Physical Sciences and Mathematics Commons^™

On-Chip Nanoscale Plasmonic Optical Modulators, Abdalrahman Mohamed Nader Abdelhamid

Theses and Dissertations

In this thesis work, techniques for downsizing Optical modulators to nanoscale for the purpose of utilization in on chip communication and sensing applications are explored. Nanoscale optical interconnects can solve the electronics speed limiting transmission lines, in addition to decrease the electronic chips heat dissipation. A major obstacle in the path of achieving this goal is to build optical modulators, which transforms data from the electrical form to the optical form, in a size comparable to the size of the electronics components, while also having low insertion loss, high extinction ratio and bandwidth. Also, lap-on-chip applications used for fast diagnostics, …

Wound Image Classification Using Deep Convolutional Neural Networks, Behrouz Rostami

Theses and Dissertations

Artificial Intelligence (AI) includes subfields like Machine Learning (ML) and DeepLearning (DL) and discusses intelligent systems that mimic human behaviors. ML has been used in a wide range of fields. Particularly in the healthcare domain, medical images often need to be carefully processed via such operations as classification and segmentation. Unlike traditional ML methods, DL algorithms are based on deep neural networks that are trained on a large amount of labeled data to extract features without human intervention. DL algorithms have become popular and powerful in classifying and segmenting medical images in recent years. In this thesis, we shall study …

Comparison Of Conic Ray Tracing For Occlusion Determination On 3d Point Cloud Data, Henry Cho

Theses and Dissertations

The US Air Force has been increasing the use of automation in its weapon systems to include the remotely piloted aircraft (RPA) platforms. The RPA career field has had issues with poor pilot retention due to job stressors. For example, RPA operators spend a lot of time and attention surveilling a suspect on the ground for many hours, so adding automation to this activity could help improve pilot retention. The research problem in this thesis attempted to automate the process of observing a ground target. This thesis presents a method termed conic ray tracing for determining visibility and occlusion of …

Laser Illuminated Imaging: Beam And Scene Deconvolution Algorithm, Benjamin W. Davis

Theses and Dissertations

Laser illuminated imaging systems deal with several physical challenges that must be overcome to achieve high-resolution images of the target. Noise sources like background noise, photon counting noise, and laser speckle noise will all greatly affect the imaging systems ability to produce a high-resolution image. An even bigger challenge to laser illuminated imaging systems is atmospheric turbulence and the effect that it will have on the imaging system. The illuminating beam will experience tilt, causing the beam to wander off the center of the target during propagation. The light returning to the detector will similarly be affected by turbulence, and …

The Wargaming Commodity Course Of Action Automated Analysis Method, William T. Deberry

Theses and Dissertations

This research presents the Wargaming Commodity Course of Action Automated Analysis Method (WCCAAM), a novel approach to assist wargame commanders in developing and analyzing courses of action (COAs) through semi-automation of the Military Decision Making Process (MDMP). MDMP is a seven-step iterative method that commanders and mission partners follow to build an operational course of action to achieve strategic objectives. MDMP requires time, resources, and coordination – all competing items the commander weighs to make the optimal decision. WCCAAM receives the MDMP's Mission Analysis phase as input, converts the wargame into a directed graph, processes a multi-commodity flow algorithm on …

Indoor Navigation Using Convolutional Neural Networks And Floor Plans, Ricky D. Anderson

Theses and Dissertations

The goal of this thesis is to evaluate a new indoor navigation technique by incorporating floor plans along with monocular camera images into a CNN as a potential means for identifying camera position. Building floor plans are widely available and provide potential information for localizing within the building. This work sets out to determine if a CNN can learn the architectural features of a floor plan and use that information to determine a location. In this work, a simulated indoor data set is created and used to train two CNNs. A classification CNN, which breaks up the floor plan into …

Optical Study Of 2-D Detonation Wave Stability, Eulaine T. Grodner

Theses and Dissertations

Fundamental optical detonation study of detonations constricted to a 2-d plane propagation, and detonations propagating around a curve. All images were processed using modern image processing techniques. The optical techniques used were shadowgraph, Schlieren, and chemiluminescence. In the 2-Dstraight channels, it was determined wave stability was a factor of cell size. It was also determined the detonation wave thickness (area between the combustion and shockwave) was a factor of how much heat available for the detonation. For the detonations propagating around a curve, it was determined the three main classifications of wave stability were stable, unstable, and detonation wave restart. …

Computational Electromagnetic Modeling Of Metasurface Optical Devices With Defect Study, Carlos D. Diaz

Theses and Dissertations

One of the first fabricated metasurface optical devices, the in-plane V-antenna lenses, were plagued by a fundamental transmission limit (<25 >). Two distinct sets of Out-of-Plane phase elements were designed with improved transmission (~60 ). These were fabricated as beamsteerers and characterized in terms of their Bidirectional Transmittance Distribution Function measured as a function of scatter angle. Experimental data from the beamsteerers was analyzed via simulations using a finite element method (FEM). The measurements showed the designed beamsteering, but also a strong zero-order diffraction not present in the simulations, which motivated this study to understand what was causing these differences. …

Studying The Conditions For Magnetic Reconnection In Solar Flares With And Without Precursor Flares, Seth H. Garland

Theses and Dissertations

Forecasting of solar flares remains a challenge due to the limited understanding of the triggering mechanisms associated with magnetic reconnection, the primary physical phenomenon connected to these events. Consequently, methods continue to rely on the climatology of solar flare events as opposed to the underlying physics principles. Models of magnetic reconnection in the solar atmosphere places the null point of the reconnection within the corona. Though as of now the coronal magnetic field cannot be directly measured, the field is tied to the photospheric magnetic field, which can be. This study utilized data from the Solar Dynamics Observatory Helioseismic and …

Characterization Of Fiber Bragg Grating Based, Geometry-Dependent, Magnetostrictive Composite Sensors, Edward Lynch

Theses and Dissertations

Optical sensors based on geometry dependent magnetostrictive composite, having potential applications in current sensing and magnetic field sensing are modeled and evaluated experimentally with an emphasis on their thermal immunity from thermal disturbances. Two sensor geometries composed of a fiber Bragg grating (FBG) embedded in a shaped Terfenol-D/epoxy composite material, which were previously prototyped and tested for magnetic field response, were investigated. When sensing magnetic fields or currents, the primary function of the magnetostrictive composite geometry is to modulate the magnetic flux such that a magnetostrictive strain gradient is induced on the embedded FBG. Simulations and thermal experiments reveal the …

Deep Learning-Based, Passive Fault Tolerant Control Facilitated By A Taxonomy Of Cyber-Attack Effects, Dean C. Wardell

Theses and Dissertations

In the interest of improving the resilience of cyber-physical control systems to better operate in the presence of various cyber-attacks and/or faults, this dissertation presents a novel controller design based on deep-learning networks. This research lays out a controller design that does not rely on fault or cyber-attack detection. Being passive, the controller’s routine operating process is to take in data from the various components of the physical system, holistically assess the state of the physical system using deep-learning networks and decide the subsequent round of commands from the controller. This use of deep-learning methods in passive fault tolerant control …

Improving Closely Spaced Dim Object Detection Through Improved Multiframe Blind Deconvolution, Ronald M. Aung

Theses and Dissertations

This dissertation focuses on improving the ability to detect dim stellar objects that are in close proximity to a bright one, through statistical image processing using short exposure images. The goal is to improve the space domain awareness capabilities with the existing infrastructure. Two new algorithms are developed. The first one is through the Neighborhood System Blind Deconvolution where the data functions are separated into the bright object, the neighborhood system, and the background functions. The second one is through the Dimension Reduction Blind Deconvolution, where the object function is represented by the product of two matrices. Both are designed …

Detection Of Stealthy False Data Injection Attacks Against State Estimation In Electric Power Grids Using Deep Learning Techniques, Qingyu Ge

Theses and Dissertations

Since communication technologies are being integrated into smart grid, its vulnerability to false data injection is increasing. State estimation is a critical component which is used for monitoring the operation of power grid. However, a tailored attack could circumvent bad data detection of the state estimation, thus disturb the stability of the grid. Such attacks are called stealthy false data injection attacks (FDIAs). This thesis proposed a prediction-based detector using deep learning techniques to detect injected measurements. The proposed detector adopts both Convolutional Neural Networks and Recurrent Neural Networks, making full use of the spatial-temporal correlations in the measurement data. …

Monte Carlo Tree Search Applied To A Modified Pursuit/Evasion Scotland Yard Game With Rendezvous Spaceflight Operation Applications, Joshua A. Daughtery

Theses and Dissertations

This thesis takes the Scotland Yard board game and modifies its rules to mimic important aspects of space in order to facilitate the creation of artificial intelligence for space asset pursuit/evasion scenarios. Space has become a physical warfighting domain. To combat threats, an understanding of the tactics, techniques, and procedures must be captured and studied. Games and simulations are effective tools to capture data lacking historical context. Artificial intelligence and machine learning models can use simulations to develop proper defensive and offensive tactics, techniques, and procedures capable of protecting systems against potential threats. Monte Carlo Tree Search is a bandit-based …

Object Detection With Deep Learning To Accelerate Pose Estimation For Automated Aerial Refueling, Andrew T. Lee

Theses and Dissertations

Remotely piloted aircraft (RPAs) cannot currently refuel during flight because the latency between the pilot and the aircraft is too great to safely perform aerial refueling maneuvers. However, an AAR system removes this limitation by allowing the tanker to directly control the RP A. The tanker quickly finding the relative position and orientation (pose) of the approaching aircraft is the first step to create an AAR system. Previous work at AFIT demonstrates that stereo camera systems provide robust pose estimation capability. This thesis first extends that work by examining the effects of the cameras' resolution on the quality of pose …

One-Dimensional Multi-Frame Blind Deconvolution Using Astronomical Data For Spatially Separable Objects, Marc R. Brown

Theses and Dissertations

Blind deconvolution is used to complete missions to detect adversary assets in space and to defend the nation's assets. A new algorithm was developed to perform blind deconvolution for objects that are spatially separable using multiple frames of data. This new one-dimensional approach uses the expectation-maximization algorithm to blindly deconvolve spatially separable objects. This object separation reduces the size of the object matrix from an NxN matrix to two singular vectors of length N. With limited knowledge of the object and point spread function the one-dimensional algorithm successfully deconvolved the objects in both simulated and laboratory data.

Comparison Of Visual Simultaneous Localization And Mapping Methods For Fixed-Wing Aircraft Using Slambench2, Patrick R. Latcham

Theses and Dissertations

Visual Simultaneous Localization and Mapping (VSLAM) algorithms have evolved rapidly in the last few years, however there has been little research evaluating current algorithm's effectiveness and limitations when applied to tracking the position of a fixed-wing aerial vehicle. This research looks to evaluate current monocular VSLAM algorithms' performance on aerial vehicle datasets using the SLAMBench2 benchmarking suite. The algorithms tested are MonoSLAM, PTAM, OKVIS, LSDSLAM, ORB-SLAM2, and SVO, all of which are built into the SLAMBench2 software. The algorithms' performance is evaluated using simulated datasets generated in the AftrBurner Engine. The datasets were designed to test the quality of each …

Extracting Range Data From Images Using Focus Error, Erik M. Madden

Theses and Dissertations

Air-to-air refueling (AAR) has become a staple when performing long missions with aircraft. With modern technology, however, people have begun to research how to perform this task autonomously. Automated air-to-air refueling (A3R) is this exact concept. Combining many different systems, the idea is to allow computers on the aircraft to link up via the refueling boom, refuel, and detach before resuming pilot control. This document lays out one of the systems that is needed to perform A3R, namely, the system that extracts range data. While stereo cameras perform such tasks, there is interest in finding other ways of accomplishing the …

Near Real-Time Zigbee Device Discrimination Using Cb-Dna Features, Yousuke Z. Matsui

Theses and Dissertations

Currently, Low-Rate Wireless Personal Area Networks (LR-WPAN) based on the Institute of Electrical and Electronics Engineers (IEEE) 802.15.4 standard are at risk due to open-source tools which allow bad actors to exploit unauthorized network access through various cyberattacks by falsifying bit-level credentials. This research investigates implementing a Radio Frequency (RF) air monitor to perform Near RealTime (NRT) discrimination of Zigbee devices using the IEEE 802.15.4 standard. The air monitor employed a Multiple Discriminant Analysis/Euclidean Distance classifier to discriminate Zigbee devices based upon Constellation-Based Distinct Native Attribute (CB-DNA) fingerprints. Through the use of CB-DNA fingerprints, Physical Layer (PHY) characteristics unique to …

Maximizing Accuracy Through Stereo Vision Camera Positioning For Automated Aerial Refueling, Kirill A. Sarantsev

Theses and Dissertations

Aerial refueling is a key component of the U.S. Air Force strategic arsenal. When two aircraft interact in an aerial refueling operation, the accuracy of relative navigation estimates are critical for the safety, accuracy and success of the mission. Automated Aerial Refueling (AAR) looks to improve the refueling process by creating a more effective system and allowing for Unmanned Aerial Vehicle(s) (UAV) support. This paper considers a cooperative aerial refueling scenario where stereo cameras are used on the tanker to direct a \boom" (a large, long structure through which the fuel will ow) into a port on the receiver aircraft. …

Simulation Of Sporadic-E Parameters Using Phase Screen Method, Daniel W. Stambovsky

Theses and Dissertations

A phase screen simulation experiment is designed and implemented to model radio occultation through sporadic-E ionospheric disturbances between a GPS transmitter operating at the L1 frequency and a second receiving satellite in low earth orbit (LEO). Simulations were made to test the linear relationship between plasma intensity and scintillation S4 index both posited (Arras and Wickert, 2018) and contended (Gooch et al., 2020) in previous literature. Results brought into question both the linear relationship and the use of S4 as a whole and an alternate metric was sought.

Measurement Of The 160Gd(P,N)160Tb Excitation Function From 4 18 Mev, Using A Stacked Foil Technique, Ryan K. Chapman

Theses and Dissertations

A stack of thin Gd, Ti, and Cu foils were irradiated with an 18 MeV proton beam at Lawrence-Berkeley National Laboratory's 88-Inch Cyclotron to investigate the ¹⁶⁰Gd(p,n)¹⁶⁰Tb nuclear reaction for nuclear forensics applications. This experiment will improve knowledge of ¹⁶⁰Tb production rates, allowing ¹⁶⁰Tb to be efficiently created in a foil stack consisting of other proton induced isotopes for forensics applications. A set of 15 measured cross sections between 4-18 MeV for ¹⁶⁰Gd(p,n)¹⁶⁰Tb were obtained using a stacked foil technique. The foil stack consisted of one stainless steel, one iron, fifteen gadolinium, …

Use Of Lidar In Automated Aerial Refueling To Improve Stereo Vision Systems, Michael R. Crowl

Theses and Dissertations

The United States Air Force (USAF) executes five Core Missions, four of which depend on increased aircraft range. To better achieve global strike and reconnaissance, unmanned aerial vehicles (UAVs) require aerial refueling for extended missions. However, current aerial refueling capabilities are limited to manned aircraft due to technical difficulties to refuel UAVs mid-flight. The latency between a UAV operator and the UAV is too large to adequately respond for such an operation. To overcome this limitation, the USAF wants to create a capability to guide the refueling boom into the refueling receptacle. This research explores the use of light detection …

Detection Of Reconnection Signatures In Solar Flares, Taylor R. Whitney

Theses and Dissertations

Solar flare forecasting is limited by the current understanding of mechanisms that govern magnetic reconnection, the main physical phenomenon associated with these events. As a result, forecasting relies mainly on climatological correlations to historical events rather than the underlying physics principles. Solar physics models place the neutral point of the reconnection event in the solar corona. Correspondingly, studies of photospheric magnetic fields indicate changes during solar flares -- particularly in relation to the field helicity -- on the solar surface as a result of the associated magnetic reconnection. This study utilizes data from the Solar Dynamics Observatory (SDO) Helioseismic and …

Electric Field Control Of Fixed Magnetic Skyrmions For Energy Efficient Nanomagnetic Memory, Dhritiman Bhattacharya

Theses and Dissertations

To meet the ever-growing demand of faster and smaller computers, increasing number of transistors are needed in the same chip area. Unfortunately, Silicon based transistors have almost reached their miniaturization limits mainly due to excessive heat generation. Nanomagnetic devices are one of the most promising alternatives of CMOS. In nanomagnetic devices, electron spin, instead of charge, is the information carrier. Hence, these devices are non-volatile: information can be stored in these devices without needing any external power which could enable computing architectures beyond traditional von-Neumann computing. Additionally, these devices are also expected to be more energy efficient than CMOS devices …

Scatter Reduction By Exploiting Behaviour Of Convolutional Neural Networks In Frequency Domain, Carlos Ivan Jerez Gonzalez

Theses and Dissertations

In X-ray imaging, scattered radiation can produce a number of artifacts that greatly

undermine the image quality. There are hardware solutions, such as anti-scatter grids.

However, they are costly. A software-based solution is a better option because it is

cheaper and can achieve a higher scatter reduction. Most of the current software-based

approaches are model-based. The main issues with them are the lack of flexibility, expressivity, and the requirement of a model. In consideration of this, we decided to apply

Convolutional Neural Networks (CNNs), since they do not have any of the previously

mentioned issues.

In our approach we split …

Digital Holography Efficiency Experiments For Tactical Applications, Douglas E. Thornton

Theses and Dissertations

Digital holography (DH) uses coherent detection and offers direct access to the complex-optical field to sense and correct image aberrations in low signal-to-noise environments, which is critical for tactical applications. The performance of DH is compared to a similar, well studied deep-turbulence wavefront sensor, the self-referencing interferometer (SRI), with known efficiency losses. Wave optics simulations with deep-turbulence conditions and noise were conducted and the results show that DH outperforms the SRI by 10's of dB due to DH's strong reference. Additionally, efficiency experiments were conducted to investigate DH system losses. The experimental results show that the mixing efficiency (37%) is …

Targeted Germanium Ion Irradiation Of Aluminum Gallium Nitride/Gallium Nitride High Electron Mobility Transistors, Melanie E. Mace

Theses and Dissertations

Microscale beams of germanium ions were used to target different locations of aluminum galliumnitride/gallium nitride (AlGaN/GaN) high electron mobility transistors (HEMTs) to determine location dependent radiation effects. 1.7 MeV Ge ions were targeted at the gap between the gate and the drain to observe displacement damage effects while 47 MeV Ge ions were targeted at the gate to observe ionization damage effects. Electrical data was taken pre, during, and post irradiation. To separate transient from permanent degradation, the devices were characterized after a room temperature anneal for at least 30 days. Optical images were also analyzed pre and post irradiation. …

Light Scattering In Diffraction Limit Infrared Imaging, Ghazal Azarfar

Theses and Dissertations

Fourier Transform Infrared (FTIR) microspectroscopy is a noninvasive technique for chemical imaging of micrometer size samples. Employing an infrared microscope, an infrared source and FTIR spectrometer coupled to a microscope with an array of detectors (128 x 128 detectors), enables collecting combined spectral and spatial information simultaneously. Wavelength dependent images are collected, that reveal biochemical signatures of disease pathology and cell cycle. Single cell biochemistry can be evaluated with this technique, since the wavelength of light is comparable to the size of the objects of interest, which leads to additional spectral and spatial effects disturb biological signatures and can confound …

Multi-Tap Extended Kalman Filter For A Periodic Waveform With Uncertain Frequency And Waveform Shape, And Data Dropouts, Justin Saboury

Theses and Dissertations

Gait analysis presents the challenge of detecting a periodic waveform in the presence of time varying frequency, amplitude, DC offset, and waveform shape, with acquisition gaps from partial occlusions. The combination of all of these components presents a formidable challenge. The Extended Kalman Filter for this system model has six states, which makes it weakly identifiable within the standard Extended Kalman Filter network. In this work, a novel robust Extended Kalman Filter-based approach is presented and evaluated for clinical use in gait analysis. The novel aspect of the proposed method is that at each sample, the present and several past …