Physical Sciences and Mathematics Commons^™

Comparative Static And Dynamic Analyses Of Solvents For Removal Of Asphaltene And Wax Deposits Above- And Below-Surface At An Iranian Carbonate Oil Field, Milad Norouzpour, Amin Azdarpour, Rafael M. Santos, Ali Esfandiarian, Moein Nabipour, Erfan Mohammadian, Abbas K. Manshad, Alireza Keshavarz

Research outputs 2022 to 2026

During production from oil wells, the deposition of asphaltene and wax at surface facilities and porous media is one of the major operational challenges. The crude oil production rate is significantly reduced due to asphaltene deposition inside the reservoir. In addition, the deposition of these solids inside the surface facilities is costly to oil companies. In this study, the efficiency of different solvents in dissolving asphaltene and wax was investigated through static and dynamic tests. The analysis of solid deposits from the surface choke of one of the Iranian carbonate oil fields showed that they consisted of 41.3 wt % …

Edna Metabarcoding Of Avocado Flowers: ‘Hass’ It Got Potential To Survey Arthropods In Food Production Systems?, Joshua H. Kestel, Philip W. Bateman, David L. Field, Nicole E. White, Rose Lines, Paul Nevill

Research outputs 2022 to 2026

In the face of global biodiversity declines, surveys of beneficial and antagonistic arthropod diversity as well as the ecological services that they provide are increasingly important in both natural and agro-ecosystems. Conventional survey methods used to monitor these communities often require extensive taxonomic expertise and are time-intensive, potentially limiting their application in industries such as agriculture, where arthropods often play a critical role in productivity (e.g. pollinators, pests and predators). Environmental DNA (eDNA) metabarcoding of a novel substrate, crop flowers, may offer an accurate and high throughput alternative to aid in the detection of these managed and unmanaged taxa. Here, …

Further Investigation Of Lead Exposure As A Potential Threatening Process For A Scavenging Marsupial Species, D. J. Hutchinson, E. M. Jones, J. M. Pay, J. R. Clarke, Michael T. Lohr, J. O. Hampton

Research outputs 2022 to 2026

There is a growing recognition of the harmful effects of lead exposure on avian and mammalian scavengers. This can lead to both lethal and non-lethal effects which may negatively impact wildlife populations. Our objective was to assess medium-term lead exposure in wild Tasmanian devils (Sarcophilus harrisii). Frozen liver samples (n = 41), opportunistically collected in 2017–2022, were analysed using inductively coupled plasma mass spectrometry (ICP-MS) to determine liver lead concentrations. These results were then used to calculate the proportion of animals with elevated lead levels ( > 5 mg/kg dry weight) and examine the role of explanatory variables that may have …

Modification Of Cellulose Ether With Organic Carbonate For Enhanced Thermal And Rheological Properties: Characterization And Analysis, Ghulam Abbas, Abdul H. Tunio, Khalil R. Memon, Aftab A. Mahesar, Faisal H. Memon, Ghazanfer R. Abbasi

Research outputs 2022 to 2026

Reduction in viscosity at higher temperatures is the main limitation of utilizing cellulose ethers in high thermal reservoir conditions for petroleum industry applications. In this study, cellulose ether (hydroxyethyl methyl cellulose (HEMC)) is modified using organic carbonates, i.e., propylene carbonate (PC) and diethyl carbonate (DEC), to overcome the limitation of reduced viscosity at high temperatures. The polymer composites were characterized through various analytical techniques, including Fourier-transform infrared (FTIR), H-NMR, X-ray diffraction (XRD), scanning electron microscope (SEM), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), -potential measurement, molecular weight determination, and rheology measurements. The experimental results of structural and morphological characterization confirm …

Co-Designing A Multi-Criteria Approach To Ranking Hazards To And From Australia’S Emerging Offshore Blue Economy, Mischa P. Turschwell, Christopher J. Brown, Myriam Lacharité, Jess Melbourne-Thomas, Keith R. Hayes, Rodrigo H. Bustamante, Jeffrey M. Dambacher, Karen Evans, Pedro Fidelman, Darla H. Macdonald, Ingrid Van Putten, Graham Wood, Nagi Abdussamie, Mathilda Bates, Damien Blackwell, Steven D'Alessandro, Ian Dutton, Jessica A. Ericson, Christopher L. J. Frid, Carmel Mcdougall, Mary-Anne Lea, David Rissik, Rowan Trebilco, Elizabeth A. Fulton

Research outputs 2022 to 2026

A multi-sectoral assessment of risks can support the management and investment decisions necessary for emerging blue economy industries to succeed. Traditional risk assessment methods will be challenged when applied to the complex socio-ecological systems that characterise offshore environments, and when data available to support management are lacking. Therefore, there is a need for assessments that account for multiple sectors. Here we describe the development of an efficient method for an integrated hazard analysis that is a precursor to full risk assessments. Our approach combines diverse disciplinary expertise, expert elicitation and multi-criteria analysis to rank hazards, so it encompasses all types …

Cyber-Aidd: A Novel Approach To Implementing Improved Cyber Security Resilience For Large Australian Healthcare Providers Using A Unified Modelling Language Ontology, Martin Dart, Mohiuddin Ahmed

Research outputs 2022 to 2026

Purpose: This paper proposes a novel cyber security risk governance framework and ontology for large Australian healthcare providers, using the structure and simplicity of the Unified Modelling Language (UML). This framework is intended to mitigate impacts from the risk areas of: (1) cyber-attacks, (2) incidents, (3) data breaches, and (4) data disclosures. Methods Using a mixed-methods approach comprised of empirical evidence discovery and phenomenological review, existing literature is sourced to confirm baseline ontological definitions. These are supplemented with Australian government reports, professional standards publications and legislation covering cyber security, data breach reporting and healthcare governance. Historical examples of healthcare cyber …

Methane Emissions In Seagrass Meadows As A Small Offset To Carbon Sequestration, Yvonne Y. Y. Yau, Gloria Reithmaier, Caludia Majtényi-Hill, Oscar Serrano, Nerea Piñeiro-Juncal, Martin Dahl, Miguel A. Mateo, Stefano Bonaglia, Isaac R. Santos

Research outputs 2022 to 2026

Seagrass meadows are effective carbon sinks due to high primary production and sequestration in sediments. However, methane (CH4) emissions can partially counteract their carbon sink capacity. Here, we measured diffusive sediment-water and sea-air CO2 and CH4 fluxes in a coastal embayment dominated by Posidonia oceanica in the Mediterranean Sea. High-resolution timeseries observations revealed large spatial and temporal variability in CH4 concentrations (2–36 nM). Lower sea-air CH4 emissions were observed in an area with dense seagrass meadows compared to patchy seagrass. A 6%−40% decrease of CH4 concentration in the surface water around noon indicates that photosynthesis likely limits CH4 fluxes. Sediments …

Microscale Pollen Release And Dispersal Patterns In Flowering Grass Populations, Carl A. Frisk, Godfrey P. Apangu, Geoffrey M. Petch, Simon Creer, Mary Hanson, Beverley Adams-Groom, Carsten A. Skjøth

Research outputs 2022 to 2026

Characterizing pollen release and dispersion processes is fundamental for knowledge advancement in ecological, agricultural and public health disciplines. Understanding pollen dispersion from grass communities is especially relevant due to their high species-specific allergenicity and heterogeneously distributed source areas. Here, we aimed to address questions concerning fine level heterogeneity in grass pollen release and dispersion processes, with a focus on characterizing the taxonomic composition of airborne grass pollen over the grass flowering season using eDNA and molecular ecology methods. High resolution grass pollen concentrations were compared between three microscale sites ( < 300 m apart) in a rural area in Worcestershire, UK. The grass pollen was modelled with local meteorology in a MANOVA (Multivariate ANOVA) approach to investigate factors relevant to pollen release and dispersion. Simultaneously, airborne pollen was sequenced using Illumina MySeq for metabarcoding, analysed against a reference database with all UK grasses using the R packages DADA2 and phyloseq to calculate Shannon's Diversity Index ( -diversity). The flowering phenology of a local Festuca rubra population was observed. We found that grass pollen concentrations varied on a microscale level, likely attributed to local topography and the dispersion distance of pollen from flowering grasses in local source areas. Six genera (Agrostis, Alopecurus, Arrhenatherum, Holcus, Lolium and Poa) dominated the pollen season, comprising on average 77 % of the relative abundance of grass species reads. Temperature, solar radiation, relative humidity, turbulence and wind speeds were found to be relevant for grass pollen release and dispersion processes. An isolated flowering Festuca rubra population contributed almost 40 % of the relative pollen abundance adjacent to the nearby sampler, but only contributed 1 % to samplers situated 300 m away. This suggests that most emitted grass pollen has limited dispersion distance and our results show substantial variation in airborne grass species composition over short geographical scales.

Seagrass Posidonia Escarpments Support High Diversity And Biomass Of Rocky Reef Fishes, Oscar Serrano Gras, Karina Inostroza, Glenn Hyndes, Alan M. Friedlander, Eduard Serrano, Caitlin Rae, Enric Ballesteros

Research outputs 2022 to 2026

Although seagrass meadows form a relatively homogenous habitat, escarpments, which form three-dimensional structures and originate from the erosion of seagrass peat, can provide important habitat for reef fishes. Here, we compare fish assemblages and habitat structural complexity among seagrass Posidonia australis escarpments and canopies, as well as limestone reef habitats, to understand the role of seagrass escarpments as reef fish habitat in Shark Bay, Western Australia. The total number of fish species, fish biomass, and top predator biomass were significantly higher in seagrass escarpments and reef habitats than in seagrass canopies due to lower habitat structural complexity and thus becoming …

Voltammetric Determination Of Inorganic Arsenic In Mildly Acidified (Ph 4.7) Groundwaters From Mexico And India, Martijn Eikelboom, Yaxuan Wang, Gemma Portlock, Arthur Gourain, Joseph Gardner, Jay Bullen, Paul Lewtas, Matthieu Carriere, Alexandra Alvarez, Arun Kumar, Shane O'Prey, Tamás Tölgyes, Dario Omanović, Subhamoy Bhowmick, Dominik Salaun, Pascal Salaun

Research outputs 2022 to 2026

Routine monitoring of inorganic arsenic in groundwater using sensitive, reliable, easy-to-use and affordable analytical methods is integral to identifying sources, and delivering appropriate remediation solutions, to the widespread global issue of arsenic pollution. Voltammetry has many advantages over other analytical techniques, but the low electroactivity of arsenic(V) requires the use of either reducing agents or relatively strong acidic conditions, which both complicate the analytical procedures, and require more complex material handling by skilled operators. Here, we present the voltammetric determination of total inorganic arsenic in conditions of near-neutral pH using a new commercially available 25 m diameter gold microwire (called …

A Review Of Methods For Detecting Rats At Low Densities, With Implications For Surveillance, Robert A. Davis, Philip J. Seddon, Michael D. Craig, James C. Russell

Research outputs 2022 to 2026

Invasive rats are the biggest threat to island biodiversity world-wide. Though the ecological impacts of rats on insular biota are well documented, introduced rats present a difficult problem for detection and management. In recent decades, improved approaches have allowed for island-wide eradications of invasive rats on small-medium sized islands and suppression on large islands, although both these still represent a formidable logistical and financial challenge. A key aspect of eradication or suppression and ongoing management is the ability to detect the presence of rats, especially at low densities. Here we review recent developments in the field of rat surveillance and …

Development Of A 3-D-Printable Device For Continuous Measuring Of Heavy Metal Ion Concentrations, Charl De Villiers, Magdalena Wajrak, Alex Lubansky

Research outputs 2022 to 2026

Three-dimensional (3-D) printing offers the potential to create a range of tailored devices within many different industrial facilities. In this article, devices were designed and fabricated using 3-D printing to house electrodes for the testing of heavy metal concentration in hazardous fluids, particularly for biological samples such as urine or blood. The devices, connected to a syringe pump, were shown to be able to be operated without leaking. Proof of concept experiments were performed using Anodic Stripping Voltammetry (ASV) methods, demonstrating that the devices are able to be used for quick, cheap testing, showing the potential of the technique as …

A Data Taxonomy For Adaptive Multifactor Authentication In The Internet Of Health Care Things, Tance Suleski, Mohiuddin Ahmed

Research outputs 2022 to 2026

The health care industry has faced various challenges over the past decade as we move toward a digital future where services and data are available on demand. The systems of interconnected devices, users, data, and working environments are referred to as the Internet of Health Care Things (IoHT). IoHT devices have emerged in the past decade as cost-effective solutions with large scalability capabilities to address the constraints on limited resources. These devices cater to the need for remote health care services outside of physical interactions. However, IoHT security is often overlooked because the devices are quickly deployed and configured as …

Going Beyond: Cyber Security Curriculum In Western Australian Primary And Secondary Schools. Final Report, Nicola F. Johnson, Ahmed Ibrahim, Leslie Sikos, Marnie Mckee

Research outputs 2022 to 2026

There is no doubt cyber security is of national interest given the rife nature of cyber crime and the alarming increase of victims who have endured identify theft, fraud and scams. Curriculum within K-12 schools tends to be fixed and any modifications are subject to extensive consultation within a prolonged review cycle. Therefore, this report has gone beyond curriculum to explore the potential of national awareness campaigns and dynamic digital cyber security licences as alternative possibilities for instigation. The role of leaders in various school sectors and systems is critical for a successful roll out. This final report culminates from …

Seagrass Soils Sequester Up To Half The Metal Emissions Of One Of The World's Largest Smelters, Anna Lafratta, Oscar Serrano, Pere Masque´, M. Fernandes, S. Gaylard, Paul Lavery

Research outputs 2022 to 2026

One of the world's largest smelters has been operating in South Australia since 1889, affecting environment and human health. Here we quantified the magnitude of Pb, Zn and Cd emissions from the smelter sequestered in the soil of an adjacent 110 km2 Posidonia australis seagrass meadows. Seagrass core records show that the smelter contaminated the entire area with decreasing sequestration with increasing distance from contamination points. The soil accumulated ~1300 t of Pb, ~3450 t of Zn, and ~ 90 t of Cd since 1889, and sequestered the equivalent of ~20 % of Pb, and ~50 % of Zn and …

Generalized Framework For Image And Video Object Segmentation Using Affinity Learning And Message Passing Gnns, Sundaram Muthu, Ruwan Tennakoon, Tharindu Rathnayake, Reza Hoseinnezhad, David Suter, Alireza Bab-Hadiashar

Research outputs 2022 to 2026

Despite significant amount of work reported in the computer vision literature, segmenting images or videos based on multiple cues such as objectness, texture and motion, is still a challenge. This is particularly true when the number of objects to be segmented is not known or there are objects that are not classified in the training data (unknown objects). A possible remedy to this problem is to utilize graph-based clustering techniques such as Correlation Clustering. It is known that using long range affinities (Lifted multicut), makes correlation clustering more accurate than using only adjacent affinities (Multicut). However, the former is computationally …

Improved Yolov5-Based Real-Time Road Pavement Damage Detection In Road Infrastructure Management, Abdullah A. Sami, Saadman Sakib, Kaushik Deb, Iqbal H. Sarker

Research outputs 2022 to 2026

Deep learning has enabled a straightforward, convenient method of road pavement infrastructure management that facilitates a secure, cost-effective, and efficient transportation network. Manual road pavement inspection is time-consuming and dangerous, making timely road repair difficult. This research showcases You Only Look Once version 5 (YOLOv5), the most commonly employed object detection model trained on the latest benchmark Road Damage Dataset, Road Damage Detection 2022 (RDD 2022). The RDD 2022 dataset includes four common types of road pavement damage, namely vertical cracks, horizontal cracks, alligator cracks, and potholes. This paper presents an improved deep neural network model based on YOLOv5 for …

Physical Layer Authenticated Image Encryption For Iot Network Based On Biometric Chaotic Signature For Mpfrft Ofdm System, Esam A. A. Hagras, Saad Aldosary, Haitham Khaled, Tarek Hassan

Research outputs 2022 to 2026

In this paper, a new physical layer authenticated encryption (PLAE) scheme based on the multi-parameter fractional Fourier transform–Orthogonal frequency division multiplexing (MP-FrFT-OFDM) is suggested for secure image transmission over the IoT network. In addition, a new robust multi-cascaded chaotic modular fractional sine map (MCC-MF sine map) is designed and analyzed. Also, a new dynamic chaotic biometric signature (DCBS) generator based on combining the biometric signature and the proposed MCC-MF sine map random chaotic sequence output is also designed. The final output of the proposed DCBS generator is used as a dynamic secret key for the MPFrFT OFDM system in which …

Blue Carbon Opportunities: Seagrass Carbon Storage And Accumulation Rates At North Minahasa And Sangihe Island, Indonesia, Paul Lavery, Anna Lafratta, Akbar Ario Digdo, Abie Ariyo Dandoro, Citra Septiani, Topan Cahyono, Oscar Serrano, Pere Masque´

Research outputs 2022 to 2026

Report prepared as a contribution to the Seagrass Ecosystem Services Project “Conservation of biodiversity, seagrass ecosystems and their services – safeguarding food security and resilience in vulnerable coastal communities in a changing climate” funded through the International Klimate Initiative (IKI).

The SES Project is a partnership between the CMS, Edith Cowan University, Yapeka, Project Seagrass, Seagrass Watch, Murdoch University, MRS, Blue Ventures, SAN, C3, ZSL, and MareCet. The collaboration enhances the understanding of seagrass ecosystem services and the capacity to develop and deliver science-based policy solutions in seagrass conservation. It brings together scientists, policy experts, business development experts and conservation …

Blue Carbon Opportunities: Seagrass Carbon Storage And Accumulation Rates At Johor And Penang, Malaysia, Paul Lavery, Anna Lafratta, Dhivya Nair, Louisa Ponnampalam, Jol Ern Ng, Fairul Izmal Jamal Hisne, Oscar Serrano, Pere Masque´

Research outputs 2022 to 2026

Report prepared as a contribution to the IKI Project “Conservation of biodiversity, seagrass ecosystems and their services – safeguarding food security and resilience in vulnerable coastal communities in a changing climate.

The IKI Seagrass Ecosystem Services Project is a partnership between the CMS, Edith Cowan University, Project Seagrass, Seagrass Watch, Murdoch University, MRS, Blue Ventures, SAN, C3, ZSL, MareCet and Yapeka. The collaboration enhances the understanding of seagrass ecosystem services and the capacity to develop and deliver science-based policy solutions in seagrass conservation. It brings together scientists, policy experts, business development experts and conservation NGOs across the globe to provide …

Coastal Groundwater-Dependent Ecosystems Are Falling Through Policy Gaps, Madeleine Dyring, Melissa M. Rohde, Ray Froend, Harald Hofmann

Research outputs 2022 to 2026

Coastal groundwater-dependent ecosystems (GDEs), such as wetlands, estuaries and nearshore marine habitats, are biodiversity hotspots that provide valuable ecosystem services to society. However, coastal groundwater and associated ecosystems are under threat from groundwater exploitation and depletion, as well as climate change impacts from sea-level rise and extreme flood and drought events. Despite many well-intentioned policies focused on sustainable groundwater use and species protection, coastal GDEs are falling through gaps generated by siloed policies and as a result, are declining in extent and ecological function. This study summarized then examined policies related to the management of coastal groundwater and connected ecosystems …

Flaws In The Methodologies For Organic Carbon Analysis In Seagrass Blue Carbon Soils, Oscar Serrano, Ines Mazarrasa, James W. Fourqurean, Eduard Serrano, Jeffrey Baldock, Jonathan Sanderman

Research outputs 2022 to 2026

The ability to accurately measure organic carbon (OC) in marine sediments or soils is overall taken for granted in scientific communities, yet this seemingly mundane task remains a methodological challenge when the soil matrix contains calcium carbonate (CaCO3), creating inaccuracies in Blue Carbon estimates. Here, we compared five common methods combining acidification, combustion, and wet oxidation pre-treatments for determination of OC in sediments and soils containing CaCO3 based on the analyses of artificial soil mixtures made of different OC and CaCO3 contents, and multiple soils from Australian seagrass cores. The results obtained showed that methods involving acidification pre-treatment entailed −17 …

Development Of A Scoring Tool For Australian Rural Food Retail Environments, Tracy L. Schumacher, Carissa A. Alderton, Leanne J. Brown, Susan Heaney, Laura Alston, Katherine Kent, Stephanie L. Godrich

Research outputs 2022 to 2026

Current tools scoring the healthiness of food retail outlets do not reflect outlets found in rural locations. This study aimed to adapt pre-existing Australian scoring tools to represent non-metropolitan areas. Rural nutrition experts were identified, and a modified Delphi technique was used to adapt two pre-existing, food-scoring tools in five iterative stages. Stages included identifying all relevant outlets, providing a description and score for each, ensuring consistency between outlet scores and pre-existing, metro-centric tools, and providing instructions for correct use. Six rural nutrition experts were identified and engaged in the modified Delphi technique. The final tool consisted of 12 categories …

Malbot-Drl: Malware Botnet Detection Using Deep Reinforcement Learning In Iot Networks, Mohammad Al-Fawa'reh, Jumana Abu-Khalaf, Patryk Szewczyk, James J. Kang

Research outputs 2022 to 2026

In the dynamic landscape of cyber threats, multi-stage malware botnets have surfaced as significant threats of concern. These sophisticated threats can exploit Internet of Things (IoT) devices to undertake an array of cyberattacks, ranging from basic infections to complex operations such as phishing, cryptojacking, and distributed denial of service (DDoS) attacks. Existing machine learning solutions are often constrained by their limited generalizability across various datasets and their inability to adapt to the mutable patterns of malware attacks in real world environments, a challenge known as model drift. This limitation highlights the pressing need for adaptive Intrusion Detection Systems (IDS), capable …

Blue Carbon Opportunities: Seagrass Carbon Storage And Accumulation Rates At Roxas, Palawan, The Philippines, Paul Lavery, Anna Lafratta, Jessa Marie Caabay, Reynante Ramilo, Helbert G. Garay, Maricar Daquioag, Oscar Serrano, Pere Masque´

Research outputs 2022 to 2026

Report prepared as a contribution to the IKI Project “Conservation of biodiversity, seagrass ecosystems and their services – safeguarding food security and resilience in vulnerable coastal communities in a changing climate”

The IKI Project is a partnership between the CMS, Edith Cowan University, Project Seagrass, Seagrass Watch, Murdoch University, MRS, Blue Ventures, SAN, C3, ZSL, MareCet and Yapeka. The collaboration enhances the understanding of seagrass ecosystem services and the capacity to develop and deliver science-based policy solutions in seagrass conservation. It brings together scientists, policy experts, business development experts and conservation NGOs across the globe to provide expert and independent …

Flipping The Thinking On Equality, Diversity, And Inclusion. Why Edi Is Essential For The Development And Progression Of The Chemical Sciences: A Case Study Approach, M. Anwar H. Khan, Timothy G. Harrison, Magdalena Wajrak, Michele Grimshaw, Kathy G. Schofield, Alison J. Trew, Kulvinder Johal, Jeannette Morgan, Karen L. Shallcross, Joyce D. Sewry, Michael T. Davies-Coleman, Dudley E. Shallcross

Research outputs 2022 to 2026

All learners have a contribution to make to the development of the Chemical Sciences, be that in novel ways to teach, and their perspectives and contexts, but also in research, both in chemical education and the wider Chemical Sciences. Through four case studies, this paper explores interactions with diverse groups and how this has altered perspectives on both teaching and research. The case studies include work with visually impaired adults, a project bringing together First Peoples in Australia with academics to explore old ways (traditional science) and new ways (modern approaches), primary (elementary) school perspectives on teaching science, and a …

Camdec: Advancing Axis P1435-Le Video Camera Security Using Honeypot-Based Deception, Leslie F. Sikos, Craig Valli, Alexander E. Grojek, David J. Holmes, Samuel G. Wakeling, Warren Z. Cabral, Nickson M. Karie

Research outputs 2022 to 2026

The explosion of online video streaming in recent years resulted in advanced services both in terms of efficiency and convenience. However, Internet-connected video cameras are prone to exploitation, leading to information security issues and data privacy concerns. The proliferation of video-capable Internet of Things devices and cloud-managed surveillance systems further extend these security issues and concerns. In this paper, a novel approach is proposed for video camera deception via honeypots, offering increased security measures compared to what is available on conventional Internet-enabled video cameras.

Improving Accuracy And Efficiency In Seagrass Detection Using State-Of-The-Art Ai Techniques, Md Kislu Noman, Syed M. S. Islam, Jumana Abu-Khalaf, Seyed M. J. Jalali, Paul Lavery

Research outputs 2022 to 2026

Seagrasses provide a wide range of ecosystem services in coastal marine environments. Despite their ecological and economic importance, these species are declining because of human impact. This decline has driven the need for monitoring and mapping to estimate the overall health and dynamics of seagrasses in coastal environments, often based on underwater images. However, seagrass detection from underwater digital images is not a trivial task; it requires taxonomic expertise and is time-consuming and expensive. Recently automatic approaches based on deep learning have revolutionised object detection performance in many computer vision applications, and there has been interest in applying this to …

Artificial Intelligence And Precision Health Through Lenses Of Ethics And Social Determinants Of Health: Protocol For A State-Of-The-Art Literature Review, Sarah Wamala-Andersson, Matt X. Richardson, Sara Landerdahl Stridsberg, Jillian Ryan, Felix Sukums, Yong-Shian Goh

Research outputs 2022 to 2026

Background: Precision health is a rapidly developing field, largely driven by the development of artificial intelligence (AI)–related solutions. AI facilitates complex analysis of numerous health data risk assessment, early detection of disease, and initiation of timely preventative health interventions that can be highly tailored to the individual. Despite such promise, ethical concerns arising from the rapid development and use of AI-related technologies have led to development of national and international frameworks to address responsible use of AI. Objective: We aimed to address research gaps and provide new knowledge regarding (1) examples of existing AI applications and what role they play …

Cybersecurity Knowledge Graphs, Leslie Sikos

Research outputs 2022 to 2026

Cybersecurity knowledge graphs, which represent cyber-knowledge with a graph-based data model, provide holistic approaches for processing massive volumes of complex cybersecurity data derived from diverse sources. They can assist security analysts to obtain cyberthreat intelligence, achieve a high level of cyber-situational awareness, discover new cyber-knowledge, visualize networks, data flow, and attack paths, and understand data correlations by aggregating and fusing data. This paper reviews the most prominent graph-based data models used in this domain, along with knowledge organization systems that define concepts and properties utilized in formal cyber-knowledge representation for both background knowledge and specific expert knowledge about an actual …