140 resultados para Random Forests Classifier


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Motor task variation has been shown to be a key ingredient in skill transfer, retention, and structural learning. However, many studies only compare training of randomly varying tasks to either blocked or null training, and it is not clear how experiencing different nonrandom temporal orderings of tasks might affect the learning process. Here we study learning in human subjects who experience the same set of visuomotor rotations, evenly spaced between -60° and +60°, either in a random order or in an order in which the rotation angle changed gradually. We compared subsequent learning of three test blocks of +30°→-30°→+30° rotations. The groups that underwent either random or gradual training showed significant (P < 0.01) facilitation of learning in the test blocks compared with a control group who had not experienced any visuomotor rotations before. We also found that movement initiation times in the random group during the test blocks were significantly (P < 0.05) lower than for the gradual or the control group. When we fit a state-space model with fast and slow learning processes to our data, we found that the differences in performance in the test block were consistent with the gradual or random task variation changing the learning and retention rates of only the fast learning process. Such adaptation of learning rates may be a key feature of ongoing meta-learning processes. Our results therefore suggest that both gradual and random task variation can induce meta-learning and that random learning has an advantage in terms of shorter initiation times, suggesting less reliance on cognitive processes.

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A new approximate solution for the first passage probability of a stationary Gaussian random process is presented which is based on the estimation of the mean clump size. A simple expression for the mean clump size is derived in terms of the cumulative normal distribution function, which avoids the lengthy numerical integrations which are required by similar existing techniques. The method is applied to a linear oscillator and an ideal bandpass process and good agreement with published results is obtained. By making a slight modification to an existing analysis it is shown that a widely used empirical result for the asymptotic form of the first passage probability can be deduced theoretically.

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Using a chiral nematic liquid crystal with a negative dielectric anisotropy, it is possible to switch between band-edge laser emission and random laser emission with an electric field. At low frequencies (1 kHz), random laser emission is observed as a result of scattering due to electro-hydrodynamic instabilities. However, band-edge laser emission is found to occur at higher frequencies (5 kHz), where the helix is stabilized due to dielectric coupling. These results demonstrate a method by which the linewidth of the laser source can be readily controlled externally (from 4 nm to 0.5 nm) using electric fields. © 2012 American Institute of Physics.

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Smectic A liquid crystals, based upon molecular structures that consist of combined siloxane and mesogenic moieties, exhibit strong multiple scattering of light with and without the presence of an electric field. This paper demonstrates that when one adds a laser dye to these compounds it is possible to observe random laser emission under optical excitation, and that the output can be varied depending upon the scattering state that is induced by the electric field. Results are presented to show that the excitation threshold of a dynamic scattering state, consisting of chaotic motion due to electro-hydrodynamic instabilities, exhibits lower lasing excitation thresholds than the scattering states that exist in the absence of an applied electric field. However, the lowest threshold is observed for a dynamic scattering state that does not have the largest scattering strength but which occurs when there is optimization of the combined light absorption and scattering properties. © 2012 American Institute of Physics.

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We have grown vertically aligned single-walled carbon nanotube forests with an area density of 1.5 × 10(13) cm(-2), the highest yet achieved, by reducing the average diameter of the nanotubes. We use a nanolaminate Fe-Al(2)O(3) catalyst design consisting of three layers of Al(2)O(3), Fe, and Al(2)O(3), in which the lower Al(2)O(3) layer is densified by an oxygen plasma treatment to increase its diffusion barrier properties, to allow a thinner catalyst layer to be used. This high nanotube density is desirable for using carbon nanotubes as interconnects in integrated circuits.

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Our group recently reproduced the water-assisted growth method, so-called "SuperGrowth", of millimeter-thick single-walled carbon nanotube (SWNT) forests by using C2H4/H2/H2O/Ar reactant gas and Fe/Al2O3, catalyst. In this current work, a parametric study was carried out on both reaction and catalyst conditions. Results revealed that a thin Fe catalyst layer (about 0.5 nm) yielded rapid growth of SWNTs only when supported on Al2O3, and that Al2O3 support enhanced the activity of Fe, Co, and Ni catalysts. The growth window for the rapid SWNT growth was narrow, however. Optimum amount of added H2O increased the SWNT growth rate but further addition of H2O degraded both the SWNT growth rate and quality. Addition of H2 was also essential for rapid SWNT growth, but again, further addition decreased both the SWNT growth rate and quality. Because Al2O3 catalyzes hydrocarbon reforming, Al2O3 support possibly enhances the SWNT growth rate by supplying the carbon source to the catalyst nanoparticles. The origin of the narrow window for rapid SWNT growth is also discussed.