41 resultados para CLOUD CORES


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With increasing demands on storage devices in the modern communication environment, the storage area network (SAN) has evolved to provide a direct connection allowing these storage devices to be accessed efficiently. To optimize the performance of a SAN, a three-stage hybrid electronic/optical switching node architecture based on the concept of a MPLS label switching mechanism, aimed at serving as a multi-protocol label switching (MPLS) ingress label edge router (LER) for a SAN-enabled application, has been designed. New shutter-based free-space multi-channel optical switching cores are employed as the core switch fabric to solve the packet contention and switching path conflict problems. The system-level node architecture design constraints are evaluated through self-similar traffic sourced from real gigabit Ethernet network traces and storage systems. The extension performance of a SAN over a proposed WDM ring network, aimed at serving as an MPLS-enabled transport network, is also presented and demonstrated. © 2012 OSA.

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The dynamic compressive response of corrugated carbon-fibre reinforced epoxy sandwich cores has been investigated using a Kolsky-bar set-up. Compression at quasi-static rates up to v 0=200ms -1 have been tested on three different slenderness ratios of strut. High speed photography was used to capture the failure mechanisms and relate these to the measured axial compressive stress. Experiments show significant strength enhancement as the loading rate increases. Although material rate sensitivity accounts for some of this, it has been shown that the majority of the strength enhancement is due to inertial stabilisation of the core members. Inertial strength enhancement rises non-linearly with impact velocity. The largest gains are associated with a shift to buckle modes composed of 2-3 half sine waves. The loading rates tested within this study are similar to those that are expected when a sandwich core is compressed due to a blast event. © 2012 Elsevier Ltd.

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The commercial far-range (>10 m) spatial data collection methods for acquiring infrastructure’s geometric data are not completely automated because of the necessary manual pre- and/or post-processing work. The required amount of human intervention and, in some cases, the high equipment costs associated with these methods impede their adoption by the majority of infrastructure mapping activities. This paper presents an automated stereo vision-based method, as an alternative and inexpensive solution, to producing a sparse Euclidean 3D point cloud of an infrastructure scene utilizing two video streams captured by a set of two calibrated cameras. In this process SURF features are automatically detected and matched between each pair of stereo video frames. 3D coordinates of the matched feature points are then calculated via triangulation. The detected SURF features in two successive video frames are automatically matched and the RANSAC algorithm is used to discard mismatches. The quaternion motion estimation method is then used along with bundle adjustment optimization to register successive point clouds. The method was tested on a database of infrastructure stereo video streams. The validity and statistical significance of the results were evaluated by comparing the spatial distance of randomly selected feature points with their corresponding tape measurements.

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Automating the model generation process of infrastructure can substantially reduce the modeling time and cost. This paper presents a method to generate a sparse point cloud of an infrastructure scene using a single video camera under practical constraints. It is the first step towards establishing an automatic framework for object-oriented as-built modeling. Motion blur and key frame selection criteria are considered. Structure from motion and bundle adjustment are explored. The method is demonstrated in a case study where the scene of a reinforced concrete bridge is videotaped, reconstructed, and metrically validated. The result indicates the applicability, efficiency, and accuracy of the proposed method.