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A smart agriculture information system delivering research data for adoption by the Australian grains industry
Get PDFOnline Farm Trials (OFT) is a bespoke online information system providing current and historical grains trials research data and information in Australia. It represents a technology that supports smart agriculture by enabling discoveries in the data. Its impact on users has been established, supporting industry knowledge and decision making and leading to improved work practices. The aim of this research is to identify the contribution of OFT, as a tool that supports smart agriculture, and to explore the current adoption, barriers, and opportunities for expanding the system for the Australian grains industry. In-depth, semi-structured interviews were conducted with leaders and innovators from the agriculture industry (N = 16). Thematic analysis of the qualitative data reveals widespread value of OFT as an important resource for accessing industry-dedicated, current and historical research trials data. Barriers to adoption were identified which included incomplete data, and a lack of industry-wide awareness. Opportunities to consolidate and expand the data, together with improved industry awareness, are essential to improving industry-wide adoption. Key learnings were identified in the research that offers benefit for the industry, and consideration for the adoption of technology in smart agriculture. This includes functionality, audience, completeness of information/data, consideration of new technologies and the promotion of the system through the delivery of real world examples to encourage industry adoption. Recommendations to support the future design and development of digital platforms in agriculture are also offered. © 202
Techno-economic assessment of an industrial prosumer with biomass investment and time varying tariffs : an Australian case study
Get PDFThis paper investigates the potential for a value chain framework to deliver impact through innovation across the timber manufacturing process. A new and efficient combustion technology that converts timber waste to energy is considered for this study. The framework to estimate the new energy costs and savings derived from the new technology, compared with current supply and demand scenarios, as well as the value generated by waste streams. The opportunity of selling excess energy to the grid or local area has been investigated. Two alternatives of time-varying tariffs and time-varying tariffs with biomass, are used for assessing the costs. According to the numerical results, tariff 3, with 25,000 tonnes of biomass feedstock per year, is the best option for the mill. The price efficiency index is reduced by approximately 40% compared to this option's usual business. In addition, the investor can save the whole energy bill compared to the current business as usual. The investor could make a profit of 1,811,635 as annual life cycle cost, with a payback period of ten years. The lowest levelised cost of energy of 0.14 c/kWh is also obtained for this option. © 2024 The Author(s
Pedal quadrant-specific strength and conditioning considerations for endurance cyclists
No full textThe performance-enhancing effects of strength training on cycling are well documented with findings from research, demonstrating resistance training with heavy loads conducted 2-3 times per week for at least 8 weeks can improve power output (maximal and submaximal), extend time to exhaustion, and reduce completion time for set distances, while not adding to the total body mass. Despite the evident benefits of strength training, there remains a lack of consensus regarding the most effective exercises to enhance endurance cycling. This uncertainty is evident when considering movement-specific exercises to enhance dynamic transfer to cycling. A range of lower-limb exercises involving hip, knee, and ankle flexion and extension seems to enhance cycling performance more so than static or single-joint exercises. These improvements may be attributed to enhanced coordination and improved pedaling technique. This study presents 5 strength training exercises designed to target cycling pedaling quadrants and replicate the unilateral opposing nature of cycling (simultaneous flexion and extension of the legs) to enhance transfer from weight room-based strength training to the bike. These exercises are presented in example programs alongside established "traditional"exercises that may be used to guide the development of strength training for cyclists. Copyright © National Strength and Conditioning Association
The presence of cognitive impairments in the acute phase of traumatic upper limb injuries : a cross-sectional observational study
Get PDFObjectives: The purpose of this study was to investigate the association between cognitive impairments and traumatic upper limb injuries of the acute phase. Material and methods: A cross-sectional observational study was conducted with three groups: a nerve-injury group, a without nerve injury group, and a control group (uninjured participants). Demographic characteristics (e.g. age, sex, body mass index, and education) and traumatic characteristics (duration since injury, injury side, pain, light touch sensation, hand motor function) were recorded. Short-term memory and executive functions were assessed using Rey Auditory and Verbal Learning Test (RAVLT) and Stroop Color and Word Test (SCWT, including SIECT and SIECN), respectively. Results: The study comprised 43 participants in the nerve-injury group, 30 participants in the group without nerve injury, and 104 participants in the control group. Generalized linear model was applied to explore the difference of cognitive functions among three groups with impactors. Significantly poorer performance on the RAVLT was observed in the nerve-injury group compared to the other two groups, and lower score of SIECT in nerve-injury group was lower compared to the control group. However, there was no significant difference of SIECN among three groups. In addition, traumatic characteristics did not significantly impact RAVLT and SIECT (p > 0.05) in all injured participants. Conclusion: Traumatic nerve injury to the upper limb appears to be associated with both short-term memory and executive function impairment, whereas musculoskeletal injuries without nerve damage showed no cognitive impairment. Therefore, it is important to monitor cognitive function following upper limb nerve injuries. © 2024 The Author(s
Assessment of IIoT sensor criticality for enhanced manufacturing cybersecurity
No full textThe adoption of the Industrial Internet of Things (IIoT) offers cost-effective and innovative solutions for manufacturing systems, advancing their autonomous processes. Critical data from IIoT sensors influence decision-making, control processes, and ensure product quality. However, sensor vulnerabilities expose systems to cyber threats. Therefore, assessing the criticality of IIoT sensor nodes, taking into account both data criticality and cybersecurity vulnerabilities, is crucial for enhancing operations and protecting IIoTintegrated manufacturing environments. To address this challenge, this thesis proposes a comprehensive framework to evaluate the criticality of IIoT sensor nodes by combining data criticality with potential cybersecurity vulnerabilities in IIoT-based manufacturing systems. First, the framework focuses on detecting critical data for dynamic product quality control. Current methods rely on static analysis, limiting adaptability. This thesis introduces an innovative dynamic method that ranks critical data based on three key criteria: (1) correlation to product outcomes, (2) percentage of quality change, and (3) sensitivity. This method uses models like polynomial regression, support vector machines (SVM), and a deep learning algorithm (DNN) to predict product quality, validated using realworld wine manufacturing data. The method identifies critical data with high accuracy, with SVM producing the lowest average prediction error for product quality. The second part of the framework introduces a novel approach for assessing Common Vulnerability Scoring System (CVSS) impact metrics, specifically adapted to the environmental and operational context of wine manufacturing. This approach evaluates potential threats and vulnerabilities in IIoT wine sensors based on the correlation between wine characteristics and quality. The findings show that CVSS 4.0 scores provide greater resilience against cyberattacks compared to CVSS 3.1, thanks to newly developed impact and threat metrics. The theoretical concept developed here can be adapted for security vulnerability assessments across various manufacturing systems, tailored to their specific contexts and applications.Doctor of Philosoph
A deep generative model for selecting representative periods in renewable energy-integrated power systems
Get PDFThe extensive integration of renewable energies into power systems has led to a challenging and computationally demanding scenario for the system planning. This is due to the increased number of time series involved and the greater complexity of time series data integrated into power systems. In this paper, a new deep learning-based time aggregation method is proposed for selecting representative periods for renewable energy-integrated power system datasets where multiple variable energy resources are present. Relying on the capabilities of deep generative models, especially Generative Adversarial Network (GAN), the proposed method selects a representative period, including one or more representative days, obtained from multiple time series with spatio-temporal correlations among them. The proposed approach contains the Long Short-Term Memory (LSTM) Network in both generator and discriminator parts. Also, it includes a loss term, specifically designed for clustering tasks, in the minimax objective of the vanilla GAN loss function to enhance the clustering performance in the latent space. Furthermore, the learning rate of the proposed model, as the most important parameter of the learning algorithm, is adaptively fine-tuned during the training process, based on the training error, to enhance its learning performance. Two real-world test cases with various datasets and time series are used for data-based and model-based evaluations. Results obtained on these two real-world test cases confirm the superiority of the proposed model with respect to the state-of-the-art conventional and deep learning-based models, obtaining the performance improvement in the range of [38.55 %, 46.14 %] in terms of Mean Absolute Percentage Error (MAPE), in the range of [45.75 %, 70.16 %] in terms of Root Mean Squared Error (RMSE), and in the range of [65.81 %, 74.58 %] in terms of Mean Absolute Error (MAE). The proposed model can significantly enhance the tractability and scalability of the planning problem of renewable energy-integrated power systems, facilitating renewable energy integration into power systems which is a key issue for net zero transitioning of communities. © 2024 The Author
Empowering fuel cell electric vehicles towards sustainable transportation : an analytical assessment, emerging energy management, key issues, and future research opportunities
Get PDFFuel cell electric vehicles (FCEVs) have received significant attention in recent times due to various advantageous features, such as high energy efficiency, zero emissions, and extended driving range. However, FCEVs have some drawbacks, including high production costs; limited hydrogen refueling infrastructure; and the complexity of converters, controllers, and method execution. To address these challenges, smart energy management involving appropriate converters, controllers, intelligent algorithms, and optimizations is essential for enhancing the effectiveness of FCEVs towards sustainable transportation. Therefore, this paper presents emerging energy management strategies for FCEVs to improve energy efficiency, system reliability, and overall performance. In this context, a comprehensive analytical assessment is conducted to examine several factors, including research trends, types of publications, citation analysis, keyword occurrences, collaborations, influential authors, and the countries conducting research in this area. Moreover, emerging energy management schemes are investigated, with a focus on intelligent algorithms, optimization techniques, and control strategies, highlighting contributions, key findings, issues, and research gaps. Furthermore, the state-of-the-art research domains of FCEVs are thoroughly discussed in order to explore various research domains, relevant outcomes, and existing challenges. Additionally, this paper addresses open issues and challenges and offers valuable future research opportunities for advancing FCEVs, emphasizing the importance of suitable algorithms, controllers, and optimization techniques to enhance their performance. The outcomes and key findings of this review will be helpful for researchers and automotive engineers in developing advanced methods, control schemes, and optimization strategies for FCEVs towards greener transportation. © 2024 by the authors
The Australian nursing and midwifery academic workforce : a cross-sectional study
Get PDFAim: To explore the demographics, employment characteristics, job satisfaction and career intentions of the Australian nursing and midwifery academic workforce. Background: The academic workforce is crucial in preparing the next generation of nurses and midwives. Thus, understanding current satisfaction, challenges, opportunities and intentions is important for recruitment and succession planning. Design: Cross-sectional online Australian academic nursing and midwifery survey. Method: Respondents were invited to complete an online survey via social media platforms, advertisements on professional websites and circulation via professional associations. Descriptive and inferential statistics were used to analyse the data. Results: Of the 250 respondents, most were Registered Nurses (n=212), female (n=222), held tenured teaching and research positions (n=126) and were over the age of 50 (n=130). Almost half of respondents held a PhD (n=98), with 55 (43.7 %) of those without a Doctoral qualification indicating no intention in undertaking doctoral studies. Over 85 % (n=213) of respondents indicated working regular unpaid hours. Female respondents had a significantly higher mean annual teaching allocation compared with males who had higher research workload allocations (p=0.033). Job satisfaction and intention to leave academia were linked with workload and perceived value. Job satisfaction was significantly higher among teaching-only and research-only academics (p=0.005). Conclusion: The sustainability of the Australian nursing and midwifery workforce is at risk due to an ageing workforce and some academics' lack of intention in pursuing doctoral studies. Gender inequities emerged as a finding in this study. Workforce strategies are required to address gender disparities and workload imbalances that have an impact on job satisfaction. © 202
The utilisation of teledentistry in Australia : a systematic review and meta-analysis
Get PDFBackground: Teledentistry is the usage of information-based technologies to deliver healthcare services remotely. It is used to deliver care in regional, rural and remote regions and was particularly useful to deliver care during the COVID-19 pandemic. Objective: This systematic review and meta-analysis aimed to determine teledentistry utilisation in Australia. Methods: The databases PubMed, Google Scholar, EMBASE and Web of Science were searched from inception to June-2024. The phrases “Dental” AND “Telehealth” AND “Australia” and “Teledentistry” AND “Australia” were used. Two authors completed the study selection and data extraction. The Joanna Briggs Institute Critical Appraisal Tools were used to assess quality and bias. Results: Eighteen articles met the inclusion criteria. There were six diagnostic tests, six cross-sectional studies, 4 economic evaluations, one qualitative study and one expert opinion. Teledentistry was accurate for screening caries (average sensitivity=69.7 %, average specificity=97.4 %). There also appeared to be a non-significant negative correlation between specificity and sensitivity (r = 0.432). Opinions regarding teledentistry were mixed from clinicians but positive from patients. Teledentistry may also lead to savings for patients and healthcare providers. Conclusion: Teledentistry increases healthcare access especially for people in regional, rural and remote areas. It is an effective screening tool for caries. Whilst the opinions of clinicians were mixed, potential implementation barriers were identified which could improve opinions of clinicians and increase implementation. Clinical Importance: This study demonstrates teledentistry as a satisfactory tool for screening caries. This could be beneficial to those with difficulties visiting dentists in-person, particularly if they live in regional, rural or remote areas. © 2024 The Author
Deterministic testbed problems for scheduling in job shops’ based manufacturing configuration
No full textJob shop configurations are complex and possess realistic environments. Generating an optimal and readily executable production schedule for job shop is highly important to meet the customer needs. Various researches have proposed viable and competitive algorithms to solve job shop scheduling problem. They have tested the proposed algorithms on their own hypothetically created testbed problems as well as on the others testbed problems to validate the performance. The search for an appropriate testbed problem is always found challenging for novices in this field of research. Therefore, this article is presenting a review of job shop scheduling testbed problems available in the literature. However, the review has been limited to the deterministic testbed problem. As a result, newcomers can conveniently find a compilation of widely recognized testbed problems in a single resource, eliminating the need to extensively explore the literature to assess and validate the efficacy of their proposed approach against existing job shop scheduling methods. Hence, in the present paper, various conclusions have been drawn during this review, including the future research directions emerged. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024