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This thesis develops an approach to improving the representation, form and timeliness of data in a complex process control interface. In traditional interfaces, a mapping is made at design time between the process parameters and an appropriate rendering at the interface. This mapping is usually the best all-purpose mapping under a set of general constraints. It is not, however, the only mapping—others may have been discarded which might have represented a better mapping under a different set of constraints. In the general case of the system functioning under normal conditions, the general mapping may be appropriate in most instances. However, if the process moves into a disturbed state, one of the other discarded mappings may be more appropriate for the new conditions. The goal of this thesis is to investigate if these other mappings can be implemented in a flexible mapping system, so that an adaptive system can make a decision on which mapping to use at run-time, based on the current state of process, the environment, the actions of the operator team, and access to a human factors database.

An adaptive pre-clinical x-ray computed tomography system, named "FaCT" was designed, built, and tested at the University of Arizona's Center for Gamma-Ray Imaging (CGRI). The FaCT system possesses the unique ability to change its magnification and dynamically mask the x-ray beam profile. Using these two abilities, the FaCT system can adapt its configuration to the object being imaged, and the task being performed, while achieving a reduction in the radiation dose applied for imaging.Development of the system included the design of all mechanical components, motion systems, and safety systems. It also included system integration of all electronics, motors, and communication channels. Control software was developed for the system and several high-performance reconstruction algorithms were implemented on graphics processing units for reconstructing tomographic data sets acquired by the system. A new geometrical calibration method was developed for calibrating the system that makes use of the full image data gathered by the system and does not rely on markers.An adaptive imaging procedure consisting of a preliminary scout scan, human guidance, and a diagnostic quality scan was developed for imaging small volumes of interest in the interior of an object at substantially reduced dose. The adaptive imaging procedure makes use of FaCT's adjustable magnification, beam-masking capability, and high-performance reconstruction software to achieve high-quality reconstruction of a volume of interest with less dose than would be required by a traditional x-ray computed tomography system without adaptive capabilities.To address ongoing research into mathematical rules for adapting an imaging system, such as FaCT, to better perform a given estimation task, a method of quantifying a system's ability to estimate a parameter of interest in the presence of nuisance parameters based on the Fisher Information was proposed. The method requires a statistical model of object variability. Possible strategies for increasing the performance of an estimation task, given an adaptive system, were suggested.

The adoption of e-learning technologies in campus universities has not realised its potential for meeting the learning needs and expectations of 21st century students. By modelling university learning and teaching as a complex adaptive system, this thesis develops a new way of understanding and managing the adoption of new learning technologies in campus universities. The literature on learning and teaching in higher education indicates that lecturers??? ability to innovate in their teaching is constrained by tacit and discipline-specific educational knowledge. Introducing new methods and technologies into mainstream university teaching requires explicit review of educational knowledge, and requires support from departmental and institutional organizational systems. Research on organizational change in other contexts, such as manufacturing industry, has used complex adaptive systems modelling to understand the systemic interdependence of individual strategies, organizations and technologies. These models suggest that the integration of new e-learning technologies into mainstream campus university teaching will involve corresponding change processes. Part of this change requires the linking up of diverse disciplinary perspectives on learning and teaching. The thesis develops a conceptual framework for researching university learning and teaching as a complex adaptive system that includes learning technologies, people, and their organization within a university. Complex adaptive systems theory suggests that the capacity of a campus university to adapt to new e-learning technologies will be reflected in patterns in the strategies of those lecturers who are early adopters of those technologies. A context-specific study in the University of New South Wales used cognitive mapping to represent and analyse the strategies of a group of 19 early adopters of e-learning technology. These early adopters were participants in a cross-discipline Fellowship programme intended to develop their ability to act as change agents within the university. Analysis of the maps gathered before and after the Fellowship, triangulated with data on the Fellows??? participation in organizational change, leads to a new way of modelling how university learning and teaching systems, including their technologies, adapt within a complex and changing higher education context.

This paper addresses the claim that there is zero privacy for Canadians on the internet. For the interpersonal computing era 1992 to 2007, the relationship between the three major agents (i.e., individual users, federal government, and business) operating on the internet was examined. Three questions guided the research: how has the popular press educated Canadians about internet privacy? what has been the response of the federal government? how have online companies protected the privacy of Canadians? Content analyses of (a) Macleans magazine, (b) the Privacy Commissioner's Annual Reports to Parliament, (c) and the privacy policies of the most visited websites were conducted. Complex Adaptive Systems theory indicated that privacy is an emergent property arising from the interaction of the agents and that the internet is an environment where the agents' interactions lead to limited privacy.

This paper addresses the claim that there is zero privacy for Canadians on the internet. For the interpersonal computing era 1992 to 2007, the relationship between the three major agents (i.e., individual users, federal government, and business) operating on the internet was examined. Three questions guided the research: how has the popular press educated Canadians about internet privacy? what has been the response of the federal government? how have online companies protected the privacy of Canadians? Content analyses of (a) Macleans magazine, (b) the Privacy Commissioner's Annual Reports to Parliament, (c) and the privacy policies of the most visited websites were conducted. Complex Adaptive Systems theory indicated that privacy is an emergent property arising from the interaction of the agents and that the internet is an environment where the agents' interactions lead to limited privacy.

The adoption of e-learning technologies in campus universities has not realised its potential for meeting the learning needs and expectations of 21st century students. By modelling university learning and teaching as a complex adaptive system, this thesis develops a new way of understanding and managing the adoption of new learning technologies in campus universities. The literature on learning and teaching in higher education indicates that lecturers??? ability to innovate in their teaching is constrained by tacit and discipline-specific educational knowledge. Introducing new methods and technologies into mainstream university teaching requires explicit review of educational knowledge, and requires support from departmental and institutional organizational systems. Research on organizational change in other contexts, such as manufacturing industry, has used complex adaptive systems modelling to understand the systemic interdependence of individual strategies, organizations and technologies. These models suggest that the integration of new e-learning technologies into mainstream campus university teaching will involve corresponding change processes. Part of this change requires the linking up of diverse disciplinary perspectives on learning and teaching. The thesis develops a conceptual framework for researching university learning and teaching as a complex adaptive system that includes learning technologies, people, and their organization within a university. Complex adaptive systems theory suggests that the capacity of a campus university to adapt to new e-learning technologies will be reflected in patterns in the strategies of those lecturers who are early adopters of those technologies. A context-specific study in the University of New South Wales used cognitive mapping to represent and analyse the strategies of a group of 19 early adopters of e-learning technology. These early adopters were participants in a cross-discipline Fellowship programme intended to develop their ability to act as change agents within the university. Analysis of the maps gathered before and after the Fellowship, triangulated with data on the Fellows??? participation in organizational change, leads to a new way of modelling how university learning and teaching systems, including their technologies, adapt within a complex and changing higher education context.

Complex System Sciences, as a field of research, has emerged in the past decade. It studies how parts of a system give rise to the collective behaviours of the system and how the system interacts with its environment. It approaches the question of how life on earth could have appeared by searching for inherent structures in living systems and trying to define common patterns within these structures. Complex Systems are also often described as systems where the whole is more complex than the mere sum of its parts, and these systems are also considered to be at the point of maximum computational ability, maximum fitness and maximum evolvability. Several scientific models have simulated Complex Adaptive Systems. These try to model the emergence of complexity within computer-simulated environments inhabited by artificially evolving organisms. My objective in this thesis is to study the application of Complex Systems and Complex Adaptive Systems to Interactive Art and to test how one could construct interactive systems that can create dynamic and open-ended image structures that increase in complexity as users interact with them. Ideally, these interactive artworks should become comparable to Complex Adaptive Systems or even become Complex Systems themselves by satisfying some of the key properties of such systems.

Recent advances in information and communications technology have led to a surge in the popularity of artificial Collective Adaptive Systems (CAS). Such systems, comprised by many spatially distributed autonomous entities with decentralised control, can often achieve discernible characteristics at the global level; a phenomenon sometimes termed emergence. Examples include smart transport systems, smart electricity power grids, robot swarms, etc. The design and operational management of CAS are of vital importance because different configurations of CAS may exhibit very large variability in their performance and the quality of services they offer. However, due to their complexity caused by varying degrees of behaviour, large system scale and highly distributed nature, it is often very difficult to understand and predict the behaviour of CAS under different situations. Novel modelling and quantitative analysis methodologies are therefore required to address the challenges posed by the complexity of such systems. In this thesis, we develop a process algebraic modelling formalism that can be used to express complex dynamic behaviour of CAS and provide fast and scalable analysis techniques to investigate the dynamic behaviour and support the design and operational management of such systems. The major contributions of this thesis are: (i) development of a novel high-level formalism, PALOMA, the Process Algebra for Located Markovian Agents for the modelling of CAS. CAS specified in PALOMA can be automatically translated to their underlying mathematical models called Population Continuous-Time Markov Chains (PCTMCs). (ii) development of an automatic moment-closure approximation method which can provide rapid Ordinary Differential Equation-based analysis of PALOMA models. (iii) development of an automatic model reduction algorithm for the speed up of stochastic simulation of PALOMA/PCTMC models. (iv) presenting a case study, predicting bike availability in stations of Santander Cycles, the public bike-sharing system in London, to show that our techniques are well-suited for analysing real CAS.