One area of vehicle handling performance that has been the focus of an OEM{'}s (Original Equipment Manufacturer) engineering effort is within the realm of vehicle straight-line performance. As the name implies, straight-line performance is determinant on the vehicle{'}s tendency to resist vehicle lateral drift when being driven straight. Vehicle lateral drift is a condition where the driver must apply a constant correctional torque to the steering wheel in order to maintain a straight line course. A full vehicle model was developed to simulate the influences of suspension parameters on vehicle drift. Adams 2010 was chosen as the multi-body dynamics (MBD) software for this research for its ability to develop a full vehicle high fidelity model without the need for physical test data. The model was created from standard Adams/Car suspension templates modified to accommodate the subject vehicle. The front suspension sub-assembly model was built upon the front MacPherson strut suspension template. Likewise, the rear suspension sub-assembly model was created from the rear multi-link suspension template. The tire model used in the full vehicle model was based on the Pacejka 2002 formulation. A model of a similar tire was generated using a custom spreadsheet based on the PAC2002, a slightly modified version of the Pacejka 2002 formulation found within Adams/Car. A virtual tire test rig and a 6/7-DoF model were created to understand and verify the behaviour of the generated tire models. The virtual tire test rig was used to compare the outputs of the PAC2002 tire model to the calculated values from a custom tire property spreadsheet. The 6/7-DoF model was used to test and verify the effect of the tire{’}s residual lateral forces. The full-vehicle model was verified using the parallel wheel travel and opposite wheel travel suspension analyses. The parallel wheel travel analysis was used to tease out binding issues within the designed travel of the suspension. The opposite wheel travel analysis was used similarly for anti-roll bar systems. Simulations based on the industry standard vehicle drift tests were run to understand the effect of certain vehicle suspension geometry on vehicle drift, namely the vehicle{’}s front and rear camber and toe angles. The full-vehicle model was also subjected to straight-line performance simulations with various road bank or crown angles. The results were compared with industry-standard vehicle drift test data gathered by the OEM on their own test track. The results indicate that the direction of vehicle pull matches with the OEM test data, but the magnitudes differ in both the positively and negatively banked road simulation results. It is likely that the difference in vehicle drift is due to the lack of steering data obtained for the full-vehicle model.

Cognitive Work Analysis (CWA) is a framework for the analysis of complex systems that involve technological tools and human operators who must operate the systems in sometimes-unexpected situations. CWA consists of five phases that cover analysis of ecological aspects of systems, such as the tools in the system and the environment, and cognitive aspects, related to the human operators in the systems. Human operators often need to be trained to use complex systems, and training research has been conducted related to the ecological aspects of CWA; however, there is a gap in the training research related to the cognitive aspects of CWA. The Skills-Rules-Models (SRM) framework is currently the main method of cognitive analysis for CWA; therefore, to begin to fill the gap in the training literature at the cognitive end of CWA, this dissertation examines the need for training as related to SRM. In this dissertation, the current research related to training and CWA is reviewed and literature on the nature of expertise as related to SRM is examined. From this review, the need for training rules that can be used in unexpected situations, as a means of reducing cognitive demand, is identified. In order to assist operators with developing the knowledge to use such rule-based behaviour, training needs and methods to meet those needs must be identified. The reuse of knowledge in new situations is the essence of training transfer, so ideas from training transfer are used to guide the development of three guidelines for determining rules that might be transferable to new situations. Then methods of developing rules that fit those three guidelines by using information from the Work Domain Analysis (WDA) and Control Task Analysis (CTA) phases of CWA are presented. In addition to methods for identifying training needs, methods for meeting those training needs are required. The review of training transfer also identified the need to use contextual examples in training while still avoiding examples that place too high of a cognitive demand on the operator, possibly reducing learning. Therefore, as a basis for designing training material that imposes a reduced cognitive demand, Cognitive Load Theory (CLT) is reviewed, and methods for reducing cognitive demand are discussed. To demonstrate the methods of identifying and meeting training needs, two examples are presented. First, two sets of training rules are created based on the results of the application of the WDA and CTA phases of CWA for two different work domains: Computer Algebra Systems and the programming language Logo. Then, from these sets of rules, instructional materials are developed using methods based on CLT to manage the cognitive demands of the instructions. Finally, two experiments are presented that test how well operators learn from the instructional materials. The experiments provide support for the effectiveness of applying CLT to the design of instructional materials based on the sets of rules developed. This combined work represents a new framework for identifying and meeting training needs related to the cognitive aspects of CWA.

With the rapid growth of the digital imaging, image processing techniques are widely involved in many industrial and medical applications. Image thresholding plays an essential role in image processing and computer vision applications. It has a vast domain of usage. Areas such document image analysis, scene or map processing, satellite imaging and material inspection in quality control tasks are examples of applications that employ image thresholding or segmentation to extract useful information from images. Medical image processing is another area that has extensively used image thresholding to help the experts to better interpret digital images for a more accurate diagnosis or to plan treatment procedures. Opposition-based computing, on the other hand, is a recently introduced model that can be employed to improve the performance of existing techniques. In this thesis, the idea of oppositional thresholding is explored to introduce new and better thresholding techniques. A recent method, called Opposite Fuzzy Thresholding (OFT), has involved fuzzy sets with opposition idea, and based on some preliminary experiments seems to be reasonably successful in thresholding some medical images. In this thesis, a Weighted Opposite Fuzzy Thresholding method (WOFT) will be presented that produces more accurate and reliable results compared to the parent algorithm. This claim has been verified with some experimental trials using both synthetic and real world images. Experimental evaluations were conducted on two sets of synthetic and medical images to validate the robustness of the proposed method in improving the accuracy of the thresholding process when fuzzy and oppositional ideas are combined.

Ease of use with digital tabletops in public settings is contingent on how well the system invites and guides interaction. The same can be said for the interface design and individual graphical user interface elements of these systems. One such interface element is menus. Prior to a menu being used however, it must first be discovered within the interface. Existing research pertaining to digital tabletop menu design does not address this issue of discovering or opening a menu. This thesis investigates how the interface and interaction of digital tabletops can be designed to encourage menu discoverability in the context of public settings. A set of menu invocation designs varying on the invocation element and use of animation are proposed. These designs are then evaluated through an observational study at a museum to observe users interactions in a realistic public setting. Findings from this study propose the use of discernible and recognizable interface elements – buttons – supported by the use of animation to attract and guide users as a discoverable menu invocation design. Additionally, findings posit that when engaging with a public digital tabletop display, users transition through exploration and discovery states before becoming competent with the system. Finally, insights from this study point to a set of design recommendations for improving menu discoverability.

Because of the ubiquitous use of contact lenses, there is considerable interest in better understanding the anatomy of the cornea, the part of the eye in contact with an exterior lens. The recent technology developments in high resolution Optical Coherence Tomography (OCT) devices allows for the in-vivo observation of the structure of the human cornea in 3D and at cellular level resolution. Prolonged wear of contact lenses, inflammations, scarring and diseases can change the structure and physiology of the human cornea. OCT is capable of in-vivo, non-contact, 3D imaging of the human cornea. In this research, novel image processing algorithms were developed to process OCT images of the human cornea, in order to determine the corneal optical scattering and transmission. The algorithms were applied to OCT data sets acquired from multiple subjects before, during and after prolonged (3 hours) wear of soft contact lenses and eye patches, in order to investigate the changes in the corneal scattering associated with hypoxia. Results from this study demonstrate the ability of OCT to measure the optical scattering of corneal tissue and to monitor its changes resulting from external stress (hypoxia).

Cognitive complexity mitigation strategies are methods and approaches utilized by users to reduce the apparent complexity of problems thus making them easier to solve. These strategies often effective because they mitigate the limitations of human working memory and attention resources. Such cognitive complexity mitigation strategies are used throughout the design, development and operational processes of complex systems. Thus, a better understanding of these strategies, and methods that leverage them, can help improve the efficiency of such processes. Additionally, changes in the use of these strategies across various environments can identify cognitive differences in operating and developing across these contexts. This knowledge can help improve the effectiveness of cross-context user transfers by suggesting change management processes that incorporate the degree of cognitive difference across contexts. In order to document cognitive complexity mitigation strategies and the change in their usage, two application domains are studied. Firstly, cognitive complexity mitigation strategies used by designers during the engineering design process are found through an ethnographic immersion with a participating engineering firm, followed by an analysis of the designer's logbooks and validation interviews with the designers. Results include identification of five strategies used by the designers to mitigate design complexity. These strategies include Blackbox Modeling, Whitebox Modeling, Decomposition, Visualization and Prioritized Lists. The five complexity mitigation strategies are probed further across a larger sample of engineering designers and the usage frequency of these strategies is assessed across commonly performed engineering design activities which include the Selection, Configuration and Parametric activities. The results indicate the preferred use of certain strategies based on the engineering activity being performed. Such preferential usage of complexity mitigation strategies is also assessed with regards to Original and Redesign projects types. However, there is no indication of biased strategy usage across these two project characterizations. These results are an example of a usage-frequency based difference analysis; such analyses help identify the strategies that experience increased or reduced usage when transferring across activities. In contrast to the first application domain, which captures changes in how often strategies are used across contexts, the second application domain is a method of assessing differences based on how a specific strategy is used differently across contexts. This alternative method is developed through a project that aims to optimize the transfer of air traffic controllers across different airspace sectors. The method uses a previously researched complexity mitigation strategy, knows as a structure based abstraction, to develop a difference analysis tool called the Sector Abstraction Binder. This tool is used to perform cognitive difference analyses between air traffic control sectors by leveraging characteristic variations in how structure based abstractions are applied across different sectors. This Sector Abstraction Binder is applied to two high-level airspace sectors to demonstrate the utility of such a method.

The emotional experience of products can have enormous impact on the overall product experience: someone who is feeling positive is more likely to be accepting of novel products or to be more tolerant of unexpected or unusual interface behaviours. Being able to improve users’ emotions through product interaction has clear benefits and is currently the focus of designers all over the world. The extent to which touch-based information can affect a user’s experience and observable behaviour has been given relatively little attention in haptic technology or other touch-based products where research has tended to focus on psychophysics relating to technical development, in the case of the former, and usability in the case of the latter. The objective of this research was therefore to begin to explore generalizable and useful relationship(s) between design parameters specific to the sense of touch and the emotional response to tactile experiences. To this end, a theoretical ’touch-emotion model’ was developed that incorporates stages from existing information and emotion processing models, and a subset of pathways (the ‘Affective’, ‘Cognitive’, and ‘Behaviour Pathways’) was explored. Four experiments were performed to examine how changes in various touch factors, such as surface roughness and availability of haptic (that is, touch-based) information during exploration, impacted user emotional experience and behaviour in the context of the model’s framework. These experiments also manipulated factors related to the experience of touch in real-world situations, such as the availability of visual information and product context. Exploration of the different pathways of the touch-emotion model guided the analysis of the experiments. In exploring the Affective Pathway, a robust relationship was found between increasing roughness and decreasing emotional valence (n = 36, p < 0.005), regardless of the availability of haptic or visual information. This finding expands earlier research that focused on the effect of tactile stimuli on user preference. The impact of texture on the Cognitive Pathway was examined by priming participants to think of the stimuli as objects varying in emotional commitment, such as a common mug (lower) or a personal cell phone (higher). Emotional response again decreased as roughness increased, regardless of primed context (n = 27, p < 0.002) and the primed contexts marginally appeared to generally improve or reduce emotional response (n = 27, p < 0.08). Finally, the exploration of the Behaviour Pathway considered the ability of roughness-evoked emotion to act as a mediator between physical stimuli and observable behaviour, revealing that, contrary to the hypothesis that increased emotional valence would increase time spent reflecting on the stimuli, increased emotion magnitude (regardless of the positive or negative valence of the emotion) was associated with increased time spent in reflection (n = 33, p < 0.002). Results relating to the Behaviour Pathway suggested that the portion of the touch-emotion model that included the last stages of information processing, observable behaviour, may need to be revised. However, the insights of the Affective and Cognitive Pathway analyses are consistent with the information processing stages within those pathways and give support to the related portions of the touch-emotion model. The analysis of demographics data collected from all four experiments also revealed interesting findings which are anticipated to have application in customizing haptic technology for individual users. For example, correlations were found between self-reported tactual importance (measured with a questionnaire) and age (n = 79, r = 0.28, p < 0.03) and between self-reported tactual importance and sensitivity to increased roughness (n = 79, r = -0.27, p < 0.04). Higher response times were also observed with increased age (rIT = 0.49, rRT = 0.48; p < 0.01). This research contributes to the understanding of how emotion and emotionevoked behaviour may be impacted by changing touch factors using the exemplar of roughness as the touch factor of interest, experienced multimodally and in varying situations. If a design goal is to contribute to user emotional experience of a product, then the findings of this work have the potential to impact design decisions relating to surface texture components of hand-held products as well as for virtual surface textures generated by haptic technology. Further, the touchemotion model may provide a guide for the systematic exploration of the relationships between surface texture, cognitive processing, and emotional response.

This thesis provides analysis and modeling for one of the Micro-Eletro-Mechanical System (MEMS) electrostatic actuator that consists of a micro-plate at the end of a cantilever beam, and introduces different type of MEMS electrostatic actuator; a paddle structure, which is a micro-plate suspended by two cantilever beams on each side. An electrode plate is placed right under the micro-plate to apply an actuation voltage. A step-by-step analysis explains how to obtain each parameter used for the simulations. Static and dynamic models are presented with governing equations for the paddle-shaped MEMS electrostatic actuator. The key findings are that the proposed electrostatic MEMS demodulator architecture taking advantage of the resonance circuit principle not only theoretically work in analytical model, and numerical simulations, but also work in real life. For the Amplitude Modulations (AM) demodulations, simulations with various damping factors are provided, and experimental data are discussed. By measuring the displacement using the phase detector circuit and vibrometer, as a proof of versatility of the demodulation architecture based on the MEMS electrostatic actuator, the results from Frequency Modulations (FM), Amplitude Shift Keying (ASK), and Frequency Shift Keying (FSK) demodulation scheme experiments that are conducted with the physically identical dimensions and configuration are provided. The future plan for further analysis and experiment is discussed at the end.

Image processing applications such as image denoising, image segmentation, object detection, object recognition and texture synthesis often require a multi-scale analysis of images. This is useful because different features in the image become prominent at different scales. Traditional imaging models, which have been used for multi-scale analysis of images, have several limitations such as high sensitivity to noise and structural degradation observed at higher scales. Parametric models make certain assumptions about the image structure which may or may not be valid in several situations. Non-parametric methods, on the other hand, are very flexible and adapt to the underlying image structure more easily. It is highly desirable to have effi cient non-parametric models for image analysis, which can be used to build robust image processing algorithms with little or no prior knowledge of the underlying image content. In this thesis, we propose a non-parametric pixel neighbourhood based framework for multi-scale image analysis and apply the model to build image denoising and saliency detection algorithms for the purpose of illustration. It has been shown that the algorithms based on this framework give competitive results without using any prior information about the image statistics.

When there is information overload on the visual modality, another system of warnings must be adopted to prevent potential risks—tactile warning systems present a viable alternative. Building on work on design approaches for auditory warning systems that match appropriate warnings to the severity of risk, this thesis presents an approach to design tactile warnings based on perceived urgency. To do this, I use a subjective rating technique. I performed three experiments to demonstrate this approach. Our research approach uses subjective rating technique to evaluate perceived urgency. Three experiments were conducted to design tactile warnings with a tactile interface developed by attaching a grid of tactors on a vest. In Experiment 1 and 2, I evaluated perceived urgency of several warning designs with three important parameters of tactile warnings with subjective rating. In Experiment 3 I examined one warning design in the context of flight simulation. The results of Experiment 1 and 2 showed that participants can discriminate between all levels of perceived urgency from most warning parameters. In Experiment 3, the results showed that selected warning design was correctly mapped with the severity of most events. The findings suggest that tactile warnings based on perceived urgency can be a possible approach, but further studies will be required to evaluate different parameters of tactile warnings.