scholarly journals RELACIÓN ENTRE LOS VIRUS INFORMATICOS (MALWARE) Y ATAQUES EN PAISES VULNERABLES DE SEGURIDAD EN INFORMATICA UTILIZANDO ANÁLISIS DE COMPONENTES PRINCIPALES (ACP)

LOGOS ◽  
2016 ◽  
Vol 6 (1) ◽  
Author(s):  
Alain Donuhue Dongo Quintana
Keyword(s):  
Principal Component Analysis ◽  
Principal Component ◽  
Free Software ◽  
Computer Viruses ◽  
Data Mining Tool ◽  
Mining Tool ◽  
Using Data ◽  
Relationship Of ◽  
The Relationship ◽  
Sobre Todo

 RESUMEN: Utilizando información de Karpesky Lab el presente artículo se observa que a través de Análisis de Componentes Principales (ACP) existe una la relación de ciertos virus informáticos sobre todo los malware en los países más vulnerables en seguridad de informática, donde se arroja como resultados que el país Argelia es el más atacado por virus troyanos, mientras que los países como Ucrania y Uzbekistán son más propensos a infectarse con virus a través de internet, se nota también que Corea del Sur como China son más atacados por los virus con intentos de infección, finalmente Bielorrusia es el país donde a través de sus PC´s tienen demasiado riesgo a contagiarse de virus. Para este análisis se ha utilizado para el cálculo el software libre R Statistics, así como también el Rattle como una herramienta de Minería de Datos. ABSTRACT Using data from Kaspersky Lab this article notes that through Principal Component Analysis (PCA ) there is the relationship of certain computer viruses especially malware in the most vulnerable countries where it is observed that the country Algeria is the most attacked by Trojan viruses , while countries like Ukraine and Uzbekistan are more likely to become infected with the virus through internet , it also notes that South Korea and China are attacked by the virus infection attempts , Bielorusia is the last country where through their PCs have too much risk of catching viruses. For this analysis was used to calculate the free software R Statistics and Rattle as a data mining tool

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

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.

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.

scholarly journals Determinants Of Chief Executive Officer Compensation: Some Recent Evidence For The Retail Sales And Food Industries

2011 ◽  
Vol 6 (1) ◽  
pp. 17
Author(s):  
W. Ken Farr ◽  
Joseph C. Samprone, Jr.
Keyword(s):  
Principal Component Analysis ◽  
Chief Executive Officers ◽  
Principal Component ◽  
Chief Executive ◽  
Retail Sales ◽  
Food Industries ◽  
Ceo Tenure ◽  
Executive Officers ◽  
Relationship Of ◽  
The Relationship

This study examines factors which influence compensation of chief executive officers (CEOs) in the retail sales and foods industries. Because many of the factors which potentially influence compensation are correlated with one another, multicollinearity becomes a problem in regression analysis. To avoid this problem, principal component analysis is employed. Specifically, the relationship of firm performance, firm size, and CEO tenure, all measured as a composite of factors, are studied to determine their influence on CEO compensation. In addition, specific industries are studied in isolation and then in combination to examine the effect of pooling data across industries.

The use of multivariate analysis in identifying relationships among disorder and mineral element content in apples

1974 ◽  
Vol 25 (5) ◽  
pp. 783 ◽  
Author(s):  
DA Ratkowsky ◽  
D Martin
Keyword(s):  
Principal Component Analysis ◽  
Mineral Content ◽  
Principal Component ◽  
Component Analysis ◽  
Calcium Deficiency ◽  
Fruit Weight ◽  
Wide Range ◽  
Mathematical Techniques ◽  
Using Data ◽  
The Relationship

The use of principal component analysis, followed by rotation of a reduced number of component axes, and its role in the identification and interpretation of relationships between disorder and mineral content in apple research is described. The relationship among bitter pit incidence, calcium deficiency and mean fruit weight per tree is illustrated by using data obtained on Jonathan apples from potted trees. Principal component analysis must be performed on unstructured data, and emphasis is placed upon the removal of treatment and block effects when constructing the correlation matrix upon which the analysis is performed. The mathematical techniques described are applicable to a wide range of agricultural experimentation.

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.

HUBUNGAN KEPADATAN BIVALVIA DENGAN PARAMETER LINGKUNGAN DI PESISIR TANJUNG PURA KABUPATEN BANGKA TENGAH

2020 ◽  
Vol 13 (2) ◽  
pp. 112-121
Author(s):  
Sudiyar . ◽  
Okto Supratman ◽  
Indra Ambalika Syari
Keyword(s):  
Negative Impact ◽  
Principal Component ◽  
Environmental Parameters ◽  
Data Retrieval ◽  
Distribution Patterns ◽  
Random System ◽  
System Method ◽  
Relationship Of ◽  
The Relationship ◽  
Anadara Granosa

The destructive fishing feared will give a negative impact on the survival of this organism. This study aims to analyze the density of bivalves, distribution patterns, and to analyze the relationship of bivalves with environmental parameters in Tanjung Pura village. This research was conducted in March 2019. The systematic random system method was used for collecting data of bivalves. The collecting Data retrieval divided into five research stasions. The results obtained 6 types of bivalves from 3 families and the total is 115 individuals. The highest bivalve density is 4.56 ind / m², and the lowest bivalves are located at station 2,1.56 ind / m²,  The pattern of bivalve distribution in the Coastal of Tanjung Pura Village is grouping. The results of principal component analysis (PCA) showed that Anadara granosa species was positively correlated with TSS r = 0.890, Dosinia contusa, Anomalocardia squamosa, Mererix meretrix, Placamen isabellina, and Tellinella spengleri were positively correlated with currents r = 0.933.

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 Derivation and Performance of Standardized Enhanced Liver Fibrosis (ELF) Test Thresholds for the Detection and Prognosis of Liver Fibrosis

2019 ◽  
Vol 3 (5) ◽  
pp. 815-826 ◽  
Author(s):  
James Day ◽  
Preya Patel ◽  
Julie Parkes ◽  
William Rosenberg
Keyword(s):  
Liver Fibrosis ◽  
Delphi Panel ◽  
Test Results ◽  
Hazard Ratios ◽  
Test Thresholds ◽  
And Performance ◽  
Using Data ◽  
Relationship Of ◽  
The Relationship ◽  
Selection Of

Abstract Introduction Noninvasive tests are increasingly used to assess liver fibrosis and determine prognosis but suggested test thresholds vary. We describe the selection of standardized thresholds for the Enhanced Liver Fibrosis (ELF) test for the detection of liver fibrosis and for prognostication in chronic liver disease. Methods A Delphi method was used to identify thresholds for the ELF test to predict histological liver fibrosis stages, including cirrhosis, using data derived from 921 patients in the EUROGOLF cohort. These thresholds were then used to determine the prognostic performance of ELF in a subset of 457 patients followed for a mean of 5 years. Results The Delphi panel selected sensitivity of 85% for the detection of fibrosis and >95% specificity for cirrhosis. The corresponding thresholds were 7.7, 9.8, and 11.3. Eighty-five percent of patients with mild or worse fibrosis had an ELF score ≥7.7. The sensitivity for cirrhosis of ELF ≥9.8 was 76%. ELF ≥11.3 was 97% specific for cirrhosis. ELF scores show a near-linear relationship with Ishak fibrosis stages. Relative to the <7.7 group, the hazard ratios for a liver-related outcome at 5 years were 21.00 (95% CI, 2.68–164.65) and 71.04 (95% CI, 9.4–536.7) in the 9.8 to <11.3 and ≥11.3 subgroups, respectively. Conclusion The selection of standard thresholds for detection and prognosis of liver fibrosis is described and their performance reported. These thresholds should prove useful in both interpreting and explaining test results and when considering the relationship of ELF score to Ishak stage in the context of monitoring.

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.

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