996 resultados para ombrophilous dense forest


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We evaluate the performance of different optimization techniques developed in the context of optical flow computation with different variational models. In particular, based on truncated Newton methods (TN) that have been an effective approach for large-scale unconstrained optimization, we de- velop the use of efficient multilevel schemes for computing the optical flow. More precisely, we evaluate the performance of a standard unidirectional mul- tilevel algorithm - called multiresolution optimization (MR/OPT), to a bidrec- tional multilevel algorithm - called full multigrid optimization (FMG/OPT). The FMG/OPT algorithm treats the coarse grid correction as an optimiza- tion search direction and eventually scales it using a line search. Experimental results on different image sequences using four models of optical flow com- putation show that the FMG/OPT algorithm outperforms both the TN and MR/OPT algorithms in terms of the computational work and the quality of the optical flow estimation.

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The objective of this work was to determine, through the use of the bearing capacity model, the traffic effects of the forest harvest operations on the preconsolidation pressure (sigmap), during one cycle of the eucalyptus plantation. The work was conducted using undisturbed soil samples, collected at the surface of the A horizon and in the top of the B horizon of an Udult (PA), Aquox (FX) and Udox (LA) soils. The undisturbed soil samples were used in the uniaxial compression tests. The soil sampling was done before and after the harvest operations. The operations performed with the Forwarder caused greater soil compaction than the ones done with the Feller Büncher and Harvester. The percentage of soil samples, in the region with additional soil compaction, indicated that the Udult was the soil class more susceptible to soil compaction, followed by the Aquox and Udox. Despite Udult is the more susceptible to soil compaction, the regeneration of the soil structure in this soil class was more efficient than in Aquox. The percentage of soil samples with sigmap values in the region with additional soil compaction in 1996, 1998 and 2004, after harvest operations, indicated a sustainable forest exploration in this period.

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The objective of this work was to compare forage production and quality of thorny and thornless "jurema-preta" (Mimosa tenuiflora (Willd.) Poiret) in a dense planted stand, subjected to annual pruning of fine branches, in Patos, PB, Brazil. The experiment consisted of two treatments (thornless and thorny "jurema-preta") in a complete randomized block design, with ten replicates of two linear plots subdivided in time. Forage mass and chemical composition of fine branches and the basal diameter of plants were measured during five years. Pruning decreased (p<0.05) increments in basal diameter and forage production. Annual dry matter yields reached 4,108 and 5,833 kg ha-1, respectively, for thornless and thorny plants, and forage quality was similar (p>0.05) for both genotypes. This roughage fodder (minimum NDF and ADF averages were 56±1.1% and 43±1.0%, respectively) had low P and K concentrations. Its average crude protein content was greater than 9.9±0.5%, which exceeds the minimum necessary for animal maintenance. Both "jurema-preta" genotypes tolerated pruning of fine branches and contributed with a significant amount of roughage fodder for animal maintenance in the dry season.

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This paper presents a new and original variational framework for atlas-based segmentation. The proposed framework integrates both the active contour framework, and the dense deformation fields of optical flow framework. This framework is quite general and encompasses many of the state-of-the-art atlas-based segmentation methods. It also allows to perform the registration of atlas and target images based on only selected structures of interest. The versatility and potentiality of the proposed framework are demonstrated by presenting three diverse applications: In the first application, we show how the proposed framework can be used to simulate the growth of inconsistent structures like a tumor in an atlas. In the second application, we estimate the position of nonvisible brain structures based on the surrounding structures and validate the results by comparing with other methods. In the final application, we present the segmentation of lymph nodes in the Head and Neck CT images, and demonstrate how multiple registration forces can be used in this framework in an hierarchical manner.