Análises moleculares de populações de Wasmannia auropunctata Roger, 1863 (Hymenoptera: Formicidae) e da presença de endossimbiontes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Análisis organizacional del partido de la democracia social brasileña en el estado de San Pablo (1988-2006)

The article represents a theoretical and methodological approach to the analysis of organizational dynamics of political parties today, based on a study of the Party of Brazilian Social Democracy (PSDB) in the State of Sao Pãulo (period between 1988 to 2006). It is hypothesized that the structure and the institutional rules of a particular party, or even their election results, are insufficient to explain the inner workings, such as the role of party organization in the electoral system. An approach that articulates the relationship patterns, election results and posts held in the party, identified the factors that explain the political capital that circulated within the party and ensured its organizational dynamics over the period analyzed.

A low-power silicon-on-insulator PWM discriminator for biomedical applications

A CMOS/SOI circuit to decode PWM signals is presented as part of a body-implanted neurostimulator for visual prosthesis. Since encoded data is the sole input to the circuit, the decoding technique is based on a double-integration concept and does not require dc filtering. Nonoverlapping control phases are internally derived from the incoming pulses and a fast-settling comparator ensures good discrimination accuracy in the megahertz range. The circuit was integrated on a 2 mu m single-metal SOI fabrication process and has an effective area of 2mm(2) Typically, the measured resolution of encoding parameter a was better than 10% at 6MHz and V-DD=3.3V. Stand-by consumption is around 340 mu W. Pulses with frequencies up to 15MHz and alpha = 10% can be discriminated for V-DD spanning from 2.3V to 3.3V. Such an excellent immunity to V-DD deviations meets a design specification with respect to inherent coupling losses on transmitting data and power by means of a transcutaneous link.

Instantaneous complex power applied to three-phase machines

The theory presented in this paper was primarily developed to give a physical interpretation for the instantaneous power flow on a three-phase induction machine, without a neutral conductor, on any operational state and may be extended to any three-phase load. It is a vectorial interpretation of the instantaneous reactive power theory presented by Akagi et al. Which, believe the authors, isn't enough developed and its physical meaning not yet completely understood. This vectorial interpretation is based on the instantaneous complex power concept defined by Torrens for single-phase, ac, steady-state circuits, and leads to a better understanding of the power phenomenon, particularly of the distortion power. This concept has been extended by the authors to three-phase systems, through the utilization of the instantaneous space vectors. The results of measurements of instantaneous complex power on a self-excited induction generator's terminals, during an over-load application transient, are presented for illustration. The compensation of reactive power proposed by Akagi is discussed and a new horizon for the theory application is opened.

Prospecting major genes in dairy buffaloes

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

A novel single-phase ZCS-PWM high power factor boost rectifier

This paper presents a novel single-phase high power factor PWM boost rectifier, featuring soft commutation of the active switches at zero-current (ZCS). It incorporates the most desirable properties of the conventional PWM and the soft-switching resonant techniques. The input current shaping is achieved with average current mode control, and continuous inductor current mode. This new PWM converter provides ZCS turn-on and turn-off of the active switches, and it is suitable for high power applications employing IGBTs. Principle of operation, theoretical analysis, a design example, and experimental results from a laboratory prototype rated at 1600 W with 400 Vdc output voltage are presented. The measured efficiency and power factor were 96.2% and 0.99 respectively, with an input current THD equal to 3.94%, for an input voltage THD equal to 3.8%, at rated load.

As relações entre capacitação de pessoas e operação de tecnologias agrícolas em empresas do setor sucroenergético

Pós-graduação em Agronegócio e Desenvolvimento - Tupã

Indicadores de bibliotecas universitárias: criação de índice de desenvolvimento baseado em redes de conhecimento compartilhado

Pós-graduação em Ciência da Informação - FFC

Design and analysis of an efficient neural network model for solving nonlinear optimization problems

This paper presents an efficient approach based on a recurrent neural network for solving constrained nonlinear optimization. More specifically, a modified Hopfield network is developed, and its internal parameters are computed using the valid-subspace technique. These parameters guarantee the convergence of the network to the equilibrium points that represent an optimal feasible solution. The main advantage of the developed network is that it handles optimization and constraint terms in different stages with no interference from each other. Moreover, the proposed approach does not require specification for penalty and weighting parameters for its initialization. A study of the modified Hopfield model is also developed to analyse its stability and convergence. Simulation results are provided to demonstrate the performance of the proposed neural network.

Transient stability analysis of electric energy systems via a fuzzy ART-ARTMAP neural network

This work presents a methodology to analyze transient stability (first oscillation) of electric energy systems, using a neural network based on ART architecture (adaptive resonance theory), named fuzzy ART-ARTMAP neural network for real time applications. The security margin is used as a stability analysis criterion, considering three-phase short circuit faults with a transmission line outage. The neural network operation consists of two fundamental phases: the training and the analysis. The training phase needs a great quantity of processing for the realization, while the analysis phase is effectuated almost without computation effort. This is, therefore the principal purpose to use neural networks for solving complex problems that need fast solutions, as the applications in real time. The ART neural networks have as primordial characteristics the plasticity and the stability, which are essential qualities to the training execution and to an efficient analysis. The fuzzy ART-ARTMAP neural network is proposed seeking a superior performance, in terms of precision and speed, when compared to conventional ARTMAP, and much more when compared to the neural networks that use the training by backpropagation algorithm, which is a benchmark in neural network area. (c) 2005 Elsevier B.V. All rights reserved.

Neural network based on adaptive resonance theory with continuous training for multi-configuration transient stability analysis of electric power systems

This work presents a methodology to analyze electric power systems transient stability for first swing using a neural network based on adaptive resonance theory (ART) architecture, called Euclidean ARTMAP neural network. The ART architectures present plasticity and stability characteristics, which are very important for the training and to execute the analysis in a fast way. The Euclidean ARTMAP version provides more accurate and faster solutions, when compared to the fuzzy ARTMAP configuration. Three steps are necessary for the network working, training, analysis and continuous training. The training step requires much effort (processing) while the analysis is effectuated almost without computational effort. The proposed network allows approaching several topologies of the electric system at the same time; therefore it is an alternative for real time transient stability of electric power systems. To illustrate the proposed neural network an application is presented for a multi-machine electric power systems composed of 10 synchronous machines, 45 buses and 73 transmission lines. (C) 2010 Elsevier B.V. All rights reserved.

Identification of lubricant contamination by biodiesel using vibration analysis and neural network

Purpose - The purpose of this paper is to provide information on lubricant contamination by biodiesel using vibration and neural network.Design/methodology/approach - The possible contamination of lubricants is verified by analyzing the vibration and neural network of a bench test under determinated conditions.Findings - Results have shown that classical signal analysis methods could not reveal any correlation between the signal and the presence of contamination, or contamination grade. on other hand, the use of probabilistic neural network (PNN) was very successful in the identification and classification of contamination and its grade.Research limitations/implications - This study was done for some specific kinds of biodiesel. Other types of biodiesel could be analyzed.Practical implications Contamination information is presented in the vibration signal, even if it is not evident by classical vibration analysis. In addition, the use of PNN gives a relatively simple and easy-to-use detection tool with good confidence. The training process is fast, and allows implementation of an adaptive training algorithm.Originality/value - This research could be extended to an internal combustion engine in order to verify a possible contamination by biodiesel.

Analysis of a hyper-diverse seed dispersal network: modularity and underlying mechanisms

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

Simulation and analysis of a collisionless optical interconnection network

This article describes the simulation and analysis of collisionless optical interconnection network, which the objective is to achieve a high performance level based on a single protocol control. The optical coupler has one shared control channel and N communication channels. Each network node two communication modules one for packet transmission/reception and another for control channel access. We show by simulation that system achieves a high performance and ensures high scalability.

Analysis of heuristic algorithms for the transportation model in static and multistage planning in network expansion systems

The usefulness of the application of heuristic algorithms in the transportation model, first proposed by Garver, is analysed in relation to planning for the expansion of transmission systems. The formulation of the mathematical model and the solution techniques proposed in the specialised literature are analysed in detail. Starting with the constructive heuristic algorithm proposed by Garver, an extension is made to the problem of multistage planning for transmission systems. The quality of the solutions found by heuristic algorithms for the transportation model is analysed, as are applications in problems of planning transmission systems.