Weed community structure in spring-seeded crops in Manitoba

1991 ◽  
Vol 71 (4) ◽  
pp. 1069-1080 ◽  
Author(s):  
A. G. Thomas ◽  
M. R. T. Dale
Keyword(s):  
Cluster Analysis ◽  
Community Structure ◽  
Weed Ecology ◽  
Analysis Techniques ◽  
Temperature And Precipitation ◽  
Weed Communities ◽  
Geographic Regions ◽  
Production Practices ◽  
Using Data ◽  
And Cluster Analysis

The phytosociological structure of weed communities in spring wheat, barley, oats, flax, and canola was investigated using data collected during a 3-yr survey of 1384 fields in Manitoba. Fields were surveyed during July and August, after the application of all herbicides. Association and cluster analysis techniques, using the presence or absence of species in a field, were employed to distinguish co-occurring groups of species. Only a small number of significant positive and negative associations were found between species and only minor clusters with a few species were formed at low similarity levels. These results indicated that the weed community was composed of species responding to conditions more or less independently of each other. A comparison of weed associations among the five crops and four geographic regions in the province indicated that the weed community structure was determined largely by climatic variables. The pattern of weed association in the four geographic regions was correlated with differences in temperature and precipitation during the spring and summer. The lack of floristic differentiation was attributed to the fact that production practices were similar for the five spring-seeded crops. Key words: Weed communities, weed ecology, cluster analysis, association analysis

scholarly journals A Computerized Text and Cluster Analysis Approach to Psychotherapy Talk

2020 ◽  
Vol 9 (1) ◽  
pp. 4-25
Author(s):  
Dennis Tay
Keyword(s):  
Cluster Analysis ◽  
Agglomerative Hierarchical Clustering ◽  
Analytic Thinking ◽  
Future Directions ◽  
Analysis Techniques ◽  
Entry Points ◽  
And Cluster Analysis ◽  
Language Styles ◽  
Computer Text ◽  
Qualitative Exploration

This paper illustrates an analytical approach combining LIWC, a computer text-analytic application, with cluster analysis techniques to explore ‘language styles’ in psychotherapy across sessions in time. It categorizes session transcripts into distinct clusters or styles based on linguistic (di)similarity and relates them to sessional progression, thus providing entry points for further qualitative exploration. In the first step, transcripts of four illustrative therapist-client dyads were scored under ten LIWC variables including ‘analytic thinking’, ‘clout’, ‘authenticity’, ‘emotional tone’, and pronoun types. In the next step, agglomerative hierarchical clustering uncovered distinct session clusters that are differently distributed in each dyad. The relationships between these clusters and the chronological progression of sessions were then further discussed in context as contrastive exemplars. Applications, limitations and future directions are highlighted.

The Structure of Weed Communities in Saskatchewan Fields

Weed Science ◽  
1987 ◽  
Vol 35 (3) ◽  
pp. 348-355 ◽  
Author(s):  
Mark R. T. Dale ◽  
A. Gordon Thomas
Keyword(s):  
Linum Usitatissimum ◽  
Brassica Campestris ◽  
Common Species ◽  
Weed Species ◽  
Oilseed Crops ◽  
Weed Communities ◽  
Using Data ◽  
And Cluster Analysis ◽  
Natural Groups ◽  
Different Soils

This paper describes the communities of weeds in cereal and oilseed crops in Saskatchewan, using data collected in a 4-yr survey that sampled more than 400 fields. The survey data for the 40 most common weeds were analyzed in an attempt to distinguish natural groups of weed species and to compare the weed communities associated with the different crops and with different soils. The crops were barley (Hordeum vulgareL.), flax (Linum usitatissimumL.), oats (Avena sativaL.), rape (Brassica campestrisL.,Brassica napusL.), and wheat (Triticum aestivumL.). Phytosociological association and cluster analysis indicated that the associations of the weed species were more or less independent of the crop, although some differences existed and were determined more by soil or the associated climate. The 40 most common species were divided into three groups related to the soil and climatic subregions of the province.

scholarly journals STUDI KEANEKARAGAMAN DAN STRUKTUR KOMUNITAS PERIFITON DI PERAIRAN SUNGAI COBAN RONDO MALANG

2020 ◽  
Vol 1 (2) ◽  
pp. 93-97
Author(s):  
Zainal Abidin
Keyword(s):  
Water Quality ◽  
Cluster Analysis ◽  
Community Structure ◽  
Environmental Changes ◽  
Aquatic Organisms ◽  
Dominance Index ◽  
Periphyton Community ◽  
Similarity Indices ◽  
And Cluster Analysis ◽  
Index Value

Periphyton is a community of microorganisms that live attached to or adjacent to a substrate sink. For aquatic organisms, periphyton habitats have a relatively fixed. With it is so, the changes of water quality and substrate greatly affects the composition of his life and abundance. Periphyton composition and abundance depends on the tolerance or sensitivity to environmental changes. This study aims to determine each periphyton community in responding to changes in habitat quality by way of adjustment in community structure. The methodology used in this prektikum involves taking data from four stations along the river Coban Rondo, in each station there are 3 replicates. And take measurements of factors such environments as supportive data turbidity, flow rate, pH, and depth. Analyzed using Simpson's Dominance Index to determine the type of periphyton dominance, as well as morisita similarity indices and cluster analysis. The results showed that the diversity in each station belonging to the category of high (H more than 3.32) because the obtained value of the index H' between 3.2 to 3.48. Species that dominate from the four stations is Pinularia with an average Index Value Important (IVI) 31,5.

scholarly journals Differential Perceptions Of Auditing Terms

2011 ◽  
Vol 5 (3) ◽  
pp. 20 ◽  
Author(s):  
Pearl Tan ◽  
Hian Chye Koh ◽  
Aik Meng Low
Keyword(s):  
Cluster Analysis ◽  
Group Differences ◽  
Audit Report ◽  
Analysis Techniques ◽  
Dimensional Scaling ◽  
Expectation Gap ◽  
And Cluster Analysis ◽  
Multi Dimensional Scaling

This paper investigates the differences in the relative perceptions of auditing terms among groups of accountants, bankers and students. Perceptual models were constructed using multi-dimensional scaling and cluster analysis techniques. The models derived therefrom indicate that there are no major inter-group differences in the relative perceptions of auditing terms. This study does not therefore support the hypothesis that the expectation gap between users and preparers of the audit report are caused by semantical problems.

scholarly journals SELECTION OF METRIC AND CATEGORICAL ATTRIBUTES OF RARE ANOMALOUS EVENTS IN A COMPUTER SYSTEM USING DATA MINING METHODS

T-Comm ◽  
2021 ◽  
Vol 15 (6) ◽  
pp. 40-47
Author(s):  
Oleg I. Sheluhin ◽  
◽  
Dmitry I. Rakovsky ◽  
Keyword(s):  
Experimental Data ◽  
Data Mining ◽  
Cluster Analysis ◽  
Current Time ◽  
Trend Component ◽  
Zero Values ◽  
Categorical Attributes ◽  
Using Data ◽  
And Cluster Analysis ◽  
Selection Of

The process of marking multi-attribute experimental data for subsequent use by means of data mining in problems of detection and classification of rare anomalous events of computer systems (CS) is considered. The labeling process is carried out using three methods: manual preprocessing, statistical analysis and cluster analysis. Among the attributes of the metric type, the authors identified two macrogroups: “integral attributes” and “impulse attributes”. It is shown that the combination of statistical and cluster analysis methods increases the accuracy of detecting anomalous events in the CS, and also allows the selection of attributes according to their information significance. The expediency of manual preprocessing of data before clustering is shown by the example of dividing attributes into macrogroups, analyzing the density distribution using violin plot and removing the trend component using the method difference stationary series. With the help of construction of violin diagrams (Violin plot) for the attribute of the “integral” macrogroup, the distribution of states of the CS is shown. It is shown that the removal of the trend component by the DS-series method, normalization and reduction to absolute values allows more accurate marking of anomalous outliers, but this is not always acceptable. The interpretation of the clustering results performed for each normalized attribute shows that the normal values for all attributes are concentrated around zero values. The result of labeling experimental data is attribute-labeled data, where each attribute at the current time is assigned one of two states: abnormal or normal.

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