
R.M. Bogdanov

The problem of determining the repair sections of the main oil pipeline is solved, basing on the classification of images using distance functions and the clustering principle, The criteria characterizing the cluster are determined by certain given values, based on a comparison with which the defect is assigned to a given cluster, procedures for the redistribution of defects in cluster zones are provided, and the cluster zones parameters are being changed. Calculations are demonstrating the range of defect density variation depending on pipeline sections and the universal capabilities of linear objects configuration with arbitrary density, provided by cluster analysis.


Author(s):  
Italo Testa ◽  
Raffaele De Luca Picione ◽  
Umberto Scotti di Uccio

AbstractThe purpose of this study was to analyse Italian high school and university students’ attitudes towards physics using the Semiotic Cultural Psychological Theory (SCPT). In the SCPT framework, attitudes represent how individuals interpret their experience through the mediation of generalized meaning with which they are identified. A view-of-physics questionnaire was used as an instrument to collect data with 1603 high school and university students. Data were analysed through multiple correspondence analysis and cluster analysis. We identified four generalized meanings of physics: (a) interesting and important for society; (b) a quite interesting, but badly taught subject at school and not completely useful for society; (c) difficult to study and irrelevant for society; and (d) a fascinating and protective niche from society. The identified generalized meanings are significantly correlated to the choice to study physics at undergraduate level and to the choice of attending physics-related activities in high school. Implications for research are discussed.


2021 ◽  
pp. 1-15
Author(s):  
Diana Vilela Azzi ◽  
Júlia Melo ◽  
Armindo de Arruda Campos Neto ◽  
Paula Midori Castelo ◽  
Eric Francelino Andrade ◽  
...  

2016 ◽  
Vol 8 (3) ◽  
pp. 32 ◽  
Author(s):  
Olivier K. Bagui ◽  
Kenneth A. Kaduki ◽  
Edouard Berrocal ◽  
Jeremie T. Zoueu

<p class="1Body">Most commercially available ground coffees are processed from Robusta or Arabica coffee beans. In this work, we report on the potential of Structured Laser Illumination Planar Imaging (SLIPI) technique for the classification of five types of Robusta and Arabica commercial ground coffee samples (Familial, Belier, Brazil, Colombia and Malaga). This classification is made, here, from the measurement of the extinction coefficient µ<sub>e</sub> and of the optical depth OD by means of SLIPI. The proposed technique offers the advantage of eliminating the light intensity from photons which have been multiply scattered in the coffee solution, leading to an accurate and reliable measurement of µ<sub>e</sub>. Data analysis uses the chemometric techniques of Principal Component Anaysis (PCA) for variable selection and Hierarchical Cluster Analysis (HCA) for classification. The chemometric model demonstrates the potential of this approach for practical assessment of coffee grades by correctly classifying the coffee samples according to their species.</p>


Pathogens ◽  
2022 ◽  
Vol 11 (1) ◽  
pp. 50
Author(s):  
Magdalena Frąc ◽  
Joanna Kaczmarek ◽  
Małgorzata Jędryczka

In contrast to the long-lasting taxonomic classification of Plenodomus lingam and P. biglobosus as one species, formerly termed Leptosphaeria maculans, both species form separate monophyletic groups, comprising sub-classes, differing considerably with epidemiology towards Brassicaceae plants. Considering the great differences between P. lingam and P. biglobosus, we hypothesized their metabolic capacities vary to a great extent. The experiment was done using the FF microplates (Biolog Inc., Hayward, CA, USA) containing 95 carbon sources and tetrazolium dye. The fungi P. lingam and P. biglobosus subclade ‘brassicae’ (3 isolates per group) were cultured on PDA medium for 6 weeks at 20 °C and then fungal spores were used as inoculum of microplates. The test was carried out in triplicate. We have demonstrated that substrate richness, calculated as the number of utilized substrates (measured at λ490 nm), and the number of substrates allowing effective growth of the isolates (λ750 nm), showed significant differences among tested species. The most efficient isolate of P. lingam utilized 36 carbon sources, whereas P. biglobosus utilized 60 substrates. Among them, 25–29 carbon sources for P. lingam and 34–48 substrates for P. biglobosus were efficiently used, allowing their growth. Cluster analysis based on Senath criteria divided P. biglobosus into two groups and P. lingam isolates formed one group (33% similarity). We deduce the similarities between the tested species help them coexist on the same host plant and the differences greatly contribute to their different lifestyles, with P. biglobosus being less specialized and P. lingam coevolving more strictly with the host plant.


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