Physical Sciences and Mathematics Commons^™

Flying Safe: Reducing Bird Strikes At Northern Illinois University, Stacey Marcinkowski

Honors Capstones

Bird-window collisions are a major source of avian mortality, particularly in urban environments where glass structures are prevalent. At Northern Illinois University (NIU), systematic monitoring conducted between 2019 and 2024 revealed Montgomery Hall to be the building with the highest incidence of bird strikes. This project aimed to test the effectiveness of a cost efficient bird strike mitigation strategy using grease marker frit dots on Montgomery Hall’s skybridge windows. We applied white dots spaced four inches apart and compared strike data collected during fall migration seasons before (2018–2022) and after (2024) dot application. While limited to one post-treatment season, results …

Two-Sample Bi-Directional Causality Between Two Traits With Some Invalid Ivs In Both Directions Using Gwas Summary Statistics, Siyi Chen

School of Public Health Faculty Publications

Mendelian randomization (MR) is a widely used method for assessing causal relationships between risk factors and outcomes using genetic variants as instrumental variables (IVs). While traditional MR assumes uni-directional causality, bi-directional MR aims to identify the true causal direction. In uni-directional MR, invalid IVs due to pleiotropy can violate assumptions and introduce biases. In bi-directional MR, traditional MR can be performed separately for each direction, but the presence of invalid IVs poses even greater challenges. We introduce a new bi-directional MR method incorporating stepwise selection (Bidir-SW) designed to address these challenges. Our approach leverages public genome-wide association study (GWAS) datasets …

Characterization Of A Magnetically Contained Hot Filament Plasma Source With A Wide-Sweeping Langmuir Probe, Jonas Rowan

Doctoral Dissertations and Master's Theses

Ionospheric plasma research in the Space and Atmospheric Instrumentation Laboratory’s Space Plasma Chamber has been hindered by the lack of a suitable plasma diagnostic instrument and understanding of its hot-filament plasma source. This thesis describes efforts made to remedy both problems. A wide-range Sweeping Langmuir Probe was developed with a ±35 V sweeping range to fully analyze ion and electron saturation regions in the entire IV curve. A method was derived to estimate the chamber source’s filament temperatures. The new Langmuir probe was integrated into a refurbished automated system designed in Python to measure plasma parameters for various chamber conditions, …

Satellite Reorientation Using Reinforcement Learning Under Unknown Attitude Failure, Matthew Willoughby

Doctoral Dissertations and Master's Theses

This study presents a reinforcement learning (RL) approach for reestablishing communication with deep-space satellites under unknown attitude determination and control system (ADCS) failures. When traditional fault-tolerant control methods cannot restore signal, the proposed RL controller acts as a last-resort measure by autonomously reorienting the satellite’s antenna toward Earth while charging the battery via solar panels. A generic reward function, designed for the RL-based method, enables the controller to adapt to diverse failure scenarios, including severe actuator noise, misalignment, and complete actuator failure. Simulations are conducted in the Basilisk environment and trained with the tonic framework and demonstrate ranging capabilities of …

Symmetry Induced Pairing In Dark Excitonic Condensate At Finite Temperature, Adham Alkady, Anatoly Kuklov

Publications and Research

Bose Einstein condensate of dark intervalley excitons must be inherently multi-component because of crystalline symmetries. Since valleys hosting such excitons are separated by large quasi-momenta, a minimal inter-component Josephson-type coupling can only be established between pairs of excitons from the time-reversed valleys. As a result, a paired condensate can emerge at finite temperature, that is, the off-diagonal order exists for the pairs from the time-reversed valleys, while the individual valleys are disordered. This prediction follows from the elementary mean field analysis regardless of the dimensionality. However, as Monte Carlo simulations show, no such a phase exists in 3D crystals. Instead, …

Weak Formulation For Solving Inverse Problems In Reproducing Kernel Hilbert Spaces (With Applications To Learning Dynamical Systems), Victor William Rielly

Dissertations and Theses

We combine numerical and machine learning techniques to present a general framework for solving inverse problems using vector valued reproducing kernel Hilbert spaces in a variational formulation. We present this framework in two papers. In the first paper, we present an original state-of-the-art method derived in the context of our general framework for learning dynamical systems. In the second paper, we generalize the method from our first paper to arrive at the framework for solving inverse problems. Then we apply our general framework to the task of learning dynamical systems. In both papers we consider numerous applications of our methods …

Improving The Reproducibility Of Deep Learning Software: An Initial Investigation Through A Case Study Analysis, Nikita Ravi, Abhinav Goel, James C. Davis, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

The field of deep learning has witnessed significant breakthroughs, spanning various applications, and fundamentally transforming current software capabilities. However, alongside these advancements, there have been increasing concerns about reproducing the results of these deep learning methods. This is significant because reproducibility is the foundation of reliability and validity in software development, particularly in the rapidly evolving domain of deep learning. The difficulty of reproducibility may arise due to several reasons, including having differences from the original execution environment, incompatible software libraries, proprietary data and source code, lack of transparency, and the stochastic nature in some software. A study conducted by …

Real-Time System Availability For Cyber-Physical Systems, Jinwen Wang

McKelvey School of Engineering Graduate Student Theses & Dissertations

Cyber-physical systems (CPSs), such as autonomous vehicles, are increasingly being deployed. The sensing, control, and actuation loop in CPSs must complete within strict timing constraints. Missing a real-time deadline can lead to catastrophic consequences, as CPSs continuously interact with the physical world. This highlights the importance of real-time system availability (i.e., timely execution) in CPS tasks, going beyond traditional security goals that primarily focus on confidentiality and integrity. From a security perspective, two factors affect real-time system availability. First, attackers with access to hardware resources in CPSs may disrupt the execution timing of real-time tasks. Second, the deployment of security …

Re: Comment Letter For The Butte Priority Soils Operable Unit (Bpsou) Draft Final Residential Metals Abatement Program (Rmap) Quality Assurance Project Plan (Qapp) (Non-Residential Parcels And Residential Daycares) (Dated February 26, 2025), Molly Roby

Silver Bow Creek/Butte Area Superfund Site

No abstract provided.

Soft Modular Robots: From Modular Tensegrity Structures To Bioinspired Sea Robots, Luyang Zhao

Dartmouth College Ph.D Dissertations

The rapid advancement of robotics necessitates systems capable of adapting to complex, unstructured environments. Soft robots, with their flexibility and compliance, excel in delicate interactions, making them ideal for medical applications and search-and-rescue missions. Modular robots, on the other hand, offer reconfigurability, enabling diverse task-specific adaptations in dynamic settings. Despite their individual advantages, the integration of soft and modular robotics remains underexplored. This proposal aims to develop soft modular robots that combine the adaptability of soft robotics with the versatility of modularity. These systems will be capable of autonomously transitioning between locomotion, manipulation, and infrastructure assembly across land, water, and …

Mapping The Key Players In Kawasaki Disease; Role Of Inflammatory Genes And Protein-Protein Interactions, Wael Hafez, Feras Al-Obeidat, Asrar Rashid, Afsheen Raza, Nouran Hamza, Nesma Ahmed, Marwa M. Abdeljawad, Raziya Kadwa, Abdelhameed Elmesery, Muneir Gador, Dina Khair, Gihan Zina, Fatema Abdulaal, Mina Wassef Girgiss, Maha Abdelhadi, Ahmed Abdelrahman, Mahmad Anwar Ibrahim, Mohamed El Sherbiny

All Works

Background: Kawasaki disease (KD) is a complex acquired condition characterized by systemic blood vessel inflammation that primarily affects children under five years of age. It is clinically diagnosed as a syndrome, making it susceptible to misdiagnoses. Severe complications such as myocardial damage and coronary artery abnormalities can be fatal; thus, early diagnosis is critical for preventing disease progression. Currently, no specific diagnostic test can distinguish KD from viral or bacterial infections. Additionally, the molecular mechanisms underlying the disease remain unclear, hindering the development of targeted therapies. Objective: This study aimed to identify the genetic patterns and molecular mechanisms associated with …

Vanadyl Phthalocyanine As A Low-Temperature/Low-Pressure Catalyst For The Conversion Of Fructose To Methyl Levulinate, Juan Luna, Mataz Alcoutlabi, Elizabeth M. Fletes, Helia Magali Morales, Jason Parsons

School of Integrative Biological & Chemical Sciences Faculty Publications

In this study, a vanadyl phthalocyanine was synthesized and characterized using XRD, FTIR, and XPS, confirming the successful metalation of the phthalocyanine ring. XRD analysis showed the vanadyl phthalocyanine crystallized in the P-1 crystal lattice, with unit cell parameters a = 12.058 Å, b = 12.598 Å, and c = 8.719 Å, and the lattice angels were 96.203°, 94.941°, and 68.204°. FTIR spectroscopy supported the metalation by the disappearance of the N-H stretch of the non-metalated phthalocyanine. The vanadyl phthalocyanine was tested as a heterogenous catalyst for the conversion of fructose into methyl levulinate in H2SO4–methanol and HCl–methanol systems. The …

Handwritten Digit Recognition Using Machine Learning, Dipok Deb

Data Science and Data Mining

Handwritten Digit Recognition (HDR) remains a fundamental benchmark in pattern recognition and machine learning due to its practical applications and inherent classification challenges posed by diverse handwriting styles. This study investigates and compares two classical statistical classifiers—Gaussian Naive Bayes (GNB) and Linear Discriminant Analysis (LDA)—to recognize the digits from the MNIST dataset. Both models assume underlying normality in feature distributions and offer computational efficiency, making them suitable for high-dimensional input such as image pixels. Using 60,000 training and 10,000 test samples, we evaluate model performance through accuracy, precision, recall, F1 score, and confusion matrices. The results reveal that while GNB …

Clustering Dataset Using K-Mean Clustering, Dipok Deb

Data Science and Data Mining

Clustering is a fundamental technique in unsupervised machine learning, widely applied in various domains such as pattern recognition, data segmentation, and anomaly detection. This study evaluates the performance of the K-Means clustering algorithm on multiple benchmark datasets, including low-dimensional, high-dimensional, and imbalanced datasets. The clustering results are assessed using four key evaluation metrics: Mean Squared Error (MSE), Adjusted Rand Index (ARI), Normalized Mutual Information (NMI), and Silhouette Score. Experimental results demonstrate that K-Means performs effectively on datasets with well-separated clusters, particularly in high-dimensional spaces, where it achieves near-perfect clustering accuracy. However, its performance deteriorates in datasets with overlapping clusters and …

Treatment Wastewater Of Oil Refinery By Fe2o3 Nps Produce By The Novel Alishewanella Jeotgali Strain Haq8., Hawraa Qays Al-Assdy, Wijdan Hussein Al-Tamimi, Asia Fadhile Almansoory

Karbala International Journal of Modern Science

Metal oxide nanoparticles like iron oxide (Fe₂O₃) exhibit strong reactivity and photolytic features in wastewater treatment and serve as an effective adsorbent for water purification due to its substantial surface area and affinity for different functionalized groups. Iron oxide nanoparticles) IONPs) are currently applied to treat oil-contaminated water. Fe₂O₃NPs were produced using an extracellular approach utilizing the Alishewanella jeotgali strain HAQ8. IONPs were characterized using UV-vis, FT-IR, XRD, AFM, SEM-EDX, and Zeta potential. λ max for the synthesized nanoparticles observed at (358) nm. The bands at 485 cm⁻¹ in the FT-IR spectrum confirmed the formation of …

Responsibility To The Land: Perspectives Of Farmers On Climate Change And Land Transition, Meira A. Smit

Environmental Studies Honors Projects

Agriculture is a defining aspect of Minnesota and Wisconsin’s culture and identity, characterized by family farms, rolling hills blanketed with crops, and cows. Interspersed are small scale diversified farms and a growing number of emerging and young farmers. Another cultural mainstay is talking about weather, a ubiquitous conversation of Midwesterners. As weather events such as erratic rainfall, drought, and pest pressure become both more common and volatile, and long-term weather patterns shift from “normal”, it is important to ask farmers what they think about it. Adapting to changes and planning for resilience are what farmers have always done, yet increasing …

Adding Libraries To The Equation: Mathematical Sciences’ Underutilization Of Academic Librarians, Jennifer L.C. Burke, Elizabeth C. Novosel, Daniel G. Kipnis, Rasitha R. Jayesekere

Libraries Scholarship

Academic librarians do not engage with all disciplinary departments equally. Despite equal or even greater efforts, some departments are less responsive to librarian outreach. One such department is mathematics. To understand mathematics departments’ relationships with their academic librarians, three mathematics librarians created a 20-question survey that was disseminated to mathematics faculty, instructors, and instructional staff in the United States and Canada. Of the 188 survey participants, more than a third reported that they never engage with their librarians, approximately half only do so occasionally, and a mere eight percent of participants collaborated with librarians to provide information literacy instruction (IL) …

On Metric Choice In Dimension Reduction For Fréchet Regression, Abdul Nasah Soale, Congli Ma, Siyu Chen

Faculty Scholarship

Fréchet regression is becoming a mainstay in modern data analysis for analysing non-traditional data types belonging to general metric spaces. This novel regression method is especially useful in the analysis of complex health data such as continuous monitoring and imaging data. Fréchet regression utilises the pairwise distances between the random objects, which makes the choice of metric crucial in the estimation. In this paper, existing dimension reduction methods for Fréchet regression are reviewed, and the effect of metric choice on the estimation of the dimension reduction subspace is explored for the regression between random responses and Euclidean predictors. An extensive …

Dynamic Riskscapes For Prey: Disentangling The Impact Of Human And Cougar Presence On Deer Behavior Using Gps Smartphone Locations, Heather N. Abernathy, Mark A. Ditmer, David C. Stoner, Kent R. Hersey, Kathryn A. Schoenecker, Pat J. Jackson, Kristin N. Engebretsen, Julie K. Young, George Wittemyer

Wildland Resources Faculty Publications

Prey species adjust their behavior along human-use gradients by balancing risks from predators and humans. During hunting seasons, prey often exhibit strong antipredator responses to humans but may develop tolerance in suburban areas to exploit human-mediated resources. Additionally, areas with high human activity may offer reduced predation risk if apex predators avoid such locations. This study examined mule deer Odocoileus hemionus behavioral responses to risks from humans and their primary predators, cougars Puma concolor, contextualized by differences in risk levels between study sites, individual risk exposure, and human habituation. We framed our investigation using three non-mutually exclusive hypotheses: (H1) …

Improving User Retention And Learning Through Interactive Tutorial Systems, Prakhyat Chaube

2025 Spring Honors Capstone Projects - Archive

The onboarding experience in software applications is crucial for user engagement and retention. Traditional static tutorials often fail to provide adaptive, role-specific learning, leading to user frustration and drop-off. This project introduces an interactive tutorial system tailored for students and tutors using the CSE Student Success Center App at the University of Texas at Arlington. Designed to enhance usability and accessibility, the system personalizes onboarding experiences through guided, role-based learning paths and real-time feedback. By streamlining the learning curve, the tutorial system fosters greater user confidence and engagement, ensuring a more intuitive transition into the application. User evaluations indicate a …

Hybridize Functions: A Tool For Automatically Refactoring Imperative Deep Learning Programs To Graph Execution, Raffi Khatchadourian, Tatiana Castro Vélez, Mehdi Bagherzadeh, Nan Jia, Anita Raja

Publications and Research

Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code—supporting symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, imperative DL frameworks encouraging eager execution have emerged but at the expense of run-time performance. Though hybrid approaches aim for the “best of both worlds,” using them effectively requires subtle considerations to make code amenable to safe, accurate, and efficient graph execution—avoiding performance bottlenecks and semantically inequivalent results. We discuss the engineering aspects of a …

A Zariski-Nagata Theorem For Smooth Toric Surfaces, Jordan Vincent Barrett

Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–

The Affine Zariski-Nagata theorem is a classical result in commutative algebra that gives an expression for the n^th symbolic power of a radical ideal I in a polynomial ring over a field in terms of the n^th ordinary powers of the maximal ideals in [affine variety]_max(I). In this thesis we discuss a well-known projective analog of Zariski-Nagata and provide the necessary background on toric varieties to present a generalization of this result to toric surfaces. We conclude with a brief discussion about work toward characterizing which abstract toric varieties have smooth point fibers with …

How Much Should Consumers With Mild To Moderate Hearing Loss Spend On Hearing Devices?, Vinaya Manchaiah, Steve Taddei, Abram Bailey, De Wet Swanepoel, Hansapani Rodrigo, Andrew Sabin

School of Mathematical & Statistical Sciences Faculty Publications

Background: This study examined the relationship between hearing device price and sound quality. Method: A novel consumer-centric metric of sound quality (“SoundScore”) was used to assess hearing devices’ audio performance. Each hearing device is tested with two fittings. The “Initial Fit” is designed to approximate the most likely fitting for an individual with a mild-to-moderate sloping sensorineural hearing loss. The “Tuned Fit” includes adjusting parameters optimized to hit prescriptive fitting targets (NAL NL2) on an acoustic manikin. Each fitting is evaluated across five dimensions. Both fittings are combined using a weighted average to create a single number from 0 to …

Estimating Pedestrian Crossing Times At Scramble Crossings Via Machine Learning And Agent-Based Modeling, Sho Takami

Honors Capstones

Scramble crosswalks differ from conventional crosswalks in their ability for pedestrians to cross diagonally. This research compares the average crossing times and investigates the walking behaviors that pedestrians adopt to produce the speediest times in the two crosswalk configurations. Identification of the most efficient set of walking behaviors is done through an agent-based model, whereas producing polynomials relating crossing times to the most prominent walking behaviors is done through regression algorithms in machine learning. With the combination of these two approaches, it is revealed that pedestrians must adopt a relaxed walking style to make each crosswalk configuration efficient. Additionally, between …

05.05.2025 Ored Connect, Liz Williamson

ORED Newsletter

Research Showcase Photos

Showcase Raffle Winners

Chancellor's Award for Research and Creative Scholarship

Video of the ORED website

First-Principles Studies Of Excited-State Properties In Large-Scale Systems, Du Li

Arts & Sciences Graduate Student Theses and Dissertations

Density Functional Theory (DFT) is widely used as a powerful tool for studying the electronic structure of materials. However, due to the local or semilocal nature of exchange-correlation functionals, such as the local density approximation and generalized gradient approximation functional, DFT often underestimates the electronic band gap. Many-body perturbation theory (MBPT) within the GW approximation provides more accurate quasiparticle energies calculation by incorporating many-electron screening effects. Additionally, solving the Bethe-Salpeter Equation (BSE) allows for a detailed analysis of excitonic effects in optical spectra. Despite their accuracy, GW-BSE calculations are computationally expensive, particularly for large-scale systems such as defects and substrate-supported …

Recent U.S. Government Policy Literature On Critical And Strategic Minerals, Bert Chapman

Libraries Faculty and Staff Scholarship and Research

Critical and strategic minerals have become increasingly important in U.S. government civilian and military policymaking in recent years. This is demonstrated by the heavy use of such minerals in many critical civilian and military infrastructures. This work will discuss how this subject has been addressed in laws, presidential documents, and works by government agencies along with congressional oversight committees and support agencies. It will stress how the United States is heavily dependent on strategic minerals from adversarial foreign countries such as China and will examine U.S. efforts to increase its ability to produce such materials in the United States by …

Transformations Of Bound Quivers, Ari Pincus-Kazmar

Mathematics, Statistics, and Computer Science Honors Projects

A quiver Q is a directed multigraph. Representations of Q are assignments of vector spaces and linear maps to the vertices and arrows of Q; these are categorically equivalent to the modules over the path algebra kQ. The indecomposable representations of a given quiver and the irreducible morphisms between them are summarized combinatorially in the Auslander-Reiten quiver which, in the case of algebras of finite representation type, gives almost complete information about the category of representations. We introduce an intuitive transformation from a family of bound quivers to a family of A-type quivers which preserves properties of the Auslander-Reiten quiver.

Modeling Literary Connections: Exploring Transregional Resistance In Dalit Poetry, Antara Bhattacharyay

Mathematics, Statistics, and Computer Science Honors Projects

Structuring socio-political identities, the caste system (a graded form of hierarchy) remains entrenched in contemporary Indian society. Dalits, marginalized by the caste system, have expressed their resistance through literature, envisioning substantive equality and social change. In this thesis, I draw on digital humanities methods to examine regional variation in translated Dalit poetry from Bengali, Hindi/Urdu, Marathi, and Tamil languages. I utilize topic modeling—a machine learning algorithm that detects latent semantic structures in a text—as a point of departure for poetry analysis. I observe how topic modeling enables newer readings of the poems, revealing regionally resonant and broader Dalit themes.

Hybridize Functions: A Tool For Automatically Refactoring Imperative Deep Learning Programs To Graph Execution, Raffi Khatchadourian, Tatiana Castro Vélez, Mehdi Bagherzadeh, Nan Jia, Anita Raja

Publications and Research

Efficiency is essential to support responsiveness w.r.t. ever-growing datasets, especially for Deep Learning (DL) systems. DL frameworks have traditionally embraced deferred execution-style DL code—supporting symbolic, graph-based Deep Neural Network (DNN) computation. While scalable, such development is error-prone, non-intuitive, and difficult to debug. Consequently, more natural, imperative DL frameworks encouraging eager execution have emerged but at the expense of run-time performance. Though hybrid approaches aim for the “best of both worlds,” using them effectively requires subtle considerations to make code amenable to safe, accurate, and efficient graph execution—avoiding performance bottlenecks and semantically inequivalent results. We discuss the engineering aspects of a …