Physical Sciences and Mathematics Commons^™

Advanced Prognostic Modeling For Breast Cancer Patients: Leveraging Data-Driven Approaches For Survival Analysis, Theophilus Gyedu Baidoo

Theses and Dissertations

Breast cancer is the second most prevalent form of cancer in women in the United States. Each year, about 264,000 cases of breast cancer are diagnosed in women and of this number, about 42,000 women lose their lives as reported by the Centers for Disease Control and Prevention. Early detection and effective treatment are crucial for improving survival rates and reducing mortality. This study aimed to explore the influential factors that may risk the survival of women with the disease and compare their predictive abilities using several error and performance metrics. The study uses a dataset from the National Cancer …

Analyzing The On Source Window Of Supernova Sn2019ejj With A Multi Layered Signal Enhancement Algorithm With Coherent Waveburst And A Convolutional Neural Network, Michael Gale Benjamin

Theses and Dissertations

Core collapse supernovae (CCSN) are highly anticipated sources of gravitational waves during the fourth observation run (O4). CCSN signals are weak and unmodeled and the rate of occurrence in our galaxy is very low. Because of this, they provide a greater challenge to detect than previously detected GW sources. CCSN simulations are used to test the detection pipeline in the event a CCSN is detected. CCSN GW signals are often indistinguishable from the noise sources present in GW data. We present a multi layered signal enhancement pipeline which we have applied Machine Learning (ML) techniques. We have used a Convolutional …

Optimizing Convolutional Neural Networks For Transient Detection In Optical Astronomy With Augmented Datasets, Wendy Mendoza

Theses and Dissertations

We present a technique for optical transient detection using artificial neural networks, particularly a Convolutional Neural Network (CNN), a deep learning algorithm. This method analyzes images of the same area of the sky captured by several telescopes, with one image serving as a reference for a probable transient’s epoch and the other as an image from a previous epoch. We train the CNN on simulated sources and test it on actual image data samples using data from the Dr. Cristina V. Torres Memorial Astronomical Observatory and Sloan Digital Sky Survey. This autonomous detection method replaces the standard procedure, which involves …

Study Of Digital Algan Alloy Based Heterostructures Using Aln/Gan Short Period Superlattice, Mohammad Kamal Hussain

Theses and Dissertations

Ultrawide Bandgap (UWBG) and Extreme Bandgap (EBG) AlxGa1-xN (x > 0.40) alloys with EG > 4.2 eV are potential candidates for high temperature and high voltage applications, compared to Wide Bandgap (WBG) GaN-based lateral channel devices. Since critical electric field (Ec) scales as (Eg)^2.5, theoretically AlGaN alloys can sustain large electric field before breaking down. However, achieving linear ohmic contacts to the 2-dimensional electron gas (2DEG) formed at the interface of AlyGa_1-xN/ Al_xGa_1-xN (y – x ≥ 0.20) High Electron Mobility Transistors (HEMTs) is challenging. Direct contact through the AlGaN barrier is difficult due …

Lessening Student Anxiety With Docker, Kourtnee Fernalld

Theses and Dissertations

Remote learning during the COVID-19 pandemic transformed the educational landscape for hands-on Computer Science courses. This paradigm shift accelerated the transition from traditional in-person programming labs to decentralized student-provided resources. Even as students returned to in-person learning, many continued to rely on their personal computers rather than embracing university-provided labs. However, this shift to decentralized, heterogeneous environments introduces various information technology and instructional challenges. The recent emergence of lightweight, container-based virtualization presents a unique opportunity to address these challenges by offering standardized environments on decentralized platforms. To investigate this opportunity, we implemented lightweight virtualization for three undergraduate computer science courses …

Obscuration Analysis Of Camera Imagery For Aviation Applications, Patrick James Roelant

Theses and Dissertations

Image feature detection is a potent tool with many applications, such as fog identification, roadway conditions, etc. As part of the recent surge in machine learning applications, cloud detection has also become an increasingly engaged area of research. Identifying low clouds is especially useful with respect to aviation, particularly in regions of complex topography prone to visibility-related hazards such as haze or fog. To address this issue, a threshold-based semi-automated algorithm was developed and tested to determine whether or not an image is obscured by fog or haze. Images were obtained from a ground-based camera network in Southern California, the …

Security Of Text To Image Conversions, Zobaida Alssadi

Theses and Dissertations

The use of images and icons to represent news or narratives has grown in popularity. Still, one critical problem is that they are not equivalent to language, making them vulnerable to adversary attacks. This study examines the impact of image-poisoning attacks based on polysemantic words and of image attacks based on cultural differences when converting text to images. Such attacks can lead to the loss of important information and create confusion and incorrect interpretations of the intended meaning, misinforming the general public. The study specifically focuses on possible effects in a news and story context. This study highlights the significance …

Forecasting >100 Mev Sep Events And Intensity Based On Cme And Other Solar Activities Using Machine Learning, Daniel Lee Griessler

Theses and Dissertations

There is a severe risk for astronauts and machinery from high intensity Solar Energetic Particle (SEP) events which can be mitigated through accurate forecast of their presence and peak intensity. By using characteristics of CME and other space weather phenomena, machine learning techniques have the potential to classify and predict the peak intensity of SEP events. The extreme scarcity of SEP events in current datasets poses a challenge to traditional machine learning techniques. In this work, we first demonstrate classifier machine learning techniques that can achieve an F1 score of 0.800 in forecasting SEP events. We then propose techniques for …

Using Asos Ceilings And Mesonet Relative Humidity To Improve General Aviation Flight Planning And Decision Making In Complex Terrain, Connor Hayden Welch

Theses and Dissertations

Despite the increasing availability of weather products and access to data, the issue of weather representativeness, especially in relation to terrain, persists in the aviation industry. Data-sparse regions pose a particular challenge, requiring focused research efforts to address this issue and reduce accident and fatality rates within the general aviation (GA) community. This thesis aims to tackle the specific problem of representing visibility conditions, with a focus on obscuration conditions in elevated terrain.

To achieve this goal, data from Automated Surface Observing System (ASOS) ceilometers and nearby mesonet relative humidity (RH) were analyzed to establish a relationship between the lowest …

Predicting Material Structures And Properties Using Deep Learning And Machine Learning Algorithms, Yuqi Song

Theses and Dissertations

Discovering new materials and understanding their crystal structures and chemical properties are critical tasks in the material sciences. Although computational methodologies such as Density Functional Theory (DFT), provide a convenient means for calculating certain properties of materials or predicting crystal structures when combined with search algorithms, DFT is computationally too demanding for structure prediction and property calculation for most material families, especially for those materials with a large number of atoms. This dissertation aims to address this limitation by developing novel deep learning and machine learning algorithms for effective prediction of material crystal structures and properties. Our data-driven machine learning …

Widely Digitally Delicate Brier Primes And Irreducibility Results For Some Classes Of Polynomials, Thomas David Luckner

Theses and Dissertations

This dissertation considers three different sections of results. In the first part of the dissertation, a result on consecutive primes which are widely digitally delicate and Brier numbers is discussed. Making use of covering systems and a theorem of D. Shiu, M. Filaseta and J. Juillerat showed that for every positive integer k, there exist k consecutive widely digitally delicate primes. They also noted that for every positive integer k, there exist k consecutive primes which are Brier numbers. We show that for every positive integer k, there exist k consecutive primes that are both widely digitally …

Study Of Non-Covalent Interactions Using Molecular Rotors And Balances, Daniel Onyekachi Madukwe

Theses and Dissertations

The main focus of this dissertation is on the quantification of non-covalent interactions using molecular rotors and balances. While molecular rotors were used to measure kinetic effects of weak non-covalent interactions, molecular balances were used to measure their thermodynamic effects. Chapters 1 and 2 focus on the use of molecular rotors in measuring and studying the kinetic effects of the hydrogen bonding interaction on the bond rotation transition states. Chapters 3 and 4 focus on the quantification of lone pair – lone pair and sp²-CH/π interactions respectively, using molecular balances. These studies were carried out in the …

Groundwater Flow And Salt Marsh Migration: The Forest/Marsh Boundary, Camille Rossiello

Theses and Dissertations

Salt marshes migrate landward in response to sea level rise, but the rate of this migration is not constant and can be influenced by pulse disturbances. Long term observations at Sapelo Island, Georgia, show that salt marsh migration has occurred during droughts, but the mechanism for this migration is unclear. Drought is thought to influence salt marsh migration by reducing fresh groundwater discharge from the upland. Rising sea level also encroaches on the upland, which could cause movement of the freshwater lens inland. A two-dimensional numerical model was built to simulate groundwater flow and solute transport based on the Marsh …

Expanding On The Solid State Chemistry Of F-Element Chalcogenides, Logan Skyler Breton

Theses and Dissertations

An overarching goal in solid state chemistry is to achieve predictability regarding the synthesis of compounds with desired properties. While this goal is far from being reached, solid state chemists are hard at work synthesizing and characterizing new materials to further our understanding of structure-property relationships, and to expand our fundamental knowledge to rationalize the outcomes of solid-state syntheses. With the advent of new solid state synthetic methods, novel compounds exhibiting exciting properties are still being discovered today. The infancy of these synthetic methods promises a myriad of undiscovered compounds with potentially interesting properties which has resulted in a recent …

A Bayesian Spatial Scan Statistic For Normal Data, Laasya Velamakanni

Theses and Dissertations

Scan statistics are useful methods for detecting spatial clustering. While they were initially developed to detect regions with an excess of binomial or Poisson events, spatial scan statistics have been extended to detect hotspots in other types of data including continuous data. They have many applications in different fields such as epidemiology (e.g. detecting disease outbreaks), sociology (e.g. detecting crime hotspots), and environmental health (e.g. detecting high-pollution areas). Spatial scan statistics identify a ‘most likely cluster’ and then use a likelihood ratio test to determine if this cluster is statistically significant. Spatial scan statistics have been extended to the Bayesian …

Yield Extraction For The Γd → Λ X Reaction, K H P Nishadi Hasarangi Silva

Theses and Dissertations

Improving and adding new experimental measurements of hyperon-nucleon (YN) and hyperon-deuteron (Yd) cross sections is an active area in nuclear physics research. Scientists use such cross-section data to understand the composition of neutron stars and develop a comprehensive picture of the baryon-baryon interaction. Using high luminosity photon beam incident on a long liquid deuterium target and the CEBAF Large Acceptance Spectrometer (CLAS) at the Thomas Jefferson National Accelerator Facility (JLab), a sample of hyperon-deuteron elastic scattering events was previously identified. The E06-103 (g13) experiment was originally designed to address the scarcity of experimental data on hyperon photoproduction off the neutron …

Machine-Learning Classification To Predict The Dimensionality Of Hybrid Organic-Inorganic Halide Perovskites, Yatiwelle Koralalage Samuditha Sandaru Yatiwella

Theses and Dissertations

Low dimensional hybrid perovskites have demonstrated remarkable performance in photovoltaic applications, primarily due to their exceptional optical and electronic properties. As the search for potential candidates for novel materials continues, understanding the structure of these materials is crucial for investigating their stability. In this study, we implement a framework to find novel material based on a machine-learning model. The machine learning model was trained to predict the dimensionality of the polyhedral network based on the connectivity of the polyhedral network in different directions. The polyhedral connectivity of low-dimensional structures can be classified into three dimensions: 0D, 1D, and 2D. This …

The Synthesis Of Novel Rare Earth Thiosilicates Using The Boron Chalcogen Mixture Method For An Interest In Their Magnetic And Optical Properties, Adam Alexander King

Theses and Dissertations

The chalcogens or the group sixteen elements excluding oxygen, are of interest due to their wide variety of structures and compositions, which gives the potential for a plethora of desired physical properties. This is due to their increased ability to catenate, forming stable chalcogen-chalcogen bonds. When the chalcogens combine with certain main group elements and transition metals they form anionic framework building blocks known as chalcometallates. One such chalcometallate of interest is the thiosilicates, compounds containing Si-S bonds as the anionic frameworks. These compounds are of interest due to their potentials in both their optical and magnetic properties. However, traditional …

Approaches To Detecting And Modeling Over-And Underdispersion In Alternative Count Data Distributions And An Application Of Logistic Regression And Random Forest Modeling To Improve Screening Tools For Tic Disorders In Children, Rebecca C. Wardrop

Theses and Dissertations

This dissertation focuses on theory and application of discrete data methods, particularly approaches to over- and underdispersion relative to the Poisson distribution and an application of random forest and logistic regression modeling. The first chapter derives a score test for over- and underdispersion in the heaped generalized Poisson distribution. Equi-, over-, and underdispersed heaped generalized Poisson and heaped negative binomial data are simulated to evaluate the performance of the score test by comparing the power it achieves to that of Wald and likelihood ratio tests. We find that the score test we derive performs comparably to both the Wald and …

Computational Studies Of Bond Dissociation Energies And Organic Reaction Mechanisms, Shehani Thishakkya Wetthasinghe

Theses and Dissertations

This dissertation presents the progress of two independent projects. Chapter 2 and Chapter 3 focus on the first project, which involves material exploration utilizing machine learning techniques. We explore the potential use of cobaltocenium (CoCp⁺₂) derivatives as metal cations in anion exchange membranes (AEMs) for alkaline fuel cells, highlighting their superior thermal and alkaline stability compared to ammonium derivatives. The stability of CoCp⁺₂ can be fine-tuned by varying the substituent groups attached to the cyclopentadienyl ring (Cp) in CoCp⁺₂ .These derivatives encompass a variety of electron-donating and electron-withdrawing groups as substituents on both …

Statistical Methods For Single Cell Sequencing Data Analysis, Fei Qin

Theses and Dissertations

The recent emergence of single cell sequencing (SCS) technology has provided us with single-cell DNA or RNA sequencing (scDNA/RNA-seq) information to investigate cellular evolutionary relationships. Despite many analysis methods have been developed to infer intra-tumor genetic heterogeneity, cluster cellular subclones, detect genetic mutations, and investigate spatially variable (SV) genes, exploring SCS data remains statistically challenging due to its noisy nature.

To identify subclones with scDNA-seq data, many existing studies use an independent statistical model to detect copy number profile in the first step, followed by classical clustering methods for subclone identification in downstream analyses. However, spurious results might be generated …

Hf Radar: Shining A Light On Ocean Currents, Douglas Cahl

Theses and Dissertations

High Frequency (HF) radar systems are commonly used to estimate surface ocean currents over the coastal ocean. Their range depends on their operational frequency and low frequency systems (≤ 10 MHz) can reach distances up to 200 km from the coastline. These systems are used to estimate surface currents by measuring the phase speed of wind-driven waves and comparing the measured speed with that expected theoretically; deviations from the theoretical still-water phase speed are attributed to ocean surface currents. Although HF radar systems are considered a mature technology and the accuracy of the radar-derived surface current estimates is well studied, …

Deep Learning Methods For Some Problems In Scientific Computing, Yuankai Teng

Theses and Dissertations

Deep learning has emerged as a powerful approach for solving complex problems in scientific computing due to the increasing availability of large-scale data and computational resources. This thesis explores the potential of deep learning methods for three specific problems in scientific computing: (i) reducing the dimensions of variables in function approximation, (ii) solving linear reaction-diffusion equations, and (iii) finding the parametric representations of parameters in the numerical schemes for solving time-dependent partial differential equations.

For the first problem, a novel deep learning architecture is developed for reducing the dimensions of variables in function approximation. The proposed method achieves state-of-the-art performance …

Measurement Of The Total Cross-Section Of Muon Neutrino Charged-Current Coherent Pion Production In Nova Near Detector, Kuruppumullage Don Chatura Dilshan Kuruppu

Theses and Dissertations

Charged Current (CC) coherent neutrino-nucleus pion production is characterized by small momentum transferred to the nucleus, which is left in its ground state. Despite the relatively large uncertainties on the production cross-section, coherent production of mesons by neutrinos represents an important process, as it can shed light on the structure of the weak current and can also constitute a potential source of background for modern neutrino oscillation experiments and searches for Beyond Standard Model (BSM) physics. This Ph.D. thesis presents a new measurement of CC coherent pion production in the NOvA near detector at the Fermi National Accelerator Laboratory (Fermilab). …

Identification Of New Disinfection Byproducts In Drinking Water And Impacts Of Algae, Md. Tareq Aziz

Theses and Dissertations

The disinfection of water has been hailed as one of the most important triumphs for public health in the 20th century. Drinking water treatment plants produce safe drinking water by inactivating microorganisms through the use of disinfectants, including chlorine, chloramine, chlorine dioxide, UV irradiation, and ozone. However, these disinfectants also produce toxic disinfection by-products (DBPs), through reactions with natural organic matter and anthropogenic pollutants, as well as bromide and iodide present in source waters. The presence of bromide and iodide results in the formation of bromo- and iodo-DBPs which are much more toxic than DBPs containing chlorine. DBPs are always …

Ally Mediation Of Social Media Use For Adults With Autism, Spring S. Cullen

Theses and Dissertations

Previous research has highlighted the unique challenges young Autistic adults face when using social media. We extend this work by analyzing how guardians and allies, such as service providers, mediate the social media usage of young Autistic adults in order to address and mitigate online risks. Based on analysis of interview transcripts (8 young adults on the Autism spectrum, 4 parents, 10 staff members), we uncover the mediation tactics used, how they differ based on the ally's relationship with the individual, and the tactics' varying degrees of effectiveness. The findings of this research contribute to the literature by informing the …

Ultracold Neutral Plasma Evolution In An External Magnetic Field, Chanhyun Pak

Theses and Dissertations

We study the expansion velocity and ion temperature evolution of ultracold neutral plasmas (UNPs) of calcium atoms under the influence of a uniform magnetic field that ranges up to 200 G. In the experiments, we use a magneto-optical trap (MOT) to capture the neutral atoms and laser-induced fluorescence (LIF) to take images of the plasma. We vary the magnetic field strengths and the initial electron temperatures and observe the plasma evolution in time. We compare the ion temperature evolution to the theory introduced in the paper by Pohl et. al. [Phys. Rev. A 70, 033416 (2004)]. The evolution of the …

Extending Model Checking Using Inductive Proofs In Distributed Digital Currency Protocols, Kyle R. Storey

Theses and Dissertations

Model checking is an effective method to verify both safety and liveness properties in distributed systems. However, the complexity of model checking grows exponentially with the number of entities which makes it suitable only for small systems. Interactive theorem provers allow for machine-checked proofs. These proofs can include inductive reasoning which allows them to reason about an arbitrarily large number of entities. However, proving safety and liveness properties in these proofs can be difficult. This work explores how combining model checking and inductive proofs can be an effective method for formally verifying complex distributed protocols. This is demonstrated on a …

Characterizing Dust From National Wind Erosion Research Network Sites Using Strontium Isotopes, Major And Trace Element Chemistry, And Mineralogy, Abby L. Mangum

Theses and Dissertations

The frequency of dust storms is increasing globally yet it is often difficult to determine dust sources in mixed events. Dust events may negatively impact human health, but the composition of major dust sources is not well characterized in arid regions globally. In the western US, the National Wind Erosion Research Network (NWERN) has various sites evaluating seasonal dust emissions to quantify dust fluxes. We used existing dust samples to characterize the isotopic, chemical, and mineralogical composition of dust over multiple seasons from ten representative NWERN sites and compared with land use, vegetation, and surficial geology. Our results show variability …

Acoustic Directivity: Advances In Acoustic Center Localization, Measurement Optimization, Directional Modeling, And Sound Power Spectral Estimation, Samuel David Bellows

Theses and Dissertations

Sound radiation from an acoustic source typically exhibits directional behavior, as is the case for the human voice, musical instruments, and loudspeakers, to name just a few. The necessity of directional data for many applications, such as sound source modeling, microphone placement, room acoustical design, and auralization, motivates directivity measurements. However, these measurements require careful understanding and implementation to produce the most meaningful results. Accordingly, this dissertation addresses several topics relevant to directivity theory, measurement, processing, and application. It first expands and amends previously published concepts of an acoustic source center and demonstrates the close relationship between the center and …