21 resultados para Network architecture


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This paper proposes a method for extracting reliable architectural characteristics from complex porous structures using micro-computed tomography (μCT) images. The work focuses on a highly porous material composed of a network of fibres bonded together. The segmentation process, allowing separation of the fibres from the remainder of the image, is the most critical step in constructing an accurate representation of the network architecture. Segmentation methods, based on local and global thresholding, were investigated and evaluated by a quantitative comparison of the architectural parameters they yielded, such as the fibre orientation and segment length (sections between joints) distributions and the number of inter-fibre crossings. To improve segmentation accuracy, a deconvolution algorithm was proposed to restore the original images. The efficacy of the proposed method was verified by comparing μCT network architectural characteristics with those obtained using high resolution CT scans (nanoCT). The results indicate that this approach resolves the architecture of these complex networks and produces results approaching the quality of nanoCT scans. The extracted architectural parameters were used in conjunction with an affine analytical model to predict the axial and transverse stiffnesses of the fibre network. Transverse stiffness predictions were compared with experimentally measured values obtained by vibration testing. © 2011 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.

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Bonded networks of metal fibres are highly porous, permeable materials, which often exhibit relatively high strength. Material of this type has been produced, using melt-extracted ferritic stainless steel fibres, and characterised in terms of fibre volume fraction, fibre segment (joint-to-joint) length and fibre orientation distribution. Young's moduli and yield stresses have been measured. The behaviour when subjected to a magnetic field has also been investigated. This causes macroscopic straining, as the individual fibres become magnetised and tend to align with the applied field. The modeling approach of Markaki and Clyne, recently developed for prediction of the mechanical and magneto-mechanical properties of such materials, is briefly summarised and comparisons are made with experimental data. The effects of filling the inter-fibre void with compliant (polymeric) matrices have also been explored. In general the modeling approach gives reliable predictions, particularly when the network architecture has been characterised using X-ray tomography. © 2005 Published by Elsevier Ltd.

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RFID technology can be used to its fullest potential only with software to supplement the hardware with powerful capabilities for data capture, filtering, counting and storage. The EPCglobal Network architecture encourages minimizing the amount of business logic embedded in the tags, readers and middleware. This creates the need for a Business Logic Layer above the event filtering layer that enhances basic observation events with business context - i.e. in addition to the (what, when, where) information about an observation, it adds context information about why the object was there. The purpose of this project is to develop an implementation of the Business Logic Layer. This application accepts observation event data (e.g. from the Application Level Events (ALE) standard interface), enriches them with business context and provides these enriched events to a repository of business-level events (e.g. via the EPC Information Services (EPCIS) capture interface). The strength of the application lies in the automatic addition of business context. It is quick and easy to adapt any business process to the framework suggested and equally easy to reconfigure it if the business process is changed. A sample application has been developed for a business scenario in the retail sector.

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RFID, in its different forms, but especially following EPCglobal standards, has become a key enabling technology for many applications. An essential component to develop track and trace applications in a complex multi-vendor scenario are the Discovery Services. Although they are already envisaged as part of the EPCglobal network architecture, the functional definition and standardization of the Discovery Service is still at a very early stage. Within the scope of the BRIDGE project, a specification for the interfaces of Discovery Services has been developed, together with a prototype to validate the design and different models to enhance supply-chain control through track and trace applications. © 2008 IEEE.

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Choosing appropriate architectures and regularization strategies of deep networks is crucial to good predictive performance. To shed light on this problem, we analyze the analogous problem of constructing useful priors on compositions of functions. Specifically, we study the deep Gaussian process, a type of infinitely-wide, deep neural network. We show that in standard architectures, the representational capacity of the network tends to capture fewer degrees of freedom as the number of layers increases, retaining only a single degree of freedom in the limit. We propose an alternate network architecture which does not suffer from this pathology. We also examine deep covariance functions, obtained by composing infinitely many feature transforms. Lastly, we characterize the class of models obtained by performing dropout on Gaussian processes.

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In the present paper, highly porous fibre networks made of 316L fibres, with different fibre volume fractions, are characterized in terms of network architecture, elastic constants and fracture energies. Elastic constants are measured using quasi-static mechanical and modal vibration testing, yielding local and globally averaged properties, respectively. Differences between quasi-static and dynamic elastic constants are attributed to through-thickness shear effects. Regardless of the method employed, networks show signs of material inhomogeneity at high fibre densities, in agreement with X-ray nanotomography results. Strong auxetic (or negative Poisson's ratio) behaviour is observed in the through-thickness direction, which is attributed to fibre kinking induced during processing. Measured fracture energies are compared with model predictions incorporating information about in-plane fibre orientation distribution, fibre volume fraction and single fibre work of fracture. Experimental values are broadly consistent with model predictions, based on the assumption that this energy is primarily associated with plastic deformation of individual fibres within a process zone of the same order as the inter-joint spacing. © 2013 Published by Elsevier Ltd. on behalf of Acta Materialia Inc. All rights reserved.