The management of long term chronic conditions is a complex and challenging task. The process relies on individuals engaging in regular recording of factors that affect their health. Yet currently, the mobile tools that people carry with them are not being fully utilised to assist in this process. This Thesis reports on research that has been completed to understand the role that mobile technologies can have in supporting people with chronic conditions. An individual engaging in personal monitoring is concerned with the data they collect, not the process used to capture the data. The results of the research conducted contribute to an advancement of knowledge around how mobile technologies can assist in personal reflection on health information to provide greater understanding of chronic disease management This understanding of the role of reflection in chronic condition management can then be used as a platform to improve the mobile interventions in future implementations. These findings are arrived at by conducting an initial investigation into the usage of existing health monitoring devices and an evaluation of these devices is detailed. The results of this early work suggests there exists a gap between real practice and the role that mobile technologies can play in assisting with the process. A deeper understanding of the management practices of people with diabetes is then achieved through a set of interviews with individuals with diabetes. The findings then define a model of chronic disease management, named the 'Diabetes Management Cycle.' Following the definition of the cycle, a mobile application was implemented and deployed during a four week evaluation with individuals with type 1 diabetes. This system was designed to support existing management practices and implemented simple methods of information capture. A second application was then developed to enable increased monitoring and subsequent reflection amongst individuals with cardiovascular conditions. The application was deployed in a six week in-situ evaluation and it was discovered a personalised 'tagging' mechanism allowed for the discovery of patterns affecting health. Based on the findings of the studies, the Thesis concludes by presenting definitions of ready- to-hand in the short- and long-term contexts of mobile health management. These ready-to-hand guidelines provide a platform for future research projects to build upon.

No / P systems are the computational models introduced in the context of membrane computing, a computational paradigm within the more general area of unconventional computing. Kernel P (kP) systems are defined to unify the specification of different variants of P systems, motivated by challenging theoretical aspects and the need to model different problems. In this paper, we present kPWorkbench, a software framework developed to support kP systems. kPWorkbench integrates several simulation and verification tools and methods, and provides a software suit for the modelling and analysis of membrane systems.

Pervasive (ubiquitous) computing is a new paradigm where the computers are submerged into the background of the everyday life. One important aspect of pervasive systems is context-awareness. Context-aware systems are those that can adapt their behaviours according to the current context. Context-aware applications are being integrated into our everyday activity aspects such as: health care, smart homes and transportations. There exist a wide range of context-aware applications such as: mobile phones, learning systems, smart vehicles. Some context-aware systems are critical since the consequence of failing to identify a given context may be catastrophic. For example, an auto-pilot system is a critical context-aware system; it senses the humidity, clouds, wind speed and accordingly adjusts the altitude, throttle and other parameters. Being a critical context-aware system has to be provably correct. Policy-based approaches has been used in many applications but not in context-aware systems. In this research, we want to discover the anatomy (i.e. architecture, structure and operational behaviour) of policy-based management as applied to context-aware systems, and how policies are managed within such a dynamic system. We propose a novel computational model and its formalisation is presented using the Calculus of Context-aware Ambients (CCA). CCA has been proposed as a suitable mathematical notation to model mobile and context-aware systems. We decided to use CCA due to three reasons: (i) in CCA, mobility and context-awareness are primitive constructs and are treated as first-class citizens; (ii) properties of a system can be formally analysed; (iii) CCA specifications are executable, and thus, leading to rapid prototyping and early validation of the system properties. We, then show how policies can be expressed in CCA. For illustration, the specification of the event-condition-action (ECA) conceptual policy model is modelled in CCA in a natural fashion. We also propose a policy-based architecture for context-aware systems, showing its different components, and how they interact. Furthermore, we give the specification of the policy enforcement mechanism used in our proposed architecture in CCA. To evaluate our approach, a real-world case study of an infostation-based mobile learning (mLearning) system is chosen. This mLearning system is deployed across a university campus to enable mobile users to access mobile services (mServices) represented by course materials (lectures, tests and tutorials) and communication services (intelligent message notification and VoIP). Users can access the mServices through their mobile devices (Hand-set phones, PDAs and laptops) regardless of their device type or location within a university campus. We have specified the mLearning system in CCA (i.e. specification based on policies of the mServices), afterwards, the specification is simulated using the CCA interpreter tool. We have developed an animation tool specially designed for the mLearning system. The animation tool provides graphical representation of the CCA processes. In terms of safety and liveness, some important properties of the mLearning system have been validated as a proof of concept.

The purpose of this thesis is the theoretical study of interference and correlation effects in multimode and continuum mode quantum systems. We are concerned with interference effects in multiport devices which in a sense are generalised Mach-Zehnder interferometers. It is shown how these multimode devices can be employed for the study of negative result and interaction free measurements. Interference and coherence effects are also studied in relation to the radiation fields generated by atoms through the process of spontaneous emission. Besides first order interference, higher order coherence effects are investigated with the aid of Glauber's photodetection theory and it is found that detectors that lie in spacelike regions may display nonclassical correlations under certain conditions. It is well known that the vanishing of field commutators between regions that cannot be connected by subluminal signals reflects the locality of quantum field theory. But is it possible that these spacelike regions exhibit correlations that violate Bell type inequalities? This is the main question and principal concern of the thesis and the answer is affirmative, nonclassical correlations between spacelike regions are indeed possible. A scheme of four detectors that lie in spacelike points was also studied. In this case we do not consider the radiation field but a free scalar field in vacuum state. Nevertheless the virtual quanta of this field may induce nonclassical correlations if the intervals between the detectors are spacelike but small enough. The fundamental reason for this fact is the nonvanishing of the Feynman propagator outside the light cone. Since this propagator is decaying expotentially with the distance it is demonstrated that for large spacelike intervals field correlations obey classical inequalities. We should also note that different inertial observers will agree on the violation or not of these inequalities since the results are manifestly Lorentz invariant.

Today, except for mathematical operations, our brain functions much faster and more efficient than any supercomputer. It is precisely this form of information processing in neural networks that inspires researchers to create systems that mimic the brain’s information processing capabilities. In this thesis we propose a novel approach to implement these alternative computer architectures, based on delayed feedback. We show that one single nonlinear node with delayed feedback can replace a large network of nonlinear nodes. First we numerically investigate the architecture and performance of delayed feedback systems as information processing units. Then we elaborate on electronic and opto-electronic implementations of the concept. Next to evaluating their performance for standard benchmarks, we also study task independent properties of the system, extracting information on how to further improve the initial scheme. Finally, some simple modifications are suggested, yielding improvements in terms of speed or performance.

Various established and emerging applications of RFID technology have been and are being implemented by companies in different parts of the world. However, RFID technology is susceptible to a variety of security and privacy concerns, as it is prone to attacks such as eavesdropping, denial of service, tag cloning and user tracking. This is mainly because RFID tags, specifically low-cost tags, have low computational capability to support complex cryptographic algorithms. Tag cloning is a key problem to be considered since it leads to severe economic losses. One of the possible approaches to address tag cloning is using an intrusion detection system. Intrusion detection systems in RFID networks, on top of the existing lightweight cryptographic algorithms, provide an additional layer of protection where other security mechanisms may fail. This thesis presents an intrusion detection mechanism that detects anomalies caused by one or more cloned RFID tags in the system. We make use of a Hybrid Fuzzy Genetics-Based Machine Learning algorithm to design an intrusion detection model from RFID system-generated event logs. For the purpose of training and evaluation of our proposed approach, part of the RFID system-generated dataset provided by the University of Tasmania’s School of Computing and Information Systems was used, in addition to simulated datasets. The results of our experiments show that the model can achieve high detection rates and low false positive rates when identifying anomalies caused by one or more cloned tags. In addition, the model yields linguistically interpretable rules that can be used to support decision making during the detection of anomaly caused by the cloned tags.

Current grid computing architectures have been based on cluster management and batch queuing systems, extended to a distributed, federated domain. These have shown shortcomings in terms of scalability, stability, and modularity. To address these problems, this dissertation applies architectural styles from the Internet and Web to the domain of generic computational grids. Using the REST style, a flexible model for grid resource interaction is developed which removes the need for any centralised services or specific protocols, thereby allowing a range of implementations and layering of further functionality. The context for resource interaction is a generalisation and formalisation of the Condor ClassAd match-making mechanism. This set theoretic model is described in depth, including the advantages and features which it realises. This RESTful style is also motivated by operational experience with existing grid infrastructures, and the design, operation, and performance of a proto-RESTful grid middleware package named DIRAC. This package was designed to provide for the LHCb particle physics experiment’s “off-line” computational infrastructure, and was first exercised during a 6 month data challenge which utilised over 670 years of CPU time and produced 98 TB of data through 300,000 tasks executed at computing centres around the world. The design of DIRAC and performance measures from the data challenge are reported. The main contribution of this work is the development of a REST model for grid resource interaction. In particular, it allows resource templating for scheduling queues which provide a novel distributed and scalable approach to resource scheduling on the grid.

Thesis (M.S.)--Brigham Young University. Dept. of Computer Science, 2006. / Includes bibliographical references (p. 199-200).

Thesis (Ph. D.)--State University of New York at Binghamton, Thomas J. Watson School of Engineering and Applied Science, Department of Mechanical Engineering, 2008. / Includes bibliographical references.

Thesis (MSc)--University of Stellenbosch, 2005. / Bibliography. Also available via the Internet.