849 resultados para Density-based Scanning Algorithm


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This paper deals with approaches for sparse matrix substitutions using vector processing. Many publications have used the W-matrix method to solve the forward/backward substitutions on vector computer. Recently a different approach has been presented using dependency-based substitution algorithm (DBSA). In this paper the focus is on new algorithms able to explore the sparsity of the vectors. The efficiency is tested using linear systems from power systems with 118, 320, 725 and 1729 buses. The tests were performed on a CRAY Y MP2E/232. The speedups for a fast-forward/fast-backward using a 1729-bus system are near 19 and 14 for real and complex arithmetic operations, respectively. When forward/backward is employed the speedups are about 8 and 6 to perform the same simulations.

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Spatial sampling designs used to characterize the spatial variability of soil attributes are crucial for science studies. Sample planning for the interpolation of a regionalized variable may use several criteria, which could be best selected from an estimated semivariogram from a previously established grid. The objective of this study was to optimize the procedure for scaled semivariogram use to plan soil sampling in sugarcane fields in the Alfisol and Oxisol regions of Jaboticabal Town in So Paulo State, Brazil. A scaled semivariogram for several soil chemical attributes was estimated from the data obtained from two grids positioned on a sugarcane field area, sampled at a depth of 0.0-0.5 m. The research showed that regular grids with uniform intervals did not express the real spatial variability of the soil attributes of Oxisols and Alfisols in the study area. The calculated final sampling density based on the scaled parameters of the semivariogram was one sample for each 2 ha in Area 1 (convex landscape) and one sample for each 1 ha in Area 2 (linear landscape), as indicated by SANOS 0.1 software. The combined use of the simulation programs and scaled semivariograms can be used to define sampling points. These results may help in soil fertility mapping and thereby improve nutrient management in sugarcane crops.

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Image categorization by means of bag of visual words has received increasing attention by the image processing and vision communities in the last years. In these approaches, each image is represented by invariant points of interest which are mapped to a Hilbert Space representing a visual dictionary which aims at comprising the most discriminative features in a set of images. Notwithstanding, the main problem of such approaches is to find a compact and representative dictionary. Finding such representative dictionary automatically with no user intervention is an even more difficult task. In this paper, we propose a method to automatically find such dictionary by employing a recent developed graph-based clustering algorithm called Optimum-Path Forest, which does not make any assumption about the visual dictionary's size and is more efficient and effective than the state-of-the-art techniques used for dictionary generation. © 2012 IEEE.

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Na região amazônica, algumas indústrias despejam cobre nos corpos receptores que, em elevadas concentrações, é tóxico para os seres vivos. A remoção de cobre de efluentes industriais é realizada por diversos processos como a adsorção. Neste trabalho mostrou-se o resultado da adsorção de cobre (II) em carvão ativado de caroço de buriti carbonizado a 400 °C e ativado a 900 °C. O carvão ativado foi caracterizado em termos de área específica, tamanho dos poros, densidades aparente e real, porosidade, microscopia eletrônica de varredura, conteúdo de cinzas, pH, umidade, carbono fixo e grupos funcionais de superfície. O estudo de equilíbrio de adsorção avaliou a influência do diâmetro das partículas do carvão, do tempo de contato adsorvente/adsorbato, do pH e da concentração inicial da solução de cobre (II) sobre a remoção de cobre (II). Com base nos resultados, concluiu-se que há uma maior eficiência de remoção de cobre (II) para diâmetro < 0,595 mm, tempo de contato de 300 minutos, pH 4,0 e concentrações iniciais de cobre (II) de 50 e 80 mg L-1. O modelo matemático de Langmuir foi o que melhor se ajustou aos dados de equilíbrio de adsorção. A partir do tempo de contato de 15 minutos todas as concentrações de equilíbrio ficaram abaixo do máximo permitido de 1,0 mg L-1 previsto pela legislação vigente para lançamento de efluentes em corpos receptores.

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The Amazon River floodplain is an important source of atmospheric CO2 and CH4. Aquatic herbaceous vegetation (macrophytes) have been shown to contribute significantly to floodplain net primary productivity (NPP) and methane emission in the region. Their fast growth rates under both flooded and dry conditions make herbaceous vegetation the most variable element in the Amazon floodplain NPP budget, and the most susceptible to environmental changes. The present study combines multitemporal Radarsat-1 and MODIS images to monitor spatial and temporal changes in herbaceous vegetation cover in the Amazon floodplain. Radarsat-1 images were acquired from Dec/2003 to Oct/2005, and MODIS daily surface reflectance products were acquired for the two cloud-free dates closest to each Radarsat-1 acquisition. An object-based, hierarchical algorithm was developed using the temporal SAR information to discriminate Permanent Open Water (OW), Floodplain (FP) and Upland (UL) classes at Level 1, and then subdivide the FP class into Woody Vegetation (WV) and Possible Macrophytes (PM) at Level 2. At Level 3, optical and SAR information were combined to discriminate actual herbaceous cover at each date. The resulting maps had accuracies ranging from 80% to 90% for Level 1 and 2 classifications, and from 60% to 70% for Level 3 classifications, with kappa values ranging between 0.7 and 0.9 for Levels 1 and 2 and between 0.5 and 0.6 for Level 3. All study sites had noticeable variations in the extent of herbaceous cover throughout the hydrological year, with maximum areas up to four times larger than minimum areas. The proposed classification method was able to capture the spatial pattern of macrophyte growth and development in the studied area, and the multitemporal information was essential for both separating vegetation cover types and assessing monthly variation in herbaceous cover extent.

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Image categorization by means of bag of visual words has received increasing attention by the image processing and vision communities in the last years. In these approaches, each image is represented by invariant points of interest which are mapped to a Hilbert Space representing a visual dictionary which aims at comprising the most discriminative features in a set of images. Notwithstanding, the main problem of such approaches is to find a compact and representative dictionary. Finding such representative dictionary automatically with no user intervention is an even more difficult task. In this paper, we propose a method to automatically find such dictionary by employing a recent developed graph-based clustering algorithm called Optimum-Path Forest, which does not make any assumption about the visual dictionary's size and is more efficient and effective than the state-of-the-art techniques used for dictionary generation.

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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Máster Universitario en Sistemas Inteligentes y Aplicaciones Numéricas en Ingeniería (SIANI)

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This thesis assesses relationships between vegetation and topography and the impact of human tree-cutting on the vegetation of Union County during the early historical era (1755-1855). I use early warrant maps and forestry maps from the Pennsylvania historical archives and a warrantee map from the Union County courthouse depicting the distribution of witness trees and non-tree surveyed markers (posts and stones) in early European settlement land surveys to reconstruct the vegetation and compare vegetation by broad scale (mountains and valleys) and local scale (topographic classes with mountains and valleys) topography. I calculated marker density based on 2 km x 2 km grid cells to assess tree-cutting impacts. Valleys were mostly forests dominated by white oak (Quercus alba) with abundant hickory (Carya spp.), pine (Pinus spp.), and black oak (Quercus velutina), while pine dominated what were mostly pine-oak forests in the mountains. Within the valleys, pine was strongly associated with hilltops, eastern hemlock (Tsuga canadensis) was abundant on north slopes, hickory was associated with south slopes, and riparian zones had high frequencies of ash (Fraxinus spp.) and hickory. In the mountains, white oak was infrequent on south slopes, chestnut (Castanea dentata) was more abundant on south slopes and ridgetops than north slopes and mountain coves, and white oak and maple (Acer spp.) were common in riparian zones. Marker density analysis suggests that trees were still common over most of the landscape by 1855. The findings suggest there were large differences in vegetation between valleys and mountains due in part to differences in elevation, and vegetation differed more by topographic classes in the valleys than in the mountains. Possible areas of tree-cutting were evenly distributed by topographic classes, suggesting Europeans settlers were clearing land and harvesting timber in most areas of Union County.

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Image-guided microsurgery requires accuracies an order of magnitude higher than today's navigation systems provide. A critical step toward the achievement of such low-error requirements is a highly accurate and verified patient-to-image registration. With the aim of reducing target registration error to a level that would facilitate the use of image-guided robotic microsurgery on the rigid anatomy of the head, we have developed a semiautomatic fiducial detection technique. Automatic force-controlled localization of fiducials on the patient is achieved through the implementation of a robotic-controlled tactile search within the head of a standard surgical screw. Precise detection of the corresponding fiducials in the image data is realized using an automated model-based matching algorithm on high-resolution, isometric cone beam CT images. Verification of the registration technique on phantoms demonstrated that through the elimination of user variability, clinically relevant target registration errors of approximately 0.1 mm could be achieved.

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Non-uniform sampling (NUS) has been established as a route to obtaining true sensitivity enhancements when recording indirect dimensions of decaying signals in the same total experimental time as traditional uniform incrementation of the indirect evolution period. Theory and experiments have shown that NUS can yield up to two-fold improvements in the intrinsic signal-to-noise ratio (SNR) of each dimension, while even conservative protocols can yield 20-40 % improvements in the intrinsic SNR of NMR data. Applications of biological NMR that can benefit from these improvements are emerging, and in this work we develop some practical aspects of applying NUS nD-NMR to studies that approach the traditional detection limit of nD-NMR spectroscopy. Conditions for obtaining high NUS sensitivity enhancements are considered here in the context of enabling H-1,N-15-HSQC experiments on natural abundance protein samples and H-1,C-13-HMBC experiments on a challenging natural product. Through systematic studies we arrive at more precise guidelines to contrast sensitivity enhancements with reduced line shape constraints, and report an alternative sampling density based on a quarter-wave sinusoidal distribution that returns the highest fidelity we have seen to date in line shapes obtained by maximum entropy processing of non-uniformly sampled data.

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The procurement of transportation services via large-scale combinatorial auctions involves a couple of complex decisions whose outcome highly influences the performance of the tender process. This paper examines the shipper's task of selecting a subset of the submitted bids which efficiently trades off total procurement cost against expected carrier performance. To solve this bi-objective winner determination problem, we propose a Pareto-based greedy randomized adaptive search procedure (GRASP). As a post-optimizer we use a path relinking procedure which is hybridized with branch-and-bound. Several variants of this algorithm are evaluated by means of artificial test instances which comply with important real-world characteristics. The two best variants prove superior to a previously published Pareto-based evolutionary algorithm.

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Nonlinear computational analysis of materials showing elasto-plasticity or damage relies on knowledge of their yield behavior and strengths under complex stress states. In this work, a generalized anisotropic quadric yield criterion is proposed that is homogeneous of degree one and takes a convex quadric shape with a smooth transition from ellipsoidal to cylindrical or conical surfaces. If in the case of material identification, the shape of the yield function is not known a priori, a minimization using the quadric criterion will result in the optimal shape among the convex quadrics. The convexity limits of the criterion and the transition points between the different shapes are identified. Several special cases of the criterion for distinct material symmetries such as isotropy, cubic symmetry, fabric-based orthotropy and general orthotropy are presented and discussed. The generality of the formulation is demonstrated by showing its degeneration to several classical yield surfaces like the von Mises, Drucker–Prager, Tsai–Wu, Liu, generalized Hill and classical Hill criteria under appropriate conditions. Applicability of the formulation for micromechanical analyses was shown by transformation of a criterion for porous cohesive-frictional materials by Maghous et al. In order to demonstrate the advantages of the generalized formulation, bone is chosen as an example material, since it features yield envelopes with different shapes depending on the considered length scale. A fabric- and density-based quadric criterion for the description of homogenized material behavior of trabecular bone is identified from uniaxial, multiaxial and torsional experimental data. Also, a fabric- and density-based Tsai–Wu yield criterion for homogenized trabecular bone from in silico data is converted to an equivalent quadric criterion by introduction of a transformation of the interaction parameters. Finally, a quadric yield criterion for lamellar bone at the microscale is identified from a nanoindentation study reported in the literature, thus demonstrating the applicability of the generalized formulation to the description of the yield envelope of bone at multiple length scales.

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Tissue grafts are implanted in orthopedic surgery every day. In order to minimize infection risk, bone allografts are often delipidated with supercritical CO2 and sterilized prior to implantation. This treatment may, however, impair the mechanical behavior of the bone graft tissue. The goal of this study was to determine clinically relevant mechanical properties of treated/sterilized human trabecular bone grafts, e.g. the apparent modulus, strength, and the ability to absorb energy during compaction. They were compared with results of identical experiments performed previously on untreated/fresh frozen human trabecular bone from the same anatomical site (Charlebois, 2008). We tested the hypothesis that the morphology–mechanical property relationships of treated cancellous allografts are similar to those of fresh untreated bone. The morphology of the allografts was determined by μCT. Subsequently, cylindrical samples were tested in unconfined and confined compression. To account for various morphologies, the experimental data was fitted to phenomenological mechanical models for elasticity, strength, and dissipated energy density based on bone volume fraction (BV/TV) and the fabric tensor determined by MIL. The treatment/sterilization process does not appear to influence bone graft stiffness. However, strength and energy dissipation of the bone grafts were found to be significantly reduced by 36% to 47% and 66% to 81%, respectively, for a broad range of volume fraction (0.14 < BV/TV < 0.39) and degree of anisotropy (1.24 < DA < 2.18). Since the latter properties are strongly dominated by BV/TV, the clinical consequences of this reduction can be compensated by using grafts with lower porosity. The data of this study suggests that an increase of 5–10% in BV/TV is sufficient to compensate for the reduced post-yield mechanical properties of treated/sterilized bone in monotonic compression. In applications where graft stiffness needs to be matched and strength is not a concern, treated allograft with the same BV/TV as an appropriate fresh bone graft may be used.