916 resultados para continuous-resource model
Resumo:
In this paper the continuous Verhulst dynamic model is used to synthesize a new distributed power control algorithm (DPCA) for use in direct sequence code division multiple access (DS-CDMA) systems. The Verhulst model was initially designed to describe the population growth of biological species under food and physical space restrictions. The discretization of the corresponding differential equation is accomplished via the Euler numeric integration (ENI) method. Analytical convergence conditions for the proposed DPCA are also established. Several properties of the proposed recursive algorithm, such as Euclidean distance from optimum vector after convergence, convergence speed, normalized mean squared error (NSE), average power consumption per user, performance under dynamics channels, and implementation complexity aspects, are analyzed through simulations. The simulation results are compared with two other DPCAs: the classic algorithm derived by Foschini and Miljanic and the sigmoidal of Uykan and Koivo. Under estimated errors conditions, the proposed DPCA exhibits smaller discrepancy from the optimum power vector solution and better convergence (under fixed and adaptive convergence factor) than the classic and sigmoidal DPCAs. (C) 2010 Elsevier GmbH. All rights reserved.
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This paper deals with the expected discounted continuous control of piecewise deterministic Markov processes (PDMP`s) using a singular perturbation approach for dealing with rapidly oscillating parameters. The state space of the PDMP is written as the product of a finite set and a subset of the Euclidean space a""e (n) . The discrete part of the state, called the regime, characterizes the mode of operation of the physical system under consideration, and is supposed to have a fast (associated to a small parameter epsilon > 0) and a slow behavior. By using a similar approach as developed in Yin and Zhang (Continuous-Time Markov Chains and Applications: A Singular Perturbation Approach, Applications of Mathematics, vol. 37, Springer, New York, 1998, Chaps. 1 and 3) the idea in this paper is to reduce the number of regimes by considering an averaged model in which the regimes within the same class are aggregated through the quasi-stationary distribution so that the different states in this class are replaced by a single one. The main goal is to show that the value function of the control problem for the system driven by the perturbed Markov chain converges to the value function of this limit control problem as epsilon goes to zero. This convergence is obtained by, roughly speaking, showing that the infimum and supremum limits of the value functions satisfy two optimality inequalities as epsilon goes to zero. This enables us to show the result by invoking a uniqueness argument, without needing any kind of Lipschitz continuity condition.
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Accurate price forecasting for agricultural commodities can have significant decision-making implications for suppliers, especially those of biofuels, where the agriculture and energy sectors intersect. Environmental pressures and high oil prices affect demand for biofuels and have reignited the discussion about effects on food prices. Suppliers in the sugar-alcohol sector need to decide the ideal proportion of ethanol and sugar to optimise their financial strategy. Prices can be affected by exogenous factors, such as exchange rates and interest rates, as well as non-observable variables like the convenience yield, which is related to supply shortages. The literature generally uses two approaches: artificial neural networks (ANNs), which are recognised as being in the forefront of exogenous-variable analysis, and stochastic models such as the Kalman filter, which is able to account for non-observable variables. This article proposes a hybrid model for forecasting the prices of agricultural commodities that is built upon both approaches and is applied to forecast the price of sugar. The Kalman filter considers the structure of the stochastic process that describes the evolution of prices. Neural networks allow variables that can impact asset prices in an indirect, nonlinear way, what cannot be incorporated easily into traditional econometric models.
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This work deals with a procedure for model re-identification of a process in closed loop with ail already existing commercial MPC. The controller considered here has a two-layer structure where the upper layer performs a target calculation based on a simplified steady-state optimization of the process. Here, it is proposed a methodology where a test signal is introduced in a tuning parameter of the target calculation layer. When the outputs are controlled by zones instead of at fixed set points, the approach allows the continuous operation of the process without an excessive disruption of the operating objectives as process constraints and product specifications remain satisfied during the identification test. The application of the method is illustrated through the simulation of two processes of the oil refining industry. (c) 2008 Elsevier Ltd. All rights reserved.
Resumo:
Carbon dioxide released from alcoholic fermentation accounts for 33% of the whole CO(2) involved in the use of ethanol as fuel derived from glucose. As Arthrospira platensis can uptake this greenhouse gas, this study evaluates the use of the CO(2) released from alcoholic fermentation for the production of Arthrospira platensis. For this purpose, this cyanobacterium was cultivated in continuous process using urea as nitrogen source, either using CO(2) from alcoholic fermentation, without any treatment, or using pure CO(2) from cylinder. The experiments were carried out at 120 mu mol photons m(-2) s(-1) in tubular photobioreactor at different dilution rates (0.2 <= D <= 0.8 d(-1)). Using CO(2) from alcoholic fermentation, maximum steady-state cell concentration (2661 +/- 71 mg L(-1)) was achieved at D 0.2 d(-1), whereas higher dilution rate (0.6 d(-1)) was needed to maximize cell productivity (839 mg L(-1) d(-1)). This value was 10% lower than the one obtained with pure CO(2), and there was no significant difference in the biomass protein content. With D 0.8 d(-1), it was possible to obtain 56% +/- 1.5% and 50% +/- 1.2% of protein in the dry biomass, using pure CO(2) and CO(2) from alcoholic fermentation, respectively. These results demonstrate that the use of such cost free CO(2) from alcoholic fermentation as carbon source, associated with low cost nitrogen source, may be a promising way to reduce costs of continuous cultivation of photosynthetic microorganisms, contributing at the same time to mitigate the greenhouse effect. (C) 2011 American Institute of Chemical Engineers Biotechnol. Prog., 27: 650-656, 2011
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The XSophe-Sophe-XeprView((R)) computer simulation software suite enables scientists to easily determine spin Hamiltonian parameters from isotropic, randomly oriented and single crystal continuous wave electron paramagnetic resonance (CW EPR) spectra from radicals and isolated paramagnetic metal ion centers or clusters found in metalloproteins, chemical systems and materials science. XSophe provides an X-windows graphical user interface to the Sophe programme and allows: creation of multiple input files, local and remote execution of Sophe, the display of sophelog (output from Sophe) and input parameters/files. Sophe is a sophisticated computer simulation software programme employing a number of innovative technologies including; the Sydney OPera HousE (SOPHE) partition and interpolation schemes, a field segmentation algorithm, the mosaic misorientation linewidth model, parallelization and spectral optimisation. In conjunction with the SOPHE partition scheme and the field segmentation algorithm, the SOPHE interpolation scheme and the mosaic misorientation linewidth model greatly increase the speed of simulations for most spin systems. Employing brute force matrix diagonalization in the simulation of an EPR spectrum from a high spin Cr(III) complex with the spin Hamiltonian parameters g(e) = 2.00, D = 0.10 cm(-1), E/D = 0.25, A(x) = 120.0, A(y) = 120.0, A(z) = 240.0 x 10(-4) cm(-1) requires a SOPHE grid size of N = 400 (to produce a good signal to noise ratio) and takes 229.47 s. In contrast the use of either the SOPHE interpolation scheme or the mosaic misorientation linewidth model requires a SOPHE grid size of only N = 18 and takes 44.08 and 0.79 s, respectively. Results from Sophe are transferred via the Common Object Request Broker Architecture (CORBA) to XSophe and subsequently to XeprView((R)) where the simulated CW EPR spectra (1D and 2D) can be compared to the experimental spectra. Energy level diagrams, transition roadmaps and transition surfaces aid the interpretation of complicated randomly oriented CW EPR spectra and can be viewed with a web browser and an OpenInventor scene graph viewer.
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Previous work has identified several short-comings in the ability of four spring wheat and one barley model to simulate crop processes and resource utilization. This can have important implications when such models are used within systems models where final soil water and nitrogen conditions of one crop define the starting conditions of the following crop. In an attempt to overcome these limitations and to reconcile a range of modelling approaches, existing model components that worked demonstrably well were combined with new components for aspects where existing capabilities were inadequate. This resulted in the Integrated Wheat Model (I_WHEAT), which was developed as a module of the cropping systems model APSIM. To increase predictive capability of the model, process detail was reduced, where possible, by replacing groups of processes with conservative, biologically meaningful parameters. I_WHEAT does not contain a soil water or soil nitrogen balance. These are present as other modules of APSIM. In I_WHEAT, yield is simulated using a linear increase in harvest index whereby nitrogen or water limitations can lead to early termination of grainfilling and hence cessation of harvest index increase. Dry matter increase is calculated either from the amount of intercepted radiation and radiation conversion efficiency or from the amount of water transpired and transpiration efficiency, depending on the most limiting resource. Leaf area and tiller formation are calculated from thermal time and a cultivar specific phyllochron interval. Nitrogen limitation first reduces leaf area and then affects radiation conversion efficiency as it becomes more severe. Water or nitrogen limitations result in reduced leaf expansion, accelerated leaf senescence or tiller death. This reduces the radiation load on the crop canopy (i.e. demand for water) and can make nitrogen available for translocation to other organs. Sensitive feedbacks between light interception and dry matter accumulation are avoided by having environmental effects acting directly on leaf area development, rather than via biomass production. This makes the model more stable across environments without losing the interactions between the different external influences. When comparing model output with models tested previously using data from a wide range of agro-climatic conditions, yield and biomass predictions were equal to the best of those models, but improvements could be demonstrated for simulating leaf area dynamics in response to water and nitrogen supply, kernel nitrogen content, and total water and nitrogen use. I_WHEAT does not require calibration for any of the environments tested. Further model improvement should concentrate on improving phenology simulations, a more thorough derivation of coefficients to describe leaf area development and a better quantification of some processes related to nitrogen dynamics. (C) 1998 Elsevier Science B.V.
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A new model for correlated electrons is presented which is integrable in one-dimension. The symmetry algebra of the model is the Lie superalgebra gl(2\1) which depends on a continuous free parameter. This symmetry algebra contains the eta pairing algebra as a subalgebra which is used to show that the model exhibits Off-Diagonal Long-Range Order in any number of dimensions.
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A mathematical model is presented that describes a system where two consumer species compete exploitatively for a single renewable resource. The resource is distributed in a patchy but homogeneous environment; that is, all patches are intrinsically identical. The two consumer species are referred to as diggers and grazers, where diggers deplete the resource within a patch to lower densities than grazers. We show that the two distinct feeding strategies can produce a heterogeneous resource distribution that enables their coexistence. Coexistence requires that grazers must either move faster than diggers between patches or convert the resources to population growth much more efficiently than diggers. The model shows that the functional form of resource renewal within a patch is also important for coexistence. These results contrast with theory that considers exploitation competition for a single resource when the resource is assumed to be well mixed throughout the system.
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Overcommitment of development capacity or development resource deficiencies are important problems in new product development (NPD). Existing approaches to development resource planning have largely neglected the issue of resource magnitude required for NPD. This research aims to fill the void by developing a simple higher-level aggregate model based on an intuitive idea: The number of new product families that a firm can effectively undertake is bound by the complexity of its products or systems and the total amount of resources allocated to NPD. This study examines three manufacturing companies to verify the proposed model. The empirical results confirm the study`s initial hypothesis: The more complex the product family, the smaller the number of product families that are launched per unit of revenue. Several suggestions and implications for managing NPD resources are discussed, such as how this study`s model can establish an upper limit for the capacity to develop and launch new product families.
Resumo:
We obtain a class of non-diagonal solutions of the reflection equation for the trigonometric A(n-1)((1)) vertex model. The solutions can be expressed in terms of intertwinner matrix and its inverse, which intertwine two trigonometric R-matrices. In addition to a discrete (positive integer) parameter l, 1 less than or equal to l less than or equal to n, the solution contains n + 2 continuous boundary parameters.
Resumo:
Background: Obesity and obstructive sleep apnea (OSA) are both associated with the prevalence of major cardiovascular illnesses and certain common factors they are considered responsible for, such as stress oxidative increase, sympathetic tonus and resistance to insulin. Objective: The aim of the present study was to compare the effect of continuous positive airway pressure (CPAP) on oxidative stress and adiponectin levels in obese patients with and without OSA. Methods: Twenty-nine obese patients were categorized into 3 groups: group 1: 10 individuals without OSA (apnea-hypopnea index, AHI <= 5) who did not have OSA diagnosed at polysomnography; group 2: 10 patients with moderate to severe OSA (AHI >= 20) who did not use CPAP; group 3: 9 patients with moderate to severe OSA (AHI >= 20) who used CPAP. Results: Group 3 showed significant differences before and after the use of CPAP, in the variables of diminished production of superoxide, and increased nitrite and nitrate synthesis and adiponectin levels. Positive correlations were seen between the AHI and the superoxide production, between the nitrite and nitrate levels and the adiponectin levels, between superoxide production and the HOMA-IR, and between AHI and the HOMA-IR. Negative correlations were found between AHI and the nitrite and nitrate levels, between the superoxide production and that of nitric oxide, between the superoxide production and the adiponectin levels, between AHI and the adiponectin levels, and between the nitrite and nitrate levels and the HOMA-IR. Conclusions: This study demonstrates that the use of CPAP can reverse the increased superoxide production, the diminished serum nitrite, nitrate and plasma adiponectin levels, and the metabolic changes existing in obese patients with OSA. Copyright (C) 2009 S. Karger AG, Basel
Resumo:
The St. Lawrence Island polynya (SLIP) is a commonly occurring winter phenomenon in the Bering Sea, in which dense saline water produced during new ice formation is thought to flow northward through the Bering Strait to help maintain the Arctic Ocean halocline. Winter darkness and inclement weather conditions have made continuous in situ and remote observation of this polynya difficult. However, imagery acquired from the European Space Agency ERS-1 Synthetic Aperture Radar (SAR) has allowed observation of the St. Lawrence Island polynya using both the imagery and derived ice displacement products. With the development of ARCSyM, a high resolution regional model of the Arctic atmosphere/sea ice system, simulation of the SLIP in a climate model is now possible. Intercomparisons between remotely sensed products and simulations can lead to additional insight into the SLIP formation process. Low resolution SAR, SSM/I and AVHRR infrared imagery for the St. Lawrence Island region are compared with the results of a model simulation for the period of 24-27 February 1992. The imagery illustrates a polynya event (polynya opening). With the northerly winds strong and consistent over several days, the coupled model captures the SLIP event with moderate accuracy. However, the introduction of a stability dependent atmosphere-ice drag coefficient, which allows feedbacks between atmospheric stability, open water, and air-ice drag, produces a more accurate simulation of the SLIP in comparison to satellite imagery. Model experiments show that the polynya event is forced primarily by changes in atmospheric circulation followed by persistent favorable conditions: ocean surface currents are found to have a small but positive impact on the simulation which is enhanced when wind forcing is weak or variable.
Resumo:
The dynamic response of dry masonry columns can be approximated with finite-difference equations. Continuum models follow by replacing the difference quotients of the discrete model by corresponding differential expressions. The mathematically simplest of these models is a one-dimensional Cosserat theory. Within the presented homogenization context, the Cosserat theory is obtained by making ad hoc assumptions regarding the relative importance of certain terms in the differential expansions. The quality of approximation of the various theories is tested by comparison of the dispersion relations for bending waves with the dispersion relation of the discrete theory. All theories coincide with differences of less than 1% for wave-length-block-height (L/h) ratios bigger than 2 pi. The theory based on systematic differential approximation remains accurate up to L/h = 3 and then diverges rapidly. The Cosserat model becomes increasingly inaccurate for L/h < 2 pi. However, in contrast to the systematic approximation, the wave speed remains finite. In conclusion, considering its relative simplicity, the Cosserat model appears to be the natural starting point for the development of continuum models for blocky structures.
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Introduction: Smoking is a serious worldwide public health problem. Animal models act as a bridge between laboratory and human studies. The models applied are difficult to reproduce because of the use of different types of inhalation chambers and mainly because of the lack of continuous monitoring of smoke concentration. Objective: To develop an inhalation chamber for rats (with only the nose exposed) in which the amount of carbon monoxide (CO) can be maintained and monitored constantly. Material and methods: Male Wistar rats weighing 250 g were exposed to 50 ppm CO produced by the smoke from a filter-free cigarette. The animals were submitted to a single 2-h exposure and then sacrificed at 0, 4, 24 and 48 h. The control group was left restrained inside the small perpendicular chambers, receiving only 5 L/min of compressed air. Results: The model was able to increase HbCO levels immediately after the end of exposure (p < 0.001). with a decrease being observed from 2 h onwards when compared to the levels of the control group. Plasma cotinine increased immediately after exposure, and showed still detectable levels at 2 and 4 h (p < 0.05). Conclusion: We conclude that the presented inhalation chamber system is able to maintain a controlled CO concentration in a model in which small animals are exposed to the inhalation of cigarette smoke, permitting well-controlled studies, as well as investigations involving other toxic gases and air pollutants. (C) 2008 SEPAR. Published by Elsevier Espana, S.L. All rights reserved.