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Articles 37561 - 37590 of 38632
Full-Text Articles in Entire DC Network
Meta-Learning Approaches For Causal Discovery In Dynamic Healthcare And Robotics Environments, Hayder Abbood Md Facp
Meta-Learning Approaches For Causal Discovery In Dynamic Healthcare And Robotics Environments, Hayder Abbood Md Facp
Mesopotamian Journal of Artificial Intelligence in Healthcare
Healthcare and robotics dynamic task domains are also known to be both complex and time-varying systems where reasoning about causal links are important for making reliable decisions. But causal structures in these domains are difficult to ascertain with limited data, distribution shifts, and changing environments. Meta-learning (or learning to learn) is a promising approach to combating these two obstacles by learning from experience across tasks to quickly adapt to new task environments. In this paper we provide a new framework that combines ideas from meta-learning and causal discovery, whose objective is to discover the underlying cause effect relationships in sequential, …
Biogpt: A Generative Transformer-Based Framework For Personalized Genomic Medicine And Rare Disease Diagnosis, Ghada Al-Kateb, Emine Cengiz, Murat Gök
Biogpt: A Generative Transformer-Based Framework For Personalized Genomic Medicine And Rare Disease Diagnosis, Ghada Al-Kateb, Emine Cengiz, Murat Gök
Mesopotamian Journal of Artificial Intelligence in Healthcare
This paper introduces BioGPT, a generative transformer-based framework designed to advance personalized genomic medicine and rare disease diagnosis. Unlike conventional models that process either genomic sequences or clinical narratives in isolation, BioGPT employs a cross-modal architecture that effectively fuses both data streams, enabling precise classification and interpretable natural language generation. The model is pre-trained on large-scale genomic and electronic health record datasets and fine-tuned for rare disease tasks. Comprehensive experiments demonstrate BioGPT’s superiority over state-of-the-art biomedical models, including RarePT, BioBERT, and DNABERT, with improvements of up to 10% in F1-score and over 20 BLEU points in justification fluency. Ablation studies …
Adaboost-Based Classification For Bone Sarcoma Outcome Prediction: A Comparative Machine Learning Approach, El-Sayed M. El-Kenawy, Ahmed Mohamed Zaki, Marwa M. Eid
Adaboost-Based Classification For Bone Sarcoma Outcome Prediction: A Comparative Machine Learning Approach, El-Sayed M. El-Kenawy, Ahmed Mohamed Zaki, Marwa M. Eid
Mesopotamian Journal of Artificial Intelligence in Healthcare
Bone sarcomas represent aggressive malignancies with complex clinical presentations where traditional prognostic methods often lack precision in predicting patient outcomes. This study developed and validated machine learning models for predicting bone sarcoma patient outcomes using a comprehensive dataset from Memorial Sloan Kettering Cancer Center spanning 2010-2020, comparing multiple algorithms including AdaBoost, Logistic Regression, Ridge Classifier, Quadratic Discriminant Analysis, and Linear Discriminant Analysis. AdaBoost demonstrated superior performance with 0.84 accuracy, 0.875 sensitivity, 0.7955 specificity, 0.8448 precision, 0.8333 negative predictive value, and 0.8596 F1 score, outperforming other algorithms which achieved 0.83 accuracy and 0.8496 F1 score. Statistical analysis confirmed significant differences between …
Data Mining Driven Segmentation Of Health Insurance Policyholders Using K-Means Clustering, Farah Ali Khairi, Laith Farhan, Oluwaseun A. Adelaja
Data Mining Driven Segmentation Of Health Insurance Policyholders Using K-Means Clustering, Farah Ali Khairi, Laith Farhan, Oluwaseun A. Adelaja
Mesopotamian Journal of Artificial Intelligence in Healthcare
This study illustrates a data‐driven approach to the segmentation of health insurance policyholders based on K-Means clustering of an open insurance dataset. Key demographic and financial features like age, body mass index (BMI), dependents, annual medical spending, and premium payment were normalized first to ensure comparability. The optimal number of clusters (k = 3) was determined using silhouette analysis, and three clusters were formed: (1) young, low‐cost individuals, (2) middle‐aged medium‐cost individuals, and (3) old, high‐cost individuals. Cluster centroids provide actionable profiles that can be utilized by insurers for target marketing, risk profiling, and development of customized plans. A set …
An Iterative Shifting Disaggregation Algorithm For Multi-Source, Irregularly Sampled, And Overlapped Time Series, Colin O. Quinn, Ronald H. Brown, George F. Corliss, Richard J. Povinelli
An Iterative Shifting Disaggregation Algorithm For Multi-Source, Irregularly Sampled, And Overlapped Time Series, Colin O. Quinn, Ronald H. Brown, George F. Corliss, Richard J. Povinelli
Electrical and Computer Engineering Faculty Research and Publications
Accurate time series forecasting often requires higher temporal resolution than that provided by available data, such as when daily forecasts are needed from monthly data. Existing temporal disaggregation techniques, which typically handle only single, uniformly sampled time series, have limited applicability in real-world, multi-source scenarios. This paper introduces the Iterative Shifting Disaggregation (ISD) algorithm, designed to process and disaggregate time series derived from sensor-sourced low-frequency measurements, transforming multiple, nonuniformly sampled sensor data streams into a single, coherent high-frequency signal. ISD operates in an iterative, two-phase process: a prediction phase that uses multiple linear regression to generate high-frequency series from low-frequency …
Computer Vision-Based Framework For Data Extraction From Heterogeneous Financial Tables: A Comprehensive Approach To Unlocking Financial Insights, Iftakhar Ali Khandokar, Priya Deshpande
Computer Vision-Based Framework For Data Extraction From Heterogeneous Financial Tables: A Comprehensive Approach To Unlocking Financial Insights, Iftakhar Ali Khandokar, Priya Deshpande
Electrical and Computer Engineering Faculty Research and Publications
Information extraction from financial document images is crucial in computer vision and NLP, as financial data often exists in image or PDF format, enabling organizations to analyze and make informed business decisions using OCR advancements. The table contents of financial document images are one of the prominent structures to confine important portions of data of the document and many Deep learning-based methods have been proposed to detect Table regions inside document images. The shortcomings of the current approach are that it is bounded within the detection of the table region and struggles in cases such as handling different layouts and …
Juvenile Record Expungement Policy In Illinois, Emma Kudelka
Juvenile Record Expungement Policy In Illinois, Emma Kudelka
Res Publica - Journal of Undergraduate Research
This policy paper explores juvenile expungement policies and their broader social impact. Research suggests that lenient expungement laws help prevent discrimination in education, housing, and military service, aiding rehabilitation youth offenders' reintegration. The paper begins with a historical overview of Illinois juvenile law, highlighting its shift from punitive to rehabilitative approaches. It then examines key legislation, including the Juvenile Court Act, Juvenile Justice, and Delinquency Prevention Act, and Youth Opportunity and Fairness Act. Illinois's juvenile expungement laws are analyzed, covering eligibility, process, and timeline. A comparative analysis follows, contrasting Illinois' policies with those of California and Florida to emphasize differences …
A Critical Review Of Consumer Perception And Environmental Impacts Of Bioplastics In Sustainable Food Packaging, Junjie Lin, Amit K. Jaiswal, Swarna Jaiswal
A Critical Review Of Consumer Perception And Environmental Impacts Of Bioplastics In Sustainable Food Packaging, Junjie Lin, Amit K. Jaiswal, Swarna Jaiswal
Articles
As awareness of environmental issues deepens and the demand for sustainability grows among societies, businesses, and consumers, minimizing the environmental impact of food packaging has become increasingly important. Bioplastics offer a promising solution due to their use of renewable resources (such as plants), their biodegradability, and their ability to retain the protective properties of traditional plastics. This review discusses recent advancements and trends in sustainable food packaging, emphasizing the role of bioplastics. Several typical types of bioplastics are introduced, along with an analysis of their advantages and limitations. Furthermore, this study investigates consumers' attitudes toward bioplastic food packaging, emphasizing their …
Psychological Reactance Theory And Tax Evasion Intentions, Diana Falsetta, Brian C. Spilker
Psychological Reactance Theory And Tax Evasion Intentions, Diana Falsetta, Brian C. Spilker
Faculty Publications
This study experimentally examines how tax administration service inefficiencies in the form of tax return processing delays from paper-filed tax returns indirectly affect taxpayer tax evasion intentions through taxpayers’ psychological reactance to the delay. We further consider whether this indirect effect is different when the taxpayer willingly chooses to paper file their tax return versus when the taxpayer is forced to do so. Consistent with Psychological Reactance Theory (PRT), we find that when taxpayers receive delayed refunds, they experience psychological reactance (e.g., anger and frustration with the tax administration) that increases their tax evasion intentions. Further, we find that the …
Foreign Tax Holiday Participation And U.S. Job And Investment Loss, Zackery D. Fox, Linda Krull, Scott G. Rane
Foreign Tax Holiday Participation And U.S. Job And Investment Loss, Zackery D. Fox, Linda Krull, Scott G. Rane
Faculty Publications
We investigate whether foreign tax holiday participation among U.S. multinational companies is associated with offshoring U.S. jobs and other domestic investment activities. We find that foreign tax holiday participation is associated with (1) an increase in offshoring U.S. jobs and (2) a decrease in domestic investment, as proxied by changes in the number of employees, capital expenditures, and R&D activity. Furthermore, we find evidence suggesting that the association between targeted, temporary tax incentives provided by foreign tax holidays and firms’ domestic activities is stronger among firms with a smaller foreign presence and is distinct from the impact of foreign statutory …
Ai-Based Predictive Analytics For Network Operations, Timur Nikisin, David White
Ai-Based Predictive Analytics For Network Operations, Timur Nikisin, David White
Academic Poster Collection
AI-Based Predictive Analytics for Network Operations
Instructional Designer Perspectives On The Pursuit Of Quality In Online Course Design, Jason K. Mcdonald, Stephen C. Yanchar
Instructional Designer Perspectives On The Pursuit Of Quality In Online Course Design, Jason K. Mcdonald, Stephen C. Yanchar
Faculty Publications
In this qualitative study we investigated the experiences of instructional designers as they sought to build quality into online courses. Through semi-structured interviews, we explored what enabled and hindered their pursuit of quality, how they experienced their efforts in this regard, what mattered to them, and complexities that accompanied this pursuit. Our analysis of participant experiences suggested four themes: (1) connections between quality and designers’ ability to act autonomously; (2) connections between quality and collaborative, team-based relationships; (3) ambivalence due to tensions between autonomy and collaboration; and (4) ways of coping with limits on autonomy and collaboration. We conclude our …
Multipath-Enhanced Directional Modulation For Secure Mmwave On-Body Communication, Wasi Ur Rehman Khan, Max J. Ammann, Hossein Raghib Hokmabadi, William Scanlon, Adam Narbudowicz
Multipath-Enhanced Directional Modulation For Secure Mmwave On-Body Communication, Wasi Ur Rehman Khan, Max J. Ammann, Hossein Raghib Hokmabadi, William Scanlon, Adam Narbudowicz
Research Outputs: 2025-Present
This paper proposes Directional Modulation (DM) for secure millimeter-wave (mmWave) on-body communication, where security is enhanced by leveraging multipath propagation. The double two-ray ground reflection model is employed to analyze a two-antenna Multi-Input Single-Output (MISO) system placed on human skin. The system operates at 24 GHz with polarization tangential to the skin. Key parameters such as antenna-separation, antenna-to-skin spacing and phase difference between transmitter antennas are varied to analyze the resulting path gain. The results obtained from analytical model are experimentally validated using Yagi antennas placed over a forearm phantom. Based on the findings, the DM technique is implemented. The …
Disclosure Benchmarking By Lawyers: Evidence Fromthe Ipo Setting, Michael S. Drake, Jeff Mcmullin, Kenneth Merkley, Chase Potter, John Treu
Disclosure Benchmarking By Lawyers: Evidence Fromthe Ipo Setting, Michael S. Drake, Jeff Mcmullin, Kenneth Merkley, Chase Potter, John Treu
Faculty Publications
Lawyers play an important advisory role in drafting financial reports, yet empirical evidence documenting the influence of external legal counsel on this process remains sparse. This study focuses on a specific aspect of lawyers’ drafting process: the practice of reviewing disclosures previously filed by other issuers—a practice termed “disclosure benchmarking.” Using initial public offering (IPO) disclosures as the setting, we find that disclosure benchmarking is associated with amore efficient Securities and Exchange Commission (SEC) review process. We further find that it is associated with several measures of disclosure quality, including disclosures that are less likely to be revised in subsequent …
Two-Year Changes Of Macular Choroidal Thickness In Response To 0.01% Atropine Eye Drops: Results From The Myopia Outcome Study Of Atropine In Children (Mosaic) Clinical Trial, Emmanuel Kobia-Acquah, Gareth Lingham, Daniel Ian Flitcroft, James Loughman
Two-Year Changes Of Macular Choroidal Thickness In Response To 0.01% Atropine Eye Drops: Results From The Myopia Outcome Study Of Atropine In Children (Mosaic) Clinical Trial, Emmanuel Kobia-Acquah, Gareth Lingham, Daniel Ian Flitcroft, James Loughman
Research Outputs: 2025-Present
Purpose: To investigate 2-year changes in macular choroidal thickness (ChT) in children receiving 0.01% atropine eyedrops and its relationship with spherical equivalent refraction (SER) progression and axial length (AL) elongation. Methods: A total of 250 myopic children aged 6–16 years (167%–0.01% atropine, 83-placebo) were enrolled in the MOSAIC (ISRCTN36732601) clinical trial. Participants with complete 2-year ChT (Topcon Triton Swept-Source OCT), SER, and AL data were included in this study. Changes in macular ChT at 2 years and associations with changes in SER and AL elongation were analysed using linear mixed models. Results: A total of 187 children (126%–0.01% atropine, 61-placebo) …
W408-006f-01 - Business Office: Post Office- Correspondence And Memoranda, Business Office
W408-006f-01 - Business Office: Post Office- Correspondence And Memoranda, Business Office
University Archives Finding Aids
No abstract provided.
Digital Passivity-Based Control Of Underactuated Mechanical Systems, Mattia Mattioni, Pablo Borja
Digital Passivity-Based Control Of Underactuated Mechanical Systems, Mattia Mattioni, Pablo Borja
School of Engineering, Computing and Mathematics
Most sensors and controllers are discrete-time devices, which may have a detrimental impact on the performance of continuous-time control laws, even leading to unstable behaviors. This paper proposes a sampled-data passivity-based control approach that solves the regulation problem for discrete-time underactuated mechanical systems. Moreover, in contrast to other discrete-time controllers for these systems, the proposed control design method does not require the solution of partial differential equations. To illustrate the approach, we consider three case studies with computational details and simulations.
Prediction Of Compressive Strength Of Fly Ash-Recycled Mortar Based On Grey Wolf Optimizer–Backpropagation Neural Network, Jing Jing Shao, Lin Bin Li, Guang Ji Yin, Xiao Dong Wen, Yu Xiao Zou, Xiao Bao Zuo, Xiao Jian Gao, Shan Shan Cheng
Prediction Of Compressive Strength Of Fly Ash-Recycled Mortar Based On Grey Wolf Optimizer–Backpropagation Neural Network, Jing Jing Shao, Lin Bin Li, Guang Ji Yin, Xiao Dong Wen, Yu Xiao Zou, Xiao Bao Zuo, Xiao Jian Gao, Shan Shan Cheng
School of Engineering, Computing and Mathematics
The evaluation of the mechanical performance of fly ash-recycled mortar (FARM) is a necessary condition to ensure the efficient utilization of recycled fine aggregates. This article describes the design of nine mix proportions of FARMs with a low water/cement ratio and screens six mix proportions with reasonable flowability. The compressive strengths of FARMs were tested, and the influence of the water/cement ratio (w/c) and age on the compressive strength was analyzed. Meanwhile, a backpropagation neural network (BPNN) model optimized by the grey wolf optimizer (GWO), namely the GWO-BPNN model, was established to predict the compressive strength of FARM. The input …
New Ethereum-Based Distributed Pki With A Reward-And-Punishment Mechanism, Chong Gee Koa, Swee Huay Heng, Ji Jian Chin
New Ethereum-Based Distributed Pki With A Reward-And-Punishment Mechanism, Chong Gee Koa, Swee Huay Heng, Ji Jian Chin
School of Engineering, Computing and Mathematics
This paper explores the critical role of Public Key Infrastructure (PKI) in ensuring the security of electronic transactions, particularly in validating the authenticity of websites in online environments. Traditional Centralised PKIs (CPKIs) relying on Certificate Authorities (CAs) face a significant drawback due to their susceptibility to a single point of failure. To address this concern, Decentralised PKIs (DPKIs) have emerged as an alternative. However, both centralised and decentralised approaches encounter specific challenges. Researchers have made several attempts using blockchain-based PKI, which implements a reward and punishment mechanism to enhance the security of traditional PKI. Most of the attempts are focused …
Speech-Aided Facial Video Super Resolution With Accurate Lip Motion And Enhanced Frequency Details, Shailza Sharma, Vivek Singh, Abhinav Dhall, Vinay Kumar
Speech-Aided Facial Video Super Resolution With Accurate Lip Motion And Enhanced Frequency Details, Shailza Sharma, Vivek Singh, Abhinav Dhall, Vinay Kumar
School of Engineering, Computing and Mathematics
Despite recent breakthroughs in face hallucination, video face hallucination remains a challenging task due to the issue of consistency across video frames. The temporal dimension in videos makes it difficult to learn facial motion and maintain color uniformity throughout the sequence. To address these challenges, we propose a novel audio-visual cross-modality support based video face hallucination network. The framework excels in learning fine spatiotemporal motion patterns by leveraging the correlation between movement of the facial structure and associated speech signal. Another significant challenge generic to face hallucination is blurriness around the key facial regions, such as mouth and lips. These …
Modelling The Hydrodynamic Response Of A Floating Offshore Wind Turbine – A Comparative Study, Shimin Yu, Edward Ransley, Ling Qian, Yang Zhou, Scott Brown, Deborah Greaves, Martyn Hann, Anna Holcombe, Emma Edwards, Tom Tosdevin, Sudhir Jagdale, Qian Li, Yi Zhang, Ningbo Zhang, Shiqiang Yan, Qingwei Ma, Bonaventura Tagliafierro, Salvatore Capasso, Iván Martínez-Estévez, Malin Göteman, Hans Bernhoff, Madjid Karimirad, José M. Domínguez, Corrado Altomare, Giacomo Viccione, Alejandro J.C. Crespo, Moncho Goméz-Gesteira, Claes Eskilsson, Gael Verao Fernandez, Jacob Andersen
Modelling The Hydrodynamic Response Of A Floating Offshore Wind Turbine – A Comparative Study, Shimin Yu, Edward Ransley, Ling Qian, Yang Zhou, Scott Brown, Deborah Greaves, Martyn Hann, Anna Holcombe, Emma Edwards, Tom Tosdevin, Sudhir Jagdale, Qian Li, Yi Zhang, Ningbo Zhang, Shiqiang Yan, Qingwei Ma, Bonaventura Tagliafierro, Salvatore Capasso, Iván Martínez-Estévez, Malin Göteman, Hans Bernhoff, Madjid Karimirad, José M. Domínguez, Corrado Altomare, Giacomo Viccione, Alejandro J.C. Crespo, Moncho Goméz-Gesteira, Claes Eskilsson, Gael Verao Fernandez, Jacob Andersen
School of Engineering, Computing and Mathematics
This paper summarises the work conducted within the 1st FOWT (Floating Offshore Wind Turbine) Comparative Study organised by the EPSRC (UK) ‘Extreme loading on FOWTs under complex environmental conditions’ and ‘Collaborative computational project on wave structure interaction (CCP-WSI)’ projects. The hydrodynamic response of a FOWT support structure is simulated with a range of numerical models based on potential theory, Morison equation, Navier-Stokes solvers and hybrid methods coupling different flow solvers. A series of load cases including the static equilibrium tests, free decay tests, operational and extreme focused wave cases are considered for the UMaine VolturnUS-S semi-submersible platform, and the results …
Scaled Physical Modelling Of Floating Offshore Wind Turbines Using A Neural Network-Based Surrogate Model For Aerodynamic Emulation, Emma C Edwards, Edward Barbour, Tom Tosdevin, Edward Ransley, Kieran Monk, Alastair Reynolds, Anna Holcombe, Scott Brown, Deborah Greaves, Martyn Hann
Scaled Physical Modelling Of Floating Offshore Wind Turbines Using A Neural Network-Based Surrogate Model For Aerodynamic Emulation, Emma C Edwards, Edward Barbour, Tom Tosdevin, Edward Ransley, Kieran Monk, Alastair Reynolds, Anna Holcombe, Scott Brown, Deborah Greaves, Martyn Hann
School of Engineering, Computing and Mathematics
Scaled physical modelling of floating offshore wind turbines is a crucial step in the continued development of floating offshore wind to reach Net-Zero goals. However, it is an inherently difficult task due to the incongruity between Reynolds scaling (important for wind effects) and Froude scaling (important for wave effects). One option to overcome this difficulty is to use a real-time hybrid testing approach, whereby a Froude-scaled model is tested in a wave basin with a thruster replacing the wind turbine. Typically, a low-fidelity numerical model is run in real time to determine the appropriate aerodynamic thrust applied by the thruster. …
Determination Of Titanium Speciation In Consumer Plastics By Raman Microspectroscopy, Johanna Brazard, Takuji B.M. Adachi, Andrew Turner, Montserrat Filella
Determination Of Titanium Speciation In Consumer Plastics By Raman Microspectroscopy, Johanna Brazard, Takuji B.M. Adachi, Andrew Turner, Montserrat Filella
School of Geography, Earth and Environmental Sciences
The main component of objects made of plastic is an organic polymer matrix, but plastics also contain a wide range of other chemicals, such as additives, processing aids and unintentionally added substances. At present, the scientific and regulatory communities face challenges due to the lack of access to basic information on their quantity and identity, which is crucial in relation to potential toxicity, management, recycling, environmental fate and resource uses. Moreover, an additional problem is that some additives, such as titanium oxide (TiO2), can be present in different crystallographic forms, which makes it necessary to characterise not only …
Mind The Gap - The Need To Integrate Novel Plankton Methods Alongside Ongoing Long-Term Monitoring, Matthew M. Holland, Luis Felipe Artigas, Angus Atkinson, Mike Best, Eileen Bresnan, Michelle J. Devlin, Dafne Eerkes-Medrano, Marie Johansen, David G. Johns, Margarita Machairopoulou, Sophie Pitois, James Scott, Jos Schilder, Rowena Stern, Karen Tait, Callum Whyte, Claire Widdicombe, Abigail Mcquatters-Gollop
Mind The Gap - The Need To Integrate Novel Plankton Methods Alongside Ongoing Long-Term Monitoring, Matthew M. Holland, Luis Felipe Artigas, Angus Atkinson, Mike Best, Eileen Bresnan, Michelle J. Devlin, Dafne Eerkes-Medrano, Marie Johansen, David G. Johns, Margarita Machairopoulou, Sophie Pitois, James Scott, Jos Schilder, Rowena Stern, Karen Tait, Callum Whyte, Claire Widdicombe, Abigail Mcquatters-Gollop
School of Biological and Marine Sciences
Changes in plankton have important implications for ecosystem services, including supporting fish stocks, carbon sequestration, nutrient cycling, and oxygen production. Standard long-term plankton monitoring relies on light microscopy to identify and count plankton taxa, with methods fully supported by international standards, providing high quality trusted data. Novel methods, including imaging and molecular, offer means of collecting select types of plankton data efficiently, filling targeted knowledge gaps left by standard monitoring and generating a more complete picture of plankton dynamics. Standard and novel monitoring methods present different advantages and costs, positioning their suitability to address different management needs. Standard plankton monitoring …
Educator Professional Subjectivities In Gamification: Knowing, Being And Doing, Natalie-Jane Howard, Elizabeth J. Cook
Educator Professional Subjectivities In Gamification: Knowing, Being And Doing, Natalie-Jane Howard, Elizabeth J. Cook
Research outputs 2022 to 2026
Gamification has emerged as a prominent innovation in contemporary education, yet its influence on the enactment of educators’ professional subjectivities remains underexplored. As such, little is known about how online gamification applications like Kahoot shape the dynamic ways educators perceive, understand and enact their professional selves within higher education contexts. Adopting a tripartite framework of knowing (epistemological), being (ontological) and doing (praxiological), this qualitative study employed visual-elicitation interviews and remote observations with ten lecturers at a Middle Eastern college. The analysis revealed three key themes shaping educator subjectivities: creating and sharing quiz content; conforming with institutional culture; and infantilizing students …
Elizabeth Usher Memorial Lecture 2024: Speech-Language Pathology Practice In Aboriginal Spaces: A Journey Of Learning And Unlearning, Elizabeth Armstrong
Elizabeth Usher Memorial Lecture 2024: Speech-Language Pathology Practice In Aboriginal Spaces: A Journey Of Learning And Unlearning, Elizabeth Armstrong
Research outputs 2022 to 2026
In this paper I describe learnings gained from 15 years collaboration with Aboriginal colleagues in Australia, in endeavours to improve rehabilitation services for Aboriginal people with brain injury and their families. Colleagues include Aboriginal researchers, clinicians, and people with communication and other disorders associated with brain injury and their families. My research journey in this field has been made possible through the work, mentoring, and support of these colleagues who introduced me to Aboriginal ways of knowing, being, and doing. My journey has involved challenging and un-learning some widely accepted Western tenets of speech-language pathology practice in order to explore …
Driving Impactful Change: Entrepreneurial Insights For Social Responsibility In The Irish Context, Anna Zherdeva, Deirdre Mcquillan, Lucia Morales
Driving Impactful Change: Entrepreneurial Insights For Social Responsibility In The Irish Context, Anna Zherdeva, Deirdre Mcquillan, Lucia Morales
Articles
Today’s volatile situation at the global level, provoked by a significant rise in Economic and Political Uncertainty, emerged as an answer on countries attempts to manage the climate change crisis, armed conflicts, the rising cost of living, a growing divide between the more prosperous Global North and the poorest Global South that are reflected on the emergence of multifaceted, multiple and long-lasting crises. During periods of heightened instability and economic uncertainty, businesses struggle to build trusting relationships with stakeholders as they seek to reduce costs. Additionally, companies seek deep engagement as they confront the costs associated with sustainability challenges and …
A Computational Fluid Dynamics (Cfd) Based Assessment Of Animal Borne Data Logger Impact, Christopher Pass
A Computational Fluid Dynamics (Cfd) Based Assessment Of Animal Borne Data Logger Impact, Christopher Pass
School of Engineering, Computing and Mathematics Theses
Animal borne data loggers are powerful tools that provide researchers with valuable insight into the behaviour and ecology of free-ranging marine animals. Despite their usefulness, the addition of a tag inevitably alters the forces acting on a swimming body and can increase the energetic cost of swimming. Computational Fluid Dynamics (CFD) tools offer a powerful means of assessing tag impact and a number of previous works have employed CFD to this end but have typically been based on a range of simplifying assumptions. Chief amongst these simplifications is that animals can be modelled as rigid bodies with a simple tag …
Graphene Biosensors For The Detection Of Alzheimer's And Cardiovascular Disease Protein Biomarkers, Theodore Bungon
Graphene Biosensors For The Detection Of Alzheimer's And Cardiovascular Disease Protein Biomarkers, Theodore Bungon
School of Engineering, Computing and Mathematics Theses
Dementia describes a syndrome or group of symptoms associated with the decline of brain functioning such as loss of memory, mood, judgment, language, thinking speed, mental sharpness and other mental abilities. Different classes of Dementia are Jakob Disease, Korsakoff Syndrome, Vascular dementia, Parkinson’s disease, Huntington disease, young onset dementia, Alzheimer’s disease (AD) etc. At present, AD is irreversible and incurable, and it worsens overtime, it is neurodegenerative, caused by the accumulation or build-up of abnormal protein in the brain. It is a type of dementia that is common, affecting about 60% of patients with dementia diagnosis. Globally, over 54 million …
Automated Vulnerability Scanning And Security Audit Framework For Maritime Systems, Avanthika Vineetha Harish
Automated Vulnerability Scanning And Security Audit Framework For Maritime Systems, Avanthika Vineetha Harish
School of Engineering, Computing and Mathematics Theses
The maritime industry is a well-established sector, with the shipping industry dating back hundreds of years. The devices in this sector differ from those in the Information Technology (IT) sector in their usage, operations, hardware, andprotocols. Technological advancements have introduced new challenges in the sector, including the increased risk of cyber attacks. To effectively identify, respond to, and analyse these threats, it is essential to understand the cyber securityvulnerabilities in maritime systems and system-of-systems.Currently, there are no standardised methods or automated tools for conducting cyber security testing of maritime systems. This thesis presents an automated vulnerability scanning and security audit …