Physical Sciences and Mathematics Commons^™

Hitch Cart “Landing Gear”, Rebekah White, Jose Raygoza, Randy Hernandez, Brandon Leon

Mechanical Engineering

This report aims to allow our sponsor, to review our design process of the Hitch Cart Landing Gear Prototype. In the design overview section of this report, we discuss the primary design modifications we made to the wheel mechanism of the existing hitch cart prototype, including the addition of the ACME screws and the folding brackets. This allows our sponsor to see the intended improvements made to the past prototype and understand the primary goal of our project. Then, in the implementation section, we cover the entire manufacturing process to allow our sponsor to understand what manufacturing steps must be …

Locally Varying Geostatistical Machine Learning For Spatial Prediction, Francky Fouedjio, Emet Arya

Research outputs 2022 to 2026

Machine learning methods dealing with the spatial auto-correlation of the response variable have garnered significant attention in the context of spatial prediction. Nonetheless, under these methods, the relationship between the response variable and explanatory variables is assumed to be homogeneous throughout the entire study area. This assumption, known as spatial stationarity, is very questionable in real-world situations due to the influence of contextual factors. Therefore, allowing the relationship between the target variable and predictor variables to vary spatially within the study region is more reasonable. However, existing machine learning techniques accounting for the spatially varying relationship between the dependent variable …

Optimizing Neural Network Architecture Using Kernel Principal Component Analysis, Saige Simcox

Theses and Dissertations

Neural networks have proven to be powerful tools for modeling a wide range of problems across applications. However, one of the challenges in implementing a neural network model lies in determining the neural network architecture, i.e. the appropriate number of hidden layers and the number of neurons per hidden layer. It has been suggested that one way to determine the number of hidden layers is by using information on the variability captured by each principal component. In this research, we expand on this idea and propose a new approach to determine the neural network architecture for a multilayer perceptron used …

The Interplay Of Social Constraints And Individual Variation In Risk Tolerance In The Emergence Of Superspreaders, Earl Carr, Matthew J. Young, Matthew J. Silk, Alexander J. Pritchard, Nina F. Fefferman

Faculty Publications and Other Works -- Ecology and Evolutionary Biology

Individual host behaviours can drastically impact the spread of infection through a population. Differences in the value individuals place on both socializing with others and avoiding infection have been shown to yield emergent homophily in social networks and thereby shape epidemic outcomes. We build on this understanding to explore how individuals who do not conform to their social surroundings contribute to the propagation of infection during outbreaks. We show how non-conforming individuals, even if they do not directly expose a disproportionate number of other individuals themselves, can become functional superspreaders through an emergent social structure that positions them as the …

Human Capital At Home: Evidence From A Randomized Evaluation In The Philippines, Noam Angrist, Sarah Kabay, Dean S. Karlan, Lincoln Lau, Kevin M. Wong

Education Division Scholarship

Children spend most of their time at home in their early years, yet efforts to promote human capital at home in many low- and middle-income settings remain limited. We conduct a randomized controlled trial to evaluate an intervention which encourages parents and caregivers to foster human capital accumulation among their children between ages 3 and 5, with a focus on math and phonics skills. Children gain 0.52 and 0.51 standard deviations relative to the control group on math and phonics tests, respectively (p<0.001). A year later effects persist, but math gains dissipate to 0.15 (p=0.06) and phonics to 0.13 (p=0.12). Effects appear to be mediated largely through instructional support by parents and not other parent investment mechanisms, such as more positive parent-child interactions or additional time spent on education at home beyond the intervention. Our results show that parents can be effective conduits of educational instruction even in low-resource settings.

Data-Driven Mathematical Modeling And Simulation Of Migration Dynamics During The Russian-Ukrainian War, Danielle Sitalo, Alonso Ogueda-Oliva, Padmanabhan Seshaiyer

Spora: A Journal of Biomathematics

In this work, we employ a governing system of ordinary differential equations (ODEs) to create a mathematical model for getting insights into the dynamics of migration of Ukrainians evacuating due to war. A suitable assumption on coefficients of this model results in the well-known logistic growth. Additionally, stability analyses of equilibrium solutions for these ODEs are performed, and we employ parameter estimation techniques to identify coefficients using online datasets via both a least-squares approach as well as a physics informed neural network approach. Our findings indicate that over time, the daily influx of Ukrainian refugees to Poland stabilizes at a …

Malware Classification Through Abstract Syntax Trees And L-Moments, Anthony J. Rose [*], Christine M. Schubert Kabban, Scott R. Graham, Wayne C. Henry, Christopher M. Rondeau

Faculty Publications

The ongoing evolution of malware presents a formidable challenge to cybersecurity: identifying unknown threats. Traditional detection methods, such as signatures and various forms of static analysis, inherently lag behind these evolving threats. This research introduces a novel approach to malware detection by leveraging the robust statistical capabilities of L-moments and the structural insights provided by Abstract Syntax Trees (ASTs) and applying them to PowerShell. L-moments, recognized for their resilience to outliers and adaptability to diverse distributional shapes, are extracted from network analysis measures like degree centrality, betweenness centrality, and closeness centrality of ASTs. These measures provide a detailed structural representation …

Performance Studies Of An Axial Flow Waterjet Pump Using An Unsteady Reynolds-Averaged Navier-Stokes Model, Stephen E. Monroe, Junfeng Wang, Chunlei Liang

Northeast Journal of Complex Systems (NEJCS)

In this study, an Unsteady Reynolds-Averaged Navier-Stokes (URANS) model is demonstrated its suitability for studying the flow and performance of open marine propellers and waterjet pumps. First, the accuracy of the URANS model is validated by studying turbulent flow past counter-rotating propellers (CRPs). Specifically, experimental data from Miller (1976) is employed for comparison against the URANS results. Subsequently, URANS is used to study the flow and performance of an Office of Naval Research (ONR) axial flow waterjet pump (AxWJ-2). Due to the large number of degrees of freedom for both simulations, parallel computations over 80 cores are performed. For the …

Solving Fractional Differential Equations On A Quantum Computer: A Variational Approach, Fong Yew Leong, Dax Enshan Koh, Jian Feng Kong, Siong Thye Goh, Jun Yong Khoo, Wei Bin Ewe, Hongying Li, Jayne Thompson, Dario Poletti

Research Collection School Of Computing and Information Systems

We introduce an efficient variational hybrid quantum-classical algorithm designed for solving Caputo time-fractional partial differential equations. Our method employs an iterable cost function incorporating a linear combination of overlap history states. The proposed algorithm is not only efficient in terms of time complexity but also has lower memory costs compared to classical methods. Our results indicate that solution fidelity is insensitive to the fractional index and that gradient evaluation costs scale economically with the number of time steps. As a proof of concept, we apply our algorithm to solve a range of fractional partial differential equations commonly encountered in engineering …

Representation Theory Arising From Groups In Physics, Jaxon Green

Master's Theses

A representation is a group homomorphism whose image is a group of invertible matrices. Representations and their associated matrices are analyzed through well-established techniques from linear algebra. We characterize representations by a unique decomposition into irreducible representations just as we characterize the decomposition of matrices into their eigenspaces. Through the study of these representations, we uncover mathematical relationships that underlie groups with physical applications. Due to physical symmetries, we study how the irreducible representations of groups that embody the actions of even the most basic rotations are utilized in the computation of irreducible representations groups that reflect more complicated mechanics, …

Competition Effects In An Intraguild Predation Model, Nicholas A. Eekhof

Electronic Thesis and Dissertation Repository

In the biological world, many interactions exist between various species. These interactions generally consist of predator-prey relationships, competition between species and beneficial relationships. One observed phenomenon, termed the fear effect, occurs when one species reacts to an increased risk of predation by another species. The fear response causes the affected species to reproduce and forage for food less. In some cases, the fear response can be beneficial, while in other times it can be harmful. In this thesis, we consider a four compartment food-chain model in which there exists a top-level predator, a mesopredator and two types of prey who …

Host-Pathogen Co-Evolution With Various Transmission Modes Of Infection And Density-Dependent Dynamics, Bita Ghodsi

Electronic Thesis and Dissertation Repository

Pathogens can be transmitted both vertically (from the parent to the offspring) and horizontally. Here, I model the co-evolution of pathogens and their hosts allowing for vertical and horizontal transmission and density-dependent host population growth. My analysis uses evolutionary game theory. I use computational methods to find that increasing vertical transmission does not always result in more benign disease outcomes. Instead, it can lead to higher pathogen-induced mortality. Furthermore, more benign outcomes evolve more readily when horizontal transmission is more profitable for the pathogen, and overall virulence increases as horizontal transmission becomes more profitable. The results also indicate that vertical …

Osculating Curves, Sepideh Bahrami

Electronic Thesis and Dissertation Repository

Consider a complex analytic curve $X$ in $\mathbb{C}^2$, along with a specific point $p \in X$. The primary concern arises in approximating geometrically the curve $X$ precisely at the point $p$. Analogously, in introductory calculus, students learn to compute the tangent line to the graph of a function $y=f(x)$ at a given point $p=(x_*,f(x_*))$ by utilizing the derivative of $f$ at $x_*$.

For analytical convenience, we assume a local representation of the curve $X$ using a power series expansion. This representation centers the point $p$ at the origin $(0,0) \in \mathbb{C}^2$. Thus, our mathematical input becomes a Taylor series:

\[ …

Impact Of Energy Allocation On Fish's Age And Weight At Maturation By Mathematical Models, Siyi Zhang

Electronic Thesis and Dissertation Repository

The age and weight at maturation are crucial traits in an organism’s life cycle, influencing its growth, survival, and reproduction. We propose a biphasic energy allocation model, distinguishing pre-maturity and post-maturity, to study the mechanisms of maturation and estimate the age and weight at maturation. This model is parameterized for female lake whitefish (Coregonus clupeaformis). We compare different functions involved in the model, estimate parameters, and do sensitivity analysis. Our results indicate that (i) weight at maturation is positively related to the fraction of energy allocated to growth which, by data fitting, is almost a constant; (ii) age …

Macro–Micro-Coupled Simulations Of Bead–Spring Breaking-Reforming Networks, Andrei Medved

Theses and Dissertations

In this work we investigate the dynamic behavior of bead-spring polymer solutions in viscoelastic fluids, which are essential in industries like materials science, biotechnology, and pharmaceuticals. The study leverages GPU-accelerated simulations and detailed modeling of polymer chain dynamics at the mesoscale, which enables efficient analysis of intricate fluid behaviors and the microscale dynamics of polymer chains. Additionally, the research examines the breaking-reforming dynamics of polymer chains, crucial for understanding phenomena such as shear thinning and thickening. The findings have broad applications, from improving inkjet printing and 3D printing technologies to developing new drug delivery systems and biocompatible materials. This work …

Analysis Of The Effect Of Vaccination, Efficient Surveillance And Treatment On The Transmission Dynamics Of Cholera, Loyinmi Adedapo Chris, Ajala Adebisi Shukurat, Alani L. Ijaola

Al-Bahir Journal for Engineering and Pure Sciences

In this study, we presented a modified SIR-SI model to investigate the dynamics and potential controls for cholera transmission, with an incident rate equipped with a saturation factor to investigate the combined impact of three vital measures which include effective surveillance, vaccination campaign and proper treatment in case severity. We established among other things, the qualitative analysis of the model to validate the results. Furthermore, the reproduction number (R0) was found to be less than unity (1), through the stability analysis. Additionally, finite different scheme was utilized in solving the differential equations of the model. MATLAB software was used for …

Mathematical Modeling, Analysis, And Simulation Of Patient Addiction Journey, Adan Baca, Diego Gonzalez, Alonso G. Ogueda, Holly C. Matto, Padmanabhan Seshaiyer

CODEE Journal

This paper aims to develop a mathematical model to study the dynamics of addiction as individuals go through their detox journey. The motivation for this work is three fold. First, there has been a significant increase in drug overdose and drug addiction following the COVID-19 pandemic, and addiction may be interpreted as a infectious disease. Secondly, the dynamics of infectious disease could be modeled via compartmental models described by differential equations and one can therefore leverage the existing analytical and numerical methods to model addiction as a disease. Finally, the work helps to inform how mathematical models governed by differential …

The Bioremediation Effect Of Microalgae On Wastewater: A Green Technology Approach, Mohamed Ahmed Reda Hamed Dr, Marwa Abdelfattah Abdallah Dr

Journal of Engineering Research

The present study lays an emphasis on the microalgae-based for simultaneous wastewater bioremediation using Chlorella vulgaris and Micrococcus luteus mixed algal cultures to remove its constituent pollutants, amazing green technology guarantees benefits with the decrease in the formation of dangerous solid sludge. Ten days of fully monitoring laboratory experimental program were performed in batch cultures to investigate the effect of various dominant mixing ratios for attaining wastewater concentrations and different governing temperature ranges on the performance of microalgae treatment. The results revealed that there is a significant impact of both wastewater concentrations and temperature treatment conditions on the capability of …

Unlocking The Potential Of Rooftop Sustainable Systems: Understanding Barriers And Facilitators, Mahmoud Desouki, Taghreed A. El-Haddad

Journal of Engineering Research

Urbanization is reducing green spaces in old cities globally, including Egypt, adversely impacting air quality, climate, and psychological well-being. The rooftop has the potential to offer viable alternatives that provide multiple benefits. They can host sustainable systems, and foster social activities. Despite these advantages, their adoption in cities like Tanta the Egyptian city, one of the world's most densely populated cities with a shrinking per capita green space, remains limited. Most rooftops are often serving as dumping grounds for trash and unused items. This study aims to explore the reasons behind this underutilization to find ways to encourage the use …

Indicators And Evidence Of Environmental Sustainability For Pedestrian In Public Parks (Towards An Approach For Formulating A Guideline Evaluation Model), Nashwa Youssif

Journal of Engineering Research

يتناول البحث أحد المجالات التي فرضت تواجدها في الأونة الأخيرة علي الساحة العلمية والبحثية التي تتعلق بالعلاقة التبادلية التأثير بين الإنسان والفراغ العمراني حيث يتنامي الإهتمام بالخصائص الإنسانيه و مدي توافقها مع هذا الفراغ العمراني.

وتعد مسارات المشاة من أهم الحيزات العمرانية التى تشكل النسيج العمراني وأحد أهم وسائل التواصل الإجتماعي والثقافي والوظيفي نظرآ لإرتباطها بالغالبية العظمي من أفراد المجتمع، ومساعدتها على جذب العديـد من الأنشطة داخل الحدائق العامة. مما يشير إلي ضرورة الإهتمام بتحسين بيئة حركة المشاه كمدخل للتواصل والإستدامة.

ومن هنا تتمثل مشكلة البحث في نقص الدراسات حول تقييم العلاقة بين معايير الاستدامة التصميمية والنظم البيئية لمسارات المشاة …

The Feasibility Of Utilizing The Open Dynamic Interaction Network (Odin) App To Assess Rema Data Across 30 Days Among Those Recovering From Alcoholism, Dennis E. Mcchargue, Bilal Khan, Jesscia Phelps, Patrick Duryea, Kimberly A. Tyler, Arthur Andrews, Ellie Reznicek, Lucy Napper, Mohamed Saad, Hsuan-Wee Lee

Department of Psychology: Faculty Publications

About ~4 million people with an alcohol use disorder receive treatment annually, and frequent relapse has produced a rapid revolving door between recovery and use. This paper presents preliminary data from a prospective micro-longitudinal study (30 days) that examines co-evolution of relapse risk processes of people with alcohol use disorders who entered a short-term residential substance use treatment. The primary goal of the current data was to assess the feasibility of using the open dynamic interaction network (ODIN) responsive ecological momentary assessment (rEMA). rEMA collected daily estimates on affect, urges, sober-support engagement, and use. The ODIN app administered twelve questions …

Hypogene Speleogenesis In Carbonates By Cooling Hydrothermal Flow: The Case Of Mt. Berenike Caves, Israel, Roi Roded, Boaz Langford, Einat Aharonov, Piotr Szymczak, Micka Ullman, Shemesh Yaaran, Boaz Lazar, Amos Frumkin

International Journal of Speleology

The Berenike hypogenic cave system near Lake Kinneret, Israel, provides a valuable case study for investigating the recently proposed Confined-Cooling-Flow (CCF) speleogenesis model. Field and speleological surveys, along with existing research, are used to provide a thorough analysis. The CCF model relies on a simple thermo-hydro-chemical scenario, involving the rise of CO2-rich hydrothermal fluids discharging into a confined layer. The cooling of these CO2-rich fluids turns them into aggressive solutions due to the inverse relation between temperature and solubility of carbonates (retrograde solubility). Previous geochemical and numerical analyses of the CCF model predict localized and persistent dissolution and speleogenesis on …

Optimization Strategies For Political Redistricting, Blake Splitter

All Dissertations

Political redistricting has remained a hot-button issue in the United States for several decades. Every ten years, most states need to redraw their districts to account for changing populations. Sometimes, these district plans can be drawn with the malevolent intention of aiding one political party over another. This dissertation summarizes four distinct methods of drawing these districts using computer algorithms while keeping several objectives in mind. We test these approaches on the case study state of South Carolina, since it provides a sufficiently challenging problem for us to test various algorithms. We find that many of these approaches improve upon …

Efficient First-Order Methods For Some Smooth Nonlinear Optimization Problems, Yunheng Jiang

All Dissertations

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On Weak Solutions And The Navier-Stokes Equations, Aryan Prabhudesai

Mathematical Sciences Undergraduate Honors Theses

In this paper, I will discuss a partial differential equation that has solutions that are discontinuous. This example motivates the need for distribution theory, which will provide an interpretation of what it means for a discontinuous function to be a “solution” to a PDE. Then I will give a detailed foundation of distributions, including the definition of the derivative of a distribution. Then I will introduce and give background on the Navier-Stokes equations. Following that, I will explain the Millennium Problem concerning global regularity for the Navier-Stokes equations and share mathematical results regarding weak solutions. Finally, I will go over …

Probabilistic And Data-Driven Methods For Numerical Pdes, Johannes Krotz

Doctoral Dissertations

This dissertation consists of three integral self-contained parts. The first part develops a novel Monte Carlo algorithm, called the near-Maximal Algorithm for Poisson-disk Sampling (nMAPS), to efficiently generate the nodes of a high-quality mesh for the calculation of flow and the associated transport of chemical species in low-permeability fractured rock, such as shale and granite. A good mesh balances accuracy requirements with a reasonable computational cost, i.e., it is generated efficiently, dense where necessary for accuracy, and contains no cells that cause instabilities or blown-up errors. Quality bounds for meshes generated through nMAPS are proven, and its efficiency is demonstrated …

Data-Driven Model Reduction Strategies For Dynamical Systems, Talha Ahmed

Doctoral Dissertations

Many physically occurring phenomena are nonlinear in nature and can be understood through dynamical systems theory which describes how the state of the particular system evolves in time. However, it is generally cumbersome to analyze these processes in depth because of the nonlinearities in the mathematical model or large sets of equations. Model reduction strategies are employed for such nonlinear processes to reduce the model dimensionality and approximate the full model dynamics. In this study, we focus on data driven model reduction strategies for various biological systems where only observable data is available and illustrate their efficacy.

Our first work …

Computation Of Moving Interface Flows In Biophysical Applications, Mohammad Murshed

Masters Theses and Doctoral Dissertations

This dissertation is concerned with the modeling, simulation, and analysis of moving interface problems involving viscous fluids and solid structures. The main computational technique employed in this work is the immersed boundary method, a widely known numerical method for fluid-structure interaction (FSI). In this technique, the fluid equations are solved in an Eulerian grid and the structure is treated as a network of Lagrangian nodes. The communication between the fluid and structure dynamics is established by the use of the Dirac delta function. Utilizing the immersed boundary method, we have studied three biophysical applications. In the first application, we computed …

Evaluation Of Factors Impacting Predictor Importance Results In Multilevel Models, Soonhwa (Suna) Paek

Theses and Dissertations

Background: Dominance Analysis (DA) was originally proposed to determine the relative importance of predictor variables in OLS regression models by comparing the change in model fit (i.e., R2) resulting from adding each predictor to each possible subset model (Azen & Budescu, 2003; Azen, 2013; Budescu, 1993). Although various educational studies show that DA can provide useful information in research, the DA procedure has not been studied extensively with Multilevel Linear Models (MLMs), which are commonly used to analyze nested data structures.

Purpose: This study aimed to identify appropriate multilevel measures of fit for the DA procedure in various MLMs, and …

Robust-Efficient Fitting Of Loss Models Via Quantile Least Squares, Mohammed Adjei Adjieteh

Theses and Dissertations

Actuaries and statisticians use statistical models to predict future losses for pricing and other purposes. However, a key challenge in modeling is estimating the unknown parameters that index these distributions. Ensuring both efficiency and robustness of the chosen method is crucial, especially given the prevalence of outliers or extreme losses in insurance claims data. The primary objective of this dissertation is to introduce a robust, efficient, and computationally easy parameter estimation method that can be applied to various loss modeling scenarios. The proposed method exploits the joint asymptotic normality of sample quantiles (of i.i.d. random variables) to construct both ordinary …