Detection of glucose and triglycerides using information visualization methods to process impedance spectroscopy data

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

Information Visualization to Enhance Sensitivity and Selectivity in Biosensing

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

Employing 2D Projections for Fast Visual Exploration of Large Fiber Tracking Data

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Human face verification based on multidimensional Polynomial Powers of Sigmoid (PPS)

In this paper, we described how a multidimensional wavelet neural networks based on Polynomial Powers of Sigmoid (PPS) can be constructed, trained and applied in image processing tasks. In this sense, a novel and uniform framework for face verification is presented. The framework is based on a family of PPS wavelets,generated from linear combination of the sigmoid functions, and can be considered appearance based in that features are extracted from the face image. The feature vectors are then subjected to subspace projection of PPS-wavelet. The design of PPS-wavelet neural networks is also discussed, which is seldom reported in the literature. The Stirling Universitys face database were used to generate the results. Our method has achieved 92 % of correct detection and 5 % of false detection rate on the database.

Validade e responsividade de uma escala multidimensional para avaliação de dor pós-operatória em gatos

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

A low-cost 3D reconstruction system using a single-shot projection of a pattern matrix

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

Toward the Optimization of an e-Tongue System Using Information Visualization: A Case Study with Perylene Tetracarboxylic Derivative Films in the Sensing Units

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

Multidimensional polynomial powers of sigmoid (PPS) Wavelet neural networks

Wavelet functions have been used as the activation function in feedforward neural networks. An abundance of R&D has been produced on wavelet neural network area. Some successful algorithms and applications in wavelet neural network have been developed and reported in the literature. However, most of the aforementioned reports impose many restrictions in the classical backpropagation algorithm, such as low dimensionality, tensor product of wavelets, parameters initialization, and, in general, the output is one dimensional, etc. In order to remove some of these restrictions, a family of polynomial wavelets generated from powers of sigmoid functions is presented. We described how a multidimensional wavelet neural networks based on these functions can be constructed, trained and applied in pattern recognition tasks. As an example of application for the method proposed, it is studied the exclusive-or (XOR) problem.

Multidimensional cluster stability analysis from a Brazilian Bradyrhizobium sp RFLP/PCR data set

The taxonomy of the N(2)-fixing bacteria belonging to the genus Bradyrhizobium is still poorly refined, mainly due to conflicting results obtained by the analysis of the phenotypic and genotypic properties. This paper presents an application of a method aiming at the identification of possible new clusters within a Brazilian collection of 119 Bradryrhizobium strains showing phenotypic characteristics of B. japonicum and B. elkanii. The stability was studied as a function of the number of restriction enzymes used in the RFLP-PCR analysis of three ribosomal regions with three restriction enzymes per region. The method proposed here uses Clustering algorithms with distances calculated by average-linkage clustering. Introducing perturbations using sub-sampling techniques makes the stability analysis. The method showed efficacy in the grouping of the species B. japonicum and B. elkanii. Furthermore, two new clusters were clearly defined, indicating possible new species, and sub-clusters within each detected cluster. (C) 2008 Elsevier B.V. All rights reserved.

Refinement and initial validation of a multidimensional composite scale for use in assessing acute postoperative pain in cats

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

Integrable hierarchy for multidimensional Toda equations and topological-anti-topological fusion

The negative symmetry flows are incorporated into the Riemann-Hilbert problem for the homogeneous A(m)-hierarchy and its (gl) over cap (m + 1, C) extension.A loop group automorphism of order two is used to define a sub-hierarchy of (gl) over cap (m + 1, C) hierarchy containing only the odd symmetry flows. The positive and negative flows of the +/-1 grade coincide with equations of the multidimensional Toda model and of topological-anti-topological fusion. (C) 2002 Elsevier B.V. B.V. All rights reserved.

Riccati-type equations, generalised WZNW equations, and multidimensional Toda systems

We associate to an arbitrary Z-gradation of the Lie algebra of a Lie group a system of Riccati-type first order differential equations. The particular cases under consideration are the ordinary Riccati and the matrix Riccati equations. The multidimensional extension of these equations is given. The generalisation of the associated Redheffer-Reid differential systems appears in a natural way. The connection between the Toda systems and the Riccati-type equations in lower and higher dimensions is established. Within this context the integrability problem for those equations is studied. As an illustration, some examples of the integrable multidimensional Riccati-type equations related to the maximally nonabelian Toda systems are given.

New class of spin projection operators for 3D models

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Confiabilidade e pontuação mínima relacionada à intervenção analgésica de uma escala multidimensional para avaliação de dor pós-operatória em gatos

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