Digital Commons Network^™

Enhancing Learning Path Recommendation Via Multi-Task Learning, Afsana Nasrin

All Theses

Personalized learning is a student-centered educational approach that acknowledges and adapts to the unique characteristics of each learner by customizing content, pacing, and assessments to meet individual needs. Key components include learner profiles, cognitive styles, learning objectives, adjustable pacing, and enabling technologies such as intelligent learning environments, intelligent tutoring systems, and data mining.

A key strategy for implementing personalized learning is learning path recommendation, a technique that guides learners through tailored sequences of content. This approach sequentially recommends personalized learning items, such as lectures, exercises, to address each student’s specific needs. Recent advances in deep learning, particularly deep reinforcement learning, …

Characterization Of Site-Specific Q295-Conjugated Tlr7 Agonist Immune-Stimulating Antibody Conjugates, Samuel Hanul Chung

Undergraduate Honors Theses

Recent advances in immunotherapy as a viable cancer treatment modality has led to the development of immune-stimulating antibody conjugates (ISACs). ISACs are analogous to antibody-drug conjugates (ADCs), which utilize the specificity and stability of an antibody to deliver cytotoxic payloads directly to a tumor. ISACs, however, deliver immune stimulating agents instead, activating adaptive and innate immune responses to engage with tumor cells. Among the various immunostimulants currently being explored, Toll-Like Receptor (TLR) agonists have risen as promising inducers of anti-cancer immune responses. Previously, the Tumey lab has explored ISACs employing an imidazole[4,5-c]quinoline TLR7 agonist with drug-antibody ratios (DAR) of ~8. …

Learning To Accelerate Tightening Of Convex Relaxations Of The Ac Optimal Power Flow Problem, Faith Cengil, Harsha Nagarajan, Russell Bent, Sandra Eksioglu, Burak Eksioglu

Industrial Engineering Faculty Publications and Presentations

We propose a novel machine learning (ML)-based approach to significantly reduce the run times of the optimality-based bound tightening (OBBT) algorithm for strengthening the convex relaxations of the non-convex Alternating Current Optimal Power Flow (AC-OPF) problem. While OBBT can yield near-global solutions via tight convex relaxations, its runtime remains a critical bottleneck on large-scale power grids. Our key contribution is a dynamic policy that selects smaller subsets of voltage magnitude and phase-angle difference variables for sequential bound tightening at every iteration of the OBBT algorithm. This ensures that the bound-tightening process remains adaptive, thereby circumventing the stalling in the optimality …

Twim #222: Biosensors In Bacteria, Madison Hayes, Alexis Austin, Dillon Nguyen, Angela Wilson, Rebecca Seipelt-Thiemann

School of Medical Diagnostics & Translational Sciences Publications

Podcast annotation TWiM #222: Biosensors in Bacteria from the weekly podcast series "This Week in Microbiology" (TWiM), a podcast where experts in microbiology discuss academic papers in their field in an informal way.

Twim #243: Beef And Bacillus, Sakiem Winston, Madison Wolford, Rebecca Seipelt-Thiemann, Angela Wilson

School of Medical Diagnostics & Translational Sciences Publications

Podcast annotation TWiM #243: Beef and Bacillus from the weekly podcast series "This Week in Microbiology" (TWiM), a podcast where experts in microbiology discuss academic papers in their field in an informal way.

Twim #286: Integrons And Invasion, Andrea Ayala-Lopez, Brittney Heist,, Thomas Salazar, Rebecca Seipelt-Thiemann, Mel Melendrez-Vallard, Angela Wilson

School of Medical Diagnostics & Translational Sciences Publications

Podcast annotation TWiM #286: Integrons and Invasion from the weekly podcast series "This Week in Microbiology" (TWiM), a podcast where experts in microbiology discuss academic papers in their field in an informal way.

Information Literacy In The Artificial Intelligence Era: A Proposed Framework, Radwan Ali, Matthew L. Wilson

Communications in Information Literacy

Artificial intelligence (AI) systems and applications have become ubiquitous across daily life. While AI offers numerous positive opportunities, it also presents numerous challenges. Information literacy (IL) advocates are concerned about the risks that accompany AI systems. Given the universal reach of AI with its potential pitfalls and perils, researchers and practitioners from various fields and disciplines should inform the dialogue on AI’s development and application. A critical aspect of this dialogue comes in the form of information literacy. Our paper aims to answer the question “How can information literacy guide users in navigating and shaping artificial intelligence technologies?” by establishing …

Experimental Measurement Demonstration Of Initial And Steady-State Heights Of A Co2 Vertical Jet Fountain In Still Air, Brock Mcrae

Chemical Engineering Undergraduate Honors Theses

Atmospheric releases of heavier-than-air gases pose acute near-field hazards in low wind, yet the near-source behavior of vertical dense-gas jets in still air is sparsely documented. This thesis demonstrates a repeatable laboratory method for measuring the initial and steady-state rise heights of a carbon dioxide (CO₂) jet issued vertically from a floor nozzle in the CHRC ultra-low-speed wind tunnel under still-air conditions. Controlled mixtures (pure CO₂, 50/50 CO₂-air, 25/75 CO₂-air) were released at four flow rates (75, 100, 125, 150 LPM) with five repeats per condition. A fixed camera and tape-measure scale enabled video extraction of jet height using Kinovea …

Calibration And Validation Of Cyclic Stretching Platform For Stiffness Testing Of Engineered Heart Tissue, Jillian Welsh

Chemical Engineering Undergraduate Honors Theses

Cardiac fibrosis (CF) is a major contributor to the high mortality rate of heart failure which affects over 23 million people worldwide. CF involves cardiac fibroblasts depositing extracellular matrix, made primarily of collagen type I, which stiffens the heart walls over time. As testing new drugs for CF is deterred by the high cost and time required for animal and clinical trials, this research helps to solve the problem by providing an in vitro platform to study fibrosis.

The work involved creating tissues containing human cardiac fibroblast (HCFB) cells. Spring testing was conducted to determine the force applied by the …

Undergraduate Awareness Of Sexual Harassment Law In Tanzania's Higher Learning Institutions: Case Studies Of Two Universities, Salma Ramadhan Fundi Phd Candidate

Tanzania Journal of Sociology

This study examines undergraduate students' awareness of legal provisions and guidelines concerning sexual harassment in Tanzanian higher education, focusing on the University of Dar es Salaam (UDSM) and the Open University of Tanzania (OUT) as case studies. Sexual harassment significantly impacts students’ well-being, safety, and academic success. Despite the existence of legal frameworks, students' knowledge of these provisions is often limited. The study employed a qualitative approach with a phenomenological research design to explore students’ experiences and perceptions of harassment policies. This design allowed participants to share the meanings they attach to their experiences and how such policies are understood …

The Rider (2025-12-01), Daniela Martinez Salazar

The Rider Archives

Vol. 11, No. 13

Expanderizing Higher-Order Random Walks, Vedat Levi Alev, Shravas Rao

Computer Science Faculty Publications and Presentations

We study a variant of the down-up (also known as the Glauber dynamics) and up-down walks over an 𝑛-partite simplicial complex, which we call expanderized higher-order random walks—where the sequence of updated coordinates corresponds to the sequence of vertices visited by a random walk over an auxiliary expander graph 𝐻. When 𝐻 is the clique with self-loops on [𝑛], this random walk reduces to the usual down-up walk, and when 𝐻 is the directed cycle on [𝑛], this random walk reduces to the well-known systematic scan Glauber dynamics. We show that whenever the usual higher-order random walks satisfy a log-Sobolev …

Full Issue (Volume 4, Issue 2): Evolving Englishes, Innovative Pedagogies, And Emerging Linguistic Insights

Journal of English and Applied Linguistics

Abstract not applicable.

Systematic Review Of Instruments Measuring Teachers' Tpack, Jose Ruben Avalos

Open Access Theses & Dissertations

The study examines the assessment of Technological Pedagogical Content Knowledge (TPACK), a framework that integrates technology, pedagogy, and content knowledge for effective teaching. Given the increasing integration of technology in education, it is crucial to understand how TPACK is assessed and the tools used to measure teachers' proficiency in these areas. This study aims to review and analyze tools used to assess TPACK, evaluate their validity and reliability, and provide a synthesis of existing research to inform future developments in TPACK assessment. A systematic review of literature was conducted, focusing on studies related to the evaluation of TPACK. Four research …

Coupling Material Formulation Strategies To Tailor Piezoelectric Properties Of Ceramic Lattices, Amanda Lauren Borgaro

Open Access Theses & Dissertations

This thesis examines the material formulation and infiltration processes required to create interpenetrating ceramic composites with a particular focus on developing piezoelectric ceramic-epoxy lattice structures (PCELS). Following this, a high–solid loading barium titanite photopolymer resin (BT40) was developed to produce BTO scaffolds with controlled porosity suitable for metal infusion. The resin’s shear-thinning behavior and scattering-dominated curing response enabled the formation of stable, uniform ceramic structures whose pore networks directly influence infiltration behavior. Building on this foundation, a low-temperature Field’s Metal (FM) infiltration method was established using controlled thermal equilibration and the melting of pre-formed alloy rods. By maintaining the ceramic …

Computational Methods For Complex Electromagnetic Geometries And Media, Edgar Bustamante

Open Access Theses & Dissertations

Additive manufacturing has enabled electromagnetic devices with increasingly complex geometries, but existing numerical tools remain limited in their ability to model and design such structures. This dissertation presents two major advancements that address these restrictions in the finite-difference frequency-domain method (FDFD) and the spatially-variant lattice algorithm (SVLA). These two numerical methods provide a foundation for future exploration in the simulation, optimization, and realization of next-generation electromagnetic devices. First, a general bianisotropic FDFD formulation based on the vector wave equation is presented that enables practical modeling of metamaterials using effective medium homogenized parameters rather than explicitly resolving subwavelength metamaterial features. The …

Image And Signal Processing Methods For Clinical Decision Support: Reference-Based Lung Segmentation On Chest X-Rays And Ecg-Based Study Of Acute Hyperkalemia Using Machine Learning, Basavarajaiah Shanmukhayya Totada

Open Access Theses & Dissertations

ABSTRACT

Study-I: An Image Processing Pipeline for Reference Guided Lung Region Detection in Chest Radiographs with Shape Similarity Matching Accurate and reliable segmentation of the lung region in chest X-ray (CXR) images is essential for computer-aided diagnosis (CAD) systems, particularly in the early detection and monitoring of lung disorders. Traditional segmentation techniques often rely on manual annotations, limiting scalability and adaptability. The proposed reference-guided approach selects the most similar healthy CXRs dynamically, ensuring flexibility while benefiting from dataset-specific reference images. Building upon prior approaches that utilize shape similarity-based selection and SIFT-flow, this study introduces a fully automated segmentation pipeline that …

Algebraic Approach To Data Processing: Techniques And Applications, Julio Urenda

Open Access Theses & Dissertations

In many areas of human knowledge, symmetries and invariances play an important role. In fundamental physics, starting with Relativity Theory, new physical theories have been formulated in terms of invariances and of the corresponding transformation groups – i.e., in terms what a mathematician would call an algebraic approach. In engineering, devices like wind tunnels, which are based on scale-invariance, enable us to test smaller-scale models of the actual designs. In biological sciences, symmetries and invariances are extremely important in analyzing the shape and functioning of living beings, from mammals to viruses. Invariance and symmetry – in the form of fairness …

Understanding Outer Solar System Ice Composition Through Impact Processes: Simulations And Hydrates, Jill Rebecca Mcdonald

Graduate Theses and Dissertations

This work concerns solar system ices, particularly water ice and clathrate hydrates. Water ice is abundant as a mineral in the outer parts of the solar system, providing source material for the formation of clathrates. We explored constituents through a combination of numerical modeling and laboratory experiments. Understanding the differences and similarities between these materials can shed light on planetary habitability, composition, and evolution. Chapter one contains relevant background information. This chapter introduces the ices that will be studied and gives insight into the locations of interest within our solar system. It also explains the mechanics of impact cratering processes …

Privacy Protection In Cloud-Based Biometric Systems, Yatish Reddy Dubasi

Graduate Theses and Dissertations

The widespread adoption of server-based biometric authentication systems, often hosted in the cloud, has introduced significant privacy risks. While these systems offer convenience, they require storing sensitive biometric templates on remote servers, creating a high-value target for adversaries. Unlike passwords, compromised biometric data is immutable and cannot be reissued, leading to an irreversible loss of privacy. This threat is exacerbated by template inversion attacks, which can reconstruct a user's original biometric trait (e.g., a face image) from its stored feature vector. This dissertation addresses these critical privacy challenges by designing, implementing, and evaluating a suite of novel frameworks for privacy-preserving …

Impact Of Polystyrene Nanoplastics On Oncogenic Signaling Pathways In Prostate Cells, Luis Alfonso Adel-Alvarez

Open Access Theses & Dissertations

Prostate cancer (PC) remains the most prevalent malignant disease among the male population worldwide, with a dramatic increase observed in the European Union from the 1980s to the 2000s. The etiology of PC is attributed to both hereditary factors and environmental pollutants. Among these, endocrine disruptors and polystyrene nanoparticles (PSNPs) interact with the prostate gland via the circulatory system, inducing intense oxidative stress. This study aims to characterize, for the first time, the pathobiological effects of PSNPs in both non-malignant (RWPE1) and malignant (22RV1) prostate cell lines. The objective was to elucidate the mechanisms by which environmental pollutants, such as …

Machine Learning And First-Principle Approach To The Stability And Properties Of Iron-Based Materials Under Extreme Conditions., Blaise Awola Ayirizia

Open Access Theses & Dissertations

This dissertation investigates the stability and physical properties of iron-based materials under extreme conditions, utilizing a combination of machine learning techniques and first principles calculations. In the first study, we employ Gaussian Process Regression (GPR) with a Marginalized Graph Kernel to analyze the mechanical stability of non-magnetic body-centered cubic (BCC) iron at high temperatures and pressures, similar to those found in Earth’s core. Our model, trained on data derived from ab initio molecular dynamics (AIMD) simulations, predicts the energy landscape, atomic forces, and potential pathways for instability in BCC iron. The findings suggest that BCC iron remains stable in extreme …

Study Of Fatigue Endurance Of Alsi10mg Post Heat Treatments And Subsequently Aged At Service Temperature, Luis Alfredo Barrera

Open Access Theses & Dissertations

Laser Powder Bed Fusion (LBPF) AlSi10Mg is used in the aerospace and automotive industries for its refined microstructure and ductility compared to cast alloys. However, LPBF processes can inherently lead to defects that may act as fatigue crack initiators, such as lack of fusion, balling, and keyhole porosity. This work focuses on the analysis of high-cycle fatigue (HCF) endurance of AlSi10Mg under expected service conditions. For this study, AlSi10Mg specimens were printed on an EOS M290 LPBF system and heat-treated by stress relief (SR1), Hot Isostatic Pressing (HIP), and Hot Isostatic Pressing + T6 (HIP+T6), as per ASTM 3318. Specimens …

3d Face Modeling From 2d Images Using Deep Neural Networks, Mario Alberto De La Cruz Armendariz

Open Access Theses & Dissertations

Applications of 3D face reconstruction include biometric authentication, personalized avatars and digital identity, medical visualization, forensic analysis, and broader human-computer interaction. We propose an approach to 3D face reconstruction that can generate a fully textured 3D facial model using only two grayscale images: a front view and a profile view of the subject. Once trained, the system can perform the reconstruction autonomously without manual intervention. Unlike traditional methods requiring multi-camera setups, depth sensors, or cloud-based processing, the proposed approach runs fully offline on a standard CPU, supporting dynamic execution across CPU cores and eliminating the need for a dedicated GPU. …

Design And Validation Of Model Predictive Controllers For Lateral Vehicle Control, Keren Flores

Open Access Theses & Dissertations

This thesis develops, implements, and evaluates a Model Predictive Control (MPC) framework for lateral vehicle guidance using a linearized bicycle model. The complete control architecture is formulated from first principles, beginning with the derivation of the continuous-time planar dynamics and their conversion into a discrete-time state-space representation suitable for real-time control. The MPC problem is constructed explicitly through the development of prediction models, output selection matrices, and quadratic cost formulations. The controller is evaluated through a Python simulation environment that includes reference trajectory generation, nonlinear vehicle propagation, and constraint handling. Robustness is examined using systematic perturbations to vehicle mass, tire …

Microgrid Assessment And Ml-Based Power System Faults Detection Leveraging Real-Time Co-Simulation, Diego Normando Gandara Mendez

Open Access Theses & Dissertations

The rapid growth of distributed energy resources (DERs) and the increasing reliance on data-driven decision making have reshaped the operational challenges of modern electric power systems. As microgrids become more prominent in distribution networks, utilities require methods that unify planning, control, and real-time situational awareness to ensure resilient operation under faulted or uncertain conditions. The goal of this MSEE thesis is to design and validate a latency-aware ML framework for rapid, reliable fault detection in distribution grids. To achieve the goal of the thesis, there are three specific objectives. Objective 1 evaluates optimized microgrid configurations under varying DER levels and …

Exploring The Impact Of Stem Degree Attainment On Intragenerational Social Mobility Among Hispanic Students And Graduates In Two Texas-Mexico Border Universities, Pilar Gonzalez

Open Access Theses & Dissertations

This research employed a two-phase, sequential, explanatory, mixed-methods design to answer the research questions. The first research question examined how obtaining a Science, Technology, Engineering, and Mathematics (STEM) higher education degree affects the socioeconomic advancement of current Hispanic students and alumni of the Louise Stokes Alliance for Minorities in Participation (LSAMP) within the context of two higher education institutions located along the Texas-Mexico border. The second research question explored the determinants shaping the professional pathways of Hispanic STEM students and graduates in the geographic vicinity of the Texas-Mexico border. For this study, STEM degrees refer to those recognized by the …

Lamda: A Longitudinal Android Malware Dataset For Benchmarking Concept Drift Detection And Adaptation, Md Ahsanul Haque

Open Access Theses & Dissertations

Machine learning (ML)-based malware detection systems often fail to account for the dynamic nature of real-world training and test data distributions. In practice, these distributions evolve due to frequent changes in the Android ecosystem, adversarial development of new malware families, and the continuous emergence of both benign and malicious applications. Prior studies have shown that such concept drift—distributional shifts in benign and malicious samples—leads to significant degradation in detection performance over time. Despite the practical importance of this issue, existing datasets are often outdated and limited in temporal scope, diversity of malware families, and sample scale, making them insufficient for …

Comparison Of Ti-6al-4v Powder And Bulk Specimen Properties Across Manufacturers In Laser Powder-Blown Ded, Alejandro Javier Hernandez

Open Access Theses & Dissertations

The investigation and comparison of 4 different Ti64 powder feedstocks from 3 different manufacturers was done to determine if the quality of the powder had a profound effect on the properties of the bulk specimens despite using the same processing parameters. The characteristics of the powder observed are the atomization process used, particle size distribution, flowability, and its density. The Ti64 printing parameters for directed energy deposition that were kept consistent were the feed rate, scanning speed, and laser power. Coupons with varying build angles (0-30°) were printed to measure the impact of overhangs on bulk specimen properties (ultimate tensile …

Phishibl: A Systematic Evaluation Of Instance-Based Learning Model For Predicting Phishing Susceptibility, Shova Kuikel

Open Access Theses & Dissertations

Despite enormous efforts to develop defenses against phishing attacks, humans still struggle to detect phishing emails given the constantly evolving attacker strategies. This thesis aims to test the predictive capabilities of a cognitive model that represents the individual susceptibility to phishing emails. While training programs aim to raise awareness, most remain outdated and ineffective against evolving attack strategies. Recent advances in Machine Learning, Artificial Intelligence, and Large Language Models (LLMs) offer new defenses, yet understanding human decision processes remains crucial, as effective systems must emulate how people evaluate unfamiliar emails based on prior experience. This research introduces a cognitive model …