In many countries across the world, fossil fuels, especially petroleum, are the largest energy source for powering the socio-economic system and the transportation sector dominates the consumption of petroleum in these societies. As the petroleum price continuously climbs and the threat of global climate changes becomes more evident, the world is now facing critical challenges in reducing petroleum consumption and exploiting alternative energy sources. A massive adoption of plug-in electric vehicles (PEVs), especially battery electric vehicles (BEVs), offers a very promising approach to change the current energy consumption structure and diminish greenhouse gas emissions and other pollutants. Understanding how individual electric vehicle drivers behave subject to the technological restrictions and infrastructure availability and estimating the resulting aggregate supply-demand effects on urban transportation systems is not only critical to transportation infrastructure development, but also has determinant implications in environment and energy policy enactment. Driving PEVs inevitably changes individual’s travel and activity behaviors and calls for fundamental changes to the existing transportation network and travel demand modeling paradigms to accommodate changing cost structures, technological restrictions, and supply infrastructures. A prominent phenomenon is that all PEV drivers face a distance constraint on their driving range, given the unsatisfactory battery-charging efficiency and scarce battery-charging infrastructures in a long period of the foreseeable future. Incorporating this distance constraint and the resulting behavioral changes into transportation network equilibrium and travel demand models (static and/or dynamic) raises a series of important research questions. This dissertation focuses on analyzing the impact of a massive adoption of BEVs on urban transportation network flows. BEVs are entirely dependent on electricity and cannot go further once the battery is depleted. As a modeling requirement in its simplest form, a distance constraint should be imposed when analyzing and modeling individual behaviors and network congestions. With adding this simple constraint, this research work conceptualizes, formulates and solves mathematical programming models for a set of new BEV-based network routing and equilibrium problems. It is anticipated that the developed models and methods can be extensively used in a systematic way to analyze and evaluate a variety of system planning and policy scenarios in decision-making circumstances of BEV-related technology adoption and infrastructure development. / text

Korat is an existing technique for test input generation using imperative constraints that describe properties of desired inputs written as Java predicates, termed RepOk methods, which are executable checks for those properties. Korat efficiently prunes the space of candidate inputs for the RepOk method by executing it on candidate inputs and monitoring the object fields that RepOk accesses in deciding if the properties are satisfied. While Korat generates inputs effectively, its correctness and efficiency rely on two assumptions about the RepOk methods. For correctness, Korat assumes the RepOk methods do not use the Java reflection API for field accesses; the use of reflection renders Korat unable to enumerate all desired inputs. For efficiency, Korat assumes the RepOk methods do not make unnecessary field accesses, which can reduce the effectiveness of Korat’s pruning. Our thesis addresses both these limitations. To support reflection, we build on the core Korat to enhance it such that it can monitor field accesses based on reflection. To assist the users with writing RepOk’s, we introduce a static analysis tool that detects potential places where the input RepOk may be edited to enhance performance of Korat. We also present experimental results using a suite of standard data structure subjects. / text

This report investigates the efficacy of using constraint-induced language therapy (CILT) for treating acquired apraxia of speech (AOS). CILT is a treatment method used with individuals with aphasia in which communication is restricted to verbal output in order to isolate the damaged language areas of the brain and reactivate impaired neural connections (Pulvermuller et al., 2001). CILT employs repetitive, massed practiced stimuli and structured shaping of expressive output within the confines of verbal expression (Pulvermuller et al., 2001). Kirmess and Maher (2010) indirectly discovered that two patients with aphasia and apraxia of speech made gains in both language output and articulatory accuracy after receiving intensive CILT, suggesting possible efficacy for the use of CILT with patients with AOS. / text

Deadlocks are critical events in Flexible Manufacturing Cells (FMC) that result from circular waits among a set of resources. Circular waits happen when a set of resources with finite capacity are in a permanent hold due to wait state to admit new jobs. Past literature examines the deadlock-free scheduling in FMCs considering many types of resources and techniques. This thesis proposes a new resource-oriented deadlock-free approach using a robot equipped with dual-grippers serving as a material handler in a FMC. The proposed methodology uses Constraint Programming (CP). The system performance is analyzed using different buffer configurations. Many test problems are generated to validate the developed models. The finding demonstrates that the proposed dual-gripper robot (DGR) can outperform the single-gripper robot (SGR) in many settings for FMCs. Likewise, the experience with the CP for the modeling and solving approach proposed in this research consolidates its application to FMC deadlock-free scheduling problems.

This is a multi-essay dissertation in the area of dynamic models of the insurance markets. I study issues in insurance markets by examining individual behavior and industry performance in dynamic settings. My first essay studies household life insurance demand and saving decisions by applying a heterogeneous-agent life cycle model with wage shocks and mortality shocks. This essay proposes the most important determinants of household life insurance demand, and shows the joint decision of life insurance purchase between couples. My second essay focuses on the property-liability insurance market, and aims to study the impact of one catastrophe event on an insurer’s underwritings and capital raising strategy. The two-period cash flow model is built to also explore what kind of insurers can benefit from catastrophic risk underwritings. My third essay extends the second essay by incorporating a dynamic cash flow model with a series of loss shocks. I find the dynamic interaction between the insurer’s balance sheet and its capital rationing resulting from loss shocks. The model generates a non-cyclical behavior of output changes in the insurance market, and this suggests the current asymmetric, unpredictable and random underwriting cycles are temporary responses to loss shocks.

Recorded by Eugene Barsky, Physiotherapy Outreach Librarian, UBC / This is a Systematic Review Presentation titled - "Effectiveness of Constraint Therapy in Children with Hemiplegia:A Systematic Review", created by Master of Physical Therapy Graduating Students, University of British Columbia - 2006, Presented on September 14-15, 2006 , Vancouver, BC, Canada

The rapid expansion of low-density suburban areas in North America has led to new travel patterns that require transit services to be more flexible. Flex-Route transit service, which combines fixed-route transit service with elements of demand-responsive transit service, has emerged as a viable transit option to address the travel needs of the residents of these areas. Existing literature in this field, however, is limited and lacks any comprehensive analysis of Flex-Route planning, design and scheduling. This research aims at exploring Flex-Route transit service to provide detailed guidelines for the planning and design of the service, as well as developing a new scheduling system for this type of unique service. Accordingly, the objectives of this research are: assessing the practicality of Flex-Route transit service in serving low-density suburban areas; identifying essential Flex-Route planning steps and design parameters; determining the feasibility and cost of replacing fixed-route transit with Flex-Route service; and developing a Flex-Route-specific dynamic scheduling system that relies on recent developments in computer and communication technologies. In this regard, we develop an analytical model that addresses several design parameters and provide a detailed analysis that includes, among other parameters, finding optimal values for Flex-Route service area and slack time. Furthermore, the analytical model includes a feasibility and cost analysis that estimates the cost incurred by several stakeholders if Flex-Route service is chosen to replace fixed-route service. The core of the scheduling system is a new developed algorithm – the Constrained-Insertion Algorithm- that exploits the powerful search techniques of Constraint Programming. The scheduling system can handle the daily operations of Flex-Route transit services; it accepts daily (or dynamic) inputs and, in minimal time, produces very cost-effective and reliable schedules. Moreover, the scheduling system has the ability to be used as simulation tool to allow transit operators to assess the feasibility and performance of proposed Flex-Route transit services before implementation. The applicability of the analytical model as well as the performance of the scheduling system were subsequently evaluated and validated through process that included testing on a case study in the City of Oakville, Canada.

The rapid expansion of low-density suburban areas in North America has led to new travel patterns that require transit services to be more flexible. Flex-Route transit service, which combines fixed-route transit service with elements of demand-responsive transit service, has emerged as a viable transit option to address the travel needs of the residents of these areas. Existing literature in this field, however, is limited and lacks any comprehensive analysis of Flex-Route planning, design and scheduling. This research aims at exploring Flex-Route transit service to provide detailed guidelines for the planning and design of the service, as well as developing a new scheduling system for this type of unique service. Accordingly, the objectives of this research are: assessing the practicality of Flex-Route transit service in serving low-density suburban areas; identifying essential Flex-Route planning steps and design parameters; determining the feasibility and cost of replacing fixed-route transit with Flex-Route service; and developing a Flex-Route-specific dynamic scheduling system that relies on recent developments in computer and communication technologies. In this regard, we develop an analytical model that addresses several design parameters and provide a detailed analysis that includes, among other parameters, finding optimal values for Flex-Route service area and slack time. Furthermore, the analytical model includes a feasibility and cost analysis that estimates the cost incurred by several stakeholders if Flex-Route service is chosen to replace fixed-route service. The core of the scheduling system is a new developed algorithm – the Constrained-Insertion Algorithm- that exploits the powerful search techniques of Constraint Programming. The scheduling system can handle the daily operations of Flex-Route transit services; it accepts daily (or dynamic) inputs and, in minimal time, produces very cost-effective and reliable schedules. Moreover, the scheduling system has the ability to be used as simulation tool to allow transit operators to assess the feasibility and performance of proposed Flex-Route transit services before implementation. The applicability of the analytical model as well as the performance of the scheduling system were subsequently evaluated and validated through process that included testing on a case study in the City of Oakville, Canada.

Constraint-based models of metabolism seldom incorporate capacity constraints on intracellular fluxes due to the lack of experimental data. This can sometimes lead to inaccurate growth phenotype predictions. Meanwhile, other forms of data such as fitness profiling data from growth competition experiments have been demonstrated to contain valuable information for elucidating key aspects of the underlying metabolic network. Hence, the optimal capacity constraint identification (OCCI) algorithm is developed to reconcile constraint-based models of metabolism with fitness profiling data by identifying a set of flux capacity constraints that optimally fits a wide array of strains. OCCI is able to identify capacity constraints with considerable accuracy by matching 1,155 in silico-generated growth rates using a simplified model of Escherichia coli central carbon metabolism. Capacity constraints identified using experimental fitness profiles with OCCI generated novel hypotheses, while integrating thermodynamics-based metabolic flux analysis allowed prediction of metabolite concentrations.

Deadlocks are critical events in Flexible Manufacturing Cells (FMC) that result from circular waits among a set of resources. Circular waits happen when a set of resources with finite capacity are in a permanent hold due to wait state to admit new jobs. Past literature examines the deadlock-free scheduling in FMCs considering many types of resources and techniques. This thesis proposes a new resource-oriented deadlock-free approach using a robot equipped with dual-grippers serving as a material handler in a FMC. The proposed methodology uses Constraint Programming (CP). The system performance is analyzed using different buffer configurations. Many test problems are generated to validate the developed models. The finding demonstrates that the proposed dual-gripper robot (DGR) can outperform the single-gripper robot (SGR) in many settings for FMCs. Likewise, the experience with the CP for the modeling and solving approach proposed in this research consolidates its application to FMC deadlock-free scheduling problems.