238 resultados para Analog parameters
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High amylose cross-linked to different degrees with sodium trimetaphosphate by varying base strength (2% or 4%) and contact time (0.5-4 h) was evaluated as non-compacted systems for sodium diclophenac controlled release. The physical properties and the performance of these products for sodium diclophenac controlled release from non-compacted systems were related to the structures generated at each cross-linking degree. For samples at 2% until 2 h the swelling ability, G' and eta* values increased with the cross-linking degree, because the longer polymer chains became progressively more entangled and linked. This increases water uptake and holding, favoring the swelling and resulting in systems with higher viscosities. Additionally, the increase of cross-linking degree should contribute for a more elastic structure. The shorter chains with more inter-linkages formed at higher cross-linking degrees (2%4h and 4%) make water caption and holding difficult, decreasing the swelling, viscosity and elasticity. For 2% samples, the longer drug release time exhibited for 2%4h sample indicates that the increase of swelling and viscosity contribute for a more sustained drug release, but the mesh size of the polymeric network seems to be determinant for the attachment of drug molecules. For the 4% samples, smaller meshes size should determine less sustained release of drug. (C) 2008 Elsevier B.V. All rights reserved.
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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This gaper demonstrates that artificial neural networks can be used effectively for estimation of parameters related to study of atmospheric conditions to high voltage substations design. Specifically, the neural networks are used to compute the variation of electrical field intensity and critical disruptive voltage in substations taking into account several atmospheric factors, such as pressure, temperature, humidity, so on. Examples of simulation of tests are presented to validate the proposed approach. The results that were obtained by experimental evidences and numerical simulations allowed the verification of the influence of the atmospheric conditions on design of substations concerning lightning.
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In this paper, a factor referred to as k(f) for linear induction motor end effect analysis is presented. The mathematical model takes into account the longitudinal entry end effect. The entry end effect produces considerable distortion in magnetic field distribution. It is shown how this influence is derived from the machine-developed force that is calculated through the application of the I-D theory. The k(f) factor establishes the relationship between the longitudinal end effect and machine parameters, mainly the number of magnetic poles, secondary resistivity, and frequency.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
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Continuous-time neural networks for solving convex nonlinear unconstrained;programming problems without using gradient information of the objective function are proposed and analyzed. Thus, the proposed networks are nonderivative optimizers. First, networks for optimizing objective functions of one variable are discussed. Then, an existing one-dimensional optimizer is analyzed, and a new line search optimizer is proposed. It is shown that the proposed optimizer network is robust in the sense that it has disturbance rejection property. The network can be implemented easily in hardware using standard circuit elements. The one-dimensional net is used as a building block in multidimensional networks for optimizing objective functions of several variables. The multidimensional nets implement a continuous version of the coordinate descent method.
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Analog neural systems that can automatically find the minimum value of the outputs of unknown analog systems, described by convex functions, are studied. When information about derivative or gradient are not used, these systems are called analog nonderivative optimizers. An electronic circuit for the analog neural nonderivative optimizer proposed by Teixeira and Zak, and its simulation with software PSPICE, is presented. With the simulation results and hardware implementation of the system, the validity of the proposed optimizer can be verified. These results are original, from the best of the authors knowledge.
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This paper presents a new approach to develop Field Programmable Analog Arrays (FPAAs),(1) which avoids excessive number of programming elements in the signal path, thus enhancing the performance. The paper also introduces a novel FPAA architecture, devoid of the conventional switching and connection modules. The proposed FPAA is based on simple current mode sub-circuits. An uncompounded methodology has been employed for the programming of the Configurable Analog Cell (CAC). Current mode approach has enabled the operation of the FPAA presented here, over almost three decades of frequency range. We have demonstrated the feasibility of the FPAA by implementing some signal processing functions.
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An analog synthesizer of orthogonal signals for digital CMOS technology and 3V supply voltage is presented. The adaptive architecture accomplishes the synthesis of mutually orthogonal signal, such as trigonometric and polynomial basis. Experimental results using 0.35 mu m AMS CMOS process are presented for generation of the cosine and Legendre basis.
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In this paper a new algorithmic of Analog-to-Digital Converter is presented. This new topology use the current-mode technique that allows a large dynamic range and can be implemented in digital CMOS process. The ADC proposed is very small and can handle high sampling rates. Simulation results using a 1.2um CMOS process show that an 8-b ADC can support a sampling rate of 50MHz.
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The conventional Newton's method has been considered inadequate to obtain the maximum loading point (MLP) of power systems. It is due to the Jacobian matrix singularity at this point. However, the MLP can be efficiently computed through parameterization techniques of continuation methods. This paper presents and tests new parameterization schemes, namely the total power losses (real and reactive), the power at the slack bus (real or reactive), the reactive power at generation buses, the reactive power at shunts (capacitor or reactor), the transmission lines power losses (real and reactive), and transmission lines power (real and reactive). Besides their clear physical meaning, which makes easier the development and application of continuation methods for power systems analysis, the main advantage of some of the proposed parameters is that its not necessary to change the parameter in the vicinity of the MLP. Studies on the new parameterization schemes performed on the IEEE 118 buses system show that the ill-conditioning problems at and near the MLP are eliminated. So, the characteristics of the conventional Newton's method are not only preserved but also improved. (C) 2003 Elsevier B.V. B.V. All rights reserved.
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An analog synthesizer of orthogonal signals for digital CMOS technology and 3V supply voltage is presented. The adaptive architecture accomplishes the synthesis of mutually orthogonal signal, such as trigonometric and polynomial basis. Simulation results using 0.35 mu m AMS CMOS process are presented for generation of the cosine and Legendre basis.
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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)