19 resultados para tuprolog estensione android input grafico console

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Metamodels have proven be very useful when it comes to reducing the computational requirements of Evolutionary Algorithm-based optimization by acting as quick-solving surrogates for slow-solving fitness functions. The relationship between metamodel scope and objective function varies between applications, that is, in some cases the metamodel acts as a surrogate for the whole fitness function, whereas in other cases it replaces only a component of the fitness function. This paper presents a formalized qualitative process to evaluate a fitness function to determine the most suitable metamodel scope so as to increase the likelihood of calibrating a high-fidelity metamodel and hence obtain good optimization results in a reasonable amount of time. The process is applied to the risk-based optimization of water distribution systems; a very computationally-intensive problem for real-world systems. The process is validated with a simple case study (modified New York Tunnels) and the power of metamodelling is demonstrated on a real-world case study (Pacific City) with a computational speed-up of several orders of magnitude.

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This study subdivides the Potter Cove, King George Island, Antarctica, into seafloor regions using multivariate statistical methods. These regions are categories used for comparing, contrasting and quantifying biogeochemical processes and biodiversity between ocean regions geographically but also regions under development within the scope of global change. The division obtained is characterized by the dominating components and interpreted in terms of ruling environmental conditions. The analysis includes in total 42 different environmental variables, interpolated based on samples taken during Australian summer seasons 2010/2011 and 2011/2012. The statistical errors of several interpolation methods (e.g. IDW, Indicator, Ordinary and Co-Kriging) with changing settings have been compared and the most reasonable method has been applied. The multivariate mathematical procedures used are regionalized classification via k means cluster analysis, canonical-correlation analysis and multidimensional scaling. Canonical-correlation analysis identifies the influencing factors in the different parts of the cove. Several methods for the identification of the optimum number of clusters have been tested and 4, 7, 10 as well as 12 were identified as reasonable numbers for clustering the Potter Cove. Especially the results of 10 and 12 clusters identify marine-influenced regions which can be clearly separated from those determined by the geological catchment area and the ones dominated by river discharge.

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Many marine radiogenic isotope records show both spatial and temporal variations, reflecting both the degree of mixing of distinct sources in the oceans and changes in the distribution of chemical weathering on the continents. However, changes in weathering and transport processes may themselves affect the composition of radiogenic isotopes released into seawater. The provenance of physically weathered material in the Labrador Sea, constrained through the use of Ar-Ar ages of individual detrital minerals, has been used to estimate the relative contributions of chemically weathered terranes releasing radiogenic isotopes into the Labrador Sea. A simple box-model approach for balancing observed Nd-isotope variations has been used to constrain the relative importance of localised input in the Labrador Sea, and the subsequent mixing of Labrador Sea Water into North Atlantic Deep-Water. The long-term pattern of erosion and deep-water formation around the North Atlantic seems to have been a relatively stable feature since 1.5 Ma, although there has been a dramatic shift in the nature of physical and chemical weathering affecting the release of Hf and Pb isotopes. The modelled Nd isotopes imply a relative decrease in water mass advection into the Labrador Sea between 2.4 and 1.5 Ma, accompanied by a decrease in the rate of overturning, possibly caused by an increased freshwater input into the Labrador Sea.

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There has been a marked decline in the summer extent of Arctic sea ice over the past few decades. Data from autonomous ice mass-balance buoys can enhance our understanding of this decline. These buoys monitor changes in snow deposition and ablation, ice growth, and ice surface and bottom melt. Results from the summer of 2008 showed considerable large-scale spatial variability in the amount of surface and bottom melt. Small amounts of melting were observed north of Greenland, while melting in the southern Beaufort Sea was quite large. Comparison of net solar heat input to the ice and heat required for surface ablation showed only modest correlation. However, there was a strong correlation between solar heat input to the ocean and bottom melting. As the ice concentration in the Beaufort Sea region decreased, there was an increase in solar heat to the ocean and an increase in bottom melting.

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Radiolarian-based paleoceanographic reconstructions generally use the abundance of selected radiolarian species. However, the recent focus on the opal flux and the development of isotope measurements in biogenic opal and the organic matter embedded in it demands a better knowledge of the origin of the opal. We present here an estimation of the opal content of the skeleton of 63 radiolarian species from two sites in the Southern Ocean. The skeletons are modelled as associations of simple geometrical shapes, and the volume thus obtained is combined with opal density to obtain the amount of opal. These data are, thus, used to determine the most important opal carriers in the radiolarian assemblage in both cores.