The subject of this dissertation is the calculation and visualization of intraoperative measurement uncertainty in computer-assisted surgical procedures. Error is the difference between the observed or measured value and the true value (called ground-truth) of a quantity. Uncertainty is the unknown difference between the measured and true values, and exists in the absence of knowledge of ground truth. If one has an algorithm for computing the ground truth then one can get an accurate estimate of error. However, in computer-assisted surgery, the ground truth is often unknown. The introduction of error to surgical procedures is inevitable: it cannot be avoided by simply taking very careful measurements, providing more accurate algorithms, or by improving instrument calibration. One can only reduce errors as much as reasonably possible, calculate a reliable estimate of the uncertainty, and provide a meaningful way to convey this uncertainty information to clinicians. In this dissertation, I demonstrate that the visualization of registration uncertainty improves surgical navigation and that real-time computation of intraoperative measurement uncertainty is possible. In an extensive user study of surgeons and surgical residents, I compare methods of visualizing intraoperative uncertainty and determine that there are several methods of effectively conveying uncertainty in surgical navigation. / Thesis (Ph.D, Computing) -- Queen's University, 2010-01-25 16:33:26.755

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Michotte's theory of ampliation suggests that causal relationships are perceived by objects animated under appropriate spatiotemporal conditions. In this thesis I extend the theory of ampliation and propose that the immediate perception of complex causal relations is also dependent upon a set of structural and temporal rules. The thesis aims at achieving two main goals. The first goal is to define a taxonomy of semantics that describe different causal events in the environment. Ten semantics are defined in this thesis and divided into two main groups; simple causal semantics and complex causal semantics. Simple causal semantics describe basic semantics, which form the building blocks for more complex information and include causal amplification, causal dampening, causal strength, and causal multiplicity. Complex causal semantics are built by enhancing or combining one or more simple semantics and include additive causality, contradictive causality, fully-mediated causality, partially-mediated causality, threshold causality, and bidirectional causality. The second goal of this thesis is to design simple visual representations to describe the causal information. Three representation types were designed during the course of this research; static-graph, static-sequence, and animation. Nine experiments were also conducted to test the effectiveness of these representations. The first five experiments compared the static-graph and the animated representations through Memory Recall and Intuitiveness Evaluations tests. Results of these experiments suggest that animations were ~8% more accurate and performed ~9% faster than the static-graph representations. The last four experiments compared an enhanced static representation, called static-sequence, to the animations to test if sequential animation of causal relations had any influence on the superior performance of the animations in the previous experiments. Results of these experiments suggest that there was no significant difference in the performance of the static-sequence representations when compared to the static-graph representations. The results also suggest that the animations performed more accurately than their static counterparts mainly due to their intuitiveness. Overall our results show that animated diagrams that are designed based on perceptual rules such as those proposed by Michotte have the potential to facilitate comprehension of complex causal relations.

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This thesis presents a system to display Structural Health Monitoring (SHM) data interactively at multiple scales that range from milliseconds to years. Typically, visualizing large SHM datasets produce static plots that take significant time to render. Our system improves upon standard tools by providing an interactive interface and a speed-optimized binning algorithm. Using the interface, a user is able to view data collected from a bridge's sensors at multiple scales in a web browser. This allows a user to visually inspect the entire range of their data to see both short and long-term trends. To render the data, the system uses a binning algorithm to calculate a five-number summary of a range of data. Those bins are combined to generate increasingly high levels of bins, which are then rendered as a binned line chart. The chart is rendered using a standard web browser on both desktop and mobile devices.

In order to create a machining line layout that supports the principles of lean a systematic approach is needed to ensure that a wide range of factors are taken into consideration. Despite this, many companies today design new layouts mainly considering delivery times of machines and equipment, and available space in the factory. A combined literature and case study has aimed to identify the most important factors in a lean line layout and a supporting structure to apply these in the design or redesign of automated machining lines. Highly automated machining environments mainly distinguish themselves from the more thoroughly studied area of assembly line layouts in two ways. Primarily, automated machining lines separate the operator from the actual processing, making line balancing and productivity less dependent on the workstation design around the operator. Secondly, automated machining lines often involve a higher level of complexity, leading to a more comprehensive work load, requiring longer training times but also offering less repetitive assignments. Automation offers improved productivity, quality and ergonomics, but if the acquisition and allocation of automation is not substantiated by a well-developed strategy, automation risks contradicting lean principles by creating a more complex, rigid layout that places the machines in the center instead of the workers. Factors that are important in the design of the typically less automated assembly lines, such as minimizing the walking distance of the operator and rotating stations to provide meaningful work assignments, must in an automated machining environment give way to factors like visualization, material flow and maintenance. Visualizing a factory helps operators and managers learn and understand the factory better. Problems can be detected and corrected faster and disturbances in production can thus be reduced. A good material flow is straight with no intersecting flows, triggered by downstream demand and reduces unnecessary buffers and WIP that bind up capital and consume space. Finally, since the machines rather than the operators produce, a good maintenance is required to avoid unplanned stops. The value of teamwork and humans in production which are strongly advocated within lean remain important also in automated machining lines but acquires a new content compared to assembly lines. Teamwork in automated machining environments occur within a group of lines rather than in a single line and it is a major factor when it comes to competence development, production planning and worker satisfaction. While teamwork in assembly lines works to balance the production flow within the line, teamwork in automated machining lines has little or no effect on the line balancing. However, joint efforts in setups and in case of machine failures or worker absence help increasing productivity, and potentially smooth the production at the plant in its entirety. The empirical studies showed that there is no standardized way of working with machining line layout design and redesign, and factors considered were often coincidental and dependent on the functions and priorities of the participants at different layout meeting. To ensure that all factors are taken into consideration a supporting tool where the most important factors were divided into ten categories was developed. Layouts are evaluated and rated on one category at a time to support a systematic way of working. Ongoing discussions, adjustments and improvements to better comply with the factors are encouraged.

Session ID: SA-G4-3 / Joint 4th International Conference on Soft Computing and Intelligent Systems and 9th International Symposium on advanced Intelligent Systems, September 17-21, 2008, Nagoya University, Nagoya, Japan

Session ID: TH-B1-2 / SCIS & ISIS 2010, Joint 5th International Conference on Soft Computing and Intelligent Systems and 11th International Symposium on Advanced Intelligent Systems. December 8-12, 2010, Okayama Convention Center, Okayama, Japan