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Articles 1 - 30 of 152
Full-Text Articles in Physical Sciences and Mathematics
Accurate Covariance Estimation For Pose Data From Iterative Closest Point Algorithm, Rick H. Yuan, Clark N. Taylor, Scott L. Nykl
Accurate Covariance Estimation For Pose Data From Iterative Closest Point Algorithm, Rick H. Yuan, Clark N. Taylor, Scott L. Nykl
Faculty Publications
One of the fundamental problems of robotics and navigation is the estimation of the relative pose of an external object with respect to the observer. A common method for computing the relative pose is the iterative closest point (ICP) algorithm, where a reference point cloud of a known object is registered against a sensed point cloud to determine relative pose. To use this computed pose information in downstream processing algorithms, it is necessary to estimate the uncertainty of the ICP output, typically represented as a covariance matrix. In this paper, a novel method for estimating uncertainty from sensed data is …
Evolution Of Coronal Magnetic Field Parameters During X5.4 Solar Flare, Seth H. Garland, Benjamin F. Akers, Vasyl B. Yurchyshyn, Robert D. Loper, Daniel J. Emmons
Evolution Of Coronal Magnetic Field Parameters During X5.4 Solar Flare, Seth H. Garland, Benjamin F. Akers, Vasyl B. Yurchyshyn, Robert D. Loper, Daniel J. Emmons
Faculty Publications
The coronal magnetic field over NOAA Active Region 11,429 during a X5.4 solar flare on 7 March 2012 is modeled using optimization based Non-Linear Force-Free Field extrapolation. Specifically, 3D magnetic fields were modeled for 11 timesteps using the 12-min cadence Solar Dynamics Observatory (SDO) Helioseismic and Magnetic Imager photospheric vector magnetic field data, spanning a time period of 1 hour before through 1 hour after the start of the flare. Using the modeled coronal magnetic field data, seven different magnetic field parameters were calculated for 3 separate regions: areas with surface |Bz| ≥ 300 G, areas of flare brightening seen …
Student Performance In Traditional In-Person Vs. Online Sections Of An Introductory Graduate Mathematics Course, Lauran E. Kittle
Student Performance In Traditional In-Person Vs. Online Sections Of An Introductory Graduate Mathematics Course, Lauran E. Kittle
Theses and Dissertations
The growth of technology impacts nearly every aspect of everyday life, to include education and learning. The availability of distance learning (online) classes has increased drastically in the last few decades, expanding access to education for millions of people. However, it is imperative to consider exactly how the growth of technology impacts education – whether it is a positive, negative, or neutral impact. Previous research comparing distance learning and in-residence (traditional) classes have widely mixed, disparate conclusions. This type of research, two-stage analysis, and modeling has yet to be conducted on a graduate school level. For this reason, a detailed …
Leveraging Subject Matter Expertise To Optimize Machine Learning Techniques For Air And Space Applications, Philip Y. Cho
Leveraging Subject Matter Expertise To Optimize Machine Learning Techniques For Air And Space Applications, Philip Y. Cho
Theses and Dissertations
We develop new machine learning and statistical methods that are tailored for Air and Space applications through the incorporation of subject matter expertise. In particular, we focus on three separate research thrusts that each represents a different type of subject matter knowledge, modeling approach, and application. In our first thrust, we incorporate knowledge of natural phenomena to design a neural network algorithm for localizing point defects in transmission electron microscopy (TEM) images of crystalline materials. In our second research thrust, we use Bayesian feature selection and regression to analyze the relationship between fighter pilot attributes and flight mishap rates. We …
Classification And Keyword Identification Of Covid 19 Misinformation On Social Media: A Framework For Semantic Analysis, Grace Y. Smith
Classification And Keyword Identification Of Covid 19 Misinformation On Social Media: A Framework For Semantic Analysis, Grace Y. Smith
Theses and Dissertations
The growing surge of misinformation among COVID-19 communication can pose great hindrance to truth, magnify distrust in policy makers and/or degrade authorities’ credibility, and it can even harm public health. Classification of textual context on social media data relating to COVID-19 is an effective tool to combat misinformation on social media platforms. In this research, Twitter data was leveraged to 1) develop classification methods to detect misinformation and identify Tweet sentiment with respect to COVID-19 and 2) develop a human-in-the-loop interactive framework to enable identification of keywords associated with social context, here, being misinformation regarding COVID-19. 1) Six fusion-based classification …
Robust Error Estimation Based On Factor-Graph Models For Non-Line-Of-Sight Localization, O. Arda Vanli, Clark N. Taylor
Robust Error Estimation Based On Factor-Graph Models For Non-Line-Of-Sight Localization, O. Arda Vanli, Clark N. Taylor
Faculty Publications
This paper presents a method to estimate the covariances of the inputs in a factor-graph formulation for localization under non-line-of-sight conditions. A general solution based on covariance estimation and M-estimators in linear regression problems, is presented that is shown to give unbiased estimators of multiple variances and are robust against outliers. An iteratively re-weighted least squares algorithm is proposed to jointly compute the proposed variance estimators and the state estimates for the nonlinear factor graph optimization. The efficacy of the method is illustrated in a simulation study using a robot localization problem under various process and measurement models and measurement …
Equichordal Tight Fusion Frames And Biangular Orthopartitionable Tight Frames, Benjamin R. Mayo
Equichordal Tight Fusion Frames And Biangular Orthopartitionable Tight Frames, Benjamin R. Mayo
Theses and Dissertations
An equichordal tight fusion frame (ECTFF) is a sequence of equidimensional subspaces of a Euclidean space that achieves equality in Conway, Hardin and Sloane's simplex bound, and so is a type of optimal Grassmannian code. In the special case where its subspaces have dimension one, an ECTFF corresponds to an equiangular tight frame (ETF); such frames have minimal coherence and so are useful for compressed sensing. More generally, an ECTFF will yield a frame with minimal block coherence when its subspaces are pairwise isoclinic, namely when it is an equi-isoclinic tight fusion frame (EITFF). In this dissertation, we generalize the …
Instabilities Of Overturned Traveling Waves, Tyler B. Pierce
Instabilities Of Overturned Traveling Waves, Tyler B. Pierce
Theses and Dissertations
The instabilities of overturned traveling waves are determined by the use of spectral methods. Two separate numerical methods, Spectral Stability Analysis and Dynamic Stability Analysis, are used to assess the instabilities of branches of waves solved from conformally-mapped Euler equations. The branches of waves with Bond number less than two were found to be spectrally stable to super-harmonic perturbations. The branches of waves with Bond number in [2,3) had some waves that were stable and some that were unstable. All overturned waves with Bond number greater than or equal to two were unstable.
Correlated Positron-Electron Orbital (Cpeo): A Novel Method That Models Positron-Electron Correlation In Virtual Ps At The Mean-Field Level, Kevin E. Blaine
Correlated Positron-Electron Orbital (Cpeo): A Novel Method That Models Positron-Electron Correlation In Virtual Ps At The Mean-Field Level, Kevin E. Blaine
Theses and Dissertations
The Correlated Positronic-Electronic Orbital (CPEO) method was developed and implemented to capture correlation effects at between the positron and electron in the modeling of systems that involve a bound positron. Methods that effectively model these systems require many hundred basis functions and use a mean field approach as the beginning step. CPEO builds an orbital for virtual Positronium (Ps) that contains a positron in a bound state along with an accompanying electron to the larger system. Assigning the virtual Ps orbital allows for the two particle variational optimization in conjunction with the other particles that compose the whole system. This …
An Analysis Of The Effects Of Technology Readiness Levels On Cost Growth, Christopher R. Bissing
An Analysis Of The Effects Of Technology Readiness Levels On Cost Growth, Christopher R. Bissing
Theses and Dissertations
This research seeks to evaluate the effects of Technology Readiness Levels (TRL) on Cost Growth. It makes use of data from Technology Readiness Assessments (TRA) and Selected Acquisition Reports (SAR) to explore relationships between TRLs at Milestone B and cost growth in Major Defense Acquisition Programs (MDAP) and Major Automated Information Systems (MAIS). Programs using higher proportions of critical technologies rated below TRL 7 tend to experience greater cost growth than programs that use more mature technologies. Current DoD doctrine requires TRL 6 to enter Milestone B. The results of this research seek to evaluate the merit of this requirement. …
A Learning Curve Model Accounting For The Flattening Effect In Production Cycles, Evan R. Boone, John J. Elshaw, Clay M. Koschnick, Jonathan D. Ritschel, Adedeji B. Badiru
A Learning Curve Model Accounting For The Flattening Effect In Production Cycles, Evan R. Boone, John J. Elshaw, Clay M. Koschnick, Jonathan D. Ritschel, Adedeji B. Badiru
Faculty Publications
We investigate production cost estimates to identify and model modifications to a prescribed learning curve. Our new model examines the learning rate as a decreasing function over time as opposed to a constant rate that is frequently used. The purpose of this research is to determine whether a new learning curve model could be implemented to reduce the error in cost estimates for production processes. A new model was created that mathematically allows for a “flattening effect,” which typically occurs later in the production process. This model was then compared to Wright’s learning curve, which is a popular method used …
Extending Critical Infrastructure Element Longevity Using Constellation-Based Id Verification, Christopher M. Rondeau, Michael A. Temple, J. Addison Betances, Christine M. Schubert Kabban
Extending Critical Infrastructure Element Longevity Using Constellation-Based Id Verification, Christopher M. Rondeau, Michael A. Temple, J. Addison Betances, Christine M. Schubert Kabban
Faculty Publications
This work supports a technical cradle-to-grave protection strategy aimed at extending the useful lifespan of Critical Infrastructure (CI) elements. This is done by improving mid-life operational protection measures through integration of reliable physical (PHY) layer security mechanisms. The goal is to improve existing protection that is heavily reliant on higher-layer mechanisms that are commonly targeted by cyberattack. Relative to prior device ID discrimination works, results herein reinforce the exploitability of constellation-based PHY layer features and the ability for those features to be practically implemented to enhance CI security. Prior work is extended by formalizing a device ID verification process that …
Modeling And Simulation Techniques Used In High Strain Rate Projectile Impact, Derek G. Spear, Anthony N. Palazotto, Ryan A. Kemnitz
Modeling And Simulation Techniques Used In High Strain Rate Projectile Impact, Derek G. Spear, Anthony N. Palazotto, Ryan A. Kemnitz
Faculty Publications
A series of computational models and simulations were conducted for determining the dynamic responses of a solid metal projectile impacting a target under a prescribed high strain rate loading scenario in three-dimensional space. The focus of this study was placed on two different modeling techniques within finite element analysis available in the Abaqus software suite. The first analysis technique relied heavily on more traditional Lagrangian analysis methods utilizing a fixed mesh, while still taking advantage of the finite difference integration present under the explicit analysis approach. A symmetry reduced model using the Lagrangian coordinate system was also developed for comparison …
Through-The-Wall Radar Detection Using Machine Learning, Aihua W. Wood, Ryan Wood, Matthew Charnley
Through-The-Wall Radar Detection Using Machine Learning, Aihua W. Wood, Ryan Wood, Matthew Charnley
Faculty Publications
This paper explores the through-the-wall inverse scattering problem via machine learning. The reconstruction method seeks to discover the shape, location, and type of hidden objects behind walls, as well as identifying certain material properties of the targets. We simulate RF sources and receivers placed outside the room to generate observation data with objects randomly placed inside the room. We experiment with two types of neural networks and use an 80-20 train-test split for reconstruction and classification.
Modeling Nonlinear Heat Transfer For A Pin-On-Disc Sliding System, Brian A. Boardman
Modeling Nonlinear Heat Transfer For A Pin-On-Disc Sliding System, Brian A. Boardman
Theses and Dissertations
The objective of this research is to develop a numerical method to characterize heat transfer and wear rates for samples of Vascomax® 300, or Maraging 300, steel. A pin-on-disc experiment was conducted in which samples were exposed to a high-pressure, high-speed, sliding contact environment. This sliding contact generates frictional heating that influences the temperature distribution and wear characteristics of the test samples. A two-dimensional nonlinear heat transfer equation is discretized and solved via a second-order explicit finite difference scheme to predict the transient temperature distribution of the pin. This schematic is used to predict the removal of material from the …
A Sequential Partial Information Bomber‐Defender Shooting Problem, Krishna Kalyanam, David W. Casbeer, Meir Pachter
A Sequential Partial Information Bomber‐Defender Shooting Problem, Krishna Kalyanam, David W. Casbeer, Meir Pachter
Faculty Publications
No abstract provided.
An Ultra-Sparse Approximation Of Kinetic Solutions To Spatially Homogeneous Flows Of Non-Continuum Gas, Alexander Alekseenko, Amy Grandilli, Aihua W. Wood
An Ultra-Sparse Approximation Of Kinetic Solutions To Spatially Homogeneous Flows Of Non-Continuum Gas, Alexander Alekseenko, Amy Grandilli, Aihua W. Wood
Faculty Publications
We consider a compact approximation of the kinetic velocity distribution function by a sum of isotropic Gaussian densities in the problem of spatially homogeneous relaxation. Derivatives of the macroscopic parameters of the approximating Gaussians are obtained as solutions to a linear least squares problem derived from the Boltzmann equation with full collision integral. Our model performs well for flows obtained by mixing upstream and downstream conditions of normal shock wave with Mach number 3. The model was applied to explore the process of approaching equilibrium in a spatially homogeneous flow of gas. Convergence of solutions with respect to the model …
Dimension-Breaking For Traveling Waves In Interfacial Flows, Matthew W. Seiders
Dimension-Breaking For Traveling Waves In Interfacial Flows, Matthew W. Seiders
Theses and Dissertations
Fluid flow models in two spatial dimensions with a one-dimensional interface are known to support overturned traveling solutions. Computational methods of solving the two-dimensional problem are well developed, even in the case of overturned waves. The three-dimensional problem is harder for three prominent reasons. First, some formulations of the two-dimensional problem do not extend to three-dimensions. The technique of conformal mapping is a prime example, as it is very efficient in two dimensions but does not have a three-dimensional equivalent. Second, some three-dimensional models, such as the Transformed Field Expansion method, do not allow for overturned waves. Third, computational time …
Ergodicity For The 3d Stochastic Navier-Stokes Equations Perturbed By Lévy Noise, Manil T. Mohan, K. Sakthivel, Sivaguru S. Sritharan
Ergodicity For The 3d Stochastic Navier-Stokes Equations Perturbed By Lévy Noise, Manil T. Mohan, K. Sakthivel, Sivaguru S. Sritharan
Faculty Publications
In this work we construct a Markov family of martingale solutions for 3D stochastic Navier–Stokes equations (SNSE) perturbed by Lévy noise with periodic boundary conditions. Using the Kolmogorov equations of integrodifferential type associated with the SNSE perturbed by Lévy noise, we construct a transition semigroup and establish the existence of a unique invariant measure. We also show that it is ergodic and strongly mixing.
Abstract © Wiley.
Harmonic Equiangular Tight Frames Comprised Of Regular Simplices, Courtney A. Schmitt
Harmonic Equiangular Tight Frames Comprised Of Regular Simplices, Courtney A. Schmitt
Theses and Dissertations
An equiangular tight frame (ETF) is a sequence of equal-norm vectors in a Euclidean space whose coherence achieves equality in the Welch bound, and thus yields an optimal packing in a projective space. A regular simplex is a simple type of ETF in which the number of vectors is one more than the dimension of the underlying space. More sophisticated examples include harmonic ETFs, which are formed by restricting the characters of a finite abelian group to a difference set. Recently, it was shown that some harmonic ETFs are themselves comprised of regular simplices. In this thesis, we continue the …
Modeling The Distribution Of Lightning Strike Distances Outside A Preexisting Lightning Area, Dawn L. Sanderson
Modeling The Distribution Of Lightning Strike Distances Outside A Preexisting Lightning Area, Dawn L. Sanderson
Theses and Dissertations
Air Force Instruction 91-203 (AFI 91-203) directs that a lightning warning be issued when lightning is occurring or imminent within a 5 nautical mile (NM) radius of a predetermined location or activity. The 45 Weather Squadron (WS), located on the central eastern coast of Florida, balances the safety of personnel and space launch vehicles with lost productivity of taking shelter from lightning. The primary objective of this study investigates if this 5 NM safety radius can be reduced while maintaining a desired level of safety. The research uses processed Lightning Detection and Ranging (LDAR) data to map the movement of …
An Imputation Approach To Developing Alternative Futures Of Country Conflict, Zachary J. Kane
An Imputation Approach To Developing Alternative Futures Of Country Conflict, Zachary J. Kane
Theses and Dissertations
Understanding what causes countries to be in a state of violent conflict is of vital importance to developing realistic national strategies on both a regional and global scale. Given these causes, it is important to understand the effects of missing data, how to impute that data, and the interrelation between data elements. Utilizing both open source data and previously generated equations that predict a country’s likelihood to transition conflict statuses, this research projects data into the future and predicts each nations’ subsequent conflict statuses. Future data is populated using a novel approach inspired by stochastic regression imputation. The replicated future …
Compressive Sampling For Phenotype Classification, Eric L. Brooks
Compressive Sampling For Phenotype Classification, Eric L. Brooks
Theses and Dissertations
Phenotype classification has become an increasingly important genomic research method for disease identification and treatment. Phenotype classification is the investigation into the genetic information concerned with locating biomarkers (features) in order to identify an observed effect. The primary challenge associated with phenotype classification is with analyzing the data due to the inherent high-dimensionality of DNA data. As a result, phenotype classification faces challenges with feature selection, and consequently, classification accuracy. This research developed a methodology to alleviate these challenges while improving classification performance. The methodology leverages concepts of compressive sampling, to arrive at a process that identifies features most relevant …
Numerical Simulation Of High Energy Laser Propagation, Dana F. Morrill
Numerical Simulation Of High Energy Laser Propagation, Dana F. Morrill
Theses and Dissertations
High energy lasers have many applications, such as in aerospace, weapons, wireless power transfer, and manufacturing. Fluid-laser interaction is important to predicting power at receiver, and other measures of laser beam quality. Typically the carrying medium of the laser is modeled statistically. This dissertation describes a novel method of coupling fluid dynamics to beam propagation in free space. The coupled laser-fluid solver captures dynamic interaction of fluid temperature and beam intensity. Ultimately, the model captures the effects of fluid convection in the laser intensity-field. Boundary conditions play an important role for fluid dynamics, more so than for beam dynamics. Simulation …
Statistical Inference To Evaluate And Compare The Performance Of Correlated Multi-State Classification Systems, Beau A. Nunnally
Statistical Inference To Evaluate And Compare The Performance Of Correlated Multi-State Classification Systems, Beau A. Nunnally
Theses and Dissertations
The current emphasis on including correlation when comparing diagnostic test performance is quite important, however, there are cases in which correlation effects may be negligible with respect to inference. This proposed work examines the impact of including correlation between classification systems with continuous features by comparing the optimal performance of two diagnostic tests with multiple outcomes as well as providing inference for a sequence of tests. We define the optimal point using Bayes Cost, a metric that sums the weighted misclassifications within a diagnostic test using a cost/benefit structure. Through simulation, we quantify the impact of correlation on standard errors …
Cross-Participant Eeg-Based Assessment Of Cognitive Workload Using Multi-Path Convolutional Recurrent Neural Networks, Ryan G. Hefron, Brett J. Borghetti, Christine M. Schubert Kabban, James Christensen, Justin Estep
Cross-Participant Eeg-Based Assessment Of Cognitive Workload Using Multi-Path Convolutional Recurrent Neural Networks, Ryan G. Hefron, Brett J. Borghetti, Christine M. Schubert Kabban, James Christensen, Justin Estep
Faculty Publications
Applying deep learning methods to electroencephalograph (EEG) data for cognitive state assessment has yielded improvements over previous modeling methods. However, research focused on cross-participant cognitive workload modeling using these techniques is underrepresented. We study the problem of cross-participant state estimation in a non-stimulus-locked task environment, where a trained model is used to make workload estimates on a new participant who is not represented in the training set. Using experimental data from the Multi-Attribute Task Battery (MATB) environment, a variety of deep neural network models are evaluated in the trade-space of computational efficiency, model accuracy, variance and temporal specificity yielding three …
Uncertainty Evaluation In The Design Of Structural Health Monitoring Systems For Damage Detection, Christine M. Schubert Kabban, Richard P. Uber, Kevin J. Lin, Bin Lin, M. Bhuiyan, Victor Giurgiutiu
Uncertainty Evaluation In The Design Of Structural Health Monitoring Systems For Damage Detection, Christine M. Schubert Kabban, Richard P. Uber, Kevin J. Lin, Bin Lin, M. Bhuiyan, Victor Giurgiutiu
Faculty Publications
The validation of structural health monitoring (SHM) systems for aircraft is complicated by the extent and number of factors that the SHM system must demonstrate for robust performance. Therefore, a time- and cost-efficient method for examining all of the sensitive factors must be conducted. In this paper, we demonstrate the utility of using the simulation modeling environment to determine the SHM sensitive factors that must be considered for subsequent experiments, in order to enable the SHM validation. We demonstrate this concept by examining the effect of SHM system configuration and flaw characteristics on the response of a signal from a …
Analysis Of Temperature And Humidity Effects On Horizontal Photovoltaic Panels, Corey J. Booker
Analysis Of Temperature And Humidity Effects On Horizontal Photovoltaic Panels, Corey J. Booker
Theses and Dissertations
The United States Air Force seeks to address power grid vulnerability and bolster energy resilience through the use of renewable energy sources. Air Force Institute of Technology engineers designed and manufactured control systems to monitor power production from the most widely-used silicon-based solar cells at 38 testing locations around the globe spanning the majority of climate types. Researchers conducted multivariate regression analysis to establish a statistical relationship between photovoltaic power output, ambient temperature, and humidity pertaining to monocrystalline and polycrystalline photovoltaic panels. Formulated models first characterized power output globally, then by specific climate type with general inaccuracy. Location-specific models are …
An Analysis Of The Estimate At Complete For Department Of Defense Contracts, Deborah B. Kim
An Analysis Of The Estimate At Complete For Department Of Defense Contracts, Deborah B. Kim
Theses and Dissertations
When contractors provide timely and reliable information on the status of a contract, both contractors and government program offices can provide an accurate estimate of a contract’s completion costs. This research shows that the cumulative cost performance indices provided by contractors and program offices are high and less accurate than those of previous years and/or that a significant amount of ACWP is being documented in the final portion of a contract. The high performance indices resulted in EACs that were low-balled during the majority of a contract’s life which shows a need to improve the use of EVM metrics for …
Radial Basis Function Generated Finite Differences For The Nonlinear Schrodinger Equation, Justin Ng
Radial Basis Function Generated Finite Differences For The Nonlinear Schrodinger Equation, Justin Ng
Theses and Dissertations
Solutions to the one-dimensional and two-dimensional nonlinear Schrodinger (NLS) equation are obtained numerically using methods based on radial basis functions (RBFs). Periodic boundary conditions are enforced with a non-periodic initial condition over varying domain sizes. The spatial structure of the solutions is represented using RBFs while several explicit and implicit iterative methods for solving ordinary differential equations (ODEs) are used in temporal discretization for the approximate solutions to the NLS equation. Splitting schemes, integration factors and hyperviscosity are used to stabilize the time-stepping schemes and are compared with one another in terms of computational efficiency and accuracy. This thesis shows …