Morphology of the eggs of the genus Belminus (Hemiptera: Reduviidae: Triatominae) by optical and scanning electron microscopy

The external morphology of eggs of the species Belminus corredori Galvao & Angulo, 2006, Belminus herreri Lent & Wygodzinsky, 1979 and Belminus ferroae Sandoval, Pabon, Jurberg & Galvao, 2007 is described for the first time using scanning electron microscopy (SEM). Females lay one egg at a time; the shape of the egg is oval with lateral flattening, a rounded caudal area and a true and simple convex operculum. The average size of the egg among these species is 0.51-0.58 mm in length and 0.36-0.4 mm in width. As a generic character we highlight the discovery of a chorion rim with one to four grooves always joined to the micropyles. All species present a clear polygonal pattern only in the operculum and in the egg's cephalic region, while the median and caudal regions show a smooth appearance, features that are shared only with the eggs of the genus Alberprosenia. A discriminant analysis of the polygonal design of the operculum proved to be useful for the identification of the species.

Comparative study between RBF and radial-PPS neural networks

The study of function approximation is motivated by the human limitation and inability to register and manipulate with exact precision the behavior variations of the physical nature of a phenomenon. These variations are referred to as signals or signal functions. Many real world problem can be formulated as function approximation problems and from the viewpoint of artificial neural networks these can be seen as the problem of searching for a mapping that establishes a relationship from an input space to an output space through a process of network learning. Several paradigms of artificial neural networks (ANN) exist. Here we will be investigated a comparative of the ANN study of RBF with radial Polynomial Power of Sigmoids (PPS) in function approximation problems. Radial PPS are functions generated by linear combination of powers of sigmoids functions. The main objective of this paper is to show the advantages of the use of the radial PPS functions in relationship traditional RBF, through adaptive training and ridge regression techniques.

An Optimum-Path Forest framework for intrusion detection in computer networks

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

A Management Tool for the Replication of Operating Systems in Wireless Communication Networks

To simplify computer management, various administration systems based on wired connections adopt advanced techniques to manage software configuration. Nevertheless, the strong relation between hardware and software makes for an individualism of that management, besides penalizing computational mobility and ubiquity. All these issues lead to degradation of scalability, flexibility and the facility to install and maintain distributed applications. This article presents an environment for centralized wireless communication network management, named WSE-OS (Wireless Sharing Environment - Operating Systems): a model based on Virtual Desktop Infrastructure (VDI) which associates virtualization techniques and safe remote access systems to create a distributed architecture as a base for a managing system. WSE-OS is capable of accomplishing the replication of operating system images using wireless communication network, besides offering abstraction of hardware to its clients, making the management more flexible and independent of wired connections. Results obtained from this work indicate that WSE-OS allows disseminating, through a single software configuration, the execution of data related to operating system images in client computers. WSE-OS can also be used as a management tool for operating systems in a wireless network.

Towards coherent optical control of a single hole spin: Rabi rotation of a trion conditional on the spin state of the hole

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Disorder effects produced by the Mn and H incorporations on the optical absorption edge of Ga1-xMnxAs:H nanocrystalline films

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

Structural and optical properties of chlorinated plasma polymers

Amorphous hydrogenated chlorinated carbon (a-C:H:Cl) films were produced by the plasma polymerization of chloroform-acetylene-argon mixtures in a radiofrequency plasma enhanced chemical vapor deposition system. The main parameter of interest was the proportion of chloroform in the feed, R(C), which was varied from 0 to 80%. Deposition rates of 80 nm min (1) were typical for the chlorinated films. Infrared reflection-absorption spectroscopy revealed the presence of C-Cl groups in all the films produced with chloroform in the feed. X-ray photoelectron spectroscopy confirmed this finding, and revealed a saturation of the chlorine content at similar to 47 at.% for R(C)>= 40%. The refractive index and optical gap, E(04), of the films were roughly in the 1.6 to 1.7, and the 2.8 to 3.7 eV range. These values were calculated from transmission ultraviolet-visible-near infrared spectra. Chlorination leads to an increase in the water surface contact angle from similar to 40 degrees to similar to 77 degrees. (C) 2011 Elsevier B.V. All rights reserved.

Strutural and optical approach of CdS@ZnS core-shell system

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Electronic structure and optical properties of BaMoO4 powders

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A novel approach based on recurrent neural networks applied to nonlinear systems optimization

This paper presents an efficient approach based on recurrent neural network for solving 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 treats optimization and constraint terms in different stages with no interference with each other. Moreover, the proposed approach does not require specification of penalty and weighting parameters for its initialization. A study of the modified Hopfield model is also developed to analyze its stability and convergence. Simulation results are provided to demonstrate the performance of the proposed neural network. (c) 2005 Elsevier B.V. All rights reserved.

Sensitivity analysis by neural networks applied to power systems transient stability

This work presents a procedure for transient stability analysis and preventive control of electric power systems, which is formulated by a multilayer feedforward neural network. The neural network training is realized by using the back-propagation algorithm with fuzzy controller and adaptation of the inclination and translation parameters of the nonlinear function. These procedures provide a faster convergence and more precise results, if compared to the traditional back-propagation algorithm. The adaptation of the training rate is effectuated by using the information of the global error and global error variation. After finishing the training, the neural network is capable of estimating the security margin and the sensitivity analysis. Considering this information, it is possible to develop a method for the realization of the security correction (preventive control) for levels considered appropriate to the system, based on generation reallocation and load shedding. An application for a multimachine power system is presented to illustrate the proposed methodology. (c) 2006 Elsevier B.V. All rights reserved.

Power flow for primary distribution networks considering uncertainty in demand and user connection

This paper presents a method for calculating the power flow in distribution networks considering uncertainties in the distribution system. Active and reactive power are used as uncertain variables and probabilistically modeled through probability distribution functions. Uncertainty about the connection of the users with the different feeders is also considered. A Monte Carlo simulation is used to generate the possible load scenarios of the users. The results of the power flow considering uncertainty are the mean values and standard deviations of the variables of interest (voltages in all nodes, active and reactive power flows, etc.), giving the user valuable information about how the network will behave under uncertainty rather than the traditional fixed values at one point in time. The method is tested using real data from a primary feeder system, and results are presented considering uncertainty in demand and also in the connection. To demonstrate the usefulness of the approach, the results are then used in a probabilistic risk analysis to identify potential problems of undervoltage in distribution systems. (C) 2012 Elsevier Ltd. All rights reserved.

Artificial neural networks for load flow and external equivalents studies

In this paper an artificial neural network (ANN) based methodology is proposed for (a) solving the basic load flow, (b) solving the load flow considering the reactive power limits of generation (PV) buses, (c) determining a good quality load flow starting point for ill-conditioned systems, and (d) computing static external equivalent circuits. An analysis of the input data required as well as the ANN architecture is presented. A multilayer perceptron trained with the Levenberg-Marquardt second order method is used. The proposed methodology was tested with the IEEE 30- and 57-bus, and an ill-conditioned 11-bus system. Normal operating conditions (base case) and several contingency situations including different load and generation scenarios have been considered. Simulation results show the excellent performance of the ANN for solving problems (a)-(d). (C) 2010 Elsevier B.V. All rights reserved.

The temperature coefficient of the optical path length as a function of the temperature in different optical glasses

An interferometric technique was used to determine the temperature coefficient of the optical path length (dS/dT) as a function of the temperature in several optical glasses. The temperature range was between 25degreesC and 180degreesC. The studied samples included undoped and doped oxide glasses, such as low silica calcium aluminosilicate, phosphates, borates and also chalcogenides. The oxide glasses had dS/dT between 10 X 10(-6) K-1 and 20x10(-6) K-1, while for the chalcogenides, these were around 70 x 10(-6)K(-1). The results showed that dS/dTs increased with the temperature in all samples. For samples doped with Nd the dS/dT values were found to be independent of concentration. on the other hand, for the phosphate glass doped with Cr, dS/dT increased about 5% when compared with the Nd doped one. In conclusion, the used interferometric method, which is a considerably simpler and a lower cost technique, and is a useful tool to measure dS/dT in semi-transparent glasses as a function of the composition and temperature. (C) 2004 Elsevier B.V. All rights reserved.

The structure and optical dispersion of the refractive index of tellurite glass

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)