Studies on lichen-dominated systems. X. The sedge meadows of the coastal raised beaches

1974 ◽  
Vol 52 (8) ◽  
pp. 1947-1972
Author(s):  
K. A. Kershaw
Keyword(s):  
Principal Component Analysis ◽  
Water Table ◽  
Principal Component ◽  
Component Analysis ◽  
Beach Ridges ◽  
Plant Associations ◽  
Sedge Meadows ◽  
Relationship Of ◽  
Raised Beaches ◽  
The Relationship

The relationship of the sedge meadows lying between raised-beach ridges at the Pen Island site in NW Ontario is described using principal-component analysis. Three major trends are detected following moss hummock formation, depth of water table, and pH. The data also show a progressive sequence from the young meadows with few hummocks and high pH to the older meadows where marked hummock formation has occurred and where the overall pH is lower. Six noda have subsequently been extracted as the central plant associations characteristic of the area.

Studies on lichen-dominated systems. V. A primary survey of a raised-beach system in northwestern Ontario

1973 ◽  
Vol 51 (7) ◽  
pp. 1285-1307 ◽  
Author(s):  
K. A. Kershaw ◽  
W. R. Rouse
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Component Analysis ◽  
Primary Survey ◽  
Northwestern Ontario ◽  
Plant Associations ◽  
Definite Trend ◽  
Major Species ◽  
Raised Beaches

A series of raised-beach systems in northwestern Ontario were examined using principal-component analysis and a number of broad plant associations were delimited. A definite trend exists from the younger raised beaches adjacent to the coastline, to the older ridges examined some 8 km inland. This trend has been characterized by the major species involved and by the plant associations relating to specific ridge groups. The paper also lays the foundation for a series of detailed studies which are currently in progress.

The Symmetrical Variation of 2DPCA for Face Recognition

2011 ◽  
Vol 255-260 ◽  
pp. 2004-2008
Author(s):  
Zeng Yue ◽  
Da Zheng Feng ◽  
Xiong Li
Keyword(s):  
Principal Component Analysis ◽  
Face Recognition ◽  
Recognition Accuracy ◽  
Principal Component ◽  
Component Analysis ◽  
Two Dimensional ◽  
Recognition Time ◽  
Relationship Of ◽  
The Relationship

This paper first discusses the relationship of Principal Component Analysis (PCA) and two-dimensional PCA (2DPCA). For 2DPCA eliminating the some covariance information which can be useful for recognition, The symmetrical Variation of 2DPCA for Face recognition (V2DPCA) is proposed. These experiments on both of ORL face bases shows improvement in recognition accuracy, fewer coefficients and recognition time over 2DPCA, and this algorithm is also superior to the traditional eigenfaces, ICA and Kernel eigenfaces in terms of the recognition accuracy.

scholarly journals Quantify Coal Macrolithotypes of a Whole Coal Seam: A Method Combing Multiple Geophysical Logging and Principal Component Analysis

Energies ◽  
2021 ◽  
Vol 14 (1) ◽  
pp. 213
Author(s):  
Chao Cui ◽  
Suoliang Chang ◽  
Yanbin Yao ◽  
Lutong Cao
Keyword(s):  
Principal Component Analysis ◽  
Coal Seam ◽  
Coalbed Methane ◽  
Principal Component ◽  
Component Analysis ◽  
Gas Production ◽  
Index Model ◽  
Geophysical Logging ◽  
The Relationship ◽  
Observation Results

Coal macrolithotypes control the reservoir heterogeneity, which plays a significant role in the exploration and development of coalbed methane. Traditional methods for coal macrolithotype evaluation often rely on core observation, but these techniques are non-economical and insufficient. The geophysical logging data are easily available for coalbed methane exploration; thus, it is necessary to find a relationship between core observation results and wireline logging data, and then to provide a new method to quantify coal macrolithotypes of a whole coal seam. In this study, we propose a L-Index model by combing the multiple geophysical logging data with principal component analysis, and we use the L-Index model to quantitatively evaluate the vertical and regional distributions of the macrolithotypes of No. 3 coal seam in Zhengzhuang field, southern Qinshui basin. Moreover, we also proposed a S-Index model to quantitatively evaluate the general brightness of a whole coal seam: the increase of the S-Index from 1 to 3.7, indicates decreasing brightness, i.e., from bright coal to dull coal. Finally, we discussed the relationship between S-Index and the hydro-fracturing effect. It was found that the coal seam with low S-Index values can easily form long extending fractures during hydraulic fracturing. Therefore, the lower S-Index values indicate much more favorable gas production potential in the Zhengzhuang field. This study provides a new methodology to evaluate coal macrolithotypes by using geophysical logging data.

scholarly journals Air Pollution and Human Development in Europe: A New Index Using Principal Component Analysis

2018 ◽  
Vol 10 (2) ◽  
pp. 312 ◽  
Author(s):  
Ana-Maria Săndică ◽  
Monica Dudian ◽  
Aurelia Ştefănescu
Keyword(s):  
Principal Component Analysis ◽  
Human Development ◽  
Quantitative Measure ◽  
Principal Component ◽  
Component Analysis ◽  
Life Expectancy At Birth ◽  
Real Gdp ◽  
Development Indicator ◽  
The Relationship ◽  
Pm2.5 Concentration

EU countries to measure human development incorporating the ambient PM2.5 concentration effect. Using a principal component analysis, we extract the information for 2010 and 2015 using the Real GDP/capita, the life expectancy at birth, tertiary educational attainment, ambient PM2.5 concentration, and the death rate due to exposure to ambient PM2.5 concentration for 29 European countries. This paper has two main results: it gives an overview about the relationship between human development and ambient PM2.5 concentration, and second, it provides a new quantitative measure, PHDI, which reshapes the concept of human development and the exposure to ambient PM2.5 concentration. Using rating classes, we defined thresholds for both HDI and PHDI values to group the countries in four categories. When comparing the migration matrix from 2010 to 2015 for HDI values, some countries improved the development indicator (Romania, Poland, Malta, Estonia, Cyprus), while no downgrades were observed. When comparing the transition matrix using the newly developed indicator, PHDI, the upgrades observed were for Denmark and Estonia, while some countries like Spain and Italy moved to a lower rating class due to ambient PM2.5 concentration.

scholarly journals Correlation of environmental factors and spatial distribution of moluscs communities in mangrove reboisation areas of Seribu Islands, Indonesia

2019 ◽  
Vol 2 (2) ◽  
Author(s):  
Syahrial Syahrial ◽  
Eryc Pranata ◽  
Hendri Susilo
Keyword(s):  
Principal Component Analysis ◽  
Spatial Distribution ◽  
Environmental Factors ◽  
Principal Component ◽  
Quality Standard ◽  
Small Plot ◽  
Line Transects ◽  
Relationship Of ◽  
The Relationship ◽  
Mangrove Reforestation

Mangrove reforestation is often carried out in various regions or regions, but information about the relationship of environmental factors and the distribution of fauna associations is still very minimal. The Principal Component Analysis (PCA) study on the correlation of environmental factors and the spatial distribution of the molusks community in the Seribu Islands mangrove reforestation area was conducted in March 2014 with the aim of analyzing environmental factors for the diversity and presence of the molusks. Environmental factors are measured insecurely, while the moluccan community is collected by making line transects and plots measuring 10 x 10 m2 and in the size of 10 x 10 m2, a small plot of 1 x 1 m2 is made. The results of the study show that environmental factors are not so different between stations and do not exceed the quality standard for the lives of 4 species of mollusks, where the parameters of aquatic pH are the environmental factors that most influence their distribution.Keywords: environmental factors, distribution, mollusks community, mangrove reforestation, Seribu Islands

Volatile profiling of fruits of 17 mango cultivars by HS-SPME-GC/MS combined with principal component analysis

2021 ◽  
Author(s):  
Kosuke Shimizu ◽  
Tetsuya Matsukawa ◽  
Risa Kanematsu ◽  
Kimihisa Itoh ◽  
Shinya Kanzaki ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
Solid Phase Microextraction ◽  
Solid Phase ◽  
Principal Component ◽  
Component Analysis ◽  
Volatile Components ◽  
Seed Parent ◽  
Aromatic Components ◽  
The Relationship ◽  
Aroma Components

Abstract Headspace solid-phase microextraction combined with GC/MS (HS-SPME-GC/MS) is one of the strongest tools for comprehensive analysis of volatile compounds and has been used to analyze aromatic components of mango and investigate its varietal characteristics. In this study, profiling of aroma compounds in 17 mango cultivars, grown in the same green house to exclude the effect of environmental factors, was conducted and the patterns were subjected to principal component analysis (PCA) to identify the relationship between the aroma components and cultivars. Fifty-nine different volatile constituents were detected from the blends of these 17 mango cultivars. The cultivars were divided into four clusters using PCA based on the volatile components determined in the study. Aiko was found to mainly contain δ-3-carene and showed a composition more similar to its pollen parent, Irwin, than to its seed parent, Chiin Hwang No. 1.

scholarly journals Why not Seek Therapy? The Role of Stigma and Psychological Symptoms in College Students

2017 ◽  
Vol 27 (67) ◽  
pp. 76-83 ◽  
Author(s):  
Makilim Nunes Baptista ◽  
Cristian Zanon
Keyword(s):  
Principal Component Analysis ◽  
Psychological Distress ◽  
Depressive Symptoms ◽  
Psychological Symptoms ◽  
Principal Component ◽  
Public Stigma ◽  
Symptoms Of Depression ◽  
Relationship Of ◽  
The Relationship

Abstract: The decision to seek therapy can reduce psychological distress and factors like public stigma, self stigma, fear of self exposure to therapist, among others, may constitute barriers in this process. This study investigated: how is the group of variables described in the literature as predictors of seeking therapy, and the relationship of variables associated with stigma and depressive symptoms, anxiogenic symptoms and stress with this search. For this purpose, 272 students responded scales that assessed these variables. The principal component analysis indicated four clusters of variables (symptoms of depression, anxiety and stress; feelings of shame, inadequacy and inhibition; perception of benefits to seek therapy; self stigma and stigma by the others). These components are hierarchically inserted into the multiple regression, indicating that the symptoms have little importance compared to the attitude of seeking therapy and stigmas.

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