FLOW PROPERTIES and TUBE FRICTION FACTOR of MILK CREAM: INFLUENCE of TEMPERATURE and FAT CONTENT

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

Pattern recognition theory in nonlinear signal processing

A body of research has developed within the context of nonlinear signal and image processing that deals with the automatic, statistical design of digital window-based filters. Based on pairs of ideal and observed signals, a filter is designed in an effort to minimize the error between the ideal and filtered signals. The goodness of an optimal filter depends on the relation between the ideal and observed signals, but the goodness of a designed filter also depends on the amount of sample data from which it is designed. In order to lessen the design cost, a filter is often chosen from a given class of filters, thereby constraining the optimization and increasing the error of the optimal filter. To a great extent, the problem of filter design concerns striking the correct balance between the degree of constraint and the design cost. From a different perspective and in a different context, the problem of constraint versus sample size has been a major focus of study within the theory of pattern recognition. This paper discusses the design problem for nonlinear signal processing, shows how the issue naturally transitions into pattern recognition, and then provides a review of salient related pattern-recognition theory. In particular, it discusses classification rules, constrained classification, the Vapnik-Chervonenkis theory, and implications of that theory for morphological classifiers and neural networks. The paper closes by discussing some design approaches developed for nonlinear signal processing, and how the nature of these naturally lead to a decomposition of the error of a designed filter into a sum of the following components: the Bayes error of the unconstrained optimal filter, the cost of constraint, the cost of reducing complexity by compressing the original signal distribution, the design cost, and the contribution of prior knowledge to a decrease in the error. The main purpose of the paper is to present fundamental principles of pattern recognition theory within the framework of active research in nonlinear signal processing.

An image processing method for morphology characterization and pitting corrosion evaluation

A digital image processing and analysis method has been developed to classify shape and evaluate size and morphology parameters of corrosion pits. This method seems to be effective to analyze surfaces with low or high degree of pitting formation. Theoretical geometry data have been compared against experimental data obtained for titanium and aluminum alloys subjected to different corrosion tests. (C) 2002 Elsevier B.V. B.V. All rights reserved.

Density and spatial distribution of Atta sexdens rubropilosa and Atta laevigata colonies (Hym., Formicidae) in Eucalyptus spp. forests

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Passive and active dispersers respond similarly to environmental and spatial processes: an example from metacommunity dynamics of tree hole invertebrates

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Recent advances in brain physiology and cognitive processing

The discovery of participation of astrocytes as active elements in glutamatergic tripartite synapses (composed by functional units of two neurons and one astrocyte) has led to the construction of models of cognitive functioning in the human brain, focusing on associative learning, sensory integration, conscious processing and memory formation/retrieval. We have modelled human cognitive functions by means of an ensemble of functional units (tripartite synapses) connected by gap junctions that link distributed astrocytes, allowing the formation of intra- and intercellular calcium waves that putatively mediate large-scale cognitive information processing. The model contains a diagram of molecular mechanisms present in tripartite synapses and contributes to explain the physiological bases of cognitive functions. It can be potentially expanded to explain emotional functions and psychiatric phenomena. © MSM 2011.

Broad-scale spatial patterns of canopy cover and pond morphology affect the structure of a Neotropical amphibian metacommunity

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

Neonatal anoxia in rats: hippocampal cellular and subcellular changes related to cell death and spatial memory

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

A comparative analysis reveals weak relationships between ecological factors and beta diversity of stream insect metacommunities at two spatial levels

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Field-scale spatial correlation between contents of iron oxides and CO2 emission in an Oxisol cultivated with sugarcane

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