Chemical classification of igneous rocks and igneous rock associations by means of discriminant analysis and cluster analysis

1972 ◽  
Vol 17 (3) ◽  
pp. 161-188
Author(s):  
W. H. Bernotat
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Igneous Rock ◽  
Igneous Rocks ◽  
Chemical Classification ◽  
And Cluster Analysis

scholarly journals Classification of Polish voivodeships with regards to the accident rate in the construction industry

2018 ◽  
Vol 174 ◽  
pp. 04007 ◽  
Author(s):  
Tomasz Nowobilski ◽  
Irena Bagińska ◽  
Krzysztof Gawron
Keyword(s):  
Cluster Analysis ◽  
Construction Industry ◽  
Occupational Safety ◽  
Statistical Data ◽  
Occupational Accidents ◽  
Accident Rate ◽  
Central Statistical ◽  
Central Statistical Office ◽  
And Cluster Analysis

The article classifies Polish voivodeships into appropriate groups with a similar level of occupational safety in the construction industry. The basis for the adopted classification was statistical data published by the Central Statistical Office regarding population, employment in the construction industry, the value of construction production and the number of occupational accidents. The conducted research allowed a logical and correct, in terms of content, division of the Polish territory to be made, taking into account the aspect of occupational safety in the construction industry. Statistica software and cluster analysis were used to solve the problem.

Of the American Quantitative Igneous Rock Classification: Part 5

2012 ◽  
Vol 31 (1) ◽  
pp. 1-41 ◽  
Author(s):  
Davis Young
Keyword(s):  
Igneous Rock ◽  
Essential Elements ◽  
Igneous Rocks ◽  
Single Individual ◽  
Chemical Analyses ◽  
Rock Classification ◽  
Natural Classification ◽  
Quantitative Classification ◽  
The Creation

The preference of the authors of the quantitative igneous rock classification for an artificial rather than a natural system, coupled with their invention of a new nomenclature to accompany the classification, indicates that some essential elements of scientific work are not empirically ascertained but are proposed and accepted (or rejected) by the relevant scientific community as a matter of free choice. The use of igneous rocks as exemplars in the education of novice geology students is discussed. It is claimed that the CIPW classification could not have been produced by a single individual geologist. The factors that allowed for the collective success in the creation of the quantitative classification are examined.Upon publication of their monumental quantitative chemico-mineralogical classification (CIPW 1902, 1903), C. W. Cross, J. P. Iddings, L. V. Pirsson, and H. S. Washington immediately received numerous letters of congratulation. Initial published reviews ranged from highly supportive to suspicious. To help buttress their classification, Washington (1903) published a compilation of igneous rock chemical analyses and Iddings (1903) published several diagrams to drive home the point that a natural classification of igneous rocks was not feasible. Led by Washington, Pirsson, and Cross, several geologists began using the CIPW classification in their petrological studies and some contributed new sub-rang names. In the meantime, Iddings worked on the first volume of a projected two-volume work on igneous rocks based on the quantitative CIPW scheme. Unsympathetic to artificial, overly precise classifications, Harker in particular rejected the CIPW system and its norm calculations and European geologists generally were unenthusiastic. Cross (1910b) offered a major rebuttal to the criticisms, particularly those of Harker, in which he challenged the likelihood of producing a valid natural classification of igneous rocks. Iddings (1913) published the second volume on igneous rocks in which he developed an elaborate correlation between the old qualitative system and the new quantitative CIPW scheme. Washington and Pirsson produced many more petrological studies of Mediterranean volcanic rocks, New Hampshire, and Hawaii that incorporated the quantitative system. Washington (1917) produced a vastly expanded compilation of chemical analyses arranged in accord with the CIPW system. Criticisms, however, continued to mount from Fermor, Daly, Shand, and others, while Tyrrell and Johannsen were lukewarm toward the new classification. The criticism that the CIPW system was of little value in fieldwork repeatedly surfaced. Dissatisfaction with the quantitative scheme led to the publication of many new classifications by geologists, such as Hatch, Winchell, Lincoln, Shand, Holmes, Johannsen, and Niggli. With the creation of satisfactory quantitative mineralogical classifications, the increasing ability to determine the proportions of minerals quantitatively, and the death of Iddings and Pirsson, enthusiasm for the CIPW system gradually began to wane. By the 1960s the classification had become a thing of the past. The value of the norm calculation, however, gained recognition and has survived to the present, assisted no doubt by the capability for doing the necessary calculations by computer.

Is there Stylometric Evidence for Q?

2011 ◽  
Vol 57 (4) ◽  
pp. 483-507 ◽  
Author(s):  
David L. Mealand
Keyword(s):  
Cluster Analysis ◽  
Discriminant Analysis ◽  
Correspondence Analysis ◽  
Source Theory ◽  
And Cluster Analysis

Stylometric tests were run to assess whether, in Matthew, Q material differs in style from that of M. Correspondence Analysis was used on larger samples. Then counts of the five most frequent words in smaller samples were tested using three further methods: GLM, Discriminant Analysis and Cluster Analysis. These tests assigned about 80% of the samples to the expected source. This result permits a cautious preference for the Two Source Theory against the theory upheld by Farrer, Goulder and Goodacre.

scholarly journals Achieving the best method to classify Eosinophilic Chronic Rhinosinusitis: a systematic review

2021 ◽  
Vol 59 (4) ◽  
pp. 330-339
Author(s):  
M.D.C. Toro ◽  
M.A. Antonio ◽  
M.G. Alves Dos Reis ◽  
M.S. de Assumpcao ◽  
E. Sakano
Keyword(s):  
Cluster Analysis ◽  
Chronic Rhinosinusitis ◽  
High Power Field ◽  
Eosinophilic Chronic Rhinosinusitis ◽  
Multiple Biopsy ◽  
Quality Of Life Index ◽  
Field Methodology ◽  
Polyp Recurrence ◽  
And Cluster Analysis

Background: Chronic Rhinosinusitis is currently classified into eosinophilic and non-eosinophilic, according to the histologic quantification of the number of eosinophils in nasal mucosa biopsy. There is a lack of unanimous histopathologic criteria and methodology for this classification and no consensus regarding a cut-off point for Eosinophils per High power field. Methodology: A systematic electronic search was performed on BVS, PUBMED, PUBMED PMC, SCOPUS, WEB OF SCIENCE, EMBASE, COCHRANE and PROQUEST databases looking for studies that reported a cut point for classification of Eosinophilic Chronic Rhinosinusitis (eCRS), and data concerning methodology of classification was extracted. Results: We identified 142 studies that reported 29 different cut-off values for classification of eCRS, and different methods of histologic analysis. Out of these studies 13 reported their own methodology to establish the cut-off point, and used different reference standards as polyp recurrence, asthma and allergy, immunocytochemistry, quality of life index, standard deviation of the control population and cluster analysis. Conclusions: Further studies are needed to determine a precise cut-off point, especially international multicentered cluster analysis. Moreover, methodologic standardization of biopsy and analysis is needed to certify comparable results. Multiple biopsy sites, densest cellular infiltration area examination and oral steroids restriction at least four weeks before sampling are advisable.

VII.—A Method of Classifying Igneous Rocks according to their Chemical Composition

1906 ◽  
Vol 3 (3) ◽  
pp. 131-135
Author(s):  
Hugh Warth
Keyword(s):  
Chemical Composition ◽  
Igneous Rocks ◽  
Standard Rock ◽  
Great Work ◽  
Chemical Classification ◽  
Close Proximity

The chemical classification of igneous rocks is rendered difficult by the large number of substances which are present in them. H. S. Washington, who based his system of classification upon the composition of standard rock-forming minerals, found it necessary in his great work to divide his 2,880 rocks into no less than 167 final groups in order to ensure a close proximity between the rocks within each group.

Does Mutual Fund Management in India Correspond to its Investment Objective Classification?

2005 ◽  
Vol 08 (04) ◽  
pp. 659-685 ◽  
Author(s):  
Luis Ferruz Agudo ◽  
Cristina Ortiz Lázaro
Keyword(s):  
Cluster Analysis ◽  
Factor Analysis ◽  
Mutual Fund ◽  
The Other ◽  
Fund Management ◽  
Institutional Control ◽  
Other Hand ◽  
Objective Classification ◽  
And Cluster Analysis

The aim of this article is to investigate the mutual fund market in India and verify whether or not the fund classification obtained from the name given to identify them corresponds to that which would be obtained were prior management to be taken into account. This industry has undergone spectacular growth in recent years, making this study extremely interesting, not least because institutional control could be less in times of expansion. The methodologies employed in the study are factor analysis and cluster analysis. The former determines that risk would clearly identify two groups of funds in the same manner as public classification of the funds. Cluster analysis, on the other hand, identifies funds that are, in fact, very close to one another, when for the bulk of investors they are not.

Classification of Three Green Tea Varieties by Micellar Electrokinetic Electrophoresis-Laser Induced Fluorescence and Pattern Recognition Methods

2012 ◽  
Vol 554-556 ◽  
pp. 1289-1292
Author(s):  
Neng Sheng Ye ◽  
Ya Li Xie ◽  
Chang Liu ◽  
Jian Li
Keyword(s):  
Cluster Analysis ◽  
Pattern Recognition ◽  
Discriminant Analysis ◽  
Laser Induced Fluorescence ◽  
Partial Least Square ◽  
Least Square ◽  
Sodium Borate ◽  
Laser Induced Fluorescence Detection ◽  
Pattern Recognition Methods

A micellar electrokinetic electrophoresis-laser induced fluorescence detection (MEKC-LIF) method was applied for the profiling of native fluorescence in three different kinds of Chinese green teas. The running buffer was 100 mM sodium borate (pH9.8) containing 20 mM SDS, and tea infusion was injected at the pressure of 0.5 psi for 5 seconds. The applied voltage was set at 25 kV, and the excited wavelength was 488 nm, and the detected wavelength was 520 nm. Ten tea samples were collected and analyzed by the developed method. Eighteen common peaks in the MEKC-LIF profiling of green teas were selected and these samples were classified into 3 groups by cluster analysis and partial least square discriminant analysis (PLS-DA). Our primary results indicated that the developed method could be applied for the classification of three different Chinese green teas

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