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Hybrid wave–wind energy site power output augmentation using effective ensemble covariance matrix adaptation evolutionary algorithm
No full textFloating hybrid wind–wave systems combine offshore wind platforms and WECs to create cost-effective, reliable energy solutions. WECs that are properly designed and tuned are required to avoid unwanted loads that can interfere with turbine motion while efficiently extracting energy from waves. The systems diversify energy sources, enhance energy security, and reduce supply risks while delivering a smoother power output through the minimisation of energy production variability. However, optimisation of these systems is hindered by physical and hydrodynamic component–component interactions, which cause a challenging optimisation space. A 5-MW OC4-DeepCwind semi-submersible platform and three spherical WECs are taken into consideration in this paper in order to explore such synergies. To address these challenges, we propose an effective ensemble optimisation (EEA) technique that combines covariance matrix adaptation, novelty search, and discretisation techniques. To evaluate the EEA performance, we used four sea sites located along Australia's southern coast. In this framework, geometry and power take-off (PTO) parameters are simultaneously optimised to maximise the average power output of the hybrid wind–wave system. Ensemble optimisation methods enhance performance, flexibility, and robustness by identifying the best algorithm or combination of algorithms for a given problem, addressing issues like premature convergence, stagnation, and poor search space exploration. The EEA was benchmarked against 14 advanced optimisation methods, demonstrating superior solution quality and convergence rates. EEA improved total power output by 111%, 95%, and 52% compared to Whale Optimisation Algorithm (WOA), Equilibrium Optimiser (EO), and Artificial Hummingbird Algorithm (AHA), respectively. Additionally, in comparisons with advanced methods, Ensemble Sinusoidal Differential Covariance Matrix Adaptation (LSHADE), Self-adaptive Differential Evolution (SaNSDE), and Social Learning Particle Swarm Optimisation (SLPSO), EEA achieved absorbed power enhancements of 498%, 638%, and 349% at the Sydney sea site, showcasing its effectiveness in optimising hybrid energy systems
Effect of multi-disciplinary deliberation on perceptions of risk and recommended actions in response to child abuse
No full textMulti-disciplinary case review meetings are commonly held to facilitate a holistic response to child abuse. This study set out to examine whether multi-agency case review meetings change the perceptions of members in response to series of child abuse vignettes. The study involved twelve participants from law enforcement, child protection, health, and education agencies who regularly responded to child abuse in their jurisdiction. The study replicated ‘Strategy Meetings’, a multi-agency meeting that occurs in Western Australia at the start of a child abuse case. The study involved a novel pre-post design, with follow-up interviews. Participants were asked to read a child abuse vignette and assess the case, participate in a 15-minute case deliberation, then complete the same individual assessment with a total of 52 pre-post assessments completed. Semi-structured interviews were conducted with nine participants a week following their session. The study found that participants generally did not change their perceptions of the case as a result of the deliberation sessions (Current Risk Scale Z = 0.173, p = 0.863, Future Risk Scale Z = 0.293, p = 0.769, & Response Scale Z = −0.161, p = 0.872). The interviews suggest that the deliberation sessions identified numerous points of difference on the cases, but these did not appear to be resolved by discussing the case in the time available. Further research on the effect of deliberation on larger samples and more diverse team structures is needed to clarify the purpose and value of holding multi-disciplinary case review meetings
Being left behind: disclosure strategies to manage the Juukan Gorge cave blast
No full textPurpose: This study aims to investigate how disclosures through different communication media were used by the Australian mining company Rio Tinto to manage its reputation after the Juukan Gorge Cave Blast.
Design/methodology/approach: Case study research was used with a focus on a single case, Rio Tinto and the Juukan Gorge incident. Data on sustainability disclosures were collected from Rio Tinto’s website, corporate reports and social media platforms (Facebook, X and LinkedIn) for the 2020 and 2021 periods. Gioia methodology was applied to analyse disclosure strategies and an extended Reputation Risk Management (RRM) framework was used as a conceptual lens.
Findings: The findings reveal a slow and inappropriate initial response from the company resulting in negative reputational consequences for the company’s senior executives. Although the company’s initial response was to avoid responsibility and mitigate offensiveness, it gradually accepted full responsibility and adopted reparation strategies such as corrective action, mortification and stakeholder engagement to rebuild its reputation. The temporal analysis suggests that Rio Tinto was “left behind” as a result of its initial response, limiting the effectiveness of its subsequent RRM strategies.
Research limitations/implications: The findings of this study contribute to an improved understanding of communication strategies for managing a reputation crisis. The extended RRM framework developed in this study provides a comprehensive list of various disclosure strategies that can be used in future studies that analyse disclosure post an environmental or social incident.
Practical implications: The findings of the study provide insights into the effectiveness of different communication strategies when communicating to stakeholders with varied interests. This study highlights that the timing of the response is critical to restoring lost reputation and a slow response which emphasises financial stakeholders at the expense of the affected communities can be detrimental to RRM, no matter how well-intentioned subsequent strategies are.
Social implications: This research focuses on a marginal stakeholder group, Indigenous people and communities. The findings offer insights to society into whether corporate strategies to manage a reputation crisis promote and support equity and inclusivity.
Originality/value: This study focuses on a community-based stakeholder, Indigenous groups, a context that has unique cultural intricacies and requires a transition beyond a corporate perspective on RRM
Disruptive desire : how might screenwriting practice be opened up by writing through desire ; testing the screenwriting method of Céline Sciamma /
No full text1 ethesis (viii, 229 pages) :colour illustrations.Includes bibliographical references (pages 205-218)In 2019, French writer/director Céline Sciamma proposed a new model of screen writingdrawn from her own practice: Writing Through Desire. This research explored and tested Sciamma’s model through the writing of a new screenplay about women, ageing and community. With a focus on driving screenplay development through the lens of desire, rather than the industry-standard lens of conflict, Sciamma’s three-step approach became the central method of exploration: Identifying the Desires of the Writer; Working at Scenes Level; and Mapping the Scenario. Research outcomes saw the development of a new set of creative tools and storytelling possibilities for screenwriters, moving from industry documents to include drawing, crafting and connecting with the heart. This new approach to screenwriting is particularly relevant to telling the stories of women and gender-diverse characters.Thesis (PhD(Communication))--University of South Australia, 2025
Integrity and cheating at university - implications for nursing
No full textAs nurses, we are trusted to uphold the highest ethical standards in the care of our patients and are often ranked among the most trusted professions.1 But what do we do when the values of honesty and integrity, central to the nursing Code of Ethics are tested during university life
50 Shades of Deceptive Patterns: A Unified Taxonomy, Multimodal Detection, and Security Implications
No full textSession 17: Phishing, Deception, and Consumer RisksDeceptive patterns (DPs) are user interface designs deliberately crafted to manipulate users into unintended decisions, often by exploiting cognitive biases for the benefit of companies or services. While numerous studies have explored ways to identify these deceptive patterns, many existing solutions require significant human intervention and struggle to keep pace with the evolving nature of deceptive designs. To address these challenges, we expanded the deceptive pattern taxonomy from security and privacy perspectives, refining its categories and scope.We created a comprehensive dataset of deceptive patterns by integrating existing small-scale datasets with new samples, resulting in 6,725 images and 10,421 DP instances from mobile apps and websites. We then developed DPGuard, a novel automatic tool leveraging commercial multimodal large language models (MLLMs) for deceptive pattern detection. Experimental results show that DPGuard outperforms state-of-the-art methods. An extensive empirical evaluation on 2,000 popular mobile apps and websites reveals that 25.7% of mobile apps and 49.0% websites feature at least one deceptive pattern instance. Through 4 unexplored case studies that inform security implications, we highlight the critical importance of the unified taxonomy in addressing the growing challenges of Internet deception.Zewei Shi, Ruoxi Sun, Jieshan Chen, Jiamou Sun, Minhui Xue, Yansong Gao, Feng Liu, Xingliang Yua
Self-similar groupoid actions on k-graphs, and invariance of K-theory for cocycle homotopies
No full textWe establish conditions under which an inclusion of finitely aligned left-cancellative small categories induces inclusions of twisted C*-algebras. We also present an example of an inclusion of finitely aligned left-cancellative monoids that does not induce a homomorphism even between (untwisted) Toeplitz algebras. We prove that the twisted C*-algebras of a jointly faithful self-similar action of a countable discrete amenable groupoid on a row-finite k-graph with no sources, with respect to homotopic cocycles, have isomorphic K-theory.Alexander Mundey, Aidan Sim
Practical guidelines for immersive journalism production
No full textImmersive journalism (IJ) is an innovative form of journalism which utilizes 360-degree footage and virtual reality environments, allowing viewers to be placed inside a scene. An increased degree of agency and immersion is offered when compared with traditional forms of journalism due to the level of interactivity virtual reality technology can deliver. However, the newness of IJ means it lacks a clear set of guidelines to better inform future practice – a point identified by academics and practitioners alike. This project investigates how better-defined recommendations for IJ production created using 360-degree video can inform the field’s practice more broadly. To accomplish this, a cyclic methodology incorporating both practice-led research and research-led practice was utilized. As technology evolves, the findings of this research can inform future definition of IJ’s scope, while the efficacy and commercial viability of content created using the identified approaches could also be assessed in further studies
STIN model adoption for chatbot in higher education online learning
No full textThis study delves into the adoption of chatbot technology in higher education, with a focus on Indonesian online learning environments. Recognizing the potential of AI-driven tools to address academic support gaps, particularly in developing regions, the research explores how performance expectancy, effort expectancy, and facilitating conditions influence students' behavioral intentions and subsequent adoption of chatbots for academic use. The study employs Structural Equation Modeling (SEM) to analyze survey data from a diverse sample of university students, enabling a nuanced understanding of the complex relationships among these factors. The findings reveal that performance expectancy-the belief that chatbots will enhance academic performance and facilitating conditions, such as internet access and institutional support, play significant roles in motivating students to adopt chatbots. However, effort expectancy, or the perceived ease of use, does not directly drive adoption intentions. This suggests that students prioritize practical benefits over user-friendliness, an insight valuable for universities aiming to implement effective chatbot systems. Moreover, the results align with the Socio-Technical Interaction Network (STIN) model, which emphasizes the need for a cohesive social and technical framework to foster technological acceptance. The STIN model's perspective underscores that students' engagement with chatbots is not just a matter of usability but also of how well the technology is supported by the broader educational infrastructure. This study offers actionable insights for Indonesian universities and other institutions in similar contexts, proposing that enhancing campus resources, like reliable internet access and technical support, can drive chatbot adoption. By focusing on performance-based benefits and strengthening the socio-technical environment, universities can effectively integrate AI-based learning tools, addressing both technical and socio-cultural barriers. Such initiatives support students' learning experiences and foster an adaptive academic ecosystem where AI tools serve as essential assets in overcoming resource limitations. Thus, the study contributes a practical roadmap for advancing e-learning in resource-constrained settings through strategic support of AI technology adoption
