The design of a texture display for three-dimensional Light Detection and Ranging (LiDAR) point clouds is investigated. The objective is to present a low fidelity display that is simple to compute in real-time, which utilizes the pattern processing capabilities of a human operator to afford an understanding of the environment. The efficacy of the display is experimentally evaluated by in comparison with a baseline point cloud rendering. Subjects were shown data based on virtual hills, and were asked to plan the least-steep traversal, and identify the hill from a set of distractors. The major conclusions are: comprehension of LiDAR point clouds from the sensor origin is difficult without further processing of the data, a separated vantage point improves understanding of the data, and a simple computation to present local point cloud derivative data significantly improves the understanding of the environment, even when observed from the sensor origin.

Few studies examine technical barriers, such as usability, to successful Computerized Provider Order Entry (CPOE) system implementation. This thesis explores this literature gap through the evaluation of the Sunnybrook CPOE order set system with a heuristic evaluation of the Sunnybrook CPOE system, the development of a more user friendly CPOE order set interface (Test Design), and a usability study comparing three order set formats (Sunnybrook CPOE, Test Design, and paper order sets). A randomized trial was conducted with 27 Sunnybrook physicians at the hospital. Results showed that the Sunnybrook CPOE order set system was less efficient (task times were on average 364 seconds longer than Test Design and 344 seconds longer than paper), less user-friendly (users were less confident, less satisfied, and more frustrated with Sunnybrook CPOE tasks), and less safe than paper order sets (more harmful errors). Test Design was as efficient and safe as paper order sets.

Multivariate control charts are valuable tools for multivariate statistical process control (MSPC) used to monitor industrial processes and to detect abnormal process behavior. It has been shown in the literature that Bayesian control charts are optimal tools to control the process compared with the non-Bayesian charts. To use any control chart, three control chart parameters must be specified, namely the sample size, the sampling interval and the control limit. Traditionally, control chart design is based on its statistical performance. Recently, industrial practitioners and academic researchers have increasingly recognized the cost benefits obtained by applying the economically designed control charts to quality control, equipment condition monitoring, and maintenance decision-making. The primary objective of this research is to design multivariate Bayesian control charts (MVBCH) both for quality control and conditional-based maintenance (CBM) applications. Although considerable research has been done to develop MSPC tools under the assumption that the observations are independent, little attention has been given to the development of MSPC tools for monitoring multivariate autocorrelated processes. In this research, we compare the performance of the squared predication error (SPE) chart using a vector autoregressive moving average with exogenous variables (VARMAX) model and a partial least squares (PLS) model for a multivariate autocorrelated process. The study shows that the use of SPE control charts based on the VARMAX model allows rapid detection of process disturbances while reducing false alarms. Next, the economic and economic-statistical design of a MVBCH for quality control considering the control limit policy proved to be optimal by Makis(2007) is developed. The computational results illustrate that the MVBCH performs considerably better than the MEWMA chart, especially for smaller mean shifts. Sensitivity analyses further explore the impact of the misspecified out-of-control mean on the actual average cost. Finally, design of a MVBCH for CBM applications is considered using the same control limit policy structure and including an observable failure state. Optimization models for the economic and economic statistical design of the MVBCH for a 3 state CBM model are developed and comparison results show that the MVBCH performs better than recently developed CBM Chi-square chart.

Recent work has proposed sliders as a useful way to measure self-reported emotion continuously. My dissertation extends this work to ask: what are relevant properties of affective self-report on sliders and variations? How reliable are affective self-reports? How do they relate to physiological data? What are individual and cultural differences? How can this method be applied to ehealth? Three emotion self-report tools (one-slider, two-slider, a touchscreen) were developed and evaluated in four experiments. The first experiment was within-subjects. Participants viewed short videos, with four self-report conditions (including no reporting) and physiological capture (heart rate variability and skin conductance). In a re-rating task, the sliders models were found to be more reliable than the touchscreen (Lottridge & Chignell, 2009a). The second and third experiments were between-subjects, and examined individual and cultural differences. Canadian and Japanese participants watched a nature video, while rating emotions and answering questions. Analyses were carried out within and across the datasets. Larger operation span displayed a minor benefit. Valence and arousal ratings were not strongly related to skin conductance. The Japanese performed on par with Canadians but reported worse performance. Based on the results, the recommendation was made that a single slider be used to rate valence, that arousal be estimated with skin conductance, and that slider psychometrics be used to assess cognitive load over time. In the fourth experiment, diabetic participants watched Diabetes-related videos. They clustered into usage patterns: some moved the slider very little during videos and more afterward, some hardly moved the slider, and some used it as expected. Two novel metrics facilitated these analyses: Emotional Bandwidth, an application of information entropy that characterizes the granularity of the self reports (Lottridge & Chignell, 2009b) and Emotional Majority Agreement, the amount of agreement relative to a sample’s self-reports (Lottridge & Chignell, 2009c). In summary, this dissertation contributes a method of measuring emotion through sliders and skin conductance that has been evaluated in a number of experimental studies. It contributes the empirical results, design recommendations, and two novel metrics of emotional response. Limitations and implications for future research and practice are also discussed.

Three experiments have been completed to investigate whether and how a software technique called real-time image mosaicing applied to a restricted field of view (FOV) might influence target detection and path integration performance in simulated aerial search scenarios, representing local and global spatial awareness tasks respectively. The mosaiced FOV (mFOV) was compared to single FOV (sFOV) and one with double the single size (dFOV). In addition to advancing our understanding of visual information in mosaicing, the present study examines the advantages and limitations of a number of metrics used to evaluate performance in path integration tasks, with particular attention paid to measuring performance in identifying complex routes. The highlights of the results are summarized as follows, according to Experiments 1 through 3 respectively. 1. A novel response method for evaluating route identification performance was developed. The surmised benefits of the mFOV relative to sFOV and dFOV revealed no significant differences in performance for the relatively simple route shapes tested. Compared to the mFOV and dFOV conditions, target detection performance in the local task was found to be superior in the sFOV condition. 2. In order to appropriately quantify the observed differences in complex route selections made by the participants, a novel analysis method was developed using the Thurstonian Paired Comparisons Method. 3. To investigate the effect of display size and elevation angle (EA) in a complex route environment, a 2x3 experiment was conducted for the two spatial tasks, at a height selected from Experiment 2. Although no significant differences were found in the target detection task, contrasts in the Paired Comparisons Method results revealed that route identification performance were as hypothesised: mFOV > dFOV > sFOV for EA = 90°. Results were similar for EA = 45°, but with mFOV being no different than dFOV. As hypothesised, EA was found to have an effect on route selection performance, with a top down view performing better than an angled view for the mFOV and sFOV conditions.

Emergency Department (ED) congestion can be better understood by examining overall system impacts, in particular inpatient admissions and discharges. This study first investigates trends of inpatient admissions, volume of patients in the ED who have been admitted (ED “boarders”), length of stay, and bed resources of three major admitting services at our teaching institution. It was found that patients admitted to the General Internal Medicine (GIM) service constituted the majority of ED boarders by default rather than design, as GIM served as a safety net for specialty services. This study investigates operational factors that impact discharge and found that day of the week and holidays followed by team organization and scheduling are significant predictors of daily variation in discharge rates. Based on these results, next, a system dynamics computer simulation was built to test the impact of various discharge smoothing strategies on the number of ED boarders. Next, this study uses the framework and tools of system dynamics methodology to design a conceptual model of the ED boarder problem that may be used as a generalizable roadmap to create sustainable improvements in ED congestion. Finally, this study introduces a novel real time metric of hospital operational discharge efficiency- daily discharge rate – to bring focus on the underlying causes of discharge variation and help indicate opportunities for improvement.

Emergency Department (ED) congestion can be better understood by examining overall system impacts, in particular inpatient admissions and discharges. This study first investigates trends of inpatient admissions, volume of patients in the ED who have been admitted (ED “boarders”), length of stay, and bed resources of three major admitting services at our teaching institution. It was found that patients admitted to the General Internal Medicine (GIM) service constituted the majority of ED boarders by default rather than design, as GIM served as a safety net for specialty services. This study investigates operational factors that impact discharge and found that day of the week and holidays followed by team organization and scheduling are significant predictors of daily variation in discharge rates. Based on these results, next, a system dynamics computer simulation was built to test the impact of various discharge smoothing strategies on the number of ED boarders. Next, this study uses the framework and tools of system dynamics methodology to design a conceptual model of the ED boarder problem that may be used as a generalizable roadmap to create sustainable improvements in ED congestion. Finally, this study introduces a novel real time metric of hospital operational discharge efficiency- daily discharge rate – to bring focus on the underlying causes of discharge variation and help indicate opportunities for improvement.

The Web has become an open decentralized global information / knowledge repository, a platform for distributed computing and global electronic markets, where people are confronted with information of unknown sources, and need to interact with “strangers”. This makes trust and the validity of information in cyberspace arise as crucial issues. This thesis proposes knowledge provenance (KP) as a formal approach to determining the origin and validity of information / knowledge on the Web, by means of modeling and maintaining the information sources, information dependencies, and trust structures. We conceptualize and axiomatize KP ontology including static KP and dynamic KP. The proposed KP ontology, provides a formal representation of linking trust in information creators and belief in the information created; lays a foundation for further study of knowledge provenance; provides logical systems for provenance reasoning by machines. The web ontology of KP can be used to annotate web information; and KP reasoner can be used as a tool to trace the origin and to determine the validity of Web information. Since knowledge provenance is based on trust in information sources, this thesis also proposes a logical theory of trust in epistemic logic and situation calculus. In particular, we formally define the semantics of trust; from it, we identify two types of trust: trust in belief and trust in performance; reveal and prove that trust in belief is transitive; trust in performance is not, but by trust in belief, trust in performance can propagate in social networks; by using situation calculus in trust formalization, the context of trust is formally represented by reified fluents; we also propose a distributed logical model for trust reasoning using social networks, by which each agent’s private data about trust relationships can be protected. This study provides a formal theoretical analysis on the transitivity of trust, which supports trust propagation in social networks. This study of trust supports not only knowledge provenance but also the general trust modeling in cyberspace.

Three experiments have been completed to investigate whether and how a software technique called real-time image mosaicing applied to a restricted field of view (FOV) might influence target detection and path integration performance in simulated aerial search scenarios, representing local and global spatial awareness tasks respectively. The mosaiced FOV (mFOV) was compared to single FOV (sFOV) and one with double the single size (dFOV). In addition to advancing our understanding of visual information in mosaicing, the present study examines the advantages and limitations of a number of metrics used to evaluate performance in path integration tasks, with particular attention paid to measuring performance in identifying complex routes. The highlights of the results are summarized as follows, according to Experiments 1 through 3 respectively. 1. A novel response method for evaluating route identification performance was developed. The surmised benefits of the mFOV relative to sFOV and dFOV revealed no significant differences in performance for the relatively simple route shapes tested. Compared to the mFOV and dFOV conditions, target detection performance in the local task was found to be superior in the sFOV condition. 2. In order to appropriately quantify the observed differences in complex route selections made by the participants, a novel analysis method was developed using the Thurstonian Paired Comparisons Method. 3. To investigate the effect of display size and elevation angle (EA) in a complex route environment, a 2x3 experiment was conducted for the two spatial tasks, at a height selected from Experiment 2. Although no significant differences were found in the target detection task, contrasts in the Paired Comparisons Method results revealed that route identification performance were as hypothesised: mFOV > dFOV > sFOV for EA = 90°. Results were similar for EA = 45°, but with mFOV being no different than dFOV. As hypothesised, EA was found to have an effect on route selection performance, with a top down view performing better than an angled view for the mFOV and sFOV conditions.

This paper presents a microsimulation model of the rental sector in the Greater Toronto (GTA). The main contributions of this research are that it develops a conceptual framework for modeling housing issues and policies, and implements a rental model within the Integrated Land Use, Transport, and Environment (ILUTE) framework developed at the University of Toronto. The key components of the rental model include: (1) the production of rental units; (2) a tenure choice model; (3) a rent setting model; and (4) a rental market model. The rental model is simulated yearly from 1986 till 2006. The preliminary results are presented for the number of households renting, the average rent per census tract, and the number of renter households facing affordability issues. Two areas of future research are proposed that seek: (1) to improve the current model’s accuracy; and (2) to develop a more dynamic model.