Physical Sciences and Mathematics Commons^™

Sea Level Rise Driven Groundwater Inundation: Effects Of Island Hydrogeology On Freshwater Lens Dynamics, Lauren K. Mancewicz

Dissertations, Master's Theses and Master's Reports

Groundwater inundation due to sea level rise poses a threat to fresh groundwater availability in coastal areas, and small islands are particularly vulnerable. On an island, when sea level rises, the freshwater lens also rises due to the difference in density between the salt and fresh groundwater. As the water table rises above the land surface it forms a lake and the water is exposed to additional evaporative losses, reducing the amount of fresh water available. This work aims to improve our understanding of groundwater inundation due to sea level rise and the impact of different hydrogeologic settings and phenomena …

Applications Of Independent And Identically Distributed (Iid) Random Processes In Polarimetry And Climatology, Dan Kestner

Dissertations, Master's Theses and Master's Reports

The unifying theme of this thesis is the characterization of “perfect randomness,” i.e., independent and identically distributed (IID) stochastic processes as these are applied in physical science. Two specific and mathematically distinct applications are chosen: (i) Radar and optical polarimetry; (ii) Analysis of time series in meteorology. In (i), IID process of a special kind, namely, with a distribution defined by symmetry, is used to link its multivariate Gaussian density to uniformity on the Poincaré sphere. This “statistical ellipsometry” approach is then used to relate polarimetric mismatches or imbalances to ellipsometric variables and suitably chosen cross-correlation measures. In (ii), recently …

Data Driven And Machine Learning Based Modeling And Predictive Control Of Combustion At Reactivity Controlled Compression Ignition Engines, Behrouz Khoshbakht Irdmousa

Dissertations, Master's Theses and Master's Reports

Reactivity Controlled Compression Ignition (RCCI) engines operates has capacity to provide higher thermal efficiency, lower particular matter (PM), and lower oxides of nitrogen (NOx) emissions compared to conventional diesel combustion (CDC) operation. Achieving these benefits is difficult since real-time optimal control of RCCI engines is challenging during transient operation. To overcome these challenges, data-driven machine learning based control-oriented models are developed in this study. These models are developed based on Linear Parameter-Varying (LPV) modeling approach and input-output based Kernelized Canonical Correlation Analysis (KCCA) approach. The developed dynamic models are used to predict combustion timing (CA50), indicated mean effective pressure (IMEP), …

The Impact Of Pre-Experiment Walking On Distance Perception In Vr, Soheil Sepahyar

Dissertations, Master's Theses and Master's Reports

While individuals can accurately estimate distances in the real world, this ability is often diminished in virtual reality (VR) simulations, hampering performance across training, entertainment, prototyping, and education domains. To assess distance judgments, the direct blind walking method—having participants walk blindfolded to targets—is frequently used. Typically, direct blind walking measurements are performed after an initial practice phase, where people become comfortable with walking while blindfolded. Surprisingly, little research has explored how such pre-experiment walking impacts subsequent VR distance judgments. Our initial investigation revealed increased pre-experiment blind walking reduced distance underestimations, underscoring the importance of detailing these preparatory procedures in research—details …

An Ambiguous Technique For Nonvisual Text Entry, Dylan C. Gaines

Dissertations, Master's Theses and Master's Reports

Text entry is a common daily task for many people, but it can be a challenge for people with visual impairments when using virtual touchscreen keyboards that lack physical key boundaries. In this thesis, we investigate using a small number of gestures to select from groups of characters to remove most or all dependence on touch locations. We leverage a predictive language model to select the most likely characters from the selected groups once a user completes each word.

Using a preliminary interface with six groups of characters based on a Qwerty keyboard, we find that users are able to …

Invasive Buckthorn Mapping: A Uav-Based Approach Utilizing Machine Learning, Gis, And Remote Sensing Techniques In The Upper Peninsula Of Michigan, Vikranth Madeppa

Dissertations, Master's Theses and Master's Reports

An Invasive species is a species that is alien or non-native to the ecosystem which causes harm to economic, environmental, or human health (E.O. 13112 of Feb 3, 1999). Invasive species have posed a serious threat to ecosystems across the globe. These invasive species have impacts on the biodiversity and productivity of invaded forests. Remotely sensed data is a valuable resource for understanding and addressing issues related to invasive species. This study presents a novel approach for mapping the distribution of two invasive plant species, Common and Glossy Buckthorn, using unmanned aerial vehicles (UAVs), machine learning algorithms, geographic information systems …

Statistical Methods For Gene Selection And Genetic Association Studies, Xuewei Cao

Dissertations, Master's Theses and Master's Reports

This dissertation includes five Chapters. A brief description of each chapter is organized as follows.

In Chapter One, we propose a signed bipartite genotype and phenotype network (GPN) by linking phenotypes and genotypes based on the statistical associations. It provides a new insight to investigate the genetic architecture among multiple correlated phenotypes and explore where phenotypes might be related at a higher level of cellular and organismal organization. We show that multiple phenotypes association studies by considering the proposed network are improved by incorporating the genetic information into the phenotype clustering.

In Chapter Two, we first illustrate the proposed GPN …

Study Of Electronic And Magnetic Properties Of Bilayer Graphene Nanoflakes And Bimetallic Chalcogenides Using First-Principles Density Functional Theory And Machine Learning, Dharmendra Pant

Dissertations, Master's Theses and Master's Reports

Graphene, a one-atom-thick material, has been a wonder material since its discovery because of its superlative electronic, mechanical, and optical properties. When a layer of graphene is rotated over another layer, it exhibits many intriguing behaviors, ranging from superconductivity to the anomalous Hall effect to ferromagnetism at a magic angle of 1°, and hence the twisted bilayer graphene has been the subject of intense research in recent years. The surge in interest in this moiré structure can be attributed to the emergence of electronic flat minibands near the magic angle. Here, we studied the electronic and magnetic properties of twisted …

Tracing The Most Powerful Galactic Cosmic-Ray Accelerators With The Hawc Observatory, Dezhi Huang

Dissertations, Master's Theses and Master's Reports

Since Victor Hess's groundbreaking detection of cosmic rays in the Earth's atmosphere in 1912, the origins of these charged particles have remained an enduring mystery. Recent studies suggest that these cosmic rays are accelerated beyond Peta electronvolts by powerful astrophysical sources within our own galaxy. While the cosmic rays themselves are being deflected in all directions by magnetic fields, the gamma rays produced by them, being electrically neutral, travel to the observer in a straight line. They carry crucial information, allowing us to trace cosmic-ray accelerators within our galaxy. The High Altitude Water Chrenkov (HAWC) Observatory, located on the slopes …

Comprehensive Analysis Of Seismic Signals From Pacaya Volcano Using Deep Learning Event Detection, Jessica L. Devlieg

Dissertations, Master's Theses and Master's Reports

Pacaya volcano located 30 km SW of Guatemala City, Guatemala, has been erupting intermittently since 1961. Monitoring of seismicity is crucial to understanding current activity levels within Pacaya. Traditional methods of picking these small earthquakes in this noisy environment are imprecise. Pacaya produces many small events that can easily blend in with the background noise. A possible solution for this problem is a machine learning program to pick first arrivals for these earthquakes. We tested a deep learning algorithm (Mousavi et al., 2020) for fast and reliable seismic signal detection within a volcanic system. Data from multiple deployments were used, …

Molecular Dynamics Modeling Of Polymers For Aerospace Composites, Swapnil Sambhaji Bamane

Dissertations, Master's Theses and Master's Reports

Polymer matrix composite materials are widely used as structural materials in aerospace and aeronautical vehicles. Resin/reinforcement wetting and the effect of polymerization on the thermo-mechanical properties of the resin are key parameters in the manufacturing of aerospace composite materials. Determining the contact angle between combinations of liquid resin and reinforcement surfaces is a common method for quantifying wettability. It is challenging to determine contact angle values experimentally of high-performance resins on CNT materials such as CNT, graphene, bundles or yarns, and BNNT surfaces. It is also experimentally difficult to determine the effect of polymerization reaction on material properties of a …

Additive P-Value Combination Test, Xing Ling

Dissertations, Master's Theses and Master's Reports

This dissertation includes four Chapters. A brief description of each chapter is organized as follows.

In Chapter 1, some developments on multiple hypotheses tests are introduced. Some preliminaries about the definition and the assumption are included.

In Chapter 2, a Stable Combination Test is proposed to combine $p$-values from multiple hypotheses tests. We show the proposed method controls the family-wise error rate at the target level and maintains asymptotically optimal power even when the elementary p-values from the individual hypotheses are dependent.

In Chapter 3, a deeper dig into the additive p-value combination test is performed. A common idea behind …

Joint Probability Analysis Of Extreme Precipitation And Water Level For Chicago, Illinois, Anna Li Holey

Dissertations, Master's Theses and Master's Reports

A compound flooding event occurs when there is a combination of two or more extreme factors that happen simultaneously or in quick succession and can lead to flooding. In the Great Lakes region, it is common for a compound flooding event to occur with a high lake water level and heavy rainfall. With the potential of increasing water levels and an increase in precipitation under climate change, the Great Lakes coastal regions could be at risk for more frequent and severe flooding. The City of Chicago which is located on Lake Michigan has a high population and dense infrastructure and …

On The Gaussian-Core Vortex Lattice Model For The Analysis Of Wind Farm Flow Dynamics, Apurva Baruah

Dissertations, Master's Theses and Master's Reports

Wind power science has seen tremendous development and growth over the last 40 years. Advancements in design, manufacturing, installation, and operation of wind turbines have enabled the commercial deployment of wind power generation systems. These have been due, in a large part, to the expertise in the simulation and modeling of individual wind turbines. The new generation of wind energy systems calls for a need to accurately predict and model the entire wind farm, and not just individual turbines. The commercial deployment of these wind farms depends on model's ability to accurately capture the different physics involved, each at its …

An Investigation Of Microseismicity During The 2018 Kilauea Caldera Collapse, Isabella S. Metts

Dissertations, Master's Theses and Master's Reports

The 2018 Kīlauea volcano eruption and incremental caldera collapse was accompanied by more than 60,000 seismic events cataloged by the Hawaiian Volcano Observatory as well as 62 caldera collapse events that occurred roughly once per day. The majority of seismicity occurred on the eastern side of the caldera between daily collapses. However, the majority of caldera subsidence occurred to the west. To understand the collapse mechanics behind this variance in subsidence and seismicity across the caldera region, repetitive waveforms and source properties can be studied.

Repeating seismic events suggest a common source that is not moving or destroyed. At Kīlauea, …

Knowledge Discovery On The Integrative Analysis Of Electrical And Mechanical Dyssynchrony To Improve Cardiac Resynchronization Therapy, Zhuo He

Dissertations, Master's Theses and Master's Reports

Cardiac resynchronization therapy (CRT) is a standard method of treating heart failure by coordinating the function of the left and right ventricles. However, up to 40% of CRT recipients do not experience clinical symptoms or cardiac function improvements. The main reasons for CRT non-response include: (1) suboptimal patient selection based on electrical dyssynchrony measured by electrocardiogram (ECG) in current guidelines; (2) mechanical dyssynchrony has been shown to be effective but has not been fully explored; and (3) inappropriate placement of the CRT left ventricular (LV) lead in a significant number of patients.

In terms of mechanical dyssynchrony, we utilize an …

Novel Approaches To Compute Manifold Operators With The Radial Basis Functions Method, Jacob James Blazejewski

Dissertations, Master's Theses and Master's Reports

The bulk of this dissertation is mainly composed of four chapters, which are organized as follows: Chapter 1 provides an introduction to the Radial Basis Functions (RBF) method by briefly outlining its historical developments and reviewing the RBF interpolation and the RBF-Finite Difference (FD) methodologies, and their advantages/disadvantages. Chapter 2 describes the Orthogonal Gradients (OGr) method and the Fast OGr method and how these can be used to compute differential operators restricted to hypersurfaces and space curves ($\Gamma$) embedded in R3. We will highlight a challenge of pairing Fast OGr with RBF-FD on nearly flat local clusters and how to …

Chemical Decomposition Of Flexible Polyurethane Foam To Generate A Media For Microbial Upcycling, Kaushik Baruah

Dissertations, Master's Theses and Master's Reports

Polyurethane waste is becoming a global concern as a large amount is being disposed of in landfills every year, and only a fraction is being recycled. Several polyurethane recycling techniques exist, of which ammonolysis and base-catalyzed hydrolysis is the least explored. Flexible polyurethane foam (FPUF) decomposition can generate amines that can act as a carbon source for the growth of microbial consortia. This study aims to generate a novel media capable of microbial upcycling via ammonolysis and base-catalyzed hydrolysis of flexible polyurethane foams (FPUFs) using ammonium hydroxide and subsequently determine the reaction conditions for maximum solubilization of polyurethane foam in …

Multiscale Molecular Modeling Studies Of The Dynamics And Catalytic Mechanisms Of Iron(Ii)- And Zinc(Ii)-Dependent Metalloenzymes, Sodiq O. Waheed

Dissertations, Master's Theses and Master's Reports

Enzymes are biological systems that aid in specific biochemical reactions. They lower the reaction barrier, thus speeding up the reaction rate. A detailed knowledge of enzymes will not be achievable without computational modeling as it offers insight into atomistic details and catalytic species, which are crucial to designing enzyme-specific inhibitors and impossible to gain experimentally. This dissertation employs advanced multiscale computational approaches to study the dynamics and reaction mechanisms of non-heme Fe(II) and 2-oxoglutarate (2OG) dependent oxygenases, including AlkB, AlkBH2, TET2, and KDM4E, involved in DNA and histone demethylation. It also focuses on Zn(II) dependent matrix metalloproteinase-1 (MMP-1), which helps …

Structural Analysis And Interpretation Of Deformation Along The Keweenaw Fault System From Lake Linden To Mohawk, Michigan, Nolan G. Gamet

Dissertations, Master's Theses and Master's Reports

The Keweenaw fault is likely the most significant and most studied fault associated with the Midcontinent Rift System. The fault roughly bisects the Keweenaw Peninsula and places Portage Lake Volcanics (~1.1 Ga) over much younger Jacobsville Sandstone (~1.0 Ga). Published bedrock geology maps with cross sections from the 1950s show the fault as a single continuous trace that is locally associated with smaller cross faults and splays. The accompanying cross-sections show hanging-wall volcanic strata having a well-defined, listric geometry with dip decreasing away from the fault to the northwest.

This M.S. thesis presents a structural analysis and interpretation of the …

Climate Changes In El Salvador: Impacts Of ‘La Canícula’ (Midsummer Drought) On Agricultural Practices And Decision-Making In Rural Communities, Paola M. Rivera González

Dissertations, Master's Theses and Master's Reports

The Central American Dry Corridor (CADC), a tropical, dry-forest region, is characterized by distinct rainy and dry seasons, which influence the local agricultural calendar and planting decisions in rural communities. La canícula is a period of decreased precipitation during the rainy season, which occurs during the corn-planting season in El Salvador. La canícula is expected to change in intensity and duration in the next decades, which would impact small-scale farmers and their livelihoods. Climate variability and uncertainty has led to crop loss, water scarcity, and food insecurity in rural communities dependent on subsistence farming. Farmers’ experiences with a changing climate …

Structural Analysis And Slip Kinematics Of The Keweenaw Fault System Between Bête Grise Bay And Gratiot Lake, Keweenaw County, Michigan, Daniel J. Lizzadro-Mcpherson

Dissertations, Master's Theses and Master's Reports

The Keweenaw fault is perhaps the most significant geologic structure on the Keweenaw Peninsula, with an estimated 7-11 km of reverse slip juxtaposing volcanic strata of the ~1.1 Ga Portage Lake Volcanics above ~1.0 Ga Jacobsville Sandstone. The fault has been interpreted as a rift-bounding normal fault later inverted by compressional pulses of the Grenville Orogeny or, more recently, as part of a detached thrust fault system unrelated to an earlier normal fault. The fault is shown on published maps as a single continuous fault trace whose sinuosity implies multiple fault segments and complex slip dynamics. Mapping along Bête Grise …

Finer Details Of Language Modeling: Text Segmentation, Working Within Resource Limits, And Watermarking, Evan Gordon Lucas

Dissertations, Master's Theses and Master's Reports

Language modeling is a vast sub-field of natural language processing and this work focuses on solving some specific problems within that field. Technically, the work falls into a number of sub-categories within natural language processing; how to segment texts, improving sparse transformer performance for summarization tasks, character level models for dialect determination, watermarking of large language models, and a general method of incorporating minimal human feedback for continual or online learning. Despite touching on many small areas, they all connect as being related to the very general problem of handling sequential data. Language and text can be thought of as …

Prediction Of Sumoylation Sites In Proteins From Language Model Representations, Evgenii Sidorov

Dissertations, Master's Theses and Master's Reports

Sumoylation is an essential post-translational modification intimately involved in a diverse range of eukaryotic cellular mechanisms and plays a significant role in DNA repair. Some researchers hypothesize that a high level of SUMOylation events in cancer cells improves cells' chances for survival under stress conditions by regulating tumor-related proteins.

This study belongs to a booming field of harnessing computational power to the domain of life. Prediction of protein structure, its molecular function, and the design of new drugs are just a few examples of the applications within this exciting area of research. By leveraging computational power, researchers can analyze vast …

A Search For Compact Object Dark Matter In The Universe Utilizing Gravitational Millilensing Of Gamma-Ray Bursts, Oindabi Mukherjee

Dissertations, Master's Theses and Master's Reports

In this dissertation, I explore the existence of Compact Object (CO) Dark Matter (DM), examining its predicted millilensing impact on the light curves of Gamma-Ray Bursts (GRBs). The hypothesis under investigation is that if CO DM exists, it will act as a gravitational lens, influencing light emanating from GRBs and creating a measurable gravitational echo. The detection of this echo is conditional on several factors, including the spatial alignment of the observer, lens, and source and the mass of the CO DM.

Recent studies have reported the potential detection of millilensing in several GRBs, including GRB 950830, GRB 081122A, GRB …

Investigating Collaborative Explainable Ai (Cxai)/Social Forum As An Explainable Ai (Xai) Method In Autonomous Driving (Ad), Tauseef Ibne Mamun

Dissertations, Master's Theses and Master's Reports

Explainable AI (XAI) systems primarily focus on algorithms, integrating additional information into AI decisions and classifications to enhance user or developer comprehension of the system's behavior. These systems often incorporate untested concepts of explainability, lacking grounding in the cognitive and educational psychology literature (S. T. Mueller et al., 2021). Consequently, their effectiveness may be limited, as they may address problems that real users don't encounter or provide information that users do not seek.

In contrast, an alternative approach called Collaborative XAI (CXAI), as proposed by S. Mueller et al (2021), emphasizes generating explanations without relying solely on algorithms. CXAI centers …

Exploring High Performance And Energy Efficient Graph Processing On Gpu, Robert P. Watling

Dissertations, Master's Theses and Master's Reports

Parallel graph processing is central to analytical computer science applications, and GPUs have proven to be an ideal platform for parallel graph processing. Existing GPU graph processing frameworks present performance improvements but often neglect two issues: the unpredictability of a given input graph and the energy consumption of the graph processing. Our prototype software, EEGraph (Energy Efficiency of Graph processing), is a flexible system consisting of several graph processing algorithms with configurable parameters for vertex update synchronization, vertex activation, and memory management along with a lightweight software-based GPU energy measurement scheme. We observe relationships between different configurations of our software, …

Physical, Optical, And Chemical Properties Of Light Absorbing Aerosols And Their Climatic Impacts, Susan Mathai

Dissertations, Master's Theses and Master's Reports

Aerosols are particles suspended in the atmosphere; they are emitted during natural phenomena such as dust storms, wildfires, and volcanic eruptions, and during anthropogenic activities like household wood burning, vehicles operations, and industrial productions, or they can form in the atmosphere from gas to particle partition. Aerosols impact earth’s weather and climate by absorbing and scattering the incoming solar and the outgoing earth thermal radiation and interacting with clouds. The optical properties of aerosols evolve as the chemical and physical properties vary during their residence in the atmosphere. In addition, the aerosols’ properties strongly depend on the vertical distribution in …

Surface Reconstruction In Iron Garnets, Sushree Dash

Dissertations, Master's Theses and Master's Reports

This dissertation presents the results of a study investigating the physical mechanisms underlying an unexpectedly large increase in magneto-optic efficiency observed in iron garnet. Such materials are technologically important for telecommunications due to their nonreciprocal optical action. In the past, our group had found evidence of an enhanced Faraday rotation in bismuth-substituted iron garnet films less than 50 nm thick. Subsequent investigation revealed that this enhancement could be traced to surface effects. This is significant because understanding these phenomena could be used to formulate engineering solutions for device miniaturization. In this dissertation, we present the result of a research project …

Deep Learning For Medical Image Segmentation Using Prior Knowledge And Topology, Chen Zhao

Dissertations, Master's Theses and Master's Reports

Image segmentation refers to the division of a digital image into distinct segments or groups of pixels/voxels. However, most of the existing deep learning approaches lack the utilization of prior knowledge, such as shape information, which could improve segmentation accuracy. In addition, conventional image segmentation frequently falls short in preserving intricate spatial details, motivating the innovation of strategies for multi-scaled feature integration. Furthermore, traditional image segmentation methods primarily concentrate on pixel-level or region-level analysis. However, given the inherent morphological similarities among various image objects, the significance of topology information surpasses that of pixel-level data in the realm of medical image …