PhD Theses Collectionhttp://hdl.handle.net/2299/1082024-03-28T22:33:05Z2024-03-28T22:33:05ZHow Racially-Minoritised Trainees Make Sense of Their Problem-Based Learning ExperiencesSaini, Geenahttp://hdl.handle.net/2299/274752024-03-05T02:30:12Z2023-12-01T00:00:00ZHow Racially-Minoritised Trainees Make Sense of Their Problem-Based Learning Experiences
Saini, Geena
Predominately non-empirical literature suggests racially-minoritised trainees have difficult and painful experiences of clinical psychology training (DClinPsy). This limited literature focuses on experiences of the DClinPsy course as a whole. Problem-Based Learning (PBL) is part of the curriculum for a third of DClinPsy courses. Despite research exploring trainees’ experiences of PBL on the DClinPsy, little is known about the racial make-up of trainees involved in these existing bodies of research. In a bid to address this gap, this inquiry sought to hear the narratives of racially-minoritised trainees who had completed PBL.
A moderate social constructionist lens was drawn on to explore, qualitatively, racially-minoritised trainees’ experiences of PBL. This study used a purposive sample of five racially-minoritised current or ex-trainees who had completed their PBL journey. Semi-structured interviews were recorded, transcribed and narratively analysed, keeping in mind thematic, performative, structural and co-constructed elements of storytelling.
Summaries and interpretations of each racially-minoritised trainees’ narratives were presented. Across all accounts, resemblances and differences were also considered, focusing on how the three main storylines (stories of the group, stories of self and stories of support) were interwoven with trainees’ racial identity and the microcosm of PBL, whilst situated within wider narratives. Racially-minoritised trainees reported that PBL is predominately ‘unsafe’ for them, but despite this, they are able to connect to the positives and learning that emerged from their PBL experiences. Support systems, group identity and connection impacted the PBL experiences for racially-minoritised trainees. All trainees situated PBL within wider socio-cultural and personal narratives, highlighting PBL cannot be viewed as separate from broader contexts. Trainees’ racial identity was ever present, shaping how they interacted, protected themselves and viewed PBL.
This unique research has produced new knowledge on PBL and racially-minoritised trainees’ experiences. Implications for DClinPsy courses were outlined, and several invitations for further research were presented.
2023-12-01T00:00:00ZExploring the design of people-centred inclusive smart cities using integrated inclusion approaches and citizen engagement strategies through case studies of London, Bengaluru, and KampalaKamtam, Prakashhttp://hdl.handle.net/2299/274742024-02-27T02:30:11Z2023-07-18T00:00:00ZExploring the design of people-centred inclusive smart cities using integrated inclusion approaches and citizen engagement strategies through case studies of London, Bengaluru, and Kampala
Kamtam, Prakash
The twenty-first century is the age of cities. A country's sustainable growth and development depend on its cities' success and failure. The smart city approach, the new and emerging model of urban development, is expected to offer plausible solutions to tackle urban challenges. However, the different smart city models that evolved around the globe are still at a nascent stage and are subject to substantial debates and questions. Critical questions still need to be answered: Does this new urban development paradigm contribute to all its citizens' well-being, leaving no one behind? Is urban inclusion a priority in current smart city planning? If so, does smart city planning address the challenges of the inclusion of vulnerable and disadvantaged populations living in cities? How ICT and digital innovations can contribute to change in our contemporary cities? Do they have the potential to improve quality of life, access, participation and opportunity and eliminate exclusion and existing inequalities?
Urban inclusion, the crucial aspect of sustainable development, is a critical challenge. It affects different people, often identified by gender, age, race, religion, class, and disabilities, including migrants and refugees. However, the current discussions of urban inclusion within the extant smart city literature are abstract and limited in their scope and considerations. This research focuses on this gap and contributes to the research literature and the advancement of practice-based knowledge to better understand inclusive development models in smart city theory, principles and projects.
The key question guiding this research is: Can smart city be equitable; does it address the current challenges of urban inclusion and contribute to the well-being of all citizens, leaving no one behind? This research investigates the critical challenges of urban inclusion in contemporary cities and explores the interplay between the smart city and the inclusion of vulnerable and disadvantaged populations. The study involves a literature review of the existing research and policy landscape, exploring evidence from multiple data sources, including rigorous document analysis, followed by a qualitative study of three case studies (London, Bengaluru and Kampala), providing an enriching spatial comparison with additional inputs from global thematic experts. To increase the credibility and validity of qualitative research, semi-structured interviews are conducted with relevant stakeholders from the case study locations and other global regions.
This study offers conceptual, theoretical, and empirical contributions to knowledge about the dimensions, challenges and relationships of the inclusion of vulnerable and disadvantaged populations in smart city planning and development. It aims to identify new tools and methods and offer policy recommendations for enhanced inclusion and equity. The integrated inclusion approach and renewed citizen engagement strategies are expected to contribute to people-centric and inclusive smart city planning. The recommendations include an integrated inclusion vision, an inclusive smart city framework and certain key elements of a citizen engagement strategy. This study focuses on vulnerable and disadvantaged populations like- the elderly, people with disabilities, women, children, youth, poor, migrants, refugees and other minority and ethnic and religious groups, including the LGBTI community, who are often neglected and excluded from mainstream development.
This study is relevant to understanding the need and urgency of an inclusive smart city development approach and suggesting the basic and essential guidelines and integrated framework to address the specific challenges identified in this study and for creating a basis for an inclusive approach and for designing future cities that are more inclusive and equitable, thus leaving no one behind.
2023-07-18T00:00:00ZReal-Time Application of Deep Learning to Intrusion Detection in 5G-Multi-Access Edge ComputingFernando, Omesh Anthonyhttp://hdl.handle.net/2299/274732024-02-27T02:30:11Z2024-01-29T00:00:00ZReal-Time Application of Deep Learning to Intrusion Detection in 5G-Multi-Access Edge Computing
Fernando, Omesh Anthony
In this thesis, we explore networks for 5G mobile telecommunication, with a real-time
detection of malicious traffic using Deep Learning (DL) and 5G mobile telecommunication
testbeds. To investigate the performance of the core network, Software Defined Networking
(SDN) and Programming Protocol-independent Packet Processors (P4) were selected due to
the potential for programming at the both control and data forwarding layer. SDN and P4 have
predominately been researched on an individual basis with limited research combining the
two to evaluate improvements to the performance of SDN. We have conducted experiments
to explore the hypothesis that combining programmability at both the control plane and
data plane provides a platform with better performance in comparison to that achieved with
SDN+OvS multi-path, grid and transit-stub network models.
A real-time 5G mobile telecommunication testbed has been constructed combining
both software and hardware components. A P4 switch was integrated into the 5G testbed
motivated by the performance gains observed in our initial experiments with P4 and OvS
switch. Service providers use Multi-access Edge Computing (MEC) technology to provide
services on-the-go with low latency, high availability, and high bandwidth, however, MEC
nodes are subject to low processing power, which leaves them susceptible to adversaries
that may target the platform for malevolent purposes. As a result, we built a 5G testbed that
included an MEC node to generate datasets representing both malicious and non-malicious
traffic for use in evaluating algorithms intended to detect malicious network traffic.
A new Intrusion Detection System (IDS) has been developed using a 3-layer
Convolutional Neural Network (CNN), capable of identifying malicious network traffic.
The IDS employs a new injective algorithm capable of encoding network traffic without
loss of information as improved RGB images. A separate algorithm capable of decoding
RGB images back to network traffic was also developed. The IDS was evaluated in terms
of its computational complexity in for example: time, memory and CPU utilisation for the
encoding and decoding algorithms, and its accuracy and loss during training and detection.
We also applied a Convolutional Neural Network to the dataset created on our testbed and
for comparative purposes, to the publicly available datasets UNSW NB-15 and InSDN. The
5G-MEC datasets and detection rate suggest that the employment of current public datasets
for research into 5G-MEC security are now inappropriate.
Lastly, we proposed, developed, deployed and evaluated a Real-Time Deep Learning
Network Intrusion Detection System (RTDL-NIDS) in an MEC node located in the newly
developed 5G-MEC mobile telecommunication testbed in real-time. The deployed Network
Intrusion Detection System, conducts a soft real-time detection. The time spent on each
detection cycle can be defined as a parameter in the RTDL-NIDS. Hence, this system can be
categorised as a soft real-time system. The RTDL-NIDS conducts an initial detection based
on known signatures, followed by the encoding of network traffic to images, detection of
malicious traffic using our CNN algorithm, and finally decoding of the images to identify
the sources of malicious users. We implemented the RTDL-NIDS to function in real-time to
collect conclusive results over the application of DL to the intrusion detection problem in
5G-MEC.
2024-01-29T00:00:00ZGiving Hope to Rebuild Lives: Practical and Emotional Support for Those Bereaved by Road Traffic CollisionsWalsh, Tomáshttp://hdl.handle.net/2299/274722024-02-27T02:30:11Z2024-01-15T00:00:00ZGiving Hope to Rebuild Lives: Practical and Emotional Support for Those Bereaved by Road Traffic Collisions
Walsh, Tomás
In the United Kingdom (UK), the Department for Transport (DfT) reported that 1,558 people died in Road Traffic Collisions (RTC) in 2021 (DfT, 2022). A considerable proportion of the UK population is impacted by RTCs yearly. RTC deaths involve police investigations, coronial processes, insurance claims, court (criminal and civil) proceedings, hospitals, and even media attention (Mitchell, 1997; WHO, 2004), which potentially impact the grief experience of bereaved families (Breen & O'Connor, 2009; Tehrani, 2004). There is limited literature on support for bereaved family members (Huang, 2016). To better understand what supports people bereaved by RTCs with their grief, feedback from RTC support service Road Victims Trust (RVT) was analysed, and RVT service users and staff were interviewed. Data was gathered and analysed using Grounded Theory, and a model of the process of grief, bereavement support and the impact of the Criminal Justice System was developed from the data.
The model conceptualises grief as a dynamic process positively and negatively impacted by psycho-social factors, including counselling, informal support, practical support and the criminal justice system.
The findings suggest that the Criminal Justice System significantly impacts the bereaved who wish to know what happened to their loved one. Family Liaison Officers (FLOs) can be a source of support and information for families but are constrained by the demands of their job and the needs of investigations. These constraints can frustrate families. RVT counsellors are given training in bereavement and legal processes; this specialist knowledge helps them to support bereaved families to normalise their grief and frustration. People who have been bereaved by RTCs believe they needed professional support from RVT very soon after bereavement and could not have waited six months, as is recommended in some literature. Some participants wanted to receive peer support from people who have been through RTC bereavement, but RVT does not offer such a service; they were ultimately satisfied with the counselling they received.
2024-01-15T00:00:00Z