3 resultados para Octave

em Scielo Saúde Pública - SP


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The specimen distribution pattern of a species can be used to characterise a population of interest and also provides area-specific guidance for pest management and control. In the municipality of Dracena, in the state of São Paulo, we analysed 5,889 Lutzomyia longipalpis specimens collected from the peridomiciles of 14 houses in a sector where American visceral leishmaniasis (AVL) is transmitted to humans and dogs. The goal was to analyse the dispersion and a theoretical fitting of the species occurrence probability. From January-December 2005, samples were collected once per week using CDC light traps that operated for 12-h periods. Each collection was considered a sub-sample and was evaluated monthly. The standardised Morisita index was used as a measure of dispersion. Adherence tests were performed for the log-series distribution. The number of traps was used to adjust the octave plots. The quantity of Lu. longipalpis in the sector was highly aggregated for each month of the year, adhering to a log-series distribution for 11 of the 12 months analysed. A sex-stratified analysis demonstrated a pattern of aggregated dispersion adjusted for each month of the year. The classes and frequencies of the traps in octaves can be employed as indicators for entomological surveillance and AVL control.

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This manuscript aims to show the basic concepts and practical application of Principal Component Analysis (PCA) as a tutorial, using Matlab or Octave computing environment for beginners, undergraduate and graduate students. As a practical example it is shown the exploratory analysis of edible vegetable oils by mid infrared spectroscopy.

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The objective of this manuscript is to describe a practical experiment that can be employed for teaching concepts related to design of experiments using Matlab or Octave computing environment to beginners, undergraduate and graduate students. The classical experiment for determination of Fe (II) using o-phenanthroline was selected because it is easy to understand, and all the required materials are readily available in most analytical laboratories. The approach used in this tutorial is divided in two steps: first, the students are introduced to the concept of multivariate effects, how to calculate and interpret them, and the construction and evaluation of a linear model to describe the experimental domain by using a 2³ factorial design. Second, an extension of the factorial design by adding axial points is described, thereby, providing a central composite design. The quadratic model is then introduced and used to build the response surface.