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An Application Of Molecular Dynamics To Hed Plasma Physics: Point And Group Defect Diffusion In Coulomb Crystals, Levi Webb

Theses and Dissertations

Molecular dynamics (MD) simulations are used to explore the microscopic behaviors of complex systems that cannot be easily studied experimentally. In particular, the microphysics of high energy density (HED) astrophysical plasma environments remain inaccessible by modern experiment---even in laser facilities, these plasmas exist only on short timescales that do not lend easily to investigation. The diffusion of point and group defects through crystallized plasmas in the cores of white dwarfs and neutron star crusts, called Coulomb crystals, has potentially macroscopic implications for the evolution of these bodies. Thus, I employ the widely-used MD code LAMMPS to simulate small Coulomb crystal …

Managing Multi-Drug Resistance: An Evolutionary Game Theory And Optimal Control Approach, Shukhrat Nasrulloev

Theses and Dissertations

Multi-drug resistance is an evolutionary process in which treatment eliminates sensitive cells, allowing resistant clones to dominate. This thesis investigates this process using a framework integrating population dynamics, evolutionary game theory, and optimal control theory. We develop a two-population logistic growth model describing competition between drug-sensitive and drug-resistant cells under treatment, construct dose-dependent payoff matrices and replicator dynamics to characterize evolutionary competition, and derive a critical drug level D_crit = (r_S - rR)/(dS - d_R) at which resistant cells gain a fitness advantage. An optimal control problem is formulated via Pontryagin's Maximum Principle to identify schedules …

Symmetry In Latin Hypercubes, Levi Neiburger

Theses and Dissertations

Let [n] = {1, ..., n}. A hypercube H of order n and dimension d is a d-dimensional array whose nᵈ cells are indexed by [n]ᵈ. A hyperplane in H is obtained by fixing one coordinate, while allowing the remaining d–1 coordinates to vary. We wish to color each cell of H from a palette of n^d-1 colors such that each hyperplane is polychromatic.

Our main result is the following. Let n be sufficiently large. There exists a symmetric coloring of the d-dimensional hypercubes of order n whose all hyperplanes are polychromatic if and only if: …

Type Ii Diabetes Treatment Comparison Via Compartment Modeling, Abigail M. Collins

Theses and Dissertations

Type II diabetes mellitus affects one in ten adults worldwide, yet the effects of treatment type and adherence level on developing complications and quality of life have not been well characterized at the population level, and mathematical modeling offers a structured way to examine these dynamics. This thesis adapts the Boutayeb et al. (2004) model to incorporate dynamic treatment types and levels of adherence, producing nine scenarios in which complication development rate and complication recovery rate differed, to compare peak complications and quality of life across treatment and adherence conditions. Using a system of ordinary differential equations and compartment modeling, …

Data Defines Success: Algorithm For Dataset Quality Assessment In Deep Learning For Malware Detection, Matei Ionescu

Theses and Dissertations

The field of artificial intelligence is based upon the premise of constructing architectures through which to propagate training data. However, the majority of existing research literature is focused on architecture. While necessary, the attention devoted to the architecture should not so precipitously exceed that of the data. It should be noted that this disparity is not without reasonable cause. Data quality is often exceedingly difficult to verify due to particularities of the field or subfield; LLM repositories of text are distinct from image recognition pictures of dog breeds which are distinct from EEG waveforms of human brains which are distinct …

Fostering A Growth Mindset In Mathematics: Faculty And Student Experiences, Yolanda G. Rush

Theses and Dissertations

According to the Center for Community College Student Engagement (2019), many students attending two-year institutions need productive persistence strategies, including the development of a growth mindset. Although some growth mindset interventions have been effective in improving academic achievement among students (Boaler, 2016; Canning et al., 2024) and persistence (Lewis, 2019) among students, especially those with developmental needs (Suh et al., 2019) and those in mathematics, little is known about the experiences of students and teachers (i.e., students’ perceptions of teachers’ intentions and implementation) as teachers work to foster a growth mindset culture (Murphy et al., 2021). In this dissertation, I …

How And Why Preservice Mathematics Teachers’ Respond To Students’ Statistical Thinking, Radhika Pathak Kharel

Theses and Dissertations

Researchers have found that how preservice teachers (PSTs) respond to students' thinking is crucial to their students' learning and to PSTs' own teaching effectiveness. Although there are some research studies on how teachers respond, there is relatively scarce research on why PSTs respond to students’ thinking the way they do. Such understanding is crucial for designing mathematics methods courses and other professional development opportunities that enable PSTs to create more thoughtful and effective teaching plans. I examined how and why PSTs respond in-the-moment to students’ statistical thinking. The study involved 16 PSTs who enrolled in a middle school mathematics methods …

Hybrid Model For Phishing Website Detection Using Transfer Learning, Atul Dubal, Mansi Subhedar, Santosh Dhamala, Manasi Patil

ASEAN Journal on Science and Technology for Development

The rapid digitization of human activities has intensified reliance on internet-based platforms, creating fertile ground for cybercriminal exploits such as phishing. Despite advancements in detection mechanisms, phishing attacks continue to evolve, leveraging sophisticated visual mimicry to deceive users. This paper proposes a robust vision-based phishing detection system using ensemble deep learning to analyse webpage screenshots. The framework integrates transfer learning with pre-trained VGG16 and DenseNet121 models, extracting complementary low-level texture features (edges, gradients) and high-level hierarchical patterns (logos, layouts). These features are fused through a custom classifier with dropout regularization to mitigate overfitting. A balanced dataset of 3,000 webpage screenshots …

Multiclass Skin Lesions Classification And Early Skin Cancer Detection Using An Attention-Enhanced Xception Architecture, Shamira Arshad Shaikh, Yogita Mistry

ASEAN Journal on Science and Technology for Development

Skin disorders are considered one of the major healthcare problems globally and need proper, prompt, effective and early diagnosis to enhance clinical practice. Traditional machine learning and deep learning approaches often exhibit limited generalization capability and reduced effectiveness in extracting discriminative features from complex multiclass dermatological datasets. For this purpose, an interpretable attention-enhanced Xception framework for automatic multiclass skin disease diagnosis based on dermoscopic images has been designed through the use of the International Skin Imaging Collaboration (ISIC) dataset. The dataset includes 2,357 dermoscopic images that belong to nine classes of skin lesions. The proposed framework integrates channel attention and …

Report On A Gpr Survey Of The Copper Harbor Cemetery, Copper Harbor, Michigan, Grace Griffin

Dissertations, Master's Theses and Master's Reports

The Copper Harbor Cemetery in Grant Township, Michigan, is one of the oldest settler cemeteries in the Keweenaw, with the earliest burial dating back to 1853. The cemetery is also still used by the community today. However, consistent burial records have not been maintained throughout the cemetery's entire history, leading to some doubt about which areas of the cemetery can be opened for new burials and where excavation should be avoided. For this reason, Grant Township commissioned a ground penetrating radar (GPR) survey of the cemetery, primarily to locate anomalies indicating possible unmarked graves and possible buried headstones. The survey …

First-Principles And Thermodynamic Modeling Of Hydrogen Storage In Mxenes, Yi Zhi Chu

Dissertations, Master's Theses and Master's Reports

Hydrogen storage is a critical component of the emerging hydrogen economy, playing a central role in enabling the global transition from fossil fuels to a sustainable, green energy system. With advances in materials research, increasing attention has been directed toward the development of promising hydrogen storage materials. Due to their diverse and advantageous physicochemical properties, MXenes have attracted significant interest in this regard. A fundamental understanding of the hydrogen interactions with the MXenes structure is crucial for explaining and predicting their hydrogen storage performance. In this work, first-principles density functional theory (DFT) combined with a revised thermodynamic model is employed …

An Investigation On Downwind Impacts Of The Keweenaw Peninsula On Lake-Effect Snow Events, Thomas M. Pavell

Dissertations, Master's Theses and Master's Reports

Lake-effect snow (LES) produces copious amounts of snow across the Great Lakes region. While mechanisms and impacts are well-understood, they remain difficult to observe and study over Lake Superior and the Upper Peninsula of Michigan due to a large gap in radar coverage and sparse in-situ measurements. The goal of this project aimed to characterize variables present across Lake Superior and counties on and downstream of the Keweenaw Peninsula that contribute to the formation and evolution of lake-effect snowbands. Nine different lake-effect snow events were analyzed in this project, identifying structures and features resulting from upstream passage over the Keweenaw …

The Excess Path Length Distribution: A Stochastic Model For Sample-Based Path Planners, Chaz B. Cornwall

Dissertations, Master's Theses and Master's Reports

Through random sampling, sample-based path planners enable autonomous agents to quickly find paths without human intervention. However, due to the paths' randomness, sample-based path planners currently require additional verification, partially nullifying agents' ability to act autonomously. I set out to characterize this uncertainty so humans know what to expect from these path planners and know how to alter the path planner to desired specifications. To ensure the results are theoretical as well as practical, I first create a stochastic model of path length uncertainty using the trade-off between sampling time and optimality. By leveraging this model, my proposed algorithm reduces …

Computational And Ai Frameworks For Identifying Key Regulatory Genes And Their Target Genes In Plants And Humans, Md Khairul Islam

Dissertations, Master's Theses and Master's Reports

This dissertation presents computational and AI-driven frameworks for identifying key regulatory genes and their downstream targets across plant and human biological systems. Three studies address distinct challenges in genomic regulation using advanced machine learning and bioinformatics approaches.

The first study introduces DyGAF (Dynamic Gene Attention Focus), a dual-attention transformer framework that identifies and ranks disease-relevant biomarker genes by simultaneously modeling independent molecular responses and interdependent regulatory network behavior. Two attention models provide complementary perspectives on gene importance and are fused through a novel combination metric. Applied to COVID-19 nasopharyngeal swab profiles, the attention-weighted representations achieved 94.23% classification accuracy, high sensitivity, …

Novel Chiral Interstellar Molecules: Quantum Anharmonic Ir And Vcd Predictions, Meredith Paik

Dissertations, Master's Theses and Master's Reports

The 2016 discovery of the chiral molecule propylene oxide (C₃H₆O) in the interstellar medium (ISM) has opened new avenues into explaining the origin of biomolecular homochirality on Earth. Thus, studies of chiral molecules in the ISM may be able to reveal more about the mechanism behind homochirality. However, while the search for chiral molecules in space has become an active field of study, astrochemical researchers have yet to detect other chiral molecules in the ISM. For this purpose, numerous characteristics for detectability have been outlined that may facilitate the discovery of other interstellar chiral molecules. With …

First-Principles Investigation Of Quasi-One-Dimensional Van Der Waals Magnets For Advancing Low-Dimensional Spintronics, Alyssa Horne

Dissertations, Master's Theses and Master's Reports

Van der Waals (vdW) magnets have been of great interest for advancing low- dimensional spintronics. A notable example is the quasi-one-dimensional (Q1D) vdW CrSbSe₃, as it is composed of individual one-dimensional units that are held together by the vdW forces. Finding other Q1D vdW magnets that exhibit non-metallic behavior together with long range ferromagnetic ordering is critical in developing next generation spintronics. Here in, using first-principles density functional theory (DFT), we investigate the compositional effects on electronic and magnetic behavior of Cr_1–xMn_xSbSe₃ (x = 0, 0.5, 1). When 50% of Cr is replaced …

Using Automotive Lidar To Reduce The Energy Consumption Of An Ego Autonomous Vehicle, Logan P. Schexnaydre

Dissertations, Master's Theses and Master's Reports

There is significant potential to reduce the energy consumption of the transportation sector through autonomous vehicles. Prior work on autonomous vehicle energy efficiency focuses on the whole system or the control subsystem. Yet, the sensing and processing components, which have direct and indirect effects on net energy use, are less explored. This dissertation fills this gap by modeling and evaluating these effects for lidar sensors, which provide high-resolution spatial data at the cost of high power and processing demands. I apply lidar to the energy-saving tasks of automated vehicle following and road surface profiling. For automated vehicle following, I model …

Evaluation Of Electroencephalography Processing Methods For Estimating Metabolic Energy Expenditure During Walking, Stephanie L. Pinelo

Graduate Studies Theses and Dissertations 2026

In this study, three EEG datasets, created via different levels of pre-processing, were used to train VO2 prediction models whose performance was tested and compared. Understanding the link between EEG and VO2 during walking is important when working in rehabilitation or studying metabolic energy optimization. Common methods of measuring these two bio-signals tend to be bulky, uncomfortable, and inefficient, so finding a way to predict VO2 from EEG via 1D CNN model training is a worthy pursuit.  It was hypothesized that, due to a CNN needing more data to find patterns for prediction, a minimally processed EEG dataset would have …

Weak Enforcement And Low Compliance In Pci Dss: A Comparative Security Study, Soonwon Park, John Hastings

Research & Publications

Although credit and debit card data continue to be a prime target for attackers, organizational adherence to the Payment Card Industry Data Security Standard (PCI DSS) remains surprisingly low. Despite prior work showing that PCI DSS can reduce card fraud, only 32.4% of organizations were fully compliant in 2022, suggesting possible deficiencies in enforcement mechanisms. This study employs a comparative analysis (qualitative and indicator-based) to examine how enforcement mechanisms relate to implementation success in PCI DSS in relation to HIPAA, NIS2, and GDPR. The analysis reveals that PCI DSS significantly lags far behind these security frameworks and that its sanctions …

Polysemicolon; Novice Programmers And Java Keywords, Briana C. Bettin

Michigan Tech Publications

Most industrial programming languages leverage the English language for reserved keywords – words which a program compiler recognizes as specific execution commands. The divide between expert and novice programmers showcases an intriguing middle-ground by which the polysemy of many keywords becomes revealed. This essay explores a sampling of the multitude of keyword interpretations that a novice programmer may derive from the Java language’s syntactic style and keywords specifically, and how the polysemy of both “English” and “code” meanings to these terms affects the novice-expert programmer transition.The transition from novice to expert, and the mapping of the career of metaphor to …

Quantum General Relativity V2, James Glimm, James Glimm

Department of Applied Mathematics & Statistics Faculty Publications

We construct a quantum general relativity theory.. The construction includes specification of a cosmological model. Based on type Ia supernova data, the model has zero dark energy and zero cosmological constant.

The analysis is at the level of theoretical physics, with some mathematical details omitted.

Mathematicly Rigorous Quantum General Relativity, I: Pure, James Glimm

Department of Applied Mathematics & Statistics Faculty Publications

A pure general relativity (quantum or classical) is one lacking in matter. Such a field has a Lorentzian space time geometry. A renormalization perturbative expansion, truncated to all finite orders, establishes both the quantum and the general relativity theory with full mathematical rigor.

Weak Solutions Of The Navier-Stokes Equation And Their Euler Limits, James Glimm

Department of Applied Mathematics & Statistics Faculty Publications

The existence of a weak solution of the incompressible isothermal Navier-Stokes equation with given initial conditions in the Sobolev space $\mathcal{H}_{-2}$ for energy fluctuations and in $\mathcal{H}_{-3}$ for enstrophy fluctuations is assumed. The existence is uniform with respect to the Euler limit of zero viscosity $\nu$. Thus, existence of weak solutions of the Euler equation with given initial conditions is established, and these Euler solutions are the zero viscosity limit of Navier-Stokes solutions, provided the Navier-Stokes solutions exist.

The Pure Yang-Mills Field: I: Fixed Time Existence, James Glimm, James Glimm

Department of Applied Mathematics & Statistics Faculty Publications

The convergence of renormalized perturbation theory to all finite orders is defined and shown to be valid for the fixed time perturbation theory of a pure Yang-Mills field.

Two pure Yang-Mills quantum gauge field theories are constructed, one based on short distance asymptotics and the other based on long distance asymptotics.

The construction depends on an assumed principle of a maximum rate of entropy production.

Mathematicly Rigorous Quantum General Relativity, I: Pure, James Glimm

Department of Applied Mathematics & Statistics Faculty Publications

A pure quantum general relativity field is one lacking in matter. Such a field has a Lorentzian space-time geometry. A renormalized perturbation expansion, truncated to all finite orders, establishes  the existence of pure quantum general relativity with full mathematical rigor

The Pure Yang-Mills Field. I: Eistence, James Glimm

Department of Applied Mathematics & Statistics Faculty Publications

Two pure Yang-Mills quantum gauge field theories are constructed, one based on short distance asymptotics and the other based on long distance asymptotics.

The construction is based on the axial gauge, ghost states, the BRST framework and Gribov extension of the Hamiltonian, with a loop expansion cutoff to all finite orders for the dynamics.

The construction is established by renormalized perturbation theory to all finite orders.

The construction depends on an assumed principle of a maximum rate of entropy production

General Relativity: Existence, James Glimm

Department of Applied Mathematics & Statistics Faculty Publications

A mathematically rigorous renormalized perturbative expansion, truncated to all finite orders, establishes the existence of quantum general relativity theories with Fermion matter fields. The expansion is initialized with the selection of a vacuum state.

Distinct infrared (IR) and ultraviolet (UV) vacuum states are considered. The IR vacuum state defines a cosmology model. The UV vacuum state defines a black hole model.

The vacuum state is initialized with a $\mathfrak{o}^3$ gauge Lie algebra defining a quark-gluon plasma. With this choice, string theory is avoided.

Finite order renormalized perturbation theory, defined using Bosons to avoid Fermion sign cancellation, is convergent to all …

The Pure Yang-Mills Field: Repeated Blowups, James Glimm, James G. Glimm

Department of Applied Mathematics & Statistics Faculty Publications

The temporal scaling of the quantum Yang-Mills solution is characterized by analytic solutions for a limited time interval, each ended by a discontinuity (blowup).

For general initial conditions, there will be a finite series of blowups and a possible resettings of the gauge group.

The principle of a maximum rate of entropy production is assumed. A finite periodic spatial volume is assumed.

The Boson Yang-Mills Field: The Loop Expansion, James Glimm

Department of Applied Mathematics & Statistics Faculty Publications

This paper demonstrates convergence of the loop expansion for Yang-Mills fields.

The loop construction of perturbation theory is based on the axial gauge, ghost states, the BRST framework and the Gribov extension of the Hamiltonian, with the loop expansion perturbatively renormalizable.

The construction is established by renormalized perturbation theory convergent to all finite orders.

Two distinct Yang-Mills theories are constructed, one based on short distance asymptotics and the other based on long distance asymptotics.

The construction depends on an assumed principle of a maximum rate of entropy production.

The paper has sufficient generality to include existence for all cases that …

Applications Of Machine Learning For Evaluating Downward-Coupled Stratosphere-Troposphere Interactions And Subseasonal Forecasts Of Opportunity, Elena M. Fernandez

Electronic Theses & Dissertations (2024 - present)

Wintertime stratospheric dynamics provide key information for understanding atmospheric teleconnections and improving subseasonal-to-seasonal (S2S) predictions on timescales of two weeks to two months. Periods of enhanced predictability, often referred to as forecasts of opportunity, arise from large-scale teleconnected variability, within which the stratosphere serves as an important precursor for tropospheric states, such as near-surface temperatures. While traditional diagnostics of downward coupled stratosphere-troposphere interactions typically rely on zonal-mean representations of wind and geopotential height, this dissertation presents an alternative vortex-centric framework through metrics that capture the daily geometric and dynamical evolution of the stratospheric polar vortex. The proposed stratospheric …