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At least 37 records · Page 2

An object-oriented data reduction system in Fortran

A data reduction system for the AAO two-degree field project is being developed using an object-oriented approach. Rather than use an object-oriented language (such as C++) the system is written in Fortran and makes extensive use of existing subroutine libraries provided by the UK Starlink project. Objects are created using the extensible N-dimensional Data Format (NDF) which itself is based on the Hierarchical Data System (HDS). The software consists of a class library, with each class corresponding to a Fortran subroutine with a standard calling sequence. The methods of the classes provide operations on NDF objects at a similar level of functionality to the applications of conventional data reduction systems. However, because they are provided as callable subroutines, they can be used as building blocks for more specialist applications. The class library is not dependent on a particular software environment thought it can be used effectively in ADAM applications. It can also be used from standalone Fortran programs. It is intended to develop a graphical user interface for use with the class library to form the 2dF data reduction system.

Bailey, J.

Comparison of experimental rotor damping data-reduction techniques

The ability of existing data reduction techniques to determine frequency and damping from transient time-history records was evaluated. Analog data records representative of small-scale helicopter aeroelastic stability tests were analyzed. The data records were selected to provide information on the accuracy of reduced frequency and decay coefficients as a function of modal damping level, modal frequency, number of modes present in the time history record, proximity to other modes with different frequencies, steady offset in time history, and signal-to-noise ratio. The study utilized the results from each of the major U.S. helicopter manufacturers, the U.S. Army Aeroflightdynamics Directorate, and NASA Ames Research Center using their inhouse data reduction and analysis techniques. Consequently, the accuracy of different data analysis techniques and the manner in which they were implemented were also evaluated. It was found that modal frequencies can be accurately determined even in the presence of significant random and periodic noise. Identified decay coefficients do, however, show considerable variation, particularly for highly damped modes. The manner in which the data are reduced and the role of the data analyst was shown to be important. Although several different damping determination methods were used, no clear trends were evident for the observed differences between the individual analysis techniques. It is concluded that the data reduction of modal-damping characteristics from transient time histories results in a range of damping values.

Warmbrodt, William

Data reduction complex analog-to-digital data processing requirements for onsite test facilities

The analog to digital processing requirements of onsite test facilities are described. The source and medium of all input data to the Data Reduction Complex (DRC) and the destination and medium of all output products of the analog-to-digital processing are identified. Additionally, preliminary input and output data formats are presented along with the planned use of the output products.

Debbrecht, J. D.

The DEEP2 Galaxy Redshift Survey: Design, Observations, Data Reduction, and Redshifts

We describe the design and data analysis of the DEEP2 Galaxy Redshift Survey, the densest and largest high-precision redshift survey of galaxies at z approx. 1 completed to date. The survey was designed to conduct a comprehensive census of massive galaxies, their properties, environments, and large-scale structure down to absolute magnitude MB = −20 at z approx. 1 via approx.90 nights of observation on the Keck telescope. The survey covers an area of 2.8 Sq. deg divided into four separate fields observed to a limiting apparent magnitude of R(sub AB) = 24.1. Objects with z approx. < 0.7 are readily identifiable using BRI photometry and rejected in three of the four DEEP2 fields, allowing galaxies with z > 0.7 to be targeted approx. 2.5 times more efficiently than in a purely magnitude-limited sample. Approximately 60% of eligible targets are chosen for spectroscopy, yielding nearly 53,000 spectra and more than 38,000 reliable redshift measurements. Most of the targets that fail to yield secure redshifts are blue objects that lie beyond z approx. 1.45, where the [O ii] 3727 Ang. doublet lies in the infrared. The DEIMOS 1200 line mm(exp −1) grating used for the survey delivers high spectral resolution (R approx. 6000), accurate and secure redshifts, and unique internal kinematic information. Extensive ancillary data are available in the DEEP2 fields, particularly in the Extended Groth Strip, which has evolved into one of the richest multiwavelength regions on the sky. This paper is intended as a handbook for users of the DEEP2 Data Release 4, which includes all DEEP2 spectra and redshifts, as well as for the DEEP2 DEIMOS data reduction pipelines. Extensive details are provided on object selection, mask design, biases in target selection and redshift measurements, the spec2d two-dimensional data-reduction pipeline, the spec1d automated redshift pipeline, and the zspec visual redshift verification process, along with examples of instrumental signatures or other artifacts that in some cases remain after data reduction. Redshift errors and catastrophic failure rates are assessed through more than 2000 objects with duplicate observations. Sky subtraction is essentially photon-limited even under bright OH sky lines; we describe the strategies that permitted this, based on high image stability, accurate wavelength solutions, and powerful B-spline modeling methods. We also investigate the impact of targets that appear to be single objects in ground-based targeting imaging but prove to be composite in Hubble Space Telescope data; they constitute several percent of targets at z approx. 1, approaching approx. 5%-10% at z > 1.5. Summary data are given that demonstrate the superiority of DEEP2 over other deep high-precision redshift surveys at z approx. 1 in terms of redshift accuracy, sample number density, and amount of spectral information. We also provide an overview of the scientific highlights of the DEEP2 survey thus far.

Galaxy

Differential maneuvering simulator data reduction and analysis software

A multielement data reduction and analysis software package has been developed for use with the Langley differential maneuvering simulator (DMS). This package, which has several independent elements, was developed to support all phases of DMS aircraft simulation studies with a variety of both graphical and tabular information. The overall software package is considered unique because of the number, diversity, and sophistication of the element programs available for use in a single study. The purpose of this paper is to discuss the overall DMS data reduction and analysis package by reviewing the development of the various elements of the software, showing typical results that can be obtained, and discussing how each element can be used.

Beasley, G. P.

Data reduction for low energy nuclear physics experiments using data frames

Low energy nuclear physics experiments are transitioning towards fully digital data acquisition systems. Realizing the gains in flexibility afforded by these systems relies on equally flexible data reduction techniques. In this paper, methods utilizing data frames and in-memory techniques to work with data, including data from self-triggering, digital data acquisition systems, are discussed within the context of a Python package, sauce. It is shown that data frame operations can encompass common analysis needs and allow interactive data analysis. Two event building techniques, dubbed referenced and referenceless event building, are shown to provide a means to transform raw list mode data into correlated multi-detector events. These techniques are demonstrated in the analysis of two example data sets.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS

Real-time data reduction capabilities at the Langley 7 by 10 foot high speed tunnel

The 7 by 10 foot high speed tunnel performs a wide range of tests employing a variety of model installation methods. To support the reduction of static data from this facility, a generalized wind tunnel data reduction program had been developed for use on the Langley central computer complex. The capabilities of a version of this generalized program adapted for real time use on a dedicated on-site computer are discussed. The input specifications, instructions for the console operator, and full descriptions of the algorithms are included.

Fox, C. H., Jr.

Intelligent Data Reduction (IDARE)

A description of the Intelligent Data Reduction (IDARE) expert system and an IDARE user's manual are given. IDARE is a data reduction system with the addition of a user profile infrastructure. The system was tested on a nickel-cadmium battery testbed. Information is given on installing, loading, maintaining the IDARE system.

Brady, D. Michael

Data reduction expert assistant

Viewgraphs on data reduction expert assistant are presented. Topics covered include: data analysis systems; philosophy of these systems; disadvantages; expert assistant; useful goals; and implementation considerations.

Miller, Glenn E.

Application of Machine Learning Techniques in Calibration and Data Reduction of Multi-Hole Probes

This work presents procedures for implementing machine learning methods into existing algorithms for multi-hole probe calibration and data reduction. It demonstrates that using artificial neural networks (ANNs) can decrease the amount of calibration data needed to achieve a specific calibration uncertainty by over 50%, while also significantly reducing data reduction times. Instead of surface fitting methods, ANNs are employed. Initially, directional calibration coefficients related to flow angles are computed based on pressure measurements, and then these flow angles serve as input parameters for subsequent ANNs to iteratively define Mach number, static pressure, and total pressure. In an alternative approach, new calibration coefficients directly relate pressure measurements from the five-hole probe to the quantities of interest, thereby eliminating the need for iterative algorithms used in conventional surface fitting methods. This method offers several advantages: an average increase of less than 1%in calibration uncertainty for flow angles and a significant reduction in data reduction times to a few seconds on average. Additionally, the methodology is confirmed to avoid both over- and under-fitting.

Machine Learning