958 resultados para Time measurements


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Several methods are examined which allow to produce forecasts for time series in the form of probability assignments. The necessary concepts are presented, addressing questions such as how to assess the performance of a probabilistic forecast. A particular class of models, cluster weighted models (CWMs), is given particular attention. CWMs, originally proposed for deterministic forecasts, can be employed for probabilistic forecasting with little modification. Two examples are presented. The first involves estimating the state of (numerically simulated) dynamical systems from noise corrupted measurements, a problem also known as filtering. There is an optimal solution to this problem, called the optimal filter, to which the considered time series models are compared. (The optimal filter requires the dynamical equations to be known.) In the second example, we aim at forecasting the chaotic oscillations of an experimental bronze spring system. Both examples demonstrate that the considered time series models, and especially the CWMs, provide useful probabilistic information about the underlying dynamical relations. In particular, they provide more than just an approximation to the conditional mean.

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The task of this paper is to develop a Time-Domain Probe Method for the reconstruction of impenetrable scatterers. The basic idea of the method is to use pulses in the time domain and the time-dependent response of the scatterer to reconstruct its location and shape. The method is based on the basic causality principle of timedependent scattering. The method is independent of the boundary condition and is applicable for limited aperture scattering data. In particular, we discuss the reconstruction of the shape of a rough surface in three dimensions from time-domain measurements of the scattered field. In practise, measurement data is collected where the incident field is given by a pulse. We formulate the time-domain fieeld reconstruction problem equivalently via frequency-domain integral equations or via a retarded boundary integral equation based on results of Bamberger, Ha-Duong, Lubich. In contrast to pure frequency domain methods here we use a time-domain characterization of the unknown shape for its reconstruction. Our paper will describe the Time-Domain Probe Method and relate it to previous frequency-domain approaches on sampling and probe methods by Colton, Kirsch, Ikehata, Potthast, Luke, Sylvester et al. The approach significantly extends recent work of Chandler-Wilde and Lines (2005) and Luke and Potthast (2006) on the timedomain point source method. We provide a complete convergence analysis for the method for the rough surface scattering case and provide numerical simulations and examples.

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This research presents a novel multi-functional system for medical Imaging-enabled Assistive Diagnosis (IAD). Although the IAD demonstrator has focused on abdominal images and supports the clinical diagnosis of kidneys using CT/MRI imaging, it can be adapted to work on image delineation, annotation and 3D real-size volumetric modelling of other organ structures such as the brain, spine, etc. The IAD provides advanced real-time 3D visualisation and measurements with fully automated functionalities as developed in two stages. In the first stage, via the clinically driven user interface, specialist clinicians use CT/MRI imaging datasets to accurately delineate and annotate the kidneys and their possible abnormalities, thus creating “3D Golden Standard Models”. Based on these models, in the second stage, clinical support staff i.e. medical technicians interactively define model-based rules and parameters for the integrated “Automatic Recognition Framework” to achieve results which are closest to that of the clinicians. These specific rules and parameters are stored in “Templates” and can later be used by any clinician to automatically identify organ structures i.e. kidneys and their possible abnormalities. The system also supports the transmission of these “Templates” to another expert for a second opinion. A 3D model of the body, the organs and their possible pathology with real metrics is also integrated. The automatic functionality was tested on eleven MRI datasets (comprising of 286 images) and the 3D models were validated by comparing them with the metrics from the corresponding “3D Golden Standard Models”. The system provides metrics for the evaluation of the results, in terms of Accuracy, Precision, Sensitivity, Specificity and Dice Similarity Coefficient (DSC) so as to enable benchmarking of its performance. The first IAD prototype has produced promising results as its performance accuracy based on the most widely deployed evaluation metric, DSC, yields 97% for the recognition of kidneys and 96% for their abnormalities; whilst across all the above evaluation metrics its performance ranges between 96% and 100%. Further development of the IAD system is in progress to extend and evaluate its clinical diagnostic support capability through development and integration of additional algorithms to offer fully computer-aided identification of other organs and their abnormalities based on CT/MRI/Ultra-sound Imaging.

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Surface-based GPS measurements of zenith path delay (ZPD) can be used to derive vertically integrated water vapor (IWV) of the atmosphere. ZPD data are collected in a global network presently consisting of 160 stations as part of the International GPS Service. In the present study, ZPD data from this network are converted into IWV using observed surface pressure and mean atmospheric water vapor column temperature obtained from the European Centre for Medium-Range Weather Forecasts' (ECMWF) operational analyses (OA). For the 4 months of January/July 2000/2001, the GPS-derived IWV values are compared to the IWV from the ECMWF OA, with a special focus on the monthly averaged difference (bias) and the standard deviation of daily differences. This comparison shows that the GPS-derived IWV values are well suited for the validation of OA of IWV. For most GPS stations, the IWV data agree quite well with the analyzed data indicating that they are both correct at these locations. Larger differences for individual days are interpreted as errors in the analyses. A dry bias in the winter is found over central United States, Canada, and central Siberia, suggesting a systematic analysis error. Larger differences were mainly found in mountain areas. These were related to representation problems and interpolation difficulties between model height and station height. In addition, the IWV comparison can be used to identify errors or problems in the observations of ZPD. This includes errors in the data itself, e.g., erroneous outlier in the measured time series, as well as systematic errors that affect all IWV values at a specific station. Such stations were excluded from the intercomparison. Finally, long-term requirements for a GPS-based water vapor monitoring system are discussed.

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We examine to what degree we can expect to obtain accurate temperature trends for the last two decades near the surface and in the lower troposphere. We compare temperatures obtained from surface observations and radiosondes as well as satellite-based measurements from the Microwave Soundings Units (MSU), which have been adjusted for orbital decay and non-linear instrument-body effects, and reanalyses from the European Centre for Medium-Range Weather Forecasts (ERA) and the National Centre for Environmental Prediction (NCEP). In regions with abundant conventional data coverage, where the MSU has no major influence on the reanalysis, temperature anomalies obtained from microwave sounders, radiosondes and from both reanalyses agree reasonably. Where coverage is insufficient, in particular over the tropical oceans, large differences are found between the MSU and either reanalysis. These differences apparently relate to changes in the satellite data availability and to differing satellite retrieval methodologies, to which both reanalyses are quite sensitive over the oceans. For NCEP, this results from the use of raw radiances directly incorporated into the analysis, which make the reanalysis sensitive to changes in the underlying algorithms, e.g. those introduced in August 1992. For ERA, the bias-correction of the one-dimensional variational analysis may introduce an error when the satellite relative to which the correction is calculated is biased itself or when radiances change on a time scale longer than a couple of months, e.g. due to orbit decay. ERA inhomogeneities are apparent in April 1985, October/November 1986 and April 1989. These dates can be identified with the replacements of satellites. It is possible that a negative bias in the sea surface temperatures (SSTs) used in the reanalyses may have been introduced over the period of the satellite record. This could have resulted from a decrease in the number of ship measurements, a concomitant increase in the importance of satellite-derived SSTs, and a likely cold bias in the latter. Alternately, a warm bias in SSTs could have been caused by an increase in the percentage of buoy measurements (relative to deeper ship intake measurements) in the tropical Pacific. No indications for uncorrected inhomogeneities of land surface temperatures could be found. Near-surface temperatures have biases in the boundary layer in both reanalyses, presumably due to the incorrect treatment of snow cover. The increase of near-surface compared to lower tropospheric temperatures in the last two decades may be due to a combination of several factors, including high-latitude near-surface winter warming due to an enhanced NAO and upper-tropospheric cooling due to stratospheric ozone decrease.

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For the first time, vertical column measurements of (HNO3) above the Arctic Stratospheric Ozone Observatory (AStrO) at Eureka (80N, 86W), Canada, have been made during polar night using lunar spectra recorded with a Fourier Transform Infrared (FTIR) spectrometer, from October 2001 to March 2002. AStrO is part of the primary Arctic station of the Network for the Detection of Stratospheric Change (NDSC). These measurements were compared with FTIR measurements at two other NDSC Arctic sites: Thule, Greenland (76.5N, 68.8W) and Kiruna, Sweden (67.8N, 20.4E). The measurements were also compared with two atmospheric models: the Canadian Middle Atmosphere Model (CMAM) and SLIMCAT. This is the first time that CMAM HNO3 columns have been compared with observations in the Arctic. Eureka lunar measurements are in good agreement with solar ones made with the same instrument. Eureka and Thule HNO3 columns are consistent within measurement error. Differences among HNO3 columns measured at Kiruna and those measured at Eureka and Thule can be explained on the basis of the available sunlight hours and the polar vortex location. The comparison of CMAM HNO3 columns with Eureka and Kiruna data shows good agreement, considering CMAM small inter-annual variability. The warm 2001/02 winter with almost no Polar Stratospheric Clouds (PSCs) makes the comparison of the warm climate version of CMAM with these observations a good test for CMAM under no PSC conditions. SLIMCAT captures the magnitude of HNO3 columns at Eureka, and the day-to-day variability, but generally reports higher HNO3 columns than the CMAM climatological mean columns.

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High-resolution simulations with a mesoscale model are performed to estimate heat and moisture budgets of a well-mixed boundary layer. The model budgets are validated against energy budgets obtained from airborne measurements over heterogeneous terrain in Western Germany. Time rate of change, vertical divergence, and horizontal advection for an atmospheric column of air are estimated. Results show that the time trend of specific humidity exhibits some deficiencies, while the potential temperature trend is matched accurately. Furthermore, the simulated turbulent surface fluxes of sensible and latent heat are comparable to the measured fluxes, leading to similar values of the vertical divergence. The analysis of different horizontal model resolutions exhibits improved surface fluxes with increased resolution, a fact attributed to a reduced aggregation effect. Scale-interaction effects could be identified: while time trends and advection are strongly influenced by mesoscale forcing, the turbulent surface fluxes are mainly controlled by microscale processes.

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The difference between the rate of change of cerebral blood volume (CBV) and cerebral blood flow (CBF) following stimulation is thought to be due to circumferential stress relaxation in veins (Mandeville, J.B., Marota, J.J.A., Ayata, C., Zaharchuk, G., Moskowitz, M.A., Rosen, B.R., Weisskoff, R.M., 1999. Evidence of a cerebrovascular postarteriole windkessel with delayed compliance. J. Cereb. Blood Flow Metab. 19, 679–689). In this paper we explore the visco-elastic properties of blood vessels, and present a dynamic model relating changes in CBF to changes in CBV. We refer to this model as the visco-elastic windkessel (VW) model. A novel feature of this model is that the parameter characterising the pressure–volume relationship of blood vessels is treated as a state variable dependent on the rate of change of CBV, producing hysteresis in the pressure–volume space during vessel dilation and contraction. The VW model is nonlinear time-invariant, and is able to predict the observed differences between the time series of CBV and that of CBF measurements following changes in neural activity. Like the windkessel model derived by Mandeville, J.B., Marota, J.J.A., Ayata, C., Zaharchuk, G., Moskowitz, M.A., Rosen, B.R., Weisskoff, R.M., 1999. Evidence of a cerebrovascular postarteriole windkessel with delayed compliance. J. Cereb. Blood Flow Metab. 19, 679–689, the VW model is primarily a model of haemodynamic changes in the venous compartment. The VW model is demonstrated to have the following characteristics typical of visco-elastic materials: (1) hysteresis, (2) creep, and (3) stress relaxation, hence it provides a unified model of the visco-elastic properties of the vasculature. The model will not only contribute to the interpretation of the Blood Oxygen Level Dependent (BOLD) signals from functional Magnetic Resonance Imaging (fMRI) experiments, but also find applications in the study and modelling of the brain vasculature and the haemodynamics of circulatory and cardiovascular systems.

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Atmospheric profiles of cosmic rays and radioactivity can be obtained using adapted meteorologi- cal radiosondes, for which Geiger tubes remain widely used detectors. Simultaneous triggering of two tubes provides an indication of energetic events. As, however, only small volume detectors can be carried, the event rate is small, which, due to the rapid balloon ascent, cannot be circumvented using long averaging periods. To derive count rates at low altitudes, a microcontroller is used to de- termine the inter-event time. This yields estimates of the coincidence rate below 5 km, where the coincidence rate is too small to determine solely by event counting

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Modern age samples from various depositional environments were examined for signal resetting. For 19 modern aeolian/beach samples all De values obtained were View the MathML source, with ∼70% having View the MathML source. For 21 fluvial/colluvial samples, all De values were View the MathML source with ∼80% being View the MathML source. De as a function of illumination (OSL measurement) time (De(t)) plots were examined for all samples. Based on previous laboratory experiments, increases in De(t) were expected for partially reset samples, and constant De(t) for fully reset samples. All aeolian samples, both modern age and additional ‘young’ samples (<1000 years), showed constant (flat) De(t) while all modern, non-zero De, fluvial/colluvial samples showed increasing De(t). ‘Replacement plots’, where a regenerated signal is substituted for the natural, yielded constant (flat) De(t). These findings support strongly the use of De(t) as a method of identifying incomplete resetting in fluvial samples. Potential complicating factors, such as illumination (bleaching) spectrum, thermal instability and component composition are discussed and a series of internal checks on the applicability of the De(t) for each individual aliquot/grain level are outlined.

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The effects of a non-uniform wind field along the path of a scintillometer are investigated. Theoretical spectra are calculated for a range of scenarios where the crosswind varies in space or time and compared to the ‘ideal’ spectrum based on a constant uniform crosswind. It is verified that the refractive-index structure parameter relation with the scintillometer signal remains valid and invariant for both spatially and temporally-varying crosswinds. However, the spectral shape may change significantly preventing accurate estimation of the crosswind speed from the peak of the frequency spectrum and retrieval of the structure parameter from the plateau of the power spectrum. On comparison with experimental data, non-uniform crosswind conditions could be responsible for previously unexplained features sometimes seen in observed spectra. By accounting for the distribution of crosswind, theoretical spectra can be generated that closely replicate the observations, leading to a better understanding of the measurements. Spatial variability of wind speeds should be expected for paths other than those that are parallel to the surface and over flat, homogenous areas, whilst fluctuations in time are important for all sites.

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Vertical divergence of CO2 fluxes is observed over two Midwestern AmeriFlux forest sites. The differences in ensemble averaged hourly CO2 fluxes measured at two heights above canopy are relatively small (0.2–0.5 μmol m−2 s−1), but they are the major contributors to differences (76–256 g C m−2 or 41.8–50.6%) in estimated annual net ecosystem exchange (NEE) in 2001. A friction velocity criterion is used in these estimates but mean flow advection is not accounted for. This study examines the effects of coordinate rotation, averaging time period, sampling frequency and co-spectral correction on CO2 fluxes measured at a single height, and on vertical flux differences measured between two heights. Both the offset in measured vertical velocity and the downflow/upflow caused by supporting tower structures in upwind directions lead to systematic over- or under-estimates of fluxes measured at a single height. An offset of 1 cm s−1 and an upflow/downflow of 1° lead to 1% and 5.6% differences in momentum fluxes and nighttime sensible heat and CO2 fluxes, respectively, but only 0.5% and 2.8% differences in daytime sensible heat and CO2 fluxes. The sign and magnitude of both offset and upflow/downflow angle vary between sonic anemometers at two measurement heights. This introduces a systematic and large bias in vertical flux differences if these effects are not corrected in the coordinate rotation. A 1 h averaging time period is shown to be appropriate for the two sites. In the daytime, the absolute magnitudes of co-spectra decrease with height in the natural frequencies of 0.02–0.1 Hz but increase in the lower frequencies (<0.01 Hz). Thus, air motions in these two frequency ranges counteract each other in determining vertical flux differences, whose magnitude and sign vary with averaging time period. At night, co-spectral densities of CO2 are more positive at the higher levels of both sites in the frequency range of 0.03–0.4 Hz and this vertical increase is also shown at most frequencies lower than 0.03 Hz. Differences in co-spectral corrections at the two heights lead to a positive shift in vertical CO2 flux differences throughout the day at both sites. At night, the vertical CO2 flux differences between two measurement heights are 20–30% and 40–60% of co-spectral corrected CO2 fluxes measured at the lower levels of the two sites, respectively. Vertical differences of CO2 flux are relatively small in the daytime. Vertical differences in estimated mean vertical advection of CO2 between the two measurement heights generally do not improve the closure of the 1D (vertical) CO2 budget in the air layer between the two measurement heights. This may imply the significance of horizontal advection. However, a reliable assessment of mean advection contributions in annual NEE estimate at these two AmeriFlux sites is currently an unsolved problem.

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The substorm current wedge (SCW) is a fundamental component of geomagnetic substorms. Models tend to describe the SCW as a simple line current flowing into the ionosphere towards dawn and out of the ionosphere towards dusk, linked by a westward electrojet. We use multi-spacecraft observations from perigee passes of the Cluster 1 and 4 spacecraft during a substorm on 15 Jan 2010, in conjunction with ground-based observations, to examine the spatial structuring and temporal variability of the SCW. At this time, the spacecraft travelled east-west azimuthally above the auroral region. We show that the SCW has significant azimuthal sub-structure on scales of 100~km at altitudes of 4,000-7,000~km. We identify 26 individual current sheets in the Cluster 4 data and 34 individual current sheets in the Cluster 1 data, with Cluster 1 passing through the SCW 120-240~s after Cluster 4 at 1,300-2,000~km higher altitude. Both spacecraft observed large-scale regions of net upward and downward field-aligned current, consistent with the large-scale characteristics of the SCW, although sheets of oppositely directed currents were observed within both regions. We show that the majority of these current sheets were closely aligned to a north-south direction, in contrast to the expected east-west orientation of the pre-onset aurora. Comparing our results with observations of the field-aligned current associated with bursty bulk flows (BBFs) we conclude that significant questions remain for the explanation of SCW structuring by BBF driven ``wedgelets". Our results therefore represent constraints on future modelling and theoretical frameworks on the generation of the SCW.

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Climate data are used in a number of applications including climate risk management and adaptation to climate change. However, the availability of climate data, particularly throughout rural Africa, is very limited. Available weather stations are unevenly distributed and mainly located along main roads in cities and towns. This imposes severe limitations to the availability of climate information and services for the rural community where, arguably, these services are needed most. Weather station data also suffer from gaps in the time series. Satellite proxies, particularly satellite rainfall estimate, have been used as alternatives because of their availability even over remote parts of the world. However, satellite rainfall estimates also suffer from a number of critical shortcomings that include heterogeneous time series, short time period of observation, and poor accuracy particularly at higher temporal and spatial resolutions. An attempt is made here to alleviate these problems by combining station measurements with the complete spatial coverage of satellite rainfall estimates. Rain gauge observations are merged with a locally calibrated version of the TAMSAT satellite rainfall estimates to produce over 30-years (1983-todate) of rainfall estimates over Ethiopia at a spatial resolution of 10 km and a ten-daily time scale. This involves quality control of rain gauge data, generating locally calibrated version of the TAMSAT rainfall estimates, and combining these with rain gauge observations from national station network. The infrared-only satellite rainfall estimates produced using a relatively simple TAMSAT algorithm performed as good as or even better than other satellite rainfall products that use passive microwave inputs and more sophisticated algorithms. There is no substantial difference between the gridded-gauge and combined gauge-satellite products over the test area in Ethiopia having a dense station network; however, the combined product exhibits better quality over parts of the country where stations are sparsely distributed.

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This paper proposes a new reconstruction method for diffuse optical tomography using reduced-order models of light transport in tissue. The models, which directly map optical tissue parameters to optical flux measurements at the detector locations, are derived based on data generated by numerical simulation of a reference model. The reconstruction algorithm based on the reduced-order models is a few orders of magnitude faster than the one based on a finite element approximation on a fine mesh incorporating a priori anatomical information acquired by magnetic resonance imaging. We demonstrate the accuracy and speed of the approach using a phantom experiment and through numerical simulation of brain activation in a rat's head. The applicability of the approach for real-time monitoring of brain hemodynamics is demonstrated through a hypercapnic experiment. We show that our results agree with the expected physiological changes and with results of a similar experimental study. However, by using our approach, a three-dimensional tomographic reconstruction can be performed in ∼3  s per time point instead of the 1 to 2 h it takes when using the conventional finite element modeling approach