10 resultados para EDGE STRUCTURE

em Aston University Research Archive


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To represent the local orientation and energy of a 1-D image signal, many models of early visual processing employ bandpass quadrature filters, formed by combining the original signal with its Hilbert transform. However, representations capable of estimating an image signal's 2-D phase have been largely ignored. Here, we consider 2-D phase representations using a method based upon the Riesz transform. For spatial images there exist two Riesz transformed signals and one original signal from which orientation, phase and energy may be represented as a vector in 3-D signal space. We show that these image properties may be represented by a Singular Value Decomposition (SVD) of the higher-order derivatives of the original and the Riesz transformed signals. We further show that the expected responses of even and odd symmetric filters from the Riesz transform may be represented by a single signal autocorrelation function, which is beneficial in simplifying Bayesian computations for spatial orientation. Importantly, the Riesz transform allows one to weight linearly across orientation using both symmetric and asymmetric filters to account for some perceptual phase distortions observed in image signals - notably one's perception of edge structure within plaid patterns whose component gratings are either equal or unequal in contrast. Finally, exploiting the benefits that arise from the Riesz definition of local energy as a scalar quantity, we demonstrate the utility of Riesz signal representations in estimating the spatial orientation of second-order image signals. We conclude that the Riesz transform may be employed as a general tool for 2-D visual pattern recognition by its virtue of representing phase, orientation and energy as orthogonal signal quantities.

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Globally, more than 1000 tonnes of titanium (Ti) is implanted into patients in the form of biomedical devices on an annual basis. Ti is perceived to be ‘biocompatible’ owing to the presence of a robust passive oxide film (approx. 4 nm thick) at the metal surface. However, surface deterioration can lead to the release of Ti ions, and particles can arise as the result of wear and/or corrosion processes. This surface deterioration can result in peri-implant inflammation, leading to the premature loss of the implanted device or the requirement for surgical revision. Soft tissues surrounding commercially pure cranial anchorage devices (bone-anchored hearing aid) were investigated using synchrotron X-ray micro-fluorescence spectroscopy and X-ray absorption near edge structure. Here, we present the first experimental evidence that minimal load-bearing Ti implants, which are not subjected to macroscopic wear processes, can release Ti debris into the surrounding soft tissue. As such debris has been shown to be pro-inflammatory, we propose that such distributions of Ti are likely to effect to the service life of the device.

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Melt quenched silicate glasses containing calcium, phosphorus and alkali metals have the ability to promote bone regeneration and to fuse to living bone. Of these glasses 45S5 Bioglass® is the most widely used being sold in over 35 countries as a bone graft product for medical and dental applications; particulate 45S5 is also incorporated into toothpastes to help remineralize the surface of teeth. Recently it has been suggested that adding titanium dioxide can increase the bioactivity of these materials. This work investigates the structural consequences of incorporating 4 mol% TiO2 into Bioglass® using isotopic substitution (of the Ti) applied to neutron diffraction and X-ray Absorption Near Edge Structure (XANES). We present the first isotopic substitution data applied to melt quench derived Bioglass or its derivatives. Results show that titanium is on average surrounded by 5.2(1) nearest neighbor oxygen atoms. This implies an upper limit of 40% four-fold coordinated titanium and shows that the network connectivity is reduced from 2.11 to 1.97 for small quantities of titanium. Titanium XANES micro-fluorescence confirms the titanium environment is homogenous on the micron length scale within these glasses. Solid state magic angle spinning (MAS) NMR confirms the network connectivity model proposed. Furthermore, the results show the intermediate range order containing Na-O, Ca-O, O-P-O and O-Si-O correlations are unaffected by the addition of small quantities of TiO2 into these systems.

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Quaternary phosphate-based glasses in the P2O5–CaO–Na2O–TiO2 system with a fixed P2O5 and CaO content of 40 and 25 mol% respectively have been successfully synthesised via sol–gel method and bulk, transparent samples were obtained. The structure, elemental proportion, and thermal properties of stabilised sol–gel glasses have been characterised using X-ray diffraction (XRD), energy dispersive X-ray spectroscopy (EDX), 31P nuclear magnetic resonance (31P NMR), titanium K-edge X-ray absorption near-edge structure (XANES), fourier transform infrared (FTIR) spectroscopy, and differential thermal analysis (DTA). The XRD results confirmed the amorphous nature for all stabilized sol–gel derived glasses. The EDX result shows the relatively low loss of phosphorus during the sol–gel process and Ti K-edge XANES confirmed titanium in the glass structure is in mainly six-fold coordination environment. The 31P NMR and FTIR results revealed that the glass structure consist of mainly Q1 and Q2 phosphate units and the Ti4+ cation was acting as a cross-linking between phosphate units. In addition DTA results confirmed a decrease in the glass transition and crystallisation temperature with increasing Na2O content. Ion release studies also demonstrated a decrease in degradation rates with increasing TiO2 content therefore supporting the use of these glasses for biomedical applications that require a degree of control over glass degradation. These sol–gel glasses also offer the potential to incorporate proactive molecules for drug delivery application due to the low synthesis temperature employed.

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Modern procurement is being shifted from paper-based, people-intensive buying systems toward electronic-based purchase procedures that rely on Internet communications and Web-enhanced buying tools. Develops a typology of e-commerce tools that have come to characterize cutting-edge industrial procurement. E-commerce aspects of purchasing are organized into communication and transaction tools that encompass both internal and external buying activities. Further, a model of the impact of e-commerce on the structure and processes of an organization's buying center is developed. The impact of the changing buying center on procurement outcomes in terms of efficiency and effectiveness is also analyzed. Finally, implications for business-to-business marketers and researchers are discussed.

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The method of isotope substitution in neutron diffraction was used to measure the structure of liquid ZnCl2 at 332(5)?°C and glassy ZnCl2 at 25(1)?°C. The partial structure factors were obtained from the measured diffraction patterns by using the method of singular value decomposition and by using the reverse Monte Carlo procedure. The partial structure factors reproduce the diffraction patterns measured by high-energy x-ray diffraction once a correction for the resolution function of the neutron diffractometer has been made. The results show that the predominant structural motif in both phases is the corner sharing ZnCl4 tetrahedron and that there is a small number of edge-sharing configurations, these being more abundant in the liquid. The tetrahedra organize on an intermediate length scale to give a first sharp diffraction peak in the measured diffraction patterns at a scattering vector kFSDP?1 Å-1 that is most prominent for the Zn-Zn correlations. The results support the notion that the relative fragility of tetrahedral glass forming MX2 liquids is related to the occurrence of edge-sharing units.

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The microscopic origin of the intermediate phase in two prototypical covalently bonded AxB1-x network glass forming systems, where A=Ge or Si, B=Se, and 0=x=1, was investigated by combining neutron diffraction with first-principles molecular-dynamics methods. Specifically, the structure of glassy GeSe4 and SiSe4 was examined, and the calculated total structure factor and total pair-correlation function for both materials are in good agreement with experiment. The structure of both glasses differs markedly from a simple model comprising undefective AB4 corner-sharing tetrahedra in which all A atoms are linked by B2 dimers. Instead, edge-sharing tetrahedra occur and the twofold coordinated Se atoms form three distinct structural motifs, namely, Se-Se2, Se-SeGe (or Se-SeSi), and Se-Ge2 (or Se-Si2). This identifies several of the conformations that are responsible for the structural variability in GexSe1-x and SixSe1-x glasses, a quantity that is linked to the finite width of the intermediate phase window.

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An array of different structural probes has been used to define the effect of adding Zn and Ti to a sodium-calcium phosphate glass. X-ray absorption spectroscopy at the Zn K-edge suggests that the Zn atoms occupy mixed (4- and 6-fold) sites within the glass matrix. X-ray diffraction reveals a feature at 2.03 angstrom that develops with the addition of Zn and Ti and is consistent with Zn-O and Ti-O near-neighbour distances. Neutron diffraction is used to resolve two distinct P-O distances and highlights the decrease in P center dot center dot center dot P coordination number from 2.0 to 1.7 as the Ti metal concentration rises, which is attributed to the O/P fraction moving away from the metaphosphate value of 3.0 to 3.1 with the addition of Ti. Other correlations, such as those associated with CaO(x) and NaO(x) polyhedra, remain largely unaffected. These results suggest that the network forming P center dot center dot center dot P correlation is most disrupted, with the disorder parameter rising from 0.07 to 0.10 angstrom with the additional modifiers. Zn appears to be introduced into the network as a direct replacement for Ca and causes no structural variation over the composition range studied.

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In this paper, we propose a new edge-based matching kernel for graphs by using discrete-time quantum walks. To this end, we commence by transforming a graph into a directed line graph. The reasons of using the line graph structure are twofold. First, for a graph, its directed line graph is a dual representation and each vertex of the line graph represents a corresponding edge in the original graph. Second, we show that the discrete-time quantum walk can be seen as a walk on the line graph and the state space of the walk is the vertex set of the line graph, i.e., the state space of the walk is the edges of the original graph. As a result, the directed line graph provides an elegant way of developing new edge-based matching kernel based on discrete-time quantum walks. For a pair of graphs, we compute the h-layer depth-based representation for each vertex of their directed line graphs by computing entropic signatures (computed from discrete-time quantum walks on the line graphs) on the family of K-layer expansion subgraphs rooted at the vertex, i.e., we compute the depth-based representations for edges of the original graphs through their directed line graphs. Based on the new representations, we define an edge-based matching method for the pair of graphs by aligning the h-layer depth-based representations computed through the directed line graphs. The new edge-based matching kernel is thus computed by counting the number of matched vertices identified by the matching method on the directed line graphs. Experiments on standard graph datasets demonstrate the effectiveness of our new kernel.

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Graph-based representations have been used with considerable success in computer vision in the abstraction and recognition of object shape and scene structure. Despite this, the methodology available for learning structural representations from sets of training examples is relatively limited. In this paper we take a simple yet effective Bayesian approach to attributed graph learning. We present a naïve node-observation model, where we make the important assumption that the observation of each node and each edge is independent of the others, then we propose an EM-like approach to learn a mixture of these models and a Minimum Message Length criterion for components selection. Moreover, in order to avoid the bias that could arise with a single estimation of the node correspondences, we decide to estimate the sampling probability over all the possible matches. Finally we show the utility of the proposed approach on popular computer vision tasks such as 2D and 3D shape recognition. © 2011 Springer-Verlag.