Physical Sciences and Mathematics Commons^™

Plumbing The Depths Of The Shallow End: Exploring Persistent Homology Using Small Data, R. Anne Flynn

All NMU Master's Theses

Persistent homology is a prominent tool in topological data analysis. This thesis is designed to be an introduction and guide to a beginner in persistent homology. This comprehensive overview discusses the math used behind it, the code needed to apply it, and its current place in the field. We explain and demonstrate the algebraic topology which fuels persistent homology. Homotopies inspire homology groups, which are able to determine how many holes a shape has. By visualizing data as a shape, persistent homology determines what type of holes are present.

We demonstrate this by using the package TDA in the manipulation …

An Analysis Of Lyrical Repetition And Popularity In Popular Music Genres, Josh White

Undergraduate Honors Capstone Projects

This paper examines the correlation between repetitiveness and popularity in the genres of Christian, Country, EDM, Hip-Hop, Latin, Pop, R&B, and Rock. Repetitiveness is defined by the frequency of repeated words in lyrics, and the average number of streams per day defines popularity. This analysis also acknowledges the "popularity" metric provided by Spotify in calculating the correlation. To calculate this correlation, I wrote a program that accesses the Spotify and Genius APIs to gather metadata related to 76,069 songs from 1,246 artists, including data on repetitiveness, tempo, duration, and Spotify's audio metrics of "danceability," "energy," "speechiness," "acousticness," and "instrumentalness." I …

Reducing Carbon Emissions With Returned Concrete, John M. Maxwell Jr.

Construction Management

The concrete industry is one of the most energy-intensive sectors of construction. Specifically, the cement production aspect is the most energy intensive, and produces the most carbon emissions. Concrete, a material ubiquitous with nearly every facet of construction; certain types of structures are composed of nearly all concrete. Production of cement is one of the biggest contributors to emissions within the industry. There have been initiatives to reduce or offset emissions from this process, through things like carbon capture, and the purchase of carbon or emissions credits. The objective of this paper was to investigate a new method of carbon …

Determination Of Common Drugs Of Abuse And Metabolites In Oral Fluid: Comparison Of Different Extraction Procedures, Melissa Koffer

Student Theses

Oral fluid has been gaining importance in forensic and clinical toxicology for many different drug testing scenarios. Oral fluid is composed of saliva, along with gingival fluid, bacteria, and food residues. Drug testing using oral fluid has many advantages over other matrices (blood, urine) such as the non-invasive collection, reduced risk of tampering, and shorter detection windows which show recent drug use. The purpose of this study was to develop an analytical method for the determination of 19 drugs of abuse and metabolites in oral fluid by liquid chromatography tandem mass spectrometry (LC-MS/MS) and compare three different extraction methods: liquid-liquid …

Using The History Of Statistics To Teach Introductory Statistics, Melissa Hansen

All Graduate Reports and Creative Projects, Fall 2023 to Present

While often taught in high school and required as part of a college degree, statistics classes are sometimes viewed by students as an obstacle rather than a support for their overall goals. One way to increase student engagement in a statistics course is to use the history of statistics. Within the literature review, the advantages to using the history of statistics are discussed as well as the more extensive research on using the history of mathematics in mathematics courses. Included are instructional strategies for using the context around the development of mathematical ideas in math classrooms which can be extended …

Modeling Vibration Stiffness: An Analytical Extension Of Hertzian Theory For Angular Contact Bearings With A Thin Viscoelastic Coating, Davis R. Burton

Honors Theses

This thesis considers the novel angular contact rolling-element bearings proposed by NASA’s Glenn Research Center, which are coated with a thin solid lubricant that exhibits viscoelastic behavior. Current analytical models for the dynamic stiffness matrix of angular contact bearings, critical for vibration analysis, lack the ability to model the effects of a solid coating, as well as the time dependencies inherent in viscoelastic theory. The author first presents an overview of the stiffness matrix derivation, followed by a treatment of the underlying Hertzian contact theory. An analytical extension of this theory is proposed which accounts for a thin elastic layer …

Exploring Binding Pockets In The Conformational States Of The Sars-Cov-2 Spike Trimers For The Screening Of Allosteric Inhibitors Using Molecular Simulations And Ensemble-Based Ligand Docking, Grace Gupta, Gennady M. Verkhivker

Mathematics, Physics, and Computer Science Faculty Articles and Research

Understanding mechanisms of allosteric regulation remains elusive for the SARS-CoV-2 spike protein, despite the increasing interest and effort in discovering allosteric inhibitors of the viral activity and interactions with the host receptor ACE2. The challenges of discovering allosteric modulators of the SARS-CoV-2 spike proteins are associated with the diversity of cryptic allosteric sites and complex molecular mechanisms that can be employed by allosteric ligands, including the alteration of the conformational equilibrium of spike protein and preferential stabilization of specific functional states. In the current study, we combine conformational dynamics analysis of distinct forms of the full-length spike protein trimers and …

An Edge Computing System With Amd Xilinx Fpga Ai Customer Platform For Advanced Driver Assistance System, Tsun Kuang Chi, Tsung Yi Chen, Yu Chen Lin, Ting Lan Lin, Jun Ting Zhang, Cheng Lin Lu, Shih Lun Chen, Kuo Chen Li, Patricia Angela R. Abu

Department of Information Systems & Computer Science Faculty Publications

The convergence of edge computing systems with Field-Programmable Gate Array (FPGA) technology has shown considerable promise in enhancing real-time applications across various domains. This paper presents an innovative edge computing system design specifically tailored for pavement defect detection within the Advanced Driver-Assistance Systems (ADASs) domain. The system seamlessly integrates the AMD Xilinx AI platform into a customized circuit configuration, capitalizing on its capabilities. Utilizing cameras as input sensors to capture road scenes, the system employs a Deep Learning Processing Unit (DPU) to execute the YOLOv3 model, enabling the identification of three distinct types of pavement defects with high accuracy and …

Hilbert Reciprocity Over Number Fields, Dillon Snyder

Honors Scholar Theses

A Hilbert symbol has the value 1 or −1 depending on the existence of solutions to a certain quadratic equation in a local field, R, or C. Hilbert reciprocity states that for a number field F and two nonzero a and b in F, the product of Hilbert symbols associated to a and b at all the places of F is 1. That is, these Hilbert symbols are −1 for a finite, even number of places of F . Hilbert reciprocity when F = Q is equivalent to the classical quadratic reciprocity law, so Hilbert reciprocity in number fields can …

A Ui-Enhanced Approach To Generic Web-Based Scheduling, Tyler Hinrichs

Honors Scholar Theses

Administrative scheduling is a key aspect of a wide variety of systems, but despite being a widespread need, it is not a straightforward task. Organizational uniqueness introduces complexity when attempting to use algorithmic methods to automate scheduling, as individual organizations often have their own ways of determining various details and constraints of a schedule. However, in this paper, we assert that there are relevant commonalities that many different schedules fundamentally possess, allowing us to create a generic scheduling application that can be productively used for as many different scenarios as possible. After devising a schema that captures this generic representation, …

Database And Machine Learning Model For Classifying Autism Spectrum Disorder From Smartphone Based Electroretinography, Rory Harris

Honors Scholar Theses

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder that negatively affects a patient’s cognitive and communication aptitude and, therefore, can severely impact that patient’s quality of life. Because of this, early diagnosis is paramount. In recent studies, electroretinography (ERG), which is a measure of the retina’s electrical response to a brief flash of light into the eye, has shown promise in detecting ASD. Access to these scans can provide early diagnosis, improving well-being. Current ERG devices are very expensive due to their on board processing capabilities. This paper aims to create an ERG device using a smartphone as the main …

3d-Printed Microfluidic Devices For Electrochemiluminescence Detection Of Mirna, Oscar Clement

Honors Scholar Theses

This thesis outlines the research conducted over the past two years on the production and application of microfluidic devices (MFDs) in electrochemiluminescent-based bioanalytical assays. The work is categorized into two main projects: designing and manufacturing MFDs and developing electrochemiluminescent (ECL) assays for detecting Alzheimer's disease (AD) associated microRNAs (miRNAs) using CRISPR technology. The process of learning to design MFDs involved acquiring proficiency in computer-aided design (CAD) software, stereolithography (SLA) 3D printing, and iterative design techniques. The development of the ECL-based assay for AD miRNA was a multidisciplinary endeavor, combining elements of inorganic and biological chemistry. Although the research on the …

How Does Hummock Creation In Submerging Salt Marshes Alter Nitrous Oxide Fluxes?, Juliette Doyle

Honors Scholar Theses

Climate change is altering ecosystems and the services they provide. Salt marsh ecosystems typically protect coastal areas and filter nitrogen out of water, but are rapidly submerging due to rising sea levels and human development that prevents landward migration. Recent restoration efforts to preserve salt marshes attempt to build elevation capital and promote vegetation and animal habitat, but it is unclear how such efforts affect salt marsh biogeochemistry and dynamics of nitrous oxide, a potent greenhouse gas. To better understand how adding sediment to submerging salt marshes may alter nitrous oxide fluxes, I leveraged a salt marsh hummock creation experiment …

An Educational Resource For Particle Identification (Pid) In Experimental Particle Physics Data, Richard Dube

Honors Scholar Theses

Although particle physics research is typically reserved for advanced undergraduates, algebra-based physics students can readily develop the foundational skills necessary to conduct particle physics research. Despite this, there is a shortage of educational resources that introduce particle physics to algebra-based physics students. This project, Particle Identification Playground, is a collection of Python-based activities that teach students about several fundamental topics in experimental particle physics research. Through these activities, students will learn about the common detectors used in particle physics, how they work, and how we can use these detectors to identify particles. Students are able to interact with 3D models …

Analyzing Information Diffusion In Social Media Networks, Amin Riazi

Masters Theses and Doctoral Dissertations

Social media is a dynamic platform where a wide range of information is shared, including both true and false content, and it involves interactions between human users and social bots. This study investigates information diffusion patterns on X (formerly Twitter) by analyzing retweet (repost) network topologies. The results reveal distinct behavioral patterns for humans and bots when spreading true and false information, highlighting the need for further examination of their roles in information dissemination. Moreover, this study tackles the challenge of differentiating between broadcast and viral information diffusion on X, acknowledging the possibility of genuine information also being potentially misleading. …

Analysis And Numerical Simulation Of Tumor Growth Models, Daniel Acosta Soba

Masters Theses and Doctoral Dissertations

In this dissertation we focus on the numerical analysis of tumor growth models. Due to the difficulty of developing physically meaningful approximations of such models, we divide the main problem into more simple pieces of work that are addressed in the different chapters. First, in Chapter 2 we present a new upwind discontinuous Galerkin (DG) scheme for the convective Cahn–Hilliard model with degenerate mobility which preserves the pointwise bounds and prevents non-physical spurious oscillations. These ideas are based on a well-suited piecewise constant approximation of convection equations. The proposed numerical scheme is contrasted with other approaches in several numerical experiments. …

Utilizing Electrical Geophysical Methods To Map Mycorrhizal Mycelium Networks Non-Invasively, Donald Pesonen

Graduate Dissertations and Theses

Mycorrhizal mycelium networks are a key component to forest health. These networks act as a transportation system for nutrients, are major players in carbon and nitrogen cycling, and can provide some level of drought resistance to the surrounding flora. Due to the location and size of these network’s filaments, studying mycelium non-invasively has been difficult. The alternative method of laboratory grown samples, lacks the important environmental factors that play into the growth and development of mycelium. Mycelium’s inherent conductivity and moisture retention allows for these networks to be a viable target for electrical geophysical equipment. CMD-Tiny, a small shallow depth …

Predicting 30-Day Unplanned Icu Readmissions Using Deep Learning And Natural Language Processing Techniques: A Mimic Iv Data Analysis, David Licerio

Computational and Data Sciences (MS) Theses

We design and implement a multi-stage modeling approach focused on predicting unplanned 30-day all- cause intensive care unit (ICU) hospital readmissions using the Medical Information Mart for Intensive Care (MIMIC IV) dataset. Structured data consisting of demographic information, comorbidities, lab results, and vital signs are combined with features extracted from medical text data consisting of patients’ diagnoses, procedures, and discharge notes and further engineered using several methods, including Latent Dirichlet Allocation (LDA), Latent Semantic Analysis (LSA), and word embeddings.

We sequentially implement three distinct Dense Neural Networks (DNNs) combined with the LightGBM gradient-boosting framework. Our model attained a 5-fold cross-validated …

3-D Reconstruction For Underwater Robots With A Monocular Camera And Lights, Monika Roznere

Dartmouth College Ph.D Dissertations

Before a robot can act, it must perceive its environment. Though, this is not a simple task when considering the challenges in underwater domains -- poor visibility conditions, limited sensor configurations, and lack of readily accessible localization. Underwater robots have, nevertheless, improved dramatically with more extensive sensor and navigation equipment. Robot and sensor use have enabled us to explore all reaches of our oceans. On the other hand, these same robots are not easily accessible or transferable to many practical tasks, including fishery management, infrastructure maintenance, disaster response, site conservation, and ecological surveys. There is a growing need for robots …

Catchment-Scale Thawing And Greening Decreases Long-Term Nitrogen Export In Ne Greenland, Shannon L. Speir, Jennifer L. Tank, Ada Pastor, Marc F. Muller, Mikhail Mastepanov, Tenna Riis

Crop, Soil and Environmental Sciences Faculty Publications and Presentations

Climate change is expected to alter nitrogen (N) export from Arctic rivers, with potential implications for fragile coastal ecosystems and fisheries. Yet, the directionality of change is poorly understood, as increased mobilization of N in a 'thawing' Arctic is countered by higher rates of vegetative uptake in a 'greening' Arctic, particularly in the understudied region of Greenland. We use an unprecedented dataset of long-term (n = 18 years) river chemistry, streamflow, and catchment-scale changes in snow and vegetation to document changing riverine N loss in Greenland. We documented decreasing inorganic and organic N loads, linked to decreasing snow stores, …

The Future Of Brain Tumor Diagnosis: Cnn And Transfer Learning Innovations, Shengyuan Wang

Mathematics, Statistics, and Computer Science Honors Projects

For the purpose of improving patient survival rates and facilitating efficient treatment planning, brain tumors need to be identified early and accurately classified. This research investigates the application of transfer learning and Convolutional Neural Networks (CNN) to create an automated, high-precision brain tumor segmentation and classification framework. Utilizing large-scale datasets, which comprise MRI images from open-accessible archives, the model exhibits the effectiveness of the method in various kinds of tumors and imaging scenarios. Our approach utilizes transfer learning techniques along with CNN architectures strengths to tackle the intrinsic difficulties of brain tumor diagnosis, namely significant tumor appearance variability and difficult …

Deterministic Global 3d Fractal Cloud Model For Synthetic Scene Generation, Aaron M. Schinder, Shannon R. Young, Bryan J. Steward, Michael L. Dexter, Andrew Kondrath, Stephen Hinton, Ricardo Davila

Faculty Publications

This paper describes the creation of a fast, deterministic, 3D fractal cloud renderer for the AFIT Sensor and Scene Emulation Tool (ASSET). The renderer generates 3D clouds by ray marching through a volume and sampling the level-set of a fractal function. The fractal function is distorted by a displacement map, which is generated using horizontal wind data from a Global Forecast System (GFS) weather file. The vertical windspeed and relative humidity are used to mask the creation of clouds to match realistic large-scale weather patterns over the Earth. Small-scale detail is provided by the fractal functions which are tuned to …

Care-Teach: Proposing An Open-Source Approach To Personalized Learning, Jaime Augusto Alvarez Perez

Theses and Dissertations

Care-Teach is an algorithmic educational model that provides teachers and educators with the tools to create interactive, text-based lessons that address a student’s need for continuity and reinforcement. Care-Teach is built around two core components: a Student Behavior Profile and the Skill Tree. These models work together to give each student a personalized learning experience that reinforces their pre-existing strengths and inclinations. The Student Behavior Profile model keeps track of a learner’s inclinations and mood, utilizing metrics such as average response time and accuracy to categorize opportunities for educator involvement. The Skill Tree is an organizational …

Electrocatalytic Degradation Of Bisphenol A Using Nickel Sulfide Supported On Graphene Oxide And Cobalt Sulfide Supported On Graphene Oxide Composite Materials, Katherine Ellynn Wright

Theses and Dissertations

The degradation of bisphenol A (BPA) by nickel sulfide supported on graphene oxide (NiS/GO) and cobalt sulfide supported on graphene oxide (CoS/GO) composite materials was investigated. The catalysts were studied to determine the optimal conditions for BPA degradation using electrocatalysis. Electrocatalytic trials were performed using varying parameters, which included electrolyte concentrations of 1.0 g/L, 2.0 g/L, and 4.0 g/L Na2SO4, pHs of 2, 4, and 6, and constant currents of either 0.100 A or 0.200 A. During the reaction samples were taken before the current was applied and 30 minutes and 60 minute intervals to observe the degradation of …

Bayesian Estimation Of Reproduction Numbers From Distributions Of Outbreaks Sizes: Branching Process Approach, Alberta Araba Johnson

Theses and Dissertations

The Generalized Poisson distribution is useful in modeling epidemiological processes as a branching stochastic processes problem. Our goal is to construct accurate and reliable estimators for the reproduction number (R0) (i.e., the number of secondary infections), particularly in the context of disease outbreaks modeled by a Galton-Watson process. Towards this goal, we construct the classical Bayes estimator, the Maximum Likelihood estimator, and the Empirical Bayes (EB) estimator under the Square Error Loss function in Chapter II. We prove that the Empirical Bayes estimator is asymptotically optimal and estimate the rate of convergence. We then proceed to monotonize the Empirical Bayes …

Variational Bias Sampling For Collaborative Filtering Recommender Systems, Prisca Stephens

Theses and Dissertations

Advancements in digitalization has yielded enormous growth of data on online platforms, overwhelming users with multitude of options to choose from. Recommender systems narrow down these options to a few relevant ones thereby facilitating the decision-making processes for users. This study presents a framework for integrating variational bias sampling into model-based collaborative filtering techniques for recommender systems. Variational bias sampling is a novel and unique way to account for random factors that affect explicit ratings in collaborative filtering recommender systems. A Gaussian distribution is used to model all the possible random factors that could affect ratings. Sampling user and item …

Mitigation Methods For Instrumental Artifacts In Gravitational Wave Data, Raghav Girgaonkar

Theses and Dissertations

Strain data from ground-based gravitational wave detectors are regularly affected by instrumental artifacts known as glitches. Such glitches form the background of false alarms in the detection of gravitational waves from compact binary coalescences, in-turn reducing search sensitivity. If left unaccounted, these glitches along with other non-stationarity may also contribute towards a corrupted representation of the statistical properties of detector noise, subsequently affecting parameter estimation for detected gravitational wave candidates. Therefore, effective data analysis methods to veto glitches and identify non-stationarities in detector data are crucial to enhancing the sensitivity of a gravitational wave search. In this thesis, we …

Conditional Constrained And Unconstrained Quantization For A Uniform Distribution On A Hexagon, Christina Hamilton

Theses and Dissertations

In this thesis, we have considered a uniform distribution on a regular hexagon and the set of all its six vertices as a conditional set. For the uniform distribution under the conditional set first, for all positive integers n ≥ 6, we obtain the conditional optimal sets of n-points and the nth conditional quantization errors, and then we calculate the conditional quantization dimension and the conditional quantization coefficient in the unconstrained scenario. Then, for the uniform distribution on the hexagon taking the same conditional set, we investigate the conditional constrained optimal sets of n-points and the conditional constrained quantization errors …

Soil Carbon Sequestration Efforts In Arid And Semi-Arid Climates Under Conservation Agriculture And Reforestation, Samantha Lynn Colunga

Theses and Dissertations

Soil organic carbon (SOC) plays a vital role in the global carbon cycle and aids in climate change mitigation. However, deforestation and intensive agricultural practices threaten topsoil and carbon (C) pools through soil disturbances releasing vast amounts of carbon dioxide (CO2) by enhancing the decomposition of organic materials. Degraded soils typically lack stable aggregates, nutrient and water retention, and overall low fertility. In arid and semi-arid regions, soils are in an even more dire situation, as low precipitation and high temperatures slow down the accumulation of SOC. This thesis has two objectives: 1) to evaluate whether conservation tillage practices increase …

How Mathematics Instructors Foster The Development Of Black Students' Mathematics Identity In Undergraduate Active Learning Mathematics Courses, Ashly J. Olusanya

Theses and Dissertations

Black students must overcome unique challenges to succeed in mathematics. Educators are tasked with identifying equitable teaching practices to support these students. Active learning (AL) is a teaching pedagogy that engages students in rigorous mathematical activities and encourages student participation. This research study will explore the professors’ beliefs about how students learn mathematics and why they use active learning in their collegiate mathematics courses. The study explores the connections between these beliefs and their reported use of instructional practices. The study also identifies the instructors’ beliefs about developing students’ mathematics identities, particularly their Black …