895 resultados para Spatial analysis


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As a newly invented parallel kinematic machine (PKM), Exechon has attracted intensive attention from both academic and industrial fields due to its conceptual high performance. Nevertheless, the dynamic behaviors of Exechon PKM have not been thoroughly investigated because of its structural and kinematic complexities. To identify the dynamic characteristics of Exechon PKM, an elastodynamic model is proposed with the substructure synthesis technique in this paper. The Exechon PKM is divided into a moving platform subsystem, a fixed base subsystem and three limb subsystems according to its structural features. Differential equations of motion for the limb subsystem are derived through finite element (FE) formulations by modeling the complex limb structure as a spatial beam with corresponding geometric cross sections. Meanwhile, revolute, universal, and spherical joints are simplified into virtual lumped springs associated with equivalent stiffnesses and mass at their geometric centers. Differential equations of motion for the moving platform are derived with Newton's second law after treating the platform as a rigid body due to its comparatively high rigidity. After introducing the deformation compatibility conditions between the platform and the limbs, governing differential equations of motion for Exechon PKM are derived. The solution to characteristic equations leads to natural frequencies and corresponding modal shapes of the PKM at any typical configuration. In order to predict the dynamic behaviors in a quick manner, an algorithm is proposed to numerically compute the distributions of natural frequencies throughout the workspace. Simulation results reveal that the lower natural frequencies are strongly position-dependent and distributed axial-symmetrically due to the structure symmetry of the limbs. At the last stage, a parametric analysis is carried out to identify the effects of structural, dimensional, and stiffness parameters on the system's dynamic characteristics with the purpose of providing useful information for optimal design and performance improvement of the Exechon PKM. The elastodynamic modeling methodology and dynamic analysis procedure can be well extended to other overconstrained PKMs with minor modifications.

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The problem of detecting spatially-coherent groups of data that exhibit anomalous behavior has started to attract attention due to applications across areas such as epidemic analysis and weather forecasting. Earlier efforts from the data mining community have largely focused on finding outliers, individual data objects that display deviant behavior. Such point-based methods are not easy to extend to find groups of data that exhibit anomalous behavior. Scan Statistics are methods from the statistics community that have considered the problem of identifying regions where data objects exhibit a behavior that is atypical of the general dataset. The spatial scan statistic and methods that build upon it mostly adopt the framework of defining a character for regions (e.g., circular or elliptical) of objects and repeatedly sampling regions of such character followed by applying a statistical test for anomaly detection. In the past decade, there have been efforts from the statistics community to enhance efficiency of scan statstics as well as to enable discovery of arbitrarily shaped anomalous regions. On the other hand, the data mining community has started to look at determining anomalous regions that have behavior divergent from their neighborhood.In this chapter,we survey the space of techniques for detecting anomalous regions on spatial data from across the data mining and statistics communities while outlining connections to well-studied problems in clustering and image segmentation. We analyze the techniques systematically by categorizing them appropriately to provide a structured birds eye view of the work on anomalous region detection;we hope that this would encourage better cross-pollination of ideas across communities to help advance the frontier in anomaly detection.

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Perfect information is seldom available to man or machines due to uncertainties inherent in real world problems. Uncertainties in geographic information systems (GIS) stem from either vague/ambiguous or imprecise/inaccurate/incomplete information and it is necessary for GIS to develop tools and techniques to manage these uncertainties. There is a widespread agreement in the GIS community that although GIS has the potential to support a wide range of spatial data analysis problems, this potential is often hindered by the lack of consistency and uniformity. Uncertainties come in many shapes and forms, and processing uncertain spatial data requires a practical taxonomy to aid decision makers in choosing the most suitable data modeling and analysis method. In this paper, we: (1) review important developments in handling uncertainties when working with spatial data and GIS applications; (2) propose a taxonomy of models for dealing with uncertainties in GIS; and (3) identify current challenges and future research directions in spatial data analysis and GIS for managing uncertainties.

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Marine protected areas (MPAs) have been widely proposed for conservation purposes and as a tool for fisheries management. The Arrábida Marine Park is the first MPA in continental Portugal having a management plan, fully implemented since 2009. The main objective of this study was to evaluate the effect of protection measures on rocky reef fish assemblages and target invertebrates through before-after and control-effect (no-take vs. fished areas) underwater visual surveys and analysis of landings trends. Second, we used surveys before, during and after implementation of the management plan to understand fishers‟ preferences for fishing grounds and adaptation to the new rules, and evaluated the reserve effect through analysis of both ecological responses and fishing effort density. Third, we identified the main oceanographic drivers influencing the structure of reef fish assemblages and predicted the community structure for the last 50 years, in light of climatic change. Overall results suggest positive responses in biomass but not yet in numbers of some commercial species, with no effects on non-target species. The reserve effect is reinforced by the increase in landings of commercial species, despite increased fishing effort density in some areas, especially with octopus traps. Fishing grounds are mainly chosen based on the distribution of target species and associated habitats, but distance to port, weather conditions and safety also influence fishers‟ choices. Moreover, different fisheries respond differently to the protection measures, and within each fishery, individual fishers show distinct strategies, with some operating in a broader area whereas others keep preferred territories. Our results also show that wind stress and temperature are the main oceanographic drivers for rocky reef fish assemblages, with tropicalization of assemblages and polewards movements of species over the last 50 years consistent with temperature trends. We believe this study provides significant lessons for marine conservation and management of coastal systems.

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Tese de doutoramento, Ciências Biomédicas, Universidade do Algarve, Departamento de Ciências Biomédicas e Medicina, 2014

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Dissertação de Mestrado, Biologia Marinha, Faculdade de Ciências e Tecnologia, Universidade do Algarve, 2015

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Detailed surveys of depth and velocity are undertaken to describe hydro-ecological status of rivers. Fieldwork for these surveys is time consuming and expensive. This paper aims to describe the methodology applied in order to determine the most suitable depth sampling strategy for effective field data collection and river representation in time and space at the Leigh Brook river site, Worcester, UK. The accuracy of three different sampling strategies for predicting depth at non-measured points has been compared and the mesohabitats that better characterise depth changes due to variations in discharge have been identified. The results show that depth changes due to discharge change are mainly located at shallow and deep glide mesohabitat types. The analysis for the comparison of sampling strategies indicates that grid sampling strategies give better results than regular transects. Since the results also show that higher errors in predictions are obtained in the deepest areas, higher sampling densities should be applied in these locations.

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Senior thesis written for Oceanography 445

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Senior thesis written for Oceanography 445

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Senior thesis written for Oceanography 445

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Energy saving, reduction of greenhouse gasses and increased use of renewables are key policies to achieve the European 2020 targets. In particular, distributed renewable energy sources, integrated with spatial planning, require novel methods to optimise supply and demand. In contrast with large scale wind turbines, small and medium wind turbines (SMWTs) have a less extensive impact on the use of space and the power system, nevertheless, a significant spatial footprint is still present and the need for good spatial planning is a necessity. To optimise the location of SMWTs, detailed knowledge of the spatial distribution of the average wind speed is essential, hence, in this article, wind measurements and roughness maps were used to create a reliable annual mean wind speed map of Flanders at 10 m above the Earth’s surface. Via roughness transformation, the surface wind speed measurements were converted into meso- and macroscale wind data. The data were further processed by using seven different spatial interpolation methods in order to develop regional wind resource maps. Based on statistical analysis, it was found that the transformation into mesoscale wind, in combination with Simple Kriging, was the most adequate method to create reliable maps for decision-making on optimal production sites for SMWTs in Flanders.

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Recent research on WW1 shows that incidents of fraternization across enemy lines took place regularly. However, fraternization remains a taboo in many contexts. The fact that the 2005 film Joyeux Noel by Christian Caron, which explicitly deals with the subject, encountered resistance from the authorities, is an indication of the kind of difficulty associated with the issue. I am drawing my inspiration from the way fraternizations are depicted in the film and in the literature in order to explore the concept of spatial justice. I define spatial justice as the question that emerges when a body desires to occupy the same space at the same time as another body. Defined like this, the question of spatial justice opens up in the dread of No Man’s Land and in particular the exchange of affects, objects and narratives that went on during fraternizations. I trace the movement of spatial justice as one of withdrawal from the asphyxiating atmosphere of the war and the propaganda machine. This withdrawal is not one of unpatriotic stance but of a courageous and difficult detachment from the supposed legality of the war that could only function on the basis of hate and demonization. While fraternizations did not end the war, they allowed for the possibility of spatial justice to emerge, as an opportunity to reorient the space and the bodies within.

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Beyond the classical statistical approaches (determination of basic statistics, regression analysis, ANOVA, etc.) a new set of applications of different statistical techniques has increasingly gained relevance in the analysis, processing and interpretation of data concerning the characteristics of forest soils. This is possible to be seen in some of the recent publications in the context of Multivariate Statistics. These new methods require additional care that is not always included or refered in some approaches. In the particular case of geostatistical data applications it is necessary, besides to geo-reference all the data acquisition, to collect the samples in regular grids and in sufficient quantity so that the variograms can reflect the spatial distribution of soil properties in a representative manner. In the case of the great majority of Multivariate Statistics techniques (Principal Component Analysis, Correspondence Analysis, Cluster Analysis, etc.) despite the fact they do not require in most cases the assumption of normal distribution, they however need a proper and rigorous strategy for its utilization. In this work, some reflections about these methodologies and, in particular, about the main constraints that often occur during the information collecting process and about the various linking possibilities of these different techniques will be presented. At the end, illustrations of some particular cases of the applications of these statistical methods will also be presented.

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In this study, the concentration probability distributions of 82 pharmaceutical compounds detected in the effluents of 179 European wastewater treatment plants were computed and inserted into a multimedia fate model. The comparative ecotoxicological impact of the direct emission of these compounds from wastewater treatment plants on freshwater ecosystems, based on a potentially affected fraction (PAF) of species approach, was assessed to rank compounds based on priority. As many pharmaceuticals are acids or bases, the multimedia fate model accounts for regressions to estimate pH-dependent fate parameters. An uncertainty analysis was performed by means of Monte Carlo analysis, which included the uncertainty of fate and ecotoxicity model input variables, as well as the spatial variability of landscape characteristics on the European continental scale. Several pharmaceutical compounds were identified as being of greatest concern, including 7 analgesics/anti-inflammatories, 3 β-blockers, 3 psychiatric drugs, and 1 each of 6 other therapeutic classes. The fate and impact modelling relied extensively on estimated data, given that most of these compounds have little or no experimental fate or ecotoxicity data available, as well as a limited reported occurrence in effluents. The contribution of estimated model input variables to the variance of freshwater ecotoxicity impact, as well as the lack of experimental abiotic degradation data for most compounds, helped in establishing priorities for further testing. Generally, the effluent concentration and the ecotoxicity effect factor were the model input variables with the most significant effect on the uncertainty of output results.