995 resultados para Discrete events


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This paper discusses the use of multi-layer perceptron networks for linear or linearizable, adaptive feedback.control schemes in a discrete-time environment. A close look is taken at the model structure selected and the extent of the resulting parametrization. A comparison is made with standard, non-perceptron algorithms, e.g. self-tuning control, and it is shown how gross over-parametrization can occur in the neural network case. Because of the resultant heavy computational burden and poor controller convergence, a strong case is made against the use of neural networks for discrete-time linear control.

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An algorithm for solving nonlinear discrete time optimal control problems with model-reality differences is presented. The technique uses Dynamic Integrated System Optimization and Parameter Estimation (DISOPE), which achieves the correct optimal solution in spite of deficiencies in the mathematical model employed in the optimization procedure. A version of the algorithm with a linear-quadratic model-based problem, implemented in the C+ + programming language, is developed and applied to illustrative simulation examples. An analysis of the optimality and convergence properties of the algorithm is also presented.

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We test Slobin's (2003) Thinking-for-Speaking hypothesis on data from different groups of Turkish-German bilinguals, those living in Germany and those who have returned to Germany.

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The integration of processes at different scales is a key problem in the modelling of cell populations. Owing to increased computational resources and the accumulation of data at the cellular and subcellular scales, the use of discrete, cell-level models, which are typically solved using numerical simulations, has become prominent. One of the merits of this approach is that important biological factors, such as cell heterogeneity and noise, can be easily incorporated. However, it can be difficult to efficiently draw generalizations from the simulation results, as, often, many simulation runs are required to investigate model behaviour in typically large parameter spaces. In some cases, discrete cell-level models can be coarse-grained, yielding continuum models whose analysis can lead to the development of insight into the underlying simulations. In this paper we apply such an approach to the case of a discrete model of cell dynamics in the intestinal crypt. An analysis of the resulting continuum model demonstrates that there is a limited region of parameter space within which steady-state (and hence biologically realistic) solutions exist. Continuum model predictions show good agreement with corresponding results from the underlying simulations and experimental data taken from murine intestinal crypts.

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We develop a database of 110 gradual solar energetic particle (SEP) events, over the period 1967–2006, providing estimates of event onset, duration, fluence, and peak flux for protons of energy E > 60 MeV. The database is established mainly from the energetic proton flux data distributed in the OMNI 2 data set; however, we also utilize the McMurdo neutron monitor and the energetic proton flux from GOES missions. To aid the development of the gradual SEP database, we establish a method with which the homogeneity of the energetic proton flux record is improved. A comparison between other SEP databases and the database developed here is presented which discusses the different algorithms used to define an event. Furthermore, we investigate the variation of gradual SEP occurrence and fluence with solar cycle phase, sunspot number (SSN), and interplanetary magnetic field intensity (Bmag) over solar cycles 20–23. We find that the occurrence and fluence of SEP events vary with the solar cycle phase. Correspondingly, we find a positive correlation between SEP occurrence and solar activity as determined by SSN and Bmag, while the mean fluence in individual events decreases with the same measures of solar activity. Therefore, although the number of events decreases when solar activity is low, the events that do occur at such times have higher fluence. Thus, large events such as the “Carrington flare” may be more likely at lower levels of solar activity. These results are discussed in the context of other similar investigations.

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Virulence for bean and soybean is determined by effector genes in a plasmid-borne pathogenicity island (PAI) in race 7 strain 1449B of Pseudomonas syringae pv. phaseolicola. One of the effector genes, avrPphF, confers either pathogenicity, virulence, or avirulence depending on the plant host and is absent from races 2, 3, 4, 6, and 8 of this pathogen. Analysis of cosmid clones and comparison of DNA sequences showed that the absence of avrPphF from strain 1448A is due to deletion of a continuous 9.5-kb fragment. The remainder of the PAI is well conserved in strains 1448A and 1449B. The left junction of the deleted region consists of a chimeric transposable element generated from the fusion of homologs of IS1492 from Pseudomonas putida and IS1090 from Ralstonia eutropha. The borders of the deletion were conserved in 66 P. syringae pv. phaseolicola strains isolated in different countries and representing the five races lacking avrPphF. However, six strains isolated in Spain had a 10.5-kb deletion that extended 1 kb further from the right junction. The perfect conservation of the 28-nucleotide right repeat of the IS1090 homolog in the two deletion types and in the other 47 insertions of the IS1090 homolog in the 1448A genome strongly suggests that the avrPphF deletions were mediated by the activity of the chimeric mobile element. Our data strongly support a clonal origin for the races of P. syringae pv. phaseolicola lacking avrPphF.

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The Routh-stability method is employed to reduce the order of discrete-time system transfer functions. It is shown that the Routh approximant is well suited to reduce both the denominator and the numerator polynomials, although alternative methods, such as PadÃ�Â(c)-Markov approximation, are also used to fit the model numerator coefficients.

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The presence of mismatch between controller and system is considered. A novel discrete-time approach is used to investigate the migration of closed-loop poles when this mismatch occurs. Two forms of state estimator are employed giving rise to several interesting features regarding stability and performance.

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Uranium series dating has been carried out on secondary uranyl silicate minerals formed during sub-glacial and post-glacial weathering of Proterozoic uraninite ores in south west Finland. The samples were obtained from two sites adjacent to the Salpauselkä III ice marginal formation and cover a range of depths, from the surface to more than 60 m. Measured ages fall into three distinct groups, 70–100 ka, 28–36 ka and < 2500 yr. The youngest set is associated with surface exposures and the crystals display clear evidence of re-working. The most likely trigger for uranium release at depths below the surface weathering zone is intrusion of oxidising glacial melt water. The latter is often characterised by very high discharge rates along channels, which close once the overpressure generated at the ice margin is released. There is excellent correspondence between the two Finnish sites and published data for similar deposits over a large area of southern and central Sweden. None of the seventy samples analysed gave a U–Th age between 40 and 70 ka; a second hiatus is apparent at 20 ka, coinciding with the Last Glacial Maximum. Thus, the process responsible for uranyl silicate formation was halted for significant periods, owing to a change in geochemical conditions or the hydrogeological regime. These data support the presence of interstadial conditions during the Early and Middle Weichselian since in the absence of major climatic perturbations the uranium phases at depth are stable. When viewed in conjunction with proxy data from mammoth remains it would appear that the region was ice-free prior to the Last Glacial Maximum.

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This paper derives exact discrete time representations for data generated by a continuous time autoregressive moving average (ARMA) system with mixed stock and flow data. The representations for systems comprised entirely of stocks or of flows are also given. In each case the discrete time representations are shown to be of ARMA form, the orders depending on those of the continuous time system. Three examples and applications are also provided, two of which concern the stationary ARMA(2, 1) model with stock variables (with applications to sunspot data and a short-term interest rate) and one concerning the nonstationary ARMA(2, 1) model with a flow variable (with an application to U.S. nondurable consumers’ expenditure). In all three examples the presence of an MA(1) component in the continuous time system has a dramatic impact on eradicating unaccounted-for serial correlation that is present in the discrete time version of the ARMA(2, 0) specification, even though the form of the discrete time model is ARMA(2, 1) for both models.

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This study presents the findings of applying a Discrete Demand Side Control (DDSC) approach to the space heating of two case study buildings. High and low tolerance scenarios are implemented on the space heating controller to assess the impact of DDSC upon buildings with different thermal capacitances, light-weight and heavy-weight construction. Space heating is provided by an electric heat pump powered from a wind turbine, with a back-up electrical network connection in the event of insufficient wind being available when a demand occurs. Findings highlight that thermal comfort is maintained within an acceptable range while the DDSC controller maintains the demand/supply balance. Whilst it is noted that energy demand increases slightly, as this is mostly supplied from the wind turbine, this is of little significance and hence a reduction in operating costs and carbon emissions is still attained.