999 resultados para Dynamic texture


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The optical constants of two cyanine dye films that we prepared were measured with a RAP-1-type (RAP is rotating analyzer and polarizer) spectroscopic ellipsometer. Toward making a simplified model for the wafers of a recordable compact disk (CD-R), we give their optimization designs developed with the cyanine dye films. in addition, the dynamic storage performances of two sample disks were tested by our dynamic storage testing system. Measurement results of the sample disks were obtained to test and verify our film designs. (C) 2000 Optical Society of America. OCIS codes: 160.4890, 160.4760, 210.4810.

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Recent theoretical and experimental results suggested that the silver superlens could be constructed through controlling silver thin film thickness and preparation conditions, and applied in subdiffraction-limited optical imaging and optical lithography. In this work, we report another significant application of silver superlens-ultrahigh density optical data storage. With the silver superlens the subdiffraction-limited pit arrays on an optical disk are dynamically read out and the carrier-to-noise ratio can reach 25 dB for the thin film thickness of 46 nm. The readout laser power and readout velocity have little effect on the carrier-to-noise ratio. Additionally, in our experiment the silver thin film thickness needs to be controlled in the range from 20 to 80 nm.

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Fast moving arrays of periodic sub-diffraction-limit pits were dynamically read out via a silver thin film. The mechanism of the dynamic readout is analysed and discussed in detail, both experimentally and theoretically. The analysis and experiment show that, in the course of readout, surface plasmons can be excited at the silver/air interface by the focused laser beam and amplified by the silver thin film. The surface plasmons are transmitted into the substrate/silver interface with a large enhancement. The surface waves at the substrate/silver interface are scattered by the sinusoidal pits of sub-diffraction-limit size. The scattered waves are collected by a converging lens and guided into the detector for the readout.

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In this study we employed a dynamic recurrent neural network (DRNN) in a novel fashion to reveal characteristics of control modules underlying the generation of muscle activations when drawing figures with the outstretched arm. We asked healthy human subjects to perform four different figure-eight movements in each of two workspaces (frontal plane and sagittal plane). We then trained a DRNN to predict the movement of the wrist from information in the EMG signals from seven different muscles. We trained different instances of the same network on a single movement direction, on all four movement directions in a single movement plane, or on all eight possible movement patterns and looked at the ability of the DRNN to generalize and predict movements for trials that were not included in the training set. Within a single movement plane, a DRNN trained on one movement direction was not able to predict movements of the hand for trials in the other three directions, but a DRNN trained simultaneously on all four movement directions could generalize across movement directions within the same plane. Similarly, the DRNN was able to reproduce the kinematics of the hand for both movement planes, but only if it was trained on examples performed in each one. As we will discuss, these results indicate that there are important dynamical constraints on the mapping of EMG to hand movement that depend on both the time sequence of the movement and on the anatomical constraints of the musculoskeletal system. In a second step, we injected EMG signals constructed from different synergies derived by the PCA in order to identify the mechanical significance of each of these components. From these results, one can surmise that discrete-rhythmic movements may be constructed from three different fundamental modules, one regulating the co-activation of all muscles over the time span of the movement and two others elliciting patterns of reciprocal activation operating in orthogonal directions.

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This paper investigates whether the effect of political institutions on sectoral economic performance is determined by the level of technological development of industries. Building on previous studies on the linkages among political institutions, technology and economic growth, we employ the dynamic panel Generalized Method of Moments (GMM) estimator for a sample of 4,134 country-industries from 61 industries and 89 countries over the 1990-2010 period. Our main findings suggest that changes of political institutions towards higher levels of democracy, political rights and civil liberties enhance economic growth in technologically developed industries. On the contrary, the same institutional changes might retard economic growth of those industries that are below a technological development threshold. Overall, these results give evidence of a technologically conditioned nature of political institutions to be growth-promoting.