71 resultados para Multi-scale fractal dimension


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The collection of spatial information to quantify changes to the state and condition of the environment is a fundamental component of conservation or sustainable utilization of tropical and subtropical forests, Age is an important structural attribute of old-growth forests influencing biological diversity in Australia eucalypt forests. Aerial photograph interpretation has traditionally been used for mapping the age and structure of forest stands. However this method is subjective and is not able to accurately capture fine to landscape scale variation necessary for ecological studies. Identification and mapping of fine to landscape scale vegetative structural attributes will allow the compilation of information associated with Montreal Process indicators lb and ld, which seek to determine linkages between age structure and the diversity and abundance of forest fauna populations. This project integrated measurements of structural attributes derived from a canopy-height elevation model with results from a geometrical-optical/spectral mixture analysis model to map forest age structure at a landscape scale. The availability of multiple-scale data allows the transfer of high-resolution attributes to landscape scale monitoring. Multispectral image data were obtained from a DMSV (Digital Multi-Spectral Video) sensor over St Mary's State Forest in Southeast Queensland, Australia. Local scene variance levels for different forest tapes calculated from the DMSV data were used to optimize the tree density and canopy size output in a geometric-optical model applied to a Landsat Thematic Mapper (TU) data set. Airborne laser scanner data obtained over the project area were used to calibrate a digital filter to extract tree heights from a digital elevation model that was derived from scanned colour stereopairs. The modelled estimates of tree height, crown size, and tree density were used to produce a decision-tree classification of forest successional stage at a landscape scale. The results obtained (72% accuracy), were limited in validation, but demonstrate potential for using the multi-scale methodology to provide spatial information for forestry policy objectives (ie., monitoring forest age structure).

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The basal dendritic arbors of 442 supragranular pyramidal cells in visual cortex of the marmoset monkey were compared by fractal analyses. As detailed in a previous study,(1) individual cells were injected with Lucifer Yellow and processed for a DAB reaction product. The basal dendritic arbors were drawn, in the tangential plane, and the fractal dimension (D) determined by the dilation method. The fractal dimensions were compared between cells in ten cortical areas containing cells involved in visual processing, including the primary visual area (Vi), the second visual area (V2), the dorsoanterior area (DA), the dorsomedial area (DM), the dorsolateral. area (DL), the middle temporal area (MT), the posterior parietal area (PP), the fundus of the superior temporal area (FST) and the caudal and rostral subdivisions of inferotemporal cortex (ITc and ITr, respectively). Of 45 pairwise interareal comparisons of the fractal dimension of neurones, 20 were significantly different. Moreover, comparison of data according to previously published visual processing pathways revealed a trend for cells with greater fractal dimensions in higher cortical areas. Comparison of the present results with those in homologous cortical areas in the macaque monkey(2) revealed some similarities between the two species. The similarity in the trends of D values of cells in both species may reflect developmental features which, result in different functional attributes.

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The basal dendritic arbors of over 500-layer III pyramidal neurones of the macaque cortex were compared by fractal analyses, which provides a measure of the space filling (or branching pattern) of dendritic arbors. Fractal values (D) of individual cells were compared between the cytochrome oxidase (CO)-rich blobs and CO-poor interblobs, of middle and upper layer III, and between sublaminae, in the primary visual area (Vi). These data were compared with those in the CO compartments in the second visual area (V2), and seven other extrastriate cortical areas. (V4, MT, LIP, 7a, TEO, TE and STP). There were significant differences in the fractal dimensions, and therefore the dendritic branching patterns, of cells in striate and extrastriate areas. Of the 55 possible pairwise comparisons of fractal dimension of neurones in different cortical areas (or CO compartments), 39 proved to be significantly different. The markedly different morphologies of pyramidal cells in the different cortical areas may be one of the features that determine the functional signatures of these cells by influencing the number of inputs received by, and propagation of potentials through, their dendritic arbors.

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The constrained regularisation procedure was applied to compute the pore size distributions (PSDs, f(x)) for a variety of activated carbons using overall adsorption equation based on the combination of the Kelvin equation and the statistical adsorbed film thickness. The impact of the boundary values of relative nitrogen pressure p/p(0) was analysed on the basis of the corresponding alterations in the PSDs. Changes in microporosity and mesoporosity of activated carbons can be described adequately only when the range of p/p(0) is as wide as possible, as at a high initial p/p(0) value, the f(x) curves can be broadened with shifted maxima especially for micropores and narrow mesopores. Comparative analysis of the PSDs and the adsorption potential, adsorption energy and fractal dimension distributions gives useful information on the complete description of the adsorbent characteristics. (C) 2001 Elsevier Science B.V. All rights reserved.

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Observational data collected in the Lake Tekapo hydro catchment of the Southern Alps in New Zealand are used to analyse the wind and temperature fields in the alpine lake basin during summertime fair weather conditions. Measurements from surface stations, pilot balloon and tethersonde soundings, Doppler sodar and an instrumented light aircraft provide evidence of multi-scale interacting wind systems, ranging from microscale slope winds to mesoscale coast-to-basin flows. Thermal forcing of the winds occurred due to differential heating as a consequence of orography and heterogeneous surface features, which is quantified by heat budget and pressure field analysis. The daytime vertical temperature structure was characterised by distinct layering. Features of particular interest are the formation of thermal internal boundary layers due to the lake-land discontinuity and the development of elevated mixed layers. The latter were generated by advective heating from the basin and valley sidewalls by slope winds and by a superimposed valley wind blowing from the basin over Lake Tekapo and up the tributary Godley Valley. Daytime heating in the basin and its tributary valleys caused the development of a strong horizontal temperature gradient between the basin atmosphere and that over the surrounding landscape, and hence the development of a mesoscale heat low over the basin. After noon, air from outside the basin started flowing over mountain saddles into the basin causing cooling in the lowest layers, whereas at ridge top height the horizontal air temperature gradient between inside and outside the basin continued to increase. In the early evening, a more massive intrusion of cold air caused rapid cooling and a transition to a rather uniform slightly stable stratification up to about 2000 m agl. The onset time of this rapid cooling varied about 1-2 h between observation sites and was probably triggered by the decay of up-slope winds inside the basin, which previously countered the intrusion of air over the surrounding ridges. The intrusion of air from outside the basin continued until about mid-night, when a northerly mountain wind from the Godley Valley became dominant. The results illustrate the extreme complexity that can be caused by the operation of thermal forcing processes at a wide range of spatial scales.

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The comparative analysis of the most widely used methods of mesoporosity characterization of two activated carbon fibers is presented. Not only the older methods are used, i.e. Barrett, Joyner and Halenda (BJH), Dubinin (the so-called first variant-D-1ST and the so-called second variant-D-2ND), Dollimore and Heal (DH), and Pierce (P) but the recently developed ones, i.e. the method of Nguyen and Do (ND) and that developed by Do (Do) are also applied. Additionally, the method of the characterization of fractality is put to use (fractal analog of FHH isotherm). The results are compared and discussed. (C) 2002 Elsevier Science B.V. All fights reserved.

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This study examined how the floc characteristics affect dewaterability of activated sludge. The floc properties were characterized by morphological parameters (floc size distribution, fractal dimension and filament index), physical properties (flocculating ability, surface charge, relative hydrophobicity and viscosity), and chemical constituents in sludge and extracted extracellular polymeric substances (EPS), including the polymeric compounds protein, humic substances, carbohydrates and the ions Ca2+, Mg2+, Fe3+ and Al3+. The dewaterability was defined in terms of the bound water content and capillary suction time (CST). The bound water and CST corresponded to a similar indication with respect to dewaterability of activated sludge. The floc physical parameters were the most important factors which effect significantly on the water binding ability of the sludge flocs. The morphological characteristics had relatively weak impact on the dewaterability. The polymeric components protein and carbohydrate had a significant contribution to enhance the water binding ability of the sludge flocs. The effect of humic substances in the sludge on the dewaterability was, however, insignificant. The CST had good statistical correlations with the polymeric constituents measured in both sludge and the extracted EPS, and the bound water was only correlated well with the individual polymers measured in the sludge. High concentration of Ca2+, Mg2+, Fe3+ and Al3+ had significant improvement for dewaterability. (C) 2003 Elsevier B.V. All rights reserved.

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In this paper, we present a novel indexing technique called Multi-scale Similarity Indexing (MSI) to index image's multi-features into a single one-dimensional structure. Both for text and visual feature spaces, the similarity between a point and a local partition's center in individual space is used as the indexing key, where similarity values in different features are distinguished by different scale. Then a single indexing tree can be built on these keys. Based on the property that relevant images have similar similarity values from the center of the same local partition in any feature space, certain number of irrelevant images can be fast pruned based on the triangle inequity on indexing keys. To remove the dimensionality curse existing in high dimensional structure, we propose a new technique called Local Bit Stream (LBS). LBS transforms image's text and visual feature representations into simple, uniform and effective bit stream (BS) representations based on local partition's center. Such BS representations are small in size and fast for comparison since only bit operation are involved. By comparing common bits existing in two BSs, most of irrelevant images can be immediately filtered. To effectively integrate multi-features, we also investigated the following evidence combination techniques-Certainty Factor, Dempster Shafer Theory, Compound Probability, and Linear Combination. Our extensive experiment showed that single one-dimensional index on multi-features improves multi-indices on multi-features greatly. Our LBS method outperforms sequential scan on high dimensional space by an order of magnitude. And Certainty Factor and Dempster Shafer Theory perform best in combining multiple similarities from corresponding multiple features.

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Systems biology is based on computational modelling and simulation of large networks of interacting components. Models may be intended to capture processes, mechanisms, components and interactions at different levels of fidelity. Input data are often large and geographically disperse, and may require the computation to be moved to the data, not vice versa. In addition, complex system-level problems require collaboration across institutions and disciplines. Grid computing can offer robust, scaleable solutions for distributed data, compute and expertise. We illustrate some of the range of computational and data requirements in systems biology with three case studies: one requiring large computation but small data (orthologue mapping in comparative genomics), a second involving complex terabyte data (the Visible Cell project) and a third that is both computationally and data-intensive (simulations at multiple temporal and spatial scales). Authentication, authorisation and audit systems are currently not well scalable and may present bottlenecks for distributed collaboration particularly where outcomes may be commercialised. Challenges remain in providing lightweight standards to facilitate the penetration of robust, scalable grid-type computing into diverse user communities to meet the evolving demands of systems biology.

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Understanding and explaining emergent constitutive laws in the multi-scale evolution from point defects, dislocations and two-dimensional defects to plate tectonic scales is an arduous challenge in condensed matter physics. The Earth appears to be the only planet known to have developed stable plate tectonics as a means to get rid of its heat. The emergence of plate tectonics out of mantle convection appears to rely intrinsically on the capacity to form extremely weak faults in the top 100 km of the planet. These faults have a memory of at least several hundred millions of years, yet they appear to rely on the effects of water on line defects. This important phenomenon was first discovered in laboratory and dubbed ``hydrolytic weakening''. At the large scale it explains cycles of co-located resurgence of plate generation and consumption (the Wilson cycle), but the exact physics underlying the process itself and the enormous spanning of scales still remains unclear. We present an attempt to use the multi-scale non-equilibrium thermodynamic energy evolution inside the deforming lithosphere to move phenomenological laws to laws derived from basic scaling quantities, develop self-consistent weakening laws at lithospheric scale and give a fully coupled deformation-weakening constitutive framework. At meso- to plate scale we encounter in a stepwise manner three basic domains governed by the diffusion/reaction time scales of grain growth, thermal diffusion and finally water mobility through point defects in the crystalline lattice. The latter process governs the planetary scale and controls the stability of its heat transfer mode.

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The texture segmentation techniques are diversified by the existence of several approaches. In this paper, we propose fuzzy features for the segmentation of texture image. For this purpose, a membership function is constructed to represent the effect of the neighboring pixels on the current pixel in a window. Using these membership function values, we find a feature by weighted average method for the current pixel. This is repeated for all pixels in the window treating each time one pixel as the current pixel. Using these fuzzy based features, we derive three descriptors such as maximum, entropy, and energy for each window. To segment the texture image, the modified mountain clustering that is unsupervised and fuzzy c-means clustering have been used. The performance of the proposed features is compared with that of fractal features.

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Multiresolution (or multi-scale) techniques make it possible for Web-based GIS applications to access large dataset. The performance of such systems relies on data transmission over network and multiresolution query processing. In the literature the latter has received little research attention so far, and the existing methods are not capable of processing large dataset. In this paper, we aim to improve multiresolution query processing in an online environment. A cost model for such query is proposed first, followed by three strategies for its optimization. Significant theoretical improvement can be observed when comparing against available methods. Application of these strategies is also discussed, and similar performance enhancement can be expected if implemented in online GIS applications.

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In this paper, we present a novel indexing technique called Multi-scale Similarity Indexing (MSI) to index imagersquos multi-features into a single one-dimensional structure. Both for text and visual feature spaces, the similarity between a point and a local partitionrsquos center in individual space is used as the indexing key, where similarity values in different features are distinguished by different scale. Then a single indexing tree can be built on these keys. Based on the property that relevant images haves similar similarity values from the center of the same local partition in any feature space, certain number of irrelevant images can be fast pruned based on the triangle inequity on indexing keys. To remove the ldquodimensionality curserdquo existing in high dimensional structure, we propose a new technique called Local Bit Stream (LBS). LBS transforms imagersquos text and visual feature representations into simple, uniform and effective bit stream (BS) representations based on local partitionrsquos center. Such BS representations are small in size and fast for comparison since only bit operation are involved. By comparing common bits existing in two BSs, most of irrelevant images can be immediately filtered. Our extensive experiment showed that single one-dimensional index on multi-features improves multi-indices on multi-features greatly. Our LBS method outperforms sequential scan on high dimensional space by an order of magnitude.

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This study offers a new perspective on the nature, content and structure of perceived service quality. The Nordic and Gap schools of quality assessment are integrated with recent advances in the literature to develop and test a multidimensional, hierarchical scale. The scale provides a framework for assessing service quality within a high involvement, high contact, ongoing service environment. Empirical results indicated that service quality conforms to a multidimensional, hierarchical structure consisting of four primary dimensions, which in turn comprise nine sub-dimensions. The results obtained extend our understanding of service evaluation and have important implications for service providers seeking to improve the quality of the services they provide.