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At least 595 records · Page 33

A 4800 bps CELP vocoder with an improved excitation

The Stochastic or Code Excited Linear Predictive Coder (CELP) is among the promising candidates for producing good quality speech at low bit rates. However, the speech quality produced suffers from perceived roughness. Many researchers have used pole-zero postfilters to mask the roughness at the output of the synthesis filter. Although the postfilters are effective in masking the noise at low bit rates, they produce spectral distortions. It is proposed that speech can be improved by introducing two modifications to the fixed stochastic codebook. In the first modification, the stochastic codebook is used only when the long term correlations are low. Otherwise, a pulse like codebook is selected. In the second modification, the selected codebook output is weighted using an adaptive spectral shaping procedure. These two modifications were incorporated in a 4800 bps CELP coder and have resulted in a perceptually improved vocoded speech.

Hassanein, Hisham↗

Sensitivity of Lower Stratospheric Assimilated Ozone on Error Covariance Modeling and Data Selection

Assimilated ozone is produced at the NASA/Goddard Data Assimilation Office by blending ozone retrieved from the Solar Backscatter UltraViolet/2 (SBUV/2) instrument and the Earth Probe Total Ozone Mapping Spectrometer (EP TOMS) measurements into an off-line transport model. The current system tends to overestimate the amount of lower stratospheric ozone. This is a region where ozone plays a key role in the forcing of climate. A biased ozone field in this region will adversely impact calculations of the stratosphere-troposphere exchange and, when used as a first guess in retrievals, the values determined from satellite observations. Since these are all important applications of assimilated ozone products, effort is being directed towards reducing this bias. The SBUV ozone data have a coarse vertical resolution with increased uncertainty below the ozone maximum, and TOMS provides only total ozone columns. Thus, the assimilated ozone in the lower stratosphere, and its vertical distribution in particular, are only weakly constrained by the incoming SBUV and TOMS data. Consequently, the assimilated ozone distribution should be sensitive to changes in inputs to the statistical analysis scheme. Accordingly, the sensitivity of the assimilated lower stratospheric ozone fields to changes in the TOMS error-covariance modeling and the SBUV data selection has been investigated. The use of a spatially correlated TOMS error covariance model led to improvements in the product. However, withholding the SBUV/2 data for the layer between 63 and 126 hPa typically degraded the product, a result which vindicates the use of this layer ozone product, despite its known errors. These efforts to improve the lower stratospheric distribution will be extended to include a more advanced forecast error covariance model, and by assimilating ozone products from new instruments on Envisat and EOS Aura.

Stajner, Ivanka↗

Virtual Observatory Science Applications

Many Virtual-Observatory-based applications are now available to astronomers for use in their research. These span data discovery, access, visualization and analysis. Tools can quickly gather and organize information from sites around the world to help in planning a response to a gamma-ray burst, help users pick filters to isolate a desired feature, make an average template for z=2 AGN, select sources based upon information in many catalogs, or correlate massive distributed databases. Using VO protocols, the reach of existing software tools and packages can be greatly extended, allowing users to find and access remote information almost as conveniently as local data. The talk highlights just a few of the tools available to scientists, describes how both large and small scale projects can use existing tools, and previews some of the new capabilities that will be available in the next few years.

McGlynn, Tom↗

Initial Navigation Alignment of Optical Instruments on GOES-R

Post-launch alignment errors for the Advanced Baseline Imager (ABI) and Geospatial Lightning Mapper (GLM) on GOES-R may be too large for the image navigation and registration (INR) processing algorithms to function without an initial adjustment to calibration parameters. We present an approach that leverages a combination of user-selected image-to-image tie points and image correlation algorithms to estimate this initial launch-induced offset and calculate adjustments to the Line of Sight Motion Compensation (LMC) parameters. We also present an approach to generate synthetic test images, to which shifts and rotations of known magnitude are applied. Results of applying the initial alignment tools to a subset of these synthetic test images are presented. The results for both ABI and GLM are within the specifications established for these tools, and indicate that application of these tools during the post-launch test (PLT) phase of GOES-R operations will enable the automated INR algorithms for both instruments to function as intended.

geolocation↗

Evaluating the Uncertainty of Terrestrial Water Budget Components over High Mountain Asia

This study explores the uncertainties in terrestrial water budget estimation over High Mountain Asia (HMA) using a suite of uncoupled land surface model (LSM) simulations. The uncertainty in the water balance components of precipitation (P), evapotranspiration (ET), runoff (R), and terrestrial water storage (TWS) is significantly impacted by the uncertainty in the driving meteorology, with precipitation being the most important boundary condition. Ten gridded precipitation datasets along with a mix of model-, satellite-, and gauge-based products, are evaluated first to assess their suitability for LSM simulations over HMA. The datasets are evaluated by quantifying the systematic and random errors of these products as well as the temporal consistency of their trends. Though the broader spatial patterns of precipitation are generally well captured by the datasets, they differ significantly in their means and trends. In general, precipitation datasets that incorporate information from gauges are found to have higher accuracy with low Root Mean Square Errors and high correlation coefficient values. An ensemble of LSM simulations with selected subset of precipitation products is then used to produce the mean annual fluxes and their uncertainty over HMA in P, ET, and R to be 2.11 ± 0.45, 1.26 ± 0.11, and 0.85 ± 0.36 mm per day, respectively. The mean annual estimates of the surface mass (water) balance components from this model ensemble are comparable to global estimates from prior studies. However, the uncertainty/spread of P, ET, and R is significantly larger than the corresponding estimates from global studies. A comparison of ET, snow cover fraction, and changes in TWS estimates against remote sensing-based references confirms the significant role of the input meteorology in influencing the water budget characterization over HMA and points to the need for improving meteorological inputs.

Terrestrial water budget↗

Early Ultraviolet Observations of Type IIn Supernovae Constrain the Asphericity of Their Circumstellar Material

We present a survey of the early evolution of 12 Type IIn supernovae (SNe IIn) at ultraviolet and visible light wavelengths. We use this survey to constrain the geometry of the circumstellar material (CSM) surrounding SN IIn explosions, which may shed light on their progenitor diversity. In order to distinguish between aspherical and spherical CSM, we estimate the blackbody radius temporal evolution of the SNe IIn of our sample, following the method introduced by Soumagnac et al. We find that higher-luminosity objects tend to show evidence for aspherical CSM. Depending on whether this correlation is due to physical reasons or to some selection bias, we derive a lower limit between 35% and 66% for the fraction of SNe IIn showing evidence for aspherical CSM. This result suggests that asphericity of the CSM surrounding SNe IIn is common—consistent with data from resolved images of stars undergoing considerable mass loss. It should be taken into account for more realistic modeling of these events.

Maayane T Soumagnac↗

Exploratory Data analysis ENvironment eXtreme scale (EDENx)

EDENx is a multivariate data visualization tool that allows interactive user driven analysis of large-scale data sets with high dimensionality. EDENx builds on our earlier system, called EDEN to enable analysis of more dimensions and larger scale data sets. EDENx provides an initial overview of summary statistics for each variable in the data set under investigation. EDENx allows the user to interact with graphical summary plots of the data to investigate subsets and their statistical associations. These plots include histograms, binned scatterplots, binned parallel coordinate plots, timeline plots, and graphical correlation indicators. From the EDENx interface, a user can select a subsample of interest and launch a more detailed data visualization via the EDEN system. EDENx is best suited for high-level, aggregate analysis tasks while EDEN is more appropriate for detail data investigations.

Steed, Chad Allen↗

Artificial Neural Network-Based Monitoring of the Fuel Assembly Temperature Sensor and FPGA Implementation

Numerous methods have been developed around the world to model the dynamic behavior and detect a faulty operating mode of a temperature sensor. In this context, we present in this study a new method based on the dependence between the fuel assembly temperature profile on control rods positions, and the coolant flow rate in a nuclear reactor. This seems to be possible since the insertion of control rods at different axial positions and variations in flow rate of the reactor coolant results in different produced thermal power in the reactor. This is closely linked to the instant fuel rod temperature profile. In a first step, we selected parameters to be used and confirmed the adequate correlation between the chosen parameters and those to be estimated by the proposed monitoring system. In the next step, we acquired and de-noised the data of corresponding parameters, the qualified data is then used to design and train the artificial neural network. The effective data denoising was done by using the wavelet transform to remove a various kind of artifacts such as inherent noise. With the suitable choice of wavelet level and smoothing method, it was possible for us to remove all the non-required artifacts with a view to verify and analyze the considered signal. In our work, several potential mother wavelet functions (Haar, Daubechies, Bi-orthogonal, Reverse Bi-orthogonal, Discrete Meyer and Symlets) were investigated to find the most similar function with the being processed signals. To implement the proposed monitoring system for the fuel rod temperature sensor (03 wire RTD sensor), we used the Bayesian artificial neural network 'BNN' technique to model the dynamic behavior of the considered sensor, the system correlate the estimated values with the measured for the concretization of the proposed system we propose an FPGA (field programmable gate array) implementation. The monitoring system use the correlation. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Ion Correlation Effects in Salt-Doped Block Copolymers

Here, we apply classical density functional theory to study how salt changes the microphase morphology of diblock copolymers. Polymers are freely jointed and one monomer type favorably interacts with ions, to account for the selective solvation that arises from different dielectric constants of the microphases. By including correlations from liquid state theory of an unbound reference fluid, the theory can treat chain behavior, microphase separation, ion correlations, and preferential solvation, at same coarse grained level. We show good agreement with molecular dynamics simulations.

36 MATERIALS SCIENCE↗

Bose-Einstein correlation of kaons in Si + Au collisions at 14.6 A GeV/c

The E-802 spectrometer at the Brookhaven Alternating Gradient Synchrotron, enhanced by a trigger for selection of events with one or more specified particles, has been used to measure the momentum-space correlation between pairs of K(+)s emitted in central Si + Au collisions at 14.6 A GeV/c. This correlation has been projected onto the Lorentz-invariant relative four-momentum axis. Fits to this correlation function yield a size for the kaon source that is comparable to that found using pi(+) pairs from a similar rapidity range, once a transformation from the particle-pair frames to a single source frame is made.

Akiba, Y.↗

Overview of Boundary Layer Transition Research in Support of Orbiter Return To Flight

A predictive tool for estimating the onset of boundary layer transition resulting from damage to and/or repair of the thermal protection system was developed in support of Shuttle Return to Flight. The boundary layer transition tool is part of a suite of tools that analyze the aerothermodynamic environment to the local thermal protection system to allow informed disposition of damage for making recommendations to fly as is or to repair. Using mission specific trajectory information and details of each damage site or repair, the expected time (and thus Mach number) at transition onset is predicted to help define the aerothermodynamic environment to use in the subsequent thermal and stress analysis of the local thermal protection system and structure. The boundary layer transition criteria utilized for the tool was developed from ground-based measurements to account for the effect of both protuberances and cavities and has been calibrated against select flight data. Computed local boundary layer edge conditions were used to correlate the results, specifically the momentum thickness Reynolds number over the edge Mach number and the boundary layer thickness. For the initial Return to Flight mission, STS-114, empirical curve coefficients of 27, 100, and 900 were selected to predict transition onset for protuberances based on height, and cavities based on depth and length, respectively.

Berry, Scott A.↗

Criteria for the use of regression analysis for remote sensing of sediment and pollutants

An examination of limitations, requirements, and precision of the linear multiple-regression technique for quantification of marine environmental parameters is conducted. Both environmental and optical physics conditions have been defined for which an exact solution to the signal response equations is of the same form as the multiple regression equation. Various statistical parameters are examined to define a criteria for selection of an unbiased fit when upwelled radiance values contain error and are correlated with each other. Field experimental data are examined to define data smoothing requirements in order to satisfy the criteria of Daniel and Wood (1971). Recommendations are made concerning improved selection of ground-truth locations to maximize variance and to minimize physical errors associated with the remote sensing experiment.

Whitlock, C. H.↗

The spin selectivity effect in chiral materials

We overview experiments performed on the chiral induced spin selectivity (CISS) effect using various materials and experimental configurations. Through this survey of different material systems that manifest the CISS effect, we identify several attributes that are common to all the systems. Among these are the ability to observe spin selectivity for two point contact configurations, when one of the electrodes is magnetic, and the correlation between the optical activity of the chiral systems and a material’s spin filtering properties. In addition, recent experiments show that spin selectivity does not require pure coherent charge transport and the electron spin polarization persists over hundreds of nanometers in an ordered medium. Finally, we point to several issues that still have to be explored regarding the CISS mechanism. Among them is the role of phonons and electron–electron interactions.

36 MATERIALS SCIENCE↗

Selecting samples of galaxies with fewer Fingers-of-God

The radial positions of galaxies inferred from their measured redshift appear distorted due to their peculiar velocities. We argue that the contribution from stochastic velocities — which gives rise to `Fingers-of-God' (FoG) anisotropy in the inferred maps — does not lend itself to perturbative modelling already on scales targeted by current experiments. To get around this limitation, we propose to remove FoG using data-driven indicators of their abundance that are local in nature and thus avoid selection biases. In particular, we show that the scale where the measured power spectrum quadrupole changes sign is tightly anti-correlated with both the satellite fraction and the velocity dispersion, and can thus be used to select galaxy samples with fewer FoG. In addition, we show that excluding galaxies in haloes more massive than a given mass threshold can help to discard many of the most problematic galaxies. Such selection could be achieved in practice using maps of the thermal Sunyaev-Zel'dovich distortion of the cosmic microwave background frequency spectrum. These techniques could potentially improve reconstructions of the large-scale velocity and displacement fields from the redshift-space positions of galaxies. They may also extend the reach of perturbative models for galaxy clustering, though in practice we find only marginal gains when fitting one-loop EFTofLSS models to simulations with mitigated FoG due to the relevance of other effects entering at two-loop order.

cosmological parameters from LSS↗

Dark Energy Survey year 1 results: Galaxy clustering for combined probes

We measure the clustering of DES year 1 galaxies that are intended to be combined with weak lensing samples in order to produce precise cosmological constraints from the joint analysis of large-scale structure and lensing correlations. Two-point correlation functions are measured for a sample of 6.6×10 5 luminous red galaxies selected using the redMaGiC algorithm over an area of 1321 square degrees, in the redshift range 0.15 z /(1+z)=0.017. We quantify and correct spurious correlations induced by spatially variable survey properties, testing their impact on the clustering measurements and covariance. We demonstrate the sample’s robustness by testing for stellar contamination, for potential biases that could arise from the systematic correction, and for the consistency between the two-point auto- and cross-correlation functions. We show that the corrections we apply have a significant impact on the resultant measurement of cosmological parameters, but that the results are robust against arbitrary choices in the correction method. We find the linear galaxy bias in each redshift bin in a fiducial cosmology to be b(σ 8 /0.81)| z=0.24 =1.40±0.07, b(σ 8 /0.81)| z=0.38 =1.60±0.05, b(σ 8 /0.81)| z=0.53 =1.60±0.04 for galaxies with luminosities L/L * >0.5, b(σ 8 /0.81)| z=0.68 =1.93±0.04 for L/L * >1 and b(σ 8 /0.81)| z=0.83 =1.98±0.07 for L/L * >1.5, broadly consistent with expectations for the redshift and luminosity dependence of the bias of red galaxies. We show these measurements to be consistent with the linear bias obtained from tangential shear measurements.

79 ASTRONOMY AND ASTROPHYSICS↗

Optical-Correlator Neural Network Based On Neocognitron

Multichannel optical correlator implements shift-invariant, high-discrimination pattern-recognizing neural network based on paradigm of neocognitron. Selected as basic building block of this neural network because invariance under shifts is inherent advantage of Fourier optics included in optical correlators in general. Neocognitron is conceptual electronic neural-network model for recognition of visual patterns. Multilayer processing achieved by iteratively feeding back output of feature correlator to input spatial light modulator and updating Fourier filters. Neural network trained by use of characteristic features extracted from target images. Multichannel implementation enables parallel processing of large number of selected features.

Chao, Tien-Hsin↗

Sea surface velocities from visible and infrared multispectral atmospheric mapping sensor imagery

High resolution (100 m), sequential Multispectral Atmospheric Mapping Sensor (MAMS) images were used in a study to calculate advective surface velocities using the Maximum Cross Correlation (MCC) technique. Radiance and brightness temperature gradient magnitude images were formed from visible (0.48 microns) and infrared (11.12 microns) image pairs, respectively, of Chandeleur Sound, which is a shallow body of water northeast of the Mississippi delta, at 145546 GMT and 170701 GMT on 30 Mar. 1989. The gradient magnitude images enhanced the surface water feature boundaries, and a lower cutoff on the gradient magnitudes calculated allowed the undesirable sunglare and backscatter gradients in the visible images, and the water vapor absorption gradients in the infrared images, to be reduced in strength. Requiring high (greater than 0.4) maximum cross correlation coefficients and spatial coherence of the vector field aided in the selection of an optimal template size of 10 x 10 pixels (first image) and search limit of 20 pixels (second image) to use in the MCC technique. Use of these optimum input parameters to the MCC algorithm, and high correlation and spatial coherence filtering of the resulting velocity field from the MCC calculation yielded a clustered velocity distribution over the visible and infrared gradient images. The velocity field calculated from the visible gradient image pair agreed well with a subjective analysis of the motion, but the velocity field from the infrared gradient image pair did not. This was attributed to the changing shapes of the gradient features, their nonuniqueness, and large displacements relative to the mean distance between them. These problems implied a lower repeat time for the imagery was needed in order to improve the velocity field derived from gradient imagery. Suggestions are given for optimizing the repeat time of sequential imagery when using the MCC method for motion studies. Applying the MCC method to the infrared brightness temperature imagery yielded a velocity field which did agree with the subjective analysis of the motion and that derived from the visible gradient imagery. Differences between the visible and infrared derived velocities were 14.9 cm/s in speed and 56.7 degrees in direction. Both of these velocity fields also agreed well with the motion expected from considerations of the ocean bottom topography and wind and tidal forcing in the study area during the 2.175 hour time interval.

Pope, P. A.↗

Origin and characterization of single-electron events in Skipper-CCDs for light dark matter searches

This manuscript summarizes the work carried out within the SENSEI (Sub-Electron-Noise Skipper-CCD Experimental Instrument) collaboration, an effort focused on the search for light dark matter using Skipper-CCDs. Firstly, it presents the data acquisition and processing protocol developed to establish a selection criteria for events compatible with the dark matter signal. This protocol also enabled the structure and tools used for the study and characterization of phenomena that impact the quality of measurements made in the search for dark matter (measurement of the Fano factor, determination of the Compton background, and characterization of the high-energy surface background), which were carried out during this work. Secondly, it discusses the comprehensive study conducted on the origin of single-electron events in Skipper-CCDs, which allowed for the selection of detector operating parameters and improved the detection sensitivity in the search for dark matter. It is highlighted the characterization of the spatial correlation between single-electron events and high-energy events, among other developed event selection criteria, and the optimization of the output device to reduce sources of luminescence during its operation. As a result of this study, the lowest levels of dark current and spurious charge ever measured in a CCD are reported. Finally, the latest published results from SENSEI are presented. The obtained limits for the scattering of a light mediator are the best reported to date across the entire investigated mass range, while for the heavy mediator, they are the best for masses below 10 MeV. In terms of dark matter absorption, the most restringent limits below 10 eV are reported. These results, achieved with only a very small fraction of the total projected exposure for SENSEI, position Skipper-CCDs as leaders in the search for light dark matter worldwide.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗