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Computer Vision-Based Framework For Data Extraction From Heterogeneous Financial Tables: A Comprehensive Approach To Unlocking Financial Insights, Iftakhar Ali Khandokar, Priya Deshpande Jan 2025

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 …

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S-Methyl Cysteine Sulfoxide And Its Potential Role In Human Health: A Scoping Review, Caroline R. Hill, Alex Haoci Liu, Lyn Mccahon, Liezhou Zhong, Armaghan Shafaei, Lois Balmer, Joshua R. Lewis, Jonathan M. Hodgson, Lauren C. Blekkenhorst Jan 2025

S-Methyl Cysteine Sulfoxide And Its Potential Role In Human Health: A Scoping Review, Caroline R. Hill, Alex Haoci Liu, Lyn Mccahon, Liezhou Zhong, Armaghan Shafaei, Lois Balmer, Joshua R. Lewis, Jonathan M. Hodgson, Lauren C. Blekkenhorst

Research outputs 2022 to 2026

Higher intakes of cruciferous and allium vegetables are associated with a lower risk of cardiometabolic-related outcomes in observational studies. Whilst acknowledging the many healthy compounds within these vegetables, animal studies indicate that some of these beneficial effects may be partially mediated by S-methyl cysteine sulfoxide (SMCSO), a sulfur-rich, non-protein, amino acid found almost exclusively within cruciferous and alliums. This scoping review explores evidence for SMCSO, its potential roles in human health and possible mechanistic action. After systematically searching several databases (EMBASE, MEDLINE, SCOPUS, CINAHL Plus Full Text, Agricultural Science), we identified 21 original research articles meeting our inclusion criteria. These …

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A Testing Load: A Review Of Cognitive Load In Computer And Paper-Based Learning And Assessment, James Pengelley, Peter R. Whipp, Anabela Malpique Jan 2025

A Testing Load: A Review Of Cognitive Load In Computer And Paper-Based Learning And Assessment, James Pengelley, Peter R. Whipp, Anabela Malpique

Research outputs 2022 to 2026

The rising use of technology in classrooms has also brought with it a concomitant wave of computer-based assessments. The argument for computer-based testing is often framed in terms of efficiency and data management: computer-based tests facilitate more efficient processing of test data and the rate at which feedback can be leveraged for student learning rather than being framed in terms of the direct effects that students experience from engaging with novel learning tools. Whilst potentially beneficial, for some students the outcomes of computer-based tests may be counter-productive. This review considers the cognitive, and often implicit, consequences of testing mode upon …

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Measuring Career Aspirations In Science, Technology, Engineering, Mathematics And Education, Michael Fitzgerald, Saeed Salimpour, David Mckinnon, Rachel Freed, Dan Reichart Jan 2025

Measuring Career Aspirations In Science, Technology, Engineering, Mathematics And Education, Michael Fitzgerald, Saeed Salimpour, David Mckinnon, Rachel Freed, Dan Reichart

Research outputs 2022 to 2026

There has been a sustained interest in student perceptions about STEM fields and their choice of careers over the past few decades. Research has shown that there is a decline in students pursuing STEM careers, and this has raised global concern. Despite these issues, no unistructural, broad, parsimonious and unambiguous quantitative instrument exists to probe student career aspirations. This paper highlights the background, extension and validation of an instrument, derived from a previous science-focussed high-quality instrument that allows student career aspirations to be quantitatively characterised. Participants were 1221 undergraduate students, 1003 of whom were judged to have provided good data, …

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Dough Rheology Properties As Affected By The Inclusion Of Oat Drink Residue Flour: A Multivariate Analysis Approach, Mahmoud Said Rashed, Eimear Gallagher, Jesus M. Frias, Milica Pojić, Shivani Pathania Jan 2025

Dough Rheology Properties As Affected By The Inclusion Of Oat Drink Residue Flour: A Multivariate Analysis Approach, Mahmoud Said Rashed, Eimear Gallagher, Jesus M. Frias, Milica Pojić, Shivani Pathania

Articles

The global shift towards plant-based food consumption presents significant environmental benefits, yet the consequential rise in related by-products still imposes a challenge to be addressed. The present work was carried out to evaluate the rheological properties of bread dough as affected by the incorporation of dry fractionated oat drink residue flours as a functional ingredient to identify the optimum condition for incorporating fibre-rich ingredients in bakery products. Mechanically dry fractionated, dried oat drink residue flour of particle size F1: > 150, F2: 150-224, and F3: 224-300 μm was blended with strong wheat flour at 10% and 20% substitution levels of the …

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Enhanced Force Sensing Utilizing A Glass-Supported Wgm Microbubble Resonator, Yiming Shen, Zhe Wang, V. R. Anand, Zhuochen Wang, Rayhan Habib Jibon, Anuradha Rout, Bo Cai, Qiang Wu, Yuliya Semenova Jan 2025

Enhanced Force Sensing Utilizing A Glass-Supported Wgm Microbubble Resonator, Yiming Shen, Zhe Wang, V. R. Anand, Zhuochen Wang, Rayhan Habib Jibon, Anuradha Rout, Bo Cai, Qiang Wu, Yuliya Semenova

Research Outputs: 2025-Present

Mechanical force sensors are critical for a wide range of advanced applications. This paper presents a high-performance whispering gallery mode (WGM) force sensor based on a glass-supported microbubble resonator (MBR). By incorporating the proposed glass support design, the proposed sensor achieves the highest force sensitivity reported for MBR-based structures, of 125.71 pm/mN and a detection limit of 52.26 μN. The sensor has a response time of 3.5 ms, enabling rapid detection of dynamic force changes. Further tests show that the sensor is capable of detecting subtle forces, such as those created by water droplets and a gentle breeze, paving the …

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Multi-Modal Framework For Autism Severity Assessment Using Spatio-Temporal Graph Transformers, Kush Gupta, Amir Aly, Emmanuel Ifeachor Jan 2025

Multi-Modal Framework For Autism Severity Assessment Using Spatio-Temporal Graph Transformers, Kush Gupta, Amir Aly, Emmanuel Ifeachor

School of Engineering, Computing and Mathematics

Diagnosing Autism Spectrum Disorder (ASD) remains challenging, as it often relies on subjective evaluations and traditional methods using fMRI data. This paper proposes an innovative multi-modal framework that leverages spatiotemporal graph transformers to assess ASD severity using skeletal and optical flow data from the MMASD dataset. Our approach captures movement synchronization between children with ASD and therapists during play therapy interventions. The framework integrates a spatial encoder, a temporal transformer, and an I3D network for comprehensive motion analysis. Through this multi-modal approach, we aim to deliver reliable ASD severity scores, enhancing diagnostic accuracy and offering a scalable, robust alternative to …

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Digital Passivity-Based Control Of Underactuated Mechanical Systems, Mattia Mattioni, Pablo Borja Jan 2025

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.

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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 Jan 2025

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 …

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New Ethereum-Based Distributed Pki With A Reward-And-Punishment Mechanism, Chong Gee Koa, Swee Huay Heng, Ji Jian Chin Jan 2025

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 …

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Mesoscale Modeling For Predicting Effective Properties And Damage Behavior Of Geopolymer Concrete, Feiyu Shi, Shanshan Cheng, Longyuan Li Jan 2025

Mesoscale Modeling For Predicting Effective Properties And Damage Behavior Of Geopolymer Concrete, Feiyu Shi, Shanshan Cheng, Longyuan Li

School of Engineering, Computing and Mathematics

Geopolymer concrete is a sustainable construction material and is considered as a promising alternative to traditional Portland cement concrete. However, there is still not much research on the effective properties and damage behavior of geopolymer concrete with consideration of its heterogeneous characteristics by means of mesoscale models combined with the regularized microplane damage model. Here, in this research, an easy and simpler approach for generating concrete mesoscale models and characterizing the angular characteristics of aggregate particles is presented. After the proposed mesoscale modeling was validated by numerical, experimental and theoretical models, it was employed further to predict the effective properties …

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State Space Model Of Airflow In The Human Vocal Apparatus, Ian Howard Jan 2025

State Space Model Of Airflow In The Human Vocal Apparatus, Ian Howard

School of Engineering, Computing and Mathematics

To simulate both airflow and air pressure required for speech production, we developed a nonlinear state-space model of airflow in the human speech apparatus. We modeled the lungs as a mechanical, force-driven piston pump venting into a simplified larynx model, represented as a valve with time-varying resistance to airflow. The pump incorporates the effects of elasticity, viscosity, friction, and inertia, as well as differential air pressure. To maintain a constant target airflow through the larynx, a proportional-derivative (PD) controller applies force and regulates the piston. The model was implemented in MATLAB. Simulation results demonstrate that the model can maintain a …

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Developing An Artificial Intelligence Framework For Identifying Fusion Blood-Based Biomarkers In Alzheimer's Disease, Ali H. Al-Nuaimi, Mohammed Kamal Nsaif, Shaymaa Al-Juboori Jan 2025

Developing An Artificial Intelligence Framework For Identifying Fusion Blood-Based Biomarkers In Alzheimer's Disease, Ali H. Al-Nuaimi, Mohammed Kamal Nsaif, Shaymaa Al-Juboori

School of Engineering, Computing and Mathematics

Alzheimer’s Disease (AD) is an irreversible neurological disorder, a major cause of disability among the elderly, with no effective therapeutic options currently available. It is an asymp-tomatic disease in the prodromal stages and begins many years before clinical appearances. Early diagnosis of AD allows patients to obtain appropriate healthcare assistance, accelerating the development of new medications. A biomarker that evaluates the alterations in the brain cells produced by AD in its preliminary periods might be significant for its early identification. Blood-based biomarkers (BBBMs) facilitate the early detection of AD. The BBBMs detection procedure is cost-efficient and minimally invasive. The aim …

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Artificial Intelligence Powered System For Epilepsy Detection Using Eeg Biomarkers, Ali H. Al-Nuaimi, Shaymaa Al-Juboori Jan 2025

Artificial Intelligence Powered System For Epilepsy Detection Using Eeg Biomarkers, Ali H. Al-Nuaimi, Shaymaa Al-Juboori

School of Engineering, Computing and Mathematics

One of the most prevalent neurological disorders is epilepsy. Epileptic seizures can occurrepeatedly in people with the condition for no recognisable reason. The diagnostic methodsdependent on EEG are promising. EEG has uncovered the dynamic functioning of all brain areasthroughout time. Its low cost, non-invasiveness, and simply make it crucial for clinicalevaluations of brain function. Integrating multiple EEG biomarkers as a compound biomarkercould provide a high performance that may accelerate the diagnosis speeds. Artificial intelligencetechniques such as machine learning and deep learning provide a significant result in healthcareapplications. Logistic Regression (LR), Naive Bayes (NB), and Neural Network (NN) wereevaluated using a …

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Speech-Aided Facial Video Super Resolution With Accurate Lip Motion And Enhanced Frequency Details, Shailza Sharma, Vivek Singh, Abhinav Dhall, Vinay Kumar Jan 2025

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 …

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A Data-Driven Approach To Offshore Wind Forecasting In The Celtic Sea, Ajit C Pillai, Peter Jenkin, Ian Ashton, Edward Steele, Marcus Juniper, Jiaxin Chen Jan 2025

A Data-Driven Approach To Offshore Wind Forecasting In The Celtic Sea, Ajit C Pillai, Peter Jenkin, Ian Ashton, Edward Steele, Marcus Juniper, Jiaxin Chen

School of Engineering, Computing and Mathematics

Accurate weather forecasting is crucial for various industries,including offshore wind, which is vital for global net zeroenergy goals. Machine learning models, trained on historicaldata, offer a new opportunity by replacing traditional physicsbasedequations. These models can learn patterns not alwaysrepresented by physical equations, potentially increasing the accuracyand efficiency of weather forecasting compared to traditionalNumerical Weather Prediction (NWP).This study applies a machine learning framework (MaLCOM)to offshore wind forecasting in the Celtic Sea. It uses anattention-based LSTM recurrent neural network to learn temporalpatterns and a random forest-based spatial nowcasting model,trained on ERA5 data, for spatiotemporal predictions. Windsderived from wave spectra measured by buoys …

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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 Jan 2025

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 …

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The Effect Of Device Geometry On The Performance Of A Wave Energy Converter, Emma C. Edwards, Craig Whitlam, John Chapman, Jack Hughes, Bryony Redfearn, Scott Brown, Scott Draper, Alistair G.L. Borthwick, Graham Foster, Dick K.P. Yue, Martyn Hann, Deborah Greaves Jan 2025

The Effect Of Device Geometry On The Performance Of A Wave Energy Converter, Emma C. Edwards, Craig Whitlam, John Chapman, Jack Hughes, Bryony Redfearn, Scott Brown, Scott Draper, Alistair G.L. Borthwick, Graham Foster, Dick K.P. Yue, Martyn Hann, Deborah Greaves

School of Engineering, Computing and Mathematics

Wave energy presents an excellent opportunity to add much-needed diversification to the global renewable energy portfolio. However, a competitive levelised cost of electricity for wave energy conversion devices is yet to be proven. Here, we optimise the geometry of a wave energy device to maximise power while also minimising the power take-off reaction moments. Using theory, numerical modelling and optimisation techniques, we show that by including minimisation of reaction moments in the optimisation, instead of only maximisation of power, it is possible to substantially lower the design loads while maintaining high efficiency. Using the underlying physics of how geometry affects …

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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 Jan 2025

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. …

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A New Cfd-Mbd Wave-Structure Interaction Model: Coupling Openfoam With Chrono, Haifei Chen, Tianyuan Wang, Deborah Greaves, Hongda Shi, Qingping Zou Jan 2025

A New Cfd-Mbd Wave-Structure Interaction Model: Coupling Openfoam With Chrono, Haifei Chen, Tianyuan Wang, Deborah Greaves, Hongda Shi, Qingping Zou

School of Engineering, Computing and Mathematics

Interconnected multibody floating structures have gained popularity recently. The dynamic response of moored interconnected floating bodies to wave action, however, are complicated and challenging to model and analyze. To tackle the problem, a novel wave-structure-interaction (WSI) model is developed for the first time by coupling a finite volume CFD model, OpenFOAM, with Project Chrono, a multi-physics simulation engine for multibody dynamics (MBD) and finite element analysis, through linking pre-compiled dynamic libraries. This paper focuses on dynamic behavior of rigid structures restrained with a mooring system. To account for the floating body motion in the fluid solver, both mesh deformation and …

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Advancing Point-Of-Care Testing With Nanomaterials-Based Screen-Printing Electrodes, S. Nazir Jan 2025

Advancing Point-Of-Care Testing With Nanomaterials-Based Screen-Printing Electrodes, S. Nazir

School of Engineering, Computing and Mathematics

Although numerous studies have been conducted on multiple screen-printing electrodes (SPEs), little emphasis has been placed on systematically assessing scholarly work on nanomaterial-equipped SPEs in bioanalytical research. The fabrication of state-of-the-art portable screen-printing measuring devices represents significant disease monitoring and diagnosis advancements. This review classifies screen-printing electrodes based on the nanomaterials used. It discusses cost, regulatory approvals for portable screen-printing electrodes in point-of-care diagnostics, sensitivity, specificity, size reductions, and proposed solutions. It looks into the significance of new nanomaterials and substrates in fabricating point-of-care diagnostic devices and miniaturisation techniques. The review primarily focuses on the recent downsizing advances that have …

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Conservation Planning For Promoting Ecosystem Service Provisioning Outside Protected Area Networks, Florence Godfrey Tarimo, Francis Moyo, Claire Kelly, Linus Kasian Munishi Jan 2025

Conservation Planning For Promoting Ecosystem Service Provisioning Outside Protected Area Networks, Florence Godfrey Tarimo, Francis Moyo, Claire Kelly, Linus Kasian Munishi

School of Geography, Earth and Environmental Sciences

Among factors that contribute to global biodiversity loss, habitat loss through unsustainable land use and land cover changes has gained prominence, with impacts being exacerbated by increasing human populations. Establishing protected area networks (PANs) is strongly advocated by national and international mechanisms, such as the Convention on Biological Diversity (CBD), as a primary strategy to guide biodiversity conservation and management; however, this can undermine conservation efforts outside protected areas. Understanding how people and biodiversity overlap and interact outside protected area networks (OPAN areas) is essential for setting realistic, sustainable targets to guide biodiversity conservation and ecosystem service provision beyond PAN. …

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Machine Learning-Based Seismic Response Forecasting Using Feature Mapping Algorithms And Scientometric Analysis Of Nailed Vertical Excavation In A Soil Mass, Surya Muthukumar, Dhanya Sathyan, Premjith B, Sanjay Kumar Shukla Jan 2025

Machine Learning-Based Seismic Response Forecasting Using Feature Mapping Algorithms And Scientometric Analysis Of Nailed Vertical Excavation In A Soil Mass, Surya Muthukumar, Dhanya Sathyan, Premjith B, Sanjay Kumar Shukla

Research outputs 2022 to 2026

Seismic analysis often involves significant uncertainty and requires detailed observations. The traditional approaches are constrained by unclear mechanisms and imprecise models to predict the stability of geostructures. The research gap between the accuracy of observed and predicted values can be bridged by employing artificial intelligence-based machine learning (ML) models. The seismic displacement of the nailed soil wall obtained from experimental studies were assessed using suitable ML approaches. Laboratory studies revealed that the critical acceleration was increased by 32% on the inclusion of nails of reinforcement length to excavation height ratio (L/H) to 0.6, and by 17% when the (L/H) was …

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Educator Professional Subjectivities In Gamification: Knowing, Being And Doing, Natalie-Jane Howard, Elizabeth J. Cook Jan 2025

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 …

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Non-Stereotypy (To Species) In Mysticete Downsweeps, Paul Nguyen Hong Duc, Christine Erbe, Shyam Madhusudhana, Daniel Wilkes, Lachlan Gill, Cristina Tollefsen, Narissa De Bruin, Aiyana Erbeking, Curt Jenner, Micheline Jenner, Angela Recalde-Salas, Chandra P. Salgado Kent, Kautilya Srivastava, Chong Wei, Robert Mccauley Jan 2025

Non-Stereotypy (To Species) In Mysticete Downsweeps, Paul Nguyen Hong Duc, Christine Erbe, Shyam Madhusudhana, Daniel Wilkes, Lachlan Gill, Cristina Tollefsen, Narissa De Bruin, Aiyana Erbeking, Curt Jenner, Micheline Jenner, Angela Recalde-Salas, Chandra P. Salgado Kent, Kautilya Srivastava, Chong Wei, Robert Mccauley

Research outputs 2022 to 2026

The Australian EEZ provides habitat for ten species of mysticete whales seasonally supporting critical life functions ranging from feeding to breeding. All of these species produce downsweeping calls, which may confound passive acoustic monitoring efforts. In an attempt to optimize a detector for Eastern Indian Ocean pygmy blue whale (EIOPBW) downsweeps, we tried a spectrogram correlator based on confirmed templates and a neural network trained on general blue whale D-calls followed by clustering algorithms. Outputs were manually validated by bioacousticians. We found that downsweeps exhibit significant variability and form a graded continuum of acoustic features, as opposed to clusters. Comparative …

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Robust Trend Estimation From Temporally Irregular Recreational Fisheries Surveys: A Panel Modeling Framework For Sparse Time Series, Ebenezer Afrifa-Yamoah, S. M. Taylor, Ute A. Mueller Jan 2025

Robust Trend Estimation From Temporally Irregular Recreational Fisheries Surveys: A Panel Modeling Framework For Sparse Time Series, Ebenezer Afrifa-Yamoah, S. M. Taylor, Ute A. Mueller

Research outputs 2022 to 2026

Monitoring of recreational fisheries faces ongoing challenges due to irregular data collection and sampling gaps. We used a robust statistical approach combining cross-sectional panel modeling with generalized linear models to analyze discontinuous time series data. We modeled recreational boating patterns across four distinct Western Australian locations using camera monitoring data (2011–2014), and integrated weather conditions and temporal factors to improve trend estimation. Environmental conditions were strongly related to boating activity, particularly wind effects of distinct north–south patterns. Recreational activity decreased at northern locations during easterly winds and at southern locations during northerly winds. Cross-validation demonstrated how environmental factors can be …

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If, And How, To Group By ‘Ability’– Considerations About Class Group Formation, Olivia Johnston, Suzanne Macqueen, Wei Zhang, Nerida Spina, Rebecca Spooner-Lane Jan 2025

If, And How, To Group By ‘Ability’– Considerations About Class Group Formation, Olivia Johnston, Suzanne Macqueen, Wei Zhang, Nerida Spina, Rebecca Spooner-Lane

Research outputs 2022 to 2026

Many schools choose to organise students into classes according to their perceived “ability”, despite evidence that the practice is not beneficial for students, overall. Class grouping by “ability” can exacerbate existing social inequalities by segregating students according to pre-existing educational advantage, which has unjustifiable consequences from a social justice perspective. There is little understanding of how decisions about class groupings are made, but such understanding is a crucial basis for exploring the persistent prevalence of this inequitable and exclusionary practice in Australian schools. This study characterises within-school processes used to decide how to group students into classes. Surveys were completed …

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Extreme Value Theory Analysis Of High Emitter Trends Across Four Us Cities From 1995 To 2021, M. Matti Maricq, Gary A. Bishop Jan 2025

Extreme Value Theory Analysis Of High Emitter Trends Across Four Us Cities From 1995 To 2021, M. Matti Maricq, Gary A. Bishop

Fuel Efficiency Automobile Test Publications

Extreme value theory provides a direct means to characterize the distribution of high emitters within a vehicle fleet and calculate statistical confidence intervals for comparisons. Defining a “high emitter” as the maximum emitter in a random sample of N vehicles implies in the limit of large N that high emitters follow an extreme value distribution, comprised of three distinct domains. The analysis of over twenty years of roadside remote sensing emissions measurements in Chicago, Denver, Los Angeles and Tulsa reveals clear differences between gasoline vehicle high emitter distributions across pollutants (hydrocarbons (HC), carbon monoxide (CO) and nitric oxide (NO)), but …

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Specialisation In The Primary Education Community, Kevin Sullivan, Susan Main, Joseph J. Scott, Kin Eng Chin, Jason Boron, Matthew Byrne, Eibhlish O'Hara, Elisabeth Taylor, Rozita Dass, Kuki Singh, Helen Adam, Gail Berman Jan 2025

Specialisation In The Primary Education Community, Kevin Sullivan, Susan Main, Joseph J. Scott, Kin Eng Chin, Jason Boron, Matthew Byrne, Eibhlish O'Hara, Elisabeth Taylor, Rozita Dass, Kuki Singh, Helen Adam, Gail Berman

Research outputs 2022 to 2026

Australian students’ results in international assessments have led to considerable attention on teacher quality and, more specifically, on how well pre-service teachers (PSTs) are being prepared to teach. Acting on one of the recommendations in the Action Now, Classroom Ready Teachers Report (TEMAG, 2014), the Australian Institute for Teaching and School Leadership updated Accreditation Standards and Procedures for Initial Teacher Education (ITE) programs to include primary specialisation into ITE courses (AITSL, 2017). The Australian Government’s Next Steps report (2022) also identified the need to obtain data on the specialisation of ITE graduates to assist with issues of supply and demand. …

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Finding Time-Proximity Communities In Temporal Heterogeneous Information Networks, Yifu Tang, Chengfei Liu, Lu Chen, Rui Zhou, Jianxin Li Jan 2025

Finding Time-Proximity Communities In Temporal Heterogeneous Information Networks, Yifu Tang, Chengfei Liu, Lu Chen, Rui Zhou, Jianxin Li

Research outputs 2022 to 2026

Community search in heterogeneous information networks (HINs) often neglects temporal dynamics, yielding structures that poorly reflect real-world interactions. We introduce the Temporal HIN Community Search (THCS) problem and propose a novel core model that captures both structural cohesiveness and temporal relevance. Our model uses a time span constraint to ensure interaction recency and a query interval for flexible temporal exploration, filtering irrelevant connections while preserving structural density. We develop two efficient online algorithms—Center-based Sliding Window search and Incremental Center Expansion—that exploit meta-path symmetry and dynamic connectivity tracking. For frequent queries, we design a Temporal HIN Core Interval-Index (TCI-Index), organising minimal …

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