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Full-Text Articles in Physical Sciences and Mathematics

Convolutional Spiking Neural Networks For Intent Detection Based On Anticipatory Brain Potentials Using Electroencephalogram, Nathan Lutes, V. Sriram Siddhardh Nadendla, K. Krishnamurthy Apr 2024

Convolutional Spiking Neural Networks For Intent Detection Based On Anticipatory Brain Potentials Using Electroencephalogram, Nathan Lutes, V. Sriram Siddhardh Nadendla, K. Krishnamurthy

Computer Science Faculty Research & Creative Works

Spiking neural networks (SNNs) are receiving increased attention because they mimic synaptic connections in biological systems and produce spike trains, which can be approximated by binary values for computational efficiency. Recently, the addition of convolutional layers to combine the feature extraction power of convolutional networks with the computational efficiency of SNNs has been introduced. This paper studies the feasibility of using a convolutional spiking neural network (CSNN) to detect anticipatory slow cortical potentials (SCPs) related to braking intention in human participants using an electroencephalogram (EEG). Data was collected during an experiment wherein participants operated a remote-controlled vehicle on a testbed …


Relative Vectoring Using Dual Object Detection For Autonomous Aerial Refueling, Derek B. Worth, Jeffrey L. Choate, James Lynch, Scott L. Nykl, Clark N. Taylor Mar 2024

Relative Vectoring Using Dual Object Detection For Autonomous Aerial Refueling, Derek B. Worth, Jeffrey L. Choate, James Lynch, Scott L. Nykl, Clark N. Taylor

Faculty Publications

Once realized, autonomous aerial refueling will revolutionize unmanned aviation by removing current range and endurance limitations. Previous attempts at establishing vision-based solutions have come close but rely heavily on near perfect extrinsic camera calibrations that often change midflight. In this paper, we propose dual object detection, a technique that overcomes such requirement by transforming aerial refueling imagery directly into receiver aircraft reference frame probe-to-drogue vectors regardless of camera position and orientation. These vectors are precisely what autonomous agents need to successfully maneuver the tanker and receiver aircraft in synchronous flight during refueling operations. Our method follows a common 4-stage process …


Extraterrestrial Life: The Possibility Of A Human-Alien Interaction, Ariana M. Piscoya Feb 2024

Extraterrestrial Life: The Possibility Of A Human-Alien Interaction, Ariana M. Piscoya

CAFE Symposium 2024

We all have heard of at least one case where someone assured having seen a flying extraterrestrial object. There are thousands of thousands of videos we can find online that “prove” the existence of aliens. In the hypothetical case where aliens are really out there, why haven't we been able to talk to them and look at them face-to-face? A human-extraterrestrial interaction has not yet been achieved for two reasons. First, alien energy is much more powerful than that of humans, so it would require thousands of thousands of years for the human race to develop a technology able to …


The Feasibility Of Motion Tracking Camera System For Magnetic Suspension Wind Tunnel Tests, Hisham M. Shehata, David Cox, Mark Schoenenberger, Colin Britcher, Eli Shellabarger, Timothy Schott, Brendan Mcgovern Jan 2024

The Feasibility Of Motion Tracking Camera System For Magnetic Suspension Wind Tunnel Tests, Hisham M. Shehata, David Cox, Mark Schoenenberger, Colin Britcher, Eli Shellabarger, Timothy Schott, Brendan Mcgovern

Mechanical & Aerospace Engineering Faculty Publications

The Entry Systems Modeling (ESM) Program at NASA has actively participated in the re-development of the Magnetic Suspension Balance System (MSBS) at the six-inch subsonic wind tunnel at NASA Langley Research Center. This initiative aims to enhance the MSBS system's capabilities, enabling the testing of stingless entry vehicle models at supersonic speeds. To achieve this, control algorithms are required to ensure magnetic levitation control and stability for models during free-oscillation dynamic responses. Currently, the system relies on electromagnetic position sensors to provide real-time 3 degrees of freedom control of a rigid body. While this approach has proven successful for subsonic …


Applications Of Ai/Ml In Maritime Cyber Supply Chains, Rafael Diaz, Ricardo Ungo, Katie Smith, Lida Haghnegahdar, Bikash Singh, Tran Phuong Jan 2024

Applications Of Ai/Ml In Maritime Cyber Supply Chains, Rafael Diaz, Ricardo Ungo, Katie Smith, Lida Haghnegahdar, Bikash Singh, Tran Phuong

School of Cybersecurity Faculty Publications

Digital transformation is a new trend that describes enterprise efforts in transitioning manual and likely outdated processes and activities to digital formats dominated by the extensive use of Industry 4.0 elements, including the pervasive use of cyber-physical systems to increase efficiency, reduce waste, and increase responsiveness. A new domain that intersects supply chain management and cybersecurity emerges as many processes as possible of the enterprise require the convergence and synchronizing of resources and information flows in data-driven environments to support planning and execution activities. Protecting the information becomes imperative as big data flows must be parsed and translated into actions …


Gnss Software Defined Radio: History, Current Developments, And Standardization Efforts, Thomas Pany, Dennis Akos, Javier Arribas, M. Zahidul H. Bhuiyan, Pau Closas, Fabio Dovis, Ignacio Fernandez-Hernandez, Carles Fernandez-Prades, Sanjeev Gunawardena, Todd Humphreys, Zaher M. Kassas, Jose A. Lopez Salcedo, Mario Nicola, Mario L. Psiaki, Alexander Rugamer, Yong-Jin Song, Jong-Hoon Won Jan 2024

Gnss Software Defined Radio: History, Current Developments, And Standardization Efforts, Thomas Pany, Dennis Akos, Javier Arribas, M. Zahidul H. Bhuiyan, Pau Closas, Fabio Dovis, Ignacio Fernandez-Hernandez, Carles Fernandez-Prades, Sanjeev Gunawardena, Todd Humphreys, Zaher M. Kassas, Jose A. Lopez Salcedo, Mario Nicola, Mario L. Psiaki, Alexander Rugamer, Yong-Jin Song, Jong-Hoon Won

Faculty Publications

Taking the work conducted by the global navigation satellite system (GNSS) software-defined radio (SDR) working group during the last decade as a seed, this contribution summarizes, for the first time, the history of GNSS SDR development. This report highlights selected SDR implementations and achievements that are available to the public or that influenced the general development of SDR. Aspects related to the standardization process of intermediate-frequency sample data and metadata are discussed, and an update of the Institute of Navigation SDR Standard is proposed. This work focuses on GNSS SDR implementations in general-purpose processors and leaves aside developments conducted on …


Numerical Study Of Owls' Leading-Edge Serrations, Asif Shahriar Nafi, Nikolaos Beratlis, Elias Balaras, Roi Gurka Dec 2023

Numerical Study Of Owls' Leading-Edge Serrations, Asif Shahriar Nafi, Nikolaos Beratlis, Elias Balaras, Roi Gurka

Physics and Engineering Science

Owls' silent flight is commonly attributed to their special wing morphology combined with wingbeat kinematics. One of these special morphological features is known as the leading-edge serrations: rigid miniature hook-like patterns found at the primaries of the wings' leading-edge. It has been hypothesized that leading-edge serrations function as a passive flow control mechanism, impacting the aerodynamic performance. To elucidate the flow physics associated with owls' leading-edge serrations, we investigate the flow-field characteristic around a barn owl wing with serrated leading-edge geometry positioned at 20° angle of attack for a Reynolds number of 40 000. We use direct numerical simulations, where …


Development Of User Interface And Testing Harness, Jacob Amezquita, William Albertini Oct 2023

Development Of User Interface And Testing Harness, Jacob Amezquita, William Albertini

College of Engineering Summer Undergraduate Research Program

No abstract provided.


Kinetic Particle Simulations Of Plasma Charging At Lunar Craters Under Severe Conditions, David Lund, Xiaoming He, Daoru Frank Han Jul 2023

Kinetic Particle Simulations Of Plasma Charging At Lunar Craters Under Severe Conditions, David Lund, Xiaoming He, Daoru Frank Han

Mathematics and Statistics Faculty Research & Creative Works

This paper presents fully kinetic particle simulations of plasma charging at lunar craters with the presence of lunar lander modules using the recently developed Parallel Immersed-Finite-Element Particle-in-Cell (PIFE-PIC) code. The computation model explicitly includes the lunar regolith layer on top of the lunar bedrock, taking into account the regolith layer thickness and permittivity as well as the lunar lander module in the simulation domain, resolving a nontrivial surface terrain or lunar lander configuration. Simulations were carried out to study the lunar surface and lunar lander module charging near craters at the lunar terminator region under mean and severe plasma environments. …


Accurate Covariance Estimation For Pose Data From Iterative Closest Point Algorithm, Rick H. Yuan, Clark N. Taylor, Scott L. Nykl Jul 2023

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 …


Filter-Based Air Sampler Capable Of Integration Into Small Unmanned Aerial Vehicles, Robert M. Eninger, Stepanie A. Ohms, Jeremy M. Slagley Apr 2023

Filter-Based Air Sampler Capable Of Integration Into Small Unmanned Aerial Vehicles, Robert M. Eninger, Stepanie A. Ohms, Jeremy M. Slagley

AFIT Patents

A filter-based air sampler, more specifically a filter-based air sampler capable of integration into small unmanned aerial systems is disclosed. The filter-based air sampler may include a filter assembly which has as its component parts: an open faced air intake component, a filter, and a filter support that has a central supporting grid. The filter assembly may joined to the housing of a fan, such as a centrifugal fan, with the supporting grid of the filter support being disposed over the air inlet of the fan.


Sharprazor: Automatic Removal Of Hair And Ruler Marks From Dermoscopy Images, Reda Kasmi, Jason Hagerty, Reagan Harris Young, Norsang Lama, Januka Nepal, Jessica Miinch, William V. Stoecker, R. Joe Stanley Apr 2023

Sharprazor: Automatic Removal Of Hair And Ruler Marks From Dermoscopy Images, Reda Kasmi, Jason Hagerty, Reagan Harris Young, Norsang Lama, Januka Nepal, Jessica Miinch, William V. Stoecker, R. Joe Stanley

Mechanical and Aerospace Engineering Faculty Research & Creative Works

Background: The removal of hair and ruler marks is critical in handcrafted image analysis of dermoscopic skin lesions. No other dermoscopic artifacts cause more problems in segmentation and structure detection. Purpose: The aim of the work is to detect both white and black hair, artifacts and finally inpaint correctly the image. Method: We introduce a new algorithm: SharpRazor, to detect hair and ruler marks and remove them from the image. Our multiple-filter approach detects hairs of varying widths within varying backgrounds, while avoiding detection of vessels and bubbles. The proposed algorithm utilizes grayscale plane modification, hair enhancement, segmentation using tri-directional …


Artificial Intelligence-Enabled Exploratory Cyber-Physical Safety Analyzer Framework For Civilian Urban Air Mobility, Md. Shirajum Munir, Sumit Howlader Dipro, Kamrul Hasan, Tariqul Islam, Sachin Shetty Jan 2023

Artificial Intelligence-Enabled Exploratory Cyber-Physical Safety Analyzer Framework For Civilian Urban Air Mobility, Md. Shirajum Munir, Sumit Howlader Dipro, Kamrul Hasan, Tariqul Islam, Sachin Shetty

VMASC Publications

Urban air mobility (UAM) has become a potential candidate for civilization for serving smart citizens, such as through delivery, surveillance, and air taxis. However, safety concerns have grown since commercial UAM uses a publicly available communication infrastructure that enhances the risk of jamming and spoofing attacks to steal or crash crafts in UAM. To protect commercial UAM from cyberattacks and theft, this work proposes an artificial intelligence (AI)-enabled exploratory cyber-physical safety analyzer framework. The proposed framework devises supervised learning-based AI schemes such as decision tree, random forests, logistic regression, K-nearest neighbors (KNN), and long short-term memory (LSTM) for predicting and …


Patch-Wise Training With Convolutional Neural Networks To Synthetically Upscale Cfd Simulations, John P. Romano, Alec C. Brodeur, Oktay Baysal Jan 2023

Patch-Wise Training With Convolutional Neural Networks To Synthetically Upscale Cfd Simulations, John P. Romano, Alec C. Brodeur, Oktay Baysal

Mechanical & Aerospace Engineering Faculty Publications

This paper expands the authors’ prior work[1], which focuses on developing a convolutional neural network (CNN) model capable of mapping time-averaged, unsteady Reynold’s-averaged Navier-Stokes (URANS) simulations to higher resolution results informed by time-averaged detached eddy simulations (DES). The authors present improvements over the prior CNN autoencoder model that result from hyperparameter optimization, increased data set augmentation through the adoption of a patch-wise training approach, and the predictions of primitive variables rather than vorticity magnitude. The training of the CNN model developed in this study uses the same URANS and DES simulations of a transonic flow around several NACA 4-digit airfoils …


Convolutional-Neural-Network-Based Des-Level Aerodynamic Flow Field Generation From Urans Data, John P. Romano, Oktay Baysal, Alec C. Brodeur Jan 2023

Convolutional-Neural-Network-Based Des-Level Aerodynamic Flow Field Generation From Urans Data, John P. Romano, Oktay Baysal, Alec C. Brodeur

Mechanical & Aerospace Engineering Faculty Publications

The present paper culminates several investigations into the use of convolutional neural networks (CNNs) as a post-processing step to improve the accuracy of unsteady Reynolds-averaged Navier–Stokes (URANS) simulations for subsonic flows over airfoils at low angles of attack. Time-averaged detached eddy simulation (DES)-generated flow fields serve as the target data for creating and training CNN models. CNN post-processing generates flow-field data comparable to DES resolution, but after using only URANS-level resources and properly training CNN models. This document outlines the underlying theory and progress toward the goal of improving URANS simulations by looking at flow predictions for a class of …


Optimization Of Ported Cfd Kernels On Intel Data Center Gpu Max 1550 Using Oneapi Esimd, Mohammad Zubair, Aaron Walden, Gabriel Nastac, Eric Nielsen, Christoph Bauinger, Xiao Zhu Jan 2023

Optimization Of Ported Cfd Kernels On Intel Data Center Gpu Max 1550 Using Oneapi Esimd, Mohammad Zubair, Aaron Walden, Gabriel Nastac, Eric Nielsen, Christoph Bauinger, Xiao Zhu

Computer Science Faculty Publications

We describe our experience porting FUN3D’s CUDA-optimized kernels to Intel oneAPI SYCL.We faced several challenges, including foremost the suboptimal performance of the oneAPI code on Intel’s new data center GPU. Suboptimal performance of the oneAPI code was due primarily to high register spills, memory latency, and poor vectorization. We addressed these issues by implementing the kernels using Intel oneAPI’s Explicit SIMD SYCL extension (ESIMD) API. The ESIMD API enables the writing of explicitly vectorized kernel code, gives more precise control over register usage and prefetching, and better handles thread divergence compared to SYCL. The ESIMD code outperforms the optimized SYCL …


Underwater Communication Acoustic Transducers: A Technology Review, Laila Shams, Tian-Bing Xu, Zhongqing Su (Ed.), Branko Glisic (Ed.), Maria Pina Limongelli (Ed.) Jan 2023

Underwater Communication Acoustic Transducers: A Technology Review, Laila Shams, Tian-Bing Xu, Zhongqing Su (Ed.), Branko Glisic (Ed.), Maria Pina Limongelli (Ed.)

Mechanical & Aerospace Engineering Faculty Publications

This paper provides a comprehensive review on transducer technologies for underwater communications. The popularly used communication transducers, such as piezoelectric acoustic transducers, electromagnetic acoustic transducers, and acousto-optic devices are reviewed in detail. The reasons that common air communication technologies are invalid die to the differences between the media of air and water are addresses. Because of the abilities to overcome challenges the complexity of marine environments, piezoelectric acoustic transducers are playing the major underwater communication roles for science, surveillance, and Naval missions. The configuration and material properties of piezoelectric transducers effects on signal output power, beamwidth, amplitude, and other properties …


Model Based Systems Engineering With A Docs-As-Code Approach For The Sealion Cubesat Project, Kevin Chiu, Sean Marquez, Sharanabasaweshwara Asundi Jan 2023

Model Based Systems Engineering With A Docs-As-Code Approach For The Sealion Cubesat Project, Kevin Chiu, Sean Marquez, Sharanabasaweshwara Asundi

Mechanical & Aerospace Engineering Faculty Publications

The SeaLion mission architecture team sought to create a model-based systems engineering approach to assist improving CubeSat success rates as well as for the SeaLion CubeSat project to guide an implementation for the flight software. This is important because university CubeSat teams are growing in number but often have untrained students as their core personnel. This was done using a document-as-code, or docs-as-code, approach. With this the team created tools for the systems architecture with the Mach 30 Modeling Language to create an architecture that is easy to learn and use even for newly admitted team members with little to …


Alternatives To Reducing Aviation Fuel-Burn With Technology: Fully Electric Autonomous Taxibot, Denzil Neo Jan 2023

Alternatives To Reducing Aviation Fuel-Burn With Technology: Fully Electric Autonomous Taxibot, Denzil Neo

Student Works

Aircraft taxiing operations in the aerodrome were identified to consume the most jet fuel apart from the cruise phase of the flight. This was also well supported by various research associating taxi operations at large, congested airports, with high jet fuel consumption, high carbon emissions, and noise pollution. Existing literature recognised the potential to address the environmental issues of aerodrome taxi operations by operating External or Onboard Aircraft Ground Propulsion Systems (AGPS). Designed to power aircraft with sources other than their main engines, external Aircraft Ground Power Systems (AGPS) have shown the potential to significantly cut jet fuel consumption and …


Jet Noise Reduction: A Fresh Start, Christopher K. Tam, Fang Q. Hu Jan 2023

Jet Noise Reduction: A Fresh Start, Christopher K. Tam, Fang Q. Hu

Mathematics & Statistics Faculty Publications

Attempts to reduce jet noise began some 70 years ago. In the literature, there have been many publications written on this topic. By now, it is common knowledge that jet noise consists of a number of components. They possess different spectral and radiation characteristics and are generated by different mechanisms. It appears then that one may aim at the suppression of the noise of a single component instead of trying to reduce jet noise overall. The objective of the present project is to reduce large turbulence structures noise. It is the most dominant noise component radiating in the downstream direction. …


Aircraft Engine Particulate Matter Emissions From Sustainable Aviation Fuels: Results From Ground-Based Measurements During The Nasa/Dlr Campaign Eclif2/Nd-Max, Tobias Schripp, Bruce E. Anderson, Uwe Bauder, Bastian Rauch, Joel C. Corbin, Greg J. Smallwood, Prem Lobo, Ewan C. Crosbie, Michael A. Shook, Richard C. Miake-Lye, Zhenhong Yu, Andrew Freedman, Philip D. Whitefield, Claire E. Robinson Oct 2022

Aircraft Engine Particulate Matter Emissions From Sustainable Aviation Fuels: Results From Ground-Based Measurements During The Nasa/Dlr Campaign Eclif2/Nd-Max, Tobias Schripp, Bruce E. Anderson, Uwe Bauder, Bastian Rauch, Joel C. Corbin, Greg J. Smallwood, Prem Lobo, Ewan C. Crosbie, Michael A. Shook, Richard C. Miake-Lye, Zhenhong Yu, Andrew Freedman, Philip D. Whitefield, Claire E. Robinson

Chemistry Faculty Research & Creative Works

The use of alternative jet fuels by commercial aviation has increased substantially in recent years. Beside the reduction of carbon dioxide emission, the use of sustainable aviation fuels (SAF) may have a positive impact on the reduction of particulate emissions. This study summarizes the results from a ground-based measurement activity conducted in January 2018 as part of the ECLIF2/ND-MAX campaign in Ramstein, Germany. Two fossil reference kerosenes and three different blends with the renewable fuel component HEFA-SPK (Hydroprocessed Esters and Fatty Acids Synthetic Paraffinic Kerosene) were burned in an A320 with V2527-A5 engines to investigate the effect of fuel naphthalene/aromatic …


Rocket Measurements Of Electron Energy Spectra From Earth’S Photoelectron Production Layer, Glyn A. Collinson, Alex Glocer, Dennis Chornay, Robert Mitchell, Rob Pfaff, Tim Cameron, Nasa Goddard Space Flight Center, Rudy A. Frahm, Traci Rosnack, Chris Pirner, Ted Gass, Jim Clemmons, Aroh Barjatya, Steven Martin, Hassanali Akbari, Shantanab Debchoudhury, Rachel Conway, Francis Eparvier, Eftyhia Zesta, Nikolaos Paschalidis Aug 2022

Rocket Measurements Of Electron Energy Spectra From Earth’S Photoelectron Production Layer, Glyn A. Collinson, Alex Glocer, Dennis Chornay, Robert Mitchell, Rob Pfaff, Tim Cameron, Nasa Goddard Space Flight Center, Rudy A. Frahm, Traci Rosnack, Chris Pirner, Ted Gass, Jim Clemmons, Aroh Barjatya, Steven Martin, Hassanali Akbari, Shantanab Debchoudhury, Rachel Conway, Francis Eparvier, Eftyhia Zesta, Nikolaos Paschalidis

Publications

Photoelectrons are crucial to atmospheric physics. They heat the atmosphere, strengthen 28 planetary ambipolar electric fields, and enhance the outflow of ions to space. However, 29 there exist only a handful of measurements of their energy spectrum near the peak of 30 photoproduction. We present calibrated energy spectra of pristine photoelectrons at their 31 source by a prototype Dual Electrostatic Analyzer (DESA) instrument flown on July 11 32 2021 aboard the Dynamo-2 sounding rocket (NASA № 36.357). Photopeaks arising from 33 30.4nm He-II spectral line were observed throughout the flight above 120km. DESA also 34 successfully resolved the rarely observed …


Smart Manufacturing—Theories, Methods, And Applications, Zhuming Bi, Lida Xu, Puren Ouyang Aug 2022

Smart Manufacturing—Theories, Methods, And Applications, Zhuming Bi, Lida Xu, Puren Ouyang

Information Technology & Decision Sciences Faculty Publications

(First paragraph) Smart manufacturing (SM) distinguishes itself from other system paradigms by introducing ‘smartness’ as a measure to a manufacturing system; however, researchers in different domains have different expectations of system smartness from their own perspectives. In this Special Issue (SI), SM refers to a system paradigm where digital technologies are deployed to enhance system smartness by (1) empowering physical resources in production, (2) utilizing virtual and dynamic assets over the internet to expand system capabilities, (3) supporting data-driven decision making at all domains and levels of businesses, or (4) reconfiguring systems to adapt changes and uncertainties in dynamic environments. …


Error Estimate Of A Decoupled Numerical Scheme For The Cahn-Hilliard-Stokes-Darcy System, Wenbin Chen, Shufen Wang, Yichao Zhang, Daozhi Han, Cheng Wang, Xiaoming Wang Jul 2022

Error Estimate Of A Decoupled Numerical Scheme For The Cahn-Hilliard-Stokes-Darcy System, Wenbin Chen, Shufen Wang, Yichao Zhang, Daozhi Han, Cheng Wang, Xiaoming Wang

Mathematics and Statistics Faculty Research & Creative Works

We analyze a fully discrete finite element numerical scheme for the Cahn-Hilliard-Stokes-Darcy system that models two-phase flows in coupled free flow and porous media. To avoid a well-known difficulty associated with the coupling between the Cahn-Hilliard equation and the fluid motion, we make use of the operator-splitting in the numerical scheme, so that these two solvers are decoupled, which in turn would greatly improve the computational efficiency. The unique solvability and the energy stability have been proved in Chen et al. (2017, Uniquely solvable and energy stable decoupled numerical schemes for the Cahn-Hilliard-Stokes-Darcy system for two-phase flows in karstic geometry. …


Optimization Of Orbital Trajectories Using Neuroevolution Of Augmenting Topologies, Nathan Wetherell May 2022

Optimization Of Orbital Trajectories Using Neuroevolution Of Augmenting Topologies, Nathan Wetherell

University Scholar Projects

This project aims to determine the feasibility of using NeuroEvolution of Augmenting Topologies (NEAT), an advanced neural network evolution scheme, to optimize orbital transfer trajectories. More specifically, this project compares a genetically evolved neural network to a standard Hohmann transfer between Earth and Mars. To test these two methods, an N-body simulation environment was created to accurately determine the result of gravitational interactions on a theoretical spacecraft when combined with planned engine burns. Once created, this simulation environment was used to train the neural networks created using the NEAT Python module. A genetic algorithm was used to modify the topology …


Characterizing And Predicting Human Visual Perception Of Unmanned Aerial Vehicle Gestures, Paul Fletcher Apr 2022

Characterizing And Predicting Human Visual Perception Of Unmanned Aerial Vehicle Gestures, Paul Fletcher

Department of Computer Science and Engineering: Dissertations, Theses, and Student Research

Unmanned Aerial Vehicles (UAVs) are being used in public domains and hazardous environments where effective communication strategies are critical. UAV gesture techniques have been shown to communicate meaning to human observers and may be ideal in contexts that require lightweight systems such as unmanned aerial flight, however, this work may be limited to an idealized range of viewer perspectives. As gesture is a visual communication technique it is necessary to consider how the perception of a robot gesture may suffer from obfuscation or self-occlusion from some viewpoints. This thesis presents the results of three online user-studies that examine participants’ ability …


An Accurate And Computationally Efficient Method For Battery Capacity Fade Modeling, D. M. Ajiboye, Jonathan W. Kimball, R.(Robert) G. Landers, John (T.) Park Mar 2022

An Accurate And Computationally Efficient Method For Battery Capacity Fade Modeling, D. M. Ajiboye, Jonathan W. Kimball, R.(Robert) G. Landers, John (T.) Park

Electrical and Computer Engineering Faculty Research & Creative Works

The Industry Demand for Accurate and Fast Algorithms that Model Vital Battery Parameters, E.g., State-Of-Health, State-Of-Charge, Pulse-Power Capability, is Substantial. One of the Most Critical Models is Battery Capacity Fade. the Key Challenge with Physics-Based Battery Capacity Fade Modeling is the High Numerical Cost in Solving Complex Models. in This Study, an Efficient and Fast Model is Presented to Capture Capacity Fade in Lithium-Ion Batteries. Here, the High-Order Chebyshev Spectral Method is Employed to Address the Associated Complexity with Physics-Based Capacity Fade Models. its Many Advantages, Such as Low Computational Memory, High Accuracy, Exponential Convergence, and Ease of Implementation, Allow …


Robust Error Estimation Based On Factor-Graph Models For Non-Line-Of-Sight Localization, O. Arda Vanli, Clark N. Taylor Jan 2022

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 …


On The Use Of High-Frequency Surface Wave Oceanographic Research Radars As Bistatic Single-Frequency Oblique Ionospheric Sounders, Stephen R. Kaeppler, Ethan S. Miller, Daniel Cole, Teresa Updyke Jan 2022

On The Use Of High-Frequency Surface Wave Oceanographic Research Radars As Bistatic Single-Frequency Oblique Ionospheric Sounders, Stephen R. Kaeppler, Ethan S. Miller, Daniel Cole, Teresa Updyke

CCPO Publications

We demonstrate that bistatic reception of high-frequency oceanographic radars can be used as single-frequency oblique ionospheric sounders. We develop methods that are agnostic of the software-defined radio system to estimate the group range from the bistatic observations. The group range observations are used to estimate the virtual height and equivalent vertical frequency at the midpoint of the oblique propagation path. Uncertainty estimates of the virtual height and equivalent vertical frequency are presented. We apply this analysis to observations collected from two experiments run at two locations in different years, but utilizing similar software-defined radio data collection systems. In the first …


Uas Obstacle Database For University Traffic Management System, Casey Calamaio Jan 2022

Uas Obstacle Database For University Traffic Management System, Casey Calamaio

Summer Community of Scholars (RCEU and HCR) Project Proposals

No abstract provided.