941 resultados para Time Line


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This paper demonstrates how a finite element model which exploits domain decomposition is applied to the analysis of three-phase induction motors. It is shown that a significant gain in cpu time results when compared with standard finite element analysis. Aspects of the application of the method which are particular to induction motors are considered: the means of improving the convergence of the nonlinear finite element equations; the choice of symmetrical sub-domains; the modelling of relative movement; and the inclusion of periodic boundary conditions. © 1999 IEEE.

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In this paper a recently published finite element method, which combines domain decomposition with a novel technique for solving nonlinear magnetostatic finite element problems is described. It is then shown how the method can be extended to, and optimised for, the solution of time-domain problems. © 1999 IEEE.

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The advent of virtualization and cloud computing technologies necessitates the development of effective mechanisms for the estimation and reservation of resources needed by content providers to deliver large numbers of video-on-demand (VOD) streams through the cloud. Unfortunately, capacity planning for the QoS-constrained delivery of a large number of VOD streams is inherently difficult as VBR encoding schemes exhibit significant bandwidth variability. In this paper, we present a novel resource management scheme to make such allocation decisions using a mixture of per-stream reservations and an aggregate reservation, shared across all streams to accommodate peak demands. The shared reservation provides capacity slack that enables statistical multiplexing of peak rates, while assuring analytically bounded frame-drop probabilities, which can be adjusted by trading off buffer space (and consequently delay) and bandwidth. Our two-tiered bandwidth allocation scheme enables the delivery of any set of streams with less bandwidth (or equivalently with higher link utilization) than state-of-the-art deterministic smoothing approaches. The algorithm underlying our proposed frame-work uses three per-stream parameters and is linear in the number of servers, making it particularly well suited for use in an on-line setting. We present results from extensive trace-driven simulations, which confirm the efficiency of our scheme especially for small buffer sizes and delay bounds, and which underscore the significant realizable bandwidth savings, typically yielding losses that are an order of magnitude or more below our analytically derived bounds.

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For many applications of emotion recognition, such as virtual agents, the system must select responses while the user is speaking. This requires reliable on-line recognition of the user’s affect. However most emotion recognition systems are based on turnwise processing. We present a novel approach to on-line emotion recognition from speech using Long Short-Term Memory Recurrent Neural Networks. Emotion is recognised frame-wise in a two-dimensional valence-activation continuum. In contrast to current state-of-the-art approaches, recognition is performed on low-level signal frames, similar to those used for speech recognition. No statistical functionals are applied to low-level feature contours. Framing at a higher level is therefore unnecessary and regression outputs can be produced in real-time for every low-level input frame. We also investigate the benefits of including linguistic features on the signal frame level obtained by a keyword spotter.

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A comparison is presented of the temporally resolved resonance-line emission from the Ne-like Ge XUV laser (pumped with nanosecond pulses) with the predictions for the same emission from the hydro-atomic code EHYBRID. The specific lines chosen were the two 3s-2p Ne-like lines at 10.01 and 9.762 Angstrom, and the 3s-2p F-like group of lines in the 9.4-9.6 Angstrom region. Modification of the code to include 112 excited levels of the F-like ion facilitated a direct comparison between experiment and model of (i) the temporal variation of the emissions and (ii) the variation of the peak intensity ratios of the F-like to Ne-like emissions with irradiance on target.

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We investigate line formation processes in Type IIb supernovae (SNe) from 100 to 500 days post-explosion using spectral synthesis calculations. The modelling identifies the nuclear burning layers and physical mechanisms that produce the major emission lines, and the diagnostic potential of these. We compare the model calculations with data on the three best observed Type IIb SNe to-date - SN 1993J, SN 2008ax, and SN 2011dh. Oxygen nucleosynthesis depends sensitively on the main-sequence mass of the star and modelling of the [O I] lambda lambda 6300, 6364 lines constrains the progenitors of these three SNe to the M-ZAMS = 12-16 M-circle dot range (ejected oxygen masses 0.3-0.9 M-circle dot), with SN 2011dh towards the lower end and SN 1993J towards the upper end of the range. The high ejecta masses from M-ZAMS greater than or similar to 17 M-circle dot progenitors give rise to brighter nebular phase emission lines than observed. Nucleosynthesis analysis thus supports a scenario of low-to-moderate mass progenitors for Type IIb SNe, and by implication an origin in binary systems. We demonstrate how oxygen and magnesium recombination lines may be combined to diagnose the magnesium mass in the SN ejecta. For SN 2011dh, a magnesium mass of 0.02-0.14 M-circle dot is derived, which gives a Mg/O production ratio consistent with the solar value. Nitrogen left in the He envelope from CNO burning gives strong [N II] lambda lambda 6548, 6583 emission lines that dominate over Ha emission in our models. The hydrogen envelopes of Type IIb SNe are too small and dilute to produce any noticeable H alpha emission or absorption after similar to 150 days, and nebular phase emission seen around 6550 angstrom is in many cases likely caused by [N II] lambda lambda 6548, 6583. Finally, the influence of radiative transport on the emergent line profiles is investigated. Significant line blocking in the metal core remains for several hundred days, which affects the emergent spectrum. These radiative transfer effects lead to early-time blueshifts of the emission line peaks, which gradually disappear as the optical depths decrease with time. The modelled evolution of this effect matches the observed evolution in SN 2011dh.

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Spectroscopic studies of line emission intensities and ratios offer an attractive option in the\r\ndevelopment of non-invasive plasma diagnostics. Evaluating ratios of selected He I line\r\nemission profiles from the singlet and triplet neutral helium spin systems allows for simultaneous\r\nmeasurement of electron density (ne) and temperature (Te) profiles. Typically, this powerful\r\ndiagnostic tool is limited by the relatively long relaxation times of the 3S metastable term of helium\r\nthat populates the triplet spin system, and on which electron temperature sensitive lines are based.\r\nBy developing a time dependent analytical solution, we model the time evolution of the two spin\r\nsystems. We present a hybrid time dependent/independent line ratio solution that improves the\r\nrange of application of this diagnostic technique in the scrape-off layer (SOL) and edge plasma\r\nregions when comparing it against the current equilibrium line ratio helium model used at\r\nTEXTOR.

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The recent drive towards timely multiple product realizations has caused most Manufacturing Enterprises (MEs) to develop more flexible assembly lines supported by better manufacturing design and planning. The aim of this work is to develop a methodology which will support feasibility analyses of assembly tasks, in order to simulate either a manufacturing process or a single work-cell in which digital human models act. The methodology has been applied in a case study relating to a railway industry. Simulations were applied to help standardize the methodology and suggest new solutions for realizing ergonomic and efficient assembly processes in the railway industry.

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In this paper, we present an on-line estimation algorithm for an uncertain time delay in a continuous system based on the observational input-output data, subject to observational noise. The first order Pade approximation is used to approximate the time delay. At each time step, the algorithm combines the well known Kalman filter algorithm and the recursive instrumental variable least squares (RIVLS) algorithm in cascade form. The instrumental variable least squares algorithm is used in order to achieve the consistency of the delay parameter estimate, since an error-in-the-variable model is involved. An illustrative example is utilized to demonstrate the efficacy of the proposed approach.

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We report on the first realtime ionospheric predictions network and its capabilities to ingest a global database and forecast F-layer characteristics and "in situ" electron densities along the track of an orbiting spacecraft. A global network of ionosonde stations reported around-the-clock observations of F-region heights and densities, and an on-line library of models provided forecasting capabilities. Each model was tested against the incoming data; relative accuracies were intercompared to determine the best overall fit to the prevailing conditions; and the best-fit model was used to predict ionospheric conditions on an orbit-to-orbit basis for the 12-hour period following a twice-daily model test and validation procedure. It was found that the best-fit model often provided averaged (i.e., climatologically-based) accuracies better than 5% in predicting the heights and critical frequencies of the F-region peaks in the latitudinal domain of the TSS-1R flight path. There was a sharp contrast however, in model-measurement comparisons involving predictions of actual, unaveraged, along-track densities at the 295 km orbital altitude of TSS-1R In this case, extrema in the first-principle models varied by as much as an order of magnitude in density predictions, and the best-fit models were found to disagree with the "in situ" observations of Ne by as much as 140%. The discrepancies are interpreted as a manifestation of difficulties in accurately and self-consistently modeling the external controls of solar and magnetospheric inputs and the spatial and temporal variabilities in electric fields, thermospheric winds, plasmaspheric fluxes, and chemistry.