Digital Commons Network^™

Finite Hybrid- And Semi-Markov Chains, Jose L. Menaldi, Maurice Robin

Mathematics Faculty Research Publications

The ergodic behaviour of finite Markov chains having also instantaneous transition are considered. Some estimates are obtained which complement our previous work [29]. Also, an optimal switching control model for semi-Markov chains is analysed, without any particular assumptions on the recurrent classes.

Möbius Transformations And Hyperbolic Geometry In The Upper Half-Plane, Emma Bunch

Mahurin Honors College Capstone Experience/Thesis Projects

In this thesis, we discuss several properties of Möbius transformations and hyperbolic geometry, a type of non-Euclidean geometry, in the upper half-plane using tools of complex analysis. We begin with preliminaries for our work, comprising the stereographic projection, the representation of circles and lines in the complex plane, conformal maps, and a result on cross-products, which we include for further development. We proceed to Möbius transformations and discuss their properties, cross-ratios, and various mappings. We additionally provide useful calculations. Lastly, we conclude with the hyperbolic metric in the upper half-plane and explore hyperbolic distance, including its invariance under Möbius transformations. …

Scaling-Rotation Curves On Matrices Of Constant Rank, Braedan Stuart

Theses & ETDs

In this thesis, we study several Riemannian metrics equipped to the manifold of Symmetric Positive-Definite (SPD) matrices. Emphasizing the “Scaling-Rotation Curves” of [10], we generalize this approach to pairs of nonsquare matrices of equal rank. Using computer software, we search for a heuristic to mitigate the poor performance of this geodesic as matrix size increases, but no pattern reveals itself. We conclude by suggesting investigation of other possible generalizations for nonlinear interpolation of nonsquare matrices.

Predicting Expected Goals And Playoff Success In The National Hockey League, Alexander Town

Theses & ETDs

We explore the within-game variables that can be used to project the typical number of goals a National Hockey League (NHL) team scores in a game. In particular, we used Poisson-type count-response models to model expected goals for a game given other variables such as shots, faceoffs won, penalty minutes, etc. Subsequently, we analyzed the teams whose actual scoring production over- and underperformed our model’s expected goals projection in the regular season, and investigated whether it could be used for predicting their performance in the playoffs. The data used to conduct this research are regular season and postseason game logs …

A Survey On Bounded Homomorphic Encryption, Charles Laforte

Theses & ETDs

This paper surveys homomorphic encryption, a new field with the goal of making a practical encryption scheme in which it is possible to perform functions on data while it remains encrypted. It examines the defining algorithms and requirements of homomorphic encryption schemes, as well as types of schemes with examples, including the ElGamal and Gentry, Sahai, and Waters schemes. This survey also overviews lattices, hard problems on lattices, and hard problems based on lattice problems, upon which many homomorphic schemes base their security. It explores the shortest vector problem, the bounded-distance decoding problem, and the learning with errors problem, among …

The Prison Yard Dilemma: How Agents Cooperate In A 2-D Space, Boland Unfug

Theses & ETDs

The prisoner’s dilemma and its variations offer profound insights into conflict and cooperation, captivating researchers across disciplines. Yet, a mutation of this classic game involving physical agents in a two-dimensional discrete environment remains largely unexplored. To explore this new facet of the prisoner’s dilemma, I developed a computer simulation using C++, Python, Box2D, and SFML that can simulate up to 1000 agents, uses deterministic, reproducible physics, and provides users with a complete history of the results. I designed this tool with the intention to discover if movement strategies were more impactful than gameplay decision rules and see if Tit For …

Analyzing Consumer Demand For Electric Vehicles, Galen Rydzik

Theses & ETDs

To reduce the impacts of climate change, there is an interest in significantly reducing greenhouse gas emissions from personal transportation in the United States. The adoption of hybrid (HEV), plug-in hybrid (PHEV), and battery electric vehicles (BEV) are alternatives to internal combustion engine vehicles (ICEV) that generate fewer direct emissions, and U.S. policy is currently poised to support the increased adoption of these vehicles. This study aims to determine underlying factors that influence the purchase of these vehicles and how challenges in the automotive market may limit their efficacy. A panel ordinary least squares consumer demand model is formed using …

Smart Homes, Grids, And Electric Vehicles Large-Scale Integration Studies Employing Machine Learning And Optimization Techniques, Rosemary E. Alden

Theses and Dissertations--Electrical and Computer Engineering

Residential digital twins are fundamental to the smart grid transition, and thus, must be both accurate and representative of existing homes and scalable for large distribution systems. Within this dissertation, new machine learning (ML) and physics-based methodologies are applied to the major individual residential loads, energy storage devices, and resources in the US to develop computationally efficient digital twins and new optimal control strategies for the virtual power plant (VPP) concept. Big data from experimental field demonstrations with dedicated metering, thousands of residential smart meter profiles, and large national human behavior surveys are employed to develop ultra-fast scalable residential load …

Deutscher Patriotismus?: Lesson Plan For Exploring German Patriotism, Janelle Carter

World Languages and Cultures Activities and Assignments

Objectives:

• Compare and contrast the differences in expressing patriotism between the US and Germany
• Introduction to the involvement soccer has in Germany’s culture, even for non-soccer fans

Joanne Stubbe And The Mechanistic Study Of Ribonucleotide Reductases, Madysen York

Natural Sciences Student Research Presentations

To catalyze the formation of deoxyribonucleotides from ribonucleotides, the enzyme has to remove an hydroxyl from the ribose sugar part of the molecule (circled in in green) (“Ribonucleotide Reductase”).

The problem is that hydroxyl doesn’t naturally want to break from the base it is attached to, leaving many researchers unable to discern the chemical process going on inside these enzymes that make the bond break possible (Strauss).

Mary Lowe Good And The Development Of Catalytic Solutions For Industrial Processes, Eleanor Heller-Walker

Natural Sciences Student Research Presentations

To study catalysts, Good used Mössbauer spectroscopy, a nuclear technique that measures how atoms absorb and emit gamma rays (“Mössbauer Spectroscopy”). This method helps scientists identify oxidation states, chemical environments, and structural changes in metal containing materials, especially iron.

This data revealed exactly how active metal sites in catalysts behave when exposed to exhaust gases, for example, when carbon monoxide (CO) or nitrogen oxides (NOₓ) contact the surface of the metal.

Using Machine Learning And Aerial Imagery To Detect Macroalgae, Dylan Niner

Theses & ETDs

Coastal ecosystems are essential for biodiversity and ecological services; they are increasingly under threat from human activity. Within these systems, macroalgae (submerged aquatic vegetation, or SAV) play a vital role. For that reason, assessing the condition and presence of SAV is important for understanding coastal ecosystem health. Traditional field surveys for SAV are limited in spatial and temporal resolution. In contrast, high-resolution Aerial (AUV) imagery, when combined with Convolutional neural networks, provides a great opportunity for analyzing this critical habitat at the necessary scales. Neural networks are computer models of interconnected nodes that learn to map inputs to outputs by …

Liberal Arts Education And Practical Pedagogy, Jessica Roberts

Theses & ETDs

This thesis explores how a liberal arts education, combined with extensive practical teaching experience and real-world insights, has shaped my philosophy and trajectory as a future educator as I traversed the college system. Drawing from interdisciplinary coursework and firsthand classroom involvement, I examine the benefits and challenges of pursuing a nontraditional path into teaching, particularly through the lens of Florida’s certification system. Rather than following a conventional teacher preparation program, I intentionally crafted an individualized academic journey grounded in humanities, social sciences, and natural sciences, complemented by sustained practicum experiences across multiple school districts. My work highlights how liberal arts …

Sectorized Based Investment Strategy During Recessions A Quantitative And Behavioral Analysis Of U.S. Market Performance, 1999–2015, John Scott

Theses & ETDs

This research analyzes the market performance of five U.S. equity sectors including Technology, Retail, Energy, Healthcare and Financials throughout recession periods from 1999 to 2015. The research concentrates its analysis on two significant market downturns: the Dot- Com Crash and the Great Recession by studying sector performance in comparison with the S&P 500 based on financial theory principles as well as behavioral economics concepts. Regular rolling calculations of 5-day standard deviations and 60-day rolling Beta measures for each sector allows evaluation of expected and actual returns by using the Capital Asset Pricing Model (CAPM) framework. The methodology provides real-time assessments …

Spectral Discrete Ordinates Method With Laguerre Polynomial Truncation Of Order N (Spectral-Ltsn) Solutions To The Generalized Linear Boltzmann Equation, Raymond Odian-Floyd

Theses & ETDs

This thesis presents a deterministic numerical solver for the Generalized Linear Boltzmann Equation (GLBE), a model that describes nonclassical neutral particle transport in heterogeneous media with spatially correlated structures [6, 10]. In such media, the classical assumption of exponentially distributed free paths fails, necessitating a formulation that explicitly accounts for the distance s traveled since the last collision. The proposed method approximates the angular flux using a spectral expansion in generalized Laguerre polynomials over the free-path variable s, discretizes the angular domain using the discrete ordinates (SN) method [8], and applies a diamonddifference scheme for spatial discretization. The resulting system …

The Effect Of Graphene Oxidation And Weight Percentage On The Biodegradability And Conductivity Of A Cellulose-Graphene (Oxide) Biocomposite, Jesse Roman

Theses & ETDs

The advent of electronics has been one of the greatest breakthroughs in human history, allowing us to significantly improve our quality of life, long-distance communication, and overall development as a society. Optimization and innovation of such technologies is ever-present today, as we continue to transition from in-person to online services. Despite the ongoing advances, the materials that we use to fabricate these devices are typically of plastic and metallic-origin, which not only persist in the environment, but are also detrimental to its health and that of humans. In fact, due to our increasing dependence on electronics, the industry is rapidly …

Evaluation Of An Efficient Ensembling Strategy For Linear Classifiers And Neural Networks, Lelaina Rose

Theses & ETDs

In this thesis I examine a specific ensembling technique—which I call “additive ensembling”—and how it performs when applied to linear classifiers, the perceptron, in particular, and feedforward neural networks. This technique differs from previous methods of ensembling, as it does not require the storage of individual weight vectors. Instead, it iteratively sums weight vectors from multiple separate models, resulting in one final summed model containing just one weight vector per class. It is implemented as an extension of scikit-learn’s machine learning library’s model classes. This algorithm is very straightforward to implement, requiring only a few lines of code and is …

Student Government Association Monthly Newsletter: November And December Edition, Madison May Albers

SGA - Newsletter

We would like to thank each and every one of you for your kind reception of our inaugural newsletter last month. We hope this one does not disappoint! This newsletter will cover all activity from November and December, as winter break is just around the corner. It also covers the results of our Educational Opportunity Fund cycle this year, so be sure to read all about that in the section titled "Bills passed." We all hope it's been a grand finals week and that you stay warm over break!

A Comparative Analysis Of Machine Learning Models For Predictive Process Monitoring Using Objectcentric Event Logs, Buthaina Hasan Aidaros Alhebshi

Theses

The increasing complexity of business processes drives the need for advanced predictive monitoring solutions capable of handling multi-entity interactions. Traditional case-centric event logs fall short of capturing these complexities, leading to the emergence of Object-Centric Event Logs (OCEL). Despite the growing interest in OCELs, their structural complexity and impact on predictive performance remain unexplored. This thesis investigates how process complexity influences the performance of machine learning models in predictive process monitoring using OCEL. A framework combining Graph Neural Networks and graph embedding-based models is applied across three predictive tasks: next activity, next timestamp, and remaining time prediction. The evaluation covers …

Bachelor Of Science In Professional Management, Nova Southeastern University

Undergraduate Programs Course Catalogs

No abstract provided.

Graduate Catalogue 2025 - 2026, Tennessee State University

Tennessee State University Graduate Catalogues

No abstract provided.

Captured Innovation: Technology Monopoly Response To Transformational Development, Reed Showalter, Laura Edelson

The University of Chicago Business Law Review

This Article examines how monopoly power warps incentives to innovate within the largest tech companies across history. Technology monopolies face competing incentives: to innovate and to maintain the status quo. As the center of their market, monopolists have resources and capacity to generate tremendous disruptive innovation. However, disruptive innovation serves only to threaten to destabilize the profitable market structure that a monopolist sits atop. We find that technology monopolists do not fail to innovate, but that they instead restrict that innovation from being released to the market or release the innovation in a diminished way, yoked to the existing technology …

Em 602-102: Management Science, Sufian Ikhmeis

Mechanical and Industrial Engineering Syllabi

No abstract provided.

Em 602-852: Management Science, Wenbo Cai

Mechanical and Industrial Engineering Syllabi

No abstract provided.

Ie 334-002: Engr Econ & Cpt Inv Analy, Athanassios Bladikas

Mechanical and Industrial Engineering Syllabi

No abstract provided.

Ie 339-102: Work Measurements And Standards, Sandra Tovar

Mechanical and Industrial Engineering Syllabi

No abstract provided.

Ie 224-002: Production Process Design, Sanchoy Das

Mechanical and Industrial Engineering Syllabi

No abstract provided.

Ie 335-452, 454: Engr Cost Analy & Control, Dielanda Dumay

Mechanical and Industrial Engineering Syllabi

No abstract provided.

Ie 459-002, Hm2: Supply Chain And Prod Planning, Wenbo Cai

Mechanical and Industrial Engineering Syllabi

No abstract provided.

Ie 449-102: Industrial Robotics, Bo Shen

Mechanical and Industrial Engineering Syllabi

No abstract provided.