102 resultados para Central Processing

em Cambridge University Engineering Department Publications Database


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The change in acoustic characteristics in personal computers to console gaming and home entertainment systems with the change in the Graphics Processing Unit (GPU), is presented. The tests are carried out using identical configurations of the software and system hardware. The prime components of the hardware used in the project are central processing unit, motherboard, hard disc drive, memory, power supply, optical drive, and additional cooling system. The results from the measurements taken for each GPU tested are analyzed and compared. The test results are obtained using a photo tachometer and reflective tape adhered to one particular fan blade. The test shows that loudness is a psychoacoustic metric developed by Zwicker and Fastal that aims to quantify how loud a sound is perceived as compared to a standard sound. The acoustic experiment reveals that the inherent noise generation mechanism increases with the increase of the complexity of the cooling solution.

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A new three-dimensional Navier-Stokes solver for flows in turbomachines has been developed. The new solver is based on the latest version of the Denton codes, but has been implemented to run on Graphics Processing Units (GPUs) instead of the traditional Central Processing Unit (CPU). The change in processor enables an order-of-magnitude reduction in run-time due to the higher performance of the GPU. Scaling results for a 16 node GPU cluster are also presented, showing almost linear scaling for typical turbomachinery cases. For validation purposes, a test case consisting of a three-stage turbine with complete hub and casing leakage paths is described. Good agreement is obtained with previously published experimental results. The simulation runs in less than 10 minutes on a cluster with four GPUs. Copyright © 2009 by ASME.

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A method for interpreting elastic-lidar return signals in heavily-polluted atmospheres is presented. It is based on an equation derived directly from the classic lidar equation, which highlights gradients of the atmospheric backscattering properties along the laser optical path. The method is evaluated by comparing its results with those obtained with the differential absorption technique. The results were obtained from locating and ranging measurements in pollutant plumes and contaminated environments around central México. © World Scientific Publishing Company.

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Reward processing is linked to specific neuromodulatory systems with a dopaminergic contribution to reward learning and motivational drive being well established. Neuromodulatory influences on hedonic responses to actual receipt of reward, or punishment, referred to as experienced utility are less well characterized, although a link to the endogenous opioid system is suggested. Here, in a combined functional magnetic resonance imaging-psychopharmacological investigation, we used naloxone to block central opioid function while subjects performed a gambling task associated with rewards and losses of different magnitudes, in which the mean expected value was always zero. A graded influence of naloxone on reward outcome was evident in an attenuation of pleasure ratings for larger reward outcomes, an effect mirrored in attenuation of brain activity to increasing reward magnitude in rostral anterior cingulate cortex. A more striking effect was seen for losses such that under naloxone all levels of negative outcome were rated as more unpleasant. This hedonic effect was associated with enhanced activity in anterior insula and caudal anterior cingulate cortex, areas implicated in aversive processing. Our data indicate that a central opioid system contributes to both reward and loss processing in humans and directly modulates the hedonic experience of outcomes.

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Statistical analysis of diffusion tensor imaging (DTI) data requires a computational framework that is both numerically tractable (to account for the high dimensional nature of the data) and geometric (to account for the nonlinear nature of diffusion tensors). Building upon earlier studies exploiting a Riemannian framework to address these challenges, the present paper proposes a novel metric and an accompanying computational framework for DTI data processing. The proposed approach grounds the signal processing operations in interpolating curves. Well-chosen interpolating curves are shown to provide a computational framework that is at the same time tractable and information relevant for DTI processing. In addition, and in contrast to earlier methods, it provides an interpolation method which preserves anisotropy, a central information carried by diffusion tensor data. © 2013 Springer Science+Business Media New York.

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Thickness of the near-interface regions (NIR) and central bulk ohmic resistivity in lead lanthanum zirconate titanate ferroelectric thin films were investigated. A method to separate the low-resistive near-interface regions (NIRs) from the high-resistive central bulk region (CBR) in ferroelectric thin films was presented. Results showed that the thickness of the NIRs depended on the electrode materials in use and the CBR resistivity depended on the impurity doping levels.