38139 research outputs found
Sort by
Will Australia Require Nuclear Energy to Achieve Zero Carbon Emissions by 2050?
No full textThe question of whether Australia can have a reliable baseload power network in the future without nuclear power with ageing coal fired power stations being retired is one of the most pressing current issues. Answering this question is the purpose of writing this article. The number one National Science and Research priority is ‘transitioning to a net zero future’, while the number four priority is ‘protecting and restoring Australia’s environment’. This topic falls squarely within these two national priorities. The current debate is largely political with the two main political parties taking diametrically opposed positions based on political ideology. The renewable energy industry trumpets solar and wind power, and points to the length of time it takes to build a nuclear power station, while organisations like the Minerals Council of Australia argue Australia is short-changing itself by not allowing nuclear power and pointing to Canada’s nuclear industry as an example to follow. However, there is little written about the subject outside of CSIRO’s annual GenCost report on the costs of different generation technologies and two reports written by Frontier Economics assessing the relative costs of nuclear power in the National Energy Market (NEM). The GenCost 2023-24 report concluded nuclear would be at least 50% more expensive than solar and wind and would not be available any earlier than 2040, while Frontier Economics estimated that the inclusion of nuclear power in the NEM in the Australian Energy Market Operator’s (AEMO) preferred Step Change scenario is 25% cheaper than AEMO’s renewables and storage approach. This article objectively examines whether Australia will require nuclear energy to achieve carbon zero emissions by 2050
An Automated Identification Method of Disturbance Ranges of Surface Coal Mines on Vegetation Based on the Fitting of NDVI Spatial Trajectory
No full textAccurately and efficiently identifying the vegetation disturbance ranges in surface coal mines is of great significance for determining the scope of land degradation and mitigating land degradation. The objective of this article is to propose an automated method for identifying disturbance ranges of surface coal mines on vegetation based on the fitting of NDVI spatial trajectory (called Disran_SpaTFit). The process of the proposed method includes preparing the NDVI spatial trajectory dataset, designing the curve conceptual function model, fitting the spatial trajectory, and selecting the optimal model to identify disturbance ranges. With the Shendong coal base in China as the study area, the mining disturbance ranges of 106 surface coal mines were automatically identified. The results show that: (1) The accuracy of the automated identification of mining disturbance distances was 91.1%, with a mean absolute error of 109 m. (2) Disran_SpaTFit is widely applicable to various heterogeneous coal mines. 96.62% of the NDVI spatial trajectories (1229 out of 1272 in total) were confirmed to match one of the four curve models designed in Disran_SpaTFit. (3) The ranges of mining disturbance in the 106 surface mines exhibit significant spatial heterogeneity across different directions and extend a certain distance away from the open-cut area. (4) Disran_SpaTFit is able to accurately identify the ranges of mining disturbances for different years, covering the changes before and during mining activities. The results in this article demonstrate that the proposed Disran_SpaTFit provides an effective tool for identifying disturbance ranges of various surface coal mines, which is of importance for ecological assessment and restoration management in mining areas
Valuing Experiential Learning: Unlocking RPL Potential in a Regional Australian University
Get PDFThis research article consolidates the key findings, methodologies, resources and recommendations emerging from the 2021–2022 Recognition of Prior Learning (RPL) project at UniSQ. A significant deliverable was the Professional Practice Credit Framework with two pilots undertaken to test this prototype and identify resources required. The pilots were conducted in two distinct contexts: the Bachelor of Communication and Media (BCNM) and the Bachelor of Cyber Security (BCYS). Whilst the project funding formally concluded, the vision remained to sustainably embed processes, training, and resources into institutional operations, transitioning from a project-based initiative to business as usual.
This article serves two interconnected purposes:
Part A: Provides a comprehensive account of the RPL project methodology, findings, and resources developed over time and underpinned by co-design principles. It establishes a foundation for further development in this area, addressing a notable gap in the Australian higher education sector. Specifically, the RPL project highlights the importance of tailoring approaches to the unique institutional and student contexts in which they are implemented. Key factors to successfully embed RPL include institutional culture, governance alignment, and acknowledging student diversity.
Part B: Focuses on the Professional Practice Credit Framework, an evolving and student-centric concept informed by continuous stakeholder engagement. This section details the Professional Practice Credit Framework's development, informed by two pilot studies and student credit referrals. It includes resources and tools aimed at enhancing procedures, processes, and practices related informal and non-formal (experiential) learning
Nature positive? Commodification, speciesism, abjection in Australia's environmental law reform
Get PDFProposed “nature positive” revisions to the Australian Government’s environmental legislation would further entrench an anthropocentric conception of nature as a commodity able to be metricised, traded, and/or replaced. The proposed legislation also manifests a form of speciesism, focusing on
threatened species at the expense of other animals whose habitat would continue to be destroyed, and fails to account for future likely changes in the survivability of various species. Moreover, it takes little account of the
suffering of individual animals nor the agential role of animals, plants, rocks, and mountains in more-than-human world-making, thus placing those nonhumans in abjection—that is, accorded no moral considerability. Using the Australian case to anchor our discussion, we conclude that truly “nature
positive” approaches to the environment require a shift in emphasis from principally enabling “sustainable” exploitation of resources by humans, toward a focus on sustaining the multitude of context-specific, intensely relational
networks of humans-other-than-humans. These relations engender a responsibility on the part of humans, when intervening through legislation, policy or practice, to pay deep attention to the specifics of nonhuman standpoints,
subjectivities and relations with place—ground truthing—so that greater knowledge and critical, less anthropocentric thinking can underpin more ethical regulatory frameworks
Intelligent modeling and analysis of hybrid organic Rankine plants: Data-driven insights into thermodynamic efficiency and economic viability
Get PDFHybrid organic Rankine cycle (HORC) is a hydrodynamic plant used from industrial processes for low-temperature heat sources, such as geothermal, solar, and waste heat. Intelligent models were developed to predict the first and the second thermodynamic efficiencies and the levelized energy cost to optimize the overall thermal and economic efficiency of hybrid organic Rankine cycle-powered plants. Deep learning, gradient-boosting framework, and Kernel models such as Long Short-Term Memory (LSTM), Light Gradient Boosting Machine (LGBM), and Kernel Ridge Regression (KRR) models were developed to predict the three outputs of HORC according to five subsets: subset-1: design variables, subset-2: temperature variables, subset-3: power variables, subset-4: heat exchanger variables, and subset-5: all previous variables. The LSTM model generally achieved superior performance across the multiple input variables used in predicting the three model outputs. The LSTM model attained the lowest mean absolute percentage error (MAPE) (4.8%–13%), the highest coefficient of determination (R2) (up to 0.994), and the lowest root mean square error (RMSE) as low as 0.002. This demonstrated superior predictive accuracy across the various model input subsets. The LGBM model, however, showed moderate performance, with the MAPE reaching up to 25.6% and the R2 ranging from 0.624 to 0.986. In contrast, the KRR model struggled to demonstrate exceptional performance, especially with the heat exchanger dataset, thus exhibiting a MAPE up to 54.4% and an R2 value as low as 0.408. Therefore, we advocate that the LSTM model could be the most reliable model for predicting the system efficiency of HORC
Multimodal fusion framework based on knowledge graph for personalized recommendation
No full textKnowledge Graphs (KGs), which contain a wealth of knowledge, have been commonly employed in recommendation systems as a valuable knowledge-driven tool for supporting high-quality representations. To further enhance the model’s ability to understand the real world, Multimodal Knowledge Graphs (MKGs) are proposed to extract rich knowledge and facts among objects from text and visual content. However, existing MKG-based methods primarily focus on the reasoning relationships between entities by utilizing multimodal information as auxiliary data in the KG while overlooking the interactions between modalities. In this paper, we propose a Multimodal fusion framework based on Knowledge Graph for personalized Recommendation (Multi-KG4Rec) to address these limitations. Specifically, we systematically analyze the shortcomings of existing multimodal graph construction methods. To this end, we propose a modal fusion module to extract the user modal preference at a fine-grained level. Furthermore, we conduct extensive experiments on two real-world datasets from different domains to evaluate the performance of our model, and the results demonstrate the efficiency of the Multi-KG4Rec
A dual-method approach using autoencoders and transductive learning for remaining useful life estimation
No full textEstimating the remaining useful life (RUL) of lithium-ion batteries presents a critical challenge, as it necessitates predicting their future performance and lifespan under diverse operational conditions. Addressing this issue is crucial for enhancing battery maintenance, improving reliability, and safeguarding devices that depend on lithium-ion technology. In this article, we propose a dual-method approach for RUL estimation. Firstly, an autoencoder (AE) extracts pivotal features from the input. Key measurable parameters, such as voltage, current, and temperature from charging profiles, are derived from the battery management system, providing robust data for the AE. The core of the AE is constructed using a spatial attention-based transductive long short-term memory (TLSTM) model, which is trained with an advanced generative adversarial network (GAN). The TLSTM model employs transductive learning, emphasizing samples near the test point to refine the fitting process and surpassing conventional LSTM models in performance. Following the AE training phase, the input's latent representation is inputted into a multilayer perceptron (MLP) designed for RUL prediction. We conduct thorough evaluations using National Aeronautics and Space Administration (NASA) datasets. Additionally, experiments from the Center for Advanced Life Cycle Engineering (CALCE) at the University of Maryland are underway to examine the influence of transfer learning (TL) on our model. The TLSTM model performs better than other deep learning models, achieving an impressive mean absolute percentage error (MAPE) ranging between 0.0053 and 0.0095. This highlights the efficacy and superiority of our approach in accurately predicting RUL, offering significant potential benefits for industries reliant on energy storage systems
Implementation of occupation-centred practice by occupational therapists in acute adult physical settings: A mixed method study in a regional and rural health service
No full textIntroduction
Occupational therapy is underpinned by the belief that occupation facilitates health and wellbeing. However, evidence suggests that occupational therapists encounter challenges to implementing occupation-centred practice. The aim of this study was to investigate the uptake, acceptability and impact of a workplace intervention designed to enhance occupation-centred practice of occupational therapists in an acute adult physical context.
Methods
A concurrent mixed methods study using a pre–post design was employed. The setting was a regional and rural health service in Queensland. Data were collected using an online survey of occupational therapists' knowledge, attitude and confidence regarding occupational therapy models, an audit of medical charts and focus group discussion and in-depth interviews. Quantitative data were presented using descriptive statistics, and discussions were thematically analysed.
Consumer and Community Involvement
No involvement.
Results
Survey results revealed minimal difference between pre- (n = 8) and post- (n = 8) interventions. The medical chart audit (pre = 40, post = 28) revealed an increase in occupational language over medically based language. Four themes were identified from the qualitative data (pre = 5, post = 6): change in theoretical awareness and acceptance of occupational therapy models; facilitators for adoption of occupational therapy models in the acute setting; what it takes: the qualities and efforts required of individuals; and enhanced professional identity. The themes revealed that participants varied in their knowledge and implementation of occupation-centred practice pre-intervention and could feel constrained by the workplace context. Post-participants recognised that actively practising occupation centredness impacted positively on their practice.
Conclusion
Participation in an initiative to increase occupation-centred practice resulted in changed behaviours and beliefs for occupational therapists in this study. Participants recognised that their individual contribution and the concerted efforts of their occupational therapy peers led to increased professional identity and understanding of occupational therapy contribution in the acute adult physical setting.
PLAIN LANGUAGE SUMMARY
Occupational therapists promote health and wellbeing by working with people of all abilities to participate in the everyday occupations of life. However, within some hospital settings, occupational therapists face a number of challenges to implementing their desired approach due to time restrictions and dominance of other professions. Because of this, consumers and health colleagues in hospitals are unclear on the role or value of occupational therapists, and occupational therapists feel misunderstood. This may impact on job satisfaction, retention of staff in this setting and missed opportunities for identifying needs for consumers. In a regional and rural setting, this may be further complicated by occupational therapists working in isolation from direct professional support.
In this project, occupational therapists in a regional and rural health service participated in an activity aimed to enhance their communication and confidence in their unique approach. The activity involved developing and using tools and resources for a hospital context that were ‘occupation-centred’ or were based on ‘occupational therapy models’. Despite occupational therapists reporting that making this change required effort, they recognised that with persistence and collaboration, there was an improved understanding of occupational therapy contribution in the setting and better job satisfaction for occupational therapists. The tools and resources that were developed can be easily adopted by other organisations. These findings show that occupational therapists working in hospitals can alter their behaviours and beliefs to be more true to the profession. And that this benefits occupational therapists, consumers and the broader health-care team