856 resultados para Exclusion process, Multi-species, Multi-scale modelling


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The presented work deals with the calibration of a 2D numerical model for the simulation of long term bed load transport. A settled basin along an alpine stream was used as a case study. The focus is to parameterise the used multi fractional transport model such that a dynamically balanced behavior regarding erosion and deposition is reached. The used 2D hydrodynamic model utilizes a multi-fraction multi-layer approach to simulate morphological changes and bed load transport. The mass balancing is performed between three layers: a top mixing layer, an intermediate subsurface layer and a bottom layer. Using this approach bears computational limitations in calibration. Due to the high computational demands, the type of calibration strategy is not only crucial for the result, but as well for the time required for calibration. Brute force methods such as Monte Carlo type methods may require a too large number of model runs. All here tested calibration strategies used multiple model runs utilising the parameterization and/or results from previous run. One concept was to reset to initial bed elevations after each run, allowing the resorting process to convert to stable conditions. As an alternative or in combination, the roughness was adapted, based on resulting nodal grading curves, from the previous run. Since the adaptations are a spatial process, the whole model domain is subdivided in homogeneous sections regarding hydraulics and morphological behaviour. For a faster optimization, the adaptation of the parameters is made section wise. Additionally, a systematic variation was done, considering results from previous runs and the interaction between sections. The used approach can be considered as similar to evolutionary type calibration approaches, but using analytical links instead of random parameter changes.

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Running hydrodynamic models interactively allows both visual exploration and change of model state during simulation. One of the main characteristics of an interactive model is that it should provide immediate feedback to the user, for example respond to changes in model state or view settings. For this reason, such features are usually only available for models with a relatively small number of computational cells, which are used mainly for demonstration and educational purposes. It would be useful if interactive modeling would also work for models typically used in consultancy projects involving large scale simulations. This results in a number of technical challenges related to the combination of the model itself and the visualisation tools (scalability, implementation of an appropriate API for control and access to the internal state). While model parallelisation is increasingly addressed by the environmental modeling community, little effort has been spent on developing a high-performance interactive environment. What can we learn from other high-end visualisation domains such as 3D animation, gaming, virtual globes (Autodesk 3ds Max, Second Life, Google Earth) that also focus on efficient interaction with 3D environments? In these domains high efficiency is usually achieved by the use of computer graphics algorithms such as surface simplification depending on current view, distance to objects, and efficient caching of the aggregated representation of object meshes. We investigate how these algorithms can be re-used in the context of interactive hydrodynamic modeling without significant changes to the model code and allowing model operation on both multi-core CPU personal computers and high-performance computer clusters.

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This paper describes the formulation of a Multi-objective Pipe Smoothing Genetic Algorithm (MOPSGA) and its application to the least cost water distribution network design problem. Evolutionary Algorithms have been widely utilised for the optimisation of both theoretical and real-world non-linear optimisation problems, including water system design and maintenance problems. In this work we present a pipe smoothing based approach to the creation and mutation of chromosomes which utilises engineering expertise with the view to increasing the performance of the algorithm whilst promoting engineering feasibility within the population of solutions. MOPSGA is based upon the standard Non-dominated Sorting Genetic Algorithm-II (NSGA-II) and incorporates a modified population initialiser and mutation operator which directly targets elements of a network with the aim to increase network smoothness (in terms of progression from one diameter to the next) using network element awareness and an elementary heuristic. The pipe smoothing heuristic used in this algorithm is based upon a fundamental principle employed by water system engineers when designing water distribution pipe networks where the diameter of any pipe is never greater than the sum of the diameters of the pipes directly upstream resulting in the transition from large to small diameters from source to the extremities of the network. MOPSGA is assessed on a number of water distribution network benchmarks from the literature including some real-world based, large scale systems. The performance of MOPSGA is directly compared to that of NSGA-II with regard to solution quality, engineering feasibility (network smoothness) and computational efficiency. MOPSGA is shown to promote both engineering and hydraulic feasibility whilst attaining good infrastructure costs compared to NSGA-II.

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In this paper the architecture of an experimental multiparadigmatic programming environment is sketched, showing how its parts combine together with application modules in order to perform the integration of program modules written in different programming languages and paradigms. Adaptive automata are special self-modifying formal state machines used as a design and implementation tool in the representation of complex systems. Adaptive automata have been proven to have the same formal power as Turing Machines. Therefore, at least in theory, arbitrarily complex systems may be modeled with adaptive automata. The present work briefly introduces such formal tool and presents case studies showing how to use them in two very different situations: the first one, in the name management module of a multi-paradigmatic and multi-language programming environment, and the second one, in an application program implementing an adaptive automaton that accepts a context-sensitive language.

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Este trabalho discute a implementação da estratégia de postponement, um conceito que vem crescendo de importância nos últimos anos. Postponement é um conceito operacional que consiste em retardar a configuração final de produtos até que os pedidos dos consumidores sejam recebidos. Apesar da atratividade teórica e relevância do tema, pouco ainda se sabe sobre seu processo de implementação, especialmente no ambiente de negócio brasileiro. Este trabalho investigou em profundidade a implementação do postponement em cinco conceituadas empresas no Brasil procurando identificar os motivos que levaram seus respectivos executivos a adotarem tal estratégia, quais foram os agentes facilitadores e os obstáculos à implementação e, finalmente, até que ponto o postponement contribuiu para um aumento da competitividade.

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As primeiras regiões metropolitanas brasileiras foram instituídas de maneira vertical e autoritária como parte da estratégia de desenvolvimento nacional promovida pelo governo militar. Percebidas como instituições não-democráticas e rejeitadas como possível quarto ente federativo, as regiões metropolitanas, desde a Constituição de 1988, foram gradualmente esvaziadas dos seus propósitos originais. Em sua orfandade, os problemas socioeconômicos proliferaram e foram acentuados, e passaram a predominar relações intergovernamentais competitivas em vez de cooperativas. Um dos principais desafios enfrentados pelo modelo federalista brasileiro, em especial quando se trata destas regiões, está relacionado à necessidade de estabelecer maior cooperação e coordenação, tidas como imprescindíveis para garantir um relacionamento mais equilibrado entre os entes federativos, assim como para a efetiva implementação de políticas de enfrentamento das desigualdades e exclusão social nas aglomerações urbanas. Este trabalho analisa o Grande Recife Consórcio Metropolitano de Transportes (CMT), empresa pública multifederativa estabelecida em 2008 entre os governos municipais e estadual da Região Metropolitana de Recife (RMR). Responsável pelo planejamento, gestão e implementação compartilhada da política de transporte público coletivo na RMR, o Grande Recife se tornou realidade com a aprovação e regulamentação da Lei Federal nº 11.107 de 2005, conhecida como a Lei de Consórcios Públicos. O Grande Recife é uma experiência pioneira e inovadora, demonstrando que é possível encontrar uma maneira de superar conflitos e desafios comuns e, ao mesmo tempo, garantir a preservação da autonomia de cada ente, bem como os direitos cidadãos. Neste trabalho consideramos essa experiência de cooperação intergovernamental como um exemplo de multi-level governance (MLG), uma vez que é ilustrativa de um novo arranjo institucional democrático entre distintas esferas governamentais para a gestão compartilhada de um serviço público.

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Poverty in Brazil has been gradually reduced. Among the main reasons, there are public policies for universalization of rights. On the other hand, the municipalities' Human Development Index indicates scenarios of growing inequality. In other words, some regions, basically of rural character, were left behind in that process of development. In 2008, the “Territórios da Cidadania” (Territories of Citizenship) Program was launched by the federal government, under high expectations. It was proposed to develop those regions and to prioritize the arrival of ongoing federal public policies where they were most demanded. The program has shown an innovative arrangement which included dozens of ministries and other federal agencies, state governments, municipalities and collegialities to the palliative management and control of the territory. In this structure, both new and existing jurisdictions came to support the program coordination. This arrangement was classified as an example of multi-level governance, whose theory has been an efficient instrument to understand the intra- and intergovernmental relations under which the program took place. The program lasted only three years. In Vale do Ribeira Territory – SP, few community leaderships acknowledge it, although not having further information about its actions and effects. Against this background, the approach of this research aims to study the program coordination and governance structure (from Vale Territory, considered as the most local level, until the federal government), based on the hypothesis that, beyond the local contingencies in Vale do Ribeira, the layout and implementation of the Territories of Citizenship Program as they were formulated possess fundamental structural issues that hinder its goals of reducing poverty and inequality through promoting the development of the territory. Complementing the research, its specific goal was to raise the program layout and background in order to understand how the relations, predicted or not in its structure, were formulated and how they were developed, with special attention to Vale do Ribeira-SP. Generally speaking, it was concluded that the coordination and governance arrangement of the Territories of Citizenship Program failed for not having developed qualified solutions to deal with the challenges of the federalist Brazilian structure, party politics, sectorized public actions, or even the territory contingencies and specificities. The complexity of the program, the poverty problem proposed to be faced, and the territorial strategy of development charged a high cost of coordination, which was not accomplished by the proposal of centralization in the federal government with internal decentralization of the coordination. As the presidency changed in 2011, the program could not present results that were able to justify the arguments for its continuation, therefore it was paralyzed, lost its priority status, and the resources previously invested were redirected.

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On Rio Grande do Norte northern coast the process of sediment transport are intensely controlled by wind and sea (waves and currents) action, causing erosion and shoreline morphological instability. Due to the importance of such coastal zone it was realized the multi-spectral mapping and physical-chemical characterization of mudflats and mangroves aiming to support the mitigating actions related to the containment of the erosive process on the oil fields of Macau and Serra installed at the study area. The multi-spectral bands of 2000 and 2008 LANDSAT 5 TM images were submitted on the several digital processing steps and RGB color compositions integrating spectral bands and Principal Components. Such processing methodology was important to the mapping of different units on surface, together with field works. It was possible to make an analogy of the spectral characteristics of wetlands with vegetations areas (mangrove), showing the possibility to make a restoration of this area, contributing with the environmental monitoring of that ecosystem. The maps of several units were integrated in GIS environment at 1:60,000 scale, including the classification of features according to the presence or absence of vegetation cover. Thus, the strategy of methodology established that there are 10.13 km2 at least of sandy-muddy and of these approximately 0.89 km2 with the possibility to be used in a reforestation of typical flora of mangrove. The physical-chemical characterization showed areas with potential to introduce local species of mangrove and they had a pH above neutral with a mean of 8.4. The characteristic particle size is sand in the fine fractions, the high levels of carbonate, organic matter and major and trace element in general are concentrated where the sediment had the less particles size, showing the high correlation that those elements have with smaller particles of sediment. The application of that methodological strategy is relevant to the better understanding of features behavior and physical-chemical data of sediment samples collected on field allow the analysis of efficiency/capability of sandy-muddy to reforestation with local mangrove species for mitigation of the erosive action and coastal processes on the areas occupied by the oil industry

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In Brazil and around the world, oil companies are looking for, and expected development of new technologies and processes that can increase the oil recovery factor in mature reservoirs, in a simple and inexpensive way. So, the latest research has developed a new process called Gas Assisted Gravity Drainage (GAGD) which was classified as a gas injection IOR. The process, which is undergoing pilot testing in the field, is being extensively studied through physical scale models and core-floods laboratory, due to high oil recoveries in relation to other gas injection IOR. This process consists of injecting gas at the top of a reservoir through horizontal or vertical injector wells and displacing the oil, taking advantage of natural gravity segregation of fluids, to a horizontal producer well placed at the bottom of the reservoir. To study this process it was modeled a homogeneous reservoir and a model of multi-component fluid with characteristics similar to light oil Brazilian fields through a compositional simulator, to optimize the operational parameters. The model of the process was simulated in GEM (CMG, 2009.10). The operational parameters studied were the gas injection rate, the type of gas injection, the location of the injector and production well. We also studied the presence of water drive in the process. The results showed that the maximum vertical spacing between the two wells, caused the maximum recovery of oil in GAGD. Also, it was found that the largest flow injection, it obtained the largest recovery factors. This parameter controls the speed of the front of the gas injected and determined if the gravitational force dominates or not the process in the recovery of oil. Natural gas had better performance than CO2 and that the presence of aquifer in the reservoir was less influential in the process. In economic analysis found that by injecting natural gas is obtained more economically beneficial than CO2

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The objective of this dissertation is to propose a Multi Criteria Decision Aid Model to be used by the costumers of the travel agencies and help them to choose the best package travel. The main objective is to contribute for the simplification of the travel package decision choice from the identification of the models of values and preference of the customers and applying them to the existing package. It is used the Analytic Hierarchy Process (AHP) method to structuralize a decision hierarchic model composed by six criteria (package cost, hotel category, security of the city, travel time, direct flight and position in ranking of the 10 most visited destination) and five real alternatives of packages for a holiday of three days created from travel agency data. The decision analysis was realized for the choice of a travel package by a group composed by two couples that regularly travels together, to which was asked to do a pairwise judgment of the criteria and the alternatives. The mains results show that, although been a group that travels together, there are different models of values in the weights of the criteria and a certain convergence in the scales of preferences of the alternatives in the criteria. It was not pointed a dominant alternative for all the members of the group separately, but an analysis of a total utility of the group shows a classification and an order of the travel packages and an alternative clearly in front of the others. The sensitivity analysis revels that there are changes in the ranking, but the two alternatives best classified in the normal analysis are the same ones in the sensitivity analysis, although with the positions changed. The analysis also led to a simplification of the process with the exclusion of alternatives dominated for the others ones. As main conclusion, it is evaluated that the model and method suggested allow a simplification of the decision process in the choice of travel packages

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We propose a new approach to reduction and abstraction of visual information for robotics vision applications. Basically, we propose to use a multi-resolution representation in combination with a moving fovea for reducing the amount of information from an image. We introduce the mathematical formalization of the moving fovea approach and mapping functions that help to use this model. Two indexes (resolution and cost) are proposed that can be useful to choose the proposed model variables. With this new theoretical approach, it is possible to apply several filters, to calculate disparity and to obtain motion analysis in real time (less than 33ms to process an image pair at a notebook AMD Turion Dual Core 2GHz). As the main result, most of time, the moving fovea allows the robot not to perform physical motion of its robotics devices to keep a possible region of interest visible in both images. We validate the proposed model with experimental results

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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 work presents the application of a multiobjective evolutionary algorithm (MOEA) for optimal power flow (OPF) solution. The OPF is modeled as a constrained nonlinear optimization problem, non-convex of large-scale, with continuous and discrete variables. The violated inequality constraints are treated as objective function of the problem. This strategy allows attending the physical and operational restrictions without compromise the quality of the found solutions. The developed MOEA is based on the theory of Pareto and employs a diversity-preserving mechanism to overcome the premature convergence of algorithm and local optimal solutions. Fuzzy set theory is employed to extract the best compromises of the Pareto set. Results for the IEEE-30, RTS-96 and IEEE-354 test systems are presents to validate the efficiency of proposed model and solution technique.

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Although some individual techniques of supervised Machine Learning (ML), also known as classifiers, or algorithms of classification, to supply solutions that, most of the time, are considered efficient, have experimental results gotten with the use of large sets of pattern and/or that they have a expressive amount of irrelevant data or incomplete characteristic, that show a decrease in the efficiency of the precision of these techniques. In other words, such techniques can t do an recognition of patterns of an efficient form in complex problems. With the intention to get better performance and efficiency of these ML techniques, were thought about the idea to using some types of LM algorithms work jointly, thus origin to the term Multi-Classifier System (MCS). The MCS s presents, as component, different of LM algorithms, called of base classifiers, and realized a combination of results gotten for these algorithms to reach the final result. So that the MCS has a better performance that the base classifiers, the results gotten for each base classifier must present an certain diversity, in other words, a difference between the results gotten for each classifier that compose the system. It can be said that it does not make signification to have MCS s whose base classifiers have identical answers to the sames patterns. Although the MCS s present better results that the individually systems, has always the search to improve the results gotten for this type of system. Aim at this improvement and a better consistency in the results, as well as a larger diversity of the classifiers of a MCS, comes being recently searched methodologies that present as characteristic the use of weights, or confidence values. These weights can describe the importance that certain classifier supplied when associating with each pattern to a determined class. These weights still are used, in associate with the exits of the classifiers, during the process of recognition (use) of the MCS s. Exist different ways of calculating these weights and can be divided in two categories: the static weights and the dynamic weights. The first category of weights is characterizes for not having the modification of its values during the classification process, different it occurs with the second category, where the values suffers modifications during the classification process. In this work an analysis will be made to verify if the use of the weights, statics as much as dynamics, they can increase the perfomance of the MCS s in comparison with the individually systems. Moreover, will be made an analysis in the diversity gotten for the MCS s, for this mode verify if it has some relation between the use of the weights in the MCS s with different levels of diversity