PCA Tomography: how to extract information from data cubes

Astronomy has evolved almost exclusively by the use of spectroscopic and imaging techniques, operated separately. With the development of modern technologies, it is possible to obtain data cubes in which one combines both techniques simultaneously, producing images with spectral resolution. To extract information from them can be quite complex, and hence the development of new methods of data analysis is desirable. We present a method of analysis of data cube (data from single field observations, containing two spatial and one spectral dimension) that uses Principal Component Analysis (PCA) to express the data in the form of reduced dimensionality, facilitating efficient information extraction from very large data sets. PCA transforms the system of correlated coordinates into a system of uncorrelated coordinates ordered by principal components of decreasing variance. The new coordinates are referred to as eigenvectors, and the projections of the data on to these coordinates produce images we will call tomograms. The association of the tomograms (images) to eigenvectors (spectra) is important for the interpretation of both. The eigenvectors are mutually orthogonal, and this information is fundamental for their handling and interpretation. When the data cube shows objects that present uncorrelated physical phenomena, the eigenvector`s orthogonality may be instrumental in separating and identifying them. By handling eigenvectors and tomograms, one can enhance features, extract noise, compress data, extract spectra, etc. We applied the method, for illustration purpose only, to the central region of the low ionization nuclear emission region (LINER) galaxy NGC 4736, and demonstrate that it has a type 1 active nucleus, not known before. Furthermore, we show that it is displaced from the centre of its stellar bulge.

3D face computational photography using PCA spaces

In this paper, we present a 3D face photography system based on a facial expression training dataset, composed of both facial range images (3D geometry) and facial texture (2D photography). The proposed system allows one to obtain a 3D geometry representation of a given face provided as a 2D photography, which undergoes a series of transformations through the texture and geometry spaces estimated. In the training phase of the system, the facial landmarks are obtained by an active shape model (ASM) extracted from the 2D gray-level photography. Principal components analysis (PCA) is then used to represent the face dataset, thus defining an orthonormal basis of texture and another of geometry. In the reconstruction phase, an input is given by a face image to which the ASM is matched. The extracted facial landmarks and the face image are fed to the PCA basis transform, and a 3D version of the 2D input image is built. Experimental tests using a new dataset of 70 facial expressions belonging to ten subjects as training set show rapid reconstructed 3D faces which maintain spatial coherence similar to the human perception, thus corroborating the efficiency and the applicability of the proposed system.

Chemotaxonomic relationships in Celastraceae inferred from principal component analysis (PCA) and partial least squares (PLS)

This paper describes a chemotaxonomic analysis of a database of triterpenoid compounds from the Celastraceae family using principal component analysis (PCA). The numbers of occurrences of thirty types of triterpene skeleton in different tribes of the family were used as variables. The study shows that PCA applied to chemical data can contribute to an intrafamilial classification of Celastraceae, once some questionable taxa affinity was observed, from chemotaxonomic inferences about genera and they are in agreement with the phylogeny previously proposed. The inclusion of Hippocrateaceae within Celastraceae is supported by the triterpene chemistry.

O percurso curricular alternativo, um desafio à inovação pedagógica?: uma abordagem etnográfica aos cenários de aprendizagem de uma turma de 5º ano com proposta de PCA

Este estudo pretendeu descrever, compreender e interpretar a cultura emergente de uma turma de 5º Ano de Escolaridade com proposta de Percurso Curricular Alternativo (PCA) em que se procurou esclarecer, à luz do conceito de inovação de que forma o PCA se constitui um desafio à Inovação Pedagógica. Ao debruçar-se sobre os padrões culturais da turma procura conhecer e avaliar o impacto desta proposta alternativa, na vida dos alunos, através do conhecimento das representações de todos os envolvidos no projeto. Além de pretender situar as práticas pedagógicas em termos de inovação ou o contínuo de práticas tradicionais, procura compreender que ambientes são emergentes da utilização das TIC. A presente investigação insere-se numa abordagem metodológica de natureza qualitativa, de cariz etnográfico, justificada pela natureza do estudo. Desenvolve-se através da imersão da investigadora no ambiente natural dos sujeitos, com vista à descrição pormenorizada e facetada da vida do grupo e o acesso a formas de entendimento e compreensão da realidade estudada a partir dos padrões culturais e significados vividos no interior da turma. Foram utilizadas diversas formas de recolha de dados, com destaque para a observação participante e a entrevista, que constituíram os principais recursos da investigação empírica, ainda que complementada com registos de cariz etnográfico como notas de campo, conversas informais e dados de opinião, recolhidos durante a permanência no contexto do estudo. As conclusões desta investigação apontam para o reconhecimento do PCA como uma medida positiva para o aluno na construção do seu projeto de vida pessoal, valorização, integração social e profissional, plenas. A utilização da tecnologia permitiu instituir novos contextos de aprendizagem ao nível micro, da sala de aula e romper com princípios, crenças e atitudes estruturantes da escola tradicional, prefigurando um desafio à Inovação Pedagógica, ou seja, à mudança e transformação da escola.

Reduction capability of soil humic substances from the Rio Negro basin, Brazil, towards Hg(II) studied by a multimethod approach and principal component analysis (PCA)

This paper characterizes humic substances (HS) extracted from soil samples collected in the Rio Negro basin in the state of Amazonas, Brazil, particularly investigating their reduction capabilities towards Hg(II) in order to elucidate potential mercury cycling/volatilization in this environment. For this reason, a multimethod approach was used, consisting of both instrumental methods (elemental analysis, EPR, solid-state NMR, FIA combined with cold-vapor AAS of Hg(0)) and statistical methods such as principal component analysis (PCA) and a central composite factorial planning method. The HS under study were divided into groups, complexing and reducing ones, owing to different distribution of their functionalities. The main functionalities (cor)related with reduction of Hg(II) were phenolic, carboxylic and amide groups, while the groups related with complexation of Hg(II) were ethers, hydroxyls, aldehydes and ketones. The HS extracted from floodable regions of the Rio Negro basin presented a greater capacity to retain (to complex, to adsorb physically and/or chemically) Hg(II), while nonfloodable regions showed a greater capacity to reduce Hg(II), indicating that HS extracted from different types of regions contribute in different ways to the biogeochemical mercury cycle in the basin of the mid-Rio Negro, AM, Brazil. (c) 2007 Published by Elsevier B.V.

Le progrès technique chez Joan Robinson : un essai de systématisation et de formalisation

This paper deals with Joan Robinson's contributions to the issue of technical progress and her attempts of treating this subject in accordance to the Keynesian theory of employment and income distribution, mainly in the long run. This paper aims to review this aspect of her work and to establish a systematisation and a formalisation of her approach. At the same time the paper exposes the problems she faced - and did not always solve. Looking through her main contributions, the paper concludes that she used different criteria for the classification of innovations and that they depended on the specific situations described by the models in which she used the classification.

Considerações sobre analgesia controlada pelo paciente (PCA) em hospital universitário

Pós-graduação em Anestesiologia - FMB

The role of TMPRSS2:ERG in molecular stratification of PCa and its association with tumor aggressiveness: a study in Brazilian patients

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Reconhecimento de faces sob diferentes condições de iluminação utilizando PCA e a transformada census

Os seres humanos identificam naturalmente outros seres humanos utilizando suas características físicas, fisiológicas ou comportamentais. Dentre essas características, destacam-se os traços faciais. O avanço tecnológico na área de Biometria tem promovido o desenvolvimento de inúmeras técnicas para o reconhecimento automático de faces por meio de computadores, entretanto, existem ainda vários fatores que dificultam esta aplicação, como por exemplo, a variação das condições de iluminação. O objetivo deste artigo é analisar os efeitos da aplicação de um filtro de processamento de imagens, denominado Transformada Census, em uma base de dados com imagens da face em diferentes condições de iluminação. Assim, experimentos foram realizados utilizando a técnica PCA com imagens da base de dados AR antes e depois da aplicação da Transformada Census. Os resultados desses experimentos mostraram que a aplicação da Transformada Census melhorou o resultado do reconhecimento das faces, reduzindo a taxa de erro.