998 resultados para Operational dynamics
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The aim of this paper is to develop models for experimental open-channel water delivery systems and assess the use of three data-driven modeling tools toward that end. Water delivery canals are nonlinear dynamical systems and thus should be modeled to meet given operational requirements while capturing all relevant dynamics, including transport delays. Typically, the derivation of first principle models for open-channel systems is based on the use of Saint-Venant equations for shallow water, which is a time-consuming task and demands for specific expertise. The present paper proposes and assesses the use of three data-driven modeling tools: artificial neural networks, composite local linear models and fuzzy systems. The canal from Hydraulics and Canal Control Nucleus (A parts per thousand vora University, Portugal) will be used as a benchmark: The models are identified using data collected from the experimental facility, and then their performances are assessed based on suitable validation criterion. The performance of all models is compared among each other and against the experimental data to show the effectiveness of such tools to capture all significant dynamics within the canal system and, therefore, provide accurate nonlinear models that can be used for simulation or control. The models are available upon request to the authors.
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A maioria dos órgãos históricos portugueses data dos finais do século XVIII ou do princípio do século XIX. Durante este período foi construído um invulgar número de instrumentos em Lisboa e nas áreas circundantes por António Xavier Machado e Cerveira (1756-1828) e outros organeiros menos prolíficos. O estudo desses órgãos, muitos dos quais (restaurados ou não) se encontram próximos das condições originais, permite a identificação de um tipo de instrumento com uma morfologia específica, claramente emancipada do chamado «órgão ibérico». No entanto, até muito recentemente, não era conhecida música que se adaptasse às idiossincrasisas daqueles instrumentos. O recente estudo das obras para órgão de José Marques e Silva (1782-1837) permitiu clarificar esta situação. Bem conhecido durante a sua vida como organista e compositor, José Marques e Silva foi um dos ultimos mestres do Seminário Patriarcal. A importância da sua produção musical reside não só num substancial número de obras com autoria firmemente estabelecida – escritas, na maior parte, para coro misto com acompanhamento de órgão obbligato – mas também na íntima relação entre a sua escrita e a morfologia dos órgãos construídos em Portugal durante a sua vida. Este artigo enfatiza a importância de José Marques e Silva (indubitavelmente, o mais significativo compositor português para órgão do seu tempo) sublinhando a relevância das suas obras para órgão solo, cujo uso extensivo de escrita idiomática e indicações de registação fazem delas um dos mais importantes documentos só início do século XIX sobre a prática organística em Portugal.
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This paper analyses earthquake data in the perspective of dynamical systems and fractional calculus (FC). This new standpoint uses Multidimensional Scaling (MDS) as a powerful clustering and visualization tool. FC extends the concepts of integrals and derivatives to non-integer and complex orders. MDS is a technique that produces spatial or geometric representations of complex objects, such that those objects that are perceived to be similar in some sense are placed on the MDS maps forming clusters. In this study, over three million seismic occurrences, covering the period from January 1, 1904 up to March 14, 2012 are analysed. The events are characterized by their magnitude and spatiotemporal distributions and are divided into fifty groups, according to the Flinn–Engdahl (F–E) seismic regions of Earth. Several correlation indices are proposed to quantify the similarities among regions. MDS maps are proven as an intuitive and useful visual representation of the complex relationships that are present among seismic events, which may not be perceived on traditional geographic maps. Therefore, MDS constitutes a valid alternative to classic visualization tools for understanding the global behaviour of earthquakes.
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This paper analyzes the Portuguese short-run business cycles over the last 150 years and presents the multidimensional scaling (MDS) for visualizing the results. The analytical and numerical assessment of this long-run perspective reveals periods with close connections between the macroeconomic variables related to government accounts equilibrium, balance of payments equilibrium, and economic growth. The MDS method is adopted for a quantitative statistical analysis. In this way, similarity clusters of several historical periods emerge in the MDS maps, namely, in identifying similarities and dissimilarities that identify periods of prosperity and crises, growth, and stagnation. Such features are major aspects of collective national achievement, to which can be associated the impact of international problems such as the World Wars, the Great Depression, or the current global financial crisis, as well as national events in the context of broad political blueprints for the Portuguese society in the rising globalization process.
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The paper formulates a genetic algorithm that evolves two types of objects in a plane. The fitness function promotes a relationship between the objects that is optimal when some kind of interface between them occurs. Furthermore, the algorithm adopts an hexagonal tessellation of the two-dimensional space for promoting an efficient method of the neighbour modelling. The genetic algorithm produces special patterns with resemblances to those revealed in percolation phenomena or in the symbiosis found in lichens. Besides the analysis of the spacial layout, a modelling of the time evolution is performed by adopting a distance measure and the modelling in the Fourier domain in the perspective of fractional calculus. The results reveal a consistent, and easy to interpret, set of model parameters for distinct operating conditions.
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LLF (Least Laxity First) scheduling, which assigns a higher priority to a task with a smaller laxity, has been known as an optimal preemptive scheduling algorithm on a single processor platform. However, little work has been made to illuminate its characteristics upon multiprocessor platforms. In this paper, we identify the dynamics of laxity from the system’s viewpoint and translate the dynamics into LLF multiprocessor schedulability analysis. More specifically, we first characterize laxity properties under LLF scheduling, focusing on laxity dynamics associated with a deadline miss. These laxity dynamics describe a lower bound, which leads to the deadline miss, on the number of tasks of certain laxity values at certain time instants. This lower bound is significant because it represents invariants for highly dynamic system parameters (laxity values). Since the laxity of a task is dependent of the amount of interference of higher-priority tasks, we can then derive a set of conditions to check whether a given task system can go into the laxity dynamics towards a deadline miss. This way, to the author’s best knowledge, we propose the first LLF multiprocessor schedulability test based on its own laxity properties. We also develop an improved schedulability test that exploits slack values. We mathematically prove that the proposed LLF tests dominate the state-of-the-art EDZL tests. We also present simulation results to evaluate schedulability performance of both the original and improved LLF tests in a quantitative manner.
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The TEM family of enzymes has had a crucial impact on the pharmaceutical industry due to their important role in antibiotic resistance. Even with the latest technologies in structural biology and genomics, no 3D structure of a TEM- 1/antibiotic complex is known previous to acylation. Therefore, the comprehension of their capability in acylate antibiotics is based on the protein macromolecular structure uncomplexed. In this work, molecular docking, molecular dynamic simulations, and relative free energy calculations were applied in order to get a comprehensive and thorough analysis of TEM-1/ampicillin and TEM-1/amoxicillin complexes. We described the complexes and analyzed the effect of ligand binding on the overall structure. We clearly demonstrate that the key residues involved in the stability of the ligand (hot-spots) vary with the nature of the ligand. Structural effects such as (i) the distances between interfacial residues (Ser70−Oγ and Lys73−Nζ, Lys73−Nζ and Ser130−Oγ, and Ser70−Oγ−Ser130−Oγ), (ii) side chain rotamer variation (Tyr105 and Glu240), and (iii) the presence of conserved waters can be also influenced by ligand binding. This study supports the hypothesis that TEM-1 suffers structural modifications upon ligand binding.
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The initial goal of this work was the development of a supported liquid membrane (SLM) bioreactor for the remediation of vaccine production effluents contaminated with a highly toxic organomercurial – thiomersal. Therefore, two main aspects were focused on: 1) the development of a stable supported liquid membrane – using room temperature ionic liquids (RTILs) – for the selective transport of thiomersal from the wastewater to a biological compartment, 2) study of the biodegradation kinetics of thiomersal to metallic mercury by a Pseudomonas putida strain. The first part of the work focused on the evaluation of the physicochemical properties of ionic liquids and on the SLMs’ operational stability. The results obtained showed that, although it is possible to obtain a SLM with a high stability, water possesses nonnegligible solubility in the RTILs studied. The formation of water clusters inside the hydrophobic ionic liquid was identified and found to regulate the transport of water and small ions. In practical terms, this meant that, although it was possible to transport thiomersal from the vaccine effluent to the biological compartment, complete isolation of the microbial culture could not be guaranteed and the membrane might ultimately be permeable to other species present in the aqueous vaccine wastewater. It was therefore decided not to operate the initially targeted integrated system but, instead, the biological system by itself. Additionally, attention was given to the development of a thorough understanding of the transport mechanisms involved in the solubilisation and transport of water through supported liquid membranes with RTILs as well as to the evaluation of the effect of water uptake by the SLM in the transport mechanisms of water-soluble solutes and its effect on SLM performance. The results obtained highlighted the determinant role played by water – solubilised inside the ionic liquids – on the transport mechanism. It became clear that the transport mechanism of water and water-soluble solutes through SLMs with [CnMIM][PF6] RTILs was regulated by the dynamics of water clusters inside the RTIL, rather than by molecular diffusion through the bulk of the ionic liquid. Although the stability tests vi performed showed that there were no significant losses of organic phase from the membrane pores, the formation of water clusters inside the ionic liquid, which constitute new, non-selective environments for solute transport, leads to a clear deterioration of SLM performance and selectivity. Nevertheless, electrical impedance spectroscopy characterisation of the SLMs showed that the formation of water clusters did not seem to have a detrimental effect on the SLMs’ electrical characteristics and highlighted the potential of using this type of membranes in electrochemical applications with low resistance requirements. The second part of the work studied the kinetics of thiomersal degradation by a pure culture of P. putida spi3 strain, in batch culture and using a synthe tic wastewater. A continuous ly stirred tank reactor fed with the synthetic wastewater was also operated and the bioreactor’s performance and robustness, when exposed to thiomersal shock loads, were evaluated. Finally, a bioreactor for the biological treatment of a real va ccine production effluent was set up and operated at different dilution rates. Thus it was possible to treat a real thiomersal-contaminated effluent, lowering the outlet mercury concentration to values below the European limit for mercury effluent discharges.
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Dissertação para obtenção do grau de Mestre em Engenharia Electrotécnica Ramo de Energia
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A new operationalmatrix of fractional integration of arbitrary order for generalized Laguerre polynomials is derived.The fractional integration is described in the Riemann-Liouville sense.This operational matrix is applied together with generalized Laguerre tau method for solving general linearmultitermfractional differential equations (FDEs).Themethod has the advantage of obtaining the solution in terms of the generalized Laguerre parameter. In addition, only a small dimension of generalized Laguerre operational matrix is needed to obtain a satisfactory result. Illustrative examples reveal that the proposedmethod is very effective and convenient for linear multiterm FDEs on a semi-infinite interval.
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Power law PL and fractional calculus are two faces of phenomena with long memory behavior. This paper applies PL description to analyze different periods of the business cycle. With such purpose the evolution of ten important stock market indices DAX, Dow Jones, NASDAQ, Nikkei, NYSE, S&P500, SSEC, HSI, TWII, and BSE over time is studied. An evolutionary algorithm is used for the fitting of the PL parameters. It is observed that the PL curve fitting constitutes a good tool for revealing the signal main characteristics leading to the emergence of the global financial dynamic evolution.
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Financial time series have a complex dynamic nature. Many techniques were adopted having in mind standard paradigms of time flow. This paper explores an alternative route involving relativistic effects. It is observed that the measuring perspective influences the results and that we can have different time textures.
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Global warming and the associated climate changes are being the subject of intensive research due to their major impact on social, economic and health aspects of the human life. Surface temperature time-series characterise Earth as a slow dynamics spatiotemporal system, evidencing long memory behaviour, typical of fractional order systems. Such phenomena are difficult to model and analyse, demanding for alternative approaches. This paper studies the complex correlations between global temperature time-series using the Multidimensional scaling (MDS) approach. MDS provides a graphical representation of the pattern of climatic similarities between regions around the globe. The similarities are quantified through two mathematical indices that correlate the monthly average temperatures observed in meteorological stations, over a given period of time. Furthermore, time dynamics is analysed by performing the MDS analysis over slices sampling the time series. MDS generates maps describing the stations’ locus in the perspective that, if they are perceived to be similar to each other, then they are placed on the map forming clusters. We show that MDS provides an intuitive and useful visual representation of the complex relationships that are present among temperature time-series, which are not perceived on traditional geographic maps. Moreover, MDS avoids sensitivity to the irregular distribution density of the meteorological stations.
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Fractional dynamics reveals long range memory properties of systems described by means of signals represented by real numbers. Alternatively, dynamical systems and signals can adopt a representation where states are quantified using a set of symbols. Such signals occur both in nature and in man made processes and have the potential of a aftermath as relevant as the classical counterpart. This paper explores the association of Fractional calculus and symbolic dynamics. The results are visualized by means of the multidimensional technique and reveal the association between the fractal dimension and one definition of fractional derivative.
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This paper presents a novel method for the analysis of nonlinear financial and economic systems. The modeling approach integrates the classical concepts of state space representation and time series regression. The analytical and numerical scheme leads to a parameter space representation that constitutes a valid alternative to represent the dynamical behavior. The results reveal that business cycles can be clearly revealed, while the noise effects common in financial indices can elegantly be filtered out of the results.