In recent years there has been increased interest in the development of sensorless switched reluctance machine drives. The proper operation of a switched reluctance machine (SRM) requires knowledge of the position of the rotor of the machine. The inclusion of a physical position sensor compromises the inherent robustness of this type of machine. Thus, there has been a need to develop techniques to estimate the position of the rotor in SRM drives. Switched reluctance machines are able to operate over a large range in speed. A fully loaded SRM is typically designed to saturate the ferromagnetic material that comprises the stator and rotor of the machine whereas a lightly loaded machine does not. Therefore, the model of the machine should be able to handle both a large range in frequency and input excitation levels of the magnetic material in the machine. The development of a new dynamic circuit-based ferromagnetic model is described in this thesis. The investigation of the behaviour of 24 gauge M19 silicon steel led to the conclusion that, for this material, a circuit model that has static parameters is unable to accurately reproduce the behaviour of the actual material over a large range of input frequencies and excitation levels without resorting to retuning the parameters of the model. This thesis provides two new mechanisms that dynamically adjust the resistance values of the flux tubes of the model. Comparisons using a normalized vertical least-squares metric between the newly proposed dynamic model and a model that has static resistance values clearly show the improvement that is gained by using these mechanisms. A practical implementation of the new model is also given. Timing using a general purpose CPU shows that this implementation of the model will most likely be able to be used as part of a multi-phase lumped parameter model for a SRM in realtime.

Thesis (PhDSoSc(Communic,InformatStud))--University of South Australia, 2002.

PBNM systems have been proposed as a feasible techology for managing massive scale applications including telecommunication service management. What is not known is how this class of system performs under carrier-scale traffic loads. This research investigates this open question and concludes, subject to the considerations herein, this technology can provide services to large scale applications. An in depth examination of several inferencing algorithms is made using experimental methods. The inferencing operation has been implicated as the major source of performance problems in rule based systems and we examine this. Moreover, these algorithms are of central importance to current and future context-aware, pervasive, mobile services. A novel algorithm, JukeBox, is proposed that is a correct, general and pure bindspace conjunctive match algorithm. It is compared to the current state of the art algorithm - Rete. We find that Rete is the superior algorithm when implemented using the hashed-equality variant. We also conclude that IO is an important cause of PBNM system performace limitations and is perhaps of more significance than the implicated inferencing operations. However, inferencing can be a bottleneck to performance and we document the factors associated with this. We describe a generally useful policy system benchmarking procedure that provides a visible, repeatable and measurable process for establishing a policy server's service rate characteristics. The service rate statistics, namely (mu) and (sigma), establish the limitations to policy system throughput. Combined with the offered traffic load to the server, using the statistic (lambda), we can provide a complete characterisation of system performance using the Pollaczek-Khinchine function. This characterisation allows us to make simple design and dimensioning heuristics that can be used to rate the policy system as a whole.

This thesis investigates the early stages of the software development process for agent-based models of pedestrian behaviour. Planning for pedestrians is becoming more important as planners and engineers become more aware of the sustainability and environmental aspects of transport and infrastructure. It is also necessary for the planning and management of pedestrian areas and events. Pedestrian behaviour is more difficult to model than other transport modes as it is not as constrained and operates at a finer scale. Many approaches have been developed for modelling pedestrian behaviour. The simplest involve a single mathematical equation taking into account area and attractiveness of an area to calculate the maximum capacity. More complicated mathematical models involving differential equations have also been used. Agent-based modelling is a recent development in modelling and simulation. These simulations contain agents who interact with each other and the environment in which they are situated. Their similarity to human societies has led to their use for many social applications. Many modellers are unsure of what agents are and how to develop models using them. In some cases, agents may be useful. In other cases, the model outputs and realism may not offset the learning curve, development time, and increased complexity of an agent-based model. (For complete abstract open document)

As populations increase and air quality continues to decline in many cities around the world, there is growing recognition that human dependency on car based transport is a serious pollution issue. The potential exists to change this aspect of human behaviour using environmental education to develop more sustainable transport practices. The application of education strategies to achieve behaviour change in transport mode choice may benefit from an interdisciplinary approach. This research examined the effectiveness of three different educational strategies in a workplace situation in achieving a shift in transport mode away from the single occupant vehicle. This research aimed to determine if workplace based education interventions that stimulate a deeper level of learning, and encourage self-regulated learning and reflective practice, are more likely to achieve positive behaviour change than interventions based on more superficial learning. A secondary aim was to determine if the characteristics or type of workplace influence the effectiveness of particular education strategies. The research focuses specifically on people’s perceptions of transport behaviour and air pollution. The research examined the effectiveness of three workplace based interventions which aimed at reducing the use of single occupant vehicles (SOV) for commuting to work resulting in an increase in the use of green transport (alternatives to the SOV). The primary goal of the three educational interventions was to achieve an increased awareness, development of positive attitudes and increased empowerment regarding sustainable transport choices. Based on a combination of environmental education and self-regulation of learning theory it was theorized that achieving the three afore mentioned educational outcomes would be highly likely to result in a change in behaviour. The three interventions differ in level of participant involvement, while the information and structure of each intervention was controlled as much as is possible in a naturalistic study. The intervention designs were based on educational theories including cognitivist information processing, Vygotskian/social constructivism, and self-regulation of learning. The first intervention provided information to participants impersonally with no additional support. The second intervention incorporated a volunteer to model pro-environmental behaviour, facilitate discussion of issues, and aid in planning commute trips using alternatives to the single occupant vehicle. The third intervention included the formation of a green transport planning group within the workplace which aimed to identify and address barriers to using alternative transport in the workplace through the development of a green transport plan. In the naturalistic workplace setting, mixed methodologies(qualitative and quantitative) were employed to examine the relative effectiveness of the three interventions in terms of participants knowledge about, attitudes towards and behaviour (action) in regard to transport, as well as changes at an organizational level. Multiple case studies and surveys were used to collect data about employee transport behaviour, attitudes, and knowledge in 13 workplaces situated in the central area of Perth, the capital city of Western Australia, before and after a period of intervention. To allow comparability between workplaces in terms of organisational structure and function six of the 13 workplaces were selected to examine in detail,one government and one engineering organization in each of the three intervention groups. It was found that the level of knowledge about car use and air quality was increased in all three intervention groups, suggesting increased involvement does not improve the chance of increasing knowledge. In contrast, significantly more positive attitudes to car use and air quality issues were developed in only the two most involving interventions, suggesting information distribution alone is unlikely to influence attitude. There were no changes in the general environmental attitudes across the intervention groups. Single occupant vehicle trips were significantly reduced in the second intervention group only. An overall significant increase was reported for self efficacy (as a measure of empowerment) but no significant change was reported for any particular intervention group. At an organizational level the third intervention resulted in the greatest organizational change, and it is likely that the measures implemented as a result of the green transport planning process will have an ongoing impact on employee transport behaviour in the participant workplaces. The effectiveness of each intervention type also varied between workplaces. Structural factors such as design of the work environment, internal mail and email systems, and work hours influenced the delivery of the interventions in some workplaces and qualitative data indicates this may have influenced success. There was also an indication that management involvement and workplace culture were major factors influencing participant perceptions of effectiveness of particular education strategies. Overall it is concluded that while the second intervention involving leadership (but without participant ownership) achieved the greatest reduction in use of the single occupant vehicle, the third intervention achieved the greatest long-term impact on participants and organizations. As a result the definition of effectiveness is complicated and is dependant on whether preferred outcomes have a short-term or a long-term focus. These findings have implications for the way in which achieving sustainable transport in metropolitan areas is approached, as well as other environmentally sustainable behaviours.

Thesis (Ed. D.)--Illinois State University, 2006. / Title from title page screen, viewed on February 4, 2008. Dissertation Committee: Dent M. Rhodes (chair), Barbara Nourie, Kenneth F. Jerich. Includes bibliographical references and abstract. Also available in print.

Thesis (Ph. D.)--University of Texas at Dallas, 2007. / Includes vita. Includes bibliographical references (leaves 101-105).

Proefschrift Universiteit van Amsterdam. / Met samenvatting in het Nederlands.

Thesis (Ph.D.)--George Mason University, 2008. / Vita: p. 127. Thesis director: Priscilla Norton. Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Education. Title from PDF t.p. (viewed Jan. 8, 2009). Includes bibliographical references (p. 109-123). Also issued in print.

Thesis (Ph.D.)--University of Delaware, 2008. / Principal faculty advisor: Susan L. Miller, Dept. of Sociology & Criminal Justice. Includes bibliographical references.