Comparative phylogeography of Trypanosoma cruzi TCIIc: New hosts, association with terrestrial ecotopes, and spatial clustering

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

The dielectric suppress and the control of semiconductor non-Ohmic feature of CaCu3Ti4O12 by means of tin doping

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Preconcentration of heavy metals ions from aqueous solutions by means of cellulose phosphate: An application in water analysis

Cellulose phosphate (CELLPHOS) was studied as a collector for analytical preconcentration of traces of Cd(II), Cr(III), Cu(II) and Ni(II) from aqueous sample solution. It has been proved that using chromatographic columns packed with CELLPHOS for preconcentration and 1.0 mol 1 -1 HCl for elution the adsorbed analytes are quantitatively enriched. An enrichment factor of 20 (100 ml sample, 5 ml concentrate) was achieved by this separation procedure, which was applied to a series of water analyses (river, sea, bog water).

Interaction of mercury(II) with humic substances from the Rio Negro (Amazonas State, Brazil) by means of an ion exchange procedure

The aquatic humic substances (HS) investigated in this study with respect to their binding capability towards mercury(II) were isolated from the river Rio Negro, Amazonas State - Brazil, by means of the adsorbent XAD 8. Labile/inert fractions of inorganic Hg(II) complexes formed with these HS were characterized using an ion-exchange batch and column technique, respectively, based on Chelite S. This collector exhibits high Hg(II) distribution coefficients, Kd, up to the order of 104 decreasing, however, in the case of small Hg(II)/HS ratios (< 0.1 μg Hg(II) / mg HS). The influence of different complexation parameters (ratio of Hg(II)/HS, pH, contact time, complexing time) relevant for Hg(II) binding in aquatic environments was assessed. The Hg(II) lability in dissolved HS is mainly influenced by the mass ratio of Hg(II)/HS and the ageing of Hg(II)-HS species formed. This is particularly obvious in the case of low Hg(II) loading of HS where slow transformation processes of freshly formed Hg(II)-HS species significantly decrease their lability, leading to incomplete recoveries (< 20%) of the total Hg(II) bound to HS.

Simulation of active control using fuzzy logic applied to a pulse combustor

This work analyzes an active fuzzy logic control system in a Rijke type pulse combustor. During the system development, a study of the existing types of control for pulse combustion was carried out and a simulation model was implemented to be used with the package Matlab and Simulink. Blocks which were not available in the simulator library were developed. A fuzzy controller was developed and its membership functions and inference rules were established. The obtained simulation showed that fuzzy logic is viable in the control of combustion instabilities. The obtained results indicated that the control system responded to pulses in an efficient and desirable way. It was verified that the system needed approximately 0.2 s to increase the tube internal pressure from 30 to 90 mbar, with an assumed total delay of 2 ms. The effects of delay variation were studied. Convergence was always obtained and general performance was not affected by the delay. The controller sends a pressure signal in phase with the Rijke tube internal pressure signal, through the speakers, when an increase the oscillations pressure amplitude is desired. On the other hand, when a decrease of the tube internal pressure amplitude is desired, the controller sends a signal 180° out of phase.

Transient stability analysis of electrical power systems using a neural network based on fuzzy ARTMAP

This work presents a methodology to analyze transient stability for electric energy systems using artificial neural networks based on fuzzy ARTMAP architecture. This architecture seeks exploring similarity with computational concepts on fuzzy set theory and ART (Adaptive Resonance Theory) neural network. The ART architectures show plasticity and stability characteristics, which are essential qualities to provide the training and to execute the analysis. Therefore, it is used a very fast training, when compared to the conventional backpropagation algorithm formulation. Consequently, the analysis becomes more competitive, compared to the principal methods found in the specialized literature. Results considering a system composed of 45 buses, 72 transmission lines and 10 synchronous machines are presented. © 2003 IEEE.

A Gm-C bump equalizer for low-voltage low-power applications

A low-voltage low-power 2nd-order CMOS pseudo-differential bump-equalizer is presented. Its topology comprises a bandpass section with adjustable center frequency and quality factor, together with a programmable current amplifier. The basic building blocks are triode-operating transconductors, tunable by means of either a DC voltage or a digitally controlled current divider. The bump-equalizer as part of a battery-operated hearing aid device is designed for a 1.4V-supply and a 0.35μm CMOS fabrication process. The circuit performance is supported by a set of simulation results, which indicates a center frequency from 600Hz to 2.4kHz, 1≤Q≤5, and an adjustable gain within ±6dB at center frequency. The filter dynamic range lies around 40dB. Quiescent consumption is kept below 12μW for any configuration of the filter.

A comparative study between two relaxed LMI-based fuzzy control designs

A comparative study, with theoretical analysis and digital simulations, of two conditions based on LMI for the quadratic stability of nonlinear continuous-time dynamic systems, described by Takagi-Sugeno fuzzy models, are presented. This paper shows that the methods proposed by Teixeira et. al. in 2003 provide better or at least the same results of a recent method presented in the literature. © 2005 IEEE.

Fuzzy logic to predict thermal damages of ground parts

One of the critical problems in implementing an intelligent grinding process is the automatic detection of workpiece surface burn. This work uses fuzzy logic as a tool to classify and predict burn levels in the grinding process. Based on acoustic emission signals, cutting power, and the mean-value deviance (MVD), linguistic rules were established for the various burn situations (slight, intermediate, severe) by applying fuzzy logic using the Matlab Toolbox. Three practical fuzzy system models were developed. The first model with two inputs resulted only in a simple analysis process. The second and third models have an additional MVD statistic input, associating information and precision. These two models differ from each other in terms of the rule base developed. The three developed models presented valid responses, proving effective, accurate, reliable and easy to use for the determination of ground workpiece burn. In this analysis, fuzzy logic translates the operator's human experience associated with powerful computational methods.

Three-phase four-wire circuits interpretation by means of different power theories

In order to contribute to the discussion of defining a generalized power theory, valid for unbalanced and non linear circuits, this paper discusses the relationship and discrepancies among four modern power theories. Three-phase four-wire circuits, under different conditions, have been analyzed, since the most conflicting and intriguing interpretations take place in case of return conductor occurrence. Simulation results of different load, power supply and line conditions will be discussed in order to elucidate the author's conclusions and to provoke the readers for additional discussions. © 2010 IEEE.

Estabilização de sistemas fuzzy T-S incertos usando realimenta̧ão derivativa

In some practical problems, for instance, in the suppression of vibration in mechanical systems, the state-derivative signals are easier to obtain than the state signals. Thus, a method for state-derivative feedback design applied to uncertain nonlinear systems is proposed in this work. The nonlinear systems are represented by Takagi-Sugeno fuzzy models during the modeling of the problem, allowing to use Linear Matrix Inequalities (LMIs) in the controller design. This type of modeling ease the control design, because, LMIs are easily solved using convex programming technicals. The control design aimed at system stabilisation, with or without bounds on decay rate. The efficiency of design procedure is illustrated through a numerical example.

Traffic flow breakdown prediction using feature reduction through Rough-Neuro fuzzy Networks

The prediction of the traffic behavior could help to make decision about the routing process, as well as enables gains on effectiveness and productivity on the physical distribution. This need motivated the search for technological improvements in the Routing performance in metropolitan areas. The purpose of this paper is to present computational evidences that Artificial Neural Network ANN could be use to predict the traffic behavior in a metropolitan area such So Paulo (around 16 million inhabitants). The proposed methodology involves the application of Rough-Fuzzy Sets to define inference morphology for insertion of the behavior of Dynamic Routing into a structured rule basis, without human expert aid. The dynamics of the traffic parameters are described through membership functions. Rough Sets Theory identifies the attributes that are important, and suggest Fuzzy relations to be inserted on a Rough Neuro Fuzzy Network (RNFN) type Multilayer Perceptron (MLP) and type Radial Basis Function (RBF), in order to get an optimal surface response. To measure the performance of the proposed RNFN, the responses of the unreduced rule basis are compared with the reduced rule one. The results show that by making use of the Feature Reduction through RNFN, it is possible to reduce the need for human expert in the construction of the Fuzzy inference mechanism in such flow process like traffic breakdown. © 2011 IEEE.

Land use image classification through optimum-path forest clustering

Land use classification has been paramount in the last years, since we can identify illegal land use and also to monitor deforesting areas. Although one can find several research works in the literature that address this problem, we propose here the land use recognition by means of Optimum-Path Forest Clustering (OPF), which has never been applied to this context up to date. Experiments among Optimum-Path Forest, Mean Shift and K-Means demonstrated the robustness of OPF for automatic land use classification of images obtained by CBERS-2B and Ikonos-2 satellites. © 2011 IEEE.

Electrical consumers data clustering through optimum-path forest

Non-technical losses identification has been paramount in the last decade. Since we have datasets with hundreds of legal and illegal profiles, one may have a method to group data into subprofiles in order to minimize the search for consumers that cause great frauds. In this context, a electric power company may be interested in to go deeper a specific profile of illegal consumer. In this paper, we introduce the Optimum-Path Forest (OPF) clustering technique to this task, and we evaluate the behavior of a dataset provided by a brazilian electric power company with different values of an OPF parameter. © 2011 IEEE.

Automatic visual dictionary generation through Optimum-Path Forest clustering

Image categorization by means of bag of visual words has received increasing attention by the image processing and vision communities in the last years. In these approaches, each image is represented by invariant points of interest which are mapped to a Hilbert Space representing a visual dictionary which aims at comprising the most discriminative features in a set of images. Notwithstanding, the main problem of such approaches is to find a compact and representative dictionary. Finding such representative dictionary automatically with no user intervention is an even more difficult task. In this paper, we propose a method to automatically find such dictionary by employing a recent developed graph-based clustering algorithm called Optimum-Path Forest, which does not make any assumption about the visual dictionary's size and is more efficient and effective than the state-of-the-art techniques used for dictionary generation. © 2012 IEEE.