Digital Commons Network^™

Cooperative Navigation Of Autonomous Vehicles In Challenging Environments, Brendon Peter Forsgren

Theses and Dissertations

As the capabilities of autonomous systems have increased so has interest in utilizing teams of autonomous systems to accomplish tasks more efficiently. This dissertation takes steps toward enabling the cooperation of unmanned systems in scenarios that are challenging, such as GPS-denied or perceptually aliased environments. This work begins by developing a cooperative navigation framework that is scalable in the number of agents, robust against communication latency or dropout, and requires little a priori information. Additionally, this framework is designed to be easily adopted by existing single-agent systems with minimal changes to existing software and software architectures. All systems in the …

Design And Development Of Clinical Decision Support System For Breast Cancer Diagnosis Using Artificial Intelligence, Karthiga R

Theses and Dissertations

The prevalence of breast cancer in women worldwide is far higher than that of cancers of the lungs, brain, or liver. Increasing ageing populations and poor lifestyle habits among the general public, primarily in industrialized nations, are significant factors contributing to the rise in cancer-related mortality rates worldwide. Approximately one woman in every three will develop breast cancer. This research proposes several advanced computer methods for analyzing breast cancer images. This work analyses breast cancer in four imaging modalities: mammography, thermography, ultrasonography and histopathology.

Each modality has some limitations in diagnosing tumors in the breast region. Heavy dose in mammogram …

Combining Expert Opinions To Assess Risk Of Change In Earth Systems: Permafrost Collapse, Global Wildfire, And Water Security, Sayedeh Sara Sayedi

Theses and Dissertations

In a world of uncertainty and change, leaders should base their decisions on best available scientific evidence. However, history has shown that science is often inadequately incorporated into the decision-making process. This dissertation investigates three environmental issues to identify the challenges of considering Earth system dynamics in policymaking and management. I also propose solutions for improving the two-way exchange of knowledge and values between researchers and policymakers. In chapter one, I investigate subsea permafrost carbon sensitivity to climate change using an expert assessment. The analysis revealed that subsea permafrost contains significant carbon stocks and is already contributing to climate change …

Who Gets The Whip? How Supplier Diversification Influences Bullwhip Effect In A Supply Chain, Tyler N. Burrows

Theses and Dissertations

Emergent technologies, such as the `blockchain,' are enabling unprecedented coordination across firms in Supply Chains (SC). Firm decision-makers ultimately are going to need to understand how they can control (and optimize) such a network of relationships. However, the study of SC-level behavior leaves many open questions. Current approaches typically assume a focal firm, and the modeling of SC behavior is usually limited to single-product serial networks. In contrast, real-world SCs show that often a firm has many suppliers, even for the same raw material. This paper aims to understand how demand disturbances (e.g. the 'bullwhip effect') propagate and intensify throughout …

Sctiger: A Deep-Learning Method For Inferring Gene Regulatory Networks From Single-Cell Gene Expression Data, Madison Dautle

Theses and Dissertations

Inferring gene regulatory networks (GRNs) from single-cell RNA-sequencing (scRNA-seq) data is an important computational question to reveal fundamental regulatory mechanisms. Although many computational methods have been designed to predict GRNs, none work on condition specific GRNs by directly using paired datasets of case versus control experiments, common in diverse biological research projects. We present a novel deep-learning based method, scTIGER, for GRN detection by using the co-dynamics of gene expression. scTIGER also employs cell type-based pseudotiming, an attention-based convolutional neural network method, and permutation-based significance testing to infer GRNs from gene modules. We first applied scTIGER to scRNA-seq datasets of …

Better Models For High-Stakes Tasks, Jacob Ryan Epifano

Theses and Dissertations

The intersection of machine learning and healthcare has the potential to transform medical diagnosis, treatment, and research. Machine learning models can analyze vast amounts of medical data and identify patterns that may be too complex for human analysis. However, one of the major challenges in this field is building trust between users and the model. Due to things like high false alarm rate and the black box nature of machine learning models, patients and medical professionals need to understand how the model arrives at its recommendations. In this work, we present several methods that aim to improve machine learning models …

Development Of An Antibiotic Resistance Breaker To Combat Staphylococcus Aureus Pathogenesis Skin Infections Ssis A Multidisciplinary, Gopalakrishnan T Mr

Theses and Dissertations

Problem Statement: Staphylococcus aureus is a highly adaptable and tenacious pathogen known to cause a wide range of infections. The survival characteristics of the pathogen in different host niches are due to their ability to produce various pathogenic determinants. Although there lies the first line of treatment regimens with antibiotics, the pathogen defends at various levels to cause the waves of resistance - a silent pandemic “AMR”.

Notable strategies are through the protective layer, biofilm that enables the inter-/intra species communication (Quorum Sensing; QS) and emerges as a battleground to withstand host-immune response and antibiotic pressure. In parallel, several research …

Investigations On Copper Assisted Oxidative Transformations For The Construction Of Diverse C-C/C-N(O) Bonds, Prasanna Kumari S

Theses and Dissertations

Copper catalyzed C-C, C-N/C-O bond formation reactions are a prominent tool to access diverse biologically relevant molecules. Herein, we present the copper- catalyzed diverse C-C/C-N(O) bond forming reactions. In Chapter-I (introduction), we briefly discussed the various copper mediated organic transformations with appropriate examples.

In Chapter II, we report a one-pot methodology for the vicinal aminoalkylation of naphthoquinone through a direct C(sp2)-H functionalization reaction. Through this method, readily available planar naphthoquinone substrates were transformed into three-dimensional molecular scaffolds through the formation of one C(sp2)-C(sp2) and two C(sp2)-N bonds. The indole fused nitrogen heterocyclic products were obtained in good yields. Apart from …

Investigations On Potassium Penta Borate Based Semi-Organic Materials For Nonlinear Optical Applications, Kamatchi K

Theses and Dissertations

Crystal growth has attained the pinnacle of a point in the current research owing to the requirement of the single crystals in the frontier field of nonlinear optics. Organic crystals exhibit high transparency, high laser damage threshold and de-localized π electron cloud. But they possess weak mechanical stability. In contrast, the inorganic crystals exhibit magnanimous mechanical and thermal properties but have modest nonlinear optical property. If we combine these two materials, then we can obtain the semi-organic materials.

Among the organic materials, the amino acids are chosen and they are mixed with inorganic material potassium penta borate octa hydrate. They …

Interrogating And Genetically Improving Drought Tolerance In The Oilseed Winter Cover Crop, Pennycress ( Thlaspi Arvense L. )., Carol S. Kiam Assato

Theses and Dissertations

Drought damage to crops is a significant threat to food security and a growing problem due to climate change. Amongst all abiotic stresses, drought is the most impactful on soil biota and crop productivity. According to the National Integrated Drought Information System (NIDIS), in 2020, 40% of the United States was under drought, and it is predicted that this number will continue to rise in the forthcoming years due to global warming. Pennycress (Thlaspi arvense L.) is a member of the Brassicaceae family related to canola and Arabidopsis that is rapidly being developed as an oilseed-producing winter cash cover crop …

Identity Management Pki System Using Blockchain, Mohamed Abdel Fattah Abdel Baki Awad

Theses and Dissertations

Identity management is one of the most important topics in the security field. Public Key Infrastructure (PKI) is the most commonly used approach in legally identity management systems. PKI systems have many centralized services that might affect the availability and trustworthiness of the system. Issues related to certificate verification methods such as Certificate Revocation List (CRL) and Online Certificate Status Protocol (OCSP) can be avoided if blockchain is used. Blockchain is a decentralized trusted system where data can only be appended to a public ledger. Edits are not allowed in blockchain. Blockchain consists of several nodes all of them have …

Afl Students’ Perception Of Using Mnemonics As A Strategy To Enhance Their Vocabulary Acquisition And Retention, Elsayed Elsisi

Theses and Dissertations

Research in the field of language teaching and learning reveals that mnemonics is one of the most effective language learning strategies for vocabulary. Researchers like Rasiban, et al. (2019); Levin (1993); Zulfa (2019); Kayaaltu (2018) suggest that using mnemonics to learn new vocabulary has a positive effect on vocabulary retention and retrieval. Research also shows however that students’ perceptions may encourage or inhibit the usage of any learning strategy depending on their perceptions of its effectiveness. Hence the importance of detecting learner perception about any learning or teaching device. Despite the above there is limited research about students’ perceptions about …

Ex ( In ) Clusion: An Exploratory Case Study Of Student Participation In Dual Credit Coursework, Rodrigo Lopez

Theses and Dissertations

Dual credit programs rely heavily on state-level legislation and other regulations from educational agencies. As dual credit has evolved from the Project Advance program developed by Syracuse University and its partner school districts, policymakers have used their position to craft policies to direct dual credit practitioners to craft programs that are more accessible and equitable for minoritized students. However, the participation of minoritized students has historically been lagging that of white and more affluent students. Research on how dual credit practitioners’ interpretation influences their recruitment and enrollment decisions is limited. This case study uses data from seven dual credit practitioners, …

South Sudanese And Syrian Refugee Community-Based Organizations In Egypt: Contributions To Resilience And Reduction Of Socioeconomic Vulnerabilities, Alaa Kasmo

Theses and Dissertations

Community-based organizations (CBOs) have emerged as crucial actors in aid delivery of global efforts, including in Egypt, where they have gained recent attention. However, CBOs’ contributions to supporting displaced communities in Egypt must be adequately investigated. This thesis examines aspects of these contributions to resilience and the reduction of socioeconomic vulnerabilities for displaced communities in Egypt. The qualitative research approach presents comprehensive case studies of interviews and focus group discussions with CBO leaders and communities, providing data on four of the Syrian and South Sudanese CBOs and their communities’ experiences and perspectives on these contributions. CBOs enhance resilience and reduce …

Equity Among Equity Workers: Public Service Motivation In An Educational Nonprofit Organization, Russell C. West Jr

Theses and Dissertations

What opportunities and challenges arise when an equity-focused educational organization aims to support employee’s individual equity practices while simultaneously developing the organization’s equity practice? In this study, employees of a non-profit educational organization were asked what rationales and expectations played a role in their decision to volunteer in an equity working group. Their responses were used to understand whether Perry’s (2000) process theory of Public Service Motivation helped describe their decision. In a second round of interviews, employees were asked what outcomes they perceived came from their participation. These responses were used to understand whether the outcomes aligned with those …

Improving And Evaluating Performance Of The Proton Prediction System Through An Expanded Solar Proton Event Catalog, Samantha R. Howard

Theses and Dissertations

Solar energetic particles (SEPs) are especially high energy protons (≥ 5 or 10MeV kinetic energies) originating from the Sun that are known to have significant effects on space-based military operations. The Air Force’s current forecast model, the Proton Prediction System (PPS), forecasts less than half of SEP events that are observed, motivating the need for an update to the operational model. To develop the updated PPS model, PPS2.0, an expanded SEP catalog was produced, which includes 103 previously unidentified events and specification of the proton flux response above background levels or prior events. Event detection and source association were initially …

Leveraging Galois Theory And Computational Results In The Search For Legendre Pairs, David M. Arquette

Theses and Dissertations

With applications spanning myriad disciplines, Hadamard matrices have tremendous utility. Infinitely many have been discovered, but there is no general proof of their existence. Proving the Hadamard conjecture would provide a significant technological edge. Hadamard matrices are difficult to construct in general; however, they can be created directly from Legendre pairs (LPs). While LPs are not trivial to find, a breakthrough in this area would be pivotal in the quest to prove the Hadamard conjecture. Most recent efforts rely upon refined search algorithms, and we seek to either develop a better such algorithm or discover an altogether new theoretical construction. …

Pattern-Of-Life Modeling With Automatic Dependent Surveillance-Broadcast (Ads-B), Sarah J. Bolton

Theses and Dissertations

This dissertation and research were sponsored by the Air Force Research Laboratory Layered Sensing Exploitation Branch (AFRL/RYA) to investigate the utility of using the data found within aircraft secondary radar to make predictions about aircraft characteristics and intent. The research focuses on making predictions on aircraft characteristics using only the kinetic data within one type of secondary radar, Automatic Dependent Surveillance-Broadcast (ADS-B), as a surrogate for primary radar. The results from this research provide a means to reduce the reliance on a type of aircraft tracking that is vulnerable to cyber attack and other integrity concerns.

Steady State Thermal Blooming With Convection: Modeling, Simulation And Analysis, Jeremiah S. Lane

Theses and Dissertations

The modeling, simulation, and analysis of high energy laser propagation is a research topic of significant interest to the defense community. A detailed understanding of the phenomenon of thermal blooming is crucial as it is detrimental to the propagation of lasers over long distances and in the presence of aerosols. The simulation of thermal blooming has historically relied on wave optics models and scaling laws for the fluid response to the laser. Since thermal blooming occurs in the presence of natural convection, however, there is a need for simulating this coupled fluid-beam effect using a first principles approach. In this …

Numerical Simulation Of Nonlinear Wave Equations With Machine Learning, Kristina O. F. Williams

Theses and Dissertations

A machine learning procedure is proposed to create numerical schemes for solutions of certain types of nonlinear wave equations on coarse grids. This method trains stencil weights of a discretization of the equation, with the truncation error of the scheme as the objective function for training. A neural network is used as a model for the stencil weights. The method uses centered finite differences to initialize the optimization routine and a second-order implicit-explicit time solver as a framework. Symmetry conditions are enforced on the learned operator to ensure a stable method. The procedure is applied to the Korteweg - de …

Methods Of Evaluating Quantum Phase Estimation Circuit Output, Charles A. Woodrum

Theses and Dissertations

The quantum phase estimation (QPE) algorithm is one of the most important quantum computing algorithms that has been developed. The QPE algorithm estimates the phase or phases of the eigenvalue or eigenvalues of a unitary operator. It is a critical step for applications like Shor’s algorithm for factoring and the HHL algorithm for solving linear systems of equations, but it remains difficult to implement on current quantum computers due to small numbers of logical qubits and high error rates. This investigation derives a more accurate estimation of the phase of a unitary operator than would otherwise be attained with the …

Advanced Statistical Methodology For The Modern Probability Of Detection, Christine E. Knott

Theses and Dissertations

Probability of detection (POD) is an invaluable part of the calculations used by the USAF to validate the capabilities of nondestructive inspection systems for detecting defects in critical structural components on aircraft. A POD study consists of a designed experiment, linear modeling, and a probability of detection verses defect size curve. This curve is useful for determining how often an aircraft should be re-inspected. Some POD studies are unsuccessful in creating realistic POD curves because the statistical modeling used has two common limitations: (1) a lack of convergence leading to no solution and, (2) violated assumptions leading to incorrect solutions. …

Analysis Of Multi-Agent Routing Solution Methodologies Exploring A Mosaic Warfare Strategy, Stephen D. Donnel

Theses and Dissertations

Recognizing that communication between assets may be possible locally but not globally (e.g., due to disruptions to a communication network), Mosaic Warfare requires the movement and operation of multiple, dispersed assets in smaller groups (i.e., tiles), within which exist hierarchical, functional relationships between assets. This research first evaluates a heuristic for an enterprise of aerial assets comprised of airborne sensors, command and control, and strike aircraft seeking to move towards and destroy stationary targets. Next, we examine routing multiple assets of different types over a network to service demands in a collaborative manner, in that, when servicing a demand, …

Evaluating The Chief Of Staff Of The Air Force 2016 Initiative To Revitalize The Squadron: A Thematic Content Analysis Of Appreciative Inquiry Mechanisms, John M. Huntz

Theses and Dissertations

A thorough thematic analysis and literature review were undertaken to understand better the integration of AI mechanisms within the Revitalize the Squadron initiative. To facilitate the initiative's implementation, the aim is to provide commanders with practical instances, dimensions, findings, and results. Throughout the coding process, instances of AI’s mechanisms were discovered in the literature. The link between PE and HQR boosted the overall vitality within the squadron, where vitality was determined to be the goal. AI, as a whole, was not found in the literature, but the analysis determined that the Revitalize the Squadron initiative was “Appreciative” in nature.

Advances In Quaternion-Valued Neural Networks, Jeremiah P. Bill

Theses and Dissertations

This dissertation investigates the construction, optimization, and application of quaternion neural networks (QNNs) to Department of Defense (DoD) related problem sets. QNNs are a type of neural network wherein the weights, biases, and input values are all represented as quaternion numbers. This work provides a critical evaluation of the myriad different quaternion backpropagation derivations that exist in the literature, testing the performance of each on a range of regression problem sets. The optimization dynamics of QNNs are explored, presenting visualizations of QNN loss surfaces and a novel method for assessing the “smoothness” of these loss surfaces. Finally, this dissertation presents …

Refining Contract Management: Essays On Relational Contracting, Transaction Costs, And Text Analysis, Timothy E. Landucci

Theses and Dissertations

This dissertation refines defense contracting by addressing aspects of managing contractual relationships. While the setting and data relate to defense contracts, the lessons can be expanded to nonprofit contracting beyond defense and even to contract management in general. First it presents a game theoretic model of a relational contract between a for-profit supplier and a non-profit buyer and explores how the model could be used to promote stability, manage costs, enhance cooperation, and encourage long-term capacity. The dissertation then explores governance alignment using transaction cost economics (TCE) and Department of the Air Force contracting data. One analysis uses data from …

Network Vulnerability Identification For The Material Routing Problem, Carson G. Long

Theses and Dissertations

This dissertation considers the importance of identifying spatiotemporal vulnerabilities in ground distribution networks and uses operations research methods to formulate models that allow military logistic planners to implement prevention and mitigation measures regarding the routing of personnel, equipment, and supplies in contested Areas of Responsibility (AOR). For optimization models relating to identifying spatiotemporal network vulnerabilities in distribution networks, this work leverages game theory, mixed-integer programming, multi-objective optimization, and metaheuristics to inform mitigation measures for shipment routing. This research has three related components: the first component develops a multi-objective mathematical program to identify spatiotemporal vulnerabilities via myopic heuristic identification, in combination …

Improving Deep Reinforcement Learning Methodology For Autonomous Defense And Escort Of Military High-Value Assets, Joseph Liles Iv

Theses and Dissertations

This dissertation explores the application of machine learning to the control of autonomous unmanned combat aerial vehicles (AUCAVs). In particular, this research applies deep reinforcement learning methodologies to a defensive air combat scenario wherein a fleet of AUCAVs protects a military high-value asset (HVA). A collection of air battle management scenarios along with an original simulation environment and a set of designed computational experiments support the approximation of high-quality decision policies by employing Markov decision processes, approximate dynamic programming algorithms, and deep neural networks for value function approximation.

Test Problem Generation And Metaheuristic Selection For The Multidemand Multidimensional Knapsack Problem, Matthew E. Scherer

Theses and Dissertations

This work focuses on instance generation methods for the multi-demand multidimensional knapsack problem (MDMKP). Specifically, instance space analysis (ISA) is used to characterize the landscape of existing instances and validate the novelty of new instances generated with a novel problem generation method, the primal problem instance generator (PPIG). The instance generator is capable of producing feasible, diverse, and challenging instances by directly controlling the problem features. PPIG contributes to the previous collections of instances and is validated through instance space analysis. The research presents an in-depth empirical evaluation of existing solution procedures for the MDMKP. The portfolio of metaheuristics examined …

Atmospheric Propagation Of Qubits: Laboratory Experiments To Field Demonstrations, Keith A. Wyman

Theses and Dissertations

Free-space quantum networks can enable global-scale quantum communication via satellite-based nodes and quantum ground transceivers. To enable building of robust global quantum networks, it is critical to learn how the state of the qubit is transformed while propagating through the atmosphere. With such an overarching goal, we built a laboratory based atmospheric turbulence simulator (ATS) to characterize the effects of atmospheric turbulence on an entangled pair of photons as a function of statistical quantities such as the Fried parameter or scintillation index for long-distance communication. Specifically, the changes in the statistical properties associated with a quantum source was investigated using …