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Spoken Language Processing And Modeling For Aviation Communications, Aaron Van De Brook
Spoken Language Processing And Modeling For Aviation Communications, Aaron Van De Brook
Doctoral Dissertations and Master's Theses
With recent advances in machine learning and deep learning technologies and the creation of larger aviation-specific corpora, applying natural language processing technologies, especially those based on transformer neural networks, to aviation communications is becoming increasingly feasible. Previous work has focused on machine learning applications to natural language processing, such as N-grams and word lattices. This thesis experiments with a process for pretraining transformer-based language models on aviation English corpora and compare the effectiveness and performance of language models transfer learned from pretrained checkpoints and those trained from their base weight initializations (trained from scratch). The results suggest that transformer language …
Defining Safe Training Datasets For Machine Learning Models Using Ontologies, Lynn C. Vonder Haar
Defining Safe Training Datasets For Machine Learning Models Using Ontologies, Lynn C. Vonder Haar
Doctoral Dissertations and Master's Theses
Machine Learning (ML) models have been gaining popularity in recent years in a wide variety of domains, including safety-critical domains. While ML models have shown high accuracy in their predictions, they are still considered black boxes, meaning that developers and users do not know how the models make their decisions. While this is simply a nuisance in some domains, in safetycritical domains, this makes ML models difficult to trust. To fully utilize ML models in safetycritical domains, there needs to be a method to improve trust in their safety and accuracy without human experts checking each decision. This research proposes …
Machine Learning And Artificial Intelligence Methods For Cybersecurity Data Within The Aviation Ecosystem, Anna Baron Garcia
Machine Learning And Artificial Intelligence Methods For Cybersecurity Data Within The Aviation Ecosystem, Anna Baron Garcia
Doctoral Dissertations and Master's Theses
Aviation cybersecurity research has proven to be a complex topic due to the intricate nature of the aviation ecosystem. Over the last two decades, research has been centered on isolated modules of the entire aviation systems, and it has lacked the state-of-the-art tools (e.g. ML/AI methods) that other cybersecurity disciplines have leveraged in their fields. Security research in aviation in the last two decades has mainly focused on: (i) reverse engineering avionics and software certification; (ii) communications due to the rising new technologies of Software Defined Radios (SDRs); (iii) networking cybersecurity concerns such as the inter and intra connections of …
Trajectory Generation For A Multibody Robotic System: Modern Methods Based On Product Of Exponentials, Aryslan Malik
Trajectory Generation For A Multibody Robotic System: Modern Methods Based On Product Of Exponentials, Aryslan Malik
Doctoral Dissertations and Master's Theses
This work presents several trajectory generation algorithms for multibody robotic systems based on the Product of Exponentials (PoE) formulation, also known as screw theory. A PoE formulation is first developed to model the kinematics and dynamics of a multibody robotic manipulator (Sawyer Robot) with 7 revolute joints and an end-effector.
In the first method, an Inverse Kinematics (IK) algorithm based on the Newton-Raphson iterative method is applied to generate constrained joint-space trajectories corresponding to straight-line and curvilinear motions of the end effector in Cartesian space with finite jerk. The second approach describes Constant Screw Axis (CSA) trajectories which are generated …
Use Of Machine Learning For Automated Convergence Of Numerical Iterative Schemes, Leonardo A. Bueno-Benitez
Use Of Machine Learning For Automated Convergence Of Numerical Iterative Schemes, Leonardo A. Bueno-Benitez
Doctoral Dissertations and Master's Theses
Convergence of a numerical solution scheme occurs when a sequence of increasingly refined iterative solutions approaches a value consistent with the modeled phenomenon. Approximations using iterative schemes need to satisfy convergence criteria, such as reaching a specific error tolerance or number of iterations. The schemes often bypass the criteria or prematurely converge because of oscillations that may be inherent to the solution. Using a Support Vector Machines (SVM) machine learning approach, an algorithm is designed to use the source data to train a model to predict convergence in the solution process and stop unnecessary iterations. The discretization of the Navier …
Real-Time Machine Learning For Quickest Detection, Yongxin Liu
Real-Time Machine Learning For Quickest Detection, Yongxin Liu
Doctoral Dissertations and Master's Theses
Safety-critical Cyber-Physical Systems (CPS) require real-time machine learning for control and decision making. One promising solution is to use deep learning to discover useful patterns for event detection from heterogeneous data. However, deep learning algorithms encounter challenges in CPS with assurability requirements: 1) Decision explainability, 2) Real-time and quickest event detection, and 3) Time-eficient incremental learning.
To address these obstacles, I developed a real-time Machine Learning Framework for Quickest Detection (MLQD). To be specific, I first propose the zero-bias neural network, which removes decision bias and preferabilities from regular neural networks and provides an interpretable decision process. Second, I discover …
Artificial Intelligence Driven Infrastructure Management And Maintenance Plan, Julian Jesso
Artificial Intelligence Driven Infrastructure Management And Maintenance Plan, Julian Jesso
Doctoral Dissertations and Master's Theses
Rapid development in trucking technology and increasing demands in freight transportation has led to longer and heavier vehicles traveling on Florida’s highway system. Vehicles with gross vehicle weight (GVW) over 80,000 pounds, or permit vehicles, have significant effects on infrastructure, thus requiring an approved permit prior to departure. The combination of these increasing loads and harsh environmental conditions that Florida is subject to requires an enhanced infrastructure management program. Additionally, there is a need to eliminate inconsistencies in permit applications and derive a uniform maintenance practice for Florida’s infrastructure. In this research, the focus was to develop an analytical procedure …
Data-Efficient Machine Learning With Focus On Transfer Learning, Shuteng Niu
Data-Efficient Machine Learning With Focus On Transfer Learning, Shuteng Niu
Doctoral Dissertations and Master's Theses
Machine learning (ML) has attracted a significant amount of attention from the artificial intelligence community. ML has shown state-of-art performance in various fields, such as signal processing, healthcare system, and natural language processing (NLP). However, most conventional ML algorithms suffer from three significant difficulties: 1) insufficient high-quality training data, 2) costly training process, and 3) domain discrepancy. Therefore, it is important to develop solutions for these problems, so the future of ML will be more sustainable. Recently, a new concept, data-efficient ma- chine learning (DEML), has been proposed to deal with the current bottlenecks of ML. Moreover, transfer learning (TL) …
Predicting General Aviation Accidents Using Machine Learning Algorithms, Bradley S. Baugh
Predicting General Aviation Accidents Using Machine Learning Algorithms, Bradley S. Baugh
Doctoral Dissertations and Master's Theses
No abstract provided.
Predicting Pilot Misperception Of Runway Excursion Risk Through Machine Learning Algorithms Of Recorded Flight Data, Edwin Vincent Odisho Ii
Predicting Pilot Misperception Of Runway Excursion Risk Through Machine Learning Algorithms Of Recorded Flight Data, Edwin Vincent Odisho Ii
Doctoral Dissertations and Master's Theses
The research used predictive models to determine pilot misperception of runway excursion risk associated with unstable approaches. The Federal Aviation Administration defined runway excursion as a veer-off or overrun of the runway surface. The Federal Aviation Administration also defined a stable approach as an aircraft meeting the following criteria: (a) on target approach airspeed, (b) correct attitude, (c) landing configuration, (d) nominal descent angle/rate, and (e) on a straight flight path to the runway touchdown zone. Continuing an unstable approach to landing was defined as Unstable Approach Risk Misperception in this research. A review of the literature revealed that an …