Nanotechnology-based Drug Delivery Systems for Dermatomycosis Treatment

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

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.

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.

Robust fault diagnosis in power distribution systems based on fuzzy ARTMAP neural network-aided evidence theory

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

LMI-based algorithm for strictly positive real systems with static output feedback

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

Robust state-derivative pole placement LMI-based designs for linear systems

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Robust State-Derivative Feedback LMI-Based Designs for Linear Descriptor Systems

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

On Fuzzy Implication Classes - Towards Extensions of Fuzzy Rule-Based Systems

Atualmente, há diferentes definições de implicações fuzzy aceitas na literatura. Do ponto de vista teórico, esta falta de consenso demonstra que há discordâncias sobre o real significado de "implicação lógica" nos contextos Booleano e fuzzy. Do ponto de vista prático, isso gera dúvidas a respeito de quais "operadores de implicação" os engenheiros de software devem considerar para implementar um Sistema Baseado em Regras Fuzzy (SBRF). Uma escolha ruim destes operadores pode implicar em SBRF's com menor acurácia e menos apropriados aos seus domínios de aplicação. Uma forma de contornar esta situação e conhecer melhor os conectivos lógicos fuzzy. Para isso se faz necessário saber quais propriedades tais conectivos podem satisfazer. Portanto, a m de corroborar com o significado de implicação fuzzy e corroborar com a implementação de SBRF's mais apropriados, várias leis Booleanas têm sido generalizadas e estudadas como equações ou inequações nas lógicas fuzzy. Tais generalizações são chamadas de leis Boolean-like e elas não são comumente válidas em qualquer semântica fuzzy. Neste cenário, esta dissertação apresenta uma investigação sobre as condições suficientes e necessárias nas quais três leis Booleanlike like — y ≤ I(x, y), I(x, I(y, x)) = 1 e I(x, I(y, z)) = I(I(x, y), I(x, z)) — se mantém válidas no contexto fuzzy, considerando seis classes de implicações fuzzy e implicações geradas por automorfismos. Além disso, ainda no intuito de implementar SBRF's mais apropriados, propomos uma extensão para os mesmos

New analytical procedure based on a cellulose bag and ionic exchanger with p-aminobenzoic acid groups for differentiation of labile and inert metal species in aquatic systems

A new procedure was developed for the in situ characterization of the lability of metal species in aquatic systems by using a system equipped with a diffusion membrane and cellulose organomodified with p-aminobenzoic acid groups (DM-Cell-PAB). To this end, the DM-Cell-PAB system was prepared by adding cellulose organomodified with p-aminobenzoic acid groups (Cell-PAB) to pre-purified cellulose bags. After the DM-Cell-PAB system was sealed, it was examined in the laboratory to evaluate the influence of complexation time, mass of exchanger, pH, metal ions (Cu, Cd, Fe, Mn, and Ni), and concentration of organic matter on the relative lability of metal species. It was found that the pH and kinetics strongly influence the process of metal complexation by the DM-Cell-PAB system. At all pH levels, Cd, Mn, and Ni showed lower complexation with Cell-PAB resin than Cu and Fe metals. Note that relative lability of metals complexed to aquatic humic substances (AHS) in the presence of Cell-PAB resin showed the following order: Cu congruent to Fe >> Ni > Mn=Cd. The results presented here also indicate that increasing the AHS concentration decreases the lability of metal species by shifting the equilibrium to AHS-metal complexes. Our results indicate that the system under study offers an interesting alternative that can be applied to in situ experiments for differentiation of labile and inert metal species in aquatic systems.

A new approach for determining stability constants of metal ion complexes in aquatic systems based on flow injection-ion exchange-flame atomic absorption spectrometry coupling

A method based an ion exchange(IE)-atomic absorption spectrometry(AAS) coupled by flow techniques, allowing the determination of formation constants of, at least, the first species of complex systems, in aqueous solution, was developed.The IE-AAS coupling reduces significantly the number of experimental steps in comparison with IE batch methods, resulting in an important increase in analytical rate. The method is simple both from experimental and computational points of view, making possible its utilization by workers without special expertise in the field of complex equilibria in solution. on the other hand, taking into account mainly the amount of hollow cathode lamps available to date, the developed procedure may be applied, within certain limitations, to the study of many systems whose features prevent the use of traditional approaches.

Methodology for load compensation in four-wire electrical power systems based on instantaneous sampling

This work describes a methodology for power factor control and correction of the unbalanced currents in four-wire electric circuits. The methodology is based on the insertion of two compensation networks, one wye-grounded neutral and other in delta, in parallel to the load. The mathematical development has been proposed in previous work [3]. In this paper, however, the determination of the compensation susceptances is based on the instantaneous values of load currents. The results are obtained using the MatLab-Simulink enviroment

Robust state-derivative feedback LMI-based designs for multivariable linear systems

In some practical problems, for instance in the control systems for the suppression of vibration in mechanical systems, the state-derivative signals are easier to obtain than the state signals. New necessary and sufficient linear matrix inequalities (LMI) conditions for the design of state-derivative feedback for multi-input (MI) linear systems are proposed. For multi-input/multi-output (MIMO) linear time-invariant or time-varying plants, with or without uncertainties in their parameters, the proposed methods can include in the LMI-based control designs the specifications of the decay rate, bounds on the output peak, and bounds on the state-derivative feedback matrix K. These design procedures allow new specifications and also, they consider a broader class of plants than the related results available in the literature. The LMIs, when feasible, can be efficiently solved using convex programming techniques. Practical applications illustrate the efficiency of the proposed methods.

Decision-Making Tool for Knowledge-Based Projects in Offshore Production Systems

The development of an offshore field demands knowledge of many experts to choose the different components of an offshore production system. All the specialized parts of this knowledge are intrinsically related. The aim of this paper is to use Fuzzy Sets and knowledge-based systems to describe and formalize the phases of development of an offshore production system project, in order to share and to manage the required knowledge for carrying out a project, while at the same time proposing alternatives for the oil field configuration.

Growth parameters and nutrient content in four multipurpose tree species with potential characteristics for agroforestry systems in a Cerrado region in Botucatu, São Paulo State, Brazil

In order to evaluate growth characteristics, adaptability, biomass production, nutrient recycling, nutrient distribution and the ability to regenerate degraded land, a trial using four multipurpose tree species (Leucaena leucocephala, Leucaena diversifolia, Acacia melanoxylon and Mimosa scabrella) was undertaken over two years in a distrophic red yellow latosol (oxisol) following a randomized block experimental design with four replications. At the age of two years, A. melanoxylon and L. diversifolia were the tallest species (5.25 and 4.97 m, respectively) and A. melanoxylon and M. scabrella had the largest diameters at 20 cm from tree base. Mimosa scabrella and A. melanoxylon had the highest dry matter production and quantity of nutrients in the above ground biomass. In all species, the highest nutrient contents were found in the leaves, followed by branches and stems. From all species, the highest Nutrient Utilization Efficiency Indexes were obtained for sulphur, phosphorous, and magnesium; L. diversifolia was the most efficient for nitrogen, potassium, calcium, sulphur, and manganese, while A. melanoxylon was the most efficient for phosphorus, magnesium, boron, iron, and zinc. Litter production levels over a three month period were as follows: M. scabrella > A. melanoxylon > L. diversifolia > L. leucocephala. Litter nutrient content was higher in M. scabrella than in the other species.