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
Lessons Learned in Human-Artificial Intelligence Teaming in Business Processes, Michael J. Mendenhall, Gilbert L. Peterson, Alexander L. Graves, and Jonathan W. Butler
Toward Digital Twin Development for Additively Manufactured Turbine Blades with Experimental and Analytical Methods, Daniel Miller, Ryan A. Kemnitz, Ramana Grandhi, and Luke Sheridan
A Unified View of a Human Digital Twin, Michael Miller and Emily Spatz
Active 2D-DNA Fingerprinting of WirelessHART Adapters to Ensure Operational Integrity in Industrial Systems, Willie H. Mims, Michael A. Temple, and Robert F. Mills
Contested Agile Combat Employment: A Site-Selection Methodology, Zachary T. Moer, Christopher M. Chini, Peter P. Feng, and Steven J. Schuldt
Impact of Operational and Restoration Interdependencies on Cost and Disruptive Effect in Multilayered Infrastructure Networks, Brigham A. Moore, Steven J. Schuldt, Ramana Grandhi, and David R. Jacques
Strategy-to-Task Assessments, Leah H. Nestico, John A. Pav, Adam J. Campbell, Joseph M. Tama, and Mark A. Gallagher
Forecasting Country Conflict Using Statistical Learning Methods, Sarah Neumann, Darryl K. Ahner, and Raymond R. Hill
Accounting for Magnetic Anomaly Map Artifacts in Magnetic Navigators, Aaron P. Nielsen, Jeremy Gray, and Jonnathan D. Bonifaz
Digital-holography Efficiency Measurements using a Heterodyne-pulsed Configuration, Steven A. Owens, Mark F. Spencer, and Glen P. Perram
Pulsed Laser Source Digital Holography Efficiency Measurements, Steven A. Owens, Mark F. Spencer, Douglas E. Thornton, and Glen P. Perram
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
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 Patnaik
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 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 Patnaik
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
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