915 resultados para Simulated microgravity


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The objective of this contribution is to extend the models of cellular/composite material design to nonlinear material behaviour and apply them for design of materials for passive vibration control. As a first step a computational tool allowing determination of optimised one-dimensional isolator behaviour was developed. This model can serve as a representation for idealised macroscopic behaviour. Optimal isolator behaviour to a given set of loads is obtained by generic probabilistic metaalgorithm, simulated annealing. Cost functional involves minimization of maximum response amplitude in a set of predefined time intervals and maximization of total energy absorbed in the first loop. Dependence of the global optimum on several combinations of leading parameters of the simulated annealing procedure, like neighbourhood definition and annealing schedule, is also studied and analyzed. Obtained results facilitate the design of elastomeric cellular materials with improved behaviour in terms of dynamic stiffness for passive vibration control.

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Proceedings of the Information Technology Applications in Biomedicine, Ioannina - Epirus, Greece, October 26-28, 2006

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A distributed, agent-based intelligent system models and simulates a smart grid using physical players and computationally simulated agents. The proposed system can assess the impact of demand response programs.

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Dissertação apresentada para obtenção do grau de Doutor em Bioquímica,especialidade Bioquímica-Física, pela Universidade Nova de Lisboa, Faculdade de Cincias e Tecnologia

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The ready biodegradability of four chelating agents, N,N -(S,S)-bis[1-carboxy-2-(imidazol-4-yl)ethyl]ethylenediamine (BCIEE), N - ethylenedi-L-cysteine (EC), N,N -bis (4-imidazolymethyl)ethylenediamine (EMI) and 2,6-pyridine dicarboxylic acid (PDA), was tested according to the OECD guideline for testing of chemicals. PDA proved to be a readily biodegradable substance. However, none of the other three compounds were degraded during the 28 days of the test. Chemical simulations were performed for the four compounds in order to understand their ability to complex with some metal ions (Ca, Cd, Co, Cu, Fe, Mg, Mn, Ni, Pb, Zn) and discuss possible applications of these chelating agents. Two different conditions were simulated: (i) in the presence of the chelating agent and one metal ion, and (ii) in the simultaneous presence of the chelating agent and all metal ions with an excess of Ca. For those compounds that were revealed not to be readily biodegradable (BCIEE, EC and EMI), applications were evaluated where this property was not fundamental or even not required. Chemical simulations pointed out that possible applications for these chelating agents are: food fortification, food process, fertilizers, biocides, soil remediation and treatment of metal poisoning. Additionally, chemical simulations also predicted that PDA is an efficient chelating agent for Ca incrustations removal, detergents and for pulp metal ions removal process.

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The aim of this work was to simulate the radionuclides dispersion in the surrounding area of a coal-fired power plant, operational during the last 25 years. The dispersion of natural radionuclides (236Ra, 232Th and 40K) was simulated by a Gaussian plume dispersion model with three different stability classes estimating the radionuclides concentration at ground level. Measurements of the environmen-tal activity concentrations were carried out by γ-spectrometry and compared with results from the air dispersion and deposition model which showed that the stabil-ity class D causes the dispersion to longer distances up to 20 km from the stacks.

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Eletrotécnica Ramo de Automação e Eletrónica Industrial

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia de Eletrónica e Telecomunicações

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A new algorithm for the velocity vector estimation of moving ships using Single Look Complex (SLC) SAR data in strip map acquisition mode is proposed. The algorithm exploits both amplitude and phase information of the Doppler decompressed data spectrum, with the aim to estimate both the azimuth antenna pattern and the backscattering coefficient as function of the look angle. The antenna pattern estimation provides information about the target velocity; the backscattering coefficient can be used for vessel classification. The range velocity is retrieved in the slow time frequency domain by estimating the antenna pattern effects induced by the target motion, while the azimuth velocity is calculated by the estimated range velocity and the ship orientation. Finally, the algorithm is tested on simulated SAR SLC data.

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Trabalho Final de Mestrado elaborado no Laboratório Nacional de Engenharia Civil (LNEC) para a obtenção do grau de Mestre em Engenharia Civil pelo Instituto Superior de Engenharia de Lisboa no âmbito do protocolo entre o ISEL e o LNEC

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Trabalho Final de Mestrado elaborado no Laboratório Nacional de Engenharia Civil (LNEC) para a obtenção do grau de Mestre em Engenharia Civil pelo Instituto Superior de Engenharia de Lisboa no âmbito do protocolo de cooperação entre o ISEL e o LNEC

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Dissertação para obtenção do grau de Mestre em Engenharia Civil

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One of the most challenging task underlying many hyperspectral imagery applications is the linear unmixing. The key to linear unmixing is to find the set of reference substances, also called endmembers, that are representative of a given scene. This paper presents the vertex component analysis (VCA) a new method to unmix linear mixtures of hyperspectral sources. The algorithm is unsupervised and exploits a simple geometric fact: endmembers are vertices of a simplex. The algorithm complexity, measured in floating points operations, is O (n), where n is the sample size. The effectiveness of the proposed scheme is illustrated using simulated data.

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Dimensionality reduction plays a crucial role in many hyperspectral data processing and analysis algorithms. This paper proposes a new mean squared error based approach to determine the signal subspace in hyperspectral imagery. The method first estimates the signal and noise correlations matrices, then it selects the subset of eigenvalues that best represents the signal subspace in the least square sense. The effectiveness of the proposed method is illustrated using simulated and real hyperspectral images.

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Hyperspectral imaging sensors provide image data containing both spectral and spatial information from the Earth surface. The huge data volumes produced by these sensors put stringent requirements on communications, storage, and processing. This paper presents a method, termed hyperspectral signal subspace identification by minimum error (HySime), that infer the signal subspace and determines its dimensionality without any prior knowledge. The identification of this subspace enables a correct dimensionality reduction yielding gains in algorithm performance and complexity and in data storage. HySime method is unsupervised and fully-automatic, i.e., it does not depend on any tuning parameters. The effectiveness of the proposed method is illustrated using simulated data based on U.S.G.S. laboratory spectra and real hyperspectral data collected by the AVIRIS sensor over Cuprite, Nevada.