Digital Commons Network^™

Drafting Policy To Address Academic Integrity: The Other Ai In Education, Elizabeth Burns

STEMPS Faculty Publications

The article focuses on the role of school librarians in drafting policies to address academic integrity amid the increasing use of artificial intelligence (AI) in K-12 education. It defines AI, including generative AI (GenAI), and discusses both the challenges and opportunities AI presents for teaching and learning, emphasizing the need for clear guidelines on ethical use. The article outlines three common AI policy models—permissive, hybrid, and restrictive—and stresses the importance of collaboration between librarians and teachers to establish consistent expectations, promote critical thinking, and ensure proper attribution of AI-generated content. School librarians are positioned as key facilitators in guiding students …

Cryogenic Sloshing In Aircraft Fuel Tanks, Stuart Colville

School of Engineering, Computing and Mathematics Theses

Liquid sloshing in next-generation sub-cooled liquid hydrogen aircraft fuel tanks can induce rapid ullage pressure and temperature drops, potentially causing cavitation in cryogenic pumping systems and compromising fuel delivery systems. Sloshing events may be initiated during taxiing, take-off, landing, and turbulence, with large accelerations producing highly non-linear liquid motion and wave-breaking conditions. Understanding such phenomena is essential for cryogenic hydrogen fuel tank design and certification for next generation aircraft.A systematic experimental methodology was employed to investigate both the wave kinematic and thermodynamic aspects of sloshing. Initial water–air experiments in a simplified horizontal circular tank were conducted to validate measurement techniques, …

Digitalisation In The Voluntary Sector: An Empirical Study On The Determinants Of It Acceptance, Deniz Dogu

School of Engineering, Computing and Mathematics Theses

Digitalisation represents a major societal trend that drives economic and social trans-formation by increasingly embedding digital information and communication techno-logies (ICT) into processes, interactions, and everyday activities across all domains of life. However, the voluntary sector has yet to fully embrace ICT. The extent to which volunteers integrate digital tools depends on factors such as technical infrastructure and willingness to adopt IT. Research in this area remains limited, and findings are often difficult to transfer across different national contexts. This PhD research addresses the gap in understanding IT acceptance in volunteering, using Germany as a case study. A comprehensive literature …

Optimisation Of Application Distribution For Heterogeneous Multi-Access Edge Computing Environments, Harald Frank

School of Engineering, Computing and Mathematics Theses

Mobile networks have evolved from pure transport networks for voice, text andimage data to multifunctional data processing platforms. This goes hand in handwith the change from manufacturer-dependent, hardware-based systems tovirtual infrastructure environments based on standard systems.This paradigm shift creates completely new possibilities for functionalities andservices which was not able with the old architecture. On the other hand, theongoing development of the mobile networks with its virtual platforms generatesnew challenges which must be analysed and solved.While the demands on the new functionalities and services are increasing, theend-user device also become more powerful. The combination of end-userdevice mobility, limited resources at the …

Towards An Evaluation Of The Business Value Of Ai: A System Dynamics Approach, Ganesh Sankaran

School of Engineering, Computing and Mathematics Theses

In the early 2010s, when Artificial Intelligence (AI) emerged from the latest "winter" of disillusionment, discussions about its use in decision-making tended to be dichotomous: humans or AI. More recently, consensus has shifted toward a complementary humans-and-AI perspective, recognising that augmentation, not substitution, is the more appropriate frame for AI's role in the foreseeable future. This shift foregrounds the challenge of evaluating outcomes in collaborative decision-making contexts.The thesis proposes a simulation-based framework, drawing on system dynamics, to evaluate whether complex, time-varying interactions between humans and AI agents result in collectively rational behaviour. The framework extends the observation of dynamic complexity …

Applications Of Evolutionary Algorithms In Wind Farm Layout Optimisation, Pawel Manikowski

School of Engineering, Computing and Mathematics Theses

The transformation from fossil fuels to renewable energy is gaining momentum. Countries worldwide are investing significant funds and resources in this shift. The motivations for this change include political, environmental, and social factors, among others. In the UK, which is surrounded by the ocean and experiences strong winds, offshore wind farms are seen as the most viable source of renewable energy. It is anticipated that by 2030, all electricity in the UK will be generated by wind turbines. Hence, the optimisation of the wind farm layouts is the desired direction of research in the UK.In Chapter 3, we discussed the …

Life Cycle Assessment Of Marine Composite Recreational Craft Manufacturing And Operations, Badr Moutik

School of Engineering, Computing and Mathematics Theses

Marine composite recreational craft are growing in number. Sectoral roadmaps for sustainable development are increasing pressure to demonstrate life cycle environmental performance. Life cycle assessment (LCA) has been identified as a key strategic decision support tool. However, current practice is undermined by sparse, non-representative data and methodological inconsistencies. These weaknesses increase the risk of biased or misleading interpretation, constrain wider uptake of LCA, and limit the sector’s ability to respond credibly to tightening environmental sustainability expectations. This thesis assesses the cradle-to-grave environmental impacts of a market-representative glass-fibre reinforced plastic (GRP) motor yacht across 16 impact categories. The research builds on …

Oscillating Water Column Geometric Hybridisation And The Air Compressibility Effect, Gunay Gazaloglu

School of Engineering, Computing and Mathematics Theses

Oscillating Water Column (OWC) devices represent one of the most operationally robust wave energy conversion technologies, yet their commercial deployment remains hindered by narrow resonant bandwidth, geometry-dependent efficiency, and uncertainties in scaling thermodynamic effects between model and prototype. This thesis addresses these limitations through a coordinated investigation combining physical experimentation, empirical and machine-learning prediction, and high-fidelity computational fluid dynamics.A systematic experimental campaign was conducted on five single- and dual-chamber OWC geometries (Conventional, U-OWC, L-OWC, DCOWC-1, and DCOWC-2) under regular waves, with controlled compressible and incompressible chamber configurations. The thermodynamic scaling discrepancy is quantified for the first time across hybrid geometries, …

Modelling And Optimisation Of Dynamic Power Cable Configurations For Floating Offshore Renewable Energy, Anna Holcombe

School of Engineering, Computing and Mathematics Theses

Floating offshore renewable energy requires dynamic power cables to transmit generated electricity from the floating device to the seabed, or to an adjacent device, so that it can be exported to shore. Dynamic power cables are connected at the top end to a floating device, and traverse the water column, subjected to loading at the hang-off, and direct hydrodynamic loading from waves and currents. Their reliability has been a concern within industry and research, particularly due to historically high failure rates of static subsea cables. It is essential that design and analysis of dynamic power cables is accurate, to mitigate …

Living With Generative Ai: Considering Constructionist Approaches To Learning And Methodological Implications Of Process Ontologies, Jimin Lee, Nancy Budwig

Psychology

The growing presence of generative artificial intelligence (GenAI) in educational practice raises questions about how learners and educators live with AI and reshapes questions about how learning unfolds across contemporary learning environments. Although research on AI in education has expanded quickly, much of this work continues to frame GenAI in technocentric and static terms, as a tool to be evaluated, rather than as a relational and developmental presence within learners' trajectories. Drawing on constructionist learning theory and post-Cartesian metatheoretical perspectives, this mini review suggests that such framings are insufficient for understanding how learning is enacted in AI-mediated contexts. We propose …

Traveling Waves For A Diffusive Sir Epidemic Model With Delay In The Diffusion Term, William Barker

Faculty Scholarship

This paper investigates the existence of traveling waves in a diffusive SIR model with delay incorporated in the diffusion terms and a nonlinear incidence rate with delay. By employing a cross-iteration scheme and partial monotonicity conditions, we establish that the existence of quasi-upper and lower solutions, along with suitable super and sub-solutions, provides sufficient conditions for the existence of a traveling wavefront. This existence result is obtained via Schauder’s fixed-point theorem. Furthermore, given an appropriate basic reproduction number, the traveling wavefront transitions from the disease-free steady state to the endemic steady state. To illustrate our approach, we explicitly construct super- …

Elastohydrodynamic Propulsion Of A Magnetically Actuated Filament, Sohum Kapadia, Julien Chopin, Arshad Kudrolli

Physics

We investigate the low-Reynolds-number propulsion of a slender elastic filament with a dipolar magnetic head actuated by an oscillating magnetic field in a viscous fluid by studying its strokes and net forward motion. To capture these dynamics, we employ an elastohydrodynamic (EH) framework that couples Euler-Bernoulli beam mechanics with resistive force theory. Unlike prescribed-kinematics models, filament shapes here emerge self-consistently from the actuation and the force and torque boundary conditions (BCs). We demonstrate that viscous boundary contributions are crucial for quantitative agreement and show that the swimming dynamics are governed by the EH length and a magneto-viscous-elastic stroke amplitude introduced …

Enhancing Offshore Wind Resource Assessment Through Neural Network-Based Hf Radar Data Analysis, Nikolas Martzikos, Matthew Craven, David Walker, Daniel Conley

School of Engineering, Computing and Mathematics

The increasing demand for offshore wind energy underscores the need for accurate wind speed estimation to support the design and operation of offshore wind farms. High-Frequency Radar (HFR), a widely used remote sensing technology in oceanographic research, offers promising potential for wind resource assessment, particularly in areas where conventional measurements are limited. This study explores the application of artificial neural networks (ANNs) for offshore wind speed prediction using HFR-derived data, addressing key challenges in model development and training. A key feature of this approach is the use of a decade-long dataset from the Celtic Sea, off the southwest UK coast, …

Next-Generation Virtual Environment Training For Cybersecurity In The Maritime Logistics Industry: A Position Paper, Tyler Cheng, Rory Hopcraft, Kimberly Tam, Ji-Jian Chin

School of Engineering, Computing and Mathematics

The maritime logistics industry is the most dependent on it in the modern world, yet it is not well protected against cyber risks. Recently, the maritime industry has been transitioning into industry-specific tech, and threats of cyberattacks are increasing as the adoption of technology and automation continues. One of the most effective methods to protect industries and ships from such security incidents, is to train seafarers to mitigate and handle such incidents. However, to the best of our knowledge, we did not find anything that addresses this gap. This article will present the idea and benefits of using virtual environments …

Usable Authentication: Are We There Yet?, Nathan Clarke, Steven Furnell

School of Engineering, Computing and Mathematics

With technology increasingly embedded in everyday life, the demand for secure and usable authentication methods has never been greater. Traditional password-based systems continue to dominate, despite well-known usability and security challenges. This paper explores the evolution of user authentication technologies, from secret knowledge and tokens to biometrics and emerging approaches such as Passkeys. It critically evaluates the extent to which usability has been achieved, identifying both successes—such as biometrics integrated into smartphones—and persistent issues, including inconsistent guidance, ecosystem dependence, and accessibility barriers. Drawing on academic and commercial developments, the discussion highlights the growing burden on users who must authenticate across …

Rapid Electrochemical Biosensor With Enhanced Accuracy And Repeatability Using Pyrene Nhs Ester Modified 3d Graphene Electrodes, S. Nazir, D. Jenkins, G. Pan

School of Engineering, Computing and Mathematics

A consistent and reproducible chemical modification of the transducer interface is essential to ensure effectiveimmobilization of bioreceptors, thereby improving the sensitivity and reproducibility of biosensors. Althoughnotable progress has been made in fabricating graphene-based biosensors, the effects of surface biofunctionalization on sensing performance remain not fully understood. This study shows that combining threedimensional (3D) graphene foam electrodes with a straightforward, single-step surface biofunctionalizationmethod is key to enhancing the performance of graphene-based biosensors. Specifically, it presents a single-stepapproach to functionalize the 3D graphene foam (Gii-Sens) with 1-pyrenebutyric acid N-hydroxysuccinimideester (Pyrene-NHS ester). Electrochemical techniques, including cyclic voltammetry (CV) and differential pulsevoltammetry (DPV), confirmed …

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 …

Diagnosing Long-Term Divergence In Build Back Better Outcomes In Low- And Lower-Middle-Income Communities, E. A. Opabola, M. Baiguera, A. Raby, T. Rossetto, A. Pomonis, E. Meilianda, Y. Idris, S. Nurdin, K. Adams, D. J. Mcgovern, N. Acikgoz, H. Mistry, F. Marafini

School of Engineering, Computing and Mathematics

Low-income communities in disaster-prone regions face persistent challenges in translating post-disaster recovery investments into sustained resilience, as they navigate trade-offs among engineering objectives, policy constraints, and evolving socio-economic needs. Despite the widespread adoption of Build Back Better (BBB) principles, evidence on the long-term sustainability of outcomes remains limited, particularly in low- and lower-middle-income contexts. This study examines the sustainability of BBB outcomes in two Indonesian case studies: Banda Aceh (approximately 18 years after the 2004 Indian Ocean tsunami) and Central Sulawesi (approximately 4 years after the 2018 earthquake, liquefaction, and tsunami). Drawing on structured housing assessments, household surveys, semi-structured interviews, …

Performance Of Chatgpt-4, Gemini, And Deepseek-V3 On English-Translated Questions From The Taiwan National Dental Technician Licensing Examination Over A Three-Week Period, Yi-Pang Lee, Ching-Yi Huang, Andy Sun, Chun-Pin Chiang

Journal of Dental Sciences

Background/purpose: Large language models (LLMs) have shown potential in answering professional examination questions. This study evaluated the performance of ChatGPT-4, Gemini, and DeepSeek-V3 in answering English-translated questions from the 2023 Taiwan National Dental Technician Licensing Examination (TNDTLE) over a three-week period.

Materials and methods: A total of 194 English-translated, text-based multiple-choice questions were selected from the 2023 TNDTLE. ChatGPT-4, Gemini, and DeepSeek-V3 were used to answer the same set of English-translated questions at four time points: baseline and one-, two-, and three-week follow-ups. Accuracy rates (ARs) were calculated and compared to evaluate changes over time and differences among the three …

Rigorous Validation Of Machine Learning Models For Orthodontic Extraction Prediction Using Nested Cross-Validation And Smotenc-Integrated Pipelines., Anh Thi-Ngoc Do, Hung Trong Hoang, Thuy-Trang Thi Ho, Hieu Ngoc Le

Journal of Dental Sciences

Background/purpose: Machine learning (ML) in orthodontics often suffers from optimistic bias due to data leakage and improper handling of class imbalance. This study implemented and evaluated a production-grade validation framework - nested cross-validation (CV) - for three distinct algorithm classes (logistic regression, random forest, and gradient boosting) using a consensus-labeled orthodontic dataset.

Materials and methods: A retrospective dataset of 500 patients (334 non-extraction/166 extraction) was curated with 41 processed features. Two stratified split protocols (70/30 and 80/20) were evaluated to assess model robustness. To ensure methodological rigor, a 5-fold outer/3-fold inner nested cross-validation was implemented. Crucially, SMOTENC (synthetic minority over-sampling …

Development Of A Risk Scoring System For Predicting Post-Extraction Medication-Related Osteonecrosis Of Jaws: A Derivation And Validation Cohort Study, Ling-Ying Wei, Ching-Ming Chiu, Sang-Heng Kok, Hung-Ying Lin, Wei-Yih Chiu, Hao-Hong Chang, Shih-Jung Cheng, Jang-Jaer Lee

Journal of Dental Sciences

Background/purpose: Although risk factors for medication-related osteonecrosis of the jaw (MRONJ) are known, clinical assessment prior to dental extraction remains largely subjective. We aimed to develop and externally validate a simple clinical risk scoring system to predict post-extraction MRONJ in osteoporotic patients receiving antiresorptive therapy (ART) and support evidence-based clinical decision-making.

Materials and methods: This retrospective cohort study used a derivation cohort (N = 1,067 extractions, 2003‒2022) to develop a 5- to 16-point risk score system based on five predictors (age ≥ 75, ART duration ≥ 24 months, bisphosphonate use, drug interruption < 3 months, and extraction site). The model was validated in an independent cohort (N = 928 extractions, 2022–2024) using a pre-defined ≥12 cut-off. Performance metrics included the area under the curve (AUC), sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV).

Results: MRONJ prevalence was lower in the validation …

Osteoblastogenesis Stimulation By Human Umbilical Cord Stem Cell Secretome During Maxillary Expansion, Alexander Patera Nugraha, Guang Hong, Firdaus Hariri, I Gusti Aju Wahju Ardani, Adya Pramusita, Nurul Aisyah Rizky Putranti, Nindya Rizky Anjani Marhendra, Naora Dewi Rahma Fadzila, Ananda Firman Putranto, Muhammad Luthfi, Wibi Riawan, Putri Cahaya Situmorang, Rony Abdi Syahputra, Thantrira Porntaveetus, Khairul Anuar Shariff, Nissia Ananda, Maudina Dwi Heriasti, Kotaro Tanimoto

Journal of Dental Sciences

Background/purpose: Maxillary expansion induced by mechanical force (MEMF) is a standard orthodontic approach for correcting transverse maxillary deficiency. The human umbilical cord mesenchymal stem cell secretome (HUCMSC-S) has the potential to stimulate accelerate bone remodeling. This study aimed to evaluate local HUCMSC-S application effect during MEMF on the expression bone morphogenetic protein (BMP)-2, BMP-4, BMP-7, vascular endothelial growth factor (VEGF), insulin-like growth factor-1 (IGF-1), transforming growth factor-beta (TGF-β), and fibroblast growth factor-2 (FGF-2) in a Wistar rat (Rattus norvegicus).

Materials and methods: Twenty-four healthy male Wistar rats (R. norvegicus) were randomly divided into four groups: …

An Investigation Into The Mechanisms, Barriers, Degree And Sphere Of Risk Influence In Corporate Security, Nicola Lockhart

Theses: Doctorates and Masters

This study investigates the sphere of corporate security risk influence within organisations, addressing the conceptual and practical ambiguity surrounding the activity’s capacity to shape organisational decisions, behaviours, and risk priorities. While corporate security’s protective role is widely recognised, its broader organisational risk influence remains under-theorised. The study defines the sphere of risk influence as the range of organisational stakeholders and environments with which the corporate security activity interacts, and within which it may engage, persuade, and mobilise action. This sphere is analytically constituted through the intersection of three dimensions: the mechanisms through which influence is attempted, the barriers that constrain …

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 …

Development And Evaluation Of A Gc-Msms Method For The Quantification Of Gamma Hydroxybutyrate In Hair, Jacob Robert Keller

Theses: Doctorates and Masters

Gamma (γ)-hydroxybutyrate (GHB) is an endogenous short-chain fatty acid, and is of forensic importance due to its use in drug facilitated sexual assault (DFSA). Exogenous GHB has a limited window of detection in blood (1-hour) and urine (12-hours). Testing hair allows detection of drugs months after ingestion. This thesis contains a literature review which compares published methods which determine concentration of endogenous GHB in hair to determine which procedures are suitable for experimental comparison. The aims of this thesis were to develop a GC-MS-based method for the detection of GHB, test various methods to improve extraction, determine linearity, precision, accuracy, …

Exploring Exhibited Works On Dentistry-Related Topics At The Student Science Fair Projects In Taiwan From 1970 To 2025, Mei-Huei Li, Feng-Chou Cheng, Kun-Ming Lien, Chun-Pin Chiang

Journal of Dental Sciences

No abstract provided.