Hierarchical Cluster Analysis of Matrix Effects on 110 Pesticide Residues in 28 Tea Matrixes

2013 ◽  
Vol 96 (6) ◽  
pp. 1453-1465 ◽  
Author(s):  
Yan Li ◽  
Guo-Fang Pang ◽  
Chun-Lin Fan ◽  
Xi Chen
Keyword(s):  
Cluster Analysis ◽  
Multivariate Analysis ◽  
Hierarchical Cluster Analysis ◽  
Pesticide Residues ◽  
Matrix Effects ◽  
Hierarchical Cluster ◽  
Physicochemical Characteristics ◽  
Analysis Tool ◽  
Signal Suppression ◽  
The Matrix

Abstract Matrix effects on 110 pesticides in 28 tea matrixes of different varieties and origins by LC/MS/MS were studied, and most of the pesticides exhibited soft and medium signal suppression. To better understand the influence of the tea varieties and the physicochemical characteristics of pesticides on the matrix effects, the multivariate analysis tool called hierarchical cluster analysis was applied. Tea matrixes were grouped into three clusters: unfermented, fermented, and post-fermented teas. Any type of tea can be chosen from each cluster as a corresponding representative matrix within that cluster to make matrix-matched solutions, which could simplify analysis while guaranteeing its accuracy. Matrix effects on most pesticides were similar despite the physicochemical diversities of the pesticides.

Pre-processing of Fourier transform infrared spectra by means of multivariate analysis implemented in the R environment

The Analyst ◽  
2015 ◽  
Vol 140 (8) ◽  
pp. 2810-2814 ◽  
Author(s):  
Krzysztof Banas ◽  
Agnieszka Banas ◽  
Mariusz Gajda ◽  
Bohdan Pawlicki ◽  
Wojciech M. Kwiatek ◽  
...  
Keyword(s):  
Cluster Analysis ◽  
Multivariate Analysis ◽  
Fourier Transform ◽  
Infrared Spectra ◽  
Hierarchical Cluster Analysis ◽  
Traditional Approach ◽  
Hierarchical Cluster ◽  
Fourier Transform Infrared ◽  
Average Intensity ◽  
Fourier Transform Infrared Spectra

Segmentation of the hyperspectral dataset by using hierarchical cluster analysis shows its advantage over the traditional approach based on the average intensity.

Extended Hierarchical Cluster Analysis for the Decomposition of Complex Design Problems

2003 ◽  
Author(s):  
Li Chen ◽  
Zhengdong Ding ◽  
Simon Li
Keyword(s):  
Cluster Analysis ◽  
Hierarchical Cluster Analysis ◽  
Decomposition Method ◽  
Block Size ◽  
Hierarchical Cluster ◽  
Function Parameter ◽  
Design Problems ◽  
Post Process ◽  
Complex Design ◽  
The Matrix

This paper presents a new decomposition method for partitioning complex design problems based on an extended Hierarchical Cluster Analysis (HCA). After a complex design problem is represented using a function-parameter incidence matrix, this new decomposition method allows transforming the originally unorganized matrix into a block-angular form matrix. By means of the resulting matrix, a coordination part and design blocks can be further identified and obtained. In particular, the extended HCA plays an important role in this method, contributive to aligning all non-zero elements, also known as 1s elements, of the matrix along its main diagonal as compactly as possible. As such, a post process, called Partition Point Analysis (PPA), can be further applied to the matrix to finally form the coordination part and the related design blocks, subject to such decomposition criteria as block size and coordination size limits. A powertrain design example is employed for illustration of the decomposition method newly developed.

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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