<p> This thesis studies critical zones of automated vehicles. The goal is for the automated vehicle to complete a car-following or lane change maneuver without collision. For instance, the automated vehicle should be able to indicate its interest in changing lanes and plan how the maneuver will occur by using model predictive control theory, in addition to the autonomous vehicle toolbox in Matlab. A test bench (that includes a scenario creator, motion logic and planner, sensors, and radars) is created and used to calculate the parameters of a critical zone. After a trajectory has been planned, the automated vehicle then attempts the car following or lane change while constantly ensuring its safety to continue on this path. If at any point, the lead vehicle brakes or a trailing vehicle accelerates, the automated vehicle makes the decision to either brake, accelerate, or abandon the lane change. </p>

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The source-to-wheel efficiency of today's electrified vehicles already far surpasses the efficiency of strictly gasoline vehicles. As sources of electricity become cleaner and more efficient, and as gasoline becomes more scarce, the need for transporation electrification is increasingly economically and environmentally driven. The automotive industry primarily makes use of permanent magnet synchronous machines (PMSMs) and induction machines (IMs), the latter has the cost advantage of containing no rare earth metals. This thesis studies two different induction motors for electrified powertrain applications using a novel optimization algorithm to create efficiency maps and compare the efficiencies of the two motors. Induction motors are difficult to banchmark due to their complicated control schemes. Each point in their operating range can be achieved with an infinite number of current/slip combinations and therefore has infinite potential efficiencies. The proposed algorithm limits the number of simulations needed to benchmark an induction machine, and provides a clear and unbiased way to compare machines based on losses at their most efficient current/slip combinations over their entire operating range. The proposed algorithm is able to calculate losses within 5% error of simulation values for both machines. The first motor studied makes use of stranded windings and geometry parameters from the Tesla Motors patents. The efficiency map created has a peak efficiency of 96% and corresponds closely to an efficiency map for a similar motor found in literature. The second motor makes use of copper bar windings, which are easier to manufacture and have lower material costs. Bar windings, typically have lower resistance and stator copper losses at low speeds, but higher effective resistance and stator losses at high speeds due to eddy effects. The motor modelled was intended simply to compare the stranded and bar windings, and to see the advantages and disadvantages. For this reason, no other changes are made to the winding layout or motor geometry, including changes that would reduce the eddy effect. The resultant efficiency map has a peak efficiency of only 90%, performing worse than the stranded wound motor across most of its operating range. At very low speeds, under 1000 rpm, the efficiency of the bar wound machine is better than that of the stranded machine. The bar wound machine also has the advantage of being over 80\% efficient everywhere. The author suggests that future research focus on applying the proposed benchmarking algorithm to stator bar motors designed to limit eddy effects. Strategies include changing the slot opening shape, increasing the number of stator bars, and moving the stator bars away from the air gap. / Thesis / Master of Applied Science (MASc)

Yes / This paper represents a significant advance on the issue of testing for implementations specified by P systems with transformation and communicating rules. Using the X-machine framework and the concept of cover automaton, it devises a testing approach for such systems, that, under well defined conditions, it ensures that the implementation conforms to the specification. It also investigates the issue of identifiability for P systems, that is an essential prerequisite for testing implementations based on such specifications and establishes a fundamental set of properties for identifiable P systems. / Marian Gheorghe and Savas Konur acknowledge the support from EPSRC (EP/I031812/1). Marian Gheorghe’s and Florentin Ipate’s work is partially supported by CNCS-UEFISCDI (PN-II-ID-PCE-2011-3-0688).

The growing need for high quality and reliability of products requires the control of the accuracy of dimensions and shape of product components. Coordinate Measurement Machines (CMM) are now able to measure the dimensions and/or the shape of objects with submicron precision. The desire for high-speed measurement, has stimulated the interest of CMM manufacturers in the use of composite materials for the structure of their machines. Composites are lighter than conventional materials, and are generally less affected by temperature changes. In cooperation with one of the major European CMM manufacturers, the problem of redesigning a steel carriage of a CMM, from composite materials component is considered. A simple strength-of-materials based calculation is used to design a prototype of the carriage, which is built and mounted on the machine to be tested. A NASTRAN finite element model of the composite component is created to analyze more accurately the behavior of the composite structure. Structural optimization is next performed to seek minimum weight and maximum stiffness designs of the structural component. / Master of Science

This work considers a means of implementing a detection algorithm for multiple stuck-at faults occurring within the structure of a generalized tree using, as the testing machines, a set of generalized sequential trees. It is shown that the testing machine can be implemented on a set of trees of the same depth as that of the tree which is being tested. Modifications are made to the generalized tree structure so as to facilitate the testing algorithm and in order to simplify initialization. The testing algorithm is modified so as to test this modified structure. In addition, after testing is complete, two means of reinitialization of the sequential trees are discussed. / Master of Science

This thesis attempts to problematize and rethink the inter-related construction of the categories of "environment" and "fitness". It argues that environments are materially and discursively constructed through the mutually constitutive mobilization of networks of human and non-human actors by particularly powerful centers of translation, and that these processes increasingly involve the construction of environments configured to the requirements of an ideal of fitness - a fitness defined in terms of risk, flexibility, response-ability, responsibility, mobility, and consumption. In developing this argument particular attention is given to the relations between bodies and technologies as actors constitutive of the networks from which environments are constructed. As a specific illustrative example of this, the efforts of the fitness equipment manufacturer NordicTrack to mobilize and translate diverse networks of actors in the space of the home and then represent these hybrid networks as ontologically purified, meaningful and marketable environments are examined. The ontological and spatial ambiguity of the types of environments constructed by corporations such as NordicTrack is then discussed, this ambiguity being registered in the difficulty of positioning the boundaries between categories such as subject and object, nature and culture, human and machine, real and virtual. Finally, having illustrated that these ambiguous environments are perhaps constituted by communities of human and non-human actors, this thesis then suggests that such a recognition might open up space for critical geographical imaginations that are responsive to the possibility that political, ethical, and moral community and agency are co-constructions of humans and non-humans. / Master of Science

In an era with compelling need for greater computation power, the aggregation of software system components is becoming more challenging and diverse. The new-generation scientific applications are growing hub of complex and intense computation performed on huge data set with exponential growth. With the development of parallel algorithms, design of multi-user web applications and frequent changes in software architecture, there is a bigger challenge lying in front of the research institutes and organizations. Network science is an interesting field posing extreme computation demands to sustain complex large-scale networks. Several static or dynamic network analysis have to be performed through algorithms implementing complex graph theories, statistical mechanics, data mining and visualization. Similarly, high performance computation infrastructures are imbibing multiple characters and expanding in an unprecedented way. In this age, it's mandatory for all software solutions to migrate to scalable platforms and integrate cloud enabled data center clusters for higher computation needs. So, with aggressive adoption of cloud infrastructures and resource-intensive web-applications, there is a pressing need for a dynamic middleware to bridge the gap and effectively coordinate the integrated system. Such a heterogeneous environment encourages the devising of a transparent, portable and flexible solution stack. In this project, we propose adoption of Virtual Machine aware Portable Batch System Cluster (VM-aware PBS Cluster), a self-initiating and self-regulating cluster of Virtual Machines (VM) capable of operating and scaling on any cloud infrastructure. This is an unique but simple solution for large-scale softwares to migrate to cloud infrastructures retaining the most of the application stack intact. In this project, we have also designed and implemented Cloud Integrator Framework, a dynamic implementation of cloud aware middleware for the proposed VM-aware PBS cluster. This framework regulates job distribution in an aggregate of VMs and optimizes resource consumption through on-demand VM initialization and termination. The model was integrated into CINET system, a network science application. This model has enabled CINET to mediate large-scale network analysis and simulation tasks across varied cloud platforms such as OpenStack and Amazon EC2 for its computation requirements. / Master of Science