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Articles 241 - 270 of 8799
Full-Text Articles in Physical Sciences and Mathematics
When Scripts Diverge: Strengthening Low-Resource Neural Machine Translation Through Phonetic Cross-Lingual Transfer, Ammon Shurtz
When Scripts Diverge: Strengthening Low-Resource Neural Machine Translation Through Phonetic Cross-Lingual Transfer, Ammon Shurtz
Theses and Dissertations
Multilingual Neural Machine Translation (MNMT) models enhance translation quality for low-resource languages by exploiting cross-lingual similarities during training--a process known as knowledge transfer. This transfer is particularly effective between languages that share lexical or structural features, often enabled by a common orthography. However, languages with strong phonetic and lexical similarities but distinct writing systems experience limited benefits, as the absence of a shared orthography hinders knowledge transfer. To address this limitation, we propose an approach based on phonetic information that enhances token-level alignment across scripts by leveraging transliterations. We systematically evaluate several phonetic transcription techniques and strategies for incorporating phonetic …
Creating An Iot User Centric Security And Privacy Label, Luke Joseph Gleba
Creating An Iot User Centric Security And Privacy Label, Luke Joseph Gleba
Theses and Dissertations
Concerns for cybersecurity awareness and training in the public have been rising at astronomical rates over the past few years. People globally have entered a critical intersection with computers. Computers are being used in everyday life, and users do not have an easy way to understand their own cyber risk. Consumers deserve to know how secure their new Internet of Things (IoT) system is in a quick, efficient way before they purchase the device and while they own it. The following research looks to improve on ideas for the criteria and the development of a security label. Few prototypes currently …
Contextual Bandits For Non-Stationary Multi-Agent Environments Using Assumptions-Alignment Tracking, Ethan Pedersen
Contextual Bandits For Non-Stationary Multi-Agent Environments Using Assumptions-Alignment Tracking, Ethan Pedersen
Theses and Dissertations
A common challenge in AI is that of an agent possessing N distinct behaviors, each of which works effectively in certain tasks and circumstances, to choose from at any particular time. A popular approach to learn optimal selections in such contexts is found in bandit algorithms. However, traditional bandits often (1) assume the environment is stationary, (2) focus on asymptotic performance, and (3) do not incorporate available external information about the environment. While contextual bandits that do consider external information are designed to combat one of these challenges, the others remain problematic in realistic domains. This is especially true of …
Soccer In-Game Event Classification Using Spatio-Temporal Data, Million Haileyesus
Soccer In-Game Event Classification Using Spatio-Temporal Data, Million Haileyesus
Theses and Dissertations
Classifying soccer ball events, such as pass, shot, ball loss, and ball out, are crucial for advancing game analytics and tactical insights. This thesis investigates the application of machine learning to classify these ball events using player and ball spatio-temporal data, as well as additional features. We implement and compare traditional machine learning algorithms (AdaBoost, Logistic Regression, and Random Forest) with several deep learning approaches, including Feed-Forward Neural Network (FFNN), sequence-to-sequence (seq2seq) recurrent models (Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU)), and Transformer. Our experiments, evaluated on a dataset comprising of three professional soccer matches using accuracy, precision, …
An Analysis Of Large Language Model Hallucination And Creativity: Linear Representations And Causal Roles, Mckay Bowcut
An Analysis Of Large Language Model Hallucination And Creativity: Linear Representations And Causal Roles, Mckay Bowcut
Theses and Dissertations
Large language models (LLMs) show remarkable abilities in both factual and creative tasks, yet the problem of hallucination persists despite advances in training and post-training methods. Recent progress in model interpretability suggests that model behavior can be predicted and influenced by analyzing and manipulating internal activations. In this thesis, we address three questions: (1) Can we identify linear representations of hallucination and creativity in the model’s latent space? (2) Do these representations play a causal role in model behavior when manipulated? (3) Are creativity and hallucination causally intertwined? To answer these, we construct a novel dataset of factual, hallucinated, and …
Development Of Natural Product Analogs As Therapeutic Agents, Jacob Mara
Development Of Natural Product Analogs As Therapeutic Agents, Jacob Mara
Theses and Dissertations
Cancer stem cells (CSC) are cancer cells in a tumor mass that may self-renew and develop into various cell types, resulting in a heterogeneous tumor. CSCs have been shown to have a role in many facets of cancer formation, including tumor genesis, proliferation, and metastatic activity. They are also implicated in chemotherapeutic treatment resistance and the recurrence of some malignancies. Based on these capacities, CSCs have been identified as the next target for cancer therapy and control. Salinomycin's potential for therapeutic use based on ongoing research, as well as the synthesis of its derivatives and their biological activity, will also …
Creativity In Large Language Models, Robert Kenneth Morain
Creativity In Large Language Models, Robert Kenneth Morain
Theses and Dissertations
As artificial intelligence systems approach human-level performance across a wide variety of domains, creative domains remain a critical yet underexplored area of research. Unlike traditional AI tasks with well-defined objectives, creative tasks rely on inherently subjective measures, making them particularly challenging for machines that lack human experiential context. This dissertation establishes the fundamental importance of creativity in AI systems and presents methods for improving and evaluating the creative capabilities of LLMs on the pathway toward AGI. This work addresses and examines key limitations in current LLM creativity through model innovations, development frameworks, and comparative studies. The dissertation develops novel architectural …
Gravitational Perturbations And Quantum Field Interactions In Modified Spacetime Backgrounds, Abhishek Rout
Gravitational Perturbations And Quantum Field Interactions In Modified Spacetime Backgrounds, Abhishek Rout
Theses and Dissertations
This dissertation presents a study of gravitational perturbations and quantum field dynamics in modified spacetime backgrounds. The research is motivated by the quest to understand how quantum fields behave in curved spacetimes, particularly when extensions to general relativity, such as Chern--Simons modifications, are introduced.
The first part examines quantum field interactions with oscillating solitonic backgrounds, inspired by breather-type solutions of the sine--Gordon equation. Fermion bound states are shown to undergo destabilization due to the oscillatory background, leading to particle production and flux propagation to infinity. These results highlight the challenges of maintaining localized fermionic states in time-dependent topological backgrounds.
The …
Coefficients Of The Characteristic Polynomial Of A Hypergraph And Their Combinatorial Properties, Utku Okur
Coefficients Of The Characteristic Polynomial Of A Hypergraph And Their Combinatorial Properties, Utku Okur
Theses and Dissertations
We investigate the combinatorial properties of the characteristic polynomial $\phi_\mathcal{H}\ev{t}$ of a hypergraph $\mathcal{H}$, in particular, its coefficients. Due to a classical result of Jacobi, the generating function of closed walks at a vertex $u$ in a graph $G$ is determined by the rational function $\phi_{G-u}(t) / \phi_G(t)$. The connection between closed walks of $G$ and its characteristic polynomial has a known elegant proof via an application of Viennot's Heaps of Pieces framework, where cycles are taken as pieces and the concurrence relation is sharing a vertex. Here, we prove a bijection between heaps with a unique maximal piece containing …
Thesis: Comparing Functional And Effective Brain Connectivity Metrics For Eeg, Diksha Srishyla
Thesis: Comparing Functional And Effective Brain Connectivity Metrics For Eeg, Diksha Srishyla
Theses and Dissertations
Background:Brain connectivity measures have been used to study communication between brain regions using electroencephalography (EEG). Functional and effective connectivity estimate the synchronization and the flow of information between regions, respectively. However, findings from studies using different measures to investigate similar connections do not converge. To guide the selection of functional and effective connectivity measures in future studies, we systematically compared a set of measures in the context of resting state EEG. We examined four functional connectivity metrics (coherence (Coh), the imaginary part of coherence (imCoh), the corrected imaginary part of phase lagged value (ciPLV), the debiased weighted phase-locking index (dwPLI)) …
Improved Extraction And Detection Of Disinfection Byproducts, Impacts Of Wildland-Urban Interface Wildfires On Drinking Water, And Change In Disinfection Byproducts Over Time In Chlorinated Vs. Chloraminated Distribution Systems, Patrick Thomas Justen
Theses and Dissertations
Drinking water disinfection is critical to prevent the occurrence of waterborne pathogens in drinking water. However, disinfection causes the unintended formation of disinfection byproducts (DBPs) through the reaction of disinfectants (e.g., chlorine, chloramine) with natural organic matter (NOM), algal matter, or anthropogenic pollutants present in source waters. Exposure to DBPs is associated with increased bladder cancer, colorectal cancer, miscarriage, and birth defects. The U.S. EPA currently regulates eleven DBPs in drinking water—four trihalomethanes, five haloacetic acids, bromate, and chlorite. However, research shows that DBP related toxicity in drinking water is driven mainly by other, non-regulated DBPs, particularly iodinated DBPs and …
Synthesis And Characterization Of Lanthanide Extended Structures And Their Novel Transuranic Analogues, Hunter Bernard Tisdale
Synthesis And Characterization Of Lanthanide Extended Structures And Their Novel Transuranic Analogues, Hunter Bernard Tisdale
Theses and Dissertations
The United States owns a substantial amount of radioactive waste as a result of decades of research, weapons manufacturing, and nuclear energy production. As nuclear energy and research continue to add to our stockpiles of waste, the issue of remediating this waste becomes more pressing. Many of the radioactive constituents of this waste, such as the transuranic (Z > 92) elements, will give off radioactivity at harmful levels for millennia. Thus, a robust method of storing this waste is paramount to ensuring public safety. Currently, nuclear waste is being processed by vitrifying it in borosilicate glass. However, this method has shortcomings …
Investigating The Influence Of Instructional Strategies On The Development Of Procedural And Conceptual Knowledge In Advanced Algebra Ii Students, Maura Frances Yinger
Investigating The Influence Of Instructional Strategies On The Development Of Procedural And Conceptual Knowledge In Advanced Algebra Ii Students, Maura Frances Yinger
Theses and Dissertations
This mixed-methods action research study investigated the influence of instructional strategies shown to improve students’ procedural and conceptual understanding in a rational expressions and equations unit in Advanced Algebra II. The instructional strategies used in the study include comparing, self-explaining, and exploring before instruction. The students (N=27) completed a pre-test and a post-test, both of which were followed by questions asking students to justify their responses on two questions. All students also responded to six digital self-explanation journal prompts. Randomly selected students were placed into three homogenous groups to participate in performance task observations. Analysis of the data …
Application Of Machine Learning For Vascular System Analysis, Alireza Bagheri Rajeoni
Application Of Machine Learning For Vascular System Analysis, Alireza Bagheri Rajeoni
Theses and Dissertations
The analysis of vascular structures is critical for diagnosing, monitoring, and treating vascular diseases such as aneurysms, stenosis, and vascular calcification. Traditional methods often rely on manual interpretation of imaging data, which is time-consuming, subjective, and not scalable. This work explores the application of advanced machine learning techniques to automate and enhance vascular system analysis. Our contributions include achieving state-of-the-art accuracy in vascular segmentation, developing a machine learning pipeline to automatically quantify vascular calcification in peripheral arterial disease, and designing a multi-stage machine learning system for abdominal aortic aneurysm analysis that identifies aneurysm boundaries and estimates aneurysm volume in a …
New Approaches On Source Coding For Quantum Stochastic Sources And Implementation Of Quantum Fanout Gate, Rabins Wosti
New Approaches On Source Coding For Quantum Stochastic Sources And Implementation Of Quantum Fanout Gate, Rabins Wosti
Theses and Dissertations
The accurate computation of advanced quantum algorithms like Shor’s integer factorization, quantum phase estimation (QPE), and the quantum Fourier transform (QFT) requires quantum circuits of considerable size and depth. It is difficult to achieve reliable computation with deep quantum circuits due to the limited coherence times of the current noisy quantum devices. The quantum fanout gate is known to be a powerful primitive for reducing the depth of many quantum circuits (Høyer and Špalek 2003; Gottesman and Chuang 1999). Shallow or constant-depth quantum circuits are desirable for both near-term and fault-tolerant quantum computations as they reduce noise and allow faster …
Implicit Neural Representation For Image Reconstruction, Canyu Zhang
Implicit Neural Representation For Image Reconstruction, Canyu Zhang
Theses and Dissertations
Image reconstruction seeks to restore corrupted images and recover visual content that has been lost or degraded. Such degradation may result from low resolution, occlusion, masking, or shadow interference. This problem has become an increasingly significant research topic, as visual information plays a central role in almost every aspect of modern life. Neural network based approaches have recently emerged as highly effective solutions for this task. In particular, convolutional neural networks and transformer based architectures have demonstrated remarkable success in producing visually convincing reconstructions. However, these models remain constrained in several important ways, one of the most critical being that …
Computational Analogies In The Era Of Large Language Models, Amarakoon Mudiyanselage Thilini Wijesiriwardene
Computational Analogies In The Era Of Large Language Models, Amarakoon Mudiyanselage Thilini Wijesiriwardene
Theses and Dissertations
Analogical reasoning is an important part of human cognition requiring the integration of abstract reasoning, pattern recognition, and background knowledge. Despite significant advances in language modeling, the capacity of current methods to accurately identify, model, and evaluate analogies remains fundamentally underexplored.
Analogies enable individuals to perceive deep similarities between superficially different situations. Effective analogy-making requires integrating knowledge about the external world with abstract reasoning and pattern recognition capabilities. While current language models (LMs), trained on massive textual corpora using autoregressive or masked objectives, achieve impressive performance across Natural Language Processing (NLP) tasks such as text generation, summarization, and classification, their …
Multi-Perspective Feature Learning For Facial Expression Recognition In The Wild, Xiangyu Hu
Multi-Perspective Feature Learning For Facial Expression Recognition In The Wild, Xiangyu Hu
Theses and Dissertations
With the rapid progress of deep learning, Facial Expression Recognition (FER) has seen substantial improvements in performance, particularly “in the wild” meaning real world conditions. Despite these advances, most existing methods extract features from facial images as the sole emotional cues, which limits the model’s ability to capture the full complexity of human emotional expressions.
In reality, facial expressions are composed of diverse and multi-perspective information, including appearance-based cues and geometric structural deformations due to activations of facial muscles. Depending exclusively on one type of representation may fail to exploit the complementary nature of these cues, an issue that becomes …
Assessing Inclusion Within Naaee Affiliate Ee Associations And Where To Go From Here, Connor Chilton
Assessing Inclusion Within Naaee Affiliate Ee Associations And Where To Go From Here, Connor Chilton
Theses and Dissertations
Environmental Education (EE) has a history that has been typically defined by traditionally dominant identities (White, male, able-bodied, etc.). The North American Association for Environmental Education (NAAEE) offers a unique position as frontrunners for the field of EE and have the duty to provide an inclusive-minded education for and about the environments throughout the world. Through NAAEE’s affiliate network within the United States, this paper details a glimpse into the work towards inclusion by surveying its leadership position holders about the broad subject and several interconnections of inclusion. Upon completion of the survey, participants who opted to participate in a …
Molecular Architecture And Mechanical Response In Polymeric Materials: Thin Films, Linear-Ring Elastomers, And Lignin, Siteng Zhang
Molecular Architecture And Mechanical Response In Polymeric Materials: Thin Films, Linear-Ring Elastomers, And Lignin, Siteng Zhang
Theses and Dissertations
Understanding the mechanical behavior of polymeric materials is critical to advancing modern technologies, from flexible electronics to sustainable adhesives. This dissertation investigates the micromechanics of polymer thin films, dual-network elastomers, and bio-based lignin materials, with an emphasis on deformation mechanisms, network topology, and mechanical properties. The work combines principles of polymer physics with materials science to uncover structure–property relationships that inform polymer design. This dissertation primarily uses coarse-grained and atomistic molecular dynamics simulations to investigate molecular-scale behavior beyond experimental reach. Through these methods, critical insights are gained into how entanglement, topology, and chain architecture govern bulk material performance. The first …
Progress Towards Confinement Of An Ultracold Neutral Plasma With Electric And Magnetic Fields, Ben Farley
Progress Towards Confinement Of An Ultracold Neutral Plasma With Electric And Magnetic Fields, Ben Farley
Theses and Dissertations
Ultracold neutral plasmas represent a regime of plasmas that is not entirely described by theory, but is critical to our understanding of many phenomena. Though their low temperature makes observing them more manageable, even "confined" ultracold plasmas do not remain contained for more than a few hundred microseconds. No steady state or long-term confinement of an ultracold plasma created by pulse ionization has ever been demonstrated. In this thesis, the construction of a Penning trap for calcium ultracold neutral plasma is presented. The trap consists of a uniform magnetic field to trap the electrons radially and a quadrupole electric field …
Electrical Characterization Of Germanium Tin Alloys And Devices For Space Reliability, Kevin K. Choe
Electrical Characterization Of Germanium Tin Alloys And Devices For Space Reliability, Kevin K. Choe
Theses and Dissertations
GeSn (germanium tin) alloys are potentially well suited for near-mid infrared space optoelectronic applications. Alloys of GeSn have similar properties to group III-V and mercury-cadmium-telluride semiconductors and are compatible with cost-effective complementary metal oxide semiconductor (CMOS) manufacturing technology. Recent progress in non-equilibrium remote plasma-enhanced chemical vapor deposition (RPECVD) has enabled the crystalline growth of GeSn with Sn concentrations of up to 10% without Sn surface segregation. Several experimental studies in previous literature report CVD- or molecular beam epitaxy (MBE)-grown GeSn alloys achieving a direct bandgap with 6%-9% Sn content. This novel growth technique opens opportunities for a cost-effective, next-generation optical …
Validation And Proposed Expansion Of The Data-Driven D Region Model, Kevin M. Watson
Validation And Proposed Expansion Of The Data-Driven D Region Model, Kevin M. Watson
Theses and Dissertations
Predicting ionosphere effects on radio wave propagation is critical for communications and over-the-horizon radar systems. The D region is challenging to model for several reasons, one of which is chemical complexity. Ion density changes during sunrise/sunset introduce substantial uncertainty in electron density profiles (EDPs). The Data Driven D Region (D3R) model solves electron densities through an ion chemistry model and assimilates relevant space weather inputs. This study evaluates D3R against the Faraday International Reference Ionosphere (FIRI) and measurements using Very Low Frequency (VLF) propagation paths. Space weather event impacts on D3R EDPs are evaluated during the disturbed period from 8-12 …
Nuclear Structure Of Neutron-Deficient Cesium-126 And Cesium-127, Connor M. Gautam
Nuclear Structure Of Neutron-Deficient Cesium-126 And Cesium-127, Connor M. Gautam
Theses and Dissertations
Lifetimes of seven excited states of 127Cs, including the states populating the isomer, were measured through a combination of spectroscopic methods. The spin and parity of the states leading up to the 171-μs isomeric level of 126Cs were assigned for the first time, new values were measured for the lifetimes of the two isomeric states, and new evidence was presented for the assignment of a detached sequence of gamma rays to the 126Cs nucleus.
Impacts Of Climate Disruption On Mobility Aircraft Performance In The Pacaf Region, Hannah M. Dauterman
Impacts Of Climate Disruption On Mobility Aircraft Performance In The Pacaf Region, Hannah M. Dauterman
Theses and Dissertations
This thesis investigates the projected impacts of climate disruption on the performance and fuel management of the C-17 Globemaster III, a critical mobility aircraft in the Pacific Air Forces (PACAF) region. As rising global temperatures reduce air density, the performance of aircraft is compromised, resulting in increased fuel consumption, as well as the potential for extended runway requirements and diminished cargo capacity. Using climate projection data from Coupled Model Intercomparison Project Phase 6 (CMIP6), this research analyzes future air temperature trends and their implications for C-17 fuel consumption. Results suggest that by 2049, the U.S. Air Force may incur an …
Multi-Fidelity Machine Learning Modeling For Aerodynamic Response Prediction Of Aerospace Vehicles, Ethan S. Jackman
Multi-Fidelity Machine Learning Modeling For Aerodynamic Response Prediction Of Aerospace Vehicles, Ethan S. Jackman
Theses and Dissertations
Hypersonic vehicle design requires understanding complex aerodynamic phenomena across the full flight regime. This study presents a novel MF surrogate modeling methodology that enables the prediction the full field response across a vehicle’s surface. A Space-Filling Curve (SFC) is used to convert unstructured data into 1D vectors. The a Convolutional Autoencoder is used with transfer learning to reduce the dimensionality of the data. An Emulator-Embedded Neural Network (E2NN) combines multi-fidelity data for fast, accurate predictions. A benchmark analytical example and hypersonic application are used to evaluate the methodology. Using various numbers of samples and sampling strategies it is found that …
Spin State Of Positronium In Two Dimensions, Emille Bryant
Spin State Of Positronium In Two Dimensions, Emille Bryant
Theses and Dissertations
We investigate the spin state of the electron-positron system positronium to determine experimental criteria that can identify a positronium anyon. Anyons have been posited to be the basis for a truly fault-tolerant quantum computer, but they have not been indisputably observed in experimental systems. Through the analysis of the fully relativistic symmetry group of fermions and bosons in three dimensions, we investigate the symmetry of its subgroups to determine that positronium in two dimensions behaves as a scalar with respect to rotations. We conclude that positronium in two dimensions has an arbitrary relative spin orientation of annihilation photons and only …
Designing An Experiment To Create And Evaluate Behavioral Changes In Air Force Pilots' Fuel Efficiency, Jackson Macias
Designing An Experiment To Create And Evaluate Behavioral Changes In Air Force Pilots' Fuel Efficiency, Jackson Macias
Theses and Dissertations
Fuel represents over 70% of the logistical resupply demand within the Department of Defense, with the United States Air Force accounting for most of that consumption. While prior fuel efficiency efforts have primarily focused on technical upgrades, this research explores how behavioral interventions can influence pilot decision-making and operational energy outcomes. Using the Theory of Planned Behavior (TPB) as a guiding framework, this study investigates the effects of targeted behavioral strategies on pilots’ attitudes, subjective norms, perceived behavioral control, intentions, and actual fuel-efficient behaviors. A quasi-experimental design was applied through a controlled pilot study using simulator flights. Six participants were …
Designing The Protocol For An Experimental Flight Simulation Study Encouraging Fuel Efficient Behavior, Thomas S. Reardon
Designing The Protocol For An Experimental Flight Simulation Study Encouraging Fuel Efficient Behavior, Thomas S. Reardon
Theses and Dissertations
This study designed and tested an experimental instrument to examine how pilots respond to fuel efficiency feedback in a flight simulator. A standardized flight plan, script, and hardware setup were created using X-Plane 12 software and physical flight simulator hardware. The chosen sortie guided participants from Monterey Regional Airport to Moffett Federal Airfield using instrument flight rules (IFR). The flight script provided step-by-step guidance to ensure consistent behavior across participants. The simulator was mapped to match real cockpit controls and allowed for precise data collection including flight time, altitude, heading, and fuel use. The goal was to support a larger …
Effect Of Workplace Design On Collaboration And Satisfaction In Space System Command, Joshua A. Hagood
Effect Of Workplace Design On Collaboration And Satisfaction In Space System Command, Joshua A. Hagood
Theses and Dissertations
This study addresses a significant knowledge gap regarding the influence of physical workplace design on employee collaboration and satisfaction with the physical environment within U.S. Space Force technical military organizations. While seminal industry research consistently demonstrates that physical design and indoor environmental quality influence employee satisfaction and collaboration (e.g., Candido et al., 2015; Sailer et al., 2021), the understanding of these impacts within military contexts remains limited. Using a quantitative post-occupancy evaluation survey, adapted from the Sustainable Post Occupancy Evaluation Survey (SPOES), multiple regression analyses revealed that physical elements collectively predict both satisfaction and collaboration. The final simplified model showed …