The age of Ubiquitous Computing is approaching fast: most people in the UK over the age of 8 carry mobile phones, which are becoming increasingly sophisticated interactive computing devices. Location-based services are also increasing in popularity and sophistication. There are many tracking and monitoring devices being developed that have a range of potential applications, from supporting mobile learning to remote health monitoring of the elderly and chronically ill. However, do users actually understand how much of their personal information is being shared with others? In a recently released report from the UK Information Commissioner, we were warned that the UK in particular is 'sleepwalking into a surveillance society', as ordinary members of the public give up vast amounts of personal information with no significant personal or societal advantage gained. In general, there will be a trade off between usefulness of disclosing private information and the risk of it being misused. This project will investigate techniques for protecting the private information typically generated from ubiquitous computing applications from malicious or accidental misuse.The project will investigate privacy requirements across the general population for a specific set of ubiquitous computing technologies. These requirements will be used to produce a Privacy Rights Management (PRM) framework that enables users to specify privacy preferences, to help visualize them, to learn from the user's behaviour what their likely preferences are, and to enforce privacy policies. We will make use of a large cohort of over 1000 OU students with a broad range of ages and backgrounds, both for identifying requirements and for evaluating tools for privacy management. This work will address a number of research issues:* how do people perceive privacy in ubiquitous systems?* what types of privacy controls would people like to have when using ubiquitous systems?* how to develop privacy control tools that are easy to use via simple interfaces (e.g. mobile phones) as well as large screen devices?* how to detect and resolve inconsistencies in users' privacy requirements?* what mechanisms can be used to automate privacy control in ubiquitous systems?The PRM framework we produce to address these issues will integrate users' privacy policies with their personal information to control how information is used. This is analogous to Digital Rights Management (DRM), which often incorporates information such as 'digital watermarks' in the data being protected or encapsulates the data such that it is self protecting. By providing an analysis and learning system within the framework, we believe that we can produce a usable system that does not burden users with complex privacy rule sets. The project relates to the Memories for Life and Ubiquitous Computing Grand Challenges, both of which raise issues relating to PRM in mobile applications.

We are witnessing a profound change in the interaction model of the World Wide Web (Web). Documents, once created from a single source and delivering static client-side content, have now evolved into composite documents created from multiple third party sources delivering dynamically changing information streams. There are few interaction problems when delivering these parallel streams visually. The real problems arise due to the underlying incoherent nature of this 'new' Web model and the composite documents it creates. Changes in context and multiple dynamic updates all compete for the user's attention, producing an incoherent cacophony if the delivery is serial and in audio. Consequently, naive one--shot sensory translation can no longer support the user.This shift in the way the Web works comes with a corresponding increase in the cognitive load required for audio interaction. Without a full understanding of this evolving interaction model, along with its extent and context, the Web will rapidly become unable to support the interaction of visually disabled people.Our objective is to investigate, design, and build a homogeneous mapping framework to support the relating of competing visual streams into a single coherent and mediated accessibility stream such that when automatically applied to a Web document a mapping from parallel visual to serial audio can be achieved. Indeed, because serial mappings are cognitively simpler to understand we would also expect to see side-benefits in cognitive impairment, ageing, and the mobile Web (Whose users share a number of cognitive similarities with visually disabled users -- RIAM EP/E002218/1).To achieve this objective we propose to undertake fundamental research in the areas of: (a) the cognition and perception of dynamic Web based information; (b) the nature of the new Web interaction / infrastructure model as it evolves; and (c) new Web technologies when applied to visually disabled and sighted users. Thus, SASWAT is multidisciplinary with an industrial route to exploitation and has five major aims: 1) Carry out a fundamental investigation of the visual experiences of sighted individuals interacting with competing dynamic information streams in order to better understand the nature of their interaction; 2) Develop a profound understanding of the nature and evolution of the underlying Web infrastructure as it moves from a traditional stateless paradigm to one focused on composite / compound documents and `push' information streams;3) Build a model of Web interaction, based on this investigation, and a mapping of perceptual and cognitive interactivity from sighted to visually disabled users;4) Design and develop an experimental framework to mediate between the competing demands of compound Web pages and multiple information streams;5) Use our corpus of knowledge and experimental tools to perform a systematic and replicable evaluation of the utility of our approaches.

Reasoning about concurrent programs is difficult because of the need to consider all possible interactions among concurrently executing threads. Modular reasoning techniques sidestep this difficulty by considering every thread in isolation under some assumptions on its environment. To date, such techniques have been largely limited to the verification of properties that guarantee the absence of bad events (safety properties). The available modular techniques do not deal well with the remaining set of properties, which ensure that good events eventually happen (liveness properties).The aim of the proposed research is to develop logics for modular reasoning about liveness and performance properties of concurrent programs and methods of automating proofs in them. The logics and the methods should be applicable to a wide range of programs, including those that use fine-grained or non-blocking synchronization.The proposed research, if successful, will build the foundations for developing efficient, yet reliable, concurrent systems. In time, its results may feed into industrial tools for software development and verification.

The age of Ubiquitous Computing is approaching fast: most people in the UK over the age of 8 carry mobile phones, which are becoming increasingly sophisticated interactive computing devices. Location-based services are also increasing in popularity and sophistication. There are many tracking and monitoring devices being developed that have a range of potential applications, from supporting mobile learning to remote health monitoring of the elderly and chronically ill. However, do users actually understand how much of their personal information is being shared with others? In a recently released report from the UK Information Commissioner, we were warned that the UK in particular is 'sleepwalking into a surveillance society', as ordinary members of the public give up vast amounts of personal information with no significant personal or societal advantage gained. In general, there will be a trade off between usefulness of disclosing private information and the risk of it being misused. This project will investigate techniques for protecting the private information typically generated from ubiquitous computing applications from malicious or accidental misuse.The project will investigate privacy requirements across the general population for a specific set of ubiquitous computing technologies. These requirements will be used to produce a Privacy Rights Management (PRM) framework that enables users to specify privacy preferences, to help visualize them, to learn from the user's behaviour what their likely preferences are, and to enforce privacy policies. We will make use of a large cohort of over 1000 OU students with a broad range of ages and backgrounds, both for identifying requirements and for evaluating tools for privacy management. This work will address a number of research issues:* how do people perceive privacy in ubiquitous systems?* what types of privacy controls would people like to have when using ubiquitous systems?* how to develop privacy control tools that are easy to use via simple interfaces (e.g. mobile phones) as well as large screen devices?* how to detect and resolve inconsistencies in users' privacy requirements?* what mechanisms can be used to automate privacy control in ubiquitous systems?The PRM framework we produce to address these issues will integrate users' privacy policies with their personal information to control how information is used. This is analogous to Digital Rights Management (DRM), which often incorporates information such as 'digital watermarks' in the data being protected or encapsulates the data such that it is self protecting. By providing an analysis and learning system within the framework, we believe that we can produce a usable system that does not burden users with complex privacy rule sets. The project relates to the Memories for Life and Ubiquitous Computing Grand Challenges, both of which raise issues relating to PRM in mobile applications.

This proposal falls into the general area of design and analysis of algorithms for discrete optimization problems. Such problems arise in Business Analytics, Management and Computer Sciences and in all Engineering subfields. The variety of models and problems arising in this area is astonishing. Nevertheless the method of choice to solve such problems in practice is some combination of mathematical programming solver (CPLEX, Gurobi, IPOPT) of a relaxed problem where some of the problem constraints (like integrality of decision variables) are relaxed or dropped and some rounding algorithm that converts a relaxed solution into a solution of the original problem. In many cases such practical algorithms work in multiple stages by slowly transforming the relaxed solution into an unrelaxed one while constantly monitoring the quality of the current solution. On the other hand it was long recognized in the Theoretical Computer Science, Mathematical Programming and Operations Research communities that understanding the performance of various methods to transform an optimal or near-optimal solution of an "easy" optimization problem into a high quality solution of a "hard" optimization problem is the key to understanding the performance of practical heuristics and design new algorithms to solve hard optimization problems. Such methods are usually called rounding algorithms since they usually transform a fractional solution into an integral one. In this project we would like to apply the modern methods of Probability Theory, Matroid and Polyhedral Theories to explain why such algorithms perform well in practice. We also would like to design new algorithms for transforming solutions of relaxed practically relevant optimization problems into solutions of original hard optimization problems. Along the way we would like to design new concentration inequalities of random processes associated with our probabilistic rounding algorithms. Such concentration inequalities are useful in explaining the quality of randomized rounding procedures and can lead to design of new rounding algorithms.