Graduate Theses & Dissertations

Pages

Smote and Performance Measures for Machine Learning Applied to Real-Time Bidding
In the context of Real-Time Bidding (RTB) the machine learning problems of imbalanced classes and model selection are investigated. Synthetic Minority Oversampling Technique (SMOTE) is commonly used to combat imbalanced classes but a shortcoming is identified. Use of a distance threshold is identified as a solution and testing in a live RTB environment shows significant improvement. For model selection, the statistical measure Critical Success Index (CSI) is modified to add emphasis on recall. This new measure (CSI-R) is empirically compared with other measures such as accuracy, lift, efficiency, true skill score, Heidke's skill score and Gilbert's skill score. In all cases CSI-R is shown to provide better application to the RTB industry. Author Keywords: imbalanced classes, machine learning, online advertising, performance measures, real-time bidding, SMOTE
Modelling Submerged Coastal Environments
Built upon remote sensing and GIS littoral zone characterization methodologies of the past decade, a series of loosely coupled models aimed to test, compare and synthesize multi-beam SONAR (MBES), Airborne LiDAR Bathymetry (ALB), and satellite based optical data sets in the Gulf of St. Lawrence, Canada, eco-region. Bathymetry and relative intensity metrics for the MBES and ALB data sets were run through a quantitative and qualitative comparison, which included outputs from the Benthic Terrain Modeller (BTM) tool. Substrate classification based on relative intensities of respective data sets and textural indices generated using grey level co-occurrence matrices (GLCM) were investigated. A spatial modelling framework built in ArcGISTM for the derivation of bathymetric data sets from optical satellite imagery was also tested for proof of concept and validation. Where possible, efficiencies and semi-automation for repeatable testing was achieved using ArcGISTM ModelBuilder. The findings from this study could assist future decision makers in the field of coastal management and hydrographic studies. Keywords: Seafloor terrain characterization, Benthic Terrain Modeller (BTM), Multi-beam SONAR, Airborne LiDAR Bathymetry, Satellite Derived Bathymetry, ArcGISTM ModelBuilder, Textural analysis, Substrate classification Author Keywords:
An Investigation of Load Balancing in a Distributed Web Caching System
With the exponential growth of the Internet, performance is an issue as bandwidth is often limited. A scalable solution to reduce the amount of bandwidth required is Web caching. Web caching (especially at the proxy-level) has been shown to be quite successful at addressing this issue. However as the number and needs of the clients grow, it becomes infeasible and inefficient to have just a single Web cache. To address this concern, the Web caching system can be set up in a distributed manner, allowing multiple machines to work together to meet the needs of the clients. Furthermore, it is also possible that further efficiency could be achieved by balancing the workload across all the Web caches in the system. This thesis investigates the benefits of load balancing in a distributed Web caching environment in order to improve the response times and help reduce bandwidth. Author Keywords: adaptive load sharing, Distributed systems, Load Balancing, Simulation, Web Caching
ADAPT
This thesis focuses on the design of a modelling framework consisting of loose-coupling of a sequence of spatial and process models and procedures necessary to predict future flood events for the years 2030 and 2050 in Tabasco Mexico. Temperature and precipitation data from the Hadley Centers Coupled Model (HadCM3), for those future years were downscaled using the Statistical Downscaling Model (SDSM4.2.9). These data were then used along with a variety of digital spatial data and models (current land use, soil characteristics, surface elevation and rivers) to parameterize the Soil Water Assessment Tool (SWAT) model and predict flows. Flow data were then input into the Hydrological Engineering Centers-River Analysis System (HEC-RAS) model. This model mapped the areas that are expected to be flooded based on the predicted flow values. Results from this modelling sequence generate images of flood extents, which are then ported to an online tool (ADAPT) for display. The results of this thesis indicate that with current prediction of climate change the city of Villahermosa, Tabasco, Mexico, and the surrounding area will experience a substantial amount of flooding. Therefore there is a need for adaptation planning to begin immediately. Author Keywords: Adaptation Planning, Climate Change, Extreme Weather Events, Flood Planning, Simulation Modelling
An Application of the Sinc-Collocation Method in Oceanography
In this thesis, we explore the application of the Sinc-Collocation method to an oceanography model. The model of interest describes a wind-driven current with depth-dependent eddy viscosity and is formulated in two different systems; a complex-velocity system and a real-value coupled system. In general, the Sinc-based methods excel over other traditional numerical methods due to their exponentially decaying errors, rapid convergence and handling problems in the presence of singularities at end-points. In addition, the Sinc-Collocation approach that we utilize exploits first derivative interpolation, whose integration is less sensitive to numerical errors. We present several model problems to demonstrate the accuracy, and stability of the method. We compare the approximate solutions determined by the Sinc-Collocation technique with exact solutions and also with those obtained by the Sinc-Galerkin approach in earlier studies. Our findings indicate that the method we utilized outperforms those used in past studies. Author Keywords: Boundary Value Problems, Eddy Viscosity, Oceanography, Sinc Numerical Methods, Wind-Driven Currents
THE PROPENSITY TOWARD EXTREMIST MIND-SET AS PREDICTED BY PERSONALITY, MOTIVATION, AND SELF-CONSTRUAL
ABSTRACT The Propensity Toward Extremist Mind-Set as Predicted by Personality, Motivation, and Self-Construal Nick Fauset Multivariate regression analyses were used to determine the effects of Personality (Neuroticism, Extraversion, Openness, Agreeableness, and Conscientiousness), Motivation (External, Amotivation, Intrinsic, and Identified), and Self-Construal (Independent and Interdependent) on three domains of Extremist Mind-Set (Proviolence, Vile World, and Divine Power). Participants consisted of first year undergraduate students (209 females, 76 males) enrolled in Introductory Psychology (N=279) and/or Introductory Economics (N=7), whom participated for course credit. The Motivation measure was problematic for students to complete and this variable was dropped from the model due to missing data. Decreases in Neuroticism, Openness, Agreeableeness, and Interdependent were significantly correlated with increases in Proviolence. Decreases in Agreeableness were correlated with increases in Vile World. Decreases in Openness, and increases in Agreeableness and Interdependent were significantly correlated with increases in Divine Power. These observations provide an interesting perspective on the types of Canadian undergraduate students who are more likely to score highly on measures of Extremism. Keywords: Militant Extremist Mental Mind-Set, Extremism, Personality, Five Factor Model, Motivation, Intrinsic, Extrinsic, Self-Construal, Independent, Interdependent Author Keywords: Extremism, Militant Extremist Mental Mind-Set, Motivation, Personality, Self-Construal
An Investigation of the Impact of Big Data on Bioinformatics Software
As the generation of genetic data accelerates, Big Data has an increasing impact on the way bioinformatics software is used. The experiments become larger and more complex than originally envisioned by software designers. One way to deal with this problem is to use parallel computing. Using the program Structure as a case study, we investigate ways in which to counteract the challenges created by the growing datasets. We propose an OpenMP and an OpenMP-MPI hybrid parallelization of the MCMC steps, and analyse the performance in various scenarios. The results indicate that the parallelizations produce significant speedups over the serial version in all scenarios tested. This allows for using the available hardware more efficiently, by adapting the program to the parallel architecture. This is important because not only does it reduce the time required to perform existing analyses, but it also opens the door to new analyses, which were previously impractical. Author Keywords: Big Data, HPC, MCMC, parallelization, speedup, Structure
Stability Properties of Disease Models under Economic Expectations
Comprehending the dynamics of infectious diseases is very important in formulating public health policies to tackling their prevalence. Mathematical epidemiology (ME) has played a very vital role in achieving the above. Nevertheless, classical mathematical epidemiological models do not explicitly model the behavioural responses of individuals in the presence of prevalence of these diseases. Economic epidemiology (EE) as a field has stepped in to fill this gap by integrating economic and mathematical concepts within one framework. This thesis investigated two issues in this area. The methods employed are the standard linear analysis of stability of dynamical systems and numerical simulation. Below are the investigations and the findings of this thesis: Firstly, an investigation into the stability properties of the equilibria of EE models is carried out. We investigated the stability properties of modified EE systems studied by Aadland et al. [6] by introducing a parametric quadratic utility function into the model, thus making it possible to model the maximum number of contacts made by rational individuals to be determined by a parameter. This parameter in particular influences the level of utility of rational individuals. We have shown that if rational individuals have a range of possible contacts to choose from, with the maximum of the number of contacts allowable for these individuals being dependent on a parameter, the variation in this parameter tends to affect the stability properties of the system. We also showed that under the assumption of permanent recovery for disease coupled with individuals observing or not observing their immunity, death and birth rates can affect the stability of the system. These parameters also have effect on the dynamics of the EE SIS system. Secondly, an EE model of syphilis infectivity among &ldquo men who have sex with men &rdquo (MSM) in detention centres is developed in an attempt at looking at the effect of behavioural responses on the disease dynamics among MSM. This was done by explicitly incorporating the interplay of the biology of the disease and the behaviour of the inmates. We investigated the stability properties of the system under rational expectations where we showed that: (1) Behavioural responses to the prevalence of the disease affect the stability of the system. Therefore, public health policies have the tendency of putting the system on indeterminate paths if rational MSM have complete knowledge of the laws governing the motion of the disease states as well as a complete understanding on how others behave in the system when faced with risk-benefit trade-offs. (2) The prevalence of the disease in the long run is influenced by incentives that drive the utility of the MSM inmates. (3) The interplay between the dynamics of the biology of the disease and the behavioural responses of rational MSM tends to put the system at equilibrium quickly as compared to its counterpart (that is when the system is solely dependent on the biology of the disease) when subjected to small perturbation. Author Keywords: economic and mathematical epidemiology models, explosive path, indeterminate-path stability, numerical solution, health gap, saddle-path stability, syphilis,

Pages

Description

Graduate student theses produced at Trent University. You may also browse theses and dissertations by year, program, or author.

In collections

Search Our Digital Collections

Query

Enabled Filters

  • (-) ≠ Reid
  • (-) ≠ Bowman
  • (-) ≠ Bell
  • (-) ≠ Weygang
  • (-) = Applied Modeling and Quantitative Methods
  • (-) ≠ Mathematics
  • (-) ≠ Kwan, Ryan
  • (-) ≠ Astronomy

Filter Results

Date

2004 - 2024
(decades)
Specify date range: Show
Format: 2024/05/02

Collection

Author Name

Show more

Name (Any)

Show more

Degree

Subject (Topic)

Show more