Doctoral Training Partnerships: a range of postgraduate training is funded by the Research Councils. For information on current funding routes, see the common terminology at https://www.ukri.org/apply-for-funding/how-we-fund-studentships/. Training grants may be to one organisation or to a consortia of research organisations. This portal will show the lead organisation only.

Doctoral Training Partnerships: a range of postgraduate training is funded by the Research Councils. For information on current funding routes, see the common terminology at https://www.ukri.org/apply-for-funding/how-we-fund-studentships/. Training grants may be to one organisation or to a consortia of research organisations. This portal will show the lead organisation only.

This network has been designed to ask how we might tell a different story of conflict and peace-building. It will examine the potential of sensory history - and an awareness of how our bodies exist in the world - to unlock alternative narratives of the Northern Irish Troubles. Using sight, sound, smell, taste and touch, the network will ask how we might discover the ways people experienced societal structures and human interactions at a deep, often unconscious level. The network proposes bringing together academics, policy makers and arts practitioners to explore ways of drawing out, articulating and representing memories of life during, and emerging from, conflict. The Troubles began just over fifty years ago, marking now a significant memory moment in its history. Fiftieth anniversaries bring an awareness that living memory is beginning to fade (and indeed visibly die) and is shifting into a cultural or societal form of remembrance. This can sometimes mean that narratives congeal around partisan versions of the past that confirm binary political identities and miss the individual, embodied experience. Religion and political affiliation were not the only factors shaping people's lives during the Troubles: they were also shaped by class, gender, sexuality, ethnicity, age, (dis)ability and geography. This network aims to develop a methodological approach that draws out the complexity of individual experiences in a way that also allows for a better understanding of the broader society in which people lived. The network proposes bringing together academics from the arts and humanities, natural sciences and social sciences to develop a sociosmatic methodology for understanding the Troubles. This means bringing together the study of interior lives and external structures in order to understand the impact of social dynamics on the individual. It will draw on the expertise of disciplines ranging from neuroscience, psychology and philosophy to history, geography and film studies to create a durable theoretical approach to the subject. Scholars from drama, music, dance and photography will share knowledge of multi-sensory research. The network will also work closely with arts practitioners to create a dynamic space for memory gathering and representation. Each network event will be designed to inspire discussion, encourage reflexivity and create meaningful collaborations between academics and arts practitioners. Morning sessions will include an arts-based activity which serves as stimulus for conversations in the afternoon and explores different representations of the sociosomatic past. Significance will also be given to the phenomenological experience of all participants. The aim is to construct a multi-sensory programme which includes walking, watching, hearing, tasting and listening as well as speaking. It is anticipated that the network's findings will be of benefit to a range of constituents. The academic audience is inter-disciplinary and includes scholars of embodied representations of the past as well as those who work on conflict and post-conflict societies internationally. A central aim of the network is to build capacity in this area of study and the programme contains a series of masterclasses aimed at early-career scholars. Moreover, the significance of arts practitioners to the network will provide avenues for further collaborations. The main findings of the network will be sent to the Commission for Victims and Survivors as part of its consultation process and contribute to preparations for the Oral History Archive as part of the Stormont House Agreement. Through its interventions and innovations, the network will formulate new and innovative ways to retell and re-present the stories of contested pasts.

To develop a dynamic, integrated, BIM capable business solution, automating key functions through the application of computer vision techniques.

The proliferation of software across all aspects of our life means that software failure can have significant economic and social impact. It is therefore highly desirable to be able to develop software that is formally verified as correct with respect to its expected specification. This has also been identified as a key objective in one of the UK Grand Challenges (GC6). Although research on formal verification has a long history, dating back to the 1960's, it remains a challenging problem to automatically verify programs written in mainstream imperative languages such as C, C++, C# and Java. This is in part due to the prolific use of (recursive) shared mutable data structures which are difficult to keep track of statically and in a precise and concise way.The emergence of separation logic promotes scalable reasoning via explicit separation of structural properties over the memory heap where recursive data structures are dynamically allocated. Using separation logic, progress has recently been made on automated verification for pointer safety in the separation/shape domain. To verify the more general memory safety and functional correctness, it will require the combination of both separation (structural) and numerical (e.g. size) information. Therefore, advanced analysis and verification techniques are needed in the combined separation and numerical domain to verify memory safety and functional correctness. Nevertheless, this remains a clear challenge for program analysis research.As a first step to tackle the challenge, Our recent development on program verification using a combined separation and numerical domain also allows user-specified inductive predicates to appear in program specifications for better expressivity. Based on this specification mechanism, a verification system called HIP/SLEEK has been built to conduct the automated verification and proof search. Our experimental results have confirmed the viability of this approach. One issue with the current system is that it is a liability for the users to supply all loop invariants and method pre/post-conditions prior to the verification. This can be very demanding and challenging for the users.As the second phase towards tackling the challenge, we propose to develop advanced inference mechanisms in the combined separation and numerical domain with user-defined predicates so that loop invariants and method pre/post-conditions can be automatically synthesised, where possible. Achieving this goal means that a much higher level of automation will be achieved, therefore a significant advance will be made in automated verification on memory safety and functional correctness.A key objective in the proposed research is to find a systematic approach to abstraction construction in the combined domain, so that appropriate abstractions can be employed by the inference process. Abstractions are required in the analysis and verification for various reasons, such as termination and scalability. Appropriate abstraction mechanisms are crucial in maintaining a desirable scalability/precision trade-off. Apart from the abstraction mechanisms, we also intend to design analysis algorithms for loop invariant synthesis, method post-condition inference and method pre-condition discovery for the combined domain with arbitrary user-defined predicates. We will build a tool to implement these analyses and apply it to sizeable benchmark programs. As a challenging example, we will apply our tool for the verification of memory safety of a Linux kernel. Such a sizeable program can well be used to test the limit of our inference mechanisms. We believe our research outcomes will further improve the level of automation, and therefore significantly extend the viability and applicability of automated verification on memory safety as well as functional correctness for substantial imperative programs.