AuthorMorrison, Thomas M.
AffiliationJT3, Edwards AFB
KeywordsAir Data System (ADS)
Indicated Barometrically-corrected Altitude
Indicated Mach Number
Indicated Angle of Attack (AOA)
Indicated Angle of Sideslip (AOS)
MetadataShow full item record
RightsCopyright © International Foundation for Telemetering
Collection InformationProceedings from the International Telemetering Conference are made available by the International Foundation for Telemetering and the University of Arizona Libraries. Visit http://www.telemetry.org/index.php/contact-us if you have questions about items in this collection.
AbstractTelemetry data are usually collected for analysis at some later time and can be monitored to follow the progress of a test. In the case of an Air Data System the signals from the sensors are sent to a computer that calculates the air data parameters for use on multiple LabView-generated displays, as well as to the Data Acquisition System. The readouts on the multiple displays need to be real-time so they are useful to the flight crew. Equations that control the different air data values are determined by what telemetry data are available and the preference of those doing the test planning. These systems need to display the information in a format useful to the flight crew and be reliable.
SponsorsInternational Foundation for Telemetering
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Cross-Validation Indicates Predictive Models May Provide an Alternative to Indicator Organism Monitoring for Evaluating Pathogen Presence in Southwestern US Agricultural WaterBelias, A.; Brassill, N.; Roof, S.; Rock, C.; Wiedmann, M.; Weller, D.; Department of Environmental Science, University of Arizona (Frontiers Media S.A., 2021)Pathogen contamination of agricultural water has been identified as a probable cause of recalls and outbreaks. However, variability in pathogen presence and concentration complicates the reliable identification of agricultural water at elevated risk of pathogen presence. In this study, we collected data on the presence of Salmonella and genetic markers for enterohemorrhagic E. coli (EHEC; PCR-based detection of stx and eaeA) in southwestern US canal water, which is used as agricultural water for produce. We developed and assessed the accuracy of models to predict the likelihood of pathogen contamination of southwestern US canal water. Based on 169 samples from 60 surface water canals (each sampled 1–3 times), 36% (60/169) and 21% (36/169) of samples were positive for Salmonella presence and EHEC markers, respectively. Water quality parameters (e.g., generic E. coli level, turbidity), surrounding land-use (e.g., natural cover, cropland cover), weather conditions (e.g., temperature), and sampling site characteristics (e.g., canal type) data were collected as predictor variables. Separate conditional forest models were trained for Salmonella isolation and EHEC marker detection, and cross-validated to assess predictive performance. For Salmonella, turbidity, day of year, generic E. coli level, and % natural cover in a 500–1,000 ft (~150–300 m) buffer around the sampling site were the top 4 predictors identified by the conditional forest model. For EHEC markers, generic E. coli level, day of year, % natural cover in a 250–500 ft (~75–150 m) buffer, and % natural cover in a 500–1,000 ft (~150–300 m) buffer were the top 4 predictors. Predictive performance measures (e.g., area under the curve [AUC]) indicated predictive modeling shows potential as an alternative method for assessing the likelihood of pathogen presence in agricultural water. Secondary conditional forest models with generic E. coli level excluded as a predictor showed < 0.01 difference in AUC as compared to the AUC values for the original models (i.e., with generic E. coli level included as a predictor) for both Salmonella (AUC = 0.84) and EHEC markers (AUC = 0.92). Our data suggests models that do not require the inclusion of microbiological data (e.g., indicator organism) show promise for real-time prediction of pathogen contamination of agricultural water (e.g., in surface water canals). Copyright © 2021 Belias, Brassill, Roof, Rock, Wiedmann and Weller.
Use of streamflow indices in hydrologic modelingShamir, Eylon.; Sorooshian, Soroosh; Imam, Bisher; Gupta, Hoshin V.; Guertin, Phil (The University of Arizona., 2003)A perennial streamflow hydrograph, when measured at the outlet of a basin, continuously and without interruption, can be considered as an integral measure of hydrologic responses. Some of the theoretical and practical aspects of treating streamflow hydrographs as integral indicators of basin properties are addressed in this dissertation. This dissertation is divided into two parts. In the first part, a framework to identify and evaluate whether a streamflow variable is consistent and distinguishable in a given time scale and therefore can be considered as a streamflow index, is developed. The suggested framework is evaluated using as an example two streamflow variables that describe some aspects of the hydrograph shape. In the second part of the dissertation, the utilization of these streamflow indices in hydrologic model parameter estimation is demonstrated. It is assumed that streamflow indices that are evaluated on long streamflow records include large variability of climatic scenarios. Therefore, regardless of climate variability, the consistency and distinguishability are maintained the indices are more related to physical properties of a basin. Consequently, the problem of estimating model parameters that are related to basin properties can be approached by a comparison of indices between the observed and simulated streamflow. Three case studies are presented: the first demonstrates that using the streamflow index which describes the shape of the hydrograph in the parameter estimation processes improves consistency of prediction skill of the 5-parameter HYMOD model in the Leaf River, Mississippi. The second case study explores an important property of the shape descriptors as being relatively insensitive to errors in the data. Such property can be potentially used to identify key sources of uncertainty and to select model parameters that are less affected by data errors. In the final case study, the shape descriptors were used to derive the parameters of the gamma function as a model for the basin's Instantaneous Unit Hydrograph (IUH).
Bibliometric indicators and the social sciencesKatz, J. Sylvan (1999-12)Social science research is published in a wider variety of publication types and addresses more national issues than natural science research. This makes the construction of internationally comparable bibliometric indicators somewhat problematic. However, in internationally oriented fields, like economics and psychology, bibliometric indicators can provide a reasonable measure of the publishing size and impact of these research communities. The UK share of the world publications in the social sciences and behavioural sciences increased between 1981 and 1998 according to data derived from the National Science Indicators on diskette (NSIOD) produced by the Institute for Scientific Information (ISI). The UK has its largest percentage share of world papers in environmental studies and geography & development. Its strongest growth in percentage share of world papers was in the management sciences. The UK share of psychology publications grew from 7% to 10% and economics publications grew from 10% to 13% over the 18-year time interval. England displayed its greatest growth in the percentage share of UK publications in rehabilitation, Scotland in communications, Wales in library & information sciences and North Ireland in psychology. It is shown in this report that the conventional impact indicator (citations/paper) gives a distorted view of the UK's impact because impact increases non-linearly with publishing size. A new indicator, the relative international citation impact (RICI) indicator that has been corrected to account for the non-linear relationship between impact and publishing size, is introduced. Using a sequence of fourteen 5-year overlapping time periods, the RICI indicator portrays a different picture of the impact of UK psychology and economics research than the conventional impact indicator. It shows that UK impact exceeded the US impact in psychology across all 13 time intervals and it matched or exceeded the US impact in economics in 8 out of the 13 intervals