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Air Force Institute of Technology

Faculty Publications

2022

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Articles 1 - 30 of 40

Full-Text Articles in Physical Sciences and Mathematics

Global Sporadic-E Occurrence Rate Climatology Using Gps Radio Occultation And Ionosonde Data, Travis J. Hodos, Omar A. Nava, Eugene V. Dao, Daniel J. Emmons Dec 2022

Global Sporadic-E Occurrence Rate Climatology Using Gps Radio Occultation And Ionosonde Data, Travis J. Hodos, Omar A. Nava, Eugene V. Dao, Daniel J. Emmons

Faculty Publications

An updated global climatology of blanketing sporadic E (Es) is developed from a combined data set of Global Positioning System (GPS) radio occultation (RO) and ground-based ionosonde soundings over the period of September 2006–January 2019. A total of 46 sites and 3.2 million total soundings from the Global Ionosphere Radio Observatory network in combination with 3.0 million occultations from the Constellation Observing System for Meteorology, Ionosphere, and Climate constellation are used to calculate global occurrence rates (ORs) for two blanketing frequency thresholds: all blanketing sporadic-E with no limit on intensity (all-Es) and moderate-Es with fbEs …

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A Statistical Analysis Of Sporadic-E Characteristics Associated With Gnss Radio Occultation Phase And Amplitude Scintillations, Daniel J. Emmons, Dong L. Wu, Nimalan Swarnalingam Dec 2022

A Statistical Analysis Of Sporadic-E Characteristics Associated With Gnss Radio Occultation Phase And Amplitude Scintillations, Daniel J. Emmons, Dong L. Wu, Nimalan Swarnalingam

Faculty Publications

Statistical GNSS-RO measurements of phase and amplitude scintillation are analyzed at the mid-latitudes in the local summer for a 100 km altitude. These conditions are known to contain frequent sporadic-E, and the S4-σϕ trends provide insight into the statistical distributions of the sporadic-E parameters. Joint two-dimensional S4-σϕ histograms are presented, showing roughly linear trends until the S4 saturates near 0.8. To interpret the measurements and understand the sporadic-E contributions, 10,000 simulations of RO signals perturbed by sporadic-E layers are performed using length, intensity, and vertical thickness distributions from previous studies, with the assumption that the sporadic-E layer acts …

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Transition-Metal Ions In Β-Ga2O3 Crystals: Identification Of Ni Acceptors, Timothy D. Gustafson, Nancy C. Giles, Brian C. Holloway, J. Jesenovec, B. L. Dutton, M. D. Mccluskey, Larry E. Halliburton Nov 2022

Transition-Metal Ions In Β-Ga2O3 Crystals: Identification Of Ni Acceptors, Timothy D. Gustafson, Nancy C. Giles, Brian C. Holloway, J. Jesenovec, B. L. Dutton, M. D. Mccluskey, Larry E. Halliburton

Faculty Publications

Excerpt: Transition-metal ions (Ni, Cu, and Zn) in β-Ga2O3 crystals form deep acceptor levels in the lower half of the bandgap. In the present study, we characterize the Ni acceptors in a Czochralski-grown crystal and find that their (0/−) level is approximately 1.40 eV above the maximum of the valence band.

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Long-Distance Propagation Of 162 Mhz Shipping Information Links Associated With Sporadic E, Alex T. Chartier, Thomas R. Hanley, Daniel J. Emmons Nov 2022

Long-Distance Propagation Of 162 Mhz Shipping Information Links Associated With Sporadic E, Alex T. Chartier, Thomas R. Hanley, Daniel J. Emmons

Faculty Publications

This is a study of anomalous long-distance (>1000 km) radio propagation that was identified in United States Coast Guard monitors of automatic identification system (AIS) shipping transmissions at 162 MHz. Our results indicate this long-distance propagation is caused by dense sporadic E layers in the daytime ionosphere, which were observed by nearby ionosondes at the same time. This finding is surprising because it indicates these sporadic E layers may be far more dense than previously thought.

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Interband Transitions And Critical Points Of Single-Crystal Thoria Compared With Urania, Christina Dugan, Lu Wang, Kai Zhang, James M. Mann, Martin M. Kimani, Wai-Ning Mei, Peter A. Dowben, James C. Petrosky Nov 2022

Interband Transitions And Critical Points Of Single-Crystal Thoria Compared With Urania, Christina Dugan, Lu Wang, Kai Zhang, James M. Mann, Martin M. Kimani, Wai-Ning Mei, Peter A. Dowben, James C. Petrosky

Faculty Publications

The interband transitions of UO2 are validated independently through cathode luminescence. A picture emerges consistent with density functional theory. While theory is generally consistent with experiment, it is evident from the comparison of UO2 and ThO2 that the choice of functional can significantly alter the bandgap and some details of the band structure, in particular at the conduction band minimum. Strictly ab initio predictions of the optical properties of the actinide compounds, based on density functional theory alone, continue to be somewhat elusive.

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Optimizing Switching Of Non-Linear Properties With Hyperbolic Metamaterials, James A. Ethridge, John G. Jones, Manuel R. Ferdinandus, Michael J. Havrilla, Michael A. Marciniak Nov 2022

Optimizing Switching Of Non-Linear Properties With Hyperbolic Metamaterials, James A. Ethridge, John G. Jones, Manuel R. Ferdinandus, Michael J. Havrilla, Michael A. Marciniak

Faculty Publications

Hyperbolic metamaterials have been demonstrated to have special potential in their linear response, but the extent of their non-linear response has not been extensively modeled or measured. In this work, novel non-linear behavior of an ITO/SiO2 layered hyperbolic metamaterial is modeled and experimentally confirmed, specifically a change in the sign of the non-linear absorption with intensity. This behavior is tunable and can be achieved with a simple one-dimensional layered design. Fabrication was performed with physical vapor deposition, and measurements were conducted using the Z-scan technique. Potential applications include tunable optical switches, optical limiters, and tunable components of laser sources.

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Generating Realistic Cyber Data For Training And Evaluating Machine Learning Classifiers For Network Intrusion Detection Systems, Marc W. Chalé, Nathaniel D. Bastian Nov 2022

Generating Realistic Cyber Data For Training And Evaluating Machine Learning Classifiers For Network Intrusion Detection Systems, Marc W. Chalé, Nathaniel D. Bastian

Faculty Publications

No abstract provided.

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Oxygen Vacancies In Lib3O5 Crystals And Their Role In Nonlinear Absorption, Brian C. Holloway, Christopher A. Lenyk, Timothy D. Gustafson, Nancy C. Giles Oct 2022

Oxygen Vacancies In Lib3O5 Crystals And Their Role In Nonlinear Absorption, Brian C. Holloway, Christopher A. Lenyk, Timothy D. Gustafson, Nancy C. Giles

Faculty Publications

LiB3O5 (LBO) crystals are used to generate the second, third, and fourth harmonics of near-infrared solid-state lasers. At high power levels, the material’s performance is adversely affected by nonlinear absorption. We show that as-grown crystals contain oxygen and lithium vacancies. Transient absorption bands are formed when these intrinsic defects serve as traps for “free” electrons and holes created by x rays or by three- and four-photon absorption processes. Trapped electrons introduce a band near 300 nm and trapped holes produce bands in the 500-600 nm region. Electron paramagnetic resonance (EPR) is used to identify and characterize the …

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Deep-Turbulence Phase Compensation Using Tiled Arrays, Mark F. Spencer, Terry J. Brennan Sep 2022

Deep-Turbulence Phase Compensation Using Tiled Arrays, Mark F. Spencer, Terry J. Brennan

Faculty Publications

Tiled arrays use modulo-2π phase compensation and coherent beam combination to correct for the effects of deep turbulence. As such, this paper uses wave-optics simulations to compare the closed-loop performance of tiled arrays to a branch-point-tolerant phase reconstructor known as LSPV+7 [Appl. Opt. 53, 3821 (2014) [CrossRef] ]. The wave-optics simulations make use of a point-source beacon and are setup with weak-to-strong scintillation conditions. This setup enables a trade-space exploration in support of a power-in-the-bucket comparison with LSPV+7. In turn, the results show that tiled arrays outperform LSPV+7 when transitioning from weak-to-strong scintillation conditions. These results are both …

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Quantifying Dds-Cerberus Network Control Overhead, Andrew T. Park, Nathaniel R. Peck, Richard Dill, Douglas D. Hodson, Michael R. Grimaila, Wayne C. Henry Sep 2022

Quantifying Dds-Cerberus Network Control Overhead, Andrew T. Park, Nathaniel R. Peck, Richard Dill, Douglas D. Hodson, Michael R. Grimaila, Wayne C. Henry

Faculty Publications

Securing distributed device communication is critical because the private industry and the military depend on these resources. One area that adversaries target is the middleware, which is the medium that connects different systems. This paper evaluates a novel security layer, DDS-Cerberus (DDS-C), that protects in-transit data and improves communication efficiency on data-first distribution systems. This research contributes a distributed robotics operating system testbed and designs a multifactorial performance-based experiment to evaluate DDS-C efficiency and security by assessing total packet traffic generated in a robotics network. The performance experiment follows a 2:1 publisher to subscriber node ratio, varying the number of …

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Distribution Of Dds-Cerberus Authenticated Facial Recognition Streams, Andrew T. Park, Nathaniel Peck, Richard Dill, Douglas D. Hodson, Michael R. Grimaila, Wayne C. Henry Sep 2022

Distribution Of Dds-Cerberus Authenticated Facial Recognition Streams, Andrew T. Park, Nathaniel Peck, Richard Dill, Douglas D. Hodson, Michael R. Grimaila, Wayne C. Henry

Faculty Publications

Successful missions in the field often rely upon communication technologies for tactics and coordination. One middleware used in securing these communication channels is Data Distribution Service (DDS) which employs a publish-subscribe model. However, researchers have found several security vulnerabilities in DDS implementations. DDS-Cerberus (DDS-C) is a security layer implemented into DDS to mitigate impersonation attacks using Kerberos authentication and ticketing. Even with the addition of DDS-C, the real-time message sending of DDS also needs to be upheld. This paper extends our previous work to analyze DDS-C’s impact on performance in a use case implementation. The use case covers an artificial …

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Improving Data-Driven Infrastructure Degradation Forecast Skill With Stepwise Asset Condition Prediction Models, Kurt R. Lamm, Justin D. Delorit, Michael N. Grussing, Steven J. Schuldt Aug 2022

Improving Data-Driven Infrastructure Degradation Forecast Skill With Stepwise Asset Condition Prediction Models, Kurt R. Lamm, Justin D. Delorit, Michael N. Grussing, Steven J. Schuldt

Faculty Publications

Organizations with large facility and infrastructure portfolios have used asset management databases for over ten years to collect and standardize asset condition data. Decision makers use these data to predict asset degradation and expected service life, enabling prioritized maintenance, repair, and renovation actions that reduce asset life-cycle costs and achieve organizational objectives. However, these asset condition forecasts are calculated using standardized, self-correcting distribution models that rely on poorly-fit, continuous functions. This research presents four stepwise asset condition forecast models that utilize historical asset inspection data to improve prediction accuracy: (1) Slope, (2) Weighted Slope, (3) Condition-Intelligent Weighted Slope, and (4) …

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Artificial Neural Networks And Gradient Boosted Machines Used For Regression To Evaluate Gasification Processes: A Review, Owen Sedej, Eric Mbonimpa, Trevor Sleight, Jeremy M. Slagley Aug 2022

Artificial Neural Networks And Gradient Boosted Machines Used For Regression To Evaluate Gasification Processes: A Review, Owen Sedej, Eric Mbonimpa, Trevor Sleight, Jeremy M. Slagley

Faculty Publications

Waste-to-Energy technologies have the potential to dramatically improve both the natural and human environment. One type of waste-to-energy technology that has been successful is gasification. There are numerous types of gasification processes and in order to drive understanding and the optimization of these systems, traditional approaches like computational fluid dynamics software have been utilized to model these systems. The modern advent of machine learning models has allowed for accurate and computationally efficient predictions for gasification systems that are informed by numerous experimental and numerical solutions. Two types of machine learning models that have been widely used to solve for quantitative …

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Active 2d-Dna Fingerprinting Of Wirelesshart Adapters To Ensure Operational Integrity In Industrial Systems, Willie H. Mims, Michael A. Temple, Robert F. Mills Jun 2022

Active 2d-Dna Fingerprinting Of Wirelesshart Adapters To Ensure Operational Integrity In Industrial Systems, Willie H. Mims, Michael A. Temple, Robert F. Mills

Faculty Publications

The need for reliable communications in industrial systems becomes more evident as industries strive to increase reliance on automation. This trend has sustained the adoption of WirelessHART communications as a key enabling technology and its operational integrity must be ensured. This paper focuses on demonstrating pre-deployment counterfeit detection using active 2D Distinct Native Attribute (2D-DNA) fingerprinting. Counterfeit detection is demonstrated using experimentally collected signals from eight commercial WirelessHART adapters. Adapter fingerprints are used to train 56 Multiple Discriminant Analysis (MDA) models with each representing five authentic network devices. The three non-modeled devices are introduced as counterfeits and a total of …

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Transportation Service Level Impact On Aircraft Availability, Vincent Mclean, Adam D. Reiman Jun 2022

Transportation Service Level Impact On Aircraft Availability, Vincent Mclean, Adam D. Reiman

Faculty Publications

Purpose — Aircraft fail to meet mission capable rate goals due to a lack of supply of aircraft parts in inventory where the aircraft breaks. This triggers an order at the repair location. To maximize mission capable rate, the time from order to delivery needs to be minimized. The purpose of this research is to examine the case of three airfields for the order to delivery time of mission critical aircraft parts for a specific aircraft type. Design/methodology/approach — This research captured data from three information systems to assess the order fulfillment process. The data were analyzed to determine the …

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Forecasting Country Conflict Using Statistical Learning Methods, Sarah Neumann, Darryl K. Ahner, Raymond R. Hill Jun 2022

Forecasting Country Conflict Using Statistical Learning Methods, Sarah Neumann, Darryl K. Ahner, Raymond R. Hill

Faculty Publications

Purpose — This paper aims to examine whether changing the clustering of countries within a United States Combatant Command (COCOM) area of responsibility promotes improved forecasting of conflict. Design/methodology/approach — In this paper statistical learning methods are used to create new country clusters that are then used in a comparative analysis of model-based conflict prediction. Findings — In this study a reorganization of the countries assigned to specific areas of responsibility are shown to provide improvements in the ability of models to predict conflict. Research limitations/implications — The study is based on actual historical data and is purely data driven. …

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Pilot Development: An Empirical Mixed-Method Analysis, Jonathan Slottje, Jason Anderson, John M. Dickens, Adam D. Reiman Jun 2022

Pilot Development: An Empirical Mixed-Method Analysis, Jonathan Slottje, Jason Anderson, John M. Dickens, Adam D. Reiman

Faculty Publications

Purpose — Pilot upgrade training is critical to aircraft and passenger safety. This study aims to identify variances in the US Air Force C-130J pilot upgrade training based on geographic location and provide a model to enhance policy that will impact future pilot training efforts that lower cost and increase operator quality and proficiency.
Design/methodology/approach — This research employed a mixed-method approach. First, the authors collected data and analyzed 90 C-130J pilots' aviation records and then contextualized this analysis with interviews of experts. Finally, the authors present a modified version of Six Sigma's define–measure–analyze–improve–control (DMAIC) that identifies and reduces the …

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Improving On Atmospheric Turbulence Profiles Derived From Dual Beacon Hartmann Turbulence Sensor Measurements, Alexander S. Boeckenstedt, Jack E. Mccrae, Santasri Bose-Pillai, Benjamin Wilson Jun 2022

Improving On Atmospheric Turbulence Profiles Derived From Dual Beacon Hartmann Turbulence Sensor Measurements, Alexander S. Boeckenstedt, Jack E. Mccrae, Santasri Bose-Pillai, Benjamin Wilson

Faculty Publications

Atmospheric turbulence is an inevitable source of wavefront distortion in all fields of long range laser propagation and sensing. However, the distorting effects of turbulence can be corrected using wavefront sensors contained in adaptive optics systems. Such systems also provide deeper insight into surface layer turbulence, which is not well understood. A unique method of profile generation by a dual source Hartmann Turbulence Sensor (HTS) technique is introduced here. Measurements of optical turbulence along a horizontal path were taken to create C2n profiles. Two helium-neon laser beams were directed over an inhomogeneous horizontal path and captured by the HTS. The …

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A Unified View Of A Human Digital Twin, Michael Miller, Emily Spatz Jun 2022

A Unified View Of A Human Digital Twin, Michael Miller, Emily Spatz

Faculty Publications

The term human digital twin has recently been applied in many domains, including medical and manufacturing. This term extends the digital twin concept, which has been illustrated to provide enhanced system performance as it combines system models and analyses with real-time measurements for an individual system to improve system maintenance. Human digital twins have the potential to change the practice of human system integration as these systems employ real-time sensing and feedback to tightly couple measurements of human performance, behavior, and environmental influences throughout a product’s life cycle to human models to improve system design and performance. However, as this …

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Feasibility Of Obtaining Surface Layer Moisture Flux Using An Ir Thermometer, Steven T. Fiorino, Lance Todorowski, Jaclyn Schmidt, Yogendra Raut, Jacob Margraf May 2022

Feasibility Of Obtaining Surface Layer Moisture Flux Using An Ir Thermometer, Steven T. Fiorino, Lance Todorowski, Jaclyn Schmidt, Yogendra Raut, Jacob Margraf

Faculty Publications

This paper evaluates the feasibility of a method using a single hand-held infrared (IR) thermometer and a mini tower of wet and dry paper towels to psychometrically obtain surface layer temperature and moisture gradients and fluxes. Sling Psychrometers have long been standard measuring devices for quantifying the thermodynamics of near-surface atmospheric gas–vapor mixtures, specifically moisture parameters. However, these devices are generally only used to measure temperature and humidity at one near-surface level. Multiple self-aspirating psychrometers can be used in a vertical configuration to measure temperature and moisture gradients and fluxes in the first 1–2 m of the surface layer. This …

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Electron Traps In Ag-Doped Li2B4O7 Crystals: The Role Of Ag Interstitial Ions, Timothy D. Gustafson, Brant E. Kananen, Nancy C. Giles, Brian C. Holloway, Volodymyr T. Adamiv, Ihor M. Teslyuk, Yaroslav V. Burak, Larry E. Halliburton May 2022

Electron Traps In Ag-Doped Li2B4O7 Crystals: The Role Of Ag Interstitial Ions, Timothy D. Gustafson, Brant E. Kananen, Nancy C. Giles, Brian C. Holloway, Volodymyr T. Adamiv, Ihor M. Teslyuk, Yaroslav V. Burak, Larry E. Halliburton

Faculty Publications

Electron paramagnetic resonance (EPR) is used to establish models for electron traps in Ag-doped lithium tetraborate (Li2B4O7) crystals. When exposed at room temperature to ionizing radiation, electrons are trapped at interstitial Ag+ ions and holes are trapped at Ag+ ions on Li+ sites. The trapped electrons occupy a 5s1 orbital on the interstitial Ag ions (some of the unpaired spin density is also on neighboring ions). Three EPR spectra are assigned to electrons trapped at interstitial Ag ions. Their g values are near 1.99 and they have resolved hyperfine structure …

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Evolution Of Combined Arms Tactics In Heterogeneous Multi-Agent Teams, Robert J. Wilson, David W. King, Gilbert L. Peterson May 2022

Evolution Of Combined Arms Tactics In Heterogeneous Multi-Agent Teams, Robert J. Wilson, David W. King, Gilbert L. Peterson

Faculty Publications

Multi-agent systems research is concerned with the emergence of system-level behaviors from relatively simple agent interactions. Multi-agent systems research to date is primarily concerned with systems of homogeneous agents, with member agents both physically and behaviorally identical. Systems of heterogeneous agents with differing physical or behavioral characteristics may be able to accomplish tasks more efficiently than homogeneous teams, via cooperation between mutually complementary agent types. In this article, we compare the performance of homogeneous and heterogeneous teams in combined arms situations. Combined arms theory proposes that the application of heterogeneous forces, en masse, can generate effects far greater than outcomes …

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Automated Computer Network Exploitation With Bayesian Decision Networks, Graeme Roberts, Gilbert L. Peterson May 2022

Automated Computer Network Exploitation With Bayesian Decision Networks, Graeme Roberts, Gilbert L. Peterson

Faculty Publications

Penetration Testing (pentesting) is the process of using tactics and techniques to penetrate computer systems and networks to expose any issues in their cybersecurity \cite{rsa}. It is currently a manual process requiring significant experience and time that are in limited supply. One way to supplement the shortage is through automation. This paper presents the Automated Network Discovery and Exploitation System (ANDES) which demonstrates that it is feasible to automate the pentesting process. The uniqueness of ANDES is the use of Bayesian decision networks to represent the pentesting domain and subject matter expert knowledge. ANDES conducts multiple execution cycles, which build …

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Factored Beliefs For Machine Agents In Decentralized Partially Observable Markov Decision Processes, Joshua Lapso, Gilbert L. Peterson May 2022

Factored Beliefs For Machine Agents In Decentralized Partially Observable Markov Decision Processes, Joshua Lapso, Gilbert L. Peterson

Faculty Publications

A shared mental model (SMM) is a foundational structure in high performing, task-oriented teams and aid humans in determining their teammate's goals and intentions. Higher levels of mental alignment between teammates can reduce the direct dialogue required for team success. For decision-making teams, a transactive memory system (TMS) offers team members a map of specialized knowledge, indicating source of knowledge and the source's credibility. SMM and TMS formulations aid human-agent team performance in their intended team types. However, neither improve team performance with a project team--one that requires both behavioral and knowledge integration. We present a hybrid cognitive model (HCM) …

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Particle-In-Cell Simulations Of Ion Dynamics In A Pinched-Beam Diode, Jesse C. Foster, John W. Mcclory, S. B. B. Swanekamp, D. D. Hinshelwood, A. S. Richardson, Paul E. Adamson, J. W. Schumer, R. W. James, P. F. Ottinger, D. Mosher May 2022

Particle-In-Cell Simulations Of Ion Dynamics In A Pinched-Beam Diode, Jesse C. Foster, John W. Mcclory, S. B. B. Swanekamp, D. D. Hinshelwood, A. S. Richardson, Paul E. Adamson, J. W. Schumer, R. W. James, P. F. Ottinger, D. Mosher

Faculty Publications

article-in-cell simulations of a 1.6 MV, 800 kA, and 50 ns pinched-beam diode have been completed with emphasis placed on the quality of the ion beams produced. Simulations show the formation of multiple regions in the electron beam flow characterized by locally high charge and current density (“hot spots”). As ions flow through the electron-space-charge cloud, these hot spots electrostatically attract ions to produce a non-uniform ion current distribution. The length of the cavity extending beyond the anode-to-cathode gap (i.e., behind the cathode tip) influences both the number and amplitude of hot spots. A longer cavity length increases the number …

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Application Of Machine Learning To Predict The Performance Of An Emipg Reactor Using Data From Numerical Simulations, Owen Sedej, Eric G. Mbonimpa, Trevor Sleight, Jeremy Slagley Mar 2022

Application Of Machine Learning To Predict The Performance Of An Emipg Reactor Using Data From Numerical Simulations, Owen Sedej, Eric G. Mbonimpa, Trevor Sleight, Jeremy Slagley

Faculty Publications

Microwave-driven plasma gasification technology has the potential to produce clean energy from municipal and industrial solid wastes. It can generate temperatures above 2000 K (as high as 30,000 K) in a reactor, leading to complete combustion and reduction of toxic byproducts. Characterizing complex processes inside such a system is however challenging. In previous studies, simulations using computational fluid dynamics (CFD) produced reproducible results, but the simulations are tedious and involve assumptions. In this study, we propose machine-learning models that can be used in tandem with CFD, to accelerate high-fidelity fluid simulation, improve turbulence modeling, and enhance reduced-order models. A two-dimensional …

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Global Gnss-Ro Electron Density In The Lower Ionosphere, Dong L. Wu, Daniel J. Emmons Ii, Nimalan Swarnalingam Mar 2022

Global Gnss-Ro Electron Density In The Lower Ionosphere, Dong L. Wu, Daniel J. Emmons Ii, Nimalan Swarnalingam

Faculty Publications

Lack of instrument sensitivity to low electron density (Ne) concentration makes it difficult to measure sharp Ne vertical gradients (four orders of magnitude over 30 km) in the D/E-region. A robust algorithm is developed to retrieve global D/E-region Ne from the high-rate GNSS radio occultation (RO) data, to improve spatiotemporal coverage using recent SmallSat/CubeSat constellations. The new algorithm removes F-region contributions in the RO excess phase profile by fitting a linear function to the data below the D-region. The new GNSS-RO observations reveal many interesting features in the diurnal, seasonal, solar-cycle, and magnetic-field-dependent variations in the …

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Considerations For Radio Frequency Fingerprinting Across Multiple Frequency Channels, Jose A. Gutierrez Del Arroyo, Brett J. Borghetti, Michael A. Temple Mar 2022

Considerations For Radio Frequency Fingerprinting Across Multiple Frequency Channels, Jose A. Gutierrez Del Arroyo, Brett J. Borghetti, Michael A. Temple

Faculty Publications

Radio Frequency Fingerprinting (RFF) is often proposed as an authentication mechanism for wireless device security, but application of existing techniques in multi-channel scenarios is limited because prior models were created and evaluated using bursts from a single frequency channel without considering the effects of multi-channel operation. Our research evaluated the multi-channel performance of four single-channel models with increasing complexity, to include a simple discriminant analysis model and three neural networks. Performance characterization using the multi-class Matthews Correlation Coefficient (MCC) revealed that using frequency channels other than those used to train the models can lead to a deterioration in performance from …

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Thermo-Fluidic Transport Process In A Novel M-Shaped Cavity Packed With Non-Darcian Porous Medium And Hybrid Nanofluid: Application Of Artificial Neural Network (Ann), Dipak Kumar Mandal, Nirmalendu Biswas, Nirmal K. Manna, Dilip Kumar Gayen, Rama S. R. Gorla, Ali J. Chamkha Mar 2022

Thermo-Fluidic Transport Process In A Novel M-Shaped Cavity Packed With Non-Darcian Porous Medium And Hybrid Nanofluid: Application Of Artificial Neural Network (Ann), Dipak Kumar Mandal, Nirmalendu Biswas, Nirmal K. Manna, Dilip Kumar Gayen, Rama S. R. Gorla, Ali J. Chamkha

Faculty Publications

In this work, an attempt has been made to explore numerically the thermo-fluidic transport process in a novel M-shaped enclosure filled with permeable material along with Al2O3-Cu hybrid nanoparticles suspended in water under the influence of a horizontal magnetizing field. To exercise the influence of geometric parameters, a classical trapezoidal cavity is modified with an inverted triangle at the top to construct an M-shaped cavity. The cavity is heated isothermally from the bottom and cooled from the top, whereas the inclined sidewalls are insulated. The role of geometric parameters on the thermal performance is scrutinized thoroughly …

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Delaunay Walk For Fast Nearest Neighbor: Accelerating Correspondence Matching For Icp, James D. Anderson, Ryan M. Raettig, Joshua Larson, Clark N. Taylor, Thomas Wischgoll Feb 2022

Delaunay Walk For Fast Nearest Neighbor: Accelerating Correspondence Matching For Icp, James D. Anderson, Ryan M. Raettig, Joshua Larson, Clark N. Taylor, Thomas Wischgoll

Faculty Publications

Point set registration algorithms such as Iterative Closest Point (ICP) are commonly utilized in time-constrained environments like robotics. Finding the nearest neighbor of a point in a reference 3D point set is a common operation in ICP and frequently consumes at least 90% of the computation time. We introduce a novel approach to performing the distance-based nearest neighbor step based on Delaunay triangulation. This greedy algorithm finds the nearest neighbor of a query point by traversing the edges of the Delaunay triangulation created from a reference 3D point set. Our work integrates the Delaunay traversal into the correspondences search of …

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