Digital Commons Network^™

Critical Young Consumers: What Types Of Porn Do Teens Watch, And Why?, Giselle Woodley, Marc Zen, Harrison W. See, Lelia Green

Research outputs 2022 to 2026

Pornography use by teens is of growing concern to parents and communities. There is, however, often little differentiation made between the types of contents being consumed or exploration of the types of pornography teens are watching and why. This paper interrogates data collected from 49 qualitative interviews, including 19 follow-up interviews and 4× focus groups with teens. This paper explores teens’ perspectives on the types of pornography accessed by themselves and their peers, and popular categories of pornography more widely. Teens appear to view various types and genres of pornography, as do adults. Some teens prefer ‘ethical’ sources of porn, …

Educate, Elevate, Empower: Shaping Future-Ready Teachers For Superdiverse Classrooms, Abdelhamid Helmy Safa

Research outputs 2022 to 2026

This paper critically examines the transformative potential of integrating Community Engagement (CE) and Culturally Responsive Pedagogy (CRP) within Initial Teacher Education (ITE) programs globally. It highlights the significance of community-based learning and the Funds of Knowledge (FoK) framework in preparing educators to address the complexities of superdiverse classrooms. Through a systematic review, the study identifies effective practices and systemic barriers in ITE, advocating for a paradigm shift that aligns teacher preparation with the cultural realities of students. The proposed model synthesizes CRP, CE, and FoK to cultivate critical consciousness and adaptive expertise, essential for fostering inclusive learning environments. By providing …

Evidence-Informed Propositions For A Whole-Of-Program Assessment Approach, Janica Jamieson, Rachel Bacon, Andrea Bramley, Janeane Dart, Simone Gibson, Gemma Jenkins, Meredith Kennedy, Sue Kleve, Claire Palermo

Research outputs 2022 to 2026

Aim: To develop evidence-informed propositions for implementing whole-of-program assessment across dietetic education settings, in response to emerging education theory, technological advances such as generative artificial intelligence, and the need for meaningful learning and trustworthy progression decisions. Methods: A four-stage multiple methods study, grounded in pragmatism, was conducted. Initial propositions were developed through a systematic scoping review of programmatic assessment literature. Thematic analysis was used to identify patterns, which were iteratively refined into themes and then preliminary propositions. These were further refined through workshops with dietetic educators, who provided feedback based on their expertise. A repeated systematic scoping review incorporated recent …

Harmonic Mitigation In Unbalanced Grids Using Hybrid Pso-Ga Tuned Pr Controller For Two-Level Spwm Inverter, Pema Dorji, Taimoor Muzaffar Gondal, Stefan Lachowicz, Octavian Bass

Research outputs 2022 to 2026

This study proposes an integrated control–optimization framework for harmonic mitigation in two-level, grid-connected inverters with battery energy storage operating under unbalanced grid conditions. A proportional–resonant controller in the stationary (Formula presented.) frame and a proportional–integral controller in the synchronous (Formula presented.) frame are compared, with controller gains optimized using PSO, GA, and a hybrid PSO–GA approach. The hybrid method achieves superior trade-offs among THD, convergence speed, and computational effort. For the PR controller, hybrid PSO–GA reduces THD to 1.07%, satisfying IEEE 1547 and IEC 61727 standards, while for the PI controller it achieves 2.70%, outperforming standalone PSO (4.12%) and GA …

Clinician-Led Development And Feasibility Of A Neural Network For Assessing 3d Dental Cavity Preparations Assisted By Conversational Ai, Mohammed El-Hakim, Haitham Khaled, Amr Fawzy, Robert Anthonappa

Research outputs 2022 to 2026

Introduction: Artificial intelligence is emerging in dental education, but its use in preclinical assessment remains limited. Large language models like ChatGPT^® V4.5 enable non-programmers to build AI models through real-time guidance, addressing the coding barrier. Aim: This study aims to empower clinician-led, low-cost, AI-driven assessment models in preclinical restorative dentistry and to evaluate the technical feasibility of using a neural network to score 3D cavity preparations. Methods: Twenty mandibular molars (tooth 46), each with two carious lesions, were prepared and scored by two expert examiners using a 20-point rubric. The teeth were scanned with a Medit i700^® and …

More Alike Than Not: The Open Access Preferences Of Humanities Scholars, Rachel E. Scott, Ana Dubnjakovic

Faculty and Staff Publications – Milner Library

Several studies have noted that humanists have not been as quick or enthusiastic in their adoption of Open Access (OA) as their colleagues in other disciplines. This article leverages the Ithaka S+R US 2021 Faculty Survey to provide contextualized analysis of the OA and Open Education Resources (OER) preferences of humanities scholars, as well as some practices related to OA and OER, relative to their colleagues in other disciplines. Findings suggest that although humanists do stand apart in many OA preferences, the small effect sizes render these differences less important than previously suspected. The implications of these findings are considered …

Sailing Into And Against The Wind: Principled Opposition To And Acceptance Of Transformative Agreements, Rachel Scott, Mitchell Scott, Ben Rawlins, Lindsey Skaggs

Faculty and Staff Publications – Milner Library

This session explores different approaches to transformative agreements (TAs) at a Carnegie R1 University and a Carnegie R2 University, offering a comparative look at how these agreements shape faculty publishing experiences and the management of article processing charges (APCs). The R2 has adopted TAs to expand read access and support open access (OA) publishing, while the R1 has taken a principled stance against TAs, citing concerns about their role in perpetuating the serials crisis and questions of long-term sustainability.

Presenters from both institutions will share institutional and library motivations, as well as faculty feedback, highlighting real-world challenges related to APC …

Pfaffian Solution For Dark–Dark Soliton To The Coupled Complex Modified Korteweg–De Vries Equation, Chenxi Li, Xiaochuan Liu, Bao-Feng Feng

School of Mathematical & Statistical Sciences Faculty Publications

In this paper, we study the coupled complex modified Korteweg–de Vries (ccmKdV) equation by combining the Hirota’s method and the Kadomtsev–Petviashvili (KP) reduction method. First, we show that the bilinear form of the ccmKdV equation under nonzero boundary condition is linked to the discrete BKP hierarchy through Miwa transformation. Based on this finding, we construct the dark–dark soliton solution in the pfaffian form. The dynamical behaviors for one- and two-soliton are analyzed and illustrated.

Empowering Community Health Workers In Dementia Care In South Texas, Stephanie Santiago-Mejias, Shanae L. Rhodes, Fayron R. Epps, Robin C. Hilsabeck, Noe Garza, Sudha Seshadri, Neela K. Patel

School of Medicine Publications

Alzheimer's disease and related dementias disproportionately affect minority racial and ethnic communities. Community health workers are essential in addressing these disparities. We evaluated the impact of an educational workshop focusing on improving knowledge and preparedness in dementia care. Sixty-one CHWs attended in-person sessions in Texas and completed surveys to measure confidence and plans to apply the knowledge gained. Results revealed a significant increase in confidence in providing dementia care post-training (p < 0.001). Qualitative analysis identified five primary roles of CHWs. These findings demonstrate the potential of training interventions to improve knowledge gaps and empower CHWs to address dementia in underserved communities.

Enhanced Recovery After Neurosurgery: A Narrative Review Comparing Clinical Outcomes, Protocols, And Challenges With Standard Postoperative Care, Tirath Patel, Hamza Yousuf Ibrahim, Rahma Naveed, Aziz Ur Rehman, Maryam Amir, Fatima Nasir, Anum Zia Khan, Nikhilesh Anand

School of Medicine Publications

Background: By integrating evidence-based pre-, intra-, and postoperative therapies, enhanced recovery after surgery (ERAS) protocols have transformed perioperative care in numerous surgical specialties. Although their use in neurosurgery aims to maximize patient recovery, minimize complications, and reduce hospital stays, the evidence remains heterogeneous, and large randomized controlled trials are scarce.

Objectives: This narrative review contrasts the clinical outcomes, advantages, and challenges of ERAS protocols with those of conventional postoperative care in neurosurgery, with a focus on cranial, spinal, pediatric, cancer, and functional procedures.

Methods: A thematic synthesis of peer-reviewed clinical evidence was conducted using PubMed, Scopus, and Google Scholar (2000-2025). …

Association Of Component Strategies Of The Target Stroke Phase 3 Nationwide Quality Improvement Program With Accelerated Door-To-Puncture And Door-In-Door-Out Times For Ischemic Stroke Endovascular Thrombectomy In The United States, Brian Mac Grory, Kaiz S. Asif, Haolin Xu, Brooke Alhant, Jay Lusk, David Hasan, Soojin Park, Amelia K. Boehme, Ameer E. Hassan, Kyle M. Fargen

School of Medicine Publications

Background: The Target Stroke Phase III program is a national quality improvement initiative led by the American Heart Association, which sought to improve the quality of care for patients with acute stroke undergoing acute reperfusion therapy including endovascular thrombectomy (EVT).

Methods: A retrospective, observational cohort study was performed using data from the American Heart Association Get With The Guidelines-Stroke Program between January 1, 2017, and March 31, 2022. Three categories of patients were analyzed: (1) patients who arrived directly at the thrombectomy hospital and had EVT, (2) patients who were transferred in from a nonthrombectomy hospital and had EVT, and …

Recommendations From Multi-Disciplinary Professionals For Survivor-Informed And Comprehensive Care For Human Trafficking Survivors, Christina Tsoi, Timothy B. Smith, Elizabeth Cutrer-Párraga, Devan Clayton, Joshua M. Marshall, Jamila Mastny

Faculty Publications

Background: Human trafficking affects millions of people worldwide with multiple adverse outcomes including psychopathology. Although research on human trafficking has become abundant in other academic disciplines (e.g., public health, criminology, social work), healthcare research specific to the mental health treatment of survivors remains limited. Objective: The purpose of this study was to gather recommendations from professionals about mental health treatment of trafficking survivors. Method: Semi-structured interviews were conducted with 21 multidisciplinary professionals working with trafficking survivors. Data were analyzed using qualitative content analysis methodology. Results: An overarching theme derived from the data concerned the recommendation to implement trafficking survivor-informed care, …

(Un)Just Transitions For Youth And The Disabled? The Exclusionary Pressures Facing Science, Technology, Engineering And Mathematics (Stem) Education, Elizabeth Done, Helen Knowler, Irina Lazar, Sylvia Hayes, Joshua Lait, Andrea Perez-Porres

School of Law, Humanities and Social Sciences

This paper highlights the under-representation of young people with disabilities in STEM subjects and career pathways, with particular reference to the engineering sector given its prominent role in the design of energy systems related to net-zero policies. We consider the role of physical infrastructure, and pedagogic and representational practices, in facilitating the marginalisation and under-representation of young people with disabilities. Ultimately, we seek a broader understanding of the ‘just transition’ that acknowledges the role of education in ensuring the active participation of all young people, regardless of learning difficulty or disability or social identity, in that transition. The research is …

Image Captioning Through The Lens Of The Gricean Maxims: Generating Meaningful And Relevant Image Descriptions, Annika Lindh

Doctoral

Image captioning models enable us to automatically generate natural language image descriptions for previously unseen images. It combines the two fields of computer vision and natural language generation, allowing models to interpret the con tent of an image and communicate that knowledge through natural language text.

Research into image captioning has the potential benefit of reducing the gap in digital information availability between fully sighted individuals and those who are visually impaired. However, automatically generated captions often fail to provide the required level of detail and specificity to achieve this goal. Furthermore, current standard evaluation methods are insufficient at measuring …

Intentionframe: A Semi-Structured, Multi-Aspect Framework For Fine-Grained Conversational Intention Understanding, Zailong Tian, Zhuoheng Han, Lizi Liao, Lizi Liao

Research Collection School Of Computing and Information Systems

Understanding user intentions in multi-turn dialogues is critical for conversational AI, yet existing approaches—relying on rigid slot-value structures or unstructured free-text—fail to fully capture conversational complexity. In this paper, we propose IntentionFrame, a semi-structured framework inspired by psychological and cognitive intention theories, which organizes conversational intents into four interrelated aspects: situation, emotion, action, and knowledge. This design not only retains interpretability but also provides LLMs with a rich context to accurately parse and respond to nuanced user inputs. To efficiently scale IntentionFrame annotations, we introduce a Weakly-supervised Reinforced Generation (WeRG) method that leverages a small set of high-quality human annotations …

Security Modelling For Cyber-Physical Systems: A Systematic Literature Review, Shao Fei Huang, Christopher M. Poskitt, Lwin Khin Shar

Research Collection School Of Computing and Information Systems

Cyber-physical systems are at the intersection of digital technology and engineering domains, rendering them high-value targets of sophisticated and well-funded cybersecurity threat actors. Prominent cybersecurity attacks on CPS have brought attention to the vulnerability of these systems and the inherent weaknesses of critical infrastructure reliant on them. Security modelling for CPS is an important mechanism to systematically identify and assess vulnerabilities, threats, and risks throughout system life cycles, and to ultimately ensure system resilience, safety, and reliability. This survey delves into state-of-the-art research on CPS security modelling, encompassing both threat and attack modelling. While these terms are sometimes used interchangeably, …

Isolation And Characterization Of Plant Growth Promoting Rhizobacteria From Soils In The Uae And Their Effect On Plant Salt Tolerance, Layla Zayed Almazrouei

Theses

Plants are constantly challenged by environmental stresses that restrict their growth and productivity. In the United Arab Emirates (UAE), soil salinity is a critical barrier to agriculture, particularly for tomato (Solanum lycopersicum), which is highly sensitive to moderate salinity levels (>2.5 dS m⁻¹). This study explored the potential of plant growth–promoting rhizobacteria (PGPR), especially actinobacteria, to enhance salt tolerance in tomato. The objective was to evaluate the effects of rhizosphere-competent (RC) and non-rhizosphere-competent (NRC) PGPR on plant physiology and yield in saline sandy soils. Actinobacterial strains were isolated from the tomato rhizosphere and screened to produce 1-aminocyclopropane-1-carboxylic …

Enhancing The Acceptability Of Decision-Making System Using Xai Case: Crime Profiling System, Mohamed Saeed Al Shamsi

Theses

In the current world, we need to place more emphasis on how easily interpretable, accurate, and acceptable data analysis results are, given that essential operations in law enforcement, among other sectors, are backed up by the use of complex computing systems. Crime profiling systems that use crime data for profiling encounter major problems because they depend on algorithm-based methods. These methods can be ambiguous and inaccurate, leading to low public acceptability. The study investigates major problems with Complex Crime profiling systems (CPS) because their unexplained algorithms result in system performance issues and public scepticism. XAI provides a solution to handle …

باستخدام مجموعة بيانات متعددة من الطائرات بدون طيار Yolo البحث والإنقاذ البحري القائم على في ظروف الطقس الصعبة, Aysha Ali Alshebli

Theses

Object detection models, powered by deep learning and computer vision, are revolutionizing marine search and rescue (SAR). By analyzing aerial imagery and live drone footage, these systems automatically identify critical targets like survivors, life rafts, and debris across vast and treacherous ocean areas. This capability enhances operational efficiency by reducing human workload and accelerating response times, even in challenging conditions such as poor light, high seas, or cluttered backgrounds. The result is continuous monitoring, faster decision-making, and a significantly improved probability of successful rescue.

Departing from prior methodologies, YOLO introduced a paradigm shift through its single-shot architecture, which concurrently predicts …

Enhanced Privacy Preserving Healthcare Data Management With Federated Learning Using Homomorphic Encryption, Omar Abdulla Ali

Theses

Federated Learning (FL) is a decentralized approach of machine learning on multiple clients jointly training models without sharing their raw data, which drastically improves privacy and enhance protection against security breach. This is particularly critical in the healthcare sector, where hospitals and medical institutions are often unable to exchange patient records due to strict privacy regulations and data-management policies. However, there is still a risk of privacy breach when clients send their model updates to the central server, because if a model update is intercepted or analyzed by a malicious entity, it could be used to recover sensitive data using …

Enhanced Air Hockey Robot Performance Through Adaptive Control Algorithim Using Ai-Based Hierarechal Decicion Archeticture, Ayham Majed Salim

Theses

This thesis presents the development of an intelligent air hockey robot that combines precise mechanical design, computer vision, and adaptive control within an AI-based hierarchical decision architecture. The system integrates synchronized stepper motors, high-speed image processing, and a real-time decision framework to achieve competitive gameplay performance. The robot detects the puck using adaptive HSV color segmentation, supported by dynamic calibration that maintains accuracy under different lighting conditions. A two-stage trajectory prediction model, based on exponential decay velocity estimation, enables anticipation of puck motion and improves response time during fast gameplay.

At the decision level, a fuzzy-logic supervisor governs the robot’s …

Determination Of Variations In Orbital Parameters Of Sample Of Satellites Through Spacecraft Tracking, Asma Ali Alasmari

Theses

The continues increasing density of Resident Space Objects (RSOs) in Earth’s orbit highlights the crucial need for Space Situational Awareness (SSA). This thesis studies the orbital changes in two regions, active low Earth orbit (LEO) satellites and inactive geostationary Earth orbit (GEO) satellites. For LEO satellites we used publicly available data (two line element TLE from Space-Track) and ASTRIAGraph. We verified the orbital elements series and time ordered them, applied a Hampel (median+MAD) mask to semi-major axis, eccentricity vector and inclination to find outliers and exclude them from event detection. The events are then detected using time normalized slopes and …

Understanding Behavioral Patterns: A Case Study Of Emirati Ex-Offenders In United Arab Emirates, Salim Ali Al Naqbi

Theses

Research on desistance has helped criminologists to better understand how people change their criminal identity and exercise personal choice. Yet in the UAE, these ideas has not often been applied to prisoners serving one or multiple offenses, even though incarceration and reoffending remain important social concerns. Because of this, desistance theory has not been fully used to study how rehabilitation is managed in UAE prisons, which means that some useful lessons may be missed. This study begins to close that gap by looking at the personal stories of 15 Emirati participants that were formerly incarcerated by adapting a qualitative and …

Microstrip Antenna Design Based On Ai And Machine Learning, Waleed Mohamed Sha Moulavi

Theses

Microstrip patch antennas (MPAs) rely on precise impedance matching for efficient power transfer between the antenna and feed line. This is often achieved using a number of different techniques, one of which is the quarter-wavelength transformer (QWT). While commercial electromagnetic (EM) solvers offer robust optimization capabilities, they often operate as "black boxes" without providing physical insights into parameter interdependencies. Furthermore, this thesis focuses on the specific scenario where the antenna input impedance is purely real. To address the lack of explicit design relationships for these specific conditions, this thesis develops and comparatively evaluates artificial intelligence (AI) models for QWT width …

How Do Emirati University Students Develop Their Academic Biliteracy? A Mixed-Method Study, Eman Kamel Rababa

Dissertations

Framed by Hornberger’s continua of biliteracy model, this study investigated the developmental dynamics of academic biliteracy among Emirati university students. The research employed a sequential mixed-methods design, conducted across three public universities in the UAE. In the initial qualitative phase, interview data were collected from 30 students. Informed by these findings and the extant literature, a quantitative survey was then developed and administered to a sample of 299 students from various disciplines. The qualitative data were analyzed using reflexive thematic analysis, while the quantitative data were examined using advanced statistical analyses, including structural equation modeling. Three primary themes emerged from …

Trustworthy Federated Learning Framework For Secure, Efficient, And Quality-Aware Distributed Ai, Asadullah Tariq

Dissertations

Federated Learning (FL) emerged as a significant advancement in the field of Artificial Intelligence (AI), enabling collaborative model training across distributed devices while maintaining data privacy. As the importance of FL and its application in various areas increased, addressing trustworthiness issues in its various aspects became crucial. In the FL process, clients contribute updates computed on their local datasets, which the server aggregates to iteratively refine the global model. However, not all client data may be relevant to the learning objective, and incorporating updates from irrelevant data can harm the model's performance. The selection of training samples significantly impacts model …

Selective Sharing And Social Bonding: A Qualitative Study Of Online Health Information Behaviour Among Older Adults In Shanghai, Minzhi Ye, Yan Liu

School of Social Work Faculty Publications

The health information landscape has been revolutionised by the advent of social media, significantly affecting older adults’ access to and interaction with online health information. In this study, we examine how older adults interact with health information on social media. In total, 30 participants aged 60 years and older from Shanghai were interviewed, focusing on their health information-seeking behaviour, perceptions, and subsequent actions using a semi-structured, in-depth interview approach. Furthermore, in this study, we employed grounded theory to analyze the data, and the results revealed that older adults utilise a comprehensive cognitive process for evaluating health information. Information-sharing decisions among …

Data As Policy, Janet Freilich, W. Nicholson Price Ii

Faculty Scholarship

A large literature on regulation highlights the many different methods of policy-making: command-and-control rulemaking, informational disclosures, tort liability, taxes, and more. But the literature overlooks a powerful method to achieve policy objectives: data. The state can provide (or suppress) data as a regulatory tool to solve policy problems. For administrations with expansive views of government’s purpose, government-provided data can serve as infrastructure for innovation and push innovation in socially desirable directions; for administrations with deregulatory ambitions, suppressing or choosing not to collect data can reduce regulatory power or serve as a back-door mechanism to subvert statutory or common law rules. …

An Analysis Of Renewable Energy Capture Utilization For Mpulungu Harbour, Dorica Nayame

World Maritime University Dissertations

No abstract provided.

Improving Auditing Of The Maritime Education And Training Institutes Of Peru : Process Analysis And Perspectives Of The Stakeholders To Design A Training Program For Auditors, Juan Alberto Sanchez Castañeda

World Maritime University Dissertations

No abstract provided.