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Steering angle sensorless control for four-wheel steering vehicle via sliding mode control method
Get PDFThis paper presents a new sensorless control method for four-wheel steering vehicles. Compared to the existing sensor-based control, this approach improved dynamic stability, manoeuvrability, and robustness in case of malfunction of the front steering angle sensor. It also provided a software redundancy and backup solution, as well as improved fault tolerance. The strategy of the sensorless control is based on the sliding mode method to estimate the replacement of the front steering input from the errors between the vehicle’s measured and desired values of the vehicle’s sideslip angle and yaw rate. The simulation results demonstrate that the observer effectively estimated the front-wheel steering angle at both low and high speeds scenarios in the cornering and lane change manoeuvres. Furthermore, the sensorless control approach can achieve equivalent control performances to the sensor-based controller including a small and stable yaw rate response and zero sideslip angle. The results of the study offer a potential solution for improving manoeuvrability, stability, and sensor fault tolerance of four-wheel steering vehicles
MESON: A Mobility-aware Dependent Task Offloading Scheme for Urban Vehicular Edge Computing
Get PDFVehicular Edge Computing (VEC) is the transportation version of Mobile Edge Computing (MEC) in road scenarios. One key technology of VEC is task offloading, which allows vehicles to send their computation tasks to the surrounding Roadside Units (RSUs) or other vehicles for execution, thereby reducing computation delay and energy consumption. However, the existing task offloading schemes still have various gaps and face challenges that should be addressed because vehicles with time-varying trajectories need to process massive data with high complexity and diversity. In this paper, a VEC based computation offloading model is developed with consideration of data dependency of tasks. The minimization of the average response time and average energy consumption of the system is defined as a combinatorial optimization problem. To solve this problem, we propose a Mobility-aware dependent task offloading (MESON) Scheme for urban VEC and develop a DRL-based algorithm to train the offloading strategy. To improve the training efficiency, a vehicle mobility detection algorithm is further designed to detect the communication time between vehicles and RSUs. In this way, MESON can avoid unreasonable decisions by lowering the size of the action space. Moreover, to improve the system stability and the offloading successful rate, we design a task priority determination scheme to prioritize the tasks in the waiting queue. The experimental results show that MESON is superior compared to other task offloading schemes in terms of the average response time, average system energy consumption, and offloading successful rate
Identifying a research agenda for postgraduate taught education in the UK: lessons from a machine learning facilitated systematic scoping review
Get PDFThis research aimed to describe and evaluate research on the Postgraduate Taught (PGT) sector in the UK from January 2008 to October 2019. The focus on PGT allowed a detailed analysis of an often overlooked part of the HE sector. Methodologically, the research is original in its use of an innovative machine learning approach to a systematic scoping review. The review scrutinised subject areas, topics studied and methodological approaches taken. Initial searches found 9,814 potentially relevant studies which were reduced to 693 for analysis. The machine learning approach was successful in reducing time without compromising accuracy. We conclude that this methodological approach is appropriate for similar reviews within education. Findings show a dominance of research into professional education programmes; a majority of research with PGT as the context rather than focus; a small number of comparative and large-scale studies; and substantial research categorised as ‘scholarship of teaching’. While further research is required to ascertain if the findings are transferable to other national contexts, this study provides a reproducible methodology and identifies areas for future research to examine
Improving quality of experience in adaptive low latency live streaming
Get PDFHTTP Adaptive Streaming (HAS), the most prominent technology for streaming video over the Internet, suffers from high end-to-end latency when compared to conventional broadcast methods. This latency is caused by the content being delivered as segments rather than as a continuous stream, requiring the client to buffer significant amounts of data to provide resilience to variations in network throughput and enable continuous playout of content without stalling. The client uses an Adaptive Bitrate (ABR) algorithm to select the quality at which to request each segment to trade-off video quality with the avoidance of stalling to improve the Quality of Experience (QoE). The speed at which the ABR algorithm responds to changes in network conditions influences the amount of data that needs to be buffered, and hence to achieve low latency the ABR needs to respond quickly. Llama (Lyko et al. 28) is a new low latency ABR algorithm that we have previously proposed and assessed against four on-demand ABR algorithms. In this article, we report an evaluation of Llama that demonstrates its suitability for low latency streaming and compares its performance against three state-of-the-art low latency ABR algorithms across multiple QoE metrics and in various network scenarios. Additionally, we report an extensive subjective test to assess the impact of variations in video quality on QoE, where the variations are derived from ABR behaviour observed in the evaluation, using short segments and scenarios. We publish our subjective testing results in full and make our throughput traces available to the research community
Underwater image clarifying based on human visual colour constancy using double‐opponency
Get PDFUnderwater images are often with biased colours and reduced contrast because of the absorption and scattering effects when light propagates in water. Such images with degradation cannot meet the needs of underwater operations. The main problem in classic underwater image restoration or enhancement methods is that they consume long calculation time, and often, the colour or contrast of the result images is still unsatisfied. Instead of using the complicated physical model of underwater imaging degradation, we propose a new method to deal with underwater images by imitating the colour constancy mechanism of human vision using double‐opponency. Firstly, the original image is converted to the LMS space. Then the signals are linearly combined, and Gaussian convolutions are performed to imitate the function of receptive fields (RFs). Next, two RFs with different sizes work together to constitute the double‐opponency response. Finally, the underwater light is estimated to correct the colours in the image. Further contrast stretching on the luminance is optional. Experiments show that the proposed method can obtain clarified underwater images with higher quality than before, and it spends significantly less time cost compared to other previously published typical methods
Leadership identity construction in a hybrid medical context: ‘Claimed’ but not ‘granted'
Get PDFIn the United Kingdom National Health Service (NHS), the growing number of hybrid clinical leaders has given rise to professional practice and identity struggles. Co-construction theories of leadership point to a need for leaders to engage in significant 'identity work' to construct themselves as leaders and to make legitimate claims for a leadership identity to potential followers. Our research aimed to contribute to the leader-follower literature by examining how medical leaders deal with professional identity struggles and changes to traditional work identities. We draw on data from a study of senior hospital doctors (consultant-level doctors from a variety of medical specialties in Health Boards in NHS Scotland). Our findings suggest that most senior hospital doctors in our study struggle to grant leadership identities to their medical leaders who claim such leadership identities, although they seek to see more doctors engaging in leadership. This article contributes to extant research on the influence of medical leadership roles on leader-follower identity construction
HIV Testing Disruptions and Service Adaptations During the COVID-19 Pandemic: A Systematic Literature Review
Get PDFAccess to treatment and care in safe clinical settings improves people’s lives with HIV. The COVID-19 pandemic disrupted vital HIV programs and services, increasing the risk of adverse health outcomes for people with HIV and HIV transmission rates in the community. This systematic literature review provides a meta-analysis of HIV testing disruptions and a synthesis of HIV/AIDS services adapted during COVID-19. We searched scholarly databases from 01 January 2020 to 30 June 2022 using key terms on HIV testing rates and services during the COVID-19 pandemic. The process of how the included articles were identified, selected, appraised, and synthesised was reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. We included 17 articles that reported changes in HIV testing during the COVID-19 pandemic and 22 that reported adaptations in HIV/AIDS services. We found that HIV testing decreased by 37% during the search period because of the COVID-19 pandemic. Service providers adopted novel strategies to support remote service delivery by expanding community antiretroviral therapy dispensing, setting up primary care outreach points, and instituting multi-month dispensing services to sustain client care. Therefore, service providers and policymakers should explore alternative strategies to increase HIV testing rates impacted by COVID-19 and leverage funding to continue providing the identified adapted services
Applied Social Science for Nursing Students
No full textThis book introduces the essential social science that you need in order to register and practice effectively as a nurse. Contributions from the social sciences enable you to better understand the world view of your patients and service users, as well as the wider social, cultural and political landscape in which they live and you provide care. This book will help you apply this knowledge to your everyday practice. Be it providing holistic person-centred care, advocating for your patients and their communities, or contributing to service improvement, understanding the social sciences is key to a nursing career that truly makes a difference
Adaptive Event-Triggered Bipartite Formation for Multiagent Systems via Reinforcement Learning
Get PDFThis article investigates the online learning and energy-efficient control issues for nonlinear discrete-time multiagent systems (MASs) with unknown dynamics models and antagonistic interactions. First, a distributed combined measurement error function is formulated using the signed graph theory to transfer the bipartite formation issue into a consensus issue. Then, an enhanced linearization controller model for the controlled MASs is developed by employing dynamic linearization technology. After that, an online learning adaptive event-triggered (ET) actor-critic neural network (AC-NN) framework for the MASs to implement bipartite formation control tasks is proposed by employing the optimized NNs and designed adaptive ET mechanism. Moreover, the convergence of the designed formation control framework is strictly proved by the constructed Lyapunov functions. Finally, simulation and experimental studies further demonstrate the effectiveness of the proposed algorithm
A 16-week progressive exercise training intervention in treatment-naïve chronic lymphocytic leukaemia: a randomised-controlled pilot study
Get PDFBackground: Chronic lymphocytic leukaemia (CLL) typically presents with asymptomatic, early-stage disease that is monitored until disease progression (‘treatment-naïve’ CLL). The objective of this pilot study was to assess the feasibility and preliminary safety of an exercise program in treatment-naïve CLL. We also sought to preliminarily assess the impact of the exercise program on disease activity, as it has been proposed that exercise training may reduce disease outgrowth in treatment-naïve CLL. Methods: A total of 40 treatment-naïve CLL patients were recruited into this randomised-controlled pilot study, and after screening, n = 28 were randomised into a 16-week, home-based, partially supervised, personalised, progressive exercise intervention (n = 14: mean ± SD: age = 62 ± 12 years) or 16 weeks of usual care, control group (n = 14: mean ± SD: age = 61 ± 10 years). The primary outcome measures were safety (number and severity of adverse events) and feasibility (uptake, retention, and adherence to the trial). Disease activity (CD5+/CD19+ CLL cells clonally restricted to kappa or lambda) and other immune cell phenotypes, with a principal focus on T cells, were measured by flow cytometry. Other secondary outcomes included DEXA-derived body composition, cardiorespiratory and functional fitness, resting cardiovascular measures. Results: Trial uptake was 40%, and the overall retention rate was 86%, with 79% of the exercise group and 93% of the control group completing the trial. Adherence to the exercise intervention was 92 ± 8%. One serious adverse event was reported unrelated to the trial, and one adverse event related to the trial was reported. The exercise intervention elicited a 2% increase in DEXA-derived lean mass in the exercise group compared with a 0.4% decrease in the control group (p = 0.01). No between-group differences were observed over time for whole-body mass, BMI, bone mineral density, body fat, blood pressure resting heart rate, or measures of cardiorespiratory or functional fitness (all p > 0.05). No between-group differences were observed over time for clonal CLL cells and CD4+ or CD8+ T-cell subsets (all p > 0.05). Conclusion: The exercise training program used in this study was feasible in people with treatment-naïve CLL who passed pre-trial screening, and we preliminarily conclude that the exercise training program was safe and also resulted in an increase in lean mass. Clinical trial registration: https://doi.org/10.1186/ISRCTN55166064, identifier ISRCTN 55166064
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