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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Creative Typesets Require Innovative Solutions: A Study of Differences in Braille IndicatorsHannan, Cheryl Kamei (The University of Arizona., 2008)Currently, students who read tactually must learn specific braille indicators that correspond to typeset changes such as bold, italic, and underline. These symbols do not stand out like printed attributes. To learn emphasis indicators, students must understand the concepts of print and memorize corresponding braille coding, which requires explicit training. Because tactile readers can only "see" that which is under his/her fingers, scanning and locating indicators is difficult. One must scan the passage word by word to find the emphasis indicator. In contrast, a sighted child can quickly glance at a page and recognize attributes instantly. The difficulty in tactually recognizing typeset, leads to slower recognition of important information and potentially affects reading fluency for beginning readers.This research study compared the use of the current braille code (CBC) with two alternate ways of presenting typeset. The research questions were: (a) Is there a difference in speed in finding the emphasis indicators when presented in three different formats? (b) Is there a difference in accuracy of recognizing the emphasis indicator when presented in three different formats? (c) What are the students' perceptions and opinions about the various indicators?A quasi-experimental design was implemented and three types of data were collected: (a) measurement of speed - in seconds, (b) measurement of accuracy - in number of correctly identified words and indicators, and (c) the perceptions of students before and after the data were collected. The independent variables were the three ways of presenting typeset (CBC, Ua, and Ub), and the dependent variables were speed and accuracy. Quantitative data were analyzed using ANOVA for speed and accuracy and correlational data were conducted to determine if relationships existed between speed and accuracy. Qualitative data were categorized and reported.Results showed a statistical difference between the speed at which students located words with emphasis, but no difference was found in their accuracy. Interview data showed that most students did not have a grasp of print concepts or understand the purposes of using the indicators. Students also indicated that they preferred the alternate formats (Ua or Ub), rather than the current braille code (CBC).
THE EFFECT OF ENGAGEMENT IN COGNITIVE REAPPRAISAL IN RESPONSE TO PREVIOUSLY CONDITIONED STIMULI ON ONLINE AND LONG-TERM EXPECTANCY RATINGS AND EMOTION INDICESRay, Colleen Andrea (The University of Arizona., 2009)Previous research has shown that cognitive reappraisal, an emotion regulation strategy, has beneficial effects on emotion experience during strategy engagement. The present study extends this work by investigating whether cognitive reappraisal impacts the anticipation of an aversive event during, and five days following, strategy engagement. Emotion profiles, including psychophysiological and self-report indices, were also examined to assess whether reappraisal inhibits affective responses. Participants underwent habituation and simple discriminatory fear conditioning. Stimuli were pictures of a snake and a spider. Two days later participants returned to the laboratory and were either i) cued to engage in cognitive reappraisal while imagining the stimuli ii) exposed to the stimuli with no reappraisal instructions iii) exposed to the stimuli while engaging in cognitive reappraisal or iv) had an experience unrelated to the stimuli (control condition). Participants returned to the lab five days later and were exposed to both pictures paralleling initial habituation and conditioning protocols. It was found that cognitive reappraisal during exposure reduced expectancy of the UCS faster than exposure alone and resulted in lower mean skin conductance response (SCR) for those low, but not high, in fear of snakes. Five days later participants in the intervention conditions, compared to the control condition, demonstrated less anticipation of the UCS and smaller emotion-modulated startle magnitudes to the UCS. These findings suggest that cognitive reappraisal may be an effective tool for reducing anticipation of an aversive event and can result in enduring fear inhibition. This may have important implications for the treatment of individuals with anxiety disorders. The present study also examined the relationship between cardiac vagal control, indexed by respiratory sinus arrhythmia (RSA), and subsequent sympathetic arousal during fear conditioning, indexed by SCR. Results demonstrate that participants with low, compared to high, resting RSA had larger SCRs during habituation and conditioning trials. In addition, participants with lower RSA showed greater SCR reactivity following UCS presentation to both conditioned stimuli, suggesting that those with the lower RSA initially differentiated less between the UCS paired and unpaired images. These findings are consistent with theories that associate faster recovery from emotionally demanding situations with greater cardiac vagal control.
Clinical Indicators that Predict Readmission Risk in Patients with Acute Myocardial Infarction, Heart Failure, and PneumoniaChen, Weihua; The University of Arizona College of Medicine - Phoenix; Antonescu, Corneliu MD; Holland, William MD (The University of Arizona., 2017-04-28)BACKGROUND: In order to improve the quality and efficacy of healthcare while reducing the overall cost to deliver that healthcare, it has become increasingly important to manage utilization of services for populations of patients. Healthcare systems are aggressively working to identify patients at risk for hospital readmissions. Although readmission rates have been studied before, parameters for identifying patients at risk for readmission appear to vary depending the patient population. We will examine existing Electronic Health Record (EHR) data at Banner Health to establish what parameters are clinical indicators for readmission risk. Three conditions were identified by the CMS to have high and costly readmissions rates; heart failure (HF), acute myocardial infarction (AMI), and pneumonia. This study will focus on attempting to determine the primary predictive variables for these three conditions in order to have maximum impact on cost savings. METHODS: A literature review was done and 68 possible risk variables were identified. Of these, 30 of the variables were identifiable within the EHR system. Inclusion criteria for individual patient records are that they had an index admission secondary to AMI, heart failure, or pneumonia and that they had a subsequent readmission within 30 days of the index admission. Pediatric populations were not studied since they have unique factors for readmission that are not generalizable. Logistics regression was applied to all data including data with missing data rows. This allowed all coefficients to be interpreted for significance. This model was termed the full model. Variables that were determined to be insignificant were subsequently removed to create a new reduced model. Chi square testing was then done to compare the reduced model to the full model to determine if any significant differences existed between the two. RESULTS: Several variables were determined to be the significant predictors of readmission. The final reduced model had 19 predictors. When analyzed using ROC analysis, the area under the curve (AUC) was 0.64. CONCLUSION: Several variables were identified that could be significant contributors to readmission risk. The final model had an AUC on it ROC of 0.64 suggesting that it would only have poor to moderate clinical value for predicting readmission.