Systems methodologies are employed to investigate strategic decision problems regarding the development of the oil sands in Canada. Many countries believe energy to be one of their most important national security factors in today’s competitive global era. Canada is no exception. Energy is an issue in Canadians’ growing concerns related to the conflicting priorities of its economy, environment, and society. Various studies have tried to map out Canada’s establishment as an energy superpower. In particular, the massive resources in Canada must be considered as competitive advantages, and oil sands (tar sands) constitute one of the most crucial elements in terms of non-renewable energy. This thesis describes Canada’s oil sands – their characteristics, cost and market analysis, as well as social, economic, and environmental impacts – in order to clarify conflicts that have arisen in recent years. In addition, the importance, potential, and constraints of the oil sands are examined as leading drivers to the country becoming an energy superpower and are compared with the Canadian Academy of Engineering (CAE)’s studies and recommendations. Multiple-criteria decision analyses based on the ProGrid methodology are carried out at different levels to clarify the structure and current position of Canada’s energy system. An Evaluation Matrix, including multiple criteria, is built, and language ladders with different weights are established to allow various groups of experts to evaluate available options. Based on their evaluations, the strong and weak points of the oil sands are analyzed. At a more detailed level, alternative solutions for water quantity and quality problems in Canada’s oil sands are prioritized with respect to specific criteria, using the ProGrid methodology. The strategic issues in Canada’s oil sands are addressed at different levels, and priorities for decision-making are determined and discussed to guide Canada in becoming an energy superpower.

Humidity sensors are one of the most widely used sensors in commercial and industrial applications for environmental monitoring and controlling. Although related technology have been studied intensively, humidity sensing in harsh environments still remains a challenge. The inability of current humidity sensors to operate in high temperature environments is generally due to the degradation of the sensing films caused by high temperature, high humidity level, and/or contamination. Our goal is the design and fabrication of a humidity sensor that is capable of working under high temperatures and in a condensing environment. The targeted application of this sensor is in the polymer electrolyte membrane (PEM) fuel cell, where humidity control is crucial for performance optimization. In this work, ordered macroporous silicon is thoroughly studied as a humidity sensing layer. In addition to the advantages of traditional porous silicon for gas sensing (high resistance to high temperature and good compatibility with current IC fabrication process), the ordered macroporous silicon used in these experiment has uniform pore size, pore shape and distribution. All the vertical aligned pores can be opened to the environment at both ends, which can significantly increase the efficiency of gas diffusion and adsorption. Moreover, this special structure opens the door to uniform surface modifications for sensing enhancement. Both ordered macroporous silicon based heterostructure and self-supporting membrane are fabricated and investigated as a humidity sensor. Heterostructure sensors with different thin film surface coatings including bare Si, thermally grown SiO2, atom layer deposited ZnO, HfO2, and Ta2O5 are characterized. Post micro-fabrication is achieved on this ordered porous structure without affecting the material and its sensing properties. It has been proven that the ordered macroporous silicon with Ta2O5 surface coating shows the best sensing property due to its ultra-hydrophilic surface. The sensor shows high sensitivity, fast response times, small hysteresis, and extraordinary stability and repeatability under high temperatures and in condensing environment. It demonstrates great potential and advantages over existing commercial humidity sensors in the fuel cell application field. In addition to ordered macroporous silicon, well aligned 1D ZnO nanorods/nanowires -another widely used nanostructure in gas sensing- is also investigated as humidity sensing materials. Both vertically and laterally aligned nanorods/nanowires are fabricated and tested against humidity changes. The sensors shows increasing resistance to increasing relative humidity, which is contrary to most published works so far. Possible mechanisms have been proposed in this thesis and future work has been suggested for further study. To the best of our knowledge, this work is the first to use ordered macroporous silicon and well aligned 1D ZnO nanorods/nanowires for humidity sensing.

The determination of the 3D motion of a camera and the 3D structure of the scene in which the camera is moving, known as the Structure from Motion (SFM) problem, is a central problem in computer vision. Specifically, the recursive (online) estimation is of major interest for robotics applications such as navigation and mapping. Many problems still hinder the deployment of SFM in real-life applications namely, (1) the robustness to noise, outliers and ambiguous motions, (2) the numerical tractability with a large number of features and (3) the cases of rapidly varying camera velocities. Towards solving those problems, this research presents the following four contributions that can be used individually, together, or combined with other approaches. A motion-only filter is devised by capitalizing on algebraic threading constraints. This filter efficiently integrates information over multiple frames achieving a performance comparable to the best state of the art filters. However, unlike other filter based approaches, it is not affected by large baselines (displacement between camera centers). An approach is introduced to incorporate, with only a small computational overhead, a large number of frame-to-frame features (i.e., features that are matched only in pairs of consecutive frames) in any analytic filter. The computational overhead grows linearly with the number of added frame-to-frame features and the experimental results show an increased accuracy and consistency. A novel filtering approach scalable to accommodate a large number of features is proposed. This approach achieves both the scalability of the state of the art filter in scalability and the accuracy of the state of the art filter in accuracy. A solution to the problem of prediction over large baselines in monocular Bayesian filters is presented. This problem is due to the fact that a simple prediction, using constant velocity models for example, is not suitable for large baselines, and the projections of the 3D points that are in the state vector can not be used in the prediction due to the need of preserving the statistical independence of the prediction and update steps.

Melanoma is the deadliest form of skin cancer if left untreated. Incidence rates of melanoma have been increasing, especially among young adults, but survival rates are high if detected early. Unfortunately, the time and costs required for dermatologists to screen all patients for melanoma are prohibitively expensive. There is a need for an automated system to assess a patient's risk of melanoma using photographs of their skin lesions. Dermatologists could use the system to aid their diagnosis without the need for special or expensive equipment. One challenge in implementing such a system is locating the skin lesion in the digital image. Most existing skin lesion segmentation algorithms are designed for images taken using a special instrument called the dermatoscope. The presence of illumination variation in digital images such as shadows complicates the task of finding the lesion. The goal of this research is to develop a framework to automatically correct and segment the skin lesion from an input photograph. The first part of the research is to model illumination variation using a proposed multi-stage illumination modeling algorithm and then using that model to correct the original photograph. Second, a set of representative texture distributions are learned from the corrected photograph and a texture distinctiveness metric is calculated for each distribution. Finally, a texture-based segmentation algorithm classifies regions in the photograph as normal skin or lesion based on the occurrence of representative texture distributions. The resulting segmentation can be used as an input to separate feature extraction and melanoma classification algorithms. The proposed segmentation framework is tested by comparing lesion segmentation results and melanoma classification results to results using other state-of-the-art algorithms. The proposed framework has better segmentation accuracy compared to all other tested algorithms. The segmentation results produced by the tested algorithms are used to train an existing classification algorithm to identify lesions as melanoma or non-melanoma. Using the proposed framework produces the highest classification accuracy and is tied for the highest sensitivity and specificity.

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.

The current and future energy situations in Canada are put into perspective, and the importance of nuclear energy and controversies surrounding it are investigated. More specifically, to demonstrate the important role nuclear energy has to play in Canada's future, a novel energy modeling tool, Canadian Energy Systems Simulator (CanESS), is employed. CanESS is a modeling platform with a huge database that assists an analyst in defining different energy scenarios by modifying the variables such as population and contributions of different energy sources to the overall production. The CanESS results clearly show that expansion of nuclear energy production is required to meet energy demand and simultaneously reduce greenhouse gas emissions. To formally study strategic issues connected to the ongoing conflict over nuclear power production in Ontario, the Graph Model for Conflict Resolution (GMCR) is utilized. This flexible systems methodology is used to study the nuclear disputes that existed in Ontario at two key points in time: the fall of 2008 and spring of 2010. The results of the 2008 analysis, especially the sensitivity analyses, show that the only decision makers (DMs) involved in the conflict who hold real power are the Federal and Ontario governments, although at the beginning of the investigation the Atomic Energy of Canada Ltd. (AECL) and the environmental groups had also been considered as participating DMs. The findings and information of the analysis in 2008, as well as an updated background for 2010, are used to perform another analysis in 2010. Meanwhile, their options or possible courses of action have also been changed. Again, at this stage the stable states of the game are found, and attitude analysis is carried out to obtain deeper insights about the dispute. The equilibria or potential resolutions of the 2008 analysis are found to be the transition states in the 2010 analysis. Specifically, it is discovered that if the Federal Government does have a negative attitude towards the Ontario Government, it is possible that the final outcome is a state that is among the least preferred states for both DMs. To formally study strategic issues connected to the ongoing conflict over nuclear power production in Ontario, the Graph Model for Conflict Resolution (GMCR) is utilized. This flexible systems methodology is used to study the nuclear disputes that existed in Ontario at two key points in time: the fall of 2008 and spring of 2010. The results of the 2008 analysis, especially the sensitivity analyses, show that the only decision makers (DMs) involved in the conflict who hold real power are the Federal and Ontario governments, although at the beginning of the investigation the Atomic Energy of Canada Ltd. (AECL) and the environmental groups had also been considered as participating DMs. The findings and information of the analysis in 2008, as well as an updated background for 2010, are used to perform another analysis in 2010. According to the results of the 2008 analysis, only the two governments are considered as the DMs in 2010. Meanwhile, their options or possible courses of action have also been changed. Again, at this stage the stable states of the game are found, and attitude analysis is carried out to obtain deeper insights about the dispute. The equilibria or potential resolutions of the 2008 analysis are found to be the transition states in the 2010 analysis. Specifically, it is discovered that if the Federal Government does have a negative attitude towards the Ontario Government, it is possible that the final outcome is a state that is among the least preferred states for both DMs.

This thesis is an exploration of how to do sustainable development for buildings, especially during the earliest stages of such development. The thesis starts by considering clear definitions of sustainability, development and sustainable development as these concepts apply to organizations in general and as they apply specifically to the charity All Our Relations (AOR) and their community of the Region of Waterloo in Ontario, Canada. Three critical challenges to the process of development are also discussed in these early chapters, namely assessment, vision and feedback. In the third chapter, these same challenges are put under the lens of sustainable development and three new, but related, challenges of connection complexity, shared futures and resilience are examined to better understand the problems and solutions that surround them. At the end of this broad introductory section, AOR’s relationships with the community are explored as part of their efforts to draft an organization-wide sustainability plan. The second part of the thesis is an attempt to apply and expand on the general ideas from the first half through a focus on buildings and specifically the building of AOR’s planned Hospice and Retreat Centre in Bloomingdale, Ontario. As part of the focus on sustainable buildings, the Leadership in Energy and Environmental Design (LEED™) system of assessing building impacts is presented and critiqued. As part of a focus on building developments the earlier challenges of assessment, vision and feedback are revisited as they apply to the concept design phase of the typical building design. The final three chapters of the thesis are a synthesis of all the previous chapters and the formal presentation of the case study concept development for the AOR building. A full summary of all previous definitions are presented and the final definition of sustainable building development is expressed as a culmination and extension of its parts: Sustainable building development is a process of creating space-for-use which recognizes both the importance of space in our lives and the impact that developing that space has on our greater goal to pursue sustainability. Potential critiques of this definition are discussed and two methods of engaging in the difficult challenges of sustainable building development are presented: the decider’s dilemma and the life-cycle-service-network model of connection complexity. Finally, the case study use of LEED as a guide for doing sustainable development in buildings is contrasted against the author’s proposed approaches. Through a series of qualitative and quantitative observations based on the results from the case study design, LEED is revealed as being effective mostly as an early guide, but lacking in the rigor and complexity needed to address properly the challenges of building sustainability.

Quadriceps muscle weakness is a condition that can result from a wide variety of causes, from diseases like polio and multiple sclerosis to injuries of the head and spine. Individuals with weakened quadriceps often have difficulty supplying the knee-extension moments required during common mobility tasks. Existing powered orthoses that provide an assistive knee-extension moment are large and heavy, with power supplies that generally last less than two hours. A new device that provides a knee-extension-assist moment was designed to aid an individual with quadriceps muscle weakness to stand up from a seated position, sit from a standing position, and walk up and down an inclined surface. The knee-extension-assist (KEA) was designed as a modular component to be incorporated into existing knee-ankle-foot-orthoses (KAFO). The KEA consists of three springs that are compressed, as the knee is flexed under bodyweight, by cables that wrap around a sheave at the knee. The KEA returns the stored energy from knee flexion as an extension moment during knee extension. During swing or other non-weight bearing activities, the device is disengaged from the KAFO by decoupling the sheave from the KAFO knee joint, allowing free knee joint motion. A prototype was built and mechanically tested to determine KEA behaviour during loading and extension and to ensure proper KEA function. For biomechanical evaluation, able-bodied subjects used the prototype KEA while performing sit-to-stand, stand-to-sit, ramp ascent, and ramp descent tasks. The KEA facilitated sitting and standing, providing an average of 53 % of the required extension moment for the two participants, which allowed one participant to reduce quadriceps usage by 38 % and the other to perform sit-to-stand in a slower and more controlled manner that was not possible without the KEA. KEA use during ramp gait caused an overall increase in quadriceps activation by 76 %, on average, with use. Future efforts will be made to modify the design to improve functionality, especially for ramp gait, and to reduce device size and weight.

A volumetric contact dynamics model has been proposed by Gonthier et al. [1, 2, 3] for the purpose of rapidly generating reliable simulations of space-based manipulator contact dynamics. By assuming materials behave as a Winkler elastic foundation model, forces and moments between two bodies in contact can be expressed in terms of the volume of interference between the undeformed geometries of the bodies. Friction between bodies is modelled by a dwell-time dependent bristle model for both tangential friction, and spinning friction torque. This volumetric model has a number of advantages. Unlike point-contact models, it allows for the modelling of contact between complex geometries and scenarios where the contact surface is relatively large, while being less computationally expensive than finite element methods. Rolling resistance is included in the model through damping effects across the volume of interference. The friction model accounts for dwell-time dependent slip-stick effects, spinning friction torque, and the Contensou effect. In this thesis, an experimental validation of the volumetric contact model is presented for the first time. Models for simple geometries in contact (e.g. cylinder-on-plane, sphere-on-plane) have been developed for stationary contact and for contact with motion normal and tangential to the contact surface. Tangential motion is modelled with pure translation, pure rotation about the normal axis, and combined motion, in order to separately consider friction forces, spinning friction torque, and the Contensou effect, respectively. An apparatus has been developed to experimentally validate these models for metal-on-metal contact. The apparatus has two configurations, one for validating the normal contact models and the other for the friction models. Experimental measurements of forces and displacements are used to identify model parameters (e.g. volumetric stiffness, friction coefficients, etc.). For normal force experiments, modelling the contact forces as proportional to volume of interference was found to be a reasonable approximation. A Hertzian model was compared with the volumetric model for spherical payloads loaded quasi-statically. Using stiffnesses estimated from spherical experiments, small misalignments of the cylindrical payloads were estimated that corresponded well with measured results. Dynamic experiments suggest an inverse relationship between impact velocity and the hysteretic damping coefficient. The high normal forces applied in the friction experiments were found to create significant wear on the contact surfaces. Coefficients of friction between titanium and aluminum were found to be consistent translationally and rotationally. Friction forces from combined translation and rotation demonstrate that the Contensou effect is accurately described by the volumetric contact model.

A risky project evaluation technique called the fuzzy real options analysis is developed to evaluate brownfield redevelopment projects. Other decision making techniques, such as multiple criteria analysis and conflict analysis, can be incorporated into fuzzy real options analysis to facilitate negotiations on brownfield redevelopment among decision makers (DMs). The value of managerial flexibility, which is important in negotiations and policy making for brownfield redevelopment, is overlooked when the traditional evaluation method, net present value (NPV), is employed. Findings of this thesis can be used to promote brownfield redevelopment, thereby helping to eliminate environmental threats and enhance regional sustainability. A brownfield is an abandoned or underutilized property that contains, or may contain, pollutants, hazardous substances, or contaminants from previous usage, typically industrial activity. Brownfields often occur when the local economy transits from industrial to service-oriented seeking more profit. Governments actively promote brownfield redevelopment to eliminate public health threats, help economic transition, and enhance sustainability. However, developers are reluctant to participate in brownfield redevelopment because they often regard these projects as unprofitable when using classic evaluation techniques. On the other hand, case studies show that brownfield redevelopment projects can be good business opportunities for developers. An improved evaluation method is developed in order to estimate the value of a brownfield more accurately. The main reason that makes the difference between estimates and ''actual'' values lies in the failure of the deterministic project evaluation tool to price the value of uncertainty, which leads to efforts to enhance the decision making under uncertainty. Real options modelling, which extends the ability of option pricing models in real asset evaluation, is employed in risky project evaluation because of its capacity to handle uncertainties. However, brownfield redevelopment projects contain uncertain factors that have no market price, thus violating the assumption of option pricing models for which all risks have been reflected in the market. This problem, called private risk, is addressed by incorporating fuzzy numbers into real options in this thesis, which can be called fuzzy real options. Fuzzy real options are shown to generalize the original model to deal with additional kinds of uncertainties, making them more suitable for project evaluation. A numerical technique based on hybrid variables is developed to price fuzzy real options. We proposed an extension of Least Squares Monte-Carlo simulation (LSM) that produces numerical evaluations of options. A major advantage of this methodology lies in its ability to produce results regardless of whether or not an analytic solution exists. Tests show that the generalized LSM produces similar results to the analytic valuation of fuzzy real options, when this is possible. To facilitate parameter estimation for the fuzzy real options model, another numerical method is proposed to represent the likelihood of contamination of a brownfield using fuzzy boundaries. Linguistic quantifiers and ordered weighted averaging (OWA) techniques are utilized to determine the likelihood of pollution at sample locations based on multiple environmental indicators, acting as a fuzzy deduction rule to calculate the triangle membership functions of the fuzzy parameters. Risk preferences of DMs are expressed as different ''ORness'' levels of OWA operators, which affect likelihood estimates. When the fuzzy boundaries of a brownfield are generated by interpolation of sample points, the parameters of fuzzy real options, drift rate and volatility, can be calculated as fuzzy numbers. Hence, this proposed method can act as an intermediary between DMs and the fuzzy real options models, making this model much easier to apply. The values of DMs to a brownfield can be input to the graph model for conflict resolution (GMCR) to identify possible resolutions during brownfield redevelopment negotiation among all possible states, or combinations of DMs' choices. Major redevelopment policies are studied using a brownfield redevelopment case, Ralgreen Community in Kitchener, Ontario, Canada. The fuzzy preference framework and probability-based comparison method to rank fuzzy variables are employed to integrate fuzzy real options and GMCR. Insights into this conflict and general policy suggestions are provided. A potential negotiation support system (NSS) implementing these numerical methods is discussed in the context of negotiating brownfield redevelopment projects. The NSS combines the computational modules, decision support system (DSS) prototypes, and geographic information systems (GIS), and message systems. A public-private partnership (PPP) will be enhanced through information sharing, scenario generation, and conflict analysis provided by the NSS, encouraging more efficient brownfield redevelopment and leading to greater regional sustainability. The integrated usage of fuzzy real options, OWA, and GMCR takes advantage of fuzziness and randomness, making better evaluation technique available in a multiple DMs negotiation setting. Decision techniques expand their range from decision analysis, multiple criteria analysis, to a game-theoretic approach, contributing to a big picture on decision making under uncertainty. When these methods are used to study brownfield redevelopment, we found that creating better business opportunities, such as allowing land use change to raise net income, are more important in determining equilibria than remediation cost refunding. Better redevelopment policies can be proposed to aid negotiations among stakeholders.