49 resultados para variable optical attenuator
Resumo:
The rheological and structural characteristics of acetoxypropylcellulose (APC) nematic melt are studied at shear rates ranging from 10 s(-1) to 1000 s(-1) which are relevant to extrusion based processes. APC shows a monotonic shear thinning behavior over the range of shear rates tested. The negative extrudate-swell shows a minimum when a critical shear rate (gamma) over dot(c) is reached. For shear rates smaller than (gamma) over dot(c), the flow-induced texture consists of two set of bands aligned parallel and normal to the flow direction. At shear rates larger than (gamma) over dot(c), the flow induced texture is reminiscent of a 2 fluids structure. Close to the shearing walls, domains elongated along the flow direction and stacked along the vorticity are imaged with POM, whereas SALS patterns indicate that the bulk of the sheared APC is made of elliptical domains oriented along the vorticity. No full nematic alignment is achieved at the largest shear rate tested. Below (gamma) over dot(c), the stress relaxation is described by a stretched exponential. Above (gamma) over dot(c), the stress relaxation is described by a fast and a slow process. The latter coincides with the growth of normal bands thicknesses, as the APC texture after flow cessation consists of two types of bands with parallel and normal orientations relative to the flow direction. Both bands thicknesses do not depend on the applied shear rate, in contrast to their orientation. (C) 2015 Elsevier Ltd. All rights reserved.
Resumo:
Taking as starting points the books The Address of the Eye: A Phenomenology of Film Experience, by Vivian Sobchak, and Les quatre concepts fondamentaux de la psychanalyse, by Jacques Lacan, this article proposes to look at two well renowned film objects – Rear Window (Alfred Hitchcock, 1954, USA) and Peeping Tom (Michael Powell, 1960, UK) – in order to equate two forms of perception that, all things considered, come together as one: the perception of the mechanical apparatuses that record and project film and the optical and mental apparatuses that operate on the human filmmakers as well as their intradiegetic protagonists. In fact, these two films not only explore the characteristics and limits of vision and affection in their diegetic world, that is part of the filmmaker’s world itself, but reveals just how much the human lives through the eye and the expression of the machine itself. Film ontology is foremost a matter of (re)production rather than creation.
Resumo:
We present results, obtained by means of an analytic study and a numerical simulation, about the resonant condition necessary to produce a Localized Surface Plasmonic Resonance (LSPR) effect at the surface of metal nanospheres embedded in an amorphous silicon matrix. The study is based on a Lorentz dispersive model for a-Si:H permittivity and a Drude model for the metals. Considering the absorption spectra of a-Si:H, the best choice for the metal nanoparticles appears to be aluminium, indium or magnesium. No difference has been observed when considering a-SiC:H. Finite-difference time-domain (FDTD) simulation of an Al nanosphere embedded into an amorphous silicon matrix shows an increased scattering radius and the presence of LSPR induced by the metal/semiconductor interaction under green light (560 nm) illumination. Further results include the effect of the nanoparticles shape (nano-ellipsoids) in controlling the wavelength suitable to produce LSPR. It has been shown that is possible to produce LSPR in the red part of the visible spectrum (the most critical for a-Si:H solar cells applications in terms of light absorption enhancement) with aluminium nano-ellipsoids. As an additional results we may conclude that the double Lorentz-Lorenz model for the optical functions of a-Si:H is numerically stable in 3D simulations and can be used safely in the FDTD algorithm. A further simulation study is directed to determine an optimal spatial distribution of Al nanoparticles, with variable shapes, capable to enhance light absorption in the red part of the visible spectrum, exploiting light trapping and plasmonic effects. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Resumo:
Hyperspectral imaging can be used for object detection and for discriminating between different objects based on their spectral characteristics. One of the main problems of hyperspectral data analysis is the presence of mixed pixels, due to the low spatial resolution of such images. This means that several spectrally pure signatures (endmembers) are combined into the same mixed pixel. Linear spectral unmixing follows an unsupervised approach which aims at inferring pure spectral signatures and their material fractions at each pixel of the scene. The huge data volumes acquired by such sensors put stringent requirements on processing and unmixing methods. This paper proposes an efficient implementation of a unsupervised linear unmixing method on GPUs using CUDA. The method finds the smallest simplex by solving a sequence of nonsmooth convex subproblems using variable splitting to obtain a constraint formulation, and then applying an augmented Lagrangian technique. The parallel implementation of SISAL presented in this work exploits the GPU architecture at low level, using shared memory and coalesced accesses to memory. The results herein presented indicate that the GPU implementation can significantly accelerate the method's execution over big datasets while maintaining the methods accuracy.