Engineering topics

Srivistava, Ashok N.

Publications and source records attributed to Srivistava, Ashok N..

3 records

NASA NTRS2012

Second Interim Report NASA - easyJet Collaboration on the Human Factors Monitoring Program (HFMP) Study

This is the second interim report jointly prepared by NASA and easyJet on the work performed under the agreement to collaborate on a study of the factors entailed in flight and cabin-crew fatigue, and decreases in performance associated with fatigue. The objective of this Agreement is to generate reliable procedures that aid in understanding the levels and characteristics of flight and cabin-crew fatigue factors, both latent and proximate, whose confluence will likely result in unacceptable crew performance. This study entails the analyses of numerical and textual data collected during operational flights. NASA and easyJet are both interested in assessing and testing NASA s automated capabilities for extracting operationally significant information from very large, diverse (textual and numerical) databases; much larger than can be handled practically by human experts.

Srivistava, Ashok N.↗

NASA NTRS2012

Bootstrap Prediction Intervals in Non-Parametric Regression with Applications to Anomaly Detection

Prediction intervals provide a measure of the probable interval in which the outputs of a regression model can be expected to occur. Subsequently, these prediction intervals can be used to determine if the observed output is anomalous or not, conditioned on the input. In this paper, a procedure for determining prediction intervals for outputs of nonparametric regression models using bootstrap methods is proposed. Bootstrap methods allow for a non-parametric approach to computing prediction intervals with no specific assumptions about the sampling distribution of the noise or the data. The asymptotic fidelity of the proposed prediction intervals is theoretically proved. Subsequently, the validity of the bootstrap based prediction intervals is illustrated via simulations. Finally, the bootstrap prediction intervals are applied to the problem of anomaly detection on aviation data.

Kumar, Sricharan↗

NASA NTRS2012

NASA - easyJet Collaboration on the Human Factors Monitoring Program (HFMP) Study

This is the first annual report jointly prepared by NASA and easyJet on the work performed under the agreement to collaborate on a study of the many factors entailed in flight - and cabin-crew fatigue and documenting the decreases in performance associated with fatigue. The objective of this Agreement is to generate reliable, automated procedures that improve understanding of the levels and characteristics of flight - and cabin-crew fatigue factors, both latent and proximate, whose confluence will likely result in unacceptable flight crew performance. This study entails the analyses of numerical and textual data collected during operational flights. NASA and easyJet are both interested in assessing and testing NASA s automated capabilities for extracting operationally significant information from very large, diverse (textual and numerical) databases, much larger than can be handled practically by human experts.

Srivistava, Ashok N.↗