9 resultados para random number generation

em Cambridge University Engineering Department Publications Database


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This study investigated the neuromuscular mechanisms underlying the initial stage of adaptation to novel dynamics. A destabilizing velocity-dependent force field (VF) was introduced for sets of three consecutive trials. Between sets a random number of 4-8 null field trials were interposed, where the VF was inactivated. This prevented subjects from learning the novel dynamics, making it possible to repeatedly recreate the initial adaptive response. We were able to investigate detailed changes in neural control between the first, second and third VF trials. We identified two feedforward control mechanisms, which were initiated on the second VF trial and resulted in a 50% reduction in the hand path error. Responses to disturbances encountered on the first VF trial were feedback in nature, i.e. reflexes and voluntary correction of errors. However, on the second VF trial, muscle activation patterns were modified in anticipation of the effects of the force field. Feedforward cocontraction of all muscles was used to increase the viscoelastic impedance of the arm. While stiffening the arm, subjects also exerted a lateral force to counteract the perturbing effect of the force field. These anticipatory actions indicate that the central nervous system responds rapidly to counteract hitherto unfamiliar disturbances by a combination of increased viscoelastic impedance and formation of a crude internal dynamics model.

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Transposon mutagenesis has been applied to a hyper-invasive clinical isolate of Campylobacter jejuni, 01/51. A random transposon mutant library was screened in an in vitro assay of invasion and 26 mutants with a significant reduction in invasion were identified. Given that the invasion potential of C. jejuni is relatively poor compared to other enteric pathogens, the use of a hyper-invasive strain was advantageous as it greatly facilitated the identification of mutants with reduced invasion. The location of the transposon insertion in 23 of these mutants has been determined; all but three of the insertions are in genes also present in the genome-sequenced strain NCTC 11168. Eight of the mutants contain transposon insertions in one region of the genome (approximately 14 kb), which when compared with the genome of NCTC 11168 overlaps with one of the previously reported plasticity regions and is likely to be involved in genomic variation between strains. Further characterization of one of the mutants within this region has identified a gene that might be involved in adhesion to host cells.

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A pivotal problem in Bayesian nonparametrics is the construction of prior distributions on the space M(V) of probability measures on a given domain V. In principle, such distributions on the infinite-dimensional space M(V) can be constructed from their finite-dimensional marginals---the most prominent example being the construction of the Dirichlet process from finite-dimensional Dirichlet distributions. This approach is both intuitive and applicable to the construction of arbitrary distributions on M(V), but also hamstrung by a number of technical difficulties. We show how these difficulties can be resolved if the domain V is a Polish topological space, and give a representation theorem directly applicable to the construction of any probability distribution on M(V) whose first moment measure is well-defined. The proof draws on a projective limit theorem of Bochner, and on properties of set functions on Polish spaces to establish countable additivity of the resulting random probabilities.

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The Reynolds number influence on turbulent blocking effects by a rigid plane boundary is studied using direct numerical simulation (DNS). A new forcing method using 'simple model eddies' (Townsend 1976) for DNS of stationary homogeneous isotropic turbulence is proposed. A force field is obtained in real space by sprinkling many space-filling 'simple model eddies' whose centers are randomly but uniformly distributed in space and whose axes of rotation are random. The method is applied to a shear-free turbulent boundary layer over a rigid plane boundary and the blocking effects are investigated. The results show that stationary homogeneous isotropic turbulence is generated in real space using the present method. By using different model eddies with different sizes and rotation speeds, we could change the turbulence properties such as the integral and micro scales, the turbulent Reynolds number and the isotropy of turbulence. Turbulence intensities near the wall showed good agreements with the previous measurement and the linear analysis based on a rapid distortion theory (RDT). The splat effect (i.e., turbulence intensities of the components parallel to the boundary are amplified) occurs near the boundary and the viscous effect prohibits the splat effect at the quasi steady state at low Reynolds number.

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DNS of turbulent hydrogen-air premixed flame is conducted for freely propagating and V-flames, using complex chemical kinetics. The results are analysed to study the influence of flame configuration on the turbulence-scalar interaction, which is critical for the scalar gradient generation process. The result suggests that this interaction process is not influenced by the flame configuration and the flame normal is found to predominantly align with the most extensive strain in the region of intense heat release.

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This paper considers the estimation of statistics of displacement of a vibrating rectangular plate with random wave scatterers. The influence of uncertainty is investigated using point impedance theory. Coherent boundary effects are seen, which decrease when the number of scatterers increases. The boundary effect is investigated using images and the first side and corner reflections are found to be a minimum requirement to estimate the spatial correlation. Statistics for point driven response are investigated under the assumption that the statistics of the natural frequencies follow those of the Gaussian Orthogonal Ensemble (GOE). The estimates are compared with Monte Carlo simulation results, and they show good agreement. © 2012 Elsevier Ltd. All rights reserved.

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The generation of ultrashort optical pulses by semiconductor lasers has been extensively studied for many years. A number of methods, including gain-/Q-switching and different types of mode locking, have been exploited for the generation of picosecond and sub-picosecond pulses [1]. However, the shortest pulses produced by diode lasers are still much longer and weaker than those that are generated by advanced mode-locked solid-state laser systems [2]. On the other hand, an interesting class of devices based on superradiant emission from multiple contact diode laser structures has also been recently reported [3]. Superradiance (SR) is a transient quantum optics phenomenon based on the cooperative radiative recombination of a large number of oscillators, including atoms, molecules, e-h pairs, etc. SR in semiconductors can be used for the study of fundamental properties of e-h ensembles such as photon-mediated pairing, non-equilibrium e-h condensation, BSC-like coherent states and related phenomena. Due to the intrinsic parameters of semiconductor media, SR emission typically results in the generation of a high-power optical pulse or pulse train, where the pulse duration can be much less than 1 ps, under optimised bias conditions. Advantages of this technique over mode locking in semiconductor laser structures include potentially shorter pulsewidths and much larger peak powers. Moreover, the pulse repetition rate of mode-locked pulses is fixed by the cavity round trip time, whereas the repetition rate of SR pulses is controlled by the current bias and can be varied over a wide range. © 2012 IEEE.

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There has been an increasing interest in applying biological principles to the design and control of robots. Unlike industrial robots that are programmed to execute a rather limited number of tasks, the new generation of bio-inspired robots is expected to display a wide range of behaviours in unpredictable environments, as well as to interact safely and smoothly with human co-workers. In this article, we put forward some of the properties that will characterize these new robots: soft materials, flexible and stretchable sensors, modular and efficient actuators, self-organization and distributed control. We introduce a number of design principles; in particular, we try to comprehend the novel design space that now includes soft materials and requires a completely different way of thinking about control. We also introduce a recent case study of developing a complex humanoid robot, discuss the lessons learned and speculate about future challenges and perspectives.