Electric powered Unmanned Aerial Vehicles (UAVs) have emerged as a promi- nent aviation concept due to the advantageous such as stealth operation and zero emission. In addition, fuel cell powered electric UAVs are more attrac- tive as a result of the long endurance capability of the propulsion system. This dissertation investigates novel power management architecture for fuel cell and battery powered unmanned aerial vehicle propulsion application. The research work focused on the development of a power management system to control the hybrid electric propulsion system whilst optimizing the fuel cell air supplying system performances. The multiple power sources hybridization is a control challenge associated with the power management decisions and their implementation in the power electronic interface. In most applications, the propulsion power distribu- tion is controlled by using the regulated power converting devices such as unidirectional and bidirectional converters. The amount of power shared with the each power source is depended on the power and energy capacities of the device. In this research, a power management system is developed for polymer exchange membrane fuel cell and Lithium-Ion battery based hybrid electric propulsion system for an UAV propulsion application. Ini- tially, the UAV propulsion power requirements during the take-off, climb, endurance, cruising and maximum velocity are determined. A power man- agement algorithm is developed based on the UAV propulsion power re- quirement and the battery power capacity. Three power states are intro- duced in the power management system called Start-up power state, High power state and Charging power state. The each power state consists of the power management sequences to distribute the load power between the battery and the fuel cell system. A power electronic interface is developed Electric powered Unmanned Aerial Vehicles (UAVs) have emerged as a promi- nent aviation concept due to the advantageous such as stealth operation and zero emission. In addition, fuel cell powered electric UAVs are more attrac- tive as a result of the long endurance capability of the propulsion system. This dissertation investigates novel power management architecture for fuel cell and battery powered unmanned aerial vehicle propulsion application. The research work focused on the development of a power management system to control the hybrid electric propulsion system whilst optimizing the fuel cell air supplying system performances. The multiple power sources hybridization is a control challenge associated with the power management decisions and their implementation in the power electronic interface. In most applications, the propulsion power distribu- tion is controlled by using the regulated power converting devices such as unidirectional and bidirectional converters. The amount of power shared with the each power source is depended on the power and energy capacities of the device. In this research, a power management system is developed for polymer exchange membrane fuel cell and Lithium-Ion battery based hybrid electric propulsion system for an UAV propulsion application. Ini- tially, the UAV propulsion power requirements during the take-off, climb, endurance, cruising and maximum velocity are determined. A power man- agement algorithm is developed based on the UAV propulsion power re- quirement and the battery power capacity. Three power states are intro- duced in the power management system called Start-up power state, High power state and Charging power state. The each power state consists of the power management sequences to distribute the load power between the battery and the fuel cell system. A power electronic interface is developed with a unidirectional converter and a bidirectional converter to integrate the fuel cell system and the battery into the propulsion motor drive. The main objective of the power management system is to obtain the controlled fuel cell current profile as a performance variable. The relationship between the fuel cell current and the fuel cell air supplying system compressor power is investigated and a referenced model is developed to obtain the optimum compressor power as a function of the fuel cell current. An adaptive controller is introduced to optimize the fuel cell air supplying system performances based on the referenced model. The adaptive neuro-fuzzy inference system based controller dynamically adapts the actual compressor operating power into the optimum value defined in the reference model. The online learning and training capabilities of the adaptive controller identify the nonlinear variations of the fuel cell current and generate a control signal for the compressor motor voltage to optimize the fuel cell air supplying system performances. The hybrid electric power system and the power management system were developed in real time environment and practical tests were conducted to validate the simulation results.

A Spoken Dialogue System's (SDS's) dialogue strategy specifies which action it will take depending on its representation of the current dialogue context. Designing it by hand involves anticipating how users will interact with the system, and/or repeated testing and refining, and so can be a difficult, time-consuming task. Since SDSs inevitably make understanding errors, a particularly important issue is how to design ``repair strategies'', the parts of the dialogue strategy which attempt to get the dialogue ``back-on-track'' following these errors. To try to produce better dialogue strategies with less time and effort, previous researchers have modelled a dialogue strategy as a sequential decision problem called a Markov Decision Process (MDP), and then applied Reinforcement Learning (RL) algorithms to example training dialogues to generate dialogue strategies automatically. More recent research has used training dialogues conducted with simulated rather than real users and learned which action to take in all dialogue contexts, (a ``full'' as opposed to a ``partial'' dialogue strategy) - simulated users allow more training dialogues to be generated, and the exploration of new dialogue contexts not present in an original dataset. As yet however, limited insight has been provided as to which dialogue contextual features are important to include in the MDP and why. Indeed, a full dialogue strategy has not been learned from training dialogues with a realistic probabilistic user simulation derived from real user data, and then shown to work well with real users. This thesis investigates the value of adding new linguistically-motivated contextual features to the MDP when using RL to learn full dialogue strategies for SDSs. These new features are recent Dialogue Acts (DAs). DAs indicate the role or intention of an utterance in a dialogue e.g. ``provide-information'', an utterance being a complete unit of a speaker's speech, often bounded by silence. An accurate probabilistic user simulation learned from real user data is used for generating training dialogues, and the recent DAs are shown to improve performance in testing in simulation and with real users. With real users, performance is also better than other competing learned and hand-crafted strategies. Analysis of the strategies, and further simulation experiments show how the DAs improve performance through better repair strategies. The main findings are expected to apply to SDSs in general - indeed our strategies are learned and tested on real users in different domains, (flight-booking versus tourist information). Comparisons are also made to recent research which focuses on handling understanding errors in SDSs, but which does not use RL or user simulations.

Thesis (M.S.)--University of Florida, 2001. / Title from first page of PDF file. Document formatted into pages; contains x, 65 p.; also contains graphics. Vita. Includes bibliographical references (p. 63-64).

Thesis (Ph. D.)--University of North Texas, Aug., 2008. / Title from title page display. Includes bibliographical references.

Thesis (Ph. D.)--University of Hong Kong, 1983. / Also availalbe in microfilm.

In an infectious animal disease outbreak, effective management of the event requires timely and accurate information collection, processing, storage and distribution. This thesis focuses on the tools to assist information collection and management. The first study describes the comparison of questionnaire methodology for the information collection in the initial epidemiologic investigation of a Canadian federally reportable disease. The second study defines attributes of an animal disease outbreak information management system (IMS). The studies were performed within a one-year period (July 2013-July 2014). The first study performed two comparisons to determine differences in the information quality (completeness and accuracy) between differing questionnaire methodology and modes of completion (hard copy and electronic). The study was conducted with 24 Canadian Food Inspection Agency (CFIA) inspectors and veterinarians using a fictitious Canadian reportable disease scenario. The first comparison used a hard copy of a Canadian Food Inspection Agency (CFIA) questionnaire designed to be applicable (or generic) for all highly infectious reportable disease investigations with a supplementary disease specific section compared to an electronic disease specific reportable disease questionnaire. There was no significant difference in the information quality (N = 22; P = 0.09). The mean difference in completeness and accuracy scores was 3.5% (95% CI -0.6, 7.6). The second comparison focused on the hard copy disease questionnaire and assessed differences in information quality between using only the generic sections of the questionnaire compared to the supplementation of a disease specific section. A difference in information quality was determined (N = 24; P < 0.0001). The mean completeness and accuracy score for the generic only sections was 50.2% (95% CI 43.6, 57.2) compared to 80.2% (95% CI 76.2, 84.5) with the inclusion of the disease-specific section. The greatest difference in information quality occurred in the tracing specific information categories (P < 0.0001) with a mean difference of completeness and accuracy scores of 67.7% (95% CI 52.0, 83.4) for the trace-in (exposure history) category and 38.3% (95% CI 28.3, 48.3) for the trace-out (potential spread of disease) category. The absence of disease-specific questions were determined to be the primary factor in the difference in information quality. The second study determined a comprehensive list of user-defined attributes of an animal disease outbreak IMS and further identified the most important (key) attributes. A list of 34 attributes and associated definitions were determined through a series of focus group sessions and two surveys of Canadian animal health stakeholders. The animal health stakeholders included federal and provincial governments, veterinary academia and animal production industry representatives. The key attributes of an animal disease outbreak IMS identified were: ‘user friendly’, ‘effectiveness’, ‘accessibility’, ‘data accuracy’, ‘reliability’ and ‘timeliness’. ‘User friendly’ received the highest frequency of ranking as the most important attribute, followed by ‘effectiveness’. Information management was identified as the main purpose of an animal disease outbreak IMS with a median rating of 10 (rating scale of 0-10 with 10 = strongly agree). The occurrence of a federally reportable disease or a large-scale animal disease outbreak can have a great impact on the animal agriculture sector, regulatory government agencies and the economy. Information collection and management are essential to assist with the epidemiologic investigation and disease control measures. The study provided a novel opportunity to study information management for an animal disease outbreak from a Canadian perspective. The knowledge obtained will add value to the future development of tools and systems designed for information collection and management involving an animal disease outbreak.

Mergers and Acquisitions (M&A) are major strategic initiatives undertaken by many organisations. Within the construction context, these have been used, amongst others, to accelerate growth, reduce the effects of the construction cycle, enter into new markets, and spread risk. During the last decade, M&A were recognised as the preferred vehicle for expansion into the global construction market. Major European and international construction organisations use mergers or acquisitions to increase their geographical coverage and business portfolio. Mergers and Acquisitions impact on a number of organisational dimensions ranging from `soft' issues such as organisational culture to `hard' issues such as IT integration. Four specific aspects of mergers and acquisitions are investigated within this thesis. These are as follows: Strategy, Business Portfolio and Performance Measurement of construction organisations and the impact of M&A on subsequent performance; the Acquisition Strategy adopted for entering emerging markets such as Central and Eastern Europe; the Impact of Mergers and Acquisitions on construction companies' Information Systems and Information Technology (IS/IT); and an Investigation of Knowledge Management Strategies for organisations that have undergone mergers and acquisitions. The thesis adopts a qualitative research methodology. An extensive literature review was conducted on mergers and acquisitions with particular emphasis on its use within the construction sector. The literature review provided a sound basis for theory development and identified areas in which further understanding was requiired. A multiple case study approach was selected for each of the four aspects studied and the data was obtained using semi-structured interviews. Based on the case study data, analysis and discussion were conducted resulting in conclusions for each of the four aspects investigated. The research concluded that Mergers and Acquisitions were an important vehicle for construction organisations to achieve growth, and expand geographically into new markets and new sectors. However,. the implications of mergers and acquisitions need to be understood and the processes . before, during and after the merger or acquisition is finalised need to be carefully planned and communicated to the relevant parties. Mergers and Acquisitions'- can offer' tremendous advantage to an organisation and several recommendations are made regarditig how the process may be improved within the construction context.

Thesis (M.S.)--Ohio University, November, 2001. / Title from PDF t.p.

Thesis (M.C.S.)--Carleton University, 2005. / Includes bibliographical references (p. 83-86). Also available in electronic format on the Internet.

Thesis (M.H.S.H.)--University of Michigan, 1976.