RSS 1.0Welcome to ChesterRep - the University of Chester's Online Research Repository
ChesterRep is the University of Chester's institutional repository and an online platform designed to collate, store, and aid discoverability of the University’s research.
All University of Chester staff are expected to use the Current Research Information System, Symplectic Elements, to submit material to ChesterRep. Guidance on how to deposit and manage publications using Elements can be found here. You can also discover more about our editorial and open access policies here. Please note that you must be a member of the University to view these pages.
If you are a student at the University of Chester and want to submit work to ChesterRep, please contact researchsupport.lis@chester.ac.uk.
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Dentistry in university education: Philosophy and purposeTertiary education or further education which is often synonymously used for higher education is to be found not only in universities but also in vocational or technical training schools, institutes, and colleges. Hence, all tertiary education is not equivalent to what is known as university education, but all university education is tertiary education. From this definition, dental education is university education. Therefore, the philosophical domains of dental education is vast and overwhelmingly numerous with great complexity and social significance in line with the philosophy of education as well as philosophy of higher education. Dentistry has evolved from a description of decaying teeth to a comprehensive program of independent professional discipline. Albeit, how dental schools are structured or how dental education is being offered within the university is not universal. Mostly the relationship between dental schools and medical schools and mode of offering dental education and medical education in relation to the overall healthcare system varies significantly. This chapter touches upon the philosophical issues of education in general with focused attention to dentistry as a university education.
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IoT embedded software manipulationThe Internet of Things (IoT) has raised cybersecurity and privacy issues, notably about altering embedded software. This poster investigates the feasibility of using Read-Only Memory (ROM) at a low level to modify IoT devices while remaining undetectable to users and security systems. The study explores the vulnerabilities in embedded code and firmware, which are frequently proprietary and inaccessible, making them challenging to safeguard efficiently. The methodology uses a black-box forensic technique to acquire software, identify functions, and create test cases to assess potential alterations. The findings aim to contribute to a better understanding of IoT security concerns, emphasising the importance of upgraded firmware protection methods. This research highlights the challenges of detecting low-level attacks on IoT devices and provides insights into improving embedded system security.
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‘Give me a minute, I just need to put you into your groups’: Transferring group activities to the online space using breakout roomsTransitions to online learning as a result of the COVID-19 pandemic challenged how group-based activities were delivered. This paper explores how a quantitative social research design project allowed insights into digital pedagogy. Transition to group working in breakout rooms required planning to be centred on an imagined student learning experience. As a Graduate Teaching Assistant (GTA), this included understanding the dynamics by group, supporting learning in the digital space, presenting accessible materials, facilitating the learning process across multiple groups, and (re)planning teaching sessions successfully for the online milieu. Breakout rooms are dispersed digital learning spaces and were in use at a time when students were experiencing significant declines in mental health, challenges with digital exclusion, disengagement, and a lack of online confidence in peer-to-peer relationships (Peper et al., 2021; Savage et al., 2020). Addressing these key factors required a more student-centred planning approach, based on individual and group needs, in ways which were not seen within face-to-face delivery. Drawing on experiences of the potential for isolation and uncertainty for students in breakout room spaces, I reimagined the digital space in terms of material presentation, facilitating student empowerment, and communicating and managing across multiple breakout rooms concurrently. These strategies contributed towards positive student experiences, providing pedagogical insights into newer online teaching practices for GTAs.
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Detecting sleep anomalies from SpO2 data using autoencoder-based neural networksSpO2 is a vital indicator for diagnosing OSA. This study presents an automated detection framework integrating an adaptive VMD denoising algorithm with deep learning-based autoencoder models to identify abnormal signals in SpO2 data. We evaluated four autoencoder architectures (VAE, CAE, LAE, and CLAE) on PPG and OPEN datasets. The VMD algorithm achieved an RMSE of 0.862% compared to the SOMNOtouch device, while the LAE model exhibited superior detection performance, achieving the highest precision, F1-score, and accuracy, attributed to its LSTM-based temporal modelling capabilities, albeit at greater computational cost. Study finds there is a non-linear relationship between architectural complexity and performance gains, where increased model sophistication may not necessarily yield proportional improvements in effectiveness. Dataset characteristics significantly influenced model performance, with limited differences observed in the small, homogeneous PPG dataset, while the diverse OPEN dataset highlighted the advantages of temporal modelling. While effective, the framework's current limitations include dataset size constraints and class imbalance issues, suggesting directions for future optimization. These findings advance our understanding of automated sleep apnoea detection and provide insights for developing more robust monitoring systems.
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‘Excuse me, I have a delivery’ The [re] construction of interview ‘space' in the Covid-19 pandemicCovid-19 has transformed the qualitative interview process, as remote video methods have become mainstream, challenging the domination of face-to-face interviews. In the pandemic churn, researchers’ focus was on ensuring participants’ safety and care in the virtual interview environment. There was more limited consideration of what this ‘new normal’ meant for the researcher. This reflection draws on two qualitative research projects conducted during the 2020/2021 pandemic period in the UK. We propose that assumptions of ‘space’ in the qualitative interview process have been (re)constructed in remote interviews during Covid19. To be present virtually creates geographic freedoms of participant access, but subjective risks from interviewing in the virtual space. Context can no longer be understood through the shared experience of an interview space. There is a delineation of what is ‘public’ or ‘private’ as participants and researchers share their domestic spheres. Using ethnographic reflections, we explore the changing notions of geographic, public and private space in the Covid-19 interview.
