Analysis Of Impulsive Differential Equation Models Of Cell Populations Undergoing Radiation Therapy,
2024
University of Nebraska-Lincoln
Analysis Of Impulsive Differential Equation Models Of Cell Populations Undergoing Radiation Therapy, Abigail D'Ovidio Long
Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–
Radiation therapy is a mode of treatment which is implemented for approximately 50% of cancer patients. Treatment needs to be able to kill cancer cells, but also do minimal damage to surrounding healthy tissue. We propose two main impulsive differential equation models of radiation therapy to capture the periodic nature of the treatment. These models build off of previous studies using clinical data to ensure biological relevance. The first model incorporates only cancer cell populations, and we provide parameter relationships which theoretically ensure treatment outcomes of cancer eradication, cancer approaching a carrying capacity, and cancer approaching a periodic solution. We …
Enhancing Mathematical Models For Covid-19 Pandemic Response: A Philippine Study,
2024
Ateneo de Manila University
Enhancing Mathematical Models For Covid-19 Pandemic Response: A Philippine Study, Timothy Robin Teng, Elvira De Lara-Tuprio, Ma. Regina Justina Estuar, Christian Pulmano, Lu Christian S. Ong, Zachary Pangan, Lenard Paulo V. Tamayo, Jasper John V. Segismundo, Mark Anthony C. Tolentino, Alyssa Nicole N. Ty
Mathematics Faculty Publications
Mathematical models supported by a robust automated data pipeline proved to be useful tools for a data-driven and science-based response and policy-making during the COVID-19 pandemic in the Philippines. In the first year of the pandemic, FASSSTER (Feasibility Analysis on Syndromic Surveillance using Spatio-Temporal Epidemiological modeleR) used a compartmental model to generate scenario-based projections of COVID-19 cases. The emergence of the Delta variant, however, and the administration of vaccines over the second half of 2021 caused significant changes in the Philippine pandemic landscape. This necessitated making adjustments to the model to better capture the local disease transmission dynamics and address …
Teachers’ Perceptions On The Impact And Effectiveness Of Certification Programs In Preparing And Retaining Educators,
2024
The University of Texas Rio Grande Valley
Teachers’ Perceptions On The Impact And Effectiveness Of Certification Programs In Preparing And Retaining Educators, Teresa De Jesus Padilla
Theses and Dissertations
Mathematics is integral to STEM fields, making math critically important for the stability and development of the nation. As a result, mathematics teachers have a crucial role in our society. A role whose importance needs the necessary support to accomplish its numerous responsibilities. However, research indicates that certification routes—traditional and alternative—often fail to adequately prepare math teachers for the challenges they face, leading to high turnover rates. This study explores the impact of these certification routes on teachers’ abilities to support student achievement, address diverse learning needs, and manage additional duties. Surveying secondary math teachers in the Rio Grande Valley, …
Bounding The Convex Hull Relaxation Of The Unit Commitment Problem With The Shapley-Folkman Theorem,
2024
Clemson University
Bounding The Convex Hull Relaxation Of The Unit Commitment Problem With The Shapley-Folkman Theorem, Lauren Henderson
All Theses
The Unit Commitment (UC) problem finds an optimal schedule for a set of generators by minimizing the total operation cost subject to demand and operational constraints. The UC problem is often modeled with a mixed-integer linear program (MILP). We employ the Shapley-Folkman Theorem to provide a bound on the size of fractional solutions of its convex hull relaxation. This result is used to obtain a bound on the optimality gap between the MILP and the convex hull relaxation, which is further tightened using several problem-specific properties of UC. We conduct extensive numerical experiments to study the tightness of this threshold, …
An Adaptive And Parallel Direct Solver For Elliptic Partial Differential Equations,
2024
Boise State University
An Adaptive And Parallel Direct Solver For Elliptic Partial Differential Equations, Damyn Chipman
Boise State University Theses and Dissertations
We introduce the quadtree-adaptive Hierarchical Poincaré-Steklov (QAHPS) method, an adaptive direct method for solving elliptic partial differential equations on a hierarchy of adaptively refined finite volume meshes. The QAHPS method builds up a solution operator set with O(N^3/2) complexity that acts as the factorization of the system matrix, with linear O(N) complexity for the application of the solution operator set to any number of right-hand side vectors. As the solution operator set is built up by merging local subdomains, it can be adapted as the mesh is refined and coarsened. The method is an …
A Comparative Analysis Of Early Algebraic Thinking Activities From U.S. And Singapore Primary Textbooks,
2024
Florida Institute of Technology
A Comparative Analysis Of Early Algebraic Thinking Activities From U.S. And Singapore Primary Textbooks, Christian Joel Hernandez
Theses and Dissertations
Many studies highlight the challenges students face when transitioning to algebra at the secondary level. Introducing algebraic concepts and fostering algebraic thinking at the primary level can help mitigate these difficulties. Prior to formal algebra instruction, early algebra can be cultivated as a mode of thinking known as algebraic thinking. Several international curricula, such as Singapore Math, incorporate early algebraic thinking into the early stages of schooling. Singapore Math, renowned for its high performance in international assessments, has been widely adopted by schools seeking to replicate its success.
This study compares two primary-level mathematics curricula—CCSSM-aligned textbooks and Singapore Math—specifically focusing …
Computational Representation, Analysis And Verification Of Requirements In Engineering Design And Systems Engineering,
2024
Clemson University
Computational Representation, Analysis And Verification Of Requirements In Engineering Design And Systems Engineering, Chandan Kumar Sahu
All Dissertations
Systems are developed to satisfy a set of requirements derived from stakeholders’ needs, defining the problem space for which the system is created as a feasible solution. The system design process begins with eliciting these requirements and concludes with validating whether the created system meets them. Requirements engineering (RE) encompasses elicitation, representation, analysis, documentation, verification, and validation. However, challenges in RE, such as imprecision in natural language (NL), proprietary restrictions, and a lack of standardized quality metrics, hinder the creation of well-formed and comprehensive requirements. These challenges complicate formalization and analysis of requirements.
This dissertation addresses these challenges by proposing …
Andre-Quillen Homology And Special Classes Of Ring Homomorphisms,
2024
Clemson University
Andre-Quillen Homology And Special Classes Of Ring Homomorphisms, Hossein Faridian
All Dissertations
This thesis is comprised of three chapters. The first chapter deals with a purely algebraic proof of a deep result of Quillen stating that the category of simplicial commutative algebras over a commutative ring is a model category. The central focus of our approach is on the study of shuffle product of connective chain complexes that provides a bridge to translate the constructions in the simplicial algebra world to the chain complex world.
The second chapter delves into Quillen's fundamental spectral sequences that relate Andre-Quillen homology and cohomology to Tor and Ext functors. Our comprehensive treatment develops and streamlines the …
Mathematical And Statistical Methods To Harness Limited Data In Models For Ecological Space Use Under Global Change,
2024
Utah State University
Mathematical And Statistical Methods To Harness Limited Data In Models For Ecological Space Use Under Global Change, Sarah C. Bogen
All Graduate Theses and Dissertations, Fall 2023 to Present
The dynamics of how plants and animals use space in their habitats has important implications for the fields of ecology and conservation. However, understanding and responding to these spatial and temporal dynamics is often limited by data availability, financial resources and biases. As average global temperatures increase, suitable habitats shift poleward and require local populations to move with suitable habitat, adapt to the changing environment, or risk extinction. Capacity to persist without movement may be estimated by considering changes to a combination of habitat characteristics. Capacity to track suitable habitat may be modeled through synthesizing information on species demographic mechanisms …
Decoding Neural Networks: An Information-Theoretic Guide To Interpretability, Error Analysis And Efficiency,
2024
Florida Institute of Technology
Decoding Neural Networks: An Information-Theoretic Guide To Interpretability, Error Analysis And Efficiency, Mackenzie J. Meni
Theses and Dissertations
This dissertation addresses critical challenges in neural network design by leveraging entropy-based techniques to improve model efficiency, interpretability, and bias reduction. Focusing on the unique demands of computer vision applications, particularly object detection and classification for real-time systems, this work introduces a series of innovative methods centered on information theory. At the core of these methods is the Probabilistic Explanations of Entropic Knowledge (PEEK) framework, a tool developed to analyze and visualize entropy distributions across feature maps. PEEK offers insights into information flow within neural networks, making it possible to pinpoint layers that contribute meaningfully to decision-making or identify those …
A Machine Learning Approach For Survival Analysis Of Transplanted Kidneys Based On Donors’ And Recipients’ Factors.,
2024
Florida Institute of Technology
A Machine Learning Approach For Survival Analysis Of Transplanted Kidneys Based On Donors’ And Recipients’ Factors., Alain Edward Despeignes
Theses and Dissertations
Over seven thousand people on average die each year in the United States waiting for an organ transplant due to the shortage of donated organs. With this alarming concern, efforts from the health organizations like the United Network Organ Sharing (UNOS) and government officials have considered avenues to remedy this distress, one of which is to investigate the characteristics among donors and recipients that affects the longevity of donated organs. The goal of this project is to investigate the survival time of transplanted kidneys from 1987 to 2018 with regards to the donors’ and the recipients’ characteristics including gender, ethnicity, …
On Representations Of The Super-Yangian Of The Queer Lie Superalgebra,
2024
The University of Texas Rio Grande Valley
On Representations Of The Super-Yangian Of The Queer Lie Superalgebra, Elena Poletaeva
School of Mathematical & Statistical Sciences Faculty Publications
Let Q(n) be the queer Lie superalgebra. We determine conditions under which two 1-dimensional modules over the super-Yangian of Q(n) can be extended nontrivially. We describe the dual modules of the simple finite-dimensional modules over YQ(1) . We use these results to describe blocks in the subcategory of finite-dimensional YQ(1) -modules admitting the zero generalized central character.
Modelling Tinnitus Functional Index Reduction Using Supervised Machine Learning Algorithms,
2024
The University of Texas Rio Grande Valley
Modelling Tinnitus Functional Index Reduction Using Supervised Machine Learning Algorithms, Edmund F. Agyemang
School of Mathematical & Statistical Sciences Faculty Publications
This study aims to model the reduction in the Tinnitus Functional Index (TFI) utilizing supervised machine learning algorithms, focusing primarily on Ordinary Least Squares (OLS), K-Nearest Neighbor (KNN), Ridge, and Lasso regressions. Our analysis highlighted Group, ISI, and SWLS as significant predictors of TFI reduction, identified through the best subset selection and confirmed by both forward and backward selection criteria in the OLS regression. Notably, the shrinkage methods, Ridge and Lasso regressions, demonstrated superior performance compared to OLS and KNN, with the Ridge regression presenting the smallest test mean square error (MSE) of 318.30. This finding establishes the Ridge regression …
On The Lagrange And Hermite Quadrature Formula,
2024
The University of Texas Rio Grande Valley
On The Lagrange And Hermite Quadrature Formula, Shuxia Li, Yonghong Chen
School of Mathematical & Statistical Sciences Faculty Publications
This paper builds on the error analysis method for Newton-Cotes quadrature formulas developed by D. R. Hayes and L. Rubin in 1970, which utilizes Lagrange interpolation polynomials. By adopting and extending their approach, this work derives the error estimate for Hermite interpolation quadrature. Specifically, we construct a polynomial P(x) analogous to the scaling function A(x) used by Hayes and Rubin, and prove its non-negativity over the interval. This allows us to establish a precise error formula for Hermite interpolation quadrature. The results provide a novel application of Hayes and Rubin's methodology, offering new insights …
A Novel Phenotype Imputation Method With Copula Model,
2024
University of North Texas
A Novel Phenotype Imputation Method With Copula Model, Jianjun Zhang, Jane Zizhen Zhao, Samantha Gonzales, Xuexia Wang, Qiuying Sha
Michigan Tech Publications
BACKGROUND: Jointly analyzing multiple phenotype/traits may increase power in genetic association studies by aggregating weak genetic effects. The chance that at least one phenotype is missing increases exponentially as the number of phenotype increases especially for a real dataset. It is a common practice to discard individuals with missing phenotype or phenotype with a large proportion of missing values. Such a discarding method may lead to a loss of power or even an insufficient sample size for analysis. To our knowledge, many existing phenotype imputing methods are built on multivariate normal assumptions for analysis. Violation of these assumptions may lead …
Bioconvection Dynamics In Rotating And Stationary Cone-Disk Systems,
2024
The University of Texas Rio Grande Valley
Bioconvection Dynamics In Rotating And Stationary Cone-Disk Systems, Puneet Rana, Mahanthesh Basavarajappa
School of Mathematical & Statistical Sciences Faculty Publications
This work focuses on the study of bioconvection in a conical region of rotating and stationary cone-disk systems utilizing nanofluids involving gyrotactic micro-organisms. The flow geometry encompasses two different configurations, namely, rotating cone-disk system (RCDS) and stationary cone-disk system (SCDS). For RCDS, four unique configurations are considered: rotating cone static disk (Model-I), static cone rotating disk (Model-II), co-rotating cone-disk (Model-III), and counter-rotating cone-disk (Model-IV), while SCDS includes both swirling and non-swirling flow scenarios. A total of six different physical configurations that differ in boundary conditions are investigated. The mathematical model comprises Navier–Stokes, energy, nanoparticle volume fraction (NVF), and micro-organism density …
On The Total Perimeter Of Pairwise Disjoint Convex Bodies,
2024
FORA Capital
On The Total Perimeter Of Pairwise Disjoint Convex Bodies, Arseniy Akopyan, Alexey Glazyrin
School of Mathematical & Statistical Sciences Faculty Publications
In this note we introduce a pseudometric on closed convex planar curves based on distances between normal lines and show its basic properties. Then we use this pseudometric to give a shorter proof of the theorem by Pinchasi that the sum of perimeters of 𝑘 convex planar bodies with disjoint interiors contained in a convex body of perimeter 𝑝 and diameter 𝑑 is not greater than 𝑝 + 2(𝑘 − 1)𝑑.
Quantum Markov Chains Related To Certain Lattice Models,
2024
United Arab Emirates University
Quantum Markov Chains Related To Certain Lattice Models, Ali Alalaai
Thesis/ Dissertation Defenses
A central open problem in quantum field theory is the construction of a general theory of quantum field, this thesis introduces quantum probability and applies it via the construction of quantum Markov chains on different hierarchical lattices (Cayley trees). Furthermore, these trees correspond to the Ising-XY-Model which then the existence of a unique Markov chain can be utilized to detect phase transitions.
A Dynamical Systems Approach For Modeling Malware Propagating Through A Network And Potential Solutions Towards Mitigating Spread,
2024
William & Mary
A Dynamical Systems Approach For Modeling Malware Propagating Through A Network And Potential Solutions Towards Mitigating Spread, James Johnson
Cybersecurity Undergraduate Research Showcase
Many people draw close parallels between malware propagating through a network and an epidemic spreading through a population. Epidemics are often modeled by a Susceptible-Infected-Recovered (SIR) model, in which a similar system of equations can model the spread of a virus through a computer network, and can be simplified when making assumptions about the network itself and its fixed number of nodes and edges. In this instance, malware propagating in a network also should reflect the network it is propagating through, in which the dynamical system will factor in the nodes of the network and their properties. The system itself …
Implementing Bernstein Operational Matrices To Solve A Fractional‐Order Smoking Epidemic Model,
2024
National University of Malaysia; Zayed University
Implementing Bernstein Operational Matrices To Solve A Fractional‐Order Smoking Epidemic Model, Jalal Al Hallak, Mohammed Alshbool, Ishak Hashim
All Works
This paper leverages the Bernstein operational matrices method for the first time in order to resolve the nonlinear fractional smoking epidemic model presented in terms of Caputo’s fractional derivative. An approximate solution is derived using Bernstein’s operational matrices and strategically chosen collocation points. This is followed by the validation of the proposed method’s accuracy and reliability against the established Runge–Kutta fourth‐order method. Furthermore, a comprehensive comparative analysis is conducted against two prominent techniques: the fractional differential transform method (FDTM) and the q‐homotopy analysis transform method (q‐HATM). The results show a superior and significant performance regarding accuracy as well as approximation. …
