To improve the accuracy in capturing the motion of deformable objects, a reconfigurable multi-camera active-vision system which can dynamically reposition its cameras online is proposed, and a design for such a system, along with a methodology to select the near-optimal positions and orientations of the set of cameras, is presented. The active-vision system accounts for the deformation of the object-of-interest by tracking triangulated vertices in order to predict the shape of the object at subsequent demand instants. It then selects a system configuration that minimizes the expected error in the recovered position of each of these vertices. Extensive simulations and experiments have verified that using the proposed reconfigurable system to both translate and rotate cameras to near-optimal poses is tangibly superior to using cameras which are either static, or can only rotate, in minimizing the error in recovered vertex positions.

In this thesis we develop and test a software algorithm for an electronic smart badge system. The smart badge system we have developed has the ability to figure out the interests of people who wear the badge by using time and position information collected by the badge. The badge can also present feedback to the wearer, so that users may be guided to people will similar interests and so may have more effective conversations. The smart badge system is based on an inference system which uses a Bayesian network. Evaluation of the system was challenging because there were no completed badges that could be used. To overcome this, we developed a simulation of crowd behaviour in a conference setting. We tuned the parameters of the model using several test situations and the final simulated behavior appeared realistic. Compared to other smart badge systems, our work is unique because it is able to enhance conversation by the real time inference of common ideas or interests of the conversion participants.

This thesis presents two novel algorithms for converting a normalised binary floating point number into a binary logarithmic number with the single-precision of a floating point number. The thesis highlights the importance of logarithmic number systems in real-time DSP applications. A real-time cross-correlation application where logarithmic signal processing is used to simplify the complex computation is presented. The first algorithm presented in this thesis comprises two stages. A piecewise linear approximation to the original logarithmic curve is performed in the first stage and a scaled-down normalised error curve is stored in the second stage. The algorithm requires less than 20 kbits of ROM and a maximum of three small multipliers. The architecture is implemented on Xilinx's Spartan3 and Spartan6 FPGA family. Synthesis results confirm that the algorithm operates at a frequency of 42.3 MHz on a Spartan3 device and 127.8 MHz on a Spartan6. Both solutions have a pipeline latency of two clocks. The operating speed increases to 71.4 MHz and 160 MHz respectively when the pipeline latencies increase to eight clocks. The proposed algorithm is further improved by using a PWL (Piece-Wise Linear) approximation of the transform curve combined with a PWL approximation of a scaled version of the normalized segment error. A hardware approach for reducing the memory with additional XOR gates in the second stage is also presented. The architecture presented uses just one 18k bit Block RAM (BRAM) and synthesis results indicate operating frequencies of 93 and 110 MHz when implemented on the Xilinx Spartan3 and Spartan6 devices respectively. Finally a novel prototype of an FPGA-based four channel correlation velocimetry system is presented. The system operates at a higher sampling frquency than previous published work and outputs the new result after every new sample it receives. The system works at a sampling frequency of 195.31 kHz and a sample resolution of 12 bits. The prototype system calculates a delay in a range of 0 to 2.6 ms with a resolution of 5.12 us.

No description available.

The task of developing a framework for which agents can communicate reliably and flexibly in open systems is not trivial. This thesis addresses the dichotomy between reliable communication and facilitation of the autonomy of agents to create more flexible and emergent interactions. By the introduction of adaptations to a distributed protocol language, agents benefit from the ability to communicate interaction protocols to elucidate the social norms (thus creating more reliable communication). Yet, this approach also provides the functionality for the agent to unilaterally introduce new paths for the conversation to explore unforeseen opportunities and options (thus restoring more autonomy than possible with static protocols). The foundation of this work is Lightweight Coordination Calculus (LCC). LCC is a distributed protocol language and framework in which agents coordinate their own interactions by their message passing activities. In order to ensure that adaptations to the protocols are done in a reasonable way, we examine the use of two models of communication to guide any transformations to the protocols. We describe the use of FIPA's ACL and ultimately its unsuitability for this approach as well as the more fecund task of implementing dialogue games, an model of argumentation, as dynamic protocols. The existing attempts to develop a model that can encompass the gulf between reliability and autonomy in communication have had varying degrees of success. It is the purpose and the result of the research described in this thesis to develop an alloy of the various models, by the introduction of dynamic and distributed protocols, to develop a framework stronger than its constituents. Though this is successful, the derivations of the protocols can be dificult to reconstruct. To this end, this thesis also describes a method of protocol synthesis inspired by models of human communication that can express the dialogues created by the previous approaches but also have a fully accountable path of construction. Not only does this thesis explore a unique and novel approach to agent communication, it is tested through a practical implementation.

The Helicopter Emergency Medical Service (HEMS) accident rate has driven operators from around the world to address the management of risks inherent to their operations. In-flight decision-making, pre-flight planning, failure to follow standard operating procedures, delayed remedial actions, and misinterpretation of environmental cues are all areas that need to be addressed for safe HEMS operations. HEMS operations are complex, being a joint exercise between the flight crew, paramedics and supporting agencies. Operations occur around-the-clock, in all-weather conditions, and often with no fore-warning. In a time critical operation, where precious minutes may cost lives, operators must decide which cases warrant a HEMS response and if so, whether the conditions are safe to conduct the mission. Intelligent systems are an emerging field offering benefits to a multitude of applications. This research forms a comprehensive investigation of the application of 'intelligent systems' to the pre-mission analysis of HEMS operations. The research has resulted in the development of a prototype decision support system capable of assisting in the pre-mission analysis of HEMS operations. The prototype system is capable of supporting flight coordinators and crew in the decision-making processes prior to HEMS operations and can potentially improve emergency medical services to the community.

With the advent of life critical and real-time services such as remote operations over satellite, e-health etc, providing the guaranteed minimum level of services at every ground terminal of the satellite communication system has gained utmost priority. Ground terminals and the hub are not equipped with the required intelligence to predict and react to inclement and dynamic weather conditions on its own. The focus of this thesis is to develop intelligent algorithms that would aid in adaptive management of the quality of service at the ground terminal and the gateway level. This is done to adapt both the ground terminal and gateway to changing weather conditions and to attempt to maintain a steady throughput level and Quality of Service (QoS) requirements on queue delay, jitter, and probability of loss of packets. The existing satellite system employs the First-In-First-Out routing algorithm to control congestion in their networks. This mechanism is not equipped with adequate ability to contend with changing link capacities, a common result due to bad weather and faults and to provide different levels of prioritized service to the customers that satisfies QoS requirements. This research proposes to use the reported strength of fuzzy logic in controlling highly non-linear and complex system such as the satellite communication network. The proposed fuzzy based model when integrated into the satellite gateway provides the needed robustness to the ground terminals to comprehend with varying levels of traffic and dynamic impacts of weather.

With the advent of life critical and real-time services such as remote operations over satellite, e-health etc, providing the guaranteed minimum level of services at every ground terminal of the satellite communication system has gained utmost priority. Ground terminals and the hub are not equipped with the required intelligence to predict and react to inclement and dynamic weather conditions on its own. The focus of this thesis is to develop intelligent algorithms that would aid in adaptive management of the quality of service at the ground terminal and the gateway level. This is done to adapt both the ground terminal and gateway to changing weather conditions and to attempt to maintain a steady throughput level and Quality of Service (QoS) requirements on queue delay, jitter, and probability of loss of packets. The existing satellite system employs the First-In-First-Out routing algorithm to control congestion in their networks. This mechanism is not equipped with adequate ability to contend with changing link capacities, a common result due to bad weather and faults and to provide different levels of prioritized service to the customers that satisfies QoS requirements. This research proposes to use the reported strength of fuzzy logic in controlling highly non-linear and complex system such as the satellite communication network. The proposed fuzzy based model when integrated into the satellite gateway provides the needed robustness to the ground terminals to comprehend with varying levels of traffic and dynamic impacts of weather.

Dr Alex Mihailidis - Presentation at UBC Thursday, March 26, 2009

This paper's main objective is to consolidate the knowledge on context in the realm of intelligent systems, systems that are aware of their context and can adapt their behavior accordingly. We provide an overview and analysis of 36 context models that are heterogeneous and scattered throughout multiple fields of research. In our analysis, we identify five shared context categories: social context, location, time, physical context, and user context. In addition, we compare the context models with the context elements considered in the discourse on intelligent systems and find that the models do not properly represent the identified set of 3,741 unique context elements. As a result, we propose a consolidation of the findings from the 36 context models and the 3,741 unique context elements. The analysis reveals that there is a long tail of context categories that are considered only sporadically in context models. However, particularly these context elements in the long tail may be necessary for improving intelligent systems' context awareness.