949 resultados para Sparse arrays


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A bottom-up approach is introduced to fabricate two-dimensional self-assembled layers of molecular spin-systems containing Mn and Fe ions arranged in a chessboard lattice. We demonstrate that the Mn and Fe spin states can be reversibly operated by their selective response to coordination/decoordination of volatile ligands like ammonia (NH3).

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Knowledge of landmarks and contours in anteroposterior (AP) pelvis X-rays is invaluable for computer aided diagnosis, hip surgery planning and image-guided interventions. This paper presents a fully automatic and robust approach for landmarking and segmentation of both pelvis and femur in a conventional AP X-ray. Our approach is based on random forest regression and hierarchical sparse shape composition. Experiments conducted on 436 clinical AP pelvis x-rays show that our approach achieves an average point-to-curve error around 1.3 mm for femur and 2.2 mm for pelvis, both with success rates around 98%. Compared to existing methods, our approach exhibits better performance in both the robustness and the accuracy.

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In this paper we present a solution to the problem of action and gesture recognition using sparse representations. The dictionary is modelled as a simple concatenation of features computed for each action or gesture class from the training data, and test data is classified by finding sparse representation of the test video features over this dictionary. Our method does not impose any explicit training procedure on the dictionary. We experiment our model with two kinds of features, by projecting (i) Gait Energy Images (GEIs) and (ii) Motion-descriptors, to a lower dimension using Random projection. Experiments have shown 100% recognition rate on standard datasets and are compared to the results obtained with widely used SVM classifier.

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Understanding and controlling the structural anisotropies of injection-molded polymers is vital for designing products such as cantilever-based sensors. Such micro-cantilevers are considered as cost-effective alternatives to single-crystalline silicon-based sensors. In order to achieve similar sensing characteristics,structure and morphology have to be controlled by means of processing parameters including mold temperature and injection speed. Synchrotron radiation-based scanning small- (SAXS) and wide-angle x-ray scattering techniques were used to quantify crystallinity and anisotropy in polymer micro-cantilevers with micrometer resolution in real space. SAXS measurements confirmed the lamellar nature of the injection-molded semi-crystalline micro-cantilevers. The homogenous cantilever material exhibits a lamellar periodicity increasing with mold temperature but not with injection speed. We demonstrate that micro-cantilevers made of semi-crystalline polymers such as polyvinylidenefluoride, polyoxymethylene, and polypropylene show the expected strong degree of anisotropy along the injection direction.

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Microinjection molding was employed to fabricate low-cost polymer cantilever arrays for sensor applications. Cantilevers with micrometer dimensions and aspect ratios as large as 10 were successfully manufactured from polymers, including polypropylene and polyvinylidenfluoride. The cantilevers perform similar to the established silicon cantilevers, with Q-factors in the range of 10–20. Static deflection of gold coated polymer cantilevers was characterized with heat cycling and self-assembled monolayer formation of mercaptohexanols. A hybrid mold concept allows easy modification of the surface topography, enabling customized mechanical properties of individual cantilevers. Combined with functionalization and surface patterning, the cantilever arrays are qualified for biomedical applications

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High brightness electron sources are of great importance for the operation of the hard X-ray free electron lasers. Field emission cathodes based on the double-gate metallic field emitter arrays (FEAs) can potentially offer higher brightness than the currently used ones. We report on the successful application of electron beam lithography for fabrication of the large-scale single-gate as well as double-gate FEAs. We demonstrate operational high-density single-gate FEAs with sub-micron pitch and total number of tips up to 106 as well as large-scale double-gate FEAs with large collimation gate apertures. The details of design, fabrication procedure and successful measurements of the emission current from the single- and double-gate cathodes are presented.

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The generation of collimated electron beams from metal double-gate nanotip arrays excited by near infrared laser pulses is studied. Using electromagnetic and particle tracking simulations, we showed that electron pulses with small rms transverse velocities are efficiently produced from nanotip arrays by laser-induced field emission with the laser wavelength tuned to surface plasmon polariton resonance of the stacked double-gate structure. The result indicates the possibility of realizing a metal nanotip array cathode that outperforms state-of-the-art photocathodes.

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In the course of this study, stiffness of a fibril array of mineralized collagen fibrils modeled with a mean field method was validated experimentally at site-matched two levels of tissue hierarchy using mineralized turkey leg tendons (MTLT). The applied modeling approaches allowed to model the properties of this unidirectional tissue from nanoscale (mineralized collagen fibrils) to macroscale (mineralized tendon). At the microlevel, the indentation moduli obtained with a mean field homogenization scheme were compared to the experimental ones obtained with microindentation. At the macrolevel, the macroscopic stiffness predicted with micro finite element (μFE) models was compared to the experimental stiffness measured with uniaxial tensile tests. Elastic properties of the elements in μFE models were injected from the mean field model or two-directional microindentations. Quantitatively, the indentation moduli can be properly predicted with the mean-field models. Local stiffness trends within specific tissue morphologies are very weak, suggesting additional factors responsible for the stiffness variations. At macrolevel, the μFE models underestimate the macroscopic stiffness, as compared to tensile tests, but the correlations are strong.

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Well-known data mining algorithms rely on inputs in the form of pairwise similarities between objects. For large datasets it is computationally impossible to perform all pairwise comparisons. We therefore propose a novel approach that uses approximate Principal Component Analysis to efficiently identify groups of similar objects. The effectiveness of the approach is demonstrated in the context of binary classification using the supervised normalized cut as a classifier. For large datasets from the UCI repository, the approach significantly improves run times with minimal loss in accuracy.

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We report the fabrication and field emission properties of high-density nano-emitter arrays with on-chip electron extraction gate electrodes and up to 106 metallic nanotips that have an apex curvature radius of a few nanometers and a the tip density exceeding 108 cm−2. The gate electrode was fabricated on top of the nano-emitter arrays using a self-aligned polymer mask method. By applying a hot-press step for the polymer planarization, gate–nanotip alignment precision below 10 nm was achieved. Fabricated devices exhibited stable field electron emission with a current density of 0.1 A cm−2, indicating that these are promising for applications that require a miniature high-brightness electron source.