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

scholarly journals Pengujian dan Penentuan Spesies Gastropoda sebagai Bioindikator di Kawasan Reboisasi Mangrove Kepulauan Seribu, Indonesia

2020 ◽  
Vol 3 (1) ◽  
pp. 30
Author(s):  
Syahrial Rial ◽  
Muhammad Fauzan Isma ◽  
Ahmad Ryadi ◽  
M. Ilham Fajriansyah
Keyword(s):  
Principal Component ◽  
Mangrove Ecosystem ◽  
Coastal Zones ◽  
Bioindicator Species ◽  
Gastropod Species ◽  
The World ◽  
Small Plot ◽  
Line Transects ◽  
Mangrove Reforestation

The development of coastal zones throughout the world has resulted in changes in the order of the mangrove ecosystem, therefore, planting activities are carried out in various regions. The study of the testing and determination of gastropod species as bioindicators in the mangrove reforestation area was carried out in the Seribu Islands. This research aims to determine how suitable the gastropod species are used as bioindicators in assessing the success of mangrove reforestation, especially in the Seribu Islands. Collection of gastropod species is done by making line transects and plots drawn from the reference point (outermost mangrove stands) and perpendicular to the coastline to the mainland. Line transects are made of plots of size 10 x 10 m and in the size of 10 x 10 m a small plot of 1 x 1 m is made. Furthermore, testing is carried out with several criteria and analyzed using multivariate Principal Component Analysis (PCA) statistics. The results of the study show that the species Littoraria scabra has met all the specified testing criteria. Then L. scabra also has the highest eigenvalue compared to the other species, making it suitable to be used as a bioindicator species in assessing the success of the Seribu Islands mangrove reforestation.

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 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 HUBUNGAN ANTARA KONDISI OSEANOGRAFI DAN DISTRIBUSI SPASIAL IKAN PELAGIS DI WILAYAH PENGELOLAAN PERIKANAN NEGARA REPUBLIK INDONESIA (WPP NRI) 712 LAUT JAWA

2019 ◽  
Vol 25 (1) ◽  
pp. 1
Author(s):  
Asep Ma'mun ◽  
Asep Priatna ◽  
Khairul Amri ◽  
Erfind Nurdin
Keyword(s):  
Principal Component Analysis ◽  
Spatial Distribution ◽  
Environmental Factors ◽  
Direct Interaction ◽  
Principal Component ◽  
Environmental Parameters ◽  
Component Analysis ◽  
Pelagic Fish ◽  
Oceanographic Parameter ◽  
October 17

Kepadatan dan penyebaran sumber daya ikan di perairan banyak dipengaruhi oleh variasi kondisi oseanografinya. Untuk mengkaji interaksi antara kondisi oseanografi dengan sebaran spasial ikan pelagis di Laut Jawa, telah dilakukan penelitian hydro acoustic dengan menggunakan KR. Bawal Putih III pada 17 Oktober-11 November 2017. Akuisisi data akustik menggunakan multi beam Simrad ME (70-120 kHz) dengan posisi transduser dipasang pada lunas kapal. Parameter lingkungan (oksigen, pH, salinitas, klorofil, suhu) diukur menggunakan CTD SBE 19 plus V2 dan parameter oseanogafi fisik (arah dan kecepatan arus) menggunakan ARM current meter, keduanya diturunkan secara vertikal sesuai kedalaman pada 48 stasiun. Analisa korelasi antara parameter oseanografi dengan kelimpahan ikan dan distribusi spasial menggunakan analisis statistik PCA (Principal Component Analysis). Hasil penelitian menunjukkan densitas ikan pelagis dipengaruhi secara berturut-turut oleh salinitas, oksigen, klorofil, pH dan suhu. Urutan ini didasarkan pada jarak dan kedekatan terhadap garis yang dibentuk faktor lingkungan terhadap titik pusat korelasi. Komponen lingkungan yang memiliki interaksi langsung dengan kelimpahan ikan pelagis adalah salinitas dan oksigen. Kedua faktor ini merupakan faktor utama dalam kegiatan osmoregulasi dan pembentukan energi untuk tubuh ikan, sementara keempat faktor lingkungan lainnya (klorofil pH, suhu dan kecepatan arus) berkorelasi secara parsial terhadap keberadaan ikan pelagis.The density and distribution of fish resources in the waters are much influenced by variations in oceanographic conditions. To examine interaction between oceanographic condition with spatial distribution of pelagic fish in Java Sea, hydroacoustic research was done using KR. Bawal Putih III on October 17 to November 11, 2017. Acoustic data acquisition used Simrad ME multi beam (70-120 kHz) with the position of the transducer installed on the keel. Environmental parameters (oxygen, pH, salinity, chlorophyll, temperature) were measured using the SBE 19 plus V2 CTD and physical oceanographic parameter (current direction and speed) using the ARM current meter, both are lowered vertically according to depth at 48 station. Correlation analysis between oceanographic parameter with fish abundance and spatial distribution using PCA (Principal Component Analysis) statistical analysis. Results show that density of pelagic fish was influenced respectively by salinity, oxygen, chlorophyll, pH and temperature. This sequence based on distance and proximity to the line formed by environmental factors towards the center of correlation. The environmental components that have a direct interaction with the abundance of pelagic fish are salinity and oxygen. These two factors are the main factors in osmoregulation and energy formation for fish bodies, while the other four environmental factors (chlorophyll pH, temperature and current velocity) correlate partially to the presence of pelagic fish. 

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 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.

Evaluation functions for integral mapping

2017 ◽  
Vol 921 (3) ◽  
pp. 24-29 ◽  
Author(s):  
S.I. Lesnykh ◽  
A.K. Cherkashin
Keyword(s):  
Principal Component Analysis ◽  
Environmental Factors ◽  
Principal Components ◽  
Principal Component ◽  
Evaluation Function ◽  
Final Value ◽  
Evaluation Functions ◽  
Geographical Environment ◽  
Environmental Background ◽  
Integral Mapping

The proposed procedure of integral mapping is based on calculation of evaluation functions on the integral indicators (II) taking into account the feature of the local geographical environment, when geosystems in the same states in the different environs have various estimates. Calculation of II is realized with application of a Principal Component Analysis for processing of the forest database, allowing to consider in II the weight of each indicator (attribute). The final value of II is equal to a difference of the first (condition of geosystem) and the second (condition of environmental background) principal components. The evaluation functions are calculated on this value for various problems of integral mapping. The environmental factors of variability is excluded from final value of II, therefore there is an opportunity to find the invariant evaluation function and to determine coefficients of this function. Concepts and functions of the theory of reliability for making the evaluation maps of the hazard of functioning and stability of geosystems are used.

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.

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