Voice data entry in air traffic control

Several of the keyboard data languages were tabulated and analyzed. The key language chosen as a test vehicle was that used by the nonradar or flight data controllers. This application was undertaken to minimize effort in a cost efficient way and with less research and development

Control Technology Needs for Electrified Aircraft Propulsion Systems

Electrified aircraft propulsion (EAP) systems hold potential for the reduction of aircraft fuel burn, emissions, and noise. Currently, NASA and other organizations are actively working to identify and mature technologies necessary to bring EAP designs to reality. This paper specifically focuses on the envisioned control technology challenges associated with EAP designs that include gas turbine technology. Topics discussed include analytical tools for the dynamic modeling and analysis of EAP systems, and control design strategies at the propulsion and component levels. This includes integrated supervisory control facilitating the coordinated operation of turbine and electrical components, control strategies that seek to minimize fuel consumption and lessen the challenges associated with thermal management, and dynamic control to ensure engine operability during system transients. These dynamic control strategies include innovative control approaches that either extract or supply power to engine shafts dependent upon operating phase, which may improve performance and reduced gas turbine engine weight. Finally, a discussion of control architecture design considerations to help alleviate the propulsion/aircraft integration and certification challenges associated with EAP systems is provided

Control Technology Needs for Electrified Aircraft Propulsion Systems

Electrified aircraft propulsion (EAP) systems hold potential for the reduction of aircraft fuel burn, emissions, and noise. Currently, NASA and other organizations are actively working to identify and mature technologies necessary to bring EAP designs to reality. This paper specifically focuses on the envisioned control technology challenges associated with EAP designs that include gas turbine technology. Topics discussed include analytical tools for the dynamic modeling and analysis of EAP systems, and control design strategies at the propulsion and component levels. This includes integrated supervisory control facilitating the coordinated operation of turbine and electrical components, control strategies that seek to minimize fuel consumption and lessen the challenges associated with thermal management, and dynamic control to ensure engine operability during system transients. These dynamic control strategies include innovative control approaches that either extract or supply power to engine shafts dependent upon operating phase, which may improve performance and reduced gas turbine engine weight. Finally, a discussion of control architecture design considerations to help alleviate the propulsion/aircraft integration and certification challenges associated with EAP systems is provided

The C4 Clustering Algorithm: Clusters of Galaxies in the Sloan Digital Sky Survey

We present the "C4 Cluster Catalog", a new sample of 748 clusters of galaxies identified in the spectroscopic sample of the Second Data Release (DR2) of the Sloan Digital Sky Survey (SDSS). The C4 cluster--finding algorithm identifies clusters as overdensities in a seven-dimensional position and color space, thus minimizing projection effects which plagued previous optical clusters selection. The present C4 catalog covers ~2600 square degrees of sky with groups containing 10 members to massive clusters having over 200 cluster members with redshifts. We provide cluster properties like sky location, mean redshift, galaxy membership, summed r--band optical luminosity (L_r), velocity dispersion, and measures of substructure. We use new mock galaxy catalogs to investigate the sensitivity to the various algorithm parameters, as well as to quantify purity and completeness. These mock catalogs indicate that the C4 catalog is ~90% complete and 95% pure above M_200 = 1x10^14 solar masses and within 0.03 <=z <= 0.12. The C4 algorithm finds 98% of X-ray identified clusters and 90% of Abell clusters within 0.03 <= z <= 0.12. We show that the L_r of a cluster is a more robust estimator of the halo mass (M_200) than the line-of-sight velocity dispersion or the richness of the cluster. L_r. The final SDSS data will provide ~2500 C4 clusters and will represent one of the largest and most homogeneous samples of local clusters.Comment: 32 pages of figures and text accepted in AJ. Electronic version with additional tables, links, and figures is available at http://www.ctio.noao.edu/~chrism/c

Intraoperative transesophageal echocardiography during surgery for congenital heart defects

AbstractObjective: This study was undertaken to further define the impact of intraoperative transesophageal echocardiography during surgery for congenital heart disease and to determine appropriate indications. Methods: The impact of transesophageal echocardiography on patient care was assessed in 1002 patients who underwent this procedure during surgery for congenital heart defects. It had major impact when new information altered the planned procedure or led to a revision of the initial repair. The safety of intraoperative transesophageal echocardiography was evaluated by review of the prospective data sheets and the medical record. A simple relative cost analysis was also performed. Results: Patient median age was 9.9 years (range 2 days to 85 years). Transesophageal echocardiography had prebypass or postbypass major impact in 13.8% of cases (n = 138/1002). Major impact was more frequent during reoperations (P <.03). Procedures that benefited most from the additional information were valve repairs (aortic or atrioventricular) and complex outflow tract reconstructions. Partial anomalous pulmonary venous connection, tricuspid valve repair (other than of Ebstein anomaly), simple atrioventricular discordance, aortic arch anomalies, and secundum atrial septal defects had major impact rates less than 5%. No major complications occurred. Minor complications occurred in 1% of patients and were most often observed in infants smaller than 4 kg. Routine use of transesophageal echocardiography for all patients with congenital heart defects proved cost-effective. Conclusions: On the combined basis of the observed rates of major impact, the minimal complications, and the relative cost advantage, we believe that routine use of transesophageal echocardiography during most intracardiac repairs of congenital heart defects is justified, particularly for patients undergoing repeat operations for congenital cardiac malformations.J Thorac Cardiovasc Surg 2002;124:1176-8

The Galaxy Luminosity Function and Luminosity Density at Redshift z=0.1

Using a catalog of 147,986 galaxy redshifts and fluxes from the Sloan Digital Sky Survey (SDSS), we measure the galaxy luminosity density at z = 0.1 in five optical bandpasses corresponding to the SDSS bandpasses shifted to match their rest-frame shape at z = 0.1. We denote the bands (0.1)u, (0.1)g, (0.1)r, (0.1)i, (0.1)z with lambda(eff) = (3216; 4240; 5595; 6792; 8111 Angstrom), respectively. To estimate the luminosity function, we use a maximum likelihood method that allows for a general form for the shape of the luminosity function,fits for simple luminosity and number evolution, incorporates the flux uncertainties, and accounts for the flux limits of the survey. We find luminosity densities at z = 0.1 expressed in absolute AB magnitudes in a Mpc(3) to be (-14.10 +/- 0.15, -15.18 +/- 0.03, - 15.90 +/- 0.03, -16.24 +/- 0.03, -16.56 +/- 0.02) in ((0.1)u, (0.1)g, (0.1)r, (0.1)i, (0.1)z), respectively, for a cosmological model with Omega(0) = 0.3, Omega(Lambda) = 0.7, and h = 1 and using SDSS Petrosian magnitudes. Similar results are obtained using Sersic model magnitudes, suggesting that flux from outside the Petrosian apertures is not a major correction. In the (0.1)r band, the best-fit Schechter function to our results has phi* = (1.49 +/- 0.04) x 10(-2) h(3) Mpc(-3), M-* - 5 log(10) h = - 20.44 +/- 0.01, and alpha = - 1.05 +/- 0.01. In solar luminosities, the luminosity density in (0.1)r is (1.84 +/- 0.04) x 10(8) h L-0.1r,L-. Mpc(-3). Our results in the (0.1)g band are consistent with other estimates of the luminosity density, from the Two-Degree Field Galaxy Redshift Survey and the Millennium Galaxy Catalog. They represent a substantial change ( similar to 0.5 mag) from earlier SDSS luminosity density results based on commissioning data, almost entirely because of the inclusion of evolution in the luminosity function model

The Sloan Digital Sky Survey Quasar Catalog I. Early Data Release

We present the first edition of the Sloan Digital Sky Survey (SDSS) Quasar Catalog. The catalog consists of the 3814 objects (3000 discovered by the SDSS) in the initial SDSS public data release that have at least one emission line with a full width at half maximum larger than 1000 km/s, luminosities brighter than M_i^* = -23, and highly reliable redshifts. The area covered by the catalog is 494 square degrees; the majority of the objects were found in SDSS commissioning data using a multicolor selection technique. The quasar redshifts range from 0.15 to 5.03. For each object the catalog presents positions accurate to better than 0.2" rms per coordinate, five band (ugriz) CCD-based photometry with typical accuracy of 0.05 mag, radio and X-ray emission properties, and information on the morphology and selection method. Calibrated spectra of all objects in the catalog, covering the wavelength region 3800 to 9200 Angstroms at a spectral resolution of 1800-2100, are also available. Since the quasars were selected during the commissioning period, a time when the quasar selection algorithm was undergoing frequent revisions, the sample is not homogeneous and is not intended for statistical analysis.Comment: 27 pages, 4 figures, 4 tables, accepted by A

Early-type galaxies in the SDSS. I. The sample

A sample of nearly 9000 early-type galaxies, in the redshift range 0.01 < z < 0.3, was selected from the Sloan Digital Sky Survey using morphological and spectral criteria. This paper describes how the sample was selected, presents examples of images and seeing corrected fits to the observed surface brightness profiles, describes our method for estimating K-corrections, and shows that the SDSS spectra are of sufficiently high quality to measure velocity dispersions accurately. It also provides catalogs of the measured photometric and spectroscopic parameters. In related papers, these data are used to study how early-type galaxy observables, including luminosity, effective radius, surface brightness, color, and velocity dispersion, are correlated with one another.Comment: 63 pages, 21 figures. Accepted by AJ (scheduled for April 2003). This paper is part I of a revised version of astro-ph/0110344. The full version of Tables 2 and 3, i.e. the tables listing the photometric and spectroscopic parameters of ~ 9000 galaxies, are available at http://astrophysics.phys.cmu.edu/~bernardi/SDSS/Etypes/TABLE

Galaxy Clustering in Early SDSS Redshift Data

We present the first measurements of clustering in the Sloan Digital Sky Survey (SDSS) galaxy redshift survey. Our sample consists of 29,300 galaxies with redshifts 5,700 km/s < cz < 39,000 km/s, distributed in several long but narrow (2.5-5 degree) segments, covering 690 square degrees. For the full, flux-limited sample, the redshift-space correlation length is approximately 8 Mpc/h. The two-dimensional correlation function \xi(r_p,\pi) shows clear signatures of both the small-scale, ``fingers-of-God'' distortion caused by velocity dispersions in collapsed objects and the large-scale compression caused by coherent flows, though the latter cannot be measured with high precision in the present sample. The inferred real-space correlation function is well described by a power law, \xi(r)=(r/6.1+/-0.2 Mpc/h)^{-1.75+/-0.03}, for 0.1 Mpc/h < r < 16 Mpc/h. The galaxy pairwise velocity dispersion is \sigma_{12} ~ 600+/-100 km/s for projected separations 0.15 Mpc/h < r_p < 5 Mpc/h. When we divide the sample by color, the red galaxies exhibit a stronger and steeper real-space correlation function and a higher pairwise velocity dispersion than do the blue galaxies. The relative behavior of subsamples defined by high/low profile concentration or high/low surface brightness is qualitatively similar to that of the red/blue subsamples. Our most striking result is a clear measurement of scale-independent luminosity bias at r < 10 Mpc/h: subsamples with absolute magnitude ranges centered on M_*-1.5, M_*, and M_*+1.5 have real-space correlation functions that are parallel power laws of slope ~ -1.8 with correlation lengths of approximately 7.4 Mpc/h, 6.3 Mpc/h, and 4.7 Mpc/h, respectively.Comment: 51 pages, 18 figures. Replaced to match accepted ApJ versio

KL Estimation of the Power Spectrum Parameters from the Angular Distribution of Galaxies in Early SDSS Data

We present measurements of parameters of the 3-dimensional power spectrum of galaxy clustering from 222 square degrees of early imaging data in the Sloan Digital Sky Survey. The projected galaxy distribution on the sky is expanded over a set of Karhunen-Loeve eigenfunctions, which optimize the signal-to-noise ratio in our analysis. A maximum likelihood analysis is used to estimate parameters that set the shape and amplitude of the 3-dimensional power spectrum. Our best estimates are Gamma=0.188 +/- 0.04 and sigma_8L = 0.915 +/- 0.06 (statistical errors only), for a flat Universe with a cosmological constant. We demonstrate that our measurements contain signal from scales at or beyond the peak of the 3D power spectrum. We discuss how the results scale with systematic uncertainties, like the radial selection function. We find that the central values satisfy the analytically estimated scaling relation. We have also explored the effects of evolutionary corrections, various truncations of the KL basis, seeing, sample size and limiting magnitude. We find that the impact of most of these uncertainties stay within the 2-sigma uncertainties of our fiducial result.Comment: Fig 1 postscript problem correcte