48080 research outputs found
Sort by
Unlocking the Maze: Exploring Nested Ecosystem of Mobility as a Service through Systematic Literature Review
No full textTechnological advancements in the transportation sector have enabled new mobility solutions. Mobility as a Service (MaaS) is one such example that represents the integration of information technology-enabled apps with transport modes to provide door-to-door and affordable transport options to substitute private cars. Research in transportation is growing in focus on MaaS, and so are commercial MaaS products in various developed countries across the world. This study employs the systematic quantitative literature review approach to select scientific research articles on MaaS published to date and proposes a nested ecosystem framework involving actors, infrastructure, value, and customers. The ecosystem framework presented in this review provides valuable guidance to both transport sector academics and practitioners, highlighting the challenges involved in the successful deployment of MaaS schemes. In the end, this review provides future research directions to expand knowledge on MaaS to answer questions in the wake of fast-growing transport technology and global mobility patterns.</p
Data augmentation using SMOTE technique: Application for prediction of burst pressure of hydrocarbons pipeline using supervised machine learning models
No full textAccurate burst pressure prediction is critical for ensuring oil and gas pipeline safety, guiding maintenance decisions, and lowering costs and risks. Traditional methods have limitations, including high experimental costs, conservative empirical models, and computationally expensive numerical algorithms. Machine learning (ML) models have supplanted traditional methods in recent years. However, small and imbalanced datasets are the big challenge to build a ML model that can generate more accurate results. Moreover, the lack of generalization in ML models trained on a dataset of pipelines with specific material grids prevents them from producing superior results on other pipeline types. First, FEA was used to make a dataset. Then, a new way to improve machine learning (ML) model generalization for burst pressure prediction is suggested: combine publicly available datasets of different pipeline specifications. In this combined dataset, some pipelines have a higher number of data samples, and some have fewer, which causes a class imbalance issue. The Synthetic Minority Oversampling Technique (SMOTE) technique was applied to address the issue of class imbalance. The performance of various ML models, Extra Trees (ET), Extreme Gradient Boosting (XGBR), Random Forest (RF), Light Gradient Boosting Machine (LGBM), and Decision Tree (DT), was evaluated to validate the model's prediction and generalization on pipelines of various material grids. Results show that all the selected ML models produced high R-squared, i.e., >0.95, on balanced data compared to the imbalance dataset. These results show that SMOTE-based augmentation is a beneficial way to fix dataset imbalance and make ML models better at predicting burst pressure in oil and gas pipelines.</p
Review of Prediction of Stress Corrosion Cracking in Gas Pipelines Using Machine Learning
No full textPipeline integrity and safety depend on the detection and prediction of stress corrosion cracking (SCC) and other defects. In oil and gas pipeline systems, a variety of corrosion-monitoring techniques are used. The observed data exhibit characteristics of nonlinearity, multidimensionality, and noise. Hence, data-driven modeling techniques have been widely utilized. To accomplish intelligent corrosion prediction and enhance corrosion control, machine learning (ML)-based approaches have been developed. Some published papers related to SCC have discussed ML techniques and their applications, but none of the works has shown the real ability of ML to detect or predict SCC in energy pipelines, though fewer researchers have tested their models to prove them under controlled environments in laboratories, which is completely different from real work environments in the field. Looking at the current research status, the authors believe that there is a need to explore the best technologies and modeling approaches and to identify clear gaps; a critical review is, therefore, required. The objective of this study is to assess the current status of machine learning’s applications in SCC detection, identify current research gaps, and indicate future directions from a scientific research and application point of view. This review will highlight the limitations and challenges of employing machine learning for SCC prediction and also discuss the importance of incorporating domain knowledge and expert inputs to enhance the accuracy and reliability of predictions. Finally, a framework is proposed to demonstrate the process of the application of ML to condition assessments of energy pipelines.</p
Clotted blood samples in the neonatal intensive care unit: A retrospective, observational study to evaluate interventions to reduce blood sample clotting
No full textBackground: Blood draws for laboratory investigations are essential for patient management in neonatal intensive care units (NICU). When blood samples clot before analysis, they are rejected, which delays treatment decisions and necessitates repeated sampling. Aim: To decrease the incidence of rejected blood samples taken for laboratory investigation as a result of clotted sample. Study Design: This retrospective observational study used routine data on blood draws from preterm infants collected between January 2017 and June 2019 in a 112-cot NICU in Qatar. Quality improvement interventions to reduce the rate of clotted blood samples included: awareness raising and safe sampling workshops with NICU staff, involvement of the neonatal vascular access team, development of a complete blood count (CBC) sample collection pathway, review of sample collection equipment, introducing the Tenderfoot® heel lance, establishment of benchmarks and provision of dedicated blood extraction equipment. Results: First attempt blood draw occurred in 10 706 cases, representing a 96.2% success rate. In 427 (3.8%) cases, the samples were clotted requiring repeat collection. The overall rate of clotted specimens decreased from 4.8% in 2017 and 2018 to 2.4% in 2019, with odds ratios of 1.42 (95% confidence interval [CI] 1.13–1.78, p =.002), 1.46 (95% CI 1.17–1.81, p </p
Clinical Practice Patterns for Transradial Coronary Artery Catheterisation in Australian and New Zealand: Mixed-Methods Survey and Interview Study
No full textBackground: While there has been an increase in the use of the transradial approach when performing percutaneous coronary angiography and intervention, there is evidence of variations in international practice. Ensuring that operators’ practices are supported by evidence is important to ensure optimal outcomes. Method: Interventional cardiologists and advanced trainees completed a cross-sectional survey followed by semi-structured interviews to map current practices for transradial coronary artery procedures in Australia and New Zealand and explore factors that influence clinical decision-making around procedural practice. Results: The right radial artery was the preferred access site (88%). Over a third (37%) of the participants indicated that they tested the hand circulation pre-procedure. Over a quarter of respondents (28.6%) reported that they would carry out transradial procedures regardless of the patient's coagulation status. Most participants (77.8%) described radial artery spasm in around 10% of transradial procedures performed. Only 62% of participants assessed for radial artery occlusion post-catheterisation. Interview data revealed four themes that guided clinical decision-making, namely (1) Decision-making based on research, (2) Using clinical experience, (3) Being led by their training, and (4) Individual patient factors. Conclusions: This study has demonstrated that despite clinical guidelines, substantial practice variation exists in transradial coronary artery catheterisation across Australia and New Zealand. The variation in practice and factors impacting clinical decision-making highlight a need for future strategies to optimise evidence translation and implementation across clinical settings.</p
Middle Stone Age technological organisation from MIS 5 at Mertenhof Rockshelter, South Africa
No full textLithic technological organisation within the southern Africa Early Middle Stone Age (∼315,000–80,000 years ago) has seen relatively little investigation owing to the subtly of technological change, frequent use of locally derived raw materials, and the archaeological spatio-temporal discontinuity. This has resulted in relatively limited use of explanatory models for technological variability, including mobility, provisioning, tool production, and core reduction strategies. This paper uses 2952 artefacts to test the lithic technological organisation across Marine Isotope Stage 5 units of Mertenhof Rockshelter. Here we argue that the scales and concepts currently used to approach Early Middle Stone Age technology requires reconsideration. The Mertenhof sequence exhibits high proportions of non-local raw materials with their transport reflective of tactical adjustments within relatively stable mobility, provisioning, and reduction strategies. We demonstrate that Early Middle Stone Age populations maintained a diverse array of tactical solutions across these strategic domains, offering a durable and flexible strategy that would be adapted to changing contexts.</p
Effect of embedding a sieving phase into the current plastic recycling process to capture microplastics
No full textThis study proposes a systematic change to the current plastic recycling process by introducing a sieving stage in between the shredding and washing units to capture the microplastics being unintentionally generated and released. The benefit of adding the sieving stage to minimise microplastics release to wash water was highlighted by comparing the findings with the case where microplastics are released to wash water and a conventional coagulation process is used to remove microplastics from water. Two coagulants, aluminium sulphate (Al2(SO4)3.18H2O) and aluminium chloride (AlCl3.6H2O), were used to remove polyethylene terephthalate (PET) and polycarbonate (PC) from water. The size of the microplastic particles played a significant role on the removal efficiency. The maximum removal efficiency of PET by AlCl3.6H2O was 99.2 % for the particles in 1.18–5 mm range, whereas the average removal efficiency over the whole tested size range of 0.15–5.00 mm was 76.1 % for the same plastic-coagulant combination. By contrast, the addition of a 5 mm sieve between the shredding and the washing units was found to capture 96–97 % of the microplastics generated. The findings of this innovative experiment demonstrate the beneficial impact that this strategy has on capturing microplastics prior to entering water matrix.</p
“More than just jua kali”: Innovators of the informal waste circular economy in Kenya
No full textJua kali is a term used in Kenya to describe informal entrepreneurs who are known for their versatility and inventiveness. The informal sector refers to economic activities that are unregulated or protected by formal legal frameworks and operate outside traditional wage employment. Individuals and groups like the jua kali have been credited with driving grassroots changes in the Global South from the bottom up. This is despite continued marginalisation from postcolonial and neo-colonial policies. This study explores the involvement of the informal sector in Kenya as actors in implementing sustainable waste management principles. As rapid population growth and increased industrial development outpaces urban infrastructure, urban areas face adverse impacts from various social pressures, particularly waste. Improper waste management can cause a range of social issues and can also contribute to global climate pressures, increased pollution, and depletion of natural resources. While informal entrepreneurs are emerging as alternative actors in implementing sustainable waste practices in urban areas in most Global South Countries, literature on informal entrepreneurs in Kenya and their impact is limited. The informal entrepreneurs in Kenya have been known to drive waste recovery and recycling processes from traditional linear production and consumption systems to regenerative and sustainable models. However, more research needs to critically discuss their potential adaptation strategies and approaches.</p
Safety Analysis and Behaviour Modelling of Vulnerable Road Users
No full textWalking and cycling are essential and important components in facilitating the sustainability of multimodal transport systems and forming a healthy lifestyle for the communities. Safety concerns of vulnerable road users bring great challenges to road infrastructure design and policy regulations development. To better understand vulnerable road users’ behaviours and protect their safety, a growing amount of research has been conducted on crash analysis, crowd dynamics and behaviour modelling over the past decades. However, how to further reduce their safety risks and improve their comfort levels under various circumstances still needs to be investigated. Especially, the increasing prevalence of emerging mobilities (e.g., e-bicycle and e-scooter) and the long-term impact of COVID-19 pandemic potentially posed great threats on vulnerable road users’ safety and comfort levels. To fill the research gap, this thesis aims to conduct safety analysis and behaviour modelling of vulnerable road users under complicated and mixed road environments. Unobtrusive observation methods were mainly adopted to collect multi-source dataset in real-life scenarios to extract road users’ trajectories, interactive behaviours and surrounding environments. The investigated scenarios included unidirectional pedestrian flow with focus on overtaking behaviour and COVID-19’s impact, crossing flow of pedestrians and cyclists at different types of bus stops with interactions and conflicts, and bidirectional mixed flow of pedestrians, cyclists and e-cyclists at non-segregated and segregated signalised intersections. In addition, pedestrian and cyclist crashes at micro- and macro-levels in the Australian Capital Territory (ACT) in Australia were explored. In total, more than 20,000 vulnerable road users (including pedestrians, cyclists and e-cyclists) were observed and analysed in this thesis. Statistical analysis was utilised to reveal the behaviour differences among heterogenous vulnerable road users, such as road user characteristics, traffic features and road environments. Microscopic models were developed to describe and reproduce road users’ movement patterns (e.g., speed, route choice, social distancing, and collision avoidance); and statistical models were adopted to estimate the effects of multiple influencing factors on safety risks of road users and operation efficiency of transport facilities (e.g., conflict occurrence, conflict severity, lag-time and evasive actions). The research findings are expected to provide valuable information to reveal reasons behind traffic crashes, and predict potential safety risks and congestion issues of vulnerable road users. Based on the research outcomes, multiple recommendations on transport infrastructure design and policy making on traffic regulations are proposed. This research is able to provide an opportunity to reduce the safety and comfort issues of vulnerable road users, improve the effectiveness of policy regulations and planning strategies, and create a safe and vulnerable road user-friendly road environment.</p
Development and Characterisation of MOSFET Sensor for Dosimetry in DaRT and Proton Therapy
No full textIn modern radiotherapy, development of cancer treatment modalities has advanced to improve patient outcome, but new therapies come with various challenges for dosimetry and quality assurance (QA). In vivo dosimetry (IVD) is a methodology that monitors the actual dose independent to treatment planning system (TPS) by placing dosimeters on the patient skin, at a distance with build-up, or inside the patient. Comprehensive in vivo dose verifications are essential to identify major deviations in treatment delivery and even serve as patient QA but are not yet implemented during treatment. However, only a few radiotherapy centres worldwide include IVD during the treatment. MOSFET dosimeters are identified as advantageous for IVD given their small sensitive volume and real-time readout response. Dosimetric characteristics of MOSFET, such as linearity of doseresponse, sensitivity as a function of bias on the gate and fading response, are highly important for their application in radiotherapy. This thesis aims to characterise the MOSFETs that are developed and designed by the Centre for Medical and Radiation Physics, University of Wollongong, with three types of radiations for use as in vivo dosimeter.</p