Applied Modeling and Quantitative Methods

This thesis presents an approach for automated grading of UML Use Case diagrams. Many software engineering courses require students to learn how to model the behavioural features of a problem domain or an object-oriented design in the form of a use case diagram. Because assessing UML assignments is a time-consuming and labor-intensive operation, there is a need for an automated grading strategy that may help instructors by speeding up the grading process while also maintaining uniformity and fairness in large classrooms. The effectiveness of this automated grading approach was assessed by applying it to two real-world assignments. We demonstrate how the result is similar to manual grading, which was less than 7% on average; and when we applied some strategies, such as configuring settings and using multiple solutions, the average differences were even lower. Also, the grading methods and the tool are proposed and empirically validated.

Author Keywords: Automated Grading, Compare Models, Use Case

The Multidimensional Inventory of Personal Intelligence (MIPI) was designed to measure three related dimensions of the personal intelligence (PI) construct: emotional intelligence (EI), social intelligence (SI), and motivational intelligence (MI). The MIPI has psychometric properties and a theoretical structure that improves on the shortcomings of existing trait EI measures. The aim of the first study was to create and validate a shortened form (MIPI- Short) that maintains the same factorial structure of the original MIPI. The purpose of the second study was to validate the new scale with measures of conceptually similar constructs (e.g., emotional intelligence, Alexithymia) with various measurement methodologies (self-report, observer-report, and performance-based). Results from Study 1 found that the MIPI-Short had good factorial structure in two independent samples, as well as adequate internal reliability, and good incremental validity. The results of Study 2 demonstrated that the MIPI-Short had good construct validity as it generally related as expected with measures of EI and Alexithymia. The findings of both studies provide evidence for the validity of the MIPI-Short as a brief measure of Personal Intelligence. Directions for further research are emphasized, as the validation process is on-going for any assessment tool.

Author Keywords: Emotional Intelligence, Personal Intelligence, Socio-Emotional Competencies

This thesis is focused on studying the population dynamics of a predator-prey system in a patchy environment, taking anti-predation responses into consideration. Firstly, we conduct mathematical analysis on the equilibrium solutions of the system. Using techniques from calculus we show that particular steady state solutions exist when the parameters of the system meet certain criteria. We then show that a further set of conditions leads to the local stability of these solutions. The second step is to extend the existing mathematical analysis by way of numerical simulations. We use octave to confirm the previous results, as well as to show that more complicated dynamics can exist, such as stable oscillations. We consider more complex and meaningful functions for nonlinear dispersal between patches and nonlinear predation, and show that the proposed model exhibits behaviours we expect to see in a population model.

Author Keywords: Anti-predation response, Asymptotic stability, Dispersal, Patch model, Population dynamics, Predator-prey

Video games have always been intrinsically linked with the technology available for the progress of the medium. With improvements in technology correlating directly to improvements in video games, this has recently not been the case. One recent technology video games have not fully leveraged is Cloud technology. This Thesis investigates a potential solution for video games to leverage Cloud technology. The methodology compares the relative performance of a Local, Cloud and a proposed Hybrid Model of video games. We find when comparing the results of the relative performance of the Local, Cloud and Hybrid Models that there is potential in a Hybrid technology for increased performance in Cloud gaming as well as increasing stability in overall game play.

Author Keywords: cloud, cloud gaming, streaming, video game

In this thesis, we present a framework to model user object-level request patterns in the World Wide Web.This framework consists of three sub-models: one for file access, one for Web pages, and one for storage sites. Web Pages are modelled to be made up of different types and sizes of objects, which are characterized by way of categories.

We developed a discrete event simulation to investigate the performance of systems that utilize our model.Using this simulation, we established parameters that produce a wide range of conditions that serve as a basis for generating a variety of user request patterns. We demonstrated that with our framework, we can affect the mean response time (our performance metric of choice) by varying the composition of Web pages using our categories. To further test our framework, it was applied to a Web caching system, for which our results showed improved mean response time and server load.

Author Keywords: discrete event simulation (DES), Internet, performance modelling, Web caching, World Wide Web

Paramedic data has significant potential for research. Paramedics see many patients every year and collect a wide variety of crucial data at each encounter. This data is rarely used for good reason: it's messy and hard to work with. But like theunderdog character in a classic movie, with a little bit of work and a lot of understanding, paramedic data has significant potential to change the world of medical research. Paramedics throughout the world are involved in research every day, but most of this research uses purpose-built data structures and never takes advantage of the existing data that paramedics create as part of their everyday work. Through a project-based approach grounded in developing a better understanding of the opioid crisis, this thesis will examine the quantity and structure of the existing paramedic data, the complexities of its current design, the steps necessary to access it, and the processes necessary to clean existing data to a point where it can be easily modelled. Once we have our dataset, we will explore the challenges of choosing key metrics by examining the effectiveness of metrics currently employed to monitor the opioid crisis and the influences public health programs and changing policies have had on these metrics. Next, we will explore the temporal distributions of opioid and other intoxicant use with an eye to providing data to support public health in their harm reduction efforts. And lastly, we will look at the effect of fixed- and floating-point temporal influences on intoxicant-related calls with an eye to how these temporal points can affect call volumes. By using this exploration of the opioid crisis, this thesis will show that with a more thorough understanding of what paramedic data is, what data points are available, and the processes needed to transform it, paramedic data has the potential to greatly expand the limits of health care data science into a more precise and more all-encompassing discipline.

Author Keywords: Ambulance, Data Science, Opioid, Overdose, Paramedic, Pre-hospital

This thesis is part of an industry project which collaborates with an aviation technology company on pilot performance assessment. In this project, we propose utilizing the pilots' training data to develop a model that can recognize the pilots' activity patterns for evaluation. The data will present as a time series, representing a pilot's actions during maneuvers. In this thesis, the main contribution is focusing on a multivariate time series dataset, including preprocessing and transformation. The main difficulties in time series classification is the data sequence of the time dimension. In this thesis, I developed an algorithm which formats time series data into equal length data.

Three classification and two transformation methods were used. In total, there are six models for comparison. The initial accuracy was 40%. By optimization through resampling, we increased the accuracy to 60%.

Author Keywords: Data Mining, K-NN, Machine Learning, Multivariate Time Series Classification, Time Series Forest

This thesis explores the shot-term relationship between exposure to ambient air pollution and human health through metrics such as mortality and hospitalization in Canada. We begin by detailing the organization and interpolation of air pollution data from its partially quality-controlled source form. Analyses of seasonal, regional and temporal trends of all major components of PM2.5, was performed, showing a seasonal variation across most regions and validating the dataset.

A one-pollutant statistical Generalized Additive Model was applied to the data, estimating the health risk associated with exposure to thirteen different components of PM2.5. The selected components were based on those that compromised the majority of the mass and included: sulphate, nitrate, zinc, silicon, iron, nickel, vanadium, potassium, organic carbon, organic matter, elemental carbon, total carbon. Trends based on annual estimates of the association for PM2.5, and its constituents,were compared, showing that carbonaceous compounds, sulphate and nitrate had similar estimates of association. Many estimates, as is common in population ecologic epidemiology, had association estimates statistically indistinguishable from zero, but with clear features of interest, including evident differences between cold and warm season associations in Canada's temperate climate.

A method to model two correlated pollutants (in this case, PM2.5 and O3) was developed using thin plate splines. In this approach, the location of the response surface (after accounting for the temperature, a smooth function of time and day of week) that corresponds to the average pollutant concentration and the average plus one unit was used as the estimate of the joint contribution of pollutants due to a unit increase. The estimates from the thin plate spline (TPS) approach were compared to the single pollutant models, with large increases and decreases in PM2.5 and O3 being captured in the TPS estimates. However, this approach indicated significantly larger error in the estimates than would be expected, indicating a possible future area for refinement.

Author Keywords: Air pollution, Environmental Epidemiology, Generalized Additive Models, Human Health, Multivariate Models, Thin Plate Splines

Objective: To improve on several methodological issues and research gaps regarding current literature investigating the stability of ADHD symptomatology across adulthood and relationships between the two core ADHD symptom dimensions (i.e., inattention and hyperactivity-impulsivity) and multiple life outcomes in adults. Method: A large sample of postsecondary students were initially assessed for ADHD symptomatology using the Conners' Adult ADHD Rating Scale (CAARS). Six years later, academic success was assessed using students' official academic records (e.g., final GPAs and degree completion status), and fifteen years later, participants were re-assessed using the CAARS and several measures of life success (e.g., relationship satisfaction, career satisfaction, and stress levels). Results: Inattention and hyperactivity-impulsivity symptoms showed strong stability across the 15-year period. Additionally, greater inattention symptoms during emerging adulthood and early middle adulthood were consistently associated with poorer life success (e.g., lower GPAs, poorer relationship and career satisfaction), particularly for men. Associations for hyperactivity-impulsivity symptoms were less consistent. Conclusion: ADHD symptomatology can be conceptualized as a stable, dimensional trait across adulthood, with robust associations with measures of life success.

Author Keywords: academic success, ADHD, adults, job satisfaction, relationship satisfaction, stability

I drew on Bourdieu's theory of capital and theorized that different forms of economic, cultural and social capital which injured workers possessed and/or acquire over their disability trajectory may affect certain outcomes of permanent impairments. Using data from a cross-sectional survey of 494 Ontario workers with permanent impairments, I measured workers' different indicators of capital in temporal order. Hierarchical regression analyses were used to test the unique association of workers' individual characteristics, pre-injury capital, post-injury capital, and the outcomes of permanent impairments. The results show that factors related to individual characteristics, pre-injury and post-injury capital were associated with workers' perceived health change, whereas pre-injury and post-injury capital were most relevant factors in explaining workers' post-injury employment status and income recovery. When looking at the significance of individual predictors, post-injury variables were most relevant in understanding the outcomes of permanent impairment. The findings suggest that many workers faced economic and health disadvantages after permanent work injury.

Author Keywords: Bourdieu, hierarchical regression, theory of capital, work-related disability, workers with permanent impairments