983 resultados para Adaptive strategy


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Changes in the environment, including increased environmental complexity, require military supply units to employ a more adaptive strategy in order to enhance military agility. We extend the Lumpkin and Dess (1996) model and develop propositions that explore the interrelationships between/amongst entrepreneurial orientation (EO); opportunity recognition, evaluation and exploitation; environmental and organizational factors; and organizational performance. We propose that the innovativeness, proactiveness, and risk-taking dimensions of EO are of primary importance in identifying adaptive solutions and that these relationships are moderated by environmental factors. The autonomy and competitive aggressiveness dimensions of EO are important in implementing solutions as adaptive strategies, especially in a military context, and these relationships are moderated by organizational factors. This chapter extends existing theory developed primarily for the civilian sector to the military. Military organizations are more rigid hierarchical structures, and have different measures of performance. At an applied level, this research provides insights for military commanders that can potentially enhance agility and adaptability.

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Electricity markets are complex environments with very particular characteristics. MASCEM is a market simulator developed to allow deep studies of the interactions between the players that take part in the electricity market negotiations. This paper presents a new proposal for the definition of MASCEM players’ strategies to negotiate in the market. The proposed methodology is multiagent based, using reinforcement learning algorithms to provide players with the capabilities to perceive the changes in the environment, while adapting their bids formulation according to their needs, using a set of different techniques that are at their disposal.

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The decision of how far to disperse from the natal territory has profound and long-lasting consequences for young animals, yet the optimal dispersal behavior often depends on environmental factors that are difficult or impossible to assess by inexperienced juveniles. Natural selection thus favors mechanisms that allow the adaptive and flexible adjustment of the offspring's dispersal behavior by their parents via either paternal or maternal effects. Here we show that different dispersal strategies maximize the reproductive success of young great tits (Parus major) originating from a parasite-infested or a parasite-free nest and demonstrate that differential transfer of maternal yolk androgens in response to parasitism can result in a modification of the offspring's dispersal behavior that appears adaptive. It demonstrates that prenatal maternal effects are an important yet so far neglected determinant of natal dispersal and highlights the potential importance of maternal effects in mediating coevolutionary processes in host-parasite systems.

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The solutions to cope with new challenges that societies have to face nowadays involve providing smarter daily systems. To achieve this, technology has to evolve and leverage physical systems automatic interactions, with less human intervention. Technological paradigms like Internet of Things (IoT) and Cyber-Physical Systems (CPS) are providing reference models, architectures, approaches and tools that are to support cross-domain solutions. Thus, CPS based solutions will be applied in different application domains like e-Health, Smart Grid, Smart Transportation and so on, to assure the expected response from a complex system that relies on the smooth interaction and cooperation of diverse networked physical systems. The Wireless Sensors Networks (WSN) are a well-known wireless technology that are part of large CPS. The WSN aims at monitoring a physical system, object, (e.g., the environmental condition of a cargo container), and relaying data to the targeted processing element. The WSN communication reliability, as well as a restrained energy consumption, are expected features in a WSN. This paper shows the results obtained in a real WSN deployment, based on SunSPOT nodes, which carries out a fuzzy based control strategy to improve energy consumption while keeping communication reliability and computational resources usage among boundaries.

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For evolving populations of replicators, there is much evidence that the effect of mutations on fitness depends on the degree of adaptation to the selective pressures at play. In optimized populations, most mutations have deleterious effects, such that low mutation rates are favoured. In contrast to this, in populations thriving in changing environments a larger fraction of mutations have beneficial effects, providing the diversity necessary to adapt to new conditions. What is more, non-adapted populations occasionally benefit from an increase in the mutation rate. Therefore, there is no optimal universal value of the mutation rate and species attempt to adjust it to their momentary adaptive needs. In this work we have used stationary populations of RNA molecules evolving in silico to investigate the relationship between the degree of adaptation of an optimized population and the value of the mutation rate promoting maximal adaptation in a short time to a new selective pressure. Our results show that this value can significantly differ from the optimal value at mutation-selection equilibrium, being strongly influenced by the structure of the population when the adaptive process begins. In the short-term, highly optimized populations containing little variability respond better to environmental changes upon an increase of the mutation rate, whereas populations with a lower degree of optimization but higher variability benefit from reducing the mutation rate to adapt rapidly. These findings show a good agreement with the behaviour exhibited by actual organisms that replicate their genomes under broadly different mutation rates. © 2010 Stich et al.

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Tuning compilations is the process of adjusting the values of a compiler options to improve some features of the final application. In this paper, a strategy based on the use of a genetic algorithm and a multi-objective scheme is proposed to deal with this task. Unlike previous works, we try to take advantage of the knowledge of this domain to provide a problem-specific genetic operation that improves both the speed of convergence and the quality of the results. The evaluation of the strategy is carried out by means of a case of study aimed to improve the performance of the well-known web server Apache. Experimental results show that a 7.5% of overall improvement can be achieved. Furthermore, the adaptive approach has shown an ability to markedly speed-up the convergence of the original strategy.

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A residual-based strategy to estimate the local truncation error in a finite volume framework for steady compressible flows is proposed. This estimator, referred to as the -parameter, is derived from the imbalance arising from the use of an exact operator on the numerical solution for conservation laws. The behaviour of the residual estimator for linear and non-linear hyperbolic problems is systematically analysed. The relationship of the residual to the global error is also studied. The -parameter is used to derive a target length scale and consequently devise a suitable criterion for refinement/derefinement. This strategy, devoid of any user-defined parameters, is validated using two standard test cases involving smooth flows. A hybrid adaptive strategy based on both the error indicators and the -parameter, for flows involving shocks is also developed. Numerical studies on several compressible flow cases show that the adaptive algorithm performs excellently well in both two and three dimensions.

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Algorithms for adaptive mesh refinement using a residual error estimator are proposed for fluid flow problems in a finite volume framework. The residual error estimator, referred to as the R-parameter is used to derive refinement and coarsening criteria for the adaptive algorithms. An adaptive strategy based on the R-parameter is proposed for continuous flows, while a hybrid adaptive algorithm employing a combination of error indicators and the R-parameter is developed for discontinuous flows. Numerical experiments for inviscid and viscous flows on different grid topologies demonstrate the effectiveness of the proposed algorithms on arbitrary polygonal grids.

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The accurate solution of 3D full-wave Method of Moments (MoM) on an arbitrary mesh of a package-board structure does not guarantee accuracy, since the discretizations may not be fine enough to capture rapid spatial changes in the solution variable. At the same time, uniform over-meshing on the entire structure generates large number of solution variables and therefore requires an unnecessarily large matrix solution. In this work, a suitable refinement criterion for MoM based electromagnetic package-board extraction is proposed and the advantages of the adaptive strategy are demonstrated from both accuracy and speed perspectives.

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3-D full-wave method of moments (MoM) based electromagnetic analysis is a popular means toward accurate solution of Maxwell's equations. The time and memory bottlenecks associated with such a solution have been addressed over the last two decades by linear complexity fast solver algorithms. However, the accurate solution of 3-D full-wave MoM on an arbitrary mesh of a package-board structure does not guarantee accuracy, since the discretization may not be fine enough to capture spatial changes in the solution variable. At the same time, uniform over-meshing on the entire structure generates a large number of solution variables and therefore requires an unnecessarily large matrix solution. In this paper, different refinement criteria are studied in an adaptive mesh refinement platform. Consequently, the most suitable conductor mesh refinement criterion for MoM-based electromagnetic package-board extraction is identified and the advantages of this adaptive strategy are demonstrated from both accuracy and speed perspectives. The results are also compared with those of the recently reported integral equation-based h-refinement strategy. Finally, a new methodology to expedite each adaptive refinement pass is proposed.

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Finite element hp-adaptivity is a technology that allows for very accurate numerical solutions. When applied to open region problems such as radar cross section prediction or antenna analysis, a mesh truncation method needs to be used. This paper compares the following mesh truncation methods in the context of hp-adaptive methods: Infinite Elements, Perfectly Matched Layers and an iterative boundary element based methodology. These methods have been selected because they are exact at the continuous level (a desirable feature required by the extreme accuracy delivered by the hp-adaptive strategy) and they are easy to integrate with the logic of hp-adaptivity. The comparison is mainly based on the number of degrees of freedom needed for each method to achieve a given level of accuracy. Computational times are also included. Two-dimensional examples are used, but the conclusions directly extrapolated to the three dimensional case.

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We propose an adaptive mesh refinement strategy based on exploiting a combination of a pre-processing mesh re-distribution algorithm employing a harmonic mapping technique, and standard (isotropic) mesh subdivision for discontinuous Galerkin approximations of advection-diffusion problems. Numerical experiments indicate that the resulting adaptive strategy can efficiently reduce the computed discretization error by clustering the nodes in the computational mesh where the analytical solution undergoes rapid variation.

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The Arctic peoples are currently faced with the challenge of adapting to climate change. Adaptive strategies have been central for the survival of the Northern communities also in the past. This doctoral dissertation is a comparative study of how two Northern societies, the Faroe Islands and Greenland, have responded to challenges caused by the interplay of environmental, political and socio-economic changes. Its main objective is to describe the characteristics of respective adaptive strategies developed in the two societies and to show which connections exist between adaptation and the development of the settlement patterns. This study is based on document analysis, supported by an analysis of demographic and economic statistics. For the field work, the empirical method of landscape-reading was applied. A narrative approach was used to explain interrelations between adaptive strategies and societal developments in the Faroe Islands and Greenland. Maps illustrating development and changes in settlement patterns in different time periods are central for this study because they illustrate the impacts of adaptation on settlement development. The results of this dissertation show that people in the Faroe Islands and Greenland have consciously developed their settlements and used this as an adaptive strategy: different types of settlements were established depending on which kind of resource base was available. Strong dependency on a single resource is likely to increase the probability that settlement development was impacted by it. The interrelation of natural resource use and settlement pattern development has weakened in the Faroe Islands and Greenland from the mid-1900s. Since then, the importance of the government settlement policies has become pronounced and the existing settlement pattern, including settlements without prospects for genuine economic viability, has been preserved. Currently, the Northern communities are increasingly dependent on worldwide developments. In the light of this study, the communities can respond to challenges of globalization and climate change and develop new kind of adaptive strategies, such as diversification of their economic activities. This dissertation shows that it is important to extend studies about community adaptation in the High North to consider the overall development of the Northern settlement patterns.

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The utilization of mixtures of glucose and sucrose at nonlimiting concentrations was studied in batch cultures of two common thermophilic fungi, Thermomyces lanuginosus and Penicilium duponti. The sucrose-utilizing enzymes (sucrose permease and invertase) in both fungi were inducible. Both sugars were used concurrently,regardless of their relative proportion in the mixture. At the optimal growth temperature (50C), T.lanuginosus utilized sucrose earlier than it did glucose, but at a suboptimal growth temperature (30°C) the two sugars were utilized at nearly comparable rates. The coutilization of the two sugars was most likely possible because (i) invertase was insensitive to catabolite repression by glucose, (ii) the activity and affinity of the glucose transport system were lowered when sucrose was included in the growth medium, and (iii) the activity of the glucose uptake system was also subject to repression by high concentrations of glucose itself. The concurrent utilization of the available carbon sources by thermophilic fungi might be an adaptive strategy for opportunistic growth in nature under conditions of low nutrient availability and thermal fluctuations in the environment.