Interruptions have negative effects on the task performance in modern work environments. These negative effects are not affordable in tasks in which decisions are time-critical and have a life-critical nature. Human-supervisory control (HSC) tasks in time-critical settings such as mission command and control and emergency response are especially vulnerable to the negative effects of interruptions since supervisors in these settings are prone to frequent interruptions which are valuable source of information and hence cannot be ignored and consequences of a wrong decision in these settings is very costly because of their life-critical nature. To address this issue, this thesis investigates an activity-centric design approach that aims to help team supervisors in a complex mission control operation to remain aware of the activities that most likely would affect their decisions, while minimizing disruption. An interruption recovery assistant (IRA) tool was designed to promote activity and situation awareness of a team of UAV operators in a representative task. Initial pilot studies showed a positive trend in effectiveness of the IRA tool on recovery time and decision accuracy. This thesis explores alternative design approaches to validate the effectiveness of an interruption recovery tool that enable mission commanders rapidly and effectively regain the situational awareness after an interruption occurs in the mission environment. This thesis overview these design approaches and present results from a series of formative evaluations of our prototype designs. These evaluations were conducted in an experimental platform designed to emulate futuristic semi-autonomous UAV team mission operations.

Symmetry has been a very useful tool to researchers in various scientific fields. At its most basic, symmetry refers to the invariance of an object to some transformation, or set of transformations. Usually one searches for, and uses information concerning an existing symmetry within given data, structure or concept to somehow improve algorithm performance or compress the search space. This thesis examines the effects of imposing or inducing symmetry on a search space. That is, the question being asked is whether only existing symmetries can be useful, or whether changing reference to an intuition-based definition of symmetry over the evaluation function can also be of use. Within the context of optimization, symmetry induction as defined in this thesis will have the effect of equating the evaluation of a set of given objects. Group theory is employed to explore possible symmetrical structures inherent in a search space. Additionally, conditions when the search space can have a symmetry induced on it are examined. The idea of a neighborhood structure then leads to the idea of opposition-based computing which aims to induce a symmetry of the evaluation function. In this context, the search space can be seen as having a symmetry imposed on it. To be useful, it is shown that an opposite map must be defined such that it equates elements of the search space which have a relatively large difference in their respective evaluations. Using this idea a general framework for employing opposition-based ideas is proposed. To show the efficacy of these ideas, the framework is applied to popular computational intelligence algorithms within the areas of Monte Carlo optimization, estimation of distribution and neural network learning. The first example application focuses on simulated annealing, a popular Monte Carlo optimization algorithm. At a given iteration, symmetry is induced on the system by considering opposite neighbors. Using this technique, a temporary symmetry over the neighborhood region is induced. This simple algorithm is benchmarked using common real optimization problems and compared against traditional simulated annealing as well as a randomized version. The results highlight improvements in accuracy, reliability and convergence rate. An application to image thresholding further confirms the results. Another example application, population-based incremental learning, is rooted in estimation of distribution algorithms. A major problem with these techniques is a rapid loss of diversity within the samples after a relatively low number of iterations. The opposite sample is introduced as a remedy to this problem. After proving an increased diversity, a new probability update procedure is designed. This opposition-based version of the algorithm is benchmarked using common binary optimization problems which have characteristics of deceptivity and attractive basins characteristic of difficult real world problems. Experiments reveal improvements in diversity, accuracy, reliability and convergence rate over the traditional approach. Ten instances of the traveling salesman problem and six image thresholding problems are used to further highlight the improvements. Finally, gradient-based learning for feedforward neural networks is improved using opposition-based ideas. The opposite transfer function is presented as a simple adaptive neuron which easily allows for efficiently jumping in weight space. It is shown that each possible opposite network represents a unique input-output mapping, each having an associated effect on the numerical conditioning of the network. Experiments confirm the potential of opposite networks during pre- and early training stages. A heuristic for efficiently selecting one opposite network per epoch is presented. Benchmarking focuses on common classification problems and reveals improvements in accuracy, reliability, convergence rate and generalization ability over common backpropagation variants. To further show the potential, the heuristic is applied to resilient propagation where similar improvements are also found.

In this thesis, I present a computational neural model that reproduces the high-level behavioural results of well-known fear conditioning experiments: first-order conditioning, second-order conditioning, sensory preconditioning, context conditioning, blocking, first-order extinction and renewal (AAB, ABC, ABA), and extinction and renewal after second-order conditioning and sensory preconditioning. The simulated neural populations used to account for the behaviour observed in these experiments correspond to known anatomical regions of the mammalian brain. Parts of the amygdala, periaqueductal gray, cortex and thalamus, and hippocampus are included and are connected to each other in a biologically plausible manner. The model was built using the principles of the Neural Engineering Framework (NEF): a mathematical framework that allows information to be encoded and manipulated in populations of neurons. Each population represents information via the spiking activity of simulated neurons, and is connected to one or more other populations; these connections allow computations to be performed on the information being represented. By specifying which populations are connected to which, and what functions these connections perform, I developed an information processing system that behaves analogously to the fear conditioning circuit in the brain.

New or improved decision analysis tools are developed in this thesis to address strategic policy analysis with specific focus on two topics: strategic conflict analysis and region-performance comparisons. A strategic conflict refers to a situation in which two or more decision makers (DMs) are to make a decision that affects issues over which they have different preferences. Various forms of strategic conflict exist all around us, in areas such as environmental management, international relations, economic competition, and relationships among individuals. The graph model for conflict resolution (GMCR) is an advanced and comprehensive tool to systematically study strategic conflicts. A well-known decision tool, the analytic network process (ANP) is adapted for use in strategic conflict analysis and a comparison of the performance of ANP with GMCR is carried out. Both methods are applied to an international trading conflict between the United States and China over the importation of television sets into the US in order to gain strategic insights about this dispute using the two different but complementary approaches. A country's overall performance comparison with respect to different kinds of indices such as economic, environmental and political indices constitutes another interesting topic for strategic policy analysis. An index aggregation approach is proposed to compare BRICSAM countries, a populous rapidly-growing economic group of nations consisting of Brazil, Russia, India, China, South Africa, ASEAN (Association of South-East Asian Nations), and Mexico with G7 (Group of Seven), the most developed country club including Canada, France, Italy, Japan, Germany, United Kingdom and the United States. A data-envelopment-analysis (DEA) based approach is proposed to aggregate different ranking indices for BRICSAM and the G7 countries. The proposed method can provide a fair overall assessment of a country's standing by maximizing its possibility of obtaining the best evaluation score. Finally, a framework to carry out generic strategic analysis for regions' competence analysis is designed based upon the theory of generic strategic analysis proposed by Porter (1980). This is a well-known approach for use in business competence analysis. The basic idea is to carry out generic strategic analysis in policy studies and two decision tools, DEA and the analytic hierarchy process, are employed to quantify the analysis of competence efficiency and potentiality, respectively. A case study of the competence analysis of provinces in China is used to demonstrate the analysis procedure.

A fuzzy approach for handling uncertain preferences is developed within the paradigm of the Graph Model for Conflict Resolution and new advances in trust modeling and assessment are put forward for permitting decision makers (DMs) to decide with whom to cooperate and trust in order to move from a potential resolution to a more preferred one that is not attainable on an individual basis. The applicability and the usefulness of the fuzzy preference and trust research for giving an enhanced strategic understanding about a dispute and its possible resolution are demonstrated by employing a realworld environmental conflict as well as two generic games that represent a wide range of real life encounters dealing with trust and cooperation dilemmas. The introduction of the uncertain preference representation extends the applicability of the Graph Model for Conflict Resolution to handle conflicts with missing or incomplete preference information. Assessing the presence of trust will help to compensate for the missing information and bridge the gap between a desired outcome and a feared betrayal. These advances in the areas of uncertain preferences and trust have potential applications in engineering decision making, electronic commerce, multiagent systems, international trade and many other areas where conflict is present. In order to model a conflict, it is assumed that the decision makers, options, and the preferences of the decision makers over possible states are known. However, it is often the case that the preferences are not known for certain. This could be due to lack of information, impreciseness, or misinformation intentionally supplied by a competitor. Fuzzy logic is applied to handle this type of information. In particular, it allows a decision maker to express preferences using linguistic terms rather than exact values. It also makes use of data intervals rather than crisp values which could accommodate minor shifts in values without drastically changing the overall results. The four solution concepts of Nash, general metarationality, symmetric metarationality, and sequential stability for determining stability and potential resolutions to a conflict, are extended to accommodate the new fuzzy preference representation. The newly proposed solution concepts are designed to work for two and more than two decision maker cases. Hypothetical and real life conflicts are used to demonstrate the applicability of this newly proposed procedure. Upon reaching a conflict resolution, it might be in the best interests of some of the decision makers to cooperate and form a coalition to move from the current resolution to a better one that is not achievable on an individual basis. This may require moving to an intermediate state or states which may be less preferred by some of the coalition members while being more preferred by others compared to the original or the final state. When the move is irreversible, which is the case in most real life situations, this requires the existence of a minimum level of trust to remove any fears of betrayal. The development of trust modeling and assessment techniques, allows decision makers to decide with whom to cooperate and trust. Illustrative examples are developed to show how this modeling works in practice. The new theoretical developments presented in this research enhance the applicability of the Graph Model for Conflict Resolution. The proposed trust modeling allows a reasonable way of analyzing and predicting the formation of coalitions in conflict analysis and cooperative game theory. It also opens doors for further research and developments in trust modeling in areas such as electronic commerce and multiagent systems.

Designers use simulations to observe the behaviour of a system and to make design decisions to improve dynamic performance. However, for complex dynamic systems, these simulations are often time-consuming and, for robust design purposes, numerous simulations are required as a range of design variables is investigated. Furthermore, the optimum set is desired to meet specifications at particular instances in time. In this thesis, the dynamic response of a system is broken into discrete time instances and recorded into a matrix. Each column of this matrix corresponds to a discrete time instance and each row corresponds to the response at a particular design variable set. Singular Value Decomposition (SVD) is then used to separate this matrix into two matrices: one that consists of information in parameter-space and the other containing information in time-space. Metamodels are then used to efficiently and accurately calculate the response at some arbitrary set of design variables at any time. This efficiency is especially useful in Monte Carlo simulation where the responses are required at a very large sample of design variable sets. This work is then extended where the normalized sensitivities along with the first and second moments of the response are required at specific times. Later, the procedure of calculating the metamodel at specific times and how this metamodel is used in parameter design or integrated design for finding the optimum parameters given specifications at specific time steps is shown. In conclusion, this research shows that SVD and metamodelling can be used to apply probabilistic robust design tools where specifications at certain times are required for the optimum performance of a system.

This thesis focuses on the design of a versatile, portable, and cost-effective fluorescence detection system for LOC devices. Components that are widely available are used, such as LEDs for excitation and a microcontroller for processing. In addition, a photoresistor is tested for the feasibility of being used as a fluorescence detector, instead of the more commonly used photomultiplier tubes. The device also focuses on upgradeability and versatility, meaning that most of the major components can be replaced as long as power requirements remain unaffected. This allows for future additions to the device once they are available, as well as giving the user the power to choose which add-ons are needed since not all users may have the same requirements. The performance of the device after testing with fluorescein dyes and stained yeast cells indicate that it is capable of executing simple tasks, such as determining the presence and concentration of an analyte if given a sufficient amount. It also provided similar readings to commercial fluorescence analysers, which proves its ability to function as a fluorescence detector device. The thesis also proposes a MEMS diffraction grating that can be used for wavelength tuning. By being able to selectively measure across a range of wavelengths, the capability of the device is increased. Examples include being able to detect multiple fluorescent emissions, which will complement the multicoloured excitation LED nicely. In addition, the device will not be limited to a predetermined set of filters. This effectively allows more fluorescent dyes to be used with the device since any wavelength in the visible range can be selectively filtered for. Simulations of the proposed diffraction grating were performed in ANSYS to confirm the validity of the calculated values. In addition, tests were performed on a slide fabricated with diffraction gratings using values as close to the calculated values as possible. All of the results indicate that there is great promise in the proposed diffraction grating design and that it should be further investigated.

Biological sample analysis is a costly and time-consuming process. It involves highly trained technicians operating large and expensive instruments in a temperature and dust controlled environment. In the world of rising healthcare cost, the drive towards a more cost-effective solution calls for a point-of-care device that performs accurate analyses of human blood samples. To achieve this goal, today's bulky laboratory instruments need to be scaled down and integrated on a single microchip of only a few square centimeters or millimeters in size. Dielectrophoresis (DEP), a phenomenon where small particles such as human blood cells are manipulated by non-uniform electric fields, stands to feature prominently in the point-of-care device. An original device that enhances DEP effect through novel geometry of the electrodes is presented. When activated with two inverting sinusoidal waveforms, the novel-shaped electrodes generate horizontal bands of increasing electric fields on the surface of the microchip. With these bands of electric fields, particles can be manipulated to form a straight horizontal line at a predictable location. Experimental results showing the collection, separation, and transportation of mammalian cells are presented. A strategy for simultaneous processing of two or more types of particles is also demonstrated. With capabilities for an accurate position control and an increased throughput by parallel processing, the novel microchip device delivers substantial improvements over the existing DEP designs. The research presented here explores the effects of novel electrode geometries in cell manipulations and contributes to the overall progress of an automated blood analysis system.

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.

Modern sonar systems have greatly improved their sensor technology and processing techniques, but little effort has been put into display design for sonar data. The enormous amount of acoustic data presented by the traditional frequency versus time display can be overwhelming for a sonar operator to monitor and analyze. The recent emphasis placed on networked underwater warfare also requires the operator to create and maintain awareness of the overall tactical picture in order to improve overall effectiveness in communication and sharing of critical data. In addition to regular sonar tasks, sonobuoy system operators must manage the deployment of sonobuoys and ensure proper functioning of deployed sonobuoys. This thesis examines an application of the Ecological Interface Design framework in the interface design of a sonobuoy system on board a maritime patrol aircraft. Background research for this thesis includes a literature review, interviews with subject matter experts, and an analysis of the decision making process of sonar operators from an information processing perspective. A work domain analysis was carried out, which yielded a dual domain model: the domain of sonobuoy management and the domain of tactical situation awareness address the two different aspects of the operator's work. Information requirements were drawn from the two models, which provided a basis for the generation of various unique interface concepts. These concepts covered both the needs to build a good tactical picture and manage sonobuoys as physical resources. The later requirement has generally been overlooked by previous sonobuoy interface designs. A number of interface concepts were further developed into an integrated display prototype for user testing. Demos created with the same prototype were also delivered to subject matter experts for their feedback. While the evaluation means are subjective and limited in their ability to draw solid comparisons with existing sonobuoy displays, positive results from both user testing and subject matter feedback indicated that the concepts developed here are intuitive to use and effective in communicating critical data and supporting the user’s awareness of the tactical events simulated. Subject matter experts also acknowledged the potential for these concepts to be included in future research and development for sonobuoy systems. This project was funded by the Industrial Postgraduate Scholarships (IPS) from Natural Science and Engineering Research Council of Canada (NSERC) and the sponsorship of Humansystems Inc. at Guelph, Ontario.