A New Strategy for Rapid Classification of Honeys by Simple Cluster Analysis Method Based on Combination of Various Physicochemical Parameters

2019 ◽  
Vol 35 (3) ◽  
pp. 390-394
Author(s):  
Xiaohua Zhang ◽  
Suya Zhang ◽  
Xiangdong Qing ◽  
Zuokun Lu
Author(s):  
Wafaa Abdul Samed Ashoor

The development of human societies is measured by the level of success achieved in health because of its direct link to human life. If any society can improve the health of its citizen, it will achieve similar success in other areas of life. If it fails in this aspect, it will fail in other aspects. So this important subject had to be discussed. This study aimed to know the difference between the Iraqi governorates in terms of the level of health indicators provided to the citizen, in addition to determining any of the indicators that contributed significantly to this difference and disparity between the provinces. Data were obtained from the Annual Statistical Abstract of 2017 issued by the Central Statistical Organization. The study included (13) governorates, except for the northern governorates, Mosul and Anbar because data is not available for these governorates and (25) variables representing health indicators. The cluster analysis method was used in the hierarchical and non-hierarchical way. The researcher concluded Baghdad is the best in providing health services to citizens, where the distance between them and other the governorates ranged from (3.875) to (4.841). and Najaf and Qadissiyah are close in providing these services to the citizen, Where the distance between them (0.411). And that the governorates clustered in three clusters, the first included (Kerkok, Diyala, Babylonl, Karbala, Wasit, Saladyn, Najaf, Qadisya, Muthanna, Thi Qar, Mysan) of and the second included Basra only and the third included Baghdad only.


2012 ◽  
Vol 524-527 ◽  
pp. 1300-1305
Author(s):  
Cheng Gang Duan ◽  
Ji Cheng Zhang

Cluster analysis is a multivariate statistical method of the study of sample (or variables) classification, gradually classified by the analysis of the sample or the similarity between the variables. In this paper, taking the case of Daqing low permeability reservoir, according to the movable fluid saturation, the average throat radius and the starting pressure gradient, we used cluster analysis method to conduct the multi-parameter classification of low permeability porous media, and achieved good results. The results showed that: The method in low permeability porous media category is feasible and has strong rationality.


2010 ◽  
Vol 41 (2) ◽  
pp. 126-133 ◽  
Author(s):  
N. Kalamaras ◽  
H. Michalopoulou ◽  
H. R. Byun

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.


2016 ◽  
Vol 4 (2) ◽  
pp. 33-57 ◽  
Author(s):  
Seiya Okubo ◽  
Takaaki Ayabe ◽  
Tetsuro Nishino

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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