This collection on AFIT Scholar presents scholarly works of the faculty of the Air Force Institute of Technology
The Faculty Publications collection accepts scholarly works that are developed under the auspices of AFIT, and accepted for publication in a journal, or for presentation at a conference. All submissions should be approved for public release before submitting to AFIT Scholar
Secondary materials may be submitted along with an article or conference paper, for the purpose of experimental result repeatability.
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Submissions from 2022
Effects of Stochastic Drag on Prediction Variance for Low Earth Orbit Satellites, Everett B. Palmer IV and William E. Wiesel
Distribution of DDS-cerberus Authenticated Facial Recognition Streams, Andrew T. Park, Nathaniel Peck, Richard Dill, Douglas D. Hodson, Michael R. Grimaila, and Wayne C. Henry
Quantifying DDS-cerberus Network Control Overhead, Andrew T. Park, Nathaniel R. Peck, Richard Dill, Douglas D. Hodson, Michael R. Grimaila, and Wayne C. Henry
Multiphoton approximation error of parametric down conversion source detection, Anil K. Patnaik, Billie DeLuca, Nicholas Guerrero, Adrian Scheppe, Michael V. Pak, and David E. Weeks
Generalized focal plane array modulation transfer function estimation approach for nonstationary laser speckle random processes, Philip J. Plummer, Kenneth J. Barnard, and Michael A. Marciniak
Iterative maximum likelihood approach to focal plane array impulse response estimation using random laser speckle, Philip J. Plummer, Kenneth J. Barnard, Michael A. Marciniak, and Tony Liu
Analysis of a Celestial Icosahedron, Torin Quick and Anthony N. Palazotto
Integrated Hypersonic Aeropropulsion Model for Multidisciplinary Vehicle Analysis and Optimization, Michael A. Ramunno, Ian M. Boyde, Ramana V. Grandhi, and Jose Camberos
Enabling Orders of Magnitude Sensitivity Improvement for Quantification of Ga in a Ce Matrix with a Compact Echelle Spectrometer, Ashwin P. Rao, Phillip R. Jenkins, John D. Auxier II, Michael B. Shattan, and Anil K. Patnaik
Development of Advanced Machine Learning Models for Analysis of Plutonium Surrogate Optical Emission Spectra, Ashwin P. Rao, Phillip R. Jenkins, John D. Auxier II, Michael B. Shattan, and Anil K. Patnaik
Analytical comparisons of handheld LIBS and XRF devices for rapid quantification of gallium in a plutonium surrogate matrix, Ashwin P. Rao, Phillip R. Jenkins, John Auxier, Michael B. Shattan, and Anil K. Patnaik
Enabling high-fidelity spectroscopic analysis of plutonium with machine learning, Ashwin P. Rao, Phillip R. Jenkins, and Anil K. Patnaik
Augmenting Field Nuclear Forensics Capabilities with Handheld Atomic Spectroscopy Devices for Nuclear Debris Analysis, Ashwin P. Rao, Christopher M. Sutphin, and Christina L. Dugan
Acceleration of an Easily Configurable Satnav SDR using SIMD, Logan Reich, Sanjeev Gunawardena, and Michael Braasch
Ensuring the Security of Space Systems from Eavesdropping Attacks, Caleb Richardson, Mark G. Reith, and Wayne C. Henry
Automated Computer Network Exploitation with Bayesian Decision Networks, Graeme Roberts and Gilbert L. Peterson
Modeling Wildfire Risk At Vandenberg SFB, Napolean Robinson [*] and Christopher M. Chini
Adiabatic Shear Banding in Nickel and Nickel-Based Superalloys: A Review, Russell A. Rowe, Paul G. Allison, Anthony N. Palazotto, and Keivan Davami
Atmospheric Optical Turbulence Mitigation using Iterative Image Registration and Least Squares Lucky Look Fusion, Michael A. Rucci, Russell C. Hardie, Richard K. Martin, and Szymon Gladysz
To drill or not to drill? Creep of an oxide‐oxide composite with diamond‐drilled effusion holes at elevated temperature, Marina B. Ruggles-Wrenn and Mehan L. Harkins
Innovation Transition Success: Practice Doesn't Make Perfect, Kaitlyn Ryan, Amy M. Cox, Ethan Blake, Clay Koschnick, and Alfred E. Thal Jr.
Complete description of fault-tolerant quantum gate operations for topological Majorana qubit systems, Adrian D. Scheppe and Michael V. Pak
Estimating Operationalized Intent using Random Forests, Michael F. Schneider, Nicholas Engle, Michael E. Miller, and Gilbert L. Peterson
Application of Machine Learning to Predict the Performance of an EMIPG Reactor Using Data from Numerical Simulations, Owen Sedej, Eric G. Mbonimpa, Trevor Sleight, and Jeremy Slagley
Artificial Neural Networks and Gradient Boosted Machines Used for Regression to Evaluate Gasification Processes: A Review, Owen Sedej, Eric Mbonimpa, Trevor Sleight, and Jeremy M. Slagley