scholarly journals Common Behaviors of Spinor-Type Instantons in 2D Thirring and 4D Gursey Fermionic Models

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Fatma Aydogmus ◽  
Eren Tosyali
Keyword(s):  
Cluster Analysis ◽  
Vector Field ◽  
Hierarchical Cluster ◽  
Classical Field ◽  
Pure Spinor ◽  
Conformal Invariant ◽  
Analysis Method ◽  
Field Equations ◽  
Cluster Analysis Method ◽  
Different Dimensions

We investigate two examples of conformal invariant pure spinor fermionic models, which admit particle-like solutions of the classical field equations. For different dimensions and quantum spinor numbers, the vector field visualizations of the models are constructed to provide a better understanding of the spinor-type instanton dynamics in phase space. The hierarchical cluster analysis method investigations of the models are also presented. Finally, the autocorrelation and power spectrum graphs of models are constructed and frequencies of motions are defined.

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.

Cluster Analysis Using N-gram Statistics for Daihinmin Programs and Performance Evaluations

2016 ◽  
Vol 4 (2) ◽  
pp. 33-57 ◽  
Author(s):  
Seiya Okubo ◽  
Takaaki Ayabe ◽  
Tetsuro Nishino
Keyword(s):  
Cluster Analysis ◽  
Imperfect Information ◽  
Computer Game ◽  
Computer Experiments ◽  
Performance Evaluations ◽  
Analysis Method ◽  
Cluster Analysis Method ◽  
N Gram ◽  
And Performance ◽  
Feature Values

In this paper, the authors elucidate the characteristics of the computer game Daihinmin, a popular Japanese card game that uses imperfect information. They first propose a method to extract feature values using n-gram statistics and a cluster analysis method that employs feature values. By representing the program card hands as several symbols, and the order of hands as simplified symbol strings, they obtain data that is suitable for feature extraction. The authors then evaluate the effectiveness of the proposed method through computer experiments. In these experiments, they apply their method to ten programs that were used in the UEC Computer Daihinmin Convention. In addition, the authors evaluate the robustness of the proposed method and apply it to recent programs. Finally, they show that their proposed method can successfully cluster Daihinmin programs with high probability.

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