Digital Commons Network^™

Optimizing Marketing Campaigns To Maximize The Response Rate For A Supermarket Using Machine Learning Techniques, Alia Almansoori

Theses

Supermarkets must improve their marketing tactics at a time of changing consumer behavior and increasing competition in the retail industry. Engaging the wide and sophisticated consumer base of today's supermarkets is difficult using traditional methods. This proposal presents a data-driven approach using cutting-edge machine learning methods to enhance supermarket marketing strategies. The main goal is to increase the response rate of marketing initiatives, which will improve consumer engagement and ultimately increase revenue. Additional primary objectives are customer segmentation and targeting, predictive modeling, personalization, ongoing performance monitoring, and ROI evaluation. The current problem centers around personalization and accuracy. Due to the …

Predicting Student Academic Performance Using Behavioural And Parental Engagement Data From Learning Management Systems, Saeed Alfalasi

Theses

This paper explores how behavioral, academic, and parental engagement data provided within the xAPI-Edu-Data dataset can be used to predict the academic performance of students when training on machine learning models with supervised learning. Due to the developing demands of the data-driven initial selection of the learners under risk, the study will create a valid and explainable predictive model that can consider the most significant factors of student success in Learning Management System (LMS). The research is based on behavioral engagement and self-regulation learning theories; the observations included in the analysis of student interaction, i.e. resource usage, classroom engagement and …

Cochlear Micropump Drug Delivery System: A Noninvasive Technique For Murine Intracochlear Drug Delivery, Janette Collins

Theses

In a 2018 World Health Organization (WHO) study, over 400 million people worldwide were affected by hearing loss (World Health Organization, 2023). Cochlear implants have provided a conventional route to aid inner ear issues but are ineffective either delivering to unintended targets or delivering unknown concentrations of a particular drug and create toxicity to the user. With medical advances and using 3-D printing technology, new opportunities to use programmable drug delivery systems to treat auditory disorders have been created. Borkholder Labs in Rochester, NY have created and improved a miniaturized implantable and scalable peristaltic micropump that provides programmable and accurate …

Predicting Undergraduate Fallout And Success, Ammar Ahmed Alzarooni

Theses

Universities need to uncover students who are likely to drop out early and do something about it. It should be easy to find and use this information. This thesis evaluated interpretable machine-learning models (MLMs) for predicting three final student outcomes including Dropout, Enrolled and Graduate, using solely demographic, administrative/financial and first-semester academic variables. Study employed publicly accessible Portuguese UCI student retention dataset (4,424 records) and incorporated end-of-Semester-1 feature window to prevent look-ahead leakage and align with actual advising cycles. We trained and compared models using stratified validation, explicit class-imbalance handling and decision-threshold optimization to make dropout detection most critical factor. …

Leveraging Open-Source Llms For Infrastructure Drift Detection And Correction, Kemoy S. Campbell

Theses

Infrastructure as Code (IaC) enables organizations to provision and manage infrastructure at scale using version-controlled, declarative specifications. Despite these advantages, infrastructure drift where deployed resources diverge from their intended configuration remains a persistent operational challenge and is often addressed manually and reactively. Recent advances in Large Language Models (LLMs) have accelerated their adoption within software engineering and DevOps workflows; however, the sensitive nature of IaC artifacts, particularly Terraform state files, has limited organizational willingness to rely on public LLM services for drift detection and remediation. This thesis investigates the feasibility of using open-source, self-hosted LLMs to assist with IaC drift …

Enhancing Json Schema Inference Via Semantic And Structural Modeling Of Heterogeneous Data, Justin R. Namba

Theses

Schema discovery is finding the structure of data. It helps users understand the meaning of data and write queries to manipulate it. This is typically easy for relational databases, but complex for non-relational (NoSQL) databases with documents. For relational databases, the schema is predefined because the data they contain is structured, but for NoSQL databases, data is usually unstructured or semi-structured. Here, we focus on a type of semi-structured data called JSON, which is a collection of documents that consists of nested key-value pairs. A JSON key and value are similar to a column name and its associated data instance …

Statistical Optimization And Anfis Modeling Of Process And Heat Treatment Effects In Gmaw-Waam 316l Stainless Steel, Joel Sam John

Theses

Additive manufacturing has evolved from the concept of merely rapid prototyping tools to that of a viable technology capable of manufacturing industrial grade parts and components. As a result, the use of metal additive manufacturing techniques has expanded in recent years, fueled by the rapid growth of manufacturing sectors amidst the 4.0 industrial revolution. Within the metal-AM domain, the concept of gas metal arc welding – wire arc additive manufacturing (GMAW-WAAM) has gained increasing traction due to its low operational costs, high deposition rates, and its ability for large scale manufacturing.  The demand of stainless-steel parts has increased owing to …

Novel Insights Into Early Alzheimer's Disease: Quantitative Gradient Recalled Echo Mri Reveals Preatrophic Neuronal And Myelin Injury Concurrent With Emerging Amyloid Pathology, Satya V V N Kothapalli, Tammie L S Benzinger, Randall J Bateman, Melody Li, Cihat Eldeniz, John C Morris, Dmitriy A Yablonskiy

2020-Current year OA Pubs

BACKGROUND: Brain amyloid accumulation is considered an early sign of Alzheimer's disease (AD) pathology, appearing decades before manifestation of clinical symptoms. However, very little is known about neurodegeneration during this early AD stage. Herein we use quantitative gradient recalled echo (qGRE) magnetic resonance imaging (MRI) to reveal preatrophic microstructural neuronal and myelin damage concurrent with amyloid pathology.

METHODS: qGRE MRI and positron emission tomography (PET) amyloid [

RESULTS: qGRE detected significantly lower gray matter neuronal density and white matter myelination in the group of participants with amyloid level below the conventional amyloid-positive threshold (mean cortical standardized uptake value ratio of …

Biological Aging Acceleration In Major Depressive Disorder: A Multi-Omics Analysis, Breno Satler Diniz, Shangshu Zhao, Gabin Drouard, Eero Vuoksimaa, Miina Ollikainen, Eric J Lenze, Ming Xu, Richard H Fortinsky, George A Kuchel, Jaakko Kaprio, Chia-Ling Kuo

2020-Current year OA Pubs

Major depressive disorder (MDD) is linked to a higher risk of premature aging, but the mechanisms underlying this association remain unclear. Using data from two population cohorts (UK Biobank and Finnish Twin Cohort), we evaluate the relationship between systemic and organ-specific proteomic and epigenetic aging acceleration and MDD. A lifetime history of MDD was associated with accelerated proteomic aging at both systemic and organ-specific levels-including the brain-in both cohorts, with stronger associations than those observed with systemic epigenetic aging. Systemic and brain-specific proteomic aging acceleration were linked to higher risks of incident MDD and a greater risk of Alzheimer's disease, …

Antihypertensive Medications And Risk Of Alzheimer's Disease: Evidence For Specific Medication Use, Osvaldo J. Laurido-Soto, Alejandra Camacho-Soto, Irene M. Faust, Kassu M. Beyene, Aaron Katz, Jordan A. Killion, Brad A. Racette

2020-Current year OA Pubs

No abstract provided.

Participatory Systems Modeling In Implementation Research: Exploring Benefits, Facilitators, And Future Needs, Natalie Riva Smith, Jennifer L Cruz, Jessica Gannon, Stephanie Mazzucca-Ragan

2020-Current year OA Pubs

BACKGROUND: Implementation science increasingly uses participatory systems modeling (PSM) approaches to handle the complexity inherent to implementation science issues. To support the process of integrating PSM with implementation science, we aimed to understand and explicate the benefits, facilitators, and future needs of applying PSM to implementation research.

METHODS: We conducted semi-structured qualitative interviews with 23 researchers (n = 18) and practitioners (n = 5). We purposively sampled participants and identified additional participants through recommendations. Interviews were inductively analyzed. Key concepts were identified via iterative description, comparison, and conceptualization.

RESULTS: Engagement with people in the system was typically focused in earlier …

Relationship Among Sleep Disturbance, Stress, And Suicidal Ideation In Clinical High Risk For Psychosis, Heather M Wastler, Daniel Mamah, Et Al.

2020-Current year OA Pubs

BACKGROUND AND HYPOTHESIS: Sleep disturbance is a well-established risk factor for suicide, though few studies to date have examined whether sleep disturbance contributes to suicide risk among individuals at clinical high risk for psychosis (CHR). The current study addressed this gap in the literature. We hypothesized that sleep disturbance would have a unique relationship with suicidal ideation/attempts when accounting for other variables in the model. We also hypothesized that the interaction between sleep disturbance/attenuated positive symptoms and sleep disturbance/stress would be related to suicidal ideation/attempts in CHR.

STUDY DESIGN: The current study used data generated by the Accelerating Medicines Partnership® …

Experimental Investigation Into The Effects Of Air Staging On Fouling In A Fixed-Bed Biomass Combustor, Akram Elsebaie

Theses: Doctorates and Masters

Biomass offers significant potential as a sustainable and renewable substitute for fossil fuels in energy generation, playing a critical role in the reduction of global warming. However, despite its environmental benefits, biomass combustion faces persistent operational challenges, particularly fouling, which reduces efficiency and increases maintenance costs. Although fouling mechanisms have been studied in various combustion systems, there is limited research which addresses its formation and behaviour in fixed-bed biomass combustors under different air staging conditions. This research investigates fouling behaviour in a counter-current combustor, focusing on the influence of design (secondary air location), operational (air staging flowrates between the primary …

Integrated Incubators: A Novel Framework For Technology-Based Creative Arts Education, Brad Phelps Nisbet

Theses: Doctorates and Masters

This thesis investigates the development and impact of an educational framework designed to bridge the gap between academia and industry within the media and entertainment sector. It addresses the prevalent "skills mismatch" where graduates often lack the specific technical competencies, foundational knowledge, practical experience, or soft skills required for entry-level positions in a rapidly evolving landscape influenced by advancements like virtual production, real-time VFX, immersive media, and Al. Grounded in both theoretical and practical insights, the framework aims to foster student creativity, technical proficiency, industry readiness, transferable skills, and adaptability, prioritising a transformative, student-centric learning experience.

The research employed a …

Study Of Fire Regimes In Southwestern Australia Using Geospatial Techniques, Ana Do Carmo Carvalho

Theses: Doctorates and Masters

The Northern Jarrah Forest in Southwestern Australia (SWA), part of a global biodiversity hotspot, is home to fire-sensitive tree species such as marri (Corymbia calophylla) and jarrah (Eucalyptus marginata). As climate change intensifies drought and extreme fire events, understanding the drivers of fire severity is increasingly critical. This thesis analyses fire regimes within the Mundaring drinking water catchment to better understand the spatiotemporal complexity of fire severity in relation to fire history and environmental factors.

The thesis commences with a review of three Fire History Databases (FHDs) used in SWA, highlighting significant inconsistencies and data gaps across time and space. …

Development Of Virtual Reality Learning Environments In Science To Engage Secondary Students In Hazardous Activities, Luke Spartalis

Theses: Doctorates and Masters

This research examines the need for change in including hazardous activities in education. As different learning technologies develop, platforms that retain authentic outcomes via virtual reality are needed. The main objective of this research is to examine the inclusion of Virtual Reality Learning Environments (VRLEs) to determine their value in areas that include hazardous conditions. The research considered the ways that VR tools could be optimised to support these activities, as well as considering the challenges of VRLE implementation. The study examined whether VRLE’s allowed for authentic experiences to sufficiently drive an acceptance of VR to complement existing teaching and …

Enhancing Deep Reinforcement Learning With Expert Demonstrations For Mobile Robot Navigation In Unstructured Off-Road Environments, Dulitha Dabare

Theses: Doctorates and Masters

Advancements in the field of Deep Learning has ushered in a boom in autonomous navigation research. Most of the work being conducted in this space, however, has focused on on-road urban navigation scenarios, with unstructured outdoor terrain navigation receiving much more limited attention. Given the wide range of applications that exist for legged and wheeled ground robots in off-road environments in areas such as agriculture, mining and disaster recovery, there is a growing need for research work to improve the navigational capabilities of mobile robots deployed in these challenging environments.

A promising candidate for application to these navigation challenges in …

Emotional Coding In Wolfgang Amadeus Mozart’S Music: The Influence Of Text-Driven Musical Patterns, Antonio Toppi

Theses: Doctorates and Masters

This thesis investigates the phenomenon of emotional coding in the music of Wolfgang Amadeus Mozart (1756–1791), with particular attention to the ways in which text-driven musical patterns influence both vocal and instrumental works. The study draws on 18th-century theories of key characteristics, musical-rhetorical figures, and topoi, compositional devices that carried emotional implications for contemporary listeners. These codes are first examined in two of Mozart’s operas, Le Nozze di Figaro (KV492) and Don Giovanni (KV527), where the setting of text to music provides a framework for associating compositional choices with emotion. Findings from the analyses are then applied to three contemporaneous …

Patient Experiences Of Receiving Home-Based Immunotherapy Infusions - A Constructivist Grounded Theory Study, Patricia Ann Cook

Theses: Doctorates and Masters

Context: The treatment of cancer and chronic health conditions has been greatly revolutionised via intravenous immunotherapy infusions. Demand, both globally and in Australia, is increasing due to several factors including aging and increased populations, subsequent increases of cancer cases, new immunotherapy indications and increased survival rates.

In Perth, Western Australia, a private service provider commenced delivering a home based immunotherapy infusions model of care as a hospital substitution service provider in 2013 and the service has now been extended across Australia. The safety and efficacy of home-based infusions have been well documented in research, and an increasing number of patients …

Multimodal Scene Understanding For Mobile Robot Navigation In Unstructured Outdoor Environments, Liyana Mudiyanselage Nipuna Dinendra Wijayathunga

Theses: Doctorates and Masters

The application of autonomous field robots in agriculture, mining, transport and logistics, disaster management, and exploration has increased with advances in sensing, perception, and autonomous navigation technologies. Western Australian off-road environments present challenges for autonomous ground robots because they contain unstructured ter rain, variations in appearance and geometry, changing illumination, and visually similar regions with different traversal characteristics. Reliable operation therefore requires scene understanding methods capable of representing the environment according to its navigability for robot traversal.

This PhD research investigates multimodal scene understanding for autonomous ground robot navigation in unstructured off-road environments. The research focuses on the development of …

Epithelial-Mesenchymal Transition And Stress Adaptations Underlie Yttrium-90 Resistance In Liver Cancer Cell Lines, Alexander Zheleznyak, Dhanusha Duraiyan, Prasanth Thunuguntla, Jessica Camacho, Shuang Wu, Jingxia Liu, Jason D Weber, Daniel L J Thorek, Benjamin S Strnad, Ryan C Fields, Matthew A Ciorba, Christine Yoon, Valerie Blanc, Nicholas Davidson, Jessica Silva-Fisher, Christopher D Malone

2020-Current year OA Pubs

UNLABELLED: Molecular signatures predict prognosis in hepatocellular carcinoma, but their relevance to transarterial radioembolization (TARE) with yttrium-90 (90Y) is unknown. We aimed to identify baseline and treatment-induced pathways associated with response and nominate biomarkers. Ten transcriptomically diverse human liver cancer cell lines were exposed to escalating activities of glass 90Y microspheres for 10 days. Normalized AUC values quantified sensitivity. Whole-transcriptome RNA sequencing at baseline and after treatment was analyzed with elastic net regression and gene set enrichment. Findings were corroborated by qRT-qPCR and exploratory analysis of pretreatment tumor samples from patients undergoing TARE. Liver cancer cell line responses to 90Y …

Investigating The Potential For First Year Residential Field Courses To Facilitate The Establishment Of Teacher-Student Relationships In Biological Sciences Undergraduate Degrees, Anne Plessis, Alison Stokes

School of Biological and Marine Sciences

Teacher-student relationships (TSRs) in higher education impact many aspects of the student experience, including engagement and performance. However, relatively little is known about the mechanisms of establishment of TSRs, and in particular how these are influenced by specific learning environments and contexts. Here, we undertake an exploratory investigation using first year biological sciences undergraduate residential field courses to examine how this teaching context affected the frequency and nature of teacher student interactions, and consequently the development of TSRs. Data were collected from teacher and student participants using questionnaires and focus groups. We found that interactions during fieldwork took place frequently …

Post-Release Mortality Of European Bass (Dicentrarchus Labrax) Discarded From Small-Scale Estuarine Fishing, J. E. Stewart, T. Stamp, P. Davies, A. Hall, T. Robbins, L. Stewart, E. V. Sheehan

School of Biological and Marine Sciences

Estuaries provide essential habitats for many fish species, but their confined and accessible nature may increase fish vulnerability to capture, and few empirical studies have quantified the value of restricting net fisheries in such areas. Furthermore, management measures for some fisheries promote discarding (e.g., of European sea bass; Dicentrarchus labrax), yet the mortality of fish discarded from small-scale inshore fisheries is poorly understood. We used condition assessments, Reflex Action Mortality Predictor scores and acoustic tracking to evaluate post-release mortality of bass captured in small-scale estuarine netting and angling. Gillnet-caught bass exhibited a range of stress responses and 20%–24% mortality shortly …

Investigating Spatial And Seasonal Differences In Microgastropod Assemblages Within The Little-Studied Camamu Bay, Brazil: A Potential Bioindicator For Remote Tropical Areas?, Francisco Kelmo, Sol De Maria Cesar Ferreira, Eduardo Henrique Galvão, Martin J. Attrill

School of Biological and Marine Sciences

This study investigates spatial and seasonal variation in the assemblages of benthic microgastropods (snails < 5–10 mm in length) within a poorly studied tropical bay. As these organisms are abundant, diverse and relatively easy to sample, with well-established taxonomy, they may prove a highly suitable group for ecological studies in such areas. Sediment samples were collected from three river basins in Camamu Bay, Brazil, during the wet and dry seasons. A total of 132 microgastropod species was recorded, demonstrating high diversity. The most abundant species were Eulithidium affine, Bittiolum varium, Cerithium atratum, Vitta virginea and Schwartziella bryerea. The least abundant species were Tenaturris gemma, Turbinella laevigata, Petaloconchus erectus, Parviturboides interruptus and Vitrinella cupidinensis. Statistical analysis revealed significant seasonal and spatial differences in diversity and assemblage composition, which correlated with environmental gradients. The results suggest that microgastropods are a suitable component of the biota for ecological and applied studies in marine sediments, particularly in remote tropical locations where full macrofaunal analysis may be challenging. Whilst further testing across impact gradients is needed, this approach offers a practical solution for ecological investigations in remote regions with limited taxonomic expertise and highlights microgastropods as a useful indicator taxon for impact biomonitoring in tropical marine sediments.

From Predictions To Explanations: Explainable Ai For Autism Diagnosis And Identification Of Critical Brain Regions: 18th International Joint Conference, Biostec 2025, Kush Gupta, Amir Aly, Emmanuel Ifeachor, Rohit Shankar

School of Engineering, Computing and Mathematics

Autism spectrum disorder (ASD) is a neurodevelopmentalcondition characterized by atypical brain maturation. However, the adaptationof transfer learning paradigms in machine learning for ASD researchremains notably limited. In this study, we propose a computeraideddiagnostic framework with two modules. This chapter presents atwo-module framework combining deep learning and explainable AI forASD diagnosis. The first module leverages a deep learning model finetunedthrough cross-domain transfer learning for ASD classification. Thesecond module focuses on interpreting the model’s decisions and identifyingcritical brain regions. To achieve this, we employed three explainableAI (XAI) techniques: saliency mapping, Gradient-weighted Class ActivationMapping, and SHapley Additive exPlanations (SHAP) analysis.This framework demonstrates that …

Investigating Policy Enactment In Community Sport Coaching: Directions For Future Research, Ben Ives, Dawn Penney, Jimmy O’Gorman, Adam J. Nichol, Paul Potrac, Lee Nelson

Research outputs 2022 to 2026

This article calls for a sophisticated investigation of policy enactment in sport-related environments, with community sport coaching used as an example case. Emphasis is placed on the need for in-depth empirical research into and theorisation of: 1) political skills involved in the enactment of policy; 2) emotion management when enacting policy; 3) performative and fabricated aspects of policy enactment; and 4) impacts of policy enactment for the health and wellbeing of workers. In doing so, this article challenges scholars to move beyond the study of policy actor types and to develop more nuanced understandings of the political, economic, organisational, interpersonal, …

Generative Imaging For Computational Pathology, Md Jillur Rahman Saurav

Computer Science and Engineering Dissertations

Hematoxylin and eosin (H&E) staining remains central to cancer diagnosis, providing morphological information essential for pathological assessment. Immunohistochemistry (IHC) and newer multiplexed imaging technologies complement H&E by revealing molecular information critical for accurate tumor subtyping and treatment decisions. In practice, however, H&E and IHC are obtained from different consecutive sections that are not spatially aligned, comprehensive multiplexed panels are expensive and tissue-consumptive, and not all stains are available at every clinical site, limiting comprehensive molecular profiling and the full diagnostic potential of these technologies in clinical practice. This dissertation addresses these gaps through three complementary generative deep learning studies in …

Density And Fiber Alignment Of The Fibrous Extracellular Matrix In Ovarian Cancer Metastases, Rachel Glantzberg, Aditi Singh, Mohammad Asghar Qanit

Wetterhahn Science Symposium Posters

The primary aim of this project is to improve and justify biophotonic approaches to label-free, non-invasive cancer detection, particularly within the context of peritoneal metastases from ovarian cancer. Ovarian cancer often metastasizes to the peritoneum, resulting in microanatomical changes in collagen and elastin fiber direction and density. While prior research has provided insights regarding collagen density changes in other types of cancer, peritoneal metastases from ovarian cancer remain minimally characterized, particularly in regards to elastin fibers. Preliminary results suggest that there is a difference in the elastin and collagen contents of healthy and cancerous tissues and that these contents differ …

Preliminary Observations From The Relativistic Electron Atmospheric Loss (Real) Satellite Mission, Evzen Selvon, Robyn Millan

Wetterhahn Science Symposium Posters

The Relativistic Electron Atmospheric Loss (REAL) spacecraft (launched in July 2025) is a 3U cubesat designed to measure the precise energies (1 keV – 2MeV) and pitch angles of electrons entering the Earth’s ionosphere. The mission involves Dartmouth, BU, JHUAPL, MSU, and NASA. REAL carries three particle sensors measuring low, medium, and high energies. This work is focused on the ElectroStatic Analyzer (ESA) instrument, designed to measure lower energy electrons (1-40 keV) in the directions parallel and perpendicular to the Earth’s magnetic field. This research aims to identify notable events observed by the REAL spacecraft for future analysis.

When Machines Collude: Rebooting Antitrust Law For The Age Of Algorithmic Markets, William K. Knight

Emory Law Journal

Increasingly, our lives are being dominated by algorithms. From social media feeds to credit scoring, algorithms play a major role in our day-to-day lives, whether we recognize it or not. An emerging issue in the modern technology landscape is the potential for algorithms to cause anticompetitive harm to free markets. As pricing algorithms become more advanced and more widespread, they could facilitate collusive arrangements in a manner that bypasses antitrust laws, thereby adversely impacting consumers through higher prices. American competition law, primarily governed by the Sherman Antitrust Act, suffers from glaring deficiencies and ambiguities that remain unresolved, leaving it manifestly …