scholarly journals Use of cluster analysis and analysis of the main components for evaluation of triticale samples

2021 ◽  
Vol 13 (29) ◽  
pp. 55-64
Author(s):  
Evgeniy Dimitrov ◽  
◽  
Krasimira Uzunova ◽  
Zlatina Uhr ◽  
◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Total Variation ◽  
Hierarchical Cluster Analysis ◽  
Coefficient Of Variation ◽  
Genetic Similarity ◽  
Genetic Difference ◽  
Hierarchical Cluster ◽  
The Other ◽  
X Triticosecale ◽  
Main Components

The study was conducted in the period 2015-2017 in the experimental field of IRGR "K. Malkov” Sadovo. The elements of productivity of 24 varieties and lines of triticale (X. Triticosecale Wittmacks) were studied. The degree of variation of each of the indicators of productivity is determined by calculating a coefficient of variation. The results obtained show that the most variable indicator is the weight of grains in the central spike whereas the slightest variation is observed in the parameters of test weight and 1000 grains weight. Hierarchical cluster analysis and analysis of the main components (PC-analysis) are applied to assess the genetic similarity and distance between the different varieties. As a result of the clustering the studied samples were divided into six groups. The varieties Trit 32/6 and KS 60 are characterized with the greatest genetic proximity, followed by line BGR 30071 with the Bulgarian variety Rozhen. The largest genetic difference was reported between line BGR 30816 and variety KT 81. The applied analysis of the main components shows that the components PC 1, PC 2 and PC 3 explain 70.6% of the total variation of all traits by genotypes. The largest numbers of samples (9) belong to component 3, as four of them are located in the negative values of PC 3, and the other five genotypes are in the positive values of PC 3. Component 1 is represented by eight samples, and component 2 includes seven triticale genotypes.

Economic Reforms in Ukraine in Comparative Perspective: Formal and Informal Dimensions

2016 ◽  
Author(s):  
Alexander Libman ◽  
Anastassia Obydenkova
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster Analysis ◽  
Institutional Environment ◽  
Hierarchical Cluster ◽  
Economic Reforms ◽  
The Other ◽  
Business Climate ◽  
Formal Institutions ◽  
Micro Level ◽  
Informal Practices

Alexander Libman and Anastassia Obydenkova set out inductively to identify the countries whose economies are most similar to Ukraine’s using a hierarchical cluster analysis of indicators of the micro-level institutions, such as obtaining permits, registering property, and enforcing contracts. This analysis indicates that in terms of formal institutions, Ukraine performs like a country of southeastern Europe, while in informal terms, it looks more like the other post-Soviet states. While the formal institutional environment in Ukraine has improved, perceptions of the business climate have worsened. This highlights the disconnect between formal institutions and informal practices. They stress that government cannot directly change informal practices—it can only change formal rules or personnel.

Distribution and Forms of Phosphorus in the Buffer Zone Sediments of Erhai Lake

2014 ◽  
Vol 1073-1076 ◽  
pp. 567-574
Author(s):  
Wen Tao Zhang ◽  
Yi Xing ◽  
Shao Yong Lu
Keyword(s):  
Cluster Analysis ◽  
Spatial Distribution ◽  
Hierarchical Cluster Analysis ◽  
Significant Positive Correlation ◽  
Surface Sediments ◽  
Hierarchical Cluster ◽  
Buffer Zone ◽  
The Other ◽  
Erhai Lake ◽  
North West

Spatial distribution of phosphorus in the buffer zone sediments of 16 rivers around Erhai Lake was investigated in July 2013 and different rivers are classified by hierarchical cluster. The average contents of TP, IP, Ca-P and Fe/Al-P were 822.18mg/kg, 602.42mg/kg, 396.79mg/kg and 150.64mg/kg. IP is the dominant mineral form in surface sediments. The order of the average contents of TP and IP conjects to be: West>South>North, West>North>South, respectively. The spatial distribution of TP, Ca-P and Fe/Al-P in the sediments shows a significant positive correlation with that of IP. All 16 investigated rivers are divided into five types according to the hierarchical cluster analysis: Shuangyuanxi River is one type, Zhonghexi River and Mocanxi River are one type, Boluojiang River and Baihexi River are one type, Yangxi River is one type and the other rivers are one type.

Extraordinary circumstances: Covid-19 – Italian Serie A scenario

2021 ◽  
pp. 175433712110192
Author(s):  
Milan Radojicic ◽  
Aleksandar Djokovic ◽  
Nikola Cvetkovic
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster Analysis ◽  
Hierarchical Cluster ◽  
Round Robin ◽  
The Past ◽  
Novel Approach ◽  
Round Robin Tournaments

Unpredictable and uncontrollable situations have happened throughout history. Inevitably, such situations have an impact on various spheres of life. The coronavirus disease 2019 has affected many of them, including sports. The ban on social gatherings has caused the cancellation of many sports competitions. This paper proposes a methodology based on hierarchical cluster analysis (HCA) that can be applied when a need occurs to end an interrupted tournament and the conditions for playing the remaining matches are far from ideal. The proposed methodology is based on how to conclude the season for Serie A, a top-division football league in Italy. The analysis showed that it is reasonable to play 14 instead of the 124 remaining matches of the 2019–2020 season to conclude the championship. The proposed methodology was tested on the past 10 seasons of the Serie A, and its effectiveness was confirmed. This novel approach can be used in any other sport where round-robin tournaments exist.

scholarly journals Detection of drought events in Greece using daily precipitation

2010 ◽  
Vol 41 (2) ◽  
pp. 126-133 ◽  
Author(s):  
N. Kalamaras ◽  
H. Michalopoulou ◽  
H. R. Byun
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster Analysis ◽  
Daily Precipitation ◽  
Hierarchical Cluster ◽  
Seasonal Distribution ◽  
Drought Severity ◽  
Severe Drought ◽  
Analysis Method ◽  
Cluster Analysis Method ◽  
Insight Into

In this study a method proposed by Byun & Wilhite, which estimates drought severity and duration using daily precipitation values, is applied to data from stations at different locations in Greece. Subsequently, a series of indices is calculated to facilitate the detection of drought events at these sites. The results provide insight into the trend of drought severity in the region. In addition, the seasonal distribution of days with moderate and severe drought is examined. Finally, the Hierarchical Cluster Analysis method is used to identify sites with similar drought features.

An investigation on conceptual understanding about cosmology

2019 ◽  
Vol 15 (S367) ◽  
pp. 397-399
Author(s):  
Arturo Colantonio ◽  
Irene Marzoli ◽  
Italo Testa ◽  
Emanuella Puddu
Keyword(s):  
High School ◽  
Cluster Analysis ◽  
High School Students ◽  
Conceptual Understanding ◽  
Hierarchical Cluster Analysis ◽  
Hierarchical Cluster ◽  
Content Area ◽  
School Students ◽  
Convenience Sample ◽  
Teaching Activities

AbstractIn this study, we identify patterns among students beliefs and ideas in cosmology, in order to frame meaningful and more effective teaching activities in this amazing content area. We involve a convenience sample of 432 high school students. We analyze students’ responses to an open-ended questionnaire with a non-hierarchical cluster analysis using the k-means algorithm.

Hierarchical Cluster Analysis Identifies Distinct Physiological States After Acute Brain Injury

2021 ◽  
Author(s):  
Swarna Rajagopalan ◽  
Wesley Baker ◽  
Elizabeth Mahanna-Gabrielli ◽  
Andrew William Kofke ◽  
Ramani Balu
Keyword(s):  
Cluster Analysis ◽  
Brain Injury ◽  
Hierarchical Cluster Analysis ◽  
Hierarchical Cluster ◽  
Acute Brain Injury
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