Digital Commons Network^™

An Evaluation Of The Idm Car-Following Model : Simulation And A Dynamical Systems Perspective, Trevor Mcclain

Theses

The Intelligent Driver Model (IDM) is a car-following model that has existed since the early 2000s, existing as one of the most widely used follow-the-leader models to simulate safe and realistic driver behavior. In this work, the IDM is used to evaluate the suitability of ROS 2-Gazebo for vehicle simulation, showing that significant non-determinism is present within the simulation. Additionally, we evaluate the effects of delay and an inserted Followerstopper car following model on the traffic dynamics of the system. Specifically, the generation of stop-and-go waves in idealized traffic from a dynamical systems perspective is examined. We also show that …

A Study Of Neural Compression Techniques For Image Compression Using A Novel Algorithmic Lossless-Ness Criteria, Abhishek Prasanna Simha

Theses

Neural compression methods claim near-lossless reconstruction capabilities based on traditional metrics such as PSNR and MS-SSIM. However, their impact on downstream machine learning tasks remains largely unexplored. This thesis evaluates three state-of-the-art CompressAI models (Cheng2020-anchor, bmshj2018-hyperprior and mbt2018 ) on high-resolution satellite imagery using semantic segmentation as a downstream task benchmark. We introduce the idea of algorithmic losslessness with respect to a downstream machine learning task and use it to benchmark existing state-of-the-art neural compression algorithms. We also compare the results with non-neural compression techniques. We conducted experiments on 11 urban satellite images using two segmentation approaches: MMSegmentation (7 classes) …

A Comparative Study Of Classical And Deep Feature Learning Methods For Prediction Of User Request Patterns For Cloud Resources, Swaroopa Ammenadka

Theses

Large-scale cloud storage systems managing petabyte-scale data face cost challenges due to sparse, irregular file access patterns. Traditional attribute-based methods often fail to capture dynamic temporal and event-driven behaviors. This thesis compares classical statistical and deep learning approaches for predicting file access patterns using five months of real-world access logs from Tsinghua University’s FTP server (2.9 million events). Five forecasting models—ARIMA, SARIMA, Exponential Smoothing, Prophet, and 1D CNNs—are evaluated across 1,161 files. A novel hybrid clustering method combines time series similarity with forecasting accuracy metrics. Results show ARIMA significantly outperforms deep learning (2.3× better accuracy: 0.0188 vs. 0.036 MAE) for …

Upper And Lower Body Volume-Equated Resistance Exercise Increases Post-Exercise Lipid Oxidation In Trained Eumenorrheic Females., Alyssa L. Parten, Abbie E. Smith-Ryan, Eric K. O'Neal, T Scott Lyons, Hunter S. Waldman

Theses

Exercise strategies targeted to increase lipid oxidation (LOx) in the resting state present an opportunity to optimize long-term metabolic health. However, research examining the effects of resistance training (RT) on LOx in females remains scarce, particularly with no studies yet examining whether differences exist in LOx between upper and lower body RT. This study examined LOx changes following volume-load equated upper and lower body RT in well-trained, eumenorrheic females. Twenty-two (age: 25.4 ± 5.6 years, BMI: 24.6 ± 2.7) females completed a 3-repetition-maximum (RM) and 1RM test for the barbell back squat (BS) and bench press (BP), respectively. From these …

Jamaica: The Stories We Never Told, Vinnette Gibson

Theses

Jamaica: The Stories We Never Told is a memoir project that describes the realities of Jamaican life through personal narratives that detail the cultural and social nuances of Jamaican experiences. Its purpose is to broaden the global perception of Jamaican culture beyond tourism, beaches, music, and sports by representing everyday realities of Jamaican life, often overlooked by the global community. It details multifaceted experiences, including challenges and positive encounters, the transition from youth to adulthood, and complex emotions throughout. This project documents the author’s lived experiences and reveals cultural nuances, including friendships, family dynamics, and the use of Patois to …

Digital Threads: Fashion Design With Clo3d, Maya Herring

Theses

CLO3D (CLO) has emerged as a prominent software service within the fashion industry, molding the conceptualization and development of 3D fashion designs. By eliminating the constraints of customary manufacturing processes and real-life production costs, CLO equips designers with tools to bring their fashion garments and designs to life. This study aims to explore the capabilities of CLO software by developing five digital bridal dresses while also examining the learning curve, challenges, and benefits associated with its usage. The objective is to identify how CLO can provide aspiring fashion designers with the tools to produce high-quality designs without traditional training.

By …

Estimating Surface Sulfur Dioxide Concentrations Over Eastern China Using Omi Satellite Data, Zachary Watson

Theses

Sulfur dioxide (SO2) is a key air pollutant as it contributes to negative health effects, acid rain, and aerosol formation. Using satellite data to monitor surface SO2 concentrations can fill in the gaps of ground-based air quality networks in less populated areas. In this study, SO2 retrievals from the Ozone Monitoring Instrument (OMI) were employed to estimate annual and seasonal average surface SO2 concentrations over eastern China, a major anthropogenic source region, from 2015 to 2018. The OMI-derived surface SO2 concentrations had a similar spatial distribution and temporal trends as ground-based measurements from an air quality monitoring network, but they …

Concentrated Benefits And Dispersed Costs: The Contributions Of Pareto, Olson, And Ostrom, Nathan John Cuthbertson

Theses

Concentrated benefits and dispersed costs (CBDC) is a central concept in the field of public choice as well as economics more broadly. The phrase concentrated benefits and dispersed costs refers to a situation in which economic benefits are concentrated and the associated costs are borne by a larger group. This thesis argues that the elements of CBDC are common in the literature without the term being used directly. This study is an exercise in the history of economic thought. The study is structured into three case studies, with each dedicated to the work of an influential economist: Vilfredo Pareto (1848-1923); …

Negotiating With-Ness: Midwives' Lived Experiences Of Gender, Inclusive Language, And Professional Identity., Kimberley-Ann De Wet

Theses

This research investigated midwives lived experiences of using gender-inclusive language in public maternity care, examining how linguistic practices intersect with professional identity, ethical commitment, and institutional constraint. Informed by feminist theory and guided by descriptive phenomenology with a constructivist paradigm, the study explored how midwives navigate the profession’s foundational ethos of being ‘with woman’ while responding to the ethical imperative to provide inclusive care in an increasingly diverse society. Semi-structured interviews were conducted with eight practising midwives in Western Australia, generating rich descriptions of how inclusive language is enacted, negotiated, and constrained in practice. Reflexive thematic analysis produced three overarching …

Sigrid Undset: Nordic Catholic Apologist, Brendan Edward Arthur

Theses

This thesis explores the depth and breadth of Sigrid Undset’s non-fiction Catholic writing, a substantial body of work that has largely remained inaccessible to all but readers of Norwegian. Through original translations and analysis, it synthesises these texts into broad themes while situating them within their historical contexts of the intellectual and cultural debates in early twentieth-century Norway. The study addresses three research questions: (1) the general themes in Undset’s Catholic non-fiction; (2) the contemporary relevance of these writings; and (3) whether Undset merits the designation “Catholic apologist.” In its method, the thesis employs textual analysis of Undset’s essays, articles …

Motherhood Or Work: Why Not Both? Representations Of Femininity In Australian Wartime Radio Serials, Emma Price

Theses

War is a gendering activity. As media is one of the many sites where gender is constructed, this study aims to investigate through a discourse analysis of serials produced by women for radio in the 1940s, the ways these programs represented or challenged social and cultural expectations placed on women. The themes female dramatists explored through the genre of radio serials, and the statements these programs made about life as a woman during the Second World War, are under-researched areas in Australian scholarship. While it must be acknowledged that the war was not a turning point in the status of …

A Framework For Mixed Reality Within Healthcare Education, Benyamin Ebadinia

Theses

Understanding complex three-dimensional systems and spatial relationships is a recurring difficulty in healthcare education, where students are often expected to reason about internal structures and multi-system processes from 2D diagrams, textbook figures, and static mannequins. This thesis presents the design, implementation, and mixed-methods evaluation of Systems Simulation, a reusable mixed reality (MR) application intended to help undergraduate nursing students explore human anatomy and pathophysiology using immersive 3D visualization.

Built in C# with the StereoKit framework for Microsoft HoloLens 2, Systems Simulation organizes nine anatomical body systems within a shared application. Learners can select a system, anchor the model in their …

Leadership In The Digital Economy: An Investigation Into How Digitalisation Is Changing The Role And Practice Of Leadership In The Australian Defence Industry, Rhogan Aitken

Theses

Digitalisation is a phenomenon that is transforming society and is the process that moves an organisation to become digital. Research was conducted on senior leaders in the Australian defence industry with the purpose of investigating how the role and practice of leadership was changing because of digitalisation. A two-phased qualitative methodology was employed. An initial Delphi study on 13 experts in digital transformation was adopted to gain consensus on key issues, with the results informing a second stage of semi-structured interviews with 32 senior leaders in the Australian defence industry. The results identified factors that were influencing leadership, including increased …

Gai Research - A Case Study On The Implications Of Generative Artificial Intelligence (Gai) On Teaching Within An Irish Technological University., Moya Cronin

Theses

The rapid emergence of Generative Artificial Intelligence (GAI) has introduced a transformative age of technology, gaining prominent attention in higher education. This mixed-methods case study examined how GAI was understood, applied, and managed within an Irish Technological University at a time of turbulence when no official GAI policies were available as a point of reference. Lecturing and research staff were invited to participate in an online survey (𝑛 = 145) and semi-structured interviews (𝑛 = 8) to share their experiences with GAI technology within the case study university. Lack of guidance was seen to affect staff’s confidence and adoption, but …

Internet Of Things (Iot) In Developing Smart City Traffic Management Systems In Dubai, Ayesha Ahmed Alnuaimi

Theses

Traffic congestion is an ever-present problem affecting most cities, negatively affecting the economy, the environment, and people’s quality of life. Dubai is one of the rapidly growing cities in terms of urbanization and the usage of technologies, and it is aware of the ability of IoT to design intelligent city traffic control systems to resolve this problem. Consequently, this study sought to assess the implication of IoT in improving traffic management systems within the Emirate of Dubai, gleaning data concerning the factors that have a direct impact on the implementation of the IoT, the challenges, and barriers met during the …

Surveillance Report​: Che-Wei Hsu​, Che-Wei Hsu

Theses

Face ID: A Surveil of Che-Wei Hsu is a lens based artistic investigation and experience into the nature of surveillance in modern society. Through performance, photography, and installation, my work explores the dynamics between being watched and watching, questioning how surveillance influences human behavior and identity. In my art practice, I think about the behavior that people would not do in front of other people or violate the social norm and perform in the public as a way to experience how surveillance influences how we act in the public, for example eating a sandwich on the ladder in front of …

Machine Learning And Artificial Intelligence Models And Techniques In Modern Power Grid Communication Architecture, Majid Jamal Majid Salim Almheiri

Theses

Smart grid is evolving in different phases and artificial intelligence (AI) models are also the part of it. In the recent developments of Smart grid system there are research areas which are left unaddressed specifically in privacy techniques, scalability, more efficient data processing techniques. This Thesis highlights the research gaps on smart grid development across various integration phases. In the initial phase of Smart grid development, challenges included scalability issues in Machine-to-Machine (M2M) communication, communication delays affecting voltage stabilization and high computational costs in implementing Genetic Algorithm (GA)-based grid state estimation are covered in this review report. Review is further …

Towards Secure Runtime Auditing Of Remote Embedded System Software, Adam Ilyas Caulfield

Theses

Modern embedded systems are increasingly deployed in various settings to execute critical sensing/actuation tasks. At the lower end of the scale, they are designed with low-cost and energy-efficient microcontroller units (MCUs) that lack the common security features of general-purpose processors. To assess their state in a cost-effective manner, Control Flow Attestation (CFA) methods provide means for a trusted device operator (i.e., the Verifier -- Vrf) to detect attacks that compromise the integrity or runtime behavior of a remotely-deployed MCU (i.e., the Prover -- Prv). This is achieved by a root-of-trust (RoT) in Prv recording an authenticated trace (CFLog) of the …

Automated Prioritization And Routing Of It Support Tickets Using Machine Learning, Mohamed Almarzooqi

Theses

The increasing complexity of IT service management underscores the need for efficient and scalable solutions to manage IT tickets. This thesis explores the application of machine learning techniques for automated prioritization & routing of IT tickets. So by leveraging publicly available dataset from Kaggle containing IT ticket the study aims to reduce manual intervention, improve resolution times, & optimize resource allocation within IT environments. The study will evaluate various machine learning algorithms, including SVM, Random Forest, & ensemble models, for their ability to classify and prioritize tickets accurately. to accurately classify and prioritize tickets. Advanced data preprocessing techniques like TF-IDF …

Neuro-Evolution For Multivariate Time Series Anomaly Detection, Aryan Jha

Theses

Given the exponential growth of data in various sectors, the timely identification of anomalies has become crucial in mitigating risks such as financial losses and data breaches. This research focuses on advancing multivariate time series anomaly detection through the innovative application of neuro-evolutionary methods. Utilizing the Evolutionary eXploration of Augmenting Memory Models (EXAMM) algorithm, the study automates the design and optimization of Long Short-Term Memory (LSTM) autoencoder networks, enabling enhanced forecasting capabilities in recurrent neural network architectures. Leveraging these networks along with a One-Class Support Vector Machine (OCSVM) to generate boundary thresholds, this project delivers a robust and scalable procedure …

Uncertainty-Aware Meta-Learning For Learning From Limited Data, Deep Shankar Pandey

Theses

Deep Learning (DL) models have achieved great success in large data fields ranging from computer vision and natural language processing to digital arts and robotics. However, the effectiveness of the DL models is challenged by many real-world limited data problems (e.g., medicine, healthcare, and security intelligence) where data for model training is scarce. Unlike DL models, humans can use the prior knowledge stored in their brains to quickly learn new tasks with limited data. Inspired by such human learning, various meta-learning models have been developed that aim to address the challenge of learning from limited data. However, existing models are …

Fake News Detection In Arabic Media Using Machine Learning And The Afnd Dataset, Hussain Ali Bahri

Theses

The proliferation of fake news in digital media poses a significant challenge to information credibility, particularly in linguistically diverse regions such as the Arab world. This study addresses the critical problem of detecting fake news in Arabic media by leveraging advanced natural language processing (NLP) techniques and the AFND dataset, which contains over 600,000 news articles categorized into "credible," "not credible," and "undecided" classes. The research focuses on developing a robust system using AraBERT, a transformer-based model specifically pre-trained for Arabic text. Key contributions of this work include a comprehensive preprocessing pipeline tailored to Arabic linguistic complexities, incorporating stopword removal, …

Predictive Policing - Leveraging Cctv Data And Ai For Crime Hotspots, Maitha Ahmad

Theses

This thesis explores fine-grained sentiment analysis in the context of police social media posts, leveraging hybrid approaches to manage the rapid flow of big data and mitigate its negative impact on youth. As social media becomes a primary medium for public interaction, understanding sentiment within police-related posts is crucial for law enforcement agencies to gauge public opinion and address community concerns effectively. The rapid dissemination of information and the potential for negative sentiments to spread swiftly pose significant challenges, particularly for young audiences. The research begins with a comprehensive review of existing sentiment analysis techniques and their applicability to large-scale …

Predicting Bus Ridership In Dubai Using Advanced Machine Learning Models, Fatma Almheiri

Theses

In rapidly urbanizing cities, the public transport systems have to be efficient and reliable with proper demand forecasting to guarantee customer satisfaction. This paper explores how evidence-based machine learning tools can be used to forecast weekly bus ridership in Dubai, using a dataset of more than 10 million trip-level boarding observations between June 2013 and July 2014. It was aggregated to 25,195 route-week observations, and preprocessed with temporal feature engineering, lag variables and rolling statistics. Three predictive models have been tested: Linear Regression (as a baseline), Random Forest and XGBoost (as an ensemble method). Mean Absolute Error (MAE), Root Mean …

Aqualoop (The Four Stages Of Earth's Water Cycle), Precious Onwubuche

Theses

This research investigates the development of an educational initiative that illustrates the water cycle using real-life simulations and moving graphics targeting high school students and older audiences to connect theoretical knowledge with hands-on learning in Earth science education. The initiative utilises visual design strategies to turn intricate hydrological processes into an engaging educational journey. The significance of this project is underscored by statistics showing that fewer than 30 percent of secondary school students master Earth science principles, such as the water cycle. This is based on 2019 information from the National Assessment of Educational Progress (NAEP). Additionally, and notably, more …

Determinants Of Profitability In Uae Banks (2019-2023): An Analysis And Forecast For The Next Five Years, Rashed Aljanahi

Theses

This study aims to analyze the factors that led to the banks' profitability in UAE from 2019 to 2023 based on factors such as capital adequacy, asset quality, and liquidity. With these factors and Return on Assets, the study seeks to determine the link between the variables affecting financial performance in the banking sector. The study relies on quantitative data from UAE banks to include statistical analysis and construct predictive models. The relationships between the variables are established using Multiple Linear Regression. At the same time, Random Forest Algorithms explore Non-Linear Interactions and Time Series Analysis using ARIMA models to …

Leveraging Future Foresight And Planning In Human Resource Management: Preparing Organizations For The Workforce Of Tomorrow, Naser Althehli

Theses

As organizations face unprecedented uncertainty as they navigate a complicated and fast-changing world, the ability to anticipate and adapt to workforce shifts has become more crucial than ever. This thesis examines how future foresight and strategic planning in human resource management (HRM) can reinforce organizational adaptability and maintain a competitive edge. By analyzing key drivers of change—including technological advancements, demographic shifts, political dynamics, and socio-economic trends—the study identifies innovative HRM strategies that enable organizations to address emerging workforce challenges and opportunities proactively. Through a structured evaluation of foresight techniques, this research highlights best practices for cultivating a resilient and future-ready …

Structure/Property/Processing Of A 3d Printed Self-Healing Polymer Blend Based On A Thermoplastic Healing Agent, Vincent Mei

Theses

Self-healing polymers can regain mechanical performance following damage, offering increased material durability and sustainability. This thesis establishes structure/property/processing relationships for a 3D printable extrinsically self-healing polymer based on a UV polymerizable thermosetting resin system blended with a low temperature thermoplastic healing agent. This work serves as the first example of a vat polymerization 3D printed soft, low Tg low-melt thermoplastic extrinsically self-healing polymer blend. This development enables high resolution fabrication of complex geometries with self-healing functionality. This strategy of imbuing self-healing properties onto vat polymerization resins will enable functionality in many application spaces including aerospace, biomedical, soft robotics, coatings, and …

Inclusive Design Archive, Roblyn Powley

Theses

The Inclusive Design Archive (IDA) is a conceptual research and design project that responds to the ongoing reliance on Eurocentric, male-dominated narratives in design education. Many art and design curricula continue to exclude underrepresented creators, movements, and methodologies, limiting students’ exposure to the full scope of global design practice. Even well-intentioned educators often lack accessible tools to bring diverse perspectives into the classroom in a structured, research-supported way. IDA offers a solution in the form of a contextual search application that helps educators and students explore topics through three intersecting lenses: Broader Perspectives, Intersectional Approaches and Alternate Narratives, and Concepts, …

Rebecca’S Silence: The Rebecca Riots And Why They Vanished For Three Years, Andrew Carl Finch

Theses

No abstract provided.