994 resultados para Cumulative time


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Considering ultrasound propagation through complex composite media as an array of parallel sonic rays, a comparison of computer simulated prediction with experimental data has previously been reported for transmission mode (where one transducer serves as transmitter, the other as receiver) in a series of ten acrylic step-wedge samples, immersed in water, exhibiting varying degrees of transit time inhomogeneity. In this study, the same samples were used but in pulse-echo mode, where the same ultrasound transducer served as both transmitter and receiver, detecting both ‘primary’ (internal sample interface) and ‘secondary’ (external sample interface) echoes. A transit time spectrum (TTS) was derived, describing the proportion of sonic rays with a particular transit time. A computer simulation was performed to predict the transit time and amplitude of various echoes created, and compared with experimental data. Applying an amplitude-tolerance analysis, 91.7±3.7% of the simulated data was within ±1 standard deviation (STD) of the experimentally measured amplitude-time data. Correlation of predicted and experimental transit time spectra provided coefficients of determination (R2) ranging from 100.0% to 96.8% for the various samples tested. The results acquired from this study provide good evidence for the concept of parallel sonic rays. Further, deconvolution of experimental input and output signals has been shown to provide an effective method to identify echoes otherwise lost due to phase cancellation. Potential applications of pulse-echo ultrasound transit time spectroscopy (PE-UTTS) include improvement of ultrasound image fidelity by improving spatial resolution and reducing phase interference artefacts.

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The acceptance of broadband ultrasound attenuation (BUA) for the assessment of osteoporosis suffers from a limited understanding of both ultrasound wave propagation through cancellous bone and its exact dependence upon the material and structural properties. It has recently been proposed that ultrasound wave propagation in cancellous bone may be described by a concept of parallel sonic rays; the transit time of each ray defined by the proportion of bone and marrow propagated. A Transit Time Spectrum (TTS) describes the proportion of sonic rays having a particular transit time, effectively describing the lateral inhomogeneity of transit times over the surface aperture of the receive ultrasound transducer. The aim of this study was to test the hypothesis that the solid volume fraction (SVF) of simplified bone:marrow replica models may be reliably estimated from the corresponding ultrasound transit time spectrum. Transit time spectra were derived via digital deconvolution of the experimentally measured input and output ultrasonic signals, and compared to predicted TTS based on the parallel sonic ray concept, demonstrating agreement in both position and amplitude of spectral peaks. Solid volume fraction was calculated from the TTS; agreement between true (geometric calculation) with predicted (computer simulation) and experimentally-derived values were R2=99.9% and R2=97.3% respectively. It is therefore envisaged that ultrasound transit time spectroscopy (UTTS) offers the potential to reliably estimate bone mineral density and hence the established T-score parameter for clinical osteoporosis assessment.

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The quality of ultrasound computed tomography imaging is primarily determined by the accuracy of ultrasound transit time measurement. A major problem in analysis is the overlap of signals making it difficult to detect the correct transit time. The current standard is to apply a matched-filtering approach to the input and output signals. This study compares the matched-filtering technique with active set deconvolution to derive a transit time spectrum from a coded excitation chirp signal and the measured output signal. The ultrasound wave travels in a direct and a reflected path to the receiver, resulting in an overlap in the recorded output signal. The matched-filtering and deconvolution techniques were applied to determine the transit times associated with the two signal paths. Both techniques were able to detect the two different transit times; while matched-filtering has a better accuracy (0.13 μs vs. 0.18 μs standard deviation), deconvolution has a 3.5 times improved side-lobe to main-lobe ratio. A higher side-lobe suppression is important to further improve image fidelity. These results suggest that a future combination of both techniques would provide improved signal detection and hence improved image fidelity.

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The fault-tolerant multiprocessor (ftmp) is a bus-based multiprocessor architecture with real-time and fault- tolerance features and is used in critical aerospace applications. A preliminary performance evaluation is of crucial importance in the design of such systems. In this paper, we review stochastic Petri nets (spn) and developspn-based performance models forftmp. These performance models enable efficient computation of important performance measures such as processing power, bus contention, bus utilization, and waiting times.

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Three simulations of evapotranspiration were done with two values of time step,viz 10 min and one day. Inputs to the model were weather data, including directly measured upward and downward radiation, and soil characteristics. Three soils were used for each simulation. Analysis of the results shows that the time step has a direct influence on the prediction of potential evapotranspiration, but a complex interaction of this effect with the soil moisture characteristic, rate of increase of ground cover and bare soil evaporation determines the actual transpiration predicted. The results indicate that as small a time step as possible should be used in the simulation.

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A forest of quadtrees is a refinement of a quadtree data structure that is used to represent planar regions. A forest of quadtrees provides space savings over regular quadtrees by concentrating vital information. The paper presents some of the properties of a forest of quadtrees and studies the storage requirements for the case in which a single 2m × 2m region is equally likely to occur in any position within a 2n × 2n image. Space and time efficiency are investigated for the forest-of-quadtrees representation as compared with the quadtree representation for various cases.

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For clustered survival data, the traditional Gehan-type estimator is asymptotically equivalent to using only the between-cluster ranks, and the within-cluster ranks are ignored. The contribution of this paper is two fold: - (i) incorporating within-cluster ranks in censored data analysis, and; - (ii) applying the induced smoothing of Brown and Wang (2005, Biometrika) for computational convenience. Asymptotic properties of the resulting estimating functions are given. We also carry out numerical studies to assess the performance of the proposed approach and conclude that the proposed approach can lead to much improved estimators when strong clustering effects exist. A dataset from a litter-matched tumorigenesis experiment is used for illustration.

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There are numerous load estimation methods available, some of which are captured in various online tools. However, most estimators are subject to large biases statistically, and their associated uncertainties are often not reported. This makes interpretation difficult and the estimation of trends or determination of optimal sampling regimes impossible to assess. In this paper, we first propose two indices for measuring the extent of sampling bias, and then provide steps for obtaining reliable load estimates by minimizing the biases and making use of possible predictive variables. The load estimation procedure can be summarized by the following four steps: - (i) output the flow rates at regular time intervals (e.g. 10 minutes) using a time series model that captures all the peak flows; - (ii) output the predicted flow rates as in (i) at the concentration sampling times, if the corresponding flow rates are not collected; - (iii) establish a predictive model for the concentration data, which incorporates all possible predictor variables and output the predicted concentrations at the regular time intervals as in (i), and; - (iv) obtain the sum of all the products of the predicted flow and the predicted concentration over the regular time intervals to represent an estimate of the load. The key step to this approach is in the development of an appropriate predictive model for concentration. This is achieved using a generalized regression (rating-curve) approach with additional predictors that capture unique features in the flow data, namely the concept of the first flush, the location of the event on the hydrograph (e.g. rise or fall) and cumulative discounted flow. The latter may be thought of as a measure of constituent exhaustion occurring during flood events. The model also has the capacity to accommodate autocorrelation in model errors which are the result of intensive sampling during floods. Incorporating this additional information can significantly improve the predictability of concentration, and ultimately the precision with which the pollutant load is estimated. We also provide a measure of the standard error of the load estimate which incorporates model, spatial and/or temporal errors. This method also has the capacity to incorporate measurement error incurred through the sampling of flow. We illustrate this approach using the concentrations of total suspended sediment (TSS) and nitrogen oxide (NOx) and gauged flow data from the Burdekin River, a catchment delivering to the Great Barrier Reef. The sampling biases for NOx concentrations range from 2 to 10 times indicating severe biases. As we expect, the traditional average and extrapolation methods produce much higher estimates than those when bias in sampling is taken into account.

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There is a need for better understanding of the processes and new ideas to develop traditional pharmaceutical powder manufacturing procedures. Process analytical technology (PAT) has been developed to improve understanding of the processes and establish methods to monitor and control processes. The interest is in maintaining and even improving the whole manufacturing process and the final products at real-time. Process understanding can be a foundation for innovation and continuous improvement in pharmaceutical development and manufacturing. New methods are craved for to increase the quality and safety of the final products faster and more efficiently than ever before. The real-time process monitoring demands tools, which enable fast and noninvasive measurements with sufficient accuracy. Traditional quality control methods have been laborious and time consuming and they are performed off line i.e. the analysis has been removed from process area. Vibrational spectroscopic methods are responding this challenge and their utilisation have increased a lot during the past few years. In addition, other methods such as colour analysis can be utilised in noninvasive real-time process monitoring. In this study three pharmaceutical processes were investigated: drying, mixing and tabletting. In addition tablet properties were evaluated. Real-time monitoring was performed with NIR and Raman spectroscopies, colour analysis, particle size analysis and compression data during tabletting was evaluated using mathematical modelling. These methods were suitable for real-time monitoring of pharmaceutical unit operations and increase the knowledge of the critical parameters in the processes and the phenomena occurring during operations. They can improve our process understanding and therefore, finally, enhance the quality of final products.

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Gulland's [Gulland, J.A., 1965. Estimation of mortality rates. Annex to Arctic Fisheries Working Group Report (meeting in Hamburg, January 1965). ICES. C.M. 1965, Doc. No. 3 (mimeographed)] virtual population analysis (VPA) is commonly used for studying the dynamics of harvested fish populations. However, it necessitates the solving of a nonlinear equation for the instantaneous rate of fishing mortality of the fish in a population. Pope [Pope, J.G., 1972. An investigation of the accuracy of Virtual Population Analysis using cohort analysis. ICNAF Res. Bull. 9, 65-74. Also available in D.H. Cushing (ed.) (1983), Key Papers on Fish Populations, p. 291-301, IRL Press, Oxford, 405 p.] eliminated this necessity in his cohort analysis by approximating its underlying age- and time-dependent population model. His approximation has since become one of the most commonly used age- and time-dependent fish population models in fisheries science. However, some of its properties are not well understood. For example, many assert that it describes the dynamics of a fish population, from which the catch of fish is taken instantaneously in the middle of the year. Such an assertion has never been proven, nor has its implied instantaneous rate of fishing mortality of the fish of a particular age at a particular time been examined, nor has its implied catch equation been derived from a general catch equation. In this paper, we prove this assertion, examine its implied instantaneous rate of fishing mortality of the fish of a particular age at a particular time, derive its implied catch equation from a general catch equation, and comment on how to structure an age- and time-dependent population model to ensure its internal consistency. This work shows that Gulland's (1965) virtual population analysis and Pope's (1972) cohort analysis lie at the opposite end of a continuous spectrum as a general model for a seasonally occurring fishery; Pope's (1972) approximation implies an infinitely large instantaneous rate of fishing mortality of the fish of a particular age at a particular time in a fishing season of zero length; and its implied catch equation has an undefined instantaneous rate of fishing mortality of the fish in a population, but a well-defined cumulative instantaneous rate of fishing mortality of the fish in the population. This work also highlights a need for a more careful treatment of the times of start and end of a fishing season in fish population models.

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A class of growth models incorporating time-dependent factors and stochastic perturbations are introduced. The proposed model includes the existing growth models used in fisheries as special cases. Particular attention is given to growth of a population (in average weight or length) from which observations are taken randomly each time and the analysis of tag-recapture data. Two real data sets are used for illustration: (a) to estimate the seasonal effect and population density effect on growth of farmed prawn (Penaeus monodon) from weight data and (b) to assess the effect of tagging on growth of barramundi (Lates calcarifer)

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The Macroscopic Fundamental Diagram (MFD) relates space-mean density and flow. Since the MFD represents the area-wide network traffic performance, studies on perimeter control strategies and network-wide traffic state estimation utilising the MFD concept have been reported. Most previous works have utilised data from fixed sensors, such as inductive loops, to estimate the MFD, which can cause biased estimation in urban networks due to queue spillovers at intersections. To overcome the limitation, recent literature reports the use of trajectory data obtained from probe vehicles. However, these studies have been conducted using simulated datasets; limited works have discussed the limitations of real datasets and their impact on the variable estimation. This study compares two methods for estimating traffic state variables of signalised arterial sections: a method based on cumulative vehicle counts (CUPRITE), and one based on vehicles’ trajectory from taxi Global Positioning System (GPS) log. The comparisons reveal some characteristics of taxi trajectory data available in Brisbane, Australia. The current trajectory data have limitations in quantity (i.e., the penetration rate), due to which the traffic state variables tend to be underestimated. Nevertheless, the trajectory-based method successfully captures the features of traffic states, which suggests that the trajectories from taxis can be a good estimator for the network-wide traffic states.

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Macro and micromixing time represent two extreme mixing time scales,which governs the whole hydrodynamics characteristics of the surface aeration systems. With the help of experimental and numerical analysis, simulation equation governing those times scale has been presented in the present work.

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Formative time lags in nitrogen, oxygen, and dry air are measured with and without a magnetic field over a range of gas pressures (0.05 ' p ' 20.2 torr 5 kPa to 2 MPa, electric field strengths (1.8xO14 EEs 60xlO V m l) and magnetic field strengths (85xl0-4 < B ' 16x10-2 Tesla). For experiments below the Paschen minimum, the electrodes are designed to ensure that breakdown occurs over longer gaps and for experiments above the Paschen minimum, a coaxial cylindrical system is employed. The experimental technique consists of applying pulse voltages to the gap at various constant values of E/p and B/p and measuring the time lags from which the formative time lags are separated. In the gases studed, formative time lags decrease on application of a magnetic field at a given pressure for conditions below the Paschen minimum. The voltages at which the formative time lags remain the same without and with magnetic fields are determined, and electron molecule collision frequencies (v/p) are determined using the Effective Reduced Electric Field [EREF] concept. With increasing ratio of E/p in crossed fields, v/p decreases in all the three gases. Measurements above the Paschen minimum yield formative time lags which increase on application of a magnetic field. Formative time lags in nitrogen in ExB fields are calculated assuming an average collision frequency of 8.5x109 sec-1 torr 1. It is concluded that the EREF concept can be applied to explain formative time lags in ExB fields.

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Both the semi-similar and self-similar flows due to a viscous fluid rotating with time dependent angular velocity over a porous disk of large radius at rest with or without a magnetic field are investigated. For the self-similar case the resulting equations for the suction and no mass transfer cases are solved numerically by quasilinearization method whereas for the semi-similar case and injection in the self-similar case an implicit finite difference method with Newton's linearization is employed. For rapid deceleration of fluid and for moderate suction in the case of self-similar flow there exists a layer of fluid, close to the disk surface where the sense of rotation is opposite to that of the fluid rotating far away. The velocity profiles in the absence of magnetic field are found to be oscillatory except for suction. For the accelerating freestream, (semi-similar flow) the effect of time is to reduce the amplitude of the oscillations of the velocity components. On the other hand the effect of time for the oscillating case is just the opposite.